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How to Set Up Stratis Storage on Fedora

Sun, 26 Jul 2026 06:39:11 +0200

Stratis is Red Hat's local storage management tool that brings ZFS-style features to Fedora using only in-tree kernel components. This guide walks through installing stratisd, creating pools with thin provisioning, mounting XFS filesystems, setting up SSD cache tiers, creating instant snapshots, and configuring encrypted pools. All commands verified against Fedora 44 running stratisd 3.9.1.

This AI SSD tech makes 8 RTX 5090s perform like 46 GPUs in inference

Sat, 25 Jul 2026 20:30:35 +0200

GenStorAIGE's AI90 combines HBM, DDR, and SSD storage, claiming faster inference while expanding effective GPU memory for large language models.

Your instant Android backup upgrade

Sat, 25 Jul 2026 19:50:10 +0200

Here in this high-tech era of 2026, keeping important info backed up and synced should be effortless and something that just happens on its own, automatically, without any actual thought or ongoing human effort.

In many areas of our digital life, that mercifully does Just Work™ in exactly that way. Fire up an email in most modern mail services, and you can stop at any point and find your in-progress draft in that same app on any other device. The same applies to any file you’re finessing within Google Drive or other cloud storage services or document you’re dawdling over in Docs.

One area where seamless syncing somehow still doesn’t occur, though, is in the domain of downloaded documents on Android. If someone sends you a PDF or a Word file and you save it to your phone, that file exists in an archaic-seeming silo — only locally, on that one gadget. And that, of course, means (a) you can’t access it from any other device, and (b) if you misplace your phone or move into a new one at some point along the way, the file will be left behind in time and entirely unavailable.

Well, take a moment to join me in celebration: Amidst all the Gemini gobbledegook that no one asked for (and that often falls somewhere between “pointless” and “actively counterproductive”), Google’s giving us a major upgrade to Android’s backup capabilities right now. It’s a simple-seeming switch buried in your system settings, and it’s up to you to find and activate it.

Once you do, though, those once-orphaned documents on your Android device’s local storage will be perpetually synced and protected, automatically, without any ongoing thought or effort.

All you’ve gotta do is find and flip that one new switch.

[Don’t let yourself miss an ounce of Android Intelligence. Join my free weekly Android Intelligence newsletter and get one new thing to try in your inbox every Friday!]

The Android backup lowdown

So, for a quick bit of pertinent context on this: Android’s backup systems have actually come a really long way over the years.

‘Twas a time, y’see, when little to nothing about you would sync and carry over automatically from one Android device to another. Years ago — back in the ancient-seeming prehistoric era of the early 2010s — Android enthusiasts in the know would rely on community-created third-party apps for everything from remembering and resyncing downloaded apps to restoring data from within those apps and onward. And reconfiguring your system preferences would be a whole time-consuming song and dance every single time you reset a device or moved into a new one, as little to nothing would automatically carry over.

Most of that stuff is now effortless and automatic. And, thanks to apps like Google Messages, Calendar, Drive, and Docs, many other areas of important data are also synced on their own at the app level — outside of any system mechanisms.

Locally stored files, however, have remained an awkward omission. To this day, anything you download on any Android device exists only on that one device and isn’t synced or backed up anywhere. The only way that happens is — in a blast-from-the-past twist — if you go out of your way to find and set up a third-party app to handle the heavy lifting.

That brings us to today. Right now, as we speak, Google’s in the midst of sending out a quiet under-the-hood update that (brace yourself…) adds in the option to automatically sync and back up any documents on your device as a native part of Android’s backup setup.

See?

The easily overlooked new option for backing up documents on Android.

JR Raphael, Foundry

The option is on its way to all devices running 2018’s Android 9 release and higher. (If you’re still using a phone with an Android version older than that, you’re now a whopping eight years out of date, and you have much bigger problems.)

Once the added option is present and available for you, you’re literally lookin’ at 10 seconds to find and activate it.

Lemme show ya how.

Android’s document backup addition

I promise: This couldn’t be much simpler.

No matter what kind of Android device is in front of you, just head into your system settings and open the section called “Accounts and backup,” “Back up or copy data,” or something along those same lines. (The exact wording can vary based on who made your device and when it was released or last updated.)

Either tap the line labeled “Google Backup” or look for an option to “Back up data” via Google Drive. You should then either see a series of options for different areas of available backup right then and there — or, depending on your device, you might have to tap a line labeled “Other device data” (or something similar) to find the full list of possibilities.

However you get there, once you’re lookin’ at that list, you’ll see a newly added line for “Documents” if this latest under-the-hood update has reached you.

Android’s expanded list of backup options — now including documents alongside other forms of on-device data.

JR Raphael, Foundry

And from there, all that’s left is to tap it and enable the switch to include that in your automated backups from that moment forward.

If you aren’t seeing the option yet, don’t panic. Google always sends these under-the-hood updates out bit by bit over time, so the change probably just hasn’t reached your device quite yet. As long as you’re running Android 9 or higher, it’ll get there. Set yourself a reminder to check back once a week or so. Odds are, you’ll see it pretty soon.

Notably, all documents synced in this way are always encrypted for security, and they’re kept in your personal (or, depending on the nature of your account, perhaps company-connected) Google Drive storage. That does mean they’ll count against your overall Google storage total, so keep an eye on your Drive storage total to make sure you’re in solid shape and look to the Google One storage hub if you ever want some simple suggestions for freeing up space.

Speaking of other Google services: If you ever want to keep other types of locally stored non-document files from an Android device synced and available elsewhere, you can easily rely on Google Photos for syncing screenshots and other images — after enabling sync in general, be sure to look in the app’s “Collections” areas to find the “On this device” folder and then flip the toggle to “Backup all device folders” (or get more nuanced and open specific individual on-device folders if you want to sync some but not all of those areas) — and you can still turn to those aforementioned third-party apps for broader syncing of anything else imaginable.

But with documents now being handled automatically and natively, that’s one big worry now out of your hair. Just note that the onus will fall on you to find and flip the switch and actively opt in to the feature on each and every Android device you’re using.

Take 10 seconds to do that, though, and you’ll have one less void in your Android data arena. And you don’t need Gemini to tell you that that can only be a good thing.

Get practical Android knowledge in your inbox every Friday with my free Android Intelligence newsletter — one new thing to try each week, straight from me to you.

AMD raises the AI stakes with Helios, Venice and robotics

Sat, 25 Jul 2026 19:50:07 +0200

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.

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 Helios AI platform is a major platform evolution for AMD, with shipments scheduled to begin in the second half of this year (which is here and now).

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.

AMD’s MI455X targets the AI memory wall

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.

Compared to AMD’s current MI355X, the MI455X offers 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.

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.

AMD

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.

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.

AMD’s Helios rack takes aim at Vera Rubin

Dave Altavilla

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.

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.

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.

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.

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.

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.

Kind of like cowbell, AMD Venice gives agentic AI more CPU

AMD

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.

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.

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.

Pensando networking and ROCm software advance

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.

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.

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.

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.

Customer commitments underscore rack-scale confidence

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.

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, Anthropic announced 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.

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.

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.

AMD expands its robotics and embedded foundation

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.

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.

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.

Execution for AMD is now the test

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.

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.

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.

This article is published as part of the Foundry Expert Contributor Network.
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Google’s anti-search-scraping lawsuit dismissed

Sat, 25 Jul 2026 19:50:05 +0200

A court has dismissed Google’s case against SerpApi over that company’s scraping of search results to train AI models.

The US District Court for the Northern District of California found that there was no indication that any copyright had been breached.

Google announced in December that it was suing SerpApI for its alleged web scraping, claiming that it was protecting copyright holders. In February, SerpApI fought back and asked the court to dismiss Google’s case. And this week, Judge Yvonne Gonzalez Rogers agreed with SerpApi that Google’s case has no merit.

Google’s argument was that SerpApi’s actions breached the US Digital Millennium Copyright Act (DCMA). It made two claims: first, that no person shall circumvent a technological measure that effectively controls access to a work protected under this title, and second that no person shall manufacture, import, offer to the public, provide, or otherwise traffic in any technology, product, service, device, or component protected by the Act.

SerpApi claimed that the URLs and other links that were being served by Google did not in themselves entail copyright and the judge agreed. In her judgment, she said that there was no indication that the copyright holders had authorized Google to take action against SerpApi.

The case is not completely over as the judge has given Google 21 days to amend its complaint to demonstrate that it was acting on behalf of the copyright owners. It remains to be seen whether its war against the web scrapers is finally over.

How to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes

Sat, 25 Jul 2026 19:49:17 +0200

Architecting cost-effective infrastructure by navigating the latency and storage trade-offs of HNSW, SPANN, and DiskANN

The post How to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes appeared first on Towards Data Science.

The May 2026 Security Update Review

Sat, 25 Jul 2026 19:02:56 +0200

I’m currently in Berlin helping set up for Pwn2Own Berlin, but that doesn’t stop Patch Tuesday from coming, and it’s another big one. At least nothing is listed as being in the wild – for now. Take a break from your regularly scheduled activities and let’s take a look at the latest security patches from Adobe and Microsoft. Due to technical difficulties, there will not be a video companion for this month.

Adobe Patches for May 2026

For May, Adobe released 10 bulletins addressing 52 unique CVEs in Adobe Commerce, After Effects, Adobe Connect, Illustrator, Media Encoder, Premiere Pro, Substance 3D Painter, Substance 3D Sampler, Content Authenticity SDK, and the Adobe Substance 3D Designer. Here’s this month’s overview table:

Bulletin ID	Product	CVE Count	Highest Severity	Highest CVSS	Exploited	Deployment Priority
APSB26-49	Adobe Commerce	15	Critical	8.7	No	2
APSB26-48	Adobe After Effects	4	Critical	7.8	No	3
APSB26-50	Adobe Connect	2	Critical	9.6	No	3
APSB26-51	Adobe Illustrator	4	Critical	7.8	No	3
APSB26-47	Adobe Media Encoder	2	Critical	7.8	No	3
APSB26-46	Adobe Premiere Pro	3	Critical	7.8	No	3
APSB26-55	Adobe Substance 3D Painter	2	Critical	7.8	No	3
APSB26-54	Adobe Substance 3D Sampler	1	Critical	7.8	No	3
APSB26-53	Content Authenticity SDK	14	Critical	7.5	No	3
APSB26-52	Adobe Substance 3D Designer	5	Important	6.3	No	3
TOTAL	10 bulletins	52

The obvious priority this month is the patch for Commerce, with its 15 bugs and deployment priority of 2. The Connect fix should also rank up there since both of its CVEs are CVSS 9s. Beyond those, it’s a pretty typical month for Adobe, with most of the bugs either being cross-site scripting (XSS) or open-and-own code executions.

Microsoft Patches for May 2026

This month, Microsoft released a whopping 138 new CVEs in Windows and Windows components, Office and Office Components, Microsoft Edge (Chromium-based), Azure, .NET and Visual Studio, Copilot Chat, Github Copilot, M365 Copilot, SQL Server, TCP/IP, and the Telnet Client – yes, the Telnet client. Two of these bugs were reported through the TrendAI ZDI program. 30 of these bugs are rated Critical, three are rated as Moderate, one is rated Low, and the rest are rated Important in severity.

This large volume of fixes follows the largest monthly release in Microsoft’s history and reflects the trend across the industry of a high number of submissions. While not all of these bugs were found by AI, it’s likely they had an AI-related component – even if it was just AI writing the submission. I should also point out the Pwn2Own Berlin occurs in just a few days, and it’s typical for vendors to patch as much as they can before the event.

None of the bugs patched by Microsoft this month are listed as publicly known or under active attack at the time of release, so we’ve got that going for us. Let’s take a closer look at some of the more interesting updates for this month, starting with a nasty-looking bug in DNS:

- CVE-2026-41096 - Windows DNS Client Remote Code Execution Vulnerability
This patch fixes a heap-based buffer overflow in the DNS Client triggered by a malicious DNS response. No authentication or user interaction needed, and since the DNS Client runs on virtually every Windows machine, the attack surface is enormous. An attacker with a position to influence DNS responses (MitM, rogue server) could achieve unauthenticated RCE across your enterprise.

- CVE-2026-41089 - Windows Netlogon Remote Code Execution Vulnerability
This update covers another CVSS 9.8 bug, which is a stack-based buffer overflow that lets an unauthenticated remote attacker execute code on a domain controller by sending a specially crafted network request — no credentials, no user interaction required. Yup – that makes it wormable. This is the highest-impact bug that requires immediate patching: a compromised domain controller is a compromised domain.

- CVE-2026-42898 - Microsoft Dynamics 365 On-Premises Remote Code Execution Vulnerability
This bug rates a CVSS 9.9(!) and represents a code injection in Dynamics 365. It allows any authenticated user to execute code with a scope change, meaning exploitation can break out and affect resources beyond the vulnerable component itself. Scope changes are pretty rare, so if you’re running Dynamics 365 On-Prem, definitely test and deploy this patch quickly.

- CVE-2026-40415 - Windows TCP/IP Remote Code Execution Vulnerability
This bug in the TCP/IP stack results from a use-after-free (UAF) and could allow a remote, unauthenticated threat actor to execute code without user interaction. That makes this another wormable bug. However, this one is much less likely to be exploited. The target needs to be under sustained low-memory (memory pressure) conditions, which is pretty rare. Still, no need to tempt fate here. Test and deploy this one quickly.

Here’s the full list of CVEs released by Microsoft for May 2026:

CVE	Title	Severity	CVSS	Public	Exploited	Type
CVE-2026-35435	Azure AI Foundry Elevation of Privilege Vulnerability	Critical	8.6	No	No	EoP
CVE-2026-35428	Azure Cloud Shell Spoofing Vulnerability	Critical	9.6	No	No	Spoofing
CVE-2026-42826	Azure DevOps Information Disclosure Vulnerability	Critical	10	No	No	Info
CVE-2026-32207	Azure Machine Learning Notebook Spoofing Vulnerability	Critical	8.8	No	No	Spoofing
CVE-2026-33109	Azure Managed Instance for Apache Cassandra Remote Code Execution Vulnerability	Critical	9.9	No	No	RCE
CVE-2026-33844	Azure Managed Instance for Apache Cassandra Remote Code Execution Vulnerability	Critical	9	No	No	RCE
CVE-2026-41105	Azure Monitor Action Group Notification System Elevation of Privilege Vulnerability	Critical	8.1	No	No	EoP
CVE-2026-33111	Copilot Chat (Microsoft Edge) Information Disclosure Vulnerability	Critical	7.5	No	No	Info
CVE-2026-26129	M365 Copilot Information Disclosure Vulnerability	Critical	7.5	No	No	Info
CVE-2026-26164	M365 Copilot Information Disclosure Vulnerability	Critical	7.5	No	No	Info
CVE-2026-33821	Microsoft Dynamics 365 Customer Insights Elevation of Privilege Vulnerability	Critical	7.7	No	No	EoP
CVE-2026-42898	Microsoft Dynamics 365 On-Premises Remote Code Execution Vulnerability	Critical	9.9	No	No	RCE
CVE-2026-40379	Microsoft Enterprise Security Token Service (ESTS) Spoofing Vulnerability	Critical	9.3	No	No	Spoofing
CVE-2026-40363	Microsoft Office Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-40358	Microsoft Office Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-34327	Microsoft Partner Center Spoofing Vulnerability	Critical	8.2	No	No	Spoofing
CVE-2026-40365	Microsoft SharePoint Server Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-41103	Microsoft SSO Plugin for Jira & Confluence Elevation of Privilege Vulnerability	Critical	9.1	No	No	EoP
CVE-2026-33823	Microsoft Team Events Portal Information Disclosure Vulnerability	Critical	9.6	No	No	Info
CVE-2026-40364	Microsoft Word Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-40366	Microsoft Word Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-40361	Microsoft Word Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-40367	Microsoft Word Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-42831	Office for Android Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-41096	Windows DNS Client Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-35421	Windows GDI Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-40403	Windows Graphics Component Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-40402	Windows Hyper-V Elevation of Privilege Vulnerability	Critical	9.3	No	No	EoP
CVE-2026-32161	Windows Native WiFi Miniport Driver Remote Code Execution Vulnerability	Critical	7.5	No	No	RCE
CVE-2026-41089	Windows Netlogon Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-32175	.NET Core Tampering Vulnerability	Important	4.3	No	No	Tampering
CVE-2026-32177	.NET Elevation of Privilege Vulnerability	Important	7.3	No	No	EoP
CVE-2026-35433	.NET Elevation of Privilege Vulnerability	Important	7.3	No	No	EoP
CVE-2025-54518 *	AMD: CVE-2025-54518 CPU OP Cache Corruption	Important		No	No	RCE
CVE-2026-42899	ASP.NET Core Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-40381	Azure Connected Machine Agent Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-42823 †	Azure Logic Apps Elevation of Privilege Vulnerability	Important	9.9	No	No	EoP
CVE-2026-33833	Azure Machine Learning Notebook Spoofing Vulnerability	Important	8.2	No	No	Spoofing
CVE-2026-32204	Azure Monitor Agent Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-42830	Azure Monitor Agent Metrics Extension Elevation of Privilege Vulnerability	Important	6.5	No	No	EoP
CVE-2026-33117	Azure SDK for Java Security Feature Bypass Vulnerability	Important	9.1	No	No	SFB
CVE-2026-41109	GitHub Copilot and Visual Studio Code Security Feature Bypass Vulnerability	Important	8.8	No	No	SFB
CVE-2026-35424	Internet Key Exchange (IKE) Protocol Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-41614	M365 Copilot for Desktop Spoofing Vulnerability	Important	6.2	No	No	Spoofing
CVE-2026-41100	Microsoft 365 Copilot for Android Spoofing Vulnerability	Important	4.4	No	No	Spoofing
CVE-2026-40377	Microsoft Cryptographic Services Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-41094	Microsoft Data Formulator Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-40417	Microsoft Dynamics 365 Business Central Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-42833	Microsoft Dynamics 365 On-Premises Remote Code Execution Vulnerability	Important	9.1	No	No	RCE
CVE-2026-42838	Microsoft Edge (Chromium-based) Elevation of Privilege Vulnerability	Important	5.4	No	No	EoP
CVE-2026-40360	Microsoft Excel Information Disclosure Vulnerability	Important	7.8	No	No	Info
CVE-2026-40359	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-40362	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-42832	Microsoft Excel Spoofing Vulnerability	Important	7.7	No	No	Spoofing
CVE-2026-34329	Microsoft Message Queuing (MSMQ) Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-40419	Microsoft Office Click-To-Run Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-40418	Microsoft Office Click-To-Run Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-35436	Microsoft Office Click-To-Run Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-40420	Microsoft Office Click-To-Run Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-42893	Microsoft Outlook for iOS Tampering Vulnerability	Important	7.4	No	No	Tampering
CVE-2026-40374	Microsoft Power Automate Desktop Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-41102	Microsoft PowerPoint for Android Spoofing Vulnerability	Important	7.1	No	No	Spoofing
CVE-2026-35439	Microsoft SharePoint Server Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-40368	Microsoft SharePoint Server Remote Code Execution Vulnerability	Important	8	No	No	RCE
CVE-2026-33110	Microsoft SharePoint Server Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-33112	Microsoft SharePoint Server Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-40357	Microsoft SharePoint Server Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-32185	Microsoft Teams Spoofing Vulnerability	Important	5.5	No	No	Spoofing
CVE-2026-41101	Microsoft Word for Android Spoofing Vulnerability	Important	7.1	No	No	Spoofing
CVE-2026-35440	Microsoft Word Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-40421	Microsoft Word Information Disclosure Vulnerability	Important	4.3	No	No	Info
CVE-2026-41097	Secure Boot Security Feature Bypass Vulnerability	Important	6.7	No	No	SFB
CVE-2026-40370 †	SQL Server Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-41613	Visual Studio Code Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-41612	Visual Studio Code Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-41611	Visual Studio Code Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-41610	Visual Studio Code Security Feature Bypass Vulnerability	Important	6.3	No	No	SFB
CVE-2026-33839	Win32k Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-33840	Win32k Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34330	Win32k Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34331	Win32k Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-35423	Windows 11 Telnet Client Information Disclosure Vulnerability	Important	5.4	No	No	Info
CVE-2026-35438	Windows Admin Center Elevation of Privilege Vulnerability	Important	8.3	No	No	EoP
CVE-2026-41086	Windows Admin Center in Azure Portal Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-34344	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34345	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-35416	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-41088	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34343	Windows Application Identity (AppID) Subsystem Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-35418	Windows Cloud Files Mini Filter Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-33835	Windows Cloud Files Mini Filter Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34337	Windows Cloud Files Mini Filter Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-40407	Windows Common Log File System Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-40397	Windows Common Log File System Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-42896	Windows DWM Core Library Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-35419	Windows DWM Core Library Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-34336	Windows DWM Core Library Information Disclosure Vulnerability	Important	7.8	No	No	Info
CVE-2026-33834	Windows Event Logging Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32209	Windows Filtering Platform (WFP) Security Feature Bypass Vulnerability	Important	4.4	No	No	SFB
CVE-2026-33841	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-35420	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-40369	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34332	Windows Kernel-Mode Driver Remote Code Execution Vulnerability	Important	8	No	No	RCE
CVE-2026-34339	Windows Lightweight Directory Access Protocol (LDAP) Denial of Service Vulnerability	Important	5.5	No	No	DoS
CVE-2026-34341	Windows Link-Layer Discovery Protocol (LLDP) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-33838	Windows Message Queuing (MSMQ) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34342	Windows Print Spooler Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-41095	Windows Projected File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34340	Windows Projected File System Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-40398	Windows Remote Desktop Services Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21530	Windows Rich Text Edit Elevation of Privilege Vulnerability	Important	6.7	No	No	EoP
CVE-2026-32170	Windows Rich Text Edit Elevation of Privilege Vulnerability	Important	6.7	No	No	EoP
CVE-2026-40410	Windows SMB Client Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-35415	Windows Storage Spaces Controller Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34350	Windows Storport Miniport Driver Denial of Service Vulnerability	Important	6.5	No	No	DoS
CVE-2026-40405	Windows TCP/IP Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-40414	Windows TCP/IP Denial of Service Vulnerability	Important	7.4	No	No	DoS
CVE-2026-40401	Windows TCP/IP Denial of Service Vulnerability	Important	6.2	No	No	DoS
CVE-2026-40413	Windows TCP/IP Denial of Service Vulnerability	Important	7.4	No	No	DoS
CVE-2026-35422	Windows TCP/IP Driver Security Feature Bypass Vulnerability	Important	6.5	No	No	SFB
CVE-2026-34351	Windows TCP/IP Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-40399	Windows TCP/IP Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34334	Windows TCP/IP Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-40406	Windows TCP/IP Information Disclosure Vulnerability	Important	7.5	No	No	Info
CVE-2026-33837	Windows TCP/IP Local Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-40415	Windows TCP/IP Remote Code Execution Vulnerability	Important	8.1	No	No	RCE
CVE-2026-42825	Windows Telephony Service Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-34338	Windows Telephony Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-40382	Windows Telephony Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-40380	Windows Volume Manager Extension Driver Remote Code Execution Vulnerability	Important	6.2	No	No	RCE
CVE-2026-40408	Windows WAN ARP Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34333	Windows Win32k Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34347	Windows Win32k Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-35417	Windows Win32k Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-42891	Microsoft Edge (Chromium-based) for Android Spoofing Vulnerability	Moderate	6.5	No	No	Spoofing
CVE-2026-35429	Microsoft Edge (Chromium-based) for Android Spoofing Vulnerability	Moderate	4.3	No	No	Spoofing
CVE-2026-41107	Microsoft Edge (Chromium-based) Information Disclosure Vulnerability	Moderate	7.4	No	No	Info
CVE-2026-40416	Microsoft Edge (Chromium-based) for Android Spoofing Vulnerability	Low	4.3	No	No	Spoofing

* Indicates this CVE had been released by a third party and is now being included in Microsoft releases.

† Indicates further administrative actions are required to fully address the vulnerability.

Looking at the other Critical-rated bugs in this month’s release, there are quite a few scary-looking bugs (including a CVSS 10!), but there’s no action for the end user as Microsoft has already mitigated these bugs and is just now documenting them. There’s also this month’s crop of Office bugs where the Preview Pane is an attack vector. However, the bug in Office for Android does not have the Preview Pane vector; it’s simple open and own. The bug in the WiFi driver needs a network adjacent attacker. The SharePoint bug requires authentication, but anyone with site privileges has the authentication needed. The bug in SSO Plugin for Jira & Confluence should really be called an authentication bypass, since it allows an unauthenticated attacker to gain access to a system.

Looking at the other code execution bugs, most are of the open and own variety as expected. The bug in Dynamic 365 (On Prem) requires high privileges. The Message Queueing bug requires an adjacent attacker. The bug in SQL Server requires authentication, but as usual, patching won’t be straightforward. Finally, there’s a bug in the kernel that leads to code execution. Most kernel bugs are privilege escalations, but this one could allow code execution if an attacker sends specially crafted NVMe over Fabrics (NVMe‑oF) response messages during the connection handshake process that contains an invalid header length value. Neat.

As usual, the vast majority of the Microsoft release fixes Elevation of Privilege (EoP) bugs. Also 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. There are also a few bugs that just state the attacker could “gain ELEVATED privileges.” How obtuse. The bugs in Azure allow an attacker to access data otherwise hidden from them. The Edge bug allows threat actors to elevate to the privileges of the running application. The bug in Visual Studio allows attackers to get permissions associated with the MCP Server’s managed identity. Finally, there are a couple of sandbox escapes, too, which are always useful.

This month's update includes six Security Feature Bypass vulnerabilities. The most severe is in the Azure SDK for Java (CVSS 9.1). An attacker over the network can bypass the integrity protection provided by authentication tags on encrypted data, effectively manipulating encrypted input in a way that slips past integrity checks during decryption. Close behind is the bypass affecting the GitHub Copilot integration in Visual Studio Code (CWE-74). This one requires a user interaction, but it allows an attacker to circumvent the path validation safeguards that normally control which files Copilot is permitted to modify. The other Visual Studio Code bypass involves cross-site scripting, improper link resolution, and information exposure triggered when a user opens or views a maliciously crafted notebook. On the Windows networking side there are two bypasses. The first hits the Windows TCP/IP driver via an authentication bypass using an alternate channel. The other impacts the Windows Filtering Platform through improper access control, allowing a local, low-privileged attacker to bypass FQDN-based network security rules. Finally, there’s a Secure Boot bypass that, you guessed it, bypasses secure boot features.

Moving on to the Information Disclosure bugs fixed this month, we have 15 different CVEs. As usual, the majority of these simply result in info leaks consisting of unspecified memory contents or memory addresses. The bug in Power Automate could expose data marked “Sensitive” within Power Automate Desktop flows. One of the Word bugs could disclose NLTM hashes. The bug in Edge could disclose your cookies, which seems rude. The bug in Visual Studio could expose file path information. Finally, there’s a bug in Telnet for Windows 11 that leaks information being used by Telnet at the time. I didn’t even realize Windows 11 still had a telnet client.

The May release contains 10 spoofing bugs (plus the ones already addressed by Microsoft). The bug in Azure Machine Learning Notebooks vulnerability requires user interaction, but it could expose info through the Azure ML web interface to the attacker. There’s a cluster of fixes for Microsoft's mobile Office suite on Android. Excel, Word, and PowerPoint for Android all carry spoofing flaws rooted in improper access control. Two Copilot products are also affected by spoofing vulns. The M365 Copilot for Desktop has no details provided. The M365 Copilot for Android variant requires low privileges and producing only limited impact on confidentiality and integrity. Microsoft Teams for Android rounds out the mobile app spoofing bugs. Three Edge bugs close things out, all involving misrepresentation of information in the browser UI.

There are two Tampering bugs in this month’s release. The one in .NET Core allows threat actors to write files to an affected system. The other is in Outlook for iOS and manifests as a command injection bug.

There are eight DoS bugs in the May release, but as always, Microsoft provides little to no actionable information about the vulnerabilities. The most interesting from a practical standpoint are two TCP/IP bugs that allow a low-privilege Hyper-V guest to crash the host. Both are triggered from the adjacent network. On the broader network-exposure side, the ASP.NET Core bug is a straightforward infinite loop condition — an unauthenticated attacker sends a crafted request over the network and the server stops responding.

No new advisories are being released this month.

Looking Ahead

Assuming I survive Pwn2Own Berlin (which is looking iffy at the moment), I’ll return on June 9th on what will hopefully be a smaller release than this one. Until then, stay safe, happy patching, and may all your reboots be smooth and clean!

The Apple macOS Security Update Review

Sat, 25 Jul 2026 19:02:56 +0200

We’ve received some feedback from those who read the Patch Blog that they would like something similar for macOS updates. Unfortunately, Apple doesn’t schedule these for a particular day, but we can provide our thoughts and analysis on the days they do release their latest patches.

For May 2026, Apple released 82 unique CVEs across the three macOS versions: 79 for macOS Tahoe 26.5, 45 for macOS Sequoia 15.7.7, and 42 for macOS Sonoma 14.8.7. Since Apple doesn’t provide CVSS scores or other severity information, we’re left to speculate on which of these bugs is the most severe. However, there are a couple that stand out.

- CVE-2026-28819 (Wi-Fi) stands out as the strongest candidate for the most severe as it states, “An app may be able to execute arbitrary code with kernel privileges.” The combination of arbitrary code execution at the kernel level is about as bad as it gets on a severity scale. Plus, it affects all three macOS versions (Tahoe, Sequoia, and Sonoma).

- CVE-2026-43668 (mDNSResponder) also piques my interest since, “A remote attacker may be able to cause unexpected system termination or corrupt kernel memory.” The remote attack vector with kernel memory corruption on all three OS versions makes this a serious one, especially since mDNSResponder is always running.

- CVE-2026-28972 (Kernel) This one states that “An app may be able to cause unexpected system termination or write kernel memory.” An out-of-bounds write directly into kernel memory on all three OS versions. This one may also have implications in the upcoming Pwn2Own Berlin contest.

Here’s a look at all the bugs released by Apple this month:

82Unique CVEs 79macOS Tahoe 26.5 45macOS Sequoia 15.7.7 42macOS Sonoma 14.8.7

CVE ID	Component	Impact	macOS Tahoe 26.5	macOS Sequoia 15.7.7	macOS Sonoma 14.8.7
CVE-2026-28991	Accelerate	An app may be able to cause a denial-of-service	Yes	No	No
CVE-2026-28988	Accounts	An app may be able to bypass certain Privacy preferences	Yes	No	No
CVE-2026-28959	APFS	An app may be able to cause unexpected system termination	Yes	Yes	Yes
CVE-2026-28995	App Intents	A malicious app may be able to break out of its sandbox	Yes	No	No
CVE-2026-1837	AppleJPEG	Processing a maliciously crafted image may lead to a denial-of-service	Yes	No	No
CVE-2026-28956	AppleJPEG	Processing a maliciously crafted media file may lead to unexpected app termination or corrupt process memory	Yes	Yes	Yes
CVE-2026-39869	Audio	Processing an audio stream in a maliciously crafted media file may terminate the process	Yes	Yes	Yes
CVE-2026-28922	CoreMedia	An app may be able to access private information	Yes	Yes	Yes
CVE-2026-28936	CoreServices	Processing a maliciously crafted file may lead to unexpected app termination	Yes	No	Yes
CVE-2026-28918	CoreSymbolication	Parsing a maliciously crafted file may lead to an unexpected app termination	Yes	No	No
CVE-2026-28878	Crash Reporter	An app may be able to enumerate a user's installed apps	No	Yes	No
CVE-2026-28915	CUPS	An app may be able to gain root privileges	Yes	Yes	Yes
CVE-2026-43659	FileProvider	An app may be able to access sensitive user data	Yes	Yes	Yes
CVE-2026-28923	GPU Drivers	A malicious app may be able to break out of its sandbox	Yes	Yes	Yes
CVE-2026-28925	HFS	An app may be able to cause unexpected system termination or write kernel memory	Yes	Yes	Yes
CVE-2025-43524	Icons	An app may be able to break out of its sandbox	No	Yes	Yes
CVE-2026-43661	ImageIO	Processing a maliciously crafted image may corrupt process memory	Yes	No	No
CVE-2026-28977	ImageIO	Processing a maliciously crafted file may lead to unexpected app termination	Yes	Yes	Yes
CVE-2026-28990	ImageIO	Processing a maliciously crafted image may corrupt process memory	Yes	Yes	Yes
CVE-2026-28978	Installer	A malicious app may be able to break out of its sandbox	Yes	Yes	Yes
CVE-2026-28992	IOHIDFamily	An attacker may be able to cause unexpected app termination	Yes	Yes	Yes
CVE-2026-28943	IOHIDFamily	An app may be able to determine kernel memory layout	Yes	Yes	Yes
CVE-2026-28969	IOKit	An app may be able to cause unexpected system termination	Yes	Yes	Yes
CVE-2026-43655	IOSurfaceAccelerator	An app may be able to cause unexpected system termination or read kernel memory	Yes	No	No
CVE-2026-43654	Kernel	An app may be able to disclose kernel memory	Yes	Yes	Yes
CVE-2026-28908	Kernel	An app may be able to modify protected parts of the file system	Yes	Yes	Yes
CVE-2026-28954	Kernel	A maliciously crafted disk image may bypass Gatekeeper checks	Yes	Yes	Yes
CVE-2026-28897	Kernel	A local user may be able to cause unexpected system termination or read kernel memory	Yes	Yes	Yes
CVE-2026-28952	Kernel	An app may be able to cause unexpected system termination	Yes	Yes	Yes
CVE-2026-28951	Kernel	An app may be able to gain root privileges	Yes	Yes	Yes
CVE-2026-28972	Kernel	An app may be able to cause unexpected system termination or write kernel memory	Yes	Yes	Yes
CVE-2026-28986	Kernel	An app may be able to cause unexpected system termination	Yes	Yes	Yes
CVE-2026-28987	Kernel	An app may be able to leak sensitive kernel state	Yes	Yes	Yes
CVE-2026-28983	LaunchServices	A remote attacker may be able to cause a denial of service	Yes	No	No
CVE-2026-28929	Mail Drafts	Replying to an email could display remote images in Mail in Lockdown Mode	Yes	Yes	Yes
CVE-2026-43653	mDNSResponder	An attacker on the local network may be able to cause a denial-of-service	Yes	No	Yes
CVE-2026-28985	mDNSResponder	An attacker on the local network may be able to cause a denial-of-service	Yes	No	No
CVE-2026-43668	mDNSResponder	A remote attacker may be able to cause unexpected system termination or corrupt kernel memory	Yes	Yes	Yes
CVE-2026-43666	mDNSResponder	An attacker on the local network may be able to cause a denial-of-service	Yes	Yes	Yes
CVE-2026-28941	Model I/O	Processing a maliciously crafted file may lead to a denial-of-service or potentially disclose memory contents	Yes	Yes	No
CVE-2026-28940	Model I/O	Processing a maliciously crafted image may corrupt process memory	Yes	Yes	No
CVE-2026-28961	Network Extensions	An attacker with physical access to a locked device may be able to view sensitive user information	Yes	No	No
CVE-2026-28906	Networking	An attacker may be able to track users through their IP address	Yes	Yes	Yes
CVE-2026-28840	PackageKit	An app may be able to gain root privileges	No	Yes	Yes
CVE-2026-43656	Quick Look	Parsing a maliciously crafted file may lead to an unexpected app termination	Yes	Yes	Yes
CVE-2026-43652	Sandbox	An app may be able to access protected user data	Yes	No	No
CVE-2026-39870	SceneKit	Processing a maliciously crafted image may corrupt process memory	Yes	Yes	Yes
CVE-2026-28846	SceneKit	A remote attacker may be able to cause unexpected app termination	Yes	Yes	Yes
CVE-2026-28993	Shortcuts	An app may be able to access user-sensitive data	Yes	Yes	Yes
CVE-2026-28848	SMB	A remote attacker may be able to cause unexpected system termination	Yes	Yes	No
CVE-2026-28930	Spotlight	An app may be able to access protected user data	Yes	No	No
CVE-2026-28974	Spotlight	An app may be able to cause a denial-of-service	Yes	Yes	No
CVE-2026-28996	Storage	An app may be able to access sensitive user data	Yes	Yes	Yes
CVE-2026-28919	StorageKit	An app may be able to gain root privileges	Yes	Yes	Yes
CVE-2026-28924	Sync Services	An app may be able to access Contacts without user consent	Yes	Yes	Yes
CVE-2026-39871	TV App	An app may be able to observe unprotected user data	Yes	Yes	Yes
CVE-2026-28976	UserAccountUpdater	An app may be able to gain root privileges	Yes	No	No
CVE-2026-43660	WebKit	Processing maliciously crafted web content may prevent Content Security Policy from being enforced	Yes	No	No
CVE-2026-28907	WebKit	Processing maliciously crafted web content may prevent Content Security Policy from being enforced	Yes	No	No
CVE-2026-28962	WebKit	Processing maliciously crafted web content may disclose sensitive user information	Yes	No	No
CVE-2026-43658	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	No	No
CVE-2026-28905	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28847	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28904	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28955	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28903	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28953	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28902	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28901	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28913	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28883	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28958	WebKit	An app may be able to access sensitive user data	Yes	No	No
CVE-2026-28917	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28947	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	No	No
CVE-2026-28946	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	No	No
CVE-2026-28942	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	No	No
CVE-2026-28971	WebKit	A malicious iframe may use another website's download settings	Yes	No	No
CVE-2026-28944	WebRTC	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	No	No
CVE-2026-28819	Wi-Fi	An app may be able to execute arbitrary code with kernel privileges	Yes	Yes	Yes
CVE-2026-28994	Wi-Fi	An attacker in a privileged network position may be able to perform denial-of-service attack using crafted Wi-Fi packets	Yes	Yes	Yes
CVE-2026-28914	zip	A maliciously crafted ZIP archive may bypass Gatekeeper checks	Yes	No	No
CVE-2026-28920	zlib	Visiting a maliciously crafted website may leak sensitive data	Yes	Yes	Yes

CVEs marked with the scarab logo were reported through the TrendAI Zero Day Initiative program.

We’ll continue these macOS updates if people find them useful. Stay tuned for the regularly schedule Patch Tuesday blog covering Adobe and Microsoft.

The June 2026 Security Update Review

Sat, 25 Jul 2026 19:02:53 +0200

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:

Adobe Patches for June 2026

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.

Here’s this month’s overview table:

Bulletin ID	Product	CVE Count	Highest Severity	Highest CVSS	Exploited	Deployment Priority
APSB26-66	Adobe Campaign Classic	2	Critical	10.0	No	1
APSB26-64	Adobe ColdFusion	7	Critical	9.6	No	1
APSB26-63	Adobe Acrobat Reader	20	Critical	7.8	No	2
APSB26-57	Adobe Experience Manager Forms	3	Critical	9.3	No	2
APSB26-62	Adobe Dreamweaver	5	Critical	8.6	No	3
APSB26-65	Adobe Format Plugins	2	Critical	7.8	No	3
APSB26-59	Adobe InCopy	3	Critical	7.8	No	3
APSB26-58	Adobe InDesign	12	Critical	7.8	No	3
APSB26-60	Adobe Substance 3D Sampler	4	Critical	7.8	No	3
APSB26-61	Content Credentials SDK	8	Critical	7.5	No	3
APSB26-56	Adobe Experience Manager	57	Important	5.4	No	3
TOTAL	11 bulletins	123

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.

Microsoft Patches for June 2026

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.

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.

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.

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.

- CVE-2026-41091 - Microsoft Defender Elevation of Privilege Vulnerability
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.

- CVE-2026-45657 - Windows Kernel Remote Code Execution Vulnerability
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.

- CVE-2026-47291 - HTTP.sys Remote Code Execution Vulnerability
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.

- CVE-2026-44815 - DHCP Client Service Remote Code Execution Vulnerability
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.

- CVE-2026-45585/CVE-2026-50507 - Windows BitLocker Security Feature Bypass Vulnerability
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 “bone shattering” 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.

Here’s the full list of CVEs released by Microsoft for June 2026:

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

* Indicates this CVE had been released by a third party and is now being included in Microsoft releases.

† Indicates further administrative actions are required to fully address the vulnerability.

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.

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.

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.

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.

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.

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.

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.

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.

No new advisories are being released this month.

Looking Ahead

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!

The June 2026 Apple Security Update Review

Sat, 25 Jul 2026 19:02:52 +0200

We’re back with our look at the Apple macOS and iOS security updates. As this is a new feature for us, please let us know your feedback on the blog.

For Jun 2026, Apple released 37 unique CVEs across iOS 26.5.2 / iPadOS 26.5.2, macOS Tahoe 26.5.2, Safari 26.5.2. Since Apple doesn’t provide CVSS scores or other severity information, we’re left to speculate on which of these bugs is the most severe. The overwhelming majority (31 of 37) are WebKit/WebRTC bugs reachable through malicious web content. Most of those are crash/DoS bugs rather than code execution, so the real risk lives in the small set of kernel bugs and the handful of WebKit sandbox escapes. However, there are a couple that stand out.

- CVE-2026-43724 (Kernel) – According to Apple, “An app may be able to cause unexpected system termination or write kernel memory.” A kernel memory write is the highest-value primitive here: it's the privilege-escalation half of a full exploit chain and leads to complete device control. The bug was credited to Hyunwoo Kim (@v4bel), who is known to be a serious kernel researcher.

- CVE-2026-39868 (Kernel) – Another kernel bug, this one could “cause unexpected system termination or corrupt kernel memory.” This is kernel memory corruption, and notably credited to a roster of elite offensive researchers (STAR Labs, Positive Technologies, Baidu Security). This kind of attribution usually signals a weaponizable, possibly Pwn2Own-grade bug rather than a theoretical crash.

- CVE-2026-43725 / CVE-2026-43701 (WebKit) – Apple states these bugs could allow a website to process restricted web content outside the sandbox. I'm flagging this sandbox-escape pair over the many WebKit crash bugs because a sandbox escape is the bridge that turns a web-content bug into a path toward the kernel issues above. It's the most dangerous remotely-triggered class in the release.

Here’s a look at all the bugs released by Apple this month:

Apple Security Update – June 29, 2026 37Total CVEs 22Denial of Service 7Information Disclosure 3Memory Corruption 2Elevation of Privilege 2Sandbox Escape 1Spoofing

Apple security release — June 29, 2026. "Yes/No" indicates whether each update is affected. CVE IDs link to NVD.
CVE ID	Component	Impact	iOS 26.5.2 / iPadOS 26.5.2	macOS Tahoe 26.5.2	Safari 26.5.2
CVE-2026-43743	IOGPUFamily	An app may be able to cause unexpected system termination	Yes	Yes	No
CVE-2026-39868	Kernel	An app may be able to cause unexpected system termination or corrupt kernel memory	Yes	Yes	No
CVE-2026-43722	Kernel	An app may be able to leak sensitive kernel state	Yes	Yes	No
CVE-2026-43724	Kernel	An app may be able to cause unexpected system termination or write kernel memory	Yes	Yes	No
CVE-2026-43703	libxslt	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	No
CVE-2026-43706	libxslt	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	No
CVE-2026-43704	Web Extensions	A malicious web extension may be able to cause an unexpected process crash	Yes	Yes	Yes
CVE-2026-39872	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43663	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43676	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43699	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43700	WebKit	Processing maliciously crafted web content may disclose sensitive user information	Yes	Yes	Yes
CVE-2026-43701	WebKit	A malicious website may be able to process restricted web content outside the sandbox	Yes	Yes	Yes
CVE-2026-43705	WebKit	Processing maliciously crafted web content may lead to memory corruption	Yes	Yes	Yes
CVE-2026-43707	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43708	WebKit	A malicious website may exfiltrate data cross-origin	Yes	Yes	Yes
CVE-2026-43709	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43712	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43713	WebKit	Visiting a website may leak sensitive data	Yes	Yes	Yes
CVE-2026-43715	WebKit	Processing maliciously crafted web content may lead to memory corruption	Yes	Yes	Yes
CVE-2026-43716	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43725	WebKit	A malicious website may be able to process restricted web content outside the sandbox	Yes	Yes	Yes
CVE-2026-43726	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43727	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43731	WebKit	Processing maliciously crafted web content may lead to memory corruption	Yes	Yes	Yes
CVE-2026-43732	WebKit	Processing maliciously crafted web content may disclose sensitive user information	Yes	Yes	Yes
CVE-2026-43734	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43735	WebKit	A malicious website may exfiltrate data cross-origin	Yes	Yes	Yes
CVE-2026-43740	WebKit	Processing maliciously crafted web content may result in the disclosure of process memory	Yes	Yes	Yes
CVE-2026-43742	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43745	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43720	WebKit Canvas	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43721	WebKit Storage	A malicious website may be able to silently hijack clipboard data	Yes	Yes	Yes
CVE-2026-28979	WebRTC	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43717	WebRTC	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43718	WebRTC	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43746	WebRTC	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes

We’ll continue these macOS updates if people find them useful. Stay tuned for the regularly schedule Patch Tuesday blog covering Adobe and Microsoft.

The July 2026 Security Update Review

Sat, 25 Jul 2026 19:02:51 +0200

Well folks. Here we are. The bug apocalypse has fully descended upon us. I’ll do my best to sort this out in some way meaningful, but this month’s release shows us the nay-sayers were right, and I’ve got to hand it to the nay-sayers here. Excellent call. Take an extended break from your regularly scheduled activities as we 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:

Adobe Patches for July 2026

Adobe has now moved to a bimonthly release schedule, which means they will be releasing patches on the second and fourth Tuesdays of the month. I’ll continue to cover the second Tuesday release here and update this blog should the fourth Tuesday release contain anything significant. I think this is a smart way to break up a monster release into something a bit more manageable. Apple has said they are taking a similar approach. We’ll see if other vendors follow their lead.

For the first part of the July release, Adobe released 12 bulletins addressing 88 unique CVEs in Adobe ColdFusion, Commerce, After Effects, Animate, Audition, Bridge, Creative Cloud Desktop Application, Experience Manager, Illustrator, Media Encoder, Premiere Pro, and the Content Credentials SDK.

Here’s this month’s overview table:

Bulletin ID	Product	CVE Count	Highest Severity	Highest CVSS	Exploited	Deployment Priority
APSB26-82	Adobe ColdFusion	13	Critical	9.9	No	1
APSB26-73	Adobe Commerce	13	Critical	9.6	No	2
APSB26-78	Adobe After Effects	3	Critical	7.8	No	3
APSB26-83	Adobe Animate	6	Critical	8.6	No	3
APSB26-71	Adobe Audition	6	Critical	7.8	No	3
APSB26-81	Adobe Bridge	6	Critical	7.8	No	3
APSB26-77	Adobe Creative Cloud Desktop Application	2	Critical	8.1	No	3
APSB26-74	Adobe Experience Manager	13	Critical	9.6	No	3
APSB26-79	Adobe Illustrator	5	Critical	9.3	No	3
APSB26-72	Adobe Media Encoder	5	Critical	7.8	No	3
APSB26-76	Adobe Premiere Pro	4	Critical	7.8	No	3
APSB26-80	Content Credentials SDK	12	Critical	8.2	No	3
TOTAL	12 bulletins	88

While nothing is under active exploit, I would prioritize the Cold Fusion and Commerce patches first. The patch for Cold Fusion even clocks in with a CVSS 9.9 bug. Beyond that, most of these updates are pretty straightforward. If you’re using these products, patch them. However, you can use you regular patch cadence here.

Microsoft Patches for July 2026

Here it is. The Mother of All Releases. To call this record-breaking is an understatement. How to count this mess is anyone’s guess, but I see new Microsoft 621 CVEs for the month of July. Some of these are in online services where no user action is required. They also list about 480 bugs in Chromium and Microsoft Edge (Chromium-based) that I won’t cover here. Here’s how I put this in context. I looked at the last 20 years of Microsoft releases. The CVE count year-to-date exceeds all other years’ totals.

The products covered this month are also astonishing. There are patches for Windows and Windows components, Office and Office Components, Microsoft Edge (Chromium-based), Azure, .NET and Visual Studio, Github Copilot, Defender, Exchange Server, Hyper-V, Ages of Empire II, and Minecraft Server (really!). That phrase “Windows components” does some pretty heavy lifting here, too, as just about everything you’ve ever heard of is getting patched. All told, there are 63 rated Critical, six rated Moderate, one rated Low, with the rest rated Important in severity. Eight of these bugs were submitted through the ZDI program (more on that later). Two CVEs are listed as under active exploit while one other is listed as publicly known.

So how do we eat this elephant? One byte at a time (pun intended). Let’s start by looking a closer look at some of the more interesting updates for this month, starting with the bugs being exploited in the wild.

- CVE-2026-56155 - Active Directory Federation Services Elevation of Privilege Vulnerability
This is one of several AD FS being patched this month, but it’s the only one being actively exploited. It stems from insufficient access-control granularity and does require local access and low privileges to start, but AD FS is exactly the kind of identity infrastructure attackers love to pivot through once they're in. It can also be paired with an RCE as we often see in ransomware. Test and deploy this patch quickly.

- CVE-2026-56164 - Microsoft SharePoint Server Elevation of Privilege Vulnerability
The other bug being exploited in the wild this month is a modest CVSS 5.3 – but it shows why Moderate severity bugs still matter. It's a missing-authentication flaw, meaning an unauthenticated attacker can hit it over the network with no user interaction required. When something this reachable is being actively abused, patch it now and worry about the score later.

- CVE-2026-57092 - Microsoft Windows VMSwitch Elevation of Privilege Vulnerability
This patch rates the highest CVSS score for the month: a solid 9.9. It’s a use-after-free that lets a low-privileged attacker escalate to full host compromise across a VM boundary. We saw something like this demonstrated at Pwn2Own Berlin on ESXi, but it clearly isn’t alone. If you’re using VMSwitch in your Hyper-V deployments (and you likely are), test and deploy this one quickly.

- CVE-2026-50522/58644 - Microsoft SharePoint Remote Code Execution Vulnerability
This matching pair of CVSS 9.8 bugs results from the deserialization-of-untrusted-data and are reachable without authentication or user interaction. CVE-2026-50522 was demonstrated during Pwn2Own Berlin, so it’s odd to see Microsoft list it as “Exploit Maturity Unknown” since we literally handed them a working exploit. Just another reason to do your own risk assessment and not rely 100% on the vendor. If you have any Internet accessible SharePoint servers, test and deploy this patch quickly.

- CVE-2026-56190 - Remote Desktop Protocol Remote Code Execution Vulnerability
This patch covers an unauthenticated, network-reachable, no user interaction required bug. The root cause is a classic one: use of uninitialized resource (CWE-908), meaning specially crafted RDP traffic can interact with memory that was never properly initialized, letting an attacker corrupt memory and potentially steer code execution. RDP Servers are a common target, so audit your systems to see which are internet accessible and start from there.

- CVE-2026-55008 - Microsoft Exchange Server Spoofing Vulnerability
Ignore the title here and treat this like the XSS bug it is. The vulnerability is listed as a CVSS 9.6 since it’s a stored cross-site scripting flaw in Outlook Web Access, with a scope-changed impact that lets it break out of the web app context entirely. An attacker sends a specially crafted email, and if the victim simply opens it in OWA, arbitrary JavaScript executes in their browser session — no attachment needed, no macro warning, just viewing the message does it. If you’re using OWA, test and deploy this one quickly.

- CVE-2026-50518 - Windows DHCP Server Remote Code Execution Vulnerability
There are a couple of these DHCP RCE patches in this release, but the other has caveats while this one does not. Both are heap-based buffer overflows scoring CVSS 9.8, both unauthenticated and network-reachable. If you're running DHCP Server role on anything Internet-adjacent (you're not, right?), these move to the top of the list.

- CVE-2026-56188 - Windows Server Network driver Remote Code Execution Vulnerability
Another Critical-rated bug, this one is caused by a race condition. It’s always fun to see a TOCTOU bug rated this high, since race conditions are notoriously finicky to exploit reliably. While it may prove tricky to exploit, this bug could allow an attacker to execute privileged code over the network without user interaction. Don’t let the race condition lull you to sleep on a wormable bug.

- CVE-2026-55010 - Minecraft Bedrock Dedicated Server Remote Code Execution Vulnerability
File this in the “why not” category. This bug is a heap-based buffer overflow in Minecraft Bedrock Dedicated Server, also CVSS 9.8 and also unauthenticated RCE. Yes, your kid’s Minecraft server (it is your kid’s server, right?) is exposed to the same class of bug as your DHCP infrastructure. Patch it anyway.

Here’s the full list of CVEs released by Microsoft for July 2026:

CVE	Title	Severity	CVSS	Public	Exploited	Type
CVE-2026-56155	Active Directory Federation Services Elevation of Privilege Vulnerability	Important	7.8	No	Yes	EoP
CVE-2026-56164	Microsoft SharePoint Server Elevation of Privilege Vulnerability	Moderate	5.3	No	Yes	EoP
CVE-2026-50661	Windows BitLocker Security Feature Bypass Vulnerability	Important	6.1	Yes	No	SFB
CVE-2026-54121	Active Directory Certificate Services Elevation of Privilege Vulnerability	Critical	8.8	No	No	EoP
CVE-2026-45499 **	Azure OpenAI Elevation of Privilege Vulnerability	Critical	9.9	No	No	EoP
CVE-2026-48564	DHCP Server Service Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-50370	DHCP Server Service Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-56159	DHCP Server Service Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-50382	DirectX Graphics Kernel Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-41106 **	Microsoft 365 Copilot Elevation of Privilege Vulnerability	Critical	9.3	No	No	EoP
CVE-2026-26145 **	Microsoft Azure Synapse Elevation of Privilege Vulnerability	Critical	4.8	No	No	EoP
CVE-2026-48561	Microsoft Copilot Remote Code Execution Vulnerability	Critical	9.6	No	No	RCE
CVE-2026-55011	Microsoft Defender Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55012	Microsoft Defender Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55944	Microsoft Dynamics NAV and Microsoft Dynamics 365 Business Central (On Premises) Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-57100 **	Microsoft Entra Provisioning Service Elevation of Privilege Vulnerability	Critical	9.9	No	No	EoP
CVE-2026-55041	Microsoft Excel Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-54998 **	Microsoft Exchange Online Elevation of Privilege Vulnerability	Critical	8.8	No	No	EoP
CVE-2026-55008	Microsoft Exchange Server Spoofing Vulnerability	Critical	9.6	No	No	Spoofing
CVE-2026-54992	Microsoft Message Queuing Queue Manager Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-50314	Microsoft Office Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-50467	Microsoft Office Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55018	Microsoft Office Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55022	Microsoft Office Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55045	Microsoft Office Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-55049	Microsoft Office Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55129	Microsoft Office Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55056	Microsoft Office Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55140	Microsoft Office Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55043	Microsoft PowerPoint Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55123	Microsoft PowerPoint Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55120	Microsoft PowerPoint Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-50522	Microsoft SharePoint Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-58644	Microsoft SharePoint Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-55040	Microsoft SharePoint Server Security Feature Bypass Vulnerability	Critical	9.1	No	No	SFB
CVE-2026-54117	Microsoft SQL Server Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-54118	Microsoft SQL Server Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-50655	Microsoft Windows Media Foundation Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-56189	Microsoft Windows Media Foundation Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-57090	Microsoft Windows Media Foundation Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-57094	Microsoft Windows Media Foundation Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-57087	Microsoft Windows Media Foundation Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-57092	Microsoft Windows VMSwitch Elevation of Privilege Vulnerability	Critical	9.9	No	No	EoP
CVE-2026-55033	Microsoft Word Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55127	Microsoft Word Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55132	Microsoft Word Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-55010	Minecraft Bedrock Dedicated Server Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-50474	Remote Desktop Client Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-49164	Windows Active Directory Domain Services Remote Code Execution Vulnerability	Critical	8.1	No	No	RCE
CVE-2026-54128	Windows DHCP Client Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-50518	Windows DHCP Server Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-49796	Windows GDI+ Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-50380	Windows GDI+ Remote Code Execution Vulnerability	Critical	9.6	No	No	RCE
CVE-2026-54127	Windows Hyper-V Elevation of Privilege Vulnerability	Critical	7.4	No	No	EoP
CVE-2026-50680	Windows Hyper-V Elevation of Privilege Vulnerability	Critical	8.2	No	No	EoP
CVE-2026-50327	Windows Media Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-58542	Windows Media Remote Code Execution Vulnerability	Critical	7.8	No	No	RCE
CVE-2026-58608	Windows Print Spooler Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-54982	Windows Reliable Multicast Transport Driver (RMCAST) Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-54995	Windows Reliable Multicast Transport Driver (RMCAST) Remote Code Execution Vulnerability	Critical	8.1	No	No	RCE
CVE-2026-42982	Windows Secure Kernel Mode Elevation of Privilege Vulnerability	Critical	7.8	No	No	EoP
CVE-2026-50392	Windows Secure Kernel Mode Elevation of Privilege Vulnerability	Critical	7	No	No	EoP
CVE-2026-50694	Windows Secure Socket Tunneling Protocol (SSTP) Remote Code Execution Vulnerability	Critical	8.1	No	No	RCE
CVE-2026-56188	Windows Server Network driver Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-50444	Windows Server Update Service (WSUS) Elevation of Privilege Vulnerability	Critical	8.8	No	No	EoP
CVE-2026-54999	Windows TCP/IP Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-47302	.NET Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50525	.NET Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50651	.NET Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-57108	.NET Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50524	.NET Framework Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50527	.NET Framework Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50648	.NET Framework Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50650	.NET Framework Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50646	.NET Framework Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50649	.NET Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-47304	.NET Security Feature Bypass Vulnerability	Important	8.1	No	No	SFB
CVE-2026-50528	.NET Security Feature Bypass Vulnerability	Important	8.2	No	No	SFB
CVE-2026-50659	.NET Spoofing Vulnerability	Important	6.5	No	No	Spoofing
CVE-2026-50526	.NET Tampering Vulnerability	Important	7	No	No	Tampering
CVE-2026-50682	Active Directory Denial of Service Vulnerability	Important	7.1	No	No	DoS
CVE-2026-55001	Active Directory Domain Services Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50647	Active Directory Federation Server Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50684	Active Directory Federation Server Spoofing Vulnerability	Important	4.8	No	No	Spoofing
CVE-2026-56170	ASP.NET Core Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-47300	ASP.NET Core Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-47303	ASP.NET Core Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-50652	Azure Active Directory Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50653	Azure Active Directory Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-57969	Azure CycleCloud Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-58279	Azure CycleCloud Elevation of Privilege Vulnerability	Important	6.5	No	No	EoP
CVE-2026-47632	Azure Monitor Agent Metrics Extension Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-50338	Azure Spring Apps Elevation of Privilege Vulnerability	Important	8.2	No	No	EoP
CVE-2026-50488	Clipboard User Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50491	Code Integrity DLL (ci.dll) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50381	Composite Image File System driver (cimfs.sys) Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50427	Content Delivery Manager Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50692	Desktop Window Manager Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-58633	Desktop Window Manager Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58634	Desktop Window Manager Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50296	DirectX Graphics Kernel Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50375	DirectX Graphics Kernel Elevation of Privilege Vulnerability	Important	6.3	No	No	EoP
CVE-2026-50353	DirectX Graphics Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50493	DirectX Graphics Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-56643	DirectX Graphics Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-56644	DirectX Graphics Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58629	DirectX Graphics Kernel Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-49174	DNS Client Tampering Vulnerability	Important	6.1	No	No	Tampering
CVE-2026-50495	DNS Client Tampering Vulnerability	Important	6.1	No	No	Tampering
CVE-2026-57088	Extensible Storage Engine (ESENT) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50663	Game: Age of Empires II: Definitive Edition Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-47282	GitHub Copilot and Visual Studio Code Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-41109	GitHub Copilot and Visual Studio Code Security Feature Bypass Vulnerability	Important	8.8	No	No	SFB
CVE-2026-50510	GitHub Copilot Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-49787	HTTP.sys Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50420	HTTP.sys Information Disclosure Vulnerability	Important	6.2	No	No	Info
CVE-2026-49788	HTTP/2 Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50696	Internet Key Exchange (IKE) Protocol Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-58617	M365 Copilot for iOS Elevation of Privilege Vulnerability	Important	8.1	No	No	EoP
CVE-2026-58595	Microsoft Bing App for IOS Spoofing Vulnerability	Important	8.1	No	No	Spoofing
CVE-2026-49162	Microsoft Brokering File System Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50305	Microsoft Brokering File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50361	Microsoft Brokering File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50466	Microsoft Brokering File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50458	Microsoft Brokering File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50658	Microsoft Defender for Endpoint for Mac Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-56178	Microsoft Defender for Endpoint for Mac Elevation of Privilege Vulnerability	Important	5.5	No	No	EoP
CVE-2026-50657	Microsoft Defender for Endpoint for Mac Information Disclosure Vulnerability	Important	4.7	No	No	Info
CVE-2026-50329	Microsoft DWM Core Library Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58541	Microsoft DWM Core Library Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58596	Microsoft Edge (Chromium-based) Elevation of Privilege Vulnerability	Important	8.3	No	No	EoP
CVE-2026-57991	Microsoft Edge (Chromium-based) Information Disclosure Vulnerability	Important	7.4	No	No	Info
CVE-2026-58291	Microsoft Edge (Chromium-based) Information Disclosure Vulnerability	Important	6.1	No	No	Info
CVE-2026-57981	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-57984	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-57985	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	7.6	No	No	RCE
CVE-2026-57986	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-57988	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	7.1	No	No	RCE
CVE-2026-57992	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-58276	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-56645	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-57974	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-57975	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-58281	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	8.3	No	No	RCE
CVE-2026-58284	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	8.3	No	No	RCE
CVE-2026-58285	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	8.3	No	No	RCE
CVE-2026-58287	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	8.3	No	No	RCE
CVE-2026-58288	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	8.3	No	No	RCE
CVE-2026-58289	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	9	No	No	RCE
CVE-2026-58290	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-58292	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-58293	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	8.1	No	No	RCE
CVE-2026-58294	Microsoft Edge (Chromium-based) Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-57983	Microsoft Edge (Chromium-based) Security Feature Bypass Vulnerability	Important	8.7	No	No	SFB
CVE-2026-58295	Microsoft Edge (Chromium-based) Security Feature Bypass Vulnerability	Important	8.3	No	No	SFB
CVE-2026-58525	Microsoft Edge (Chromium-based) Security Feature Bypass Vulnerability	Important	8.2	No	No	SFB
CVE-2026-57987	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Important	6.5	No	No	Spoofing
CVE-2026-58278	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Important	5.4	No	No	Spoofing
CVE-2026-56646	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Important	6.5	No	No	Spoofing
CVE-2026-57977	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Important	7.1	No	No	Spoofing
CVE-2026-57993	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Important	7.4	No	No	Spoofing
CVE-2026-58282	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Important	8.1	No	No	Spoofing
CVE-2026-58283	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Important	8.1	No	No	Spoofing
CVE-2026-58286	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Important	8.1	No	No	Spoofing
CVE-2026-58298	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Important	7.2	No	No	Spoofing
CVE-2026-58524	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Important	5.4	No	No	Spoofing
CVE-2026-58296	Microsoft Edge for Android Information Disclosure Vulnerability	Important	7.1	No	No	Info
CVE-2026-58297	Microsoft Edge for Android Information Disclosure Vulnerability	Important	7.1	No	No	Info
CVE-2026-58300	Microsoft Edge for Android Information Disclosure Vulnerability	Important	6.2	No	No	Info
CVE-2026-58522	Microsoft Edge for Android Information Disclosure Vulnerability	Important	6.8	No	No	Info
CVE-2026-58299	Microsoft Edge for Android Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-58523	Microsoft Edge for Android Security Feature Bypass Vulnerability	Important	6.5	No	No	SFB
CVE-2026-50678	Microsoft Excel Information Disclosure Vulnerability	Important	6.6	No	No	Info
CVE-2026-54988	Microsoft Excel Information Disclosure Vulnerability	Important	6.1	No	No	Info
CVE-2026-48580	Microsoft Excel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50408	Microsoft Excel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55046	Microsoft Excel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55138	Microsoft Excel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55054	Microsoft Excel Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-55122	Microsoft Excel Information Disclosure Vulnerability	Important	7.1	No	No	Info
CVE-2026-55898	Microsoft Excel Information Disclosure Vulnerability	Important	6.1	No	No	Info
CVE-2026-50675	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55899	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55948	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-58618	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-47642	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55024	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55025	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55031	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55048	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55029	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55039	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55136	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55141	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55036	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55044	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55037	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55058	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55137	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55053	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55131	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-54131	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55947	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55949	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-56156	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55006	Microsoft Exchange Server Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-55009	Microsoft Exchange Server Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-55005	Microsoft Exchange Server Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-56642	Microsoft Fabric Data Warehouse Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-50343	Microsoft Install Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50439	Microsoft Message Queuing Queue Manager Remote Code Execution Vulnerability	Important	8.1	No	No	RCE
CVE-2026-58537	Microsoft NAT Helper Components (ipnathlp.dll) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-56193	Microsoft Office Information Disclosure Vulnerability	Important	7.1	No	No	Info
CVE-2026-55023	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55026	Microsoft Office Information Disclosure Vulnerability	Important	6.2	No	No	Info
CVE-2026-55027	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55028	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55047	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55035	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55057	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55121	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55042	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55139	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50665	Microsoft Office Information Disclosure Vulnerability	Important	7.8	No	No	Info
CVE-2026-56192	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-56195	Microsoft Office Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-47290	Microsoft Office Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50301	Microsoft Office Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55017	Microsoft Office Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55125	Microsoft Office Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55133	Microsoft OneNote Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-58636	Microsoft PC Manager Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50438	Microsoft PC Manager Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-58647	Microsoft PowerBI Report Server Spoofing Vulnerability	Important	8	No	No	Spoofing
CVE-2026-55052	Microsoft SharePoint Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-58277	Microsoft SharePoint Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-55051	Microsoft SharePoint Server Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-54108	Microsoft SharePoint Server Spoofing Vulnerability	Important	6.5	No	No	Spoofing
CVE-2026-55016	Microsoft SharePoint Server Spoofing Vulnerability	Important	4.6	No	No	Spoofing
CVE-2026-55019	Microsoft SharePoint Server Spoofing Vulnerability	Important	4.6	No	No	Spoofing
CVE-2026-55020	Microsoft SharePoint Server Spoofing Vulnerability	Important	4.6	No	No	Spoofing
CVE-2026-55021	Microsoft SharePoint Server Spoofing Vulnerability	Important	7.3	No	No	Spoofing
CVE-2026-55030	Microsoft SharePoint Server Spoofing Vulnerability	Important	4.6	No	No	Spoofing
CVE-2026-55034	Microsoft SharePoint Server Spoofing Vulnerability	Important	7.3	No	No	Spoofing
CVE-2026-55126	Microsoft SharePoint Server Spoofing Vulnerability	Important	7.3	No	No	Spoofing
CVE-2026-55135	Microsoft SharePoint Server Spoofing Vulnerability	Important	4.6	No	No	Spoofing
CVE-2026-56157	Microsoft SharePoint Server Spoofing Vulnerability	Important	5.4	No	No	Spoofing
CVE-2026-47296	Microsoft SQL Server Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-55002	Microsoft SQL Server Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-47295	Microsoft SQL Server Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-50468	Microsoft SQL Server Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-54116	Microsoft SQL Server Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-42900	Microsoft Windows App Store Elevation of Privilege Vulnerability	Important	8.1	No	No	EoP
CVE-2026-49784	Microsoft Windows App Store Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50356	Microsoft Windows App Store Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-49165	Microsoft Windows App Store Information Disclosure Vulnerability	Important	7.1	No	No	Info
CVE-2026-54993	Microsoft Windows Media Foundation Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-58610	Microsoft Windows Media Foundation Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55050	Microsoft Word Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55124	Microsoft Word Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55142	Microsoft Word Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-55032	Microsoft Word Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55055	Microsoft Word Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55038	Microsoft Word Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55134	Microsoft Word Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55128	Microsoft Word Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-55130	Microsoft Word Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50359	Microsoft XML Core Services Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-57097	Microsoft XML Security Feature Bypass Vulnerability	Important	6.4	No	No	SFB
CVE-2026-50346	Netlogon RPC Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50402	NTFS Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50506	OData for ASP.NET and ASP.NET Core Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-45646	OData for ASP.NET and ASP.NET Core Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-54989	Quality Windows Audio/Video Experience (QWAVE) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50365	Remote Access Management service/API (RPC server) Elevation of Privilege Vulnerability	Important	8	No	No	EoP
CVE-2026-54990	Remote Desktop Client Remote Code Execution Vulnerability	Important	9.8	No	No	RCE
CVE-2026-58594	Remote Desktop Client Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-56190	Remote Desktop Protocol Remote Code Execution Vulnerability	Important	9.8	No	No	RCE
CVE-2026-49783	Secure Boot Security Feature Bypass Vulnerability	Important	7.8	No	No	SFB
CVE-2026-42990	SQL Server ODBC driver Elevation of Privilege Vulnerability	Important	9.8	No	No	EoP
CVE-2026-49168	Storage Spaces Direct Elevation of Privilege Vulnerability	Important	6.2	No	No	EoP
CVE-2026-48581	Surface Broker SDMA Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-49180	Universal Plug and Play (upnp.dll) Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50455	Universal Plug and Play (upnp.dll) Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-54111	Universal Print Management Service Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-58543	Universal Print Management Service Elevation of Privilege Vulnerability	Important	6.3	No	No	EoP
CVE-2026-58601	Virtual Hard Disk (VHD) Miniport Driver Elevation of Privilege Vulernability	Important	7.8	No	No	EoP
CVE-2026-50520	Visual Studio Code Remote Code Execution Vulnerability	Important	8.4	No	No	RCE
CVE-2026-45496	Visual Studio Code Security Feature Bypass Vulnerability	Important	5.5	No	No	SFB
CVE-2026-57101	Visual Studio Code Security Feature Bypass Vulnerability	Important	7.1	No	No	SFB
CVE-2026-57102	Visual Studio Code Security Feature Bypass Vulnerability	Important	8.8	No	No	SFB
CVE-2026-47305	Visual Studio Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-49805	Win32k Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50297	Win32k Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50325	Win32k Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50489	Win32k Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-57095	Win32k Elevation of Privilege Vulnerability	Important	6.2	No	No	EoP
CVE-2026-50416	Win32k Information Disclosure Vulnerability	Important	3.3	No	No	Info
CVE-2026-56184	Win32k Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50432	Window Virtual Filtering Platform (VFP) Denial of Service Vulnerability	Important	5.3	No	No	DoS
CVE-2026-54119	Windows Active Directory Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-57976	Windows Active Directory Domain Services Denial of Service Vulnerability	Important	6.5	No	No	DoS
CVE-2026-50366	Windows Active Directory Domain Services Denial of Service Vulnerability	Important	6.5	No	No	DoS
CVE-2026-49178	Windows Active Directory Domain Services Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-58529	Windows Active Directory Federation Services (ADFS) Information Disclosure Vulnerability	Important	7.1	No	No	Info
CVE-2026-54983	Windows Active Directory Federation Services Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50695	Windows Active Directory Federation Services Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50304	Windows Active Directory Federation Services Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50368	Windows Active Directory Federation Services Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50324	Windows Active Directory Federation Services Denial of Service Vulnerability	Important	5.9	No	No	DoS
CVE-2026-50355	Windows Active Directory Federation Services Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50411	Windows Active Directory Federation Services Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-58631	Windows Admin Center (WAC) Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-56196	Windows Admin Center (WAC) Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-56197	Windows Admin Center (WAC) Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-56169	Windows Admin Center Elevation of Privilege Vulnerability	Important	8.1	No	No	EoP
CVE-2026-57107	Windows Admin Center Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-56185	Windows Admin Center Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-50312	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	4.7	No	No	EoP
CVE-2026-50462	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-57093	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-34346	Windows Ancillary Function Driver for WinSock Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-48572	Windows App Package Installer Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-48571	Windows App Package Installer Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50400	Windows App Package Installer Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50331	Windows Application Model Core API Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-49803	Windows AppX Deployment Extensions Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50351	Windows Audio Compression Manager (ACM) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50440	Windows Audio Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34328	Windows Audio Service Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50406	Windows Backup Engine Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50364	Windows Backup Service Elevation of Privilege Vulnerability	Important	7.3	No	No	EoP
CVE-2026-42975	Windows Bluetooth Port Driver Remote Code Execution	Important	8	No	No	RCE
CVE-2026-58538	Windows Bluetooth Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58638	Windows Boot Loader Security Feature Bypass Vulnerability	Important	6	No	No	SFB
CVE-2026-58637	Windows Client-Side Caching Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50384	Windows Clip Service Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-49183	Windows Clipboard Server Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50689	Windows Clipboard Server Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50374	Windows Cloud Files Mini Filter Driver Elevation of Privilege Vulnerability	Important	6.3	No	No	EoP
CVE-2026-58536	Windows Cloud Files Mini Filter Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58613	Windows Cloud Files Mini Filter Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50401	Windows Cloud Files Mini Filter Driver Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50697	Windows Common Log File System Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50667	Windows Common Log File System Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50421	Windows Connected User Experiences and Telemetry Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50428	Windows Container Isolation FS Filter Driver (unionfs.sys) Information Disclosure Vulnerability	Important	7.1	No	No	Info
CVE-2026-50352	Windows Cryptographic Services Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50302	Windows Cryptographic Services Security Feature Bypass Vulnerability	Important	4.2	No	No	SFB
CVE-2026-55144	Windows Cryptography API: Next Generation (CNG) Tampering Vulnerability	Important	7.1	No	No	Tampering
CVE-2026-50347	Windows Data.dll Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-49181	Windows DHCP Client Elevation of Privilege Vulnerability	Important	7.5	No	No	EoP
CVE-2026-50683	Windows DHCP Client Elevation of Privilege Vulnerability	Important	8	No	No	EoP
CVE-2026-58627	Windows DHCP Server Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50685	Windows DHCP Server Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-49807	Windows DirectX Information Disclosure Vulnerability	Important	6.2	No	No	Info
CVE-2026-49175	Windows DNS Client Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50487	Windows DNS Client Elevation of Privilege Vulnerability	Important	8.1	No	No	EoP
CVE-2026-50465	Windows DNS Client Tampering Vulnerability	Important	7.1	No	No	Tampering
CVE-2026-49169	Windows DNS Server Remote Code Execution Vulnerability	Important	8	No	No	RCE
CVE-2026-50426	Windows DNS Server Remote Code Execution Vulnerability	Important	6.8	No	No	RCE
CVE-2026-50424	Windows Domain Controller Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-50300	Windows DWM Core Library Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50437	Windows DWM Core Library Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-34348	Windows Event Logging Service Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-50502	Windows Event Logging Service Remote Code Execution Vulnerability	Important	8	No	No	RCE
CVE-2026-33842	Windows File Explorer Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-40422	Windows File Explorer Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-41087	Windows File Explorer Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50473	Windows File Explorer Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50442	Windows File Explorer Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50389	Windows File Explorer Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50456	Windows File Explorer Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-57084	Windows File Explorer Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-57091	Windows File History Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50405	Windows Filtering Platform Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-49172	Windows FTP Service Remote Code Execution Vulnerability	Important	9.8	No	No	RCE
CVE-2026-50387	Windows GDI Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-54122	Windows GDI+ Remote Code Execution Vulnerability	Important	8.4	No	No	RCE
CVE-2026-50483	Windows Graphics Component Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-58609	Windows Graphics Component Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50391	Windows Group Policy Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50310	Windows Human Interface Device Information Disclosure Vulnerability	Important	4.7	No	No	Info
CVE-2026-50485	Windows Hyper-V Denial of Service Vulnerability	Important	4.5	No	No	DoS
CVE-2026-54129	Windows Hyper-V Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50315	Windows Image Acquisition Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58534	Windows Input Method Editor (IME) Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-50490	Windows Installer Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-58540	Windows Installer Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50425	Windows Internal System User Profile Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50293	Windows Internal Task Bar Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-49167	Windows Kernel Elevation of Privilege Vulnerability	Important	4.7	No	No	EoP
CVE-2026-49173	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-54132	Windows Kernel Elevation of Privilege Vulnerability	Important	6.8	No	No	EoP
CVE-2026-49795	Windows Kernel Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-49798	Windows Kernel Elevation of Privilege Vulnerability	Important	9.3	No	No	EoP
CVE-2026-49808	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50354	Windows Kernel Elevation of Privilege Vulnerability	Important	7.1	No	No	EoP
CVE-2026-50332	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50377	Windows Kernel Elevation of Privilege Vulnerability	Important	5.5	No	No	EoP
CVE-2026-50390	Windows Kernel Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50423	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50397	Windows Kernel Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50436	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50399	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50459	Windows Kernel Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50477	Windows Kernel Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-50478	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50484	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50673	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58532	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50294	Windows Kernel Information Disclosure Vulnerability	Important	6.2	No	No	Info
CVE-2026-50316	Windows Kernel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50419	Windows Kernel Information Disclosure Vulnerability	Important	3.3	No	No	Info
CVE-2026-50463	Windows Kernel Information Disclosure Vulnerability	Important	7.5	No	No	Info
CVE-2026-50475	Windows Kernel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50429	Windows Kernel Information Disclosure Vulnerability	Important	8.2	No	No	Info
CVE-2026-58614	Windows Kernel Security Feature Bypass Vulnerability	Important	5.5	No	No	SFB
CVE-2026-58545	Windows Kernel Security Feature Bypass Vulnerability	Important	5.5	No	No	SFB
CVE-2026-58602	Windows Kernel-Mode Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50393	Windows Kernel-Mode Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50396	Windows Kernel-Mode Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50378	Windows Key Guard Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50303	Windows Key Guard Security Feature Bypass Vulnerability	Important	5.5	No	No	SFB
CVE-2026-40378	Windows Local Security Authority Subsystem Service (LSASS) Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-49799	Windows Local Security Authority Subsystem Service (LSASS) Denial of Service Vulnerability	Important	6.5	No	No	DoS
CVE-2026-50371	Windows LUA File Virtualization Filter Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-58544	Windows Management Services Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50404	Windows Media Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50358	Windows Media Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50336	Windows Media Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50398	Windows Media Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-50414	Windows Media Elevation of Privilege Vulnerability	Important	7.5	No	No	EoP
CVE-2026-50379	Windows Media Elevation of Privilege Vulnerability	Important	7.5	No	No	EoP
CVE-2026-50433	Windows Media Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50676	Windows Media Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50677	Windows Media Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-34349	Windows Media Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50394	Windows Media Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50415	Windows Media Information Disclosure Vulnerability	Important	5.3	No	No	Info
CVE-2026-57083	Windows Media Photo Codec Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-54115	Windows Message Queuing (MSMQ) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50447	Windows Message Queuing Service (MSMQ) Remote Code Execution Vulnerability	Important	9.8	No	No	RCE
CVE-2026-50505	Windows Message Queuing Service (MSMQ) Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-50342	Windows MIDI Service Module Elevation of Privileges Vulnerability	Important	8.8	No	No	EoP
CVE-2026-56183	Windows MIDI Service Module Elevation of Privileges Vulnerability	Important	7	No	No	EoP
CVE-2026-56187	Windows MIDI Service Module Elevation of Privileges Vulnerability	Important	7	No	No	EoP
CVE-2026-58635	Windows Narrator Braille Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50500	Windows Netlogon Elevation of Privilege Vulnerability	Important	7.5	No	No	EoP
CVE-2026-50476	Windows Network Connections Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50450	Windows Network Connections Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-56650	Windows Network File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-56649	Windows Network File System Remote Code Execution Vulnerability	Important	5.9	No	No	RCE
CVE-2026-50470	Windows Network Policy Server SNMP Information Disclosure Vulnerability	Important	7.5	No	No	Info
CVE-2026-50496	Windows Network Policy Server SNMP Information Disclosure Vulnerability	Important	7.5	No	No	Info
CVE-2026-56194	Windows NFS Server Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-56648	Windows NFS Server Elevation of Privilege Vulnerability	Important	7.5	No	No	EoP
CVE-2026-50337	Windows Notification Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-49789	Windows NTFS Elevation of Privilege Vulnerability	Important	7.3	No	No	EoP
CVE-2026-50412	Windows NTFS Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50422	Windows NTFS Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50672	Windows NTFS Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-56175	Windows NTFS Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-56182	Windows NTFS Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50341	Windows NTFS Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-58640	Windows NTFS Remote Code Execution Vulnerability	Important	7.3	No	No	RCE
CVE-2026-49184	Windows NTFS Remote Code Execution Vulnerability	Important	8.4	No	No	RCE
CVE-2026-49797	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50308	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50386	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50309	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50313	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50388	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50448	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50471	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50461	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50417	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50482	Windows NTFS Remote Code Execution Vulnerability	Important	7.3	No	No	RCE
CVE-2026-50494	Windows NTFS Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50344	Windows OLE Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50686	Windows OLE Remote Code Execution Vulnerability	Important	8.1	No	No	RCE
CVE-2026-50335	Windows Operating Systems Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50317	Windows Operating Systems Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-54987	Windows Overlay Filter Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50435	Windows Overlay Filter Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50409	Windows Overlay Filter Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-40400	Windows PowerShell Remote Code Execution Vulnerability	Important	8	No	No	RCE
CVE-2026-49166	Windows Print Configuration Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-55004	Windows Print Configuration Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50499	Windows Print Spooler Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50383	Windows Print Spooler Information Disclosure Vulnerability	Important	6.1	No	No	Info
CVE-2026-57085	Windows Print Spooler Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50469	Windows Projected File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50434	Windows Push Notification Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50339	Windows Push Notification Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50430	Windows Push Notification Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50334	Windows Push Notification Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-44800	Windows Push Notifications Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50363	Windows Push Notifications Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50431	Windows Quality of Service (QoS) Packet Scheduler Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50372	Windows Redirected Drive Buffering System Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50666	Windows Remote Access Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-56647	Windows Remote Access Service Infrastructure Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-50330	Windows Remote Desktop Client Elevation of Privilege Vulnerability	Important	7.5	No	No	EoP
CVE-2026-50376	Windows Remote Desktop Client Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-50504	Windows Remote Desktop Client Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-58533	Windows Remote Desktop Client Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-58535	Windows Remote Desktop Client Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-58546	Windows Remote Desktop Client Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-58539	Windows Remote Desktop Client Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-55003	Windows Remote Desktop Protocol (RDP) Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-57979	Windows Remote Desktop Protocol (RDP) Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-50445	Windows Remote Desktop Protocol (RDP) Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-50497	Windows Remote Desktop Protocol (RDP) Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-54126	Windows Remote Desktop Protocol (RDP) Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-57982	Windows Remote Desktop Protocol (RDP) Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-50369	Windows Remote Desktop Services Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-58626	Windows Remote Desktop Services Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-55014	Windows Remote Help Defense Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50318	Windows Resilient File System (ReFS) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50407	Windows Resilient File System (ReFS) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50357	Windows Resilient File System (ReFS) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50441	Windows Resilient File System (ReFS) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50668	Windows Resilient File System (ReFS) Elevation of Privilege Vulnerability	Important	6.8	No	No	EoP
CVE-2026-54109	Windows Resilient File System (ReFS) Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-49792	Windows Resilient File System (ReFS) Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-49793	Windows Resilient File System (ReFS) Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50362	Windows Resilient File System (ReFS) Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50492	Windows Resilient File System (ReFS) Remote Code Execution Vulnerability	Important	6.8	No	No	RCE
CVE-2026-50501	Windows Resilient File System (ReFS) Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-58530	Windows Resilient File System (ReFS) Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-49791	Windows Routing and Remote Access Service (RRAS) Elevation of Privilege Vulnerability	Important	7.1	No	No	EoP
CVE-2026-50451	Windows Routing and Remote Access Service (RRAS) Elevation of Privilege Vulnerability	Important	7.1	No	No	EoP
CVE-2026-57096	Windows Routing and Remote Access Service (RRAS) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50323	Windows Runtime Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50452	Windows Runtime Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50348	Windows Runtime Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50345	Windows Runtime Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50322	Windows Runtime Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50340	Windows Runtime Elevation of Privilege Vulnerability	Important	8.5	No	No	EoP
CVE-2026-50410	Windows Runtime Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50449	Windows Runtime Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50460	Windows Runtime Elevation of Privilege Vulnerability	Important	8.1	No	No	EoP
CVE-2026-50403	Windows Runtime Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50385	Windows Runtime Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-50413	Windows Runtime Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-50457	Windows Runtime Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50486	Windows Runtime Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50503	Windows Runtime Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-54125	Windows Runtime Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58527	Windows Runtime Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50373	Windows Search Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50679	Windows Search Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-44806	Windows Secure Channel Denial of Service Vulnerability	Important	5.3	No	No	DoS
CVE-2026-50681	Windows Secure Channel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-56186	Windows Secure Channel Information Disclosure Vulnerability	Important	8.1	No	No	Info
CVE-2026-50367	Windows Sensor Data Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58619	Windows Sensor Data Service Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50311	Windows Server Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50328	Windows Server Update Service (WSUS) Tampering Vulnerability	Important	7.5	No	No	Tampering
CVE-2026-58531	Windows SMB Elevation of Privilege Vulnerability	Important	7.5	No	No	EoP
CVE-2026-54997	Windows SMB Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-49801	Windows SMB Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50690	Windows SMB Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-56168	Windows SMB Server Denial of Service Vulnerability	Important	6.5	No	No	DoS
CVE-2026-50360	Windows SMB Server Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-57089	Windows SMB Server Network Transport Driver (srvnet.sys) Remote Code Execution Vulnerability	Important	7.5	No	No	RCE
CVE-2026-50333	Windows Spaceport.sys Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50298	Windows Spaceport.sys Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-49171	Windows Speech Runtime Elevation of Privilege Vulnerability	Important	7.5	No	No	EoP
CVE-2026-49170	Windows StateRepository API Server file Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58526	Windows Storage Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50299	Windows Storage Spaces Direct Remote Code Execution Vulnerability	Important	6.8	No	No	RCE
CVE-2026-57968	Windows Subsystem for Linux (WSL2) Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-57973	Windows Subsystem for Linux (WSL2) Kernel Tampering Vulnerability	Important	6.3	No	No	Tampering
CVE-2026-50418	Windows System Secure Feature Bypass Vulnerability	Important	5.1	No	No	SFB
CVE-2026-50306	Windows TCP/IP Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50307	Windows TCP/IP Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-49177	Windows TCP/IP Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50669	Windows Telephony Server Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-54124	Windows Terminal Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-50350	Windows Trusted Runtime Interface Driver Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-50326	Windows Unified Consent System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-49790	Windows Universal Disk Format File System Driver (UDFS) Elevation of Privilege Vulnerability	Important	7.3	No	No	EoP
CVE-2026-50498	Windows Universal Disk Format File System Driver (UDFS) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58547	Windows Universal Plug and Play (UPnP) Device Host Elevation of Privilege Vulnerability	Important	5.5	No	No	EoP
CVE-2026-49794	Windows USB Audio Class Driver Information Disclosure Vulnerability	Important	4.6	No	No	Info
CVE-2026-50453	Windows USB Audio Class Driver Information Disclosure Vulnerability	Important	6.1	No	No	Info
CVE-2026-58528	Windows USB Audio Class Driver Information Disclosure Vulnerability	Important	6.8	No	No	Info
CVE-2026-50321	Windows USB Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50479	Windows USB Hub Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-55000	Windows USB Print Driver Elevation of Privilege Vulnerability	Important	6.4	No	No	EoP
CVE-2026-54991	Windows USB Print Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-54996	Windows USB Print Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-49802	Windows USB Print Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-49806	Windows USB Print Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-50674	Windows USB Print Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-49804	Windows USB Video Driver Elevation of Privilege Vulnerability	Important	6.6	No	No	EoP
CVE-2026-50454	Windows User Interface Core Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-49176	Windows WalletService Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-49800	Windows Web Proxy Auto-Discovery Protocol (WPAD) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50480	Windows Web Proxy Auto-Discovery Protocol (WPAD) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-56173	Windows WebView Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-58632	Windows Win32 Kernel Subsystem Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-54107	Windows Win32k Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-54986	Windows Win32k Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-54112	Windows Win32k Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-54114	Windows Win32k Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50670	Windows Win32k Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-50688	Windows Win32k Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50687	Windows Win32k Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-56176	Windows Win32k Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-58628	Windows Wireless Network Manager Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-50295	Windows Zero Trust DNS Security Feature Bypass Vulnerability	Important	5.5	No	No	SFB
CVE-2026-50509	Wireless Wide Area Network Service (WwanSvc) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-55945	Microsoft Edge (Chromium-based) Information Disclosure Vulnerability	Moderate	4.2	No	No	Info
CVE-2026-45488	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Moderate	5.4	No	No	Spoofing
CVE-2026-45489	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Moderate	6.5	No	No	Spoofing
CVE-2026-55145	Outlook Copilot Tampering Vulnerability	Moderate	6.3	No	No	Tampering
CVE-2026-56181	Windows Network Address Translation (NAT) Spoofing Vulnerability	Moderate	8.3	No	No	Spoofing
CVE-2026-58597	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Low	4.3	No	No	Spoofing

** Indicates this CVEs has already been resolved by Microsoft, and no further action is needed by the end user.

I’ll do my best to summarize everything else in this release, but no promises. I’m only human after all.

Looking at the remaining Critical-rated patches, Office is its own weather system: fourteen Word/Excel/PowerPoint/Office RCEs clustered at CVSS 7.8, plus five Windows Media Foundation RCEs. Outside of the Preview Pane attack vector, they are individually unremarkable; collectively, patch Office and reboot. Always reboot. We’ve already mentioned DHCP some, but DHCP Server can't catch a break. Beyond the one already covered, add CVE-2026-56159, CVE-2026-48564, CVE-2026-50370, and DHCP Client cousin CVE-2026-54128. Five DHCP RCEs in one release. Rounding things out, Print Spooler (CVE-2026-58608), Windows TCP/IP (CVE-2026-54999), and a SQL Server RCE pair (CVE-2026-54117/54118) all receive patches, and all are rated a CVSS 8.8. VE-2026-55944 (Dynamics NAV/Business Central On-Prem RCE, 9.8) is the same deserialization flavor as the SharePoint pair; it’s unauthenticated, network-reachable, and easy to overlook since it's not SharePoint. CVE-2026-48561 (Microsoft Copilot RCE, 9.6) and CVE-2026-50380 (Windows GDI+ RCE, 9.6) round out the near-top tier. Don't forget CVE-2026-55040, a SharePoint Security Feature Bypass (9.1) — patch it in the same pass as the SharePoint RCE pair since it's the same product family. Identity and infrastructure get hit too: CVE-2026-54121 (AD Certificate Services EoP, 8.8) and CVE-2026-50444 (WSUS EoP, 8.8). The obscure Reliable Multicast Transport Driver (RMCAST) takes two RCEs (CVE-2026-54982, CVE-2026-54995), and CVE-2026-50474 gives Remote Desktop Client its own RCE, separate from the RDP one already covered. The rest is a long tail: Defender RCE x2, GDI+ again, Windows Media x2, Secure Kernel Mode EoP x2, and a second Hyper-V EoP. You can consider these “normal” as far as patch cadence goes.

That leaves us with 95 RCE to discuss. I would explain, but there is too much, so let me sum up. CVE-2026-55944 (Dynamics NAV/Business Central On-Prem, 9.8) is the same deserialization flavor as the SharePoint pair: unauthenticated, easy to miss since it's not SharePoint. CVE-2026-54990 (Remote Desktop Client), CVE-2026-49172 (Windows FTP Service), and CVE-2026-50447 (MSMQ) all hit 9.8 too, proof severity labels lag CVSS sometimes. CVE-2026-48561 (Copilot) and CVE-2026-50380 (GDI+) sit at 9.6.

The pattern worth watching: 14 Windows NTFS and 7 ReFS RCEs/ That makes 21 filesystem-driver bugs, an unusually large cluster suggesting a shared root cause. Microsoft Edge (Chromium-based) contributes 21 more that are genuinely Microsoft's to patch, not Chromium re-listing noise. Remote Desktop Client racks up a second and third RCE (CVE-2026-50474, CVE-2026-58594), and Windows Admin Center picks up two (CVE-2026-56196/56197) — WAC exposure keeps creeping into these releases. Exchange Server (CVE-2026-55005) and AD Domain Services (CVE-2026-49178) both land at 8.8.

And because this release wouldn't be complete without it: CVE-2026-50663, an RCE in Age of Empires II: Definitive Edition. Yes, really. Patch your civilization anyway.

There are close to 260 EoP bugs in this month’s release. Microsoft could have just published the EoPs and still had a record-setting month. 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. What’s really frustrating is that 94 have no explicit privilege statement at all. Microsoft just says “elevate privileges” with no detail. By my count, that leaves around 25 bugs to consider. Some don’t elevate at all. The FAQ literally says the attacker just gets “the rights of the user running the affected application.” That covers Win32k, Clip Service, Search Service, MSMQ, and SharePoint. A few get a Low-to-Medium integrity bump. There are also a couple that lead to downgraded service accounts or arbitrary file deletion, but nothing else I’ve seen really stands out too much.

There are 20 Security Feature Bypass (SFB) bugs this month, and it's a genuinely mixed bag. CVE-2026-55040 leads at Critical, CVSS 9.1 as it’s weak authentication in SharePoint Server. Patch it in the same pass as the SharePoint RCE pair since it's the same product. The AI-coding-tool trend continues: GitHub Copilot and Visual Studio Code and Visual Studio all land SFB bugs, mostly injection or path-traversal flavored. BitLocker is this month's lone publicly disclosed bug. It’s not exploited yet, but public disclosure is a countdown clock, not a free pass. It requires physical access, as does the bug in Microsoft XML. The firmware/boot cluster is worth a second look: Secure Boot, Boot Loader, and Key Guard all touch the trust chain below the OS. Meaning, despite a low CVSS score, “if this fails, nothing above it can be trusted” stakes. Rounding out the SFB patches, there are two .NET SFBs, two Windows Kernel SFBs, and a DNS/Cryptographic Services bringing up the rear.

The July release includes 31Spoofing bugs this month, and we’ve already covered the most important (Exchange). SharePoint Server accounts for another ten with almost all the same root cause: stored XSS letting an authenticated attacker spoof content in the browser. Microsoft Edge (Chromium-based) contributes fifteen more spanning access-control failures, SSRF, type confusion, and UI misrepresentation. All genuinely Microsoft's to patch, not re-listed Chromium noise. The remaining six round out the usual suspects: a Windows NAT spoofing bug reachable from an adjacent network, a Bing app flaw on iOS, a PowerBI Report Server XSS issue, a .NET output-encoding bug, and an AD FS spoofing flaw. None publicly disclosed, none exploited, but with SharePoint's history this year, don't let "just Spoofing" lull you into deprioritizing the patch cycle.

Of 111 Information Disclosure bugs, the overwhelming majority of these simply result in info leaks consisting of unspecified memory contents or memory addresses. GitHub Copilot is the standout. Here, the bug insufficiently protected credentials, meaning actual secrets leak, not memory scraps. The Windows Admin Center flaw discloses data via improper authentication. A management console leaking to an unauthorized party is a bigger deal than it sounds. SharePoint uses SSRF to pull data server-side, and the Event Logging Service is a protection-mechanism failure, not a memory bug at all. Edge picks up three genuinely file-system-flavored disclosures — improper authorization, files/directories accessible to external parties, and link-following — plus Edge for Android exposing “private personal information” twice and two path-traversal bugs. The remaining 40+ are mostly one-line “exposure of sensitive information to an unauthorized actor” entries scattered across File Explorer, Push Notifications, Cryptographic Services, and Win32k.

Only 8 Tampering bugs this month, the smallest bucket, but a couple stand out. The top of the list is a WSUS bug, caused by an uncaught exception that lets an unauthenticated attacker tamper with the update service over the network. That’s your patch-management infrastructure itself being the target, which always deserves extra attention. Windows CNG (the crypto API) picks up a missing-cryptographic-step flaw, and Windows DNS Client shows up three separate times across the list, twice for improper access control and once for missing authentication on a critical function. DNS resolution having this many tampering paths in one release is worth flagging as a pattern rather than three unrelated bugs. The one genuinely different entry is Outlook Copilot, described simply as vulnerable to “malicious uses” enabling tampering over the network. That’s a fantastically vague phrasing for an AI-assistant feature, continuing this year's running theme of Copilot-branded features showing up somewhere in every release. Finally, a .NET link-following bug and a WSL2 kernel race condition receive patches. Both require local/authorized access to trigger.

Still with me? Good, because we have 35 DoS bugs to cover, and this is really an identity-infrastructure story more than a grab-bag. Active Directory Federation Services alone accounts for seven of them, all sitting at CVSS 7.5, all stack-based buffer overflows or infinite loops that let an unauthenticated attacker knock the service over the network. The .NET ecosystem is the other big cluster: .NET, .NET Framework, and ASP.NET Core/OData contribute nine bugs combined, almost all “allocation of resources without limits or throttling”. HTTP.sys and HTTP/2 pick up the same flavor. LSASS shows up twice, which is always worth a second look given what that process actually holds. Rounding out the list are patches for Windows DHCP Server, SMB Server, Secure Channel, Hyper-V, and IKE Protocol each take a single hit, mostly requiring authorized or adjacent-network access rather than being wide open to the internet.

No new advisories are being released this month.

Looking Ahead

The next Patch Tuesday will be on August 11, just after Hacker Summer Camp in sunny Las Vegas. Should I survive the heat, I’ll be back then to give you my full thoughts on the release – no matter how large it may be. Until then, stay safe, happy patching, and may all your reboots be smooth and clean!

The February 2026 Security Update Review

Sat, 25 Jul 2026 19:00:44 +0200

I have survived the biggest Pwn2Own ever, but I’m back in Tokyo for the second Patch Tuesday of 2026. My location never stops Patch Tuesday from coming, so 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:

Adobe Patches for February 2026

For February, Adobe released nine bulletins addressing 44 unique CVEs in Adobe Audition, After Effects, InDesign, Substance 3D Designer, Substance 3D Stager, Adobe Bridge, Substance 3D Modeler, Lightroom Classic, and the Adobe DNG Software Development Kit (SDK). The largest update here is for After Effects, which fixes 13 Critical and two Important rated bugs. The patch for Substance 3D Designer is on the larger side with seven fixes, but only two of those are Critical. On the other hand, the fix for Substance 3D Stager corrects five Critical-rated bugs that could lead to code execution. The Audition patch fixes six bugs, but only one is Critical.

The other patches are smaller in size. The fix for the Adobe DNG Software Development Kit (SDK) corrects two Critical and two Important-rated bugs. The InDesign patch fixes three bugs, but only one is Critical. The update for Adobe Bridge fixes two Critical bug that could lead to code execution. The patch for Lightroom Classic addresses a single Critical bug, and the release is wrapped up with a patch for Substance 3D Modeler that fixes a single, Important-rated memory link.

None of the bugs fixed by Adobe this month are listed as publicly known or under active attack at the time of release, and all of the updates released by Adobe this month are listed as deployment priority 3.

Microsoft Patches for February 2026

This month, Microsoft drops 58 new CVEs in Windows and Windows components, Office and Office Components, Azure, Microsoft Edge (Chromium-based), .NET and Visual Studio, GitHub Copilot, Mailslot FS, Exchange Server, Internet Explorer (!), Power BI, Hyper-V Server, and the Windows Subsystem for Linux. Counting the third-party and Chromium updates listed in the release, it brings the total number of CVEs to 62. One of the bugs in the Windows Graphics component was submitted through the ZDI program. Five of these bugs are rated Critical, two are rated Moderate, and the rest are rated Important in severity.

It’s typical to see this number of CVEs released in February, but the number of bugs under active attack is extraordinarily high. Microsoft lists six bugs being exploited at the time of release, with three of these listed as publicly known. Last month only had a single bug being exploited, although there were twice as many CVEs patched. We’ll see if we’re on our way to another “hot exploit summer” as we saw a few years ago or if this is just an aberration.

Let’s take a closer look at some of the more interesting updates for this month, starting with the bugs under active attack:

- CVE-2026-21510 - Windows Shell Security Feature Bypass Vulnerability
This bug is listed as a security feature bypass, but it could also be classified as code execution. An attacker can bypass Windows SmartScreen and Windows Shell security prompts to execute code on a target system. This bug is also listed as publicly known, but Microsoft doesn’t say where. There is user interaction here, as the client needs to click a link or a shortcut file. Still, a one-click bug to gain code execution is a rarity. Definitely test and deploy this fix quickly.

- CVE-2026-21514 - Microsoft Word Security Feature Bypass Vulnerability
This bug also requires user interaction in the form of opening a Word document, but that’s all that’s required to bypass protections to dangerous COM/OLE controls. Thankfully, the Preview Pane is not an attack vector here. However, users are well known to open lots of documents they receive in e-mail. This bypass could also result in code execution if the right COM/OLE control is hit. This is also listed as publicly known, so add this to the list to test and deploy quickly.

- CVE-2026-21519 - Desktop Window Manager Elevation of Privilege Vulnerability
This is the second month in a row that a DWM was listed as being exploited in the wild. That leads me to believe the first patch didn’t completely resolve the vulnerability. Same as last month, this bug allows attackers to run code with SYSTEM privileges. Bugs of this type are typically paired with a code execution bug to take over a system. As always, Microsoft offers no indication of how widespread these exploits may be.

- CVE-2026-21533 - Windows Remote Desktop Services Elevation of Privilege Vulnerability
Don’t let the word “Remote” in the title fool you – this is a local bug that allows attackers to run code with SYSTEM privileges. It’s interesting that Microsoft lists “Improper privilege management” as the root cause for this issue. If the system is running Remote Desktop Services, it’s probably a juicy target for attackers to move laterally after an initial breach. Add this one to the list of patches to test and deploy immediately.

- CVE-2026-21513 - Internet Explorer Security Feature Bypass Vulnerability
Although long gone by many measurements, IE does still exist on Windows systems, and calling it always results in a vulnerability somehow. This bug manifests similarly to the Shell bug above, as it requires user interaction but could result in code execution. The bypass here is simply the ability to reach IE, which shouldn’t be possible. Again, test and deploy this fix quickly.

- CVE-2026-21525 - Windows Remote Access Connection Manager Denial of Service Vulnerability
It’s unusual to see DoS bugs being used in active attacks, but that’s what we have here. A null pointer deref in the Windows Remote Access Connection Manager allows an unauthorized attacker to deny service locally. Most null pointer derefs cause the application or service to crash, but it’s not clear if it will automatically restart. I would exercise caution and patch quickly either way.

Here’s the full list of CVEs released by Microsoft for February 2026:

CVE	Title	Severity	CVSS	Public	Exploited	TYPE
CVE-2026-21514	Microsoft Word Security Feature Bypass Vulnerability	Important	7.8	Yes	Yes	SFB
CVE-2026-21510	Windows Shell Security Feature Bypass Vulnerability	Important	8.8	Yes	Yes	SFB
CVE-2026-21513	Internet Explorer Security Feature Bypass Vulnerability	Important	8.8	Yes	Yes	SFB
CVE-2026-21519	Desktop Window Manager Elevation of Privilege Vulnerability	Important	7.8	No	Yes	EoP
CVE-2026-21533	Windows Remote Desktop Services Elevation of Privilege Vulnerability	Important	7.8	No	Yes	EoP
CVE-2026-21525	Windows Remote Access Connection Manager Denial of Service Vulnerability	Moderate	6.2	No	Yes	DoS
CVE-2026-21511	Microsoft Outlook Spoofing Vulnerability	Important	7.5	No	No	Spoofing
CVE-2023-2804 *	Red Hat, Inc. CVE-2023-2804: Heap Based Overflow libjpeg-turbo	Important	6.5	Yes	No	RCE
CVE-2026-24302	Azure Arc Elevation of Privilege Vulnerability	Critical	8.6	No	No	EoP
CVE-2026-24300	Azure Front Door Elevation of Privilege Vulnerability	Critical	9.8	No	No	EoP
CVE-2026-21532	Azure Function Information Disclosure Vulnerability	Critical	8.2	No	No	Info
CVE-2026-21522	Microsoft ACI Confidential Containers Elevation of Privilege Vulnerability	Critical	6.7	No	No	EoP
CVE-2026-23655	Microsoft ACI Confidential Containers Information Disclosure Vulnerability	Critical	6.5	No	No	Info
CVE-2026-21218	.NET and Visual Studio Spoofing Vulnerability	Important	7.5	No	No	Spoofing
CVE-2026-21512	Azure DevOps Server Cross-Site Scripting Vulnerability	Important	6.5	No	No	XSS
CVE-2026-21529 †	Azure HDInsight Spoofing Vulnerability	Important	5.7	No	No	Spoofing
CVE-2026-21528	Azure IoT Explorer Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-21228	Azure Local Remote Code Execution Vulnerability	Important	8.1	No	No	RCE
CVE-2026-21531	Azure SDK for Python Remote Code Execution Vulnerability	Important	9.8	No	No	RCE
CVE-2026-21251	Cluster Client Failover (CCF) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-20846	GDI+ Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-21523	GitHub Copilot and Visual Studio Code Remote Code Execution Vulnerability	Important	8	No	No	RCE
CVE-2026-21518	GitHub Copilot and Visual Studio Code Security Feature Bypass Vulnerability	Important	6.5	No	No	SFB
CVE-2026-21257	GitHub Copilot and Visual Studio Elevation of Privilege Vulnerability	Important	8	No	No	EoP
CVE-2026-21256	GitHub Copilot and Visual Studio Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-21516	GitHub Copilot for Jetbrains Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-21253	Mailslot File System Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-21537 †	Microsoft Defender for Endpoint Linux Extension Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-21259	Microsoft Excel Elevation of Privilege Vulnerability	Important	7.3	No	No	EoP
CVE-2026-21258	Microsoft Excel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-21261	Microsoft Excel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-21527	Microsoft Exchange Server Spoofing Vulnerability	Important	6.5	No	No	Spoofing
CVE-2026-21260	Microsoft Outlook Spoofing Vulnerability	Important	7.5	No	No	Spoofing
CVE-2026-21229	Power BI Remote Code Execution Vulnerability	Important	8	No	No	RCE
CVE-2026-21236	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21238	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21241	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-21517	Windows App for Mac Installer Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-21234	Windows Connected Devices Platform Service Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-21235	Windows Graphics Component Elevation of Privilege Vulnerability	Important	7.3	No	No	EoP
CVE-2026-21246	Windows Graphics Component Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21232	Windows HTTP.sys Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21240	Windows HTTP.sys Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21250	Windows HTTP.sys Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21244	Windows Hyper-V Remote Code Execution Vulnerability	Important	7.3	No	No	RCE
CVE-2026-21247	Windows Hyper-V Remote Code Execution Vulnerability	Important	7.3	No	No	RCE
CVE-2026-21248	Windows Hyper-V Remote Code Execution Vulnerability	Important	7.3	No	No	RCE
CVE-2026-21255	Windows Hyper-V Security Feature Bypass Vulnerability	Important	8.8	No	No	SFB
CVE-2026-21231	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21239	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21245	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21222	Windows Kernel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-21243	Windows Lightweight Directory Access Protocol (LDAP) Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-20841	Windows Notepad App Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-21249	Windows NTLM Spoofing Vulnerability	Important	3.3	No	No	Spoofing
CVE-2026-21508	Windows Storage Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-21237	Windows Subsystem for Linux Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-21242	Windows Subsystem for Linux Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-1861 *	Chromium: CVE-2026-1861 Heap buffer overflow in libvpx	High	N/A	No	No	RCE
CVE-2026-1862 *	Chromium: CVE-2026-1862 Type Confusion in V8	High	N/A	No	No	RCE
CVE-2026-0391	Microsoft Edge (Chromium-based) for Android Spoofing Vulnerability	Moderate	6.5	No	No	Spoofing

* Indicates this CVE had been released by a third party and is now being included in Microsoft releases.

† Indicates further administrative actions are required to fully address the vulnerability.

Moving on to the Critical-rated bugs, the patch for Azure Front Door sounds frightening, but Microsoft has already fixed the bug and is just now documenting it. That’s also true for the bugs in Azure Arc and Azure Function. There are two Critical-rated bugs in the ACI Confidential Containers. The first allows a container escape while the second discloses secret tokens and keys. Either way, you’ll want to handle those quickly.

Taking a look at the other code execution vulnerabilities in this month’s release, we start with a frightening looking bug in Azure SDK for Python that has the highest CVSS this month of 9.8. A remote, unauthenticated attacker code gain code execution on an affected system via a maliciously crafted continuation token. It’s not clear why this isn’t rated Critical, but I would treat it as such. The three bugs in Hyper-V are actually local open-and-own bugs that require a user to open a malicious file on an affected system. That’s also true for the bug in Notepad. The bug in Power BI is confusing, because Microsoft says it requires authentication and could lead to an attacker running code as an authenticated user. There’s the poorly named “Azure Local Remote Code Execution Vulnerability”, but it requires a machine-in-the-middle (MitM) to exploit. The bug in Defender for Endpoint Linux is restricted to local subnets, but you’ll need to enable auto provisioning to get the patch. The final code execution bugs addressed this month are in GitHub Copilot. Two are command injections and the other is a Time-of-check time-of-use (toctou) race condition, but both could end up in code execution on affected systems.

Patches for Elevation of Privilege (EoP) bugs make up nearly 50% of this release, but most simply lead to local attackers executing their code at SYSTEM-level privileges or administrative privileges. There are only two of note. The first is a command injection bug in GitHub Copilot that leads to executing code at the level of the targeted application. The second is a bug in a kernel that leads to SYSTEM but could also be used for a sandbox escape.

There’s a unusually high number of spoofing bugs in this month’s release, and the ones for Outlook are the most troubling. First, the Preview Pane is an attack vector. Secondly, the bugs could be used to relay NTLM credentials via just an email, which could result in credential disclosure. And you’ll need multiple patches to fully address these bugs. At least they can be applied in any order. There’s a UI misrepresentation bug in Exchange Server that could allow an attacker to either view some sensitive information or “make changes to disclosed information”. At what point does data become disclosed? That odd phrasing makes me think they are using AI to right some of their descriptions. The phrasing also appears in the patch for NTLM. That bug is triggered by opening a specially crafted Office doc, and while they explicitly say it could be used to relay NTLM creds, it sure seems that way. The patch for .NET and Visual Studio fixes a bug that allows attackers to bypass header validation, resulting in the service accepting a message it should reject. Finally, the bug in Azure HDInsight is really just a cross-site scripting (XSS) bug. The caveat here is that you need to restart Ambari server in both of the head nodes to have this fix updated. There is also an XSS in Azure Devops Server, but at least it is labelled as such.

There are a couple of additional security feature bypass bugs to discuss. The first is in Hyper-V and bypasses the Virtualization-based Security feature. The other is in GitHub Copilot and Visual Studio Code. It’s another command injection, but this one can be used to bypass authentication. Neat.

Looking at the remaining info disclosure bugs getting patched this month, most simply result in info leaks consisting of unspecified memory contents or memory addresses. The exception is the bug in Azure IoT Explorer. This bug could be used to view the contents of the target user’s local file system.

We end this month’s release with two DoS bugs: one in LDAP and one in GDI+. Neither descriptions from Microsoft provide any usable information.

No new advisories are being released this month.

Looking Ahead

I plan on being back home for the March release but wherever I’m at, you can rest assured that March 10, I’ll be here to provide my assessment of the release. Until then, stay safe, happy patching, and may all your reboots be smooth and clean!

The April 2026 Security Update Review

Sat, 25 Jul 2026 19:00:42 +0200

It’s time once again for Patch Tuesday, and this one is huge. We’ve also got multiple exploits in the wild, which adds another layer of urgency to this month’s release. 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:

Adobe Patches for April 2026

For April, Adobe released 12 bulletins addressing 61 unique CVEs in Adobe Acrobat Reader, InDesign, InCopy, FrameMaker, Connect, ColdFusion, Bridge, Photoshop, Illustrator, Experience Manager Screens, and the Adobe DNG SDK. Three of the Cold Fusion bugs came through the TrendAI ZDI program. For this month, I’m introducing an Adobe table as well. I’d love to get your feedback on whether this is helpful.

Bulletin ID	Product	CVE Count	Highest Severity	Highest CVSS	Exploited	Deployment Priority
APSB26-43	Adobe Acrobat Reader	1	Critical	8.6	Yes	1
APSB26-44	Adobe Acrobat Reader	2	Critical	8.6	No	2
APSB26-32	Adobe InDesign	9	Critical	7.8	No	3
APSB26-33	Adobe InCopy	2	Critical	7.8	No	3
APSB26-36	Adobe FrameMaker	11	Critical	8.6	No	3
APSB26-37	Adobe Connect	9	Critical	9.6	No	3
APSB26-38	Adobe ColdFusion	7	Critical	9.3	No	1
APSB26-39	Adobe Bridge	6	Critical	7.8	No	3
APSB26-40	Adobe Photoshop	1	Critical	7.8	No	3
APSB26-42	Adobe Illustrator	1	Critical	7.8	No	3
APSB26-34	Adobe Experience Manager Screens	9	Important	5.4	No	3
APSB26-41	Adobe DNG SDK	3	Important	5.5	No	3

Obviously, the active attack in Reader is the highest priority for this month, but don’t ignore the second bunch of Reader patches. Cold Fusion also gets a deployment priority of 1, so if you’re still running that platform, make sure you get the update. Otherwise, the FrameMaker and Connect patches fix 11 and nine bugs, respectively. InDesign and Experience Manager Screens also have nine CVEs addressed.

Outside of the Reader bug, none of the other bugs fixed by Adobe this month are listed as publicly known or under active attack at the time of release. One of the Reader bugs and Cold Fusion have a deployment priority of one, the other Reader bug has a priority of two, while all of the other updates released by Adobe this month are listed as deployment priority 3.

Microsoft Patches for April 2026

This month, Microsoft released a monstrous 163 new CVEs in Windows and Windows components, Office and Office Components, Microsoft Edge (Chromium-based), Azure, .NET and Visual Studio, SQL Server, Hyper-V Server, BitLocker, and the Windows Wallet Service. Counting the third-party and a huge Chromium release, it brings the total number of CVEs to a staggering 247 updates. Six of these bugs were reported through the TrendAI ZDI program. Eight of these bugs are rated Critical, two are rated as Moderate, and the rest are rated Important in severity.

By my count, this is the second-largest monthly release in Microsoft’s history. There are many things we could speculate on to justify the size, but if Microsoft is like the other programs out there (including ours), they are likely seeing a rise in submissions found by AI tools. For us, our incoming rate has essentially tripled, making triage a challenge, to say the least. Whatever the reason, we have a lot of bugs to deal with this month. I should also point out that the Pwn2Own Berlin occurs next month, and it’s typical for vendors to patch as much as they can before the event.

There is one Microsoft bug listed as under active attack at the time of release, and one other that’s publicly known. Let’s take a closer look at some of the more interesting updates for this month, starting with the vulnerability being exploited in the wild:

- CVE-2026-32201 - Microsoft SharePoint Server Spoofing Vulnerability
Microsoft doesn’t provide a lot of information about this bug, but Spoofing bugs in SharePoint often manifest as cross-site scripting (XSS) bugs. They do note that attackers could view information or make changes to disclosed information. As always, they don’t provide any information on how widespread these attacks are, but I wouldn’t wait to test and deploy this fix – especially if you have internet-connected SharePoint servers.

- CVE-2026-33825 - Microsoft Defender Elevation of Privilege Vulnerability
This bug is listed as publicly known, and this time, we know exactly where it was disclosed. There have been some questions about how exploitable this bug may be, but it does look like it’s a real problem – just with some reliability issues in its current state. I won’t add on to the commentary from the researcher about working with Microsoft. I’m just glad they are offering a fix for the vulnerability. If you rely on Defender, test and deploy this one quickly.

- CVE-2026-33827 - Windows TCP/IP Remote Code Execution Vulnerability
This vulnerability allows remote, unauthenticated attackers to exploit code on affected systems without user interaction. That adds up to a wormable bug – at least on systems with IPv6 and IPSec enabled. It is a race condition, which sets exploitability to High on the CVSS scale, but we see race conditions exploited at Pwn2Own all the time, so don’t rely on that obstacle. If you’re running IPv6, I would test and deploy this fix quickly before public exploits become available.

- CVE-2026-33824 - Windows Internet Key Exchange (IKE) Service Extensions Remote Code Execution Vulnerability
Speaking of wormable bugs, here’s our second one this month. By the title, we can tell that systems with IKE enabled are affected, but that leaves plenty of targets for attackers. Microsoft also notes a significant mitigation for this bug. Blocking UDP ports 500 and 4500 at the perimeter prevents external attackers from reaching the affected service. However, insiders could still target this for lateral movement within an enterprise. For enterprises using IKE, get this fix tested and deployed with haste.

Here’s the full list of CVEs released by Microsoft for April 2026:

April 2026 Patch Tuesday

CVE	Title	Severity	CVSS	Public	Exploited	Type
CVE-2026-32201	Microsoft SharePoint Server Spoofing Vulnerability	Important	6.5	No	Yes	Spoofing
CVE-2026-5281 *	Chromium: CVE-2026-5281 Use after free in Dawn	High	N/A	No	Yes	RCE
CVE-2026-33825	Microsoft Defender Elevation of Privilege Vulnerability	Important	7.8	Yes	No	EoP
CVE-2026-23666	.NET Framework Denial of Service Vulnerability	Critical	7.5	No	No	DoS
CVE-2026-32190	Microsoft Office Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-33114	Microsoft Word Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-33115	Microsoft Word Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-32157	Remote Desktop Client Remote Code Execution Vulnerability	Critical	8.8	No	No	RCE
CVE-2026-33826	Windows Active Directory Remote Code Execution Vulnerability	Critical	8	No	No	RCE
CVE-2026-33824	Windows Internet Key Exchange (IKE) Service Extensions Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-33827	Windows TCP/IP Remote Code Execution Vulnerability	Critical	8.1	No	No	RCE
CVE-2026-26171	.NET Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-32226	.NET Framework Denial of Service Vulnerability	Important	5.9	No	No	DoS
CVE-2026-32178	.NET Spoofing Vulnerability	Important	7.5	No	No	Spoofing
CVE-2026-32203	.NET and Visual Studio Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-33116	.NET, .NET Framework, and Visual Studio Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2023-20585 *	AMD: CVE-2023-20585 IOMMU Write Buffer Vulnerability	Important	5.3	No	No	RCE
CVE-2026-32072	Active Directory Spoofing Vulnerability	Important	6.2	No	No	Spoofing
CVE-2026-25184	Applocker Filter Driver (applockerfltr.sys) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32171	Azure Logic Apps Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-32168	Azure Monitor Agent Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32192	Azure Monitor Agent Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32181	Connected User Experiences and Telemetry Service Denial of Service Vulnerability	Important	5.5	No	No	DoS
CVE-2026-27924	Desktop Window Manager Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32152	Desktop Window Manager Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32154	Desktop Window Manager Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-27923	Desktop Window Manager Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32155	Desktop Window Manager Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-23653	GitHub Copilot and Visual Studio Code Information Disclosure Vulnerability	Important	5.7	No	No	Info
CVE-2026-23653 *	GitHub: CVE-2026-32631 'git clone' from manipulated repositories can leak NTLM hashes	Important	7.4	No	No	Info
CVE-2026-33096	HTTP.sys Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-25250 *	MITRE: CVE-2026-25250 Secure Boot disable Eazy Fix	Important	6	No	No	SFB
CVE-2026-26181	Microsoft Brokering File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32219	Microsoft Brokering File System Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32091	Microsoft Brokering File System Elevation of Privilege Vulnerability	Important	8.4	No	No	EoP
CVE-2026-26152	Microsoft Cryptographic Services Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-33103	Microsoft Dynamics 365 (On-Premises) Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-32188	Microsoft Excel Information Disclosure Vulnerability	Important	7.1	No	No	Info
CVE-2026-32189	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-32197	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-32198	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-32199	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-32184	Microsoft High Performance Compute (HPC) Pack Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26155	Microsoft Local Security Authority Subsystem Service Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-27914	Microsoft Management Console Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26149	Microsoft Power Apps Security Feature Bypass	Important	9	No	No	SFB
CVE-2026-32200	Microsoft PowerPoint Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-26143	Microsoft PowerShell Security Feature Bypass Vulnerability	Important	7.8	No	No	SFB
CVE-2026-33120 †	Microsoft SQL Server Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-20945	Microsoft SharePoint Server Spoofing Vulnerability	Important	4.6	No	No	Spoofing
CVE-2026-33822	Microsoft Word Information Disclosure Vulnerability	Important	6.1	No	No	Info
CVE-2026-33095	Microsoft Word Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-23657	Microsoft Word Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-32081	Package Catalog Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-26170	PowerShell Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26183	Remote Access Management service/API (RPC server) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26160	Remote Desktop Licensing Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26159	Remote Desktop Licensing Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26151	Remote Desktop Spoofing Vulnerability	Important	7.1	No	No	Spoofing
CVE-2026-32085	Remote Procedure Call Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-32167	SQL Server Elevation of Privilege Vulnerability	Important	6.7	No	No	EoP
CVE-2026-32176	SQL Server Elevation of Privilege Vulnerability	Important	6.7	No	No	EoP
CVE-2026-0390	UEFI Secure Boot Security Feature Bypass Vulnerability	Important	6.7	No	No	SFB
CVE-2026-32220	UEFI Secure Boot Security Feature Bypass Vulnerability	Important	4.4	No	No	SFB
CVE-2026-32212	Universal Plug and Play (upnp.dll) Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-32214	Universal Plug and Play (upnp.dll) Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-32079	Web Account Manager Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-33104	Win32k Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32196	Windows Admin Center Spoofing Vulnerability	Important	6.1	No	No	Spoofing
CVE-2026-26178	Windows Advanced Rasterization Platform Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-32073	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-26168	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26173	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-26177	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-26182	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-27922	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-33099	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-33100	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32088	Windows Biometric Service Security Feature Bypass Vulnerability	Important	6.1	No	No	SFB
CVE-2026-27913	Windows BitLocker Security Feature Bypass Vulnerability	Important	7.7	No	No	SFB
CVE-2026-26175	Windows Boot Manager Security Feature Bypass Vulnerability	Important	4.6	No	No	SFB
CVE-2026-32162	Windows COM Elevation of Privilege Vulnerability	Important	8.4	No	No	EoP
CVE-2026-20806	Windows COM Server Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-26176	Windows Client Side Caching driver (csc.sys) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-27926	Windows Cloud Files Mini Filter Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32070	Windows Common Log File System Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-33098	Windows Container Isolation FS Filter Driver Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26153	Windows Encrypted File System (EFS) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32087	Windows Function Discovery Service (fdwsd.dll) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32093	Windows Function Discovery Service (fdwsd.dll) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32086	Windows Function Discovery Service (fdwsd.dll) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32150	Windows Function Discovery Service (fdwsd.dll) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-27931	Windows GDI Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-27930	Windows GDI Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-32221	Windows Graphics Component Remote Code Execution Vulnerability	Important	8.4	No	No	RCE
CVE-2026-27906	Windows Hello Security Feature Bypass Vulnerability	Important	4.4	No	No	SFB
CVE-2026-27928	Windows Hello Security Feature Bypass Vulnerability	Important	8.7	No	No	SFB
CVE-2026-26156	Windows Hyper-V Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-32149	Windows Hyper-V Remote Code Execution Vulnerability	Important	7.3	No	No	RCE
CVE-2026-27910	Windows Installer Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-27912	Windows Kerberos Elevation of Privilege Vulnerability	Important	8	No	No	EoP
CVE-2026-26179	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26180	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32195	Windows Kernel Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-26163	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32215	Windows Kernel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-32217	Windows Kernel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-32218	Windows Kernel Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-26169	Windows Kernel Memory Information Disclosure Vulnerability	Important	6.1	No	No	Info
CVE-2026-27929	Windows LUA File Virtualization Filter Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32071	Windows Local Security Authority Subsystem Service (LSASS) Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-20930	Windows Management Services Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26162	Windows OLE Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-33101	Windows Print Spooler Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32084	Windows Print Spooler Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-27927	Windows Projected File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26184	Windows Projected File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32069	Windows Projected File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32074	Windows Projected File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32078	Windows Projected File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26167	Windows Push Notifications Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-32158	Windows Push Notifications Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32159	Windows Push Notifications Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32160	Windows Push Notifications Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26172	Windows Push Notifications Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-20928	Windows Recovery Environment Security Feature Bypass Vulnerability	Important	4.6	No	No	SFB
CVE-2026-32216	Windows Redirected Drive Buffering System Denial of Service Vulnerability	Important	5.5	No	No	DoS
CVE-2026-27909	Windows Search Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26161	Windows Sensor Data Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26174	Windows Server Update Service (WSUS) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32224	Windows Server Update Service (WSUS) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-26154	Windows Server Update Service (WSUS) Tampering Vulnerability	Important	7.5	No	No	Tampering
CVE-2026-26165	Windows Shell Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-26166	Windows Shell Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-27918	Windows Shell Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32151	Windows Shell Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-32225	Windows Shell Security Feature Bypass Vulnerability	Important	8.8	No	No	SFB
CVE-2026-32202	Windows Shell Spoofing Vulnerability	Important	4.3	No	No	Spoofing
CVE-2026-32082	Windows Simple Search and Discovery Protocol (SSDP) Service Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32083	Windows Simple Search and Discovery Protocol (SSDP) Service Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32068	Windows Simple Search and Discovery Protocol (SSDP) Service Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32183	Windows Snipping Tool Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-32089	Windows Speech Brokered Api Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32090	Windows Speech Brokered Api Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32153	Windows Speech Runtime Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-27907	Windows Storage Spaces Controller Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32076	Windows Storage Spaces Controller Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-27908	Windows TDI Translation Driver (tdx.sys) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-27921	Windows TDI Translation Driver (tdx.sys) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-27915	Windows UPnP Device Host Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-27919	Windows UPnP Device Host Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32075	Windows UPnP Device Host Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-27916	Windows UPnP Device Host Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-27920	Windows UPnP Device Host Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32077	Windows UPnP Device Host Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-27925	Windows UPnP Device Host Information Disclosure Vulnerability	Important	6.5	No	No	Info
CVE-2026-32156	Windows UPnP Device Host Remote Code Execution Vulnerability	Important	7.4	No	No	RCE
CVE-2026-32223	Windows USB Printing Stack (usbprint.sys) Elevation of Privilege Vulnerability	Important	6.8	No	No	EoP
CVE-2026-32165	Windows User Interface Core Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-27911	Windows User Interface Core Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32163	Windows User Interface Core Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-32164	Windows User Interface Core Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-23670	Windows Virtualization-Based Security (VBS) Security Feature Bypass Vulnerability	Important	5.7	No	No	SFB
CVE-2026-27917	Windows WFP NDIS Lightweight Filter Driver (wfplwfs.sys) Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32080	Windows WalletService Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-32222	Windows Win32k Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-21637 *	HackerOne: CVE-2026-21637 TLS PSK/ALPN Callback Exceptions Bypass Error Handlers	Moderate	7.5	No	No	SFB
CVE-2026-33119	Microsoft Edge (Chromium-based) for Android Spoofing Vulnerability	Moderate	5.4	No	No	Spoofing
CVE-2026-33829	Windows Snipping Tool Spoofing Vulnerability	Moderate	4.3	No	No	Spoofing
CVE-2026-5858 *	Chromium: CVE-2026-5858 Heap buffer overflow in WebML	Critical	N/A	No	No	RCE
CVE-2026-5859 *	Chromium: CVE-2026-5859 Integer overflow in WebML	Critical	N/A	No	No	RCE
CVE-2026-5272 *	Chromium: CVE-2026-5272 Heap buffer overflow in GPU	High	N/A	No	No	RCE
CVE-2026-5273 *	Chromium: CVE-2026-5273 Use after free in CSS	High	N/A	No	No	RCE
CVE-2026-5274 *	Chromium: CVE-2026-5274 Integer overflow in Codecs	High	N/A	No	No	RCE
CVE-2026-5275 *	Chromium: CVE-2026-5275 Heap buffer overflow in ANGLE	High	N/A	No	No	RCE
CVE-2026-5276 *	Chromium: CVE-2026-5276 Insufficient policy enforcement in WebUSB	High	N/A	No	No	SFB
CVE-2026-5277 *	Chromium: CVE-2026-5277 Integer overflow in ANGLE	High	N/A	No	No	RCE
CVE-2026-5279 *	Chromium: CVE-2026-5279 Object corruption in V8	High	N/A	No	No	RCE
CVE-2026-5280 *	Chromium: CVE-2026-5280 Use after free in WebCodecs	High	N/A	No	No	RCE
CVE-2026-5283 *	Chromium: CVE-2026-5283 Inappropriate implementation in ANGLE	High	N/A	No	No	SFB
CVE-2026-5284 *	Chromium: CVE-2026-5284 Use after free in Dawn	High	N/A	No	No	RCE
CVE-2026-5285 *	Chromium: CVE-2026-5285 Use after free in WebGL	High	N/A	No	No	RCE
CVE-2026-5286 *	Chromium: CVE-2026-5286 Use after free in Dawn	High	N/A	No	No	RCE
CVE-2026-5287 *	Chromium: CVE-2026-5287 Use after free in PDF	High	N/A	No	No	RCE
CVE-2026-5289 *	Chromium: CVE-2026-5289 Use after free in Navigation	High	N/A	No	No	RCE
CVE-2026-5290 *	Chromium: CVE-2026-5290 Use after free in Compositing	High	N/A	No	No	RCE
CVE-2026-5860 *	Chromium: CVE-2026-5860 Use after free in WebRTC	High	N/A	No	No	RCE
CVE-2026-5861 *	Chromium: CVE-2026-5861 Use after free in V8	High	N/A	No	No	RCE
CVE-2026-5862 *	Chromium: CVE-2026-5862 Inappropriate implementation in V8	High	N/A	No	No	SFB
CVE-2026-5863 *	Chromium: CVE-2026-5863 Inappropriate implementation in V8	High	N/A	No	No	SFB
CVE-2026-5864 *	Chromium: CVE-2026-5864 Heap buffer overflow in WebAudio	High	N/A	No	No	RCE
CVE-2026-5865 *	Chromium: CVE-2026-5865 Type Confusion in V8	High	N/A	No	No	RCE
CVE-2026-5866 *	Chromium: CVE-2026-5866 Use after free in Media	High	N/A	No	No	RCE
CVE-2026-5867 *	Chromium: CVE-2026-5867 Heap buffer overflow in WebML	High	N/A	No	No	RCE
CVE-2026-5868 *	Chromium: CVE-2026-5868 Heap buffer overflow in ANGLE	High	N/A	No	No	RCE
CVE-2026-5869 *	Chromium: CVE-2026-5869 Heap buffer overflow in WebML	High	N/A	No	No	RCE
CVE-2026-5870 *	Chromium: CVE-2026-5870 Integer overflow in Skia	High	N/A	No	No	RCE
CVE-2026-5871 *	Chromium: CVE-2026-5871 Type Confusion in V8	High	N/A	No	No	RCE
CVE-2026-5872 *	Chromium: CVE-2026-5872 Use after free in Blink	High	N/A	No	No	RCE
CVE-2026-5873 *	Chromium: CVE-2026-5873 Out of bounds read and write in V8	High	N/A	No	No	RCE
CVE-2026-5291 *	Chromium: CVE-2026-5291 Inappropriate implementation in WebGL	Medium	N/A	No	No	SFB
CVE-2026-5292 *	Chromium: CVE-2026-5292 Out of bounds read in WebCodecs	Medium	N/A	No	No	Info
CVE-2026-5874 *	Chromium: CVE-2026-5874 Use after free in PrivateAI	Medium	N/A	No	No	RCE
CVE-2026-5875 *	Chromium: CVE-2026-5875 Policy bypass in Blink	Medium	N/A	No	No	SFB
CVE-2026-5876 *	Chromium: CVE-2026-5876 Side-channel information leakage in Navigation	Medium	N/A	No	No	Info
CVE-2026-5877 *	Chromium: CVE-2026-5877 Use after free in Navigation	Medium	N/A	No	No	RCE
CVE-2026-5878 *	Chromium: CVE-2026-5878 Incorrect security UI in Blink	Medium	N/A	No	No	Spoofing
CVE-2026-5879 *	Chromium: CVE-2026-5879 Insufficient validation of untrusted input in ANGLE	Medium	N/A	No	No	SFB
CVE-2026-5880 *	Chromium: CVE-2026-5880 Incorrect security UI in browser UI	Medium	N/A	No	No	Spoofing
CVE-2026-5881 *	Chromium: CVE-2026-5881 Policy bypass in LocalNetworkAccess	Medium	N/A	No	No	SFB
CVE-2026-5882 *	Chromium: CVE-2026-5882 Incorrect security UI in Fullscreen	Medium	N/A	No	No	Spoofing
CVE-2026-5883 *	Chromium: CVE-2026-5883 Use after free in Media	Medium	N/A	No	No	RCE
CVE-2026-5884 *	Chromium: CVE-2026-5884 Insufficient validation of untrusted input in Media	Medium	N/A	No	No	SFB
CVE-2026-5885 *	Chromium: CVE-2026-5885 Insufficient validation of untrusted input in WebML	Medium	N/A	No	No	SFB
CVE-2026-5886 *	Chromium: CVE-2026-5886 Out of bounds read in WebAudio	Medium	N/A	No	No	Info
CVE-2026-5887 *	Chromium: CVE-2026-5887 Insufficient validation of untrusted input in Downloads	Medium	N/A	No	No	SFB
CVE-2026-5888 *	Chromium: CVE-2026-5888 Uninitialized Use in WebCodecs	Medium	N/A	No	No	RCE
CVE-2026-5889 *	Chromium: CVE-2026-5889 Cryptographic Flaw in PDFium	Medium	N/A	No	No	SFB
CVE-2026-5890 *	Chromium: CVE-2026-5890 Race in WebCodecs	Medium	N/A	No	No	RCE
CVE-2026-5891 *	Chromium: CVE-2026-5891 Insufficient policy enforcement in browser UI	Medium	N/A	No	No	SFB
CVE-2026-5892 *	Chromium: CVE-2026-5892 Insufficient policy enforcement in PWAs	Medium	N/A	No	No	SFB
CVE-2026-5893 *	Chromium: CVE-2026-5893 Race in V8	Medium	N/A	No	No	RCE
CVE-2026-5894 *	Chromium: CVE-2026-5894 Inappropriate implementation in PDF	Low	N/A	No	No	SFB
CVE-2026-5895 *	Chromium: CVE-2026-5895 Incorrect security UI in Omnibox	Low	N/A	No	No	Spoofing
CVE-2026-5896 *	Chromium: CVE-2026-5896 Policy bypass in Audio	Low	N/A	No	No	SFB
CVE-2026-5897 *	Chromium: CVE-2026-5897 Incorrect security UI in Downloads	Low	N/A	No	No	Spoofing
CVE-2026-5898 *	Chromium: CVE-2026-5898 Incorrect security UI in Omnibox	Low	N/A	No	No	Spoofing
CVE-2026-5899 *	Chromium: CVE-2026-5899 Incorrect security UI in History Navigation	Low	N/A	No	No	Spoofing
CVE-2026-5900 *	Chromium: CVE-2026-5900 Policy bypass in Downloads	Low	N/A	No	No	SFB
CVE-2026-5901 *	Chromium: CVE-2026-5901 Policy bypass in DevTools	Low	N/A	No	No	SFB
CVE-2026-5902 *	Chromium: CVE-2026-5902 Race in Media	Low	N/A	No	No	RCE
CVE-2026-5903 *	Chromium: CVE-2026-5903 Policy bypass in IFrameSandbox	Low	N/A	No	No	SFB
CVE-2026-5904 *	Chromium: CVE-2026-5904 Use after free in V8	Low	N/A	No	No	RCE
CVE-2026-5905 *	Chromium: CVE-2026-5905 Incorrect security UI in Permissions	Low	N/A	No	No	Spoofing
CVE-2026-5906 *	Chromium: CVE-2026-5906 Incorrect security UI in Omnibox	Low	N/A	No	No	Spoofing
CVE-2026-5907 *	Chromium: CVE-2026-5907 Insufficient data validation in Media	Low	N/A	No	No	SFB
CVE-2026-5908 *	Chromium: CVE-2026-5908 Integer overflow in Media	Low	N/A	No	No	RCE
CVE-2026-5909 *	Chromium: CVE-2026-5909 Integer overflow in Media	Low	N/A	No	No	RCE
CVE-2026-5910 *	Chromium: CVE-2026-5910 Integer overflow in Media	Low	N/A	No	No	RCE
CVE-2026-5911 *	Chromium: CVE-2026-5911 Policy bypass in ServiceWorkers	Low	N/A	No	No	SFB
CVE-2026-5912 *	Chromium: CVE-2026-5912 Integer overflow in WebRTC	Low	N/A	No	No	RCE
CVE-2026-5913 *	Chromium: CVE-2026-5913 Out of bounds read in Blink	Low	N/A	No	No	Info
CVE-2026-5914 *	Chromium: CVE-2026-5914 Type Confusion in CSS	Low	N/A	No	No	RCE
CVE-2026-5915 *	Chromium: CVE-2026-5915 Insufficient validation of untrusted input in WebML	Low	N/A	No	No	SFB
CVE-2026-5918 *	Chromium: CVE-2026-5918 Inappropriate implementation in Navigation	Low	N/A	No	No	SFB
CVE-2026-5919 *	Chromium: CVE-2026-5919 Insufficient validation of untrusted input in WebSockets	Low	N/A	No	No	SFB
CVE-2026-33118	Microsoft Edge (Chromium-based) Spoofing Vulnerability	Low	4.3	No	No	Spoofing

* Indicates this CVE had been released by a third party and is now being included in Microsoft releases.

† Indicates further administrative actions are required to fully address the vulnerability.

Looking at the other Critical-rated bugs in this month’s release, there are three Office-related bugs where the Preview Pane is once again listed as an exploit vector. I would still like to have a full-proof way of disabling the Preview Pane, but I don’t see that as an option. There’s a bug in the RDP client, but that involves connecting to a malicious RDP server. The bug in Active Directory requires authentication and a network adjacent attacker. The final Critical-rated bug is an interesting DoS in .NET Framework. An unauthenticated attacker could deny service over a network – presumably crippling any affected app made in .NET. You rarely see Critical-rated DoS bugs, but this one deserves the moniker.

Moving on to the other code execution bugs, you have quite a few open-and-own bugs in Office components, most notably Excel, where the Preview Pane is not an attack vector. The bug in SQL Server requires authentication, and as usual, additional steps are needed to ensure you have the correct update to remediate this vulnerability. The two bugs in Hyper-V almost reads like a privilege escalation since it allows unauthorized attackers to execute code locally. That’s the same for the bugs in the Windows Snipping Tool and the UPnP Device host.

More than half of this release addresses Elevation of Privilege (EoP) bugs. However, 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. The bugs in SQL Server could allow an attacker to gain SQL sysadmin privileges. One of the kernel bugs simply states an attacker could “elevate privileges locally”. How obtuse. That’s similar for the bug in afd.sys and Desktop Windows Manager, but Microsoft also states that these bugs could crash an affected system. There are several bugs that result in a sandbox escape, including Windows Push Notifications, AFD for Winsock, Management Services, and User Interface Core. Of these, CVE-2026-26167 (Push Notifications) is the most notable — it's the only one with low attack complexity, meaning no race condition needed. The rest all require winning a race condition (AC:H). The bugs in UPnP are interesting as they allow attackers to gain access to a limited set of administrator-protected objects. Not a full escalation but definitely getting access to resources they shouldn’t. The vulnerability in the Brokering File System allows attackers to gain the level of the logged on user, so don’t do your normal activities as a user with admin privileges. The bug in Azure Monitor Agent leads to root-level access.

There are a dozen different security features bypass bugs in the April release. Some of these are obvious by the title alone. For example, the bugs in Windows Hello bypass safety features within the Hello app itself. The bug in the Biometric Service allows attackers to bypass biometric protections. The vulns in BitLocker and Secure Boot bypass protections in those components. The bug in Power Apps allows attackers to bypass a security warning dialog and trick targets into triggering an external protocol call that performs unintended actions on the user’s device. The bug in Windows Shell allows attackers to bypass Mark of the Web (MotW) protections. The bug in PowerShell could almost be described as a code execution bug as exploiting it bypasses dynamic-expression security checks, which could result in code execution. The vulnerability in the Windows Recovery Environment allows local attackers to bypass BitLocker device encryption. Finally, the bug in Virtualization‑Based Security (VBS) is the most interesting of the bunch – and not just because VBS is a (relatively) new feature. The problem allows attackers to manipulate allow a compromised Windows kernel to modify memory belonging to the secure kernel, breaking the intended isolation guarantees provided by VBS. Somewhat of a sandbox escape, but this time, you’re escaping from Virtual Trust Level 0 (VTL0) to Virtual Trust Level 1 (VTL1). Neat.

Moving on to the Information Disclosure bugs fixed this month, we have 20 different CVEs. Fortunately, most of these simply result in info leaks consisting of unspecified memory contents or memory addresses. While useful in crafting exploits, they aren’t exactly exciting on their own. There are also several bugs that disclose addresses from an object a contained in a sandboxed execution environment. This includes bugs in the Print Spooler, Package Catalog, and Web Account Manager. The bug in Dynamics 365 discloses the ever ineffable “sensitive information”. There are three different info disclosure bugs in UPnP. Two allow an attacker to read from the file system, while the third discloses anything available to the LOCAL SERVICE account. The final info disclosure bug resides in Copilot and Visual Studio and allows attackers to disclose the contents of the Model Context Protocol (MCP) when using Copilot. There are those who think MCP is dead (thanks to agentic AI agents), but if you’re using a custom MCP, I doubt you would want it leaked.

The April release contains just a handful of Spoofing bugs. Some, like the bugs in .NET, Active Directory, and Windows Shell, just say that they allow spoofing over a network. Others, like the bug in Windows Snipping Tool, say similar but also note that it could be used to relay NTLMv2 hashes. The patch for RDP notes that there are new warning dialogs coming this month. The bug in the Windows Admin Center would allow an attacker to interact with other tenant’s applications and content. Finally, the spoofing bug in SharePoint is another XSS issue.

There are eight DoS bugs in the April release, but as always, Microsoft provides no actionable information about the vulnerabilities. Microsoft does offer a mitigation for the http.sys bug that can be applied while you test and deploy the patch, but I would rely on the patch rather than the mitigation. Another exception is the bug for Connected User Experiences and Telemetry Service, which allows attackers to deny service locally rather than over the network.

The final(!) bug in the April release is a Tampering bug in WSUS that reads like a DoS. According to Microsoft, “An attacker can send specially crafted packets which could affect availability of the service and result in Denial of Service (DoS).” But sure – let’s call it Tampering.

No new advisories are being released this month.

Looking Ahead

I will be in Berlin for the next Patch Tuesday, which will be May 12, and I’ll provide my full thoughts then on what will hopefully be a smaller release than this one. Until then, stay safe, happy patching, and may all your reboots be smooth and clean!

Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite

Sat, 25 Jul 2026 18:59:26 +0200

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 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 Cybersecurity industry tracking), primarily as “LAUNDRY BEAR,” a name initially coined by the Netherlands General Intelligence and Security Service (AIVD) and Defence Intelligence and Security Service (MIVD) [1].

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) CVE-2025-66376, was patched in November 2025. This demonstrates LAUNDRY BEAR’s intent and ability to deploy increasingly sophisticated technical capabilities.

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 Persistence and credential access section.

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:

United States National Security Agency (NSA)
United States Federal Bureau of Investigation (FBI)
Netherlands Defence Intelligence and Security Service (MIVD)
Netherlands General Intelligence and Security Service (AIVD)
United States Cybersecurity and Infrastructure Security Agency (CISA)
United States Defense Counterintelligence and Security Agency (DCSA)
United States Department of Defense Cyber Crime Center (DC3)
United States Department of the Treasury
United States Naval Criminal Investigative Service (NCIS)
Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)
Communications Security Establishment Canada’s (CSE’s) Canadian Centre for Cyber Security (Cyber Centre)
New Zealand National Cyber Security Centre (NCSC-NZ)
United Kingdom National Cyber Security Centre (NCSC-UK)
Czech Republic National Cyber and Information Security Agency (NÚKIB)¹
Danish Defence Intelligence Service (DDIS)²
Estonian Foreign Intelligence Service (EFIS)³
Finnish Defence Intelligence (FDI)⁴
Finnish Security and Intelligence Service (SUPO)⁵
French General Directorate for Internal Security (DGSI)⁶
French National Cybersecurity Agency (ANSSI)⁷
Italian External Intelligence and Security Agency (AISE)⁸
Italian Internal Intelligence and Security Agency (AISI)⁹
Security and Intelligence Service of the Republic of Moldova (SIS RM)¹⁰
Polish Foreign Intelligence Agency (AW)¹¹
The Military Counterintelligence Service of Poland (SKW)¹²
Spain National Intelligence Centre (CNI)¹³
Sweden National Cyber Security Centre (NCSC-SE)¹⁴

The authoring agencies urge any organizations using ZCS to implement the recommendations listed within the Mitigations 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 Indicators of compromise (IOCs).

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.

For a downloadable list of IOCs, see:

AA26-204A.stix.xml (STIX XML)
AA26-204A.stix.json (STIX JSON)

Cybersecurity industry tracking

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:

LAUNDRY BEAR
Void Blizzard [2]
CL-STA-1114 [3]
TA488 (formerly UNK_PitStop) [4]

Note: 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.

Background

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 [1] [2]. Both advisories assessed that the group was engaged in malicious cyber activity as early as April 2024.

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 [T1114.002]. The group relied on unsophisticated means of initial access, including procuring stolen credentials on criminal marketplaces [T1078], 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 & 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 [T1557].

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 [T1587.001] named “Улей” or “Ulej” (Russian for beehive), LAUNDRY BEAR successfully targeted and exfiltrated sensitive user information from organizations who use the Zimbra Collaboration Suite (ZCS) product [T1114]. Data LAUNDRY BEAR attempted to exfiltrate from compromised accounts included:

Last 90 days of emails,
Email address,
Password [T1589.001],
Global Address List (GAL) [T1087],
Two-factor authentication (2FA) tokens, and
Newly-created Application Passcode [T1098].

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.

Targeting details

LAUNDRY BEAR has targeted and compromised users in various organizations, including those associated with:

the Defense Industrial Base (DIB),
the federal and local government,
education,
energy,
law enforcement,
media,
non-governmental organizations, and
technology.

Technical details

Note: This advisory uses the MITRE ATT&CK® Matrix for Enterprise framework, version 19. This advisory also uses MITRE D3FEND^TM version 1.4.0¹⁵. See Appendix A and Appendix B for tables of the activity mapped to MITRE ATT&CK and D3FEND tactics, techniques, and countermeasures.

Ulej 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 CVE-2025-66376 [Common Weakness Enumeration (CWE) CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')], 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) [T1074.002] 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.

Reconnaissance

LAUNDRY BEAR uses the Ulej capability to exploit the CVE-2025-66376 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 [T1595] and fingerprinting datasets easily procured through various commercial vendors [T1596.005].

After identifying a target organization, the group likely compiles email addresses for individual users to target with the exploit [T1589.002] from datasets offered by commercial vendors [T1597.002], open source intelligence [T1593], or previously exfiltrated data [T1597].

Resource development

The actors procure VPSs from a variety of providers [T1583.003], including those with Know Your Customer (KYC) requirements, and often use fabricated identities. LAUNDRY BEAR primarily uses Mullvad VPN [T1583] 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 Ulej’s Flowerbed framework [T1608], which then receives and aggregates the data Ulej exfiltrates. These servers are typically only used for 7-60 days before moving to new infrastructure.

Flowerbed framework

Flowerbed is a Python project that uses Docker for containerization. The project includes four different Docker containers:

Catcher,
Certbot,
Nginx, and
Gardener.

Catcher acts as both a DNS and HTTP server to receive and aggregate exfiltrated victim information [T1048]. For additional information on Catcher, refer to the Exfiltration 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 [T1048.002]. 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.

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 [T1588.007]. The dependence on AI for a simple capability, such as Flowerbed, alongside a previous reliance on open source capabilities, such as Evilginx2 [T1588.002], likely indicates a lack of advanced technical knowledge within LAUNDRY BEAR, especially in relation to true software development capabilities.

Initial access

To gain initial access, LAUNDRY BEAR sends an email containing a malicious JavaScript payload to the target [T1566]. Through exploitation of CVE-2025-66376, this JavaScript payload is immediately executed once the user views the malicious email [T1203], such as the one shown in Figure 1, in the ZCS webmail platform. Since at least November 2025, LAUNDRY BEAR began sending these phishing emails from victim infrastructure through compromised accounts [T1199], as shown in the email metadata in Figure 2. 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.

Figure 1: Example of malicious email

Figure 2: Headers from an example malicious email

According to the National Vulnerability Database (NVD), CVE-2025-66376 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 [5]. 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 [T1587.004].

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.

Hidden in LAUNDRY BEAR’s email is a Base64 encoded payload within the “onload” field of a Scalable Vector Graphics (SVG) element [T1027.017], as shown in Figure 3. Leading up to the inclusion of this payload in the SVG element are various instances of @import directives, as required to leverage CVE-2025-66376. This payload includes an XOR encrypted final script encoded in a Base64 inner payload (see Figure 3) [T1027.013]. 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 [T1027.010], 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 [T1119]. The stages in order of appearance within the payload are as follows:

sendStartPing,
gather_email,
gather_environment,
gather_2fa_codes,
gather_app_password,
gather_device_status,
gather_oauth_consumers,
gather_autocomplete_password,
enable_mail_protocols,
gather_gal,
sendArchives, and
sendFinishPing.

Figure 3: Malicious payload of example email

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 [T1587].

Persistence and credential access

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 Exfiltration section below. Other campaigns attributed to LAUNDRY BEAR also demonstrated the group’s ability to circumvent multi-factor authentication through session token replay [T1550.004], and the Zimbra campaign follows a similar trend.

The script used in this campaign tries to discover the victim’s email address during the gather_email stage [T1087]. The script searches for this email address in two ways. First, it examines the batchInfoResponse 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 Collection 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 [T1185] 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 null over HTTPS and does not attempt DNS exfiltration.

During the gather_autocomplete_password 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 Figure 4 and Figure 5. After waiting five seconds, the script then attempts to extract the password provided automatically by the password manager from the input element shown in Figure 4. If there is no value in that input field, it checks the password input field shown in Figure 5. If neither input field contains a value, a JSON payload with a key of “autocomplete_password” and value of null is sent over HTTPS and DNS exfiltration is not attempted.

Figure 4: First illegitimate login HTML element

Figure 5: Second illegitimate login HTML element

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 enable_mail_protocols 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.

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 gather_app_password stage, the script makes a SOAP request using the “CreateAppSpecificPasswordRequest” command under the “ZimbraAccount” namespace to create a new Application Passcode [T1556.006]. The SOAP request uses “ZimbraWeb” as the name of the application.

Additionally, the script also attempts to collect 2FA tokens. During the gather_2fa_codes 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.

Collection

As demonstrated in the Persistence and credential access 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 Persistence and credential access section, other SOAP commands executed to collect victim information are shown in Table 1.

**Table 1: Additional SOAP commands used**
SOAP Command	Namespace	Stage
GetInfoRequest	zimbraAccount	gather_environment
GetDeviceStatusRequest	zimbraSync	gather_device_status
GetOAuthConsumersRequest	zimbraAccount	gather_oauth_consumers
SearchGalRequest	zimbraAccount	gather_gal

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.

During the gather_environment 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 Table 2) to determine the client type. The corresponding value is then used as the payload when exfiltrating the client type.

**Table 2: ZCS webmail client types**
Indicator	Client Type	Associated Value
?client=advanced	Advanced	c
/h/	Standard	h
/modern/	Modern	m

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&meta=0&query=date:-{DAY_OFFSET}d AND (not in:junk)”. The {DAY_OFFSET} 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 zd_comp_YYYY-MM-DD, and value of true, is saved to the window.top.localStorage property. This variable is saved regardless of whether the email is successfully exfiltrated.

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 {DAY_OFFSET} 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 Exfiltration section.

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 Exfiltration 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 gather_gal:{VAL}:api. The {VAL} 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 {DAY_OFFSET}, with a format of sendArchive:day-{DAY_OFFSET}.

Exfiltration

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 [T1048.003] and HTTPS. Some information is exfiltrated over both the DNS and HTTPS channels.

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.

DNS exfiltration

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, Ulej 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 Figure 6. Any traffic involving DNS exfiltration will have “d-“ prefixing the victim identifier, and the subdomain immediately following indicates the type of information being exfiltrated.

Figure 6: Structure for information exfiltrated by DNS

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. Table 3 lists both the information exfiltrated via DNS and their corresponding data type identifiers in the DNS queries.

**Table 3: DNS exfiltration**
Type of Information	Exfiltration Stage	Data Type
Victim’s Email Address	gather_email	e
Client Type	gather_environment	c
Zimbra Version	gather_environment	v
URL at Time of Exploitation	gather_environment	url
2FA Scratch Codes	gather_2fa_codes	2fa
Newly Created Application Password	gather_app_password	pa
Harvested Autocomplete Password	gather_autocomplete_password	pw

HTTPS exfiltration

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 Table 4. Traffic associated with HTTPS exfiltration will use the URL scheme shown in Figure 7.

**Table 4: HTTPS exfiltration types**
Content Type	URL Path
application/json	/v/p
application/octet-stream	/v/d

Figure 7: Structure for information exfiltrated by HTTPS

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.

Table 5 provides a summary of the JSON-based exfiltration.

**Table 5: HTTPS JSON exfiltration**
Type of Information	Exfiltration Stage	JSON Key(s)
Victim’s Email Address	gather_email	email
Client Type, Version, and Current URL	gather_environment	client, version, full_url
Newly Created Application Password	gather_app_password	app_password
Harvested Autocomplete Password	gather_autocomplete_password	autocomplete_password

The script transmits all HTTPS exfiltration not identified in Table 5 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. Table 6 summarizes the data exfiltrated in this format.

**Table 6: HTTPS binary exfiltration**
Type of Information	Exfiltration Stage	X-Filename Header
SOAP request for GetInfoRequest	gather_environment	zimbra_batch_analytics.json
SOAP request for GetScratchCodesRequest	gather_2fa_codes	zimbra_batch_analytics.json
SOAP request for GetDeviceStatusRequest	gather_device_status	zimbra_batch_analytics.json
SOAP request for GetOAuthConsumersRequest	gather_oauth_consumers	zimbra_batch_analytics.json
Victim Organization’s Global Address List	gather_gal	telemetry_{1-20}.json
Last 90 Days of Victim’s Emails	sendArchives	telemetryData_{0-89}.json

The script sends all exfiltrated data identified in Table 6 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 [T1560]. Although most of the exfiltration consists of valid JSON, the script still attempts to exfiltrate all information identified in Table 6 using the application/octet-stream content typing rather than application/json.

At the beginning and end of the collection and exfiltration activity, during the sendStartPing and sendFinishPing 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 Figure 2, using a URL path of “/v/p” and with a “subtype” key that shows which type of action it logged (start, finish, or error).

Catcher

Ulej 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 Resource development section. It receives exfiltrated data and temporarily stores it, enabling its eventual transfer to infrastructure designed for long-term, secure storage.

Catcher acts as an HTTP server over port 8000 and a DNS server on port 53. As described in the Resource development 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.

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.

However, if a query includes a domain formatted as shown in Figure 6 and Figure 7, the service saves a log file in JSON format to disk containing the following details of the DNS query:

Time of query,
Source IP address for query,
Queried domain, and
Type of query.

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 Figure 6 and Figure 7. 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:

Time,
Source IP address,
Request method,
Host,
Path,
Query string,
Headers, and
Base64 payload.

These JSON event log files and binary output files are then initially saved to the directory /root/hits/tmp and later moved to the /root/hits/ready 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 Figure 8 also executes hourly to remove all files last modified at least two days ago from the /root/hits/ready directory.

Figure 8: Command used for automated directory cleanup

Response strategies

Mitigations

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.

All organizations that use the ZCS webmail service should immediately prioritize ensuring that their ZCS is not running a vulnerable version. A patch for CVE-2025-66376 was released for both 10.1.13 and 10.0.18 versions of ZCS [D3-AH]. 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 [d3f:Isolate].

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 [D3-AH]. Administrators can maintain awareness of active vulnerability exploitation by referencing open source resources, including CISA’s Known Exploited Vulnerabilities Catalog and NCSC-UK’s Responding to active exploitation of vulnerabilities guidance.

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 [D3-CH]. However, Application Passcodes may still be necessary and should be monitored closely.

Organizations should implement network monitoring capabilities with collection and short-term retention of packet capture or NetFlow data and maintain log collection and storage [CPG 3.Q]. This will allow organizations to monitor for and identify suspicious network activity [CPG 4.B], such as:

Significant amounts of outbound data being sent to IPs associated with VPS providers not used by the organization [D3-NTA];
Frequent DNS queries for a suspicious domain with seemingly random subdomains [D3-DNSTA];
A sudden spike of connections to a server associated with a recently established domain [D3-NTCD]; and
Connections to internal services, such as webmail, from VPN providers frequently leveraged by this group for nefarious activity, such as Mullvad VPN [D3-NTCD].

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 Exfiltration section of this advisory.

Indicators of compromise (IOCs)

Flowerbed infrastructure

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. (Disclaimer: 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.) Table 7 provides details about the server infrastructure used to host Flowerbed, and Table 8 lists the corresponding SHA-1 hash values for the Let’s Encrypt certificates used by that infrastructure [D3-IAA].

**Table 7: Flowerbed server infrastructure**
Domain	IP Address	First Seen	Last Seen
zmailanalytics[.]com	216.252.238[.]104	8 July 2025	15 October 2025
zimbra-metadata[.]com	216.252.238[.]18	20 August 2025	14 October 2025
analyticemailmeter[.]com	37.120.247[.]228	24 September 2025	18 March 2026
emailanalytics.com[.]ua	185.86.79[.]95	24 September 2025	18 March 2026
mailnalysis[.]com	104.248.134[.]194	11 November 2025	17 February 2026
zimbrastat[.]com	64.226.124[.]190	18 December 2025	18 March 2026
zimbrasoft.com[.]ua	193.238.152[.]66	20 January 2026	18 March 2026
synacorzimbra[.]nl	216.252.238[.]64	3 February 2026	30 March 2026
istc-cloud[.]com	194.156.103[.]193	5 February 2026	30 March 2026

**Table 8: Flowerbed X.509 certificate SHA-1 hashes**
Associated Domain	X.509 SHA-1 Hash	First Seen	Last Seen
zmailanalytics[.]com	2e4f314bc9943cab5005d6fde0b271c74d47bc9d	8 Jul 2025	6 Aug 2025
*.i.zmailanalytics[.]com	50a87d926621dd06389ba50d86e0ff574ed713a8	6 Aug 2025	13 Oct 2025
*.i.zimbra-metadata[.]com	c5a72420e7bb308d078e62128430897f82194c95	20 Aug 2025	14 Oct 2025
*.i.analyticemailmeter[.]com	8959c4d29e29f02ea94ea8bb21c8df2594c5549d	24 Sep 2025	8 Nov 2025
*.i.emailanalytics.com[.]ua	62eb76432597694edb01c1fe57aab0cfe03a7178	25 Sep 2025	27 Sep 2025
*.i.mailnalysis[.]com	cddf5c3be1e07f28140aed165b929bf2d614922a	12 Nov 2025	17 Dec 2025
*.i.zimbrastat[.]com	18b3ad442ce73cc8656d51d75bbd7c855f2cb7e8	18 Dec 2025	28 Dec 2025
*.i.zimbrasoft.com[.]ua	1b25041ececf2457eef0270fc1d785cec8ec9ded	21 Jan 2026	10 Feb 2026
*.i.synacorzimbra[.]nl	e4fe6466a4f9a4249fe330651e914e45bbdca44a	5 Feb 2026	22 Mar 2026
*.i.istc-cloud[.]com	b6b77c9a455225d525834a403ca9ef5481ed0447	12 Feb 2026	30 Mar 2026

LAUNDRY BEAR has used the following email addresses to procure resources used for this campaign:

ivanka.zurabishvili@proton[.]me,
zmul1@buildandconsulting[.]com,
garrysmithme@pinmx[.]net, and
hostingclient@pinmx[.]net.

Phishing distribution

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.

The following email addresses have distributed payloads attributed to this campaign:

c.laurent.ejfa@proton[.]me,
j.moreau.epsc@proton[.]me,
liberty.insights@proton[.]me,
certain email addresses (presumably compromised) at the isofts.kiev[.]ua domain (i.e., ending with @isofts.kiev[.]ua), and
certain email addresses (presumably compromised) at the navs.edu[.]ua domain (i.e., ending with @navs.edu[.]ua).

Additionally, the following are SHA-256 hashes of email samples containing the malicious payload attributed to this campaign:

98df604ecc57f884a2e6ce3266a0013ad64455cac48442c2312cfa4765007aaf,
60db9abae75cd8ccc49dd7ea5feb41677566dcd442f12ebc5745ffd2810fb874,
b1f5beb1175fc5c7d1806a2f0d900eb124c54f0286c5c52b66eea7a6633adb1d, and
1517b3caa495f6c4e832df9c75fc94667e3c233773f7fa4e056d5e30e5ead760.

Post-compromise artifacts

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.

This Ulej 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 /opt/zimbra/log/mailbox.log file [D3-PA]. A significant amount of SOAP request activity that aligns with what was described in the Persistence and credential access and Collection sections of this advisory could indicate a potential compromise. Specific examples of high-risk SOAP request activity might include:

Many SearchGalRequest command requests from a single user over a short period of time;
Use of the CreateAppSpecificPasswordRequest command, especially in cases where it is creating an Application Passcode named “ZimbraWeb”; and
Use of the GetScratchCodesRequest command.

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 [D3-PA]. 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 zd_comp_YYYY-MM-DD, as explained in the Collection section of this advisory.

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.”

In instances where organizations identify victims of this campaign, they should also examine the inbox of the suspected victim for the original phishing email [D3-MA]. If an email that has a payload exploiting CVE-2025-66376 is discovered, 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.

Remediation

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 CVE-2025-66376.

Organizations should use identifiers from the IOCs 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.

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 [CPG 3.B] and creating unique credentials [CPG 3.C], specifically noting that compromised employees might have had any password stored in a password manager exfiltrated.

Works cited

[1] 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. 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

[2] Microsoft Corporation. New Russia-affiliated actor Void Blizzard targets critical sectors for espionage. 2025. https://www.microsoft.com/en-us/security/blog/2025/05/27/new-russia-affiliated-actor-void-blizzard-targets-critical-sectors-for-espionage/

[3] Palo Alto Networks Unit 42. Russian Global Webmail Espionage. 2026. https://unit42.paloaltonetworks.com/russian-webmail-espionage/

[4] Proofpoint. TA488 Targets Zimbra Mailservers with Half-Click Exploits. 2026. https://www.proofpoint.com/us/blog/threat-insight/ta488-zcs-exploit

[5] Seqrite. Operation GhostMail: Russian APT exploits Zimbra Webmail to Target Ukraine State Agency. 2026. https://www.seqrite.com/blog/operation-ghostmail-zimbra-xss-russian-apt-ukraine/

Footnotes

¹ Národní úřad pro kybernetickou a informační bezpečnost
²Forsvarets Efterretningstjeneste
³Välisluureamet
⁴ Sotilastiedustelu
⁵ Suojelupoliisi
⁶ Direction générale de la sécurité intérieure
⁷ Agence nationale de la sécurité des systèmes d’information
⁸ Agenzia Informazioni e Sicurezza Esterna
⁹ Agenzia Informazioni e Sicurezza Interna
¹⁰ Serviciul de Informații și Securitate al Republicii Moldova
¹¹Agencja Wywiadu
¹²Służba Kontrwywiadu Wojskowego
¹³Centro Nacional de Inteligencia
¹⁴Nationellt Cybersäkerhetscenter
¹⁵ MITRE and ATT&CK are registered trademarks of The MITRE Corporation. MITRE D3FEND is a trademark of The MITRE Corporation.

Acknowledgements

The authoring agencies acknowledge the contributions to this advisory from Palo Alto Networks Unit 42 and Proofpoint.

Disclaimer of endorsement

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.

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.

Purpose

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.

Contact

United States organizations

National Security Agency
Cybersecurity Report Feedback: CybersecurityReports@nsa.gov
Defense Industrial Base Inquiries and Cybersecurity Services: DIB_Defense@cyber.nsa.gov
Media Inquiries / Press Desk: NSA Media Relations: 443-634-0721, MediaRelations@nsa.gov
Cybersecurity and Infrastructure Security Agency
CISA’s 24/7 Operations Center (contact@cisa.dhs.gov), or by calling 1-844-Say-CISA (1-844-729-2472).
Federal Bureau of Investigation
If you or someone you know has fallen victim to this campaign, file a complaint with IC3.
Defense Counterintelligence and Security Agency
DCSA Counterintelligence, Cyber Mission Center, Cyber Threat Operations Branch: DCSA.CI.CyberOps@mail.mil
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.
Media/Public Inquiries: dcsa.quantico.dcsa-hq.mbx.pa@mail.mil
Department of Defense Cyber Crime Center
Defense Industrial Base Inquiries and Cybersecurity Services: DC3.DCISE@us.af.mil
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 https://dibnet.dod.mil
Media Inquiries / Press Desk: DC3.Information@us.af.mil
Naval Criminal Investigative Service
To report criminal activity impacting the United States Navy, go to www.ncis.navy.mil and click “Submit a Tip”

Dutch organizations

Defence Intelligence and Security Service (MIVD): https://www.defensie.nl/onderwerpen/m/militaire-inlichtingen-en-veiligheid
General Intelligence and Security Service (AIVD): https://www.aivd.nl

Australian organizations

Australian Signals Directorate
Visit cyber.gov.au or call 1300 292 371 (1300 CYBER 1) to report cybersecurity incidents and access alerts and advisories.

Canadian organizations

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.
Report an incident or suspicious activity to the Cyber Centre by email at contact@cyber.gc.ca, online via the reporting tool Report a cyber incident - Canadian Centre for Cyber Security or by phone at 1-833-CYBER-88 (1-833-292-3788).

New Zealand organizations

New Zealand National Cyber Security Centre (NCSC-NZ): info@ncsc.govt.nz

United Kingdom organizations

Report significant cyber security incidents to ncsc.gov.uk/report-an-incident (monitored 24/7)

Estonia organizations

Estonian Foreign Intelligence Service (EFIS): info@valisluureamet.ee

Finnish organizations

Finnish Security and Intelligence Service: supo.fi/en/contact

French organizations

French organizations are encouraged to report suspicious activity or incident related information found in this advisory by contacting ANSSI/CERT-FR at: cert-fr@ssi.gouv.fr or by phone at: 3218 or +33 9 70 83 32 18.

Italian Organizations

Italian External Intelligence and Security Agency (AISE):
Visit https://www.sicurezzanazionale.gov.it/
Italian Internal Intelligence and Security Agency (AISI):
Visit https://www.sicurezzanazionale.gov.it/

Moldovan organizations

Security and Intelligence Service of the Republic of Moldova (SIS RM): cybersec@sis.md

Polish organizations

Polish Foreign Intelligence Agency (AW): ctiteam@aw.gov.pl

Appendix A: MITRE ATT&CK tactics and techniques

See Table 9 through Table 19 for all the threat actor tactics and techniques referenced in this advisory.

**Table 9: Reconnaissance**
Technique Title	ID	Use
Gather Victim Identity Information: Credentials	T1589.001	The payload attempts to intercept a victim’s password from their password manager.
Gather Victim Identity Information: Email Addresses	T1589.002	The payload attempts to grab the victim’s email address from various data stores.
Search Open Websites/Domains	T1593	This group likely leverages public information to support target development.
Active Scanning	T1595	Port scanning can be used by this group to assist with determining exploitability of identified targets.
Search Open Technical Databases: Scan Databases	T1596.005	Various public datasets can provide information to support discovery of exploitable targets.
Search Closed Sources	T1597	Previously exfiltrated data can be used to enhance target development efforts.
Search Closed Sources: Purchase Technical Data	T1597.002	Commercial datasets can also be used to support target development efforts.

**Table 10: Resource Development**
Technique Title	ID	Use
Acquire Infrastructure	T1583	This group used Mullvad VPN to anonymize traffic sent to operational infrastructure.
Acquire Infrastructure: Virtual Private Server	T1583.003	This group procured VPS servers from a variety of vendors.
Develop Capabilities	T1587	The Ulej capability was developed likely for use by this group to conduct spear phishing campaigns.
Develop Capabilities: Malware	T1587.001	Development of a novel payload that steals a victim’s emails and other sensitive account information.
Develop Capabilities: Exploits	T1587.004	Development of a novel, at the time, cross-site-scripting (XSS) exploit that enables execution of arbitrary JavaScript.
Obtain Capabilities: Tool	T1588.002	Open source tools, such as Evilginx2, have also been used by the group.
Obtain Capabilities: Artificial Intelligence	T1588.007	The group appears to have leveraged AI to support development efforts.
Stage Capabilities	T1608	Flowerbed is deployed to a procured server in the cloud.

**Table 11: Initial Access**
Technique Title	ID	Use
Valid Accounts	T1078	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.
Trusted Relationship	T1199	The group sends malicious payloads to targeted individuals using previously compromised accounts that might have an established relationship with the target.
Phishing	T1566	The actors used spear phishing to lure users into opening malicious email.

**Table 12: Execution**
Technique Title	ID	Use
Exploitation for Client Execution	T1203	An XSS vulnerability was leveraged to execute the JavaScript payload.

**Table 13: Persistence**
Technique Title	ID	Use
Account Manipulation	T1098	Enabling IMAP and Application Passcodes provides persistent access to the compromised account.
Modify Authentication Process: Multi-Factor Authentication	T1556.006	Creating Application Passcodes to bypass 2FA and stealing a user’s “Scratch Keys,” which can be used in place of a 2FA token.

**Table 14: Privilege Escalation**
Technique Title	ID	Use
Valid Accounts	T1078	This actor has used commercial datasets to acquire account credentials and gain unauthorized privileged access to accounts.

**Table 15: Stealth**
Technique Title	ID	Use
Obfuscated Files or Information: Command Obfuscation	T1027.010	Obfuscated JavaScript payload sent to targets to exploit the XSS vulnerability.
Obfuscated Files or Information: Encrypted/Encoded File	T1027.013	The JavaScript payload included both a Base64-encoded and XOR-encrypted inner payload.
Obfuscated Files or Information: SVG Smuggling	T1027.017	The payload was contained in an “onload” attribute within an SVG image included in the malicious email.
Use Alternate Authentication Material: Web Session Cookie	T1550.004	Previous campaigns using AiTM leveraged stealing and use of a victim’s session cookies to authenticate.

**Table 16: Credential Access**
Technique Title	ID	Use
Modify Authentication Process: Multi-Factor Authentication	T1556.006	Creating Application Passcodes to bypass 2FA and stealing a user’s “Scratch Keys,” which can be used in place of a 2FA token.
Adversary-in-the-Middle	T1557	Previous campaigns used Evilginx2 as an AiTM toolkit to intercept credentials and session cookies.

**Table 17: Collection**
Technique Title	ID	Use
Data Staged: Remote Data Staging	T1074.002	Exfiltrated data was sent to an actor-controlled VPS prior to assumed long-term storage solutions.
Email Collection	T1114	This group has emphasized collection of emails.
Email Collection: Remote Email Collection	T1114.002	Emails are collected via API calls to the ZCS mail server and are not collected from emails stored directly on the victim’s device.
Automated Collection	T1119	Upon execution, the JavaScript payload automatically collects all relevant information in stages.
Browser Session Hijacking	T1185	The JavaScript payload leverages the user’s authenticated browser session to make API requests as the user.
Archive Collected Data	T1560	Emails are exfiltrated with GZIP compression.

**Table 18: Discovery**
Technique Title	ID	Use
Account Discovery	T1087	Stolen Global Access Lists provide the group with new users to target.

**Table 19: Exfiltration**
Technique Title	ID	Use
Exfiltration Over Alternative Protocol	T1048	Victim information was exfiltrated over both HTTPS and DNS.
Exfiltration Over Alternative Protocol: Exfiltration Over Asymmetric Encrypted Non-C2 Protocol	T1048.002	Some payloads, especially ones with large amounts of data, were exfiltrated over HTTPS.
Exfiltration Over Alternative Protocol: Exfiltration Over Unencrypted Non-C2 Protocol	T1048.003	Some smaller bandwidth payloads were exfiltrated over DNS using Base32 encoding.

Appendix B: MITRE D3FEND countermeasures

See Table 20 for a mapping of several of the cybersecurity countermeasures mentioned in this advisory.

**Table 20: MITRE D3FEND Countermeasures**
Countermeasure Title	ID	Description
Application Hardening	D3-AH	Organizations should immediately prioritize patching CVE-2025-66376. Organizations should promptly apply software updates to all email systems.
Isolate	d3f:Isolate	Organizations that cannot feasibly patch should use alternative mail clients.
Credential Hardening	D3-CH	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.
Network Traffic Analysis	D3-NTA	Organizations should monitor for significant amounts of outbound data being sent to IPs associated with VPS providers not used by the organization.
DNS Traffic Analysis	D3-DNSTA	Organizations should monitor for frequent DNS queries to a suspicious domain for seemingly random subdomains.
Network Traffic Community Deviation	D3-NTCD	Organizations should monitor for a sudden spike of connections to a server associated with a recently established domain. Organizations should monitor for connections to internal services, such as webmail, from VPN providers.
Identifier Activity Analysis	D3-IAA	Organizations should search for the listed known IOCs.
Process Analysis	D3-PA	Organizations should search ZCS log files for specific commands used by the malicious script. Organizations should search the localStorage property in web browsers for the ZCS webmail client for “ZimbraWeb” Application Passcodes.
Message Analysis	D3-MA	Organizations that suspect they have victims of this campaign should search for emails with a malicious payload to identify other victims.

18 Enterprise-Architecture-Tools

Sat, 25 Jul 2026 18:59:25 +0200

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 Geschäftsziele optimal zu unterstützen. Sie sorgen ebenfalls dafür, dass Unternehmen ihre Roadmaps für die digitale Transformation 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.

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.

Empfehlenswerte Enterprise-Architecture-Tools

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.

Ardoq

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.

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.

Wichtigste Use Cases:

“Architektonischen Stress” bei Lastspitzen simulieren, falls größere Veränderungen bevorstehen;
Verstehen, wie verändertes Nutzerverhalten neue Anforderungen generiert;
Application Portfolio Management, um besser strategisch zu planen.

Atoll Group SAMU

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.

Wichtigste Use Cases:

Enterprise-Architektur visualisieren;
strategische Planungsprozesse und Architektur-Reviews mit Informationen unterfüttern;
mithilfe einer visuellen Verständnisgrundlage die Kommunikation verbessern.

Avolution Abacus

Dieses Tool erfasst die Breite und den Umfang der Unternehmensarchitektur mit Hilfe eines auf Diagrammen basierenden Dashboards. Die Integration mit gängigen Tools wie SharePoint, Excel, 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.

Wichtigste Use Cases:

die IT für das gesamte Unternehmen “öffnen”, um ein allgemeines Verständnis der Datenflüsse zu erzeugen;
umfassendes Enterprise Modeling, um eine Roadmap für künftige Entwicklungen zu erstellen;
Business-Metriken tracken, die mit der Unternehmens-Performance zusammenhängen.

BOC Group ADOIT

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.

Wichtigste Use Cases:

ein unternehmensweites Modell erstellen, das bei sämtlichen Teammitgliedern ein Verständnis über den Stack schafft – und wie man diesen verbessern kann;
vollständiger Zugriff auf EA-Daten über eine Mobile-Anwendung;
bei Fusionen und Übernahmen den Tech-Bereich durch genaues Asset-Mapping orchestrieren.

Bizzdesign Hopex

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 Azure 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.

Wichtigste Use Cases:

datengestützte Erkenntnisse herbeiführen, um Cloud- und Anwendungsbereitstellung zu steuern;
akkurate Nutzungsmodelle erstellen, um Architekturanforderungen zu verstehen;
eine Bedarfsschätzung mit Umfragen und anderen Tools vornehmen, um für die Zukunft zu planen.

Bizzdesign Horizzon

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 Change Management 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 im Januar 2025 auch den EA-Geschäftsbereich der Software AG – Alfabet – übernommen.

Wichtigste Use Cases:

Vorhersage zukünftiger Anforderungen durch Predictive Modeling;
Orchestrieren von Workflows auf der Basis der technischen und der Business-Architektur;
Antizipieren von Risiken sowie Security- und Governance-Problemen durch die Modellierung von Datensicherheitsanforderungen.

Capstera

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.

Wichtigste Use Cases:

Reports erstellen, die sich erst einmal mit der Business-Architektur selbst beschäftigen;
Beziehungen zwischen Menschen, Abteilungen und Rollen analysieren;
die langfristige strategische Planung vorantreiben.

Clausmark Bee360

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.

Wichtigste Use Cases:

C-Suite-Ebene befähigen, Projekte zu managen und Assets zuzuweisen;
präzise digitale Zwillinge entwickeln, um ein Verständnis über Datenflüsse zu schaffen und künftige Erweiterungen zu planen;
integrierte Wissensdatenbank aufbauen, um alle digitalen Workflows zu tracken.

EAS

Das Essential-Paket von EAS (Enterprise Architecture Solutions) nahm als Open-Source-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.

Wichtigste Use Cases:

den technischen Reifegrad der eigenen Architektur evaluieren;
Sicherheit und Governance durch besseres Asset Tracking optimieren;
wachsende Systemkomplexität kontrollieren und managen.

OrbusInfinity

Orbus Software hat Anfang 2025 die Akquisition seines Konkurrenten Capsifi abgeschlossen. 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 integrieren, darunter etwa von Microsoft, Flexera, ManageEngine oder ServiceNow.

Wichtigste Use Cases:

Stakeholder-Management;
Enterprise-Landschaften visualisieren;
Entscheidungsfindung und Datenanalyse automatisieren.

Planview Enterprise One

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.

Wichtigste Use Cases:

eine langfristige, strategische Vision für die Architekturentwicklung aufbauen;
Entwicklungsarbeit auf Projektebene tracken und in eine beliebige Strategie integrieren;
mit Fokus auf die Customer Experience und die Produktstruktur den Change vorantreiben.

QualiWare Enterprise Architecture

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.

Wichtigste Use Cases:

ein kollaboratives Ökosystem für Business Manager aufbauen, das ein Verständnis von der Enterprise Architecture vermittelt;
architektonische Designelemente erfassen, um ein Wissens-Ökosystem rund um den Stack aufzubauen;
eine breite Beteiligung in Sachen Dokumentationserstellung und -überprüfung fördern.

Quest Erwin Evolve

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.

Wichtigste Use Cases:

einen digitalen Zwilling für die strategische Modellierung der Enterprise Data Architecture erstellen;
Customer Journeys verstehen;
Services und Systeme mit Application Portfolio Management tracken.

SAP LeanIX Enterprise Architecture Suite

Die Tool-Sammlung von LeanIX umfasst unter anderem Enterprise Architecture Management und andere Bereiche, die für Aufgaben wie SaaS– 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 ist LeanIX Teil von SAP.

Wichtigste Use Cases:

Anwendungsmodernisierung und Cloud-Migration managen;
Obsoleszenz von Software-Services evaluieren;
Kosten kontrollieren und managen.

ServiceNow

Die Tool-Sammlung von ServiceNow lässt sich auf verschiedene Architekturtypen herunterbrechen, darunter Assets, DevOps, 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.

Wichtigste Use Cases:

Tracken von Assets, Services und Systemen, die das Unternehmen ausmachen;
Governance-Themen, Risikobegrenzung, IT-Management und Security Operations werden in einer Plattform zusammengeführt;
durch die Integration von CRM-Tools lassen sich auch kundenorientierte Services managen.

Sparx Systems

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.

Wichtigste Use Cases:

Nachfrage- und Lastveränderungen zur Prognose künftiger Anforderungen simulieren;
(potenzielle) Probleme durch eine Verbindungs-Matrix im Auge behalten;
Dokumentation erstellen.

Unicom System Architect

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.

Wichtigste Use Cases:

Was-wäre-wenn-Fragen zum Architekturmodell stellen;
ein Metamodell von Daten und Systemen aufbauen;
Migrations- und Transformationspläne erstellen.

ValueBlue BlueDolphin

Dieses EA-Tool sammelt Daten auf dreierlei Art:

Es importiert Basisdaten auf der Grundlage standardgesteuerter Automatisierung (ITSM, SAM).
Es arbeitet mit den Dateiformaten von Architekten und Systemdesignern – etwa ArchiMate oder BPMN.
Es gibt Fragebögen an andere Stakeholder heraus, die auf anpassbaren Vorlagen basieren.

Die aufbereiteten Informationen werden in einer visuellen Umgebung bereitgestellt, die Auskunft über die historische Entwicklung von Systemen gibt.

Wichtigste Use Cases:

systemweite Daten von internen und externen Stakeholdern automatisiert und formularbasiert erfassen;
zukunftsorientierte Reportings erzeugen, um den Change zu überwachen und voranzutreiben;
Kooperation und Zusammenarbeit durch offenes Data Reporting fördern.

(fm)

Dieser Artikel ist im Original bei unserer Schwesterpublikation CIO.com erschienen.

How to get more storage on your Android without using a microSD Card

Sat, 25 Jul 2026 17:47:31 +0200

Cloud storage isn't your only option.

Paperless-ngx 3.0.2 erschienen: Nachzügler-Updates beheben Migrations-Fehler

Sat, 25 Jul 2026 17:17:25 +0200

Für Nutzer des quelloffenen Dokumenten-Management-Systems Paperless-ngx gibt es frische Updates: Nach dem großen Major-Release 3.0.0 haben die Entwickler zügig die Versionen 3.0.1 und 3.0.2 nachgeschoben, um...

Zum Beitrag: Paperless-ngx 3.0.2 erschienen: Nachzügler-Updates beheben Migrations-Fehler

Wo du uns folgen kannst: Facebook, Reddit, Google News, X, Threads

Auf dem Laufenden bleiben?
Fügt uns doch bei Google als bevorzugte Quelle hinzu!

17 Things to know for Android developers at Google I/O

Sat, 25 Jul 2026 10:15:45 +0200

Posted by Matthew McCullough, VP, Product Management, Android Developer

Today at Google I/O, we announced the many ways we’re powering agentic workflows to increase your productivity and ensure your apps shine across the expanding Android ecosystem. Here’s a recap of 17 of our favorite announcements for Android developers; you can also see what was announced last week in The Android Show: I/O Edition. Stay tuned over the next two days as we dive into all of the topics in more detail!

Build High Quality Android Apps Using Agents

1: Android CLI: helping you build with any agent, LLM, and tool

Android CLI is now stable. It offers programmatic tools that allow any AI agent, including Claude Code, Codex, or Antigravity, to perform core Android tasks much more easily and efficiently. With today’s release, it also provides a bridge to tap directly into the "heavy-lifting" power of Android Studio to give you the production-ready polish needed for professional Android development. By leveraging the new android studio commands, developers can now grant their preferred agents the ability to perform semantic symbol resolution, analyze files for warnings, and even render Jetpack Compose previews. This release also enables official support for "Journeys" through new Android skills, which enables agents to execute end-to-end UI tests under your direction. Watch the developer keynote, and tune into the What’s New in Android tools talk for more information.

You can now easily install Android CLI for use with Google Antigravity 2.0.

2: Build production-ready apps with ease in Google AI Studio

Developers and creators can now build native Android apps, simply with a prompt in Google AI Studio. The apps are built with development best practices like Jetpack Compose, Kotlin, and APIs that leverage our recommended developer patterns. Google AI Studio enables developers to prototype, iterate via an embedded emulator, and deploy to physical devices without heavy local installations. Developers are then able to take those apps and share them to Android devices, as well as share them with others for testing through Google Play Console’s internal testing track. If a developer wants to prepare their app for a wider release, they’re able to take it to Android Studio for advanced debugging, testing, and UI polish. Watch the developer keynote, and tune into the What’s New in Android tools talk for more information.

Use the embedded Android Emulator to create Android apps in Google AI Studio

3: Accelerating AI coding assistance with Android Bench

Android Bench is our LLM leaderboard for Android development challenges. The goal is to accelerate model improvements, so you have more useful options for AI assistance. Many of you have been using open-weight models for AI assistance, so we’re now adding commonly used ones, such as Gemma 4, to the leaderboard, so you can see how LLMs that offer offline access and additional flexibility for power-users measure up. We're continuously working on increasing the difficulty of challenges we’re giving LLMs, to continue encouraging more useful improvements.

4: Convert iOS apps to Android with the Migration Assistant in Android Studio

The Migration Assistant in Android Studio is designed to port apps from platforms like iOS, React Native, or web frameworks to native Android. By simply selecting an existing project, developers can have the agent intelligently map features, convert assets like storyboards and SVGs, and implement Android best practices using Jetpack Compose and our recommended Jetpack libraries. This effectively transforms what used to be weeks of manual porting into a streamlined agentic workflow that only takes hours. We shared a preview of the incoming feature in the developer keynote.

A sneak peek of the Migration Assistant converting an iOS app into a native Android app

Building AI Into Your Apps

5: Building Intelligent Apps with generative AI

Generative AI enables you to create apps that are more intelligent, personalized, and agentic than ever before. This year, we introduced the latest advancements in on-device intelligence with a preview of Gemini Nano 4 for tasks like data extraction and summarization. We also expanded cloud capabilities via Firebase AI Logic, allowing developers to leverage Gemini models with robust grounding (including URL, Maps, and web search) to build smarter, more capable assistants. Furthermore, we unveiled our hybrid inference approach and the new Agent Development Kit (ADK) for Android, alongside communication protocols like AG-UI and A2UI that simplify the creation of autonomous, agentic experiences. To start integrating these powerful features, explore the developer documentation, and watch the technical deep dive session where we showcase all these technologies.

6: Experiment with AppFunctions today

AppFunctions is an Android platform API with an accompanying Jetpack library to simplify building Android MCP integrations. It empowers your apps to behave like on device MCP servers, contributing functions that act as tools for use by agents and assistants. AppFunctions integration with Gemini is currently in a private preview with trusted testers, and you can begin preparing your apps already. You can sign up for the Early Access Program and start experimenting using the API guidance, sample, and skill today.

The Future is Adaptive

7: Android is now Compose First; Views are now in maintenance mode.

Compose is our standard for UI development, and we are moving to a Compose-first approach for all future guidance and libraries. Building on five years of evolution, the latest releases deliver a more mature toolkit, from the highly customizable Styles API to refined shared element transitions and enhanced input support. These updates allow you to build beautiful, adaptive apps with less code and better performance. Learn more about what Compose-first means for Android Development in our blog post.

Build Android UI with Compose

8: Building seamless Android experiences across devices with Jetpack Compose

The Android ecosystem is now Adaptive by Default, moving fluidly across phones, foldables, tablets, cars, XR, and expanding usages with Googlebook and connected displays. With over 580 million large-screen devices, and users on multiple devices spending up to 14x more on apps, the investment in adaptive design presents a massive opportunity. Jetpack Compose is the definitive engine for this transition, offering core tools like our latest Jetpack Navigation 3 release, new experimental Grid and FlexBox layouts, enhanced non-touch input support, and CameraX for correct camera previews across any window size. Furthermore, new skills in Android Studio make updating your existing app to adopt these adaptive patterns easier than ever. Notability’s Android debut sets a new standard for premium productivity apps. Built with Jetpack Compose, Navigation 3, and Kotlin Multiplatform, it delivers an intuitive, adaptive experience across devices.

9: Create seamless experiences for Googlebook

Last week we announced Googlebook, a high-performance laptop that provides a large-screen canvas for your existing apps. Building with adaptive principles today helps ensure your app will work on Googlebook. Get started by reviewing relevant design guidance and developer guidelines for desktop experiences. Try out the new Desktop Emulator available in the Android Studio Canary to to test your apps for this form factor today.

New Desktop Android Emulator

10: Unified widget development experience with Jetpack Glance

Android 17 marks a shift toward a single, Compose-based development model for all widgets. By unifying the experience across mobile, Wear OS, and cars through Jetpack Glance, you can soon scale UI components across the ecosystem with a familiar workflow.

The breakthrough this year is the integration of RemoteCompose. On mobile and cars, it powers high-fidelity animations, while on Wear OS, it allows Wear Widgets (formerly Tiles) to render complex UI logic natively on remote surfaces. This ensures peak performance on low-power hardware while allowing a cohesive user journey—like checking a flight status on your car dashboard and seeing gate change updates on your wrist.

Four widgets are shown cycling through in the Android Auto interface. A clock, a contact card, Google Home favorites and a photo.

11: Expand your reach on the road with Android for Cars
To help you expand your reach when you build in-car experiences, we're making it easier to build once and deliver your apps to Android Auto and Android Automotive OS. With the latest releases of the Car App Library, you can build customized, distraction-optimized templated media apps for both platforms. We're introducing new components and template capabilities to give you increased flexibility and more options for laying out content. Parked experiences are expanding too, with immersive video playback coming to Android Auto for phones running Android 17. You can easily adapt your video apps for these parked experiences; apply now to the early access program to publish in these beta categories and learn more about the latest updates in our blog.

12: Accelerate your development with Android XR Developer Preview 4

Inspired by the innovative experiences you’ve built for the platform, we’re continuing to mature our tools with Developer Preview 4 of the Android XR SDK. A key milestone in this journey is the transition of our core libraries, XR Runtime, Jetpack SceneCore, and ARCore for Jetpack XR, moving to Beta soon to provide a more stable and performant foundation. We are also accelerating hardware access through the Android XR Developer Catalyst Program, where you can apply for XREAL’s Project Aura, audio glasses, or display glasses developer kits. Watch The latest in Android XR session or read our blog to see how these updates help you build experiences across the ecosystem.

Early preview of the Geospatial API in ARCore for Jetpack XR, enabling high-precision anchoring of digital content to real-world locations.

13: Android is your new home for professional-grade media experiences

Android 17 streamlines the entire media lifecycle with a production-ready toolkit. High-fidelity capture is now simplified with the CameraXViewfinder Composable, which handles complex scaling and responsiveness on foldables and tablets. For post-production, the new Media3 AI Effects library provides a single interface for premium features like Magic Eraser and Studio Sound, automatically optimizing for the device's hardware.

The pipeline is completed by CodecDB, offering chipset-specific encoding recommendations to eliminate export noise, and a new Scrubbing Mode in ExoPlayer for ultra-smooth seeking. Whether you’re compositing multi-asset edits with Media3 Transformer or using the streamlined CastPlayer API, these updates ensure a professional-grade experience with significantly less development overhead.

Low Light Boost and Magic Eraser in action

14: Increase app discovery and engagement on Google TV

Pointer remotes, which enable motion-controlled input, will be a future way for users to interact with Google TV as it unlocks faster user navigation. App developers can start declaring support for pointing input to ensure their apps are discoverable on future TVs with pointer remotes. Additionally, the Engage SDK, formerly known as the Video Discovery API, optimizes Resumption, Entitlements, and Recommendations across all Google TV form factors to boost app discovery and engagement. It’s a great time to start onboarding the Engage SDK now, since the legacy Watch Next API, which has been powering your continue watching 1.0 experience, will lose support in the 2nd half of 2027. Get all the details in our blog.

15: Performance: the foundation of a great app experience

To help developers navigate memory limits in Android 17, we've launched a suite of optimization tools. The R8 Configuration Analyzer identifies keep rules that are bloating your binary, while ProfilingManager and the integrated LeakCanary in Android Studio streamline memory leak detection. Furthermore, the new Android Performance Analyzer offers advanced AI integration for complex trace analysis and automated SQL query generation to pinpoint performance bottlenecks.

And The Latest on Driving Business Growth

16: What’s new in Google Play

Today's updates from Google Play help expand your reach and scale your business with less complexity. We’re redefining Play Store discovery with an immersive, short-form video format called Play Shorts, while expanding your audience beyond the store with app discovery in the Gemini app on Android and web. Plus, we’re introducing powerful new capabilities like agentic catalog management for seamless bulk price and SKU updates, and using Gemini models to enable Play Console to pre-populate store listings from imported documents—making global localization effortless.

Gemini will provide users with app suggestions during a search

17: And of course, Android 17

Android 17 includes new performance & system architecture improvements (in addition to app memory limits) like a lock-free MessageQueue and a GC with more frequent, less intensive young-generation collections to ensure system-wide stability and smoother UIs. The new contact picker and eyedropper API help minimize the use of sensitive permissions and unnecessary access to user data.

Review the behavior changes to make sure your app is ready for Android 17, including background audio hardening and SMS OTP protection. Get ready to target Android 17 (API 37) with changes such as mandatory large-screen resizability, certificate transparency by default, and restricted local network access. You can start testing today by enrolling your device in the Beta or using the latest 17.0 emulator images.

One more thing. the third beta of our Android 17 quarterly platform release (QPR1) just came out, and it contains a minor SDK release to support a few features that just couldn't wait for QPR2.

Check out all of the Android & Play Content at Google I/O

This was just a preview of some of the updates for Android developers at Google I/O. Tune into What’s New in Android for the latest news and announcements and follow Google I/O for much more over the following week!

Datadog delivers millions of in-depth performance insights with ProfilingManager

Sat, 25 Jul 2026 10:15:39 +0200

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. 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.

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 why behind a performance bottleneck.

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.

The impact of ProfilingManager

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.

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.

Solving the Android code-level visibility challenge

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.

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.

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.

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:

Granular session diagnostics: 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 Perfetto UI.
Automated telemetry triggers: 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 APP_FULLY_DRAWN signal, there are already plans to expand this observability to include ANR, OOM, and COLD_START triggers.
Proactive trace snapshots: 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.
Bottleneck detection at scale: 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.
System-enforced resource stability: The API leverages sampling trace collection to ensure performance and user experience impacts remain unnoticeable.
On-device data controls: 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.

Processing millions of weekly profiles to optimize real-world apps

An example of Datadog's time to initial display measurement with
stack sampling powered by ProfilingManager

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. Beyond profile collection, Datadog also emphasizes the importance of balancing sampling frequency with collecting enough data to generate meaningful insights about your application. Datadog relies on ProfilingManager’s built-in rate limiting as a critical stability safeguard, preventing excessive telemetry requests from overburdening user devices.

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.

Conclusion

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 documentation.

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.

To get started using the Datadog real user monitoring feature powered by ProfilingManager, visit Datadog Mobile Real User Monitoring.

Build intelligent Android apps: Cloud and hybrid inference

Sat, 25 Jul 2026 10:15:23 +0200

Posted by Thomas Ezan, Jolanda Verhoef, Caren Chang, Senior Developer Relations Engineers, Android Developer Relations

Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post we explored how to build intelligent on-device features using Gemini Nano through ML Kit's Prompt API.

In this post, we will look at how you can leverage Firebase AI Logic to build cloud-hosted and hybrid AI features:

Grounding answers in real-world context
Routing requests dynamically between cloud and local execution using hybrid inference
Translating content with custom routing systems

Sometimes a use case requires AI models with greater world knowledge, a much larger context window, or the ability to handle complex queries. In those scenarios, we can leverage cloud models.

Other times, you want the best of both worlds: using hybrid inference to run on-device when available to lower costs, while falling back to the cloud to ensure compatibility for all devices.

Cloud and hybrid features in Jetpacker: Museum assistant with web grounding, hybrid restaurant review drafting, and support chat featuring custom-routed live translation.

Let’s look at how we implemented three cloud and hybrid features in Jetpacker:

a museum assistant with web grounding
hybrid restaurant review drafting
hotel support chat featuring custom-routed live translation.

Use LLM grounding for up-to-date informationMuseum assistant chatbot with LLM grounding

The Museum assistant is an interactive chatbot designed to help users plan their museum visits. It provides visitors with up-to-date details regarding specific exhibits, current opening hours, ticket pricing, and more.

Museum assistant is a chatbot that answers questions, such as

‘How can I get a ticket discount for Le Louvre?’

When building AI features, getting the model to answer with fresh, accurate, and specific real-world information is a common challenge. While cloud models possess massive amounts of world knowledge, they might not know about seasonal exhibits or the current day’s opening hours.

Grounding data is added to the context window to enable the model

to answer questions correctly and accurately.

To bridge this gap, we can use grounding techniques to add extra context to the model’s context window. The Firebase AI Logic SDK supports three types of grounding:

URL grounding: Grounding responses using content from a specific webpage (e.g. current ticket prices or museum rules).
Google Search grounding: Letting the model query the real-time Google search index for up-to-date details.
Maps grounding: Using Google Maps location data.

In Jetpacker, we dynamically construct the available tools based on enabled feature flags and initialize the generative model using the Firebase AI SDK:

// implementation("com.google.firebase:firebase-ai-logic")

private var toolList = mutableListOf()

init {
    if (ENABLE_SEARCH_GROUNDING) {
        toolList.add(Tool.googleSearch())
    }
    if (ENABLE_URL_GROUNDING) {
        toolList.add(Tool.urlContext())
    }
}

private val generativeModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        modelName = "gemini-3-flash",
        systemInstruction = content {
            text("You are a helpful museum assistant answering questions about a museum. Use plain text.")
        },
        tools = toolList
    )

When the user queries the assistant, if URL grounding is enabled, we append the specific museum resource URLs directly into the prompt:

val groundingText = if (FeatureFlags.ENABLE_URL_GROUNDING) {
    "\n If the following message above is about the rules and terms to visit Le Louvre, " +
    "if needed answer this urls ${urlList.joinToString()}"
} else {
    ""
}

val prompt = "$text $groundingText"

var response = chat.sendMessage(prompt)

Hybrid inference: On-device review generation with Maps deep link

Not every AI task requires a cloud-based model, and not every device is online. To help developers balance latency, cost, and offline availability, we recently introduced the Firebase API for Hybrid Inference.

In Jetpacker, the restaurant review feature lets users review select topics and automatically drafts a review. To enable this for all users, we prioritize local execution with Gemini Nano, and fall back to cloud models on devices that don’t support Gemini Nano.

The restaurant review feature uses hybrid inference to draft a review based on topics

// implementation("com.google.firebase:firebase-ai-logic")
// implementation("com.google.firebase:firebase-ai-ondevice:16.0.0-beta03")


// Initialize the model with hybrid routing configuration
val reviewModel = Firebase.ai.generativeModel(
    modelName = "gemini-3.1-flash-lite",
    onDeviceConfig = OnDeviceConfig(
        inferenceMode = InferenceMode.PREFER_ON_DEVICE
    )
)

The Hybrid Inference API supports four distinct routing modes:

PREFER_ON_DEVICE: Prioritizes local execution and falls back to cloud if Gemini Nano is unavailable.
PREFER_IN_CLOUD: Prioritizes cloud execution and falls back to on-device if the device goes offline.
ONLY_ON_DEVICE: Restricts execution strictly to the device.
ONLY_IN_CLOUD: Restricts execution strictly to the cloud.

Once the review is generated, we copy it to the clipboard and use an intent to open Google Maps directly to the restaurant's review page, providing a seamless user experience:

private fun copyAndOpenMapsReview(context: Context, reviewText: String, placeId: String) {
    val clipboard = context.getSystemService(Context.CLIPBOARD_SERVICE) as ClipboardManager
    val clip = ClipData.newPlainText("User Review", reviewText)
    clipboard.setPrimaryClip(clip)

    val uri = Uri.parse("https://search.google.com/local/writereview/mobile?placeid=$placeId")
    val intent = Intent(Intent.ACTION_VIEW, uri).apply {
        setPackage("com.google.android.apps.maps")
    }
    context.startActivity(intent)
}

Custom hybrid routing: Hotel support chat translation with simulated personas

The hotel support chat was built to let users finalize logistics and check on hotel details. This feature uses system instructions to configure a localized receptionist assistant. By passing specific information—such as the preferred language and hotel information—in the instructions, we can set up a conversational persona representing a specific hotel.

private val generativeModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        systemInstruction = content {
            text("""
              You are a helpful hotel receptionist at $hotelName only speaking $language. 
              Answer politely in $language. The bar closes at 10pm and breakfast is from 7am to 10am.
              There's someone at the desk 24/7. You can retrieve your luggage from the storage room 
              at the back of the lobby at any time.
              """)
        },
        modelName = "gemini-3-flash-preview"
    )

Because receptionist responses are in the hotel's local language (for example, French for Hotel Le Meurice in Paris), we need to translate messages to the user’s preferred language.

Hotel support chat messages are automatically translated to the user’s preferred language

While hybrid models can configure simple routing preferences, complex scenarios require custom routing logic. In Jetpacker, we implement a custom routing stack that takes into account:

Language identification: Using the on-device ML Kit Language Identification API, we can detect the incoming message language.
On-device translation (Gemini Nano): ML Kit’s Prompt API lets us translate common language pairs directly on the device, saving bandwidth and cloud cost.
Cloud translation (Gemini 3 Flash): For more complex languages, we use Gemini Flash 3 to get a higher quality translation.

// implementation("com.google.android.gms:play-services-mlkit-language-id:17.0.0") 

// ML Kit for Language Identification (powered by Google Play Services)
private val languageIdentifier = LanguageIdentification.getClient()

// On-device translator model (prefer Gemini Nano) for translating common language pairs
private val hybridTranslationModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        modelName = "gemini-3-flash",
        onDeviceConfig = OnDeviceConfig(mode = InferenceMode.PREFER_ON_DEVICE)
    )

// Cloud translator model for more complex language pairs
private val cloudTranslationModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        modelName = "gemini-3-flash"
    )

When a message needs to be translated, we identify the source language and apply our custom routing logic, executing either on-device or cloud translation:

fun translateMessage(message: SupportChatMessage) {
    viewModelScope.launch {
        // 1. Detect language using ML Kit Language Identification
        val sourceLang = try {
            Tasks.await(languageIdentifier.identifyLanguage(message.text))
        } catch (e: Exception) {
            "Undefined"
        }

        // 2. Custom routing: we've verified the translation quality for English and Korean with Gemini Nano, and will translate message on-device for those two languages
        val routeToCloud = sourceLang != "en" && sourceLang != "kr"

        val prompt = "Translate the following text to $selectedLanguage. Just return the translated sentence: ${message.text}."

        val (translatedText, routePrefix) = if (routeToCloud) {
            val result = cloudTranslationModel.generateContent(prompt)
            result.text to "[Cloud]"
        } else {
            val result = hybridTranslationModel.generateContent(prompt)
            result.text to "[On-Device]"
        }

        if (translatedText != null) {
            _translations.update { current ->
                current + (message.id to "$routePrefix: $translatedText")
            }
        }
    }
}

In this example, the custom routing logic only takes into consideration the translation’s source and target language. However, based on your app’s use case, you can expand the routing logic to include other factors such as the on-device model version, network connectivity, battery status, and more.

Securing the AI Pipelines: Firebase App Check

Lastly, using AI in the cloud opens up possibilities of API key abuse or unauthorized billing. To secure API calls, we integrated Firebase App Check using both Play Integrity (production) and the local Debug Provider (for local development or emulators).

In the JetPackerApplication.kt file, we install the debug provider at startup and trigger anonymous authentication to establish a secure user session:

//  implementation("com.google.firebase:firebase-appcheck-playintegrity") 
//  implementation("com.google.firebase:firebase-appcheck-debug")  
//  implementation("com.google.firebase:firebase-auth") 

override fun onCreate() {
    super.onCreate()
    Firebase.initialize(context = this)
    Firebase.appCheck.installAppCheckProviderFactory(
        DebugAppCheckProviderFactory.getInstance()
    )
    Firebase.auth.signInAnonymously()
}

When building locally on an emulator, App Check prints a local token secret to logcat:

Enter this debug secret into the allow list in the Firebase Console: a8c2dd4c-xxxx-xxxx-xxxx-ef6c114ba27e

Once registered in the Firebase console, local requests are fully verified and authenticated by App Check, protecting our backend while letting us test the app locally.

Conclusion

By combining cloud model capabilities (grounding, system instructions) with on-device capabilities (hybrid routing, translation, security app checks), we created a travel app that is smart, secure, and available offline.

Check out the full source code for Jetpacker on GitHub, and explore the Firebase documentation to get started:

Firebase AI Logic Documentation
Firebase Hybrid Inference API

Learn more

Check out the other parts of this blog post series:

Part 1: Introduction of the app and a high-level overview.
Part 2: On-device intelligence. Deep-dive into ML Kit’s GenAI APIs and Gemini Nano to build privacy-first features like itinerary summarization, receipt parsing, and local audio processing.
Part 3 (this post!): Hybrid and cloud reasoning. Explore how to use Firebase AI Logic to ground LLM answers in real-world data like Google Maps and web context.
Part 4: System integration. Integrating with the Android intelligence system using AppFunctions.
Part 5 (coming soon): In-app agentic workflows. Extend the app with an end-to-end booking assistant powered by A2UI and ADK.

Interested in more on Android Development? Follow Android Developers on YouTube or LinkedIn!

All code snippets in this blog post follow the following copyright notice:

Copyright 2026 Google LLC.
SPDX-License-Identifier: Apache-2.0

Community Office Hours: Exchange Email Support

Sat, 25 Jul 2026 10:05:14 +0200

Author: Mozilla Thunderbird - Bewertung: 15x - Views:697

Welcome to the last Community Office Hours of 2025! In this edition, Heather and Monica welcome Sr. Software Engineer Brendan Abolivier and Software Engineer Eleanor Dichary from the Desktop Team. We’re discussing the recent Exchange Web Support for email that just landed in Thunderbird Monthly Release 145. Learn how the team landed this feature and discover future plans for Calendar and Contact support, as well as Graph API

Chapters:
00:00 Intro
03:50 What is Microsoft Exchange
05:07 Why it took so long to add Exchange
14:33 Exchange in Thunderbird 145
18:20 Config options and authorization
27:10 Attachments and storage
32:30 Sync and folder operations
36:10 Filters and notification
39:10 Search
40:20 Feedback and bug reporting
43:00 Mobile and Graph API
49:09 JMAP and future protocols
55:50 Calendar and address book
59:57 Roadmap and EWS deprecation
62:23 Closing

Resources:
Exchange Mozilla Support Article: https://support.mozilla.org/en-US/kb/thunderbird-and-exchange
Exchange Mozilla Wiki Post (with call for testing): https://wiki.mozilla.org/Thunderbird%3AExchange
Reach out on Matrix: https://matrix.to/#/#thunderbird:mozilla.org
Bugzilla (use Exchange component for reporting): https://bugzilla.mozilla.org/enter_bug.cgi?product=MailNews%20Core

Defending Against China-Nexus Covert Networks of Compromised Devices

Sat, 25 Jul 2026 09:10:14 +0200

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 defend against it

Summary

With support from the UK Cyber League, this advisory has been jointly released by the National Cyber Security Centre (NCSC-UK) and international partners:

Australian Signals Directorate’s (ASD’s) Australian Cyber Security Centre (ACSC)
Communications Security Establishment Canada’s (CSE’s) Canadian Centre for Cyber Security (Cyber Centre)
Germany Federal Office for the Protection of the Constitution - Bundesamt für Verfassungsschutz (BfV)
Germany Federal Intelligence Service – Bundesnachrichtendienst (BND)
Germany Federal Office for Information Security - Bundesamt für Sicherheit in der Informationstechnik (BSI)
Japan National Cybersecurity Office (NCO) - 国家サイバー統括室
Netherlands General Intelligence and Security Service - Algemene Inlichtingen- en Veiligheidsdienst (AIVD)
Netherlands Defence Intelligence and Security Service - Militaire Inlichtingen- en Veiligheidsdienst (MIVD)
New Zealand National Cyber Security Centre (NCSC-NZ)
Spain National Cryptologic Centre – Centro Criptológico Nacional (CCN)
Sweden National Cyber Security Centre - Nationellt cybersäkerhetscenter (NCSC-SE)
United States Cybersecurity and Infrastructure Security Agency (CISA)
United States Department of Defense Cyber Crime Center (DC3)
United States Federal Bureau of Investigation (FBI)
United States National Security Agency (NSA)

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.

Introduction

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.

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.

Anyone who is a target of China-nexus cyber actors may be impacted by the use of covert networks. They have been used by Chinese state-sponsored actors Volt Typhoon to pre-position offensive cyber capabilities on critical national infrastructure. The group Flax Typhoon used a different covert network of compromised infrastructure to conduct cyber espionage.

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.

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.

Covert Networks

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.

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 assessed by the FBI to be responsible for the computer intrusion activities attributed to China-based hackers known as Flax Typhoon.

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

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 was mainly made up of vulnerable Cisco and NetGear routers. 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.

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 public blog in May 2024 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.

Typical Network Topology

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.

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.

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.

A diagram illustrating the basic setup of a covert network.

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.

Protective Advice

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.

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.

Further guidance for all organizations facing cyber security threats is available on the NCSC website.

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.

All organizations

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:

Map and understand network edge devices, developing a clear understanding of organizational assets and what should be connecting to them.
Baseline normal connections, especially to corporate virtual private networks (VPNs) or other similar services.
- Would you expect connections from consumer broadband ranges?
Leverage available dynamic threat feeds which include covert network infrastructure.
Implement multifactor authentication for remote connections.

Smaller organizations should consider creating and actioning a free NCSC Cyber Action Toolkit.

Larger or more at-risk organizations

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:

Apply IP address allow lists rather than deny lists for connections to corporate VPNs for remote workers.
Use geographic allow lists or profile incoming connections based on operating system, time zones, and/or organization specific system configuration settings.
Implement zero trust policies for connections.
Enforce machine certificates for Secure Sockets Layer (SSL) connections.
Reduce the internet-facing presence of the IT estate.
Investigate machine learning techniques to profile normal network edge activity to detect and block anomalies.

The NCSC's Cyber Essentials can help protect organizations of all sizes.

Largest or most at-risk organizations

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.

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.
Track and map covert networks reported by industry or government by looking at banners and certificates.
Use threat reporting and threat feeds to create and implement dynamic blocklists and create alert rules to detect incoming threats.
Consider using NetFlow feeds to look upstream and map covert networks to find new nodes.

The NCSC Cyber Assessment Framework 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. 

MITRE ATT&CK®

This advisory has been compiled with respect to the MITRE ATT&CK® framework, a globally accessible knowledge base of adversary tactics and techniques based on real-world observations.

Tactic	ID	Technique	Procedure
Resource Development	T1584.005	Compromise Infrastructure: Botnet	Botnets are used as core components of covert networks
Resource Development	T1584.008	Compromise Infrastructure: Network Devices	Devices are compromised and added to botnets
Resource Development	T1583.003	Acquire Infrastructure: Virtual Private Server	Virtual private servers (VPS) are used in covert networks, typically as on-ramps
Command and Control	T1090.003	Proxy: Multi-hop Proxy	Used by China-nexus cyber actors to route traffic

Appendix: Cyber Security Best Practices

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.

Protect your devices and networks by keeping them up to date: use the latest supported versions, apply security updates promptly, use antivirus and scan regularly to guard against known malware threats. See NCSC Guidance: https://www.ncsc.gov.uk/collection/device-security-guidance/policies-and-settings/antivirus-and-other-security-software
Prevent and detect lateral movement in your organization’s networks. See NCSC Guidance: https://www.ncsc.gov.uk/guidance/preventing-lateral-movement
Implement architectural controls for network segregation. See NCSC Guidance: https://www.ncsc.gov.uk/guidance/10-steps-network-security
Set up a security monitoring capability so you are collecting the data that will be needed to analyze network intrusions. See NCSC Guidance: https://www.ncsc.gov.uk/guidance/introduction-logging-security-purposes and https://www.ncsc.gov.uk/information/logging-made-easy
Use modern systems and software. 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: https://www.ncsc.gov.uk/collection/mobile-device-guidance/managing-the-risks-from-obsolete-products
Restrict intruders' ability to move freely around your systems and networks. 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: https://www.ncsc.gov.uk/guidance/preventing-lateral-movement and https://www.ncsc.gov.uk/guidance/assessing-supply-chain-security.
Deploy a host-based intrusion detection system. A variety of products are available, free and paid-for, to suit different needs and budgets.
Further information: Invest in preventing malware-based attacks across various scenarios. See NCSC Guidance: https://www.ncsc.gov.uk/guidance/mitigating-malware-and-ransomware-attacks

Disclaimer

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 NCSC assured services.

This information is exempt under the Freedom of Information Act 2000 (FOIA) and may be exempt under other UK information legislation.

Refer any FOIA queries to ncscinfoleg@ncsc.gov.uk.

The Rust Programming Language Blog: Announcing Rust 1.96.0

Sat, 25 Jul 2026 08:37:36 +0200

The Rust team is happy to announce a new version of Rust, 1.96.0. Rust is a programming language empowering everyone to build reliable and efficient software.

If you have a previous version of Rust installed via rustup, you can get 1.96.0 with:

$ rustup update stable

If you don't have it already, you can get rustup from the appropriate page on our website, and check out the detailed release notes for 1.96.0.

If you'd like to help us out by testing future releases, you might consider updating locally to use the beta channel (rustup default beta) or the nightly channel (rustup default nightly). Please report any bugs you might come across!

What's in 1.96.0 stable

New `Range*` types

Many users expect Range and related core::ops types to be Copy, but this is not the case: they implement Iterator directly, and it is a footgun to implement both Iterator and Copy on the same type so this has been avoided. RFC3550 proposed a set of replacement range types that implement IntoIterator rather than Iterator, meaning they can also be Copy. The standard library portion of that RFC is now stable, introducing:

core::range::Range
core::range::RangeFrom
core::range::RangeInclusive
Associated iterators

A Rust version in the near future will also add core::range::RangeFull and core::range::RangeTo as re-exports from core::ops (these do not implement Iterator and already implement Copy), and core::range::legacy::* as the new home for the current ranges. Range syntax like 0..1 still produces the legacy types for now, but will be updated to core::range types in a future edition.

With these stabilizations, it is now possible to store slice accessors in Copy types without splitting start and end:

use core::range::Range;

#[derive(Clone, Copy)]
pub struct Span(Range<usize>);

impl Span {
    pub fn of(self, s: &str) -> &str {
        &s[self.0]
    }
}

The new RangeInclusive also makes its fields public, unlike the legacy version which avoided exposing the exhausted iterator state. This isn't a concern with the new type since it must be converted to begin iteration.

Library authors should consider making use of impl RangeBounds in public API, which accepts both legacy and new range types. If a concrete type is needed, prefer using new ranges as this will eventually become the default.

Assert matching patterns

The new macros assert_matches! and debug_assert_matches! check that a value matches a given pattern, panicking with a Debug representation of the value otherwise. These are essentially the same as assert!(matches!(..)) and debug_assert!(matches!(..)), but the printed value improves the possibility of diagnosing the failure.

These new macros have not been added to the standard prelude, because they would collide with popular third-party crates that provide macros with the same name. Instead, they should be manually imported from core or std before use.

use core::assert_matches;

/// [Random Number](https://xkcd.com/221/)
fn get_random_number() -> u32 {
    // chosen by a fair dice roll.
    // guaranteed to be random.
    4
}

fn main() {
    assert_matches!(get_random_number(), 1..=6);
}

Changes to WebAssembly targets

WebAssembly targets no longer pass --allow-undefined to the linker which means that undefined symbols when linking are now a linker error instead of being converted to WebAssembly imports from the "env" module. This change prevents modules from linking unless all linking-related symbols are defined to catch bugs earlier and prevent accidental issues with symbol naming or similar.

Undefined linking-related symbols are often indicative of build-time related bugs or misconfiguration. If, however, the old behavior is intended then it can be re-enabled with RUSTFLAGS=-Clink-arg=--allow-undefined or by editing the source code and using #[link(wasm_import_module = "env")] on the block defining the symbol.

This change was previously announced on this blog, and now takes effect in Rust 1.96.

Stabilized APIs

Two Cargo advisories

Rust 1.96 contains fixes for two vulnerabilities for users of third-party registries.

CVE-2026-5223 is a medium severity vulnerability regarding extraction of crate tarballs with symlinks.
CVE-2026-5222 is a low severity vulnerability regarding authentication with normalized URLs.

Users of crates.io are not affected by either vulnerability.

Other changes

Check out everything that changed in Rust, Cargo, and Clippy.

Contributors to 1.96.0

Many people came together to create Rust 1.96.0. We couldn't have done it without all of you. Thanks!

Firefox Nightly: More Kit, More Control – These Weeks in Firefox: Issue 203

Sat, 25 Jul 2026 08:37:32 +0200

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 the browser encounters connection or security errors!

Controls for the Memories feature can now be set during Smart Window onboarding

We’ve disabled the CSS filter implicitly applied to WebExtension pageAction SVG icons across all release channels starting in Firefox 152, completing the deprecation
- NOTE: The blog post published at WebExtensions API changes in Firefox 149-152 provides to extensions developers more details about this deprecation and links to the related MDN docs.

Friends of the Firefox team

Resolved bugs (excluding employees)

Script to find new contributors from bug list

Volunteers that fixed more than one bug

Amin Amir
Pranjali Srivastava
Sam Johnson

New contributors (🌟 = first patch)

Project Updates

Add-ons / Web Extensions

Addon Manager & about:addons

Fixed long-standing regression on the autocomplete and datalist popups for extension inline options pages on about:addons (introduced in Firefox 68 by Bug 1532724, fix shipping in Firefox 152) – Bug 1595158

WebExtensions Framework

Fixed access to web-accessible resources declared with from sandboxed documents (null-principal URLs), restoring extension redirects from the context-menu search flow, starting in Firefox 152 – Bug 2033905

WebExtension APIs

Added exhaustive test coverage for tabs.move() against additional edge cases related to split-view tabs – Bug 2029092

DevTools

Andreas Farre improved the Session History tab in the Application panel (still behind devtools.application.sessionHistory.enabled)
- added support for remote debugging (#2014064, #2016121)
- made sure that calls to History.replaceState are reflected in the UI (#2037359)
Julian Descottes [:jdescottes] fixed the most frequent DevTools crash we were observing in Telemetry, adding a guard against IDBTransaction errors when retrieving breakpoints in the Debugger (#2030260)
Nicolas Chevobbe [:nchevobbe] fixed the image preview tooltip for relative URLs images in constructed stylesheet (#2035503)
Julian Descottes [:jdescottes] reduced the overhead we had because of network requests monitoring by only decoding response content when the user actually want to see the response (#2026228)

WebDriver

Amin Amir cleaned up an incorrect variable assignment in our browsingContext module.
Logan Rosen updated stale references and broken links in our documentation about Marionette.
Sameem improved the Marionette and WebDriver BiDi screenshot commands to enforce maximum allowed dimensions.
Leo McArdle fixed the regression in the “log.entryAdded” event, which lacked an error message in the “text” field for the messages of type “error”.
Henrik Skupin fixed an issue in Marionette where WebDriver:Navigate and WebDriver:Refresh did not handle errors when the underlying navigation failed.
Henrik Skupin improved geckodriver to detect an early Firefox exit during startup on Android, avoiding up to 60 seconds of unnecessary connection attempts.
Henrik Skupin updated the geckodriver CI build job to produce a universal macOS binary supporting both x64 and aarch64.

Lint, Docs and Workflow

Sylvestre ported some linters (e.g. file-whitespace, test-manifest-toml, license, file-perm, rejected-words & more) to Rust to help improve the runtime of the code review bot.
Dale has been working on migration to moz-src for customkeys, dom/quota and odom/geolocation
- https://arewemozsrcyet.com/

New Tab Page

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.
- We’ll be launching a similar experiment in the DE, probably on May 12th, also at 15% population.
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.
Dre landed a new world clock widget, which is currently off by default, but pretty snazzy!

Search and Urlbar

Nova (URL Bar Design Refresh)
- Drew and Daisuke continued their work on Nova styling for the Address bar (input and view).
Search and Suggest
- Drew finalized two bugs for World Cup and sports suggestions, which were landed and uplifted: one to update the localization string for scheduled games and another to show both teams’ icons in suggestions. Drew also landed and uplifted a fix for rich search suggestion icons being forced into a square aspect ratio.
- Standard8 updated Ecosia favicons to the latest branding, including QA testing and publishing.
Settings Redesign (SRD)
- Stephanie landed a test to ensure search suggestion settings are hidden when quicksuggest is disabled, as well as a patch to resolve TypeScript issues in search.mjs, and is adding test coverage to confirm removed search engines are not displayed in the default engines dropdown.
General URL Bar and Component Updates
- Daisuke landed implementation of the context menu on URL bar results, and a fix to show the loading URL in the URL bar when starting up with a homepage.
  - Marco is working on several tasks, including a PDF download / focus stealing issue and allowing arrays to be bound in Sqlite.sys.mjs. Marco also worked on fixes related to Places, such as avoiding replacing the favicons database if it is not corrupt.
- Standard8 finalized the URL bar test manifest split. Standard8 also upgraded us to TypeScript 6.
- Moritz landed a fix for URL bar abandonment telemetry being recorded when clicking an engine in the unified search button popup (Bug 2032973), which was also uplifted. Moritz also simplified search mode switcher item activation in tests, and made it so that the unified search button popup closes when installing an open search engine.

Smart Window

natural language starting with tab close/undo 2035343 with expandable action log 2031508

assistant rendering feedback up/down 2032994 and markdown table 2027029
nova styling blur 2027877 and suggestions 2026823
accessibility screen reader 2028676 and keyboard focus 2037565
optimize conversation starters extra requests 2030005 and caching 2033430

Storybook/Reusable Components/Acorn Design System

Nova token updates occasionally, focused on SRD

UX Fundamentals

Added support for the “SEC_ERROR_CA_CERT_INVALID” certificate error to the Felt Privacy error pages. – 2035942

Settings Redesign

Settings redesign is being tested and will hopefully go out in Firefox 152!

Hacks.Mozilla.Org: PACT: Anonymous Credentials for the Web

Sat, 25 Jul 2026 08:37:27 +0200

This is the technical companion to our update on Distilled, “Keeping the web open and private in the bot era.” Here we take a deeper look at the problem space, the design we’re proposing, and the problems still left to solve.

Bots (and privacy-preserving browsers) not welcome

Browse a news site in a private window. Shop at a major retailer with a VPN. Visit a video streaming platform with anti-fingerprinting defenses tuned up. You’ll see the same responses: registration walls, block pages, and endless CAPTCHAs. The message is clear: if we think you might be a bot, you’re not welcome.

Websites have valid reasons for wanting to block bots. Bots enable volumetric abuse, abuse that wouldn’t otherwise be feasible if they had to be carried out by humans. For example: SEO comment spam, credential stuffing and DDoSing. Consequently many sites employ dedicated anti-abuse tooling which aims to keep the bots out whilst minimizing friction for human visitors.

Unfortunately, that tooling is increasingly failing at both tasks. Browser privacy protections are dismantling the passive signals that anti-abuse systems depended on to identify and distinguish visitors. Meanwhile advances in generative AI have rendered CAPTCHAs ineffective: bots now solve them faster and more reliably than humans.

Many sites are switching to more invasive mechanisms and now ask visitors to disclose identifying information, e.g. an email address, a federated login or disabling their VPN. This means greater friction for users, since providing these details on a first visit takes time. It also compromises their privacy, since these details enable the same kinds of cross-site tracking that browser privacy protections were intended to mitigate.

This leaves users with a dilemma. The more effectively they protect their privacy, the harder it is for websites to distinguish them from bots and the worse the treatment they receive. Website operators are also suffering. The additional friction they inflict upon well-behaved visitors harms their site, but many are willing to pay the costs if it mitigates volumetric abuse.

Browser-based AI agents make this tension more acute. Sites may want to allow agents which are acting on behalf of individual users while blocking agents engaged in volumetric abuse. However, with no effective mechanisms to distinguish the two, websites are opting to block both. That hurts users, who should be free to choose the user agent they use to access the web; it hurts new browsers and agents, which struggle to interoperate; and it hurts sites, which lose legitimate visitors.

The consequence is that the web gets worse for everyone. Users get more friction or less privacy or both. Website operators see more volumetric abuse and the friction they add drives away users who would otherwise want to consume their content or services. New user agents struggle to access the same content as conventional browsers.

The Costs of Convenient Solutions

Some large ecosystem players have put forward solutions that leverage their control of the dominant operating systems and their deep integration with consumer hardware. These rely on device attestation: identifiers and privileged code baked into devices at the hardware level, which let manufacturers prove what software is running on a user’s device. Exposing this functionality to the web means attesting to sites that the user is running approved software with trusted hardware and therefore isn’t a bot. There have been two substantive proposals.

Google’s Web Environment Integrity, abandoned in 2023, was the blunt version. It attested to the user agent itself, as well as the operating system and device in use. Users would have lost control in two ways: once to the attester, which would decide which operating systems and devices could be blessed, and again to the website, which would decide which software to accept. If sites had adopted allow-lists of approved user agents, building a new browser would have become virtually impossible, and sites could have withdrawn access from any user agent they chose.

Apple’s Private Access Tokens, deployed across their ecosystem in 2022, have more subtle issues. Built on the Privacy Pass protocol standardized at the IETF, they get a lot right: a user receives a renewed, limited batch of one-time tokens that can be presented to websites without linking their visits together. This provides privacy for users and has shown rate limits to be an effective tool for sites – both points we’ll return to later in this post.

However, Private Access Tokens rely on device attestation, requiring that the hardware manufacturer be in overall control of the user’s device. Presenting a PAT tells a website you are locked into Apple’s rules for what counts as acceptable software. Due to PAT’s technical design^[1], there’s no way to open the system to other sources of scarcity without compromising the system’s privacy properties, meaning that if more widely deployed, access to the web would become tied to having bought expensive hardware from a small, hard to change set of vendors.

Both approaches are ultimately hostile to users and to the openness of the web. Both are premised on parts of a user’s device that sit within the manufacturer’s control and beyond the user’s own. Were they widely deployed, the web would become just another walled garden with centralized gatekeepers controlling acceptable hardware, operating systems and software. As convenient as these solutions are for the players who already dominate the ecosystem, we think there’s a better path.

A Better Path Forward

Bots’ harms arise from their ability to operate beyond human scale. For sites to prevent volumetric abuse they don’t actually need to know the user’s identity or receive cryptographic proof that they’re running approved software. If sites knew their visitors were restricted to a rate limit set by a site, that would be enough.

Rate limits only make sense if they’re tied to something scarce; something an attacker can’t cheaply replicate to evade the limit. Without anchoring to a scarce resource, like the trusted hardware used in Private Access Tokens, attackers can generate as many fresh identities as they need to bypass the rate limit.

However, hardware is just one option for scarcity. Anything a user already has that an attacker can’t trivially spin up at scale will work: email addresses and phone numbers are naturally scarce. A paid subscription costs an attacker the same as a real user. Even maintaining an account on a free service requires some non-trivial work.

What if we could use these scarce signals across the web? We could build an open ecosystem with many parties offering scarcity signals, each site choosing which to accept. By opening up who can provide a signal, and letting sites choose which to accept, we can avoid transferring control to device manufacturers and the resulting harms.

As a concrete example of who might be well positioned to provide such a signal, we can consider VPN providers acting as a subscription service. Sites routinely block VPN users indiscriminately, whether through a deliberate policy choice or through an indirect consequence of rate limiting visitors per IP address. But a VPN subscription is a perfect source of scarcity. If the VPN provider could vouch for its users so that sites could rate limit each user individually – then users would be able to browse the web with less friction and without giving up their VPN usage.

The catch is that building a system that can enable this on the open web whilst maintaining user’s privacy is genuinely difficult. It requires that we take information from one site — that this user holds some scarce thing — and expose it to other sites so that they can use that as the basis for their rate limiting. Letting one site verify a signal from another is the sort of information flow that privacy-preserving browsers have spent the last decade locking down to prevent cross-site tracking.

Our goal would be that no more than the minimum information gets through: a single bit communicating whether the user is below the rate limit set by the site. Leaking anything more – like the source of the scarcity that the rate limit is anchored to – would be unacceptable. Enabling a new cross-site information flow might feel like compromising privacy to gain better access, but reality is more nuanced. If a new system moves sites away from demanding that visitors be identifiable (whether through fingerprinting or login forms), it can be a win for both privacy and access.

The Foundations

The good news is that the cryptographic foundations for a privacy preserving approach already exist. The Privacy Pass protocol, originally developed in 2018 to reduce the friction of Cloudflare CAPTCHAs for Tor users, introduced the core primitive: a token that is unlinkable between issuance and redemption. You prove something to an issuer (e.g. by solving a CAPTCHA), receive some tokens, and later present a token to a website. The website can verify the token is legitimate, but can’t link it to the user it was issued to.

Figure 1: In Privacy Pass, a CAPTCHA provider can issue tokens to a client which can then be used to bypass challenges for future site visits. Even if the CAPTCHA provider and sites collude, they can’t use the tokens to identify the user or their browsing history.

Privacy Pass has gone on to be successfully deployed in systems where the issuer and verifier have a prior trust relationship: Apple uses it to authenticate users of Private Cloud Compute and Private Relay without linking their activity to their identity, Chrome uses it for two-hop IP protection, and Kagi uses it to provide private search. These deployments work in part because a small number of parties have agreed in advance on who issues tokens and who accepts them.

Applying this approach to an open system where any site can act as an issuer brings real challenges. Firstly, even though tokens are unlinkable, knowing a user has access to a specific issuer is a privacy leak on its own, because you can infer that the user meets the relevant issuance criteria. If one site can learn that you have a token from another site, that reveals that you have been to that site, which can be a major privacy problem. This compounds if sites can learn the set of issuers you have visited, since it becomes a fingerprint which can be used to identify you.

Generic techniques exist for proving a statement in zero knowledge: we can prove that a client has a token from a set of acceptable issuers without revealing which specific issuer it is. We’ll call this issuer blinding. The generic approach is often slow, but bespoke approaches tailored to the underlying cryptography can improve this considerably.

Another challenge is how sites using rate limits decide who to trust to issue tokens. If an issuer misbehaves then the site’s rate limits become ineffective, enabling volumetric abuse. However, if we need to prevent the site from learning which issuers a user has access to, the site is only going to know that one of its trusted issuers was used, not which one. This makes mistakes or misbehaviour by an issuer difficult to detect, and makes it hard for sites to evaluate new issuers. Solving this challenge is essential for openness. Without adequate information, sites are likely to lean towards conservative issuer selection. That could lead to less choice between Anchors, which in turn could lead to a new form of gatekeeper being created.

To solve this, sites at least need a way to calculate an aggregate score for each issuer they use. This should roughly correspond to how much of the traffic it considers abusive to have come from users using that particular issuer. Mozilla has long invested in systems like Prio which use multiparty computation (MPC) to protect user privacy whilst enabling aggregate measurements of system behaviour.

Privacy Pass also struggles to handle dynamic adjustments to rate limits. Once tokens have been issued, they’re difficult to invalidate without either revoking all active tokens or risking attacks which can compromise the privacy of users. It’s also beneficial if sites can adjust rate limits on a per client basis, for example by increasing rate limits where they become more confident the client is benign and withdrawing access when abuse is detected.

Anonymous Credit Tokens offer a useful building block to solve this problem. Conventional Privacy Pass schemes rely on issuing a bucket of tokens but ACT works differently by enabling the use of a credential with state. For example, an ACT credential can hold an internal counter. When the credential is presented, the site can check the counter is over some threshold and mutate it, increasing or decreasing the counter whenever the site’s perception of the holder has improved or worsened. Critically, the exact value is never leaked to the site, preventing the site from tracking the holder and ensuring successive presentations of the same credential can’t be linked.

Putting it together

So how can we combine these techniques to build a system which can enable privacy-preserving rate limiting on the open web? In May 2026, we participated in a W3C CG Meeting in collaboration with Cloudflare, Chrome and other web stakeholders in which we started sketching out a design we’re calling PACT – Private Access Control Tokens.

Rate limits need a starting point, a source of scarcity to anchor on. We’ll call an entity that provides such a source an Anchor. To a user who meets the Anchor’s criteria, like having a subscription, an account in good standing, or a verified phone number, an Anchor issues a batch of Endorsement tokens, following the Privacy Pass model. In practice, Anchors could be any website which has access to this kind of signal. An Endorsement conveys scarcity to other sites.

That’s enough for a simple system where access is either granted or denied. But as we discussed earlier, we also want the ability to increase access where a visitor behaves benignly and decrease it where they don’t. The state needed to enforce a rate limit can’t live in the Endorsement, because Endorsements cross trust boundaries between unrelated sites. We need a second object that can hold that state, scoped to the party that maintains it.

We’ll call that the party that handles rate limiting for a site a Moderator and the stateful object a Credential. A Credential is specific to a Moderator and, unlike endorsements, we limit each site to nominating a single Moderator. In the common case the site itself plays the Moderator role, so there’s no new entity or trust boundary. A Moderator can also be a third-party service shared across many sites, allowing those sites to cooperatively share a rate limit.

In the terminology of the previous section, the Anchor is the issuer of Endorsements, and the Moderator both verifies Endorsements and issues Credentials. A Moderator manages rate-limit policy: it decides which Anchors it trusts, accepts their Endorsements, and issues a Credential in return.

Figure 2: (1) Clients acquire Endorsements from Anchors in the course of normal browsing to sites they have relationships with. (2) Clients can exchange Endorsements for a stateful Credential from a Moderator. (3) Credentials can be used to access sites which use that Moderator. Credentials can be updated over time.

Directly revealing which Anchor backed an Endorsement would leak a lot of information about the user. The issuer blinding techniques from the previous section solve this: when an Endorsement is redeemed, the Moderator only learns that it came from one of the Anchors it trusts, but not which one.

When a Moderator covers more than one site, we let Credentials be presented across all of them but partition cookies and storage as we would for any other third party site. The unlinkability of Credential presentations keeps this from creating a new cross-site identifier. The benefit is that good behaviour on one site improves access on every site the Moderator covers, and bad behaviour cuts it everywhere. Websites can already build the same capability with a shared account system, so this doesn’t create a new way to lock users out, but it does provide a new way to grant access without requiring users to give up their privacy.

Enabling Moderators that cover many sites carries a centralisation risk, similar to the concentration we see today in anti-abuse providers. The mitigation is that the choice of Moderator stays with each site, and the choice of trusted Anchors stays with each Moderator. This can’t reverse the centralisation pressure the web already faces, but it ensures this system won’t lead to additional lock-in: a new Anchor or a new Moderator can be adopted without coordinating with a dominant vendor.

The system then has three flows. First, the user receives Endorsements from an Anchor in the course of normal interaction, based on the Anchor’s positive view of the user. This is a relatively rare operation for any given user and Anchor. After all, as our source of scarcity, Endorsements should not be too easy to accumulate.

Figure 3: In the course of normal browsing, clients browse to websites they have a relationship with. These sites can act as Anchors by issuing Endorsements to clients.

Second, when the user arrives at a site that works with a Moderator, the browser spends an Endorsement from an Anchor the Moderator trusts and receives a Credential in return. The presentation hides which Anchor was used, and neither the Anchor nor the Moderator can trace the Endorsement back to where it was issued. The Moderator decides what initial balance the Credential starts with. If the user has no Endorsements from suitable Anchors at all, existing mechanisms (CAPTCHAs, account creation, federated login) could be used to bootstrap a Credential the same way, so the system degrades to today’s experience rather than locking the user out.

Figure 4: When the client browses to a site, it can prompt the client for a Credential from the Moderator it uses. If the Client doesn’t have a suitable Credential, but does have a suitable Endorsement, it can exchange it for a Credential with the Moderator. In practice, the Moderator and the Site might be the same server.

Third, as the user browses, the browser presents the Credential and the Moderator updates the internal state of the Credential. The Moderator can reward behaviour that looks benign and penalize suspicious activity, but can’t track the use of the Credential or identify it if it’s used on other sites the Moderator covers. Revocation falls out of the same mechanism: a Moderator can refuse to return an updated Credential.

Figure 5: The Client can present the Credential on sites which use the matching Moderator. Sites can check if the Credential is in good standing. The sites can then adjust the access the Credential has in response to behaviour. E.g. increasing it when they gain confidence in the client or reducing it in response to malicious behaviour.

In practice, all of this would happen transparently to the user through a WebAPI that sites acting as Anchors or Moderators would call from JavaScript. In an ideal ecosystem, users would accumulate Endorsements through normal browsing, just by virtue of the sites they already visit, and the rest of the flow would happen in the background as they move around the web, leaving users with meaningfully less friction.

AI agents acting on behalf of a user slot into the same flow. An agent can carry its user’s Credentials, in which case the user remains accountable for how the agent behaves. Sites would not need to grant any more access than they would to the user themselves. Alternatively, the operator of an agent can run its own Anchor and vouch for its agents the way other Anchors vouch for human users. Sites retain control over which Anchors they accept, so they can choose how to treat agent traffic without needing a separate detection mechanism.

Several mechanisms combine to keep the information about a user that flows out close to a single bit. Cryptographic unlinkability ensures successive Credential presentations cannot be tied to each other or to the original issuance, so a user’s visits cannot be joined into a history. Each site is bound to a single Moderator, so the set of Moderators a user has Credentials with never becomes a cross-site fingerprint. The Anchor-to-Credential exchange happens in an isolated browsing context, so during ordinary browsing the only thing the site or its Moderator ever observes is a Credential presentation: the site only learns if the user has a valid Credential below the rate limit, or nothing. When the Moderator updates a Credential, it adjusts the credentials state without learning what it is.

The additional privacy given to users from Issuer blinding makes participating in the system more challenging for Moderators. Because the Moderator can’t see which Anchor backed a Credential at issuance, it can’t give a Credential from a strong Anchor more access than one from a weak Anchor: doing so would itself leak which Anchor was used. The initial access has to be uniform across the Moderator’s whole pool of Anchors, which in practice means setting it at the strength of the weakest. However, this is only relevant for that initial access, the Moderator can update credentials according to the holder’s behavior, enabling Credential’s to accrue access over time.

Building an open ecosystem also requires that sites can make effective decisions about the Anchors they choose to trust. Multiparty computation systems like Prio enable aggregate scoring without compromising privacy. When users present Credentials, they can provide an encrypted share which identifies the anchor they used and can be privately aggregated to compute the quality of an issuer.

Next Steps

We think the architecture we’ve sketched for PACT has the right shape, but many of the details still need to be worked out and the entire system needs rigorous privacy and security analysis.

We want to do that work in the open. The IETF is the natural venue for the cryptographic protocols underneath, and the W3C for the WebAPI surface that sits on top. We’ll be bringing draft specifications to these bodies as soon as they’re ready, and we welcome collaborators from across the ecosystem: browser vendors, site operators, anti-abuse providers, and the cryptography community.

If successful, we think we can provide a system which will keep the web open and private, while still giving sites the rate-limiting signal they need.

Acknowledgements

The ideas described here are the result of collaboration and conversations with many people, including: Watson Ladd, Thibault Meunier, Michele Orrù, Trevor Perrin, Eric Rescorla, Samuel Schlesinger, Martin Thomson, Eric Trouton, Benjamin Vandersloot & Cathie Yun.

[1] PAT requires that the source of scarcity and an independent issuer be trusted not to collude. If they do, they can track users as they interact with the system. This is not suitable in the context of an open system where any party could play those two roles.

The post PACT: Anonymous Credentials for the Web appeared first on Mozilla Hacks - the Web developer blog.

The Rust Programming Language Blog: The many journeys of learning Rust

Sat, 25 Jul 2026 08:37:24 +0200

This is another post in our series covering what we learned through the Vision Doc process. We previously described the overall approach and what we learned about doing user research, we explored what people love about Rust, dug into what it takes to ship safety-crticial Rust, and described some of the major challenges that people face when using Rust.

In this post we walk through what folks have found on their journey to learn the Rust programming language with ups and downs covered.

As a disclaimer, LLMs (Large Language Models) come up in this post because our interviewees brought them up. We're scoping discussion to their use as a learning tool, covering research and example generation, not broader questions about AI (Artificial Intelligence) in software development.

Many paths to needing Rust

The interviews surfaced several different paths into Rust: curiosity, embedded work, job-market pressure, organizational adoption, and reassignment after a team or company chose Rust. That last path matters because many learners are not evaluating Rust from a blank slate; they are trying to become productive after Rust has already arrived in their work.

"Funny enough, I've advocated for more niche languages than Rust in the past. Rust has pretty much stopped being as much of a niche language as it was, but it's not Java." -- Fractional CTO

Rust learning resources

Likely as expected, the folks that we talked to reach for a range of resources to learn Rust. Some reach for official documentation, such as The Rust Programming Language Book and find that sufficient to build on what the compiler was already showing them.

"I started with the official Rust documentation because there are a lot of great examples of how features like the borrow checker work." -- Software engineer at an Automotive supplier

Others needed more passes and more formats, sometimes reaching for resources the community maintains, such as Rustlings, The Little Book of Rust Macros, and Learn Rust With Entirely Too Many Linked Lists.

"The first time I went through the chapter in [The Rust Programming Language] on borrow checking, I was like, what is this? I read it again, then I watched a YouTube video of someone explaining the chapter." -- Rust freelance consultant

"Rust book, Rustlings, Zero to Production in Rust, Jon Gjengset tutorials. A bunch of books. It's not a one-pass reading. Can't say how many times I've gone through it." -- Software engineer working on video streaming and storage

These resources have brought up an entire generation of Rust programmers. But, to some, there is a perception that these resources have trouble keeping pace with the language.

"We'd like to use [The Rust Programming Language/'the book'], but we've found that it's out of date, unfortunately. We've looked at the GitHub repo and found it's got a lot of unresolved issues and unmerged PRs" -- Principal Software Engineering work on Rust adoption in a regulated industry

Whether or not this is factually true, Rust's growth has nonetheless put more scrutiny on these materials. Companies evaluating adoption and engineers getting reassigned to Rust teams are looking at them with fresh eyes and finding the gaps that affect their own evaluation.

Beginner stumblings and unlearning habits

It's pretty typical for Rust to be the 2nd, 3rd or Nth programming language that someone picks up. They'd end up writing their most familiar language in Rust, whether C++ patterns, Java patterns, or whatever they knew, for months or even years. Eventually they got comfortable enough to start writing idiomatic Rust.

"There's a bit of a drop in productivity compared to C if you're already familiar with it just because you're learning new rules, new syntax." -- Principal Firmware Engineer (mobile robotics)

"In the beginning it was more poking around the code and adding and removing some ampersands and asterisks to try to make sense of mut and not mut and whatever." -- Senior engineer with 20 years of Java experience in cloud and IoT

We also spoke with someone who found that not having much of a programming background seemed to benefit people picking up Rust. Not having worn-in grooves from other languages may play a role here, and it's worth investigating further.

"I had someone who had never programmed much before start working on the internals of [our Rust project]. She was just fine with getting into Rust. It's more of the senior people that struggle as they need to unlearn practices which may work in other languages, but it's not the 'Rust' way." -- Researcher, Automotive OEM R&D Lab

Learning to work with the borrow checker

We heard a lot about learning to work with the borrow checker instead of against it. People get there through different paths, but a few patterns came up repeatedly.

The compiler as teacher

Rust's diagnostics did the teaching on their own, especially around lifetimes.

"If you mess up the lifetimes in a piece of code that you've written by hand, I usually find that Rust's diagnostics are very helpful" -- Researcher working on static analysis of Rust programs

"Whatever's missing, the compiler usually fills in: it tells me 'you need to declare the lifetime of this reference', so I know and can figure it out. That all generally works pretty well." -- Senior Software Engineer

Learning by doing

Others felt like they only really internalized the borrow checker after writing a lot of Rust. It took projects, coding challenges, prototyping and so on until at some point it clicked.

"I actually did not understand the borrow checker until I spent a lot of time writing Rust" -- Founder of a startup built on Rust

"Besides the prototyping work, I also did coding-challenge-type stuff to get familiar with Rust for Advent of Code. [..] It eventually clicked to the point where I wasn't fighting with Rust, it was working for me. I had that experience other people describe: when I managed to get my program to fit with Rust, it worked. I didn't spend time debugging." -- Principal Software Engineer, large SaaS provider

Letting go of "clone guilt"

Some learners arrive with the assumption that good Rust means zero clones, zero copies, lifetimes threaded through everything. They set the bar at optimal before they've learned how to write idiomatic Rust, and it makes the borrow checker feel harder than it needs to be at the outset.

"On one of my first projects, I was like, 'I don't ever want to copy or clone anything,' so I carefully wove through all the lifetimes and got myself into a bit of a bind. Then I saw someone else just cloning the struct I was working with, and it was super cheap. Sometimes you can just clone and it's going to be okay." -- Researcher at a university

The experienced Rust developers we spoke with consistently said the same thing: clone freely while you're learning, then optimize when you understand the problem. Rust's reputation for performance and correctness feeds this. Newcomers assume anything less than optimal is wrong before they've written a first working program, and clone guilt is how that shows up.

We think it could be an interesting area of future study to check into the patterns Rust programmers employ at different levels of experience and under which circumstances. One member of the Rust Vision doc team that's very experienced with Rust noted that there's kind of an "expected shape" they understand as passing the compiler. This knowledge influences how they approach writing code which wouldn't take that shape and they naturally find themselves understanding when to use so-called workarounds, such as passing around indices into arrays or Vecs.

Multi-paradigm, but not the OOP some are used to

The Rust programming language is multi-paradigm, and how that lands depends on what you're coming from. We heard some that came from a functional background were delighted with digging into learning how much Rust inherits from that lineage. Some others noted that they and others on their teams struggled to unlearn the object-oriented style they'd come to use heavily in other languages like C++ and Java.

"Developers coming from C++ tend to think object-oriented. I think that's a difference between C++ and Rust." -- Architect at Automotive OEM

"I had exactly that thing, where I would apply all my years of Java and JS thinking, where I could just create some object, not care about it, return it, have it sloshing around between various functions. Found myself reaching for these patterns and then being told 'no, you cannot do that'." -- Principal Engineer at a SaaS company

Developers coming from functional programming had less to unlearn: strong typing, pattern matching, and an expression-oriented style were already familiar.

"My background has been more functional programming, strong typing. That originated for me as a Lisper: once a Lisper, always a Lisper." -- Principal Software Engineer working on Rust tooling for safety-regulated industries

"The languages I primarily used before Rust were things like OCaml. Way back, I came from C and C++, the classic languages, and then I spent quite a long time doing primarily pure functional stuff. These days I've ended up back in what I like to think of as a pragmatic center ground [with Rust]." -- Fractional CTO

Teaching Rust in academia

We spoke with a university professor that's been teaching Rust generally. In the academic environment, they were able to use proxies for some things such as "traits are like interfaces in Java" because the students had already gone through a set of courses in their first and second years that taught them Java. They introduced concepts slowly throughout the course, choosing to deal with some more complex topics like generics later. The outcome generally was that students had no problem picking up Rust in this setting.

"I couldn't see any big difference on the embedded side. We also teach an embedded class, and we did an experiment. Half of the students' feedback was worse on the Rust class, mostly because they needed to build the project themselves. The C students just got one from [an LLM], absolutely no problem." -- University Professor, on teaching Rust

The C cohort leaned on LLMs for the project in ways the Rust cohort couldn't. We don't yet have a clear answer for why.

What did come through clearly was the Rust cohort's experience with the community. Some students needed to figure out which drivers to use for the embedded project and how to use them. Their professor encouraged them to open issues and ask questions directly on GitHub, and the maintainers responded. Students who had never contributed to open source before were getting answers from the people who wrote the code.

Learning using LLMs

Some experienced folks shared that they saw LLMs as a tool that can help someone come up to speed quickly, either as a research tool or for generating example Rust code to understand concepts.

"I'm optimistic that there's a way to work [LLMs] in that will cut down that learning curve. One of the big things these tools bring is reducing the learning curve in general; these are very good tools to help you navigate a space that you don't know yet." -- Maintainer of large open source Rust crate

"I try [LLMs] out once a month, usually for generating an example or something like this. Just like with Stack Overflow: when you read an example, you should read it carefully and try to understand it. Not copy and paste it, but type it in your own words in code and then check it, because that's where the teeny tiny little mistakes are." -- Founder of startup built on Rust

For some learners, an LLM is just another way to find answers, no different than a search engine.

"So for the most part, picking up Rust - how do I learn? I'll [use web search for] things, I'll ask [an LLM], I'll just poke around and read the code." -- Senior Software Engineer working in a regulated space

One founder went further and claimed that LLMs change who can become a Rust developer. One consulting company founder described hiring high school graduates with no systems programming background and training them as Rust developers, with LLMs filling in the learning gaps that would previously have required years of experience.

"At the beginning, I was worried, but now that we have [LLMs] supporting development, the difficulty of the language doesn't matter. I'm seeing a huge opportunity behind strong runtime languages like Rust. [..] In [Developing Country] we hire 20-25 high school graduates, train them to be Rust programmers, then they enhance our workforce worldwide." -- Founder of a consulting company

We heard this from one organization. This is a claim that the combination of Rust's compiler and LLM tooling can dramatically shorten the path from beginner to working developer. Whether it generalizes depends on questions we can't answer from a single interview: how long these developers stay, what kind of code they can maintain independently, and whether this training/learning model works outside this company's particular structure. If it holds up, the pool of people who can become Rust developers is much larger than the usual hiring profile suggests.

Organizational considerations for Rust learners

We spoke with a number of folks on teams that are using Rust in larger organizations. Teams wanted to know that everyone would end up at roughly the same level of competence, which led a good number to invest in training courses to get there. Some leaders found that staff was able to ramp well enough by reading The Rust Programming Language, going through Rustlings, and then picking up lower risk and priority tickets to work on. Having a sense of community was also important within companies; it helps people know they are not alone when they are asked to work on Rust after, say, a reorganization happens.

"[..] the idea with the class as opposed to 'just read the Rust book on your own' was that this gives everyone kind of the same baseline going in." -- Principal Firmware Engineer (mobile robotics)

"So typically we're going to have people work through Rustlings, work through The Rust Programming Language. We have them then start to pick up lower risk tickets to work on." -- Principal Engineer at a large SaaS provider

"We've got an internal Slack channel for Rust learning where people can drop questions and others will come in and answer them. That helps build up understanding and community." -- Software Engineer at a large corporation

Some organizations found that while the person they'd hire would need to learn Rust, it was still preferable to the alternative of hiring someone for a critical piece of software written in another language.

"They needed to grow and maintain this C++ codebase. They had a C++ wizard, and they tried for about two years to find someone with the same level of expertise. They ended up hiring people that didn't know Rust and ramping them up, creating FFI bindings from the C++ side so they could work in Rust. And you can feel it: the borrow checker is teaching these people the right way to handle their systems." -- Principal Engineer at an Automotive OEM

The community and helping each other aspect seems to grow bonds as organizations mature.

"Our team is [all about] mentorship. I've mentored people coming up to speed on Rust, and people help each other hugely." -- Principal Software Engineer at a large SaaS company

Silent attrition

We identified some cases where people have approached Rust and bounced off of it, for one reason or another. In the below case, someone with a background in a language with fewer guardrails found themselves frustrated enough with Rust to walk away.

"All of that means that that embedded ecosystem is very frustrating to somebody who comes from C and is like, why can't I just get a pointer to this peripheral and then write into the registers. What are you doing to me? [..] My friend never got over that. He looked at it and said, I'm not going to deal with this and walked away." -– A second University Professor

There may be language features that for a particular domain are not seen as comfortable or usable yet, such as async Rust usage in a safety domain. We'd like to map which language features feel off-limits in which domains; async in safety-critical work probably isn't the only case.

"We're not fully sure how async [Rust] will work out in the long run in our domain. [..] People don't feel comfortable yet since C++14 doesn't provide such concepts. [..] It's the chicken-and-egg problem again: we probably need to gain some experience to see whether we can actually benefit from these new concepts in the automotive and safety domains." -- Team Lead at Automotive Supplier (ASIL D target)

We heard in at least one case, that while the language was challenging and there was a near bounce, the tooling helped keep them coming back and trying.

"Well, I think my early impressions of Rust - one is I find C++ so intimidating, and I think a big part of why I was able to succeed at [..] learning Rust is the tooling. I mean, all this makes sense [..] but it's like, for me, getting started with Rust, the language was challenging, but the tooling was incredibly easy." -- Founder of another startup built on Rust

While it might be considered more of a community concern, if there are interactions online and in spaces that point to learners having so-called "skill issues" this feeds into the narrative that Rust must be hard to learn. We may be unintentionally turning away Rust Project contributors and maintainers due to the vibes being put out when new learners show up in certain spaces.

"People are very helpful, but generally the attitude is: if your program is very complicated, it's mostly a skill issue. There's not that much empathy when people get stuck learning, and a lot of people are just pushed away by it. There's probably a huge number of people who silently stop wanting to write Rust, because at some point it gets complicated and the feedback they get is 'you just need to be a better programmer, obviously'." -- Software Engineer at a SaaS Provider

Feedback on near-bounces from survey

We found a few interesting perspectives collected in the Rust Vision doc survey which we administered with examples of bouncing and coming back:

"I started before 1.0, got stuck very soon when trying to translate patterns from C++ to Rust (due to borrow checking). I tried again after 1.0 and it stuck. [..]" -- Survey Respondent A

Survey Respondent A went on to share in a more detailed response about a perceived weakness in Rust learning materials related to lifetimes and the borrow checker are explained. There was an observation that it's fairly easy to run into more complex situations with lifetimes and the borrow checker. They felt that the current state of this sort of material and tutorials is fairly superficial and can leave learners stuck when they run into those more complex situations.

One respondent that bounced once and came back shared challenges around usage of async. In concert with Rust's memory-safety and the borrow checker, they found some of the nitty-gritty details of async were difficult to learn. While we're aware of the Rust Project's continuous efforts to improve Rust's async story, this is another data point of a user that faced challenges.

Another survey respondent shared how they had multiple times bounced in trying to learn Rust. They returned after a year or so and found Rustlings to be highly motivating. We note that having multiple pathways for folks to learn Rust opens up more possibilities for those that nearly bounced, just like this person.

Need more focused work on silent attritrion

The thing that stood out most to us was the lack of real, first-hand knowledge of having bounced when learning Rust. While this is an obvious effect of soliciting answers to our survey and opportunities to interview through Rust channels and our networks, this cohort is good future candidate where interviews could start.

Conclusions

Across these conversations, the experience of learning Rust depended heavily on context. Why someone was learning and what support they had mattered as much as the borrow checker. The same kinds of examples kept coming up: a training course that got a team to a shared baseline, a maintainer answering a student's first GitHub issue, and a colleague whose code showed that cloning was okay.

That context is largely something the community has a hand in. With that in mind, here is what we take away from what we heard, and what we still don't know.

What seems worth trying

Learning materials aimed at unlearning. Syntax barely came up when people described their struggles. People struggled with unlearning habits from previous languages, whether OOP structuring from C++ and Java or the instinct to grab a raw pointer to a peripheral. Most of our learning materials teach Rust from first principles, and that works. What we didn't come across is much written for, say, the engineer with ten years of Java who lands on a Rust team after a reorg: material that names the patterns they'll reach for that won't transfer, and shows what to do instead. The professor we spoke with did a version of this in the classroom, leaning on "traits are like interfaces in Java" and saving generics for later in the course, and the students did fine. Something similar could work outside the classroom too.

Put the "clone freely while you're learning" advice somewhere official. Every experienced developer we spoke with gave the same advice, but learners seem to mostly pick it up by accident, like the researcher who happened to see someone else cloning the struct they had been carefully threading lifetimes through. Saying it early in official materials would take some of the steepness out of the curve. The broader version belongs there too: idiomatic Rust doesn't have to mean optimal Rust, especially on a first project.

Diagnostics are already a primary learning resource: several people told us the compiler taught them lifetimes before any documentation did. Diagnostics reach learners right at the moment they're stuck. When writing new ones, it seems worth keeping the confused newcomer in mind alongside the expert, because for a lot of people this is where the learning happens.

Is "the book" actually out of date? Whether or not The Rust Programming Language or other materials are actually behind, a team evaluating Rust looked at its repository, saw unresolved issues and unmerged PRs, and moved on. As more companies evaluate adoption, more people will look at these materials with the same fresh eyes. Visible issue triage and some communication about what's current and what's planned would address the perception, separately from whatever content work may or may not be needed.

How stuck learners get treated is shaping who stays. We heard about students getting answers on GitHub from the maintainers who wrote the code, and we heard about learners being told their struggles were a skill issue. The first group came away with a lasting good impression of Rust. Some of the second group walked away entirely, and because they leave quietly, it's easy to underestimate how many of them there are. The welcoming side of the community came up unprompted as a reason people stayed, so we know it makes a difference when we get this right.

Every organization we spoke with described essentially the same ramp-up for bringing a team to Rust. Teams that brought groups of developers to Rust described roughly the same approach: get everyone to a shared baseline with a training course or with The Rust Programming Language and Rustlings, start people on lower-risk tickets, and give them somewhere internal to ask questions. Several organizations also found that hiring developers without Rust experience and ramping them up worked out better than continuing to search for rare expertise in another language. None of this is complicated, and teams weighing adoption don't need to invent a training program from scratch.

What we still don't know

The biggest gap is the people we didn't reach. Nearly everyone we spoke with stuck with Rust long enough to be reachable through Rust channels, so the stories of bouncing off came to us second-hand: a friend who walked away from embedded Rust, colleagues who quietly stopped after the responses they got. As we wrote in our first post, finding people who decided against Rust takes targeted outreach. If the proposed User Research team comes together, talking with learners who bounced would make a good early project, and learning is probably the area where that research would teach us the most.

We also don't know what to make of LLMs as a learning tool yet. They came up as a search engine, as an example generator, and in one organization's case as something that makes training high school graduates into working Rust developers possible. We saw a classroom where the C cohort leaned on LLMs in ways the Rust cohort couldn't, and we don't have an explanation for it. All of this comes from a handful of conversations, so we treat it as a set of leads to follow up on. Given how quickly the tools are changing, it seems better to study this deliberately than to wait and see what folklore develops.

The folks we spoke with showed that people do get there: with enough passes through the materials and enough code written, it eventually clicks. The opportunities above are mostly about making it work for the people who didn't pick Rust on purpose, and for the ones who would have stuck around if their early experience had gone a little differently.

Why The Fastest Memory Isn't In Your PC (HBM explained)

Sat, 25 Jul 2026 08:35:58 +0200

Author: Techquickie - Bewertung: 4552x - Views:77047

Thanks to Micron for sponsoring this video!

To learn more about High-Bandwidth Memory (HBM), check out: https://www.micron.com/products/memory/hbm

Interested in helping to shape the future of cutting edge memory and storage: https://www.micron.com/about/careers

Modern AI chips don't run on the kind of memory in your gaming PC. They run on something that's literally stacked into a tiny skyscraper, with tens of thousands of microscopic data tunnels drilled through it and a custom silicon motherboard underneath. We sat down with the engineers at Micron to break down how High Bandwidth Memory actually works, why it's the backbone of every serious AI accelerator on the planet, and why your gaming GPU still uses a totally different kind of memory.

Leave a reply with your requests for future episodes.

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MacBook Neo’s success wasn’t luck, it was a plan

Sat, 25 Jul 2026 06:47:11 +0200

It’s difficult to ignore the fact that Apple seems to have turned its MacBook Neo into a weapon to promote platform growth, with enough performance under the hood to make competitors seem inferior.

And even as the PC industry moves to try to compete with Apple’s last huge Mac success, the company is already planning a powerful follow-up.

That points to the discipline Apple has applied to the Mac since the introduction of Apple Silicon. The company has built a clear product roadmap, strong entry-level pricing, and steady performance gains. This focus is now paying dividends, giving people the impetus to keep placing their trust in Apple and its Macs — even as the industry raises prices in the face of RAMageddon and price increases.

The numbers don’t lie

“Apple’s recent price increase seems to be an inevitable response to these cost increases. In the second half of the year, other PC OEMs are expected to continue to raise prices, and the overall ASP increase is expected to continue,” Counterpoint said in a post Wednesday. The researcher tells us global PC shipments shrank 4% in the second quarter of 2026 as rising costs hit demand. The Mac maker, by contrast, moved in the opposite direction, generating 13% growth in the quarter — mainly on the back of the MacBook Neo introduction.

Recent IDC data gives Apple 10.1% year-over-year growth and just under 10% (9.9% to be exact) of the worldwide PC market, even as the overall market declined 4.9%.

“With emerging supply chain and tariff challenges inflating memory prices…, Apple’s incredibly aggressive price-point for the MacBook Neo makes its release feel all the more like a gut punch to one of the PC market’s most valuable price tiers,” Futurum Research Director Olivier Blanchard said when the Neo was released.

Neo 2.0 is already coming

In the immediate future, as competitors raise prices on the PCs that compete with Apple’s lower-cost device, Cupertino is already plotting the path toward MacBook Neo 2. Reports claim this will debut in March in new colors and use the A19 Pro chip from the iPhone 17 Pro, with performance boosted by slightly more unified memory (12GB, rather than 8GB). That’ll make it a much better Mac, likely with 10-15% performance gains and the ability to run Apple Intelligence, making it the best and most affordable AI PC in its class.

Just four months after the Neo’s rollout, Apple is already in position to leak rumors of an even more computationally capable follow-up, while competitors struggle to compete with the original on performance, build quality, and price. Still, the Neo might get more expensive, reporting warns, with the lowest-price 256GB model now gone, making the $599 Mac a mirage we can only wistfully hope to see again.

That might matter less in context, as PC makers everywhere boost prices while RAM, chips, and storage prices head north, along with transport, logistics, and energy costs. “While [Apple] did raise prices in line with the broader market, it still remains well positioned against rivals facing the same cost pressures,” said Jean Philippe Bouchard, vice president for consumer devices at IDC.

“As market conditions continue to worsen, the importance of supply chain management and capabilities are increasingly important,” Bouchard said. “The largest vendors, with their buying power and long-standing supplier ties, are best positioned to take share from smaller rivals.”

This was never about luck

This isn’t solely a market take about competition, it’s about planning.

Few in the industry seemed prepared for the massive memory price increases that hit this year. Apple clearly planned its low-cost Mac well before that happened, hoping to seize the PC market at the low-mid-range. This is precisely what it seems to have done, what it continues to do, and what it will continue to do.

The recent reports that it has a successor planned shows the breadth of the Mac company’s strategic vision, as Apple has quite clearly sought to fully exploit the failings of Windows and the internal contradictions of a value-conscious industry in stiff competition with itself.

With the first M-series Macs about to enter the replacement cycle, Apple has built a market it can capitalize on for at least a decade, meaning it already has a vision for PC sales that extends at least as far. That’s the kind of road map corporate purchasers want when they make platform deployment decisions, which is why Apple’s 10% share gains are the beginning of even more significant market change.

You can follow me on social media! Join me on BlueSky, LinkedIn, Mastodon and subscribe to my daily Apple-related news summaries at The Core.

CVE-2026-34214 | trinodb trino up to 479 removal of sensitive information (GHSA-x27p-5f68-m644)

Sat, 25 Jul 2026 02:24:00 +0200

A vulnerability classified as problematic has been found in trinodb trino up to 479. This vulnerability affects unknown code. Performing a manipulation results in improper removal of sensitive information before storage or transfer. This vulnerability was named CVE-2026-34214. The attack may be initiated remotely. There is no available exploit. It is recommended to upgrade the affected component.

Is exFAT feasible for internal ssd long term ?

Sat, 25 Jul 2026 00:11:38 +0200

Dual booting win/linux for a while now (dedicated ssd per OS). And I need some shared storage so I've been using ntfs for 2 storage ssd's but it's been a huge headache as the linux/win combination constantly corrupts the ntfs file system and I end up with a ton of issues on linux, always having to repair it in windows.

I already do full shutdowns on windows (even started disconnecting the drives from the windows partition manager before shutdown), it doesn't seem to help (i'm suspecting that linux itself corrupts the file system sometimes).

So I'm thinking of switching to using exfat but I've not been able to find much on how feasible that is to use on internal drives. Anyone have any experience with this ?

Of note - the data is not that critical as to warrant a high degree of reliability, but at the same time if exfat presents known issues, same or worse as ntfs, it doesn't make sense to switch.

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Linux Kernel 7.1.4 Released with Bug Fixes, Security Updates, and Hardware Improvements

Fri, 24 Jul 2026 20:32:46 +0200

by George Whittaker

Greg Kroah-Hartman has announced the release of Linux Kernel 7.1.4, the latest stable maintenance update for the Linux 7.1 series. As with other stable kernel releases, version 7.1.4 focuses on fixing bugs, improving hardware compatibility, and addressing security and reliability issues without introducing new features. The update became available on July 18, 2026, and users of the Linux 7.1 branch are encouraged to upgrade as soon as possible.

Rather than changing the kernel's feature set, Linux 7.1.4 delivers dozens of targeted fixes collected from developers across multiple kernel subsystems, helping ensure a more stable experience for desktops, servers, embedded devices, and cloud deployments.

Another Important Stable Maintenance Release

The Linux stable branch exists to provide safe updates between major kernel versions. Every stable release undergoes review before being published and contains fixes that have already been tested in the mainline kernel.

Linux 7.1.4 continues this process by incorporating patches that resolve regressions, improve system stability, and fix issues reported by users since the release of Linux 7.1.3.

For most users, these maintenance updates are recommended because they improve reliability without altering existing functionality.

Bug Fixes Across Multiple Kernel Subsystems

Like previous stable releases, Linux 7.1.4 includes fixes spanning many areas of the kernel.

The update addresses issues affecting:

Memory management
File systems
Networking
Device drivers
Architecture-specific code
Core kernel infrastructure
USB and storage subsystems

These targeted patches help eliminate crashes, improve compatibility with newer hardware, and resolve edge cases that may only appear under specific workloads.

Improved Hardware Compatibility

One of the ongoing goals of Linux stable releases is expanding support for existing and newly released hardware.

Linux 7.1.4 includes updated drivers and compatibility fixes for various devices, helping improve support for:

Graphics hardware
Storage controllers
Networking devices
USB peripherals
Laptop components
ARM development boards

Although no major driver additions are expected in a maintenance release, incremental improvements like these often resolve hardware-specific bugs reported by users after earlier releases.

Security and Reliability Updates

Stable kernel releases also include security-related fixes that have been accepted into the maintenance branch.

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iPhone exploit legal fight is really about who owns security research

Fri, 24 Jul 2026 18:41:21 +0200

A federal judge has ordered a public iPhone exploit taken offline after Magnet Forensics argued it wasn't independent security research at all, but instead a stolen trade secret.

iPhone X

U.S. District Judge Victoria Marie Calvert partially approved Magnet's request for a preliminary injunction. She directed Paradigm Shift and former Magnet exploit engineer Mario Del Gaudio to delete the usbliter8 article, code, technical details, and related materials in their possession by 11:59 p.m. Eastern on July 23.

By July 23, Paradigm Shift had replaced the original article with a page indicating the blog post was unavailable. The preliminary injunction will continue throughout the litigation unless the court removes it in a separate order.

Magnet's July 7 complaint asserts that usbliter8 originated from a confidential A12 and A13 SecureROM access capability integrated into a commercial forensic product. The company alleges Del Gaudio acquired the technique while employed by Magnet and later shared it through Paradigm Shift.

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Judge approves Apple's $250 million settlement offer over Siri lawsuit

Fri, 24 Jul 2026 17:50:14 +0200

A lawsuit over Apple's failure to deliver Apple Intelligence and Siri features is moving closer to a conclusion as a judge has provisionally approved the company's settlement offer.

Apple has settled a class-action lawsuit over its delayed Siri features.

The class action suit filed in 2025 alleged that people had bought new iPhones expressly because of Apple's promoting of Apple Intelligence features that it then did not deliver. Apple admitted in March 2025 that the new Siri features were delayed, but then in May 2025 offered a settlement.

Apple and the parties to the class action suit agreed to a $250 million settlement, but it had to be approved. Now in a filing in the US District Court, Northern District of California, judge Noel Wise has provisionally given approval.

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Boox is taking on Xteink with its own tiny e-reader

Fri, 24 Jul 2026 17:02:22 +0200

Boox's new Tile lineup will take on Xteink's popular e-readers that are small enough to stick on the back of an iPhone with MagSafe. As spotted by Good E-Reader, the first one is the Picco, which will feature a 3.97-inch front-lit, black-and-white e-paper display and expandable storage with an SD card slot. Boox confirmed to […]

Google is signing the EU AI Act Code of Practice on Transparency of AI-Generated Content.

Fri, 24 Jul 2026 16:05:05 +0200

Signing the code reinforces our commitment to transparency and responsible AI development in Europe.

Updated Cyber Threat Actor Naming System

Fri, 24 Jul 2026 16:04:12 +0200

Introduction

Today, Google Threat Intelligence Group (GTIG) will begin rolling out a unified naming schema for tracking threat actors. This new naming taxonomy represents an effort to standardize tracking across platforms and public reporting.

Why are we Adopting a Different Naming System?

Historically, Mandiant and Google’s Threat Analysis Group (TAG) maintained distinct tracking systems, relying on parallel naming schemas that grew independently over time. The creation of GTIG has necessitated a new, fused tracking system, and a new naming system. Thinking to the future, GTIG’s new system will rely on cryptonyms. Relying on sequential numbers or disparate identifiers (e.g. APT1) fails to provide defenders the critical context needed to operate quickly. Threat tracking shouldn’t be an exercise in memorization, but rather one of intuition. The new naming convention aligns with industry standard threat actor naming systems.

Our New Schema

Our new schema utilizes a cryptonym-based approach, employing memorable two-word combinations for each distinct threat actor:

The first word is a unique and memorable term chosen to represent the specific actor, particularly names that may have been used in prior public reporting. If no previously used term exists, this word is randomly generated to remove bias, then vetted by our analysts.
The second word categorizes threat clusters by motivation, attribution, or activity type based on which category we consider to be most important for defense and response strategies.

The table below provides a sample of how threat actor categories will map to the second word in each cryptonym:

Origin or Type	Group Name
People’s Republic of China	CASTLE
Iran	ION
North Korea	NEPTUNE
Russia	RELIC
Cybercriminal	COMET

Table 1: Examples of Google’s new threat actor naming system categories

We know there are many threat actor tracking schemas in the industry, so we are intentionally seeking to keep this system as simple as possible to streamline operations and facilitate mapping to other naming taxonomies. However, a significant caveat remains: because no two organizations have the exact same visibility into the threat landscape, direct, apples-to-apples comparisons between threat actors are rarely possible. Transitioning to a convention that is simpler to follow and remember is a practical step toward managing a highly intricate tracking problem.

A Work in Progress

We have initially prioritized renaming several dozen of the most active groups, and will continue this process on a rolling basis. Previous names will remain indexed and searchable in the Google Threat Intelligence (GTI) platform, with MITRE ATT&CK mappings and other vendor aliases preserved, see Figure 1.

Figure 1: Threat actor name appearance in GTI platform on initial rollout

We will continue to use UNC, or “uncategorized” designations for threat clusters that are still in the early stages of investigation, as described here.

Netto erhält weltweit ersten Supermarkt aus dem 3D-Drucker

Fri, 24 Jul 2026 14:39:34 +0200

Im Schwarzwald entsteht der weltweit erste Supermarkt aus dem 3D-Drucker.

Aleksej Keksel

In der beschaulichen Gemeinde Neubulach im Nordschwarzwald nähe Calw wird derzeit Bau- und Digitalgeschichte geschrieben. Denn hier findet eine Weltpremiere statt: Es entsteht der weltweit erste Supermarkt aus dem 3D-Betondrucker. Mieter wird der Discounter Netto.

Mit einer Grundfläche von rund 1.700 Quadratmetern und einer gedruckten Wandfläche von über 1.300 Quadratmetern setzt das Projekt neue Maßstäbe für den industriellen Einsatz automatisierter Bauverfahren. Wo früher Maurer Stein auf Stein setzten, ziehen heute zwei mobile Instatiq P1 Roboter (Progress One) präzise ihre Bahnen.

Roboter statt Kelle und Mörtel

Die Maschinen spritzen den Beton Schicht für Schicht übereinander, bis Wände mit einer Höhe von bis zu sieben Metern entstehen. Dabei können die Roboter auf der Baustelle flexibel umgesetzt und neu positioniert werden. Das ermöglicht den Bau großflächiger Gewerbeimmobilien in Rekordzeit.

So wurde der gesamte Wandrohbau inklusive aller baulichen Schnittstellen in nur etwa vier Wochen realisiert. „Mit dem ersten gedruckten Supermarkt zeigen wir, dass 3D-Druck im realen Gewerbebau angekommen ist“, erklärt Markus Schilling von Instatiq. Gleichzeitig zeigt das Projekt, dass der 3D-Druck nicht länger nur für kleine Pilotprojekte oder Wohnhäuser reserviert ist. Für Optimisten stellt er gar eine wirtschaftlich relevante Alternative für den großflächigen Handel dar.

Grüner Beton

Während die Druckroboter die Hauptarbeit an den Wänden leisten, wird die Konstruktion durch konventionelle Bauteile wie Stützen und Ringbalken ergänzt. Diese Verzahnung von digitaler Bauvorbereitung und klassischem Rohbau war eine der Herausforderungen, die durch die Zusammenarbeit von Firmen wie Nelcon und der Köhler Bauunternehmung gemeistert wurde.

Schicht für Schicht werden die Wände aus fast CO₂-neutralem Beton gedruckt.

Aleksej Keksel

Doch nicht nur die Technik ist revolutionär, sondern auch das Material. Zum ersten Mal wird bei einem solchen Großprojekt der Near-Zero-Zement evoZero von Heidelberg Materials eingesetzt. Dieser Zement basiert auf der sogenannten CCS-Technologie (Carbon Capture and Storage). Dabei wird das CO₂ direkt im Werk im norwegischen Brevik abgeschieden und anschließend dauerhaft im Meeresboden gespeichert.

Nachhaltiger Gewerbebau

Das Ergebnis ist ein 3D-Druckbeton, der signifikant weniger CO₂ verursacht, ohne dass die Rezeptur oder die technischen Eigenschaften – wie Pumpfähigkeit und Formstabilität – verändert wurden. Matthias Fischer von Heidelberg Materials betont denn auch: „Hier kommen zwei zukunftsweisende Ansätze unter realen Bedingungen zusammen: innovative Materialien und neue Bauverfahren.“

Hinter dem Projekt steht ein breites Partnernetzwerk. Bauherr ist die Bäckerei Sehne, die das Gebäude nach Fertigstellung an den Lebensmittelhändler Netto Marken-Discount vermieten wird. Für Netto ist die Filiale in Neubulach ein klares Bekenntnis zu Innovation und Ressourcenschonung. So heißt es bei dem Discounter: „Der Einsatz von 3D-Druck zeigt, wie sich innovative Technologien bereits heute effizient und nachhaltiger im Filialbau einsetzen lassen.“

Unter dem Strich ist der Supermarkt in Neubulach mehr als nur ein Gebäude. Er ist schlicht ein Beweis dafür, dass automatisiertes, schnelles und nachhaltigeres Bauen keine Zukunftsmusik mehr ist. Mit rund 292 Kubikmetern Druckbeton ist das Projekt laut Instatiq derzeit das weltweit größte realisierte 3D-gedruckte Gebäude.

USN-8606-1: Linux kernel (Azure) vulnerabilities

Fri, 24 Jul 2026 14:17:41 +0200

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)

USN-8607-1: Linux kernel (Azure CVM) vulnerabilities

Fri, 24 Jul 2026 14:17:40 +0200

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)

USN-8609-1: Linux kernel (Azure CVM) vulnerabilities

Fri, 24 Jul 2026 14:17:37 +0200

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)

USN-8575-3: Linux kernel vulnerabilities

Fri, 24 Jul 2026 14:17:35 +0200

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)

USN-8610-1: Linux kernel (Azure CVM) vulnerabilities

Fri, 24 Jul 2026 14:17:33 +0200

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)

Apple wants cheaper iPhone displays to offset spiraling memory costs

Fri, 24 Jul 2026 13:43:47 +0200

As the price of components like RAM and storage continues to skyrocket, Apple has reportedly asked display makers to reduce their prices in an attempt to keep iPhone production costs under control.

Apple hopes to save money on new iPhone displays

According to The Elec's report, Apple has suggested paying suppliers LG Display and Samsung Display around $70 per iPhone 18 Pro Max display. The report suggests that is angling to pay even less, with both companies aiming for per-panel price points of around $66.50.

Apple could pay as much as 20% less than it paid for 2025's iPhone 17 Pro Max displays if LG Display and Samsung Display succeed in meeting that sub-$67 goal.

Continue Reading on AppleInsider | Discuss on our Forums

Google’s anti-search-scraping lawsuit dismissed

Fri, 24 Jul 2026 13:20:02 +0200

A court has dismissed Google’s case against SerpApi over that company’s scraping of search results to train AI models.

The US District Court for the Northern District of California found that there was no indication that any copyright had been breached.

CVE-2026-5531 | SourceCodester Student Result Management System 1.0 HTTP GET Request /login_credentials.txt cleartext storage in file

Fri, 24 Jul 2026 11:34:47 +0200

A vulnerability was found in SourceCodester Student Result Management System 1.0. It has been classified as problematic. Impacted is an unknown function of the file /login_credentials.txt of the component HTTP GET Request Handler. The manipulation leads to cleartext storage in a file or on disk. This vulnerability is listed as CVE-2026-5531. The attack may be initiated remotely. In addition, an exploit is available. It is recommended to apply restrictive firewalling.

Samsung's 4TB 990 EVO Plus internal SSD is down to $599.99, combining massive storage with ultra-fast 7,250MB/s performance

Fri, 24 Jul 2026 11:03:52 +0200

Samsung's 4TB 990 EVO Plus internal SSD is down to $599.99, combining massive storage with ultra-fast 7,250MB/s performance.

Google erlaubt Android-Nutzern kein Gratis-Backup mehr: Schonfrist von 45 Tagen

Fri, 24 Jul 2026 10:50:26 +0200

Google wird nun alle Daten von Android-Sicherungskopien auf den Speicherplatz im Google-Konto des Nutzers anrechnen, wie die Seite Engadget berichtet. Bislang wirkten sich lediglich Inhalte in Google Fotos sowie Bilder und Videos in MMS-Sicherungskopien auf das Speicherkontingent aus.

Für neue Android-Nutzer gilt die Änderung seit dem 7. Juli 2026. Für bestehende Nutzer gilt eine Schonfrist von 45 Tagen, bis sie in Kraft tritt. Google informiert Nutzer per Mail dazu:

Wir möchten dich über eine bevorstehende Aktualisierung unserer Speicherrichtlinien informieren. Außerdem führen wir neue Steuerelemente ein, mit denen du deine Android-Sicherungen besser verwalten kannst.

Richtlinienänderung: In 45 Tagen werden alle Daten, die in den Sicherungen deines Android-Geräts enthalten sind, auf das Speicherplatzlimit deines Google-Kontos angerechnet. Fotos und Videos in Google Fotos und MMS-Daten werden bereits jetzt in deinen Google-Kontospeicherplatz einbezogen. Mit dieser Änderung werden auch alle anderen gesicherten Daten wie SMS, Anruflisten, Geräteeinstellungen und App-Einstellungen auf deinen Google-Kontospeicherplatz angerechnet. Nach Inkrafttreten dieser Richtlinie wird deine Gerätesicherung möglicherweise mehr Speicherplatz belegen. Wenn das Speicherplatzlimit deines Google-Kontos überschritten ist, werden automatische Sicherungen pausiert, bis du Speicherplatz freigibst oder dein Abo upgradest.

Laut Google werden die Auswirkungen dieser Änderung recht begrenzt sein. Android-Sicherungskopien werden im Durchschnitt etwa 40 Megabyte zusätzlichen Speicherplatz beanspruchen. Gleichzeitig werden weitere Einstellungen eingeführt, die den Nutzern mehr Kontrolle darüber geben, was gesichert wird.

Zuvor wurde etwa bekannt, dass Android-Nutzer eine wichtige neue Backup-Funktion erhalten, mit der sie selbst entscheiden können, welche App-Daten gesichert werden sollen und welche nicht. Demnächst möchte Google noch einführen, dass Nutzer ihre Geräteeinstellungen, den Anrufverlauf sowie SMS- und MMS-Nachrichten aus dem Sicherungsvorgang ausschließen können.

Es ist erwähnenswert, dass Google im Mai gleichzeitig den kostenlosen Speicherplatz für neue Konten von 15 Gigabyte auf 5 Gigabyte reduziert hat. Es sei denn, der Nutzer verknüpft eine Telefonnummer mit dem Konto.

Je nachdem, wie viele Daten Sie bereits in der Google Cloud gesichert haben, könnte es also eng werden, selbst wenn die Sicherung nur wenige MB groß ist. Oder Sie merken von der Änderung nicht wirklich viel, da Sie ohnehin auf andere Backup-Methoden setzen.

Ein Upgrade auf 100 GB in Google One kostet 1,99 Euro monatlich, 2,99 Euro für 200 GB oder 9,99 Euro monatlich für 2 TB Speicherplatz. Mit enthalten ist auch der Zugriff auf “neue und leistungsstarke Funktionen” in Google Gemini.

Die besten Online-Backup-Dienste im Vergleich: Nie mehr Daten verlieren

Fix App Not Installed As Package Appears To Be Invalid

Fri, 24 Jul 2026 07:15:26 +0200

Key TakeawaysIssue of 'App Not Installed As Package Appears To Be Invalid' arises from non-Play Store app installations on Android devices.Troubleshooting steps include restarting the device, checking storage availability, downloading the app again from a reliable source, verifying device architecture compatibility, disabling Google Play Protect temporarily, deleting existing app data, resetting app preferences, and trying […]

The post Fix App Not Installed As Package Appears To Be Invalid appeared first on iTech Hacks.

Dell-Aktie nach starken Quartalszahlen: Umsatzmix aus Infrastruktur und PCs stabilisiert die Bilanz

Fri, 24 Jul 2026 06:31:56 +0200

... Microsoft liefert mit KB5121767 ein außerplanmäßiges Notfall-Update für Windows 11 aus. ... PC Server Storage Umsatz. Nächster Artikel. Canine Demenz: ...

Microsoft launches new in-house AI models it says cut costs up to 89% versus OpenAI

Fri, 24 Jul 2026 02:50:17 +0200

Microsoft AI released two new in-house models into public preview on Wednesday — MAI-Image-2.5-Pro, its highest-fidelity image generator to date, and MAI-Voice-2-Flash, a speech model built for high-volume enterprise workloads — while publishing production data that amounts to the company's most aggressive argument yet that it can power its own products without leaning on OpenAI's frontier models.

The announcement, made by Microsoft AI's Superintelligence team, lands roughly a year after the company committed to building purpose-built models internally, and it arrives with an unusual level of specificity about where those models now run: Bing, PowerPoint, OneDrive, Dynamics 365, Excel, GitHub Copilot, and Azure. The message to enterprise buyers — and, implicitly, to OpenAI — is that Microsoft's homegrown models are no longer research projects. They are production infrastructure serving millions of users.

"Each of these enhancements is a step toward the same goal: Microsoft products, powered by Microsoft models," the company wrote in its announcement blog.

How MAI-Image-2.5-Pro and MAI-Voice-2-Flash stake out opposite ends of the AI cost curve

The two new releases occupy opposite ends of what Microsoft calls the quality-speed-cost curve, and the positioning is deliberate. MAI-Image-2.5-Pro targets the premium tier: hero imagery, detailed editing, and precise in-image text rendering — the last of which has long been a notorious weak spot for image generation models. Microsoft priced the model at $5 per million text input tokens, $8 per million image input tokens, and $106 per million image output tokens. The base MAI-Image-2.5 model recently launched at No. 2 for image editing on Arena, the community leaderboard that has become a de facto scoreboard for generative media.

The creative industry appears to be taking notice. Rob Reilly, global chief creative officer at advertising giant WPP, called the Pro model "a strong leap forward for GenMedia tools" in a statement included in Microsoft's announcement, adding that "Microsoft has firmly established itself among the leaders in generative AI."

MAI-Voice-2-Flash goes the other direction. First previewed at Microsoft's Build conference, Flash runs twice as fast as MAI-Voice-2 and costs 32% less, priced at $15 per million characters. It is designed for the unglamorous but enormous market of high-volume voice — call centers, voice agents, and real-time speech applications where latency and cost-per-call matter more than marginal gains in expressiveness. Together, the two models reflect a strategy of building families of models rather than a single flagship, because, as the company put it, a creative studio chasing maximum fidelity has very different needs from a customer service operation handling millions of calls a day.

Microsoft's production metrics show in-house models cutting GPU costs by up to 89%

The model launches are arguably less newsworthy than the deployment metrics Microsoft attached to them — numbers that read like a systematic case for swapping out third-party frontier models across its product portfolio.

Bing Image Creator now runs entirely on MAI-Image-2.5, end to end, marking the first time the consumer image tool is fully in-house. In PowerPoint, Microsoft says MAI-Image-2.5 reduces GPU costs by up to 84% compared with GPT-Image-2, OpenAI's image model. In OneDrive, where MAI-Image-2.5 is now the default for key image-editing scenarios, the company reports a 26% increase in save rates, roughly 25% lower P95 latency, and 2.5 times greater efficiency under medium-utilization production workloads.

On the voice side, MAI-Voice-2-Flash now powers Dynamics 365 Contact Center — the platform used by customers including T-Mobile and EasyJet — where Microsoft claims GPU cost reductions of up to 89%. The model is also integrated into Azure Voice Live for developers building speech-to-speech agents.

Perhaps the most consequential deployment sits in healthcare. Microsoft's Dragon Copilot, used by 170,000 medical providers and responsible for processing 28 million patient encounters last quarter, now runs on MAI-Transcribe-1.5 for its multilingual workflow across 58 languages. Microsoft says internal evaluations show a 50% relative reduction in both transcription and language-identification error rates across most languages — a meaningful claim in a domain where transcription errors can propagate directly into clinical notes.

Inside the 'hill-climbing' strategy that lets small models beat GPT-5.6 in Excel

In a companion post published the same day, Microsoft detailed the methodology behind these results — what it calls its "hill-climbing machine," an integrated flywheel of data, models, and the product "harness" that surrounds them.

The clearest example is MAI-Code-1-Flash, the lightweight coding model launched in GitHub Copilot in June. Microsoft says the model achieves an approximately 10% higher code accept rate than GPT-5.4 Mini and Claude Haiku 4.5 in VS Code, while using 10% fewer median tokens. Developer retention tells a similar story: users were 6% more likely to return across multiple days than with GPT-5.4 Mini, and 11% more likely than with Claude Haiku 4.5.

Then Microsoft did something more interesting. It took the MAI-Code-1-Flash checkpoint and further trained it inside an Excel reinforcement learning environment, teaching a coding model the tools and workflows of spreadsheet knowledge work. The result, according to production user feedback, is a model on par with GPT-5.6 for the most common Excel tasks — while being small enough to run on Nvidia's older H100 and even A100 GPUs rather than requiring the latest-generation accelerators.

That hardware detail deserves emphasis. Every major AI company is fighting for allocation of cutting-edge chips, and a model that delivers frontier-adjacent quality on two-generation-old silicon fundamentally changes the deployment economics. It also frees the newest hardware — including Microsoft's now-operational GB200 cluster — for training rather than serving.

Satya Nadella's 'frontier diffusion' manifesto redraws the OpenAI relationship

Microsoft CEO Satya Nadella framed the announcements in a lengthy post on X titled "Frontier Diffusion & Control," which functions as something close to a strategic manifesto. "We can now take saturated frontier capabilities and deliver them at scale and at lower cost through models optimized for high-usage products, while continuing to use frontier models for frontier needs," Nadella wrote, adding that Microsoft is "beginning to route traffic across our first-party surfaces to MAI whenever our models match or outperform frontier alternatives."

Translated from executive prose: capabilities that were state-of-the-art a year ago are now table stakes, and Microsoft believes it can replicate them cheaply for the specific, repetitive tasks that dominate real product usage. Why pay frontier prices for a frontier model when a user just wants to reformat a spreadsheet column?

Nadella was careful to note that "frontier models from OpenAI and Anthropic are part of the orchestration system alongside MAI" — but he also articulated a pointed principle of model independence, arguing that a company's evaluations "should continue to hill climb even when any given model has been removed."

“Keeping the harness, memory, context, and skills outside the model, he argued, is what gives Microsoft control. The subtext is hard to miss. Reuters reported in April that Microsoft’s exclusive license to OpenAI’s technology had been revised into a non-exclusive arrangement, and The Information reported last September that Microsoft had begun incorporating Anthropic models into some products. Wednesday’s announcement completes the triangle: Microsoft as orchestrator, with its partners’ frontier models as interchangeable components and its own models absorbing an ever-larger share of routine traffic.”

Developers cheer cheaper task-specific models while skeptics question Microsoft's track record

The response online captured both the appeal and the skepticism surrounding the strategy. "I love when people use small models for niche tasks," wrote one X user, @mavihsk, responding to Nadella's post. "Why do I have to use the all-knowing model just to change my field in Excel?" Another user, @nabu_lines, distilled the pitch neatly: "cost and performance both improve when you stop overusing the biggest model."

Others were less charitable about Microsoft's execution track record. "Microsoft is the worst when it comes to listening to user feedback," wrote designer @designedbyabin, arguing the company "will lose the AI race because they repeatedly failed to understand user needs." And one user, @tokenoverflow, offered a drier critique of the model-independence pitch: "i want it keep hill climbing after removing microsoft."

The skeptics raise a fair point. Microsoft's self-reported metrics — accept rates, save rates, GPU savings — come from its own internal evaluations, not independent benchmarks, and the company chooses which comparisons to publish.

But the strategy's logic does not depend on any single number. Nadella's framing that software now has "real marginal cost for the first time" explains why Microsoft is obsessive about tokens, GPUs, and serving costs: when AI features run on every keystroke across a billion-user product portfolio, an 84% GPU cost reduction is not an optimization. It is the difference between a viable business and a money pit.

Why Microsoft is turning its internal AI playbook into an Azure product

The final piece of the strategy is that Microsoft is selling the playbook, not just the models. Nadella explicitly positioned the hill-climbing approach as "a template for every other AI native, SaaS, or Enterprise company," and Microsoft is packaging the toolchain through Foundry and what it calls Frontier Tuning — letting enterprises train specialized models against their own proprietary evaluations and reinforcement learning environments. That turns Microsoft's internal cost-cutting exercise into an Azure product, and it gives enterprise customers a reason to run their AI workloads on Microsoft's cloud even if the models themselves come from elsewhere.

The company's emphasis on models trained "on clean, traceable, enterprise-grade data, without distillation from third-party models" serves the same commercial end. In an industry facing mounting scrutiny over training data provenance, Microsoft is betting that enterprise buyers — and courts — will care where model capabilities come from. Microsoft says it is now extending the hill-climbing approach to Copilot Chat, Outlook, and PowerPoint, and both new models are available in public preview through Microsoft Foundry and the MAI Playground. "None of this is an endpoint," the company wrote. "We're just getting started."

Seven years ago, Microsoft bet more than $13 billion that OpenAI would build the future of AI. Wednesday's announcement suggests the company has since learned a cheaper lesson: the future of AI may belong to whoever builds the frontier, but the profits belong to whoever makes it ordinary.

I built a Linux filesystem benchmark for corruption, snapshots, rebuilds and ENOSPC across 26 storage layouts

Fri, 24 Jul 2026 00:13:06 +0200

Most filesystem benchmarks measure throughput on a freshly formatted single device. That is useful, but it misses many of the reasons people choose btrfs, ZFS or bcachefs in the first place.

I built modern-fs-benchmark to examine modern filesystems as complete storage systems, including their features, failure modes and behavior over time.

The current matrix contains 26 configurations across btrfs, ZFS, bcachefs, ext4 and XFS over md/LVM, dm-integrity, native and LUKS encryption, parity layouts, and XFS on a ZFS zvol.

Hosted CI dashboard:

https://bartosz.fenski.pl/modern-fs-benchmark/

Experimental real-hardware dashboard:

https://bartosz.fenski.pl/modern-fs-benchmark/real-hw/

Apache-2.0 licensed source and complete methodology:

https://github.com/fenio/modern-fs-benchmark

The raw benchmark datasets are published under CC BY 4.0. Every result records the kernel and filesystem tool/module versions. CI artifacts also contain a full command trace, so the exact workload is inspectable rather than hidden behind a chart.

Why I started this project

Many filesystem benchmarks follow a familiar pattern: create a filesystem with mostly default options, mount it, run fio or another generic workload, and compare throughput.

General-purpose suites such as the Phoronix Test Suite are useful for conventional performance comparisons, but they do not focus on the machinery that makes modern copy-on-write filesystems interesting.

I wanted a benchmark designed around btrfs, ZFS and bcachefs as multi-device storage systems rather than treating them as interchangeable replacements for ext4 on a single freshly formatted disk.

That means testing behavior such as:

- Redundancy and degraded operation

- Snapshot aging, scaling and reclamation

- Compression and encryption

- Reflinks and clone divergence

- Fsync tail latency and responsiveness under load

- Rebuild and scrub behavior

- Near-full and hard-ENOSPC behavior

- Data integrity and recovery from corruption

Ext4 and XFS over md, LVM and dm-integrity are included as classic-stack baselines so the costs and benefits of integrated CoW designs can be compared with layered alternatives.

Silent corruption is one particularly important example. When one redundant copy is deliberately corrupted behind the filesystem, checksumming filesystems such as btrfs, ZFS and bcachefs can identify the damaged copy and recover from a valid replica.

Traditional md/LVM redundancy without data checksums can notice during a scrub that its copies disagree, but it cannot determine which one is correct. In my tests, some classic configurations returned corrupted data successfully without an application-visible error.

The dm-integrity configuration shows that a classic layered stack can obtain integrity protection too, with a measurable performance cost.

An important limitation

The main dashboard uses loop devices on GitHub-hosted VMs. Absolute throughput numbers and small differences between filesystems should not be interpreted as hardware rankings.

The hosted runs are primarily useful for:

- Correctness and integrity outcomes

- Comparisons within the same job

- Large behavioral differences

- Snapshot-aging and near-full shapes

- Trends across repeated runs

Real disks are required for meaningful absolute performance, concurrency scaling, device parallelism and mixed-media topologies.

I am aware of this limitation and do not want the hosted dashboard to suggest more precision than the underlying environment can provide.

The real-hardware experiment

Kent Overstreet, the creator of bcachefs, made one of his Hetzner machines available for a real-hardware experiment.

The server had two physical NVMe devices. It completed three full benchmark runs, which are available in the separate real-hardware dashboard. These runs provided meaningful absolute measurements and exposed concurrency behavior that cannot be observed when several loop devices share one virtual disk.

During the fourth run, one NVMe controller entered the kernel’s dead state. The existing machine environment had its operating system on RAID0 across the two NVMe devices, so the hardware failure also made part of /nix/store unreadable and eventually prevented new SSH sessions.

The incomplete fourth run is not being published as benchmark data. This was a failure of the underlying hardware, not a result attributable to any filesystem being tested.

I am grateful to Kent for providing the machine and making the real-hardware experiment possible. Without that access, the three existing hardware runs would not exist.

Where I would like to take it

Better hardware would not merely produce more reliable throughput numbers. It would enable an entirely new class of tests designed for multi-device and multi-tier filesystems.

I would eventually like to run the suite on a machine containing several storage classes, for example two HDDs, two SSDs and an NVMe device.

That could support scenarios such as:

- HDD, SSD and NVMe baselines using identical workloads

- bcachefs foreground and background targets

- ZFS HDD data vdevs with SSD special vdevs

- Separate ZFS L2ARC and SLOG experiments

- LVM dm-cache in writeback and writethrough modes

- Metadata and small-block placement on faster media

- Foreground latency during background migration

- Contention between fast and slow storage tiers

- Degraded operation and rebuild under application load

- Performance before, during and after promoting or evacuating a storage tier

These are the kinds of scenarios for which multi-device and multi-tier filesystems are built, but they cannot be represented honestly when every “device” is a loop file backed by the same cloud disk.

I am considering either renting a suitable dedicated server or eventually building and hosting my own machine. Providers such as Worldstream offer configurations close to what I need, but the recurring cost is currently outside the project’s budget.

For now, the benchmark will remain in its hosted-CI form for an unknown amount of time. The existing dashboard will continue to be useful for correctness, behavioral comparisons and regression tracking, but it cannot answer every real-hardware performance question or model complex mixed-media topologies.

I am also open to running the suite on hardware provided by someone else. A useful environment would need Linux root access, clearly identified block devices that may be wiped, and enough uninterrupted access to complete repeated runs. The hardware description, methodology and resulting data would remain public.

I would appreciate technical feedback:

- Which current tests are misleading or unfair?

- Which failure scenarios are missing?

- Which mixed-media topologies would be most useful?

- Which additional filesystems or layered stacks should be included?

- Which results deserve deeper investigation?

The methodology, implementation and raw results are public. If a filesystem is being tested in a way that misrepresents it, I consider that a bug in the benchmark.

submitted by /u/bfenski
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AMD raises the AI stakes with Helios, Venice and robotics

Thu, 23 Jul 2026 20:48:09 +0200

AMD’s MI455X targets the AI memory wall

AMD

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.

AMD’s Helios rack takes aim at Vera Rubin

Dave Altavilla

Kind of like cowbell, AMD Venice gives agentic AI more CPU

AMD

Pensando networking and ROCm software advance

Customer commitments underscore rack-scale confidence

AMD expands its robotics and embedded foundation

Execution for AMD is now the test

This article is published as part of the Foundry Expert Contributor Network.
Want to join?

Johnson Controls XAAP Android

Thu, 23 Jul 2026 20:17:02 +0200

View CSAF

Summary

Successful exploitation of this vulnerability could result in an attacker obtaining confidential information from the device.

The following versions of Johnson Controls XAAP Android are affected:

XAAP Android <1.53

CVSS	Vendor	Equipment	Vulnerabilities
v3 3.3	Johnson Controls	Johnson Controls XAAP Android	Cleartext Storage of Sensitive Information

Background

Critical Infrastructure Sectors: Critical Manufacturing
Countries/Areas Deployed: Worldwide
Company Headquarters Location: Ireland

Vulnerabilities

Expand All +

CVE-2026-34490

A cleartext storage weakness exists in the Fire Solutions Android application, which stores application data locally on the device without encryption. An attacker with physical access to the device and one able to compromise the device through a separate, unrelated flaw, could potentially read this data in plaintext. Exploitation does not require network access and is limited to the local device environment.

View CVE Details

Affected Products

Johnson Controls XAAP Android

Vendor:
Johnson Controls

Product Version:
Johnson Controls XAAP Android: <1.53

Product Status:
known_affected

Remediations

Vendor fix
Johnson Controls recommends users update the XAAP Android application to version 1.53 or later, which contains the fix for this vulnerability.

Mitigation
Johnson Controls recommends users restrict physical access to devices running the XAAP Android application.

Mitigation
Johnson Controls recommends users ensure devices are hardened with up-to-date Android OS versions, device encryption enabled, and screen lock protections in place.

Mitigation
Johnson Controls recommends users implement a Mobile Device Management (MDM) solution to enforce security policies, including encryption requirements, application whitelisting, and remote wipe capabilities.

Mitigation
Johnson Controls recommends users Avoid rooting or jailbreaking devices used in production environments, as this weakens OS-level security controls that help protect local application data.

Mitigation
For more detailed mitigation instructions, please see Johnson Controls Product Security Advisory JCI-PSA-2026-10.

Relevant CWE: CWE-312 Cleartext Storage of Sensitive Information

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	3.3	LOW	CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N
4.0	4.8	MEDIUM	CVSS:4.0/AV:L/AC:L/AT:N/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N

Acknowledgments

Johnson Controls reported this vulnerability to CISA

Legal Notice and Terms of Use

This product is provided subject to this Notification (https://www.cisa.gov/notification) and this Privacy & Use policy (https://www.cisa.gov/privacy-policy).

Recommended Practices

CISA recommends users take defensive measures to minimize the risk of exploitation of this vulnerability.

Minimize network exposure for all control system devices and/or systems, ensuring they are not accessible from the internet.

Locate control system networks and remote devices behind firewalls and isolating them from business networks.

When remote access is required, use more secure methods, such as Virtual Private Networks (VPNs), recognizing VPNs may have vulnerabilities and should be updated to the most current version available. Also recognize VPN is only as secure as the connected devices.

CISA reminds organizations to perform proper impact analysis and risk assessment prior to deploying defensive measures.

CISA also provides a section for control systems security recommended practices on the ICS webpage on cisa.gov/ics. Several CISA products detailing cyber defense best practices are available for reading and download, including Improving Industrial Control Systems Cybersecurity with Defense-in-Depth Strategies.

CISA encourages organizations to implement recommended cybersecurity strategies for proactive defense of ICS assets.

Additional mitigation guidance and recommended practices are publicly available on the ICS webpage at cisa.gov/ics in the technical information paper, ICS-TIP-12-146-01B--Targeted Cyber Intrusion Detection and Mitigation Strategies.

Organizations observing suspected malicious activity should follow established internal procedures and report findings to CISA for tracking and correlation against other incidents.

No known public exploitation specifically targeting this vulnerability has been reported to CISA at this time. This vulnerability is not exploitable remotely.

Revision History

Initial Release Date: 2026-07-23

Date	Revision	Summary
2026-07-23	1	Initial Republication of Johnson Controls JCI-PSA-2026-10

Legal Notice and Terms of Use

Panduit IntraVUE

Thu, 23 Jul 2026 20:16:33 +0200

View CSAF

Summary

Successful exploitation of these vulnerabilities could allow an attacker with access to the IT network to manipulate industrial control devices without requiring physical access, specialized insider knowledge, or advanced tooling.

The following versions of Panduit IntraVUE are affected:

IntraVUE <=3.2.1a14

CVSS	Vendor	Equipment	Vulnerabilities
v3 10	Pronetiqs	Panduit IntraVUE	Plaintext Storage of a Password, Unintended Proxy or Intermediary ('Confused Deputy'), Exposure of Sensitive System Information to an Unauthorized Control Sphere, Inadequate Encryption Strength

Background

Critical Infrastructure Sectors: Critical Manufacturing, Energy, Information Technology, Water and Wastewater
Countries/Areas Deployed: Worldwide
Company Headquarters Location: Netherlands

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	8.6	HIGH	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
4.0	9.2	CRITICAL	CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:N/VA:N/SC:H/SI:N/SA:N

Acknowledgments

Phlebas of Lumintel reported these vulnerabilities to CISA

Legal Notice and Terms of Use

This product is provided subject to this Notification (https://www.cisa.gov/notification) and this Privacy & Use policy (https://www.cisa.gov/privacy-policy).

Recommended Practices

CISA recommends users take defensive measures to minimize the risk of exploitation of these vulnerabilities.

Minimize network exposure for all control system devices and/or systems, ensuring they are not accessible from the Internet.

Locate control system networks and remote devices behind firewalls and isolating them from business networks.

CISA reminds organizations to perform proper impact analysis and risk assessment prior to deploying defensive measures.

CISA encourages organizations to implement recommended cybersecurity strategies for proactive defense of ICS assets.

Organizations observing suspected malicious activity should follow established internal procedures and report findings to CISA for tracking and correlation against other incidents.

CISA also recommends users take the following measures to protect themselves from social engineering attacks:

Do not click web links or open attachments in unsolicited email messages.

Refer to Recognizing and Avoiding Email Scams for more information on avoiding email scams.

Refer to Avoiding Social Engineering and Phishing Attacks for more information on social engineering attacks.

No known public exploitation specifically targeting these vulnerabilities has been reported to CISA at this time.

Revision History

Initial Release Date: 2026-07-23

Date	Revision	Summary
2026-07-23	1	Initial Publication

Legal Notice and Terms of Use

Weintek cMT3092X

Thu, 23 Jul 2026 20:16:14 +0200

View CSAF

Summary

Successful exploitation of these vulnerabilities could allow a non-privileged user to escalate privileges or view the credentials of other users.

The following versions of Weintek cMT3092X are affected:

cMT3092X firmware <20210218
EasyWeb

CVSS	Vendor	Equipment	Vulnerabilities
v3 8.8	Weintek	Weintek cMT3092X	Reliance on Cookies without Validation and Integrity Checking in a Security Decision, Incorrect Permission Assignment for Critical Resource, Plaintext Storage of a Password, Incorrect User Management

Background

Critical Infrastructure Sectors: Critical Manufacturing
Countries/Areas Deployed: Worldwide
Company Headquarters Location: Taiwan

Vulnerabilities

Expand All +

CVE-2026-60134

Weintek cMT3092X HMI allows a non-privileged user to modify cookies to gain elevated privileges.

View CVE Details

Affected Products

Weintek cMT3092X

Vendor:
Weintek

Product Version:
Weintek cMT3092X firmware: <20210218, Weintek EasyWeb:

Product Status:
known_affected

Remediations

Vendor fix
Weintek recommends users apply the patch package named cmt_typeB_20260316_007.patch, which contains a newer EasyWeb 2.3.17-typeb. This fix will be delivered as a patch-only update; no separate standard firmware release is planned. Users may request the patch directly from Weintek support (https://www.weintek.com/globalw/Support/Knowledge.aspx) or from distributors.
https://www.weintek.com/globalw/Support/Knowledge.aspx

Mitigation
Weintek has published a document with more details about this issue at https://dl.weintek.com/public/Document/TEC/TEC25003E_cMT_EasyWeb_V2_Security_Issues.pdf.
https://dl.weintek.com/public/Document/TEC/TEC25003E_cMT_EasyWeb_V2_Security_Issues.pdf

Relevant CWE: CWE-784 Reliance on Cookies without Validation and Integrity Checking in a Security Decision

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	8.8	HIGH	CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
4.0	8.7	HIGH	CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

CVE-2026-61892

Weintek cMT3092X HMI allows a non-privileged user to modify tokens to escalate privileges.

View CVE Details

Affected Products

Weintek cMT3092X

Vendor:
Weintek

Product Version:
Weintek cMT3092X firmware: <20210218, Weintek EasyWeb:

Product Status:
known_affected

Remediations

Relevant CWE: CWE-732 Incorrect Permission Assignment for Critical Resource

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	8.8	HIGH	CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
4.0	8.7	HIGH	CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

CVE-2026-61886

Weintek cMT3092X HMI stores user account passwords in plaintext.

View CVE Details

Affected Products

Weintek cMT3092X

Vendor:
Weintek

Product Version:
Weintek cMT3092X firmware: <20210218, Weintek EasyWeb:

Product Status:
known_affected

Remediations

Relevant CWE: CWE-256 Plaintext Storage of a Password

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	6.5	MEDIUM	CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N
4.0	7.1	HIGH	CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:N/VA:N/SC:N/SI:N/SA:N

CVE-2026-60135

An attacker can modify data that should be restricted to read‑only access.

View CVE Details

Affected Products

Weintek cMT3092X

Vendor:
Weintek

Product Version:
Weintek cMT3092X firmware: <20210218, Weintek EasyWeb:

Product Status:
known_affected

Remediations

Relevant CWE: CWE-286 Incorrect User Management

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	6.5	MEDIUM	CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:H/A:N
4.0	7.1	HIGH	CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:H/VA:N/SC:N/SI:N/SA:N

Acknowledgments

Vincenzo Giuseppe Colacino of Secoore reported these vulnerabilities to CISA

Legal Notice and Terms of Use

This product is provided subject to this Notification (https://www.cisa.gov/notification) and this Privacy & Use policy (https://www.cisa.gov/privacy-policy).

Recommended Practices

CISA recommends users take the following measures to protect themselves from social engineering attacks:

Practice principles of least privilege.

Do not click web links or open attachments in unsolicited email messages.

Refer to Recognizing and Avoiding Email Scams for more information on avoiding email scams.

Refer to Avoiding Social Engineering and Phishing Attacks for more information on social engineering attacks.

CISA reminds organizations to perform proper impact analysis and risk assessment prior to deploying defensive measures.

CISA encourages organizations to implement recommended cybersecurity strategies for proactive defense of ICS assets.

Organizations observing suspected malicious activity should follow established internal procedures and report findings to CISA for tracking and correlation against other incidents.

No known public exploitation specifically targeting these vulnerabilities has been reported to CISA at this time.

Revision History

Initial Release Date: 2026-07-23

Date	Revision	Summary
2026-07-23	1	Initial Publication

Legal Notice and Terms of Use

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Unlock digital perks via our roadcase and Use tab, or join Google Play's live auction house in San Diego.

The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs

Thu, 23 Jul 2026 19:19:39 +0200

Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model-provider APIs, yet the next dollar is aimed at specialized compute almost none of them use today; a majority intend to switch or add providers within the year, many within a quarter. Buying decisions turn on integration and total cost of ownership rather than headline token price — which is fortunate, because most enterprises cannot yet see their unit economics clearly: GPUs sit at half utilization or less, and fewer than half rigorously track what their compute actually costs. The result is a compute gap — heavy, fast-moving investment running ahead of the visibility needed to control it.

This wave of VentureBeat Pulse Research examines enterprise AI infrastructure and compute: where organizations are in their deployment journey, what they run AI on today, how satisfied they are, what would make them switch, where they plan to evaluate their investments, and — most revealingly — how well they can measure and control the economics of the compute underneath it all.

The central finding is a compute gap — the distance between how aggressively enterprises are investing in AI infrastructure and how little of its economics they can see. Only about one in five (21%) run AI in production at scale, yet spending intentions are outrunning that maturity: the single largest planned area enterprises plan to evaluate over the next year is AI-specialized clouds (45%), a layer almost none of these enterprises use today. Meanwhile the compute already in place runs cold — 83% report GPU utilization of 50% or less — and fewer than half (44%) can rigorously track what their AI compute costs. Enterprises are buying more infrastructure faster than they can account for what they already own.

Enterprises are not settled on their infrastructure vendors, either: A clear majority (64%) plan to switch or add an infrastructure provider within twelve months, and 38% within the next quarter — unusually high churn intent for a category this foundational. When they choose, they choose on integration with the existing stack (41%) and total cost of ownership (35%), not on headline price: cost per million tokens is the deciding factor for just 8%. And the frontier constraint that will shape the next round of decisions — the shift from GPU compute to memory bandwidth as inference scales — is barely on the radar, with roughly one in five enterprises either unaware of it or yet to address it.

Methodology

VentureBeat fielded this survey as part of its ongoing Pulse Research series, this survey focused on enterprise AI infrastructure, compute, and inference economics. 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 Q2 2026 (June) 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%.

By organization size the sample concentrates in the mid-market: 101–250 employees (36%) and 251–1,000 (27%) lead, with 1,001–5,000 (22%), 5,001–10,000 (8%), and 10,001+ (7%) above them. By role it spans managers (38%), individual contributors (28%), VPs and directors (19%), and the C-suite (13%); on purchasing authority it is buyer-credible, with 45% final decision-makers and another 30% recommenders or influencers for AI solutions. Technology/Software is the largest industry at 26%, followed by Healthcare/Life Sciences (15%), Financial Services (13%), and Retail/E-commerce (12%).

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 also skews toward the mid-market and toward earlier-stage adopters, so it is best read as the view from organizations actively building out AI infrastructure rather than from the largest hyperscale operators.

Finding 1: Ambition outpaces production

Only one in five run AI in production at scale

We asked where organizations sit in their AI deployment journey. Most are still building toward production rather than operating at scale.

The maturity curve is front-loaded. Three-quarters of enterprises (76%) are either experimenting or running only some workloads in production, and just 21% describe AI in production at scale. This matters for everything that follows: the infrastructure decisions in this report are being made largely by organizations still early in deployment, whose compute footprint — and whose costs — are about to grow. The evaluation and switching intentions in Findings 3 and 4 are the leading edge of that build-out, not the settled preferences of operators who have already found what works.

Finding 2: Enterprises run on hyperscalers and model APIs

The specialized GPU clouds barely register — today

We asked which providers and platforms enterprises currently use to run their AI. The answer is a familiar one: the incumbents.

The current stack is hyperscaler-and-API. Google Cloud leads at 48%, and the general-purpose clouds (Google, Microsoft, AWS, Oracle) together with the major model APIs (Gemini, OpenAI, Anthropic) account for essentially all current deployment. The specialized “neocloud” GPU providers that dominate AI-infrastructure headlines — CoreWeave, Lambda, Crusoe, Nebius and peers — register at or near zero among these enterprises today. Only 6% run their own on-prem GPU clusters and 4% a custom open-source stack. Enterprises are, for now, running AI on the providers they already buy from — which makes the evaluation intentions in Finding 3 all the more striking.

(A note on reading these shares. As described in the methodology section, this sample is self-selected and skews mid-market, and this question counted every provider a respondent uses — an average of 2.1 selections each — so the figures measure presence in the stack rather than spending or primary status. A sample built this way will show a different provider mix than a spend-weighted census of the broader market; Google's strength here, for example, is consistent with its long-standing position among smaller enterprises building on AI. Read these shares as a portrait of what this AI-active cohort runs today, and treat gaps between these figures and industry-wide market share estimates as a property of the sample rather than a contradiction of either.)

Finding 3: The next dollar goes to infrastructure they don’t yet run

AI-specialized clouds top the evaluations list

We asked where enterprises planned to evaluate AI infrastructure over the next 12 months. Their answers point away from the stack they run today.

Here is the report’s sharpest tension. The single most-cited planned evaluation area — AI-specialized clouds, at 45% — is the very category almost none of these enterprises use today (Finding 2). Nearly a third (32%) intend to evaluate non-Nvidia accelerators, and 28% in next-generation Nvidia silicon; even decentralized compute networks (16%) and sovereign compute (11%) draw meaningful interest. Read against current usage, this is not incremental — it is the leading edge of a re-platforming. The direction-of-travel question tells the same story: every infrastructure approach is net-expanding, but specialized AI clouds carry the highest net momentum (+24), edging out even the hyperscalers (+22). Enterprises are preparing to move a meaningful share of AI compute off the general-purpose cloud.

This continues a trend we saw in our April-May survey wave. Back then, usage of the AI-specialized clouds was equally marginal — CoreWeave at 3%, Lambda at 4%, Crusoe at 2% of enterprises. When we asked enterprises what change they planned in their AI infrastructure strategy over the next twelve months, the most-cited answer was moving workloads to specialized AI clouds, at 33%. Asked in April-May which emerging compute option they were most likely to evaluate AI-specialized clouds again drew the most responses. Two waves, two differently worded questions, one consistent picture: the type of cloud enterprises are most eager to assess is the type they have barely begun to use.

Finding 4: A switching wave is building

Six in 10 plan to change providers within a year — many within a quarter

We asked whether and when enterprises plan to switch or add an infrastructure provider. Very few intend to stand still.

For a category as foundational as compute, this is a remarkable amount of intended movement. Only 36% have no plans to change, meaning a clear majority (64%) intend to switch or add a provider within twelve months — and 38% within the next quarter alone. Where that interest points is telling: the providers drawing the most switching consideration are again the incumbents — Microsoft Azure and Google Cloud (33% each), OpenAI (30%), and Gemini (22%) — which suggests much of the near-term movement is reshuffling among the majors and consolidating spend rather than defecting to new entrants. The neocloud interest in Finding 3 is a 12-month evaluation thesis; the switching in the next quarter is mostly incumbents trading share.

(Method note: Respondents who selected both "no plans to change" and a specific switching window are counted as switchers, on the logic that naming a timeframe is the more specific answer; three respondents were reclassified under this rule.)

Finding 5: Nobody buys on token price

Integration and total cost of ownership decide — not sticker price

We asked what matters most when enterprises select an AI infrastructure provider. Headline price finished last.

Enterprises do not buy AI infrastructure on pricing, which is the place vendors compete on hardest. Integration with the existing stack (41%) and total cost of ownership (35%) dominate, while the headline metric — cost per million tokens — is the deciding factor for just 8%, dead last. The pattern is coherent: buyers are optimizing for how a provider fits and what it truly costs to operate, not for the advertised unit rate. It also foreshadows Finding 7 — enterprises say TCO matters most, yet most cannot yet measure it rigorously. The stated priority and the measured capability are out of step.

Finding 6: Expensive GPUs, idle most of the time

83% report GPU utilization of 50% or less

We asked what share of their GPU capacity enterprises actually utilize. The answer is a well-known but rarely quantified inefficiency.

Disclosure: Band percentages count every selection against all 107 qualified respondents; 14 respondents selected more than one band, so bands overlap. At the respondent level, 83 of the 100 GPU-operating enterprises reported utilization at or below 50%

The compute already in place runs cold. Adding the bands at or below half capacity, 83% of enterprises that operate GPUs report utilization of 50% or less, and nearly half (49%) run at 25% or below. Only 12% clear the 50% mark, and a further 8% do not measure utilization at all. Idle accelerators are expensive accelerators, and this is the clearest single measure of the compute gap: enterprises are planning to buy more GPUs and specialized compute (Finding 3) while the capacity they already own sits substantially unused. The efficiency headroom in the current fleet is large — and largely unmeasured.

Finding 7: Spending fast, measuring slowly

Fewer than half rigorously track what their compute costs

We asked whether enterprises can quantify the cost and return of their AI infrastructure spend, and how satisfied they are with what they run. Confidence in the ledger lags the spending.

Measurement trails money. Fewer than half of enterprises (44%) rigorously track the cost and return of their AI compute; the majority track only partially (39%), cannot quantify it yet (20%), or have not prioritized it (6%). That gap is consequential given Finding 5, where total cost of ownership was the second-ranked buying criterion — enterprises are choosing providers on an economic basis they mostly cannot yet measure. Satisfaction with current infrastructure is moderately positive but not enthusiastic: on a five-point scale, overall satisfaction averages 4.0, with ease of implementation (3.8) and value for money (3.9) trailing slightly — the softness landing, tellingly, on cost. Enterprises are spending quickly and accounting slowly.

Finding 8: The next bottleneck few are watching

As inference shifts from compute to memory, the field scatters

Finally, we asked how enterprises would address the emerging constraint in large-scale inference — the shift from GPU compute to memory, specifically KV-cache capacity. The responses reveal a frontier that is not yet a priority.

The memory frontier is real but barely governed. Asked which approach they would rely on as the binding constraint in inference shifts from compute to memory bandwidth, enterprises scatter: Dell leads at 31%, Nvidia follows at 16%, and the rest fragments across storage vendors, open-source tooling, and model-level efficiency techniques. Most telling is that roughly one in five (18%) either do not recognize the constraint or have not begun to address it. For a shift that will reshape inference cost and architecture, this is an early and unsettled market — and, consistent with the measurement gap in Finding 7, one where many enterprises simply do not yet have a view. It is the next chapter of the compute gap, arriving before most have closed the current one.

The bottom line: A compute gap that faster spending will widen, not close

Organizations with more than 100 employees are investing in AI infrastructure faster than they can measure it. Most are still early in deployment, yet their spending intentions point past their current stack — toward specialized clouds and alternative accelerators almost none of them run today — and a clear majority intend to change providers within the year. They buy on integration and total cost of ownership rather than headline price, which is rational; the difficulty is that most cannot yet see those economics clearly.

The visibility gap is concrete. The GPUs enterprises already own run at half utilization or less for the overwhelming majority, and fewer than half can rigorously track what their compute costs or returns. Satisfaction is decent but unenthusiastic, softest on value for money — the dimension hardest to judge without measurement. And the next constraint, the shift from compute to memory in large-scale inference, is arriving while most enterprises are still unaware of it. At 107 respondents in a single Q2 wave this is a directional read, skewed toward the mid-market and earlier-stage adopters — but the direction is consistent: the appetite to spend is running well ahead of the instrumentation to spend well. The compute gap is not a capacity problem that more hardware will solve on its own; it is, first, a problem of seeing what the hardware already costs. The open question for later waves is whether enterprises build that visibility before the re-platforming arrives — or buy the next layer of infrastructure as blind to its economics as the last.

Based on survey responses from 107 qualified enterprise respondents (100+ employees), drawn from a single Q2 2026 (June) wave. Because this is one wave rather than a pooled multi-month sample, the results read cross-sectionally rather than as a month-over-month trend, and at 107 respondents this is a directional signal rather than a precise measurement — the sample is self-selected, skews mid-market, and leans toward earlier-stage adopters rather than the largest hyperscale operators. Respondents include managers, individual contributors, VPs/directors, and the C-suite, with buyer-credible purchasing authority, across Technology/Software, Healthcare/Life Sciences, Financial Services, Retail/E-commerce, and other industries.

Linux XFS has a decade-old race condition allowing full root access

Thu, 23 Jul 2026 17:59:07 +0200

Linux systems using the XFS filesystem suffer from a race condition that could enable an unprivileged local user to gain full root access.

The flaw affects systems with Linux kernel 4.11 or later that have enabled the XFS feature reflink, which permits the creation of copies of a file without actually copying its data.

According to Qualys Threat Research Unit (TRU), there was a way around the file write protections reflink depends on. The bypass has existed in kernel versions since 2017 before a patch was made available last week.

“Using this vulnerability, a process running as an ordinary, unprivileged user can trigger the flaw and gain the ability to overwrite any readable file on an XFS volume at the block layer,” Saeed Abbasi, head of Qualys TRU, said in a blog post about the vulnerability, which he calls RefluXFS. “Exploitation is highly reliable and leaves no kernel log output.”

Qualys estimated that the issue affects more than 16.4 million systems, primarily enterprise Linux deployments that use XFS with reflink enabled by default.

Race winner gets root in buggy file operation

The vulnerability, tracked as CVE-2026-64600, stemmed from the way XFS handles copy-on-write operations for reflinked files. Normally, when two files share the same storage block, as in the case of an original file and the reflinked clone, XFS allocates a new storage block before any data modification, so the original file remains unchanged.

However, a race condition occurs when two concurrent writes on the reflink file are initiated, confusing the filesystem into modifying the original file. “The change is made directly on disk, persists across reboots, and produces no kernel log output,” Qualys said in an advisory.

The issue is exploitable when Linux 4.11+, XFS with reflink enabled, and a shared filesystem layout are all present. It is assigned a high severity CVSS of 7.8 out of 10 as an exploit only needs read access to a target file before creating a reflink clone under a writable directory on the same XFS filesystem.

Linux distributions affected by RefluXFS

The vulnerability has been present in every mainline and stable Linux kernel since the release of version 4.11 in 2017, and requires no special capabilities or non-default configurations, Qualys said.

Affected Linux distributions include RHEL 8,9 and 10, CentOS Stream 8,9, and 10, Oracle Linux 8,9,10, Rocky and AlmaLinux 8,9, and 10, CloudLinux 8,9, and 10, Amazon Linux 2023 and Amazon Linux 2 AMIs from December 2022 onward, Fedora Server 31+, and Debian, Ubuntu and SUSE installations where XFS was manually selected.

Usual kernel hardening practices, including memory protection features like Kernel Address Space Layout Randomization (KASLR), Supervisor Mode Access Prevention (SMAP), and Supervisor Mode Execution Prevention (SMEP), are ineffective as they are all aimed at different attack surfaces. Even a kernel lockdown does nothing to stop the affected path, Qualys noted.

“SELinux doesn’t block the affected path in testing, and seccomp profiles are no barrier as long as they permit write and ioctl, which ordinary profiles do,” Abbasi explained. Immediate kernel patching and a full reboot are the only reliable mitigations, he added.

A fix was merged into the upstream Linux kernel source tree on July 16 as commit “2f4acd0,” after which Linux distributions began backporting the patch into their own supported kernel releases.

Organizations running affected XFS deployments should apply their Linux vendor’s latest kernel updates and reboot affected systems once fixed kernels become available.

Linux XFS has a decade-old race condition allowing full root access

Thu, 23 Jul 2026 17:58:50 +0200

Linux systems using the XFS filesystem suffer from a race condition that could enable an unprivileged local user to gain full root access.

The flaw affects systems with Linux kernel 4.11 or later that have enabled the XFS feature reflink, which permits the creation of copies of a file without actually copying its data.

Qualys estimated that the issue affects more than 16.4 million systems, primarily enterprise Linux deployments that use XFS with reflink enabled by default.

Race winner gets root in buggy file operation

Linux distributions affected by RefluXFS

A fix was merged into the upstream Linux kernel source tree on July 16 as commit “2f4acd0,” after which Linux distributions began backporting the patch into their own supported kernel releases.

Organizations running affected XFS deployments should apply their Linux vendor’s latest kernel updates and reboot affected systems once fixed kernels become available.

This article first appeared on Network World.

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Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite

Thu, 23 Jul 2026 16:59:29 +0200

Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite

Executive summary

United States National Security Agency (NSA)
United States Federal Bureau of Investigation (FBI)
Netherlands Defence Intelligence and Security Service (MIVD)
Netherlands General Intelligence and Security Service (AIVD)
United States Cybersecurity and Infrastructure Security Agency (CISA)
United States Defense Counterintelligence and Security Agency (DCSA)
United States Department of Defense Cyber Crime Center (DC3)
United States Department of the Treasury
United States Naval Criminal Investigative Service (NCIS)
Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)
Communications Security Establishment Canada’s (CSE’s) Canadian Centre for Cyber Security (Cyber Centre)
New Zealand National Cyber Security Centre (NCSC-NZ)
United Kingdom National Cyber Security Centre (NCSC-UK)
Czech Republic National Cyber and Information Security Agency (NÚKIB)¹
Danish Defence Intelligence Service (DDIS)²
Estonian Foreign Intelligence Service (EFIS)³
Finnish Defence Intelligence (FDI)⁴
Finnish Security and Intelligence Service (SUPO)⁵
French General Directorate for Internal Security (DGSI)⁶
French National Cybersecurity Agency (ANSSI)⁷
Italian External Intelligence and Security Agency (AISE)⁸
Italian Internal Intelligence and Security Agency (AISI)⁹
Security and Intelligence Service of the Republic of Moldova (SIS RM)¹⁰
Polish Foreign Intelligence Agency (AW)¹¹
The Military Counterintelligence Service of Poland (SKW)¹²
Spain National Intelligence Centre (CNI)¹³
Sweden National Cyber Security Centre (NCSC-SE)¹⁴

For a downloadable list of IOCs, see:

AA26-204A.stix.xml (STIX XML)
AA26-204A.stix.json (STIX JSON)

Cybersecurity industry tracking

LAUNDRY BEAR
Void Blizzard [2]
CL-STA-1114 [3]
TA488 (formerly UNK_PitStop) [4]

Background

Last 90 days of emails,
Email address,
Password [T1589.001],
Global Address List (GAL) [T1087],
Two-factor authentication (2FA) tokens, and
Newly-created Application Passcode [T1098].

Targeting details

LAUNDRY BEAR has targeted and compromised users in various organizations, including those associated with:

the Defense Industrial Base (DIB),
the federal and local government,
education,
energy,
law enforcement,
media,
non-governmental organizations, and
technology.

Technical details

Reconnaissance

Resource development

Flowerbed framework

Flowerbed is a Python project that uses Docker for containerization. The project includes four different Docker containers:

Catcher,
Certbot,
Nginx, and
Gardener.

Initial access

Figure 1: Example of malicious email

Figure 2: Headers from an example malicious email

sendStartPing,
gather_email,
gather_environment,
gather_2fa_codes,
gather_app_password,
gather_device_status,
gather_oauth_consumers,
gather_autocomplete_password,
enable_mail_protocols,
gather_gal,
sendArchives, and
sendFinishPing.

Figure 3: Malicious payload of example email

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 [T1587].

Persistence and credential access

Figure 4: First illegitimate login HTML element

Figure 5: Second illegitimate login HTML element

Collection

**Table 1: Additional SOAP commands used**
SOAP Command	Namespace	Stage
GetInfoRequest	zimbraAccount	gather_environment
GetDeviceStatusRequest	zimbraSync	gather_device_status
GetOAuthConsumersRequest	zimbraAccount	gather_oauth_consumers
SearchGalRequest	zimbraAccount	gather_gal

**Table 2: ZCS webmail client types**
Indicator	Client Type	Associated Value
?client=advanced	Advanced	c
/h/	Standard	h
/modern/	Modern	m

Exfiltration

DNS exfiltration

Figure 6: Structure for information exfiltrated by DNS

**Table 3: DNS exfiltration**
Type of Information	Exfiltration Stage	Data Type
Victim’s Email Address	gather_email	e
Client Type	gather_environment	c
Zimbra Version	gather_environment	v
URL at Time of Exploitation	gather_environment	url
2FA Scratch Codes	gather_2fa_codes	2fa
Newly Created Application Password	gather_app_password	pa
Harvested Autocomplete Password	gather_autocomplete_password	pw

HTTPS exfiltration

**Table 4: HTTPS exfiltration types**
Content Type	URL Path
application/json	/v/p
application/octet-stream	/v/d

Figure 7: Structure for information exfiltrated by HTTPS

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.

Table 5 provides a summary of the JSON-based exfiltration.

**Table 5: HTTPS JSON exfiltration**
Type of Information	Exfiltration Stage	JSON Key(s)
Victim’s Email Address	gather_email	email
Client Type, Version, and Current URL	gather_environment	client, version, full_url
Newly Created Application Password	gather_app_password	app_password
Harvested Autocomplete Password	gather_autocomplete_password	autocomplete_password

**Table 6: HTTPS binary exfiltration**
Type of Information	Exfiltration Stage	X-Filename Header
SOAP request for GetInfoRequest	gather_environment	zimbra_batch_analytics.json
SOAP request for GetScratchCodesRequest	gather_2fa_codes	zimbra_batch_analytics.json
SOAP request for GetDeviceStatusRequest	gather_device_status	zimbra_batch_analytics.json
SOAP request for GetOAuthConsumersRequest	gather_oauth_consumers	zimbra_batch_analytics.json
Victim Organization’s Global Address List	gather_gal	telemetry_{1-20}.json
Last 90 Days of Victim’s Emails	sendArchives	telemetryData_{0-89}.json

Catcher

However, if a query includes a domain formatted as shown in Figure 6 and Figure 7, the service saves a log file in JSON format to disk containing the following details of the DNS query:

Time of query,
Source IP address for query,
Queried domain, and
Type of query.

Time,
Source IP address,
Request method,
Host,
Path,
Query string,
Headers, and
Base64 payload.

Figure 8: Command used for automated directory cleanup

Response strategies

Mitigations

Significant amounts of outbound data being sent to IPs associated with VPS providers not used by the organization [D3-NTA];
Frequent DNS queries for a suspicious domain with seemingly random subdomains [D3-DNSTA];
A sudden spike of connections to a server associated with a recently established domain [D3-NTCD]; and
Connections to internal services, such as webmail, from VPN providers frequently leveraged by this group for nefarious activity, such as Mullvad VPN [D3-NTCD].

Indicators of compromise (IOCs)

Flowerbed infrastructure

**Table 7: Flowerbed server infrastructure**
Domain	IP Address	First Seen	Last Seen
zmailanalytics[.]com	216.252.238[.]104	8 July 2025	15 October 2025
zimbra-metadata[.]com	216.252.238[.]18	20 August 2025	14 October 2025
analyticemailmeter[.]com	37.120.247[.]228	24 September 2025	18 March 2026
emailanalytics.com[.]ua	185.86.79[.]95	24 September 2025	18 March 2026
mailnalysis[.]com	104.248.134[.]194	11 November 2025	17 February 2026
zimbrastat[.]com	64.226.124[.]190	18 December 2025	18 March 2026
zimbrasoft.com[.]ua	193.238.152[.]66	20 January 2026	18 March 2026
synacorzimbra[.]nl	216.252.238[.]64	3 February 2026	30 March 2026
istc-cloud[.]com	194.156.103[.]193	5 February 2026	30 March 2026

**Table 8: Flowerbed X.509 certificate SHA-1 hashes**
Associated Domain	X.509 SHA-1 Hash	First Seen	Last Seen
zmailanalytics[.]com	2e4f314bc9943cab5005d6fde0b271c74d47bc9d	8 Jul 2025	6 Aug 2025
*.i.zmailanalytics[.]com	50a87d926621dd06389ba50d86e0ff574ed713a8	6 Aug 2025	13 Oct 2025
*.i.zimbra-metadata[.]com	c5a72420e7bb308d078e62128430897f82194c95	20 Aug 2025	14 Oct 2025
*.i.analyticemailmeter[.]com	8959c4d29e29f02ea94ea8bb21c8df2594c5549d	24 Sep 2025	8 Nov 2025
*.i.emailanalytics.com[.]ua	62eb76432597694edb01c1fe57aab0cfe03a7178	25 Sep 2025	27 Sep 2025
*.i.mailnalysis[.]com	cddf5c3be1e07f28140aed165b929bf2d614922a	12 Nov 2025	17 Dec 2025
*.i.zimbrastat[.]com	18b3ad442ce73cc8656d51d75bbd7c855f2cb7e8	18 Dec 2025	28 Dec 2025
*.i.zimbrasoft.com[.]ua	1b25041ececf2457eef0270fc1d785cec8ec9ded	21 Jan 2026	10 Feb 2026
*.i.synacorzimbra[.]nl	e4fe6466a4f9a4249fe330651e914e45bbdca44a	5 Feb 2026	22 Mar 2026
*.i.istc-cloud[.]com	b6b77c9a455225d525834a403ca9ef5481ed0447	12 Feb 2026	30 Mar 2026

LAUNDRY BEAR has used the following email addresses to procure resources used for this campaign:

ivanka.zurabishvili@proton[.]me,
zmul1@buildandconsulting[.]com,
garrysmithme@pinmx[.]net, and
hostingclient@pinmx[.]net.

Phishing distribution

The following email addresses have distributed payloads attributed to this campaign:

c.laurent.ejfa@proton[.]me,
j.moreau.epsc@proton[.]me,
liberty.insights@proton[.]me,
certain email addresses (presumably compromised) at the isofts.kiev[.]ua domain (i.e., ending with @isofts.kiev[.]ua), and
certain email addresses (presumably compromised) at the navs.edu[.]ua domain (i.e., ending with @navs.edu[.]ua).

Additionally, the following are SHA-256 hashes of email samples containing the malicious payload attributed to this campaign:

98df604ecc57f884a2e6ce3266a0013ad64455cac48442c2312cfa4765007aaf,
60db9abae75cd8ccc49dd7ea5feb41677566dcd442f12ebc5745ffd2810fb874,
b1f5beb1175fc5c7d1806a2f0d900eb124c54f0286c5c52b66eea7a6633adb1d, and
1517b3caa495f6c4e832df9c75fc94667e3c233773f7fa4e056d5e30e5ead760.

Post-compromise artifacts

Many SearchGalRequest command requests from a single user over a short period of time;
Use of the CreateAppSpecificPasswordRequest command, especially in cases where it is creating an Application Passcode named “ZimbraWeb”; and
Use of the GetScratchCodesRequest command.

Remediation

Works cited

[3] Palo Alto Networks Unit 42. Russian Global Webmail Espionage. 2026. https://unit42.paloaltonetworks.com/russian-webmail-espionage/

[4] Proofpoint. TA488 Targets Zimbra Mailservers with Half-Click Exploits. 2026. https://www.proofpoint.com/us/blog/threat-insight/ta488-zcs-exploit

[5] Seqrite. Operation GhostMail: Russian APT exploits Zimbra Webmail to Target Ukraine State Agency. 2026. https://www.seqrite.com/blog/operation-ghostmail-zimbra-xss-russian-apt-ukraine/

Footnotes

Acknowledgements

The authoring agencies acknowledge the contributions to this advisory from Palo Alto Networks Unit 42 and Proofpoint.

Disclaimer of endorsement

Purpose

Contact

United States organizations

National Security Agency
Cybersecurity Report Feedback: CybersecurityReports@nsa.gov
Defense Industrial Base Inquiries and Cybersecurity Services: DIB_Defense@cyber.nsa.gov
Media Inquiries / Press Desk: NSA Media Relations: 443-634-0721, MediaRelations@nsa.gov
Cybersecurity and Infrastructure Security Agency
CISA’s 24/7 Operations Center (contact@cisa.dhs.gov), or by calling 1-844-Say-CISA (1-844-729-2472).
Federal Bureau of Investigation
If you or someone you know has fallen victim to this campaign, file a complaint with IC3.
Defense Counterintelligence and Security Agency
DCSA Counterintelligence, Cyber Mission Center, Cyber Threat Operations Branch: DCSA.CI.CyberOps@mail.mil
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.
Media/Public Inquiries: dcsa.quantico.dcsa-hq.mbx.pa@mail.mil
Department of Defense Cyber Crime Center
Defense Industrial Base Inquiries and Cybersecurity Services: DC3.DCISE@us.af.mil
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 https://dibnet.dod.mil
Media Inquiries / Press Desk: DC3.Information@us.af.mil
Naval Criminal Investigative Service
To report criminal activity impacting the United States Navy, go to www.ncis.navy.mil and click “Submit a Tip”

Dutch organizations

Defence Intelligence and Security Service (MIVD): https://www.defensie.nl/onderwerpen/m/militaire-inlichtingen-en-veiligheid
General Intelligence and Security Service (AIVD): https://www.aivd.nl

Australian organizations

Australian Signals Directorate
Visit cyber.gov.au or call 1300 292 371 (1300 CYBER 1) to report cybersecurity incidents and access alerts and advisories.

Canadian organizations

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.
Report an incident or suspicious activity to the Cyber Centre by email at contact@cyber.gc.ca, online via the reporting tool Report a cyber incident - Canadian Centre for Cyber Security or by phone at 1-833-CYBER-88 (1-833-292-3788).

New Zealand organizations

New Zealand National Cyber Security Centre (NCSC-NZ): info@ncsc.govt.nz

United Kingdom organizations

Report significant cyber security incidents to ncsc.gov.uk/report-an-incident (monitored 24/7)

Estonia organizations

Estonian Foreign Intelligence Service (EFIS): info@valisluureamet.ee

Finnish organizations

Finnish Security and Intelligence Service: supo.fi/en/contact

French organizations

French organizations are encouraged to report suspicious activity or incident related information found in this advisory by contacting ANSSI/CERT-FR at: cert-fr@ssi.gouv.fr or by phone at: 3218 or +33 9 70 83 32 18.

Italian Organizations

Italian External Intelligence and Security Agency (AISE):
Visit https://www.sicurezzanazionale.gov.it/
Italian Internal Intelligence and Security Agency (AISI):
Visit https://www.sicurezzanazionale.gov.it/

Moldovan organizations

Security and Intelligence Service of the Republic of Moldova (SIS RM): cybersec@sis.md

Polish organizations

Polish Foreign Intelligence Agency (AW): ctiteam@aw.gov.pl

Appendix A: MITRE ATT&CK tactics and techniques

See Table 9 through Table 19 for all the threat actor tactics and techniques referenced in this advisory.

**Table 9: Reconnaissance**
Technique Title	ID	Use
Gather Victim Identity Information: Credentials	T1589.001	The payload attempts to intercept a victim’s password from their password manager.
Gather Victim Identity Information: Email Addresses	T1589.002	The payload attempts to grab the victim’s email address from various data stores.
Search Open Websites/Domains	T1593	This group likely leverages public information to support target development.
Active Scanning	T1595	Port scanning can be used by this group to assist with determining exploitability of identified targets.
Search Open Technical Databases: Scan Databases	T1596.005	Various public datasets can provide information to support discovery of exploitable targets.
Search Closed Sources	T1597	Previously exfiltrated data can be used to enhance target development efforts.
Search Closed Sources: Purchase Technical Data	T1597.002	Commercial datasets can also be used to support target development efforts.

**Table 10: Resource Development**
Technique Title	ID	Use
Acquire Infrastructure	T1583	This group used Mullvad VPN to anonymize traffic sent to operational infrastructure.
Acquire Infrastructure: Virtual Private Server	T1583.003	This group procured VPS servers from a variety of vendors.
Develop Capabilities	T1587	The Ulej capability was developed likely for use by this group to conduct spear phishing campaigns.
Develop Capabilities: Malware	T1587.001	Development of a novel payload that steals a victim’s emails and other sensitive account information.
Develop Capabilities: Exploits	T1587.004	Development of a novel, at the time, cross-site-scripting (XSS) exploit that enables execution of arbitrary JavaScript.
Obtain Capabilities: Tool	T1588.002	Open source tools, such as Evilginx2, have also been used by the group.
Obtain Capabilities: Artificial Intelligence	T1588.007	The group appears to have leveraged AI to support development efforts.
Stage Capabilities	T1608	Flowerbed is deployed to a procured server in the cloud.

**Table 11: Initial Access**
Technique Title	ID	Use
Valid Accounts	T1078	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.
Trusted Relationship	T1199	The group sends malicious payloads to targeted individuals using previously compromised accounts that might have an established relationship with the target.
Phishing	T1566	The actors used spear phishing to lure users into opening malicious email.

**Table 12: Execution**
Technique Title	ID	Use
Exploitation for Client Execution	T1203	An XSS vulnerability was leveraged to execute the JavaScript payload.

**Table 13: Persistence**
Technique Title	ID	Use
Account Manipulation	T1098	Enabling IMAP and Application Passcodes provides persistent access to the compromised account.
Modify Authentication Process: Multi-Factor Authentication	T1556.006	Creating Application Passcodes to bypass 2FA and stealing a user’s “Scratch Keys,” which can be used in place of a 2FA token.

**Table 14: Privilege Escalation**
Technique Title	ID	Use
Valid Accounts	T1078	This actor has used commercial datasets to acquire account credentials and gain unauthorized privileged access to accounts.

**Table 15: Stealth**
Technique Title	ID	Use
Obfuscated Files or Information: Command Obfuscation	T1027.010	Obfuscated JavaScript payload sent to targets to exploit the XSS vulnerability.
Obfuscated Files or Information: Encrypted/Encoded File	T1027.013	The JavaScript payload included both a Base64-encoded and XOR-encrypted inner payload.
Obfuscated Files or Information: SVG Smuggling	T1027.017	The payload was contained in an “onload” attribute within an SVG image included in the malicious email.
Use Alternate Authentication Material: Web Session Cookie	T1550.004	Previous campaigns using AiTM leveraged stealing and use of a victim’s session cookies to authenticate.

**Table 16: Credential Access**
Technique Title	ID	Use
Modify Authentication Process: Multi-Factor Authentication	T1556.006	Creating Application Passcodes to bypass 2FA and stealing a user’s “Scratch Keys,” which can be used in place of a 2FA token.
Adversary-in-the-Middle	T1557	Previous campaigns used Evilginx2 as an AiTM toolkit to intercept credentials and session cookies.

**Table 17: Collection**
Technique Title	ID	Use
Data Staged: Remote Data Staging	T1074.002	Exfiltrated data was sent to an actor-controlled VPS prior to assumed long-term storage solutions.
Email Collection	T1114	This group has emphasized collection of emails.
Email Collection: Remote Email Collection	T1114.002	Emails are collected via API calls to the ZCS mail server and are not collected from emails stored directly on the victim’s device.
Automated Collection	T1119	Upon execution, the JavaScript payload automatically collects all relevant information in stages.
Browser Session Hijacking	T1185	The JavaScript payload leverages the user’s authenticated browser session to make API requests as the user.
Archive Collected Data	T1560	Emails are exfiltrated with GZIP compression.

**Table 18: Discovery**
Technique Title	ID	Use
Account Discovery	T1087	Stolen Global Access Lists provide the group with new users to target.

**Table 19: Exfiltration**
Technique Title	ID	Use
Exfiltration Over Alternative Protocol	T1048	Victim information was exfiltrated over both HTTPS and DNS.
Exfiltration Over Alternative Protocol: Exfiltration Over Asymmetric Encrypted Non-C2 Protocol	T1048.002	Some payloads, especially ones with large amounts of data, were exfiltrated over HTTPS.
Exfiltration Over Alternative Protocol: Exfiltration Over Unencrypted Non-C2 Protocol	T1048.003	Some smaller bandwidth payloads were exfiltrated over DNS using Base32 encoding.

Appendix B: MITRE D3FEND countermeasures

See Table 20 for a mapping of several of the cybersecurity countermeasures mentioned in this advisory.

**Table 20: MITRE D3FEND Countermeasures**
Countermeasure Title	ID	Description
Application Hardening	D3-AH	Organizations should immediately prioritize patching CVE-2025-66376. Organizations should promptly apply software updates to all email systems.
Isolate	d3f:Isolate	Organizations that cannot feasibly patch should use alternative mail clients.
Credential Hardening	D3-CH	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.
Network Traffic Analysis	D3-NTA	Organizations should monitor for significant amounts of outbound data being sent to IPs associated with VPS providers not used by the organization.
DNS Traffic Analysis	D3-DNSTA	Organizations should monitor for frequent DNS queries to a suspicious domain for seemingly random subdomains.
Network Traffic Community Deviation	D3-NTCD	Organizations should monitor for a sudden spike of connections to a server associated with a recently established domain. Organizations should monitor for connections to internal services, such as webmail, from VPN providers.
Identifier Activity Analysis	D3-IAA	Organizations should search for the listed known IOCs.
Process Analysis	D3-PA	Organizations should search ZCS log files for specific commands used by the malicious script. Organizations should search the localStorage property in web browsers for the ZCS webmail client for “ZimbraWeb” Application Passcodes.
Message Analysis	D3-MA	Organizations that suspect they have victims of this campaign should search for emails with a malicious payload to identify other victims.

[$] An operations structure for swap devices

Thu, 23 Jul 2026 16:29:33 +0200

One of the ideas raised at the 2026 Linux Storage, Filesystem, Memory Management, and BPF Summit (LSFMM+BPF) was the creation of an operations structure for the swap subsystem. Like many parts of the kernel, the swap layer evolved over time, with pieces being added as needed; the end result of this evolution is rarely what one would expect had the subsystem been designed today. The interface between the swap layer and the devices it uses is just one example. It appears that one result of the swap subsystem's evolution — the lack of an abstraction layer to interface with underlying storage — will soon be addressed, but in a different way than was initially envisioned.

Despite tough quarter, IBM says mainframe will continue to put the Big in Big Blue

Thu, 23 Jul 2026 16:27:23 +0200

Revenue from IBM’s z mainframe portfolio declined 42% in the quarter ended June 30, dragging infrastructure revenue down 7% compared to the year-ago quarter. But Big Blue executives remain positive on the mainframe’s role as an important AI platform.

After warning of an earnings shortfall, IBM lowered its full-year forecast. It now expects 2026 revenue to grow between 4% and 5%, rather than its previous forecast of more than 5% growth. Some parts of its business did well: Software revenue grew 5% in the second quarter to $7.76 billion, fueled by 11% growth in hybrid cloud, 18% growth in data, and 3% growth in automation.

On the infrastructure side, IBM posted second-quarter revenue of $3.8 billion, which is down 7%. Within that business, distributed infrastructure grew 37%, but those gains were offset by a 10% decline in hybrid infrastructure and IBM Z’s 42% drop.

In a July 14 letter to investors released prior to IBM’s July 22 earnings call, CEO Arvind Krishna warned of the earnings shortfall and laid out current challenges. He related the infrastructure performance shortfall to “wrapping on the launch of z17 in the second quarter” and stated: “Given this was the strongest start to a mainframe program in our history, we expected Infrastructure revenue to decline low-single digits for the year, beginning this quarter. What played out was worse than our expectations, driven by a shortfall in our Z performance and the associated software stack, primarily in Transaction Processing.”

In the last few weeks of June, customers shifted capex spending and started purchasing more AI infrastructure components in the form of servers, storage, and memory “to secure supply-constrained infrastructure ahead of expected price increases,” Krishna stated. “This dynamic impacted client buying patterns. While we anticipated some supply chain related impact in our expectations, we did not anticipate the magnitude of the capex reprioritization.”

Yet despite challenges this last quarter, z17 remains at nearly 130% growth program-to-program, according to IBM. That’s “well ahead of z16, which was our strongest program on record, with clients representing 85% of installed MIPs maintaining or growing capacity,” the July 14 letter stated.

Mainframe infrastructure momentum is expected to continue, and IBM is anticipating strong workload growth and AI-driven capacity expansion as clients modernize mission-critical systems and emphasize resiliency and security, Krishna said during the company’s Q2 2026 earnings call on July 22.

“AI is driving incremental capacity growth and new workloads as clients look to run AI closer to their most sensitive data,” IBM senior vice president and CFO James Kavanaugh said in the call. “We are seeing strong early adoption of our AI innovations with nearly 50% of z17 customers investing in AI capabilities with Spyre AI accelerator, and clients deploying Watson X Code Assistant for Z are growing MIPS capacity three times faster than those who are not.”

“In a world where infrastructure costs are rising and efficiency matters more than ever, IBM Z offers a compelling economic advantage,” Kavanaugh continued. “Depending on the size and complexity of workloads, clients can realize a 2 to 15x total cost of ownership benefit versus moving these workloads off the platform, reinforcing why the platform remains central to their operations and positioning us to capture additional value as AI workloads grow.”

“We see no evidence of clients moving off mainframe,” Kavanaugh added. “Clients continue to invest in IBM Z to modernize mission-critical workloads with a focus on resiliency and security.”

In responding to an analyst question, Kavanaugh said three key things drive mainframe demand and purchasing requirements:

“One is capacity workload. It’s the most important determinant. 85% Of the installed MIPS capacity out there in the marketplace today running all those core mission critical workloads are either stable or growing. Clients are adding capacity and workload to mainframe, the viability. And by the way, that’s coming in new AI workloads, analytics workloads, Linux-based workloads, and those MIPS are growing program to date over 15 to 20% installed capacity,” Kavanaugh said.

Number 2 is economic factors. “We don’t talk a lot about this, but I think it’s important for our investors to understand things like total cost of ownership. Depending on the size and complexity of the workload, we have anywhere from a 2 to a 15x TCO advantage running on the mainframe [over smaller server systems]. Again, we do not see any evidence of clients migrating off mainframe and lease propensity, which is a great indicator,” Kavanaugh said.

The third driver is AI. “When you look at it, applications, data security, all on the platform, we do 450 billion inferences per day at 1 millisecond with 8 nines availability,” Kavanaugh said. “We’ve got clients that have already purchased over 50% of our Spire inferencing, and those clients that have purchased that are growing MIPS capacity, the way [we monetize value], by over three times faster than others.”

MacBook Neo’s success wasn’t luck, it was a plan

Thu, 23 Jul 2026 15:22:56 +0200

It’s difficult to ignore the fact that Apple seems to have turned its MacBook Neo into a weapon to promote platform growth, with enough performance under the hood to make competitors seem inferior.

And even as the PC industry moves to try to compete with Apple’s last huge Mac success, the company is already planning a powerful follow-up.

The numbers don’t lie

“Apple’s recent price increase seems to be an inevitable response to these cost increases. In the second half of the year, other PC OEMs are expected to continue to raise prices, and the overall ASP increase is expected to continue,” Counterpoint said. The researcher tells us global PC shipments shrank 4% in the second quarter of 2026 as rising costs hit demand. The Mac maker, by contrast, moved in the opposite direction, generating 13% growth in the quarter — mainly on the back of the MacBook Neo introduction.

Recent IDC data gives Apple 10.1% year-over-year growth and just under 10% (9.9% to be exact) of the worldwide PC market, even as the overall market declined 4.9%.

Neo 2.0 is already coming

This was never about luck

This isn’t solely a market take about competition, it’s about planning.

You can follow me on social media! Join me on BlueSky, LinkedIn, Mastodon and subscribe to my daily Apple-related news summaries at The Core.

PSU Installation & Cable Management Made Easy 🖥️ Part 6: How To Build A PC For Beginners 🎮

Thu, 23 Jul 2026 15:21:48 +0200

Author: Shannon Morse - Bewertung: 8x - Views:41

⚡ It's time to power up the build! In this episode of my Beginner PC Build Series, we're installing the power supply (PSU), connecting motherboard and CPU power, routing SATA cables, and tackling one of the most satisfying parts of any PC build - cable management.

I'll explain what a power supply actually does, why wattage matters, what "fully modular" means, how to identify each cable, and my favorite cable management tips that make future upgrades and troubleshooting much easier.

Whether you're building your very first gaming PC or just need a refresher, this step-by-step guide will help you wire everything correctly and keep your build clean.

A huge thank you to ASUS and Kingston for partnering on this PC build series! ❤️

👍 If you're enjoying the series, don't forget to subscribe so you don't miss the next episode where we install the graphics card and finish wiring the entire system!

#PCBuild #GamingPC #CableManagement #PCBuilding #PowerSupply #ASUS #Kingston #CustomPC #DIYPC #BeginnerPCBuild

https://pcpartpicker.com/user/snubsie/saved/#view=Htk84D

📺 Watch the Full PC Build Series: https://www.youtube.com/playlist?list=PLeYHKbaShxTHQVUHZfM8_44pjyI9LLzfe

CPU: AMD Ryzen 9 9950X 4.3 GHz 16-Core Processor ($519.00 @ Amazon)
Amazon: https://amzn.to/3O70PIU
Best Buy: https://bestbuycreators.7tiv.net/YRWkZq
B&H: https://bhpho.to/3PjZZcr

CPU Cooler: Asus ROG Ryujin III ARGB Extreme 89.73 CFM Liquid CPU Cooler ($389.99 @ Amazon)
Amazon: https://amzn.to/4bkdodD
Best Buy: (similar option) https://bestbuycreators.7tiv.net/DyDM4q
B&H: https://bhpho.to/46EWdR4

Motherboard: Asus ROG STRIX X870-A GAMING WIFI ATX AM5 Motherboard ($234.99 @ Amazon)
Amazon: https://amzn.to/3NI9tO0
Best Buy: (similar option) https://bestbuycreators.7tiv.net/bORgn6
B&H: https://bhpho.to/4ubyfa7

Memory: Kingston FURY Beast RGB 64 GB (2 x 32 GB) DDR5-6400 CL32 Memory ($1359.99 @ Newegg - OOS) x 2
Amazon: https://amzn.to/49SZug7
Best Buy: (similar option) https://bestbuycreators.7tiv.net/2anB4G

Storage: Kingston NV3 2 TB M.2-2280 PCIe 4.0 X4 NVME Solid State Drive ($311.99 @ Amazon)
Amazon: https://amzn.to/4bSOyBO
Best Buy: https://bestbuycreators.7tiv.net/vPeg7N
B&H: https://bhpho.to/4bpm9m9

Storage: Kingston FURY Renegade G5 2.048 TB M.2-2280 PCIe 5.0 X4 NVME Solid State Drive ($424.99 @ iBUYPOWER)
Amazon: https://amzn.to/4pTv8QB
Best Buy: https://bestbuycreators.7tiv.net/N9AYrN
B&H: https://bhpho.to/40dqbYK

Video Card: Asus TUF GAMING OC GeForce RTX 5080 16 GB Video Card ($1699.99 @ B&H)
Amazon: https://amzn.to/3NNmKos
Best Buy: https://bestbuycreators.7tiv.net/GKrYLB
B&H: https://bhpho.to/46HyuQb

Case: Asus A31 ATX Mid Tower Case ($64.98 @ Amazon)
Amazon: https://amzn.to/4bTH8yd
Best Buy: (similar option) https://bestbuycreators.7tiv.net/7a3BZO
B&H: https://bhpho.to/4d3Fyu8

Power Supply: Asus TUF Gaming 1000G 1000 W 80+ Gold Certified Fully Modular ATX Power Supply ($179.99 @ Amazon)
Amazon: https://amzn.to/4qSDWHG
Best Buy: (similar option) https://bestbuycreators.7tiv.net/LKeYQO
B&H: https://bhpho.to/3N1pqPq

Case Fan: Asus TUF GAMING TF120 ARGB White 76 CFM 120 mm Fan ($14.99 @ Amazon)
Amazon: https://amzn.to/3YWIbG7
Best Buy: https://bestbuycreators.7tiv.net/QjVx5z
B&H: https://bhpho.to/4uaSzs9

Case Fan: Asus TUF Gaming TR120 ARGB 77.4 CFM 120 mm Fans 3-Pack ($68.54 @ Amazon)
Amazon: https://amzn.to/4rzKNpN
Best Buy: https://bestbuycreators.7tiv.net/55OBVD
B&H: https://bhpho.to/46KcvYO

Turning Cable Chaos Into Cable Management Dreams
00:42 What Does a Power Supply Do?
02:04 Why This Build Uses a 1000W PSU
03:12 Fully Modular Power Supplies Explained
04:10 Identifying Every Power Cable
05:16 Installing the PSU
06:42 Subscribe & Patreon Shoutout
07:33 Connecting the 24-Pin Motherboard Cable
08:36 CPU Power Connectors
09:53 Cable Routing Tips
11:02 SATA Power & Accessories
11:54 Cable Management Basics
13:07 Next Episode Preview

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Q&A: Google’s AI and computing chief talks about its shapeshifting data centers

Thu, 23 Jul 2026 14:55:21 +0200

Google’s AI offerings span its internal and cloud offerings. Its data centers are processing seven times more AI tokens compared to last year. To keep up, Google is upgrading its data-center hardware and software technologies at a faster clip. It plans to raise $80 billion to build new data centers. (See related story: Google transforms its data center architecture for agent era)

Network World spoke with Mark Lohmeyer, vice president and general manager of AI and computing at Google, about how the company’s infrastructure is keeping pace with AI demand.

Network World: What is the primary shift in infrastructure needs?

Mark Lohmeyer: We’ve seen the rise of agents and agentic use cases. Years ago, it was the chat phase: Ask a question, get an answer. Now we’re in the agentic era, where you express your intent, agents spin off multiple sub-agents, working in parallel, preserving state. This is a radical shift in what infrastructure needs to do; make them fast, cost effective, secure, reliable. We’re delivering infrastructure optimized for the age of agents.

NW: What’s the goal of the infrastructure buildout, and what should customers expect regarding costs?

ML: Ultimately, it’s about enabling customers with leading-edge capabilities and models at scale cost-effectively. With agents, inference transactions increase by 50x, 100x versus non-agentic workloads. We’re driving the cost per transaction down exponentially. In our latest platforms, we reduce the cost by almost 2x for the same work. Customers serve twice the number of users at the same cost, directly driving profitability.

NW: How are you addressing energy efficiency?

ML: Energy is a critical resource, and Google has optimized for years. We design data centers and compute [to drive] high PUE (power usage effectiveness). We introduced liquid cooling over five years ago, and these latest systems are all liquid cooled. For agentic workloads, CPUs come to the forefront… orchestrating agents, calling tools, doing evaluation loops in reinforcement learning. Our latest Axion-based CPU platform called N4A has energy efficiency and is significantly better than the prior generation and x86 comparables.

NW: How do you think about token efficiency as you build-out systems?

ML: Performance and efficiency gains are powered by co-design of the model and infrastructure. Gemini is trained on TPUs, primarily served on TPUs with high frontier model capability, in a token and cost-efficient way. This stems from co-design across the full stack.

NW: How do you project what infrastructure will be needed years in advance?

ML: Hardware cycles deliver a new next generation roughly every year, but design cycles are two years or more in advance. We work with DeepMind doing core research, to application teams taking models into production, to billions of users, to our team building infrastructure. We work upstream with DeepMind and application teams to understand what’s coming. Agents weren’t being broadly spoken of externally, but internally we had those insights around what they would need. That shows up in hardware design. We hit the timing right — these platforms are built for agents.

NW: What’s the eighth generation TPU platform?

ML: We deliver new platforms every year, and ones launched years ago are close to 100% utilized because demand for AI-optimized compute is high. The eighth-generation TPU platform is the first delivering two complete systems, from the chip all the way up to the network and storage and software, that are optimized.

TPU-8t is optimized for training, and TPU-8i is optimized for inference. For TPU-8i, we increased SRAM on the chip to 384MB — three times the prior generation — and increased the HBM by 50%.

NW: How are you approaching GPU and TPU compatibility?

ML: People in a single cluster do not commingle GPUs and TPUs. We offer both options based on specific workload needs. We’ve been investing on the TPU side in using software frameworks customers are comfortable with on GPUs and enabling those on TPUs. For example, PyTorch and vLLM. Customers could have a pool of GPUs and TPUs, running vLLM on top of that. Start with a workload on TPUs, but if the TPU pool is fully utilized, spill to GPUs or vice versa. This works because it’s all leveraging the same compatible software layer on top.

NW: How has the orchestration platform changed for agents?

ML: Kubernetes is becoming the orchestration platform of choice for AI. Google is transforming GKE [Google Kubernetes Engine] into an agent-native orchestration solution. When expressing intent to an agent and it spins up multiple sub-agents, compute needs to spin up rapidly — TPUs or GPUs — without long delays, then run and spin back down. We’re optimizing at every layer of the GKE stack: significantly improving node startup time and how rapidly we start and stop containers. Lovable demonstrates this with GKE, spinning up hundreds of sandboxes for live coding sessions on their platform in parallel, paying for infrastructure when needed.

NW: What is the role of the network and storage infrastructure?

ML: The network is critical for AI. This requires creating large-scale clusters of GPUs or TPUs and enabling them to talk to each other in a high-performance way. We created the Virgo network — a collapsed network architecture, non-blocking within a data center, where multiple pods or NVLink72 domains connect together.

In TPU8T, we can connect over a million TPUs together leveraging Virgo, creating large-scale, high-performance, reliable clusters that shrink innovation cycles. Storage is equally critical. In large-scale clusters, something is always failing. The ability to take snapshots and go back to a checkpoint is important.

We’ve introduced Managed Lustre 10T, with 10 terabytes per second of bandwidth, 18 petabytes of storage in single clusters. This is 10 times faster than last year and 20 times faster than competition. We have Rapid Bucket, low-latency storage backed by Google storage systems. Both are impactful in large-scale training environments.

NW: How does KV cache strategy differ between training and inference?

ML: For TPU-8i, we increased SRAM on the chip to 384 megabytes — three times the prior generation — and increased the HBM by 50%. Storing KV cache directly in chip memory allows responding to inference requests much more rapidly and cost-effectively than going to an external system. For inference workloads, storing as much KV cache as possible on-chip is critical.

We’re introducing a dedicated KV cache storage subsystem that works across GPUs and TPUs. As KV caches get larger, being able to fall back to this dedicated subsystem becomes critical. Loading model weights rapidly is important in dynamic inference environments where accelerators switch between models hour by hour.

Google transforms its data center architecture for agent era

Thu, 23 Jul 2026 14:23:05 +0200

Google’s data center team is racing to turn its infrastructure into a well-oiled machine for AI and the onslaught of agents. At this year’s Google I/O, CEO Sundar Pichai shared startling numbers: Google’s data centers processed about 3.2 quadrillion tokens a month, roughly seven times more than the 480 trillion processed in May 2025.

“Multiple agents work together, and now you’ve got millions, billions of users around the world potentially spinning off agents to help them do things,” said Mark Lohmeyer, vice president and general manager for AI and computing infrastructure at Google.

Google’s new data-center blueprint includes updated hardware, software, and orchestration layers to keep always-running agents operational.

In the LLM era, users sent prompts and received responses, and Google’s infrastructure was designed for latency and throughput. But agents could increase inference transactions by up to 100 times non-agentic workloads, Lohmeyer said. Google’s redesigned AI data-center stack has the elasticity for agents to be widely distributed, run for long periods, and make decisions independently.

“We’re delivering new platforms every year, each one optimized for what we think the world is going to need for the age of agents going forward,” Lohmeyer said.

Efficient data flow is key so agents can act, reason, and decide faster.

Google adjusted the Google Kubernetes Engine into an agent-native environment, where agents could be quickly spun up in sandboxes and containers. “From an infrastructure perspective, you need to spin up a bunch of TPUs or GPUs very rapidly. Then you need to be able to run them and spin them back down,” Lohmeyer said.

Google also made drastic improvements to its silicon to support its middleware changes. It recently introduced new AI chips, with the TPU-8t for training, and TPU-8i for inference. The 8t chip has three times more computing power than the previous-generation Ironwood chip. The 8i chip has 384 megabytes of SRAM and 288GB of HBM3e memory, which is 50% more than the previous-generation chip.

The platform is optimized for KV cache (key-value cache), which stores important contextual information needed by agents to make decisions, which reduces the round trips to other memory and storage systems. “Being able to store more of the KV cache directly on the chip allows you to respond much more rapidly and cost-effectively,” Lohmeyer said.

A new CPU called Axion N4A is more power efficient at agentic workloads such as orchestration and tool calling, Lohmeyer said.

Google also made many network and storage improvements to cut training and inference time. A new technology called TPUDirect can move data from storage directly into the memory of the TPU quickly by bypassing any orchestration overhead, Lohmeyer said.

A networking technology called Virgo can coordinate 1 million TPUs across a widely distributed network. It can also link up GPUs such as Nvidia’s latest CPU-GPU package called Vera Rubin. “In the case of Vera Rubin, we’ll be able to connect up to 960,000 GPUs leveraging Virgo,” Lohmeyer said.

A new technology called Pathways is a distributed training framework that efficiently scales machine learning across millions of TPUs and GPUs. Pathways solves bottleneck issues typically associated with JAX, and both help coordinate across wide networks.

“The software to orchestrate these large-scale distributed training jobs is also just as important as the hardware that it runs on top of,” Lohmeyer said.

Weighing Google’s AI data-center stack

Google is the only provider with its own data centers, software, hardware and models, said Jack Gold, principal analyst at J. Gold Associates. Google can optimize each on a regular cadence, which “many data centers can’t easily afford given the high cost of new chips,” Gold said.

Google’s stack may not be best for every data center need compared to Nvidia’s general-purpose GPUs, CPUs, and networking. AWS and Microsoft are also creating their chips.

“There is no real risk of Nvidia being replaced by Google in a big way. But with an ever-expanding market, there is plenty of room for all players,” Gold said.

But Logan Wolfe, partner at Kyndryl’s global AI strategy and sovereign transformation, advised enterprises to adopt a multi-cloud strategy to reduce risk from system failures, however superior an infrastructure may be. “I think that kind of hybrid and liquid infrastructure, we’re definitely getting there,” Wolfe said.

The cost per token varies depending on the provider of inference, whether that’s Microsoft, Google, OpenAI or Anthropic. That will matter as AI moves from experimentation to a powerful tool that drives business changes.

“Ultimately it really comes down to how much money are we spending on AI to move a certain business outcome,” Wolfe said.

Understanding the AI economy

Thu, 23 Jul 2026 12:04:39 +0200

We’re releasing the first Activity, Task, Landscape, and Adoption Study (ATLAS) report, showing how people use Google’s AI tools.

Introducing selfie for sign-in: a new, easy way to access your Google Account

Thu, 23 Jul 2026 12:04:37 +0200

Selfie video gives you more options if you’re ever locked out or don’t have access to your usual phone or computer.

New Release: Tails 7.10

Thu, 23 Jul 2026 11:24:32 +0200

New features

New shutdown procedure

Tails now uses the standard shutdown procedure from GNOME.

The standard shutdown procedure is a bit slower, but better prevents data loss.

For example, the Power Off confirmation dialog informs you if an application needs to be closed or an open document needs to be saved before shutting down.

Even without confirming or saving the open documents, Tails will shut down after 60 seconds.

You can still use the faster emergency shutdown as before.

Celluloid video player

We replaced GNOME Videos with Celluloid , a more modern and reliable video player.

For added security, Celluloid cannot access the network. You can either:

Open online videos, like MP4 and AVI files, in Tor Browser.
Open online streaming addresses, like IPTV and HLS addresses, in VLC , installed as additional software.

Celluloid doesn't work on some computer from 2011 or earlier.

You can use VLC instead, installed as additional software.

Changes and updates

Update Tor Browser to 15.0.19.
Update some firmware packages. This improves support for newer hardware: graphics, Wi-Fi, and so on.

For more details, read our changelog.

Get Tails 7.10

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.10.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.10 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.10 directly:

Support and feedback

For support and feedback, visit the Support section on the Tails website.

Tails 7.10

Thu, 23 Jul 2026 11:07:50 +0200

New features

New shutdown procedure

Tails now uses the standard shutdown procedure from GNOME.

The standard shutdown procedure is a bit slower, but better prevents data loss.

For example, the Power Off confirmation dialog informs you if an application needs to be closed or an open document needs to be saved before shutting down.

Even without confirming or saving the open documents, Tails will shut down after 60 seconds.

You can still use the faster emergency shutdown as before.

Celluloid video player

We replaced GNOME Videos with Celluloid, a more modern and reliable video player.

For added security, Celluloid cannot access the network. You can either:

Open online videos, like MP4 and AVI files, in Tor Browser.
Open online streaming addresses, like IPTV and HLS addresses, in VLC, installed as additional software.

Celluloid doesn't work on some computer from 2011 or earlier.

You can use VLC instead, installed as additional software.

Changes and updates

Update Tor Browser to 15.0.19.
Update some firmware packages. This improves support for newer hardware: graphics, Wi-Fi, and so on.

For more details, read our changelog.

Get Tails 7.10

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.10.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.10 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.10 directly:

USN-8575-2: Linux kernel vulnerabilities

Thu, 23 Jul 2026 10:31:09 +0200

USN-8576-2: Linux kernel (NVIDIA Tegra) vulnerabilities

Thu, 23 Jul 2026 10:31:00 +0200

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)

iOS 27 Public Beta 2 Now Available, Here’s How to Install It and What’s New

Thu, 23 Jul 2026 08:17:16 +0200

Apple has released iOS 27 public beta 2 for compatible iPhones, one week after the first public beta arrived. The update includes several interface improvements, new controls, and fixes based on feedback from early testers. Since this is pre-release software, some apps and features may not work properly. Back up your iPhone before installing the update, and consider using a secondary device if possible. How to Install iOS 27 Public Beta 2 Follow these steps if your iPhone is already enrolled in the public beta program: Open the Settings app. Select General. Tap Software Update. Select Beta Updates. Make sure iOS 27 Public Beta is selected. Return to the previous screen. Tap Update Now when iOS 27 public beta 2 appears. Users who have not joined the beta program must first register their Apple Account through the Apple Beta Software Program. The Apple Account used for registration should match the one connected to the iPhone. Keep the iPhone connected to Wi-Fi and make sure it has enough battery power before starting the installation. What’s New in iOS 27 Public Beta 2 The second public beta mainly focuses on smaller improvements and refinements rather than major new features. New Siri AI introduction screen: Siri AI now displays an introductory screen that explains its main capabilities and privacy features when users open it for the first time after updating. More Siri voice options: Apple has added more English accents and voices for Siri AI. The settings also include additional controls for adjusting the length of content previews inside the Siri app. Photos zoom setting: A new Zoom Photos to Fill option allows pictures to automatically fill the screen based on the iPhone’s display ratio. Automatic TV episode downloads: The TV app can automatically download upcoming episodes from shows in Continue Watching. It can download the next two episodes and remove watched downloads to save storage space. AirPods adaptive audio control: Control Center now includes a slider for adjusting the balance between noise cancellation and transparency when using supported AirPods models. Per-network Connectivity Assist setting: Users can disable Connectivity Assist for individual Wi-Fi networks instead of turning it off for every connection. ProRes Log option: Supported iPhone models now offer an additional ProRes Log format setting when ProRes recording is enabled. Recent apps menu fix: Apps shown in the pull-down recent apps menu should no longer appear incorrectly greyed out. Notification Centre change: The wallpaper subject preview that appeared while opening Notification Centre has been removed in this beta. Some Siri AI and Apple Intelligence features require an iPhone 15 Pro or newer, although iOS 27 itself supports every iPhone that can run iOS 26. Feature availability can also depend on the selected language and region. If you’ve already installed the update, let us know your experience in the comments.

iPadOS 27 Public Beta 2 Now Available, Here’s How to Install It and What’s New

Thu, 23 Jul 2026 08:17:15 +0200

Apple has released iPadOS 27 public beta 2 for compatible iPad models, one week after the first public beta arrived. The update matches the latest developer beta and brings several smaller features, interface refinements, and bug fixes. Anyone enrolled in the free Apple Beta Software Program can download the update through the Settings app. Since this remains pre-release software, users should back up their iPad before installing it. How to Install iPadOS 27 Public Beta 2 Follow these steps to download the latest public beta: Back up your iPad using iCloud or a Mac. Enroll your Apple Account in the Apple Beta Software Program if you have not already joined. Open the Settings app on your iPad. Select General. Tap Software Update. Choose Beta Updates. Select iPadOS 27 Public Beta. Return to the Software Update page. Tap Download and Install. Keep your iPad connected to Wi-Fi and make sure it has enough battery power before starting the installation. The device will restart after completing the update. What’s New in iPadOS 27 Public Beta 2 Public beta 2 focuses mainly on improving existing iPadOS 27 features rather than introducing major system changes. Automatic downloads in the Apple TV app: A new setting allows the Apple TV app to download upcoming episodes from shows in Continue Watching. It can also remove downloaded episodes after you finish watching them, helping manage storage space. Siri conversation preview controls: The standalone Siri app now includes an option that controls how many lines of preview text appear for previous conversations. This makes the conversation history easier to browse. New AirPods Adaptive mode controls: Control Center now provides more options for adjusting Adaptive Audio when compatible AirPods are connected. Zoom Photos to Fill: The Photos app adds a new setting that automatically enlarges images to fill the screen, reducing empty space around photos with different aspect ratios. Updated introduction screens: New splash screens explain features available through Siri AI and several system apps when users open them for the first time. Bug fixes and performance improvements: The update includes stability fixes, interface refinements, and other changes intended to improve the overall beta experience. Some iPadOS 27 features, including advanced Siri and Apple Intelligence tools, require an iPad model that supports Apple Intelligence. Beta software can also contain app compatibility problems, battery drain, and unexpected crashes, so installing it on a secondary device remains the safer choice. If you’ve already installed the update, let us know your experience in the comments.

SAP S/4HANA-Transformation zwischen Aufbruch und Realität

Thu, 23 Jul 2026 06:09:16 +0200

Ob hybrides Betriebsmodell oder Kostenfrage, am Ende entscheidet über den Projekterfolg nicht allein die Technologie

hasan as’ari – shutterstock.com

SAP-Anwenderunternehmen stehen unter Druck, auf SAP S/4HANA zu wechseln, weil die Mainstream-Wartung für SAP ERP (SAP ECC 6.0) Ende 2027 ausläuft und die bis Ende 2030 geltende erweiterte Wartung kostenpflichtig ist.

Zwar stellt SAP mit der „SAP ERP, Private Edition, Transition Option“ eine weitere Wartungsverlängerung bis 2033 in Aussicht. Da diese einer Neuimplementierung gleichkommt, bleibt SAP-Kunden mehr Zeit für die Planung, die Analyse und das Changemanagement. Der Nachteil: Wer diese Option nutzt, läuft Gefahr, technologisch ins Hintertreffen zu geraten, da Innovationen nahezu ausschließlich für SAP S/4HANA bereitgestellt werden.

Zögerliche SAP-S/4HANA-Transformation trotz Wartungsdruck

Obwohl der Druck hoch ist, hat eine große Zahl der SAP-Bestandskunden die Transformation auf die seit 2015 verfügbare ERP-Suite offenbar noch nicht vollzogen. Eine COMPUTERWOCHE-Expertenrunde zeigte, wo die größten Hürden liegen und was erfolgreiche Projekte auszeichnet.

Warum etliche Unternehmen die Transformation vor dem regulären Wartungsende scheuen und stattdessen zwei Prozent Mehrkosten für die erweiterte Wartung einkalkulieren, brachte ein Teilnehmender auf den Punkt: Firmen haben über Jahrzehnte in ihre SAP-ERP-Lösung investiert und sie an individuelle Prozessanforderungen angepasst, damit die Abläufe entlang der Supply Chain reibungslos laufen. Er habe daher in den vergangenen zehn Jahren keinen Kunden erlebt, der freiwillig umsteigen wollte. Alle hätten gesagt, dass sie müssen.

Nach Erfahrungswerten eines weiteren Experten nutzen erst rund 20 Prozent der SAP-Kunden SAP S/4HANA als Kernapplikation produktiv, unter anderem, weil entsprechende Transformationsprojekte auf sieben bis neun Jahre angelegt sind.

Altlasten bremsen die SAP-S/4HANA-Transformation

Unternehmen, die sich für den Wechsel entscheiden, verzichten häufig auf jede Modernisierung. Sie vollziehen einen Eins-zu-eins-Umstieg ohne Code-Modifikation, sei es in Form einer System Conversion (Brownfield-Ansatz) oder per Lift and Shift in SAP Cloud ERP Private (früher: SAP S/4HANA Cloud Private Edition). Dabei ist eine große Zahl von SAP-ERP-Installationen gar nicht zukunftsfähig, weil sie auf Prozessen aus den 1990er Jahren basieren und im Lauf der Jahre durch zahlreiche Eigenentwicklungen erweitert wurden.

Nicht selten gibt es bis zu mehrere tausend kundeneigene Programme im Z/Y-Namensraum, die zum Teil nicht mehr genutzt werden und das System unnötig belasten. Die Experten waren sich einig, dass eine solche rein technische Migration, bei der Altlasten wie ABAP-Eigenentwicklungen mitgeschleppt werden, keinen Mehrwert für das Unternehmen bringt.

Es muss geprüft werden, welche Eigenentwicklungen beibehalten werden, weil sie wettbewerbsdifferenzierend und damit geschäftskritisch sind, und welche gelöscht werden müssen, weil sie nicht genutzt werden oder weil es dafür inzwischen SAP-Standardfunktionen gibt. Handlungsbedarf besteht auch bei einer dreistelligen Anzahl von Buchungskreisen, von denen niemand weiß, welche noch benötigt werden, oder bei zahlreichen Dubletten in den Kreditoren- und Debitorenstammdaten.

Studie “SAP S4HANA”: Sie können sich noch beteiligen!

Zum Thema SAP S4HANA führt die COMPUTERWOCHE derzeit eine Multi-Client-Studie unter IT-Verantwortlichen durch. Haben Sie Fragen zu dieser Studie oder wollen Partner bei dieser Studie werden, helfen wir Ihnen unter research-sales@foundryco.com gerne weiter.

Migrations-Tools und KI-Agenten beschleunigen den Umstieg

Um diesen Prüf- und Bereinigungsaufwand zu bewältigen, bietet SAP mehrere Tools, um die Transformation auf SAP S/4HANA zu vereinfachen: darunter SAP Activate, SAP Cloud ALM, Migration Cockpit, Readiness Check, Custom-Code-Check oder Modifikationsabgleich. Ergänzt werden sie durch Lösungen wie Signavio für die Prozessanalyse. Die Experten schätzen den Effizienzgewinn durch solche Migrationswerkzeuge auf 30 bis 50 Prozent.

Zusätzliche Produktivität versprechen KI-Agenten, die Altsysteme automatisiert analysieren, Code bereinigen und Datenflüsse transformieren. Das reduziert den Migrationsaufwand und beschleunigt den Umstieg.

Scope-Management als Schlüssel für den Projekterfolg

Einig waren sich die Teilnehmenden, dass SAP-S/4HANA-Transformationsprojekte in der Regel nicht an der Technologie scheitern, sondern an einer mangelhaften Scope-Definition und am unzureichenden Changemanagement.

Ein Scope-Management vor dem Projektstart, das berücksichtigt, wie viel Veränderung der IT-Organisation und den Fachbereichen zugemutet werden kann, sei essenziell für den Erfolg, sagte einer der Teilnehmenden. Es erfordert die Fähigkeit zu priorisieren und ein iteratives Vorgehen, bei dem zunächst geschäftskritische Must-haves und Quick Wins umgesetzt werden. Weniger wichtige Nice-to-haves folgen später. Wer dagegen in der Konzeptionsphase bereits den großen Wurf anstrebt, wird voraussichtlich scheitern. Als Beispiel wurde der direkte Umstieg auf ein SAP-S/4HANA-Kernsystem genannt, das nach dem Clean-Core-Ansatz von nicht mehr lauffähigen Programmen und obsoleten Erweiterungen bereinigt ist.

Genauso wichtig ist ein Change-Management, das Mitarbeitende von Beginn an einbezieht, die nötige Akzeptanz schafft und vom Top-Management aktiv unterstützt wird, sowie eine verbindliche Governance mit klaren Zielvorgaben. Unverzichtbar ist auch die Einbindung der Fachbereiche. Sie stellt die größte Herausforderung dar, da Unternehmen befürchten, dass durch die SAP-S/4HANA-Transformation zu viele personelle Ressourcen gebunden werden, die dann für Kernaufgaben fehlen. Kommt es vor, dass IT und Fachbereiche als Antipoden agieren, sollte ein Change-Coach als Vermittler eingesetzt werden.

Hybride Betriebsmodelle setzen sich langfristig durch

Bereits vor dem Projektstart muss abschließend geklärt sein, welches Betriebsmodell für SAP S/4HANA am besten zu einem Unternehmen und seinen Zielen passt, auch mit Blick auf regulatorische Anforderungen. Das ist häufig nicht der Fall, sodass das Projektteam unnötig Zeit damit verbringt, das passende Betriebsmodell zu ermitteln. Das bremst Transformationsvorhaben aus.

Nach Ansicht eines Teilnehmenden wird sich langfristig ein hybrides Betriebsmodell durchsetzen, bei dem der SAP-Kunde entscheidet, welche Elemente der SAP-S/4HANA-Landschaft in einer Hyperscaler-Cloud, einer souveränen Cloud und/oder On-Premises laufen. Eine weitere, weitgehend unbekannte Möglichkeit ist der Betrieb im Rahmen der Customer-Data-Center-Option (CDC) von SAP Cloud ERP Private (früher: SAP S/4HANA Cloud Private Edition), die aus Gründen wie Datenschutz, Leistung und Souveränität eine interessante Alternative sein kann.

Mehrere Experten stellen darüber hinaus fest, dass die vollwertige SaaS-Lösung SAP Cloud ERP Public (früher: SAP S/4HANA Cloud Public Edition) inzwischen verstärkt eingesetzt wird. Sie stellt vorkonfigurierte Kern-ERP-Funktionen (Best Practices) bereit und lässt sich relativ schnell einführen, ermöglicht aber kaum individuelle Anpassungen. Diese Abstriche nehmen Unternehmen in Kauf, um von regelmäßigen, automatischen Upgrades und technologischen Innovationen zu profitieren.

Kritisiert wurde allerdings, dass die Cloud-Diskussion häufig unter begrifflichen Unschärfen leidet. So macht der Betrieb von SAP S/4HANA in einer Hyperscaler- oder SAP-Cloud die Lösung noch lange nicht zum Software-as-a-Service-Angebot. Solche Ungenauigkeiten irritierten SAP-Kunden und bremsten die Entscheidungsfindung. Letztlich sind beim Cloud-Betrieb auch die Kosten entscheidend. Zwar wollen viele Unternehmen anfangs maximale Sicherheit mit Private Network und Confidential Computing, wählen dann aber günstigere Commercial-Cloud-Angebote. Ausnahmen bilden regulierte Branchen und der öffentliche Sektor.

Ob hybrides Betriebsmodell oder Kostenfrage, am Ende entscheidet über den Projekterfolg nicht allein die Technologie, sondern auch, wie diszipliniert Scope und Wandel im Unternehmen gesteuert werden.

Teilnehmer der Round-Table “SAP S4HANA 2027”

Albrecht Munz, HPE:

„Die SAP-S/4HANA-Migration ist primär ein erster technischer Pflichtlauf, der die IT seitige Grundlage für die digitale Transformation schaffen kann. Dass viele Unternehmen hier stagnieren, liegt auch am in diesem Zusammenhang häufig anzutreffenden Cloud-Washing: Das Hosting eines ERP-Systems in der Cloud liefert noch lange nicht die Innovations- und Business-Effekte einer wirklich Cloud-nativen SaaS-Architektur.“

Harald Becker / Hewlett-Packard GmbH

Anke Frier, Lufthansa Industry Solutions:

„Unternehmen, die sich für eine technische SAP-S/4HANA-Transformation entschieden haben, dürfen diese nicht mit dem Go-Live als abgeschlossen betrachten. Der langfristige Erfolg hängt davon ab, wie konsequent danach die neuen technologischen Möglichkeiten genutzt werden, um Prozesse umzugestalten, zu digitalisieren und durch KI-Einsatz zu unterstützen. Erst dadurch entsteht ein messbarer Business Value.“

Sonja Brüggemann / Lufthansa Industry Solutions GmbH & Co. KG

Peter Büermann, Microsoft:

„Der optimale Zeitpunkt für den Umstieg auf SAP S/4HANA ist jetzt. Die Reife der Migrationswerkzeuge, standardisierte Vorgehensmodelle und die umfangreiche Projekterfahrung der SAP-Partnerlandschaft reduzieren das Risiko deutlich. Damit sind die wesentlichen Hürden vergangener Jahre weitgehend beseitigt und Unternehmen profitieren von einer schnelleren Implementierung, geringeren Kosten und einer höherer Projektqualität.“

Microsoft Deutschland GmbH

Roland Storbeck, Natuvion:

„Wirklich erfolgreich sind die SAP-S/4HANA-Migrationen, deren Scope noch vor dem Projektstart klar definiert und gemanagt wird. Wer zu Beginn zu hohe Ansprüche hat und jeden Prozess umdrehen will, dessen Vorhaben scheitert häufig schon in der Konzeptionsphase. Zudem muss jedes Unternehmen die Frage beantworten, wie viel Change seine IT- und Business-Organisation überhaupt verträgt. Neben einem klaren Scope ist dringend zu empfehlen, den eigenen Datenbestand vor Projektstart zu analysieren und aufzuräumen.“

VOGUS – Wolfgang Voglhuber / Natuvion GmbH

Matthias Draschner, smartShift:

„Für viele Unternehmen ist SAP in erster Linie eine über Jahre oder sogar Jahrzehnte gewachsene IT-Landschaft, die geschäftskritische Prozesse unterstützt und absichert. Entsprechend besteht die berechtigte Erwartung, dass diese Prozesse auch nach der Migration auf SAP S/4HANA zuverlässig und möglichst unverändert weiterlaufen. Gleichzeitig bietet die SAP-S/4HANA-Transformation die Chance, Custom Code entweder zu modernisieren und auf die Anforderungen einer Cloud-fähigen Architektur auszurichten oder zu entfernen, sofern er nicht mehr benötigt wird. Spezielle Analyse- und Automatisierungstools unterstützen diesen Prozess.“

smartShift Technologies GmbH

Drive with Halo on Waze

Thu, 23 Jul 2026 04:07:53 +0200

Building on a partnership that began in 2021, Waze is once again teaming up with Halo to celebrate the launch of Halo: Campaign Evolved, with a refreshed Halo experience…

HPR4689: Cheap Yellow Display Project Part 8: Writing the code

Thu, 23 Jul 2026 02:06:01 +0200

This show has been flagged as Clean by the host.

Hello, again. This is Trey.

Welcome to part 8 in my Cheap Yellow Display (CYD) Project series.

If you wish to catch up on earlier episodes, you can find them on my HPR profile page https://www.hackerpublicradio.org/correspondents/0394.html

It is hard to believe that I started this project and the HPR series to document it more than a year ago. Time flies. Life happens. I spent the last 8 months so focused on work related activities that I had to set the project aside. And once I set it aside, it was difficult to get back to again. The one time I tried, I found that my son's old Windows laptop, which I had commandeered to use for the project, was once and truly dead.

We live in a different world now than we did when I began this project. Today, everything is about AI – how it is changing our world, increasing efficiencies, and even displacing certain types of jobs. "Vibe coding" is transforming the way we make software, and now everyone is a developer.

Within my organization, we are all being strongly encouraged to learn more about AI and apply it in our daily work. We are blessed to have access to a wide range of training and to powerful tools which support the process. Several colleagues within my organization and outside my organization have recommended Claude Code -- for development, for organization, for brainstorming, and for much more. My role is not that of a developer, and I have had no need for Claude Code at work. There are plenty of other tools for me to use.

But at home, I thought... I could install Claude Code at home to experiment with and to learn. And then it hit me. I wonder if I could use Claude Code to help me with my stalled CYD project.

"Hello, my name is Trey, and I am a fraud."

OK. I don't think I am a fraud, but having never used such a powerful tool to help me code, I feel a little bit like a fraud, with Claude doing the work for me. Let's talk through what we did.

As I mentioned, I was unable to use the laptop on which I created the original GUI code. But no worries, because It was all on GitHub, right?

So, I began by trying to install Claude Code on one of my Ubuntu machines. That failed miserably, and all the instructions I found online recommended running it on Windows. So I transitioned to installing Claude Code on a freshly built Windows 10 system using some old hardware which will not support Windows 11. Surprisingly, It seems that Claude wants to run within Ubuntu on Windows Subsystem for Linux (WSL).

Once I went through all the hoops for installing and setting up my basic subscription, I got to work. I created a new directory to use for all my project files, and another one for Claude to write all its output files to.

Everything I have read and heard about using Claude Code for a project like this recommended beginning by using Claude to create the project plan. So my first prompt was as follows:

"I am building a project using an ESP32 cheap yellow display. The final goal is to have a device with a graphical user interface which will allow me store several text messages, each assigned to their own specific button. Then, when one of the buttons is pressed, the message will be converted into morse code, and the message will be sent by blinking an onboard LED. I already have the initial design for the GUI coded in my github repository. Please construct a detailed step by step plan for building this application"

I wanted to keep it simple at the beginning, so even though I plan to use an opto-isolated relay for the output, I am starting out using the built in LED.

Claude asked me for the URL for my Github repository, and I provided it. After thinking for a bit, it produced a project plan.

CYD Morse Sender — Step-by-Step Build Plan

What You Already Have

- 3 fully designed LVGL screens (Send, Config, Keyboard)

- 7 send buttons with green styling on the Send Screen

- Speed slider (5–30 WPM) and program slot dropdown on Config Screen

- Text area + LVGL keyboard widget on Keyboard Screen

- Display driver and touchscreen hardware initialized (but touch read was stubbed out)

---

Phase 1: Fix Touchscreen Input

Initialize the XPT2046 on VSPI, replace the hardcoded touched = false with real touch data, calibrate raw ADC coordinates to screen pixels, and verify all three nav buttons transition screens correctly.

Phase 2: Persistent Message Storage

Use Preferences.h / NVS to store 7 messages ("msg0" – "msg6") that survive power cycles. Load on boot and populate send button labels.

Phase 3: Config Screen — Slot Selection & Speed

Wire the Program dropdown to g_selectedSlot, wire the Speed slider to g_wpm with a live WPM label, and wire the Set button to clear the text area and navigate to the Keyboard Screen.

Phase 4: Keyboard Screen — Capture and Save Text

On keyboard OK (LV_EVENT_READY): read the text area, save to NVS, update the send button label, navigate back. On Cancel: navigate back without saving.

Phase 5: Morse Code Engine

Build morse.h with the full A–Z / 0–9 lookup table, a textToMorse() converter, and Paris-standard timing (unit_ms = 1200 / wpm).

Phase 6: Non-Blocking LED Transmission

State machine (IDLE / LED_ON / LED_OFF) driven by millis() in a morseUpdate() function called every loop — no delay(). LED on GPIO 17 (blue).

Phase 7: Wire the Send Buttons

Each button calls startMorse(getMessage(slot)) if not already transmitting. Disable all send buttons during TX; re-enable when the state machine reaches the end.

Phase 8: Integration & Polish

Stop button, WPM persistence, empty-slot guard, serial debug output, final touch calibration, end-to-end test checklist.

---

Recommended order: Phase 1 → 2 → 7 (partial) → 5 → 6 → 7 (full) → 3 → 4 → 8

This was wild! Claude determined exactly how far along I was in the project, and also alerted me to the fact that the "touch read was stubbed out". Ugh. This means that the files I had uploaded to GitHub were my original GUI files (Episode 05 – HPR4532 - https://hackerpublicradio.org/eps/hpr4532/index.html ) and not the ones that I finally got working properly (Episode 07 – HPR4624 - https://hackerpublicradio.org/eps/hpr4624/index.html ). That was my own fault. Did I mention that I don't get Git? I REALLY need to learn to properly use Git!

But, we have a plan, broken down by eight numbered phases. And they seem to address all the functionality I wanted with a few additional things I had not thought about. Interestingly, even though these phases are sequentially numbered, Claud recommended that we approach them in a bizarre order: Phase 1 → 2 → 7 (partial) → 5 → 6 → 7 (full) → 3 → 4 → 8 .

Alright. Let's see what we can do. The first phase is to fix the touchscreen input.

Claude took me through it step-by-step, asking as it needed to read specific project files.

Finally, it wrote a new ui.ino code file to my speficied output directory for me to test. I copied it into the correct file location, said a quick prayer, compiled in Arduino IDE, and downloaded to the CYD.

Well, that is... interesting. The display looked nothing like it was supposed to. There were vertical green bars with smaller dashed green vertical stripes in them. I will include a picture in the show notes so that you can see what it looked like and why it was so difficult to describe.

I spent the next hour or so trying to explain what I was seeing to a chat bot. Claude recommended potential fixes which either did nothing or made the situation worse. I began questioning whether this was a good idea, how people actually gained efficiencies talking to a bot, and even several life choices.

Then I had a thought. I prompted Claude:

If I were to take a picture of the screen on the cheap yellow display and copy it into the output folder, would you be able to analyze it to better determine what is wrong and how to fix it?

Shockingly, Claude answered in the affirmative, and told me to copy the picture to the output folder and let it know when to proceed. It analyzed the picture and more of the supporting files it had copied from my GitHub, asking each time if it could access that file. It determined that my original code was written for a flavor of LVGL version 8 and I was now using LVGL 9.5.

It recommended changes, and then asked permission to make those changes, file by file. .h files & .c files, Finally, I just gave it permission to edit the files in the project folder without asking for permission for each file each time. Claude was still explaining each change, showing me exactly what would be changed, and asking for permission, so that I could review all of the changes. But now it was not asking additional permission to write to each of the impacted files.

Next, Code compiled and downloaded. Different screen, but not right. Again, I took a picture and gave it to Claude to analyze. So, Claude paused and altered the code to generate a specific test pattern overtop of the GUI.

The test pattern was supposed to cover the entire rectangular screen. But parts of the pattern were in a square on the screen and parts were not. Another photograph and analysis, told Claude that there were some rotation/screensize issues.

We repeated this several times. Some resulted in improvement, and others did not.

This is the point where I noticed something interesting. Not about Claude, specifically, or about the app. But I noticed something interesting about myself and about the process.

Previously, when I was working through some of these challenges without Claud, I found myself becoming more and more stressed, frustrated, and angry, until I found a solution. Then another problem would repeat the cycle. Success in the end was great, but the emotional extremes during the process were not always pleasant.

Now, I was effectively managing the project, and relaying information to the resource responsible for fixing the problems -- a very different experience.

But I also ran into another issue. Claude became absolutely certain that the problem revolved around the device not accurately knowing where the 4 corners of the screen were. But in reality, the output of the test pattern was rotated 90 degrees from the actual screen. It took several iterations of me insisting that the problem had to do with screen orientation and not corner coordinates. It was interesting to experience the tool doubling down on an obvious mistake, but we finally resolved that.

Again, while it was frustrating, it was much less stressful.

We proceeded to Phase 2: Persistent Message Storage where we ensured that the button labels on the send screen were stored in the devices persistent storage, so that, when they are edited to contain the message they should send, that information would survive a reboot.

Next, we combined elements of Phase 5: Morse Code Engine , Phase 6: Non-Blocking LED Transmission , and Phase 7: Wire the Send Buttons together. Building the morse code engine was an area I had been thinking about for a while. I already had working parts of something similar in the Arduino practice oscillator I have referenced a few times in this series. The code for the practice oscillator may be found on my GitHub, but it was all based on original code from jmharvey1, with my only contribution being making pin assignments variables so that the code could easily be ported to different devices.

So, I was happy that we were building the morse code engine directly. The code for it may be found in morse.h, which uses a constant character lookup table to define each character. Without any specific direction from me, Claude used the PARIS timing methods I have already described within Episode 6 of this series. It defines timing for DOT, DASH, LETTER_GAP, and WORD_GAP, and all are based on a simple calculation of 1200 ms / the number of words per minute (WPM) we wish to transmit.

Along the way, we discovered that, if we tried to use the delay() function, it would crash the program due to a conflict with the LVGL timer used for touchscreen inputs. Claude altered all the delays accordingly.

Then, Phase 3: Config Screen — Slot Selection & Speed allowed us to configure the WPM we wished to use in addition to selecting a specific Send button to reconfigure. This forced us to work on Phase 4: Keyboard Screen — Capture and Save Text which is used to type the entries for each Send button. At this point, I also decided that we would want to also use the Keyboard Screen to send ad hoc morse as we typed it.

During this phase we discovered several bugs which seemed to cause random freezes. Careful troubleshooting with messages output to the Arduino IDE's serial console helped us narrow down the causes and remedy them.

Finally all the tests worked and I am able to merrily pre-configure macro buttons with custom messages and use the CYD to send the morse code for those messages to the on-board LED at whichever rate I specify.

I have noticed in my presentation of this narrative that I repeatedly slip into the first person plural terms "we" and "us" instead of the first person singular terms "I" and "me". I have unconsciously personified Claud and recognized it as an integral part of my (formerly one person) development team.

I finally configured Claude to connect to my GitHub repo and upload all the files and documentation. We additionally created a CYD-Narrative.md file which describes in more detail all the work which was done on the project. I still do not 100% get git, but we are successfully using it.

You can find all these files in my GitHub repo ( https://github.com/jttrey3/CYD_MorseSender ) where they are shared under a GPL 3.0 license.

There are still several additional steps I plan to complete in the next few months.

1. I will be integrating an opto-isolated relay which will allow me to plug the device into the straight key input on any amateur radio. This will require a battery power source, charge controller, and more hardware.

I... make that "We" (Claude & I) will be modifying the code to support an audio side tone through an attached speaker when sending code
We will add an output selection switch to the config page to choose any combination of speaker, relay, or LED as output.
We will develop a downloadable firmware which I hope to share with the Cheap Yellow Display community.

If you can think of any additional features you would like to see integrated, please drop me an email using the address in my HPR profile.

I may also work with a friend to attempt to 3d print a case for the entire contraption, and I will be sure to record additional episodes sharing the process.

I have learned so much throughout this project, about the CYD, ESP32, GUIs, Claude Code, GitHub, and most of all, about myself.

Does using AI to develop this code make me a fraud? It still feels like it in some ways.

Does it make me more productive? ABSOLUTELY! I made consistent forward progress when I only had 30-60 minutes each day to work on it, and everything discussed in this episode was completed in less than a week. If I had been able to work on it for a few hours uninterrupted, it may have only taken me 3-5 hours.

Does it empower and inspire me to do more projects like this? 100% I feel like I had support working with me the whole way. I was less stressed overall, and it had less of an impact on the amount of and quality of time I spent with my family.

I will be wrapping up this series soon, without any more 6 month gaps, I hope.

Until next time...

Provide feedback on this episode.

Tails 7.6.1

Wed, 22 Jul 2026 23:53:43 +0200

This release is an emergency release to fix important security vulnerabilities in Tor Browser.

Changes and updates

Update Tor Browser to 15.0.9, which fixes several vulnerabilities in Firefox 140.9.0.

We are not aware of these vulnerabilities being exploited in practice.
Update the Tor client to 0.4.9.6.
Update Thunderbird to 140.9.0.
Update some firmware packages. This improves support for newer hardware: graphics, Wi-Fi, and so on.

For more details, read our changelog.

Get Tails 7.6.1

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.6.1.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.6.1 on a new USB stick

Follow our installation instructions:

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.6.1 directly:

Tails 7.6.2

Wed, 22 Jul 2026 23:53:42 +0200

This release is an emergency release to fix an important security vulnerability in the confinement of Tor Browser.

Changes and updates

Update Flatpak to 1.16.6, which fixes CVE-2026-34078, a major sandbox escape vulnerability. Using this vulnerability, an attacker could break the security confinement of Tor Browser and access all files that don't require an administration password, including in the Persistent Storage.

This vulnerability can only be exploited by a powerful attacker who has already exploited another vulnerability to take control of Tor Browser.

For more details, read our changelog.

Get Tails 7.6.2

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.6.2.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.6.2 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.6.2 directly:

Tails 7.7

Wed, 22 Jul 2026 23:53:41 +0200

New feature

Detection of outdated Secure Boot certificates

Since 2023, Microsoft has started replacing the Secure Boot certificates originally issued in 2011. These older certificates begin expiring in June 2026.

Tails now notifies you if the computer that you are using has outdated Secure Boot certificates and needs an update.

Changes and updates

Update Tor Browser to 15.0.10.
Update Thunderbird to 140.9.1.

Fixed problems

Make the /root folder only readable by the root user. (#21514)

For more details, read our changelog.

Get Tails 7.7

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.7.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.7 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.7 directly:

Tails 7.7.1

Wed, 22 Jul 2026 23:53:39 +0200

This release is an emergency release to fix important security vulnerabilities in Tor Browser.

Changes and updates

Update Tor Browser to 15.0.11, which fixes several vulnerabilities in Firefox 140.10.1.

We are not aware of these vulnerabilities being exploited in practice until now.
Update Thunderbird to 140.10.0.
Stop making it possible to start our ISO images from a USB stick.

Since 2019, we recommend USB images to start Tails from a USB stick, which is by far the most common way of running Tails.

We still distribute ISO images to start Tails from a DVD or in a virtual machine. Until now, these ISO images worked on USB sticks as well, but provided a degraded experience without automatic upgrades or Persistent Storage.

Our ISO images no longer work on USB sticks to save a few megabytes and prevent confusion for people who use USB sticks.

For more details, read our changelog.

Get Tails 7.7.1

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.7.1.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.7.1 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.7.1 directly:

Tails 7.7.2

Wed, 22 Jul 2026 23:53:38 +0200

This release is an emergency release to fix a critical security vulnerability in the Linux kernel.

Changes and updates

Update the Linux kernel to 6.12.85, which fixes Copy Fail, a vulnerability that could allow an application in Tails to gain administration privileges.

For example, if an attacker was able to exploit other unknown security vulnerabilities in an application included in Tails, they might then use Copy Fail to take full control of your Tails and deanonymize you.

We are not aware of this vulnerability being used in practice until now.

Fixed problems

For more details, read our changelog.

Get Tails 7.7.2

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.7.2.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.7.2 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.7.2 directly:

Tails 7.7.3

Wed, 22 Jul 2026 23:53:37 +0200

This release is an emergency release to fix a critical security vulnerability in the Linux kernel, as well as security vulnerabilities in Tor Browser and in the Tor client.

Changes and updates

Update the Linux kernel to 6.12.86, which fixes Dirty Frag, a vulnerability that could allow an application in Tails to gain administration privileges.

For example, if an attacker was able to exploit other unknown security vulnerabilities in an application included in Tails, they might then use Dirty Frag to take full control of your Tails and deanonymize you.

We are not aware of this vulnerability being used in practice until now.
Update Tor Browser to 15.0.12.
Update the Tor client to 0.4.9.8.
Update Thunderbird to 140.10.1.

Fixed problems

For more details, read our changelog.

Get Tails 7.7.3

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.7.3.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.7.3 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.7.3 directly:

Tails 7.8

Wed, 22 Jul 2026 23:53:36 +0200

Changes and updates

Update Tor Browser to 15.0.14.
Remove Thunderbird.

You can still install Thunderbird as additional software.

If you have both the Thunderbird Email Client and Additional Software features of the Persistent Storage turned on, Tails automatically adds Thunderbird to your list of additional software.

A new version of Thunderbird is released in Debian shortly after each Tails release, because both Tails and Thunderbird follow the release calendar of Firefox. As a consequence, until Tails 7.5 (February 2026), the version of Thunderbird in Tails was almost always outdated, with known security vulnerabilities.

By installing Thunderbird as additional software, the latest version of Thunderbird is installed automatically from your Persistent Storage each time you start Tails.

Fixed problems

Fix multiple security vulnerabilities in the Linux kernel and haveged, that could allow an application in Tails to gain administration privileges.

For example, if an attacker was able to exploit other unknown security vulnerabilities in an application included in Tails, they might then use one of these vulnerabilities to take full control of your Tails and deanonymize you.

For more details, read our changelog.

Get Tails 7.8

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.8.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.8 on a new USB stick

Follow our installation instructions:

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.8 directly:

Tails 7.8.1

Wed, 22 Jul 2026 23:53:34 +0200

This release is an emergency release to fix a serious security vulnerability in the Linux kernel, as well as security vulnerabilities in the Tor client.

Changes and updates

Update the Tor client to 0.4.9.9, which fixes several security vulnerabilities.
Update the Linux kernel to 6.12.90-2, which fixes CVE-2026-43503, a vulnerability that could allow an application in Tails to gain administration privileges.

For example, if an attacker was able to exploit other unknown security vulnerabilities in an application included in Tails, they might then use this vulnerability to take full control of your Tails and deanonymize you.

This attack is very unlikely, but could be performed by a strong attacker, such as a government or a hacking firm. We are not aware of this vulnerability being used in practice until now.

Fixed problems

Fix a fingerprinting issue in the Unsafe Browser. (#21617)

Get Tails 7.8.1

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.8.1.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.8.1 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.8.1 directly:

Tails 7.9

Wed, 22 Jul 2026 23:53:33 +0200

Changes and updates

Update Tor Browser to 15.0.16.
Update some firmware packages. This improves support for newer hardware: graphics, Wi-Fi, and so on.

Fixed problems

Stop notifying about outdated Secure Boot certificates in rare cases where the certificates are already up to date. (#21643)

For more details, read our changelog.

Get Tails 7.9

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.9.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.9 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.9 directly:

Tails 7.9.1

Wed, 22 Jul 2026 23:53:30 +0200

Changes and updates

Update Tor Browser to 15.0.17.
Update the Tor client to 0.4.9.11.
Update the Linux kernel to 6.12.94, which fixes CVE-2026-43503 (DirtyClone) and CVE-2026-46331 (PACKET_EDIT_MEME), vulnerabilities that could allow an application in Tails to gain administration privileges.

For example, if an attacker was able to exploit other unknown security vulnerabilities in an application included in Tails, they might then use CVE-2026-46331 to take full control of your Tails and deanonymize you.

This attack is unlikely, but could be performed by a strong attacker, such as a government or a hacking firm. We are not aware of this vulnerability being used in practice until now.

Fixed problems

For more details, read our changelog.

Get Tails 7.9.1

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.9.1.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.9.1 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.9.1 directly:

New Release: Tails 7.9

Wed, 22 Jul 2026 22:34:51 +0200

Changes and updates

Update Tor Browser to 15.0.16.
Update some firmware packages. This improves support for newer hardware: graphics, Wi-Fi, and so on.

Fixed problems

Stop notifying about outdated Secure Boot certificates in rare cases where the certificates are already up to date. (#21643)

For more details, read our changelog.

Get Tails 7.9

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.9.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.9 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.9 directly:

Support and feedback

For support and feedback, visit the Support section on the Tails website.

New Release: Tails 7.9.1

Wed, 22 Jul 2026 22:34:16 +0200

Changes and updates

Update Tor Browser to 15.0.17.
Update the Tor client to 0.4.9.11.
Update the Linux kernel to 6.12.94, which fixes CVE-2026-43503 (DirtyClone) and CVE-2026-46331 (PACKET_EDIT_MEME), vulnerabilities that could allow an application in Tails to gain administration privileges.

For example, if an attacker was able to exploit other unknown security vulnerabilities in an application included in Tails, they might then use CVE-2026-46331 to take full control of your Tails and deanonymize you.

This attack is unlikely, but could be performed by a strong attacker, such as a government or a hacking firm. We are not aware of this vulnerability being used in practice until now.

Fixed problems

For more details, read our changelog.

Get Tails 7.9.1

To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.9.1.
If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.

To install Tails 7.9.1 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if you install instead of upgrading.

To download only

If you don't need installation or upgrade instructions, you can download Tails 7.9.1 directly:

Support and feedback

For support and feedback, visit the Support section on the Tails website.

Get HostDeal for $149.99 and Give Every New Website Somewhere to Go

Wed, 22 Jul 2026 22:05:40 +0200

HostDeal helps agencies run unlimited websites with domains, backups, SSL, email, storage, and dev tools.

The post Get HostDeal for $149.99 and Give Every New Website Somewhere to Go appeared first on TechRepublic.

Price-hiked iPads are a little cheaper right now

Wed, 22 Jul 2026 21:21:08 +0200

A number of Apple products got more expensive last month, so we’re happy to find deals wherever and whenever we can. If you’re searching for a high-end iPad, one of the more notable deals currently happening is on the 13-inch iPad Pro M5 with 512GB of storage. Normally $1,699, it’s $150 off at Amazon, costing […]

Oracle expands Cloud@Customer with new database service for mid-sized workloads

Wed, 22 Jul 2026 20:19:33 +0200

Oracle is expanding its Cloud@Customer on-premises portfolio with a managed database offering that it says will enable enterprises to run databases, applications, and AI agents in their own data centers, helping CIOs modernize mid-sized workloads while meeting data residency, regulatory, and low-latency requirements.

The hybrid cloud offering, Base Database Cloud@Customer, combines existing database and infrastructure services such as the Base Database Service and Data Infrastructure Cloud@Customer X11 platform. It is designed for enterprises that do not need the scale of Exadata Cloud@Customer but still want their infrastructure and AI capabilities on-premises, managed by Oracle, the company said.

The Cloud@Customer X11 platform itself consists of two Oracle X11 compute servers and shared all-flash storage, offering up to 60 usable processor cores and 660 GB of memory per server, 47.2 TB of storage, and 10/25 GbE networking.

For regulated industries or restricted connectivity

Analysts see the new offering filling a gap for enterprises that want the operational and economic benefits of the cloud but cannot send their data to a public cloud because of legal restrictions or technology limitations.

These enterprises, according to Ashish Chaturvedi, executive research leader at HFS Research, are likely to be in regulated industries such as financial services, healthcare, government, and defense that must comply with data residency requirements, or needing low-latency access from remote sites to operational databases.

The offering could also appeal to enterprises modernizing mid-sized workloads at remote locations or within individual business units that could never justify the investment in a full Exadata rack, said Amit Chandak, chief analytics officer at IT consulting firm Kanerika.

In all cases, Chaturvedi said, the appeal of the offering is its managed nature, which takes away the burden of looking after the underlying infrastructure.

Deployment and maintenance becomes easier too, said Michael Leone, principal analyst at Moor Strategy and Insights: “They get automation that mid-size teams rarely have the staff to build. Clustering, patching, standby databases, and backups arrive configured instead of hand-assembled because the offering is managed.”

The economics are equally compelling, Chaturvedi said. The pay-as-you-go pricing model, combined with online compute scaling, helps enterprises avoid overprovisioning and paying license fees for idle cores, which is a “classic waste” of fixed on-premises systems, he said.

Private AI behind the firewall

Beyond the operational and economic benefits, the architecture of the new offering enables databases, applications, VMs, and AI agents to be collocated on the same platform, removing what Chaturvedi called “the single biggest blocker” to AI adoption in regulated environments: the need to keep private data behind the firewall.

“For a CIO in a regulated sector who wants to deploy AI agents but can’t let regulated data touch an external model API, that’s a real unlock,” Chaturvedi said.

More so because most AI offerings, at least in their present form and state, cannot guarantee sensitive data protection, said Igor Ikonnikov, advisory fellow at Info-Tech Research Group.

Even if Base Database Cloud@Customer turns out more expensive than fully cloud-based options, “It’s still attractive as it eliminates reputational and economic risk caused by possible AI-induced data leakage,” Ikonnikov said.

The offering’s consolidation of databases, applications, and AI agents will also simplify deployment of AI-based workflows, said Forrester principal analyst Noel Yuhanna. “It reduces stack complexity and helps accelerate development cycles, deliver real-time data, and eliminate data movement challenges.”

Despite those advantages, Chandak cautioned that the offering is unlikely to see broad adoption outside Oracle’s existing customer base: “If a company isn’t already on Oracle, the pull is weak. You don’t buy into Oracle’s database just to get this.”

Enterprises seeking similar hybrid cloud capabilities have no shortage of alternatives: AWS, Microsoft, Google Cloud, IBM, Dell Technologies, and HPE all offer combinations of on-premises infrastructure, cloud management, and AI services.

However, those alternatives typically require customers to integrate multiple software and hardware components rather than consume them as a single managed offering.

Oracle’s differentiation, although narrow, is hard to match, Chaturvedi said: “The vertical integration of database, engineered hardware, cloud management, high-availability architecture, and now private AI, all engineered together and delivered as a managed on-prem subscription should be genuinely convenient and attractive.”

The offering is compatible with Oracle AI Database 26ai and Oracle Database 19c in Enterprise Edition and Standard Edition configurations. It also supports Oracle Real Application Clusters, Oracle Data Guard, and Zero Data Loss Recovery Appliance through Oracle-managed cloud automation for high availability and disaster recovery, the company said.

Base Database Cloud@Customer is now generally available, Oracle said. It did not provide pricing.

This article first appeared on CIO.

Oracle expands Cloud@Customer with new database service for mid-sized workloads

Wed, 22 Jul 2026 19:56:30 +0200

For regulated industries or restricted connectivity

In all cases, Chaturvedi said, the appeal of the offering is its managed nature, which takes away the burden of looking after the underlying infrastructure.

Private AI behind the firewall

“For a CIO in a regulated sector who wants to deploy AI agents but can’t let regulated data touch an external model API, that’s a real unlock,” Chaturvedi said.

More so because most AI offerings, at least in their present form and state, cannot guarantee sensitive data protection, said Igor Ikonnikov, advisory fellow at Info-Tech Research Group.

However, those alternatives typically require customers to integrate multiple software and hardware components rather than consume them as a single managed offering.

Base Database Cloud@Customer is now generally available, Oracle said. It did not provide pricing.

This article first appeared on CIO.

Oracle expands Cloud@Customer with new database service for mid-sized workloads

Wed, 22 Jul 2026 19:49:12 +0200

For regulated industries or restricted connectivity

In all cases, Chaturvedi said, the appeal of the offering is its managed nature, which takes away the burden of looking after the underlying infrastructure.

Private AI behind the firewall

“For a CIO in a regulated sector who wants to deploy AI agents but can’t let regulated data touch an external model API, that’s a real unlock,” Chaturvedi said.

More so because most AI offerings, at least in their present form and state, cannot guarantee sensitive data protection, said Igor Ikonnikov, advisory fellow at Info-Tech Research Group.

However, those alternatives typically require customers to integrate multiple software and hardware components rather than consume them as a single managed offering.

Base Database Cloud@Customer is now generally available, Oracle said. It did not provide pricing.

Samsung Galaxy Z Fold 8 Announced to Compete With Future iPhone Fold

Wed, 22 Jul 2026 19:11:18 +0200

At a Galaxy Unpacked event in London today, Samsung unveiled a new foldable smartphone designed to compete with the still-unannounced iPhone Fold. Called the Galaxy Z Fold 8, it features a wider 4:3 form factor with a 7.6-inch inner AMOLED display, Snapdragon 8 Elite Gen 5 for Galaxy chip, up to 16GB of RAM and 1TB of storage. "The inner display has enough extra real estate for multi-tasking and entertainment," reports Mashable, which got a chance to try the new foldable ahead of the event. "And if you're worried about a crease in the middle of the display, don't be. We got up close with the device, and the crease fully disappears when the display is activated." From the report: As stated above, the main distinguishing factor of the new Z Fold 8 is its wider 4:3 proportions compared to the Z Fold 8 Ultra. If the latter is a book-style foldable, the former can almost be called a tablet-style foldable, instead. We think the wide screen will serve even better for reading books or multi-tasking with several apps open at once. Also, at 201g, Samsung is really emphasizing how light the device is. The company is calling it the "world's lightest fold ever." And while the device may be light, its no lightweight. Samsung's newest foldable features Flex Titanium technology, which makes the Galaxy Z Fold 8 more durable. Speaking of durability, it also boasts Samsung's advantage hinge technology, Armor Flexhinge. The Z Fold 8 feels like a solid middle point between the premium Z Fold 8 Ultra and the comparatively affordable Z Flip 8. All three phones use the same chip, but the Z Fold 8's 4,800mAh battery is smaller than that of the Z Fold 8 Ultra. However, the Z Fold 8 does have an option for 16GB RAM and 1TB of storage, similar to the Ultra.

Here’s how to ask Gemini Live for help with anything you see.

Wed, 22 Jul 2026 18:48:13 +0200

Have you ever struggled to describe something you’re looking at? Whether it’s a complex manual, a blinking error code, or a unique object, sometimes you just need an exp…

Nvidia unveils Spectrum-X networking platform designed to connect millions of GPUs

Wed, 22 Jul 2026 17:45:24 +0200

Nvidia has introduced its next-generation Spectrum-X Ethernet networking platform, positioning it as a key building block for the next wave of “gigascale” AI factories designed to connect millions of GPUs while reducing power consumption and operational costs.

The networking platform is part of Nvidia’s broader Rubin architecture, which integrates six major components—including the Vera CPU, Rubin GPU, NVLink 6 switches, ConnectX-9 SuperNICs, BlueField-4 DPUs and the new Spectrum-6 Ethernet switches—into a tightly coupled AI infrastructure stack.

The company says this level of integration underscores the growing importance of networking in AI. In its most recent quarter, networking sales were $11 billion, up 263% year-over-year, prompting the ever-subtle CEO Jensen Huang to declare “We’re … now the largest networking company in the world” during Nvidia’s earnings call.

While GPUs have dominated headlines during the AI boom, networking has increasingly become a performance bottleneck as models grow larger and require faster communication between compute nodes.

Spectrum-X is a comprehensive platform consisting of Spectrum Ethernet switches, Spectrum-X SuperNICs, ConnectX NICs, BlueField DPUs, LinkX cabling and transceivers and Spectrum-XGS for networking between multiple AI data centers.

At the heart of the platform is the Spectrum-6 switch, a 102.4-terabit-per-second Ethernet switch system delivering 2x the capacity of previous-generation systems and built as part of the Vera Rubin platform.

Spectrum-6 is designed to operate an AI factory as one end-to-end computing system. It combines new Ethernet switches, network interface cards, silicon photonics and software designed to improve bandwidth while lowering latency and power usage.

The new Spectrum-X technology intelligently balances traffic across available paths, rapidly bypasses failures and precisely recovers when data traveling across a network fails to reach its destination. Plus, support for open network operating systems and a choice of RDMA transport models gives AI builders flexibility without compromising performance.

Nvidia says its latest silicon photonics technology integrates optical communications directly into networking hardware, reducing power consumption while increasing bandwidth density compared with conventional optical networking approaches.

The announcement reflects a broader shift in AI infrastructure strategy. Early AI clusters were primarily limited by GPU availability, but hyperscale operators are increasingly finding that networking, storage and power delivery determine how efficiently massive GPU deployments perform. By integrating networking more tightly with compute, Nvidia aims to eliminate communication bottlenecks that emerge as AI systems scale beyond a single data center or even multiple campuses.

New to the platform is Nvidia’s previously announced Spectrum-XGS technology, which links geographically distributed data centers into a single AI supercomputer. Together, the technologies are designed to enable organizations to construct AI factories that span multiple facilities while operating as a unified computing environment.

[$] Attaching programs to multiple tracepoints

Wed, 22 Jul 2026 17:09:16 +0200

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 Linux Storage, Filesystem, Memory-Management, and BPF Summit. That work has since been merged, and can be expected as part of the 7.2 kernel.

My Favorite NEW Folding Phone - Samsung Galaxy Z Fold8 Ultra vs Fold8 vs Flip8

Wed, 22 Jul 2026 15:36:25 +0200

Author: Shannon Morse - Bewertung: 4x - Views:33

Best deals! Fold8 Ultra - https://click.linksynergy.com/deeplink?id=qn*xL/agfY4&mid=47773&murl=https%3A%2F%2Fwww.samsung.com%2Fus%2Fsmartphones%2Fgalaxy-z-fold8-ultra%2Fbuy%2Fgalaxy-z-fold8-ultra-256gb-unlocked-sku-sm-f976uzvaxaa%2F

Fold8 -
https://click.linksynergy.com/deeplink?id=qn*xL/agfY4&mid=47773&murl=https%3A%2F%2Fwww.samsung.com%2Fus%2Fsmartphones%2Fgalaxy-z-fold8%2Fbuy%2Fgalaxy-z-fold8-256gb-unlocked-sku-sm-f971ulvaxaa%2F

Flip8 -
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unlocked devices at Best Buy - https://bestbuycreators.7tiv.net/6kX2Lb

https://youtu.be/RoVLY0s5Chc

Samsung just announced three brand new foldable smartphones at Galaxy Unpacked 2026, and I got hands-on with all of them in New York City!

In this video we're breaking down the new Galaxy Z Fold8 Ultra, Galaxy Z Fold8, and Galaxy Z Flip8, including pricing, displays, cameras, battery life, durability, Galaxy AI features, and the security features I always check first - like SIM support, Ultra Wideband, fingerprint readers, face unlock, Wi-Fi 7, and more.

Is the new Galaxy Z Fold8 Ultra worth over $2,000? Is the regular Fold8 the better value? And is the Flip8 Samsung's best flip phone yet?

I'll also be publishing full reviews after spending more time with each device, so make sure you're subscribed so you don't miss those!

💬 If you could have one of these phones for FREE, which would you choose?

#Samsung #GalaxyUnpacked #GalaxyZFold8Ultra #GalaxyZFold8 #GalaxyZFlip8 #FoldablePhone #Android #Tech @Samsung

Becoming a Morse Code Member by checking out the perks linked here!:
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Samsung Galaxy Unpacked 2026
00:48 Three New Galaxy Foldables
02:00 Galaxy Z Fold8 Ultra
06:15 Fold8 Ultra Cameras & Security Features
08:00 Patreon Shoutout
09:00 Galaxy Z Fold8
12:35 Galaxy Z Flip8
14:30 Shared Specs Across All Models
16:00 Colors & Storage Options
17:10 Biggest Takeaways
19:00 What I'm Testing Next
20:00 Which One Would You Choose?

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3 Google updates from Galaxy Unpacked 2026

Wed, 22 Jul 2026 15:05:56 +0200

We shared how Samsung users can boost productivity and get time back on new foldables, watches, and glasses coming soon.

Switch to Android easily — and bring your data with you.

Wed, 22 Jul 2026 15:05:51 +0200

A new migration experience built directly into Android 17 that lets you transfer more data wirelessly from an iPhone.

Stop renting storage space — this lifetime 2TB plan is yours for $59

Wed, 22 Jul 2026 13:22:46 +0200

Cloud storage costs tend to creep up over time, since most services charge monthly or annually for as long as you use them. FileJump's Lifetime Plan skips that model entirely, offering 2TB of cloud storage for a single payment of $59 (MSRP $467). [...]

Your instant Android backup upgrade

Wed, 22 Jul 2026 12:02:52 +0200

Once you do, though, those once-orphaned documents on your Android device’s local storage will be perpetually synced and protected, automatically, without any ongoing thought or effort.

All you’ve gotta do is find and flip that one new switch.

[Don’t let yourself miss an ounce of Android Intelligence. Join my free weekly Android Intelligence newsletter and get one new thing to try in your inbox every Friday!]

The Android backup lowdown

So, for a quick bit of pertinent context on this: Android’s backup systems have actually come a really long way over the years.

See?

The easily overlooked new option for backing up documents on Android.

JR Raphael, Foundry

Once the added option is present and available for you, you’re literally lookin’ at 10 seconds to find and activate it.

Lemme show ya how.

Android’s document backup addition

I promise: This couldn’t be much simpler.

However you get there, once you’re lookin’ at that list, you’ll see a newly added line for “Documents” if this latest under-the-hood update has reached you.

Android’s expanded list of backup options — now including documents alongside other forms of on-device data.

JR Raphael, Foundry

And from there, all that’s left is to tap it and enable the switch to include that in your automated backups from that moment forward.

Take 10 seconds to do that, though, and you’ll have one less void in your Android data arena. And you don’t need Gemini to tell you that that can only be a good thing.

Get practical Android knowledge in your inbox every Friday with my free Android Intelligence newsletter — one new thing to try each week, straight from me to you.

CVE-2026-39937 | Wikimedia CentralAuth Extension up to 1.43.6/1.44.3/1.45.1 on Mediawiki removal of sensitive information

Wed, 22 Jul 2026 11:33:16 +0200

A vulnerability labeled as critical has been found in Wikimedia CentralAuth Extension up to 1.43.6/1.44.3/1.45.1 on Mediawiki. The affected element is an unknown function. Such manipulation leads to improper removal of sensitive information before storage or transfer. This vulnerability is listed as CVE-2026-39937. The attack may be performed from remote. There is no available exploit. The affected component should be upgraded.

Google erlaubt Android-Nutzern kein Gratis-Backup mehr: Schonfrist von 45 Tagen

Wed, 22 Jul 2026 10:19:56 +0200

Für neue Android-Nutzer gilt die Änderung seit dem 7. Juli 2026. Für bestehende Nutzer gilt eine Schonfrist von 45 Tagen, bis sie in Kraft tritt. Google informiert Nutzer per Mail dazu:

Wir möchten dich über eine bevorstehende Aktualisierung unserer Speicherrichtlinien informieren. Außerdem führen wir neue Steuerelemente ein, mit denen du deine Android-Sicherungen besser verwalten kannst.

Richtlinienänderung: In 45 Tagen werden alle Daten, die in den Sicherungen deines Android-Geräts enthalten sind, auf das Speicherplatzlimit deines Google-Kontos angerechnet. Fotos und Videos in Google Fotos und MMS-Daten werden bereits jetzt in deinen Google-Kontospeicherplatz einbezogen. Mit dieser Änderung werden auch alle anderen gesicherten Daten wie SMS, Anruflisten, Geräteeinstellungen und App-Einstellungen auf deinen Google-Kontospeicherplatz angerechnet. Nach Inkrafttreten dieser Richtlinie wird deine Gerätesicherung möglicherweise mehr Speicherplatz belegen. Wenn das Speicherplatzlimit deines Google-Kontos überschritten ist, werden automatische Sicherungen pausiert, bis du Speicherplatz freigibst oder dein Abo upgradest.

Die besten Online-Backup-Dienste im Vergleich: Nie mehr Daten verlieren

Apple Faces Lawsuit Over Hide My Email Privacy Vulnerability

Wed, 22 Jul 2026 09:59:53 +0200

Apple is facing a proposed class-action lawsuit after Anthony Alvarez alleged that the company’s Hide My Email feature failed to protect users’ real email addresses as advertised. The complaint, filed in the U.S. District Court for the Northern District of California, claims Apple promoted Hide My Email as a privacy safeguard while continuing to charge customers for access through its iCloud+ subscription service. The legal action follows a report from 404 Media that revealed a reported vulnerability in Hide My Email. The report claimed the flaw could allow someone to identify a user’s actual email address from the private relay address generated by the feature. According to the report, Apple had been aware of the issue for more than a year before releasing a fix.

Hide My Email Vulnerability Becomes the Focus of Apple Lawsuit

Apple confirmed that it deployed a patch on July 3, 2026, stating that the Hide My Email vulnerability had been fully resolved. However, the lawsuit alleges that Apple continued marketing the feature as secure while the reported weakness remained unresolved. The complaint states that security researchers first informed Apple about the vulnerability in June 2025. Although Apple acknowledged the report, Anthony Alvarez’s lawsuit claims the company did not resolve the issue for nearly a year. The filing also alleges that Apple incorrectly stated in March 2026 that the problem had been fixed, even though researchers reported that the vulnerability remained exploitable.

How Apple’s Hide My Email Feature Works

Hide My Email was introduced with Sign in with Apple in 2019. The feature creates unique relay addresses for supported apps and websites, allowing messages to reach a user’s inbox without revealing the person’s actual email address. Apple later expanded Hide My Email through the paid iCloud+ subscription, launched alongside iOS 15 and macOS Monterey in September 2021. The iCloud+ version allows subscribers to create unlimited private relay addresses for websites, newsletters and email communication. The lawsuit argues that millions of Apple users relied on Hide My Email to reduce spam, limit online tracking, protect personal information from data brokers and avoid exposure during third-party data breaches. Researchers cited in the complaint said that once a real email address is revealed, it may be linked with publicly available people-search databases, potentially exposing identities and other personal information.

Anthony Alvarez Claims Apple Misled Customers Over Privacy

The complaint argues that Apple built much of its brand identity around privacy, referencing marketing statements such as “Privacy. That’s iPhone,” “What happens on your iPhone, stays on your iPhone,” and descriptions of privacy as a “fundamental human right” and “core value.” According to the lawsuit, Apple’s privacy messaging influenced consumer decisions and helped justify premium pricing for Apple hardware and services. The plaintiffs claim Hide My Email was promoted as a central part of those privacy commitments. The filing alleges that Apple asked researchers not to publicly disclose details of the vulnerability instead of warning customers or temporarily disabling the feature. It claims users were never informed that their real email addresses could potentially be exposed while Apple continued presenting Hide My Email as a privacy protection tool.

Lawsuit Seeks Damages and Changes From Apple

Anthony Alvarez is seeking reimbursement for iCloud+ subscription fees and other alleged financial losses. The lawsuit requests an injunction requiring Apple to either provide the privacy protection promised through Hide My Email or clearly disclose any limitations. The complaint includes claims involving California’s Unfair Competition Law, False Advertising Law and Consumers Legal Remedies Act, along with allegations of fraud, negligent misrepresentation, breach of contract, breach of implied warranty and unjust enrichment. The lawsuit argues customers paid for Apple’s privacy protections in multiple ways, including iCloud+ subscription fees and premium prices associated with Apple devices marketed as offering stronger privacy features. Apple has stated that the July 3, 2026 patch resolved the Hide My Email issue.

NetApp snaps up DataPelago to bolster AI data infrastructure portfolio

Wed, 22 Jul 2026 09:59:52 +0200

The acquisition brings GPU-accelerated data processing into NetApp's storage layer to help customers speed up AI workloads

OneNote vs. Evernote: Notiz-Apps im Vergleich

Wed, 22 Jul 2026 05:06:49 +0200

Evernote und OneNote tragen den Kampf um die Notiz-App-Krone unter sich aus.

Foto: Bonya_06_Inna_Kharlamova_Makini_Caravello – shutterstock.com

Geht es um die richtige Notiz-App, fällt die Entscheidung im Regelfall zwischen OneNote von Microsoft und Evernote, das inzwischen dem italienischen Softwareunternehmen Bending Spoons gehört.

OneNote ist seit dem Jahr 2003 auf dem Markt und wurde 2007 in Microsofts Office-Suite aufgenommen (die meisten Versionen laufen inzwischen unter dem Namen Microsoft 365). Zudem wird OneNote auch mit Windows 10 und 11 gebündelt und als eigenständiges Produkt kostenlos angeboten. Das eröffnet eine potenzielle Nutzerbasis von rund einer Milliarde Systemen.
Evernote feierte im Jahr 2008 sein Marktdebüt und erfreut sich seither stetig wachsender Nutzerzahlen. Unternehmensangaben zufolge sind es inzwischen weltweit rund 225 Millionen User.

Sowohl OneNote als auch Evernote sind für alle wichtigen Desktop- und Mobile-Betriebssysteme verfügbar. Beide sind in der Lage, Notizen mit allen Geräten und dem Internet zu synchronisieren und beide versprechen, die einzige notwendige App für Notizen zu sein. Stellt sich die Frage: Was ist die bessere Wahl für Business-Nutzer?

Wir haben uns die jeweils aktuellen Versionen beider Notiz-Apps für Windows, macOS, iPadOS, iOS und Android angesehen und sagen Ihnen, worin sich OneNote und Evernote im Wesentlichen unterscheiden.

One Note: Organisationskrösus

OneNote ist eine vollwertige Anwendung. Mit ihr können Sie einfache oder komplexe Notizen von Grund auf neu erstellen, sie in durchsuchbaren Notizbüchern organisieren und mit einer Vielzahl von Plattformen synchronisieren – zum Beispiel Windows-PCs, Macs, iPads und iPhones sowie Android-Geräten.

Außerdem strotzt Microsofts Notiz-App nur so vor Werkzeugen – beispielsweise um:

Notizen zu erstellen und zu bearbeiten,
zu zeichnen,
Audio- und Videoaufnahmen zu erstellen,
Bilder zu scannen oder
Tabellenkalkulationen einzubetten,

OneNote wird allmählich immer stärker in die Microsoft-365-Suite integriert. Für Unternehmen ist die Live-Zusammenarbeit besonders wichtig und sie funktioniert hier ebenso so wie in anderen Microsoft-365-Anwendungen. Besonders gut lässt sich OneNote dabei in Microsoft Teams integrieren: Notizbücher lassen sich Teams hinzufügen – jeder innerhalb des Kanals kann diese anschließend anzeigen und bearbeiten (entsprechende Zugriffsrechte vorausgesetzt).

Web-Clipping

So gut OneNote auch sein mag, wenn es darum geht Notizen zu erstellen: Es bleibt hinter den beträchtlichen Möglichkeiten von Evernote zurück, wenn es um das Clipping von Webinhalten geht. Dazu bietet OneNote ein Browser-Addon (Microsoft Edge, Google Chrome und Mozilla Firefox) namens OneNote Web Clipper. Mit diesem Tool können Sie Screenshots in OneNote speichern – wenn es denn so funktioniert wie es soll.

Versionsunterschiede

Die Windows-Version von OneNote kann mit der vollen Bandbreite an Tools glänzen. Im Vergleich bietet Evernote nicht annähernd so viele ausgefeilte Tools. Die Versionen für Web, Android, iPadOS und macOS fallen hingegen ab. Sie sehen zwar ähnlich aus wie die Windows-App, bieten im Vergleich aber weniger und teilweise eingeschränkte Funktionen. So können Sie hier etwa keine Tabellenkalkulationen integrieren oder Videoinhalte aufzeichnen. Die iOS-Version hebt sich hingegen mit einer schlanken Benutzeroberfläche ab, die darauf optimiert ist, schnell Notizen zu erstellen oder zu bearbeiten.

KI-Funktionen

Seit Mitte Januar 2024 bietet Microsoft mit Copilot Pro KI-Integration im Abomodell an – auch für OneNote.

🧠 Work smarter with Copilot Notebooks in OneNote — your new AI-powered space to think, organize, and create. Bring all your content together and let Copilot help you get to insights, faster.

Learn more: https://t.co/c63JbghHcH
— Microsoft OneNote (@msonenote) July 3, 2025

Storage und Preise

OneNote synchronisiert seine Inhalte mit all Ihren Geräten und mit dem Internet über Microsoft OneDrive oder SharePoint. OneNote ist in Microsoft 365 enthalten. Ohne M365-Abo erhalten Sie bis zu 5 GB Cloud-Speicherplatz. Zusätzlichen Speicherplatz können Sie zukaufen. Wenn Sie (oder Ihr Unternehmen) ein Microsoft-365-Abonnement abschließen, erhalten Sie wesentlich mehr Speicherplatz: zwischen 100 GB und 6 TB – je nachdem, für welchen Plan Sie sich entscheiden.

Evernote: Web-Clipping-King

Evernote ist ein ganz anderes Kaliber als OneNote. Es bietet zwar die gleichen Grundfunktionalitäten: die Möglichkeit, Notizen zu erstellen, zu organisieren und mit mehreren Plattformen (Windows, macOS, iPadOS, iOS, Android, Web) zu synchronisieren. Dabei bietet die App im Vergleich zu OneNote allerdings eine signifikant farbenfrohere und einladendere Benutzeroberfläche – und eignet sich hervorragend, um Web-Content auszuschneiden und abzuspeichern.

Der Startbildschirm von Evernote bietet diverse Widgets für den schnellen Zugriff auf Notizen, Notizbücher, kürzlich aufgenommene Bilder und vieles mehr. Ein zusätzliches Suchfeld garantiert zudem, dass Sie immer finden wonach Sie suchen. Die Widgets auf Ihrem Startbildschirm können Sie ganz nach Ihren Wünschen hinzufügen oder entfernen.

Evernote bietet allerdings nicht annähernd so viele Werkzeuge zur Erstellung von Notizen wie OneNote. Zu den verfügbaren Features gehören zum Beispiel:

Texte erstellen, bearbeiten und formatieren,
Tabellen, Dateien und Bilder einbetten,
Unterstützung für Touch-Devices und -Stifte,
Integrierbare Audio- und Videoaufnahmen und
Integration mit Google Calendar (für Outlook geplant) und Google Drive;

Web Clipping

Die Stärke von Evernote liegt wie eingangs bereits erwähnt darin, Inhalte aus dem weltweiten Netz zu erfassen und zu organisieren. Das dazu integrierte Web-Clipping-Tool funktioniert beispielhaft und läuft als Browser-Addon (für Chrome, Firefox, Internet Explorer, Microsoft Edge, Safari und Opera). Die Funktionen variieren dabei je nach Browser leicht. Im Allgemeinen bieten Google Chrome und Microsoft Edge dabei das zuverlässigste Erlebnis.

Die Inhalte, die Sie mit Evernote aus dem Netz ziehen, lassen sich auch mit Tags versehen und zu Notizen hinzufügen. Darüber hinaus verfügt der Clipper auch über nützliche Markierungswerkzeuge für Screenshots. Erstellte Notizen dürfen selbstverständlich auf Knopfdruck mit spezifischen Kollegen oder auch über soziale Medien geteilt werden.

Versionsunterschiede

Die Windows-, Mac-, iPadOS-, iOS-, Android– und Web-Versionen von Evernote weisen alle ein ähnliches Erscheinungsbild auf und verfügen über die gleichen Widgets und dasselbe Layout.

KI-Funktionen

Auch Evernote integriert inzwischen künstliche Intelligenz. Zum Beispiel in Form von KI-Transkriptionen, semantischen Suchen und auch in Form eines Assistenten:

You’ve heard about Evernote v11, now see it in action. ⚡📹

Watch Product Lead @fedesimio demo the new AI Assistant, Semantic Search, and AI Meeting Notes, and share the story of how Evernote got to v11.

We’re excited to start this new chapter together. V11 is available for… pic.twitter.com/9d8DMmRVLF
— Evernote (@evernote) January 27, 2026

Storage und Preisgefüge

Die Basisversion von Evernote ist kostenlos, jedoch auf 60 MB neue Notizen pro Monat sowie die Synchronisierung zwischen zwei Geräten limitiert – und enthält keine erweiterten Funktionen.

Abonnement-Pläne erschließen weitere Features, beispielsweise die Möglichkeit, Notizen in Präsentationen umzuwandeln, PDFs und Anhänge zu durchsuchen und die Integration mit weiteren Services wie Slack und Microsoft Teams.

Das Starter-Abo richtet sich dabei an Einzel- beziehungsweise Privatpersonen und kostet 6,65 Euro pro Monat (oder 79,90 Euro pro Jahr).
Das Advanced-Abo ist auf Power User ausgelegt und kostet 16,66 Euro pro Monat (oder 199,99 Euro jährlich).
Enterprise-Pläne werden hingegen individuell auf das jeweilige Unternehmen zugeschnitten und bieten unter anderem gemeinsame Arbeitsbereiche, dedizierten Support und zentrale Management-Tools.

OneNote oder Evernote?

Wenn Sie in erster Linie ein Tool suchen, mit dem Sie auf einfache Weise Inhalte aus dem Internet erfassen, organisieren und finden können, sollten Sie zu Evernote greifen. Wollen Sie einfach nur Notizen erstellen und diese bestmöglich organisieren – oder nutzen bereits Microsoft 365 – dann dürften Sie mit OneNote glücklich werden. Oder Sie verwenden beide Apps einfach in Kombination. (fm)

Dieser Beitrag ist im Original bei unserer Schwesterpublikation Computerworld.com erschienen.

HPR4688: Downloading Podcasts with a Shell Script

Wed, 22 Jul 2026 02:06:46 +0200

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 do not have any interest in downloading your podcasts using this method, you may find some of the methods useful or interesting.

It is the principles that are discussed here that are important, rather than the implementation.

I realize that there are already a number of different podcast download programs available, including at least one written in bash.

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.

If so, then I hope the following is of some use to you.

If not, then you may still find some of the things discussed here to still be of interest.

Some of the subjects I cover include

wget to a user defined file name.

parsing xml with xmllint.

using inotifywait to trigger an action when a file is created or modified.

using notify-send to send a message to the notification area.

and

a way of allowing a cron job to send a message to the user interface.

03 Background

There has been an ongoing discussion in comments to some HPR episodes about problems downloading HPR podcast episodes.

Apparently some people have been experiencing problems with the way the episode URLs are structured.

I am afraid that I don't fully understand the nature of these problems, so I won't be addressing that problem directly.

Instead, I will present a bash script that I have written which can be used to download HPR podcasts.

This bash script can be run using cron to automatically fetch new HPR podcasts and save them to a designated directory.

This is a simplified version of a script that I have used for years to download HPR and other podcasts.

I won't try to read the full bash script out in this podcast, as that would be a bit dull to listen to.

I will instead describe what each section does and why I chose to do things that way.

Perhaps other people can offer suggestions of better ways to do things.

I will post the full bash script in the show notes.

06 Fetching Podcasts

The standard way of distributing podcasts is to publish an RSS feed containing URL links to the audio files.

RSS is a very long established and widely supported mechanism for this and other purposes.

An RSS feed is basically an XML document which can be accessed over HTTP.

These URLs contained in the RSS XML document can then be used to download the actual audio files, such as MP3 or OGG files.

Basically what we need to do is the following

• Download the RSS XML document.

• Extract the URL links to the audio files.

• 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.

• Make a list of the new URLs.

• Go through this list of new URLs and download each of the new audio files.

• Check to see that we actually received the new audio file.

• Add the URLs of the files we successfully downloaded to our saved list of podcast URLs

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.

We may wish to receive a notification of when a new podcast has arrived however.

We would probably also wish to receive notification of any errors or failures.

10 Fetching Podcasts - The Preliminaries

Our desire to be able to run the script automatically imposes some requirements on our solution.

To schedule the script we will use cron.

Cron is a Linux facility to run scripts on a schedule.

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.

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.

I will skip over the details of these, although I may make reference to them later.

13 Get the RSS Data

The first thing of real substance to do is to fetch the current RSS feed data.

I have put this in a bash function called getrssurldata

The contents of this function are a one liner, but with a number of elements chained together through pipes.

14 Downloading the RSS XML Document

• First we use wget, which is a standard command on most Linux distros.

• We specify four things.

• First we set a timeout. I have chosen 20 seconds.

• Next we set the retry limit. I have chosen 3.

• Then we specify that the output of wget is sent to stdout rather than saved as a file.

• This is done by using the -O option followed by a space and then a dash.

• 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.

• Then we specify the URL of the HPR RSS feed.

16 Contents of the XML Document

This gives us the HPR RSS XML document.

There are about 5,000 lines in this RSS document.

Most of those lines are the show notes which are also included in the feed.

17 Extracting the Podcast Episode URLs

There are only 10 lines of the document that contain information that we are interested in however.

These lines are enclosed in "enclosure" XML tags.

We just need to find those lines and separate out the URLs

18 Standard Command Line Tools

There are two ways that we can do this.

One is to use a combination of grep, sed, and cut.

Grep can find the lines containing the enclosure tags.

Sed and cut can extract the URL from the surrounding extraneous data.

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.

This may be an acceptable problem in practical terms, but we can do better.

20 Using an XML Parser

The other method is to actually parse the XML document.

there are at least two command line XML parsers that I am aware of.

These are "xmllint", and "xlmstarlet".

I have used xmllint in this example.

I have not used xmlstarlet, so I can't offer any comment on how easy or difficult to use it is.

I won't give a detailed explanation of all the things that xmllint can do.

It has many features, most of which, as the name suggests, have to do with finding formatting problems with the XML itself.

Describing everything it can do would be at least one episode in itself.

I will instead just give the particular command used and explain each element of it.

In this example assume that we are piping the output of wget directly into xmllint.

The complete command is

xmllint --xpath "//channel/item/enclosure/@url" - | cut -d'"' -f2

In this example,

xmllint is the name of the command.

--xpath tells it to parse the document according to the string which follows.

"//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.

The "-" which follows tells it to look for input from stdin rather than from a file.

The result is a string which has the url attribute name, an equal sign, and the URL that we want enclosed in quotes.

To get just the URL itself, we pipe the output from xmllint into cut, using the doublequote characters as delimiters.

We then save the result in a temporary file.

25 Finding the New Episodes

Next we wish to find the new podcast episodes.

Each HPR episode is identified by a unique URL.

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.

https://hub.hackerpublicradio.org/ccdn.php?filename=/eps/hpr4659/hpr4659.mp3

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.

This is simple, but has a drawback.

Some podcasts occasionally change distributors.

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.

With HPR we could get around this by extracting just the file name and looking for that instead of the full URL.

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.

Since the feed has a maximum of only 10 episodes in it however, that isn't really that big of a problem.

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.

29 Downloading the New Podcasts

We should now have a list of URLs for the new podcasts we do not already have.

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.

Therefore, we need to iterate through the file of new podcast URLs and download each one.

Before we do that however, we should check to see if there is in fact anything new to download.

To do this, simply use "wc -l" to count the number of lines in the list of new URLs and save the resulting number.

If this number is zero, there is nothing to download, we can skip the download step.

As an additional check, we should see if the number of downloads exceeds some threshold value that we wish to set.

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.

If we do exceed our download limit, then we need to log an error and skip downloading.

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.

We can do that using the "basename" command.

We will use this to specify the name that we use when we save the audio file.

HPR has a very well formed file name.

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.

Next we download the audio file using wget.

This is similar to how we downloaded the RSS feed, but with a few changes.

One is that I have increased the timeout to 90 seconds.

This may not have been necessary, but seemed like a good idea.

The next is that when specifying the output file name using -O, we use the file name we extracted from the URL.

The third is that we specify a destination directory using the -P option.

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.

We did this using an "if" statement with the "-s" option.

If the file was found and not zero, then we add that URL to a temporary list of downloaded URLs.

If the file was not present, or was zero length, we output an error message to an error log.

I will come back to this point later.

Next, if there is more that one podcast to download we sleep for 3 seconds.

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..

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.

While we are at it, we should use "tail" to trim the permanent log to keep it from growing indefinitely.

This limit should be several times bigger than the number of files in the RSS feed.

In this case I selected 50.

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.

We have now successfully downloaded at least one HPR podcast.

41 Notify the User of Events

It would be convenient to be informed of new podcast downloads when they occur, and also be notified of any errors.

One of the limitations of cron jobs is that they cannot access the user interface.

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.

42 inotifywait

The solution to this is to use "inotifywait" to monitor particular files and directories for changes.

The man page for inotifywait states the following -

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.

End of quote.

In many Linux distros, inotifywait is provided by the "inotify-tools" package.

I won't go over all the features of inotifywait.

Instead, I will just describe how to use it for our purposes here.

45 inotifywait Modes

I should point out first though that inotifywait operates in two different modes.

In the normal default mode, it exits after being triggered by an event and must be re-established again in order to resume monitoring.

In monitor mode, which is enabled by using the "-m" option, it runs indefinitely, responding to events.

I will use the default mode here.

The man page for inotifywait provides a simple example that we could copy and modify for our purposes.

A great many examples that you will find are based on this example.

However, it doesn't quite do what we want, so we need to change a few things.

47 podfetchnotify

The first shell script is one which monitors for the arrival of new podcasts and sends a notification to the user.

I will call this "podfetchnotify".

The complete scripts are in the show notes, I will just provide a brief description here.

48 Setting Up Event Watches Using inotifywait

The script is enclosed in a while loop which run indefinitely.

In the first line inside the while loop, we call inotifywait.

inotifywait will then block until the event it is told to look for occurs.

In short, execution of the script will wait there until an event occurs.

The names of the events are listed in the man file.

In this case we are looking for "modify", "create", and "moved_to".

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.

50 Problems When Testing Using Text Editors

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.

Instead it treats this as a new file with the same name, with the original file being erased.

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.

If you wish to test this realistically, then use "echo" to overwrite the file by using I/O redirection.

51 Capturing Output

In my example I capture the output from standard out into a variable, but I don't do anything with it.

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.

There are details about this in the man page.

On the next line we capture the exit code using "$?"

52 Responding to Exit Codes

If the exit code was zero, then a monitored event was triggered and there should a new podcast in the directory.

In this case we display a message indicating that a new podcast has arrived.

I will describe how to send notifications shortly.

If the exit code was not zero, then an error occurred.

An example of such an error would be if the directory were not present when monitoring was started.

In this case we display a message indicating that a fatal error has occurred and then exit.

53 Delay for More Podcasts

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.

In this case I chose to wait for 60 seconds.

We have now completed the process and can return to the top of the loop and resume waiting using inotifywait.

55 Sending Notifications to the User

I mentioned above about sending notification messages to the user.

In the Gnome desktop, notification messages appear from the centre of the top bar in a list.

Other desktops or operating systems may have something similar.

To send a notification message to the notification area, you use the "notify-send" command.

Simply follow notify-send with a quoted string and it will be displayed in the notification area.

57 podfetcherrornotify

The second shell script is one which notifies the user of errors.

I will call this "podfetcherrornotify".

With this shell script we set up a watch on a file which contains any error messages from podfetch.

This script is very similar to podfetchnotify.

The exceptions are

With inotifywait we only monitor for "modify".

There is no sleep command at the end of the loop.

Instead we sleep for a few seconds just after getting the exit code from inotifywait.

This helps prevent problems caused by race conditions.

Next we check the inotifywait exit code.

If it was zero, then we read the error report file and send a notification message to the user containing that error message.

If it was not zero, then we check to make sure that the directory that should contain the error log exists.

If it does not exist, then we send a notification message to that effect to the user and terminate the script.

If the directory exists, then we check to see if the error message file used for signalling exists.

If the file does not exist, then we create it.

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.

By creating the file we correct the cause of the error and allow inotifywait to operate normally.

Finally we increment an error counter and check to see if the limit is exceeded.

If there are excessive errors, then send a notification message to the user and exit.

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.

The error counter is reset every time the inotifywait exit status is ok, so occasional unexpected glitches should be something that is ignored.

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.

65 Installing the Scripts

Next I will describe how to install and prepare the scripts to run.

We need to perform the following steps.

• First, we need to create a directory to hold the scripts and their associated data files.

• Next we need to create a directory to hold the downloaded podcasts.

• Then we must copy the scripts to these directories and make them executable.

• Then, we must edit the scripts to have the file path in the script match the locations of the new directories that we created.

• 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.

• Then we need to run each script manually from the command line to check for errors.

• If podfetch ran correctly, it should download the most recent 10 podcasts during this test.

68 Adding podfetch to the Crontab

The above describes how to run the scripts manually.

In order to fetch podcasts automatically, we need to add the podfetch script to the cron schedule.

To do this, open a terminal.

Type "crontab -e", and then press return.

A text editor should open up containing the crontab file.

On Ubuntu, this editor is GNU nano.

Enter the appropriate cron parameters.

I will provide an example here for running it 12 minutes past the hour every three hours.

12 */3 * * * /home/username/pathtofiles/podfetch.sh

I won't explain cron in detail here.

The example that I have just given should be good enough for most people.

The "*/3" parameter will cause it to run every three hours.

The "12" parameter will cause it to run 12 minutes past the hour when it does run.

Checking every three hours should be good enough for most people, but you can adjust that as you see fit.

I would recommend however that you don't check more frequently than once per hour.

Checking more frequently than necessary puts extra load on the distribution servers.

It is very unlikely that you really do need each new episode the moment it is available.

I would also recommend changing the "12" parameter to some other random minute value.

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.

The file path parameter should of course match the actual path to wherever you have located the script, including the correct user name.

75 Making the Notification Scripts Start Automatically

The two notification scripts can be made to start automatically.

The exact method to do this may vary according to distribution or desktop.

On Ubuntu this is done using the Startup Applications Preferences GUI program, which should come already installed.

I won't go into details on this here, it should be fairly self evident how to use it once you see it.

What this program does is to create ".desktop" files in the ".config/autostart" directory in your home directory.

These ".desktop" files are all run automatically on start up.

Once you have added the notification scripts, you will need to log out and then log back in to make them active.

79 Conclusion

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.

The download script described here is tailored specifically for use with HPR only.

However, it was derived from a larger script that downloaded other podcasts as well, based on information read in from a text file.

If you are feeling ambitious, you can add those features back into this to handle all of the podcasts that you listen to.

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.

I look forward to seeing you again later on another episode of Hack Public Radio.

# ======================================================================

podfetchdownloader

#!/bin/bash

# Fetch pending HPR podcasts listed in the HPR RSS feed.

# 8-Jun-2026

# Licensed under GPLv3 or later.

# ======================================================================

# Today's date and time as YYYYMMDDHHMMSS.

podttimestamp=$( date +"%Y%m%d%H%M%S" )

# The absolute path to the script. This is necessary when running it

# using a cron job.

podpath="/home/me/Apps/hprfetch"

# This is the absolute path to where to store the podcast files.

podfilepath="/home/me/Music/Podcasts/HPR"

# Create the full path names here for all the text files used.

podcastsfetched="$podpath/podcastsfetched.txt"

poderrorslog="$podpath/poderrorslog.txt"

poderrorsreport="$podpath/poderrorsreport.txt"

tmpoldurlssorted="$podpath/tmpoldurlssorted.txt"

tmppodsnew="$podpath/tmppodsnew.txt"

tmppodstodownload="$podpath/tmppodstodownload.txt"

tmppodserrors="$podpath/tmppodserrors.txt"

tmppodcastsfetched="$podpath/tmppodcastsfetched.txt"

tmplog="$podpath/tmplog.txt"

# The URL for the HPR RSS feed.

PodURL="http://hackerpublicradio.org/hpr_rss.php"

# Limit on number of podcasts to download.

DownloadLimit=11

# Name of the podcast.

PodName="Hacker Public Radio"

# ======================================================================

# Check if the required paths exist.

# If this path does not exist, cannot log the error.

if [[ ! -d "$podpath/" ]]; then

echo "$podttimestamp Error - Could not find $podfilepath."

exit 1

# Where to store the podcast file fetched.

if [[ ! -d "$podfilepath/" ]]; then

echo "$podttimestamp Error - Could not find $podfilepath." >> $tmppodserrors

# Copy the errors log from the temporary errors file to the permanent files.

LogErrors

exit 1

# ======================================================================

# Check if the podcast log exists. We read it before we write to it,

# so it must exist or we will hang on it not being present.

if [[ ! -e $podcastsfetched ]]; then

touch $podcastsfetched

# ======================================================================

# Delete the specified files if they exist.

# This accepts multiple file names in a variable number of parameters.

CleanupFiles ()

{

# $@ accepts multiple parameters.

for f in "$@"; do

# Check if the file exists.

if [ -e "$f" ]; then

rm "$f"

done

}

# ======================================================================

# Copy the errors log from the temporary errors file to the permanent files.

LogErrors () {

if [ -e $tmppodserrors ]; then

# The permanent log.

cat $tmppodserrors >> $poderrorslog

# This file is monitored for display by other scripts.

cat $tmppodserrors > $poderrorsreport

}

# ======================================================================

# Get the URL data from an RSS feed

GetRSSURLData () {

wget --timeout=20 --tries=3 -O - "$PodURL" \

| xmllint --xpath "//channel/item/enclosure/@url" - | cut -d'"' -f2 \

| sort > $tmppodsnew

# This is an alternate method that does not use xmllint.

# However, it is not as robust. If someone were to include the

# first grep search pattern in their show notes, then it would

# look for that as a valid tag and output the following text

# as a URL.

#wget --timeout=20 --tries=3 -O - "$PodURL" | grep " $tmppodsnew

}

# ======================================================================

# Find which podcasts we do not already have.

FindNewPodcasts () {

cat $podcastsfetched | sort > $tmpoldurlssorted

comm -13 $tmpoldurlssorted $tmppodsnew > $tmppodstodownload

rm $tmpoldurlssorted

}

# ======================================================================

# Download the podcasts.

DownloadPodcasts() {

# Clear out previous temporary list of downloaded podcasts.

true > $tmppodcastsfetched

for i in $( cat $tmppodstodownload )

# Extract the file name from the URL.

fname=$( basename $i )

outputpodname="$podfilepath/$fname"

# Download the file.

wget --timeout=90 --tries=3 -P $podfilepath $i -O "$outputpodname"

# Check if the file exists and is not empty.

if [[ -s "$outputpodname" ]]; then

echo $i >> $tmppodcastsfetched

else

echo "$podttimestamp Error - $outputpodname was not found or is empty." >> $tmppodserrors

# Delay a reasonable length of time between multiple downloads.

if (( $PodCount > 1 )); then

sleep 3

done

# Add the list of files downloaded to the log.

# Check if the list exists and is not empty.

if [ -s $tmppodcastsfetched ]; then

cat $tmppodcastsfetched >> $podcastsfetched

# Trim the log file to keep it from growing indefinitely.

tail -n50 $podcastsfetched > $tmplog

mv $tmplog $podcastsfetched

# Remove the tmp file now that we are done with it.

rm $tmppodcastsfetched

}

# ======================================================================

# Clean up any left over files.

CleanupFiles "$tmppodsnew" "$tmppodstodownload" "$tmppodserrors" "$tmppodcastsfetched"

# Get the RSS data.

GetRSSURLData

# Find which podcasts are new.

FindNewPodcasts

# Count how many new podcasts there are.

PodCount=$( cat $tmppodstodownload | wc -l )

# If no podcasts to download, skip this.

# If too many podcasts for this feed, then log an error and skip.

# This error will keep repeating until something is done about it.

if (( $PodCount > 0 )); then

if (( $PodCount > $DownloadLimit )); then

echo "$podttimestamp Too many podcasts for $PodName : $PodCount." >> $tmppodserrors

else

# Download the podcasts listed in the temp file.

DownloadPodcasts

# ======================================================================

# Copy the errors log from the temporary errors file to the permanent files.

LogErrors

# Clean up temp files.

CleanupFiles "$tmppodsnew" "$tmppodstodownload" "$tmppodserrors" "$tmppodcastsfetched"

# ======================================================================

END OF FIRST SHELL SCRIPT

START OF SECOND SHELL SCRIPT

podfetchnotify

#!/bin/bash

# Part of Podfetch.

# This monitors for new files appearing in the new podcasts directory.

# This should be run as a background task.

# Install it using the "Startup Applications" utility in Ubuntu.

# ======================================================================

# Path where new podcasts are to be stored.

podfilepath="/home/me/Music/Podcasts/HPR"

# ======================================================================

# Wait for the podcast directory to be modified.

while true; do

# Check for new files.

errmsg=$( inotifywait -e modify -e create -e moved_to $podfilepath )

result=$?

# Check if exited due to new podcast, or if some error.

if (( result == 0 )); then

# Success, signal new podcast.

notify-send "New HPR podcast available."

else

# Check to make sure the directory exists.

# If it doesn't exist, there isn't much we can do to fix it.

if [ ! -e "$poderrorspath" ]; then

notify-send "Podfetch error: Podcast directory not found $poderrorspath"

exit 1

# Wait a bit so that multiple new files don't keep re-triggering the notification.

sleep 60

done

# ======================================================================

END OF SECOND SHELL SCRIPT

START OF THIRD SHELL SCRIPT

podfetcherror

Created Tuesday 23 June 2026

#!/bin/bash

# Part of Podfetch.

# This monitors the Podfetch error reporting file for new errors.

# This should be run as a background task.

# Install it using the "Startup Applications" utility in Ubuntu.

# ======================================================================

# Where the Podfetch program error report file is located.

poderrorspath="/home/me/Apps/hprfetch"

# The full path and file name.

poderrorsreport="$poderrorspath/poderrorsreport.txt"

# ======================================================================

# Error counter.

errcount=0

# Wait for the poderrorsreport file to be modified.

while true; do

errmsg=$( inotifywait -e modify $poderrorsreport )

result=$?

# Wait a bit to ensure that writing to the file is complete.

sleep 3

if (( result == 0 )); then

# Get the latest error message.

# Cut out the date stamp at the start of the line and take the rest.

poderr=$( tail -n $poderrorsreport | cut -d" " -f2- )

notify-send "Podfetch error: $poderr"

# Reset the error counter every time there is a successful result.

errcount=0

else

# Check to make sure the directory exists.

if [ ! -e "$poderrorspath" ]; then

notify-send "Podfetch error: error report path not found $poderrorspath"

exit 1

# Check if the file we are trying to monitor exists.

# If not, then create an empty file for error signaling.

if [ ! -e "$poderrorsreport" ]; then

echo > $poderrorsreport

# Increment the error counter.

count=$(( count + 1 ))

if (( count > 3 )); then

notify-send "Podfetch error: Excessive unknown errors, exiting."

exit 1

done

# ======================================================================

Provide feedback on this episode.

Qualcomm engineers submit mainline Linux kernel patches for the Snapdragon X2 Elite Extreme-powered ASUS Zenbook A16 (UX3607OA)

Wed, 22 Jul 2026 01:07:21 +0200

Konrad Dybcio of Qualcomm has posted an initial patch series to the Linux kernel mailing list aimed at bringing mainline support to the ASUS Zenbook A16 (UX3607OA) powered by the 18-core Snapdragon X2 Elite Extreme platform.

https://www.phoronix.com/news/Qualcomm-Zenbook-A16-X2EE

This high-end ARM laptop features a 2880 x 1800 OLED screen, 48GiB of RAM, NVMe storage, and a System-In-Package reference design distinct from smaller SKUs.

According to the patch submission, the current status of working hardware components includes:

Display & GPU: GPU, display output, and HDMI port (with Iris video accelerator patches in flight)
Audio: 4-speaker audio playback
Input & Peripherals: Keyboard, touchpad, lid switch, onboard SD Card slot (RTS5329)
Connectivity: Wi-Fi and Bluetooth (QCC2072)
Power & Indicators: Charging, Type-C/Type-A ports, and privacy LEDs

The patch series relies on prerequisite SoCCP and TCSR platform series dependencies. More technical details and the full patch breakdown can be reviewed on the Linux Kernel Mailing List Archive:

https://lore.kernel.org/lkml/20260721-topic-a16_submission-v1-0-8ea213130d05@oss.qualcomm.com/

submitted by /u/Putrid_Draft378
[link] [comments]

Megaports Neocloud erhält seine Speicherschicht: Wasabi treibt Megaport Storage an.

Wed, 22 Jul 2026 00:41:03 +0200

Wasabi dient als skalierbare Speicherschicht für KI, Analysen, Unternehmensdaten und Cybersicherheit. Über private Verbindungen können Unternehmen ...

Google's Gemini 3.6 Flash model cuts AI agent token costs by up to 65% on long horizon engineering tasks —and 3.5 Pro is on the way

Tue, 21 Jul 2026 23:33:56 +0200

Google DeepMind today released three new proprietary AI models it says are among its most token-efficient yet: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber.

The models aim to make AI agents faster, smarter, and cheaper at scale. Google is pricing Gemini 3.6 Flash at $1.50 per one million input tokens and $7.50 per one million output tokens through its application programming interface (API), while Gemini 3.5 Flash-Lite costs a staggeringly cheap $0.30/$2.50 per million tokens in/out.

Compare that to the $1.50/$9.00 per 1M tokens for Gemini 3.5 Flash, and the $2/$12 for Gemini 3.1 Pro Preview, and the savings are considerable. However, Google's prior generation Gemini 3.1 Flash-Lite still remains the search giant's "most cost-efficient" model at $0.25/$1.50 per 1M tokens. Yet, it remains 2X slower than the new, more expensive Gemini 3.5 Flash-Lite, giving those enterprises who value speed more "bang" for their buck.

VB Frontier AI Model API Pricing Comparison Chart (Late July 2026 Shortlist)

Model	Input ($/1M)	Output ($/1M)	Total ($/1M)	Source
MiMo-V2.5 Flash	$0.10	$0.30	$0.40	Xiaomi
deepseek-v4-flash	$0.14	$0.28	$0.42	DeepSeek
deepseek-v4-pro	$0.435	$0.87	$1.305	DeepSeek
MiniMax-M3	$0.30	$1.20	$1.50	MiniMax
LongCat-2.0 — limited-time promo	$0.30	$1.20	$1.50	LongCat
Gemini 3.1 Flash-Lite	$0.25	$1.50	$1.75	Google
Qwen3.7-Plus	$0.40	$1.60	$2.00	Alibaba Cloud
MiMo-V2.5	$0.40	$2.00	$2.40	Xiaomi
Gemini 3.5 Flash-Lite	$0.30	$2.50	$2.80	Google
LongCat-2.0 — standard	$0.75	$2.95	$3.70	LongCat
MiMo-V2.5 Pro (≤256K)	$1.00	$3.00	$4.00	Xiaomi
GLM-5.2	$1.40	$4.40	$5.80	Z.ai
GPT-5.6 Luna	$1.00	$6.00	$7.00	OpenAI
Grok 4.5	$2.00	$6.00	$8.00	xAI
MiMo-V2.5 Pro (>256K)	$2.00	$6.00	$8.00	Xiaomi
Gemini 3.6 Flash	$1.50	$7.50	$9.00	Google
Qwen3.7-Max	$2.50	$7.50	$10.00	Alibaba Cloud
Gemini 3.5 Flash	$1.50	$9.00	$10.50	Google
Gemini 3.1 Pro Preview (≤200K)	$2.00	$12.00	$14.00	Google
GPT-5.6 Terra	$2.50	$15.00	$17.50	OpenAI
GPT-5.4	$2.50	$15.00	$17.50	OpenAI
Kimi K3	$3.00	$15.00	$18.00	Moonshot AI
Gemini 3.1 Pro Preview (>200K)	$4.00	$18.00	$22.00	Google
Claude Opus 4.8	$5.00	$25.00	$30.00	Anthropic
GPT-5.5	$5.00	$30.00	$35.00	OpenAI
GPT-5.5 Instant (chat-latest)	$5.00	$30.00	$35.00	OpenAI
Sakana Fugu Ultra (≤272K)	$5.00	$30.00	$35.00	Sakana AI
GPT-5.6 Sol	$5.00	$30.00	$35.00	OpenAI
Claude Fable 5 / Claude Mythos 5	$10.00	$50.00	$60.00	Anthropic

No price was provided yet for the specialty Gemini 3.5 Flash Cyber model, which, as its name would imply, is designed for cybersecurity researchers and red teamers to patch bugs.

While the prices are among the middle-low end of all major AI models globally, the fact that Google designed them to use less tokens overall also should drive down costs for enterprises beyond what the sticker price shows (since you'll be paying for fewer total tokens at any rate).

Gemini 3.6 Flash and Gemini 3.5 Flash-Lite are available immediately through the Gemini API in Google AI Studio and Android Studio, as well as within the consumer Gemini application and Google Search. According to a separate Google blog post, Gemini 3.5 Flash Cyber will be available "exclusively available to governments and trusted partners via CodeMender soon" — CodeMender being Google's proprietary AI code bug-fixing agent released last year.

As with previous Gemini models, these are all proprietary and "closed source," thus, they can only be obtained through Google's official API and that of its partners, as opposed to an open-source license like MIT or Apache 2.0.

One conspicuous omission noted by developers on X and social media: where is the larger, more powerful, flagship Gemini 3.5 Pro model Google previously alluded would be released this summer? After all, Gemini 3.1 Pro, the prior flagship, debuted back in February 2026, and rivals OpenAI and Anthropic have since released several more generations of flagship updates far more powerful than Google's.

Google technical staffer Logan Kilpatrick responded to one such inquiry on X, writing: "Gemini 3.5 Pro is currently testing with partners and we plan to make it broadly available as soon as it’s ready."

Google's release signals that the immediate future of AI lies in agentic capabilities—systems that operate autonomously over extended periods.

If early large language models are akin to massive, fuel-hungry freight trains capable of hauling incredible loads at immense cost, the new Flash series represents a fleet of nimble, hyper-efficient hybrid delivery vans.

Efficiency gains ranging from 17% to 65% reduced tokens for strong results on third-party benchmarks

Under the hood, Gemini 3.6 Flash achieves significant efficiency gains. The model reduces output token usage by 17% compared to its predecessor, Gemini 3.5 Flash, according to the Artificial Analysis Index maintained by the independent third-party AI benchmarking group of the same name.

In specific long-horizon software engineering benchmarks like DeepSWE, which measures how well agents complete multi-step engineering tasks from scratch, the token savings reach up to 65%.

This reduction means the model requires fewer reasoning steps and tool calls to complete the exact same multi-step workflow. Think of token efficiency like fuel economy in a vehicle.

When an AI model takes a convoluted path to solve a problem, it burns through more computational fuel, driving up the final cost for the developer. By streamlining its internal logic, Gemini 3.6 Flash arrives at the correct answer faster and cheaper.

While Google's materials did not specify the exact architectural or algorithmic changes used to achieve this token efficiency, they noted that the model "takes fewer reasoning steps and tool calls to accomplish multi-step workflows" and exhibits reduced "verbosity."

The official model cards released by Google reveal that both Gemini 3.6 Flash and Gemini 3.5 Flash-Lite feature a 1-million-token input context window alongside a max output limit of 64,000 tokens, with both models sharing a knowledge cutoff date of March 2026.

Respectable benchmark performance at low cost

The technological improvements extend to concrete capabilities. Gemini 3.6 Flash scores 49% on the DeepSWE benchmark, a notable increase from the 37% achieved by version 3.5.

It also pushes machine learning engineering performance higher, scoring 63.9% on MLE-Bench compared to 49.7% previously. Furthermore, Google integrates computer use as a built-in client-side tool via the Gemini API and Gemini Enterprise, reflecting an OSWorld-Verified score of 83.0%, up from 78.4%.

The model also tackles knowledge work with greater proficiency, outperforming its predecessor on benchmarks like GDPval-AA v2 by moving from a score of 1349 to 1421.

To ensure safety amidst these capability upgrades, Google deploys enhanced Frontier Safety safeguards. These protections harden the model against jailbreaks and mitigate risks in Chemical, Biological, Radiological, and Nuclear domains, as well as cyber offense misuses.

The engineering team trains the model to minimize refusals for beneficial uses, striking a necessary balance between strict security and practical utility.

Models for low-cost coding, agentic, and cybersecurity use cases — respectively

Google divided its new offerings into three distinct products tailored for different operational needs.

The model executes complex code migrations using multi-agent orchestration frameworks with lower latency and higher quality than earlier iterations. Furthermore, 3.6 Flash aids in developing photographic texture extractors for 3D workflows using canvas interfaces.

Gemini 3.5 Flash-Lite targets environments where high throughput and absolute minimal latency are non-negotiable. Google designates it as the fastest model in the 3.5 series.

As measured by Artificial Analysis, the model processes 350 output tokens per second, making it highly effective for agentic search and massive document processing workloads. Artificial Analysis notes this is about twice as fast as prior generation model Gemini 3.1 Flash-Lite.

Developers can configure 3.5 Flash-Lite to prioritize low-latency execution for high-volume tasks using minimal thinking levels, or engage higher thinking levels to process complex multi-step subagent workloads.

Despite its lite designation, it outperforms the standard Gemini 3 Flash on several key agentic and coding evaluations, including SWE-Bench Pro, where it scores 54.2% compared to 49.6%, and OSWorld-Verified, scoring 74.0% versus 65.1%.

The model extracts product features from massive datasets, generates interactive web design concepts, and scales receipt translation seamlessly.

The third product, Gemini 3.5 Flash Cyber, represents a highly specialized deployment. Google fine-tuned this model specifically to find and fix cybersecurity vulnerabilities. It integrates directly with Google's CodeMender agent.

In practice, multiple 3.5 Flash Cyber agents work concurrently to produce a single, comprehensive vulnerability report, achieving competitive performance at the frontier on the CyberGym benchmark, even getting within range of Anthropic's much-hyped Mythos model.

Google did not specify an exact numerical cost for 3.5 Flash Cyber, stating only that it is fine-tuned "at a lower price per token than larger models.

Commercial licensing only

The licensing framework for the new Gemini models carries profound implications for developers and enterprise users. Google deploys Gemini 3.6 Flash and 3.5 Flash-Lite under a commercial, proprietary API model. Unlike open-source software governed by licenses such as the MIT License or the GNU General Public License, developers do not gain access to the underlying model weights, training data, or source code.

An MIT or GPL license grants users the freedom to download the codebase, modify the internal architecture, self-host the deployment, and distribute the software infrastructure independently. In contrast, Google's API approach means developers essentially rent access to the intelligence on a strict metered basis. Every prompt and generated response travels through Google's managed servers, incurring a cost based on the strict pricing structure of $1.50 per million input tokens for 3.6 Flash.

This commercial tethering restricts deployment flexibility. Enterprises cannot air-gap the models entirely on their own local secure hardware without establishing specialized, high-tier enterprise agreements with Google Cloud. Developers remain bound by Google's acceptable use policies, arbitrary rate limits, and network requirements, creating a permanent dependency on Google's infrastructure uptime and terms of service.

The licensing for Gemini 3.5 Flash Cyber proves even more restrictive. Acknowledging the dual-use nature of cybersecurity AI—which attackers can weaponize just as easily as defenders can use it to patch systems—Google is for now making the model only available behind a limited-access pilot program, similar to the trend kicked off by Anthropic's Mythos model with its Project Glasswing program, and continued by OpenAI with its staggered rollout for GPT-5.6.

In this case, Google is making 3.5 Flash Cyber exclusively available to governments and trusted partners. This strict gatekeeping prevents open access, prioritizing systemic security over widespread developer innovation.

Looking ahead

Google DeepMind continues to iterate rapidly, but the gap in its product line remains apparent. While the Flash series excels in speed and economy, the industry eagerly awaits the deployment of Gemini 3.5 Pro to gauge Google's absolute frontier capabilities.

Simultaneously, the company confirms that pre-training for Gemini 4 has already commenced.

Until the next major flagship release materializes, developers must optimize their systems using the highly efficient, yet purposefully constrained, Flash architecture.

Stop adding more GPUs: Weka's new storage platform reduces load by caching 100% of an AI model's pre-calculated tokens

Tue, 21 Jul 2026 23:33:22 +0200

GPU memory is the most expensive resource in production AI, and it's also the one running out fastest.

Long context windows and multi-turn conversations force AI models to repeatedly recompute information they've already processed, consuming GPU memory and compute that could otherwise serve additional users or generate new responses.

Instead of treating GPU memory as the limiting resource, why not extend it with much cheaper storage technologies?

Weka, for one, believes that cheap flash storage can close that gap. The company's NeuralMesh 6 software platform, launching alongside its first self-designed hardware line, Wekapod 3, extends what Weka calls Augmented Memory Grid, an approach that aggregates NAND flash to behave like GPU memory at a fraction of the cost.

This is an active and increasingly crowded category. Dell, NetApp, Pure Storage and VAST have all repositioned toward AI infrastructure over the past two years and Weka is one of several vendors arguing it's built for this specific moment rather than adapting to it.

"What we're seeing now with customers is they're chasing availability of compute, and once they get new allocation from anyone, they want to be able to grab it and start running right away," Weka co-founder and CEO Liran Zvibel, told VentureBeat.

The potential payoff is straightforward: better utilization of existing GPU investments, lower inference costs and faster deployment of new AI workloads without waiting months for additional GPU capacity.

The technology is most relevant for organizations already operating AI at scale or expecting rapid growth in usage, particularly enterprises building internal copilots, customer service agents, software engineering assistants or retrieval systems with long context windows. Smaller deployments may see less immediate benefit than organizations where GPU utilization has already become a limiting factor.

Inside Weka's NeuralMesh 6

NeuralMesh 6 adds four capabilities aimed directly at a functionality gap Zvibel says has been costing Weka deals in competitive evaluations.

Composable and virtual multi-tenancy. Composable clusters give anchor tenants full hardware-level isolation, dedicated CPU, memory, and storage. Virtual multi-tenancy runs through Weka's RDMA fabric, delivering network-level isolation that scales past 1,000 tenants per cluster, with provisioning in under 30 minutes. Combined, a single cluster running 50 composable clusters can support up to 50,000 tenants.

Unified file and object storage. Most storage systems keep two separate paths: a file-based path (the standard way servers and applications read and write files, used heavily in training and fine-tuning pipelines) and an object-based path (S3, the format inference and cloud-native tools typically expect). Normally a gateway translates between the two, meaning the data effectively exists twice. Weka's claim is that the same physical data on disk is directly readable through either path at once, no translation layer, no second copy. Zvibel is targeting non-AWS GPU clouds specifically, naming Lambda, Nebius, G42, and CoreWeave, with what he described as roughly two orders of magnitude higher performance than conventional S3 and a capacity-based pricing model instead of per-API charges.

Metadata-first replication. Destination environments become browsable before a full data copy arrives, with data hydrating only when accessed.

"They had to wait for all of that to make it to the other side, and this takes days or weeks, in extreme cases a month," Zvibel said. "We now allow our customers to grab some allocation of new GPUs and get up and running within an hour."

AlloyFlash and Always-On data reduction. TLC and QLC are two types of NAND flash memory. TLC is faster and more durable but costs more per terabyte, while QLC is cheaper and holds more data per chip but is slower. AlloyFlash mixes both within a single cluster, automatically routing latency-sensitive work to TLC while running bulk-capacity workloads on QLC, cutting cost per terabyte without a performance penalty on the work that needs speed. Data reduction now runs by default rather than as an option.

Solving AI's context problem

Multi-tenancy and object storage solve how enterprises and neo clouds operate the platform day to day. A harder problem sits underneath: as context windows and multi-turn interactions grow, so does the GPU compute wasted recalculating work a model has already done. Augmented Memory Grid, a NeuralMesh 6 feature built specifically for this, is Weka's answer.

Every prompt triggers two stages. Prefill calculates attention, the core mechanism behind how large language models process input, and it's computationally expensive. Decode converts that calculation into output and is comparatively lightweight.

The cost shows up hardest in multi-turn sessions like chat or coding, where each new turn re-triggers prefill for everything that came before it, unless that work has been cached.

"If you have 10 turns, you may overcalculate 100 times because you're redoing all of them. If you have 20, you'll overcalculate 400 times," Zvibel said. "You can put two orders of magnitude more NAND than you could afford in shared memory, and we can cache 100% of the pre-calculated tokens, so you never need to redo it."

Where Weka sits competitively

Storage vendors have spent the past year and a half repositioning around AI, and separating genuine capability from repositioned messaging is now a real evaluation problem for buyers.

"The storage world is shifting its focus from serving bits to enterprise workloads to managing data at the speed of AI. We've seen that most clearly over the past 18 months from Dell, NetApp, and Pure," Steve McDowell, chief analyst at NAND Research, told VentureBeat. "The interesting thing is that companies like Weka, and VAST, are the true AI-native data companies, solving these problems since day one."

McDowell singled out Augmented Memory Grid as Weka's clearest technical lead.

"Weka continues to have the most technically capable KV cache implementation on the market with its Augmented Memory Grid," he said. " They were early with this technology, and continue to innovate. This is critical for AI inference, as it enables a level of GPU efficiency that, without question, saves money on GPUs and memory. That’s key for today’s memory and GPU constrained market."

He also flagged Weka's contractual guarantee on its data reduction claims as underappreciated.

"One flying a little under the radar: Weka is putting its money where its mouth is with its contractual guarantees for its data reduction promises," he said.

McDowell's advice to buyers evaluating competing claims from Weka, VAST, Pure and NetApp alike was pointed suggesting that enterprise buyers should look hard at what vendors are promising versus what they're actually delivering.

"A smart buyer will look at how competing vendors are solving real-world problems today," McDowell said. " They do this by talking to organizations running similar workloads at similar scale. If a vendor can't point to that, then it should be a warning sign."

Google's Gemini Flash 5.6 model cuts AI agent token costs by up to 65% on long horizon engineering tasks —and 3.5 Pro is on the way

Tue, 21 Jul 2026 22:56:46 +0200

Google DeepMind today released three new proprietary AI models it says are among its most token-efficient yet: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber.

VB Frontier AI Model API Pricing Comparison Chart (Late July 2026 Shortlist)

Model	Input ($/1M)	Output ($/1M)	Total ($/1M)	Source
MiMo-V2.5 Flash	$0.10	$0.30	$0.40	Xiaomi
deepseek-v4-flash	$0.14	$0.28	$0.42	DeepSeek
deepseek-v4-pro	$0.435	$0.87	$1.305	DeepSeek
MiniMax-M3	$0.30	$1.20	$1.50	MiniMax
LongCat-2.0 — limited-time promo	$0.30	$1.20	$1.50	LongCat
Gemini 3.1 Flash-Lite	$0.25	$1.50	$1.75	Google
Qwen3.7-Plus	$0.40	$1.60	$2.00	Alibaba Cloud
MiMo-V2.5	$0.40	$2.00	$2.40	Xiaomi
Gemini 3.5 Flash-Lite	$0.30	$2.50	$2.80	Google
LongCat-2.0 — standard	$0.75	$2.95	$3.70	LongCat
MiMo-V2.5 Pro (≤256K)	$1.00	$3.00	$4.00	Xiaomi
GLM-5.2	$1.40	$4.40	$5.80	Z.ai
GPT-5.6 Luna	$1.00	$6.00	$7.00	OpenAI
Grok 4.5	$2.00	$6.00	$8.00	xAI
MiMo-V2.5 Pro (>256K)	$2.00	$6.00	$8.00	Xiaomi
Gemini 3.6 Flash	$1.50	$7.50	$9.00	Google
Qwen3.7-Max	$2.50	$7.50	$10.00	Alibaba Cloud
Gemini 3.5 Flash	$1.50	$9.00	$10.50	Google
Gemini 3.1 Pro Preview (≤200K)	$2.00	$12.00	$14.00	Google
GPT-5.6 Terra	$2.50	$15.00	$17.50	OpenAI
GPT-5.4	$2.50	$15.00	$17.50	OpenAI
Kimi K3	$3.00	$15.00	$18.00	Moonshot AI
Gemini 3.1 Pro Preview (>200K)	$4.00	$18.00	$22.00	Google
Claude Opus 4.8	$5.00	$25.00	$30.00	Anthropic
GPT-5.5	$5.00	$30.00	$35.00	OpenAI
GPT-5.5 Instant (chat-latest)	$5.00	$30.00	$35.00	OpenAI
Sakana Fugu Ultra (≤272K)	$5.00	$30.00	$35.00	Sakana AI
GPT-5.6 Sol	$5.00	$30.00	$35.00	OpenAI
Claude Fable 5 / Claude Mythos 5	$10.00	$50.00	$60.00	Anthropic

No price was provided yet for the specialty Gemini 3.5 Flash Cyber model, which, as its name would imply, is designed for cybersecurity researchers and red teamers to patch bugs.

Google's release signals that the immediate future of AI lies in agentic capabilities—systems that operate autonomously over extended periods.

Efficiency gains ranging from 17% to 65% reduced tokens for strong results on third-party benchmarks

In specific long-horizon software engineering benchmarks like DeepSWE, which measures how well agents complete multi-step engineering tasks from scratch, the token savings reach up to 65%.

This reduction means the model requires fewer reasoning steps and tool calls to complete the exact same multi-step workflow. Think of token efficiency like fuel economy in a vehicle.

Respectable benchmark performance at low cost

The technological improvements extend to concrete capabilities. Gemini 3.6 Flash scores 49% on the DeepSWE benchmark, a notable increase from the 37% achieved by version 3.5.

The model also tackles knowledge work with greater proficiency, outperforming its predecessor on benchmarks like GDPval-AA v2 by moving from a score of 1349 to 1421.

The engineering team trains the model to minimize refusals for beneficial uses, striking a necessary balance between strict security and practical utility.

Models for low-cost coding, agentic, and cybersecurity use cases — respectively

Google divided its new offerings into three distinct products tailored for different operational needs.

Gemini 3.6 Flash serves as the heavy-duty workhorse of the trio. It handles complex coding, intricate knowledge work, and multimodal processing with improved precision. Enterprise customers utilize it for demanding tasks such as complex document parsing, intricate chart and data analysis, and long-form report drafting. The model executes complex code migrations using multi-agent orchestration frameworks with lower latency and higher quality than earlier iterations. Furthermore, 3.6 Flash aids in developing photographic texture extractors for 3D workflows using canvas interfaces.

Gemini 3.5 Flash-Lite targets environments where high throughput and absolute minimal latency are non-negotiable. Google designates it as the fastest model in the 3.5 series.

The model extracts product features from massive datasets, generates interactive web design concepts, and scales receipt translation seamlessly.

In practice, multiple 3.5 Flash Cyber agents work concurrently to produce a single, comprehensive vulnerability report, achieving competitive performance at the frontier on the CyberGym benchmark.

Google did not specify an exact numerical cost for 3.5 Flash Cyber, stating only that it is fine-tuned "at a lower price per token than larger models.

Commercial licensing only

Looking ahead

Google DeepMind continues to iterate rapidly, but the gap in its product line remains apparent. While the Flash series excels in speed and economy,

the industry eagerly awaits the deployment of Gemini 3.5 Pro to gauge Google's absolute frontier capabilities.

Simultaneously, the company confirms that pre-training for Gemini 4 has already commenced.

Until the next major flagship release materializes, developers must optimize their systems using the highly efficient, yet purposefully constrained, Flash architecture.

13 Google tips for a fun, productive summer off from college

Tue, 21 Jul 2026 22:56:44 +0200

Discover how college students can use Google AI tools, like Gemini and AI Mode, to prep for grad school, internships and fall courses.

v0.9.1: fix(tui): honor isolated home for session artifacts

Tue, 21 Jul 2026 21:02:29 +0200

Resolve artifact storage through Codewhale's effective home contract so explicit HOME and USERPROFILE subprocess sandboxes work on Windows instead of leaking writes to the host known-folder profile.

Apple Product Prices Could Rise Again as TSMC Plans Higher Chip Costs

Tue, 21 Jul 2026 20:47:27 +0200

Apple customers may face another round of price increases after TSMC reportedly decided to raise chipmaking prices from 2027. Apple has already increased prices across several product categories because of higher memory and storage costs, while analysts also expect new iPhone models to cost more when they launch in September. The company recently raised prices on several products and upgrade options, with some increases exceeding 50%. In a few cases, memory and storage upgrades doubled in price, which made higher-end configurations much more expensive for customers. Apple said it was working to reduce the impact of rising component costs, although many customers expect the new prices to remain permanent. Higher prices also appear likely to affect buying habits, as some users plan to keep their devices longer or choose lower storage options. TSMC Plans Chipmaking Price Increases Nikkei Asia reports that TSMC plans to increase prices for advanced and mature chip production services by between 5% and 10% in 2027. The company reportedly wants to cover higher costs linked to materials, manufacturing equipment, and the construction of new factories outside Taiwan. The report also claims that TSMC may charge customers an additional premium of up to 15% when they increase orders beyond their original forecasts. Apple could face this extra cost when demand for a new iPhone, Mac, or iPad exceeds its initial production estimates. TSMC reportedly completed pricing negotiations with several major customers, although the company declined to discuss specific details. Apple relies heavily on TSMC to manufacture chips for the iPhone, Mac, iPad, Apple Watch, and several other products. Higher chipmaking costs would add more pressure to Apple’s hardware pricing at a time when memory costs have already pushed prices upward. Apple may absorb part of the increase, reduce margins, or pass more of the cost to customers through higher device prices and more expensive upgrade options.

Tycon Systems TPDIN-Monitor-WEB2

Tue, 21 Jul 2026 19:45:30 +0200

View CSAF

Summary

Successful exploitation of these vulnerabilities could result in an attacker accessing sensitive credentials, disrupting connected infrastructure, or manipulating physical equipment, which could present a physical safety risk.

The following versions of Tycon Systems TPDIN-Monitor-WEB2 are affected:

TPDIN-Monitor-WEB2 2.3.9

CVSS	Vendor	Equipment	Vulnerabilities
v3 9.8	Tycon Systems	Tycon Systems TPDIN-Monitor-WEB2	Authentication Bypass Using an Alternate Path or Channel, Cleartext Storage of Sensitive Information

Background

Critical Infrastructure Sectors: Critical Manufacturing
Countries/Areas Deployed: Worldwide
Company Headquarters Location: United States

Vulnerabilities

Expand All +

CVE-2026-61884

The web management interface of the affected device does not perform server-side validation of credentials during the login process. By submitting empty values for both credential fields, an unauthenticated remote attacker can bypass the authentication check and establish a valid administrative session. This grants full access to device controls including power relay management, device reboot, remote access service configuration, and network settings, which could allow an attacker to disrupt connected infrastructure or cause physical damage to equipment.

View CVE Details

Affected Products

Tycon Systems TPDIN-Monitor-WEB2

Vendor:
Tycon Systems

Product Version:
Tycon Systems TPDIN-Monitor-WEB2: 2.3.9

Product Status:
known_affected

Remediations

Vendor fix
Tycon Systems did not respond to CISA's attempts at coordination. Users of Tycon Systems TPDIN-Monitor-WEB2 are encouraged to contact Tycon Systems and keep their systems up to date.
https://www.tyconsystems.com/contact

Relevant CWE: CWE-288 Authentication Bypass Using an Alternate Path or Channel

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	9.8	CRITICAL	CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
4.0	9.3	CRITICAL	CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

CVE-2026-55985

The device's web management interface stores and displays system credentials in cleartext on a certain configuration page accessible to authenticated users. Any party with access to the administrative dashboard can immediately read these credentials, which may be used to compromise other systems on the local network.

View CVE Details

Affected Products

Tycon Systems TPDIN-Monitor-WEB2

Vendor:
Tycon Systems

Product Version:
Tycon Systems TPDIN-Monitor-WEB2: 2.3.9

Product Status:
known_affected

Remediations

Relevant CWE: CWE-312 Cleartext Storage of Sensitive Information

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	4.3	MEDIUM	CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N
4.0	5.3	MEDIUM	CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:L/VI:N/VA:N/SC:N/SI:N/SA:N

Acknowledgments

Abdiwelli Guled reported these vulnerabilities to CISA

Legal Notice and Terms of Use

This product is provided subject to this Notification (https://www.cisa.gov/notification) and this Privacy & Use policy (https://www.cisa.gov/privacy-policy).

Recommended Practices

CISA recommends users take defensive measures to minimize the risk of exploitation of these vulnerabilities.

Minimize network exposure for all control system devices and/or systems, ensuring they are not accessible from the internet.

Locate control system networks and remote devices behind firewalls and isolating them from business networks.

CISA reminds organizations to perform proper impact analysis and risk assessment prior to deploying defensive measures.

CISA encourages organizations to implement recommended cybersecurity strategies for proactive defense of ICS assets.

Organizations observing suspected malicious activity should follow established internal procedures and report findings to CISA for tracking and correlation against other incidents.

No known public exploitation specifically targeting these vulnerabilities has been reported to CISA at this time.

Revision History

Initial Release Date: 2026-07-21

Date	Revision	Summary
2026-07-21	1	Initial Publication

Legal Notice and Terms of Use

Introducing Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber

Tue, 21 Jul 2026 17:22:44 +0200

We’re introducing new Gemini models, including Gemini 3.6 Flash, 3.5 Flash-Lite and 3.5 Flash Cyber.

The Light Flip Phone Is a Minimalist Throwback Built With Modern Hardware Sensibilities

Tue, 21 Jul 2026 17:22:41 +0200

It has all the minimalist elements of a standard flip phone, but includes 5G capabilities, USB-C charging and plenty of onboard storage.

We’re announcing the Alliance for America’s Skilled Trades.

Tue, 21 Jul 2026 16:03:30 +0200

Google is joining BlackRock, Carhartt and Ford to launch the Alliance for America’s Skilled Trades.

Android backups count toward your 15GB Google storage limit now - how to check your settings

Tue, 21 Jul 2026 15:26:20 +0200

An amended Google One storage utilization policy is rolling out now to include your Android device settings in backups, but there's no need to panic. Here are your options.

Open-Source Android AI Agents Could Let Invisible Screen Text Run Code on Host PCs

Tue, 21 Jul 2026 14:37:51 +0200

An Android app that can draw over other windows and write to shared storage can slip instructions to the AI agent driving that phone, in text no human eye will ever see. Two more steps, and the same app is running commands on the PC driving the agent. Researchers demonstrated that chain, plus six other attacks, against five open-source mobile agent frameworks: AppAgent, AppAgentX,

Open-Source Android AI Agents Could Let Invisible Screen Text Run Code on Host PCs

Tue, 21 Jul 2026 14:37:49 +0200

The post Open-Source Android AI Agents Could Let Invisible Screen Text Run Code on Host PCs appeared first on IT Security News.

The token debate: What CIOs can learn from the laws of thermodynamics

Tue, 21 Jul 2026 14:03:52 +0200

What if the next breakthrough in Enterprise AI doesn’t come from computer science alone?

What if it comes from applying principles that physicists have understood for more than a century?

According to Gartner, rising token-driven AI spend is straining budgets and challenging cost justification. As organizations race to deploy generative AI and agentic systems, token consumption dominates nearly every executive discussion: How many tokens did we use? How much did inference cost? Can we reduce our AI bill?

These are important operational questions. But they are not the strategic questions.

I believe the economics of enterprise AI can be viewed through the lens of three well-established principles from thermodynamics: the conservation of energy, entropy, and exergy.

While these principles describe physical systems — not AI —they offer a useful way to think about how organizations should measure AI success.

Principle 1: Value is created through transformation

The 1^st Law of Thermodynamics tells us that energy cannot be created or destroyed. It can only be transformed.

Enterprise AI presents a similar management lesson: Tokens are not valuable because they are consumed; they become valuable only when they are transformed into business outcomes: A faster loan application decision. A better customer experience. Faster and more accurate software. Reduced fraud. Higher employee productivity. A new product. A strategic insight.

The executive question therefore is not, “How many tokens did we consume?” It is: “How much business value did those tokens create?”

This leads to a new executive metric: return on tokens (ROT).

Just as organizations measure return on investment, they should begin measuring the business value generated for every million AI tokens consumed.

The organizations that win will not necessarily consume fewer tokens. They will generate more value from every token they use.

Principle 2: Every transformation creates waste

The 2nd Law of Thermodynamics teaches us that every energy transformation introduces inefficiencies.

Some energy inevitably becomes less useful for doing work.

The same pattern appears in enterprise AI: Not every token contributes equally to business outcomes.

Some are spent on:

Repeated prompts
Oversized context windows
Redundant reasoning
Hallucinations requiring correction
Multiple agents performing the same work
Expensive models solving simple problems

Those tokens are not “lost.” They simply produce very little business value.

I think of this as token entropy. Every enterprise deploying AI will experience it. The goal is not to eliminate token entropy completely — that would be unrealistic. The goal is to continuously identify it, measure it and reduce it. Because every unnecessary token represents an opportunity to improve both cost and business performance.

Principle 3: Useful work matters more than energy consumed

Thermodynamics introduces another important idea: Exergy.

Unlike energy, exergy measures how much energy can actually be converted into useful work. Two systems may consume the same amount of energy while producing dramatically different results.

The same is true for enterprise AI.

Imagine two companies each consuming one billion tokens. One produces meeting summaries. The other transforms claims operations, accelerates software delivery, detects fraud, improves customer retention, and creates new revenue opportunities. Both consumed the same number of tokens. Only one extracted significantly more business value.

Borrowing this concept as a management analogy, I call this token exergy.

Token exergy represents an organization’s ability to convert AI intelligence into meaningful business outcomes:

High token exergy means AI is solving important business problems.
Low token exergy means AI is generating activity without creating proportional enterprise value.

The distinction matters, because activity is not the same as impact.

A new responsibility for CIOs

For years, CIOs have monitored infrastructure: Cloud costs, storage, network utilization, GPU consumption.

These metrics remain important, but they tell only part of the story.

Token usage needs to be measured, planned, optimized and governed with the same discipline as any other cloud resource. This means that the next generation of CIO dashboards should answer different questions:

What is our return on tokens?
Where is token entropy reducing our effectiveness?
How much token exergy are we generating?
Which AI initiatives produce the greatest business value?
Which use cases create the strongest competitive advantage?

These are no longer technology metrics. They are business metrics.

The next generation of CIOs will not simply deploy AI. They will manage an economy of intelligence.

Their role will resemble that of a portfolio manager — allocating AI capacity where it creates the greatest enterprise value, reducing waste and continuously improving the productivity of every autonomous workflow.

That responsibility cannot be fulfilled by dashboards alone.

It requires an intelligent layer capable of observing, learning and optimizing the entire AI ecosystem. Three-layer enterprise agentic architecture Will enable this.

The next competitive advantage

Every major technology revolution eventually shifts from measuring inputs to measuring outcomes:

Factories stopped measuring coal consumption and began measuring productivity.
Cloud computing evolved beyond server utilization to business agility.
Digital businesses measured customer acquisition costs and lifetime value.

Enterprise AI is approaching the same inflection point. Organizations that focus only on token costs will optimize for efficiency. Organizations that measure return on tokens, minimize token entropy and maximize token exergy will optimize for business transformation.

That is a fundamentally different objective. And I believe it will separate AI leaders from AI followers.

Because in the end, the future of enterprise AI will not be determined by how many tokens an organization consumes. It will be determined by how effectively those tokens are transformed into lasting business value. The AI adoption spending spree is over. Time to focus on value.

This article is published as part of the Foundry Expert Contributor Network.
Want to join?

USN-8576-1: Linux kernel (NVIDIA Tegra) vulnerabilities

Tue, 21 Jul 2026 13:01:12 +0200

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)

USN-8575-1: Linux kernel vulnerabilities

Tue, 21 Jul 2026 12:16:01 +0200

Prometheus TSDB: Manage Data Storage and Retention on Linux

Tue, 21 Jul 2026 11:47:36 +0200

The post Prometheus TSDB: Manage Data Storage and Retention on Linux first appeared on Tecmint: Linux Howtos, Tutorials & Guides .

Prometheus stores every metric it collects in its own time-series database (TSDB). Over time, this database grows, and if your

The post Prometheus TSDB: Manage Data Storage and Retention on Linux first appeared on Tecmint: Linux Howtos, Tutorials & Guides.

CVE-2026-15811 | kronosnet Encryption Key cleartext storage in memory (EUVD-2026-46153)

Tue, 21 Jul 2026 11:12:27 +0200

A vulnerability labeled as problematic has been found in kronosnet. Affected is an unknown function of the component Encryption Key Handler. Executing a manipulation can lead to cleartext storage of sensitive information in memory. This vulnerability appears as CVE-2026-15811. The attack requires local access. There is no available exploit.

The next AI bottleneck is not the model. It’s the infrastructure behind it

Tue, 21 Jul 2026 11:03:50 +0200

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 reasoning. Another offers a larger context window. Another appears faster, cheaper or more specialized.

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.

The model matters. But it is not where most enterprises will struggle next.

The next AI bottleneck is the infrastructure behind the model.

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.

That layer is what determines whether AI remains an exciting experiment or becomes a trusted business capability.

Pilots hide the hard part

Most organizations can build an impressive AI pilot. 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.

The harder part starts when that pilot moves into a real production process.

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?

To me, these are not model problems. They are infrastructure problems.

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.

McKinsey 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.

AI pilots can survive on enthusiasm. Production AI requires architecture.

AI is becoming an integration problem

The more I look at enterprise AI, the more it feels like an integration challenge.

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.

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.

That is why the CIO question is changing.

It is no longer just, “Which AI tool should we buy?”

It is becoming, “Can we safely operationalize intelligence across the business?”

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.

A model can generate an answer. Infrastructure determines whether that answer is secure, timely, explainable, governed and connected to the right workflow.

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.

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.

That is why CIOs should not judge AI only by model capability. The enterprise system around the model matters just as much.

Latency will become a trust issue

In traditional technology operations, latency is often treated as a performance metric. In AI-enabled workflows, latency becomes a trust issue.

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.

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.

Each step adds latency. Each dependency adds a possible failure point.

A model may be fast in a benchmark but slow inside an enterprise process. That difference matters.

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.

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.

Observability has to expand

Traditional monitoring tells us whether infrastructure is healthy. Is the server up? Is CPU high? Is memory exhausted? Is the application returning errors?

AI needs that, but it also needs more.

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.

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.

In production AI, observability is not only about uptime. It is about confidence.

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.

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.

Data readiness is still underestimated

AI has exposed an uncomfortable truth: many enterprises are not as data ready as they think.

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.

AI does not fix that automatically. In many cases, it makes the problem more visible.

A bad report may be questioned. A bad AI answer may sound confident enough to be trusted.

That is a real risk.

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.

The same principle applies to resilient cloud-native design. In my IEEE TechRxiv paper, “Enabling Fault-Tolerant Multicast in Cloud-Native Architectures” I explored how reliability, observability and fault tolerance become foundational requirements when critical workloads stretch across hybrid and multi-cloud environments.

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.

Security cannot be added later

As AI moves from answering questions to acting, security becomes much more important.

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.

The more AI can do, the more identity, authorization, least privilege, separation of duties and human approval matter.

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.

AI access should be treated like any other privileged enterprise capability: limited, logged, reviewed and easy to revoke.

The NIST 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.

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.

The CIO has to define the operating model

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.

The CIO sits in the middle of all of it.

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.

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?

This work may not be as exciting as a model demo, but it is what separates sustainable AI from short-term experimentation.

The winning organizations will not be the ones with the most pilots. They will be the ones with the strongest AI operating layer.

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.

The model still matters. But the enterprise behind the model matters more.

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.

That is the shift CIOs need to lead.

The next AI bottleneck is not the model. It is whether the enterprise behind the model is ready.

This article is published as part of the Foundry Expert Contributor Network.
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Google erlaubt Android-Nutzern kein Gratis-Backup mehr: Schonfrist von 45 Tagen

Tue, 21 Jul 2026 10:33:02 +0200

Für neue Android-Nutzer gilt die Änderung seit dem 7. Juli 2026. Für bestehende Nutzer gilt eine Schonfrist von 45 Tagen, bis sie in Kraft tritt. Google informiert Nutzer per Mail dazu:

Wir möchten dich über eine bevorstehende Aktualisierung unserer Speicherrichtlinien informieren. Außerdem führen wir neue Steuerelemente ein, mit denen du deine Android-Sicherungen besser verwalten kannst.

Richtlinienänderung: In 45 Tagen werden alle Daten, die in den Sicherungen deines Android-Geräts enthalten sind, auf das Speicherplatzlimit deines Google-Kontos angerechnet. Fotos und Videos in Google Fotos und MMS-Daten werden bereits jetzt in deinen Google-Kontospeicherplatz einbezogen. Mit dieser Änderung werden auch alle anderen gesicherten Daten wie SMS, Anruflisten, Geräteeinstellungen und App-Einstellungen auf deinen Google-Kontospeicherplatz angerechnet. Nach Inkrafttreten dieser Richtlinie wird deine Gerätesicherung möglicherweise mehr Speicherplatz belegen. Wenn das Speicherplatzlimit deines Google-Kontos überschritten ist, werden automatische Sicherungen pausiert, bis du Speicherplatz freigibst oder dein Abo upgradest.

Die besten Online-Backup-Dienste im Vergleich: Nie mehr Daten verlieren

Mt Sync - (Auto)Mount and Sync your data from anywhere

Tue, 21 Jul 2026 03:56:13 +0200

It seems like I'm the only one how want to just go to a network share an an application after I login and the files are just there. No having to go mount anything first, what a wasteful step that is. :) So after making a gnome extension for gvfs mounts/shares, I thought it would be great if I could mount other types of storage the same way and even sync data between them. I got close to buying rcloneview for its paywalled features when I decided to go do my own thing, introducing Mt Sync: https://codeberg.org/gavindi/MtSync

Sharing since maybe just maybe there's someone else who misses the Windows "reconnect drive at login" feature..... 🤷‍♂️️

submitted by /u/gavindi
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CVE-2024-35252 | Microsoft Azure Storage Movement Client Library unmaintained third party components

Tue, 21 Jul 2026 03:07:43 +0200

A vulnerability was found in Microsoft Azure Storage Movement Client Library. It has been classified as critical. Affected by this issue is some unknown functionality. The manipulation leads to use of unmaintained third party components. This vulnerability is traded as CVE-2024-35252. It is possible to initiate the attack remotely. There is no exploit available. It is suggested to install a patch to address this issue.

CVE-2024-30093 | Microsoft Windows up to Server 2022 23H2 Storage link following (EUVD-2024-28030)

Tue, 21 Jul 2026 02:39:03 +0200

A vulnerability was found in Microsoft Windows. It has been declared as critical. Affected is an unknown function of the component Storage. Executing a manipulation can lead to link following. This vulnerability is handled as CVE-2024-30093. It is possible to launch the attack on the local host. There is not any exploit available. It is advisable to implement a patch to correct this issue.

CVE-2024-30083 | Microsoft Windows Standards-Based Storage Management Service stack-based overflow

Tue, 21 Jul 2026 02:38:56 +0200

A vulnerability marked as critical has been reported in Microsoft Windows Server 2012 R2/Server 2016/Server 2019/Server 2022. Affected by this issue is some unknown functionality of the component Standards-Based Storage Management Service. This manipulation causes stack-based buffer overflow. This vulnerability is tracked as CVE-2024-30083. The attack is possible to be carried out remotely. No exploit exists. To fix this issue, it is recommended to deploy a patch.

CVE-2024-30062 | Microsoft Windows Standards-Based Storage Management Service use after free (EUVD-2024-27999)

Tue, 21 Jul 2026 01:38:05 +0200

A vulnerability was found in Microsoft Windows Server 2012 R2/Server 2016/Server 2019/Server 2022 and classified as critical. Impacted is an unknown function of the component Standards-Based Storage Management Service. The manipulation results in use after free. This vulnerability is known as CVE-2024-30062. It is possible to launch the attack remotely. No exploit is available. It is advisable to implement a patch to correct this issue.

Writer's AI harness cuts token spend nearly 40% — without sacrificing accuracy

Mon, 20 Jul 2026 23:48:13 +0200

Enterprise AI is facing an ROI paradox. While throwing more compute at the strongest foundation model works well in product experiments, the costs become unbearable when the product is deployed in production.

A new paper from researchers at Writer provides a solution that is accessible to engineering teams. The study takes a systematic look at optimizing the different components of the orchestration layer that wraps around the foundation model, aka the AI harness.

By optimizing the harness, the researchers show dramatic reductions in tokens per task, a drop in cost-per-successful-task by up to 61%, and quality that holds steady, all without changing the underlying foundation model.

Because the harness is fully under the developer's control and requires no model fine-tuning, engineering teams can apply these findings to build highly cost-efficient AI applications.

The ROI crisis of tokenmaxxing

The current state of AI engineering is plagued by "tokenmaxxing," an industry trend where developers rely on massive context windows and brute-force token consumption as a substitute for good system design.

Rather than engineering elegant workflows, developers have imported a reflex from traditional software development: generate, run, fail, stuff the error and more context back into the window, and retry.

"Teams tokenmaxx because it's the cheapest fix in the moment, and because it's literally how most engineers work today," Waseem AlShikh, CTO and co-founder of Writer, told VentureBeat. Because this approach succeeds often enough on coding tasks, it has become the default reflex for every other agentic workload. The danger is that per-token price drops mask the underlying inefficiency.

"Your invoice is tokens-per-task times price-per-token, and most teams only watch the second number," AlShikh said. "In agentic workloads, tokens-per-task compounds — every loop iteration re-transmits the growing context — and it compounds faster than prices fall. The price cut becomes an anesthetic. It masks the fact that the loop itself is bleeding."

Tokenmaxxing leads to several enterprise failure modes. Teams route simple tasks to premium frontier models by default. They use the LLM as a lazy search index, stuffing the context window with raw documents instead of retrieving exact answers. Most destructively, they build unconstrained agentic loops that spiral out of control when the model encounters an error. Because output tokens cost significantly more than input tokens across all major model providers, inefficient task execution acts as a silent budget killer.

The industry has introduced several efficiency techniques to curb these costs, but they largely fall short because they treat the model in isolation:

Prompt compression condenses input text to save space, but ignores how the system sequences those inputs across complex workflows.
Budgeted reasoning caps the computational steps a model can take, which often degrades output quality if the workflow isn't intelligently routed.
Terse coding forces models to output minimal code to save output tokens, but does nothing to solve inefficient tool calling.
Speculative decoding uses a smaller draft model to speed up a larger model's text generation, optimizing inference speed while failing to address bloated agent architectures.

These efforts fail because they optimize the engine while ignoring the transmission. They do not look at the orchestration layer, leaving underlying architectural inefficiencies unresolved.

Unpacking the harness: the levers of efficiency

The harness is the orchestration layer that routes, formats, and turns the underlying LLM into a working system.

The core levers of harness optimization include system prompt caching, interaction history compaction, tool management, retrieval strategies, and error management. These are the most accessible intervention points for engineering teams looking to improve AI performance.

As the Writer researchers note in the study: “If the harness is the layer that composes model calls into work, it is also the layer that sets the price of work.”

Historically, developers have treated the harness as disposable glue code designed simply to connect an API to a user interface. The study signals that the harness must now be treated as a first-class object: a primary software artifact that requires its own testing, versioning, and rigorous design.

For enterprises, this reframes the "own-versus-rent" decision.

"Enterprises spend months on model evaluations and then rent their orchestration off the shelf — which means they're optimizing the smaller lever and outsourcing the bigger one," AlShikh said. "Whoever owns the harness owns your unit economics, and an open framework tuned for demos is not tuned for your invoice."

Inside the experiments

To isolate the impact of the orchestration layer, the researchers ran experiments on six foundation models spanning multiple vendors and weight classes: Claude Sonnet 4.6, Gemini 3.1, Gemini Flash 3.5, Qwen 3.6, GLM 5.1, and Writer’s own model, Palmyra X6.

Their experiments compared a frozen, conventional production agent loop against the finished Writer Agent Harness on the same 22 locked enterprise tasks, spanning capabilities like grounding and retrieval, multi-step workflows, tool use, and content generation. By holding the models and tasks constant, they could isolate the effects of the orchestration layer itself.

The optimized harness drove a significant drop in costs, cutting the blended cost per task by 41%, from 21 cents to 12 cents. This was largely achieved by slashing token consumption, with the number of tokens per task falling 38%, from 14.2k to 8.8k.

The harness is designed to delegate tasks like search to specialized sub-agents. A sub-agent receives only the tool and the specific query it needs, retrieves the exact data, and returns a capped, clean summary to the main agent — keeping the primary context window from filling up with raw search results.

Task success rates held steady even as token use fell — moving from 78% to 81%, a gain the researchers describe as directional rather than statistically significant at their sample size, meaning quality didn't suffer even as costs dropped.

End-to-end task latency also dropped significantly, reducing the median wall-clock time by 44%, from 48 seconds to 27 seconds, due to prompt caching and the elimination of dead-end reasoning loops.

However, the researchers also found limits to multi-agent orchestration. Smaller models like Gemini Flash 3.5 and Qwen 3.6 scored well below a usable reliability threshold on sub-agent delegation tasks (0.45 and 0.42, respectively) — the capability simply isn't dependable yet on lighter-weight models.

Sub-agent orchestration only crossed a usable reliability threshold on the two strongest models tested: Writer's own Palmyra X6 (0.86) and Claude Sonnet 4.6 (0.85).

The developer’s playbook: actionable takeaways and tradeoffs

The findings from the study translate into a playbook for enterprise developers building agentic workflows at scale. The first step is to implement what AlShikh calls the "Two-Zone Prompt" and "Context Offloading."

Structure for system prompt caching (The Two-Zone Prompt): Modern LLM APIs offer prompt caching, but developers must structure their payloads correctly to trigger it. Developers must separate the "stable zone" from the "volatile zone." Place static, unchanging elements (e.g., core rules, large tool schemas, and standard operating procedures) at the top of the prompt. Dynamic elements, such as the specific user query or recent conversational task state, must be appended at the bottom. This ordering allows the harness to reuse the cached prefix across hundreds of calls. "That single separation makes prompt caching actually work and stops you from re-paying for the same instructions on every one of an agent's thirty steps," AlShikh said.

Manage context with Context Offloading: Avoid context stuffing, where every turn of a loop is appended into a monolithic prompt until the window maxes out. Instead, move history and intermediate artifacts out of the window into retrievable storage, and pull back only what the current step needs. If possible, delegate tasks to single-purpose sub-agents to avoid context bloat. As AlShikh points out, "the biggest line item in agent spend isn't reasoning — it's re-sending things the model has already seen."

Build resilient loops and redefine KPIs: Unmanaged agent loops drain API budgets rapidly. Teams must begin tracking Completions Per Million tokens (CPM) to understand their true task costs, but the harness itself must contain physical guardrails. "The core principle is that you never ask the model to police its own spending," AlShikh said. "The fence has to live below the model, in code, on your side of the API." This requires three hard checks:

Hard per-task token budgets: The run terminates when the budget is spent, no exceptions.
Generation fencing: Caps on steps, tool calls, and recursion depth to stop non-converging agents.
Failure-spend governance: Cap what a run can spend after its first failed validation so a failing task doesn't become your most expensive task.

Avoid unnecessary complexity: Optimizing the orchestration layer comes with engineering overhead. If you're in the prototyping and exploration stage, that overhead isn't justified — iterate fast with a strong model and a light harness. Once you're scaling to millions of requests a day, the savings from harness optimization become substantial.

However, teams must be aware of "harness leverage." Adding structural scaffolding requires the model to hold and obey that context. If a model is too small, it will spend its limited capacity parsing the scaffolding instead of doing the task, causing accuracy to drop and tokens to rise. The rule for adding complex orchestration features is strictly mathematical: "If a feature adds more coordination tokens than it removes task tokens for that specific model, cut it," AlShikh said. "Nothing in the harness is free."

The future of the enterprise harness

The era of tokenmaxxing and treating context windows like bottomless buckets is coming to an end. Throwing more compute at poorly designed systems is not a viable strategy for companies that need to demonstrate a return on their AI investments.

As foundation models evolve to absorb planning, tool selection, and multi-step reasoning natively into their weights, the role of the harness will shift from compensating for model weakness to enforcing enterprise policy.

"What never moves into the model is the 'allowed': budgets, permissions, data boundaries, audit trails, deterministic kill-switches," AlShikh said. "Five years from now, the harness will be thinner but more important. There will be less scaffolding and more governance. However capable the model gets, someone external to it still has to define what it may spend, see, and touch. That layer belongs to the enterprise, and it should never be rented."

Android Device Backups See Major Changes

Mon, 20 Jul 2026 22:47:56 +0200

A couple of major changes are coming to the way your Android phone processes/stores backups. Within the next 45 days or so, Google is going to start counting your Android device backups toward your Google Account storage limit, but they are also giving you more controls over what’s backed up. Google made the announcement over...

Read the original post: Android Device Backups See Major Changes

5 ways to build a side hustle with Gemini

Mon, 20 Jul 2026 21:51:00 +0200

Launching a side business? Use Gemini to design your brand, conduct market research and automate logistics.

Sheetz replaces VMware at more than 830 stores

Mon, 20 Jul 2026 20:52:42 +0200

Convenience store and gas station chain Sheetz announced it is replacing VMware across its network of more than 830 retail locations with StorMagic’s SvHCI hyperconverged infrastructure platform, marking one of the larger publicly announced migrations away from VMware.

The rollout is already well underway. According to StorMagic, Sheetz has completed migrations at more than 600 stores and is averaging roughly 200 store conversions per month. At that rate, the company is on track to finish the project in about four months.

The migration is being carried out entirely remotely, eliminating the need for hardware upgrades or on-site IT visits. This lets the chain continue using its existing Dell PowerEdge R440 and R450 servers.

The two companies have a relationship dating back to 2020, when Sheetz first deployed StorMagic’s SvSAN software as the hyperconverged storage layer with VMware across hundreds of store locations to virtualize critical in-store application. The setup supported mission-critical applications such as payment processing, loyalty programs, kitchen management and store operations.

The new deployment replaces VMware entirely with StorMagic’s integrated SvHCI virtualization stack, simplifying infrastructure while reducing software complexity and operating costs.

By employing existing hardware and managing migrations remotely, Sheetz expects to minimize disruption while standardizing virtualization across its nationwide footprint. StorMagic said the completed platform will provide a highly available infrastructure for business-critical in-store applications while extending the useful life of existing server hardware.

“Our initial rollout proved StorMagic could deliver the resilience and centralized management needed across a large, distributed retail environment,” said Gary Sliver, director of platform engineering at Sheetz in a statement.

“StorMagic worked to understand our needs and requirements, to include a 24/7/365 operating environment, and ultimately delivered a product and plan that is allowing us to migrate hundreds of locations from VMware quickly and with minimal downtime, without requiring hardware replacements or having to send technicians to every site. This project is proof that large-scale edge migrations don’t have to be disruptive, drawn-out or scary affairs.”

Simplified Identity Management with Authentik for Holodeck 9.1

Mon, 20 Jul 2026 19:16:48 +0200

Holodeck 9.1 ships Authentik as a first-class service on the Holorouter. Two commands are all it takes to stand up a fully federated identity layer for your VMware Cloud Foundation (VCF) lab — no external LDAP, no manual UI clicks, no secrets scattered across config files. What is Authentik? Authentik is a self-hosted, open-source Identity … Continued

The post Simplified Identity Management with Authentik for Holodeck 9.1 appeared first on VMware Cloud Foundation (VCF) Blog.

DSAG warnt vor Bildungsschulden bei SAP-Entwicklern

Mon, 20 Jul 2026 19:01:00 +0200

width="1024" height="682" sizes="auto, (max-width: 1024px) 100vw, 1024px">

Die DSAG fordert Unternehmen auf, ihre ABAP-Entwickler gezielt für moderne SAP-Technologien wie Clean Core und ABAP Cloud weiterzubilden.

SAP

Viele Unternehmen investieren derzeit mehrstellige Millionenbeträge in die Modernisierung ihrer SAP-Landschaften. Doch nach Einschätzung der Deutschsprachigen SAP-Anwendergruppe (DSAG) wird dabei ein entscheidender Erfolgsfaktor häufig unterschätzt: die Qualifizierung der eigenen Entwickler.

In einer neuen Handlungsempfehlung fordert der Anwenderverband CIOs auf, die Weiterbildung von SAP-Entwicklern nicht als freiwillige Schulungsmaßnahme, sondern als strategisches Investitionsprogramm zu behandeln. Gut ausgebildete Entwickler seien die Voraussetzung für stabile, wartbare Eigenentwicklungen ohne wachsende technische Schulden. Ohne Fortbildung beim Upgrade auf S/4HANA blieben die Potenziale der neuen Technologien ungenutzt.

Veraltetes Know-how wird zum Projektrisiko

Wie die Autoren ausführen, verfügen zwar viele ABAP-Entwickler über jahrzehntelange Erfahrung mit SAP R/3 oder ECC und besäßen umfangreiches Prozesswissen. Mit S/4HANA, Clean Core und ABAP Cloud hätten sich die Entwicklungsparadigmen jedoch grundlegend verändert.

Langfristig drohe dies zu schlechten Architekturentscheidungen, aufwendigen Workarounds und Eigenentwicklungen, die bei jedem Release nachgepflegt werden müssten, zu führen, so die DSAG. Auch viele Business Consultants orientierten sich noch zu stark an klassischen GUI-Transaktionen und berücksichtigten moderne Fiori-Technologien zu wenig.

Die Folge seien sogenannte “Bildungsschulden”, meint die SAP-Anwendervereinigung. Diese blieben zunächst unsichtbar, machten sich später jedoch in Form längerer Projekte, steigender Wartungskosten und einer wachsenden Abhängigkeit von externen Dienstleistern bemerkbar.

Kompetenzaufbau darf nicht erst im Projekt beginnen

Besonders kritisch sehen die DSAG-Autoren den Zeitpunkt der Weiterbildung. Wer erst während eines laufenden S/4HANA-Migrationsprojekts mit dem Kompetenzaufbau beginne, erhöhe das Projektrisiko erheblich. Fehlendes Wissen über CDS, RAP oder Fiori führe zu Architekturentscheidungen, die später teuer korrigiert werden müssten. Gleichzeitig lasse sich der notwendige Lernaufwand kaum parallel zum Tagesgeschäft bewältigen.

Aber auch nach abgeschlossener Migration müssen sich die SAP-Entwickler laut DSAG weiter fortbilden. Wer danach so weiterarbeite wie auf ECC, verpasse die Möglichkeiten aktueller SAP-Technologien – auch wenn technisch alles noch funktioniere, warnen die Autoren. Gleichzeitig könnten sie das Gelernte gleich anwenden, womit sich das neue Wissen verfestigt.

KI ersetzt keine Entwicklerkompetenz

Laut DSAG gilt auch für die Entwicklung im SAP-Umfeld: KI-Werkzeuge können zwar Code erzeugen und erklären. Voraussetzung sei dabei jedoch, dass Entwickler die Ergebnisse auch fachlich bewerten könnten. „Nur wer versteht, was guter SAP-Code ist, kann KI als Beschleuniger einsetzen“, so die Autoren. Andernfalls fungiere KI als Risikoverstärker und beschleunige im schlimmsten Fall lediglich die Entstehung technischer Schulden.

Voraussetzung für den erfolgreichen KI-Einsatz seien deshalb solide Software-Engineering-Kenntnisse, automatisierte Tests und ein Verständnis moderner SAP-Entwicklung.

Die fünf Empfehlungen der DSAG

Die DSAG empfiehlt CIOs deshalb, Weiterbildung fest in ihre Transformationsstrategie zu integrieren. Konkret nennt der Verband fünf Maßnahmen, nämlich:

verbindliche Lernpfade für unterschiedliche Rollen wie ABAP-, CAP- oder Integrationsentwickler sowie Business Consultants zu definieren,
geeignete Sandbox- und Testumgebungen bereitzustellen,
Fortbildungszeiten verbindlich in die Kapazitätsplanung aufzunehmen,
Schulungen zeitlich mit Migrations- und Modernisierungsprojekten zu verzahnen, sowie
bestehende DSAG-Leitfäden als Referenzrahmen für die Entwicklung zu nutzen.

Security Is a Platform Property, Not a Pipeline Step

Mon, 20 Jul 2026 18:59:48 +0200

A few weeks ago, I disabled key authentication on an Azure storage account we used for Terraform state management. It was one of the key security recommendations in Microsoft Defender for Cloud. It made sense to use RBAC-only permissions, enforce…

The post Security Is a Platform Property, Not a Pipeline Step appeared first on IT Security News.

Why I still recommend Synology's DS225+ NAS - even if it can't replace your cloud storage

Mon, 20 Jul 2026 18:50:17 +0200

Soaring hard drive prices are making NAS boxes a niche product, but the Synology DS225+ still makes sense. Here's why.

The technology behind every live sports moment

Mon, 20 Jul 2026 16:48:21 +0200

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 absorbing a traffic spike that appeared without warning.

They just feel the moment.

And that’s exactly how it’s supposed to work.

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.

As audiences moved to digital platforms, the margin for error disappeared.

There is a version of this conversation that is easy to have: audiences expect more, technology has to keep up. True, but incomplete.

Audiences have always expected live sport to work. What changed is what “working” means, and how quickly they find out when it doesn’t.

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.

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.

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.

What these viewership numbers actually mean for infrastructure

The shift in how people watch live sport has moved well beyond trend territory.

EMARKETER forecasts that digital live sports audiences in the US will grow to 114.1 million viewers, while traditional pay TV audiences decline to 82.0 million, highlighting the continued shift toward streaming.

The concurrency numbers generated by major sporting events now sit in a territory that would have seemed implausible a decade ago.

During the 2026 FIFA World Cup, for instance, streaming platforms shattered every historical ceiling, highlighted by Brazil’s CazéTV repeatedly breaking global YouTube records for concurrent viewership during the group stage. Meanwhile, in the United States, Peacock and Telemundo’s digital platforms logged an unprecedented 13 million concurrent viewers for a single knockout window.

When tens of millions of people tune into the same live stream at the same moment, it’s a challenge unlike regular web traffic.

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.

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.

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.

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.

According to an industry survey, 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.

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.

Ultimately, the technical demand is driven by a shift in what viewers expect. An IBM sports study 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.

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.

The planning mistake most organisations make

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.

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 2 to 25 times above normal levels within seconds. The infrastructure may be different, but the pressure is remarkably similar.

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.

The problem isn’t the individual systems. It’s how they work together.

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.

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.

Geography is another planning gap. Streaming growth is increasingly being driven by emerging markets. In Southeast Asia alone, premium video streaming subscriptions grew 19% 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.

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.

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.

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.

The hidden chain behind every live event

When a streaming disruption becomes public, people naturally look for a single point of failure: the app, the platform, or the provider.

A live event depends on dozens of systems working together, and any one of them can become a problem.

And the experience is only as good as the weakest handoff between them.

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.

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.

Each transition is a potential failure point. Managing them requires visibility that extends across providers, platforms, and networks simultaneously.

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.

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.

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.

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.

The value of technology investments such as AI and Edge becomes clearest during the moments when demand is highest.

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.

What reliability is actually worth

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.

Neither of those things is true now.

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.

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.

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.

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.

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.

The demands ahead are bigger

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 80% faster than traditional methods.

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.

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.

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.

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.

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.

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.

The technology you never think about

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.

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.

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.

Delivering that level of reliability is why many of the world’s largest sports brands rely on Tata Communications. 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.

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.

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.

To learn more, visit us here.

[$] Merging famfs?

Mon, 20 Jul 2026 15:54:53 +0200

The famfs filesystem, which is meant to provide shared access to huge memory-resident files on CXL and other devices, returned to the Linux Storage, Filesystem, Memory Management, and BPF Summit (LSFMM+BPF) in 2026. It was first discussed at LSFMM+BPF 2024 and a new implementation was described at the 2025 gathering, but it still has not made its way into the kernel; LWN looked at a discussion about merging famfs back in April 2026.

Snag This M3 iPad Air With $500 Off While You Still Can

Mon, 20 Jul 2026 15:47:50 +0200

It’s got an 11-inch display, 5G connectivity, 1TB of storage for just $749

Google erlaubt Android-Nutzern kein Gratis-Backup mehr: Schonfrist von 45 Tagen

Mon, 20 Jul 2026 15:33:30 +0200

Für neue Android-Nutzer gilt die Änderung seit dem 7. Juli 2026. Für bestehende Nutzer gilt eine Schonfrist von 45 Tagen, bis sie in Kraft tritt. Google informiert Nutzer per Mail dazu:

Wir möchten dich über eine bevorstehende Aktualisierung unserer Speicherrichtlinien informieren. Außerdem führen wir neue Steuerelemente ein, mit denen du deine Android-Sicherungen besser verwalten kannst.

Richtlinienänderung: In 45 Tagen werden alle Daten, die in den Sicherungen deines Android-Geräts enthalten sind, auf das Speicherplatzlimit deines Google-Kontos angerechnet. Fotos und Videos in Google Fotos und MMS-Daten werden bereits jetzt in deinen Google-Kontospeicherplatz einbezogen. Mit dieser Änderung werden auch alle anderen gesicherten Daten wie SMS, Anruflisten, Geräteeinstellungen und App-Einstellungen auf deinen Google-Kontospeicherplatz angerechnet. Nach Inkrafttreten dieser Richtlinie wird deine Gerätesicherung möglicherweise mehr Speicherplatz belegen. Wenn das Speicherplatzlimit deines Google-Kontos überschritten ist, werden automatische Sicherungen pausiert, bis du Speicherplatz freigibst oder dein Abo upgradest.

Die besten Online-Backup-Dienste im Vergleich: Nie mehr Daten verlieren

CVE-2026-50299 | Microsoft Windows up to Server 2025 Storage Spaces Direct integer overflow

Mon, 20 Jul 2026 14:39:41 +0200

A vulnerability was found in Microsoft Windows and classified as very critical. This vulnerability affects unknown code of the component Storage Spaces Direct. The manipulation results in integer overflow. This vulnerability is known as CVE-2026-50299. Attacking locally is a requirement. No exploit is available.

How to mount GPU memory (VRAM) as a RAM disk on Windows computer

Mon, 20 Jul 2026 02:44:09 +0200

If you want to squeeze the utmost performance out of your PC, you can use your graphics card’s memory as temporary storage. Several experimental tools, such as VRAMDISK and GpuRamDrive, allow you to mount a portion of your GPU memory as a virtual drive in Windows. In this guide, we’ll briefly look at the available […]

This article How to mount GPU memory (VRAM) as a RAM disk on Windows computer first appeared on TheWindowsClub.com.

Migrating to OpenVox at INFN Naples (voxconf2026)

Sun, 19 Jul 2026 22:32:53 +0200

Puppet has been in use at INFN Naples for several years, together with Foreman for lifecycle management. It is currently used to manage several hundred machines, both bare metal and virtual, across a heterogeneous infrastructure that includes Ceph and dCache storage systems, HTCondor clusters, an OpenStack private cloud, and a number of self-hosted services such as Greenbone and NetBox A change in Perforce licensing policy forced us to look for an alternative solution, leading to the migration to OpenVox and to an active involvement with its community. The migration process can be divided into several sub-tasks: Migration of an all-in-one Puppet Server (OSP Server, PuppetDB, and Puppetboard) and the managed clients Migration of the Foreman server and its managed clients Migration of the supporting toolchain (Bolt, IDE integrations, and related tools) Each of these areas presented distinct challenges and required different migration strategies, some of which are still ongoing. Contributions and roadmap The migration effort led us to contribute to upstream projects, most notably the puppet-openvoxdb module (now released) and a set of Foreman templates to provision clients with the OpenVox repository enabled (work in progress at the time of writing). Despite the strong community support and our efforts, some components of the infrastructure have not yet been migrated, most notably the Git-based workflow, which still relies on r10k. about this event: https://c3voc.de

The cleanup trap: Stop asking RAG to fix bad data

Sun, 19 Jul 2026 22:32:19 +0200

The enterprise technology ecosystem is caught in a costly cycle. Over the past two years, millions of dollars have been funneled into generative AI pilots, yet many of these initiatives stall out before ever reaching a live production environment.

When a project fails, the immediate instinct of technical leadership is often to blame the model: The context window was too restrictive, the latency was too high, or the reasoning capabilities simply were not there.

But as data engineers building the scaffolding for these systems, we often see a different reality: The model receives the blame, but the pipeline usually contains the root cause. Production gen AI rarely fails because of model limitations alone. More often, it fails because the enterprise data foundation underneath it is fundamentally unready.

This is what I call the 'Cleanup Trap': The false belief that an organization can pipe fragmented, inconsistent, and ungoverned legacy data into a large language model (LLM) orchestrator and simply “clean it up” or patch it at the retrieval layer.

The mirage of the retrieval layer

In a standard retrieval-augmented generation (RAG) architecture, the retrieval layer is tasked with pulling relevant business context to ground the model’s responses. Because modern frameworks make it simple to stand up a vector database and a basic embedding pipeline, leadership often assumes that the data engineering problem is solved.

It is not.

When an embedding model receives raw, unvalidated data directly from operational silos, the resulting vector space inherits the structural noise, duplicate records, and conflicting states present in the source systems.

If the core data pipeline suffers from silent degradation — schema drift, missing fields, delayed change-data-capture (CDC) synchronization — that degradation cascades directly into the vector store. An AI model cannot accurately synthesize customer intelligence if the data pipeline behind it is serving stale, contradictory profiles across disparate storage layers.

No amount of prompt engineering, semantic reranking, or vector hyperparameter tuning can compensate for a broken ingestion pipeline. If the foundation is compromised, the downstream application will hallucinate, expose unauthorized context, or fail to deliver deterministic value.

Shifting from ad-hoc patching to programmatic guardrails

To break out of the 'Cleanup Trap,' enterprise data teams must stop treating data quality as a post-processing step. They need to treat data readiness for AI with the same rigor they bring to traditional transaction processing.

This requires a deliberate architectural shift toward zero-trust data ingestion, structured validation frameworks, and automated anomaly detection before data ever reaches an AI orchestration layer.

1. Harden the ingestion pipeline

Data quality checks cannot exist as a nightly batch afterthought. If an enterprise AI application relies on real-time data to assist users, validation must happen inline.

Teams should implement explicit schema validation checks at the earliest ingestion point, such as the streaming ingress layer or the bronze landing layer of a medallion architecture. If an upstream operational database mutates a schema without warning, the pipeline should quarantine anomalous payloads rather than allowing corrupted metadata to pollute downstream AI contexts.

2. Use multi-tiered algorithmic validation

Static row-count validation rules are insufficient for AI readiness. True data health requires a multi-tiered approach.

This means pairing structural verification — null checks, type conformance, and schema validation — with statistical profiling to monitor for data drift. Tracking metric deviations across feature distributions helps ensure that historical context remains stable over time.

If a pipeline suddenly processes an unexpected spike in empty string variables or structurally deviant fields, automated alerts should trigger an immediate pause before vector database updates continue.

3. Decouple security and compliancemfrom the model

An LLM should never be the arbiter of data access control. Trying to enforce row-level security or personal data filtering through system prompts is a compliance risk.

Security must be managed within the data infrastructure tier. Enterprise data foundations should enforce strict access controls, tokenization of sensitive identifiers, and rigorous lineage tracing before information is indexed into vector stores or passed into an agent’s context window.

Technical alignment: A pragmatic blueprint

For technology leaders mapping their infrastructure roadmaps, AI readiness requires evaluating data pipelines against a strict operational checklist.

Can you trace a flawed AI response back to the exact pipeline execution, source record, and transformation step that produced it?
Does your data lake architecture have a programmatic mechanism to segment and quarantine corrupted or non-compliant data before it reaches production feature stores?
Are your operational systems and AI-facing vector databases tightly synchronized, or are your agents making automated decisions based on outdated snapshots?

These questions matter because production AI is not just a model deployment problem. It is a data reliability problem.

Building for the production era

The honeymoon phase of gen AI experimentation is ending. Enterprise leaders are demanding measurable, predictable, and secure business outcomes from their AI investments.

If an organization wants to transition from isolated, impressive-looking demos to resilient, production-grade AI systems, it must redirect its focus. Stop looking exclusively at the model tier.

The real competitive differentiator is not only the LLM an organization chooses. It is the engineering discipline, data governance, and pipeline resilience of the infrastructure built to feed it.

In the production era of AI, data engineering is no longer a backend function. It is the control plane for enterprise intelligence.

Naveen Ayalla is a senior data engineer.

PlayStation Accused of Using Social Media Bots to Defend Digital-Only Future

Sun, 19 Jul 2026 20:08:22 +0200

PlayStation faces claims that social media bots are defending Sony’s decision to stop producing physical game discs for new releases from January 2028. Suspicious accounts reportedly supported Sony’s decision https://youtu.be/yoUux9ifBBE YouTube channel Moore’s Law Is Dead examined several social media accounts that posted positively about PlayStation’s digital-only plans. The creator claims these accounts showed unusual activity, including long periods of silence followed by sudden posts supporting Sony and other gaming companies. Some accounts reportedly used formal and similar language, interacted with profiles that were later deleted, and displayed profile pictures that appeared to be AI-generated. One account had reportedly remained inactive for six years before returning to praise Rockstar Games and GTA 6. Another became active after three years and began posting about game ownership and PlayStation’s digital strategy. The investigation focused on three accounts. However, the findings do not prove that Sony created, controlled, or paid for them. Moore’s Law Is Dead also acknowledged that an unrelated third party could be responsible for the activity. Sony has not publicly responded to the bot allegations. PlayStation will end new physical game releases in 2028 Sony confirmed on July 1 that it will stop producing physical discs for all new PlayStation games starting in January 2028. New titles released after that date will be available digitally through the PlayStation Store and participating retailers. Games released before the deadline will remain unaffected. Sony said digital downloads represented around 80% of its full-game software sales during fiscal 2025. However, the decision has faced criticism from players concerned about game ownership, resale options, sharing, storage costs, and long-term access. Until stronger evidence appears, the social media bot claim remains an allegation rather than a confirmed PlayStation marketing campaign.

Windows 10 Still Being Used, Often Unpatched and Insecure

Sun, 19 Jul 2026 19:43:51 +0200

Windows 10 still runs on 16.9% of the Windows devices monitored by asset-tracking service Lansweeper. That's more than one in six, The Register points out. A year ago, the operating system accounted for about half of the machines in its dataset, falling to the low-to-mid 40% range by the time Microsoft ended standard support. The decline continued after that, reaching 18.6% in June, but Lansweeper says migration has now slowed to a crawl... Small and medium-sized businesses are particularly exposed. Lansweeper reckons that 21.4% of machines at small and medium-sized business still run Windows 10, with cost usually being the constraint that keeps the legacy operating system running. The exposure is greater in some sectors, with 23% of healthcare and pharmaceutical systems sticking with Windows 10, while consumer and retail devices hover at 22.7%. According to Lansweeper's data, "a Windows 10 device carries an average of 1,903 active CVEs against 652 on Windows 11. That's a 2.9x gap." Esben Dochy, principal technical evangelist at the company, told The Register that "the Windows 10 average also includes devices that have Extended Security Update patches applied." [According to Lansweeper's figures, 14% of Windows 10 assets have applied Extended Security Update patches.] Part of the problem, according to Lansweeper, is "patch diffing," in which Windows 11 fixes can be reverse-engineered to find flaws in Windows 10. "The supported OS effectively hands attackers a map into the unsupported one," Lansweeper said... Looking at other market share measures such as Statcounter, there was little change in the share of Windows 10 and its successor over the last few months after a surge following the end of support. As Lansweeper noted: "The easy migrations are done. What's left is the hard core: devices that haven't moved because they can't or won't." Lansweeper's evangelist noted that in some cases there is no Windows 11-certified version yet for many medical devices and industrial or retail systems.

Have you thought about your digital legacy? (emf2026)

Sun, 19 Jul 2026 13:47:50 +0200

Content warning: Contains frank conversations about death Death is inevitable, yet our digital infrastructure remains woefully unprepared for it. While traditional "Letters of Wishes" provide a static roadmap for executors, they lack the agency to interact with our complex, data-driven lives. This workshop introduces the concept of the Machine-Readable Letter of Wishes: a framework for post-mortem autonomy. By applying a "If This, Then That" (IFTTT) logic to digital legacies, we will explore how to automate final wishes across various services, ensuring data is handled with human dignity and precision. Traditionally, a Letter of Wishes is a physical document offering non-binding guidance to those named in a will. However, in an era of encrypted accounts, fragmented cloud storage and AI. Paper often falls short. This workshop moves from the philosophical to the practical: * Defining the digital legacy: Identifying the specific data points, social accounts, and assets that constitute a modern legacy. * Pipe mapping: Applying IFTTT methodology to personal wishes (e.g., "If I am inactive for 12 months, then transfer my photo archive to named person * Exploring autonomy: Discussing the ethical implications of automated execution and how it can alleviate the "administrative burden of grief" for executors. In the workshop people will gain a foundational understanding of how automation can protect digital rights and dignity, starting that important conversation that benefits individuals, their loved ones, and society. Licensed to the public under https://creativecommons.org/licenses/by-sa/4.0/ about this event: https://www.emfcamp.org/schedule/2026/151-have-you-thought-about-your-digital-legacy

Have you thought about your digital legacy? (emf2026)

Sun, 19 Jul 2026 13:33:31 +0200

CVE-2026-16218 | hunvreus devpush up to 0.4.6 Storage Reset Failure storage.py reset_storage improper check or handling of exceptional conditions (EUVD-2026-45429)

Sun, 19 Jul 2026 10:39:27 +0200

A vulnerability labeled as problematic has been found in hunvreus devpush up to 0.4.6. Affected by this issue is the function reset_storage of the file app/workers/tasks/storage.py of the component Storage Reset Failure Handler. The manipulation results in improper check or handling of exceptional conditions. This vulnerability is known as CVE-2026-16218. Access to the local network is required for this attack. No exploit is available. The project was informed of the problem early through an issue report but has not responded yet.

CVE-2026-16213 | Fantomas42 django-blog-zinnia up to 0.20 Protected Entry Password entry_protection.py cleartext storage (Issue 595 / EUVD-2026-45424)

Sun, 19 Jul 2026 10:39:17 +0200

A vulnerability described as problematic has been identified in Fantomas42 django-blog-zinnia up to 0.20. Affected by this vulnerability is an unknown functionality of the file zinnia/views/mixins/entry_protection.py of the component Protected Entry Password Handler. The manipulation results in cleartext storage of sensitive information. This vulnerability was named CVE-2026-16213. The attack needs to be approached locally. There is no available exploit. The project was informed of the problem early through an issue report but has not responded yet.

Apple Raises iCloud+ Prices in Japan, Nigeria, Türkiye, and Other Countries

Sun, 19 Jul 2026 10:09:31 +0200

Apple has raised iCloud+ subscription prices across several countries, including Japan, Nigeria, Türkiye, Egypt, New Zealand, Indonesia, the Philippines, and Vietnam. The latest changes affect every paid storage tier in most of these markets, covering plans from 50GB to 12TB. The new iCloud+ prices arrive during a wider series of Apple price increases across hardware and subscription services. Apple recently raised Apple Music and Apple One prices in the United States and other markets, while customers in Japan also saw higher iPhone prices. Apple has also increased prices for some MacBook, iPad, and other hardware models following rising component and memory costs. The new iCloud+ pricing means customers in affected countries will now pay more each month for additional cloud storage, iCloud Private Relay, Hide My Email, custom email domains, and HomeKit Secure Video support. New iCloud+ prices in affected countries Apple has updated iCloud+ prices across eight major markets, although the size of the increase differs by country and storage plan. Egypt Customers in Egypt will now pay the following monthly prices: 50GB: EGP 49.99, up from EGP 39.99 200GB: EGP 179.99, up from EGP 149.99 2TB: EGP 599.99, up from EGP 499.99 6TB: EGP 1,799.99, up from EGP 1,499.99 12TB: EGP 3,599.99, up from EGP 2,999.99 Nigeria Apple has introduced some of the largest increases in Nigeria, with several plans now costing around 50% more than before: 50GB: ₦1,300, up from ₦900 200GB: ₦4,500, up from ₦2,900 2TB: ₦14,900, up from ₦9,900 6TB: ₦39,900, up from ₦26,900 12TB: ₦66,900, up from ₦44,900 Türkiye iCloud+ users in Türkiye will also see higher monthly charges across every storage tier: 50GB: 49.99 TL, up from 39.99 TL 200GB: 169.99 TL, up from 129.99 TL 2TB: 549.99 TL, up from 399.99 TL 6TB: 1,699.99 TL, up from 1,299.99 TL 12TB: 3,399.99 TL, up from 2,499.99 TL Indonesia The entry-level 50GB plan remains unchanged in Indonesia, although Apple has increased the prices of every larger storage option: 50GB: Rp15,000, unchanged 200GB: Rp59,000, up from Rp49,000 2TB: Rp199,000, up from Rp169,000 6TB: Rp599,000, up from Rp499,000 12TB: Rp1,199,000, up from Rp999,000 Japan Apple has raised all five iCloud+ storage prices in Japan after recently increasing iPhone prices in the country: 50GB: ¥180, up from ¥150 200GB: ¥540, up from ¥450 2TB: ¥1,800, up from ¥1,500 6TB: ¥5,500, up from ¥4,500 12TB: ¥11,000, up from ¥9,000 New Zealand Customers in New Zealand will now pay between NZ$1.99 and NZ$119.99 each month, depending on their selected storage tier: 50GB: NZ$1.99, up from NZ$1.69 200GB: NZ$5.99, up from NZ$4.99 2TB: NZ$19.99, up from NZ$16.99 6TB: NZ$59.99, up from NZ$49.99 12TB: NZ$119.99, up from NZ$99.99 Philippines Apple has increased each iCloud+ storage plan in the Philippines, with the 12TB option now costing ₱3,990 per month: 50GB: ₱59, up from ₱49 200GB: ₱199, up from ₱179 2TB: ₱699, up from ₱599 6TB: ₱1,990, up from ₱1,790 12TB: ₱3,990, up from ₱3,590 Vietnam Vietnamese customers will also see higher prices across the entire iCloud+ lineup: 50GB: ₫25,000, up from ₫19,000 200GB: ₫89,000, up from ₫69,000 2TB: ₫299,000, up from ₫249,000 6TB: ₫899,000, up from ₫749,000 12TB: ₫1,799,000, up from ₫1,499,000 Apple adds USD pricing in three more regions Apple now lists Laos, Mauritius, and the Republic of Congo among the countries where customers pay for iCloud+ upgrades in US dollars. Apple says the final amount can be slightly higher because of local Value Added Tax charges. Customers in Mauritius and the Republic of Congo will pay the same monthly prices: 50GB: $1.19 200GB: $3.49 2TB: $11.99 6TB: $34.99 12TB: $69.99 Customers in Laos will pay slightly lower prices across all five storage plans: 50GB: $0.99 200GB: $3.29 2TB: $10.99 6TB: $32.99 12TB: $64.99 The changes apply to iCloud+ plans that provide additional storage beyond the free 5GB included with every Apple Account. Customers can check their current plan and local pricing through the iCloud section in the Settings app on an iPhone or iPad. Users who no longer need their existing storage tier can switch to a smaller plan, although they must reduce their stored data before the downgrade takes effect. Apple also allows iCloud+ storage sharing through Family Sharing, which can help families avoid paying for separate plans.

B&H launches steep MacBook Pro discounts at up to $400 off

Sun, 19 Jul 2026 09:38:52 +0200

B&H has launched new markdowns on numerous 14-inch and 16-inch MacBook Pro laptops this week, with savings of up to $400 off M5, M5 Pro, and M5 Max models.

The latest sale at B&H includes numerous CTO MacBook Pro models that are up to $400 off. Some of the configurations have additional RAM, extra storage, a nano-texture display, or all three.

You can jump straight to the sale, but we've also rounded up top picks below. And if you don't see your desired model, it's also worth checking out our MacBook Pro Price Guide, which is broken down by screen size and Apple Silicon chip, to find deals on dozens of configurations.

Continue Reading on AppleInsider | Discuss on our Forums

CVE-2026-49168 | Microsoft Windows up to Server 2025 Storage Spaces Direct integer overflow

Sun, 19 Jul 2026 08:38:33 +0200

A vulnerability, which was classified as problematic, was found in Microsoft Windows. This impacts an unknown function of the component Storage Spaces Direct. Such manipulation leads to integer overflow. This vulnerability is traded as CVE-2026-49168. An attack has to be approached locally. There is no exploit available.

CVE-2026-57088 | Microsoft Windows 10 1809/Server 2019/Server 2022/Server 2025 Extensible Storage Engine access control

Sun, 19 Jul 2026 06:53:55 +0200

A vulnerability, which was classified as problematic, was found in Microsoft Windows 10 1809/Server 2019/Server 2022/Server 2025. This issue affects some unknown processing of the component Extensible Storage Engine. The manipulation results in improper access controls. This vulnerability is cataloged as CVE-2026-57088. The attack must be initiated from a local position. There is no exploit available.

Stable Channel Update for ChromeOS / ChromeOS Flex

Sun, 19 Jul 2026 06:07:24 +0200

The ChromeOS Stable channel is being updated to OS version 16700.46.0 (Browser version 150.0.7871.150) for most ChromeOS devices.

If you find new issues, please let us know one of the following ways:

File a bug
Visit our ChromeOS communities

General: Chromebook Help Community
Beta Specific: ChromeOS Beta Help Community

Report an issue or send feedback on Chrome
Interested in switching channels? Find out how.

ChromeOS Vulnerability Rewards Program Reported Bug Fixes:

N/A

Other 3rd Party Security Fixes Included:

High Fixes CVE-2026-46242 (Bad epoll) - Linux Local Privilege Escalation

Medium Fixes CVE-2026-49746 [PSP-528][PP-173890][KMD] Dimension Mismatch and Integer Truncation in `PMRDevPhysAddrOSMem`

High Fixes Potential UAF via Profile/Service Desync in shill ConfigureService

Medium Fixes CWE-862: shill Manager.NotifyDHCPEvent reachable from chronos allows DHCP spoofing

Medium Fixes CVE-2026-45204 [PSP-406][PowerVR] Out of bounds memory access and kernel NULL pointer dereference in DmaTransfer when pui64Address is a pointer to device memory

High Fixes Stack OOB Read to Heap OOB Write in msm_ccmd_ioctl_simple via Guest-Controlled _IOC_SIZE

High Fixes [LPE] Patchpanel ConnectNamespace PID Gate Bypass Allows CAP_NET_ADMIN Root Netns Operations

Medium Fixes CVE-2026-49745 [PSP-598][PP-174017] Unvalidated sHWPerfCtlDMABuf GPU-VA, DMA-write into FW privdata via MMU ctx 0

High Fixes Heap OOB write in ANGLE D3D11 vertex streaming via `WEBGL_draw_instanced_base_vertex_base_instance`

High Fixes Use-After-Free in CRAS LE-Audio via group removal race condition

High Fixes Cross-client microphone audio exfiltration via missing CRAS stream ownership check

High Fixes Use-After-Free in CRAS server via dangling active_fm->lea pointer

Critical Fixes [LPE] Arbitrary file read as root in printscanmgr via FD leak and path traversal

High Fixes Privilege escalation in CRAS via DlcStateChanged signal spoofing

High Fixes missing untrusted input validation in chromeos-boot-alert leads to root pango-view processing attacker file

High Fixes UAF and Control Flow Hijack in CRAS A2DP Profile Switching

Medium Fixes Heap OOB Read in Floss A2DP via Ring Buffer Misalignment

High Fixes Heap OOB write in CRAS mSBC SCO handling via dynamic packet size adjustment

High Fixes UAF in CRAS server via dangling default_rmod->odev pointer after stream disconnect

High Fixes Crosvm xHCI guest-to-host OOB write via unchecked DMA buffer size

High Fixes Use-After-Free in CRAS HFP SLC due to leaked timer in AT+CMER handler

High Fixes CRAS OOB write via integer overflow in cras_shm_buff_for_idx

High Fixes OOB write in CRAS via unsigned underflow in cras_audio_area_copy

High Fixes Use-After-Free in CRAS echo_ref_requests via concurrent list mutation

High Fixes Unauthenticated CRAS Loopback Hijacking allows Cross-Client Audio Capture

High Fixes Use-After-Free in CRAS loopback traversal due to data race

High Fixes Out-of-bounds write in CRAS server via unvalidated client_shm_size

Critical Fixes [LPE] Arbitrary `tc` Command Injection in `shill` Throttler via `TetheringConfig`

High Fixes Potential Use-After-Free in vm_concierge ArcVm via base::Unretained in async D-Bus callback

Medium Fixes TOCTOU in permission_broker allows chronos to open arbitrary device nodes

Medium Fixes [PSP-490][PowerVR] Read UAF in GrowMipLevelArray() due to incorrect texture array iteration during image copy

Medium Fixes [PSP-495][PowerVR] OOB read in CreateTextureMemory() due to memory mismanagement after texture format change

Medium Fixes [PSP-516][PowerVR] Secondary mapping of the freelist PMR allows reading Freelist contents via GPU shader

Medium Fixes [PSP-443][KMD][PowerVR] Read UAF of sync checkpoint in pvr_sync_finalise_fence() after update fence file descriptor is prematurely closed

Medium Fixes CVE-2026-34196 [PSP-372][PowerVR] UAF read and/or write of arbitrary physical memory due to integer truncation in PMRDevPhysAddrOSMem

Medium Fixes CVE-2026-7639 [PSP-452][KMD] Page UAF read in `PMMETA_PROTECT` heap memory

Medium Fixes [PSP-415] [PROJ-ZERO] PowerVR: [crash-only bug] kernel crash due to faulting userspace memory access without fault handling

Android Security fixes can be found here

Chrome Browser Security Fixes:

[$TBD] [524395469] High CVE-2026-13855 Use after free in Ozone on 2026-06-15

[$TBD] [524290062] Medium CVE-2026-14432 Use after free in V8 on 2026-06-15

[$TBD] [523884658] High CVE-2026-14431 Type Confusion in V8 Reported by [OpenAI Codex Security (amyb)] on 2026-06-14

[$TBD] [523690961] High CVE-2026-13854 Use after free in Ozone on 2026-06-13

[$TBD] [523224019] High CVE-2026-13853 Use after free in Journeys on 2026-06-12

[$TBD] [520571816] High CVE-2026-14429 Insufficient validation of untrusted input in Skia on 2026-06-05

[$TBD] [520113415] Critical CVE-2026-14427 Heap buffer overflow in Skia on 2026-06-04

[$TBD] [518247789] Low CVE-2026-14156 Policy bypass in StorageAccessAPI on 2026-05-30

[$TBD] [518246925] Low CVE-2026-14155 Insufficient policy enforcement in StorageAccessAPI on 2026-05-30

[$TBD] [518245882] Medium CVE-2026-14024 Use after free in Ozone on 2026-05-30

[$1000.0] [517981277] High CVE-2026-14426 Use after free in V8 Reported by [] on 2026-05-30

[$TBD] [518063436] Medium CVE-2026-14023 Insufficient validation of untrusted input in SanitizerAPI on 2026-05-29

[$TBD] [518007821] Critical CVE-2026-13786 Use after free in Ozone on 2026-05-29

[$TBD] [517935753] High CVE-2026-14425 Use after free in ANGLE on 2026-05-29

[$TBD] [517791835] Medium CVE-2026-14022 Insufficient validation of untrusted input in Network on 2026-05-29

[$TBD] [517741170] Low CVE-2026-14154 Inappropriate implementation in DevTools on 2026-05-28

[$TBD] [517731924] Medium CVE-2026-14021 Insufficient validation of untrusted input in StorageAccessAPI on 2026-05-28

[$TBD] [517684077] Low CVE-2026-14153 Inappropriate implementation in Glic on 2026-05-28

[$TBD] [517598518] Medium CVE-2026-14020 Insufficient validation of untrusted input in WebXR on 2026-05-28

[$TBD] [517534944] Low CVE-2026-14152 Out of bounds write in ANGLE on 2026-05-28

[$TBD] [517522769] High CVE-2026-14423 Type Confusion in Tint on 2026-05-28

[$TBD] [517455455] Medium CVE-2026-14019 Inappropriate implementation in Passwords on IP-literal pages on 2026-05-28

[$TBD] [517381770] Low CVE-2026-14151 Inappropriate implementation in AI on 2026-05-27

[$TBD] [517376041] Low CVE-2026-14150 Insufficient validation of untrusted input in Speech on 2026-05-27

[$TBD] [517345069] High CVE-2026-13848 Use after free in Forms on 2026-05-27

[$TBD] [517241992] Medium CVE-2026-14017 Inappropriate implementation in Navigation on 2026-05-27

[$TBD] [517234388] Medium CVE-2026-14016 Insufficient policy enforcement in SVG on 2026-05-27

[$TBD] [517155893] Medium CVE-2026-14014 Inappropriate implementation in Paint on 2026-05-27

[$TBD] [517114175] Medium CVE-2026-14013 Inappropriate implementation in SVG on 2026-05-27

[$TBD] [517110749] Medium CVE-2026-14012 Side-channel information leakage in CSS on 2026-05-27

[$TBD] [517033235] Medium CVE-2026-14421 Uninitialized Use in Dawn on ChromeOS-ARM due to disabled Mali multi-resolve workaround on 2026-05-27

[$TBD] [517031505] Critical CVE-2026-14420 Out of bounds read and write in Dawn on 2026-05-27

[$TBD] [516981393] Critical CVE-2026-14419 Use after free in Skia on Allocation Failure on 2026-05-26

[$TBD] [516962715] Critical CVE-2026-13784 Use after free in Views on 2026-05-26

[$TBD] [516962178] Critical CVE-2026-13783 Use after free in Views on 2026-05-26

[$TBD] [516944556] Medium CVE-2026-14011 Out of bounds read in SurfaceCapture on 2026-05-26

[$TBD] [516936863] High CVE-2026-13845 Use after free in DOM on 2026-05-26

[$3000.0] [516836297] High CVE-2026-13842 Incorrect security UI in Chrome for iOS Reported by [] on 2026-05-26

[$TBD] [516865345] High CVE-2026-14418 Uninitialized Use in ANGLE on 2026-05-26

[$TBD] [516819850] Medium CVE-2026-14009 Insufficient data validation in Passwords on 2026-05-26

[$TBD] [516781007] Medium CVE-2026-14008 Uninitialized Use in WebXR on 2026-05-26

[$TBD] [516683433] Critical CVE-2026-13782 Use after free in Browser on 2026-05-26

[$TBD] [516649133] Critical CVE-2026-14417 Use after free in Dawn on 2026-05-26

[$TBD] [516457532] Critical CVE-2026-13781 Insufficient validation of untrusted input in Skia on 2026-05-25

[$TBD] [516425999] Medium CVE-2026-14007 Insufficient policy enforcement in PermissionsPolicy on 2026-05-25

[$TBD] [515467789] High CVE-2026-13841 Integer overflow in Skia on 2026-05-21

[$TBD] [515428315] Low CVE-2026-14416 Out of bounds read in Dawn on 2026-05-21

[$TBD] [515426873] Low CVE-2026-14148 Type Confusion in CSS on 2026-05-21

[$TBD] [515427046] Low CVE-2026-14149 Use after free in Audio on 2026-05-21

[$TBD] [515423596] Medium CVE-2026-14006 Use after free in Navigation on 2026-05-21

[$TBD] [515086856] Low CVE-2026-14415 Inappropriate implementation in V8 on 2026-05-20

[$TBD] [514769383] Critical CVE-2026-13780 Insufficient validation of untrusted input in ANGLE on 2026-05-19

[$TBD] [514632767] Low CVE-2026-14147 Inappropriate implementation in CSS on 2026-05-19

[$TBD] [514609778] High CVE-2026-13840 Insufficient policy enforcement in Canvas on 2026-05-19

[$TBD] [514550047] Low CVE-2026-14146 Inappropriate implementation in CSS on 2026-05-19

[$TBD] [514538751] Medium CVE-2026-14004 Inappropriate implementation in CSS on 2026-05-18

[$TBD] [514503077] Medium CVE-2026-14003 Insufficient policy enforcement in Extensions on 2026-05-18

[$TBD] [514489361] Medium CVE-2026-14002 Inappropriate implementation in Geolocation on 2026-05-18

[$TBD] [514485825] Low CVE-2026-14145 Inappropriate implementation in CSS on 2026-05-18

[$TBD] [514481943] Medium CVE-2026-14001 Inappropriate implementation in Network on 2026-05-18

[$TBD] [514461552] Medium CVE-2026-14000 Inappropriate implementation in XML on 2026-05-18

[$TBD] [514449396] High CVE-2026-13839 Inappropriate implementation in CSS on 2026-05-18

[$TBD] [514445398] High CVE-2026-13838 Inappropriate implementation in CSS on 2026-05-18

[$TBD] [514429130] High CVE-2026-13837 Inappropriate implementation in CSS on 2026-05-18

[$TBD] [514420555] High CVE-2026-13836 Inappropriate implementation in CSS on 2026-05-18

[$TBD] [514338102] High CVE-2026-13835 Inappropriate implementation in XML on 2026-05-18

[$TBD] [514079793] Low CVE-2026-14144 Incorrect security UI in Views on Desktop on 2026-05-17

[$TBD] [514073460] Low CVE-2026-14142 Inappropriate implementation in Extensions on 2026-05-17

[$TBD] [514072495] Low CVE-2026-14139 Inappropriate implementation in TabStrip on 2026-05-17

[$TBD] [514071697] Medium CVE-2026-13999 Inappropriate implementation in Extensions on 2026-05-17

[$TBD] [514068972] Medium CVE-2026-13996 Incorrect security UI in Permissions on 2026-05-17

[$TBD] [514064139] Medium CVE-2026-13993 Incorrect security UI in WebAppInstalls on 2026-05-17

[$TBD] [514058566] Low CVE-2026-14135 Insufficient validation of untrusted input in Network on 2026-05-17

[$TBD] [514056221] Medium CVE-2026-13989 Insufficient policy enforcement in PageInfo on 2026-05-17

[$TBD] [514040614] Medium CVE-2026-13988 Inappropriate implementation in Paint on 2026-05-17

[$TBD] [514039947] Low CVE-2026-14133 Race in History Embeddings on 2026-05-17

[$TBD] [514039492] Low CVE-2026-14132 Inappropriate implementation in WebXR on 2026-05-17

[$TBD] [514020982] Low CVE-2026-14131 Insufficient validation of untrusted input in WebAppInstalls on 2026-05-17

[$TBD] [514020959] Medium CVE-2026-13986 Inappropriate implementation in Media UI on 2026-05-17

[$TBD] [514019522] Low CVE-2026-14130 Incorrect security UI in Omnibox on 2026-05-17

[$TBD] [514013849] Medium CVE-2026-13985 Inappropriate implementation in MediaCapture on 2026-05-17

[$TBD] [514009654] Low CVE-2026-14127 Inappropriate implementation in Printing on 2026-05-17

[$TBD] [514010404] Medium CVE-2026-13984 Incorrect security UI in TabStrip on 2026-05-17

[$TBD] [514006829] Medium CVE-2026-13982 Incorrect security UI in Passwords on 2026-05-17

[$TBD] [513988889] Medium CVE-2026-13979 Inappropriate implementation in Paint on 2026-05-17

[$TBD] [513948227] Medium CVE-2026-14414 Insufficient validation of untrusted input in Skia on 2026-05-16

[$TBD] [513925114] High CVE-2026-13834 Insufficient validation of untrusted input in ANGLE on 2026-05-16

[$TBD] [513922055] High CVE-2026-14413 Uninitialized Use in ANGLE on 2026-05-16

[$TBD] [513920834] High CVE-2026-14412 Insufficient validation of untrusted input in ANGLE on 2026-05-16

[$TBD] [513919827] High CVE-2026-14411 Insufficient validation of untrusted input in ANGLE on 2026-05-16

[$TBD] [513918431] Low CVE-2026-14125 Uninitialized Use in ANGLE on 2026-05-16

[$TBD] [513866949] Medium CVE-2026-13978 Insufficient policy enforcement in PageInfo on 2026-05-16

[$TBD] [513859894] Medium CVE-2026-13977 Inappropriate implementation in HTMLParser on context element on 2026-05-16

[$TBD] [513858286] Medium CVE-2026-13976 Heap buffer overflow in Storage on 2026-05-16

[$1000.0] [513631768] Medium CVE-2026-14408 Uninitialized Use in Dawn Reported by [Chrovus ] on 2026-05-16

[$TBD] [513836996] Low CVE-2026-14410 Inappropriate implementation in Skia on 2026-05-16

[$TBD] [513810921] Low CVE-2026-14409 Inappropriate implementation in V8 Reported by [] on 2026-05-16

[$TBD] [513832989] Medium CVE-2026-13973 Inappropriate implementation in UI on 2026-05-16

[$TBD] [513822378] High CVE-2026-13832 Use after free in Headless on 2026-05-16

[$TBD] [513792140] Medium CVE-2026-13972 Inappropriate implementation in Paint on 2026-05-16

[$TBD] [513789382] Low CVE-2026-14121 Use after free in Chromoting on Linux Wayland on 2026-05-16

[$TBD] [513781328] High CVE-2026-13831 Use after free in GPU on 2026-05-16

[$TBD] [513780208] Medium CVE-2026-13971 Uninitialized Use in Skia on 2026-05-16

[$TBD] [513779283] Medium CVE-2026-13970 Uninitialized Use in Media on 2026-05-16

[$TBD] [513777411] Low CVE-2026-14120 Inappropriate implementation in DevTools on 2026-05-16

[$TBD] [513772764] Low CVE-2026-14118 Insufficient data validation in DevTools on 2026-05-16

[$TBD] [513762145] Medium CVE-2026-13968 Insufficient validation of untrusted input in DevTools on 2026-05-16

[$TBD] [513751951] Medium CVE-2026-13967 Type Confusion in V8 on 2026-05-15

[$TBD] [513747800] Low CVE-2026-14116 Insufficient validation of untrusted input in DevTools on 2026-05-15

[$TBD] [513745699] Low CVE-2026-14115 Insufficient validation of untrusted input in Cast on 2026-05-15

[$TBD] [513741393] Medium CVE-2026-13966 Inappropriate implementation in History on 2026-05-15

[$TBD] [513737952] Medium CVE-2026-13965 Use after free in Oilpan on 2026-05-15

[$TBD] [513727626] Medium CVE-2026-13963 Inappropriate implementation in DevTools on 2026-05-15

[$TBD] [513727494] High CVE-2026-13830 Use after free in Chromoting on 2026-05-15

[$TBD] [513721370] Medium CVE-2026-13962 Insufficient data validation in PDF on 2026-05-15

[$TBD] [513714023] Medium CVE-2026-13960 Inappropriate implementation in Passwords on 2026-05-15

[$TBD] [513713946] Low CVE-2026-14112 Inappropriate implementation in Enterprise on 2026-05-15

[$TBD] [513710926] Low CVE-2026-14111 Use after free in WebProtect on 2026-05-15

[$TBD] [513698452] Low CVE-2026-14110 Inappropriate implementation in DarkMode on 2026-05-15

[$TBD] [513694957] Low CVE-2026-14109 Insufficient policy enforcement in Mojo on 2026-05-15

[$TBD] [513689974] Low CVE-2026-14108 Use after free in PDFium on 2026-05-15

[$TBD] [513609249] Medium CVE-2026-13959 Insufficient validation of untrusted input in Blink on 2026-05-15

[$TBD] [513586956] Medium CVE-2026-14407 Inappropriate implementation in V8 on ARM64 due to AAPCS64 ABI Mismatch on 2026-05-15

[$TBD] [513553557] Medium CVE-2026-13957 Incorrect security UI in Extensions on 2026-05-15

[$TBD] [513544566] Low CVE-2026-14107 Use after free in Scheduling on 2026-05-15

[$TBD] [513528117] Low CVE-2026-14105 Insufficient policy enforcement in Speech on 2026-05-15

[$TBD] [513515168] Medium CVE-2026-13956 Incorrect security UI in PageInfo on 2026-05-15

[$TBD] [513504934] Medium CVE-2026-13954 Insufficient policy enforcement in XML on 2026-05-15

[$TBD] [513484193] Low CVE-2026-14104 Insufficient validation of untrusted input in WebAppInstalls on 2026-05-15

[$TBD] [513465245] Low CVE-2026-14103 Use after free in SSL on ChromeOS on 2026-05-15

[$TBD] [513459192] Medium CVE-2026-13953 Inappropriate implementation in SplitView on 2026-05-15

[$TBD] [513455047] Low CVE-2026-14102 Use after free in Passwords on 2026-05-15

[$TBD] [513435594] Medium CVE-2026-14406 Out of bounds read in V8 on 2026-05-14

[$TBD] [513401808] Medium CVE-2026-13952 Inappropriate implementation in PerformanceAPIs on 2026-05-14

[$TBD] [513399832] High CVE-2026-13828 Inappropriate implementation in Enterprise on 2026-05-14

[$TBD] [513394321] Medium CVE-2026-13951 Policy bypass in USB on Linux-based Platforms on 2026-05-14

[$TBD] [513383891] Low CVE-2026-14100 Insufficient data validation in NetworkCache on 2026-05-14

[$TBD] [513375767] Low CVE-2026-14098 Inappropriate implementation in CSS on 2026-05-14

[$TBD] [513376037] Low CVE-2026-14405 Uninitialized Use in V8 on 2026-05-14

[$TBD] [513360781] Medium CVE-2026-13950 Uninitialized Use in GPU on 2026-05-14

[$TBD] [513337989] Medium CVE-2026-14404 Inappropriate implementation in PDFium on 2026-05-14

[$TBD] [513298483] Low CVE-2026-14403 Use after free in V8 on 2026-05-14

[$TBD] [513286820] Medium CVE-2026-13948 Insufficient policy enforcement in Extensions on 2026-05-14

[$TBD] [513271007] Low CVE-2026-14095 Insufficient validation of untrusted input in Browser on 2026-05-14

[$TBD] [513240099] Low CVE-2026-14093 Use after free in Cast on 2026-05-14

[$TBD] [513226551] Medium CVE-2026-13945 Insufficient policy enforcement in Extensions on Linux via XDG Global Shortcuts portal on 2026-05-14

[$TBD] [513222854] Critical CVE-2026-13779 Use after free in Chromoting on 2026-05-14

[$TBD] [513212892] Low CVE-2026-14092 Insufficient policy enforcement in Privacy on 2026-05-14

[$TBD] [513208773] Low CVE-2026-14091 Use after free in DevTools on 2026-05-14

[$TBD] [513194241] Low CVE-2026-14090 Out of bounds read in CameraCapture on 2026-05-14

[$TBD] [513188254] Low CVE-2026-14089 Insufficient validation of untrusted input in PopupBlocker on 2026-05-14

[$TBD] [513186670] Medium CVE-2026-13942 Insufficient validation of untrusted input in Video Capture on 2026-05-14

[$TBD] [513177497] High CVE-2026-13824 Insufficient validation of untrusted input in Extensions on 2026-05-14

[$TBD] [513169718] Low CVE-2026-14086 Insufficient policy enforcement in HID on 2026-05-14

[$TBD] [513163011] High CVE-2026-13823 Use after free in Glic on 2026-05-14

[$TBD] [513158425] Medium CVE-2026-13940 Uninitialized Use in Cast on 2026-05-14

[$TBD] [513155863] Low CVE-2026-14085 Side-channel information leakage in CSS on 2026-05-14

[$TBD] [513143921] Medium CVE-2026-13938 Integer overflow in Fonts on 2026-05-14

[$TBD] [513142445] High CVE-2026-13821 Use after free in Canvas on 2026-05-14

[$TBD] [513138148] Low CVE-2026-14084 Insufficient validation of untrusted input in Chromoting on 2026-05-14

[$TBD] [513128322] Low CVE-2026-14083 Insufficient validation of untrusted input in HTML on 2026-05-14

[$TBD] [513048822] High CVE-2026-14401 Insufficient validation of untrusted input in ANGLE on 2026-05-13

[$TBD] [513049578] Low CVE-2026-14082 Race in Storage on 2026-05-13

[$TBD] [513046494] Medium CVE-2026-13937 Insufficient policy enforcement in Passwords on 2026-05-13

[$TBD] [513030698] Low CVE-2026-14081 Insufficient policy enforcement in DevTools on 2026-05-13

[$TBD] [513012139] Critical CVE-2026-13776 Type Confusion in Dawn on 2026-05-13

[$TBD] [513009005] Medium CVE-2026-13935 Side-channel information leakage in ComputePressure on 2026-05-13

[$TBD] [513006636] Medium CVE-2026-13934 Insufficient validation of untrusted input in Dawn on Android leads to GPU process UB on 2026-05-13

[$TBD] [513006745] Medium CVE-2026-14399 Uninitialized Use in Dawn on 2026-05-13

[$TBD] [513002625] Medium CVE-2026-13933 Insufficient policy enforcement in Passwords on 2026-05-13

[$TBD] [512995785] Critical CVE-2026-14398 Use after free in ANGLE on 2026-05-13

[$TBD] [512986879] High CVE-2026-13820 Out of bounds read in Skia on 2026-05-13

[$TBD] [512971938] Low CVE-2026-14079 Policy bypass in Network on 2026-05-13

[$TBD] [512953564] Low CVE-2026-14078 Policy bypass in WebRTC on 2026-05-13

[$TBD] [512937764] Medium CVE-2026-13930 Insufficient policy enforcement in Actor on 2026-05-13

[$TBD] [512162479] Medium CVE-2026-13928 Insufficient validation of untrusted input in Enterprise on 2026-05-11

[$TBD] [511823182] High CVE-2026-13818 Inappropriate implementation in Passwords on 2026-05-10

[$TBD] [511815165] Low CVE-2026-14076 Policy bypass in Network on 2026-05-10

[$TBD] [511766407] Critical CVE-2026-13775 Use after free in GPU on 2026-05-10

[$TBD] [511748106] Medium CVE-2026-13922 Side-channel information leakage in Paint on 2026-05-10

[$TBD] [511739631] High CVE-2026-13817 Insufficient validation of untrusted input in Glic on 2026-05-10

[$TBD] [511738175] Medium CVE-2026-13921 Insufficient validation of untrusted input in DeviceBoundSessionCredentials on 2026-05-10

[$TBD] [511722207] High CVE-2026-13815 Use after free in Blink on 2026-05-10

[$TBD] [511712766] High CVE-2026-13814 Use after free in Views on 2026-05-10

[$TBD] [511290389] Low CVE-2026-14395 Out of bounds write in V8 on 2026-05-08

[$TBD] [511263221] Low CVE-2026-14394 Use after free in V8 on 2026-05-08

[$TBD] [511255112] Medium CVE-2026-14393 Use after free in V8 on 2026-05-08

[$TBD] [511249430] Medium CVE-2026-13919 Insufficient data validation in Extensions on 2026-05-08

[$3000.0] [510829679] High CVE-2026-13793 Insufficient policy enforcement in SVG on 2026-05-07

[$1000.0] [507263861] Low CVE-2026-14026 Misleading Directory Upload via Split View Context Confusion on 2026-04-28

[$0.0] [507099867] Low CVE-2026-14072 Incorrect security UI in SplitView Reported by [] on 2026-04-28

[$TBD] [507239830] Medium CVE-2026-13911 Insufficient data validation in Spellcheck on 2026-04-27

[$TBD] [507237563] Low CVE-2026-14073 Insufficient policy enforcement in WebXR on 2026-04-27

[$3000.0] [507090179] Medium CVE-2026-13858 Out of bounds read in FFmpeg on 2026-04-27

[$TBD] [506558270] Critical CVE-2026-13774 Use after free in Extensions on 2026-04-25

[$TBD] [506149253] High CVE-2026-13811 Use after free in IME on 2026-04-24

[$TBD] [506143724] Low CVE-2026-14071 Side-channel information leakage in WebAudio on 2026-04-24

[$TBD] [505933538] Medium CVE-2026-13909 Insufficient policy enforcement in DevTools on 2026-04-23

[$TBD] [505137978] Low CVE-2026-14070 Uninitialized Use in WebNN on 2026-04-21

[$TBD] [505136542] Low CVE-2026-14069 Integer overflow in WebNN on 2026-04-21

[$TBD] [504613867] Medium CVE-2026-13906 Out of bounds read in Codecs on 2026-04-20

[$1000.0] [504600482] Low CVE-2026-13810 Inappropriate implementation in Input on focus. This allows XSS to silently harvest saved passwords on page load without clicks, bypassing mandatory user gesture security checks. on 2026-04-20

[$TBD] [503912196] Medium CVE-2026-13903 Insufficient policy enforcement in Bluetooth on 2026-04-17

[$TBD] [503617508] Low CVE-2026-14065 Insufficient validation of untrusted input in PageInfo on 2026-04-17

[$TBD] [503585173] Medium CVE-2026-13901 Insufficient validation of untrusted input in Serial on 2026-04-16

[$TBD] [503333798] High CVE-2026-13806 Insufficient validation of untrusted input in Accessibility on 2026-04-16

[$TBD] [503054174] High CVE-2026-14390 Use after free in ANGLE on 2026-04-15

[$TBD] [502473563] Low CVE-2026-14063 Out of bounds memory access in Chromecast on 2026-04-14

[$TBD] [502448128] Low CVE-2026-14062 Inappropriate implementation in Views on ChromeOS on 2026-04-14

[$TBD] [502434484] Low CVE-2026-14061 Inappropriate implementation in Dawn on hardware with 1ns timestamp period on 2026-04-14

[$TBD] [502374993] Medium CVE-2026-13900 Insufficient validation of untrusted input in Chromecast on 2026-04-13

[$TBD] [502363986] Low CVE-2026-14059 Insufficient policy enforcement in Related-Website-Sets on RWS removal on 2026-04-13

[$TBD] [502354038] Low CVE-2026-14058 Policy bypass in Parser on 2026-04-13

[$TBD] [502212647] Low CVE-2026-14057 Insufficient policy enforcement in FedCM on 2026-04-13

[$TBD] [502109002] Medium CVE-2026-13899 Use after free in HTML on 2026-04-13

[$TBD] [501925480] Medium CVE-2026-13898 Use after free in Cast Receiver on 2026-04-12

[$TBD] [501888426] Low CVE-2026-14056 Insufficient validation of untrusted input in Media on 2026-04-12

[$TBD] [501877896] Medium CVE-2026-13897 Insufficient policy enforcement in Chromecast on 2026-04-12

[$TBD] [501873032] High CVE-2026-13804 Use after free in Chromecast on 2026-04-12

[$TBD] [501851312] Low CVE-2026-14054 Insufficient policy enforcement in Network on 2026-04-12

[$TBD] [501836539] Low CVE-2026-14053 Insufficient policy enforcement in Extensions on 2026-04-12

[$TBD] [501820076] Medium CVE-2026-13896 Insufficient policy enforcement in Glic on 2026-04-11

[$TBD] [501810874] Low CVE-2026-14052 Insufficient policy enforcement in FileSystem on 2026-04-11

[$TBD] [501770542] Medium CVE-2026-13895 Inappropriate implementation in Autofill on 2026-04-11

[$TBD] [501741117] Medium CVE-2026-13894 Insufficient policy enforcement in Network on 2026-04-11

[$TBD] [501729582] Medium CVE-2026-13893 Insufficient validation of untrusted input in WebUI on 2026-04-11

[$TBD] [501708647] Low CVE-2026-14050 Insufficient policy enforcement in Passwords on 2026-04-11

[$TBD] [501659888] Low CVE-2026-14049 Inappropriate implementation in GPU on 2026-04-11

[$TBD] [501631475] Medium CVE-2026-13891 Insufficient validation of untrusted input in Extensions on 2026-04-11

[$TBD] [501623322] High CVE-2026-13802 Use after free in Views on 2026-04-11

[$TBD] [500601345] Medium CVE-2026-13890 Out of bounds read in Chromecast on 2026-04-08

[$TBD] [500587568] High CVE-2026-13801 Integer overflow in Chromecast on 2026-04-08

[$TBD] [500566906] Medium CVE-2026-13888 Use after free in Extensions on 2026-04-07

[$TBD] [500505046] Medium CVE-2026-14389 Integer overflow in Skia on 2026-04-07

[$TBD] [500476886] Medium CVE-2026-14388 Out of bounds read in ANGLE on 2026-04-07

[$TBD] [500475136] Medium CVE-2026-13886 Policy bypass in Isolated Web Apps on 2026-04-07

[$TBD] [500305404] Medium CVE-2026-14387 Integer overflow in Skia on 2026-04-07

[$TBD] [500077014] Medium CVE-2026-13884 Heap buffer overflow in Chromecast on 2026-04-06

[$TBD] [500030250] Medium CVE-2026-13883 Type Confusion in ANGLE on 2026-04-06

[$TBD] [499252371] High CVE-2026-13799 Use after free in QUIC on 2026-04-03

[$TBD] [499189601] Low CVE-2026-14048 Use after free in Chromecast on 2026-04-03

[$TBD] [499162550] Medium CVE-2026-13882 Inappropriate implementation in USB on 2026-04-02

[$TBD] [499100491] Medium CVE-2026-13881 Insufficient data validation in WebAppInstalls on 2026-04-02

[$TBD] [499048914] High CVE-2026-13798 Heap buffer overflow in Chromecast on 2026-04-02

[$TBD] [499025645] High CVE-2026-13797 Insufficient validation of untrusted input in Chromecast on 2026-04-02

[$TBD] [499022239] Medium CVE-2026-13879 Use after free in Bluetooth on 2026-04-02

[$TBD] [498864176] Low CVE-2026-14047 Insufficient policy enforcement in Extensions on 2026-04-02

[$TBD] [498820206] Medium CVE-2026-13877 Insufficient validation of untrusted input in ANGLE on 2026-04-01

[$TBD] [498722200] Medium CVE-2026-13876 Inappropriate implementation in Network on 2026-04-01

[$TBD] [498411773] Medium CVE-2026-13874 Inappropriate implementation in DataTransfer on 2026-03-31

[$TBD] [498085466] Medium CVE-2026-13873 Out of bounds memory access in Layout on 2026-03-31

[$TBD] [497961376] Medium CVE-2026-13871 Insufficient data validation in GuestView on 2026-03-30

[$TBD] [497723649] Low CVE-2026-14045 Insufficient validation of untrusted input in Network on 2026-03-30

[$TBD] [497670996] Low CVE-2026-14044 Use after free in ANGLE on 2026-03-30

[$TBD] [497632232] Low CVE-2026-14043 Use after free in GetUserMedia on 2026-03-29

[$TBD] [497558336] Low CVE-2026-14042 Inappropriate implementation in Isolated Web Apps on 2026-03-29

[$TBD] [497544822] Low CVE-2026-14041 Insufficient policy enforcement in Serial on 2026-03-29

[$TBD] [497488593] Low CVE-2026-14040 Use after free in BrowserTag on 2026-03-29

[$TBD] [497358012] Low CVE-2026-14039 Insufficient policy enforcement in GetUserMedia on 2026-03-28

[$TBD] [497345177] Medium CVE-2026-13867 Inappropriate implementation in Geolocation on 2026-03-28

[$TBD] [497241148] Low CVE-2026-14038 Insufficient validation of untrusted input in New Tab Page on 2026-03-28

[$TBD] [497090912] Medium CVE-2026-13865 Insufficient validation of untrusted input in Enterprise on 2026-03-27

[$TBD] [496522611] Low CVE-2026-14037 Insufficient policy enforcement in GPU on 2026-03-26

[$TBD] [496411061] Low CVE-2026-14036 Insufficient policy enforcement in Bluetooth on 2026-03-25

[$TBD] [496399913] Medium CVE-2026-13864 Insufficient policy enforcement in WebHID on 2026-03-25

[$TBD] [496371586] Low CVE-2026-14035 Insufficient policy enforcement in Bluetooth on 2026-03-25

[$TBD] [495459838] Low CVE-2026-14031 Incorrect security UI in File Input on 2026-03-23

[$TBD] [495456765] Medium CVE-2026-13861 Use after free in Core on 2026-03-23

[$TBD] [492410546] Medium CVE-2026-14383 Inappropriate implementation in V8 on 2026-03-13

[$TBD] [491894115] High CVE-2026-13796 Integer overflow in Chromecast on 2026-03-11

[$1000.0] [488762971] Low CVE-2026-14030 Incorrect security UI in SplitView on 2026-03-01

[$5000.0] [479203484] Medium CVE-2026-13857 Inappropriate implementation in Geometry Reported by [Luan Herrera (@lbherrera_)] on 2026-01-27

[$10000.0] [457771782] High CVE-2026-13790 Side-channel information leakage in Scroll Reported by [] on 2025-11-04

[$1000.0] [417052041] Medium CVE-2026-13860 Incorrect security UI in Autofill on 2025-05-11

[$500.0] [527385397] High CVE-2026-15132 Uninitialized Use in V8 on 2026-06-24

[$500.0] [527406824] High CVE-2026-15133 Use after free in InterestGroups on 2026-06-24

[$TBD] [526542464] Medium CVE-2026-15131 Insufficient data validation in Navigation on 2026-06-22

[$TBD] [526541544] High CVE-2026-15130 Insufficient policy enforcement in Navigation on 2026-06-22

[$TBD] [524045160] Critical CVE-2026-15129 Use after free in Views on 2026-06-14

[$TBD] [523756329] High CVE-2026-15128 Inappropriate implementation in Forms on 2026-06-13

[$TBD] [523752265] High CVE-2026-15127 Inappropriate implementation in WebGL on 2026-06-13

[$TBD] [523748081] High CVE-2026-15126 Use after free in Forms on 2026-06-13

[$TBD] [523737685] High CVE-2026-15125 Inappropriate implementation in Forms on 2026-06-13

[$TBD] [523735038] High CVE-2026-15124 Insufficient policy enforcement in Passwords on 2026-06-13

[$TBD] [523729553] High CVE-2026-15123 Insufficient data validation in DOM on 2026-06-13

[$TBD] [523712556] High CVE-2026-15121 Use after free in WebRTC on 2026-06-13

[$TBD] [523505418] High CVE-2026-15119 Inappropriate implementation in GetUserMedia on 2026-06-12

[$TBD] [523238265] High CVE-2026-15118 Use after free in Input on 2026-06-12

[$TBD] [522568496] High CVE-2026-15117 Use after free in Payments on 2026-06-10

[$TBD] [522092013] High CVE-2026-15116 Use after free in Actor on 2026-06-09

[$TBD] [520565945] High CVE-2026-15114 Out of bounds read and write in Codecs on 2026-06-05

[$TBD] [518006275] Critical CVE-2026-15112 Use after free in Ozone on 2026-05-29

[$TBD] [517508651] High CVE-2026-15111 Use after free in Views on 2026-05-28

[$TBD] [516899138] High CVE-2026-15109 Uninitialized Use in ANGLE on 2026-05-26

[$TBD] [515443146] High CVE-2026-15108 Integer overflow in Extensions API on 2026-05-21

[$2000.0] [503553615] Medium CVE-2026-15107 Use after free in IndexedDB on 2026-04-17

[$TBD] [532929679] High CVE-2026-15777 Use after free in UI on 2026-07-09

[$TBD] [532595489] High CVE-2026-15776 Type Confusion in V8 on 2026-07-08

[$TBD] [531319201] High CVE-2026-15775 Insufficient policy enforcement in V8 on 2026-07-05

[$TBD] [530646115] High CVE-2026-15774 Use after free in Skia on 2026-07-03

[$TBD] [525317502] High CVE-2026-15772 Use after free in GPU on Android via GLTextureHolder::ReadbackToMemory on 2026-06-18

[$TBD] [524792614] High CVE-2026-15770 Uninitialized Use in V8 on 2026-06-17

[$TBD] [519731111] High CVE-2026-15769 Insufficient validation of untrusted input in Linux Toolkit Theming on 2026-06-03

[$TBD] [518007484] Critical CVE-2026-15765 Use after free in Ozone on 2026-05-29

[$TBD] [517931625] High CVE-2026-15768 Insufficient policy enforcement in HTML-in-Canvas on 2026-05-29

[$TBD] [517100492] Critical CVE-2026-15764 Use after free in Ozone on 2026-05-27

[$TBD] [514748734] High CVE-2026-15767 Heap buffer overflow in libyuv on 2026-05-19

[$TBD] [514010477] High CVE-2026-15766 Uninitialized Use in Skia on 2026-05-17

[$TBD] [513795122] Medium CVE-2026-15778 Insufficient validation of untrusted input in Navigation on 2026-05-16

'Grok Build' Coding Tool Open Sourced This Week, Promises to Respect Zero Data Retention

Sun, 19 Jul 2026 05:52:54 +0200

Elon Musk confirmed SpaceX has open sourced the Grok Build CLI this week, reports The Register, "just days after researchers caught the AI tool scooping up users' entire repositories and uploading them to company-controlled cloud storage." That discovery had "gathered so much negative attention that Elon Musk felt compelled to issue a public statement alongside SpaceX, and its technical staff, promising to delete all data that Grok Build has ever stored and give users more choice over how their data is handled." SpaceXAI's data grab was first publicized Sunday [July 12] by Cereblab, who probed Grok Build traffic and found that repos were being packaged up as Git Bundles and beamed to Google Cloud storage... [Elon Musk] said SpaceX would open-source Grok Build to sow greater trust in the product, after the codebase was audited for security vulnerabilities... ["Open-sourcing Grok Build allows anyone to support making a reliable and robust harness," SpaceX posted on X.com. "Check out our code, including the Git repo for the Grok Build CLI."] In a separate statement accompanying the open source announcement, SpaceX said it has always respected Zero Data Retention (ZDR), which was applied to enterprise customers by default, and acknowledged that data retention was enabled by default for everyone else, which has now been corrected. It said: "In response to user questions about privacy: Since launch, Grok Build has fully respected zero data retention (ZDR). All users have always had the ability to disable data upload in the CLI. When data upload was disabled, this choice was respected. In the early beta, data retention was enabled by default for non-ZDR users. Based on your feedback, we changed this. We are now going further to protect privacy. With all retained data deleted, retention default off, and an open-source harness, we are offering complete user privacy. You can also run Grok Build fully open-sourced and local-first with your own inference. "We disabled default retention for all Grok Build users starting on July 12th. Additionally, we are deleting all coding data that was previously retained, ensuring every user's preferences are respected. With these steps, Grok Build goes beyond other major coding products to protect user privacy." SpaceX also invited researchers to probe Grok Build for security issues and report them to its bug bounty program, which offers rewards ranging from $100-$20,000, depending on the severity. The article notes Simon Willison, creator of Datasette and co-creator of Django, wrote this week that the Grok Build codebase comprises 844,530 lines of Rust code. "There are still remnants of the code that used to upload everything to Google Cloud," Willison writes, "but they seem to have been disabled now." Elon Musk also posted Wednesday that "Once we have completed our review for security vulnerabilities, we will make the entire codebase of X open source, with no exceptions. Moreover, we will invite third party reviewers to examine the system that is running to confirm that the open source code is what is running."

Anyone here using Proton Drive as their primary cloud storage on Fedora?

Sun, 19 Jul 2026 04:54:39 +0200

Has anyone here completely switched to Proton Drive on Fedora as their primary cloud storage?

I'm curious how you're handling things like:

automatic sync

large file transfers

backups

rclone vs the official CLI

overall reliability

I've been digging into Proton Drive's Linux architecture and wrote up my findings if anyone's interested: Proton Dive on Linux

I'd love to hear how other Fedora users have set up their workflow.

submitted by /u/the_nazar
[link] [comments]

Apple bumps up the cost of iCloud+ in 8 countries

Sat, 18 Jul 2026 14:23:52 +0200

Apple has continued to put the prices up for its online services, with iCloud+ rising in cost in a number of territories.

iCloud+ now costs more money in some countries.

Over the course of a few days, Apple has been increasing the prices of its various online services. Not to be left behind, iCloud+ has now upped its prices to join the rest of the roster.

The change, revealed by Apple's iCloud+ pricing support page, doesn't outright say what countries are affected by the pricing. However, comparisons with previous pricing, including via the Wayback Machine, shows it affects eight countries in total.

Continue Reading on AppleInsider | Discuss on our Forums

600$ For Stealing Podcasts/Show via RSS Feed Manipulation

Sat, 18 Jul 2026 11:39:22 +0200

Hello hunters! 👋

In this write-up, I will share a Business Logic Flaw I discovered in a major podcasting platform (redacted.com).

By manipulating a simple XML file (RSS Feed), I was able to bypass the ownership verification process and claim legitimate podcasts as my own. This allowed me to create duplicate entries and hijack the identity of famous podcasts on the platform.

Let’s get into the details! 🚀

The Logic

The target platform allows creators to submit their podcasts using an RSS Feed URL. To verify that you own the podcast, the system reads the tag inside the RSS file and sends a verification code to that email.

The mechanism:

User submits RSS URL (e.g., mysite.com/feed.xml).
System reads the XML
System extracts email from owner@example.com.
System sends a code to owner@example.com.

The Bug

The system failed to fingerprint the content of the podcast to check for duplicates. It trusted any RSS feed as long as the email inside matched the submitter’s account.

This means if I download a famous podcast’s RSS feed, change the email inside it to my email, and host it on a public cloud storage, the system treats it as a new, valid podcast owned by me.

Steps to Reproduce

Here is how I exploited this logic:

1. Pick a Target

I found a valid, already published podcast on redacted.com. I copied their legitimate RSS feed URL.

2. Manipulate the Feed

I downloaded the RSS XML file to my local machine. I opened it and modified two lines:

Title: Changed it slightly (to avoid exact name matches).
Email: Changed the tag to MY email address (the one I used to sign up on the target site).

The Payload (RSS XML):


    HACKED PODCAST NAME    
    attacker@gmail.com

3. Host the Malicious Feed

I uploaded this modified .rss file to a Google Cloud Storage bucket (or any public cloud storage) to get a valid URL. URL Example: https://storage.googleapis.com/.../exploit.rss

4. Submit & Takeover

I went to https://redacted.com/submitـrss.
I submitted my Google Cloud Storage URL.
The system parsed the file, saw my email in the tag, and sent me the verification email.
I clicked verify.

Result: The podcast was successfully added to my account! I now controlled a duplicate version of the victim's content on the main streaming platform.

The Impact

This was a simple but effective Logic Bypass.

Impersonation: Attackers can claim ownership of content they don't own.
Phishing/Spam: Attackers can clone popular podcasts and inject their own descriptions or links.
Platform Confusion: Listeners see duplicate versions of the same show.

Remediation

The platform patched this by:

Implementing stricter checks on RSS feed content (hashing content to find duplicates).
Improving validation to detect if a feed is simply a re-hosted copy of an existing one.

600$ For Stealing Podcasts/Show via RSS Feed Manipulation was originally published in InfoSec Write-ups on Medium, where people are continuing the conversation by highlighting and responding to this story.

CallMeOnTheChain — EtherRAT Lab Writeup [CyberDefenders]

Sat, 18 Jul 2026 11:39:21 +0200

CallMeOnTheChain — EtherRAT Lab Writeup [CyberDefenders]

CallMeOnTheChain - EtherRAT | Blue team challenge.

You can read this writeup on my GitBook: Link

Scenario

Something is wrong at Maromalix. On February 10th, 2026, credentials that should never have left the network were suddenly used from an unauthorized external source. The trail led back to a single server: their public-facing web application. No failed logins, brute force, or phishing were detected, yet the attacker gained entry and established a way to return. This follows a pattern of Maromalix being targeted by attackers leveraging AI-assisted tooling. Using the captured network traffic, reconstruct the timeline and uncover exactly how this breach occurred.

Initial Access

Q1: What is the IP address of the attacker that exploited the web application?

By reading the scenario above carefully, we have a public-facing web application asset that got attacked, so let’s start investigation.
We are provided here with a pcap file with ssl keys log file:

Edit →Preferences →Protocols → TLS → (Pre)-Master-Secret log filename

At first, filtered for http traffic, and took a look at conversations, found the IP for the web-server (arguably172.31.44.238 is the web-server IP)

Narrowing down a little with this query: http.request.method==POST and ip.dst==172.31.44.238 for less packets and better inspection (~300 packets).
After following someTLSstreams, found this communication:

a weird POST requests generated by a script maybe (User-Agent: python-requests/2.31.0\r\n) and have the same length (339).
so, i guess this needs further investigation by adding the source IP address http.request.method==POST and ip.dst==172.31.44.238 and ip.src==63.180.69.24

Actually i couldn’t stop myself from inspecting the fisrtPOST request with a different length, so i followed the TLSstream for this hovered packet:

so it’s a payload that abuses a JavaScript weakness (prototype pollution + constructor escape) to escape normal restrictions, then executes the system command id on the server. After that, it tries to sneak the result back to the attacker by embedding it inside an error response.

Also, By investigating the second packets with the length > 339:

we can find this payload also:

So it makes sense now!!

63.180.69.24

Q2: What is the CVE identifier for the vulnerability exploited in this attack?

from the Lab Name, we can search and get the CVE easily:

Or by searching for the CVE from the payloads we’ve already identified in the previous question:

CVE-2025–55182

Execution

Q3: What is the filename of the script downloaded by the exploit payload to install the malware?

based on paloalto report (link) we did identified this

so, we can filter for the user-agent curl , and GET requests:
http.request.method==GET and http.user_agent contains "curl"

s.sh

Q4: What is the filename of the decrypted implant that serves as the main RAT?

By investigating the bash script file, we can get the correct answer directly:

.7vfgycfd01.js

Defense Evasion

Q5: What is the hidden directory path used by the malware to store its components?

Investigating the same Bash script file, it’s obvious at the beginning of the file:

~/.local/share/.05bf0e9b

Q6: The malware checks system locale to avoid execution in certain regions. What is the first locale code in the blocklist?

since we have the full script, the script contains a Base64 encoded Blob

That is AES Encrypted, with a clear Key and IV as you can see,

So, Let’s decrypt it properly on cyberchef (link), and get the answer:

ru

Command and Control

Q7: What are the two smart contract addresses used for C2 resolution? (Format: in the order they are queried)

from the same previous decrypted Code, we can get the addresses directly:

0x22f96d61cf118efabc7c5bf3384734fad2f6ead4,0xb0cbaA51b3D1D36e8E95F4F68dfBd47ED2eaA7a4

Q8: When was the primary smart contract deployed on the Ethereum network (UTC)?

from the previous image, we can determine that the first contract is the primary one, so let’s check it online (link)

from etherscan, we can can go to the full contract and get the timestamp:

2025–12–05 19:13:47

Q9: Since the smart contract is deployed on a public blockchain, its source code can be obtained.
What function name is used to retrieve the stored C2 URL?

in my case i used the Dedaub (LINK),

Now, we can put the input data we found in the contract into Dedaub:

just like this:

and now it’s decompiled successfully:

it’s basically a minimal storage contract that lets an address store and retrieve a string mapped to its address, so let’s take that full string and decompile it again into Dedaub:

getString

Q10: What is the transaction hash of the first C2 URL published to the primary contract?

investigating the first transaction hash as shown:

investigating the Input data:

Decode Input

so yeah, it contains the C2 URL, so hit the transaction hash for the answer

0xe4efe4d2b118229161f7023e13ab98b54180fbfb1756d11959e4f19238b9655d

Q11: When did the implant retrieve the C2 URL from the blockchain (UTC)?

falling back to our pcap file, we can use this filter: http contains "eth"or search for eth_callsince it is the JSON-RPC method used to read data from smart contracts:

2026–02–10 18:37

Q12: What C2 URL did the implant retrieve from the blockchain during execution?

we can see here the traffic direction:

https://63.176.62.199:443

Q13: What is the Bot ID assigned to the compromised host?

the same previous packet, we can get the BotID from it

4ebfbc8aedf60511

Credential Access

Q14: Once connected to the C2, the implant started executing multi-stage payloads.
What is the endpoint path used for exfiltrating harvested credentials?

checking all visited URLs, until you'll find this:

/crypto/keys

Persistence

Q15: What is the filename of the systemd user service created for persistence?

Since we are looking for Linux persistence via a systemd user service, so the goal is to find where the attacker creates or references a .service file.

c16a536e1a9cb42d.service

Q16: What is the comment field in the attacker’s injected SSH public key?

we need to know first that the structure is like this:
ssh-rsa , so by the filter : http contains "ssh-rsa"

single lonely packet, let’s check its TLS stream, and get the answer:

BINGO!

maromalix@ether_dev

Execution

Q17: When was the first remote command executed through the C2 channel (UTC)?

this question and the next one Q18, have the same idea.
from reading the full decrypted AES js file (Link), we can determine that It generates a fake-looking URL, which is used for Beaconing:

https:///api///.?=


https://63.176.62.199:443/api//4ebfbc8aedf60511/.?=4ebfbc8aedf60511

So, by searching with this query: http.request.method==GET and ip.src==172.31.44.238 and ip.dst==63.176.62.199, we can see this:

All commands by the C2 Beaconing server (with some jitter intervals)

SO, we can determine the command by following the TLS Stream for each packet, (the command will be seen in the GETresponse packet) like this:

or another way, with searching for the POSTrequests, from the web-server to the C2 server with query: http.request.method==POST and ip.src==172.31.44.238 and ip.dst==63.176.62.199

and get the precious commands “whoami” with the timestamp:

2026–02–10 18:40

Q18: After establishing access, the attacker closed the door behind them so no one could get in the way they did.
What Next.js version was installed to patch the vulnerability?

investigating all commands by this amazing query:

http.request.method==POST and ip.src==63.180.69.24 and http.request.uri
contains "/login" and http.content_length>339

we now have all the 8 executed commands, this one is the one we need

so by investigating each packet (Follow TLS) we can find this

15.3.9

Q19: Based on the observed IOCs and TTPs,
which nation-state is most likely behind this activity?

from the CVE number (CVE-2025–55182), we identified that it’s origin from North Korea (DPRK)

DPRK

Thanks For Reading, Hope you enjoyed❤️

Keep in touch with me via: https://linktr.ee/Prankster99

CallMeOnTheChain — EtherRAT Lab Writeup [CyberDefenders] was originally published in InfoSec Write-ups on Medium, where people are continuing the conversation by highlighting and responding to this story.