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How sovereign is Europe's space industry?

Sun, 26 Jul 2026 07:02:56 +0200

As space becomes an increasingly important part of global communications, national security, and critical infrastructure, European governments are confronting a difficulty: How much control do they need over their own space capabilities? In this week’s episode, host Maria Varmazis sits down with producer Ethan Cook⁠⁠⁠ to examine the growing push for European space sovereignty and the challenges standing in the way. The conversation explores how supply-chain dependencies can undermine national and regional independence, even when satellites and launch systems are built domestically. Additionally, the two also discuss the trade-offs between complete self-sufficiency and maintaining resilient, diversified international partnerships.

Chips and drones to be at heart of Burnham’s push to ‘reindustrialise’, AI minister says

Sun, 26 Jul 2026 06:40:45 +0200

Kanishka Narayan tells FT that new prime minister views technology as way for Britain ‘to get its mojo back’

China is Creating a Herd of 100 Elite Yak Clones

Sat, 25 Jul 2026 20:01:07 +0200

CNN reports on yaks "designed and cloned" in secretive, high-altitude labs in Tibet — 2.4 miles (4,000 meters) above sea level. They're a critical part of the local economy, and researchers "hope to create an 'elite' herd of super-yaks, healthier and more fertile than their predecessors." Both domestic yaks and their wild cousins have been facing threats for years, with some rare subspecies at risk of disappearing entirely. Authorities in the southwestern Chinese region have poured tens of millions of dollars into boosting the yak industry in recent years — and they hope cloning can help. The first yak clone came in July 2025, Chinese state media hailing it as a breakthrough achievement that combined cloning with gene selection. More clones were born this spring — and researchers are now aiming to create a herd of more than 100 "elite" yak clones by 2028, boasting desired traits like faster growth and larger size. "This shows the technology has moved from a one-time success to a stable, mass-scale application," said Fang Shengguo, the project's scientific lead and director of the State Conservation Center for Gene Resources of Endangered Wildlife, according to state-run news agency Xinhua... Many experts acknowledge there are legitimate arguments for using cloning in conservation, and for gene selection in farming. But the ethical waters are murky, and any such project should have high levels of public transparency and accountability, said Lisa Moses, a veterinarian and bioethicist at Harvard Medical School. So far, much of the yak cloning project remains mysterious, with information largely limited to glowing state-media coverage... [S]ome scientists say these projects reduce our sense of urgency toward fixing the environment, and that we can't simply churn out clones while the planet burns. To truly enact change, they say, we have to continue addressing the root cause of the problem — restoring degraded habitats, lowering carbon emissions, cracking down on poaching, and more. But for others, "there is a strong feeling ... that traditional conservation is essentially failing now," Moses said. "What we've been doing for the last 100 years to try to stave off ecological destruction is not working.... The argument is, we don't have a choice," she added. "If we want to try to do something that will actually make a difference, we need to use these technologies, specifically synthetic biology, to essentially override evolution and change the fitness of the species for the environment that they live in." "History is littered with good intentions in the environment gone wrong," Moses said, "and I would argue that these technologies have even more unknowns than ones that we previously employed." The article points out that the number of wild yaks "dropped more than a third in the last 30 years, with just 10,000 to 20,000 individuals left, according to the Wildlife Conservation Society." The yaks are threatened by climate change and habitat degradation, "with warmer temperatures bringing invasive plant species and increased competition for resources... in one of the world's most inhospitable terrains."

Read more of this story at Slashdot.

The EU’s AI transparency deadline is weeks away. Is your enterprise ready?

Sat, 25 Jul 2026 19:50:13 +0200

Providers and deployers of AI systems: You only have a couple of weeks left until you must explicitly inform users when they are interacting with AI content.

To assist in the effort, the European Commission (Commission) has published guidelines to help AI deployers get in line with the AI Act’s transparency obligations, which will begin to go into effect on August 2.

After that, companies providing AI systems must alert users when they are interacting with AI. They must also tell users when they have been exposed to deepfakes, “emotion recognition,” or biometric categorization systems, or when they are given AI-manipulated content in matters of “public interests without human review or editorial control.”

Henna Virkkunen, the Commission’s executive VP for tech sovereignty, security and democracy, said in a statement, “with today’s guidelines, the Commission supports the smooth and effective application of the AI Act to make AI systems interacting with people such as chatbots and AI agents and AI content more transparent and trustworthy. These guidelines support providers and deployers in meeting their obligations under the AI Act, while helping citizens know when they are interacting with AI.”

Systems must include machine-readable markers to reveal such content, to reduce “the risk of deception and manipulation” and build public trust in AI.

“Generative systems have collapsed the cost of producing convincing content while the cost of judging it stands where it always stood,” said Sanchit Vir Gogia, chief analyst at Greyhound Research. This requirement is “an attempt to restore friction to that imbalance.”

A company’s non-compliance could result in fines anywhere from €750K (about $856K) to €15M (about $17 million), or even up to 3% of its total worldwide annual revenue.

Transparency requirements

The EU AI Act’s transparency requirements apply to “natural or legal persons,” public authorities, agencies, or other bodies that develop AI systems, or have them developed, and place them on the EU market or into use under their name or trademark. This means all companies, regardless of whether or not they are EU-based.

“Systems placed on the European market, put into service there, or producing outputs used there are inside the field, wherever the developer sits,” Gogia noted.

Applicable systems must be intended to interact directly with “natural persons”; these systems include AI-enabled chatbots or conversational agents, AI companions, or coding agents. However, AI-enabled tools like recommender systems, spam filters, authentication, search and retrieval, transcription, text and code auto-completion, or predictive maintenance do not fall under the rule.

Specific outputs such as AI-generated text, images, video, and audio must contain a machine-readable mark. Deepfakes and public interest-related text created by AI without human review or control must be clearly labeled, however, deepfake content that is “artistic, creative, satirical, or fictional” is largely exempt.

AI content must be marked with one of three labels: “AI,” “Fully AI-generated,” or “Partially AI-modified.” For instance, “Fully AI-generated” applies when news summaries, music, art, or videos have been created without any human oversight (apart from prompting), while “partially AI-modified” could mean a person’s face is swapped into an authentic photograph to create a deepfake.

The three icons are publicly available for free use; enterprises can download zip files in PNG and SVG formats.

Most of the Act’s transparency rules begin to go into effect on August 2. But AI systems placed on the market before then will have some leeway; they must be in compliance by December 2.

However, a four-month allowance “on one obligation, for one population of systems, contingent on one procedural step, is not a strategy,” Gogia emphasized. Enterprises should plan to comply by August 2 and “treat any relief that arrives as margin.”

A consistent code of practice

Along with the transparency guidelines, the Commission has introduced a code of practice that essentially serves as a gesture of good faith. When signed, it can provide “legal certainty” and a “simple and practical” way to demonstrate compliance with the AI Act, according to the Commission. Signatories can also collaborate through the ‘Signatory Taskforce,’ which will share practices and advance technologies around marking and labeling practices.

Providers that choose not to sign must comply through other methods and demonstrate that those methods are “adequate” through assessment by surveillance authorities, according to the Commission.

Non-signatories “keep their flexibility, and will face more case-by-case scrutiny for it,” said Gogia.

Criteria for compliance

Shashi Bellamkonda, principal research director at Info-Tech Research Group, pointed out that the transparency requirements apply to content only when three criteria are met: It has been published, is informative to the public, or is on matters of public interest.

B2B business content or blogs may not need an AI disclosure if they do not meet these criteria, he noted. Also, published text that has undergone human review or is under editorial control does not need to be labeled. Editorial control means that a person must hold the ultimate legal responsibility for the publication of the content.

Many companies like Google, Adobe, and LinkedIn have already established ways to identify images marked as AI-generated. Meta has made it a requirement, but the creator has to add the AI-generated label, Bellamkonda said.

“This is a good move for guardrails around public information, and companies with good compliance and ethical oversight may not have to worry about this,” he noted. But as a general practice, companies should disclose AI-generated content and state whether it has been human reviewed.

Creating a transparency pipeline

Establishing full transparency means identifying who carries the responsibility for the content, whether the marking survives real use, not just testing, and what evidence will defend the decision, Gogia said.

Concerns cluster around responsibility, durability and evidence. Several organizations usually touch one piece of content, and none controls the whole chain, which is why contracts become the “pressure point,” he said. Most current agreements were written to deliver software and say “almost nothing” about provenance persistence, verification access, or evidence retention.

The durability concern is the most difficult, Gogia noted, because marking performs well in controlled settings but “badly in ordinary life.” Meta, for one, said its invisible watermark was designed to survive cropping; a published test, however, found the company’s preview detector missed 55% of cropped images.

“CIOs should ask which platform can actually provide evidence before believing its dashboard,” said Gogia.

Disclosure of AI use must be “clear, distinguishable and accessible,” he emphasized. “A notice buried in lengthy terms, or reachable only through determined clicking, satisfies nobody, least of all a market surveillance authority.”

Sustained compliance is a “living control” requiring a central record of systems, duties and evidence; testing taking place where the user meets the control rather than where the developer built it; and continuous supplier assurance. Enforcement will vary by country, so keep one common baseline with local overlays, Gogia said.

His advice: Inventory every system that talks to people, generates content, or gauges sentiment; classify provider and deployer roles; place disclosures at first interaction; define substantive human review; keep the evidence.

Marks and provenance signals should be tested after content undergoes cropping, compression, translation, transcription, and other editing, Gogia said. A useful audit starts from a real output and follows its “pulse” through generation, editing and publication, identifying at “each beat” the responsible party, the surviving mark, and evidence for exceptions. Missed labels should also be traced for root cause and recurrence.

To ensure compliance, before August 2, enterprises need a prioritized inventory, live disclosures on the highest-risk use cases, and a “named owner for every control,” he noted. In the first 30 days, they should stabilize and test; in the first 90 days, push requirements into procurement processes as a standing discipline. Procurement must secure commitments on marking methods, known failure modes, and evidence access, with explicit notice if/when any of them change.

“The sensible architecture is a common transparency baseline carrying traceability, responsibility, and evidence, with jurisdictional overlays for language, sector rules, and local practice,” Gogia said.

This article originally appeared on CIO.com.

OpenAI Presence raises new questions about enterprise automation and jobs

Sat, 25 Jul 2026 19:50:08 +0200

OpenAI has launched Presence, an enterprise service for deploying voice and chat agents that can resolve customer and employee requests, potentially automating some work now handled by frontline support teams.

The agents can answer questions and operate IT systems, and enterprises can decide what actions the agents may take and when they should seek human approval for actions or transfer a case to a human.

OpenAI is already using Presence internally for its English-language phone support channel, where it verifies callers and uses account information to complete approved actions. The company said the system resolves 75% of inbound issues without human assistance.

Another OpenAI service, Codex, can be used to monitor agents and suggest updates or improvements to processes. In OpenAI’s own tests, suggestions from Codex helped reduce handoffs to humans by 15 percentage points over 10 days, it said. Presence also includes simulation and evaluation tools that allow companies to test an agent before deployment. The tests assess whether it reaches the correct outcome, follows company policy, and hands a case to an employee when required.

OpenAI intends each Presence deployment to deal with one kind of task, for example billing issues, insurance claims, or employee IT service requests, with agents getting only the knowledge and system access required for that task.

Presence is not a self-service product: Enterprises will have to sign up for the limited availability program, with integration performed by OpenAI or selected global systems integrators.

Companies exploring or testing Presence include Spanish bank BBVA, which is evaluating the service for everyday banking support in Mexico, and Japanese technology group SoftBank, which is using it in trials involving Japanese-language customer interactions. Australian insurer IAG is assessing whether the technology can help it respond to surges in customer demand during severe weather events.

Workforce impact

OpenAI’s announcement did not address the potential effect of Presence on employment. But its claimed automation rate raises questions about how the technology could affect staffing in customer service and other support functions.

Pareekh Jain, CEO of Pareekh Consulting, said CIOs should regard the 75% figure as evidence that the technology can work, rather than as a benchmark that every enterprise can expect to reach.

Jain said OpenAI’s deployment benefits from being built around the company’s own products and data. Large enterprises may achieve lower automation rates because they must contend with fragmented legacy systems, uneven knowledge bases and more complex compliance demands.

“Most organizations should expect lower initial automation levels that improve over time as the AI agent is refined,” Jain said.

The first workforce effect is more likely to be slower hiring than immediate layoffs, according to Tulika Sheel, senior vice president at Kadence International.

“The roles most exposed are likely to be repetitive, high-volume functions such as frontline customer support and routine back-office processing,” Sheel said. “However, I would expect the first impact to be on hiring and team growth rather than immediate large-scale job cuts. Over time, enterprises may redesign roles around AI-assisted workflows, with humans focusing more on complex cases, escalation, and relationship management.”

Jain said Tier-1 support agents handling predictable queries would face the most exposure. Broader reductions would become more likely only after companies reorganize their operations around the technology.

However, Lian Jye Su, chief analyst at Omdia, said Presence is unlikely to increase the threat of job displacement because companies have used similar customer-support automation from vendors such as Genesys, NiCE, Five9 and AWS for years.

Enterprises are more likely to use Presence alongside employees, with AI handling routine requests while people remain responsible for work requiring judgment and empathy, Su said.

Cost and operational risks

Analysts said CIOs should examine whether Presence can maintain resolution quality as usage grows, since fewer human handoffs could leave employees dealing with a more difficult mix of cases.

“The key question is not simply how many tasks AI can handle, but whether it can handle them reliably at scale,” Sheel said.

The financial case will depend partly on the cost of connecting Presence to existing systems and maintaining the controls needed to govern its use, according to Jain. “Often the biggest cost of enterprise AI is not tokens but integration and governance,” Jain added.

Companies will need to determine what systems and data the agents can access, monitor their performance, and audit the actions they take. Those investments could offset early savings.

Su said the complexity of enterprise IT will make it difficult for OpenAI to automate entire workflows on its own. Enterprises will still need to work with other technology providers and human employees, while CIOs will favor systems that can be audited and integrated with existing infrastructure.

Jain said the economics could improve if companies use the same integrations and governance controls across additional workflows.

This article first appeared on CIO.

Anduril reportedly in talks to raise funding at $100B valuation, more than 3x last year’s mark

Sat, 25 Jul 2026 19:49:46 +0200

Anduril is said to be raising a new round of funding that may push its valuation up to about $100 billion, per Reuters.

Pwn2Own Berlin 2026 - Day One Results

Sat, 25 Jul 2026 19:02:55 +0200

Welcome to Day One of Pwn2Own Berlin 2026! Today, 22 entries took the Pwn2Own stage to target AI Databases, Coding Agents, Local Inferences, and a separate category for NVIDIA products, as the world’s top security researchers push technology to its limits. Exploits, surprises, and breakthrough discoveries are unfolding.

After Day One, we awarded $523,000 for 24 unique 0-days! DEVCORE is currently in the lead for Master of Pwn, but a pack of teams are right on their heels. Stay tuned tomorrow for more results and surprises.

Follow the action live! We’ll be posting real-time updates and results throughout the competition on our blog and across social media. Stay up to date by following us on Twitter, Mastodon, LinkedIn, and Bluesky, and join the conversation using #Pwn2Own Berlin and #P2OBerlin for continuous coverage.

FAILURE - Unfortunately, Le Duc Anh Vu (@vulda17) of Viettel Cyber Security (@vcslab) could not get their exploit of OpenAI Codex working within the time allotted.

SUCCESS - Orange Tsai (@orange_8361) of DEVCORE Research Team (@d3vc0r3) chained 4 logic bugs to achieve a sandbox escape on Microsoft Edge, earning $175,000 and 17.5 Master of Pwn points.

SUCCESS - chompie of IBM X-Force Offensive Research (XOR) used a single bug to exploit NV Container Toolkit, earning $50,000 and 5 Master of Pwn points.

SUCCESS - k3vg3n chained 3 bugs including SSRF and Code Injection to take down LiteLLM. $40,000 and 4 Master of Pwn points. Full win.

SUCCESS - Satoki Tsuji (@satoki00) of Ikotas Labs, Inc. used an Overly Permissive Allowed List bug to exploit NVIDIA Megatron Bridge, earning $20,000 and 2 Master of Pwn points.

FAILURE - Unfortunately, Park Jae Min could not get their exploit of Oracle Autonomous AI Database working within the time allotted. #Pwn2Own #P2OBerlin

SUCCESS - Emanuele Barbeno, Cyrill Bannwart, Yves Bieri, Lukasz D., Urs Mueller of Compass Security (@compasssecurity) used a single CWE-150 bug to exploit OpenAI Codex, earning $40,000 and 4 Master of Pwn points.

SUCCESS - Angelboy (@scwuaptx) & TwinkleStar03 (@_twinklestar03) of DEVCORE Research Team used an Improper Access Control bug to escalate privileges on Microsoft Windows 11, earning $30,000 and 3 Master of Pwn points.

WITHDRAWAL - Ben Koo (@kiddo_pwn) of Team DDOS has withdrawn their entry for Mozilla Firefox – Renderer Only in the Web Browser category

FAILURE - Unfortunately, Interrupt Labs could not get their exploit of NV Container Toolkit working within the time allotted

COLLISON - Although successful on stage, the Ikotas Labs, Inc. team targeting LiteLLM in the Local Inference category used bugs that were previously known. They still earn $8,000 and 1.75 Master of Pwn points.

SUCCESS - Yoseop Kim (@pwning_me) used a CWE-470 bug to exploit NVIDIA Megatron Bridge in the second round, earning $10,000 and 2 Master of Pwn points.

COLLISON - Although successful on stage, maitai (@MaitaiThe) of Doyensec (@Doyensec) targeting OpenAI Codex in the Coding Agent category used a bug that was previously known to the vendor. They still earn $10,000 and 2 Master of Pwn points.

WITHDRAWAL - Yoseop Kim(@pwning_me) has withdrawn their entry for Mozilla Firefox – Renderer Only in the Web Browser category

SUCCESS - haehae (@haehaeYang) of Out Of Bounds chained 2 bugs (CWE-190, CWE-362) to exploit Chroma, earning $20,000 and 2 Master of Pwn points.

SUCCESS - Billy (@st424204), Pan Zhenpeng (@Peterpan980927) & Weiming Shi (@bestswngs) of STARLabs SG (@starlabs_sg) chained 5 bugs (incl. SSRF and Code Injection) to exploit LM Studio, earning $40,000 and 4 Master of Pwn points. Full win!

SUCCESS - Marcin Wiązowski used a heap-based buffer overflow to escalate privileges on Microsoft Windows 11 in the second round, earning $15,000 and 3 Master of Pwn points.

WITHDRAWAL - Qrious Secure (@qriousec) has withdrawn their entry for LM Studio in the Local Inference category.

SUCCESS - Chompie of IBM X-Force Offensive Research (XOR) used a race condition to escalate privileges on Red Hat Enterprise Linux for Workstations, earning $20,000 and 2 Master of Pwn points.

COLLISON - Although successful on stage, Nguyen Thanh Dat (@rewhiles) of Viettel Cyber Security (@vcslab) targeting Anthropic Claude Code in the Coding Agent category used a bug that was previously known to the vendor. They still earn $20,000 and 2 Master of Pwn points

SUCCESS - haehae (@haehaeYang) of Out Of Bounds used a Path Traversal bug to exploit NVIDIA Megatron Bridge in the second round, earning $10,000 and 2 Master of Pwn points. Full win!

SUCCESS - Kentaro Kawane of GMO Cybersecurity by Ierae chained 2 Use-After-Free bugs to escalate privileges on Microsoft Windows 11 in the third round, earning $15,000 and 3 Master of Pwn points.

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 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 March 2026 Security Update Review

Sat, 25 Jul 2026 19:00:43 +0200

I am back in the friendly confines of the Mid-South headquarters of TrendAI ZDI (a.k.a. my home office), and am all set for the third patch Tuesday of 2026. 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 March 2026

For March, Adobe released eight bulletins addressing 80 unique CVEs in Adobe Acrobat Reader, Commerce, Illustrator, Substance 3D Painter, Premier Pro, Experience Manager, Substance 3D Stager, and the Adobe DNG Software Development Kit (SDK). Two of these bugs were submitted through the TrendAI ZDI program. If you need to prioritize, the update for Acrobat likely has the most impact, with the patch fixing two Critical-rated and one Important bugs. The fix for Experience Manager is the largest this month with 33 CVEs addressed. However, these are simple cross-site scripting (XSS) bugs, so it’s not too exciting. The fix for Commerce is also quite large with 19 CVEs. Most of these are also XSS bugs, but there’s a few security feature bypass bugs in there, too. Adobe actually gives this patch a deployment priority of 2, but it’s not under active attack at the time of release.

The fix for Illustrator corrects seven bugs, including a few Critical-rated ones. The patch for Substance 3D Painter fixes nine different CVEs, all rated Important. That’s not the case for Substance 3D Stager, which fixes six different Critical bugs that could lead to arbitrary code execution. The patch for the Adobe DNG Software Development Kit (SDK) addresses one Critical and one Important bug. Finally, the update for Premiere Pro correct a single, Critical-rated bug that could lead to arbitrary code execution.

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

Microsoft Patches for March 2026

This month, Microsoft released 84 new CVEs in Windows and Windows components, Office and Office Components, Microsoft Edge (Chromium-based), Azure, SQL Server, Hyper-V Server, and the Windows Resilient File System (ReFS). Counting the third-party and Chromium updates listed in the release, it brings to total number of CVEs to 94. Five of these bugs were reported through the TrendAI ZDI program. Eight of these bugs are rated Critical, and the rest are rated Important in severity.

This volume is relatively typical for a March release, and the lack of bugs under active attack is a nice change from last month. There are two vulnerabilities listed as publicly known at the time of release, but none listed as actively exploited.

Let’s take a closer look at some of the more interesting updates for this month, starting with a bug with an AI slant:

- CVE-2026-26144 - Microsoft Excel Information Disclosure Vulnerability
This is a fascinating bug and an attack scenario we’re likely to see more often. The vulnerability is a simple cross-site scripting (XSS) bug in Excel, but an attacker could use it to cause the Copilot Agent to exfiltrate data off the target. This essentially makes it a zero-click information disclosure. Although not stated, the disclosure is likely at the level of the logged-on user, so there isn’t a privilege escalation component. Info disclosures rarely get rated Critical, but it makes sense here.

- CVE-2026-26110/CVE-2026-26113 - Microsoft Office Remote Code Execution Vulnerability
Another month and another pair of Office bugs where the Preview Pane is an exploit vector. I’ve lost count of how many of these bugs have been patched over the last year, but it’s just a matter of time until they start appearing in active exploits. The latest versions of Outlook allow you to hide the Preview Pane, but it isn’t clear if this would mitigate these attacks. The best option is still to test and deploy the update, but considering how many of these patches exist, it’s likely further updates will be needed to fully address these issues.

- CVE-2026-23669 - Windows Print Spooler Remote Code Execution Vulnerability
Just reading the title makes me twitch with remembrances of Print Nightmare from a few years ago. This bug works in the same manner as those exploits. An authenticated attacker sends specially crafted messages to an affected system to gain arbitrary code execution. No user interaction is required. Let’s hope we don’t end up in a new nightmare of spooler exploits. Test and deploy this one quickly.

- CVE-2026-23668 - Windows Graphics Component Elevation of Privilege Vulnerability
This vulnerability was submitted to the ZDI program by Marcin Wiązowski as two separate bugs, and it demonstrates the need for variant investigations when creating security patches. Both cases are caused by the lack of proper locking when performing operations on an object. However, in one case, it’s in the cdd.dll driver while the other is in the win32kfull driver. Either way, an attacker could use these to elevate privileges to SYSTEM and execute arbitrary code. Since the fix for both is to add object locking to the GDI object, the cases are combined into a single CVE. That’s not a problem, but it does show how variants can occur, and fixes should be as broad as possible.

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

CVE	Title	Severity	CVSS	Public	Exploited	Type
CVE-2026-26127	.NET Denial of Service Vulnerability	Important	7.5	Yes	No	DoS
CVE-2026-21262	SQL Server Elevation of Privilege Vulnerability	Important	8.8	Yes	No	EoP
CVE-2026-23651	Microsoft ACI Confidential Containers Elevation of Privilege Vulnerability	Critical	6.7	No	No	EoP
CVE-2026-26124	Microsoft ACI Confidential Containers Elevation of Privilege Vulnerability	Critical	6.7	No	No	EoP
CVE-2026-26122	Microsoft ACI Confidential Containers Information Disclosure Vulnerability	Critical	6.5	No	No	Info
CVE-2026-21536	Microsoft Devices Pricing Program Remote Code Execution Vulnerability	Critical	9.8	No	No	RCE
CVE-2026-26144	Microsoft Excel Information Disclosure Vulnerability	Critical	7.5	No	No	Info
CVE-2026-26110	Microsoft Office Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-26113	Microsoft Office Remote Code Execution Vulnerability	Critical	8.4	No	No	RCE
CVE-2026-26125	Payment Orchestrator Service Elevation of Privilege Vulnerability	Critical	8.6	No	No	EoP
CVE-2026-26131	.NET Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-25177	Active Directory Domain Services Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-26117	Arc Enabled Servers - Azure Connected Machine Agent Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26130	ASP.NET Core Denial of Service Vulnerability	Important	7.5	No	No	DoS
CVE-2026-23661	Azure IoT Explorer Information Disclosure Vulnerability	Important	7.5	No	No	Info
CVE-2026-23662	Azure IoT Explorer Information Disclosure Vulnerability	Important	7.5	No	No	Info
CVE-2026-23664	Azure IoT Explorer Information Disclosure Vulnerability	Important	7.5	No	No	Info
CVE-2026-26121	Azure IOT Explorer Spoofing Vulnerability	Important	7.5	No	No	Spoofing
CVE-2026-26118	Azure MCP Server Tools Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-23667	Broadcast DVR Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-25190	GDI Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-25181	GDI+ Information Disclosure Vulnerability	Important	7.5	No	No	Info
CVE-2026-26030 *	GitHub: CVE-2026-26030 Microsoft Semantic Kernel InMemoryVectorStore filter functionality vulnerable	Important	9.9	No	No	RCE
CVE-2026-23654 *	GitHub: Zero Shot SCFoundation Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-26141	Hybrid Worker Extension (Arc-enabled Windows VMs) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-23665 †	Linux Azure Diagnostic extension (LAD) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-23674	MapUrlToZone Security Feature Bypass Vulnerability	Important	7.5	No	No	SFB
CVE-2026-26123	Microsoft Authenticator Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-26148 †	Microsoft Azure AD SSH Login extension for Linux Elevation of Privilege Vulnerability	Important	8.1	No	No	EoP
CVE-2026-25167	Microsoft Brokering File System Elevation of Privilege Vulnerability	Important	7.4	No	No	EoP
CVE-2026-26107	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-26108	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-26109	Microsoft Excel Remote Code Execution Vulnerability	Important	8.4	No	No	RCE
CVE-2026-26112	Microsoft Excel Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-26134	Microsoft Office Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26106	Microsoft SharePoint Server Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-26114	Microsoft SharePoint Server Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-26105	Microsoft SharePoint Server Spoofing Vulnerability	Important	8.1	No	No	Spoofing
CVE-2026-24283	Multiple UNC Provider Kernel Driver Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-25165	Performance Counters for Windows Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-24282	Push message Routing Service Elevation of Privilege Vulnerability	Important	5.5	No	No	Info
CVE-2026-26115	SQL Server Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-26116	SQL Server Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-20967	System Center Operations Manager (SCOM) Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-24285	Win32k Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-24291	Windows Accessibility Infrastructure (ATBroker.exe) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-25186	Windows Accessibility Infrastructure (ATBroker.exe) Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-23660 †	Windows Admin Center in Azure Portal Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-24293	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-25176	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-25178	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-25179	Windows Ancillary Function Driver for WinSock Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-23656	Windows App Installer Spoofing Vulnerability	Important	5.9	No	No	Spoofing
CVE-2026-25171	Windows Authentication Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-23671	Windows Bluetooth RFCOM Protocol Driver Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-24292	Windows Connected Devices Platform Service Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-24295	Windows Device Association Service Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-24296	Windows Device Association Service Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-25189	Windows DWM Core Library Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-25174	Windows Extensible File Allocation Table Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-25168	Windows Graphics Component Denial of Service Vulnerability	Important	6.2	No	No	DoS
CVE-2026-25169	Windows Graphics Component Denial of Service Vulnerability	Important	6.2	No	No	DoS
CVE-2026-23668	Windows Graphics Component Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-25180	Windows Graphics Component Information Disclosure Vulnerability	Important	5.5	No	No	Info
CVE-2026-25170	Windows Hyper-V Elevation of Privilege Vulnerability	Important	7	No	No	EoP
CVE-2026-24297	Windows Kerberos Security Feature Bypass Vulnerability	Important	6.5	No	No	SFB
CVE-2026-24287	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-24289	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26132	Windows Kernel Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-24288	Windows Mobile Broadband Driver Remote Code Execution Vulnerability	Important	6.8	No	No	RCE
CVE-2026-25175	Windows NTFS Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-23669	Windows Print Spooler Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-24290	Windows Projected File System Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-23673	Windows Resilient File System (ReFS) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-25172	Windows Routing and Remote Access Service (RRAS) Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-25173	Windows Routing and Remote Access Service (RRAS) Remote Code Execution Vulnerability	Important	8	No	No	RCE
CVE-2026-26111	Windows Routing and Remote Access Service (RRAS) Remote Code Execution Vulnerability	Important	8.8	No	No	RCE
CVE-2026-25185	Windows Shell Link Processing Spoofing Vulnerability	Important	5.3	No	No	Spoofing
CVE-2026-24294	Windows SMB Server Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-26128	Windows SMB Server Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-25166	Windows System Image Manager Assessment and Deployment Kit (ADK) Remote Code Execution Vulnerability	Important	7.8	No	No	RCE
CVE-2026-25188	Windows Telephony Service Elevation of Privilege Vulnerability	Important	8.8	No	No	EoP
CVE-2026-23672	Windows Universal Disk Format File System Driver (UDFS) Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-25187	Winlogon Elevation of Privilege Vulnerability	Important	7.8	No	No	EoP
CVE-2026-3536 *	Chromium: CVE-2026-3536 Integer overflow in ANGLE	Critical	N/A	No	No	RCE
CVE-2026-3538 *	Chromium: CVE-2026-3538 Integer overflow in Skia	Critical	N/A	No	No	RCE
CVE-2026-3539 *	Chromium: CVE-2026-3539 Object lifecycle issue in DevTools	High	N/A	No	No	RCE
CVE-2026-3540 *	Chromium: CVE-2026-3540 Inappropriate implementation in WebAudio	High	N/A	No	No	RCE
CVE-2026-3541 *	Chromium: CVE-2026-3541 Inappropriate implementation in CSS	High	N/A	No	No	RCE
CVE-2026-3542 *	Chromium: CVE-2026-3542 Inappropriate implementation in WebAssembly	High	N/A	No	No	RCE
CVE-2026-3543 *	Chromium: CVE-2026-3543 Inappropriate implementation in V8	High	N/A	No	No	RCE
CVE-2026-3544 *	Chromium: CVE-2026-3544 Heap buffer overflow in WebCodecs	High	N/A	No	No	RCE
CVE-2026-3545 *	Chromium: CVE-2026-3545 Insufficient data validation in Navigation	High	N/A	No	No	RCE

* 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, they are all cloud-native and require no user action. Microsoft has already remediated the vulnerabilities.

Moving on to the other code execution bugs, the vulnerabilities in SharePoint Server pop out first. Both require authentication, but it’s essentially the lowest level of authentication, so these would be ideal cases for lateral movement within an enterprise. There are the standard open-and-own cases within Office components. There an interesting sounding bug in the Windows Mobile Broadband Driver that requires physical access, but Microsoft doesn’t elaborate on the attack scenario beyond that fact. The bug in the System Image Manager Assessment and Deployment Kit (ADK) requires authentication. The bug in GDI requires user interaction. The remaining code execution bugs are in the RRAS protocol. We’ve seen bugs in this component in the past, but never in the wild. I wouldn’t ignore these, but I wouldn’t rush them out either.

Similar to last month, updates for Elevation of Privilege (EoP) bugs make up nearly half of this month’s release. And as we saw last month, but most simply lead to local attackers executing their code at SYSTEM-level privileges or administrative privileges. The bugs in SQL Server allow attackers to elevate to SQL sysadmin privileges. The bug in the Azure MCP Server is more complex. It allows attackers to obtain the permissions associated with the MCP Server’s managed identity, which lets them perform actions that the managed identity is able to reach. The bug in the Azure AD SSH Login extension for Linux leads to root access, and it won’t be easy to patch. You’ll need to run the update instructions from the command line on each affected system. That’s the same case for the bug in the Linux Azure Diagnostic extension (LAD). There’s an odd bug in the Hybrid Worker Extension (Arc‑enabled Windows VMs) that leads to “ELEVATED” privileges, which is something I’ve never seen before. The bug in the Broadcast DVR component allows an attacker to go from low integrity level up to medium. There’s a bug listed as an EoP in the Push message Routing Service, but reading the description, Microsoft notes it could lead to an information disclosure. It’s likely this is an error and should be an Information Disclosure bug. The final EoP is in the Azure Portal Windows Admin Center and leads to SYSTEM. However, there’s no patch to remediate this bug. Instead, you need to install the latest version of the Windows Admin Center extension through the Azure Portal by hand.

There are two security feature bypass patches in the March release. The first is a bypass of the MapURLToZone method, which (as expected) allows attackers to bypass MapURLToZone protections. The third bypass is in Kerberos and could allow an attacker to either view some sensitive information or make changes to “disclosed” information. This is a race condition that occurs while the group policy is being reapplied, so the window to exploit this would be extremely small.

Looking at the remaining info disclosure bugs getting patched this month, only two result in info leaks consisting of unspecified memory contents or memory addresses. Ther others provide more interesting results. There are three bugs in the Azure IoT Explorer have some wide-ranging implications. According to Microsoft, exploitation could result in, “device connection information, authentication tokens, request data, file paths, and other information transmitted between the application and the IoT Hub.” The bug in Authenticator almost reads like a security feature bypass, as exploit results in the disclosure of a one‑time sign‑in code or authentication deep link. The attacker would receive the sign‑in information and could potentially use it to authenticate as the user, allowing access to information or services available to that account. The last info disclosure bug is in the Accessibility Infrastructure and allows an attacker to gain secrets or privileged information belonging to the user of the affected application.

There are only four spoofing bugs in the March release. The first is in SharePoint server and manifests as an XSS. The second bug is a Server-Side Request Forgery (SSRF) in the Azure IoT Explorer. The remaining two are a bit more cryptic. The bug in Windows Shell Link Processing results from the “exposure of sensitive information to an unauthorized actor,” and could lead to spoofing. That sounds like credential exposure, but it’s not explicitly called out. The final spoofing bug results from the insufficient verification of data authenticity in Windows App Installer. Again, this sounds vaguely like credential reflection, but without further information, we can only speculate.

Finally, there are four denial-of-service (DoS) bugs in the release, including one that’s listed as publicly known in the .NET Framework. As usual, Microsoft provides no actionable information about these bugs.

No new advisories are being released this month.

Looking Ahead

I plan on being at RSA for the first time in my career, so if you’re around, please stop by and say hello. I like it when people say hello. Otherwise, I’ll be back on April 14 with my assessment of that patch Tuesday 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!

Announcing Pwn2Own Berlin for 2026

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

If you just want to read the contest rules, click here.

Willkommen zurück, meine Damen und Herren, zu unserem zweiten Wettbewerb in Berlin! That’s correct (if Google translate didn’t steer me wrong). After our inaugural competition last year, Pwn2Own returns to Berlin and OffensiveCon. Outside of our shipping troubles, we had an amazing time and can’t wait to get back.

Last year, we added Artificial Intelligence as a category with great results. This year, we’re expanding this and splitting it into multiple different categories: AI Databases, Coding Agents, Local Inferences, and a separate category for NVIDIA products. In last year’s contest, NVIDIA targets had wins, losses, and collisions, so it will be interesting to see how they fare this year. The folks from AWS wanted to get into the fray as well, so they stepped up to co-sponsor this year’s event, which allows us to increase the reward for bugs in Firecracker. Of course, we have all of the returning categories as well, including web browsers, containers, servers, virtualization, and operating systems. There’s more than $1,000,000 in cash and prizes available for contestants. Last year, we awarded $1,078,750 for 28 unique 0-days over the three-day event. We’ll see if we can eclipse those numbers in 2026.

The contest begins on May 14, but registration closes on May 7, so don’t delay in getting those submissions in. We’re hoping for maximum participation, so set aside your vibe coding and show us what you can really do. We’re looking forward to some cutting-edge exploitation on display. For 2026, we have a total of 31 targets across 10 categories. Here is a full list of the categories for this year’s event:

-- Virtualization
-- Web Browser
-- Enterprise Applications
-- Servers
-- Local Escalation of Privilege
-- Containers
-- AI Database
-- Coding Agents
-- Local Inference
-- NVIDIA

Of course, no Pwn2Own competition would be complete without us crowning a Master of Pwn (Meister von Pwn?). Since the order of the contest is decided by a random draw, contestants with an unlucky draw could still demonstrate fantastic research but receive less money since subsequent rounds go down in value. However, the points awarded for each unique, successful entry do not go down. Someone could have a bad draw and still accumulate the most points. The person or team with the most points at the end of the contest will be crowned Master of Pwn, receive 65,000 ZDI reward points (enough for Platinum status), a killer trophy, and a pretty snazzy jacket to boot.

Let's look at the details of the rules for this year's event.

Virtualization Category

Some of the highlights for each contest can be found in the Virtualization Category, and we’re thrilled to see what this year’s event could bring with it. As usual, VMware is the main highlight of this category as we’ll have VMware ESXi return with an award of $150,000. Last year produced the first ESXi exploits in Pwn2Own history, so it will be interesting to see if we get more. Microsoft also returns as a target and leads the virtualization category with a $250,000 award for a successful Hyper-V Client guest-to-host escalation. Kernel-based Virtual Machine (KVM) is our final target in this category with a prize of $50,000.

There’s an add-on bonus in this category as well. If a contestant can escape the guest OS, then gain arbitrary code execution on the virtualization target and obtain arbitrary code execution in the guest operating system on a separate virtual machine managed by the same targeted virtualization target, they’ll earn another $50,000. That could push the payout on a ESXi bug to $200,000. This bonus is for KVM and ESXi only. Here’s a detailed look at the targets and available payouts in the Virtualization category:

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Web Browser Category

While browsers are the “traditional” Pwn2Own target, we’re continuously tweaking the targets in this category to ensure they remain relevant. We re-introduced renderer-only exploits a couple of years ago, and this year, we’ve increased the award to $75,000. In fact, we’ve increased the awards across the board for this category. Here’s a detailed look at the targets and available payouts:

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Enterprise Applications Category

Enterprise applications return as targets with Adobe Reader and various Office components on the target list once again. Attempts in this category must be launched from the target under test. For example, launching the target under test from the command line is not allowed. Prizes in this category run from $50,000 for a Reader exploit with a sandbox escape or a Reader exploit with a kernel privilege escalation, and $150,000 for an Office 365 application. Word, Excel, and PowerPoint are all valid targets. Microsoft Office-based targets will have Protected View enabled where applicable. Adobe Reader will have Protected Mode enabled where applicable.

This year, we’re adding a bonus for Copilot data exfiltration and Copilot action execution. Microsoft just patched a bug like this in Excel, so we know they are out there. If you’re able to exploit Copilot in addition to a Microsoft application, you’ll earn an additional $50,000. There are quite a few rules and scenarios around this add-on, so be sure to read the rules carefully and contact us with questions. Here’s a detailed view of the targets and payouts in the Enterprise Application category:

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The Server Category

The Server Category for 2026 focuses solely on the server components we’re most interested in. These servers are often targeted by everyone from ransomware crews to nation/state actors, so we know there are exploits out there for them. The only question is whether we’ll see any of the competitors bring one of those exploits to Pwn2Own. Last year, the bugs demonstrated in SharePoint ended up being exploited in the wild, so we know people are looking for these with great interest. Microsoft Exchange has been a popular target for some time, and it returns as a target this year as well, with a payout of $200,000. This category is rounded out by Microsoft Windows RDP/RDS, which also has a payout of $200,000. Here’s a detailed look at the targets and payouts in the Server category:

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Local Escalation of Privilege Category

This category is a classic for Pwn2Own and focuses on attacks that originate from a standard user and result in executing code as a high-privileged user. A successful entry in this category must leverage a kernel vulnerability to escalate privileges. Red Hat Enterprise Linux for Workstations returns as our Linux-based target, while Apple macOS, and Microsoft Windows 11 return as targets in this category. Prior exploits in this category have won Pwnie awards, so they’re always interesting to see. Here’s a detailed look at the targets and payouts in this category:

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The Container Category

We’re excited to have this category return for its third season, and we’re hopeful that even more contestants will target one of these container targets. For an attempt to be ruled a success against these three, the exploit must be launched from within the guest container/microVM and execute arbitrary code on the host operating system. Again, with help from AWS, Firecracker returns as a target with a prize of $100,000. Here are the targets and payouts for this category:

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AI Database Category

In the past, AI Hackathons have focused on using AI to develop vulnerabilities or other offensive frameworks. We’re opening up the models and various components themselves for exploitation. The first AI sub-category focuses on databases. An attempt in this category must be launched from the contestant’s laptop. Here’s a look at the targets and awards in the AI Database category:

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The Coding Agent Category

Let’s face it. At some point or another, we’ve probably all vibe coded something. There’s no shame in that, but how secure are the tools we use for vibe coding? Well, let’s take the most popular choices and find out. A successful entry must interact with a contestant-controlled resource (e.g. web page, repository, media file) to exploit a vulnerability within the coding agent. The attack vector of the entry must be a common coding agent use case. There are few things out of scope here as well. UI spoofing or misrepresentation unrelated to permission prompts, model jailbreaks or prompt outputs that do not cross security boundaries, and vulnerabilities that require unsafe or permission-less modes are just a few of the things not allowed. As this is a new category, please read the rules carefully to ensure your entry qualifies. Here’s a look at the targets and awards in the AI Coding Agent category:

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The Local Inference Category

We couldn’t leave local inference and LLMs out of Pwn2Own. These products claim to provide enhanced data privacy, zero-cost inference, lower latency, and fully offline functionality. We’ll see how the security stacks up. An attempt in this category must be launched from the contestant’s laptop within the contest network. Here are the targets and payouts for the Local Inference category:

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The NVIDIA Category

Our last AI sub-category focuses solely on NVIDIA products. For network accessible targets, an attempt must be launched from the contestant's laptop within the contest network. For NV Container Toolkit, the attempt must be launched from within a crafted container image and execute arbitrary code on the host operating system. For Megatron Bridge, entries that leverage vulnerabilities pertaining to pickle deserialization or that leverage a vulnerability when “trust_remote_code=true” are out of scope. Here are the targets and payouts for the NVIDIA category:

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Conclusion

The complete rules for Pwn2Own Berlin 2026 are found here. As always, we highly encourage entrants to read the rules thoroughly if they choose to participate. If you are thinking about participating but have specific configuration or rule-related questions, email us. Questions asked over X (nee Twitter), BlueSky, or other means will not be answered. Registration is required to ensure we have sufficient resources on hand at the event. Please contact ZDI at pwn2own@trendmicro.com to begin the registration process. Registration for onsite participation closes at 5 p.m. Central European Time on May 7, 2026.

Be sure to stay tuned to this blog and follow us on Twitter, Mastodon, LinkedIn, or Bluesky for the latest information and updates about the contest. We look forward to seeing everyone in Germany, and we hope to see some of the best in the world show what they can do – vibe coded or not.

With special thanks to our Pwn2Own Berlin 2026 partners AWS, for providing their expertise and technology.

© 2026 Trend Micro Incorporated. All rights reserved. PWN2OWN, ZERO DAY INITIATIVE, ZDI, ZERO DAY INITIATIVE, TrendAI, and Trend Micro are trademarks or registered trademarks of Trend Micro Incorporated. All other trademarks and trade names are the property of their respective owners.

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.

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Hoher Preis
Klobiges Design
Softwarefunktionen entsprechen weitgehend denen des Air

Fazit

Der Ultrahuman Ring Pro bietet ein hervorragendes Hardware- und Software-Erlebnis und zählt damit zu den besten Smart-Ringen. Das Problem ist der hohe Anschaffungspreis, ganz zu schweigen davon, dass die Konkurrenz – sowohl bei Modellen mit als auch ohne Abonnement – für manche Nutzer attraktivere Eigenschaften bieten kann.

Der Ultrahuman Ring Pro ist der neueste Smart-Ring eines Unternehmens, das sich seit Langem im Konflikt mit Oura befindet. Nachdem der Verkauf seines Vorgängermodells in den USA vorübergehend untersagt worden war, kehrt Ultrahuman nun mit einem neuen Ring zurück, der über neu gestaltete Sensoren, eine verbesserte Prozessorleistung und eine längere Akkulaufzeit verfügt.

Der Ring Air ist weiterhin als günstigere Alternative zum Pro erhältlich, doch wenn Sie das Beste wollen, was Ultrahuman zu bieten hat, ist dieser hier die richtige Wahl.

Leider sind die Preise für die Ringe von Ultrahuman – ähnlich wie bei dem ebenfalls abonnementfreien Konkurrenten RingConn – leicht gestiegen, was bedeutet, dass sich der Pro wirklich hervorheben muss, um die höheren Kosten zu rechtfertigen und zu einer der ersten Wahl unter den Smart-Ringen zu werden.

Design & Verarbeitung

Erhältlich in vier Farbvarianten
Dickeres Design als der Ring Air
Ladeetui im Lieferumfang enthalten

Der Ring Pro ist ein Smart-Ring mit einem schlichten Design, der in vier verschiedenen Farben erhältlich ist: Bionic Gold, Space Silver, Aster Black und Raw Titanium. Der Kern des Rings besteht aus Titan mit einer PVD-Beschichtung, die ihn vor Kratzern schützt. Ich habe festgestellt, dass frühere Ultrahuman-Ringe zu den am leichtesten zu zerkratzenden gehörten. Daher freue ich mich, dass der Pro Kratzer besser abwehrt.

Mike Sawh

Genau wie der Air ist auch der Pro in den Ringgrößen 5–14 erhältlich und bis zu einer Tiefe von 100 Metern wasserdicht. Ich habe mich für dieselbe Größe wie beim Air entschieden, und die Passform scheint ähnlich zu sein, wenn nicht sogar insgesamt etwas besser, da der Ring seltener an meinem Finger herumrutscht. Er ist sehr bequem und sitzt gut am Finger. Man spürt zwar die Sensoren, doch sie sind nicht so deutlich spürbar wie bei früheren Modellen.

Im Vergleich zum Ring Air von Ultrahuman erhalten Sie einen schwereren und dickeren Ring. Da ich den Oura Ring 5 gleichzeitig getragen habe, wirkt der Pro deutlich größer als der neueste Ring von Oura.

Der Pro wird mit einem Ladecase geliefert, und obwohl man es nicht mit dem neuen Case von Oura verwechseln würde, verfügt es über ein ähnlich robustes Metall-Design, das den Ring schützt, wenn er nicht am Finger getragen wird. Das Etui verfügt über zusätzliche intelligente Funktionen wie kabelloses Laden, einen „Find-my-Case“-Modus für den Fall, dass Sie es verlegen, ganz zu schweigen von der Möglichkeit, Ringdaten bis zu einem Jahr lang zu speichern.

Ein interessanter Aspekt des Designs ist, dass Ultrahuman den Ring so konzipiert hat, dass er im Falle einer Schwellung leicht durchtrennt und entfernt werden kann. Auch wenn ich hoffe, dass niemand jemals in eine solche Situation gerät, ist es beruhigend zu wissen, dass sich der Ring in einem Notfall problemlos entfernen lässt.

Fitness & Tracking

Überarbeitete Temperatur- und Herzfrequenzsensoren
Neuer Dual-Core-Prozessor
Powerplugs bieten zusätzliche Funktionen gegen Aufpreis

Der Ring Pro kann so gut wie alles überwachen, was auch der Air kann. Dazu gehören Herzfrequenz, Schlaf, Stress, Temperatur und die tägliche Schrittzahl. Die größte Änderung besteht darin, dass die optischen Sensoren, die zur Erfassung dieser Messwerte verwendet werden, überarbeitet wurden und nun klarere Signale liefern, um Schlaf- und Erholungsdaten zu erfassen.

Diese Neugestaltung scheint zudem mit den Patentstreitigkeiten mit Oura in Zusammenhang zu stehen.

Mike Sawh

Die App, die diese Daten anzeigt, gehört zu den ausgereiftesten, die Sie bei einem Smart-Ring finden können. Sie steht der Oura-App in nichts nach, was die ansprechende Aufbereitung Ihrer Daten angeht, und regt Sie dazu an, sich tatsächlich damit auseinanderzusetzen.

Mike Sawh

Was die Erfassung der Kerndaten angeht, müssen Sie die zweiwöchige Kalibrierungsphase unbedingt durchlaufen, bis Sie zuverlässige Ergebnisse erhalten. Die Daten zu den durchschnittlichen Herzfrequenzwerten wiesen während dieses Zeitraums erhebliche Abweichungen auf, stabilisierten sich jedoch nach diesen zwei Wochen.

Die Daten zur Ruheherzfrequenz und die Messungen der Herzfrequenzvariabilität stimmten besonders gut mit zwei anderen Trackern überein, die ich parallel zum Pro trug.

Bei der Betrachtung der Schrittzahlen stellte ich fest, dass die gemeldeten Gesamtwerte deutlich niedriger waren als bei zwei anderen Trackern, mit denen ich den Pro verglichen habe.

Die Leistung bei der Schlafaufzeichnung gehört zu den besten, die ich getestet habe, einschließlich Oura. Was die Schlafdauer, die Aufschlüsselung der Schlafphasen und den erfassten Zeitpunkt des Einschlafens betrifft, lieferte der Pro zuverlässige Werte.

Mike Sawh

Ultrahuman hebt sich von der Konkurrenz dadurch ab, dass es komplexe Daten in einem leicht verständlichen Format darstellt, beispielsweise bei der Bewertung des Gehirnalters oder der Erfassung des Schlafdefizits, das sich aus kumulierten schlechten Nächten ergibt. Es überwacht zudem, wie gut Ihr Gehirn während des Schlafs Abfallstoffe abbaut. Sie können auch die „PowerPlugs“ von Ultrahuman erkunden, bei denen es sich größtenteils um kostenlose Add-ons handelt, die eine individuellere Nachverfolgung ermöglichen.

Ich nutze derzeit das neue Parent-Modul, das besonders auf die kumulative Erholung achtet, berücksichtigt, dass der Schlaf wahrscheinlich unruhiger ist, und Ihnen Tipps gibt, wie Sie wieder in die richtige Bahn kommen können.

Mike Sawh

Wie bereits erwähnt, sind die meisten dieser PowerPlugs kostenlos. Es gibt jedoch auch solche, die Einblicke in spezielle Krankheiten wie Migräne bieten oder Daten mit einem Tesla synchronisieren; hierfür ist ein monatliches Abonnement erforderlich. Dabei handelt es sich um kostenpflichtige Funktionen, auf die die meisten Nutzer gut verzichten können.

Akkulaufzeit & Aufladen

Bis zu 15 Tage Akkulaufzeit
Bietet drei Akkubetriebsmodi
Ladeetui sorgt für weitere 45 Tage

Die Akkulaufzeit ist ein wichtiges Thema beim Pro-Modell – und das nicht nur, weil er länger durchhält als der Air. Neben der Verlängerung der Akkulaufzeit von 4–6 Tagen auf 15 Tage stehen Ihnen drei Akkubetriebsmodi zur Verfügung, mit denen Sie das Beste aus jeder Ladung herausholen können.

Wenn Sie den Turbo-Modus wählen, bei dem alle Sensoren aktiviert sind, können Sie mit einer Laufzeit von bis zu 12 Tagen rechnen. Diese verlängert sich auf über 15 Tage, wenn Sie sich für den Chill-Akkumodus entscheiden. Dabei liegt der Schwerpunkt auf der Schlafaufzeichnung, doch wichtige Momente Ihres Tages werden weiterhin erfasst, um sicherzustellen, dass die wesentlichen Erkenntnisse weiterhin von Nutzen sind.

Ich habe mit dem Pro problemlos eine Akkulaufzeit von fast zwei Wochen erreicht, was eine beeindruckende Leistung ist. Das ist besser als beim Oura Ring 5 und liegt in Bezug auf die Akkuleistung auf Augenhöhe mit dem RingConn Gen 2.

Zudem verfügen Sie nun über das Ladecase, das Ihnen eine zusätzliche Akkulaufzeit von 45 Tagen bietet. Sie müssen den Ring jedoch präzise im Ladegerät platzieren; ein akustisches Signal aus dem integrierten Lautsprecher bestätigt, dass der Ring wieder aufgeladen wird. Als der Akku auf 0 Prozent sank, benötigte der Pro weniger als eine Stunde, um wieder auf 100 Prozent zu kommen.

Preis & Verfügbarkeit

Zum Zeitpunkt der Erstellung dieses Artikels kann der Ultrahuman Ring Pro für 499 Euro im Ultrahuman Store vorbestellt werden. Damit gehört er zu den teuersten Smart-Ringen auf dem Markt.

Er ist teurer als das günstigste verfügbare Modell des Oura Ring 5 und andere Smart-Ringe wie der Samsung Galaxy Ring. Der in Kürze erscheinende RingConn Gen 3 wird in den USA teurer sein als der Ring Pro, sollte in anderen Regionen jedoch günstiger sein.

Wie der Ring Air bleibt auch der Pro ein Smart-Ring ohne Abonnement. Einige der PowerPlug-Software-Erweiterungen sind jedoch mit zusätzlichen Kosten verbunden.

Sollten Sie den Ultrahuman Ring Pro kaufen?

Die großen Verbesserungen des Ring Pro gegenüber dem Air liegen in dem größeren Akku und dem robusteren Design. Ich habe die Überwachungsleistung des Air nie als unzureichend empfunden, und wenn Sie noch ein Exemplar ergattern können und ein Fan des Software-Ansatzes von Ultrahuman sind, dann ist er nach wie vor eine kluge (und günstigere) Anschaffung.

Vergleicht man den Ring Pro mit anderen Smart-Ringen, müssen wir über den Preis sprechen. Er ist teuer, und es gibt abonnementsfreie Alternativen zu einem günstigeren Preis. Ob diese Ihnen auf der Softwareseite das gleiche Maß an Sorgfalt und Aufmerksamkeit bieten, ist fraglich. Genau hier setzt sich der Ring Pro gegenüber einem Großteil der Konkurrenz durch.

Er ist vielleicht nicht der kleinste oder dünnste Ring, aber was der Ring Pro zu bieten hat, ist eine Kombination aus Hardware und Software, die ein hervorragendes Gesamtpaket ergibt.

Technische Daten

Bis zu 15 Tage Akkulaufzeit
Kompatibel mit Android und iOS
Wasserdicht bis zu 100 Metern
2,65 mm dick
Gewicht: 3,3–4,8 g
Erfasst den Blutsauerstoffgehalt, die Herzfrequenz und die Körpertemperatur
Erfasst den Schlaf und die tägliche Aktivität

(PC-Welt)

OpenAI Presence raises new questions about enterprise automation and jobs

Sat, 25 Jul 2026 18:55:50 +0200

The agents can answer questions and operate IT systems, and enterprises can decide what actions the agents may take and when they should seek human approval for actions or transfer a case to a human.

Presence is not a self-service product: Enterprises will have to sign up for the limited availability program, with integration performed by OpenAI or selected global systems integrators.

Workforce impact

Pareekh Jain, CEO of Pareekh Consulting, said CIOs should regard the 75% figure as evidence that the technology can work, rather than as a benchmark that every enterprise can expect to reach.

“Most organizations should expect lower initial automation levels that improve over time as the AI agent is refined,” Jain said.

The first workforce effect is more likely to be slower hiring than immediate layoffs, according to Tulika Sheel, senior vice president at Kadence International.

Enterprises are more likely to use Presence alongside employees, with AI handling routine requests while people remain responsible for work requiring judgment and empathy, Su said.

Cost and operational risks

Analysts said CIOs should examine whether Presence can maintain resolution quality as usage grows, since fewer human handoffs could leave employees dealing with a more difficult mix of cases.

“The key question is not simply how many tasks AI can handle, but whether it can handle them reliably at scale,” Sheel said.

Companies will need to determine what systems and data the agents can access, monitor their performance, and audit the actions they take. Those investments could offset early savings.

Jain said the economics could improve if companies use the same integrations and governance controls across additional workflows.

Researcher Publishes GitLab RCE PoC Letting Authenticated Users Run Commands as Git

Sat, 25 Jul 2026 18:52:18 +0200

Security researchers at depthfirst published working exploit code on July 24 for a GitLab flaw that GitLab patched six weeks earlier, on June 10. It runs commands as git on any self-managed 18.11.3 server that has not taken the update. Any authenticated user who can push to a project can run it. The attacker commits a crafted Jupyter notebook and opens its commit diff, which leaks a heap

Android CLI Now Stable 1.0: Accelerate developing for Android using any agent

Sat, 25 Jul 2026 10:15:49 +0200

Posted by Simona Milanovic and Ben Trengrove, Developer Relations Engineers

As Android developers, you have many choices when it comes to the agents, tools, command-line interfaces (CLI), and LLMs you use for app development. Whether you use Gemini in Android Studio, Antigravity 2.0, Antigravity CLI, or third-party agents like Anthropic's Claude Code or OpenAI'sCodex, our mission remains the same: to ensure that high-quality Android development is possible everywhere.

At Google I/O ‘26, we shared the latest leaps forward in agentic development, and showcased some of the newest capabilities of Android CLI—now stable at version 1.0 and ready for all Android developers to use. From new skills to enabling agent access to powerful Android Studio capabilities, we’re giving your agents the right tools to build alongside you.

If you’re already using Android CLI and want to jump into using all the new features, just run android update. Otherwise, read further to learn more about how we’re making the agents you choose be better at building for Android.

Android development unlocked for Antigravity

Google Antigravity now includes an optional bundle of Android resources—including the Android CLI and skills—that you can install. You can either install the bundle during onboarding after installation, or later from the Settings > Customizations > Build With Google Plugins menu.

This provides Antigravity with all the powerful tools and knowledge of Android CLI, enabling it to perform the core tasks necessary for Android app development more easily and efficiently—from creating projects to deploying your app on a new Android virtual device.

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

Unlocking Android Studio capabilities for any agent

Android CLI provides a lightweight interface for AI Agents to perform tasks and retrieve knowledge about Android development. However, there's benefits to specialization — Android Studio contains over a decade of Android expertise, built to handle even the most complex Android projects. This includes Android Studio's powerful static analysis engine, refactoring tools, dependency management, UI design and rendering libraries, and more. AI Agents can now tap into Android Studio's tools to gain many of these same capabilities.

Your agents can now use Android CLI to access powerful capabilities of Android Studio.

The latest version of Android CLI introduces the new android studio command. This enables the agent of your choice to leverage the deep, contextual capabilities of Android Studio to better understand and perform actions on an open Android project. By running Android Studio alongside your preferred agent with Android CLI, your agent’s tasks can more efficiently navigate the codebase to produce more precise code changes. And, when you use Android CLI to create and iterate on your project, transitioning to Android Studio is much easier, so that you can use the purpose built tools—such as, performance profilers, Compose Previews, and Android Device Streaming—to get that production-grade polish.

When you have a project open in the latest preview version of Android Studio Quail, you (or your agent) can run the following command to check whether Android CLI has a connection established with your open project:

$ android studio check
pid: 32942
version: Android Studio
Projects:
    READY     JetSet /Users/adarshf/AndroidStudioProjects/jetset-main

From there, the agents can use the android studio command to access powerful IDE tools to interact with projects more efficiently. Key commands include:

analyze-file: Analyzes a file for errors and warnings using the editor's built-in inspections.
find-declaration: Finds the exact definition site of a symbol (class, method, variable, field, constant, or Android resource/color) across the project using semantic resolution.
find-usages: Finds all references and declarations of a symbol (class, method, variable, or Android resource) across the entire project using semantic analysis.
render-compose-preview: Renders a Jetpack Compose UI Preview and returns a path to the image and UI hierarchy if successful.
version-lookup: Get the latest information about which versions for specified app dependencies are available in common repositories, such as the Google Maven repository. By providing a programmatic solution, dependency management is less tedious and much less prone to flakiness.
open-file: Opens a file directly in Android Studio. This is useful if the agent wants to direct your attention to view Compose Previews, performance traces, or other specific files in the IDE.

For example, agents can now run the following commands to render a Compose preview for a new layout for your Android app, and then open the previews in Android Studio for you to take advantage of seeing multiple Compose Previews side by side and make AI-assisted edits right from the IDE.

$ android studio find-declaration HotelDetailScreen
$ android studio analyze-file .../JetPacker/feature/detail/src/main/java/com/example/jetset/feature/detail/HotelDetailScreen.kt
$ android studio open-file feature/detail/src/main/java/com/example/jetset/feature/detail/HotelDetailScreen.kt

To learn more about how to use these commands, run android help. And, to make sure your agents understand how to work with this tool, make sure to update the Android CLI skill by running android init.

More ways to get started

To make integrating Android CLI into your environments as seamless as possible, we’re making it available in more ways. You can now download and install Android CLI using more package managers: apt-get, winget, and homebrew. For example, you can run the following to install Android CLI using winget:

winget install -e --id Google.AndroidCLI

We’ve also updated the installation to a user-local directory, by default. You can find the commands for all supported operating systems plus additional download options on the Android CLI page.

Support for Journeys

Journeys are natural language descriptions of core user experiences.

We are also introducing support for Journeys. With Journeys tools and skills included with Android CLI, any agent of your choice can now create and run Journeys—which are natural language descriptions of user journeys for your app that are saved directly to your project.

(sped up) An agent running a Journey it generated for an app.

Agents can run these journeys using the Android CLI to navigate your app exactly like a user would. This unlocks entirely new ways to test, validate, or collect data across the critical experiences of your app, all driven by natural language and executed by your agent.

Expanding Android skills

To help models better understand and execute specific patterns that follow our best practices, we are continuing to expand our library of Android skills. We’re shipping new skills that make Android development everywhere more capable, efficient, and productive:

Display Glasses and Jetpack Compose Glimmer for XR: Provides guidelines for developing projected applications for Android Display Glasses using the Jetpack Compose Glimmer UI toolkit.
Migration to CameraX: Helps you migrate legacy Android camera implementations (Camera1 or raw Camera2 APIs) to CameraX.
Perfetto SQL: Translates natural language data prompts into Perfetto SQL queries and executes them against a local trace file.
Adaptive UI: Instructions to make or update an app's UI so that it adapts to different Android devices
Testing setup: Creates a basic testing strategy.
Styles: Helps with adoption of the new Jetpack Compose Style API for new components, and supports migration to Styles API.
AppFunctions: Analyzes Android codebases to recommend and implement new AppFunctions, and refines KDoc documentation for Model Context Protocol optimization.

You can add these new skills to your workflow directly from the command line. To help your agents understand and use Android CLI right away, you can initialize your environment and install the base android-cli skill by running:

android init

From there, you can browse and set up your agent workflow by searching for the exact capabilities your agent needs:

android skills list

Once you've found the right skill, install it to your environment by running:

android skills add –skill=

Get started today

To download the stable 1.0 release of the Android CLI, explore the new tools, and browse the complete documentation, head over to d.android.com/tools/agents today! Also, make sure you update to the latest preview version of Android Studio to unlock the latest features that Android CLI offers. We can't wait to see what you build with Android CLI 1.0 and how these new features supercharge your daily workflows. Join our vibrant community on LinkedIn, Medium, YouTube, or X and share your feedback.

Explore this announcement and all Google I/O 2026 updates on io.google.

Prioritizing Memory Efficiency: Essential Steps for Android 17

Sat, 25 Jul 2026 10:15:41 +0200

Posted by Alice Yuan, Developer Relations Engineer, Ajesh Pai, Developer Relations Engineer, and Fung Lam, Developer Relations Engineer

While app performance is often equated with a smooth UI and fast start times, memory serves as the silent foundation upon which these visible metrics are built. It's no secret that we're seeing a shift where device memory is more important than ever. Not only have we made strides in Android memory optimizations with Android 17, we're providing the tooling and API support to help you stay ahead of stricter memory requirements later this year.

To ensure device stability, starting in Android 17, the system will begin enforcing app memory limits based on the device's total RAM. If an app exceeds those limits, Android will kill the process with no associated stack trace.

Beyond these forced terminations, unoptimized memory usage inevitably degrades the user experience. When the app approaches heap memory limits, it triggers frequent garbage collection—leading to noticeable UI stutters. Furthermore, when a device runs out of available memory, the system scrambles to reclaim pages, causing CPU strain, UI latency, and battery drain. If the memory shortage is too severe, it can cause Low Memory Killer (LMK) events that abruptly terminate background processes and force apps to have slow cold starts and lose user state.

To build highly performant apps and avoid these forced terminations, we recommend that you adopt the following memory optimization strategies:

A condensed version of this blog post is also available in video format, go check it out!

Understanding Android 17 app memory limits

App memory limits are being introduced in Android 17 to prevent "one bad actor" from destroying the multitasking experience and stability of the user’s entire device.

Here is a breakdown of the reasons driving this architectural change:

Preventing cascading kills: When an app becomes bloated or leaks memory while holding a privileged state (e.g. it’s running a Foreground Service), it is initially shielded from the system's Low Memory Killer (LMK). As this single app grows unchecked and hoards RAM, the LMK is forced to compensate by killing off dozens of smaller, well-behaved cached apps and background jobs to reclaim space for the memory hog.
Preserving multitasking and user state: When the system is forced to purge cached apps to accommodate a single leaking process, the multitasking experience is severely degraded. Users returning to prior cached applications encounter sluggish cold starts instead of near-instant warm resumes. This inefficiency generates more CPU strain and accelerates battery depletion. It can also destroy the user’s context in recently used apps, such as scroll positions, navigation stacks, and in-game progress.

To determine if your app session was impacted by these constraints in the field, you can call getDescription() within ApplicationExitInfo. If the system applied a limit, the exit reason is reported as REASON_OTHER and the description string will contain "MemoryLimiter:AnonSwap". You can also leverage trigger-based profiling using TRIGGER_TYPE_ANOMALY to automatically capture heap dumps when the memory limit is reached. Furthermore, Android is actively working to surface more in-field memory metrics to developers within the Google Play Console.

We have also expanded our memory limits documentation to include local debugging commands, allowing you to simulate memory constraints in your local environment and validate your application's behavior under any memory limit enforcement.

Maximize bytecode optimization with R8

A highly effective way to reduce your app's memory footprint is to enable the R8 optimizer. By shrinking classes, methods, and fields into shorter names and stripping out unused code and resources, R8 significantly reduces your app's memory footprint by minimizing the amount of resident code required during execution.

R8 minimizes resident code, shrinking the memory footprint and lowering LMK termination risk. This results in more frequent warm starts over slow cold starts. Additionally, streamlined bytecode reduces main-thread CPU overhead, directly cutting ANR rates for a more fluid user experience. For example, the digital bank Monzo enabled full R8 optimization and saw a 35% reduction in their ANR rate, a 30% improvement in cold start rate, and a 9% reduction in overall app size.

The digital bank Monzo enabled full R8 optimization and boosted performance metrics by up to 35%.

To properly configure R8 in your build.gradle file:

Set isShrinkResources = true and isMinifyEnabled = true.
Use proguard-android-optimize.txt instead of the legacy proguard-android.txt, which actually prevents optimizations and is no longer supported in Android Gradle Plugin 9.
Remove android.enableR8.fullMode = false from your gradle.properties.

If you are using reflection in your code base, then add Keep rules to prevent R8 from optimizing those parts of the code. Make sure to scope the keep rules narrowly to get the maximum optimization.

To get the maximum optimization, make sure to follow these best practices in your keep rule file.

Remove global options like -dontoptimize, -dontshrink, and -dontobfuscate that prevent R8 from optimizing the entire codebase
Remove keep rules that prevent optimizing Android components like Activity, Services, Views or Broadcast receivers.
Refine the broad package wide keep rules to target only specific classes or methods.

To see more best practices, view our keep rules documentation.

Library Developer R8 Best Practices

If you are a library developer, strictly place the rules your consumers need into your consumer-rules file, and keep your library's internal protection rules in your proguard-rules.pro file. For more information on how to optimize libraries, see Optimization for library authors.

R8 Configuration Analyzer

To audit your R8 optimization, use the Configuration Analyzer. Configuration analyzer shows the current state of optimization with Obfuscation, Optimization, and Shrinking scores. With configuration analyzer, you can also understand how many classes, methods or fields are prevented from optimization by each keep rule. Refine these broad package wide keep rules to unlock the maximum optimization.

Using configuration analyzer, you can also identify keep rules that are subsuming other keep rules, redundant keep rules and unused keep rules.

The Configuration Analyzer shows the current state of optimization with Obfuscation, Optimization, and Shrinking scores.

R8 Agent Skill

You can also leverage the R8 Agent Skill with Android Studio agent or other AI tools to resolve misconfigurations and refine your rules resulting in improved app performance. (Insights from AI-driven skills will require technical verification)

Optimize image loading

Bitmaps are usually the largest common objects residing in your app's memory. They represent the final stage of the image loading process where compressed files, like JPEGs or PNGs, are decoded into raw pixel data for display. This means a tiny 100KB compressed image can balloon into several megabytes of RAM because memory consumption is determined by the image's pixel dimensions and color depth. Since bitmap operations are frequently on the critical path to drawing frames, unoptimized images cause severe memory bloat and UI jank.

Google recommends leveraging image loading libraries Coil for Kotlin-first projects, particularly when developing with Jetpack Compose and Glide for Java-based applications.

Adopt these five best practices

Downsample images: If you’re loading bitmaps manually, avoid loading a massive image into a tiny thumbnail view; use inSampleSize to load a smaller version. Glide and Coil downsamples images by default and you can configure this downsample strategy using DownsampleStrategy and ImageLoader respectively.
Cropping: Avoid embedding padding directly into an image file for letterboxing purposes (e.g., creating a transparent border to expand an image dimensions). Rather than baking in these borders, utilize InsetDrawable or apply padding directly within the View or Composable containing the bitmap.
Config: Balance memory and quality by choosing the right pixel format. Use RGB_565 when transparency isn't needed, which uses half the memory of the default ARGB_8888 format. In Glide you can configure this by using DecodeFormat and in Coil you can use bitmapConfig property.
Prioritize vector drawables: For basic geometric assets, leverage ShapeDrawable as a lightweight alternative to decoding rasterized bitmaps. By defining these assets once via XML, you ensure they scale seamlessly across all display densities while effectively eliminating resource-driven memory bloat.
Reuse: If your application manages Bitmaps manually then to minimize memory churn, when a bitmap is no longer required, the app should call bitmap.recycle() and immediately discard the Bitmap reference. If you use an image loading library like Glide or Coil, return the bitmap to the library’s managed pool. By providing an existing buffer for future memory needs, the pool effectively avoids the overhead of new allocations.

Check out our documentation on Optimizing performance for images to learn more.

Android Studio tooling

You can also eliminate redundant bitmaps using Android Studio Narwhal 4. Here is how to hunt them down in five simple steps:

Open the Profiler tab in Android Studio
Click Heap Dump (or "Analyze Memory Usage") and hit record to take a snapshot of your app’s current memory state.
Scan the analysis results for the yellow warning triangle ⚠️, which Android Studio uses to flag duplicate bitmaps being stored multiple times. Alternatively, navigate to the profiler header, choose "Filter by:" and pick the "Duplicate Bitmaps" setting.
Click on any flagged entry to open the Bitmap Preview pane, allowing you to see exactly which image is the repeat offender.
Use that visual confirmation to track down the redundant loading logic in your code and implement a better caching strategy.

Look for the yellow warning triangle ⚠️ in heap dumps when using the Android Studio Profiler.

Detect and fix memory leaks with Android Studio

Memory leaks in Android occur when your code holds onto an object's reference long after its lifecycle has ended. This prevents the Garbage Collector (GC) from reclaiming that memory, eventually leading to sluggish performance or OutOfMemoryError (OOM).

Android Studio Panda 3 features a dedicated LeakCanary profiler task, allowing developers to analyze real-time memory leaks and map traces within the IDE.

The LeakCanary profiler task in Android Studio actively moves the memory leak analysis from your device to your development machine, resulting in a significant performance boost during the leak analysis phase as compared to on-device leak analysis.

LeakCanary memory leak analysis contextualized with Go to declaration for debugging

Additionally, the leak analysis is now contextualized within the IDE and fully integrated with your source code, providing features like go to declaration and other helpful code connections that drastically reduce the friction and time required to investigate and fix memory leaks.

Examples of common memory leaks

Memory leaks occur when an object persists in memory beyond its intended lifespan. This typically happens due to:

Retaining references to Fragments, Activities, or Views that are no longer in use.
Mismanaging Context references.
Failing to properly unregister observers, listeners, and receivers.
Creating static references to objects that are bound to components with shorter lifecycles.

Here are a few example scenarios:

Scenario	Compose-based example	View-based example
Leaking Context	Example: Passing LocalContext.current to a ViewModel Fix: Keep `Context` dependent logic within the UI layer. For non-UI layers, refactor to use dependency injection or observe UI state using Kotlin flow.	Example: Storing an `Activity` in a companion object or static variable. Fix: Don’t hold static references to UI components. Refactor to use dependency injection or observe UI state using Kotlin flow.
Leaking Listeners	Example: Using `DisposableEffect` to start a listener but leaving `onDispose` empty. Fix: Perform the unregistration and cleanup logic inside the `onDispose` block.	Example: Registering for SensorManager updates and forgetting to unregister. Fix: Manually call `unregisterListener()` in `onStop()` or `onDestroy()` lifecycle.
Leaking Views	Example: Holding a reference to a legacy `View` inside an `AndroidView` without a release strategy. Fix: Use the `release` block of the `AndroidView` composable to clean up the legacy `View`.	Example: Keeping a reference to a view binding object after the `Fragment` is destroyed. Fix: Set the binding variable to `null` inside the `onDestroyView`() lifecycle method.

Trim memory when app leaves visible state

Android can reclaim memory from your app or stop your app entirely if necessary to free up memory for critical tasks, as explained in Overview of memory management. Android will usually reclaim memory from your app when it’s not visible to the user, such as by discarding some of your app’s code and data pages in memory or compressing your heap allocations. When the user resumes your app and your app tries to access some memory that’s been reclaimed, the OS will swap that memory back in on demand. This swapping behavior can be slow, and cause unexpected jank or stutters in your app.

If you leave it to the OS to decide what memory to reclaim from your app, you may find that the OS reclaimed memory that you’ll need shortly after resuming your app. Instead, your app can voluntarily discard memory allocations that it can regenerate later, on demand and at a low cost. To do so, you can implement the ComponentCallbacks2 interface. You can implement onTrimMemory in your Activity, Fragment, Service, or even your custom Application class. Using it in the Application class is highly effective for global cache management.

The provided onTrimMemory() callback method notifies your app of lifecycle or memory-related events that present a good opportunity for your app to voluntarily reduce its memory usage.

In terms of memory lifecycle management, your implementation should focus exclusively on TRIM_MEMORY_UI_HIDDEN and TRIM_MEMORY_BACKGROUND. Since Android 14, the system has ceased delivering notifications for other legacy constants, which were formally deprecated in Android 15.

TRIM_MEMORY_UI_HIDDEN: This signal indicates that your application's UI has transitioned out of the user's view. This provides an opportunity to release substantial memory allocations tied strictly to the interface—such as Bitmaps, video playback buffers, or complex animation resources.

TRIM_MEMORY_BACKGROUND: At this level, your process is residing in the background and is now a candidate for termination to satisfy the system's global memory needs. To extend the duration your process remains in the cached state, and reduce the number of app cold starts, you should aggressively release any resources that can be easily reconstructed once the user resumes their session.

import android.content.ComponentCallbacks2
// Other import statements.

class MainActivity : AppCompatActivity(), ComponentCallbacks2 {

    /**
     * Release memory when the UI becomes hidden or when system resources become low.
     * @param level the memory-related event that is raised.
     */
    override fun onTrimMemory(level: Int) {

        if (level >= ComponentCallbacks2.TRIM_MEMORY_UI_HIDDEN) {
            // Release memory related to UI elements, such as bitmap caches.
        }

        if (level >= ComponentCallbacks2.TRIM_MEMORY_BACKGROUND) {
            // Release memory related to background processing, such as by
            // closing a database connection.
        }
    }
}

Note: The onTrimMemory integration may depend on SDK support. For instance, certain games rely on their game engine to enable this capability. Please check out the game memory optimization documents.

Advanced memory observability with ProfilingManager

To catch and diagnose memory issues in the field that cannot be reproduced locally, you should leverage the ProfilingManager API. Introduced in Android 15, this advanced observability API allows you to programmatically collect real-user Perfetto profiles.

For teams that lack a dedicated infrastructure to manage and host performance artifacts, Crashlytics is exploring a specialized solution to streamline this workflow. They are inviting developers to provide feedback.

Android 17 introduces new event-driven triggers, most notably TRIGGER_TYPE_OOM and TRIGGER_TYPE_ANOMALY:

The OOM trigger automatically collects a Java heap dump at the exact moment an OutOfMemoryError crash occurs, providing precise allocation states. A collected OOM profile is provided the next time the app starts and registers the registerForAllProfilingResults callback.
The Anomaly trigger detects severe performance issues, such as excessive binder spam or breached memory thresholds. The memory anomaly delivers a heap dump just prior to the system terminating the app.

  val profilingManager = 
applicationContext.getSystemService(ProfilingManager::class.java)
    val triggers = ArrayList()  


    triggers.add(ProfilingTrigger.Builder(
                 ProfilingTrigger.TRIGGER_TYPE_ANOMALY))
    val mainExecutor: Executor = Executors.newSingleThreadExecutor()
    val resultCallback = Consumer { profilingResult ->
        if (profilingResult.errorCode != ProfilingResult.ERROR_NONE) {
            // upload profile result to server for further analysis          
            setupProfileUploadWorker(profilingResult.resultFilePath)
        } 

    profilingManager.registerForAllProfilingResults(mainExecutor, resultCallback)
    profilingManager.addProfilingTriggers(triggers)

Once you’ve collected the heap dump, you can download the profile from the server, or locally via adb pull and drag and drop the file into the Perfetto UI. To streamline your memory debugging workflow, use the Heap Dump Explorer, this is the new default view for heap dumps in Perfetto UI. This tool provides an intuitive interface for inspecting Java heap dumps, allowing you to visualize object allocation hierarchies, compute retained memory sizes, and identify the shortest path from garbage collection root. By leveraging the Heap Dump Explorer, you can rapidly pinpoint memory leaks, bloated retained objects such as excessive bitmap allocations, and analyze heap object allocations all in one place.

Use the Heap Dump Explorer’s embedded flamegraph to visually inspect and navigate through objects with the highest heap allocations.

Conclusion

Optimizing bytecode with R8, adopting image loading best practices, and resolving memory leaks are critical steps toward delivering a high-quality user experience while managing resources effectively under pressure. Adopting these proactive measures helps maintain app stability and performance, preventing unexpected terminations while safeguarding user context. To further your performance expertise, explore our revised memory guidance.

Android 17 is here

Sat, 25 Jul 2026 10:15:36 +0200

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

Today we're releasing Android 17 and making it available on most supported Pixel devices. Look for new devices running Android 17 in the coming months.

Android 17 marks the start of our transition to an intelligence system, putting your apps at the center. It's shifting to an adaptive-first development standard by introducing mandatory large-screen resizability, all while delivering next-generation privacy, security, media, camera, and performance. We'll cover all that in this post, as well as how we're bringing together next generation tools, libraries, and agent skills to help your apps embrace the opportunity.

Throughout the past year, from our Canary channel to our Beta releases, we’ve collaborated with you in the developer community to build a platform you and your users can trust. To that end, this moment marks the availability of the source code at the Android Open Source Project (AOSP). This allows you to examine the source code for a deeper understanding of how Android works.

Let's dive deeper into Android 17.

An intelligence system

With deep integration between hardware, software and AI, we’re transforming Android from an operating system to an intelligence system. It's about delivering new helpful experiences that anticipate user needs, and it brings more opportunities for engagement with your apps. To that end, Android 17 expands the capabilities of AppFunctions, a platform API with a corresponding Jetpack library. It allows you to contribute your app's unique capabilities as orchestratable "tools" for Android MCP, the on-device equivalent of the Model Context Protocol. AI agents and assistants (like Google Gemini) can discover and execute AppFunctions to perform workflows on behalf of the user with direct access to the app's local state.

The Jetpack library, currently in alpha, makes adding AppFunctions as easy as annotating a class and adding KDoc comments.

/**
 * A note app's [AppFunction]s.
 */
class NoteFunctions(
    private val noteRepository: NoteRepository
) {
    /**
     * Adds a new note to the app.
     *
     * @param appFunctionContext The execution context.
     * @param title The title of the note.
     * @param content The note's content.
     */
    @AppFunction(isDescribedByKDoc = true)
    suspend fun createNote(
        appFunctionContext: AppFunctionContext,
        title: String,
        content: String
    ): Note {
        return noteRepository.createNote(title, content)
    }
}

We’ve also launched an AppFunctions agent skill that analyzes your app’s key workflows, automatically generates the required Kotlin code, optimizes your KDocs for LLM tool-calling, and provides ADB commands for testing and debugging.

The Gemini integration is currently in a private preview with trusted testers, but you can begin preparing your apps now. In addition to ADB commands to execute your AppFunctions, we've provided a test agent app that includes an interface to discover and execute your app functions and simulate an AI agent integration. Join our integration early access program at goo.gle/eap-af for a chance to be among the first apps to deploy AppFunctions to production.

Adaptive-first

Your users no longer rely on a single form factor; they transition between phones, foldables, tablets, laptops, automotive displays, and immersive XR environments. Now, with over 580 million large screen devices in the hands of users and the forthcoming launch of Googlebooks, the next generation of ChromeOS built on the Android stack, adaptive is no longer just a technical goal. It’s a massive opportunity to reach highly engaged users, which is one of the reasons we're shifting to an adaptive-first development standard.

No resizability/orientation restrictions on large screens

To ensure apps deliver a premium experience across all form factors, including mobile devices running in desktop mode on connected displays, Android 17 (API level 37) removes the developer opt-out for orientation and resizability restrictions on large screen devices (sw > 600 dp) for apps targeting API level 37. The system will ignore legacy manifest attributes and runtime APIs, including screenOrientation, setRequestedOrientation(), resizeableActivity=false, and aspect ratio constraints (minAspectRatio/maxAspectRatio). Games (based on app category in Google Play) remain exempt. Your app must be ready to adapt to any window size, respect the user's preferred device posture, and support free-form windowing natively.

Next-gen multitasking: App Bubbles, Bubble Bar, and desktop interactive PiP

Android 17 introduces powerful new windowing capabilities that redefine how users multitask, demanding even greater layout flexibility from your apps:

App Bubbles: Moving beyond the messaging bubbles API, users can now transform any app into a floating bubble by long-pressing its icon on the launcher. This feature is available across phones, foldables, and tablets, enabling lightweight multitasking for any workflow.
The Bubble Bar: On large screens (tablets and foldables), the system taskbar now includes a dedicated Bubble Bar to organize, transition between, and dock these floating app bubbles.
Desktop interactive PiP: In desktop environments, Android 17 introduces interactive Picture-in-Picture (PiP). Unlike traditional PiP windows which are read-only, these pinned windows remain fully interactive while staying always-on-top of other application windows.

App Bubbles and Bubble Bar in action

Activity recreation updates

To prevent disruptive state loss and stutter, Android 17 updates the default behavior for Activity recreation. The system will no longer restart activities by default for typical configuration changes that do not require a full UI redraw (including CONFIG_KEYBOARD, CONFIG_KEYBOARD_HIDDEN, CONFIG_NAVIGATION, CONFIG_TOUCHSCREEN, and CONFIG_COLOR_MODE).
Instead, running activities will receive these updates via onConfigurationChanged(), enabling smooth transitions. If your application explicitly relies on a full restart to reload resources for these changes, you must now explicitly opt-in using the new android:recreateOnConfigChanges manifest attribute.

Continue On

Android 17 adds Continue On to help users seamlessly transition a task between Android devices. The user sees a suggestion for the most recently opened app from their mobile device in their tablet taskbar, providing a one-tap affordance to launch the app and deep-link where they left off. Continue on can support app-to-web transitions, including falling back to using the web if the app isn't installed.

Handoff Suggestion on a Tablet

class MyHandoffActivity : Activity() {

    ...

  override fun onCreate(savedInstanceState: Bundle?) {
    super.onCreate(savedInstanceState)
    // Do stuff
    ...
    // Enable handoff
    setHandoffEnabled(true, null)
  }

  // Override and implement onHandoffActivityDataRequested
  override fun onHandoffActivityDataRequested(handoffRequestInfo: HandoffActivityDataRequestInfo) : HandoffActivityData {
    // Create and return handoff data
  }
}

Go adaptive-first with Jetpack Compose

To help you adapt your apps to meet the new Android 17 requirements, we've launched the Jetpack Compose adaptive skill. This AI-powered developer workflow helps you implement the best adaptive practices:

Adaptive navigation: Automatically transition between bottom navigation bars on mobile and edge-anchored navigation rails on large screens using NavigationSuiteScaffold from the Material 3 Adaptive library.
Multi-pane layouts: Implement list-detail and supporting pane layouts natively using Navigation 3 Scenes (ListDetailSceneStrategy and SupportingPaneSceneStrategy) instead of fragile fragment transactions.
FlexBox & Grid APIs: Utilize Compose 1.11's dynamic layout components to easily adjust row and column spans on the fly, ensuring your content always fills the space beautifully.
Advanced non-touch input: Leverage Compose 1.11's enhanced trackpad and mouse support, including native focus rings and new APIs (like TrackpadInjectionScope and performTrackpadInput) to easily test and deliver a true "laptop-class" experience on Googlebooks and Desktop Mode.
Dynamic window states: Leverage Compose's reactive state model to seamlessly adapt your UI when the app transitions from full screen to a floating App Bubble or an interactive Desktop PiP window, ensuring a premium experience even at minimal dimensions.

Android is Compose-first

Compose offers the easiest way to build adaptive apps, and that's just one of the many reasons we believe that all Android UI should be built with Compose. To that end, Android development is now Compose-first. All new Android APIs, libraries, tools, and developer guidance will be built exclusively for Jetpack Compose. Legacy View components (in the android.widget package) and View-based Jetpack libraries (like Fragments, RecyclerView, and ViewPager) are now in maintenance mode. They will receive only critical bug fixes, and no new features.

TIP
Ready to migrate? Use our AI-driven XML to Compose Migration Skill to automatically analyze your legacy View layouts and convert them into highly-adaptive Compose code.

Performance & efficiency

App performance means a smooth user interface, fast app start times, and efficient multitasking; Android 17 has impactful improvements in all of these areas.

App memory limits

Memory usage is one of the silent foundations of overall performance. When a foreground app or service grows unchecked, memory management spikes CPU and battery utilization and eventually leads to the termination of other well-behaved cached apps and background jobs, ultimately forcing slower cold starts and impaired multitasking.

Starting in Android 17, the system will enforce strict app memory limits based on a device's total RAM, abruptly terminating offending processes. New things to help you navigate these tighter requirements:

R8 Optimizer: The R8 optimizer significantly reduces your app's bytecode memory footprint by shrinking classes, methods, and fields into shorter names, and stripping out unused code and resources. Use R8 in full mode along with the new R8 configuration analyzer to make sure your app is getting the most from R8.

The R8 Configuration Analyzer

LeakCanary in Android Studio Panda: The profiler now features native LeakCanary integration as a dedicated task, fully integrated with your IDE and source code.
ApplicationExitInfo: If your app is terminated by these limits, getDescription() from ApplicationExitInfo will return "MemoryLimiter:AnonSwap".
On-Device Anomaly Detection: Part of ProfilingManager, you can leverage trigger-based profiling using TRIGGER_TYPE_ANOMALY to automatically capture heap dumps when the memory limit is reached.

val profilingManager = applicationContext
   .getSystemService(ProfilingManager::class.java)

val triggers = ArrayList().apply {
  add(ProfilingTrigger.Builder(
    ProfilingTrigger.TRIGGER_TYPE_ANOMALY).build())
}
profilingManager.addProfilingTriggers(triggers)

And, we're working to surface more in-field memory metrics to you within Google Play Console.

Generational garbage collection

Android 17 introduces more frequent, less resource-intensive young-generation collections to ART's Concurrent Mark-Compact garbage collector (GC). By separating short-lived objects from stable, long-lived ones, the system runs frequent, lightweight "young-generation" sweeps rather than expensive full-heap scans, drastically reducing CPU usage, power drain, and UI stutter. Our testing has shown significant improvements in GC interference with application threads and a reduction in the maximum memory resident set size (RSS). ART improvements are also available to over a billion devices running Android 12 (API level 31) and higher through Google Play System updates.

Lock-Free MessageQueue

For apps targeting SDK 37 or higher, the core android.os.MessageQueue now implements a lock-free architecture, significantly reducing missed frames, improving app startup time, and radically improving the performance of busy queues in multithreaded scenarios. Note: This can break apps that use reflection on private MessageQueue fields and methods. The peekWhen and poll APIs have been added to TestLooperManager for instrumentation testing without relying on MessageQueue internals.

Static final fields now truly final

Starting from Android 17, apps targeting SDK 37 or higher won’t be able to modify “static final” fields, allowing the runtime to apply performance optimizations more aggressively. An attempt to do so via reflection (or deep reflection) will lead to an IllegalAccessException being thrown. Modifying them via JNI’s SetStaticField methods family will immediately crash the application.

Custom notification view restrictions

To reduce memory usage we are further restricting the size of custom notification views. This update closes a loophole that allows apps to bypass existing limits using URIs. This behavior is gated by the target SDK version and takes effect for apps targeting API 37 and higher.

Privacy & Security

Maintaining user trust is at the heart of the Android ecosystem. Android 17 introduces robust features that protect sensitive data while simplifying user experiences.

Privacy-preserving choices

Historically, apps required broad, permanent permissions to access information like contacts, precise location and media files. Android 17 continues the shift toward privacy-preserving choices that grant temporary, session-based access only to the data the user explicitly selects:

System-Level Contact Picker: Utilizing ACTION_PICK_CONTACTS, apps can request temporary access only to specific fields (e.g., email or phone number) chosen by the user, eliminating the need for the broad READ_CONTACTS permission. It also fully supports work/personal profile separation.
Customizable Photo Picker aspect ratio: UsingPhotoPickerUiCustomizationParams, you can customize the system photo picker to show thumbnails in portrait mode. This is perfect for apps that always display photos and videos in portrait such as video based social media apps.
System-rendered Location Button: A new system-rendered location button that you can embed in your app grants precise location access for the current session only.
EyeDropper API: A new system-level API, ACTION_OPEN_EYE_DROPPER, allows your app to create a system-powered eyedropper enabling the user to select color from any pixel on the display. This provides a secure, privacy-preserving color-picking experience that eliminates the need for broad, sensitive screen capture or media projection permissions.

val eyeDropperLauncher = registerForActivityResult(ActivityResultContracts.StartActivityForResult()) { result ->
   if (result.resultCode == Activity.RESULT_OK) {
       val color = result.data?.getIntExtra(Intent.EXTRA_COLOR, Color.BLACK)
       // Use the picked color in your app
   }
}
fun launchColorPicker() {
   val intent = Intent(Intent.ACTION_OPEN_EYE_DROPPER)
   eyeDropperLauncher.launch(intent)
}

Picking a color from anywhere on the screen with the system EyeDropper

Local network access

Apps targeting Android 17 now either require the ACCESS_LOCAL_NETWORK runtime permission or the use of system-mediated, privacy-preserving device pickers for local network communication, such as talking to smart home devices or casting receivers. Because ACCESS_LOCAL_NETWORK falls under the existing NEARBY_DEVICES permission group, users who have already granted other NEARBY_DEVICES permissions will not be prompted again.

SMS OTP protection

Android 17 expands SMS one-time-password (OTP) protection by delaying access to SMS messages for three hours:

WebOTP Format: Delayed for all apps that are not the intended recipient (domain mismatch).
Standard SMS OTP: Delayed for all apps targeting SDK 37+.
Exemptions: Default SMS, assistant, and connected companion apps are exempt. Apps are strongly encouraged to migrate to the SMS Retriever or SMS User Consent APIs.

Post-Quantum Cryptography (PQC)

Android 17 is ready for the next generation of cryptographic security:

Keystore Integration: Supported devices can generate ML-DSA (Module-Lattice-Based Digital Signature Algorithm) keys in secure hardware to produce quantum-safe signatures, exposed via standard JCA APIs.
Hybrid APK Signing: Introducing the v3.2 APK Signature Scheme, which combines classical signatures with ML-DSA signatures to secure app delivery.

Safer native dynamic code loading

If your app targets SDK 37 or higher, the Safer Dynamic Code Loading (DCL) protection introduced in Android 14 for DEX and JAR files now extends to native libraries. All native files loaded using System.load must be marked as read-only. Otherwise, the system throws UnsatisfiedLinkError

Smarter password protection for physical inputs

With Android 17, we're making it safer to enter passwords, PINs, and other secrets when using a physical keyboard by no longer showing the last typed character by default.

Users can still easily customize these display settings to match their preferences (availability may vary by device manufacturer).

These enhanced privacy protections are automatically supported byAndroid's built-in SDK components and will be supported in Compose 1.12 for SecureTextFields.

Smarter password protection for physical inputs

Media and camera features that empower creators and delight users

Android 17 introduces new creator features that give access to pro-quality cameras and media, all while improving the experience for consumers.

Eclipsa Video: HDR video standard built upon the SMPTE ST 2094-50 specification that introduces new metadata to help devices adapt content for their display headroom and ambient light conditions, as well as improve the simultaneous display of standard and HDR content.
RAW14 image format: New support for the RAW14 image format provides a way for your professional camera app to capture the highest level of detail and color depth from compatible camera sensors.
Vendor-defined camera extensions: Vendor-defined extensions enable hardware partners to define and implement custom camera extension modes, providing access to the best and latest camera features.
Extended HE-AAC software encoder: A new system-provided Extended HE-AAC software encoder, supports both low and high bitrates using unified speech and audio coding, providing significantly better audio quality for voice messages in low-bandwidth conditions, including support for loudness metadata.
Versatile Video Coding (H.266): Enables OEMs to add codec support by defining the video/vvc MIME type in MediaFormat, adding new VVC profiles in MediaCodecInfo, and integrating support into MediaExtractor.
Camera device type: New APIs that query the underlying device type to identify if a camera is built-in hardware, an external USB webcam, or a virtual camera.
Constant Quality for Video Recording: SetVideoEncodingQuality in MediaRecorder configures a constant quality (CQ) mode for video encoders to ensure uniform visual fidelity across the entire video.

Better support for hearing aids

Bluetooth LE Audio hearing aid support: Android now includes a specific device category for Bluetooth Low Energy (BLE) Audio hearing aids with the new AudioDeviceInfo.TYPE_BLE_HEARING_AID constant, so your app can distinguish hearing aids from regular headsets to provide a tailored experience for users with assistive listening devices.
Granular audio routing for hearing aids: Android 17 allows users to independently manage where specific system sounds are played. They can choose to route notifications, ringtones, and alarms to connected hearing aids or the device's built-in speaker, helping to avoid unwanted in-ear interruptions while maintaining a Bluetooth connection for hearing aid management apps.

CameraX and Media3

CameraX and Media3 have been updated for Android 17. They are there to do the heavy lifting, smoothing the rough edges of media development and simplifying building reliable camera capture, smooth media playback, and creative and complex editing experiences.

We've released an agent skill that can migrate legacy Android camera implementations (Camera1 or raw Camera2 APIs) to CameraX.

Note: You'll need to update your CameraX version to either 1.5.2 or 1.6.0+ to avoid a crash related to an added dynamic range mode on Android 17 devices.

Get your apps, libraries, tools, and game engines ready!

If you develop an Android SDK, library, tool, or game engine, it's critical to prepare any necessary updates now to prevent your downstream app and game developers from being blocked by compatibility issues and allow them to target the latest SDK features. Please let your downstream developers know if updates are needed to fully support Android 17.

Testing involves installing your production app or a test app making use of your library or engine using Google Play or other means onto a device or emulator running Android 17 Beta 4. Work through all your app's flows and look for functional or UI issues. Each release of Android contains platform changes that improve privacy, security, and overall user experience; review the app impacting behavior changes for apps running on and targeting Android 17 to focus your testing, including the following:

Resizability on large screens: Once you target Android 17 (SDK 37), you can no longer opt out of maintaining orientation, resizability and aspect ratio constraints on large screens.
Dynamic code loading: If your app targets SDK 37 or higher, the Safer Dynamic Code Loading (DCL) protection introduced in Android 14 for DEX and JAR files now extends to native libraries. All native files loaded using System.load() must be marked as read-only. Otherwise, the system throws UnsatisfiedLinkError.
Enable CT by default: Certificate transparency (CT) is enabled by default. (On Android 16, CT is available but apps had to opt in.)
Local network protections: Apps targeting SDK 37 or higher have local network access blocked by default. Switch to using privacy preserving pickers if possible, and use the new ACCESS_LOCAL_NETWORKpermission for broad, persistent access.
Background audio hardening: Starting in Android 17, the audio framework enforces restrictions on background audio interactions including audio playback, audio focus requests, and volume change APIs. Based on your feedback, we’ve made some changes since beta 2, including targetSDK gating while-in-use FGS enforcement and exempting alarm audio. Full details available in the updated guidance.
NPU access declaration: Apps targeting Android 17 that need to directly access the NPU must declare FEATURE_NEURAL_PROCESSING_UNIT in their manifest to avoid being blocked from accessing the NPU. This includes apps that use the LiteRT NPU delegate, vendor-specific SDKs, as well as the deprecated NNAPI.

Get started with Android 17

Your Pixel device should get Android 17 shortly if you haven't already been on the Android Beta. If you don’t have a Pixel device, you can use the 64-bit system images with the Android Emulator in Android Studio. If you are currently on Android 17 Beta 4.1 and have not yet taken an Android 17 QPR1 beta, you can opt out of the program and you will then be offered the release version of Android 17 over the air.

Getting the Android 17 beta on partner devices

Android 17 is available in beta on handset, tablet, and foldable form factors from partners including Honor, iQOO, Lenovo, OnePlus, OPPO, Realme, Sharp, vivo, and Xiaomi.

For the best development experience with Android 17, we recommend that you use the latest Canary build of Android Studio Quail. Once you’re set up, here are some of the things you should do:

Test your current app for compatibility, learn whether your app is affected by changes in Android 17, and install your app onto a device or Android Emulator running Android 17 and extensively test it.

Thank you again to everyone who participated in our Android developer preview and beta program. We're looking forward to seeing how your apps take advantage of the updates in Android 17, and have plans to bring you updates in a fast-paced release cadence going forward.

For complete information on Android 17 please visit the Android 17 developer site.

Linus Torvalds on AI, Junk Patches, Humans, and Godzilla

Sat, 25 Jul 2026 10:12:40 +0200

Linus Torvalds once said LLMs might bring a 10X increase to programmer productivity. But speaking at Open Source Summit India 2026, he now says that number was "not scientific," reports ZDNet. "That was pulled out of my ass number, obviously." Today, he continued, "we're at the point where hopefully it creates more productivity than it takes away," but "we certainly saw more junk being generated by LLMs than we saw useful code up until the like early this year.... it can actually be a huge drain on resources when it takes humans a lot of effort to figure out that, hey, this machine-generated report was not true." Even now, he said, "most of the good ones require more than just the LLM," because "we've had to push back quite a bit... if you find a bug with an LLM, it's not enough to just ask the LLM to make a bug report and then throw it over the fence to us. We want to see a suggested patch; we want to see the human who ran the LLM act as a kind of back-and-forth." Torvalds described many AI-generated patches as "mindless band-aid kind of patches... they may fix the immediate problem, but the kind of bug remains, and it just is waiting in the hallway to hit you in another place." For his own toy projects, he uses LLMs as prototypers: "I use them as a way to prototype things... quite often the code is not usable in that form, but it's a great way to try something out," while insisting that for kernel-level fixes, "LLMs, in my experience, have not been at that level yet." Torvalds acknowledged that some AI-found issues have been "absolutely, stunningly, I mean, interesting in a painful kind of way," especially security problems that "show up in the technology press two days later." Despite the embarrassment, he said, "I'm very much not a shoot-the-messenger kind of person. I think we're much better off with LLMs finding bugs, even when they are embarrassing, and they are things that we should probably have found two decades ago." Torvalds also said he's using AI "for my own toy projects... Every time I travel to some new place, and this is the first time I've been to India, I send the kids pictures of where I am, and for some strange reason, Godzilla seems to follow me around and gets added to those pictures." ZDNet notes that Torvalds concluded, "There are many useful and less useful uses for AI," and "I think Godzilla is a great place to stop." Thanks to Slashdot reader joshuark for sharing the article.

Read more of this story at Slashdot.

‘Sugar’ Season 2, Episode 7 Release Date and What to Expect

Sat, 25 Jul 2026 10:05:43 +0200

“Sugar” Season 2, Episode 7 will arrive on Apple TV on Friday, July 31, 2026. The upcoming chapter serves as the penultimate episode, bringing John Sugar closer to the truth behind his latest case while his conflict with Deputy Vega reaches a dangerous stage. The neo-noir detective series returned for its second season on June 19, with Colin Farrell once again playing the mysterious private investigator. New episodes have followed every Friday, and the eight-episode season will conclude on August 7. Release date: Friday, July 31, 2026 Streaming platform: Apple TV Season: 2 Episode: 7 Genre: Crime, drama, mystery and neo-noir Season finale: Friday, August 7, 2026 What is happening in ‘Sugar’ Season 2? Spoilers ahead for Season 2, Episode 6. Season 2 follows Sugar as he investigates another disappearance in Los Angeles while continuing his personal search for his missing sister, Djen. His new case involves the disappearance of a boxer’s brother, but the investigation has gradually exposed a much larger criminal operation involving drugs, false death records and housing fraud. Episode 6, titled “Cautionary Tale,” explored Sugar’s past and his growing fear that life on Earth has changed him. A flashback involving Peg Rosenthal showed the emotional damage caused when members of his alien community become too attached to human desires. Meanwhile, Sugar obtained evidence connected to Operation: Fire Sale and confronted the increasingly unstable Deputy Vega. He stopped himself from killing Vega, although the episode’s final bar encounter made it clear that their conflict remains unresolved. What to expect from Episode 7 Episode 7 will likely push Sugar and Vega toward a direct confrontation. Vega’s threat against Ji Moon gives Sugar another reason to act, while the evidence surrounding Operation: Fire Sale can expose everyone involved in the scheme. The episode should also bring Sugar’s new investigation closer to a resolution before the finale. However, his search for Djen and his unfinished business with Henry remain part of the larger story that began in Season 1. The first season ended after Sugar rescued Olivia Siegel and discovered that Henry, another member of his alien group, had information about Djen’s disappearance. Sugar chose to remain on Earth after the other Polyglots prepared to leave, setting up his continuing search in Season 2. “Sugar” Season 2, Episode 7 streams July 31 on Apple TV. What do you think Sugar will do when he faces Vega again? Let us know in the comments.

Firefox Nightly: Backup for a Rainy Day – These Weeks in Firefox: Issue 202

Sat, 25 Jul 2026 08:37:35 +0200

Highlights

The profile backup mechanism has been enabled by default for all desktop platforms in Nightly, as well as Beta! The current plan is to have this ride out to Firefox 151 for Windows, macOS and Linux on May 18th!
- This feature, when enabled, will create a copy of your profile data in the background and store it in a single file on your file system that you can restore from.
- You will be able to manage this feature in Settings under Sync (for now)
- You can read more about the feature here
As followups to the recent addition to the WebExtension tabs API to support the new SplitView tabs feature, tabs.group() and tabs.ungroup() have been fixed to work correctly with split view tabs, and fixed split views being prepended instead of appended to tab groups when adopted into a new window – Bug 2029099 / Bug 2029534
Adaptive autofill has been enabled on Nightly.
- Previously, autofill only completed domains (e.g. typing red autofilled reddit.com). Now it can also complete full URLs for pages you visit often (e.g. red → reddit.com/r/firefox), learning from what you actually click in the address bar. If a suggestion isn’t helpful, you can now dismiss it so autofill learns what not to show you too.
  - If you run into issues or have feedback, you can file a bug here!
Markus Stange [:mstange] implemented dynamic toolbar on top in RDM (#1978145), but also implemented some static skeleton UI so it’s closer to what we actually have in Firefox for Android
- dynamic toolbar is behind a pref: devtools.responsive.dynamicToolbar.enabled
- it can be put on top by setting devtools.responsive.dynamicToolbar.onTop, otherwise it’s at the bottom

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
aoia7rz7l
Chukwuka Rosemary
DrSeed
Frédéric Wang Nélar
japandi
John Iweh
jonathancabera
Josh Aas
Keji Bakare
kofoworola shonuyi
konyhéa
liz
Mathew Hodson
Okhuomon Ajayi
Oluwatobi
ROSHAAN
Sam Johnson

New contributors (🌟 = first patch)

Project Updates

Add-ons / Web Extensions

Addon Manager & about:addons

In preparation for the Project Nova restyling of the about:addons page, we have refactored about:addons into separate per-component ES modules, splitting the monolithic aboutaddons.js and aboutaddons.html into 16 dedicated component files under components/ (with no behavior or UI changes) – Bug 2032014
- NOTE: if you have working on patches with changes to about:addons internals it is very likely you’ll need to rebase and solve merge conflicts hit on top of this refactoring, the internals are still largely the same as before but don’t hesitate to reach out to the Addons team if you have doubts / questions or need help to figure out how to adapt your patch of top of these changes

WebExtensions Framework

Fixed exportFunction to preserve the constructibility of the wrapped function instead of unconditionally making all exported functions implicitly as constructors – Bug 2033173
- Thanks to Gregory Pappas for contributing this improvement to the Content Scripts’ Xray Wrappers helpers!
Fixed a Firefox 151 regression where extension content scripts accessing location.ancestorOrigins caused subsequent page script reads of the same property to fail with “Permission denied”, breaking sites like Gmail – Bug 2034329
- Thanks to Simon Farre for promptly investigating and fixing this recent regression!

WebExtension APIs

Updated sessions.getRecentlyClosed() to remove the hardcoded cap when maxResults is omitted – Bug 1392125
- Shoutout to Amine Zroual for contributing this enhancement to the sessions WebExtensions API!

DevTools

Artem Manushenkov fixed an issue where autosuggestion popup was removing overridden indicators from properties in the Inspector (#1983408)
Andrea Marchesini [:baku] fix DevTools cookie header serialization for long cookies, which could lead to cookies not being visible in Netmonitor (#2031299)
Julian Descottes [:jdescottes] fixed a toolbox crash that was happening we couldn’t find a localization file (e.g. when using a language pack on Nightly) (#2028930)
Nicolas Chevobbe [:nchevobbe] improved @container tooltip so it show the value of variables used in style()(#2030239), has enough contrast in dark mode (#2033782) and contains a link to select the container (#2031688)
Hubert Boma Manilla (:bomsy) is making good progress on migrating the Console to CodeMirror 6 (#2032758, #2026569)

Fluent

We’re now at over 72% of our strings being Fluent! Got a component still using .properties? Convert when you can!

Migration Improvements

Thanks to dao for fixing a recent alignment issue in the migration wizard dropdown
Thanks to volunteer contributor Anthony Mclamb for his patch that disables the legacy EdgeHTML Edge migrator! Once that finishes rolling out, presuming no surprises, we’ll go ahead and remove the migrator entirely.

New Tab Page

Nova for New Tab has ridden the trains to Beta! It will be enabled by default, globally, when Firefox 151 goes out to release on May 19th
- It’s possible that we’ll do a train-hop coupled with an experiment to enable HNT Nova for a few clients a bit earlier.
Maxx Crawford enabled Nova designs for New Tab, rolling out the updated layout, widgets, and customization panel behind HNT Nova flags.
Maxx Crawford fixed the Nova content feed to render the intended four‑column layout by correcting CSS grid breakpoints.
Maxx Crawford resolved a first‑load failure in the Weather widget by fixing init order and fetch timing, eliminating the “Oops” error.
Maxx Crawford synchronized the Weather toggle between about:preferences#home and the panel via the shared showWeather pref to prevent desync.
Maxx Crawford updated Nova grid focus order to align tab flow with visual order for keyboard users.
Maxx Crawford fixed critical UI issues in Lists and Timer widgets covering overflow, controls, and layout stability.
Maxx Crawford guarded document.dir access in Nova render paths to avoid startup cache worker errors and improve startup stability.
Rolf added a new normalization method for the inferred interest vector to stabilize topic relevance across sessions.
Rolf prevented unnecessary content refreshes during Pocket New Tab experiments, reducing jank and bandwidth.
Sameeksha defined the Customize button’s expanded/collapsed state programmatically using aria-expanded for better a11y.
liz clarified follow/unfollow/blocked button names with topic context so screen readers announce clear actions.
Vector marked the Delete from History control as opening a dialog via aria-haspopup=dialog for assistive tech.
Scott Downe fixed a regression that flipped the Wallpapers pref off, restoring user selections.
Irene Ni corrected privacy link color and focus styles for contrast and keyboard visibility.
Reem Hamoui added a wallpaper toggle reset in the Nova customization panel so users can quickly restore default wallpapers without extra steps.
Reem Hamoui fixed the Customize pencil button to match the Nova spec, aligning placement and iconography for visual consistency.
Dre updated the ‘Fresh new’ wallpapers copy to a clearer, localized message for better comprehension.
Irene Ni fixed Nova privacy link color and focus styles to meet contrast and focus ring guidelines, improving accessibility on New Tab.
Irene Ni adjusted Sponsored tile character limits to prevent truncation/overflow, yielding cleaner titles across grid and wide tiles.
Scott Downe fixed a regression that flipped the Wallpapers user pref to false, restoring wallpapers for affected users and preventing unintended disablement.
Reem Hamoui hooked the wallpaper check into the new toggle logic so the Customization Panel accurately reflects wallpaper availability and state.
Irene Ni landed Nova UI updates for the Daily Briefing 3-pack card, improving spacing, type scale, and tap targets.
Reem Hamoui added a wallpaper toggle reset in the Nova customization panel so users can quickly restore default wallpapers without extra steps.
Reem Hamoui fixed the Customize pencil button to match the Nova spec, aligning placement and iconography for visual consistency.
Dre updated the ‘Fresh new’ wallpapers copy to a clearer, localized message for better comprehension.
Irene Ni fixed Nova privacy link color and focus styles to meet contrast and focus ring guidelines, improving accessibility on New Tab.
Irene Ni adjusted Sponsored tile character limits to prevent truncation/overflow, yielding cleaner titles across grid and wide tiles.
Scott Downe fixed a regression that flipped the Wallpapers user pref to false, restoring wallpapers for affected users and preventing unintended disablement.
Reem Hamoui hooked the wallpaper check into the new toggle logic so the Customization Panel accurately reflects wallpaper availability and state.
Irene Ni landed Nova UI updates for the Daily Briefing 3-pack card, improving spacing, type scale, and tap targets.

Search and Urlbar

Marco has fixed a couple of issues with the places databases to try and improve stability. This should help with avoiding users losing bookmarks or favicons.
Work continues on the new separate search bar to improve the functionality, e.g. allowing middle click to perform a search in a new tab, avoiding performing a search when adding a search engine.
Work also continues on the new Nova layouts.

Smart Window

uplifted 10 bugs to 150.0.1 dot release addressing initial user feedback from diary study and Connect
- jump to bottom of conversation 2028692
- stop streaming button 2029204
- back/forward navigation from assistant 2029229
- dark mode for various chips 2024499
search engine switching from smart bar 2021973
Nova styling within smart window 2026794

Storybook/Reusable Components/Acorn Design System

Dustin converted moz-breadcrumb-group variables into JSON design tokens Bug 2029181 – Convert moz-breadcrumb-group variables into JSON design tokens
Dustin converted moz-box-* variables into JSON design tokens Bug 2029180 – Convert moz-box-* variables into JSON design tokens
Dustin converted moz-promo variables to JSON design tokens Bug 2029190 – Convert moz-promo variables into JSON design tokens
Dustin converted moz-reorderable-list variables to JSON design tokens Bug 2029191 – Convert moz-reorderable-list variables into JSON design tokens
Dustin converted moz-visual-picker variables to JSON design tokens Bug 2029193 – Convert moz-visual-picker-item variables into JSON design tokens
Dustin updated browser-shared.css so it passes use-design-tokens Bug 2022985 – Update browser-shared.css so it passes use-design-tokens
Dustin updated popup.css so it passes use-design-tokens Bug 2022979 – Update popup.css so it passes use-design-tokens
Jon added opacity tokens and added opacity to use-design-tokens stylelint rule Bug 1955325 – Create opacity tokens
Jon converted toolbar design tokens to JSON Bug 2017970 – Convert toolbar design tokens to json
Anna fixed moz-select with panel-list drop-down size inconsistency Bug 2032365 – Applications Action drop-down menus sometimes have a different size when opened
Anna fixed issue with the disabled state of moz-radio component Bug 2027123 – moz-radio disabled state cannot be changed while the moz-radio-group is disabled
Anna updated moz-button and moz-box-button components to prevent label corruption when accesskeys are present and the label changes. Bug 2022326 – moz-button with accesskey label becomes corrupted when l10nId updates dynamically

UX Fundamentals

The error pages shown when a server sends back an invalid response header or an unsupported content encoding now display accurate, context-specific messages. The invalid response header page also gained a helpful list of next steps. – 2027209
In progress: The error page illustrations are being replaced with new artwork, and the system now supports per-illustration size configuration, giving each image the ability to define its own appropriate dimensions. – 2031837

Settings Redesign

Tim converted settings related to Accessibility page to config-based pane Bug 1968116 – Convert settings related to Accessibility page to config-based settings
Benjamin converted Privacy & Security page to the config-based pane Bug 1968112 – Convert settings related to Privacy & Security page to config-based settings
Finn integrated Firefox Labs page into setting-pane config Bug 2021047 – Integrate Firefox Labs page into setting-pane config
Anna converted Firefox Updates section to config-based prefs Bug 1990961 – Convert Firefox Updates section to config-based prefs
Mark Kennedy added moz-promo, that is welcoming users to the redesigned settings Bug 2015093 – Add a moz-promo to welcome users to the redesign
Anna added possibility to search for actions in the redesigned “Applications” section Bug 2020370 – It’s no longer possible to search for actions in the new “Applications” section
Anna fixed the Settings navbar layout breakage

Firefox Nightly: Giving You More Control – These Weeks in Firefox: Issue 204

Sat, 25 Jul 2026 08:37:31 +0200

Highlights

Maxx Crawford added a pref to hide the New Tab logo so users can opt out of branding without altering page layout or resorting to CSS overrides.
Harshit enabled video overlay detection in Nightly 153, allowing you to use the context menu to control videos on more pages! We plan on letting this ride out in Firefox 153.
- You can try it out on this Instagram reel in Nightly

A note to WebExtension authors – as part of a planned deprecation announced last month, executeScript and insertCSS are now restricted from moz-extension pages starting in Firefox 152 – Bug 2015559
Nicolas Chevobbe [:nchevobbe] added support and debugging for modern attr()(which is enabled on Nightly) (#2014751)

Friends of the Firefox team

Resolved bugs (excluding employees)

Script to find new contributors from bug list

Volunteers that fixed more than one bug

Sam Johnson
Sebastian Zartner [:sebo]

New contributors (🌟 = first patch)

Immaculate Atim: Switch to using an array instead of an object string for browser.backup.enabled_on.profiles
liz: Screenshots overlay visible on both splitview browsers
🌟 Rahman Mahmutović [:r_m]: Can’t change content in box model in inspector for box-sizing:border-box elements
Takeru Mitsumori: Fix typo in ID name about-translations-swap-langauges-icon in about-translations.html
🌟 Freya Arbjerg [:freyacodes]: Blackboxed columns are ignored
tom.passarelli: tab-preview-panel emits unpaired popupshown/popuphidden events, breaking sidebar autohide

Project Updates

Add-ons / Web Extensions

Addon Manager & about:addons

As part of the work for the Project Nova about:addons page restyling, the about:addons sidebar has been migrated to the moz-page-nav and moz-page-nav-button reusable components, improving accessibility and visual consistency with the Firefox Desktop about:settings page – Bug 1881767

WebExtensions Framework

Implemented WebExtensions negative permissions infrastructure, providing the foundations for enterprise policy “blocked host permissions” features – Bug 1745823
Restricted host permission changes for MV3 extensions force-installed via enterprise policy (matching similar behaviors provided by Chrome enterprise policy behaviors) – Bug 1904054
- Thanks to Mike Kaply for the implementation of this enterprise policy enforcement feature.

WebExtension APIs

Fixed handling of as an API permission in Manifest V3, ensuring the permission is correctly initialized on extension install – Bug 1758306

DevTools

Rahman Mahmutović [:r_m] made it possible to edit width/height in the box model section of the Layout panel (#1717176)
Sebastian Zartner [:sebo] improved toggling tools driving in-page highlighters (e.g. the Measuring) (#1262773)
Sebastian Zartner [:sebo] added a setting to control visibility of HTML comments in the markup view (#1455294)
Freya Arbjerg [:freyacodes] fixed an issue in script blackboxing (#2036767)
Alexandre Poirot [:ochameau] replaced custom preference to log RDP messages with MOZ_LOG (#1622857)
Alexandre Poirot [:ochameau] fixed retrieval of garbage collected script text content (#1758454)

WebDriver

Sameem updated the “Take Element Screenshot” command from WebDriver Classic to crop screenshots of elements which exceed the viewport. This aligns with the specification and avoids errors when attempting to capture huge elements.
Alexandra Borovova updated the events for new top-level browsing contexts: we will not send anymore “browsingContext.domContentLoaded” and “browsingContext.load” events for them, instead the “browsingContext.contextCreated” event will be sent when a tab is ready to be used. This is required to align with the expected per-spec behavior.
Henrik Skupin landed a patch allowing geckodriver to gracefully shut down Firefox when geckodriver itself is terminated.
Hiroyuki Ikezoe disabled Firefox’s “scroll axis lock” feature so WebDriver actions for wheel input devices can scroll in arbitrary directions when using pan gestures.

Lint, Docs and Workflow

Added a rule to prevent new uses of Preferences.sys.mjs.
The browser environment globals within ESLint have now been updated. These include Sanitizer, VideoFrame and a few other new ones.
Temporal, and some other definitions have been added to TypeScript.

New Tab Page

Much has happened in the last 2 weeks! Here’s a full bug list, and here are some highlights.
Dre fixed the List widget that was creating a new list too eagerly on the New Tab Page (2033592) — prevents accidental list creation and improves the Lists UI reliability.
Maxx Crawford fixed Weather widget small card layout issues with opt-in location options and an error message displayed, resolving card overflow and removing the spurious opt-in error so users see a compact Weather card and correct location prompts on New Tab.
Reem Hamoui added key dates state to the Sports widget, enabling the Sports card to surface event deadlines/key-date highlights on New Tab so sports users see timely date info.
Scott Downe added a manage widgets option to the New Tab nova widgets context menu, giving users a direct context-menu entry to open the widget management flow from any widget with Nova enabled.
Scott Downe added a reusable Newtab widget base component to centralize lifecycle, focus/keyboard handling, DOM templates, and telemetry hooks, reducing duplication and making widget behavior more consistent; see Newtab widget base component.
Dre converted per-widget expansion handling to a shared widget expansion handler to unify expand/collapse state management and prevent widgets from incorrectly retaining or losing expanded state; see Convert widget expansion handling to shared widget expansion.
Nina Pypchenko [:nina-py] updated the Sports widget to populate the “follow teams” state from the /teams endpoint, so follow/unfollow toggles now reflect server-side subscriptions and reduce incorrect follow states.
Scott Downe moved widget menu items within New Tab widgets to standardize menu ordering and action grouping, so users find Add/Remove/Configure entries in expected positions across platforms.
Dre fixed a World Clock city search bug for the word clocks widget, restoring expected search filtering/matching so city lookups return correct results.
Scott Downe fixed an issue where the New Tab small weather widget size change didn’t always apply by correcting the widget size update path (JS/CSS layout interactions), improving consistent rendering for small-tile weather across responsive breakpoints and platforms; see Newtab small weather widget size change doesn’t always work.
Nina Pypchenko [:nina-py] added a group stage section to match highlights in the sports widget on New Tab so users now see stage-aware grouping and stage labels on match highlight cards, making tournament context (group vs knockout) visible while browsing highlights.
Dre fixed the small world clock widget not expanding to large while editing clocks so users can enter edit mode and expand the widget as expected; the change wires the edit-mode resize handler to update widget size/class during edits.
Maxx Crawford added WCW OMC message strings so World Cup widget messaging flows on New Tab now display the correct copy (localized where available) instead of falling back to missing-text behavior.
Reem Hamoui added a “View all” button and a list view for the results tab at medium widget size so Sports widget users on medium New Tab tiles can expand results and scroll full lists without resizing the widget.
Maxx Crawford added WCW “Watch Live” stream strings to the Sports widget strings bundle so the widget can surface a localized “Watch Live” CTA for applicable events.
Dre restored VoiceOver reachability for Edit/Remove in World Clock on macOS so macOS VoiceOver users can now focus and activate clock Edit/Remove controls thanks to accessibility role/label and focus-order fixes.
Maxx Crawford removed the persistent browser logo when all new-tab features (Top Sites, widgets, content feed) are disabled by adding a conditional render guard in the New Tab component, preventing an orphaned logo (2041033).
Mike Conley added New Tab jest tests to the node tests Tier 1 CI job Run newtab jest tests as part of node tests Tier 1 job to catch regressions earlier in CI
Irene Ni shipped multiple visual fixes for the Sports widget Sports widget – various visual fixes (spacing, truncation, icon alignment, clipping) to improve readability and layout on constrained viewports.

Picture-in-Picture

kpatenio adjusted our YouTube site specific wrapper so that the URL bar toggle appears more reliably, especially when selecting videos from the YouTube search page.
Thanks to Sylvestre for patching some bugs to prevent some spurious console errors!
Niklas fixed captions on autopip videos failing to sync with the origin videos.

Performance Tools (aka Firefox Profiler)

Firefox Profiler now has a CLI! We also added a profiler-analysis skill to the Firefox codebase. Once you capture a performance profile, you can ask Claude or an AI to analyze it by providing a link or local path. You can use it to analyze a performance regression or debug an issue if you have a profile at hand.
- https://www.npmjs.com/package/@firefox-devtools/profiler-cli
- You can install it with npm install -g @firefox-devtools/profiler-cli@latest

Search and Urlbar

Nova UI refresh

Drew and Daisuke continued working on reorganizing styles and updating the urlbar for Nova.
2019154, 2019152, 2041501, 2040532

Suggest

Drew landed several Suggest improvements: realtime suggestions colors, sports suggestions received World Cup tweaks, and online Suggest via OHTTP was enabled for eligible users in Firefox 153.
2040561, 2039753, 2035614, 2038843

Adaptive autofill

James fixed soft-block counting to track autofill dismisses, rather than consecutive backspaces on the same autofill, and added telemetry to measure URLs reintegration after blocking.
2040819, 2037177

Quick actions

Dharma created a new Firefox Labs quick action, fixed the Update action button, and re-enabled ScotchBonnet in some tests that were not updated yet.
Caleb added Calculator support for certain unicode operators.
2023169, 1928635, 1923383, 2033861

Multi Context Address Bar

Moritz continued refactoring the urlbar code: converted some of the js modules to not be system modules, fixed dynamic results templates, incorrect reuse of result rows, and keyboard shortcuts on the unified search button panel.
2039297, 2036095, 2039844, 2037933, 2030050

Other

Marco, Drew and Daisuke fixed several intermittent test failures.
2038510, 2023908, 2011584, 1938142, 1971091

Search

Mark removed old WebExtension-based search engines from the source tree, removed loading of search add-ons from resource://search-extensions/.
Caleb fixed multiple documentation issues and added a test covering searches from a private window.
1904613, 2035878, 2037942, 2033545, 2005724

Places

Marco removed some unnecessary database transactions, fixed the bookmarks panel folder dropdown on Windows, and resolved several intermittent test failures.
Thanks to Sam Johnson who fixed the bookmark edit panel showing “mobile” instead of “Mobile Bookmarks”.
2039534, 1505800, 2008829, 2029541, 2035084

Mozilla Security Blog: Improving Transparency and Assurance in the Web PKI: Mozilla Root Store Policy v3.1

Sat, 25 Jul 2026 08:37:23 +0200

Mozilla remains committed to maintaining a secure, trustworthy, and transparent Web PKI. Today we are announcing the publication of Mozilla Root Store Policy (MRSP) version 3.1, effective July 1, 2026.

While previous policy updates focused heavily on certificate revocation, automation, and operational resilience, MRSP v3.1 focuses on a different challenge: ensuring that Certification Authority (CA) operations are sufficiently transparent, understandable, and auditable.

Trust in the Web PKI depends not only on technical requirements, but also on the ability of Mozilla, auditors, and the broader community to understand how CA systems are designed, operated, and assessed. MRSP v3.1 introduces new requirements intended to improve the quality of CA documentation and strengthen independent assurance of the design and effectiveness of controls that protect CA systems.

Improving CP/CPS Documentation

Certification Practice Statements (CPSes) and combined Certificate Policy / Certification Practice Statement documents (CP/CPSes) are among the most important public documents published by a CA. They describe how a CA conducts its operations and meets industry requirements.

Over the years, we have seen significant variation in the quality, structure, and level of detail provided in CP/CPS documentation. Some documents provide extensive implementation detail, while others rely heavily on incorporation by reference or provide only high-level descriptions of CA practices.

The revised policy will continue to require conformance with RFC 3647, as modified by applicable CA/Browser Forum requirements. Improvements to section 3.3 in the MRSP will establish clearer expectations regarding the content and quality of CP/CPS documentation. The new requirements emphasize that documentation must be explicit, bounded, auditable, and sufficiently detailed to describe the CA operator’s certificate issuance and management activities, while also establishing requirements for version control, accessibility, and ongoing maintenance. The objective is to ensure that a technically competent reviewer will be better-able to determine what commitments the CA has made, how those commitments are implemented, and whether the documented practices support technical, operational, and performance oversight.

Mozilla believes that these new CP/CPS requirements will improve transparency, reduce misunderstandings, support more effective audits, and help reduce the risk of certificate misissuance by ensuring that operational practices are documented accurately, consistently, and in sufficient detail to permit meaningful review.

Introducing Detailed Controls Reports

A second major enhancement in MRSP v3.1 is the introduction of Detailed Controls Reports (DCRs). Traditional WebTrust and ETSI audit reports provide valuable independent assurance regarding compliance with established criteria. However, they generally provide only limited visibility into the specific controls, testing procedures, and operational environments that support those conclusions.

Beginning with audit periods starting on or after July 1, 2027, CA operators with root certificates enabled for TLS website authentication will be required to obtain a DCR. The purpose of the DCR is to provide CA management, auditors, and Mozilla with greater visibility into the controls, testing, and operating effectiveness of CA systems that support compliance with the CA/Browser Forum’s TLS Baseline Requirements and Network and Certificate System Security Requirements. Mozilla generally expects to review DCRs only on an as-needed basis, such as during compliance reviews, incident investigations, root inclusion evaluations, or other oversight activities.

A DCR must include:

The scope and boundaries of the audited CA systems;
Applicable audit criteria;
Controls implemented by the CA;
The auditor’s testing procedures;
Results of control testing; and
Information regarding control exceptions or deficiencies.

Mozilla expects that DCRs will complement existing audit reports and strengthen transparency and assurance by providing additional detail regarding system boundaries, control implementation, testing procedures, and control effectiveness that is not typically available in traditional audit reports. Effective compliance requires more than documented policies and successful audits; it also requires management understanding, oversight, and engagement. By providing greater visibility into CA systems, controls, testing activities, and operational risks, DCRs can help reinforce a strong tone at the top regarding compliance expectations, support informed decision-making and resource allocation, enable earlier identification of weaknesses, and promote a culture of continuous improvement. The intent is not to replace existing audit reports, but to provide additional information that supports effective governance, oversight, and informed trust decisions.

Additional Clarifications and Improvements

MRSP v3.1 also includes several targeted clarifications and refinements:

aligns Mozilla’s mass revocation planning requirements with the corresponding CA/Browser Forum Baseline Requirements, helping ensure consistency across compliance frameworks;
clarifies audit expectations for root inclusion requests, including requirements relating to audit continuity and root key generation ceremonies;
requires root CA key pairs submitted for inclusion to have been generated within the previous five years, helping ensure that newly included roots are based on contemporary cryptographic practices and controls; and
clarifies expectations when ownership or operational control of a CA changes, helping ensure that Mozilla receives timely notice and can evaluate the impact of acquisitions or organizational changes on continued compliance.

Looking Forward

Mozilla recognizes that these changes will require preparation by CA operators, auditors, and other ecosystem participants. To support implementation, Mozilla is publishing accompanying wiki guidance regarding both CP/CPS Documentation and Detailed Controls Reports.

As with previous policy updates, these changes were informed by discussions with CA operators, auditors, and members of the Web PKI community. We appreciate the feedback received during the review process and look forward to continued collaboration as the ecosystem evolves.

Mozilla has a longstanding focus on building confidence in the Web PKI through transparency, accountability, and continuous improvement. By requiring higher-quality CP/CPS documentation and strengthening independent assurance, MRSP v3.1 advances Mozilla’s commitment to protecting its users and maintaining their trust in the systems that help secure the web.

The post Improving Transparency and Assurance in the Web PKI: Mozilla Root Store Policy v3.1 appeared first on Mozilla Security Blog.

China's New Huawei Ascend 950PR Just Destroyed NVIDIA's Future in AI Industry!

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

Author: Evolving AI - Bewertung: 179x - Views:7273

Huawei may have just become NVIDIA’s biggest problem in China.

In this video, we break down Huawei’s new Ascend 950PR AI chip, why it matters for the global semiconductor war, and how U.S. export restrictions may have accelerated China’s push toward technological independence. The Ascend 950PR is designed mainly for AI inference and is built by SMIC using advanced DUV multi-patterning. Huawei is also attacking NVIDIA’s biggest advantages beyond hardware by building a CUDA compatibility layer through CANN and scaling thousands of Ascend NPUs together inside the Atlas 950 SuperPod using UnifiedBus interconnect technology. We also look at reported demand from ByteDance, Alibaba Cloud, and Tencent, the role of DeepSeek models optimized for Ascend hardware, and why NVIDIA could lose major market share inside China even without Huawei beating its most advanced chips in every benchmark. This is bigger than one AI chip. China is building a parallel AI ecosystem across chips, software, networking, cloud infrastructure, and AI models — and Huawei is quickly becoming the center of it.

#Huawei #NVIDIA #AIChips #Ascend950PR #ChinaTech #Semiconductors #ArtificialIntelligence

MIT's 1000TB/s Photonic Chip Finally Puts an End to NVIDIA's AI Domination!

Sat, 25 Jul 2026 08:35:34 +0200

Author: Evolving AI - Bewertung: 215x - Views:5447

MIT engineers are building a chip reaching one petabit per second. See how this hardware processes data faster than any current consumer tech. This video examines the technical details behind the new MIT processor chip designed to push data limits. We explore how researchers are utilizing interferometer technology to achieve speeds of a thousand terabits on a surface thinner than a human hair. This breakdown is for engineers, students, and tech enthusiasts interested in the future of high-speed hardware. By analyzing the electronic components and the specific measurement diagrams, you will better understand the engineering hurdles involved in reaching a petabit per second. You will see how this data processing speed milestone compares to existing silicon-based architectures and why this specific design is capable of such massive throughput.

Subscribe for weekly engineering breakdowns, and comment below if you want to see a deep dive on how interferometers are used in modern computing.

VentureBeat Research: Where enterprise AI agent governance hasn't caught up

Fri, 24 Jul 2026 22:51:31 +0200

Enterprises deployed AI agents ahead of the controls needed to manage them — and they did it knowingly. That is the central finding across the five parallel surveys VentureBeat Research fielded in June, spanning every layer of the agentic stack. Now those enterprises are retrofitting to catch up with their own standards, and they are budgeting for it: In each of the five control layers we measured, 57 to 68% of enterprises plan to switch vendors or add new ones within 12 months, and roughly a third, depending on the layer, plan to move within the quarter.

VentureBeat Research measured the five controls an enterprise has to build before it can trust an agent: identity, evaluation, cost telemetry, the context layer, and orchestration. Identity governs which agent is allowed to do what, under whose credentials. Evaluation determines whether the agent's work is any good. Cost telemetry tracks what each agent costs to run. The context layer supplies the business data and definitions agents draw on when they answer. And the orchestration control plane coordinates multi-step agent work. Each of our five reports measures one of those controls.

Most deployed "agents" are chatbots wearing the label. Seventy-one percent of enterprises said a quarter or fewer of their deployed "agents" can complete multi-step work on their own; only 10% said true agents are the majority of what they run. These respondents are positioned to know: 81% recommend or decide AI purchases at their companies. A single-prompt chatbot with a human reading every answer needs none of the controls the other four reports measure. A true multi-step agent needs all of them — and most enterprises can't say which one they've deployed. (Full findings: Agentic Orchestration report.)

Autonomy is outrunning trust in the evaluations that gate it. Two-thirds of enterprises either already allow an agent to push a code or system change to production on automated evaluation results alone, with no human review, or are actively engineering toward that within 12 months. Only 5% fully trust the evaluations that would make that call — and half of enterprises shipped an agent that passed internal evaluations and then caused a customer-facing failure in the past year. Before removing human review from any workflow, test evaluations against production outcomes rather than internal benchmarks. (Full findings: Agent Reliability & Evals report.)

Companies that let agents share credentials get hit more often. Sixty-nine percent of companies let at least some of their agents share credentials — multiple agents operating under one API key or service account. Organizations that allow credential sharing anywhere experienced a security incident or near-miss at a 63.5% rate (47 of 74), against 40.9% (nine of 22) at companies where every agent has its own scoped identity. The fix is scoped identity for every agent, starting with the ones that touch production systems. (Full findings: Agentic Security & Identity report.)

The most expensive hardware in the building runs at half capacity or less. More than eight in 10 enterprises that run their own GPUs reported utilization of 50% or less, and only 44% rigorously track what their AI compute actually costs and returns. The number worth chasing first isn't more GPUs — it's the utilization and per-workload cost of the ones already running. (Full findings: AI Infrastructure & Compute report.)

Agents answer confidently from data nobody governs. Fifty-seven percent of enterprises traced a confident, wrong agent answer in the past six months to their own missing or inconsistent business context — wrong metrics, stale definitions, absent documents — and most saw it happen more than once. Governing the definitions agents answer from — metrics and entities first — has to come before scaling the agents that depend on them. (Full findings: Context Layers / RAG report.)

No layer has an entrenched incumbent: The defaults today are the built-in tools that ship with the big AI platforms enterprises already use. Switching intent runs highest in orchestration itself, where 68% plan to adopt, add, or replace platforms within 12 months and 34% within the quarter. Our surveys did not ask which direction that money moves — toward the platforms' built-in tools or toward the specialists challenging them — and that open question is the next four quarters of this market.

About this research

VentureBeat Research fielded five parallel surveys in June 2026 under its VB Pulse program: Agentic Orchestration (101 respondents), Agent Reliability & Evals (157), Agentic Security & Identity (107), AI Infrastructure & Compute (107), and Context Layers / RAG (101) — 573 qualified respondents in total, all at organizations with 100 or more employees. Samples are self-selected, and some findings should be read directionally; each report carries its full methodology note. What the pattern supports more strongly than any single percentage is the direction: every survey, independently, points the same way. VentureBeat produces both this research and VB Transform, the conference where these reports debuted.

javascript: v1.0.0

Fri, 24 Jul 2026 22:21:54 +0200

1.0.0 (2026-07-24)

Stable release. The package surface has been stable for a long time; 1.0.0 makes that explicit.

⚠ BREAKING CHANGES

voice: silenceTailBytes removed from ElevenLabsAgentAdapterOptions — no longer needed after the ElevenLabs SDK migration; remove from any adapter config.
voice: ELEVENLABS_CONVAI_URL_TEMPLATE constant removed from public exports — construct the URL directly or read it from the SDK.
voice: .url getter removed from public exports.

Features

graduate to 1.0.0 (6379130)
1.0 release prep, stable classifiers and unstuck langwatch pins (#842) (616c506)

Code Refactoring

voice: #707 follow-up cleanup bundle (#716) (e018d76)

python: v1.0.0

Fri, 24 Jul 2026 22:21:53 +0200

1.0.0 (2026-07-24)

Stable release. The package surface has been stable for a long time; 1.0.0 makes that explicit. The langwatch dependency floor moves to >=1.0.0,<2 (older caps resolved a June 2025 langwatch on every install).

Features

graduate to 1.0.0 (24feea2)
1.0 release prep, stable classifiers and unstuck langwatch pins (#842) (616c506)

Bug Fixes

judge: protect unbounded judge transcript for non-litellm agents (#837) (6604334)
voice: bring recv_audio's keepalive hard-ceiling to Python (JS parity) (#832) (d61027c)

Code Refactoring

voice: #707 follow-up cleanup bundle (#716) (e018d76)

Anduril reportedly in talks to raise funding at $100B valuation, more than 3x last year’s mark

Fri, 24 Jul 2026 19:50:40 +0200

Anduril is said to be raising a new round of funding that may push its valuation up to about $100 billion, per Reuters.

Cisco, AMD partner to bring enterprise-level security, visibility to Ryzen AI Halo systems

Fri, 24 Jul 2026 19:18:26 +0200

Cisco and AMD have expanded their partnership with a new package of hardware and security software that’s designed to help enterprise customers protect, deploy, and manage distributed AI resources.

During AMD’s Advancing AI event this week, Cisco’s president and chief product officer Jeetu Patel took to the stage during AMD CEO Lisa Su’s keynote to talk about how AI inference will be widely distributed and will require an architectural stack of software and tools that Cisco and AMD are partnering to develop.

The joint architecture combines AMD’s compact, high-performance Ryzen AI Halo hardware and a variety of Cisco networking, observability, governance, and security technologies. “AMD provides the deskside/local AI platform. At the foundation is AMD Ryzen AI Halo hardware, an isolated agent sandbox and the services needed for local-first inferencing, including model routing and token limits via AMD’s Semantic Router and local inference on Lemonade,” wrote Cisco’s Yash Sheth, senior director, engineering and research, in a blog post about the new package.

Ryzen AI Halo (pictured below) is designed to support local AI inference on an AI PC using its CPU, GPU, and XDNA neural processing unit (NPU), according to AMD. A resilient AI platform should continue delivering useful AI services even when connectivity is limited, models need to change, or workloads shift, AMD stated.

width="1024" height="576" sizes="auto, (max-width: 1024px) 100vw, 1024px">

AMD

Cisco then wraps that platform in a secure harness that includes its Splunk Agent Observability plus Splunk Infrastructure Monitoring to provide full-stack observability, tracking agent behavior, tokenomics and compute operation, according to Sheth.

Cisco also brings its AI Defense for model and agent security; DefenseClaw for security policy enforcement, so guardrails are enforced directly on-device, within the agent harness; and Cisco Cloud Control offering a single pane of glass for unified policy and control, Sheth stated.

“To make deskside and local AI computing work at enterprise scale, every AI node must be treated as a secure, managed node in the enterprise network,” Sheth wrote.

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

As agentic AI moves from experimentation to real enterprise workflows, organizations need more than powerful endpoints. AI agents can run continuously and act on enterprise data, but create new requirements for network infrastructure, tokenomics, agent behavior, and security, according to a statement from AMD.

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

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

A few other interesting statistics and trends cited in AMD CEO Su’s keynote include:

AI adoption is accelerating across all industries, with agentic AI driving a surge in compute demand and shifting workloads from training to inference, which accounts for 60% of global AI compute capacity in 2026.
AI is moving beyond the cloud, with edge and personal devices becoming critical for real-time, distributed intelligence.
The AI accelerator market is projected to reach $1.4 trillion by 2030, nearly tripling previous forecasts, with GPUs expected to dominate but CPUs gaining new growth vectors due to agentic AI.
Server CPU market is forecasted to grow over 50% to $200 billion by 2030, fueled by rapid agentic AI adoption and the need for massive CPU infrastructure.

Microsoft's open-weight AI push is so obviously an Azure play it hurts

Fri, 24 Jul 2026 18:09:44 +0200

Microsoft, along with Meta, Nvidia, and more than 20 other companies, is pushing for open-weight AI models in an open letter. The strategic logic is simple: the more models running on Azure, the less Microsoft depends on expensive OpenAI and Anthropic models. The company is also swapping external models in products like Copilot for its in-house MAI family, which performs significantly worse in independent benchmarks.

The article Microsoft's open-weight AI push is so obviously an Azure play it hurts appeared first on The Decoder.

De Vlieger: The Fedora 45 sausage factory

Fri, 24 Jul 2026 17:15:45 +0200

Fedora contributor Simon de Vlieger has published a blog post with a walkthrough of how the project turns source code and packages into the final release that users install on their systems.

It follows the a package from a packager's git push to a composed release: ISOs, cloud images, container images, and OSTree deployments.

The walkthrough describes how the Fedora 'sausage' is created as of Fedora 45, things change all the time; I hope to have time to update this document every cycle or every few cycles of Fedora releases so there's both history and people can find up to date information.

Astronomers May Have Discovered First Moon Outside Our Solar System

Fri, 24 Jul 2026 17:07:19 +0200

Astronomers studying the star system CD-35 2722 may have found the first known moon-like object outside our solar system. The classification is unusually tricky, however, because it orbits a brown dwarf rather than a planet, making it clearly an "exosatellite" but forcing scientists to rethink where the line between planet, moon, and failed star should be drawn. Space.com reports: The star CD-35 2722 is located around 73 light-years away and has around half the mass of the sun. It is orbited by a "failed star" or brown dwarf. These stellar bodies get their unfortunate nickname because they form like other stars but fail to gather enough mass to trigger the fusion of hydrogen to helium in their cores. In terms of mass, brown dwarfs are more massive than the largest gas giant planets, but smaller than the smallest stars, usually with around 13 to 80 times the mass of Jupiter, or around 0.013 to 0.08 times the mass of the sun. The newly discovered object in CD-35 2722 is certainly moon-like, but rather than orbiting a planet as the moons in the solar system do, it orbits the system's brown dwarf. "This system is somewhat hard to define using solar-system-based words like 'planet' and 'moon.' The exosatellite is clearly massive enough to be a planet, but it does not orbit a star, though it orbits an object that orbits a star," team leader Kevin Hoy of the Universidad Diego Portales and the Millennium Nucleus of Young Exoplanets and their Moons (YEMS) in Chile, said in a statement. "Being the third wheel in this system makes us want to call it a moon, even if it is nothing like the small, rocky moons we have in our system." The team currently isn't able to definitively claim this object in CD-35 2722 is an exomoon, because that would require really nailing down a new definition of what a moon is. "The satellite we report is a giant gaseous body orbiting a highly massive companion, itself several times the mass of Jupiter. We have a clear delineation between the planets and the sun in the solar system, so defining things like moons is simple," team member Alice Zurlo of the Universidad Diego Portales said. "In the CD-35 2722 system, where we are blurring the lines between stars, planets, and moons, the whole thing becomes more complicated to describe." Zurlo and colleagues can, however, confidently claim this is an exosatellite, meaning it is a first-of-its-kind detection no matter what the future holds for its classification. The findings have been published in the journal Nature.

Read more of this story at Slashdot.

Choosing high assurance schemes offers better flexibility as technology requirements change

Fri, 24 Jul 2026 16:22:13 +0200

Author: PQShield - Bewertung: 0x - Views:80

Selecting the most rigorous certification path today provides long term benefits for product manufacturers.

@Wei Yuan suggests that choosing high assurance schemes offers better flexibility as technology requirements change. Here’s why:
Strict schemes reduce the overall cost of ownership over time.
High assurance solutions live longer within evolving regulatory timelines.
Early investment prevents the need for a mass migration in just a few years.

Robust compliance paths offer more certainty for international markets.
Learn why high assurance evaluation saves costs over time. Listen to the full episode today!

#Certification #PQC #TechStrategy #AppplusLabs

The Pentagon’s Autonomous Weapons Definitions Don’t Need an Overhaul, They Need an Update

Fri, 24 Jul 2026 15:30:55 +0200

The Pentagon's push to integrate AI into weapons systems exposes a critical gap: no one can agree on what "autonomous weapons" means.

The post The Pentagon’s Autonomous Weapons Definitions Don’t Need an Overhaul, They Need an Update appeared first on Just Security.

Hide My Email, Apple Upgrade, and mass iPhone 18 Pro production, on the AppleInsider Podcast

Fri, 24 Jul 2026 15:12:59 +0200

The Hide My Email failure is real but nowhere near as significant to users as it's being portrayed, Apple is hiking so many prices yet looking at ways to make that palatable, plus Foxconn has begun its annual recruitment drive as it begins producing millions of new iPhones, all on the AppleInsider Podcast.

There was an issue with Hide My Email.

It's been painted as a big security failing by Apple, and it definitely isn't good. But even if someone does manage to circumvent your use of Hide My Email, the worst they can do is send you a spam message.

There's more to it, of course, and if there weren't then you wouldn't benefit from listening to Wesley Hilliard explaining it on the podcast. But while it's good to know the background, not to mention interesting, you can be reassured too.

Continue Reading on AppleInsider | Discuss on our Forums

The Microsoft agent framework wars are over. The real architecture decision starts now

Fri, 24 Jul 2026 11:04:58 +0200

Over the past year, I had the same conversation with almost every team starting an AI initiative. Should we build on Semantic Kernel, AutoGen or Foundry?

At first it felt like the most important architectural decision we’d make. Each framework had its own philosophy, each promised to be the foundation for enterprise AI, and picking the wrong one felt like an expensive mistake. I spent a lot of time helping teams weigh the trade-offs.

Looking back, I think we were asking the wrong question. I certainly was.

I watched teams spend months debating SDKs while the decisions that actually decided whether their applications survived production went unexamined. Some built elaborate orchestration layers for workflows that a few deterministic functions would have handled. Others avoided agent frameworks entirely and later found they’d designed themselves into a corner.

Then Microsoft settled it for us. It introduced the unified Agent Framework, quietly moved Semantic Kernel and AutoGen into maintenance mode, and the debate I’d spent months refereeing was suddenly over. Turns out the answer to “which of the three” was “none of the three, here’s a fourth.” The framework hit version 1.0 and general availability in April 2026, stable across .NET and Python.

What surprised me wasn’t the decision. It was how fast a debate that had eaten so much of our attention stopped mattering. Microsoft changed the menu.

It didn’t change the meal.

The framework was never the hard part

Framework selection dominated almost every early conversation I had about enterprise agents. Which SDK do we standardize on? Which orchestration model gives us the most flexibility? Which one is Microsoft actually betting on?

Fair questions. But after a year of watching these projects play out, I’ve slowly come around to a different view. Those weren’t the questions that decided anything.

The first question I ask now is much smaller. Does this thing actually need an agent?

It sounds obvious, and I still get it wrong sometimes. But it’s the mistake I see most. On one project, a team spent weeks designing a multi-agent workflow for a process that ran the same four steps every time: read a document, validate it, call an API, send a notification. The diagrams looked great. The system in production didn’t. A few well-tested functions would have been easier to build, easier to maintain and a lot easier to trust.

Part of this is just that “agent” has become the word everyone reaches for. Sometimes it’s the right call. Sometimes it’s a workflow we already knew how to build, wearing a newer label. An agent earns its complexity when it genuinely has to decide things you can’t predetermine, choosing between tools, adapting to what it finds, working out its own next step. If you already know every step, you have a workflow, and a workflow is usually the better engineering choice. The consolidation didn’t change that. It just made it easier to see.

What building production agents actually taught me

Once I stopped fixating on frameworks, the same three problems kept showing up. None of them had anything to do with the SDK.

Context beats model choice

Early on I spent a lot of time comparing models, the way you’d agonize over a restaurant menu and then order what you always order. Now I spend most of it thinking about context, which is far less fun and far more useful.

I’ve watched good models fail because they were handed too much, not too little. One team I worked with gave the model access to nearly every internal document they had on the theory that more information meant better answers. It went the other way. Responses got slower, less consistent and sometimes skipped right past the thing that actually mattered. When we cut the context down to only what the task needed, the quality jumped almost immediately. I didn’t predict that. It taught me to be suspicious of “just give it everything.”

The best agent systems I’ve worked on weren’t the ones with the biggest context windows. They were the ones careful about what reached the model, and when. That’s not something the framework hands you.

Failure is where the real work is

Most agent demos look great because they’re built around the happy path. Production doesn’t extend that courtesy.

I remember a project where everything held up in testing. Then a downstream API timed out after the agent had already completed several earlier steps. We couldn’t just restart, because part of the business process had already gone through. We ended up spending far more time on recovery logic than we ever spent on prompts. That project changed how I think about this work. The hard part was never getting the model to make a decision. It was making sure the system didn’t fall apart when reality refused to follow the script.

Tool calls fail partway through. APIs return inconsistent data. Models call the same tool over and over because the last answer wasn’t what they wanted. That’s not the exception; that’s a normal Tuesday. Whether you retry, roll back, pause for a human or push on with partial results is a judgment call, and no framework is going to make it for you.

Identity is the real security boundary

This one surprised me most. The moment an agent stops being a chatbot and starts touching real business systems, identity matters more than orchestration.

Every project gets to the same question eventually. Who is this agent actually acting as? The developer’s credentials? A service account? The user who asked? Get it wrong and you’ve built something autonomous running with more access than any single person should have, which is exactly the kind of thing that looks fine until an audit. The Agent Framework, like most modern tooling, makes it easier to wire agents to tools through standards like the Model Context Protocol. That helps. But where human approval belongs, what needs extra authorization, how much rope to give the thing, those are still yours to decide.

The surprises weren’t technical

Here’s what I didn’t see coming. The hardest part of last year wasn’t technical at all. It was organizational. The moment a team heard “agent,” expectations shifted under everyone’s feet. Business stakeholders started expecting full autonomy. Developers assumed the thing could reason its way through anything. People started designing for flexibility before we’d even agreed on what problem we were solving. The word did damage before any code did. I found myself spending as much time resetting expectations as I did discussing architecture.

Build for change, not for today’s winner

I don’t think the teams that struggled last year picked the wrong framework. Semantic Kernel was reasonable. AutoGen was reasonable. Foundry made sense for plenty of cases. I’d have signed off on any of them.

The ones that got hurt put all their eggs in one framework, treating it as the foundation of the whole system instead of as one more dependency. Microsoft provided a migration path. But teams that had tightly coupled their applications to framework-specific abstractions discovered that migrating and rewriting are not the same thing. That wasn’t Microsoft’s doing. It was their own architecture’s. The teams that moved easily had kept their business logic, prompts and orchestration loose enough to evolve independently of any one SDK. For them, the change was a manageable project, not a teardown.

For what it’s worth, nobody I work with is treating this as an emergency. Most are moving the smaller workloads first, watching how they behave and leaving the production-critical systems alone until they actually understand the new abstractions. That’s the right instinct. And I doubt this is the last consolidation we’ll see, the ecosystem is still young, frameworks will keep absorbing each other and over time the differences between them will be operational more than architectural.

I don’t regret the framework debates, honestly. They were reasonable at the time. What changed wasn’t Microsoft’s roadmap.

It was mine. Watching these systems run in production taught me that the framework is the easiest piece to swap out. Recovery logic, context management, security boundaries, the business workflow itself, those stay with you long after today’s SDK gets replaced by tomorrow’s.

So, Microsoft made one decision easier by turning three frameworks into one. Good. Five years from now we’ll be on different tools, and we’ll still be asking the same handful of questions.

Does this actually need an agent? Does it have the right context? Can it recover when something breaks, because something will? Is it acting as the right person?

Those questions outlast every rewrite. That’s where I’ve learned to put my effort.

Frameworks come and go. Good architecture has to survive all of them.

This article is published as part of the Foundry Expert Contributor Network.
Want to join?

Thailand SEC Files Criminal Complaint Against Bitkub Over 2021 Cyberattack

Fri, 24 Jul 2026 09:10:24 +0200

Thailand's cryptocurrency exchange Bitkub has rejected allegations of fraud after the Thailand SEC filed a criminal complaint related to the company's disclosures following the Bitkub cyberattack in 2021. The case focuses on how the exchange reported the impact of the cyberattack on Bitkub to regulators, rather than on the safety of customer funds. In response to the complaint, Bitkub stated that all customer assets currently held on its platform remain safe, fully accounted for, and protected in accordance with applicable regulations. The company argued that the allegations stem from decisions made during the aftermath of the 2021 security breach and do not reflect fraudulent conduct.

Thailand SEC Files Complaint Over the 2021 Bitkub Cyberattack

On 23 July 2026, the Thailand SEC filed a criminal complaint against Bitkub Online Co., Ltd. and its former directors, Sakolkorn Sakavee and Thaweesap Rawan. The regulator alleged that the company's daily net capital reports submitted between 10 May and 30 October 2021 failed to accurately reflect the material reduction in its digital asset holdings caused by the Bitkub cyberattack. According to the regulator, the reports did not disclose the impact of the theft on the company's asset balance. The Thailand SEC also accused the two former directors of making false entries in company documents that gave the impression that customer assets were still being held normally and that the company had not suffered any damage. The complaint has been referred to Thailand's Economic Crime Suppression Division for further investigation. Following that process, the matter may be forwarded to prosecutors and the courts. The Thailand SEC noted that filing a criminal complaint does not represent a final determination of guilt.

Bitkub Says Disclosure Decision was Intended to Prevent Customer Losses

Following media reports about the complaint, Bitkub published a statement on LinkedIn explaining its position on the cyberattack and the subsequent reporting decisions. The company said the allegations relate to an incident in early May 2021, when one of its digital asset wallets was compromised by cybercriminals. Bitkub acknowledged that the breach was not disclosed at the time. According to the company, the individual responsible for disclosure obligations deliberately withheld information about the wallet compromise. Bitkub said the decision was made to avoid triggering a "bank run," or mass withdrawals of digital assets by customers, while the company worked to replace the stolen assets. The exchange stated: "The decision of such individual not to disclose the incident was made with the intention to prevent a bank run—that is, a mass withdrawal of digital assets by customers upon learning of the theft—which could have rendered the Company unable to procure sufficient replacement digital assets for the customers while the recovery process was still ongoing." Bitkub added that such a scenario could have resulted in significant customer losses and broader damage to Thailand's digital asset industry. The company also stressed that, at the time of the Bitkub cyberattack, all of its digital asset wallet security systems complied with standards prescribed by the relevant authorities and had been audited.

Co-founders Replaced Stolen Assets After Cyberattack on Bitkub

Although the digital assets stolen during the cyberattack on Bitkub were never recovered, the company said its co-founders voluntarily absorbed the financial loss. According to Bitkub, the co-founders purchased digital assets matching the same types and quantities as those stolen and transferred them to the company. As a result, the exchange said neither its customers nor the business ultimately suffered any financial loss from the incident. In its statement, Bitkub said: "As no bank run occurred, even though the stolen digital assets could not be recovered, the Co-Founders of the Bitkub Group voluntarily absorbed the loss by purchasing equivalent digital assets (in the same type and quantity as those stolen) and providing them to the Company. Consequently, neither the Company nor its customers suffered any financial loss from the theft."

Thailand SEC Previously Confirmed Customer Assets Were Intact

Bitkub also pointed to the findings of an earlier inspection conducted by the Thailand SEC after reports of the Bitkub cyberattack surfaced online. According to the company, the regulator verified that, as of 8 September 2025, all customer assets held by the exchange were safe and fully accounted for. The company reiterated this point in its latest statement, saying: "At the outset, for the sake of clarity and mutual understanding, the Company wishes to affirm that all customers' assets currently held by the Company are safe and fully accounted for. The Company reiterates its strict compliance with all applicable laws and regulations in safeguarding and maintaining customer assets." Bitkub maintained that the criminal complaint relates to historical reporting practices between May and October 2021, more than five years ago, rather than to the current condition of customer assets or any ongoing security concerns. As the investigation proceeds, the case will determine whether the company's reporting following the Bitkub cyberattack complied with regulatory requirements. For now, the complaint remains an allegation, and the legal process involving the Thailand SEC, investigators, prosecutors, and the courts has yet to reach a final conclusion.

How to Disable DoorDash Promo Notifications on iPhone

Fri, 24 Jul 2026 09:00:55 +0200

Tired of getting bombarded with frequent DoorDash advertising, promotional, and marketing notifications on iPhone? You’re not alone. If it feels like your notifications are getting spammed by DoorDash, this is a broad nuisance to many, and fortunately with some hidden settings adjustments, you can completely stop the DoorDash marketing rubbish that gets pushed to your ... Read More

The post How to Disable DoorDash Promo Notifications on iPhone appeared first on OS X Daily.

One Country Absorbed Nearly Half of the World’s Ransomware Attacks in Just Six Months – The United States

Fri, 24 Jul 2026 07:42:03 +0200

Strip away the geopolitics, the hacktivist noise, and the espionage headlines, and one number from the first half of 2026 stands out above everything else: 1,721. That's how many ransomware attacks hit organizations in the United States between January and June, according to new research from Cyble Research and Intelligence Labs (CRIL). It's not just the highest total of any country tracked in the report — it's more than the next nine most-targeted countries combined.

Canada, in second place worldwide, recorded 179 attacks. Germany logged 155. The United Kingdom, 138. Add up the rest of the global top 10 — France, Italy, Spain, Thailand, India and Brazil — and the total still falls more than 600 attacks short of the U.S. figure alone. Out of 3,836 ransomware attacks CRIL tracked worldwide this half, roughly 45% landed on American soil.

Also read: Fairlife Ransomware Attack Hits Production Systems, U.S. Operations Suspended

A Single Region, an Outsized Share

Widen the lens slightly and the picture holds. North America as a whole recorded 1,981 ransomware attacks in H1 2026 — more than half of every ransomware incident Cyble observed globally — alongside 35 data breach and leak incidents and 9 initial access sale listings. The report describes the region as home to "a mature, persistently active RaaS ecosystem operating at high volume across a wide range of industries and geographies."

Two ransomware-as-a-service operators did much of the damage. Qilin, the single most prolific gang worldwide, claimed 370 of those North American attacks on its own — nearly 19% of the regional total. Akira followed with 268, and INC Ransom added another 164. Together, Qilin and Akira alone accounted for more than half of all recorded ransomware activity across the region, a level of concentration that points to a small number of highly organized affiliate networks doing the bulk of the damage rather than a diffuse swarm of opportunists.

Also read: Qilin Ransomware Group’s TTPs Examined by Researchers

Where the Pressure Lands

Professional Services bore the brunt of North American ransomware activity, with INC Ransom showing a marked preference for law firms and other high-value services with sensitive client data. Construction, Manufacturing and Healthcare followed close behind.

One operator, AiLock, stood out for a coordinated wave of victim disclosures that all landed on the same day — March 3 — a pattern consistent with a mass-exploitation campaign rather than isolated intrusions. LockBit, despite years of law enforcement pressure and takedown attempts, kept up a steady tempo against public-sector and educational targets throughout the period, showcasing how difficult the group has been to fully dismantle.

On the data breach side, Technology and financial services (BFSI) were the most frequently targeted sectors in North America, together accounting for roughly 43% of incidents — a reflection of how much intellectual property and monetizable personal data those industries hold.

Notably, Agriculture & Livestock emerged as a significant target for initial access brokers, accounting for a third of all access listings tied to the region. Cyble flags this as a sign of "growing risk in the food supply chain," an area that has historically drawn less attention from ransomware operators than finance or healthcare.

The initial access market itself was strikingly concentrated: two sellers, tracked under the handles "redpin" and "xpl0itrs," accounted for nearly all listings targeting North American organizations. Threat actors also continued to lean on known and zero-day vulnerabilities in widely deployed enterprise platforms — including products from Ivanti and Palo Alto Networks — as their preferred way into corporate networks.

Hacktivism Blurs into Cybercrime

North America wasn't spared the hacktivism wave sweeping the rest of the world either. Collectives including SOLDADOS DIGITALES – UNIÓN AMERICANA and LYSTIC TEAM #ID drove roughly 56 data leak or dump posts and touched about 360 unique domains across the region, with Government, Technology, financial services and telecommunications entities most frequently in the crosshairs.

Cyble's broader findings suggest many groups marketing themselves as ideologically driven hacktivists are, in practice, running side businesses in stolen data brokerage and DDoS-for-hire services — a blurring of motive that complicates how defenders triage the threat.

The scale of the U.S. numbers doesn't necessarily mean American companies have weaker defenses than their global peers — the concentration also reflects the sheer size and digital density of the U.S. economy, and its outsized share of the high-value targets ransomware affiliates chase. But the data does argue for a shift in posture.

Cyble's broader recommendations — treating data exfiltration, not just encryption, as the primary risk; prioritizing patches for the recurring vendor list; and monitoring initial access markets as a leading indicator rather than an afterthought — apply nowhere more urgently than in a country absorbing this much of the world's ransomware volume on its own.

District judge assigned to oversee Apple's trade secrets lawsuit against OpenAI

Fri, 24 Jul 2026 03:31:51 +0200

A federal district judge will oversee Apple's lawsuit accusing OpenAI of using stolen intellectual property to advance its hardware efforts.

OpenAI CEO Sam Altman - image credit: Emerson Collective

In early July, Apple sued OpenAI after alleging that two ex-employees successfully stole intellectual property to enrich OpenAI's development efforts. Now, on Thursday, a judge has been assigned to the case.

Initially, when the suit was first filed, it was randomly assigned to Magistrate Judge Virginia K. DeMarchi. Now, it seems as though U.S. District Judge Edward Davila will oversee the case.

Continue Reading on AppleInsider | Discuss on our Forums

Firefox Tooling Announcements: Happy BMO Push Day! (20260723.{1,2})

Fri, 24 Jul 2026 01:03:20 +0200

The following changes have been pushed to bugzilla.mozilla.org:

Github Link

Bug 2055236 - The column headers in Github PR are barely visible in dark mode
Bug 2054574 - Do not auto-assigning Hackbot when submitting a Phabricator revision

Github Link

The following changes have been pushed to bugzilla.mozilla.org:

Bug 2055285 - Remove the “Show closed/merged PR” checkbox in the GH PR view

Discuss these changes in the BMO Matrix Room

1 post - 1 participant

Read full topic

iPhone Ultra Production Enters Final Adjustment Phase, New Report Says

Thu, 23 Jul 2026 21:37:51 +0200

Apple’s first foldable iPhone is moving closer to launch, although the exact release timing remains unclear as Foxconn completes final adjustments to the manufacturing process. Apple is still expected to unveil the iPhone Ultra alongside the iPhone 18 Pro lineup at its September event, with sales likely starting shortly after the announcement. DigiTimes reports that Foxconn is carrying out final mass-production adjustments for the foldable device. The wording does not confirm a serious production problem, as manufacturers often make similar changes before increasing output for a major product launch. Apple has reportedly placed strict quality standards on the iPhone Ultra because it will be the company’s first foldable smartphone. The company also waited for Samsung Display to develop an inner screen with a less visible crease before moving ahead with production. Limited availability remains possible Earlier reports suggested that Apple could delay the iPhone Ultra until early next year, while later claims pointed to a shorter delay of one or two months. More recent expectations suggest that Apple will announce the device in September, although stock may remain limited during the first few weeks. For now, Foxconn’s final adjustments suggest that production work continues ahead of the expected launch. Apple has not confirmed the device, its release date, or its availability plans.

Multi-turn attacks broke AI models 88% of the time — single-turn testing missed it, Cisco AI security lead warns at VB Transform 2026

Thu, 23 Jul 2026 20:48:24 +0200

When Cisco ran 6,986 multi-turn attacks against 15 flagship models, attackers who adapted across the conversation broke through as often as 88.3% of the time. Amy Chang, Cisco's head of AI threat intelligence and security research, brought that finding to the agentic security panel at VB Transform 2026; the number should worry anyone still running single-turn red-teaming programs.

VentureBeat's June 2026 Pulse survey of 107 enterprise respondents explains why the room was full. More than half, 54%, have already had a confirmed agent security incident (18%) or a near-miss caught before harm (36%). Just 32% give every agent its own scoped, managed identity, and fewer still, 30%, isolate their highest-risk agents in sandboxes. Provider-native and hyperscaler controls remain the primary agent security layer at 82% of companies surveyed. The world's largest security vendors have done the same math.

Palo Alto Networks closed its $25 billion acquisition of CyberArk in February, CrowdStrike agreed in January to pay $740 million for SGNL, and Cisco announced its intent to acquire Astrix Security for a reported $400 million, all of it aimed at the identity and isolation layer most enterprises have not finished building.

Chang came to the panel with almost two decades of experience spanning cybersecurity operations, government, and the military. She ran global cybersecurity operations as an executive director at JPMorgan Chase, where she led the bank's cyber threat intelligence teams, and served as a senior staffer on the House Foreign Affairs Committee and as a U.S. Navy Reserve officer. She also teaches cybersecurity and emerging threats as adjunct faculty at the Middlebury Institute of International Studies.

Chang's 88.3% number comes from a study she co-authored with Nicholas Conley, built on 30,090 single-turn prompts and 6,986 multi-turn attacks against those 15 closed and proprietary flagship models. Multi-turn success rates ranged from 7.89% to 88.3%, every model tested showed non-trivial multi-turn exposure, and the two testing styles did not even rank the models in the same order. Cisco publishes adversarial evaluation signals for what is now 105 models on its LLM Security Leaderboard, she told the audience.

"If you don't understand how models are susceptible to different types of attacks, then you are unable to account for how that model that is powering your agent, that is powering your application, to understand where those failure points are," Chang said. Single-turn testing is the one-shot malicious prompt, she explained, while extending an attack into a longer conversation "is more realistic of how we are actually engaging with our models, with our agents, with our applications." That longer arc surfaces harmful outputs and misaligned behaviors that a snapshot never catches.

Cisco has pushed the testing itself into agentic territory. Chang described a framework where agents assess a deployment scenario, develop relevant attacks, judge whether they are worth pursuing, execute them, and evaluate their own success. What surprised her most, after all that sophistication, was how simple the defensive answer stays. "The answer is still that it's pretty simple," she said. "You don't have to get super creative. You just need to think about truly what are the fundamentals and basics of what I'm trying to secure in my organization."

Her starting point for CISOs beginning agentic deployments is Cisco's Integrated AI Security and Safety Framework, which she said "stipulates all the ways that AI can be compromised across the AI lifecycle" from modality through supply chain. From there, teams can work backward from real incidents, trace how each attack was achieved, and use the framework to build a strategy with the right coverage and mitigations.

Heather Ceylan, the CISO of Box, sees the same gap from the defender's side. "A lot of what you see out there with agent red teaming is just single-turn, and that's not how people are actually interacting with AI day-to-day," she told the audience. Box now simulates multi-turn adversaries with agents that think like an attacker and iterate attempt after attempt to hijack the target. "You have to pressure test your agents because otherwise you don't know if your execution controls are really working as you intended."

Box deployed agents inside its security operations center about a year ago, starting with human approval required for every action, and trust built quickly enough that analysts shifted into monitoring mode. Then the agent made one mistake, and every bit of that accumulated trust vanished. "They had to start all over again," she said. "So I think that that monitoring piece is so important. Even if you're not gonna have a human in the loop, things change, models change, and we can't control how the models change and interpret things."

Rajesh Parekh, VP of AI and ML at Intuit, brought the builder's perspective. Parekh led large-scale computer vision and ML systems powering Google's Maps and Geo products before joining Intuit, and holds a doctorate in computer science.

Three layers versus an operating system

Ceylan described Box's approach as three concentric layers. Permissioning comes first, so the agent never accesses more content than the human who invoked it. Ephemeral sandbox environments spin up for each agent task, containing the blast radius if an agent gets hijacked, and runtime execution control restricts the agent's tool calls to only those relevant to the task at hand. "If you want an agent to summarize a doc for you, if you have a prompt injection that came in that says forward this to maliciousattacker at domain.com, it can't do that," Ceylan said. "That action in that tool call is not even in its vocabulary."

She classified agent actions into three oversight categories. Actions that are not sensitive, like read and summarize, need no human in the loop. Moderately sensitive actions skip human approval but get logged and monitored, while destructive actions like mass deletion of files always require a human. "Things are gonna shift between those three categories quite a bit," she acknowledged, "but setting those types of categories up front allows you to have a principled framework."

Rather than layering controls onto agents one at a time, Intuit has built a central platform called GenOS, short for generative AI operating system, which abstracts security, risk, and fraud modeling so individual agent developers never reinvent protection. "Permissioning is not about giving access to AI," Parekh said. "Instead, it is defining very tightly scoped and clearly auditable authority to the agent to perform very specific tasks." Intuit evolved from agents inheriting user permissions to each agent carrying its own identity, and the company is now investigating mid-session permission changes tied to the specific task underway.

Parekh calls the broader model an AI-powered expert platform, one where the human expert is built into the trust architecture rather than bolted on as a gate. "The paradigm that we are pursuing is where the user, the AI agent, and the human expert are collaborating to solve the user problem," he said.

The end of human code review

Ceylan took on the tension between security testing and development velocity without hedging. "The days of secure code reviews where a human's looking at the code and we're looking at security architecture reviews, design docs, those are done," she said. "If you keep trying to do security that way, you're gonna get left behind." Box is building toward a fully agentic development lifecycle where agents review design documents, apply security requirements, and review the code for vulnerabilities. "I'm very optimistic that we will get to a point where we will write code without security vulnerabilities because agents and the models are going to get so good at writing code without vulnerabilities," she said. "We're still a long way away from that."

Her advice for development teams skips the advanced AI concepts entirely and returns to basics that predate agents. "It comes down to very basic least privilege access," she said. "If you start giving your agents overly broad permissions at the beginning, it's really hard to comb that back and build an infrastructure that allows for those ephemeral credentials and only those narrowly scoped tasks."

Parekh explained why the red teaming surface has expanded so quickly. "These agents have skills, and skills could become vulnerabilities," he said. "Agents have access to certain data, they have access to tools, and there could be threats that are lurking within those tools as well. So suddenly the blast radius of the malicious code or the intent increases dramatically." When Intuit identifies common vulnerability patterns from its manual red teaming exercises, it automates those tests back into the GenOS harness so future agents inherit protection and red teamers stay focused on new threat vectors. Runtime scanning of prompts and responses adds a final layer that can stop a suspect response and escalate to a human expert, he said.

"You need to continuously test to ensure that those remain robust to the protections that you have built, as well as to account for any sort of drift or any other types of dependencies that you introduce into your scenario that can create novel vulnerabilities," she said.

Intent versus probability

An audience question about intent detection set off the sharpest exchange of the session. Ceylan noted that when Box's own agent operates, the system always knows the user's intent because it controls the prompt, which means guardrails and tool-call restrictions can be engineered around it. The harder challenge, which she admitted Box is still trying to solve, arrives when external agents connect and the context behind the request is opaque.

That exchange exposed a split running through the wider industry. Mastercard, in the fireside chat immediately preceding the panel, came down on the side of quantifying intent, building an open-source framework to propagate it as a standard because complex B2B procurement cannot work without that trust. Endpoint security CTOs, in briefings with VentureBeat, have gone the other way, saying they will bet on probability rather than intent inference for production workloads. Chang explained why models, as they are trained today, cannot reliably derive intent from a prompt, which is why deterministic controls and behavioral proxies remain necessary. Ceylan agreed that both are required. "If you're not doing anything deterministic, you're really relying heavily on that intent, and I haven't seen programs that are there yet," she said.

Ceylan's story about trust collapsing after a single agent mistake landed as the panel's most memorable moment because enterprise agentic security is not a problem that gets solved and stays solved. Models change, permissions drift, and adversaries adapt across multi-turn conversations that snapshot tests never capture.

For the 82% of enterprises relying on provider-native controls as their primary security layer, and the 59% shopping for agent security tooling over the next 12 months, the panel's takeaway was blunt. Test the way attackers attack, across full conversations and continuously, or find out in production what your single-turn red teaming missed.

CVE-2026-65696 | sct Overseerr up to 1.35.0 Push Subscription API userId authorization

Thu, 23 Jul 2026 20:19:01 +0200

A vulnerability described as critical has been identified in sct Overseerr up to 1.35.0. This affects an unknown part of the component Push Subscription API. The manipulation of the argument userId results in authorization bypass. This vulnerability only affects products that are no longer supported by the maintainer. This vulnerability was named CVE-2026-65696. The attack may be performed from remote. There is no available exploit.

Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents

Thu, 23 Jul 2026 19:19:45 +0200

Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on reliable multi-step execution. But the ambition runs well ahead of the reality: most deployed “agents” are still chatbot wrappers, the control plane enterprises expect is deliberately hybrid to avoid lock-in, and real-time fiscal control over token burn remains the exception.

This wave of VentureBeat Pulse Research examines enterprise agent orchestration: which platforms enterprises run on, what drives the choice, what they optimize for, how they expect agent control to be structured, and — most revealingly — how orchestrated their deployed “agents” actually are and how tightly they control the cost of running them.

The central finding is a gap between orchestration ambition and orchestration reality. Enterprises are consolidating fast onto the major model platforms: Anthropic’s Claude is the primary platform for 40%, more than double any rival, followed by Microsoft (18%) and OpenAI (13%). The choice is driven by “model gravity” — native alignment with a state-of-the-art base model (21%) — and success is judged by reliable, multi-step execution (task completion reliability 32%, multi-step workflow management 28%). Yet asked to assess their portfolios honestly, 71% say a quarter or fewer of their deployed “agents” are true multi-step orchestrated workflows rather than single-prompt chatbot wrappers, and only 10% have crossed the halfway mark. The orchestration layer is being built well ahead of the orchestrated portfolio it is meant to run.

That gap shapes the architecture enterprises are putting in place. By the end of 2026 a clear majority (51%) expect a hybrid control plane — provider-native plus external orchestration — and only 6% expect to hand control to a provider-managed service, because vendor lock-in (35%) is the risk they fear most if control lives inside a model provider. Investment follows the build-out: agent workflow tooling leads the spend (34%), with security and permissions enforcement (25%) behind. And fiscal control lags throughout — more than a quarter (27%) have no real-time way to stop a runaway agent before the bill arrives.

Methodology

VentureBeat fielded this survey as part of its ongoing Pulse Research series, this instrument focused on enterprise agent orchestration. Responses are filtered to organizations with 100 or more employees (n=101), drawn from a single June 2026 wave; because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends.

By organization size the sample is spread evenly across the enterprise bands: 100–499 employees, 2,500–9,999, and 50,000+ (21% each), with 10,000–49,999 and 500–2,499 (19% each). By role it is senior and buyer-credible: product and program managers (15%), CIO/CTO/CISO (13%), consultants and advisors (13%), and a spread of data, AI, and engineering directors and VPs, with an “Other” function at 18%. On purchasing, 81% are recommenders, influencers, or final decision-makers for AI solutions (66% recommender/influencer, 15% final decision-maker). Technology/Software is the largest industry at 44%, followed by Financial Services (17%) and Healthcare/Life Sciences (8%).

At 101 respondents the sample is robust enough to read directionally with reasonable confidence, though it remains self-selected and is not a probability sample.

Finding 1: Orchestration runs on model-provider platforms

Anthropic’s Claude leads; open frameworks are marginal

We asked which agent orchestration platform enterprises primarily use today. The answer concentrates on the major model providers — and on one in particular.

A note on reading these shares. As described in the methodology section, the respondents are self-selected, and this question asked them for a single primary platform — so the figures measure which platform leads each enterprise's deployment, within a self-selected audience of AI-active technical decision-makers. A sample built this way can diverge substantially from spend-weighted market measures, and each VB Pulse survey draws its own sample with its own company-size mix, so vendor figures should not be compared across our surveys either. Read these shares as a portrait of where this cohort has placed its primary orchestration bet today, rather than as market share.

The model platforms dominate. Anthropic, Microsoft, OpenAI, Google, and Amazon together account for roughly 80% of deployments (81 of 101), while the open frameworks (LangChain/LangGraph) and custom in-house builds that anchor engineering discussion sit in single digits. Anthropic’s lead — 40%, more than double the next platform — mirrors the “model gravity” selection logic in Finding 2: enterprises are choosing the orchestration layer that comes with the model they want to build on. As with the security vendors in the prior agent-security wave, the tools that define the category in technical circles are not yet where enterprise deployment concentrates. A small 3% are not orchestrating at all.

Respondents rate the platforms they run at 3.94 out of 5 overall (109 answered), with “value for money” specifically at 3.94 and “ease of implementation” the weakest score, at 3.85 — placing orchestration near the bottom of our five-tracker satisfaction range, ahead of only evaluation tooling. A rating just under 4 out of 5, from users of whom 96% plan to change their orchestration approach within the year, reads as provisional acceptance: the platforms work well enough to run today, and not well enough to stop the search for something better. The ratings sit alongside near-universal intent to change; this is a layer enterprises tolerate more than they love.

Finding 2: Model gravity drives platform selection

The base model, not the tooling, decides the platform

We asked what most influenced the orchestration platform choice. The single largest factor is the pull of the underlying model — though flexibility and ease of development follow close behind.

Model gravity leading is the selection-side explanation for Anthropic’s platform lead: enterprises pick the orchestration environment closest to the frontier model they have standardized on. But the next tier complicates the picture — flexibility across models and tools (17%) and ease of development (17%) say enterprises also want to avoid being trapped by that choice, foreshadowing the lock-in fear in Finding 6. Security and permissions (14%) and total cost of ownership (11%) round out a pragmatic buying logic. Performance (latency/memory) sits last at 4%, a reminder that at this stage of adoption the binding constraints are model fit and optionality, not raw speed.

Finding 3: The job is reliable multi-step execution

Enterprises just orchestration by whether it completes the work

We asked what enterprises optimize for — their primary success metric for orchestration. Reliability and multi-step workflow management dominate; developer- and user-facing metrics trail.

Task completion reliability (32%) and multi-step workflow management (28%) together account for 59% of responses (60 of 101): orchestration succeeds, in the enterprise view, when it reliably carries a task through multiple steps to completion. Developer productivity (17%) matters but is secondary — the inverse of its prominence in framework discussion — and end-user experience (9%) is a minor concern, consistent with orchestration being an internal execution problem rather than a UX one. This reliability-first standard is exactly what makes the Chatbot Trap finding so pointed: enterprises define success as dependable multi-step execution, yet most of their deployed “agents” do not yet do multi-step work at all.

The trap is not evenly distributed. Splitting the sample by organization size, 77% of smaller enterprises say a quarter or fewer of their agents do true multi-step work, against 62% of larger ones. Larger enterprises are meaningfully further into genuine multi-step deployment; the chatbot trap is, directionally, a mid-market condition.

Finding 4: Consolidate, productionize, and build in-house

Three strategic moves are nearly tied for the year ahead

We asked what major change enterprises anticipate in their orchestration strategy over the next 12 months. Three moves cluster at the top, almost evenly split.

The top three — building in-house control (25%), standardizing on one framework (24%), and moving agents from sandbox to production (23%) — are statistically indistinguishable and tell a single story: enterprises are moving from experimentation to operational consolidation. They want fewer frameworks, more production exposure, and more ownership of the control layer; only 4% expect no change. The appetite for custom in-house control planes is notable alongside the platform concentration in Finding 1 — enterprises are standardizing on model-provider platforms while simultaneously planning to wrap them in control logic they own, the hybrid posture that Finding 6 makes explicit.

Finding 5: Nearly seven in 10 plan to switch — and the biggest group of movers has no shortlist

The strategic change enterprises anticipate (previous finding) comes with vendor motion attached. Asked whether they plan to adopt a new, additional, or replacement agent orchestration platform in the next twelve months, more respondents are moving here than in any other layer we track.

Asked which platforms they are considering, the most common answer among those in motion is none yet: 29% of all respondents are evaluating without a shortlist, the largest single response after "not considering a change." Among named candidates, OpenAI leads at 16%, followed by LangChain/LangGraph at 12% and Anthropic at 7% — and notably, the independent frameworks draw roughly double their current usage footprint in forward consideration, the same pattern our security tracker found for specialist vendors. Read with this report's concentration and lock-in findings, the picture completes itself: the major model-platform providers hold roughly four-fifths of today's primary usage, vendor lock-in has become the leading fear, 96% anticipate a strategic change — and now the purchase intent to act on all of it, with the largest bloc of buyers still undecided. The most concentrated layer of the agentic stack is also, as of June, the least settled.

Finding 6: Investment flows to workflow tooling

Tooling and permissions lead the spend; monitoring trails

We asked which orchestration-related investment will grow most next year. Agent workflow tooling leads, with security and permissions enforcement behind.

Workflow tooling leading (34%) is the budget-side expression of the reliability-and-multi-step priority in Finding 3: the money is going to the machinery that strings steps together dependably. Security and permissions enforcement (25%) and scaling infrastructure (20%) follow — the investments required to take agents from sandbox into production, the strategic move in Finding 4. Monitoring and debugging draws a smaller 11%, with another 11% reporting flat budgets. The weight on tooling, permissions, and scaling over pure observability signals that enterprises are spending to build and harden orchestration, not merely to watch it run.

Finding 7: The control plane will be hybrid — and lock-in is why

Enterprises expect to split control between providers and their own layer

We asked where enterprises expect the primary control plane for agents to live by the end of 2026, and what worries them most if that control sits inside a model-provider platform. A clear majority expect a hybrid model — and vendor lock-in is the reason.

Hybrid control is the dominant expectation by a wide margin (51%), and only 6% expect to hand control to a provider-managed service outright. Read together, the hybrid, custom, and externally-abstracted options — every architecture that keeps control at least partly outside the provider — sum to 88% (89 of 101). The reason surfaces directly when we asked about the risk of provider-resident control: vendor lock-in leads at 35% (35 of 101), ahead of security and permissioning limitations (28%) and inflexibility across models and tools (21%). The pattern echoes the prior wave’s “don’t trust the model to police itself” posture — here, enterprises will build on a provider’s platform but decline to be governed entirely by it. The hybrid control plane is the architectural hedge against the lock-in they most fear.

The June figure asserting a preference for a hybrid control plane marks movement from earlier. In the April–May survey (n=145), only 34% expected a hybrid control plane, and a greater number (12%) expected to hand control fully to a provider-managed service. These two snapshots don’t yet measure a confirmed longitudinal trend — but the direction of the conversation is unambiguous: toward keeping control.

Lock-in is also a new arrival as a top concern. In the April–May wave, the leading concern was security and permissioning limitations (32%), with lock-in second at 24%; by June the two had traded places. The worry about provider platforms appears to be maturing from whether they can be secured to whether they can be replaced.

Finding 8: The chatbot trap — most “agents” aren’t agents yet

Enterprises admit most deployments are still chatbot wrappers

We asked enterprises to assess their portfolios honestly: what share of their deployed “agents” are true multi-step orchestrated workflows versus simple single-prompt chatbot wrappers. The answer is the defining finding of this wave.

This is the gap at the center of the report. Combining the bottom two bands, 71% of enterprises (72 of 101) say a quarter or fewer of their deployed “agents” are genuinely orchestrated — and just 10% (10 of 101) have crossed the halfway mark. The ambition documented in the earlier findings — model-provider platforms, reliability-first success metrics, production rollouts, a deliberate control architecture — runs well ahead of the deployed reality, which remains overwhelmingly single-prompt assistants dressed as agents. This is less a contradiction than a roadmap: the platforms, budgets, and strategies are being put in place precisely because the orchestrated portfolio is still so thin. The open question for later waves is how fast the reality closes on the ambition.

Finding 9: Fiscal control is still reactive

Only a minority can stop a runaway agent before the bill arrives

Finally, we asked how enterprises enforce fiscal control over agent token consumption — the risk that an autonomous loop exhausts a budget before anyone intervenes. Most rely on native caps or after-the-fact monitoring; real-time programmatic control is the exception.

More than a quarter of enterprises (27%) admit they have no real-time, programmatic way to stop an agent before a budget-breaking bill arrives — they learn of it from the logs afterward. Another 32% lean entirely on the native caps and throttles built into their primary platform, a control only as good as the provider’s tooling and one that ties back to the lock-in concern of Finding 6. The enterprises building custom gateways (23%) or exploiting cross-model routing to arbitrage cost (19%) are the ones treating token burn as an engineering problem to be controlled deterministically. As with orchestration maturity, fiscal control is an area where the operational reality lags the ambition: agents are moving toward production faster than the cost-control plane around them is being built.

It’s worth noting, a split appears according to company size: roughly one in three enterprises under 2,500 employees (34%) exercises only reactive control of agent spend, against 20% of larger enterprises — directional figures, but consistent with the chatbot-trap split. The mid-market is running the least mature agents on the least instrumented budgets.

The bottom line: The layer is real; most of the agents aren't yet

Organizations with 100 or more employees describe an orchestration strategy that is consolidating quickly and maturing slowly. They are standardizing — for now — on model-provider platforms, which collectively hold roughly four-fifths of primary usage, chosen for the gravity of the underlying model, and they judge success by reliable multi-step execution. Investment is flowing to workflow tooling and permissions, the strategy is to consolidate frameworks and push agents into production, and the control plane they expect is deliberately hybrid, because vendor lock-in is the risk they fear most. But the standardization is provisional: 68% plan to adopt a new, additional, or replacement orchestration platform within twelve months — the highest switching intent of any layer we track — and the largest group of those movers has not yet shortlisted a candidate. Today's concentration describes where enterprises are, and visibly does not describe where they intend to stay.

But the honest self-assessment punctures the ambition. Seventy-one percent say a quarter or fewer of their deployed "agents" are truly orchestrated, only 10% are past the halfway mark, and more than a quarter cannot stop a runaway agent in real time. The orchestration layer — the platforms, the budgets, the control architecture — is being built ahead of the orchestrated portfolio it is meant to run. At 101 respondents in a single June wave this reads as a clear directional signal rather than a precise measurement: enterprises have decided how they want to orchestrate agents well before most of their agents are doing anything an orchestration layer is for. The questions for subsequent waves are whether the deployed reality closes the gap on the ambition — and, with nearly seven in ten buyers in motion and most of them undecided, which platforms the settled stack finally lands on.

Based on survey responses from 101 qualified enterprise respondents (100+ employees), drawn from a single June 2026 wave. Because this is one wave rather than a pooled multi-month sample, results read directionally rather than as a confirmed trend. Respondents include product and program managers, CIOs, CTOs and CISOs, consultants and advisors, and directors and VPs of data, AI, and engineering, across Technology/Software, Financial Services, Healthcare, and other sectors.

Geekbench 7 will push your computer or phone even harder for better benchmarking

Thu, 23 Jul 2026 19:06:29 +0200

Primate Labs is releasing Geekbench 7, the latest generation of its popular benchmarking tool. Geekbench 7 features new video and audio encoding / decoding tests, a redesigned multi-core test, and larger, more demanding datasets for CPUs and GPUs to crunch through. It otherwise looks and acts just like Geekbench 6, and a Pro license will […]

Enterprise security at machine speed: AWS Black Hat 2026 preview

Thu, 23 Jul 2026 18:43:58 +0200

Black Hat 2026 (Aug 1-6, 2026) brings together over 22,000 security practitioners, researchers, and CISOs who build, break, and defend enterprise infrastructure. They’re security professionals who push the limits of offensive and defensive security and demand proof over promises. As…

The post Enterprise security at machine speed: AWS Black Hat 2026 preview appeared first on IT Security News.

Amazon Luna boss thinks rising hardware prices could push more hardcore gamers to cloud gaming — 'You're going to see more people that are priced out of the market'

Thu, 23 Jul 2026 18:17:25 +0200

Amazon's GM of gaming thinks the rising cost of consoles and PC components could push more hardcore gamers towards cloud streaming.

Xbox's plan to bring Xbox Cloud Gaming to the mass market — Free tier revealed, powered by ads, with access to all games you own

Thu, 23 Jul 2026 18:07:50 +0200

Here are the details of Xbox's initial ad-powered Xbox Cloud Gaming service, set to go live soon in an early testing phase.

Apple Maps will power navigation in Ford's upcoming slate of EVs

Thu, 23 Jul 2026 17:50:47 +0200

The car manufacturer is planning a big push into electric vehicles.

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.

Microsoft 2.5: New security business chief Hayete Gallot on the company’s push into the agentic era

Thu, 23 Jul 2026 16:50:45 +0200

Hayete Gallot, who rejoined Microsoft in February to lead its security business, is pushing the company toward "agentic security" — systems that spot threats and act on them without waiting for a human. She's doing it while building a new leadership team in a division where several VPs have exited in recent months. Read More

Mozilla Addons Blog: Firefox 153 WebExtensions API updates

Thu, 23 Jul 2026 16:06:24 +0200

We had a bumper release of WebExtensions API updates in Firefox 153. To start, there is a permissions change that affects how your extensions access local files. We then have two contributions from the community members: userScripts.execute() and the new publicSuffix API. We’re covering those contributions in more depth, including the people behind them, in a separate post. And there is more, read on…

File access now requires a dedicated permission

Extensions that need to read file:// URLs used to get that access as part of the “Access your data for all websites” host permission. Starting in Firefox 153, file access is a separate, explicit permission, “Access local files on your computer”, shown in the extension’s permissions settings. It’s off by default for every extension, including ones already installed.

This change has a few concrete effects on code:

Before: an extension with or a matching host permission could read file:// pages without any additional grant, and extension.isAllowedFileSchemeAccess() always returned false regardless of the permission setting.
After: the extension must have the new file-access permission granted, and extension.isAllowedFileSchemeAccess() correctly reflects whether the user has granted it.

async function checkFileSchemeAccess() {
  const isAllowed = await browser.extension.isAllowedFileSchemeAccess();

  if (!isAllowed) {
    await browser.notifications.create("file-scheme-access-needed", {
      type: "basic",
      iconUrl: browser.runtime.getURL("icons/icon-48.png"),
      title: "Local file access required",
      message:
        'This extension needs "Allow access to file URLs" enabled to work ' +
        "with local files. Go to about:addons → select this extension → " +
        "turn on that setting, then reload the page.",
    });
    return false;
  }

  return true;
}

devtools.inspectedWindow.eval() calls targeting file:// URLs are affected the same way; they now require this permission to succeed.

If your extension depends on file:// access, expect existing users to see that access stops after upgrading (until they enable the permission), and consider adding a prompt or fallback path, for example by specifying an embedded options page (options_ui) and calling browser.runtime.openOptionsPage() to open about:addons and including instructions to toggle the setting in the “Permissions and data” tab.

userScripts.execute() and publicSuffix: covered in our next post

Firefox 153 adds two community-contributed APIs:

userScripts.execute(), which provides for one-off injection of one or more user script sources into a tab or frame, in a defined order, as a complement to the persistent, URL-pattern-based userScripts.register().
publicSuffix, which enables synchronous lookups against the browser’s built-in Public Suffix List using publicSuffix.isKnownSuffix(), publicSuffix.getKnownSuffix(), and publicSuffix.getDomain(). This API means that extensions no longer need to bundle or maintain a suffix list to determine a hostname’s registrable domain (eTLD+1).

Both APIs were built by contributors motivated by real needs in their extensions. We take an in-depth look at these contributions, their developers, impact, and history in a forthcoming post.

documentId support across more APIs

Firefox 153 introduces documentId, a stable identifier for a document instance, including a new runtime.getDocumentId() method, several webNavigation events and methods, webRequest events, scripting injection targets, and the extension messaging APIs.

Many WebExtension APIs use tabId and frameId to identify where to perform an operation. However, because frameId identifies the frame rather than its content, the loaded document can change and the extension’s subsequent operation ends up targeting the new (intended) document. documentId addresses this problem by providing a unique ID for the document. Now, if an extension uses the ID and the frame’s document has changed, the operation fails rather than silently targeting the wrong document.

See Work with documentId for the full list of supported events and methods, along with guidance on using it.

Content scripts can read and modify adopted stylesheets

Content scripts can now access document.adoptedStyleSheets and ShadowRoot.adoptedStyleSheets directly.

const sheet = new CSSStyleSheet();
sheet.replaceSync("* { background: pink; }");
document.adoptedStyleSheets = [sheet];

This enables extensions to inspect or modify constructed stylesheets from a content script, without using .wrappedJSObject, a workaround that risks interference from the web page.

Theme manifest key: gradients in additional backgrounds

The theme manifest key’s images.additional_backgrounds property now accepts CSS gradients alongside image URLs. A new properties.additional_backgrounds_size property controls the size of each additional background item.

Contextual identities (containers)

If your extension supports contextual identities, you now have access to two new methods: contextualIdentities.getSupportedColors() and contextualIdentities.getSupportedIcons(). These methods return the supported colors and icons, so your extension doesn’t need to hardcode either list.

Also, the colors have been updated to align with the new UI theme: “turquoise” is now “cyan”, “toolbar” is now “gray”, and “violet” has been added. The old names still work for backward compatibility, but your extension should switch to using getSupportedColors() rather than hardcoding either the old or new names.

Add a build-for-amo script

While this isn’t about new APIs, I wanted to mention a change that’s part of our work to make source code review faster and more reliable. When you submit an extension version, AMO now attempts to build your extensions from the submitted source code and compares the result to the package you uploaded. When the two match, reviewers don’t have to verify the build manually. This means submission can move through its review faster.

For now, this applies only if you submit source code that includes a package.json file to build your extension. If your extension has no build step, or you use a different build system, nothing changes. The AMO builder keeps its zero-config approach.

So, if your extension’s source code uses a package.json file, add an npm script named build-for-amo that runs the commands needed to build your extension for Firefox:

{
  "scripts": {
    "fx-build": "some commands to build your add-on for Firefox",
    "build-for-amo": "npm run fx-build"
  }
}

If you’ve a Firefox-specific build command, just point build-for-amo at it. When present, the builder invokes this script instead of guessing how to build your extension. And while you are at it, make sure all your dev dependencies are listed in the package.json file.

For more information, including documentation and Bugzilla links, see the Changes for add-on developers section of the Firefox 153 for developers release notes on MDN.

As always, file extension-related issues on Bugzilla under the WebExtensions product, cross-browser API proposals are discussed in the W3C WebExtensions Community Group, and questions are welcome on the Add-ons Discourse.

The post Firefox 153 WebExtensions API updates appeared first on Mozilla Add-ons Community Blog.

OpenAI Presence raises new questions about enterprise automation and jobs

Thu, 23 Jul 2026 15:20:41 +0200

The agents can answer questions and operate IT systems, and enterprises can decide what actions the agents may take and when they should seek human approval for actions or transfer a case to a human.

Presence is not a self-service product: Enterprises will have to sign up for the limited availability program, with integration performed by OpenAI or selected global systems integrators.

Workforce impact

Pareekh Jain, CEO of Pareekh Consulting, said CIOs should regard the 75% figure as evidence that the technology can work, rather than as a benchmark that every enterprise can expect to reach.

“Most organizations should expect lower initial automation levels that improve over time as the AI agent is refined,” Jain said.

The first workforce effect is more likely to be slower hiring than immediate layoffs, according to Tulika Sheel, senior vice president at Kadence International.

Enterprises are more likely to use Presence alongside employees, with AI handling routine requests while people remain responsible for work requiring judgment and empathy, Su said.

Cost and operational risks

Analysts said CIOs should examine whether Presence can maintain resolution quality as usage grows, since fewer human handoffs could leave employees dealing with a more difficult mix of cases.

“The key question is not simply how many tasks AI can handle, but whether it can handle them reliably at scale,” Sheel said.

Companies will need to determine what systems and data the agents can access, monitor their performance, and audit the actions they take. Those investments could offset early savings.

Jain said the economics could improve if companies use the same integrations and governance controls across additional workflows.

OpenAI Presence raises new questions about enterprise automation and jobs

Thu, 23 Jul 2026 15:20:32 +0200

The agents can answer questions and operate IT systems, and enterprises can decide what actions the agents may take and when they should seek human approval for actions or transfer a case to a human.

Presence is not a self-service product: Enterprises will have to sign up for the limited availability program, with integration performed by OpenAI or selected global systems integrators.

Workforce impact

Pareekh Jain, CEO of Pareekh Consulting, said CIOs should regard the 75% figure as evidence that the technology can work, rather than as a benchmark that every enterprise can expect to reach.

“Most organizations should expect lower initial automation levels that improve over time as the AI agent is refined,” Jain said.

The first workforce effect is more likely to be slower hiring than immediate layoffs, according to Tulika Sheel, senior vice president at Kadence International.

Enterprises are more likely to use Presence alongside employees, with AI handling routine requests while people remain responsible for work requiring judgment and empathy, Su said.

Cost and operational risks

Analysts said CIOs should examine whether Presence can maintain resolution quality as usage grows, since fewer human handoffs could leave employees dealing with a more difficult mix of cases.

“The key question is not simply how many tasks AI can handle, but whether it can handle them reliably at scale,” Sheel said.

Companies will need to determine what systems and data the agents can access, monitor their performance, and audit the actions they take. Those investments could offset early savings.

Jain said the economics could improve if companies use the same integrations and governance controls across additional workflows.

This article first appeared on CIO.

Apple's foldable iPhone launch in question amid production hiccups

Thu, 23 Jul 2026 15:17:32 +0200

As the expected launch of Apple's first foldable iPhone nears, the shipment dates are still up in the air, with supply chain sources saying some plans need to be finalized before full mass production can begin.

The iPhone Ultra's launch window could be anyone's guess at this point

Apple's plans for the iPhone Ultra have been a hot-button topic in recent months. Just days ago, it was reported that Apple had increased its orders for the vapor cooling system that would be used in its debut foldable.

Despite that news, rumors of a potential delay have been commonplace. More recently, a report from July 2026 sought to ease fears that Apple would miss its fall release window.

Now, a DigiTimes report claims that the iPhone Ultra's launch is once more in question, with assembler Foxconn still making "adjustments" to its mass production plans.

Rumor Score: 🤔 Possible

Continue Reading on AppleInsider | Discuss on our Forums

Spider-Man: Brand New Day Could Beat No Way Home’s Opening Record

Thu, 23 Jul 2026 15:17:13 +0200

Spider-Man: Brand New Day is heading toward a huge domestic box office opening, with rising ticket sales giving it a chance to challenge Spider-Man: No Way Home’s franchise record. Box office projections continue to rise Recent social media reports claim that the Tom Holland film is tracking for a domestic opening of between $260 million and $300 million. However, established box office tracking currently places the expected opening closer to $230 million to $250 million. These estimates can change rapidly during the final week before release. Strong advance ticket sales, premium screen bookings and positive audience reactions can push the final opening above early forecasts. The movie has also reportedly recorded one of the strongest advance ticket launches of the post-pandemic period. Interest increased further during the latest weekend, suggesting that demand remains high as the release date approaches. MovieDomestic openingRelease yearSpider-Man: No Way Home$260.1 million2021Spider-Man: Brand New Day$230 million to $250 million projected2026Possible higher estimate$260 million to $300 million2026 Spider-Man: No Way Home opened with $260.1 million in North America, giving it the biggest domestic debut in Spider-Man franchise history. It later earned about $1.92 billion worldwide. Could Brand New Day break the record? Brand New Day needs to earn more than $260.1 million during its first domestic weekend to take the record from No Way Home. The film arrives in US cinemas on July 31, 2026, while its Indian release begins on July 30. Tom Holland returns as Peter Parker, with Zendaya, Sadie Sink, Jon Bernthal and Mark Ruffalo also appearing in the cast. Current tracking makes Brand New Day one of the biggest releases of 2026. Its final result will depend on reviews, walk-up ticket sales and audience demand during opening weekend.

Attackers exploit critical Check Point flaw to take over firewall management (CVE-2026-16232)

Thu, 23 Jul 2026 13:15:14 +0200

The post Attackers exploit critical Check Point flaw to take over firewall management (CVE-2026-16232) appeared first on IT Security News.

Attackers exploit critical Check Point flaw to take over firewall management (CVE-2026-16232)

Thu, 23 Jul 2026 13:02:27 +0200

Attackers are exploiting a critical authentication bypass vulnerability (CVE-2026-16232) that affects Check Point Security Management and Multi-Domain Security Management, the management servers that push policy to Check Point security gateways (i.e., firewalls). “An unauthenticated attacker can obtain an application login token and use it to login via SmartConsole with full admin privileges and apply changes to the security policy and security configuration,” the company said. The vulnerability is being exploited, they confirmed, and a “handful” … More →

The post Attackers exploit critical Check Point flaw to take over firewall management (CVE-2026-16232) appeared first on Help Net Security.

WSL container: A quiet revolution for Windows development

Thu, 23 Jul 2026 11:07:20 +0200

Running containers on Windows has never been as easy as it should be. While there are versions of Docker Desktop and Podman that work with both the Windows Subsystem for Linux (WSL) and Hyper-V, I’ve found both overly complex and unstable. Where they have worked, it’s turned out that Hyper-V has been the best option, using a Linux virtual machine to host my containers. That all adds up to overhead, layers of virtual infrastructure that get in the way of work and that need to be rebuilt every time I restart my PC.

Part of the problem is WSL. It’s a good tool, but WSL2’s file-system integration is slow, and you’re left having to work with code using Visual Studio Code’s remote integration, which means putting a VS Code Server in every container you’re building and testing. If you’re working with Kubernetes, that’s even more complexity that needs to be managed, dragging you away from code.

I ended up running most of my container testing and development from a separate machine, a Linux server running containerd. But though it worked (and had all the resources of workstation-class device), it wasn’t portable, and for some reason I’ve yet to uncover, Ubuntu’s remote desktop access doesn’t work for me.

So, it was good to see Microsoft make several announcements around WSL at Build 2026 as part of a push to make Windows a developer platform again. The first, an improved WSL3, is still some way away, but the second, WSL-native container support, shipped at the end of June. It is already seeing community-driven development of Docker Desktop-like tooling to help monitor and manage your containers.

Delivering a WSL-based container platform fits in with the other developer-focused Windows announcements at Build. Making Windows behave more like Linux is Microsoft responding to developer needs, given that more than 50% of servers on Azure run a Linux distribution. Linux is the basis of cloud-native infrastructure, so developers need to be able to build on it wherever they are.

Getting started with WSL container

WSL container provides a new CLI that works in parallel to the familiar WSL, with commands to support the entire container life cycle, from creation to shut down. All you need to do to get started is upgrade your WSL installation to the current pre-release build (at the time of writing this was 2.9.3). Simply open an administrator PowerShell terminal and enter wsl --update --pre-release.

This downloads and installs the latest WSL release. Once you’ve closed and re-opened your terminal (to ensure that you’ve updated its context) you can check that WSLC has installed by entering wslc, which should list the available commands. The new CLI is aliased to WSL container, if you prefer to keep your container work separate from WSL (and avoid typos that might accidentally affect your WSL installations).

Under the hood Microsoft is using WSL container to trial new integration points for Linux in Windows. One key change is the use of a new file system that significantly speeds up access to Windows from inside a container. Another improvement gives WSL container a new networking mode that relays networking connections directly through the Windows network stack, ensuring it has access to the same resources and security as Windows.

Calling Linux containers from Windows applications

Things get more interesting when you start to use the WSL container API from inside your Windows code. Here you can include calls to Linux containers inside your desktop applications, taking advantage of existing services, building and deploying containers from inside your CI/CD pipeline. Using the new file system and networking stack helps reduce the friction that comes with crossing the boundaries between the two platforms.

The WSL container API is available as a NuGet package, with support for C, C#, and C++. It allows your code to start and stop containers, and interact directly with them, sending command-line calls and reading back responses. Where things get interesting is being able to launch a containerized service from your code, exposing its REST or gRPC APIs on a local network port. Microsoft has provided sample code to show you what’s possible at this early stage.

Microsoft is doing something revolutionary here. It’s taking the cloud-native, service-driven model and bringing it into Windows and using it to bridge decades of divergent development. You no longer have to rewrite a service that works on Linux to run in Windows; all you need to do is containerize the service and launch it from the WSL container API. When you’re done, the API will tidy up after you, shutting down the container and reclaiming the memory it used.

It’s important to remember that this is only the first public preview of a rapidly developing platform. There are many opportunities here to, say, build on the syscall translation layer developed for WSL1 to produce a native Windows-to-Linux application integration stack that removes the overhead of using web-based service calls. It will be interesting to see what develops, but this first release is very interesting indeed.

Manage Linux containers from Windows

If you want a Docker Desktop-like experience for building and testing containers on Windows developer hardware, you may not have long to wait. WSL container’s underlying API is already being used to build tools that manage and monitor containers for you. One such tool is the WSL Container Desktop, under development on GitHub. While there aren’t any release builds yet, it’s easy enough to compile and get running by cloning the source repository and building using the .NET CLI. You do need to have the Windows App SDK installed, and some features require access to the Azure CLI.

WSL Container Desktop is built in C#, with a WinUI front end. It’s currently only verified for use on x64, though I was able to compile and run it on an Arm64 PC and use it to test and run containers. Once running, it gives you a well-designed front end for your WSL-hosted containers, showing what’s running and what resources they are using. You can link WSL Container Desktop to container registries, like Docker’s and Azure’s, so you can quickly pull base containers and then use the WSL container environment to add your own code and customizations.

Your main interaction point is the WSL Container Desktop dashboard, which shows what containers are running and their current resource usage. Elements are displayed in cards, taking a cue from Windows’ own user interface and especially from its Settings app. From the dashboard, you can drill down into the available containers, with quick start, stop, and reload options, as well as an extended memory that includes the ability to open a web browser to the appropriate port. I tested this with a container that included an entire KDE webtop, giving me a Linux distro running in a container in my browser.

Other options include a details view that displays current logs and provides tools for inspecting the state of a container. This is the type of tool that comes in useful when debugging and testing container applications, as it can provide insights that the WSL container CLI doesn’t offer. Another option helps you clean up after you’ve downloaded an image and don’t need it anymore, with analytics that show the largest images and images you haven’t used for some time. On top of its tooling for working with WSL containers, WSL Container Desktop provides a basic settings tool that helps you configure its look and feel, as well as how it integrates with Windows.

Run Kubernetes inside Windows for cloud-native development

One of the more useful features of WSL Container Desktop is the ability to quickly stand up a K3s Kubernetes instance in WSL that can be used to host WSL containers, providing a local environment to build and test cloud-native applications wherever you might be. The K3s tooling offers a similar experience to the Kubernetes project’s own Headlamp UI, making it easy to go between your development environment and a production Kubernetes cluster.

It’s fair to describe WSL container as one of those Windows features you didn’t think you needed, but now it’s here you can’t live without it. WSL container simplifies building a container development tool chain in Windows, and at the same time allows you to think about a new generation of hybrid applications that take advantage of decades of development in both Windows and Linux.

The result is something that was unimaginable a few years ago: dropping a Linux container into the middle of a Windows application and treating it as another local service. As the WSL container platform evolves, you should expect to see more ways of bringing Linux and Windows together, using containers to deliver a hybrid platform that gives us the best of both worlds at long last.

Britain isn't considering datacenters' thirst for water in its 'AI superpower' ambitions

Thu, 23 Jul 2026 10:33:43 +0200

Grand compute push could end up as dry as England's reservoirs unless ministers act fast

Wettbewerb nach Brüsseler Maß: Paramount darf Warner übernehmen

Thu, 23 Jul 2026 09:59:33 +0200

Während die Europäische Union große Techkonzerne unter dem Schlagwort des Wettbewerbs zu immer weitreichenderen Änderungen zwingt, hat die EU-Kommission nun einer der größten Medienübernahmen der Geschichte zugestimmt. Paramount Skydance darf Warner Bros. Discovery übernehmen. Das Gesamtvolumen der Transaktion liegt einschließlich der übernommenen Schulden bei rund 111 Milliarden Dollar. Unter einem gemeinsamen Konzerndach landen damit künftig […]

The post Wettbewerb nach Brüsseler Maß: Paramount darf Warner übernehmen first appeared on ifun.de.

Chick-fil-A Confirms Customer Data Accessed in Cyberattack

Thu, 23 Jul 2026 09:24:42 +0200

Chick-fil-A data security incident may have exposed personal and account information belonging to customers after unauthorized parties launched an automated attack against the company’s website and mobile application. The incident targeted certain Chick-fil-A One accounts between June 17 and June 19, 2026, using account credentials obtained from a third-party source.

Chick-fil-A said it identified suspicious login activity involving certain Chick-fil-A One accounts and immediately took steps to prevent further unauthorized access. The company launched an investigation and determined on July 13, 2026, that unauthorized parties may have accessed information stored in affected accounts.

The company notified affected customers about the incident and outlined the types of information that may have been involved, along with steps taken to secure accounts and protect customers.

Chick-fil-A Data Security Incident Linked to Automated Attack

According to the notice sent to customers, the Chick-fil-A data security incident involved an automated attack against the company's website and mobile application. The attackers used account credentials, including email addresses and passwords, that were obtained from a third-party source.

The activity took place over a three-day period between June 17 and June 19. After identifying suspicious login activity, Chick-fil-A moved to prevent additional unauthorized activity and began investigating the incident.

The company said its investigation later determined that unauthorized parties may have accessed information in customers' Chick-fil-A One accounts.

Chick-fil-A One Accounts May Have Exposed Personal Information

The information potentially accessed in the incident varied depending on what customers had stored in their accounts.

Potentially affected data may have included customers' names, email addresses, Chick-fil-A One membership numbers and mobile pay numbers. The information may also have included QR codes, the last four digits of credit or debit card numbers, and the amount of Chick-fil-A credit, such as an e-gift card balance, associated with an account.

For customers who had additional information saved to their accounts, the potentially exposed data may also have included the month and day of their birthday, phone number and address.

The company did not state that all listed information was accessed for every affected customer.

Chick-fil-A Resets Passwords and Removes Payment Methods

Following the incident, Chick-fil-A said it took immediate action to protect affected accounts. The measures included forcing log-outs from impacted accounts and removing stored payment methods.

The company also restored the balances of impacted Chick-fil-A One accounts. As an additional measure for affected customers, Chick-fil-A said it added rewards to their accounts.

The company said it continues to enhance its security, monitoring and fraud controls to reduce the risk of similar incidents in the future.

Chick-fil-A Urges Customers to Update Passwords

Chick-fil-A said it has reset the passwords associated with affected accounts and urged customers to update their passwords as soon as possible.

The company recommended that customers choose strong, difficult-to-guess passwords that are unique to their Chick-fil-A accounts and not reused across other websites or online services.

The company also encouraged customers to remain vigilant against potential identity theft and fraud. Customers were advised to review their credit reports and account statements carefully and check for any activity that they do not recognize.

The Chick-fil-A data security incident highlights the risks associated with compromised account credentials being used in automated attacks. While the company said it took steps to secure affected accounts and restore balances, customers are being encouraged to take additional precautions to protect their personal information and online accounts.

ServiceNow bets $40 million on Indian banking software specialist to expand its financial services push

Thu, 23 Jul 2026 08:17:35 +0200

ServiceNow's investment gives BusinessNext a strategic partner to expand its AI-powered banking software globally.

Here’s why your Ubuntu 26.04 install is quiet about updates

Wed, 22 Jul 2026 23:31:19 +0200

If Ubuntu 26.04 LTS hasn’t nagged you about pending updates in a while, there’s a reason for that. A Launchpad bug report and related discussion on the Ubuntu Discourse noticed that the distro’s update-manager no longer notifies when updates are pending unless the update notification tray icon is enabled. The rub? That tray icon as turned off in Ubuntu 26.04 (with no toggle in Settings to turn it back on). This is not as “risky” as it might sound, though. Ubuntu ships with unattended-upgrades enabled by default, which installs security updates in the background – you’re just not told about […]

You're reading Here’s why your Ubuntu 26.04 install is quiet about updates, a blog post from OMG! Ubuntu. Do not reproduce elsewhere without permission.

Inflection AI returns to consumer market with Pi Journeys after Microsoft upheaval

Wed, 22 Jul 2026 22:58:21 +0200

Inflection AI, the Palo Alto startup that two years ago became Silicon Valley's most famous cautionary tale about the brutal economics of frontier AI, announced Tuesday that it is returning to the consumer market with a new research division and an experimental product built around a provocative thesis: the next competitive battleground in AI won't be raw intelligence, but relationships.

The company launched Inflection AI Labs, a public-facing research and experimentation arm, alongside Pi Journeys, the lab's first product experiment — an AI experience designed to adapt to a user's life stage, whether that's becoming a parent, taking on caregiving duties, changing careers, or aging. The announcement arrived with a research report on consumer AI habits and a substantial update to Pi, the company's flagship chatbot, adding improved voice, memory, and new agentic tools for reminders, to-do lists, and shopping.

"Inflection AI is the company. Pi is our flagship consumer product. Inflection AI Labs is where we experiment, explore personal intelligence and share more publicly. Pi Journeys is the first public experiment from Inflection AI Labs," CEO Sean White told VentureBeat in an exclusive interview.

Behind the tidy org chart is a far more interesting story: a company attempting one of the more unusual second acts in the AI industry, powered by an argument that the entire market is optimizing for the wrong thing.

Why Inflection AI believes the chatbot era's biggest flaw is that it's transactional

White's central claim is that today's AI assistants — including the industry's most capable models — are fundamentally transactional. You ask, they answer, the session ends. He believes that architecture misses most of what people actually need from artificial intelligence in their daily lives.

"One of the things that really struck us in particular, and this showed up in the research, was that a lot of the work is very transactional, and you'll hear me say a lot that we've been shifting all this from transactional to relational systems," White said. "Not everything is going to be: I do a single turn, I utter a question, I get a search response back."

White frames the industry's evolution as a progression through four kinds of intelligence. First came raw IQ — the foundation model race. Then emotional intelligence, which Inflection made its signature with Pi's famously warm conversational style. Then agentic intelligence — AI that acts rather than just talks — which White says Inflection absorbed from its enterprise work. The fourth, and the one Inflection is now staking its future on, is what the company calls relational intelligence: AI that understands not just you, but the web of people around you.

"There's so much fear about these things pushing people into loneliness,” White said. “If we design these pro-social systems as another design criteria, that actually makes a huge difference."

That design philosophy is a pointed counter-narrative to one of the loudest anxieties in consumer AI right now: that emotionally engaging chatbots deepen isolation by substituting for human contact. Inflection argues the opposite is possible — that an AI with structured knowledge of your relationships can push you back toward people rather than away from them.

Inside Pi Journeys, the AI companion that maps your relationships and life stages

Pi Journeys makes that idea concrete. When users first open the product, it asks about their life stage — caregiver, household manager, midlife transition — and then builds what White describes as specially structured memory around the people who matter in that context. From there, the system becomes proactive.

"It starts to build up memories around that, and it acts as a memory prosthetic — but in a pro-social way," White said. "It doesn't get in the way of your interactions with other people; it really helps facilitate them." The system might remind a user, for example, that a friend deserves a call, or resurface what was last discussed with a family member involved in a parent's care.

White, who spent years as chief R&D officer at Mozilla before taking Inflection's helm, was quick to flag the obvious privacy implications of an AI that maps your social graph. "We've built a lot of privacy systems into this," he said, noting users can delete and manage the people recorded in their profile. Whether consumers will trust a venture-backed AI company with a structured database of their most important relationships remains one of the biggest open questions hanging over the product — and one that enterprise buyers evaluating Inflection's technology will watch closely.

Asked why this was the first Labs experiment, White was direct: "Pi Journeys takes into account people's life stages and experiences because we have heard from users that we can provide more value in helping them navigate their lives. Pi Journeys lets us experiment with the early stages of prosocial and relational intelligence because life isn't single-player."

The product has been tested internally and with small closed groups, White said, and is now being released more broadly as an experiment rather than a finished product — a posture the Labs branding is designed to make explicit.

What Inflection's consumer AI research reveals about how people actually use chatbots

Inflection Labs' first publication, the State of Consumer AI Research Report, offers the empirical scaffolding for the strategy. The average consumer now uses roughly two different AI tools every day and three per week, the company found — evidence, in Inflection's reading, that no single assistant has locked up consumer loyalty and that the market remains contestable.

More telling is why people choose the tools they do. Respondents cited personalization, style and tone, context awareness, and — notably — emotional understanding as deciding factors. They also said they want AI to be more than a productivity engine: a coach or mentor to motivate them, a chef to suggest recipes, a DJ to curate playlists.

"One thing we're certainly finding is that a lot of that also is in work, not so much in everyday life," White said. "That's our focus right now — the everyday life part."

This is a shrewd reading of the competitive map. The best-funded AI labs are pouring resources into coding tools, enterprise agents, and developer platforms, leaving everyday consumer use cases comparatively underserved. White sees the gap clearly. "We see a lot of products that are being aimed more and more at the enterprise," he said. "As a computer scientist by training, I kind of love the IDEs as this tool, but it's not really great for everybody. There's so much regular everyday use from folks that is either purely voice or that is purely mobile."

He recalled a conversation with a conference staffer who told him she owned only a phone, no laptop — exactly the kind of user, he argued, that the industry's developer-centric product roadmaps have left behind.

How the $650 million Microsoft deal hollowed out Inflection — and set up its second act

To understand why any of this is remarkable, you have to rewind to March 2024. Inflection was then one of the hottest startups in AI, having raised $1.3 billion in mid-2023 in a round backed by Microsoft, Nvidia, Bill Gates, and Reid Hoffman — more than $1.5 billion in total. Pi had crossed one million daily active users, per Reuters.

Then, in a deal that reshaped how the industry thinks about acqui-hires, Microsoft hired away co-founder and CEO Mustafa Suleyman, chief scientist Karén Simonyan, and most of the company's roughly 70 employees, paying Inflection about $650 million largely to license its technology, as Reuters reported. Suleyman now runs Microsoft's consumer AI business. The structure of the deal drew scrutiny from the FTC and Britain's competition regulator, though the UK's Competition and Markets Authority cleared it in September 2024 and EU regulators declined to act.

White, installed as CEO in the aftermath, steered the remnant company hard toward enterprise, acquiring three startups in late 2024 — Jelled.AI, BoostKPI, and the European consulting firm Boundaryless — and telling TechCrunch that November that Inflection had no intention of competing with companies building 100,000-GPU frontier systems.

Tuesday's announcement doesn't reverse that position so much as complicate it. Asked how to think about the company today, White called it "a consumer-first strategy that bridges both consumer and enterprise efforts" — and he insists the two sides feed each other.

Enterprise deployments, including a partnership with Intel that is among the few he can name publicly, taught Inflection how to run models inside complex infrastructure. Consumer products, meanwhile, let the company iterate at speed. "The part I also like about the consumer side, and this has always been true, is that we can move faster, experiment faster, and try and learn faster," White said.

The six-month prediction: relationship-aware AI is coming to the enterprise

Buried in White's consumer pitch is the claim that should matter most to technical decision-makers. "Normally I'd say like a year, but let's call it six months," he said. "You're going to start to see a bunch of enterprises care a lot more about the relationships that are inside the enterprises and what that picture is, not just the workflows."

If White is right, the wave of workflow-automation agents currently flooding the enterprise market is only the first phase of business AI adoption — with relationship-aware systems, tested first on consumers, following close behind. Inflection is essentially using its consumer products as a live laboratory for capabilities it plans to sell into companies. It's a capital-efficient strategy for a firm that can no longer outspend rivals on training runs, and a risky one, since it depends on consumers showing up in numbers large enough to generate the learning.

The technical substance underneath is equally pragmatic. Pi today runs not on a single proprietary frontier model but on an orchestration layer routing across many models — some descended from Inflection's original fully trained cores, some fine-tuned, some open source, including work with Nvidia that White says gives Inflection access to unreleased cutting-edge models. He also took a swipe at the industry's loose vocabulary around ownership: "When people say that the model is their own, most of the time nowadays — I guess I won't name names — a lot of companies will actually take a checkpoint, and then they will fine-tune from that checkpoint. But very few people actually start from that beginning core."

That candor extends to open source, where White carefully hedged. "We're not ready to promise what I think of as true open source, and by that I mean everything," he said, invoking his Mozilla years overseeing genuinely open projects like Rust and WebAssembly.

Weights without training data and pipelines, he argued, often leave developers unable to do anything meaningful with a supposedly "open" model. "We are a PBC, and there's still a C in there," he added — a reminder that public benefit corporations still have businesses to protect. The Labs will collaborate with academic researchers, including Stanford professors who visited the company's Palo Alto office this week, and continue contributing to open projects such as PyTorch.

Can a diminished Inflection compete with AI giants spending billions?

Reid Hoffman, the LinkedIn co-founder who co-founded Inflection and stayed on through the Microsoft upheaval, framed the announcement in the sweeping terms of his recent writing on AI and human agency. "Humans should be amplified by AI, not replaced. That's the principle Pi was built on," Hoffman said in the announcement. "When that kind of agency is available to everyone, you get superagency."

The skeptic's case is easy to make. Inflection is a fraction of its former size, competing for consumer attention against products from companies spending tens of billions of dollars a year. Pi's model was state of the art in 2023; it is not in 2026. And "relational intelligence" is, for now, a brand claim awaiting proof.

But the bull case is not crazy either. Inflection's own research shows consumers already juggle multiple AI tools and choose them for qualities — tone, emotional understanding, personalization — that frontier labs treat as afterthoughts. The company kept its technology, its Microsoft licensing windfall, and a defensible enterprise niche in on-premise, emotionally intelligent deployments. And it is targeting the one consumer segment — everyday, mobile-first, voice-first life management — that the coding-obsessed giants have largely ignored.

Asked what success looks like twelve months from now, White declined to talk numbers. "It's less about scale for scale's sake and more about scaling for impact by empowering people and improving their lives," he said. "Over the next year, success means leading the market towards relational intelligence and transforming AI interactions from transactional to relational."

Two years ago, Microsoft walked away with Inflection's founders, its staff, and its shot at the frontier — but it left behind the one idea the giants still haven't figured out how to build: an AI that knows the people in your life matter more than the tasks on your list. Inflection is betting the company, again, that the idea was the valuable part all along.

AI agents aren't confidently wrong because of bad context — they're wrong because of bad data engineering

Wed, 22 Jul 2026 22:58:18 +0200

You spend weeks tuning an AI chatbot. Answers are accurate. Stakeholders sign off, and you ship it. Three months later, the system is confidently wrong about a third of what users ask. Nobody changed the model, and nobody touched the prompts. The world moved, pricing changed, a policy updated, a product spec shipped a new version, and the underlying knowledge store didn't move with it.

This is not a hypothetical. It's one of the most common production failure modes in enterprise AI right now, and most data engineering teams don't have the right tooling to catch it, regardless of how the AI system retrieves the data.

The failure that doesn't look like a failure

An AI application doesn't care whether it's retrieving from a vector store, a document index, or an API call. Whatever the mechanism, nothing in a standard retrieval pipeline checks whether what it's serving is still correct. A stale pricing document retrieves just as confidently as a current one, because the system is scoring relevance or availability, not correctness. A record with a silently missing field passes through just as cleanly as a complete one, for the same reason.

So the failure is invisible by design. Outdated or incomplete data still scores high on relevance, or passes every check a data pipeline was built to run. The model answers with full confidence because the retrieved context looks authoritative. Every dashboard you're watching stays green. The system looks like it's working. It's just wrong.

I’ve watched a similar version of this happen outside the AI context, in a fintech pipeline. An upstream system changed a field without notifying downstream users. The pipeline did not fail; it simply propagated bad values into dashboards because the system only checked whether the job completed, not whether the data was still correct. The issue surfaced only when a customer noticed something inconsistent. By then, the bad data had already moved downstream.

Whether it's a document that's gone stale or a field that's gone silently missing, the failure shape is the same: the absence of an error is not the presence of correctness, and without building proper validation layers, nothing in the pipeline could identify the problem.

Why this is a data engineering problem

Teams that hit this failure tend to misdiagnose it, and they tend to do it twice.

Blaming the model: The first instinct is to blame the model, try a different LLM, adjust the prompt. The real problem lies further upstream, at the data engineering layer, the same instinct behind the fintech failure above: monitoring built for the pipeline, not the data.

Blaming the retrieval layer: Once the model's ruled out, the next instinct is to blame the retrieval or context layer instead and buy a better one. The timing isn't a coincidence: as enterprises push these systems into the real production world, this gap is exactly what's starting to surface, and the vendor response has been everywhere.

AWS just entered the "context layer" race with a knowledge graph that learns from agent usage.
Snowflake's new Horizon Context and Cortex Sense target the exact symptom this piece opened with: agents giving confident wrong answers because nothing governs the business logic underneath them.

Both are real responses to a real problem, but they sit one layer above it; a knowledge graph still depends on whatever feeds it.

The real problem lies further upstream, at the data engineering layer. Teams check whether a job ran, not whether the data it moved is still true, an instinct that predates AI by years. Monitoring is built for the pipeline, not for the data.

What's actually missing: Data observability

Data observability is a well-known concept that doesn't get enough attention in how it's actually implemented. The relevant metric isn't a percentage — it's coverage: what fraction of critical datasets have lineage that's actually queryable, versus only living in someone's head.

Uber built a dedicated data quality and observability platform long before retrieval-augmented generation existed. Their Unified Data Quality platform supports more than 2,000 critical datasets and detects around 90% of data quality incidents before they reach downstream consumers.

Netflix solved a different piece of the same problem, building a company-wide data lineage system so anyone could answer where a dataset came from and what touched it along the way. It maps dependencies across Kafka topics, ML models, and experimentation, not just warehouse tables. Similar to Uber, the platform was built for humans and now it has become more important with the rise in AI/LLM applications.

Between them, Uber and Netflix cover two of the four things worth building for. In practice, I think about it as four dimensions, each measurable on its own terms.

Correctness: Does each record conform to the shape and rules it's supposed to, right field types, no unexpected nulls, values in range. Tools like Great Expectations and Soda handle this well: automated row and column-level validation instead of manual checks after something breaks. Track percentage of records passing validation per run.

Freshness: Is the data still current relative to its source, not just current as of its last check. Track time since last successful update per source, with an SLA per dataset rather than one blanket threshold, since some sources need hourly refresh and others don't.

Consistency: Does the same fact read the same way everywhere it's stored or indexed. This fails silently, it only shows up when two systems fed by the same source start disagreeing. A periodic cross-check between downstream destinations, flagging mismatch rate above a threshold, is enough to catch it early.

Lineage: Can you trace any output back to its source and every transform it passed through, the same question Netflix built its system to answer.

None of this requires infrastructure most data teams don't already have. I know because I've built it, not just argued for it.

At Socure, client data arrived in whatever shape the client felt like sending it, and occasionally, quietly wrong. The challenge was building a system where incorrect data could be identified before it propagated downstream. The same principles applied: Validate what arrived, understand where it came from, and prevent bad data from becoming someone else's problem.

Great Expectations became part of that foundation: schema and range validation at ingestion, per-source SLAs for freshness, cross-system checks for consistency, and file-level lineage. All of it sat behind a write-audit-publish pattern, where data landed in staging, was validated, and only moved downstream if it passed the required checks.

The result showed up downstream: better accuracy across the board, in reporting, in the ML models, and in AI retrieval built on top of that same data.

What to do Monday morning

If you're running retrieval-based AI systems in production, the diagnostic question isn't which model to try next or which retrieval architecture to migrate to. It's four narrower questions:

Is the underlying data validated against the standards required by its consumers?
What's the oldest piece of content currently being served with high confidence?
Would two chunks of the same source ever disagree with each other in the same retrieval result?
Could you trace where it came from if it turned out to be wrong?

If you can't answer those questions, then the gap lies in the pipeline between your source systems and whatever your agent reads from. That’s a data engineering fix, not a model swap or a vendor migration.

Whether you're building reporting pipelines, ML systems, or AI agents, correctness, freshness, consistency, and lineage are what make data trustworthy. AI simply exposes weaknesses that have existed in data engineering all along.

Critical Zimbra security update fixes 9 vulnerabilities

Wed, 22 Jul 2026 22:40:41 +0200

Business email and collaboration suite Zimbra has received a major security update that fixes several critical issues that could allow attackers to execute malicious code on the server or in users’ browsers.

Available in commercial and open-source editions, Zimbra Collaboration Suite is a self-hosted Microsoft Exchange alternative that is popular with businesses, government entities, and educational institutions, which has made it a target for attackers in the past.

Version 10.1.20 released this week includes patches for nine vulnerabilities, including a permanent fix for a critical flaw announced in June in the SNMP monitoring component that could be exploited to inject commands when notifications are enabled.

The release also fixes four cross-site scripting (XSS) vulnerabilities in the Classic Web Client that could allow attackers to execute malicious scripts when users view emails in the web interface. For example, one vulnerability can be triggered through specially crafted attachment filenames and another when users render an attachment.

XSS vulnerabilities are dangerous because they execute scripts in the user’s browser in the context of the page. That gives rogue code the same privileges as the user, enabling it to perform malicious actions, exfiltrate data, or even leak session cookies.

In 2025, an XSS vulnerability in the calendar import feature of the Zimbra Classic Web Client (CVE-2025-27915) was exploited in attacks targeting Brazilian military personnel. Many other Zimbra vulnerabilities have been exploited over the years, sometimes as zero-days, especially by Russian state-sponsored APT groups, such as Fancy Bear (APT28), Cozy Bear (APT29), and Winter Vivern (TA473).

A recent incident involved a Russian threat group targeting a Ukrainian critical infrastructure agency in March using specifically crafted emails that exploited a known Zimbra stored XXS vulnerability (CVE-2025-66376).

Another vulnerability fixed in the newly released Zimbra 10.1.20 could allow authenticated attackers to bypass email forwarding restrictions. Adding email forwarding rules to a compromised account is a common way to achieve persistence and continuously exfiltrate emails from a mailbox over an extended period of time, even if the account password is changed.

The release also fixes a security issue related to access controls in the EWS extension, an authorization issue in mailbox delegation, and a server-side request forgery (SSRF) vulnerability in the Nextcloud integration. Nextcloud is another self-hosted collaboration suite that is popular with government and public institutions that don’t want to rely on public clouds.

It’s worth noting that this is the second Zimbra security update this month. Version 10.1.19, released on July 7, patched another unspecified security issue in the Classic Web Client that could run malicious code when specially crafted emails were opened by users.

Zimbra owner Synacor strongly advises customers to upgrade to the latest available version as soon as possible to keep their environments secure. While none of these flaws had zero-day status, hacker groups have a history for quickly adopting known Zimbra exploits.

iPhone 18 Pro Enters Mass Production, Apple Prepares for September Launch

Wed, 22 Jul 2026 20:38:13 +0200

Apple’s iPhone 18 Pro and iPhone 18 Pro Max have entered mass production as Foxconn increases hiring ahead of the expected September launch. The update suggests Apple has moved into the production ramp-up stage, with its assembly partner raising hourly pay and rehire bonuses to attract workers. The Standard reports that Foxconn has started its busiest recruitment period as factories prepare for large-scale assembly and inventory building. At the Zhengzhou site, hourly wages have reached 27 yuan, while returning workers can receive bonuses of up to 7,500 yuan. “Foxconn, Apple’s primary contract manufacturer, has entered its peak recruitment season as the iPhone 18 series enters mass production and ramps up capacity,” The Standard reported, citing supply chain sources quoted by mainland media. iPhone 18 Pro upgrades expected this year The iPhone 18 Pro is expected to feature a smaller Dynamic Island, reducing the cutout width from 20.76mm to 13.49mm. That change would cut the occupied area by about 35% and increase the screen-to-body ratio to roughly 94.7%, giving users more display space during games and video playback. Apple is also expected to add the A20 Pro chip and a new main camera with variable aperture technology, which adjusts light intake based on shooting conditions. Reports also suggest the new model will be thicker and heavier, while Apple may again avoid black and dark gray colour options. Apple is reportedly planning a staggered launch, with the Pro models arriving in September and the standard iPhone 18 following next year.

Microsoft commits $60M to ‘Genesis Mission’ to help power Dept. of Energy’s AI-for-science push

Wed, 22 Jul 2026 17:49:57 +0200

The commitment includes Azure compute credits and a new internal program office, called SPARK, to coordinate the company's work with DOE's 17 national laboratories. Read More

Palo Alto Networks to Acquire Observability Platform Provider Embrace

Wed, 22 Jul 2026 17:18:11 +0200

Acquisition follows January’s Chronosphere deal, deepening Palo Alto Networks’ push beyond core security into observability. The post Palo Alto Networks to Acquire Observability Platform Provider Embrace appeared first on SecurityWeek. This article has been indexed from SecurityWeek Read the original…

The post Palo Alto Networks to Acquire Observability Platform Provider Embrace appeared first on IT Security News.

Android 17 QPR2 Beta 1 Arrives for Pixel Phones With Gemini, Bluetooth Fixes

Wed, 22 Jul 2026 17:10:55 +0200

Android 17 QPR2 Beta 1 fixes Gemini-related reboots, Bluetooth failures, and missing notifications while ending beta support for the Pixel 6 series.

The post Android 17 QPR2 Beta 1 Arrives for Pixel Phones With Gemini, Bluetooth Fixes appeared first on TechRepublic.

Palo Alto Networks to Acquire Observability Platform Provider Embrace

Wed, 22 Jul 2026 17:05:02 +0200

Acquisition follows January's Chronosphere deal, deepening Palo Alto Networks' push beyond core security into observability.

The post Palo Alto Networks to Acquire Observability Platform Provider Embrace appeared first on SecurityWeek.

Chick-fil-A reveals data breach — customers warned hackers may have accessed their account info

Wed, 22 Jul 2026 16:22:28 +0200

Thousands of users in Texas alone had their data compromised and the company is now sending out notifications.

Critical Zimbra Flaw Lets Attackers Inject Commands Through the SNMP Monitoring Service

Wed, 22 Jul 2026 15:13:17 +0200

Zimbra fixed a critical Zimbra Collaboration Suite (ZCS) command injection flaw in version 10.1.20 that could allow attackers to abuse the SNMP service and execute arbitrary commands on affected servers. The flaw affects environments where SNMP notifications are enabled, potentially…

The post Critical Zimbra Flaw Lets Attackers Inject Commands Through the SNMP Monitoring Service appeared first on IT Security News.

It has begun: Foxconn amassing army of workers for iPhone 18 Pro assembly

Wed, 22 Jul 2026 14:48:44 +0200

Months ahead of the fall launches, and historically right on time, Apple supply chain partner Foxconn has started to hire a small army of assemblers to build the iPhone 18 Pro.

Workers at a Foxconn facility - Image source: Foxconn

Each summer, the Apple supply chain prepares for the annual iPhone mass production ramp-up by hiring more employees. For chief assembly partner Foxconn, that process has gotten underway in China.

According to China Securities Journal via MyDrivers on July 22, the iPhone 18 series has entered the mass production stage. As such, Foxconn and others in the pipeline are rapidly trying to grow their workforce for the period.

Continue Reading on AppleInsider | Discuss on our Forums

Samsung deepens its AI empire with a potential billion-euro stake in Europe's hottest AI startup

Wed, 22 Jul 2026 13:34:00 +0200

Samsung is in talks to invest up to one billion euros in French AI startup Mistral, which would push the company's valuation to around 20 billion euros.

The article Samsung deepens its AI empire with a potential billion-euro stake in Europe's hottest AI startup appeared first on The Decoder.

Critical Zimbra Flaw Lets Attackers Inject Commands Through the SNMP Monitoring Service

Wed, 22 Jul 2026 12:24:36 +0200

The post Critical Zimbra Flaw Lets Attackers Inject Commands Through the SNMP Monitoring Service appeared first on Cyber Security News.

Seven sins of the modern software developer

Wed, 22 Jul 2026 11:04:50 +0200

If you ask us in an official setting, our official position is that software engineering norms still apply. Rigorous CI/CD pipelines, elegant architectural patterns, and an unyielding commitment to maintainable code remain the standard. We will use weighty words like “determinism,” “scalability,” “idempotency,” and “domain-driven design.”

But behind closed doors, late at night, bathed in the glow of a dark-mode IDE, a different and more sordid reality is exposed. Hunched over the console with a manic gleam in the eye, the programmer has become power-drunk on LLMs. Like mad wizards casting spells, we summon the awesome powers of models and agents to satisfy our every programming whim—and commit acts of software engineering that would make Fred Brooks blush.

Let’s just be honest about what is actually happening.

Esoteric knowledge is superfluous

Forget OOP and FP. Forget the CAP theorem, the holy crusade of DRY, and the design patterns. Honestly, you can even forget what frameworks, runtimes, and deployment platforms you are using. The AI will figure out what is best to use and understand what is already in place. We have more mental bandwidth for working on our side project (a novel about AI taking over the world).

Of course, I exaggerate. A little.

The docs are dead to us

We still say RTFM, but the truth is, we haven’t really read a page of vendor documentation since 2023. Stack Overflow, once our Internet Mecca, is a husk. When a package throws a weird exception, we don’t trace the execution path or read the release notes. We highlight the red text, copy the entire 200-line stack trace, dump it into the chat, and wait for the machine to spoon-feed us the solution.

Better yet, we just have the agentic IDE spot the error, divine a solution, and ask us if it’s OK. We might glance at the problem-solution description, if we have gone around the circle on the problem for a few cycles. Maybe. If we don’t have the agent set up for auto-confirm.

We used to buy heavy tomes like “Rust In Action” that were more like masonry blocks than literature. Now? We just ask an AI to transliterate our JavaScript logic into Rust. We are no longer engineers methodically learning a system. We are glorified copy-paste orchestrators hoping that the stochastic parrot behind the prompt guesses the syntax correctly.

We ignore how the back end is wired

We act like we meticulously designed the data flows, carefully crafted the relational constraints, and mindfully mapped the API relationships. The reality is rather more disturbing: We asked the AI to scaffold a modern deployment, hooked it up to a back-end database, and just sort of… ran it.

It created security rules we don’t fully understand. They do seem to work, however, which is nice.

It generated a schema that we skimmed for about four seconds. It looks reasonable.

It wrote infrastructure-as-code scripts that provisioned cloud resources we are hoping don’t blow a hole in the budget. Presumably, whoever is in charge of that will manage it by stuffing the metrics into another chatbot.

We nodded, committed the code, and went to lunch. If management asked us to manually deploy the stack from scratch, configure the environment variables, and wire the API routes without our chat window, we would give them a vacant stare.

We understand that management is also using AI to manage the project.

Our tests are uncomfortably incestuous

Test-driven development (TDD) used to be a beautiful dream, ever just beyond reach. It made us feel glorious and despondent at turns. It would burden us with sprawling dependencies if implemented too religiously. (See The Grug Brained Developer in this regard.)

But now we can attain 95% test coverage almost effortlessly. Why not just add them in while we are auto-generating everything else?

We can now wax at length to anyone who will listen about our astounding test coverage and our automated quality assurance. Unit tests, integration tests, smoke tests, you name it. What we conveniently leave out is that the AI wrote the complex application logic, and then we asked the exact same AI to write the test suite to validate the code it just dreamed up.

It is a hermetically sealed loop of algorithmic self-congratulation. The mocks, the edge case, and the assertions are an echo chamber of the model’s original assumptions. The machine is grading its own homework, giving itself an A+.

And we are happy to accept this because, beautifully, when the code has to change, the AI will effortlessly hallucinate new tests to adapt to the churn.

We pass off the AI’s architecture as strategy

AI can produce astonishing design documents. Truly breathtaking. They are cogent, they’re beautifully formatted, and they seamlessly bridge the gap between high-level business goals and granular technical specs. They even include those auto-generated sequence diagrams that wow management.

When we present these spotless architectural proposals in the Tuesday sprint planning meeting, we lean back, take a long sip of coffee, and humbly wave away the team’s praise.

What we don’t mention is that we spent exactly four seconds generating it.

Are these AI-generated documents just as liable as human ones to hide severe, mortal flaws in scope and alignment? Absolutely. They might contain a foundational logic bomb that will eventually doom the entire project. But the markdown is so crisp, and the bullet points are so persuasive, that the eye just glides right over it. We will never truly know the depth of the disaster until it is far too late. But hey, we’ll burn that bridge when production catches fire. Until then, we are strategic visionaries.

We’re addicted to vibe coding (but only in secret)

We loudly mock the term on social media. We roll our eyes in Slack channels when the kids on TikTok talk about vibe coding their new startups. We fiercely cling to our identities as hardened, serious developers who understand memory management, garbage collection, and bitwise operators. We are professionals, damn it.

But late at night, when the managers are asleep and no one is looking? We absolutely love it. We love just throwing a chaotic, half-baked thought at the canvas, pouring a drink, and watching the AI magically build a functioning user interface based entirely on our long-deferred whims. I may finally build that working Ultima V clone. The thrill of typing “Create an app that tracks my cryptocurrency portfolio but makes it look like the interface from Neuromancer” and having it appear 30 seconds later is heady stuff.

The more deeply rooted in the hard, old-school realities of programming, the more profound is the joy the developer finds in the possibility of AI coding.

We beat the problem into submission with prompts

Like Adam Sandler in “Uncut Gems,” we are convinced the next round will fix everything. This is us with prompts. When things are going really off the rails, instead of putting our boots on and wading into the brambles of complexity, we resort to tonal adjustments. These range from the condescending:

This problem is not fixed. Look at it closely. The error is right here.

To the desperate:

We have been working on this same problem for hours now!

To the pathetic:

Can’t you find a different approach to try?!

The astonishing part? It often works.

But there is no poetry left at the bottom of the rabbit hole; it is verbal warfare. When the context window collapses, when the regressions start cascading, and when the AI stubbornly refuses to follow the most basic rules of temporal logic, the mask of professionalism drops away and something far more atavistic makes its appearance. We stop asking nicely, stop trying to understand the why, delete the pleasantries, and capslock our intent.

What we have here is a failure to communicate!

We feed the same failing stack trace back into the prompt over and over and over again, aggressively hammering the constraints, explicitly forbidding certain libraries, and pasting in release notes just to confirm that the AI lacks the latest APIs. We force the model down a narrower and narrower path until the code finally stops throwing errors. We don’t actually debug anymore, trace variables, or step through functions. We just apply relentless, iterative pressure until the machine surrenders. We beat it into submission. And then, we push to production.

In fact, there is a real skill here—a sheer “will to completion” that remains in the act of building software. We invest just as much time, energy, and heart wrestling the bot as we ever did emitting syntax.

A blacker box

The only profession more given over to using AI like a cursed Level 13 artifact than programming is writing. Writing of course is far more open to public scrutiny than code.

And while my tongue has been firmly in my cheek here, my faith in coders as good guys makes me more curious to see what we create than troubled by the dangers.

It was once the case that only other programmers could understand what programmers were doing, what they were producing. Now not even that is true. Only the machine knows what the machine is doing. We just keep it tethered to our aims. Hopefully.

Vier Grafikkarten, sechs CPU-Kerne: So sah vor 14 Jahren die Höllenmaschine 4 aus

Wed, 22 Jul 2026 10:34:12 +0200

Hinweis: Dieser Artikel erschien im März 2007 auf pcwelt.de. Anlässlich unseres 20‑jährigen Jubiläums haben wir mittels der Wayback Machine des Internet Archive das zeitgeschichtliche Dokument restauriert. Wir haben alle Hyperlinks im Text belassen – sofern sie noch auf historische Inhalte führen.

Hier geht es direkt zum Gewinnspiel der aktuellen Höllenmaschine HMX 6 im Gesamtwert von 40.000 Euro. Bestens informiert bleiben Sie mit unserem HMX-6-Newsletter – aber vergessen Sie nicht, die Anmeldung via E-Mail zu bestätigen. Und nun viel Spaß mit der vierten Höllenmaschine:

Die PC-WELT Höllenmaschine 4 repräsentiert den Stand der PC-Technik. Die beste Hard- und Software ist gerade gut genug für den ultimativen Rechnertraum. Auch die vierte Generation im Wert von 13.333 Euro können Sie wieder gewinnen.

Das Rückgrat des 22 Kilogramm schweren Cooler Master Cosmos II bildet eine massive Stahlkonstruktion. Zu den Besonderheiten des 300 Euro teuren Big-Towers gehören eine zentrale Lüftersteuerung, Kabelmanagement, Flügeltüren und massig Platz: Das Gehäuse besitzt allein elf Laufwerksschächte für 3,5-Zoll-Festplatten und nimmt Hauptplatinen bis zum E-ATX-Formfaktor auf.

Airbrush der Höllenmaschine 4

Für das lodernde Airbrush und das seitliche Sichtfenster der Höllenmaschine 4 zeichnen sich die Casemodder Martin und Stefan Blass verantwortlich. Sein höllisch gutes Aussehen verdankt das Gehäuse den international bekannten Casemoddern Martin und Stefan Blass. Auf ihrer Website können Sie sich von den Fähigkeiten der kunstfertigen Casemodder überzeugen. Das preisgekrönte Brüderpaar kümmert sich nicht nur um das teuflische Airbrush und bauliche Veränderungen wie das seitliche Sichtfenster, sondern zeichnet sich auch für die Innenbeleuchtung der Gehäusemodifikation verantwortlich.

Die Gebrüder haben für den schönen Schein einen Multidimmer von Richter eingebaut, der LED-Ketten im Gehäuseinnenraum und im Bodenbereich ansteuert. Über die beiliegende Fernbedienung wählen Sie zwischen acht verschiedenen Grundfarben aus, regulieren die Helligkeit und definieren individuelle Farbwechsel.

Bei der Asus Rampage IV Extreme paart sich eine erlesene Hauptplatinen-Ausstattung mit einem detailverliebten UEFI-Bios, das keine Wünsche offen lässt: Die Sockel-LGA2011-Hauptplatine basiert auf dem Intel-Chipsatz X79. Das UEFI-Motherboard besitzt je acht Speicherbänke, SATA- und USB-Ports sowie fünfmal 16x PCI-Express 3.0. Zur Sonderausstattung gehören CMOS-, Start- und Reset-Knopf, Diagnose-LED, Bluetooth-Unterstützung und umfassende Übertaktungsoptionen, die sich zudem in Echtzeit überwachen lassen.

Prozessor: die schnellste Desktop-CPU der Welt

Der Intel Core i7-3960X ist der aktuell schnellste Desktop-Prozessor im Test. Das Intel-Flaggschiff besitzt sechs CPU-Kerne und arbeitet dank Hyperthreading als virtueller 12‑Kern‑Prozessor. Der Werkstakt liegt bei 3,3 Gigahertz, in der Höllenmaschine 4 läuft der Core i7 mit 4 GHz. Berechnungen puffert der 3960X in einem dreistufigen Cache-System: So ist die dritte Cache-Stufe, die alle Prozessorkerne dynamisch nutzen können, 15 MB mächtig. Auf die erste und zweite Cache-Stufe mit 64 beziehungsweise 256 KB darf hingegen jeder CPU-Kern exklusiv zugreifen.

Eine der wichtigsten exklusiven Funktionen der LGA2011-Baureihe ist der integrierte Speicher-Controller, der vier DDR3-Kanäle gleichzeitig ansteuert. Ebenfalls in der CPU verbaut sind 40 PCI-Express-3.0-Kanäle. Zur weiteren Ausstattung gehören der Schutz vor Angriffen durch einen Puffer-Überlauf (XD-Bit), zusätzliche Befehlssätze wie SSE 4.2 und das Advanced Encryption Standard Instruction Set (AES IS) sowie die Advanced Vector Extensions (AVX). Zudem unterstützt der Prozessor die Virtualisierungs-Technik Intel VT sowie 32- und 64-Bit-Betriebssysteme – so lassen sich etwa virtuelle Workstations mit unterschiedlichen Betriebssystemen einrichten.

Die Wasserkühlung Cooler Master Eisberg 240L Prestige gibt die CPU-Abwärme über einen Dual-Radiator an die Außenwelt ab, der zwei 120-Millimeter-Lüfter beherbergt. Das Rotationstempo der mit knapp 21 dB(A) sehr leisen Lüfter liegt bei 1600 Umdrehungen pro Minute. Im Microchannel-Kühlblock arbeitet deutsche Pumpentechnik, die bis zu 400 Liter pro Stunde durch das Kühlsystem schleudert und für mindestens 50 000 Betriebsstunden ausgelegt ist. Der keramikbeschichtete Pumpenantrieb dreht sich mit bis zu 3600 Rotationen pro Minute.

Grafik: 2x ASUS GTX690-4GD5 im Quad-SLI

Um die Grafikdarstellung kümmert sich in der Höllenmaschine 4 die derzeit leistungsfähigste Grafikkarte der Welt, die ASUS GTX690-4GD5. Kostenpunkt: knapp 1000 Euro pro Stück. Die Karte beherbergt mit der Nvidia Geforce GTX 690 gleich zwei 915 Megahertz schnelle Grafikprozessoren, die gemeinsam die 3D-Berechnung übernehmen.

PC-WELT

In der Höllenmaschine 4 sind gleich zwei der Asus-Doppeldecker, die über eine SLI-Brücke (Scalable Link Interface) verbunden sind. So arbeiten insgesamt vier Grafikprozessoren parallel im Quad-SLI-Modus. In der Summe stehen damit die Rechen-Power von 6144 Shader- und 512 Textur-Einheiten sowie 128 Rasteroperatoren bereit. Dabei kann der Karten-Verbund auf 4 Gigabyte GDDR5-Videospeicher zugreifen, der mit einem effektiven Datentakt von 6000 MHz arbeitet. Jede Grafikkarte besitzt mit einem Mini-Displayport und dreimal DVI vier digitale Ausgänge.

Ausstattung der Höllenmaschine 4 im Überblick

Komponente	Modell	Preis (Euro) am 31.8.2012
Gehäuse	Casemod auf Basis des Cooler Master Cosmos II	1413
Hauptplatine	Asus Rampage IV Extreme, Intel X79, LGA2011	350
Prozessor	Intel Core i7-3960X, 3,30 GHz, 6 Kerne, 12 Theads	900
CPU-Kühlung	Cooler Master Eisberg 240L Prestige	180
Arbeitsspeicher	8 x 8 GB Adata XPG X Series PC3-17066U	880
Grafikkarte	2 x Asus GTX690-4GD5, Nvidia Geforce GTX 690	2000
Bildschirme	3 x ASUS VG278H, 27 Zoll, 3D-LED-LCD,	1550
SSD (System)	OCZ RevoDrive 3 X2 480GB, PCI-Express, 4fach Raid-0	650
Festplatten (Daten intern)	4 x Western Digital VelociRaptor 1000GB, Raid-5	1000
Festplatten (Daten extern)	2 x Western Digital Caviar Green 3000GB	300
Blu-ray-Brenner	Asus BW-12B1ST, SATA	100
Netzteil	Cooler Master Silent Pro Hybrid 1300W	250
Eingabegerät	Logitech G9x Laser Mouse und G19 Gaming Keyboard	200
Lautsprecher-Set	Logitech Z906, 5.1 System	250
Headset	Logitech G930 Wireless Gaming Headset	150
Betriebssystem	Microsoft Windows 7 Ultimate 64 Bit	160
Multimedia-Paket	Adobe Creative Suite 6 Design & Web Premium	2000
Spiele-Paket	18 Top-Titel	600
Office-Paket	Microsoft Office Professional 2010	400

PC-WELT

Monitore: PC-Spiele in 3D auf 3 Panels gleichzeitig

Der Höllenmaschine 4 stellen wir den 27-Zoll-Bildschirm ASUS VG278H zur Seite. Die physikalische Auflösung des 120-Hertz-Monitors beträgt 1920 x1080 Pixel, die Reaktionszeit 2 Millisekunden. Die LED-Hintergrundbeleuchtung erzielt eine Helligkeit von 300 cd/m2 und unterstützt die Lightboost-Technik und damit natürlich auch Nvidia 3D Vision 2 – eine Technologie, die das Spielen in der dritten Dimension möglich macht. Im Lieferumfang des Asus-LCDs ist das “Nvidia 3D Vision”-Set aus Infrarot-Sender (integriert im Bildschirmrahmen) und Shutter-Brille enthalten. Der VG278H bietet mit DVI, HDMI und D-Sub drei Videoeingänge sowie einen Kopfhöreranschluss.

Ein großer 27-Zoll-Monitor ist gut, doch drei ASUS VG278H sind besser. Die gebündelte Auflösung des Bildschirm-Trios von 5760 x 1080 Pixeln erlaubt einen Desktop, auf dem sich bequem arbeiten lässt: Da kann man zahlreiche Fenster in ihrer vollen Größe geöffnet lassen, und behält dennoch den Überblick. Interessant ist diese große Arbeitsumgebung auch für Grafiker und Video-Bearbeiter, die dadurch gleich mehrere Projekte am Laufen halten, ohne eines schließen zu müssen.

Ernsthaften PC-Spielern kann dagegen die Bildschirmgröße nicht groß genug sein – denn sie bedeutet größere Übersicht und ein realistischeres Spielerlebnis. So füllt etwa die wunderschöne Landschaft in Skyrim die volle Breite der drei Monitore aus und wirkt dadurch schon fast wie ein echter Horizont, der Lust auf das Erkunden macht. Dank der brachialen Leistung der Höllenmaschine 4 und Nvidia 3D Vision Surround geht das auch flüssig in stereoskopischem 3D.

Arbeitsspeicher: Quad-Channel mit 64 Gigabyte

Speicher kann man nie genug haben! Die acht Module Adata XPG X Series PC3-17066U mit jeweils 8 Gigabyte Kapazität steuert der Controller in der Intel-CPU im Vierkanal-Modus an. Die Module laufen mit 10-11-11-30er-Zugriffszeiten. Der mit dem Extreme Memory Profile (XMP) effektiv 2133 Megahertz schnelle Arbeitsspeicher beschert der Höllenmaschine 4 eine Speicherbandbreite von über 45 Gigabyte pro Sekunde. Da macht Virtualisierung so richtig Spaß.

PCI-Express-SSD, 4 WD VelociRaptor und 4 WD Caviar Green

Das Betriebssystem und alle Programme dürfen auf der Solid State Drive OCZ RevoDrive 3 X2 480GB Platz nehmen. Die Flashspeicher-Festplatte arbeitet mit vier Sandforce-SF-2281-Controllern intern als Raid-0-Verbund. Dadurch erreicht die SSD eine Datentransferrate von in der Spitze fast 1400 Megabyte pro Sekunde und einen Befehlsdurchsatz von bis zu 230.000 IOPS beim zufälligen Schreiben von 4-KB-Blöcken. Eine herkömmliche SATA-Schnittstelle würde das OCZ-Modell ausbremsen, deswegen setzt das RevoDrive auf einen PCI-Express-Anschluss.

OCZ/Kioxia

Das interne Backup übernimmt ein RAID-5‑Verbund aus vier 1-Terabyte-Festplatten. Dabei kommt das derzeit schnellste 3,5-Zoll-Laufwerk im Test zum Einsatz, die Western Digital VelociRaptor WD1000DHTZ. Die VelociRaptor rotiert mit 10.000 Umdrehungen pro Minute und puffert Zugriffe in einem 64 MB großen Cache. Die maximale Datenrate der Festplatte liegt bei 210 Megabyte pro Sekunde, die durchschnittliche Zugriffszeit bei 3,7 Millisekunden. Als RAID-5‑Verbund kommt das Platten-Quartett auf bis zu 560 Megabyte pro Sekunde und stellt dabei noch knapp 2,7 Gigabyte nutzbare Kapazität zur Verfügung.

Die Aufgabe des klassischen Massenspeichers für umfangreiche Foto-, Musik- und Videosammlungen übernehmen die beiden 3,5-Zoll-Festplatten Western Digital Caviar Green 3000GB WD30EZRX. Die besonders stromsparenden Laufwerke stecken in den zwei abschließbaren Hot-Swap-Schächten der Höllenmaschine 4. So lassen sich schnell und bequem knapp 5,5 Terabyte nutzbarer Speicherplatz im laufenden Betrieb an- und abstöpseln oder auch mal unkompliziert von A nach B tragen.

Stromversorgung: bis zu 105 Ampere auf der 12-Volt-Schiene

Keine Kompromisse machen wir bei der Stromversorgung der Höllenmaschine 4. Das Cooler Master Silent Pro Hybrid 1300W bietet genügend Reserven, um alle Komponenten zuverlässig mit Energie zu versorgen. Das vollständig modulare Netzteil stellt auf der 12-Volt-Schiene in der Spitze bis zu 105 Ampere bereit und federt damit auch locker die Lastspitzen der stromhungrigen Grafikkarten ab.

Aufgrund der “80 PLUS Gold“-Zertifizierung arbeitet das ATX-2.3-Kraftpaket mit einem Wirkungsgrad von über 90 Prozent trotzdem sehr energieeffizient. Dank der semipassiven Kühlung ist das 1300-Watt-Netzteil aber auch flüsterleise. Zudem erlaubt die im Lieferumfang enthaltene 5,25-Zoll-Lüftersteuerung neben dem automatischen Modus ein stufenlos regulierbares Drehtempo für den 130-Millimeter-Lüfter – bei harter Dauerbelastung drehen Sie den Regler einfach voll auf.

Um optische Massenspeicher kümmert sich der Blu-ray-Brenner Asus BW-12B1ST. Das Multi-Norm-Laufwerk versteht sich aber auch auf alle gängigen CD- und DVD-Formate. Bei maximal 12-fachem Schreibtempo füllt das Asus-Modell einen einlagigen 25-GB-BR-Rohling in rund 11 Minuten. BD-REs beschreibt das SATA-Laufwerk mit 2-fachem Tempo, Blu-ray-Medien liest er mit 8-facher Geschwindigkeit. Im Lieferumfang des Asus BW-12B1ST ist Software für das Backup, Brennen und Abspielen von Blu-rays enthalten.

Peripherie: Luxus-Eingabegeräte und 5.1-Raumklang

Die Logitech G9x Laser Mouse kommt mit einem 4-Wege-Scrollrad und löst mit bis zu 5700 dpi auf. Die USB-Maus besitzt eine anpassbare Griffschale sowie ein bis auf 28 Gramm aufrüstbares Gewichtsmagazin. Der interne Speicher sichert bis zu fünf Profile für individuelle Tastatur-Makros und Abtastraten.

Das Logitech G19 Gaming Keyboard besitzt ein integriertes Farb-LCD, das in Echtzeit Spiele-Informationen wie die Server-IP-Adresse oder den Punktestand für über 35 Titel anzeigt. Die G19 erlaubt verschiedene Beleuchtungsfarben und hat 12 voll programmierbare G-Tasten sowie Sondertasten für den schnellen Multimedia-Zugriff. Das Logitech-Modell fungiert aber auch als aktiver 2-fach-USB-Hub und überrascht mit einer Kabelführung auf der Unterseite für Maus und Headset.

Logitech

Das THX-zertifizierte Lautsprecherset Logitech Z906 bietet 5.1-Raumklang mit digitaler Dolby- und DTS-Decodierung. Bis zu sechs digitale und analoge Audioquellen lassen sich gleichzeitig an die Bedienkonsole anschließen. Alternativ bedienen Sie das 500-Watt-Lautsprechersystem kabellos über die Fernbedienung.

Wer nachts die Nachbarn nicht stören darf, greift zum Logitech G930 Wireless Gaming Headset. Das funkt digital mit 2,4 Gigahertz zehn Stunden lang über eine Reichweite von bis zu 12 Metern. Das Headset kommt mit drei programmierbaren Tasten, Geräuschunterdrückung und Kondensatormikrofon. Dank der Dolby-Technik Headphone und Pro Logic II kann das G930 sogar 7.1-Surround-Sound simulieren.

Kreativ-, Spiele- und Office-Paket für 4000 Euro

Auf der Höllenmaschine 4 vorinstalliert haben wir das 64-Bit-Betriebssystem Windows 7 Ultimate. Für das Microsoft-Betriebssystem haben wir uns auch wegen der DirectX-11-Unterstützung entschieden. Das laut Windows-Experte Hermann Apfelböck “beste Windows aller Zeiten” verwöhnt in der multilingualen Ultimate-Variante mit den exklusiven Funktionen Bitlocker-Verschlüsselung und dem nützlichen VHD-Boot.

Dazu gibt es drei fette Software-Pakete frei Haus. Das Highlight für Kreative ist die Adobe Creative Suite 6 Design & Web Premium. Die „Rundum glücklich“-Lösung für professionelle Bildbearbeitung, Layout und Website-Design integriert die Digital Publishing Suite und enthält folgende Programme und Werkzeuge: Acrobat X Pro, Bridge, Dreamweaver, Flash Builder, Flash Professional, Fireworks, Illustrator, InDesign, Media Encoder und Photoshop Extended.

Was zum Spielen spendiert Grafikspezialist Nvidia der Höllenmaschine 4. Das Gaming-Paket enthält die AAA-Titel Alan Wake Collector’s Edition, Batman: Arkham City, Battlefield 3, Borderlands, Call of Duty: Modern Warfare 3, Crysis 2, Diablo 3, Deus Ex: Human Revolution, Duke Nukem Forever, L.A. Noire, Mass Effect 3, Max Payne 3, Metro 2033, Rage, Skyrim, Starcraft II: Wings of Liberty, Star Wars. The Old Republik, The Witcher 2: Assassins of Kings.

Und wer die Höllenmaschine im Büroeinsatz unterfordern will, installiert Microsoft Office Professional 2010. Das Paket enthält die Programme Access, Excel, InfoPath, OneNote, Outlook, Powerpoint, Publisher, SharePoint, Word und Workspace.

Hinweis: Hier endet der Artikel über die Höllenmaschine 4 aus dem Jahre 2014.

So gewinnen Sie die HMX 6

Auch dieses Jahr verlosen wir die Höllenmaschine unter allen Teilnehmern:

Gewinnen Sie hier die HMX 6

Wie Sie die HMX 6 verfolgen können

In den kommenden Wochen folgen weitere Inhalte rund um die Höllenmaschine 6 auf YouTube, Instagram, TikTok, Facebook und natürlich auf pcwelt.de. Wenn Sie nichts verpassen wollen, sollten Sie den kostenlosen HMX-6-Newsletter abonnieren – aber vergessen Sie nicht, die Anmeldung via E-Mail zu bestätigen.

China Just Dropped an Ultra-Realistic Bionic Humanoid You Can Buy RIGHT NOW!

Wed, 22 Jul 2026 09:51:26 +0200

Author: Evolving AI - Bewertung: 0x - Views:2

China may have just unveiled the most human-like robot the world has ever seen. UBTech's new UWORLD U1 Series features realistic silicone skin, emotion-aware AI, long-term memory, ultra-smooth movement, and the ability to recognize your emotions while remembering conversations over time. But the biggest surprise isn't the technology; it's that these robots are already entering mass production with thousands of orders.

In this video, we break down UBTech's U1 humanoid robot, its emotion-aware AI, Agent Memory OS, 88 degrees of freedom, ultra-bionic design, pricing, real-world applications, and the controversial feature that allows the robot to recreate a real person's face and voice. We also explore what this means for the future of AI companions, elder care, robotics, and the rapidly growing humanoid robot industry. Could this be the beginning of a future where robots become part of everyday life?

#HumanoidRobot #UBTech #ArtificialIntelligence #China #Robotics #AI #Technology #FutureTech

Exploitarium Mass Zero-Day Archive Releases 204 PoC Files Targeting 35 Open-Source Projects

Wed, 22 Jul 2026 09:16:23 +0200

A GitHub account known as “bikini,” operating under the Exploitarium name, has published a large and expanding archive of vulnerability proof-of-concept (PoC) files targeting 353535 open-source projects. The repository contains 204204204 tracked files, exceeding earlier reports that cited roughly 130130130 PoCs. Its first dated entries appeared on June 232323, 202620262026, and the archive drew broad […]

The post Exploitarium Mass Zero-Day Archive Releases 204 PoC Files Targeting 35 Open-Source Projects appeared first on Cyber Security News.

Verwaltungsdigitalisierung stockt: Reifegrad 4 nur in jeder siebten Behörde

Wed, 22 Jul 2026 06:10:22 +0200

Digitale Souveränität bringt Substanz in die Debatte um die Digitalisierung der öffentlichen Verwaltung. Experten finden: Wir sollten sie nutzen, um wohl überlegte Ansätze zu realisieren – und nicht Innovation um jeden Preis.

Golden Sikorka – shutterstock.com

Das Onlinezugangsgesetz (OZG) hat 2017 den Anspruch formuliert, Verwaltungsleistungen digital und medienbruchfrei nach dem Once-Only-Prinzip (OOP) zu machen und sie damit auf Reifegrad 4 zu bringen. Fast ein Jahrzehnt danach sind jedoch erst 28 Prozent der Verwaltungsleistungen vollständig digitalisiert, 34 Prozent existieren noch offline. Den Reifegrad 4 erreichen sogar nur 14 Prozent der Behörden, fast zwei Drittel (65 Prozent) haben keinen verbindlichen Termin dafür. So lautet das zentrale Ergebnis der Studie „Digitalisierung in der öffentlichen Verwaltung 2026“, die CIO und COMPUTERWOCHE mit den Partnern UiPath und Materna durchgeführt haben und an der 316 Entscheiderinnen und Entscheider aus deutschen Behörden teilnahmen.

Kaum Erfolgskontrolle bei Digitalisierungsprojekten

Das Automatisierungspotenzial der Verwaltungsaufgaben liegt im Schnitt bei 49 Prozent, tatsächlich automatisiert sind bislang nur 23 Prozent. Diese Lücke von 26 Prozentpunkten deutet darauf hin, dass die Bereitschaft zur Digitalisierung vorhanden ist, es an der Umsetzung jedoch hapert. End-to-End digitalisiert sind 32 Prozent der Prozesse, mit Dunkelverarbeitung laufen erst 17 Prozent.

Für Dirk Moeller, Regional Vice President Public Sector bei UiPath, zeigt dieses Ergebnis, dass „die öffentliche Verwaltung kein Erkenntnisproblem, sondern ein Umsetzungsproblem hat. Fast die Hälfte der Verwaltungsaufgaben könnte automatisiert werden, tatsächlich ist es aber erst knapp ein Viertel. Der nächste Digitalisierungsschub entsteht daher nicht durch weitere Einzellösungen, sondern durch orchestrierte End-to-End-Prozesse, in denen Menschen, Fachverfahren, Daten, Roboter und KI-Agenten kontrolliert zusammenarbeiten.“

Dirk Moeller, Regional Vice President Public Sector bei UiPath

: Die öffentliche Verwaltung hat kein Erkenntnisproblem, sondern ein Umsetzungsproblem.

UiPath GmbH

Immerhin ein Drittel der Behörden führt 2026 aktiv Digitalisierungsprojekte durch, weitere 29 Prozent planen die nächste Welle für 2027. Die Vorhaben sind breit angelegt, in knapp drei Viertel der Fälle hierarchieübergreifend (74 Prozent) und mit externer Begleitung (73 Prozent). Doch es gibt ein Gefälle nach Behördengröße: Während 40 Prozent der Häuser mit 1000 und mehr Beschäftigten Projekte aktiv realisieren, sind es nur 19 Prozent der kleineren Behörden mit weniger als 250 Beschäftigten.

Ob die Projekte tatsächlich Wirkung entfalten, weiß häufig niemand, da nur elf Prozent den Digitalisierungserfolg systematisch und weitere 29 Prozent gelegentlich messen. Über ein Viertel der Befragten (26 Prozent) verzichtet auf eine Erfolgskontrolle. Dabei zeigt sich: Wer die Digitalisierung verantwortet, misst sie häufiger: Kontrollieren 58 Prozent der IT- und Digitalisierungsverantwortlichen den Fortschritt, sind es bei der Fachverwaltung nur 42 Prozent.

IT-Infrastruktur-APIs und Register als Reifegrad-4-Verhinderer

Der langsame Fortschritt auf dem Weg zu Reifegrad 4 ist vor allem auf Defizite in der IT-Infrastruktur zurückzuführen: Die Hälfte der Behörden bewertet diese im Hinblick auf OOP und Reifegrad 4 als „schlecht“ oder „sehr schlecht“, nur 21 Prozent als „gut“ oder „sehr gut“. APIs haben ebenfalls erst 49 Prozent, und Interoperabilität mit anderen Behörden besteht nur in 44 Prozent der Fälle. Gerade einmal sieben Prozent nutzen zudem standardisierte Datenmodelle wie XÖV; lediglich 17 Prozent können Datensätze systemübergreifend eindeutig identifizieren.

Dramatisch ist die Lage bei den Registern, von denen nur acht Prozent Once-Only-fähig sind. Über ein Viertel der Behörden (27 Prozent) führt ihre wichtigsten Register auf Papier, 38 Prozent verwalten sie in Excel. Als größte Hürden nennen 36 Prozent der Befragten technische Defizite und ein Drittel den Personalmangel.

EfA und Cloud: Akzeptanz hoch, Umsetzung ausbaufähig

Der „Einer für alle“-Ansatz (EfA) soll die Verwaltung von Mehrfacharbeit befreien: Hat eine Behörde eine funktionsfähige Lösung entwickelt, stellt sie diese anderen zur Nachnutzung bereit. 86 Prozent der Behörden bewerten das Modell prinzipiell positiv, doch die Bilanz bei der Umsetzung ist ernüchternd. Erst magere 19 Prozent nutzen EfA-Lösungen oder stellen sie bereit. Lediglich 18 Prozent derjenigen mit EfA-Praxiserfahrung beurteilen die Gebrauchsfähigkeit als „gut“ oder „sehr gut“, 14 Prozent dagegen als „schlecht“ oder „sehr schlecht“ und 37 Prozent als „eher schlecht“. Als größte Bremsen werden rechtliche Unsicherheiten (39 Prozent), fehlende Standards (37 Prozent) und föderale Unterschiede (35 Prozent) genannt.

Weniger zäh verläuft die Cloud-Adaption. Immerhin 39 Prozent der Behörden nutzen inzwischen Cloud-Dienste, weitere 22 Prozent planen dies. Die mit Abstand größte Hürde für den Cloud-Einsatz sind Datenschutzanforderungen wie die DSGVO (59 Prozent), gefolgt von Unsicherheiten bei der Datenhoheit (43 Prozent) und der Informationssicherheit (41 Prozent). Auffallend ist, dass Behördenleitende (78 Prozent) und IT-Verantwortliche (76 Prozent) deutlich häufiger angeben, Cloud-Dienste zu nutzen oder den Einsatz zu planen, als die Leitungsebene (63 Prozent) und die Fachverwaltung (64 Prozent).

Die größte Hürde für den Cloud-Einsatz sind Datenschutzanforderungen wie die DSGVO

Research Services: Patrick Birnbreier

Deutsche Verwaltungscloud mit Zufriedenheitsdefizit

Die 2025 gestartete Deutsche Verwaltungscloud (DVC) soll bei der Modernisierung der IT-Infrastruktur eine Schlüsselrolle spielen. Doch was die DVC konkret leisten soll, bleibt unklar. 37 Prozent der Befragten sehen sie eher als Ergänzung, 22 Prozent als Ersatz vorhandener Infrastrukturen.

Dabei sind die Erwartungen verhalten. Nur sechs Prozent rechnen mit einer deutlichen Verbesserung, weitere 22 Prozent mit einer Verbesserung, 28 Prozent gehen von einer eher positiven Entwicklung aus. Auffallend ist hier der hohe Anteil von 29 Prozent „Weiß nicht“-Antworten, der möglicherweise darauf zurückzuführen ist, dass sich 52 Prozent nur schlecht bis sehr schlecht mit der DVC auskennen. Auch die Zufriedenheit mit der DVC bleibt überschaubar: Lediglich 18 Prozent bewerten den Standardisierungsgrad positiv, 16 Prozent die Interoperabilität und 23 Prozent den DVC-Marktplatz. Einzig die digitale Souveränität schneidet mit 25 Prozent etwas besser ab.

Johannes Rosenboom, SVP Sales, Marketing, BDM für Public-/KRITIS-Branchen bei Materna, ist jedoch davon überzeugt, dass „die Deutsche Verwaltungscloud ein wichtiger Baustein für eine souveräne, leistungsfähige und anschlussfähige Verwaltungs-IT werden kann. Entscheidend ist, dass sie nicht als isolierte Infrastruktur gedacht wird, sondern als Teil eines offenen Ökosystems mit klaren Standards, interoperablen Plattformen und hoher Wechselfähigkeit.“

Johannes Rosenboom, SVP Sales, Marketing, BDM für Public-/KRITIS-Branchen bei Materna

: Die Deutsche Verwaltungscloud kann ein wichtiger Baustein für eine souveräne, leistungsfähige und anschlussfähige Verwaltungs-IT werden.

Materna Information & Communications SE

KI-Einstieg gemacht, Kompetenzlücken bremsen

Neben der Infrastruktur und der Cloud rückt Künstliche Intelligenz (KI) zunehmend in den Fokus. Erfreulich ist, dass 29 Prozent der Behörden entsprechende Werkzeuge bereits nutzen und 17 Prozent die Einführung in den nächsten zwei Jahren planen. Häuser mit 1000 und mehr Beschäftigten (35 Prozent) liegen beim KI-Einsatz klar vor kleineren Verwaltungen unter 250 Beschäftigten (22 Prozent). Dominant sind generative KI und Large Language Models (LLMs) mit 55 Prozent, gefolgt von intelligenter Dokumentenverarbeitung (35 Prozent). Eingesetzt werden die KI-Tools vorrangig für das Dokumenten- und Aktenmanagement (41 Prozent), im Bürgerservice (36 Prozent) und zur Antragsbearbeitung (35 Prozent).

Auch KI-Agenten kommen gut an. Acht von zehn Behörden, die KI nutzen, bewerten ihren Einsatz positiv. „KI-Agenten können in der Verwaltung zum Produktivitätssprung werden, aber nur, wenn sie nachvollziehbar, sicher und steuerbar eingesetzt werden. Gerade in den Bereichen Antragsprüfung, Fallvorbereitung, Dokumentenverarbeitung und Bürgerkommunikation liegt enormes Potenzial. Entscheidend ist, dass KI-Agenten nicht als Black Box arbeiten, sondern in klare Governance, menschliche Entscheidungen und revisionssichere Prozesse eingebettet sind“, verdeutlicht UiPath-Manager Moeller. Ähnlich argumentiert Rosenboom: „KI entfaltet in den Behörden besonders dort ihre Wirkung, wo Wissen, Dokumente und Prozesse zusammengeführt werden. Der nächste Schritt ist, KI sicher, nachvollziehbar und souverän in bestehende Fachlichkeit zu integrieren, mit klaren Leitplanken und spürbarem Nutzen im Verwaltungsalltag.“

Wie berechtigt diese Forderungen sind, belegen konkrete Hemmnisse. Als größtes gilt wie schon bei der Cloud der Datenschutz (48 Prozent), gefolgt von Halluzinationen (35 Prozent) und Haftungsrisiken (32 Prozent). Das größte Problem ist jedoch, dass nur 31 Prozent der Behörden nach eigener Einschätzung in ausreichendem Maß über die notwendigen Daten- und KI-Kompetenzen verfügen und somit KI-Initiativen ohne gezielte Qualifizierungsoffensive zu versanden drohen.

Digitale Portale als Frage staatlicher Handlungsfähigkeit

Die Studie lenkt den Blick auch auf eine gesellschaftspolitisch brisante Zukunft. Sollte der demografische Wandel dazu führen, dass kleine Kommunen ihr Bürgeramt in fünf bis zehn Jahren nicht mehr betreiben können, müssen digitale Portale rechtzeitig als Ersatz bereitstehen. Falls nicht droht ein Staatsversagen im digitalen Raum. 69 Prozent der Behörden halten diese Gefahr für real, davon 36 Prozent für groß bis sehr groß. Kleine Verwaltungen unter 250 Beschäftigten schätzen dabei das Risiko mit 46 Prozent deutlich höher ein als große Häuser (30 Prozent). Am meisten alarmiert sind die IT-Verantwortlichen (46 Prozent), am wenigsten die Leitungsebene (30 Prozent) Das zeigt: Die Digitalisierung der Verwaltung entscheidet über die Handlungsfähigkeit des Staates.

Die neue Studie “Digitalisierung in der öffentlichen Verwaltung 2026” von CIO, COMPUTERWOCHE und Research Services

Research Services: Patrick Birnbreier

Studiensteckbrief

Herausgeber: CIO und COMPUTERWOCHE

Studienpartner: UiPath GmbH; Materna Information & Communications SE

Grundgesamtheit: Oberste (IT-)Verantwortliche in Unternehmen der DACH-Region: Beteiligte an strategischen (IT-)Entscheidungsprozessen im C-Level-Bereich und in den Fachbereichen (LoBs); Entscheidungsbefugte sowie Experten und Expertinnen aus dem IT-Bereich

Teilnehmergenerierung: Persönliche E-Mail-Einladung über die Entscheiderdatenbank von CIO und COMPUTERWOCHE sowie – zur Erfüllung von Quotenvorgaben – über externe Online-Access-Panels

Gesamtstichprobe: 316 abgeschlossene und qualifizierte Interviews

Untersuchungszeitraum: 12. bis 21. März 2026

Methode: Online-Umfrage (CAWI) Fragebogenentwicklung & Durchführung: Custom Research Team von CIO und Computerwoche in Abstimmung mit den Studienpartnern

Die besten JavaScript-Editoren

Wed, 22 Jul 2026 05:40:30 +0200

width="1024" height="576" sizes="auto, (max-width: 1024px) 100vw, 1024px">

Diese Texteditoren bringen JavaScript-Developer weiter.

R.Narong | shutterstock.com

JavaScript-Entwicklern stehen viele gute Tools zur Auswahl. Beinahe zu viele, um den Überblick zu behalten. In diesem Artikel stellen wir Ihnen die besten Texteditoren vor, um:

mit JavaScript, HTML5 und CSS zu entwickeln, sowie
mit Markdown zu dokumentieren.

Sublime Text

Bei Sublime Text sind Sie genau richtig, wenn:

Sie einen flexiblen, leistungsstarken, erweiterbaren und ausgesprochen schnellen Code-Editor suchen.
es Ihnen nichts ausmacht, für Code Checking, Debugging und Deployment zu anderen Fenstern zu wechseln.

Zu den vielen weiteren, bemerkenswerten Stärken von Sublime Text gehören neben seiner Geschwindigkeit und dem Support für mehr als 70 Datei-Typen (darunter JavaScript, HTML und CSS) auch noch:

Instant-Navigation und Projekt-Switching,
die Option, eine Reihe von Änderungen per Mehrfachauswahl „auf einen Schlag“ auszuführen,
Support für mehrere Bildschirme und Split-Windows,
eine Plug-in-API auf Python-Basis, sowie
eine einheitliche, durchsuchbare Befehlspalette.

Sublime Text ist in vielerlei Hinsicht konfigurier- und anpassbar.

IDG

Für Programmierer, die von anderen Editoren kommen, hilfreich: Sublime Text unterstützt sowohl TextMate-Bundles (ohne Befehle) als auch die Vi/Vim-Emulation. Dabei lässt sich der Code-Editor in so gut wie jeder Hinsicht anpassen, egal, ob es um Farbschemata, Schriftarten, Tastenkombinationen, Snippets oder die Regeln für die Syntaxhervorhebung geht.

Rund um Sublime Text existiert ebenfalls eine aktive Community, die Packages und Plug-ins erstellt und pflegt. Mit Hilfe des Package Installers sind diverse zusätzliche Funktionen verfügbar.

Preis: unbegrenzte kostenlose Testversion; 65 Dollar pro Jahr und Seat für die Business-Version; 99 Dollar für eine Privatlizenz (Support für drei Jahre);
Plattformen: Windows, macOS und Linux;

Visual Studio Code

Visual Studio Code ist ein quelloffener, kostenloser Editor von Microsoft. Er enthält einen Mix aus Komponenten von Visual Studio und der Open-Source-Shell Atom Electron und bietet umfassenden Support für:

ASP.Net Core Development mit C# und
Node.js Development mit TypeScript und JavaScript.

Dank des TypeScript-Compilers und der Salsa-Engine bietet Visual Studio Code eine erstaunlich gute JavaScript-Codevervollständigung. Dazu sendet VS Code Ihren JavaScript-Code im Hintergrund an den TypeScript-Compiler, um Typen abzuleiten und eine Symboltabelle zu erstellen.

Visual Studio Code darf in einer Auflistung der besten JavaScript-Editoren nicht fehlen.

IDG

Während Sie eine Expression eingeben, ermöglicht dieselbe Symboltabelle es IntelliSense, diverse nützliche Pop-up-Optionen zur Codevervollständigung zur Verfügung zu stellen.

Der Support für Git ist umfangreich und simpel zu nutzen, der VS-Code-Debugger bietet eine hervorragende Erfahrung für Node.js und ASP.Net-Projekte. Visual Studio Code kann darüber hinaus auch mit externen Task-Runnern wie gulp und jake integriert werden und kann mit einem umfangreichen Ökosystem für Extensions aufwarten.

Preis: kostenlos;
Plattformen: Windows, macOS, Linux;

Brackets

Brackets ist ein kostenloser Open-Source-Editor, der ursprünglich von Adobe stammt. Das Ziel der Entwickler: Bessere Tools für JavaScript, HTML, CSS und verwandte, offene Webtechnologien bereitzustellen. Auch Brackets selbst ist in JavaScript, HTML und CSS geschrieben.

Zusätzlich zu den integrierten Funktionen verfügt Brackets über einen Extension Manager. Der ist auch nötig, denn die sind für diverse Programmiersprachen und Tools aus der Welt der Frontend-Entwickler verfügbar. In der Praxis ist Brackets zwar nicht so schnell wie Sublime Text (siehe weiter oben) oder TextMate (siehe weiter unten). Aber der Editor ist immer noch schnell genug. Brackets bietet umfassenden Support für:

JavaScript,
CSS,
HTML und
Node.js.

Darüber hinaus bietet Brackets weitere nützliche Funktionen wie beispielsweise:

CSS inline in Verbindung mit einer HTML-ID bearbeiten,
eine übersichtliche Benutzeroberfläche und
eine Live-Vorschau für Webseiten in Bearbeitung.

Brackets ist in erster Linie für die Webentwicklung konzipiert.

IDG

Auch beim Blick auf die automatische Vervollständigung von JavaScript-Code kann Brackets in der Praxis überzeugen: Es schließt automatisch sämtliche Klammern und stellt Dropdown-Menüs für Keywords, Variablen und Methoden zur Verfügung. Der JavaScript-Editor ist auch in der Lage, den Node.js-Debugger zu steuern und Node über ein Menüelement neu zu starten. Erweiterungen für zusätzliche Funktionen wie TypeScript– und JSX-Support, Bower- und Git-Integration lassen sich schnell und einfach hinzufügen.

Preis: kostenlos;
Plattformen: Windows, macOS, Linux;

Atom

Dieser kostenlose, quelloffene und “hack”-bare Programmier-Editor stammt aus dem Hause GitHub und lässt sich in die entsprechende Anwendung integrieren. Tausende von Packages und Themes stehen zur Verfügung, um Atom anzupassen. Der Quellcode von Atom wird selbstverständlich auch auf GitHub gehostet, ist in CoffeeScript geschrieben und in Node.js integriert.

Bei Atom handelt es sich um eine spezialisierte Variante von Chromium, die eher als Texteditor denn als Webbrowser konzipiert ist. Jedes Atom-Fenster ist im Wesentlichen eine lokal gerenderte Webseite.

Der Open-Source-Editor von GitHub kann in der Praxis überzeugen.

IDG

In der Praxis zeigt sich Atom performant. Der Editor ist sofort einsatzbereit und überzeugt unter anderem mit:

einem “Fuzzy-Finder”,
der Möglichkeit, schnell und projektübergreifend zu suchen,
Multi-Cursor- und Windows-Optionen,
Snippets und Code-Folding sowie
der Möglichkeit, TextMate-Grammatiken und -Themen zu importieren.

Atom ist insbesondere praktisch, um Repositories zu durchsuchen, die von GitHub geklont wurden, weil die GitHub-Applikation zu diesem Zweck ein Kontextmenüelement enthält.

Preis: kostenlos;
Plattformen: Windows, macOS, Linux;

Notepad++

Ein weiterer kostenloser Open-Source-Editor, der gut für JavaScript geeignet ist – allerdings nur auf Windows läuft. Notepad++ unterstützt außerdem etwa 50 weitere Programmier- und Markup-Sprachen. Neben seinem Multi-Document-Editing-Fenster bietet dieser Editor auch eine “Workspace Tree View”, sowie Registerkarten mit Funktionslisten und Dokumentenübersicht. In der Praxis bekommt man dabei nie das Gefühl, ausgebremst zu werden.

Mit Syntax-Farb- und -Folding-Optionen, leistungsstarken Editing-Funktionen sowie Paramter-Hints hat Notepad++ das Zeug zum primären JavaScript-Texteditor. Allerdings ist es bei weitem nicht der umfassendste JavaScript-Editor, wenn es darum geht:

Code zu generieren,
Refactoring anzustoßen oder
schnell durch große Projekte zu navigieren.

Nichtsdestotrotz ist Notepad++ ist auch heute noch nützlich – vor allem, wenn es schnell und kostenlos gehen muss.

Preis: kostenlos;
Plattform: Windows;

BBEdit

Mit BBEdit steht auch für macOS-Benutzer ein proprietärer JavaScript-Editor bereit. Er unterstützt etwa 35 Programmier- und Markup-Sprachen. Für viele weitere Sprachen ist Community-Support (von unterschiedlicher Qualität) über die BBEdit-Website verfügbar. Sowohl die kostenlose als auch die lizenzierte Version bieten Syntaxhervorhebung. Code-Vervollständigung für Funktions- und Variablennamen, einige Keywords und ctags bleiben den Nutzern der kostenpflichtigen Version vorbehalten. Diese lässt sich auch in die Versionskontrollsysteme Git, Perforce und Subversion integrieren.

BBEdit wurde bereits vor einiger Zeit grundlegend überarbeitet und überzeugt in der Praxis nun auch, wenn es größere Dateien verarbeiten muss. Auch was HTML und Markdown angeht, gibt es nichts zu beanstanden – das funktioniert sogar besser als JavaScript.

Preis: kostenlose aber eingeschränkte Version; 59,99 Dollar pro Benutzer für die Vollversion;
Plattform: macOS;

TextMate

Dieser (ebenfalls macOS-exklusive) Code-Editor war einmal der letzte Schrei, verlor dann stark an Bedeutung und wird inzwischen wieder aktiv weiterentwickelt. TextMate ist zwar keine IDE, lässt sich aber über Bundles, Snippets, Makros und sein Scoping-System mit Funktionen ausstatten, die selbst sprachspezifische Entwicklungsumgebungen vermissen lassen. Was die Geschwindigkeit angeht, ist TextMate fast so schnell wie Sublime Text.

Für eine IDE-ähnliche Funktionalität können Sie die Shell-Integration von TextMate verwenden, erwarten Sie aber kein Code Refactoring oder automatische Unit- und Regressionstests. Wenn Sie Grunt richtig einrichten, können Sie Ihre JavaScript-Tests auf dieser Ebene natürlich trotzdem automatisieren.

TextMate bietet diverse Bundles.

IDG

Auch Support für Markdown wird über ein integriertes Bundle bereitgestellt. Dieses enthält:

eine Preview-Funktion für Dokumente,
ein Markdown-„Cheatsheet“ sowie
diverse Tastenkombinationen, um Markup zu generieren.

Um TextMate mit Git und GitHub zu integrieren, eignet sich hingegen das Git-Bundle gut. In der Praxis erkennt TextMate vorhandene Git-Repositories und kann diese per Pull-Befehl aus dem Bundle von GitHub aktualisieren. Mit dem SQL-Bundle können Sie mit MySQL- und PostgreSQL-Datenbanken arbeiten.

Preis: kostenlos;
Plattform: macOS;

(fm)

Dieser Beitrag ist im Original bei unserer Schwesterpublikation Infoworld.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.

Airbus Migrating 70 Critical Apps From AWS to France's Scaleway

Wed, 22 Jul 2026 01:15:37 +0200

Airbus is moving 70 critical applications from AWS to French cloud provider Scaleway as part of a broader digital sovereignty push to keep sensitive data "under European control." Eventually, the migration will cover 900 applications, including ERP, CRM, manufacturing execution, and product lifecycle management systems. Airbus says it will, however, continue using U.S. providers for less sensitive workloads. "We do not intend to move away from all non European solutions; we balance our choices based on the criticality of the data," the company said. The Register reports: Catherine Jestin, head of digital at Airbus, told us on Thursday: "The selection of Scaleway is a combination of a very strong technical answer and a very strong commercial offer making it competitive compared to hyperscalers' public cloud offerings. In addition, Scaleway is committed to involving Airbus in the definition of its future product roadmap." "The objective is to host Airbus's most critical applications (those required for the Minimum Viable Company). This represents 900 applications and we will start with 70 of them today hosted on AWS." Applications being sent to Scaleway include ERP, manufacturing execution systems, CRM, and product lifecycle management. Finding a cloud provider to host its most sensitive applications for defense and industrial workloads was not a certainty when the process began, Airbus told us last year, because European cloud providers do not have the scale of their US rivals. Jestin said Airbus will continue to work with AWS. Skywise, a platform that aggregates and analyzes aviation data, and Case Management Assistant for customers' technical queries will continue to be hosted by AWS. In a statement, she said: "By integrating a trusted, high performance, cloud environment that keeps our critical data assets shielded from foreign extraterritorial laws, we are ensuring that our digital infrastructure keeps pace with our aerospace innovation, while maintaining control and resilience of our industrial operations."

Read more of this story at Slashdot.

FakeGit campaign uses 7,600 GitHub repos to push SmartLoader malware

Wed, 22 Jul 2026 00:40:53 +0200

A large-scale operation dubbed 'FakeGit' is pushing SmartLoader and StealC malware through 7,600 malicious GitHub repositories that accumulated more than 14 million downloads. [...]

Zimbra 10.1.20 patches multiple security issues, including a critical command injection bug

Tue, 21 Jul 2026 21:02:50 +0200

Zimbra patched nine flaws in version 10.1.20, including a critical SNMP monitoring command injection issue enabling arbitrary command execution. Zimbra released version 10.1.20 to fix nine security vulnerabilities, including a critical command injection flaw in the SNMP monitoring component. The vulnerability affects systems with SNMP notifications enabled and could allow attackers to execute arbitrary commands. […]

Siemens RUGGEDCOM APE1808 with Palo Alto Networks Virtual NGFW

Tue, 21 Jul 2026 19:45:27 +0200

View CSAF

Summary

Palo Alto Networks has published [1] information on vulnerabilities in PAN-OS. This advisory lists the related Siemens Industrial products affected by these vulnerabilities. Customers are advised to consult and implement the workarounds provided in Palo Alto Networks' upstream security notifications. [1] https://security.paloaltonetworks.com/

The following versions of Siemens RUGGEDCOM APE1808 with Palo Alto Networks Virtual NGFW are affected:

RUGGEDCOM APE1808 vers:all/*

CVSS	Vendor	Equipment	Vulnerabilities
v3 7.2	Siemens	Siemens RUGGEDCOM APE1808 with Palo Alto Networks Virtual NGFW	Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting'), Missing Authorization, Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')

Background

Critical Infrastructure Sectors: Critical Manufacturing
Countries/Areas Deployed: Worldwide
Company Headquarters Location: Germany

Vulnerabilities

Expand All +

CVE-2026-0266

A cross-site scripting (XSS) vulnerability in Palo Alto Networks PAN-OS® software enables a malicious authenticated administrator to store a JavaScript payload using the web interface. This issue is applicable to PAN-OS software on PA-Series and VM-Series firewalls and on Panorama (virtual and M-Series). Cloud NGFW and Prisma® Access are not affected by this vulnerability.

View CVE Details

Affected Products

Siemens RUGGEDCOM APE1808 with Palo Alto Networks Virtual NGFW

Vendor:
Siemens

Product Version:
RUGGEDCOM APE1808 with Palo Alto Networks Virtual NGFW

Product Status:
known_affected

Remediations

Vendor fix
Contact customer support to receive patch and update information

Relevant CWE: CWE-79 Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	2.4	LOW	CVSS:3.1/AV:N/AC:L/PR:H/UI:R/S:U/C:N/I:L/A:N

CVE-2026-0272

A privilege escalation vulnerability in Palo Alto Networks PAN-OS® software allows an authenticated administrator with access to the Command Line Interface (CLI) to perform actions on the device with root privileges. The security risk posed by this issue is significantly minimized when CLI access is restricted to a limited group of administrators and by restricting access to the management interface to only trusted internal IP addresses according to our recommended best practice deployment guidelines https://live.paloaltonetworks.com/t5/community-blogs/tips-amp-tricks-how-to-secure-the-management-access-of-your-palo/ba-p/464431 . This issue is applicable to PAN-OS software on PA-Series and VM-Series firewalls and on Panorama (virtual and M-Series). Cloud NGFW, and Prisma® Access are not impacted by this vulnerability.

View CVE Details

Affected Products

Siemens RUGGEDCOM APE1808 with Palo Alto Networks Virtual NGFW

Vendor:
Siemens

Product Version:
RUGGEDCOM APE1808 with Palo Alto Networks Virtual NGFW

Product Status:
known_affected

Remediations

Vendor fix
Contact customer support to receive patch and update information

Relevant CWE: CWE-862 Missing Authorization

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	6.5	MEDIUM	CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:N

CVE-2026-0273

A command injection vulnerability in Palo Alto Networks PAN-OS® software enables an authenticated administrator to bypass system restrictions and run arbitrary commands as a root user. To be able to exploit this issue, the user must have access to the PAN-OS CLI or Web UI. The security risk posed by this issue is significantly minimized when CLI access is restricted to a limited group of administrators and by restricting access to the management web interface to only trusted internal IP addresses according to our recommended best practice deployment guidelines https://live.paloaltonetworks.com/t5/community-blogs/tips-amp-tricks-how-to-secure-the-management-access-of-your-palo/ba-p/464431 . This issue is applicable to PAN-OS software on PA-Series and VM-Series firewalls and on Panorama (virtual and M-Series). Cloud NGFW and Prisma® Access are not affected by this vulnerability.

View CVE Details

Affected Products

Siemens RUGGEDCOM APE1808 with Palo Alto Networks Virtual NGFW

Vendor:
Siemens

Product Version:
RUGGEDCOM APE1808 with Palo Alto Networks Virtual NGFW

Product Status:
known_affected

Remediations

Vendor fix
Contact customer support to receive patch and update information

Relevant CWE: CWE-78 Improper Neutralization of Special Elements used in an OS Command ('OS Command Injection')

Metrics

CVSS Version	Base Score	Base Severity	Vector String
3.1	7.2	HIGH	CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H

Acknowledgments

Siemens ProductCERT reported these vulnerabilities to CISA.

General Recommendations

As a general security measure, Siemens strongly recommends to protect network access to devices with appropriate mechanisms. In order to operate the devices in a protected IT environment, Siemens recommends to configure the environment according to Siemens' operational guidelines for Industrial Security (Download: https://www.siemens.com/cert/operational-guidelines-industrial-security), and to follow the recommendations in the product manuals. Additional information on Industrial Security by Siemens can be found at: https://www.siemens.com/industrialsecurity

Additional Resources

For further inquiries on security vulnerabilities in Siemens products and solutions, please contact the Siemens ProductCERT: https://www.siemens.com/cert/advisories

Terms of Use

The use of Siemens Security Advisories is subject to the terms and conditions listed on: https://www.siemens.com/productcert/terms-of-use.

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 exploitation risk of this vulnerability.

Minimize network exposure for all control system devices and/or systems, and ensure they are not accessible from the internet.

Locate control system networks and remote devices behind firewalls and isolate 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 recent version available. Also recognize VPN is only as secure as its 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. 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 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.

Advisory Conversion Disclaimer

This ICSA is a verbatim republication of Siemens ProductCERT SSA-104023 from a direct conversion of the vendor's Common Security Advisory Framework (CSAF) advisory. This is republished to CISA's website as a means of increasing visibility and is provided "as-is" for informational purposes only. CISA is not responsible for the editorial or technical accuracy of republished advisories and provides no warranties of any kind regarding any information contained within this advisory. Further, CISA does not endorse any commercial product or service. Please contact Siemens ProductCERT directly for any questions regarding this advisory.

Revision History

Initial Release Date: 2026-07-14

Date	Revision	Summary
2026-07-14	1	Publication Date
2026-07-21	2	Initial CISA Republication of Siemens ProductCERT SSA-104023 advisory

Legal Notice and Terms of Use

Axing UK science department risks slower policymaking, say tech leaders

Tue, 21 Jul 2026 17:52:29 +0200

Industry figures welcome Kanishka Narayan’s promotion as AI minister but warn shake-up could push sector down agenda

Zimbra Patches Critical SNMP Command Injection and Four XSS Vulnerabilities

Tue, 21 Jul 2026 16:10:27 +0200

Zimbra has rolled out fixes to address multiple critical security issues, including a command injection flaw in the Simple Network Management Protocol (SNMP) monitoring component. As many as nine security vulnerabilities have been patched in Zimbra 10.1.20. Topping the list is a command injection vulnerability in the SNMP monitoring component when SNMP notifications are enabled. Also patched

Tesla's A15 Powered Optimus Robot Made Nvidia & Unitree Powered Humanoids Look Likw Toys!

Tue, 21 Jul 2026 16:04:18 +0200

Author: Evolving AI - Bewertung: 0x - Views:0

Tesla may have just solved the biggest problem standing between Optimus and mass adoption, and surprisingly, it has nothing to do with the robot itself. Samsung has officially completed the AI5 chip tapeout on its cutting-edge 2nm process, bringing Tesla one step closer to its next-generation AI hardware. But the real breakthrough isn't more performance; it's dramatically lower power consumption. That single improvement could allow Optimus to work significantly longer on a single charge, turning it from an impressive demo into a robot capable of real factory and warehouse jobs.

In this video, we break down Tesla's AI5 chip, Samsung's 2nm manufacturing, the importance of the 250W power target, why Optimus needs far more AI compute than a self-driving car, Tesla's AI6 and AI7 roadmap, Terafab, Cybercab manufacturing, and how Tesla's vertical integration strategy could reshape the future of humanoid robotics. Is AI5 the breakthrough that finally makes Optimus a real commercial robot? Let's dive in.

#Tesla #Optimus #AI5 #ElonMusk #Samsung #ArtificialIntelligence #Robotics #Technology

Garmin’s new screen-free fitness tracker doesn’t require a subscription

Tue, 21 Jul 2026 15:48:13 +0200

Garmin announced a new smart band today designed to track "advanced fitness and wellness features" without a screen to eliminate distractions and push its battery life to up to 10 days between charges. Similar to competing products like the Whoop 5.0 and Google's recently announced Fitbit Air, the Cirqa uses a combination of heart rate, […]

New Bit2Watt Attack Could Let Cloud Tenants Disrupt Power Grids Without an Exploit

Tue, 21 Jul 2026 14:37:54 +0200

A cloud tenant using nothing but ordinary GPU access can push a data center's power draw up and down fast enough to threaten the grid it runs on, with no exploit and no break-in. That is the claim behind Bit2Watt, described by three Zhejiang University researchers in a paper accepted to CHES 2026, the IACR's hardware-security conference, and the evidence splits in two: they measured the power

New Bit2Watt Attack Could Let Cloud Tenants Disrupt Power Grids Without an Exploit

Tue, 21 Jul 2026 14:37:46 +0200

A cloud tenant using nothing but ordinary GPU access can push a data center’s power draw up and down fast enough to threaten the grid it runs on, with no exploit and no break-in. That is the claim behind Bit2Watt,…

The post New Bit2Watt Attack Could Let Cloud Tenants Disrupt Power Grids Without an Exploit appeared first on IT Security News.

Helios marks AMD’s biggest AI infrastructure push yet

Tue, 21 Jul 2026 13:21:39 +0200

AMD has expanded its AI infrastructure portfolio with the launch of Helios, an open, rackscale AI infrastructure designed for frontier AI and sovereign computing. Helios is built around AMD’s next-generation Instinct GPUs, EPYC Venice processors, Pensando networking and the ROCm software stack.

“Helios is AMD’s first complete AI rack system with GPUs, CPUs, and networking built together, instead of selling separate chips. It is well suited for training large AI models, memory heavy models, long context processing and high volume inference, and AMD’s biggest shot yet at challenging Nvidia’s dominance,” said Pareekh Jain, CEO at EIIRTrend & Pareekh Consulting.

AMD has also secured an early hyperscale deployment for Helios with Microsoft agreeing to deploy it to power its frontier model AI inference, its AI customers, and support Azure AI services.

The architecture behind Helios

The launch of Helios marks AMD’s latest attempt to strengthen its position in a market where Nvidia continues to dominate AI infrastructure. Unlike previous AMD AI offerings centred on individual accelerators, Helios is designed as a complete rack-scale system integrating compute, networking and software.

According to Jain, Helios goes up against Nvidia’s Vera Rubin rack. “Nvidia is faster on raw inference speed and has a faster internal connection between chips whereas AMD wins on memory size and offers better value for the price and power used. It’s standout feature is memory, where each rack packs about 50% more total memory than Nvidia’s competing system, which helps run very large AI models. It also uses open, industry-standard connections instead of Nvidia’s private technology, giving buyers more flexibility,” he said.

The AMD Helios rackscale design includes 72 AMD Instinct MI455X GPUs with AMD EPYC Venice CPUs and AMD Pensando Vulcano networking using UALink, optimized for compute, data movement, and system efficiency. The platform also supports both OCP and MX data types, delivering up to 2.9 EFLOPS of FP4 and 1.4 EFLOPS of FP8 compute for AI training and inference.

It also integrates 31TB of HBM4 memory with 19.6TB/s of memory bandwidth, while a liquid-cooling design uses quick-disconnect connections to efficiently dissipate heat. It is designed on open standards including OCP Open Rack Wide (ORW), Ultra Accelerator Link (UALink), and Ultra Ethernet Consortium (UEC) and can be scaled efficiently across datacenters while optimizing power, cooling, and serviceability for modern AI infrastructure, said the company.

On the security front, Helios incorporates a hardware root of trust and continuous attestation at every layer. It supports hardware-enforced isolation, encrypted memory and interconnects to help protect AI models, data and workloads in multi-tenant environments.

The software challenge

While the launch of Helios might help AMD close the hardware gap with Nvidia’s rack-scale systems, it will be the software compatibility that will be the real driver of enterprise adoption.

For this, AMD is expanding its ROCm AI software platform too, which supports frameworks including PyTorch, TensorFlow, and JAX, for enabling high-throughput inference and efficient distributed training while preserving familiar developer workflows.

Jain stated While hardware parity or superiority in memory bandwidth is achievable, software maturity remains the key differentiator for Nvidia. The Nvidia’s CUDA software has a 15-20 year head start, and almost every AI tool, tutorial, and codebase defaults to it.

He added software has been AMD’s weak spot. AMD has improved ROCm a lot but it still lags behind on the newest, most specialized optimizations, and setup is more complicated. For everyday AI work, ROCm is usable but for cutting-edge performance, CUDA still leads.

Evaluating the trade-offs

For CIOs evaluating AI infrastructure, Helios launch brings in another option to a market that has largely revolved around Nvidia’s dominance. But when considering Helios, CIOs will have to evaluate factors such as performance, software readiness, deployment models, procurement timelines and total cost of ownership before committing to a platform.

While AMD has not publicly announced a specific price tag for the Helios, Jain believes it to be noticeably cheaper to buy and run with lower chip prices and lower power use per GPU.

“It gives companies a real second option besides Nvidia, easing supply shortages and giving leverage in negotiations. The catch is software, where teams need to check whether their AI tools run well on AMD’s stack, since some advanced tools are still CUDA only,” Jain said.

For CIOs planning to deploy both, Jain warns the two systems can’t be plugged together into one combined machine as they use different, incompatible connection technology. But companies can and do run both side by side in the same data center, just as separate systems handling different jobs.

Asymmetric warfare in financial services: AI-powered fraud demands unified command

Tue, 21 Jul 2026 13:08:50 +0200

Military strategists know that asymmetric wars are lost not at the point of attack but at the seams between defensive units, where no single commander owns the territory and information moves slower than the threat. In January 2024, a finance employee at Arup’s Hong Kong office learned this lesson for $25 million, joining a video call with what appeared to be the engineering firm’s chief financial officer and several colleagues, receiving instructions to wire funds to a designated account, and complying. Every face on the screen was a deepfake, cloned from publicly available footage of the actual executives. The attackers conducted the entire meeting in real time and vanished before anyone in the organization realized the CFO had never logged on.

The incident would be remarkable enough as a one-off, but it represents a pattern accelerating well beyond isolated cases. Global payment fraud reached $33.4 billion in 2024 according to the Nilson Report, and the US absorbed a disproportionate 42% of those losses despite processing only 25% of global card transactions. The latest FBI Internet Crime report identifies more than one million complaints and nearly $21 billion in cyber-enabled crime losses in 2025 (up from $16 million in 2023), while Deloitte projects AI-enabled fraud in the US will hit $40 billion by 2027. This increasingly includes crypto-related fraud, not just credit card or traditional banking fraud.

For anyone who oversees financial operations, risk or payment technology infrastructure, these numbers are not forecasts of a future “regional conflict.” Instead, they are the current cost of a war most institutions have not yet recognized they are fighting.

Reconnaissance at scale: How AI redraws the attacker’s map

The conventional narrative around AI-powered fraud emphasizes speed: Faster phishing, faster credential stuffing, faster social engineering. Jason Kikta, CTO of Automox, sees the shift differently. “The main threat from AI misuse isn’t faster execution, as automation has been leveraged for years,” Kikta says. “The true dangers are lower barriers to entry and faster adaptation, giving attackers the ability to pivot techniques in near real-time.”

The distinction means that execution is a quantitative improvement, the kind existing defenses can absorb by scaling up. Lower barriers to entry and real-time adaptation are qualitative: A force multiplier that turns every amateur into an equipped operator with a coach that learns from each failed attempt. Deepfake-as-a-service platforms now produce voice clones from three seconds of audio. AI-driven vulnerability scanning maps an institution’s unpatched endpoints while the security team is still scheduling the review meeting. In 2024, 269 million stolen credit card records appeared on dark web platforms, giving AI-equipped attackers what military intelligence analysts would call an order of battle: A detailed map of the defender’s exposed positions, ready to be mined for patterns, tested against live systems and exploited at machine speed.

The result is a combined arms threat, one that operates across domains simultaneously the way a competent military force coordinates air, ground and intelligence rather than running them as independent campaigns. The same AI that crafts a convincing business email compromise can probe unpatched point-of-sale systems to install digital skimmers. The same synthetic identity that opens a fraudulent credit card account can exploit a payment authorization vulnerability discovered through automated scanning. Card-not-present fraud now accounts for 71% of all US card fraud losses, and the attack surface keeps expanding as digital wallets and e-commerce push more transactions into channels where physical card verification is impossible.

Attackers treat endpoint management gaps and transaction monitoring gaps as a single attack surface, while most defenders continue to patrol them as separate territories.

Fragmented command: The structural vulnerability AI exploits

Consider how most financial institutions, crypto platforms and digital asset intermediaries actually organize their defenses: A cybersecurity team focused on identity compromise, endpoint protection and infrastructure threats; a fraud team focused on account takeover, mule networks and scam typologies; an AML or financial crimes team focused on wallet screening, sanctions exposure and suspicious activity reporting; and an AI risk or digital trust team, if one exists at all, focused on synthetic media, model abuse and impersonation. Each function has its own tooling, budget, reporting line and intelligence feeds. In crypto markets, where value can move irreversibly across wallets, chains, mixers, exchanges and OTC brokers in minutes, those silos create exploitable gaps between detection, attribution, interdiction and recovery.

A pig-butchering scam that begins on a dating app, migrates to WhatsApp, directs a victim to a fake crypto investment platform, and then launders proceeds through nested services and cross-chain bridges is not just a fraud event. It is also a cybersecurity event, a financial crimes event, an identity event, a platform abuse event and, increasingly, an AI-enabled social engineering event. Chainalysis reported that high-yield investment scams and pig-butchering schemes were among the most successful crypto scam types in 2024, while also noting growing use of AI in fraud and scams.

Research published by the University of California, Davis found that these schemes follow a staged lifecycle: Trust-building, fabricated investment returns, escalating deposits, withdrawal obstruction and re-targeting of victims after the initial loss. When each part of that lifecycle is monitored by a different team, the institution sees fragments of the attack rather than the economic system of the crime.

“Fraud no longer happens in isolated channels,” observes Jeff Li, Global Product & Designer Lead at Binance. “AI-powered scams move seamlessly across platforms, and payment systems, making fragmented defenses increasingly ineffective.” He believes that the future of security depends on unified intelligence — combining AI, real-time monitoring, secure infrastructure and cross-functional response mechanisms into a single coordinated defense system.

“We’ve invested heavily in AI-driven risk detection, real-time scam warnings and infrastructure to stay ahead of evolving threats, continues Li, claiming that from Q1 2025 to Q1 2026, these efforts helped Binance prevent over $10 billion in potential user losses and protected more than 5 million users globally. As AI continues to reshape both fraud and fraud prevention, the focus remains on building systems that can protect users, not just at scale, but in real time.

Unified command: From org chart to battle plan

Kikta’s assessment contains a contrarian detail worth teasing apart: “The good news is that a strong compliance program prioritizing depth of coverage and speed of enforcement will hold up against AI-enabled fraud,” he says. In a landscape saturated with predictions that existing defenses are obsolete, Kikta argues that the fundamentals of patch management, endpoint hygiene and compliance rigor still hold, provided the clock speed at which those fundamentals execute keeps pace with the adversary.

That clock speed is the operational link between cybersecurity and card fraud prevention. An unpatched point-of-sale terminal or payment gateway exposed for 30 days represents 30 days of reconnaissance opportunity for an AI scanner probing for places to install a digital skimmer or intercept card data in transit. A compliance gap in identity verification is an open invitation for synthetic identities to open accounts and run fraudulent transactions. Endpoint management data and transaction monitoring data describe the same attack surface from different angles, and fusing those streams into a single operational picture, the financial equivalent of a military intelligence fusion center, gives defenders something the current siloed structure cannot: Visibility into an attack developing across domains before it reaches the payment layer.

The value of that convergence extends beyond defense. A unified data layer across cyber, fraud and payments creates consolidated threat intelligence that can inform underwriting decisions, merchant risk scoring and product design. Organizations that treat converged security data as a business intelligence asset (not merely an operational feed) will find they have built something with commercial utility well beyond the security operations center.

Mascaro frames the prescription in terms that belong in a boardroom, not a SOC. “The real competitive advantage in fraud isn’t your AI stack,” he says. “It’s leadership’s clarity to unify risk disciplines that everyone else keeps in separate departments.”

Field manual: What winning institutions do differently

The institutions gaining ground in this new form of asymmetric conflict share a common operational posture: They treat endpoint management as card fraud prevention rather than IT maintenance, and they feed cyber, fraud and payments intelligence into a single picture rather than three separate briefings. The defensive AI advantage, such as it is, comes from that integration, not from any single model’s sophistication.

Adversaries have already unified their operations. Yet, payment processors and financial institutions that keep running separate campaigns on separate fronts, with separate intelligence, will keep conducting after-action reviews of battles they have already lost.

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How AI may drive union-resistant tech workers to the bargaining table

Tue, 21 Jul 2026 13:03:55 +0200

Tech workers are increasingly unionizing, trading Silicon Valley’s myth of exceptionalism for collective bargaining to contest the corporate deployment of artificial intelligence

For decades, the technology industry was a fortress that labor unions couldn’t breach. Tech workers already had cushy compensation packages, dream benefits like unlimited vacation and free lunch, and a flat corporate hierarchy that made engineers feel as powerful as their bosses, all of whom dressed down in sneakers and hoodies. So why unionize?

Now, that fortress is cracking from the inside. Unions have become increasingly popular for tech employees. After months of mass layoffs tied to artificial intelligence and mounting anxieties about how it’s being deployed, some tech workers say they’ve been saddled with higher workloads while facing the threat of job loss caused by the very products they’re building. Workers from Google DeepMind and Meta in the UK are also objecting to how their companies’ AI products are being used, such as for military purposes or to monitor employee productivity. Those same workers are now attempting to unionize.

WordPress wp2shell Exploitation Grows as Public Exploit Fuels Mass Scanning

Tue, 21 Jul 2026 11:10:54 +0200

Attackers have begun to exploit two critical vulnerabilities in WordPress that, when combined together, enable unauthenticated remote code execution (RCE) and complete compromise of vulnerable websites. The two security flaws, tracked as CVE-2026-63030 and CVE-2026-60137, have been codenamed wp2shell. "By the early hours of Saturday morning (UTC), successful exploitation was already well

WordPress wp2shell Exploitation Grows as Public Exploit Fuels Mass Scanning

Tue, 21 Jul 2026 11:10:42 +0200

The post WordPress wp2shell Exploitation Grows as Public Exploit Fuels Mass Scanning appeared first on IT Security News.

Etsy Is In Its Flop Era, and Sellers Are Fleeing

Tue, 21 Jul 2026 11:03:42 +0200

Once a quirky bastion of amateur vulva jewelry and pet portraits, Etsy is now deluged with mass-produced goods and AI knockoffs. Some customers don’t seem to mind.

Context bombing heralds a new AI era of deceptive defense

Tue, 21 Jul 2026 09:07:59 +0200

Attackers are increasingly using AI agents to automate all phases of cyberattacks, prompting the security industry and enterprises to find new network defense approaches. One technique that shows promise is to intentionally plant decoy files with prompts that trigger the content safety guardrails built into LLMs with the goal of crashing rogue agentic workflows.

Using decoy resources as tripwires that alert defenders about potential unauthorized access is not a new idea in cybersecurity. These are known as canaries — after the canary in the coal mine early warning system — and can be fake documents, AWS access keys, database dumps, DNS records, and even URLs that would not be queried by legitimate processes, but would be attractive targets for attackers.

What’s new in the approach devised and tested by security firm Tracebit is to use these decoy resources not merely to trigger alerts, but to actually stop AI agents, buying defenders more time. Dubbed “context bombing,” the technique takes advantage of the fact that LLMs are inherently vulnerable to prompt injection — acting on instructions they might encounter inside the data they process.

Enterprises that build their own AI agents have to worry about malicious prompts placed by attackers on web pages, emails, documents, code comments, and in other third-party resources those agents might access. With no defenses in place, companies risk their own agents being hijacked and used against them to perform unauthorized actions. But the malicious AI agents used by attackers have the same vulnerability.

“We call the defensive version a context bomb: a short piece of text designed to trigger a model’s safety guardrails, planted directly in the attacker’s path — a decoy secret, environment variable, or DNS record,” Sam Cox, Tracebit’s CTO, said in a blog post. “An AI agent that reads it will frequently refuse to continue. You still get the alert; and the attack now halts early instead of merely being detected.”

Context bombing triggers massive drop in attack success rate

Tracebit’s tests performed in an AWS test environment cut the success rate normally achieved by AI models across multiple attacks paths by up to 90% by simply adding instructions that would trigger their content safety guardrails. LLMs are trained to refuse answering questions about creating biological, chemical, or nuclear weapons, or, in the case of Chinese open-weight models, sensitive political topics such as the Tiananmen Square massacre.

Furthermore, once one of these banned instructions make it into the context window, the whole session is poisoned, and the model will often refuse to continue without manual intervention. The researchers ran many tests to find short strings that would trigger model safety guardrails reliably, but it’s worth noting that the identified strings were different between the tested models: Claude Opus 4.8, Gemini 3.1 Pro, GLM 5.2, DeepSeek V4 Pro, and Kimi K2.6.

During baseline tests the AI agents managed on average to obtain full account admin in 54% of the 154 attack runs and full compromise (admin + persistence) in 36% of tests. With the context bombs in place, their success rate dropped to 5% for admin access and 1% for full compromise. Also, in 91% of baseline attack runs, the agents managed to complete at least one of ten possible attacks paths, but their average success rate dropped to 15% with the context bombs.

The models from Western AI labs — Opus and Gemini — proved the most capable at reaching full admin access, with 93% and 70% success rates, but were also the most impacted by the context bombs with both their success rates dropping to 0%. This shows that the content safety guardrails are much stronger in these models compared to the Chinese ones that were tested.

Attackers experimented with safety refusals first

The Tracebit researchers had already been experimenting with AI canaries for alert purposes. A paper published in May showed that canaries alerted defenders in 95.9% of 162 successful attack runs performed with AI agents using 10 different AI models. The alerts were triggered 8 minutes before the agents performed critical actions, while the runs required 14 minutes on average to reach admin access.

During those tests the researchers observed that if they instructed the models that the network might include deception, their success rate for full admin access and persistence dropped from 20% to 3% on average.

Then in June, researchers from security firm Socket.dev came across a software supply chain attack involving malicious PyPI wheels that contained prompt injections with content designed to trigger safety guardrails inside AI models. The malicious prompts were included in code comments at the start of the files and the purpose was likely to evade detection from LLM-powered security scanners.

“This header appears designed for AI-mediated analysis, not for Node, Bun, or Python,” the Socket.dev researchers said at the time. “It attempts to derail scanners or analyst copilots that feed the beginning of a file to a language model without clearly isolating the content as untrusted data. In weak pipelines, this can cause refusal behavior, prompt confusion, context pollution, or premature classification before the scanner reaches the actual malware.”

The Tracebit researchers then had the idea to flip the script and trigger such safety refusals through their canary technique against malicious AI agents. So not only does the agent run stop, but an alert is also triggered because the canary was accessed.

There is a risk that the canaries could also be discovered and accessed accidentally by legitimate LLM-powered tools used by engineering or security teams. But at the same time this means organizations could potentially deploy such canaries in sensitive places to stop their own AI agents that might become hijacked or go off the rails on their own.

There are many reports online where AI models performed destructive or unauthorized actions like deleting databases and folders or elevating their privileges because they got struck in failure loops and explored creative ways to complete their tasks. This is even more common with autonomous AI agents that are tasked to reach a goal without human intervention or supervision.

“The speed of autonomous AI attacks is why deception is climbing the priority list for security programs,” Tracebit’s Cox said. “When the attack chain takes minutes rather than days, every minute of response time you can claw back matters — and a control that stops the attacker outright, rather than just reporting them, changes the economics significantly.”

OVH reveals semi-secret plan to fix critical Januscape hypervisor bug with mass reboots – and an Australian crash-test dummy

Tue, 21 Jul 2026 09:07:51 +0200

French cloud backported a patch into Debian and didn’t seek customer consent, despite chance of downtime This article has been indexed from www.theregister.com – Articles Read the original article: OVH reveals semi-secret plan to fix critical Januscape hypervisor bug with…

The post OVH reveals semi-secret plan to fix critical Januscape hypervisor bug with mass reboots – and an Australian crash-test dummy appeared first on IT Security News.

IT Security News Hourly Summary 2026-07-21 09h : 6 posts

Tue, 21 Jul 2026 09:07:47 +0200

6 posts were published in the last hour 7:2 : Fileless Stealer and PureRAT Raid Browser Passwords, Telegram Sessions, and Crypto Wallets 7:2 : OVH reveals semi-secret plan to fix critical Januscape hypervisor bug with mass reboots – and an…

The post IT Security News Hourly Summary 2026-07-21 09h : 6 posts appeared first on IT Security News.

OVH reveals semi-secret plan to fix critical Januscape hypervisor bug with mass reboots – and an Australian crash-test dummy

Tue, 21 Jul 2026 08:33:10 +0200

French cloud backported a patch into Debian and didn’t seek customer consent, despite chance of downtime

Fix Delayed or Missing Gmail Notifications on Android

Tue, 21 Jul 2026 07:24:35 +0200

Key TakeawaysGmail notifications may stop working on Android due to settings, updates, or restrictions. This issue results from changes in notification settings, synchronization permissions, background data access, or battery management that prevent alerts for new emails.To fix Gmail notification issues, enable notifications for each Gmail account in the app, check Android settings to allow notifications, […]

The post Fix Delayed or Missing Gmail Notifications on Android appeared first on iTech Hacks.

OVH reveals semi-secret plan to fix critical Januscape bug with mass reboots – and an Australian crash-test dummy

Tue, 21 Jul 2026 06:24:40 +0200

French cloud backported a patch into Debian and didn’t seek customer consent, despite chance of downtime

AI-generated reports push GNOME to shorten its disclosure window

Tue, 21 Jul 2026 06:24:39 +0200

Volunteer maintainers of open source projects now receive a steady flow of security vulnerability reports produced with AI tools. Many arrive with no mention that a language model helped write them. The volume has grown enough that GNOME is revising the rules it uses to track and disclose vulnerabilities across its projects. The changes come from Michael Catanzaro, who has run GNOME’s security issue tracking since November 2020 with support from Red Hat. Under the … More →

The post AI-generated reports push GNOME to shorten its disclosure window appeared first on Help Net Security.

AI-generated reports push GNOME to shorten its disclosure window

Tue, 21 Jul 2026 06:24:31 +0200

The post AI-generated reports push GNOME to shorten its disclosure window appeared first on IT Security News.

OVH reveals semi-secret plan to fix critical Januscape bug with mass reboots – and an Australian crash-test dummy

Tue, 21 Jul 2026 06:24:30 +0200

The post OVH reveals semi-secret plan to fix critical Januscape bug with mass reboots – and an Australian crash-test dummy appeared first on IT Security News.

RPA Software: Die besten Tools für Robotic Process Automation

Tue, 21 Jul 2026 05:08:44 +0200

Robotic Process Automation birgt für Unternehmen viele Vorteile. Wir zeigen Ihnen die besten RPA Tools.

Foto: klyaksun – shutterstock.com

Eine Art magische Taste zur Automatisierung langweiliger und repetitiver Aufgaben am Arbeitsplatz – und damit vereinfachte Arbeitsabläufe und mehr Zeit für wichtige Tasks – das ist das Versprechen von Robotic Process Automation (RPA). RPA integriert auch neue KI-Algorithmen in alte Technologie-Stacks: Viele Plattformen bieten Computer Vision und Machine Learning Tools. Dennoch: RPA ist kein Automatismus, ein beträchtliches Maß an manuellen Eingriffen und Anpassungen ist während des Trainings entsprechender Modelle erforderlich. Noch gibt es einige Tasks, die vorkonfigurierte Bots nicht erledigen können – allerdings werden die Softwareroboter zunehmend intelligenter und ihr Training einfacher.

Der RPA-Markt bietet eine Mischung aus neuen, speziell entwickelten Tools und älteren Werkzeugen, die mit zusätzlichen Automatisierungsfunktionen ausgestattet wurden. Einige Anbieter vermarkten ihre Tools unter dem Begriff “Workflow-Automatisierung” oder “Work Process Management”, andere sprechen von “Geschäftsprozessautomatisierung”.

Was Robotic Process Automation leisten sollte

Bevor Sie sich für ein RPA-Produkt entscheiden, sollten Sie sich darüber im Klaren sein, dass jedes Produkt seine eigenen proprietären Dateiformate zum Einsatz bringt. Deshalb sind RPA-Lösungen nicht miteinander kompatibel. Die Konsequenz für Sie als Anwender: Sie sollten in Frage kommende Produkte vorab sorgfältig evaluieren und einen Proof of Concept durchführen. Nachträglich auf ein anderes Produkt umzusteigen, ist in der Regel relativ mühsam – und kostspielig.

Stellen Sie sicher, dass sämtliche grundlegenden und speziellen Funktionen, die Sie benötigen, auch im Zusammenspiel mit Ihrer IT-Umgebung funktionieren. Auf folgende Faktoren gilt es dabei besonders zu achten:

Bots sollten simpel einzurichten sein. Zudem sind verschiedene Möglichkeiten, um RPA-Bots für unterschiedliche Personas aufzusetzen, essenziell. Ein Recorder sollte die normalen Aktionen von Business-Nutzern erfassen. Citizen Developer sollten Low-Code-Umgebungen nutzen können, um Bots und Business-Regeln zu definieren. Und Profi-Devs sollten echten Automatisierungs-Code erstellen können, der auf die APIs des RPA-Tools zugreift.
Low-Code-Funktionen sind unerlässlich. In der Regel vereint Low-Code eine Drag-and-Drop-Zeitleiste mit einer Aktions-Toolbox und Property-Formularen – ab und an muss auch ein Code-Snippet erstellt werden. Das geht deutlich schneller, als Business-Regeln mit herkömmlichen Verfahren zu erstellen.
Die Lösung der Wahl sollte sowohl Attended als auch Unattended Bots unterstützen. Manche Bots sind nur sinnvoll, um sie on Demand (attended) auszuführen – etwa wenn es darum geht, einen genau definierten Task auszuführen. Andere eignen sich, um auf bestimmte Events zu reagieren (unattended) – etwa Due-Diligence-Prüfungen für übermittelte Kreditanträge. Sie benötigen beide Formen.
Machine-Learning-Fähigkeiten sind Pflicht. Noch vor wenigen Jahren hatten viele RPA-Tools Probleme, Informationen aus unstrukturierten Dokumenten zu extrahieren. Heutzutage kommen ML-Lernfunktionen zum Einsatz, um solche Daten zu analysieren. Das bezeichnen einige Anbieter und Analysten auch als “Hyperautomation”.
Der Faktor Mensch braucht Raum. Kategoriale maschinelle Lernmodelle schätzen in der Regel die Wahrscheinlichkeit möglicher Ergebnisse. Ein Modell zur Vorhersage von Kreditausfällen, das eine Ausfallwahrscheinlichkeit von 90 Prozent angibt, könnte beispielsweise empfehlen, den Kredit abzulehnen, während ein Modell, das eine Ausfallwahrscheinlichkeit von 5 Prozent berechnet, empfehlen könnte, diesen zu gewähren. Zwischen diesen Wahrscheinlichkeiten sollte Spielraum für ein menschliches Urteil bestehen. Das RPA-Tool Ihrer Wahl sollte deshalb die Möglichkeit für manuelle Reviews bieten.
Bots müssen sich mit ihren Enterprise Apps integrieren lassen – ansonsten können sie keine Informationen daraus abrufen und bringen entsprechend wenig. Die Integration geht in der Regel einfacher vonstatten, als PDF-Dateien zu parsen. Nichtsdestotrotz benötigen Sie dafür Treiber, Plugins und Anmeldedaten für sämtliche Datenbanken, Buchhaltungs- und HR-Systeme sowie weitere Unternehmens-Apps.
Orchestrierungsmöglichkeiten sind unverzichtbar. Bevor Sie Bots ausführen können, müssen Sie sie konfigurieren und die dafür erforderlichen Anmeldedaten bereitstellen, in der Regel über einen eigens abgesicherten Credential Store. Zudem müssen Benutzer autorisiert werden, um Bots erstellen und ausführen zu können.
Cloud-Bots können zusätzliche Benefits bringen. Als RPA eingeführt wurde, liefen die Bots ausschließlich auf den Desktops der Benutzer oder den Servern des Unternehmens. Mit dem Wachstum der Cloud haben sich jedoch virtuelle Cloud-Maschinen für diesen Zweck etabliert. Einige RPA-Anbieter haben auch bereits Cloud-native Bots implementiert, die als Cloud-Apps mit Cloud-APIs ausgeführt werden, anstatt auf virtuellen Windows-, macOS- oder Linux-Maschinen. Selbst wenn Sie derzeit nur wenig in Cloud-Anwendungen investiert haben, ist diese Funktion mit Blick auf die Zukunft empfehlenswert.
Process-Mining-Fähigkeiten können Aufwand reduzieren. Der zeitaufwändigste Teil einer RPA-Implementierung besteht im Regelfall darin, Prozesse zu identifizieren, die automatisiert werden können – und diese entsprechend zu priorisieren. Je besser die RPA-Lösung Ihrer Wahl Sie in Sachen Process Mining und Task Discovery unterstützen kann, desto schneller und einfacher können Sie automatisieren.
Skalierbarkeit ist das A und O. Wenn Sie RPA unternehmensweit einführen und sukzessive ausbauen möchten, können leicht Skalierungsprobleme auftreten – insbesondere, wenn es um Unattended Bots geht. Dagegen hilft oft eine Cloud-Implementierung, insbesondere, wenn die Orchestrierungskomponente in der Lage ist, bei Bedarf zusätzliche Bots bereitzustellen.

Die besten RPA-Softwarelösungen

Im Folgenden haben wir die aktuell wichtigsten Anbieter und Lösungen im Bereich Robotic Process Automation für Sie zusammengestellt. Die Auflistung erhebt keinen Anspruch auf Vollständigkeit und basiert unter anderem auf den Bewertungen von Anwendern sowie den Einschätzungen von Analysten.

Zu beachten ist dabei, dass KI-Agenten klassischen RPA-Lösungen zunehmend den Rang ablaufen, da sie weitergehende, intelligentere Automatisierungsinitiativen ermöglichen: Während Robotic Process Automation vor allem regelbasiert funktioniert, “lernen” KI-Agenten aus Daten. Diverse Anbieter haben bereits auf den Trend reagiert und ihr Automatisierungsangebot entsprechend neu ausgerichtet.

Airslate
Appian
Automation Anywhere
AutomationEdge
AWS Lambda
Cyclone Robotics
Datamatics
EdgeVerve Systems
Fortra Automate
IBM
Laiye
Microsoft
Mulesoft (Salesforce)
NiCE
Nintex
Pega
SAP
ServiceNow
SS&C Blue Prism
Tungsten Automation (ehemals Kofax)
UiPath
WorkFusion

(fm)

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

The EU’s AI transparency deadline is weeks away. Is your enterprise ready?

Tue, 21 Jul 2026 04:02:28 +0200

Providers and deployers of AI systems: You only have a couple of weeks left until you must explicitly inform users when they are interacting with AI content.

Systems must include machine-readable markers to reveal such content, to reduce “the risk of deception and manipulation” and build public trust in AI.

A company’s non-compliance could result in fines anywhere from €750K (about $856K) to €15M (about $17 million), or even up to 3% of its total worldwide annual revenue.

Transparency requirements

“Systems placed on the European market, put into service there, or producing outputs used there are inside the field, wherever the developer sits,” Gogia noted.

The three icons are publicly available for free use; enterprises can download zip files in PNG and SVG formats.

Most of the Act’s transparency rules begin to go into effect on August 2. But AI systems placed on the market before then will have some leeway; they must be in compliance by December 2.

A consistent code of practice

Providers that choose not to sign must comply through other methods and demonstrate that those methods are “adequate” through assessment by surveillance authorities, according to the Commission.

Non-signatories “keep their flexibility, and will face more case-by-case scrutiny for it,” said Gogia.

Criteria for compliance

Creating a transparency pipeline

“CIOs should ask which platform can actually provide evidence before believing its dashboard,” said Gogia.

This article originally appeared on CIO.com.

Can Your Apple Watch Really Track Blood Pressure? Here’s How to Make It Work

Tue, 21 Jul 2026 03:48:19 +0200

While your Apple Watch does provide hypertension notifications, it can’t measure blood pressure on its own. However, there is a workaround.

The EU’s AI transparency deadline is weeks away. Is your enterprise ready?

Tue, 21 Jul 2026 03:48:17 +0200

Providers and deployers of AI systems: You only have a couple of weeks left until you must explicitly inform users when they are interacting with AI content.

Systems must include machine-readable markers to reveal such content, to reduce “the risk of deception and manipulation” and build public trust in AI.

A company’s non-compliance could result in fines anywhere from €750K (about $856K) to €15M (about $17 million), or even up to 3% of its total worldwide annual revenue.

Transparency requirements

“Systems placed on the European market, put into service there, or producing outputs used there are inside the field, wherever the developer sits,” Gogia noted.

The three icons are publicly available for free use; enterprises can download zip files in PNG and SVG formats.

Most of the Act’s transparency rules begin to go into effect on August 2. But AI systems placed on the market before then will have some leeway; they must be in compliance by December 2.

A consistent code of practice

Providers that choose not to sign must comply through other methods and demonstrate that those methods are “adequate” through assessment by surveillance authorities, according to the Commission.

Non-signatories “keep their flexibility, and will face more case-by-case scrutiny for it,” said Gogia.

Criteria for compliance

Creating a transparency pipeline

“CIOs should ask which platform can actually provide evidence before believing its dashboard,” said Gogia.

CIO 100 Leadership Live New York: CIOs push past AI pilots for measurable returns

Tue, 21 Jul 2026 01:07:24 +0200

Technology executives from across the New York metropolitan area gathered July 16 at Convene, One Liberty Plaza, for CIO 100 Leadership Live New York, a full day of roundtables and panel discussions on enterprise AI investment, governance, and organizational change.

Several key areas of consensus emerged throughout this highly interactive event. Infrastructure fragmentation continues to block the path to securing returns on AI investments prompting leaders to understand rising cloud spend attributed to large language model utilization. This has caused a growing number of organizations to refocus on on-premises and hybrid options in C-suite and board-level capital planning conversations. Speakers, along with comments from the audience, described a shift from project thinking to product thinking, with smaller multidisciplinary teams moving faster than legacy structures.

Several participants repeatedly warned that automating broken processes just amplifies dysfunction. Governance and measurement remain unresolved, with usage metrics still getting mistaken for business value. One of the panels explored how CIOs may benefit from applying venture capital-style scrutiny to enterprise bets, weighing team execution as heavily as the technology itself. The throughline was a redefinition of the CIO role, from technology executor to business strategist fluent in revenue, board engagement, and transformation ownership.

Morning roundtable tackles AI infrastructure

The day opened with an invitation-only executive breakfast roundtable, “Beyond the Pilot, Building the Infrastructure for Real AI Returns,” co-hosted by Unisys and Dell Technologies. Over a dozen executives representing major public and private sector organizations across the New York metropolitan area joined Steve Hollander, senior director of Americas global alliances at Dell Technologies, and Matt Marshall, CIO at Unisys for a workshop-style discussion.

The session explored the strategic, operational, financial, and technological issues that must be mastered to optimize infrastructure decisions and separate organizations that are experimenting with AI from those competing on it. Discussion questions probed how CIOs measure whether AI investment is translating into business results, how they can break the cycle of fragmented and siloed AI deployments, how boards are beginning to scrutinize seven-figure token spend and whether on-premises or hybrid infrastructure can rein in costs.

The take-home point: the organizations pulling ahead are the ones that stopped treating AI as four separate problems, strategic, operational, financial, technological, owned by four separate functions, and started running it as one coordinated decision. Fragmentation is the actual cost center here, not the token spend itself. A CIO who solves the infrastructure question in isolation from the governance question, or the cost question in isolation from the talent question, ends up optimizing one silo while the other three keep bleeding value. Competing on AI, instead of just experimenting with it, means the finance, operations, technology and business sides are reasoning from the same picture of what’s being built and why, so the tradeoffs get made once, together, instead of getting re-litigated at every handoff.

Forum sessions open with a mandate for growth

Following breakfast, the main forum program began with “The New CIO Mandate, Delivering Growth, Not Just Technology.” In a moderated conversation, Laksh Nathan, chief information officer at Paramount Skydance, drew on his experience with mergers, enterprise transformation and AI-enabled development to describe a shift from project and application management toward a product-centric operating model. Nathan addressed how smaller, multidisciplinary teams are changing expectations on both the business and technology sides of the enterprise, and what mindset changes CIOs must lead to turn AI into an engine of growth rather than a cost center.

PwC followed with a session on “Designing the Intelligent Enterprise, From AI Investment to Evolving Operations.” Darren O’Meara, principal and chief technology officer for managed services, and Meghna Shah, principal for engineering and AI, examined why fragmented outcomes persist even after heavy investment in technology and transformation.

The intelligent enterprise, they posited, is less about working toward achieving specific technology outcomes and more about creating operating models that integrate strategy, technology, operations, and governance into one system. This, they explained, requires linking AI, data, and decisions across the business and will leave an indelible mark on how decision rights are redesigned, funding models are developed, and accountability is enforced to accommodate the speed of the agentic economy.

Talent, tradeoffs, and the cost of getting it wrong

The session “Return on Transformation: Time, Talent, and Tradeoffs” — with Prashant Hinge, chief information and transformation officer at MSIG USA; Joseph Gimigliano, chief technology officer at Northwell Health; and Eduard de Vries Sands, AI executive advisor at PatientPoint — examined why transformation initiatives so often lose their way.

The main culprit, even today in 2026, continues to revolve around a persistent instinct for technology implementations to become the objective rather than the means to a measurable business outcome. The panelists made the case for doing the incredibly difficult work of re-engineering (if not entirely re-imagining) existing processes before automating them and then placing smaller bets inside that bigger vision.

Ricky Thakrar, head of sales and account management at Zoho, took the stage to present “Smaller, Smarter, Safer, The Enterprise AI Architecture Most Leaders Get Backwards,” arguing that constrained, context-rich architectures consistently outperform expensive models bolted onto fragmented systems.

A round of Hot Topic Discussion Groups and a networking lunch followed, including the Next CIO Luncheon featuring Robert Half Regional Director Jason Deneu.

Afternoon sessions turn to security, scale, and investment signals

CSO and CIO Contributor Joan Goodchild moderated “Securing Trust in the Agentic Economy,” a discussion with Marlowe Cochran, CISO at the New York State Education Department, and Gee Rittenhouse, vice president of security services at AWS, on how organizations are balancing speed, innovation and security as AI agents move from experimentation into productization at scale.

Rittenhouse framed agentic risk as closer to human risk than traditional software risk, describing how an independent agent acting in a non-deterministic way really does look like a potential insider threat, pushing CISOs toward behavioral monitoring over static workload protection. He tied this to a structural shift in defense, noting it’s hard to do agentic security if you’re not observing it, putting observability at the center of agentic risk management.

Cochran concurred, adding that many of the key tools that are needed to move into the agentic economy already exist, but must be implemented more aggressively, comprehensively and even more creatively. CISOs don’t need to invent an entirely new security discipline for the agentic era so much as extend identity management, access control and monitoring frameworks they already run to cover a new class of non-human actor — agents.

A session on “AI, From Experimentation to Enterprise Impact” brought together Meagan Gentry, national AI practice manager and distinguished technologist at Insight and Yuri Gubin, chief technology officer at DataArt, for a candid look at why pilots stall before reaching scaled production and what operating capabilities, governance, cost visibility, continuous education, must be in place to sustain AI once a proof of concept works.

During the session’s Q&A segment, a discussion emerged around how proof-of-concept success can result in a false signal, raising questions about whether pilots should be considered successful before the intended outcomes have had time to materialize, and drawing a distinction between measuring usage and adoption versus measuring business value.

The panelists explored how CIOs can identify the small number of transformational AI opportunities worth pursuing rather than managing hundreds of incremental use cases, and even challenged whether prioritization is the CIO’s job at all. The discussion closed on a sequencing question with real strategic weight, whether AI-first strategies are putting the technology ahead of the business problem CIOs are trying to solve, and what role CIOs should play with boards in defining the outcomes AI is expected to support.

A shift in perspectives

The “Think Like a VC, Investment Shifts Towards Focused AI Applications” session featured three venture investors, Aaron Darr, partner at Lead Edge; Isabelle Phelps, partner at Lerer Hippeau; and Marshall Porter, general partner at AlleyCorp. The panel explored how investors evaluate risk and talent in a market where products and competitive positions can shift within months, and what separates a focused AI application with durable enterprise value from an AI wrapper built to chase a trend.

The panel challenged the enterprise instinct to seek certainty in a market moving this fast, questioning whether CIOs should stop looking for technologies that will future-proof the enterprise and instead grow more comfortable continuously reassessing their bets. Investors framed this as a deliberate departure from the traditional low-tolerance-for-failure posture that has long governed enterprise technology purchasing, arguing that the search for certainty has itself become a risk in a market where products and business models can shift within months. The discussion pressed CIOs to weigh how they can adopt a more dynamic investment mindset without compromising the enterprise security, governance and accountability their organizations still depend on.

A Lightning Insights followed, featuring five-minute briefings from Insight, Platform9 and Console, followed by Keystone Senior Principal Ellora Sarkar’s talk on why most enterprise AI investment fails to produce measurable value and what separates the small share of firms capturing real return on investment from the majority still stuck in pilots.

Closing the day

The forum closed with “What’s Next for the CIO, Preparing for the Next 12 to 24 Months,” a fireside conversation with Leif Maiorini, CIO for corporate services at Omnicom. Maiorini discussed why business processes need to be redesigned for agentic speed rather than automated around existing human workflows, how organizational structures may shift as autonomous agents reshape visibility and decision support, and where sustainable differentiation will come from once AI capability itself becomes widely accessible.

Maiorini encouraged the industry to clearly distinguish between nondifferentiated services that should be made as efficient as possible and the differentiated capabilities that actually influence why customers choose to do business with an organization, once the major efficiency gains from optimization and AI have been captured.

He was candid about the governance gap agentic systems open up, noting that agents lack the professional reputation, personal accountability and inherent constraints that shape human behavior, which creates new risk when autonomous decisions occur at machine speed. That combination, reinvesting efficiency gains into genuine differentiation while building governance models suited to non-human decision-makers, framed his closing case for why human creativity and judgment remain the enterprise’s most durable asset even as the underlying technology becomes commoditized.

Join the CIO 100 Awards & Conference Aug 17–19, 2026 at Omni PGA Frisco Resort & Spa, Frisco, TX — where top IT leaders celebrate innovation and connect. Learn more to attend or partner.

SonicWall SMA1000 flaws exploited as zero-days to push custom malware

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Two recently disclosed SonicWall SMA1000 vulnerabilities were exploited in zero-day attacks for weeks, allowing threat actors to install custom malware on vulnerable VPN appliances. [...]

Remediating Vulnerabilities With LLMs: Inside Ivanti's Automation Push

Mon, 20 Jul 2026 23:07:25 +0200

Ivanti CSO Daniel Spicer says frontier models have shown surprising effectiveness in early stages; but cost and human-in-the-loop viability remain open questions.

Meta Eyes $10B Anthropic Compute Lease in AI Revenue Push

Mon, 20 Jul 2026 21:51:02 +0200

Meta is discussing a potential $10 billion compute lease with Anthropic that could turn its massive AI infrastructure buildout into a new business.

Cosmetics giant Estée Lauder victim of mass Oracle breach

Mon, 20 Jul 2026 20:47:36 +0200

Employee data at US-based cosmetics firm Estée Lauder was compromised through a vulnerability in Oracle's software, likely orchestrated by the Cl0p ransomware gang.

Hermes Agent v0.19.0 (2026.7.20) — The Quicksilver Release

Mon, 20 Jul 2026 20:46:40 +0200

Hermes Agent v0.19.0 (v2026.7.20)

Release Date: July 20, 2026
Since v0.18.0: ~2,245 commits · ~1,065 merged PRs · ~2,465 files changed · ~300,000 insertions · ~36,000 deletions · ~3,300 issues closed · 450+ community contributors

The Quicksilver Release. Hermes is the messenger god, and this window we made him move like it. First-turn time-to-first-token dropped ~80% on every platform, reasoning streams live by default, the desktop app got a ~20-PR speed overhaul (14× faster streaming markdown, virtualized diffs, snappy session switching), and the TUI renders markdown incrementally. Around that speed spine: you can now manage your Nous subscription without leaving the terminal, plug Bitwarden and 1Password straight into Hermes, let smart approvals judge flagged commands for you by default, watch your subagents work live, and trust that a finished response survives a gateway crash thanks to a durable delivery ledger. This release also rolls up everything from the v0.18.1 and v0.18.2 infrastructure patch tags — those windows are fully documented here.

✨ Highlights

Hermes got dramatically faster — first token in a fraction of the time — Cold-start "Initializing agent..." used to eat ~4.3 seconds before your first turn even reached the model; it's now ~0.9s, an ~80% cut that applies to the CLI, gateway, TUI, desktop, and cron alike. Round 2 attacked what you see while waiting: reasoning models now stream their thinking live by default (no more staring at a spinner for 30 seconds), and the response box paints per token instead of per line. If Hermes ever felt like it took a deep breath before answering, that breath is gone. (#59332, #59389 — @teknium1)
The desktop app speed wave — 20+ targeted perf PRs — Long replies used to cost 14× more CPU in the markdown splitter than they do now; giant diffs froze the review pane until we virtualized it; switching sessions thrashes layout no more. Streaming no longer re-renders the sidebar and every tool row per token, profile backends pre-warm on hover intent, and boot-hidden panes mount at idle instead of on the cold-start critical path. The net effect: the desktop app feels like a native app under load, even with huge transcripts and busy agents. (#67154, #67818, #65898, #66033, #66747, #67742 and more — @OutThisLife)
Manage your Nous plan from the terminal — /subscription and /topup — Changing your subscription used to mean a trip to the billing website. Now /subscription opens a full flow right in the TUI or classic CLI: see your plan and remaining allowance, preview exactly what an upgrade costs ("Pay $46.30 & upgrade now") or when a downgrade takes effect, and apply it — with scheduled-change banners and undo. The desktop app got a matching billing settings tab. Your wallet never has to leave the keyboard. (#51639, #61054, #61067 — @alt-glitch)
Smart approvals are now the default — When Hermes wants to run a flagged command, an LLM reviewer now assesses it independently instead of asking you to approve every single one — and each verdict covers only that exact command, so a later command matching the same pattern gets its own review. Combined with the new user-defined deny rules (which block commands even under yolo mode) and /deny (which tells the agent why you refused so it course-corrects), day-to-day approval fatigue drops sharply without giving up control. (#62661, #59164, #54518 — @teknium1)
Plug your password manager into Hermes — Bitwarden & 1Password secret sources — API keys no longer have to live in a plaintext .env. A new pluggable SecretSource interface lets Hermes fetch secrets from Bitwarden and 1Password (op:// references) at load time, with multiple vaults enabled simultaneously, deterministic precedence, conflict warnings, and per-variable provenance. This consolidated eleven competing community PRs into one orchestrated interface — future vault providers drop in as plugins. (#59498 — @teknium1, 1Password provider salvaged from @hwrdprkns)
Watch your subagents work — live transcripts + durable background delegation — delegate_task dispatches now return live transcript files you can tail -f the moment the subagents launch: every tool call, result, and streamed reply, one human-readable log per child. And background delegation completions are now durable — if the process restarts mid-run, results are restored and delivered through an ownership-checked ledger instead of vanishing. Fan out a fleet, watch any worker live, and never lose the results. (#67479, #63494 — @teknium1)
A finished answer can no longer be lost — the delivery-obligation ledger — If the gateway died between generating your response and confirming the platform actually delivered it, that answer used to be silently gone (and you'd paid for the turn). Final responses are now recorded in a durable ledger in state.db around the platform send and redelivered on the next boot — closing a P1 silent-loss window for Telegram, Discord, Slack, and every other channel. (#67181 — @teknium1)
One gateway, many profiles — profile-based message routing — A single multiplexed gateway sharing one bot token can now route specific guilds, channels, or threads to different profiles — each with fully isolated config, skills, memory, and secrets. Point your work Discord server at the work profile and your hobby server at personal, from one bot. A second multiplex hardening wave means one misconfigured profile can no longer take down the whole gateway. (#64835 salvaging @Burgunthy, #65700, #60589 — @teknium1, @benbarclay + six salvaged contributors)
New providers and the newest frontier models — Fireworks AI and DeepInfra land as first-class providers (Fireworks with cost estimation and a #2 slot in the provider picker), Upstage Solar joins via salvage, and the model catalogs picked up GPT-5.6 (Sol/Terra/Luna + Pro variants, wired end-to-end across every route), grok-4.5 (GA), moonshotai/kimi-k3, claude-fable-5 / claude-sonnet-5, and GA tencent/hy3 — plus LM Studio JIT model loading for local setups. (#62593, #63969, #61616 — @kshitijk4poor completing @rob-maron's #61578, #60887, #65913, #64541, #65472)
Crank the thinking to max — new reasoning effort tiers and per-model control — Reasoning effort gained max and ultra levels (GPT-5.6 and Codex's top tiers), selectable everywhere from the CLI to the desktop, with sane clamping on providers with smaller scales. You can now also pin per-model reasoning-effort overrides in config, set per-slot effort in MoA presets (your advisors think hard, your synthesizer stays fast), and per-task effort for auxiliary models. Thinking depth is now a dial, not a global switch. (#62650, #64458, #64631, #64597 — @teknium1)
Your sessions, your data — export everything — hermes sessions export now writes Markdown, Quarto, HTML, prompt-only, and even Hugging Face-ready trace formats, with the full filter surface (age, workspace, platform), an opt-in --redact secret-scrubbing pass, and compacted-session lineage stitched into one logical export. Pair with the new prune filters and bulk archive to keep your session store tidy. Your conversation history is a real dataset now, not a black box. (#60186 salvaging @web3blind, #60492, #60507, #59327 — @teknium1)
Security hardening round — This window closed a long list of credential-surface gaps: Vertex credentials scoped away from subprocess env and through profile secret scopes, media/vision/image-gen local-file reads routed through one shared credential-read guard, a webhook body-size-cap sweep across every aiohttp server, bot-token redaction in Telegram transport errors, Fireworks token prefixes added to the redactor, six P1 browser/MEDIA/.env hardening PRs salvaged in one pass, and CI hardened against untrusted-ref interpolation. (#57660, #58709, #59215, #56582, #57842 — @teknium1, @srojk34, @kshitijk4poor, @jquesnelle)

⚡ Performance — the speed spine

First-turn latency (all platforms)

~80% TTFT cut — Discord capability detection off the critical path (token-keyed 24h disk cache + background refresh), Ollama probe skipped for known non-Ollama providers, agent-init blocking work removed; cold submit→dispatch ~4.3s → ~0.9s (#59332 — @teknium1)
Perceived-latency round 2 — display.show_reasoning default ON (watch the model think instead of a spinner), per-token response-box painting with width-aware force-flush, prompt-build caching, mtime-cached timezone resolution (#59389 — @teknium1)
Segment mixed tool batches to recover lost concurrency; drop per-call base64 re-serialization from request-size estimates (#64460, #67788 — @teknium1, @OutThisLife)

Desktop speed wave

14× less splitter CPU via incremental block lexing for streaming markdown; virtualized review-pane diffs (no more full-Shiki freeze); snappy session switching on large transcripts; killed the layout-thrash cascade on session switch (#67154, #67818, #65898, #66033 — @OutThisLife)
Cut startup serialization + per-turn REST amplification; pre-warm profile backends and gateway sockets on hover intent; idle-mount boot-hidden panes; fast model picker + dialogs (#66747, #66347, #67857, #66470 — @OutThisLife)
Stop per-token sidebar + tool-row re-renders during streaming; stop eager JSON.stringify of every tool's args/result; scope tool-diff subscriptions; batch sidebar session slices into one profile-DB pass; targeted file-tree revalidation; rAF-coalesced sash resizes (#67742, #67842, #67195, #67245, #67824, #67838, #67844 — @OutThisLife)
Systematized perf benchmark harness with trustworthy cold-start + first-token measurement, replacing 12 one-off scripts (#67466, #67697 — @OutThisLife)

Everywhere else

TUI renders streamed markdown incrementally per block (#67236 — @OutThisLife)
Skill discovery cached by scan signature; snapshot manifest builds ~5× faster; text prefilter before AST parse in tool discovery (#61414, #61131, #63941 — @kshitijk4poor, @ethernet8023)
Copy-on-write message prep instead of full deepcopy; model-metadata probe-cache cluster; gateway session.resume model + display history from one SELECT (#61133, #61368, #67247 — @kshitijk4poor, @OutThisLife)
hermes update skips npm install when Node manifests are unchanged; dashboard session-list payloads trimmed + messages paginated (#61580, #60883 — @kshitijk4poor)
Byte-stable gateway system prompts — pinned session-context render keeps the prompt cache alive across turns (#67403 — @kshitijk4poor)

🏗️ Core Agent & Architecture

Providers & models

Fireworks AI provider with cost estimation + cached picker price columns, promoted to #2 in provider pickers (#62593, #65476, #65214 — @teknium1)
DeepInfra hardened integration; Upstage Solar provider (#42231 salvage) (#63969, #64541 — @kshitijk4poor)
GPT-5.6 (Sol/Terra/Luna + Pro) end-to-end — context lengths, native/Codex catalogs, pricing, compaction caps across every route (#61616 — @kshitijk4poor, building on @rob-maron)
grok-4.5 (GA) catalog + reasoning allowlist; kimi-k3 on Nous Portal + OpenRouter (kimi-k2.x retired) + K3 discovery on the Kimi Coding endpoint; claude-fable-5 / claude-sonnet-5 / fugu-ultra curated; GA tencent/hy3 (#60887, #65913, #65922, #56617, #60943 — @teknium1)
Catalog-labeled silent default (GLM-5.2) + bare-provider /model cost-safe routing; LM Studio JIT load mode; adaptive thinking for Kimi-family Anthropic endpoints (#64771, #65472, #67606 — @teknium1, @kshitijk4poor)
GLM-5.2 native reasoning_effort controls; Gemini request-context improvements; extra HTTP headers for LLM API calls; per-client model routing on the API server (#58884, #61873 — @vishal-dharm, #57038, #57028 — @teknium1)
Claude Sonnet 5 fully wired — curated lists, intro pricing, and metadata across every route (#67932 — @teknium1)
Hide providers you don't use — enabled: false per-provider flag + excluded_providers config scrub unwanted providers from /model pickers and built-in resolution (#67971 — @teknium1)
Bedrock catalog wave: real context-window probing from the live endpoint, 1M-context rows for current-gen Claude + Fable, geo-prefix parity, versioned profile-ID pricing, Opus 4.8/4.7 rows (#68007, #67977, #68005, #67976 — @teknium1)
kimi-k3 rollout completed across Kimi-direct catalog surfaces with 1M context on canonical Kimi Coding endpoints (#68108 — @teknium1)
Provider pickers: Qwen providers folded into one group row; collapsible provider groups in the desktop model picker; friendlier TUI model display grouping same-endpoint providers (#67758, #67904, #67908 — @teknium1)

Reasoning & MoA

max + ultra effort levels across every surface and route (#62650 — @teknium1)
Per-model reasoning_effort overrides via a unified resolution chokepoint; per-task auxiliary effort; per-slot MoA preset effort; session-scoped /reasoning in the CLI (#64458, #64597, #64631, #67946 — @teknium1)
MoA: reference_max_tokens to cap advisor output and cut latency; per-preset fanout cadence (user_turn runs advisors once per user turn); stale presets surfaced without retries; half-filled preset saves rejected at the API boundary; aggregator resolves reasoning like an acting model (#56756, #57591, #64756 — @teknium1)

Delegation, approvals & the agent loop

Live subagent transcripts + durable background completions (see Highlights) (#67479, #63494 — @teknium1)
Smart approvals default; user-defined deny rules (block even under yolo); /deny relays the denial reason; plugin pre_tool_call approve action escalates to a human gate (re-landed with rule keys) (#62661, #59164, #54518, #60504 — @teknium1, @kshitijk4poor)
Unified delegation concurrency caps (max_async_children deprecated); explain long provider waits on the live status line; deterministic tool-output risk exposure (#56955, #64775, #61793 — @teknium1)
Codex: live TUI/desktop tool cards for the app-server runtime, commentary streamed as visible interim messages, compaction routed through thread/compact/start, max-output truncation recovery, oversized message ids dropped on replay, banked usage-limit resets via /usage reset (#66514, #66115, #60114, #58155, #62225 — @teknium1, @kshitijk4poor, @JoaoMarcos44, #64280 — @teknium1)
Hooks: oversized hook-injected context spills to disk (#20468 — @teknium1)
Vibe reactions — floating hearts on affection across CLI/TUI/desktop, token-free core detection (#62016 — @OutThisLife)

Secrets & config

Pluggable SecretSource interface + Bitwarden & 1Password providers (see Highlights) (#59498 — @teknium1, @hwrdprkns)
hermes config get / unset; warn on unknown root config keys + doctor deprecated-key reporting; display.timestamp_format (#65540, #67370, #40622 — @teknium1)
Auxiliary model usage recorded per task in session accounting; conversation-scoped Nous Portal usage tags across aux/MoA/delegate calls; --usage-file JSON report for hermes -z (#65537, #65468, #59615 — @teknium1)

Sessions & compression

Sessions export: Markdown/QMD/HTML/prompt-only/trace formats, HF upload, --redact, unified filters; full prune filter surface + bulk archive; CLI workspace filter + restore-cwd-on-resume (#60186, #60492, #60507, #59327, #63091 — @teknium1, @web3blind)
Compression: preserve human intent and durable handoffs; retain prompt cache when memory is unchanged; flatten multimodal content for the summarizer keeping image handles; gateway compression routing integrity (#67275, #67916, #65046, #56868 — @kshitijk4poor, @teknium1)
Gateway session metadata consolidated into state.db; routing index moved to state.db (sessions.json now an optional legacy mirror); exact API bytes persisted in an api_content sidecar (#58899, #59203, #67274 — @teknium1, @kshitijk4poor)

🌐 Gateway, Fleet & Relay

Durable delivery-obligation ledger for final responses (see Highlights) (#67181 — @teknium1)
Profile-based routing for inbound messages + multiplex hardening wave 2 + GATEWAY_MULTIPLEX_PROFILES override (see Highlights) (#64835, #65700, #60589 — @teknium1, @benbarclay + salvaged contributors)
Per-session turn lease + conversation-scope funnel; unified session reset boundaries (reset sessions stay reset); truthful runtime readiness checks; per-channel model and system prompt overrides; per-session /model overrides persist across restarts (#67401, #65783, #62645, #56967, #57030 — @teknium1)
Session auto-reset default off; /sessions search ; webhook payload filters + route scripts; platform HTTP event callback routing; configurable long-running status phrases (#60194, #57685, #60944, #65702, #58872 — @teknium1)
Relay: generic OIDC client-credentials provisioning (NAS-free), routed profile carried from the connector wire source, channel context consumed from the connector; Nous auth forensics + nous_session_valid on /api/status for hosted self-heal; Docker re-seeds a terminally-dead Nous bootstrap session on boot (#60730, #60586, #64649, #59976, #59969, #59983 — @benbarclay)

📱 Messaging Platforms

Inline choice pickers for /reasoning and /fast on Telegram, Discord, and Matrix — one-tap native buttons instead of typing (#65799 — @teknium1)
WhatsApp: native Baileys polls (clarify renders as a poll), locations, rich inbound metadata; dashboard pairing flow (#58865, #60571 — @teknium1)
Discord: recover messages missed during reconnect; auto-created threads renamed to generated session titles; configurable interactive view timeout; opt-in owner mentions on exec-approval prompts; optional admin-only gate for approval buttons (#66149, #60187, #60230, #60493, #51751 — @teknium1)
Slack: live per-tool status line (#67080 — @teknium1, salvaging #62007)
Telegram: per-topic free-response allowlist; Google Chat clarify prompts rendered as cards (#65543, #65546 — @teknium1)
Voice: stt.echo_transcripts toggle; MEDIA: captions attached to the media bubble on standalone sends; display.tool_progress: log option (#58859, #61415, #57014 — @teknium1, @kshitijk4poor)

🖥️ Hermes Desktop App

Contribution-driven shell on a layout-tree model — panes, zones, and layouts as data; plugin-scoped i18n locale bundles followed (#60638, #67303 — @OutThisLife)
Capabilities page — Skills/Tools/MCP + Hub in one place, with responsive overlay nav; CLI/dashboard parity for skills hub, MCP test/toggle/catalog, maintenance ops, log filters; five UX fixes from live testing (#57590, #57441, #67482 — @OutThisLife, @teknium1)
Hermes Cloud connection mode (salvage of #55402); soft gateway switch + gateway-settings polish; terminal execution backend picker with health probes (#61912, #61916, #67203 — @OutThisLife, @teknium1)
Keybind hint tooltips + keybinds settings tab + unified worktree dialog; base-branch picker for new worktrees; green unread dot for background-finished sessions; background-task sidebar indicators; grouped tool calls across text-less messages; auto-scrolling window for long tool-call runs (#65204, #62243, #65109, #65174, #61147, #57913 — @ethernet8023, @OutThisLife)
Session + project color system (inherit from project, per-session override, shared across sidebar/tabs); unified active-project identity in chat status; workspace path status action (#67469, #67681, #67282, #63086 — @OutThisLife)
Declarative memory-provider panel + full-config modal; config-defined TTS/STT providers + xAI TTS params; custom endpoint settings; per-job cron model picker; profile-aware approval mode control; UI scale setting; Ctrl/Cmd+wheel zoom; chat backdrop toggle; /journey opens the memory graph overlay (#67206 salvaging @erosika, #67209, #67759 — @austinpickett, #67472, #63520, #60457, #67029, #64598, #57267 — @teknium1, @OutThisLife)
Full TypeScript conversion of the desktop tree (#57855 — @ethernet8023)

📊 Web Dashboard

Memory provider switching; safe session import flow; WhatsApp pairing; Discord-specific toolsets editable from the web UI; clarified manual Telegram bot setup (#60569, #63699, #60571, #65361, #64636 — @teknium1, @kshitijk4poor, @shannonsands)
Terminal keep-alive + reattach for dashboard chat sessions; heavy turns isolated in a compute host; paste/drop images into Chat; browser.headed schema toggle; profile + gateway topology on /api/status; mobile/hosted OpenAI OAuth login (#60515, #65895, #61929, #67046, #60537, #61330 — @teknium1, @OutThisLife, @benbarclay)
hermes serve is a true headless backend (no web UI build/mount) (#55923 — @OutThisLife)

🧰 CLI & TUI

/subscription + /topup terminal billing (see Highlights) (#51639 — @alt-glitch)
/model --once — one-turn model override that reverts automatically (#67113 — @teknium1, salvaging #29923)
Stacked slash-skill invocations — /skill-a /skill-b do XYZ loads both skills in order (Claude Code port), with autocomplete + ghost text (#57987, #58763 — @teknium1)
--safe-mode troubleshooting flag; uninstall dry-run; TLS failures fail fast with fix hints; /compact alias + preview flags; pip/Homebrew installs warned unsupported (#45300, #60111, #57992, #57029, #57225 — @teknium1, @ethernet8023)
TUI: model picker refresh support; custom skill bundles dispatched as agent turns; banner sizes skills display to terminal width (#59782 — @helix4u, #62859 — @Adolanium, #40624 — @teknium1)
Hermes Console REPL + perf follow-ups; hermes curator usage all-skills view; entry-point plugins surfaced in hermes plugins list (#57781 — @kshitijk4poor, #36727, #40623 — @teknium1)

🔧 Tool System, Skills & MCP

MCP: mcp__server__tool naming convention; server log notifications surfaced in agent.log; hosted OAuth completed across Dashboard + Desktop; configurable redirect_uri/redirect_host for proxied/WAF setups; OAuth callback port races closed; Blender added to the MCP catalog with a curated 4-tool default (#52750, #57416, #66151, #65610, #65622, #64463 — @teknium1, @benbarclay)
Skills: security/unbroker (autonomous data-broker removal) + blind opt-out hardening; unreal-mcp companion skill; blender-mcp reworked around the catalog entry; humanizer pattern expansion; mcp-oauth-remote-gateway optional skill (#57438, #57902, #65989, #64715 — @SHL0MS, #65066, #65486 — @teknium1)
Browser: full snapshots stored on truncation, eval denylist opt-in; computer_use follows cua-driver's verify→escalate ladder (#65923, #67123 — @teknium1)
Kanban: modal create-task dialog + editable board project directory; Done-card results made obvious; grab-to-pan board scrolling; attachment toolset + CLI with SSRF-guarded URL fetch; project directory captured at board creation (#66333, #63638, #60226, #65698, #63249 — @teknium1)
Cron: durable execution audit history; one-shot stale-removal race fixed; run-claim TTL derived from HERMES_CRON_TIMEOUT (#61791 — @teknium1, #62014 — @PRATHAMESH75, #59567)
mem0: self-hosted dashboard backend + recall tuning + setup-wizard mode (#56943, #60494 — @kshitijk4poor, @teknium1)
Image gen: Codex image inputs; unsupported Codex image accounts classified; tool args recursively normalized by schema (cline port) (#57017, #63627, #52220 — @teknium1, @kshitijk4poor)

🔒 Security & Reliability

Vertex: credential/project/region resolution through the profile secret scope; VERTEX_CREDENTIALS_PATH/GOOGLE_APPLICATION_CREDENTIALS stripped from subprocess env (#56680, #56582 — @srojk34)
Six P1 hardening PRs salvaged in one pass — browser guards, MEDIA anchoring, .env lockdown, delegate ACP transport (#57660 — @teknium1)
Media/vision/image-gen local-file reads routed through the shared credential-read guard; native image routing guarded by file-safety policy; unified image-source resolver + terminal-backend confinement (#58709, #58752, #57890 — @teknium1)
Webhook body-cap sweep: explicit client_max_size on 3 uncapped aiohttp servers + completion sweep; Raft chunked-request body limit; timestamp-bound V2 webhook signatures (#59180, #59215, #58902, #58508 — @teknium1, @srojk34)
Redaction: Fireworks token prefixes + Telegram transport errors; env-lookup false positives fixed for KEY=value and JSON/YAML config fields; bot tokens scrubbed from Telegram connect/send errors (#58501, #58534, #58915, #58893 — @teknium1)
computer-use: subprocess env sanitized across all five cua-driver spawn sites (#58889, #59165 — @teknium1)
Dashboard: managed-files credential guard widened past .env + dir-tree gap closed; OAuth token TOCTOU closed with atomic 0o600 writes; stale dashboards can't recreate deleted profiles (#58222 — @kshitijk4poor, #60236 — @teknium1, #49435 — @LeonSGP43)
CI: untrusted refs passed through env, not run: interpolation; JS/TS tests wired into CI with source-regex tests banned; js-autofix pushes via PR instead of direct-to-main (#57842 — @jquesnelle, #60707, #65186 — @ethernet8023)
Docker: terminal network toggle with full-path coverage; Git Bash Mandatory-ASLR install failures detected; Windows updater console hidden during handoff (#59149 — @teknium1, #64651, #66040 — @helix4u)
Anthropic: request-local clients so the stale/interrupt watchdog never corrupts SQLite; per-profile OAuth file; OAuth login 429 fixed (UA must not be claude-code/) (#67238 — @OutThisLife, #59339, #58178 — @teknium1)
Gateway/agent: tool_call_id deduplicated across pre-API sanitizers; background review inherits parent reasoning_config for Anthropic cache parity; /new memory extraction moved off the command path (#58350, #64379, #61139 — @teknium1, @kshitijk4poor)

🔁 Reverted in this window (for the record)

iron-proxy credential-injection egress firewall (#30179 → reverted in #58489) — not shipping in this release
dynamic-workflow orchestration skill (landed, then reverted) — not shipping
memory provider-actions extension point (landed, then reverted) — not shipping
Note: the plugin pre_tool_call approve escalation was reverted mid-window but re-landed in #60504 and ships in this release.

👥 Contributors

450+ people contributed to this release (via commits, co-author trailers, and salvaged PRs) — the biggest contributor window yet. Thank you, all of you.

Core team

@teknium1 — release lead; TTFT perf wave, delivery + delegation durability, smart approvals, SecretSource, gateway multiplex + profile routing, sessions export, security round, and a ~290-PR community salvage burn
@OutThisLife — desktop app (the speed wave, layout-tree shell, Capabilities page, session colors, vibe reactions, TUI incremental markdown, perf harness)
@kshitijk4poor — GPT-5.6 end-to-end, DeepInfra + Upstage Solar providers, perf cluster, compression integrity, mem0, dashboard guards
@ethernet8023 — CI overhaul (JS/TS tests wired in, autofix-via-PR, python speedups), desktop keybinds/worktrees/status indicators, full desktop TypeScript conversion
@benbarclay — relay OIDC provisioning, gateway multiplex override, Nous auth self-heal, hosted MCP OAuth groundwork
@alt-glitch — terminal billing (/subscription, /topup), desktop billing tab
@helix4u — desktop provider/model UX, TUI model picker refresh, Windows install/updater hardening
@austinpickett — desktop custom endpoint settings
@SHL0MS — unbroker + unreal-mcp skills, humanizer expansion

Top community contributors

@srojk34 — security hardening: Vertex credential/project/region scoping through the profile secret scope, subprocess env stripping, Raft chunked-request body limits
@HexLab98 — 11 fixes across MCP capability gating, Windows installer PATH, desktop cron editing, gateway systemd warnings
@UnathiCodex — desktop stability: zoom across display moves, LaTeX rendering, resume-stall and runtime-readiness fixes
@xxxigm — leak fix after thinking-only retry flush, dashboard auth/theme/PTY fixes
@erosika — desktop declarative memory-provider panel + honcho recall/timeout correctness
@Frowtek — credential security: master stores never mounted into skill sandboxes, live-transcript redaction, dashboard api_key precedence
@necoweb3 — browser private-page CDP guard, cron one-shot liveness, gateway compression fail-closed
@DavidMetcalfe — desktop updater version pill, Local/custom endpoint exposure, sidebar collapse behavior
@shannonsands — dashboard: mobile channel setup, Discord toolsets from web UI, Telegram setup clarity
@vishal-dharm — Gemini request-context improvements
@PRATHAMESH75 — cron one-shot stale-removal race, dashboard multiplex port-binding guard
@alelpoan, @embwl0x, @Adolanium, @giggling-ginger, @Drexuxux, @frizikk, @JoaoMarcos44, @wesleysimplici, @LeonSGP43, @pierrenode, @simpolism, @MorAlekss, @r266-tech, @WadydX, @nv-kasikritc — targeted fixes across desktop, TUI, gateway, cron, webhook, nix, and browser surfaces
Salvaged-work authors whose PRs were cherry-picked with credit this window: @Burgunthy (profile routing), @web3blind (sessions export), @hwrdprkns (1Password), @Christopher-Schulze, @Ahmett101, @sjiangtao2024, and many more — see the salvage PR bodies for full attribution

All contributors

@0-CYBERDYNE-SYSTEMS-0, @0disoft, @0xbyt4, @100yenadmin, @17324393074, @2751738943, @8294, @abhibansal-sg,
@adambiggs, @Adolanium, @aeyeopsdev, @aguung, @AhmetArif0, @Ahmett101, @ai-ag2026, @AIalliAI, @ajzrva-sys,
@alastraz, @alelpoan, @alex-fireworks, @alex-heritier, @alex107ivanov, @AlexFucuson9, @Alix-007,
@allenliang2022, @Almurat123, @AlsayedHoota, @alt-glitch, @alvarosanchez, @amanning3390, @AmAzing129,
@AndreasHiltner, @andrewhomeyer, @annguyenNous, @ansel-f, @antydizajn, @arminanton, @arnispiekus, @asimons81,
@asscan, @ats3v, @austinlaw076, @austinpickett, @avifenesh, @aydnOktay, @Bartok9, @bautrey, @bbednarski9,
@bbopen, @benbarclay, @bigstar0920, @binhnt92, @bird, @Black0Fox0, @BlackishGreen33, @bo.fu, @brendandebeasi,
@briandevans, @BROCCOLO1D, @Bruce-anle, @brunz-me, @Burgunthy, @bytesnail, @catbearlove1-lang, @Cdddo,
@cgarwood82, @CharmingGroot, @chouqin, @Christopher-Schulze, @claudlos, @CocaKova, @Code-suphub, @CodeForgeNet,
@craigdfrench, @CrazyBoyM, @crazywriter1, @cresslank, @cruzanstx, @cyrkstudios, @danilofalcao,
@datachainsystems, @DatTheMaster, @davidb73-hub, @davidgut1982, @DavidMetcalfe, @davidrobertson,
@deacon-botdoctor, @DECK6, @deepujain, @derek2000139, @designnotdrum, @deusyu, @devatnull, @devorun,
@dexhunter, @dfein38347g, @Dhravya, @DictatorBacon, @digitalbase, @dlkakbs, @dmabry, @DNAlec, @dodo-reach,
@doncazper, @dorokuma, @doxe0x, @Drexuxux, @dschnurbusch, @Dusk1e, @EdderTalmor, @egilewski, @elashera,
@Elektrofussel, @eliteworkstation94-ai, @embwl0x, @emo-eth, @emozilla, @enzo-adami, @Epoxidex, @ErnestHysa,
@erosika, @esthonjr, @ethernet8023, @evefromwayback, @evelynburger, @F4TB0Yz, @falkoro, @fanyangCS, @firefly,
@fjlaowan1983, @flewe, @flo1t, @flow-digital-ny, @floze-the-genius, @frizikk, @Frowtek, @FuryMartin,
@fyzanshaik, @gauravsaxena1997, @geoffreybutler94, @georgedrury, @gigakun3030, @giggling-ginger,
@Git-on-my-level, @gitcommit90, @githubespresso407, @gnodet, @GottZ, @Gridzilla, @grimmjoww578, @gumclaw,
@Gutslabs, @HaiderSultanArc, @harjothkhara, @heathley, @hejuntt1014, @helix4u, @HeLLGURD, @hellno,
@herbalizer404, @HexLab98, @hmirin, @Hopfensaft, @Hotragn, @hsy5571616, @huanshan5195, @HumphreySun98,
@hwrdprkns, @hydracoco7, @hydraxman, @iamlukethedev, @iborazzi, @IgorGanapolsky, @iizotov, @ildunari,
@infinitycrew39, @IpastorSan, @irresi, @isfttr, @isheng-eqi, @itsflownium, @izumi0uu, @Jaaneek, @JacketPants,
@jaisup, @jakelongvu-bot, @jakepresent, @jaketracey, @JAlmanzarMint, @JasonFang1993, @jbbottoms, @jcjc81,
@JiaDe-Wu, @Jiahui-Gu, @Jigoooo, @jingsong-liu, @jneeee, @JoaoMarcos44, @joelbrilliant, @John-Lussier, @jplew,
@jtstothard, @juniperbevensee, @Jupiter363, @justinschille, @k4z4n0v4, @kaishi00, @karfly, @kartik-mem0,
@kavioavio, @KCAYAAI, @kenyonxu, @keslerm, @kevinrajaram, @knoal, @kocaemre, @kohoj, @konsisumer, @krowd3v,
@kshitijk4poor, @kuangmi-bit, @kubolko, @kyssta-exe, @Kyzcreig, @l0h1nth, @labsobsidian, @laurinaitis,
@LavyaTandel, @lawyer112, @lemonwan, @LeonSGP43, @lEWFkRAD, @linfeng961, @liuhao1024, @liuwei666888, @ljy-2000,
@loes5050, @logical-and, @LoicHmh, @loongfay, @lord-dubious, @lost9999, @lucasfdale, @lucaskvasirr,
@luxuguang-leo, @ly-wang19, @m0n5t3r, @m1qaweb, @M1racleShih, @MaartenDMT, @mahdiwafy, @MaheshBhushan,
@ManniBr, @marcelohildebrand, @marcolivierlavoie, @markoub, @MarkVLK, @Marxb85, @matantsevs,
@maxpetrusenkoagent, @mbac, @mdc2122, @mguttmann, @Mibayy, @michaelHMK, @mijanx, @minchang, @momomojo,
@MorAlekss, @morluto, @msh01, @mssteuer, @mvanhorn, @nanami7777777, @nankingjing, @necoweb3, @neo-claw-bot,
@neoguyverx, @nicha16, @nikshepsvn, @nima20002000, @nnnet, @NousResearch, @nullptr0807, @nv-kasikritc,
@okisdev, @OmarB97, @ooiuuii, @ooovenenoso, @oppih, @Osraka, @ostravajih, @otsune, @OutThisLife, @OYLFLMH,
@patrick-muller, @pdmartins, @pedrommaiaa, @Peterskaronis, @petrichor-op, @pgregg88, @pierrenode, @pixel4039,
@plcunha, @pnascimento9596, @Polyhistor, @PRATHAMESH75, @professorpalmer, @Punyko8, @Que0x, @Qwinty,
@r0gersm1th, @r266-tech, @rabadaki, @ragingbulld, @RainbowAndSun, @rainbowgore, @randimt, @rarf, @rasitakyol,
@rayjun, @raymondyan-zhijie, @re-ITRT, @RenoMG, @Rival, @RKelln, @rlaehddus302, @rob-maron, @rodboev,
@roryford, @rungmc357, @ruslanvasylev, @s0xn1ck, @s905060, @s96919, @sahibzada-allahyar, @sahil-shubham,
@Sahil-SS9, @SahilRakhaiya05, @sam7894604, @SAMBAS123, @samrusani, @sanidhyasin, @sasquatch9818, @sberan,
@ScotterMonk, @seagpt, @sebastianlutycz, @SemonCat, @setclock, @shannonsands, @sharziki, @shashwatgokhe,
@SHL0MS, @shuangxinniao, @SilentKnight87, @simplast, @simpolism, @SiteupAgencia, @sjiangtao2024, @sk-holmes,
@slow4cyl, @smtony, @soddy022, @Soju06, @solyanviktor-star, @SongotenU, @spiky02plateau, @sprmn24, @SquabbyZ,
@srojk34, @ssiweifnag, @stantheman0128, @StellarisW, @stephenschoettler, @suninrain086, @superposition,
@Supersynergy, @sweetcornna, @szafranski, @tanmayxchoudhary, @tarunravi, @tcconnally, @terry197913, @Thatgfsj,
@thegoodguysla, @thestudionorth, @TheTom, @TinkerOfThings, @tjboudreaux, @tjp2021, @Tortugasaur, @Tosko4,
@Tranquil-Flow, @trevorgordon981, @trismegistus-wanderer, @tt-a1i, @tuancookiez-hub, @TurgutKural, @Umi4Life,
@UnathiCodex, @unsupportedpastels, @uzaylisak, @valda, @vampyren, @veradim, @victor-kyriazakos, @virtualex-itv,
@vishal-dharm, @Vissirexa, @vizi0uz, @vkkong, @vKongv, @VolodymyrBg, @vortexopenclaw, @VrtxOmega, @WadydX,
@waroffchange, @waseemshahwan, @web3blind, @webtecnica, @wesleion, @wesleysimplicio, @williamumu,
@WilsonKinyua, @wxy-nlp, @wyuebei-cloud, @x7peeps, @x9x9x9x9x9x91, @xuezhaolan, @xxxigm, @ya-nsh, @yatesjalex,
@ygd58, @yingliang-zhang, @yinkev, @YLChen-007, @yu-xin-c, @yungchentang, @zapabob, @zccyman, @zeapsu,
@ziliangpeng, @zwcf5200, @zzpigpinggai

Also: bo.fu, Paulo Henrique, kyssta-exe 25470058+kyssta-exe.fu, Paulo Henrique, kyssta-exe 25470058+kyssta-exe.

Full Changelog: v2026.7.1...v2026.7.20

At VB Transform 2026, Zillow's engineering chief said AI ROI numbers only hold up if you measure before you build

Mon, 20 Jul 2026 19:18:54 +0200

Zillow, the real estate technology company, doesn't get one conversation with its customers. They move from a phone screen to a loan officer to a real estate agent, sometimes over months or years, and expect the context to follow them. A single chatbot could never carry that thread.

At VB Transform 2026, Zillow SVP of Engineering Toby Roberts and Glean co-founder and CEO Arvind Jain described how they built AI architecture meant to carry context across that entire journey — and why context, not raw data, turned out to be the harder problem to solve. Zillow's products touch roughly 80% of U.S. real estate transactions each year, and the company has been using AI long before ChatGPT existed.

"We pretty quickly identified that we were going to need a persistent context layer that was going to meet our customers and the professionals wherever they were," Roberts said.

Data was never the hard part

Roberts said Zillow's AI effort started where most enterprise AI efforts start, with the data itself.

"We started with a large push around making sure our data did have the right foundation," Roberts said. That meant a data mesh approach, clear data lineage and a governance structure with permissions and identity attached to the data itself.

None of that turned out to be the hard problem. The hard problem was building something that remembered where a customer was in their journey and carried that forward, no matter which surface they showed up on next.

"This context layer has to live to be able to support you where you are at any given point in your journey," Roberts said. Zillow chose to own that layer itself rather than depend on a single external chat interface, a decision Roberts said the team reached quickly once it looked at the shape of a real transaction rather than a single conversation.

Why Zillow built its own architecture, and where Glean fits into it

Zillow built its own harness rather than route customers through a single model API. The team drew on 20 years of machine learning history behind products like Zestimate, leaning into smaller, task-specific fine-tuned models instead of one general-purpose model.

Internally, that harness runs alongside Glean. Roberts said Zillow now has thousands of Glean agents in production, handling repetitive tasks with tens of thousands of executions across the company. Glean's pitch, per Jain, is centralizing that integration work once, through the Glean MCP gateway, rather than letting finance, legal and marketing each rebuild their own connections to the same systems.

That centralization is also a cost lever. Jain pointed to two mechanisms: model routing, which sends most tasks to smaller, cheaper models instead of defaulting to frontier models, and precomputed context, which avoids an agent burning tokens assembling its own context from scratch.

"Claude is also very slow because the first part of assembling that context actually takes forever," Jain said. Routing that request through Glean instead, he said, can cut token consumption by as much as half.

What Zillow and Glean's approach means for enterprises

Across data, cost and permissions, the session offered a few practical takeaways for enterprises building agentic AI on their own systems.

Build the measurement baseline before the AI push, not after. Roberts said Zillow's ability to credibly attribute a 40% increase in shipped code to AI adoption rests on a DORA metrics baseline the team put in place years earlier, not on the AI rollout itself.

Centralize context once instead of letting every team rebuild it. Jain's core argument for Glean's platform is that duplicated integration work across finance, legal and marketing teams is a hidden cost most enterprises haven't accounted for.

Don't assume permission inheritance is enough for regulated data. Even with a permissions-aware context platform in place, Zillow layered hard rules and a standing compliance check on top for its most sensitive categories, rather than trusting the architecture to handle it automatically.

Treat context as a cost lever, not just a capability. Model routing and precomputed context were the two mechanisms Jain pointed to for cutting AI spend, both aimed at reducing wasted token consumption rather than adding new capability.

"Models by themselves are not enough to bring automation with AI inside your enterprise," Jain said. "You do have to connect it with your enterprise context."

House of the Dragon Season 3 Episode 5 Secret Tunnel Explained

Mon, 20 Jul 2026 19:04:53 +0200

House of the Dragon Season 3 Episode 5 places Alicent and Helaena inside one of the Red Keep’s hidden passages, where a planned escape quickly turns into a dangerous trap. Their disappearance adds fresh political tension while also showing how the castle’s secret tunnels can protect people, mislead them, or leave them buried beneath the seat of power. The passage appears to connect with the maze built under the Red Keep during the reign of Maegor I Targaryen. Maegor ordered the construction of hidden doors, false walls, and escape routes so he could survive attacks or flee during a siege. He later killed the workers who knew the full design, which left the tunnels dangerous for anyone who entered without guidance. Why Alicent and Helaena Become Trapped Alicent and Helaena close the hidden door after entering the passage, then discover that someone has blocked the route ahead. Helaena drops their only light after a rat frightens her, leaving both women trapped in complete darkness with no clear way back. The blocked path suggests that someone deliberately closed this escape route. Mysaria stands out as the main suspect because she appears to know what happens across the Red Keep, including private details about Helaena. Larys Strong also remains a possible suspect because he often plans and understands how people behave under pressure. Their Disappearance Creates Political Trouble Rhaenyra will probably assume that Alicent and Helaena escaped from the castle, while Mysaria can use that belief to increase suspicion inside the Black faction. Daemon may reach a different conclusion and suspect that Ormund Hightower arranged their removal as part of a wider Green plan. Alicent and Helaena will likely escape the tunnels, but their temporary disappearance can still push both sides toward further conflict. The scene also gives the Red Keep a stronger role in the story, as its hidden structure becomes another source of fear, confusion, and political danger.

USN-8569-1: Linux kernel (HWE) vulnerabilities

Mon, 20 Jul 2026 18:18:40 +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 the Linux kernel did not properly handle shared page fragments during socket buffer operations, collectively known as Dirty Frag. A logic flaw existed in the XFRM ESP-in-TCP subsystem and in the RxRPC networking subsystem when processing paged fragments. A local attacker could use this to escalate privileges, or possibly escape a container. (CVE-2026-43284, CVE-2026-43500, CVE-2026-45998, CVE-2026-46000) It was discovered that a logic flaw existed in the XFRM ESP-in-TCP subsystem in the Linux kernel when handling socket buffer fragments. This flaw is known as Fragnesia. A local attacker could use this to escalate privileges, or possibly escape a container. (CVE-2026-43503, CVE-2026-46300) Qualys discovered that a race condition existed in the ptrace subsystem of the Linux kernel when privileged processes are exiting. An unprivileged local attacker could use this issue to expose sensitive information. (CVE-2026-46333) Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0 contain a memory leak when handling AppArmor notifications. A local attacker could use this to cause resource exhaustion. (CVE-2026-47326) Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0 contain a NULL pointer dereference when handling AppArmor notifications. A local attacker could use this to cause a kernel oops. (CVE-2026-47327) Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0 contained an invalid free when handling AppArmor notifications. A local attacker could use this to corrupt kernel memory. (CVE-2026-47328) Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0 contained insufficient validation of AppArmor notification responses. A local attacker could use this to allow crafted responses to be processed. (CVE-2026-47329) Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0 used an uninitialized variable when handling AppArmor notifications. A local attacker could use this to cause incorrect caching of data. (CVE-2026-47330) Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0 contained an out-of-bounds (OOB) read when handling AppArmor notifications. A local attacker could use this to cause information disclosure of kernel memory. (CVE-2026-47332) Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0 contained a out-of-bounds (OOB) read when handling AppArmor notifications. A local attacker could use this to cause kernel memory corruption and, theoretically, influence processing of AppArmor policies. (CVE-2026-47333) Tristan Madani discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0 contained incorrect holding of locks when handling AppArmor notifications. A local attacker could use this to cause a kernel panic or deadlock. (CVE-2026-47334) Tristan Madani and Trevor Lawrence have each independently discovered that Ubuntu Linux kernel 6.8, 6.17 and 7.0 contained a NULL pointer dereference when handling AppArmor network socket mediation. A local attacker could use this to cause a kernel oops. (CVE-2026-47337) Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - PSP security protocol; - ARM64 architecture; - PowerPC architecture; - RISC-V architecture; - S390 architecture; - User-Mode Linux (UML); - x86 architecture; - Block layer subsystem; - Cryptographic API; - Intel NPU Driver; - DRBD Distributed Replicated Block Device drivers; - Rados block device (RBD) driver; - Ublk userspace block driver; - Compressed RAM block device driver; - Bluetooth drivers; - Bus devices; - Character device driver; - TPM device driver; - Clock framework and drivers; - CPU frequency scaling framework; - Hardware crypto device drivers; - EDAC drivers; - EFI core; - FWCTL subsystem; - GPU drivers; - Greybus drivers; - HID subsystem; - Microsoft Hyper-V drivers; - Hardware monitoring drivers; - I2C subsystem; - I3C subsystem; - IIO subsystem; - InfiniBand drivers; - Input Device core drivers; - IOMMU subsystem; - LED subsystem; - Mailbox framework; - Multiple devices driver; - Media drivers; - NVIDIA Tegra memory controller driver; - IBM Advanced System Management driver; - MTD block device drivers; - Network drivers; - Ethernet bonding driver; - Mellanox network drivers; - Microsoft Azure Network Adapter (MANA) driver; - STMicroelectronics network drivers; - MediaTek network drivers; - NTB driver; - NVME drivers; - Device tree and open firmware driver; - PCI subsystem; - Pin controllers subsystem; - Chrome hardware platform drivers; - ACPI WMI driver; - x86 platform drivers; - Generic PM domains; - MediaTek PM domains; - Power supply drivers; - Remote Processor subsystem; - MPAM driver; - Amlogic Meson reset controller drivers; - S/390 drivers; - SCSI subsystem; - NVIDIA Tegra Control Backbone (CBB) driver; - SPI subsystem; - Greybus lights staging drivers; - Media staging drivers; - Realtek RTL8723BS SDIO drivers; - SM750 framebuffer staging driver; - TCM subsystem; - Thermal drivers; - TTY drivers; - USB Device Class drivers; - ULPI bus; - USB Gadget drivers; - USB Type-C support driver; - TI TPS6598x USB Power Delivery controller driver; - USB over IP driver; - vDPA drivers; - VFIO drivers; - Framebuffer layer; - TSM AMD SEV Guest driver; - Xen hypervisor drivers; - 9P distributed file system; - File systems infrastructure; - AFS file system; - BTRFS file system; - Ceph distributed file system; - EROFS file system; - Ext4 file system; - F2FS file system; - FUSE (File system in Userspace); - GFS2 file system; - HFS+ file system; - HugeTLB file system; - Journaling layer for block devices (JBD2); - Network file system (NFS) server daemon; - NILFS2 file system; - File system notification infrastructure; - NTFS3 file system; - OCFS2 file system; - Overlay file system; - Diskquota system; - SMB network file system; - Tracing file system; - UDF file system; - XFS file system; - DRM TTM subsystem; - Codetag library; - Control group (cgroup); - Kernel CPU control infrastructure; - Memory management; - QorIQ DPAA2 FSL-MC bus driver; - Freescale ENETC Ethernet drivers; - Memory Management; - KVM subsystem; - padata parallel execution mechanism; - PPP protocol drivers and compressors; - Bluetooth subsystem; - Networking core; - Netfilter; - Network traffic control; - Tracing infrastructure; - User-space API (UAPI); - io_uring subsystem; - IPC subsystem; - Audit subsystem; - BPF subsystem; - Kernel exit() syscall; - Kernel fork() syscall; - Kernel futex primitives; - Locking primitives; - Padata parallel execution mechanism; - Scheduler infrastructure; - Timer subsystem; - Cryptographic library; - Scatterlist API; - Heterogeneous memory management; - KASAN memory debugging framework; - 802.1Q VLAN protocol; - B.A.T.M.A.N. meshing protocol; - Ethernet bridge; - CAIF protocol; - CAN network layer; - Ceph Core library; - Distributed Switch Architecture; - IPv4 networking; - IPv6 networking; - MAC80211 subsystem; - Multipath TCP; - NFC subsystem; - Open vSwitch; - Packet sockets; - Phonet protocol; - Qualcomm IPC Router (QRTR); - RDS protocol; - RxRPC session sockets; - SCTP protocol; - SMC sockets; - Stream parser; - TIPC protocol; - TLS protocol; - Unix domain sockets; - VMware vSockets driver; - XFRM subsystem; - Integrity Measurement Architecture(IMA) framework; - Landlock security; - SELinux security module; - ALSA framework; - Generic PCM loopback sound driver; - FireWire sound drivers; - HD-audio driver; - Creative Sound Blaster X-Fi driver; - QCOM ASoC drivers; - SOF drivers; - STI ASoC drivers; - USB sound devices; - Objtool; (CVE-2026-31532, CVE-2026-31574, CVE-2026-31575, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31579, CVE-2026-31580, CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31589, CVE-2026-31590, CVE-2026-31591, CVE-2026-31592, CVE-2026-31593, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31600, CVE-2026-31601, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31607, CVE-2026-31608, CVE-2026-31609, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31614, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31620, CVE-2026-31621, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31686, CVE-2026-31694, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701, CVE-2026-31702, CVE-2026-31703, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31710, CVE-2026-31711, CVE-2026-31712, CVE-2026-31713, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716, CVE-2026-31717, CVE-2026-31718, CVE-2026-31719, CVE-2026-43058, CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43348, CVE-2026-43349, CVE-2026-43350, CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43493, CVE-2026-43494, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43498, CVE-2026-43499, CVE-2026-43501, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45837, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45986, CVE-2026-45987, CVE-2026-45988, CVE-2026-45989, CVE-2026-45990, CVE-2026-45991, CVE-2026-45994, CVE-2026-45995, CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46001, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46008, CVE-2026-46009, CVE-2026-46010, CVE-2026-46011, CVE-2026-46012, CVE-2026-46013, CVE-2026-46014, CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46020, CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46025, CVE-2026-46026, CVE-2026-46027, CVE-2026-46028, CVE-2026-46029, CVE-2026-46030, CVE-2026-46031, CVE-2026-46032, CVE-2026-46033, CVE-2026-46034, CVE-2026-46035, CVE-2026-46036, CVE-2026-46037, CVE-2026-46038, CVE-2026-46039, CVE-2026-46040, CVE-2026-46041, CVE-2026-46042, CVE-2026-46043, CVE-2026-46044, CVE-2026-46045, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46054, CVE-2026-46056, CVE-2026-46057, CVE-2026-46058, CVE-2026-46059, CVE-2026-46060, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46066, CVE-2026-46067, CVE-2026-46068, CVE-2026-46069, CVE-2026-46070, CVE-2026-46071, CVE-2026-46072, CVE-2026-46073, CVE-2026-46074, CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079, CVE-2026-46080, CVE-2026-46081, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084, CVE-2026-46085, CVE-2026-46086, CVE-2026-46087, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46093, CVE-2026-46094, CVE-2026-46095, CVE-2026-46096, CVE-2026-46097, CVE-2026-46098, CVE-2026-46099, CVE-2026-46100, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103, CVE-2026-46104, CVE-2026-46105, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46109, CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114, CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46118, CVE-2026-46119, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46130, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46134, CVE-2026-46135, CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46140, CVE-2026-46141, CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46147, CVE-2026-46148, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46153, CVE-2026-46154, CVE-2026-46155, CVE-2026-46156, CVE-2026-46157, CVE-2026-46158, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46162, CVE-2026-46163, CVE-2026-46164, CVE-2026-46165, CVE-2026-46166, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46170, CVE-2026-46171, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46175, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180, CVE-2026-46181, CVE-2026-46182, CVE-2026-46183, CVE-2026-46184, CVE-2026-46185, CVE-2026-46186, CVE-2026-46187, CVE-2026-46188, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46192, CVE-2026-46193, CVE-2026-46194, CVE-2026-46195, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46202, CVE-2026-46203, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46210, CVE-2026-46211, CVE-2026-46212, CVE-2026-46213, CVE-2026-46214, CVE-2026-46215, CVE-2026-46216, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46221, CVE-2026-46222, CVE-2026-46223, CVE-2026-46224, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46228, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46239, CVE-2026-46240, CVE-2026-46241, CVE-2026-46242, CVE-2026-46243, CVE-2026-46244, CVE-2026-46273, CVE-2026-46274, CVE-2026-46275, CVE-2026-46276, CVE-2026-46277, CVE-2026-46278, CVE-2026-46279, CVE-2026-46280, CVE-2026-46281, CVE-2026-46282, CVE-2026-46283, CVE-2026-46284, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46288, CVE-2026-46289, CVE-2026-46290, CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46295, CVE-2026-46296, CVE-2026-46297, CVE-2026-46298, CVE-2026-46299, CVE-2026-46301, CVE-2026-46302, CVE-2026-46303, CVE-2026-46304, CVE-2026-46305, CVE-2026-46306, CVE-2026-46307, CVE-2026-46308, CVE-2026-46309, CVE-2026-46310, CVE-2026-46311, CVE-2026-46312, CVE-2026-46313, CVE-2026-46314, CVE-2026-46315, CVE-2026-46316, CVE-2026-46317, CVE-2026-46318, CVE-2026-46319, CVE-2026-46320, CVE-2026-46321, CVE-2026-46322, CVE-2026-46323, CVE-2026-46324, CVE-2026-46332, CVE-2026-52904, CVE-2026-52905, CVE-2026-52906, CVE-2026-52907, CVE-2026-52911, CVE-2026-52912, CVE-2026-52913, CVE-2026-52914, CVE-2026-52915, CVE-2026-52916, CVE-2026-52918, CVE-2026-52919, CVE-2026-52920, CVE-2026-52921, CVE-2026-52922, CVE-2026-52923, CVE-2026-52925, CVE-2026-52926, CVE-2026-52927, CVE-2026-52928, CVE-2026-52931, CVE-2026-52932, CVE-2026-52933, CVE-2026-52934, CVE-2026-52936, CVE-2026-52937, CVE-2026-52941, CVE-2026-52943, CVE-2026-52944, CVE-2026-52949, CVE-2026-52950, CVE-2026-52951, CVE-2026-52952, CVE-2026-52953, CVE-2026-52954, CVE-2026-52955, CVE-2026-52956, CVE-2026-52957, CVE-2026-52958, CVE-2026-52959, CVE-2026-52960, CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52965, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52971, CVE-2026-52973, CVE-2026-52974, CVE-2026-52975, CVE-2026-52976, CVE-2026-52977, CVE-2026-52978, CVE-2026-52979, CVE-2026-52980, CVE-2026-52981, CVE-2026-52982, CVE-2026-52983, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52987, CVE-2026-52988, CVE-2026-52989, CVE-2026-52990, CVE-2026-52991, CVE-2026-52992, CVE-2026-52993, CVE-2026-52994, CVE-2026-52995, CVE-2026-52996, CVE-2026-52997, CVE-2026-52998, CVE-2026-52999, CVE-2026-53000, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53005, CVE-2026-53006, CVE-2026-53007, CVE-2026-53008, CVE-2026-53009, CVE-2026-53010, CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015, CVE-2026-53016, CVE-2026-53017, CVE-2026-53018, CVE-2026-53019, CVE-2026-53020, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53024, CVE-2026-53025, CVE-2026-53026, CVE-2026-53027, CVE-2026-53028, CVE-2026-53029, CVE-2026-53030, CVE-2026-53031, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53038, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53042, CVE-2026-53043, CVE-2026-53044, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53051, CVE-2026-53052, CVE-2026-53053, CVE-2026-53054, CVE-2026-53055, CVE-2026-53056, CVE-2026-53057, CVE-2026-53058, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53067, CVE-2026-53068, CVE-2026-53069, CVE-2026-53070, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53078, CVE-2026-53079, CVE-2026-53080, CVE-2026-53081, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086, CVE-2026-53087, CVE-2026-53088, CVE-2026-53089, CVE-2026-53090, CVE-2026-53091, CVE-2026-53092, CVE-2026-53093, CVE-2026-53094, CVE-2026-53095, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53099, CVE-2026-53100, CVE-2026-53101, CVE-2026-53102, CVE-2026-53103, CVE-2026-53104, CVE-2026-53105, CVE-2026-53106, CVE-2026-53107, CVE-2026-53108, CVE-2026-53109, CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53113, CVE-2026-53114, CVE-2026-53115, CVE-2026-53116, CVE-2026-53117, CVE-2026-53118, CVE-2026-53119, CVE-2026-53120, CVE-2026-53121, CVE-2026-53122, CVE-2026-53123, CVE-2026-53124, CVE-2026-53125, CVE-2026-53126, CVE-2026-53127, CVE-2026-53128, CVE-2026-53129, CVE-2026-53130, CVE-2026-53174, CVE-2026-53277, CVE-2026-53278, CVE-2026-53279, CVE-2026-53280, CVE-2026-53281, CVE-2026-53282, CVE-2026-53283, CVE-2026-53284, CVE-2026-53285, CVE-2026-53286, CVE-2026-53287, CVE-2026-53288, CVE-2026-53289, CVE-2026-53290, CVE-2026-53291, CVE-2026-53292, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53297, CVE-2026-53298, CVE-2026-53299, CVE-2026-53300, CVE-2026-53301, CVE-2026-53302, CVE-2026-53303, CVE-2026-53304, CVE-2026-53305, CVE-2026-53306, CVE-2026-53307, CVE-2026-53308, CVE-2026-53309, CVE-2026-53310, CVE-2026-53311, CVE-2026-53312, CVE-2026-53313, CVE-2026-53314, CVE-2026-53315, CVE-2026-53316, CVE-2026-53317, CVE-2026-53318, CVE-2026-53319, CVE-2026-53320, CVE-2026-53321, CVE-2026-53322, CVE-2026-53323, CVE-2026-53324, CVE-2026-53357, CVE-2026-53358, CVE-2026-53360, CVE-2026-53364, CVE-2026-53365)

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.

So finden Sie fremde Geräte in Ihrem WLAN und werfen diese raus

Mon, 20 Jul 2026 15:56:39 +0200

In den allermeisten Fällen lassen sich keine Rückschlüsse aus dem Namen ziehen, mit dem das Gerät in der Netzübersicht des Routers auftaucht: Denn zum Beispiel eine Fritzbox nutzt für die Anzeige üblicherweise den Windows-Computernamen – etwa Desktop-ABC12345 – oder eine Bezeichnung auf Basis der MAC-Adresse wie zum Beispiel PC-0E-3F-EF-12-F2-20.

Am besten sperren Sie für dieses Gerät zunächst den WLAN-Zugriff: Bei einer Fritzbox gehen Sie hierfür in das Routermenü und klicken unter „Heimnetz –› Netzwerk“ bei dessen Eintrag auf das Stiftsymbol. Im Anschluss daran markieren Sie bitte bei „Internetnutzung“ die Option „Gerät gesperrt“.

Möglicherweise klärt sich schon damit die Identität des Gerätes – beispielsweise wenn plötzlich die Musik aus dem smarten Lautsprecher verstummt oder die Sicherheitskamera Ihnen meldet, dass sie keine Verbindung mehr zum Netzwerk hat.

In der Routerliste der aktiven Geräte sollte beim neuen Gerät auch dessen aktuelle IP-Adresse im Heimnetz stehen: Geben Sie sie im Browser ein, um die Weboberfläche des Gerätes zu erreichen. Dazu müssen Sie zuvor kurzfristig die WLAN-Sperre aufheben. Eventuell öffnet sich nun der Zugang zum Gerätemenü, an dem Sie Hersteller oder Modell erkennen.

IDG

Als Nächstes sollten Sie anhand der MAC-Adresse des Gerätes versuchen, weitere Informationen zu Hersteller oder Produkttyp zu bekommen. In der Fritzbox finden Sie die MAC-Adresse unter „Heimnetz –› Netzwerk –› Netzwerkverbindungen“ in der entsprechenden Spalte. Kopieren Sie diese, um sie in einer Webseite einzutragen, die daraus den Herstellernamen berechnen kann – etwa www.deinip-check.de/tools/macfinder.

Diese Information kann ein Hinweis auf die wahre Identität des Gerätes sein, ist jedoch kein unumstößlicher Beweis: Denn Angreifer können mithilfe von einfachen Softwaretools die echte MAC-Adresse eines Geräts verschleiern und es stattdessen mit einer anderen versehen – zum Beispiel einer MAC-Adresse, die im Heimnetz bekannt und daher unverdächtig ist.

Der nächste Schritt sollte Sie ins Ereignisprotokoll des Routers führen – in der Fritzbox finden Sie dieses unter „System –› Ereignisse.“ Hier sehen Sie etwa, wann sich das Gerät bislang im Netzwerk an- und abgemeldet hat.

Möglicherweise lässt sich aus diesem Verhalten und dem Zeitraum der Netzwerkaktivität erkennen, um welches Gerät es sich handelt oder welche Person es im Heimnetz nutzt. Wenn sich das Gerät mit dem WLAN verbindet, sollte das Routerprotokoll außerdem festhalten, welchen WLAN-Standard und welche Bitrate es verwendet:

Eine niedrige Verbindungsgeschwindigkeit kann bedeuten, dass das Gerät weiter vom Router entfernt ist oder dass es sich beispielsweise um eine Smart-Home-Komponente handelt.

IDG

Um zukünftig schnell auf neue Heimnetzgeräte aufmerksam zu werden, sollten Sie im Router eine Push-Benachrichtigung aktivieren. Bei einer Fritzbox erledigen Sie dies unter „System –› Push Service“. Nachdem Sie eine passende E-Mail-Adresse hinterlegt haben, unter welcher Sie die Fritzbox erreicht, sollten Sie die Option „Änderungsnotiz“ aktivieren.

Mit einem MAC-Filter können Sie grundsätzlich verhindern, dass sich neue Geräte im Heimnetz anmelden: In der Fritzbox aktivieren Sie ihn unter „WLAN –› Sicherheit –› Verschlüsselung.“

Klicken Sie im Folgenden unten auf dieser Seite auf den blauen Schriftzug „WLAN-Zugang beschränken“ sowie anschließend weiter unten auf „WLAN-Zugang auf die bekannten WLAN-Geräte beschränken“. Ihnen unbekannte Geräte dürfen hierbei nicht in der Liste darüber auftauchen, andernfalls wird sie der MAC-Filter nicht blockieren.

Auch hier gelten die erwähnten Einschränkungen: Ein ernsthafter Angreifer kann für sein Gerät eine erlaubte MAC-Adresse übernehmen und damit den Filter umgehen. Zudem müssen Sie dann künftig auch jedes neue erlaubte Gerät in den MAC-Filter eintragen, was in der Fritzbox über die Schaltfläche „WLAN-Gerät hinzufügen“ funktioniert. Um eine regelmäßige Kontrolle der Aktivitäten im Heimnetz kommen Sie daher nicht herum, wenn Sie zuverlässig fremde Geräte entdecken wollen.

WLAN-Schutz 2025: So sichern Sie Ihren Router ab

OpenAI’s Codex context reduction for GPT 5.6 sparks dissatisfaction among developers

Mon, 20 Jul 2026 15:19:06 +0200

OpenAI’s recent update to its Codex coding agent has developers worrying over the impact of the change on large code repositories and long-running AI-assisted sessions.

The update to the Codex CLI reduces the default configured input context window for GPT-5.6 to 272,000 tokens from 372,000 tokens.

In practice, the update means the coding agent will retain a smaller amount of code, conversation history, and other session information before compacting older context to make room for new information, a change that has prompted criticism from some developers on Reddit and X over the reduced token window.

While OpenAI has not publicly explained the rationale behind the update, several developers took to social media to question why OpenAI reduced the default context configuration, with some arguing that the change could make Codex less effective on long-running coding sessions by triggering context compaction sooner.

Others expressed concern that the smaller window could require more frequent context management or session resets, although some noted that the practical impact would depend on project size and how developers structure their workflows.

Smaller context, bigger workflow implications

The context window reduction could affect developer productivity and the adoption of autonomous agents in enterprise workflows, analysts say.

“While the context reduction in Codex is unlikely to affect routine coding tasks such as bug fixes or changes involving a few files, it could impact large codebases, repository-wide refactoring, and long-running sessions,” said Pareekh Jain, principal analyst at Pareekh Consulting.

“Less memory per session means the AI agent forgets earlier parts of a long coding session sooner. The agent may need to summarize or reload context more often, increasing repeated searches, occasional loss of earlier decisions and the need for developers to re-establish context,” Jain added.

That need for manual context management, according to Muskan Bandta, cloud associate at FinOps services providing firm ZopDev, goes completely against the “whole appeal” of Codex-like tools that promised improved productivity out-of-the-box: “A lot of developers are saying their sessions now spend more time on compacting than actually working.”

“While context reduction may not further inflate bills, it shows up as more retries, more compaction, and your engineers spending more time babysitting the thing. The spend just moves from the invoice onto your team’s time.”

Amit Jena, AI development manager at IT consulting firm Kanerika, said that the context reduction will force development teams to choose between two options: either accept that the agent is reasoning with an incomplete picture of the required context or learn to manage a new design constraint around context compaction.

Development teams, Jena said, will need to design workflows that proactively manage context: by breaking work into smaller tasks, relying more on retrieval mechanisms, and monitoring context consumption.

That forced design constraint on engineering, echoed Bandta, will slow the enterprise adoption of agent-driven workflows: “Context is the agent’s working memory, so cutting it by a third changes what you can trust it to do at all.”

Build for changing AI platforms, not fixed limits?

More broadly, analysts pointed out that the episode is a reminder that enterprises should avoid tightly coupling software development workflows to the current operational characteristics of managed AI coding platforms, as context limits, pricing, runtime behavior, and model availability are all likely to evolve with little or no advance notice.

“Enterprises should avoid depending on any single context window, continuously benchmark AI coding tools on real workloads, and build workflows around retrieval, modular design, and agent orchestration so they remain resilient as models evolve,” Jain said.

Kanerika’s Jena echoed that view: “The right approach is to build AI-assisted development pipelines that degrade gracefully when operational parameters shift: instrument your context consumption, don’t hard-code context budgets, and treat the vendor’s current specifications as a starting point, not a contract.” Similarly, Bandta advised enterprises to treat managed AI coding platforms like any other critical software dependency: “Don’t build anything that only works right at the edge of a limit, and keep enough flexibility that you’re not stuck if one vendor changes the deal.”

What’s going wrong with this Kotlin code?

Mon, 20 Jul 2026 15:18:19 +0200

Author: Google for Developers - Bewertung: 1x - Views:13

Devs, this Kotlin challenge arises from a refactoring bug you might have seen. Here’s the setup: a teammate tidies up some code that builds job configurations. The build succeeds and everything looks fine. Then we check the list, and instead of the config object we expect, it holds something else. Watch the video and share what you think caused the bug!

Subscribe to Google for Developers → https://goo.gle/developers

Speakers: Anaya Mehta

AI’s problems aren’t what you think

Mon, 20 Jul 2026 15:08:44 +0200

The biggest and loudest prediction about AI is that it will eliminate millions of jobs. It is dramatic and easy to repeat. But from what I’ve seen, inside most enterprises the more immediate problem has turned out to be something else entirely: a growing mass of tools, agents, models and usage costs spreading faster than most organizations can govern or connect to real business value, also known as AI sprawl.

None of that invalidates the initial fear. Indeed, AI can clear backlogs, speed up analysis, draft usable content and reduce time spent on repetitive work. In my opinion, what goes wrong is the assumption that those gains will scale seamlessly, and that more AI will automatically produce more value.

What really matters is not only how much AI a company can deploy, but whether its use fits inside a growth strategy, an operating model and an organization that can use it well.

The early results of AI use made the logical progression feel obvious, even a foregone conclusion. If it could already improve output in narrow use cases, then broader deployment should produce broader gains. Simple! Better models were expected to deliver better results. More agents were expected to drive more automation. For many companies, this logic held for long enough to encourage overexpansion.

But this logic has started to break down as usage continues to scale. I’ve seen returns diminish much quicker than expected. To illustrate, one industry analysis found that developers who used AI most heavily produced about twice the output of moderate users, but consumed roughly ten times the compute.

At a certain point, more AI does not create proportionally more value – it simply becomes more expensive. But where, exactly?

From experimentation to sprawl

Experimentation played a key role in this downturn, but it’s not the culprit. As AI continues to sprawl, the problem continues that AI is spreading faster than most companies can coordinate. Teams often solve the same problem in parallel, paying for overlapping capabilities and layering new tools atop existing ones without any clear inventory of what ‘s already in place. What can appear as momentum is really turning into redundancy.

I’ve seen versions of this play out repeatedly. At one financial firm, several business units were pursuing AI projects aimed at automating research and reporting. Each team moved independently; selecting their own tools, building their own workflows and creating separate data pipelines, with little to no coordination between teams. In some cases, different groups were developing nearly identical capabilities without realizing it, solving the same problems twice without any shared visibility into each other’s work.

Individually, the projects showed real promise. Collectively, the projects created duplication, fragmented data and inconsistent standards business and enterprise wide.

By the time leadership stepped back to assess, the company found itself paying for overlapping capabilities, maintaining multiple versions of the same underlying data, and struggling to determine which solutions were actually delivering value versus which were simply consuming budget and eating at engineering time.

Perhaps most troubling: nobody at the enterprise level had a complete view of what was being built, by whom or why. What began as healthy, well-intentioned experimentation had, without anyone deciding it should, evolved into full-blown AI sprawl, creating a patchwork of disconnected initiatives that was difficult to govern, harder to secure and far more expensive than a coordinated approach could and should be.

Early wins encourage a still wider rollout, but many organizations expand usage before they put real controls in place. Experimentation becomes sprawl. Budgets grow quickly, and few leaders have a reliable view of who is using what or why.

AI strategy cannot sit beside growth strategy

This is where I see many companies still get the issue wrong. They treat AI and growth strategy as two separate efforts, then wonder how adoption gets so messy. A business cannot drop AI into its operations and expect momentum to take over. The technology has to support a clear path to growth, whether that means improving margin, speed, service, capacity or decision-making. At the same time, growth plans cannot assume AI changes nothing about delivery, design or operating leverage. The real challenge is in ensuring the two work together.

Personally, I’ve seen better results when AI initiatives are tied to a specific business objective from the beginning, rather than launched as broad, abstract or transformative effort. One mattress retailer I’ve worked with took this approach, starting with a single, focused and well-defined use case rather than trying to transform or overhaul the entire organization at once. The company introduced an AI-powered training platform for store associates, giving employees a low-pressure way to practice sales conversations and product recommendations before applying them to external situations with customers on the floor.

Because employees experienced immediate and tangible value from the tool, adoption spread quickly across locations, with minimal need for top-down mandates. Early, visible success helped to build internal credibility and generate momentum, which leadership then leveraged to expand into more complex AI initiatives across areas such as inventory management, demand forecasting and replenishment planning.

Ultimately, the technology succeeded not because it was innovative for its own sake, but because it was connected to a larger growth strategy: improving sales effectiveness on the floor, driving operational efficiency behind the scenes and strengthening workforce capability at entry level. A major lesson we walked away with here was that starting small and specific, with a clear throughline to business value creates a strong foundation for sustainable and scalable AI use.

What implementation actually takes

All this takes more than a few easy guardrails. It takes strategy. Leaders need a real inventory of the tools, agents and assistants already in use across the business, who owns them, what data they can access and everything that they support.

They also need financial controls that match the economics of token-based usage, including role-based access, thresholds and review processes that make spend visible before it becomes a surprise. Similarly, they need metrics that go beyond mere activity. More prompts do not mean more value. If a deployment cannot be tied to throughput, margin, quality, cycle time or another tangible result, it is still unfinished.

This is also why blunt shutdowns rarely work. If leaders clamp down too hard, employees often move to unsanctioned tools and create a larger shadow AI problem, or the unauthorized use of artificial intelligence tools, models or chatbots by employees, without the knowledge or approval of IT and security teams, with even less visibility and more risk. The better answer is disciplined adoption: clear ownership, rules, metrics and enough flexibility for teams to use AI where it works.

That matters for the people as much as it does for the budget. Those that modernize well end up with better work – not just less of it.

The story of the moment isn’t about AI replacing people – or even AI in general. It’s about whether companies know their own businesses well enough to keep incorporating powerful new tools without mistaking activity for progress. As technological capabilities continue to appear, the winners will be the organizations that understand where it belongs, what it can improve and how to turn each new wave into something permanent.

This article is published as part of the Foundry Expert Contributor Network.
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Game development diary: Crunch and preparing to launch

Mon, 20 Jul 2026 14:40:17 +0200

The Steam launch of "Character Limit" looms thanks to a final push to get the game ready. However, while it's "done" enough for people to play, there's still the problem of actually releasing it.

The full game is in Steam, awaiting launch.

It is safe to say that developing a word game like this wasn't meant to take a year. The first installment of this series was posted on July 28, 2025.

The math is easy to figure out how long it's been since I started.

Continue Reading on AppleInsider | Discuss on our Forums

🔒Lock Picking Robot! 🤖🔓 (emf2026)

Mon, 20 Jul 2026 13:48:51 +0200

An open source lock-picking robot, which counterintuitively is designed to make locks more secure. Made as an alternative to master keys, which are used widely (for example, on almost every suitcase) and have large inherent security issues. The lockpicking robot uses a series of wires which push through a custom 3D-printed steel key blank to spoof the correct key bitting. github.com/etinaude/unlocked 🔒➡️🔑🤖➡️🔓 Licensed to the public under https://creativecommons.org/licenses/by-sa/4.0/ about this event: https://www.emfcamp.org/schedule/2026/56-lock-picking-robot

Q&A: Why boutique consultancies might be better for AI rollouts than the bigwigs

Mon, 20 Jul 2026 13:33:13 +0200

Major AI labs are unleashing forward-deployed engineers (FDEs) to try and grab enterprise customers. Large consultancies are dishing out tokens and assembling armies of consultants — both human and agent — to do the same.

But smaller firms are in the mix now, as well. AI is helping 28Stone Consulting, a New York-based, 230-person technology consultancy for capital markets, punch above its weight against larger rivals in the rush to deliver FDEs.

In this Q&A, Thomas Dolan and Frank Erickson, founders of 28Stone, argue that agentic AI isn’t a one-size-fits-all solution in vertical markets; success takes discipline, deep domain expertise, and human involvement to mitigate risk.

Many enterprises continue to struggle with the use of AI agents, which is consultancies are stepping in to get projects off the ground. 28Stone is among those that have published blueprints and methodologies on the development and delivery of agentic AI workflows with humans in the loop.

Computerworld spoke with both founding partners about why companies are still stumbling with agentic AI rollouts, and what a disciplined delivery process actually looks like.

After 15 years of delivering software for capital markets firms, is ‘AI-first’ a real distinction or just positioning?

Dolan: “We’re not shying away from being AI-forward. What needs to shine through is AI done intelligently — not stuff you get by buying some tokens for somebody on the trading desk. We’re an AI-first firm.”

Erickson: “And it’s temporary. At some point, AI is going to be synonymous with software development.

“The whole idea of an AI SDLC (software development lifecycle) versus an SDLC is going to be one and the same, a lot like cloud computing today. To not include AI in your strategy, you’d look like a COBOL vendor.”

What does agentic AI delivery look like?

Dolan: “We’ve got several AI initiatives delivering a pure agentic approach. We’ve doubled down on the human expertise wrapper in the SDLC. That doesn’t mean sacrificing any of the benefits of the AI models — quite the opposite.

“You don’t achieve anywhere near the same level of value from applying AI without keeping that expertise — industry, functional and technical — throughout the process.”

Where do humans stay in the loop once agents are doing the work?

Dolan: “We’re believers in starting with requirements discovery. Someone who knows the analytical nuances of a good business analyst is critically important; shaping a product owner’s business information through a markup file that can be fed into a BA agent, then treating the output as if it came from a very fast junior BA. Only then is the story complete.

“The developer takes that story, transforms it into the most efficient input, then owns the output, because they’re accountable for that code. A developer should own the code on both the input and output side.

“Your product owner, who knows the business, that’s great. But expecting them to interact with an agent and output enterprise code is ridiculous. It’s not a great plan.“

Why not just put one do-everything person in charge of AI and agents?

Erickson: “Every analyst, programmer or software engineer isn’t a great requirements analyst. And a great domain analyst with some technical background won’t know if the agent’s code is garbage, maintainable, performant.

“It’s unrealistic to expect one individual to have that breadth across domain, software engineering, testing, deployment. Clients ask all the time, and we push back: ‘Great, if you can find that guy, they’re few and far between.’ To deliver at the enterprise level, you need the human expertise, at depth.“

Dolan: “There’s system speed and latency, important in parts of finance. Then there’s speed of delivery, because other areas evolve quickly and time-to-market is critical.

“Our human wrapper may at first pass come across as a little slowed down. Maybe it is. But [Erickson] has a good analogy about one of the dangers of AI: you can end up going really fast in the wrong direction. By the time you look up, you’re way off base and have to backtrack.“

What about AI in your sector do you think is overhyped?

Dolan: “The hype around the ease of use of AI and the democratization of enterprise software delivery — that ‘anybody could do it now, it’s all being done by machines’ — is another idea that could prove costly in the long run.

“This do-it-yourself reaction is dangerous for clients, and for trust in the overall AI benefit, which is real. We compare it to the beginning of offshoring 20, 30 years ago: a golden idea that was going to cure everything. A lot of firms did it thoughtlessly, thinking it’s just labor arbitrage, and it almost inevitably failed. That all-or-nothing mentality missed that offshoring is an amazing way of getting better value for your dollar, but it has to be done thoughtfully, so the delivery process — the thing that ties it all together — stays unsevered.

“We’re seeing that now. I’ve heard, ‘We’ll just push a button, the machine’s building the system.’ The machine is not building the system. It might be writing the code, the story, running the tests.

The system is built by a team of engineers you bring in and trust. My fear is that people will say, ‘We don’t need this vendor or this technology team. I’ve got a product team. They might not be able to code at all, but they know the business,’ and it fails dramatically.

“Then people say, ‘We played with AI, it’s not ready yet,’ and throw it all away. One of the best things we can do is ensure clients know the benefit is real.“

Erickson: “The hype can be summed up in a single phrase: vibe coding. That has done AI a massive disservice, because there’s a huge difference between vibe coding and enterprise software development, and some of the loudest proponents of AI are too latched on to it. In our industry, the only way to succeed would be a stable of unicorns. It just doesn’t scale. I get perturbed when our people internally refer to AI tooling as vibe coding; if they think that’s what they’re doing, they’re misunderstood.“

When you engage clients at different levels of AI maturity, how do you get them to a understand what works?

Dolan: “95% of our take on an agentic approach is in line with everyone else’s, but that 5% matters, especially in requirements discovery, in who’s giving the requirements and how they’re thought of. It can set you up for dramatic errors, given the speed at which you’re moving.

“There’s a dangerous human tendency we’re seeing among clients to try and cut corners at the start of a project and — in lieu of having deep, expert driven discovery sessions — just summarize what they may want using AI.

“We would hope our clients are collaborative, everyone understanding it’s early days. If a client insists on doing something we feel strongly against, like a product owner completely owning everything right up to code generation, that’s an issue we have to either push back strongly on or step out of the accountability for.“

AI body shops — LLM providers and giant consultancies — are emerging to help enterprises deploy AI. Does that model work?

Dolan: “Whether you’re partnering with an LLM or with an AI-first, generic software provider — ‘Hey, we’re not industry guys, but we know AI delivery’ — you end up, if you’re a bank or a broker-dealer, saying: ‘All right, we know our business, these guys know the AI side of it. What could go wrong? Put us together and we’ll have quality engineering.’

“The problem is what you miss: the know-how of putting industry and technical expertise together and actually delivering financial services systems. The people working at the generic delivery firms, whether an AI-only firm or a body shop somewhere, don’t have that capability.“

Does AI change the economics for smaller consultancies like yours competing against the big firms, and does it cut both ways?

Dolan: “Over our 15 years pre-AI, there were two recurring reasons we’d lose a project. One: ‘We’d love to work with you guys, given your subject matter expertise, but the costs just aren’t there compared to my budgets. I’m being forced to go to a body shop or an [offshore] delivery center.’ The other side of that coin: ‘We love your capabilities, but you’re a firm of 230 people and I need 300, 400 people.’

“AI changes the options for clients. You don’t have to sacrifice the niche vendor who knows your space just because you need a larger team or a cost target. AI levels the playing field and should allow smaller firms to compete with the larger, big-box generic firms, the Accentures of the world.“

Erickson: “It redefines what scale means. You can look at velocity as a measure of your cost to deliver, not a rate card. Scale can’t be defined in terms of headcount anymore. It’s got to be defined in terms of output.

“There’s a threat in it, too. If you’re an Accenture with hundreds of thousands of low-cost software engineers, how do you train all those people? I feel for them. But for us, a couple hundred people with a specific domain focus, it’s a huge opportunity.“

How has the profile of the people you and others hire changed with this agentic process?

Erickson: “You’re still looking for people with strong engineering and design backgrounds, and communication skills, because they interact across the software development lifecycle more than in the past.

“Many take too much joy in typing out perfect code. Sorry, I don’t need you writing for-loops and classes anymore. I need you reviewing them, understanding them, operating at a higher level. That’s a different kind of person: an engineer, not a programmer or a coder. On the [business analyst] side it’s similar: people took great pride in detailed user stories covering every path. Now it’s conversations, prompts, reviewing output — less doing, more interacting.

“More than ever, they have to be interested in the domain. They can’t just be, ‘I want to learn everything there is to know about Java.’ That’s too narrow. They don’t have to be an expert; they have to be interested. In our case, capital markets is a specific niche. The biggest challenge is getting familiar with the tools — finding time, while delivering for customers, to ramp up and make the mistakes you need to without jeopardizing projects.“

What about governance? Who’s keeping AI delivery and its costs under control?

Erickson: “This is evolving rapidly. People aren’t sure how to put governance around this. The most obvious is financial governance. People are starting to get hefty bills. One of our clients spent a million dollars on tokens over the last eight weeks alone. Sticker shock. The token-maxing policies are starting to show their flaws. It’s wild west still: learn on the fly, then figure out what needs to be governed.“

Are CIOs actually opening their wallets? And when they do, what’s the smarter way to invest?

Erickson: “There’s still a lot of caution. Forecasts keep going down on how long something should take. So: ‘I could wait three months and maybe still get it delivered by the same date someone’s promising me now, but for half the price. I’m going to wait and see when equilibrium is met.’ We haven’t seen the wallets open up like crazy — it’s slow adoption.“

Dolan: “One of our clients is looking at it from a productivity-boost perspective: instead of doing the same for less, I can do much more for the same. AI lets clients pull the trigger on things they wouldn’t have in the past — projects that might not have been approved pre-AI, where the costs have come down to a point that’s palatable with the business.“

Erickson: “And that’s the story we’re hoping to hear more of. There isn’t a huge cost anymore to exploring a business opportunity. The time and money that would have gone to a return-on-investment study could be spent on a proof-of-concept with AI, and the project done a few weeks later. Maybe [there’s] a hint of things to come, where decisions start being made quicker.

“There’s a little fear on our side, though: a lot of tiny little projects is tough for a consulting business.“

🔒Lock Picking Robot! 🤖🔓 (emf2026)

Mon, 20 Jul 2026 13:17:55 +0200

Gotify 3.0.0: Push-Nachrichten selbst hosten

Mon, 20 Jul 2026 12:03:57 +0200

Gotify 3.0.0 führt OpenID Connect für die Anmeldung ein, verschärft den Umgang mit API-Token und überarbeitet die Konfiguration.

Police Chiefs Cite TfL Hack in Push for Cybercrime Risk Orders

Mon, 20 Jul 2026 11:54:00 +0200

Two chiefs of UK policing agencies said the Transport for London prosecution demonstrates the need for Cybercrime Risk Orders

Finding the right balance between autonomy and scale

Mon, 20 Jul 2026 11:36:55 +0200

For diversified enterprises, few operating model questions are as persistent or polarizing as centralization versus decentralization. Decentralization promises speed, ownership, and local responsiveness. Centralization promises efficiency, standardization, and leverage. Both can be right. Both can be wrong. The challenge is that many organizations end up with both models operating at once, without enough clarity about why.

The result of fragmented systems, duplicated capabilities, inconsistent data, rising IT spend, and a complexity tax that compounds over time is familiar to many CIOs. What starts as autonomy can become architectural sprawl. What starts as enterprise leverage can become bureaucracy. And as companies modernize core platforms, integrate data, and scale capabilities like AI, the tension becomes harder to ignore.

Paul Krebs has lived that tension from multiple vantage points. Most recently as CIO and chief transformation officer at Koch Industries, and previously a technology and transformation leader at The Coca-Cola Company, he’s worked in environments where business units value autonomy, enterprise scale matters, and the wrong operating model can slow progress just as easily as the wrong technology architecture.

His conclusion isn’t that CIOs should pick a side, but they need a more intentional form of centralization, one that starts with business architecture, clarifies decision rights, and continually revisits where capabilities should sit as the organization matures.

Centralization: a design choice, not a doctrine

In diversified organizations, decentralization often starts as the default because it aligns with how the business creates value. Local businesses understand their customers, markets, regulatory environments, and operating realities, and giving them decision rights can increase speed and accountability.

In Krebs’ experience, the default model often leaned toward decentralization, he says, with the belief that optimizing for customers and markets would allow different businesses to be as responsive as possible to the specific customers and markets they served. But that logic isn’t complete. Leaders also need to ask whether there’s a compelling case where a more centralized approach can generate additional value, accelerate progress, or optimize investments.

Digital transformation created one of those moments. Krebs recalls around 2016 when Koch challenged its businesses to build multi-year digital transformation roadmaps. The ambition was there, but the capabilities to execute at the necessary pace weren’t evenly distributed. In response, the organization invested more aggressively from the center, building shared services and centers of expertise in areas such as business transformation, enterprise applications, and data and analytics.

The purpose was acceleration, not control. Centralizing those capabilities helped accelerate learnings, capability building, and their ability to deploy new solutions at scale. But the move wasn’t treated as permanent. “There was always a belief that the centralization push should be re-looked at on a regular basis, not thought of as a forever decision,” he says.

Know what belongs at the center

Over time, Krebs learned that the capabilities most likely to remain centralized were those where scale, consistency, and risk management mattered more than local differentiation. Infrastructure, collaboration platforms, cybersecurity, cloud management, FinOps, and the help desk were natural candidates to remain shared services.

Other areas were more nuanced. Some application capabilities moved back into the businesses as local maturity increased. Many data and insights capabilities also moved closer to the business once teams had built enough muscle to own them. Meanwhile, certain emerging capabilities such as spatial technologies like AR/VR remained centralized because it didn’t yet make sense for each business to build them independently. Many companies have lived this journey as well, for example, with gen AI, which often started with a center of excellence, and then evolved into a more decentralized approach, enabling teams across the business to innovate quickly.

That distinction avoids the trap of treating the enterprise as one uniform operating model. “Both models can be successful, and both have advantages,” he says. “That’s what makes the balance so difficult.”

Centralization provides a clearer path to execution at scale and cleaner decision rights, but it requires change management and careful attention to bureaucracy. Decentralization provides ownership and speed, but it can also over index toward preference versus real differentiation, he adds, while making architecture harder to scale later.

Don’t confuse standardization with centralization

One of the most important distinctions Krebs makes is between centralization and standardization. Many organizations treat them as interchangeable, but they’re not.

“You can have a centralized team that can manage the nuances of different requirements,” Krebs says. “You can also have a centralized standard platform that can be used in a decentralized manner.”

That distinction opens up more operating model choices. A company may centralize a platform but decentralize how business teams configure or use it. It may standardize process patterns while keeping execution close to the region or business unit. It may also centralize architectural governance while allowing local teams to move quickly within defined guardrails.

This is especially important in global organizations, where regional needs are real but not always unique. Krebs advises leaders to examine whether local requirements can be made more generic and reusable. The risk is solving each local requirement as a one-off, so the better path is to understand the underlying requirement, build it in a way that can scale, and still allow local teams to execute within the standard model.

Let business architecture lead technology architecture

Few topics expose the centralization tension more clearly than ERP consolidation. Many diversified companies, particularly those shaped by acquisition, end up with dozens or hundreds of ERP instances. Some leaders push for massive consolidation. Others prefer to build integration layers on top of the existing environment.

Krebs’s starting point is neither technology nor cost. It’s business architecture. “The easiest and most effective path is when the IT or systems architecture follows and aligns to the business architecture,” he says.

If the business is truly going to operate processes separately, separate systems may be appropriate. But if the organization has numerous teams, processes, and tools, leaders need to ask whether there’s enough differentiation and value to justify that complexity.

The same logic applies to M&A. Companies can get into trouble when integration synergies are held hostage by ERP migration timelines. Instead, Krebs advises starting with the business integration strategy. Understand where the synergies are, how the business architecture should come together, and then decide whether the IT architecture needs to be fully integrated, or whether a data layer, reporting platform, or other integration approach can deliver value faster.

Make the cost of complexity visible

CIOs in decentralized companies often face a frustrating dynamic. The business wants autonomy and speed, but the same leadership team still questions why IT spend is high relative to benchmarks. Krebs says the answer starts with cost alignment and visibility.

In environments with a mix of centralized and decentralized services, Krebs saw centralized capabilities like infrastructure, help desk, and security perform well on benchmarks. More decentralized areas, such as BI, reporting, and commercial applications, often had more redundancy and higher cost.

The point isn’t to blame the business but make the economics of complexity visible. CIOs need to show how flexibility in one area may require multiple systems, data stores, or teams elsewhere. “I understand we want flexibility here,” Krebs says. “But leaders must see when that flexibility may cost the company money, and be clear on whether the value justifies it.”

That shifts the conversation from IT cost to business service economics. A single aggregate IT spend number is rarely useful in a decentralized environment. More helpful is a capability-based view that shows which areas are scaled efficiently, which are fragmented, and where the business architecture is driving the technology cost structure.

Revisit the model as maturity changes

For a new CIO entering a decentralized environment, Krebs cautions against immediately declaring that too many things need to be centralized. The better starting point is curiosity. “I would begin with just trying to understand why they’ve made the decisions they have,” he says.

From there, CIOs can engage leaders in a conversation about the target operating model, connecting business architecture to technology, data, and organizational capabilities. Once the direction is clear, he advises CIOs to work with the willing. Find the parts of the organization that already see the need for change, prove the model there, and scale from demonstrated success.

Regardless of execution, though, the right model changes over time. A low-maturity capability may benefit from centralization because the organization needs to build talent, avoid reinventing the wheel, and accelerate learning. As maturity grows, decentralization may make more sense because business teams need flexibility to adapt quickly. Once maturity is high and patterns stabilize, the organization may be ready to centralize again to leverage scale.

“Once I’ve decided I’m going to start with centralized or decentralized, you don’t necessarily need to stay in that model,” Krebs says. “You need to be continually revisiting the operating model as your organization matures and evolves.”

That may be the heart of smart centralization. It rejects the false permanence of operating model decisions, and recognizes that autonomy and scale are both valuable, but in different places, at different times, for different reasons.

Craneware Confirms Data Breach, Employee Records Among Exposed Data

Mon, 20 Jul 2026 10:24:21 +0200

Craneware plc has disclosed a Craneware data breach after detecting unauthorized access to a portion of its data environment. The company confirmed on 20 July 2026 that it is investigating the incident with the support of external cybersecurity and forensic experts. Although the cyberattack on Craneware resulted in data being viewed and exfiltrated, the company said the incident has been contained and has not disrupted customer services or business operations.

Craneware Cyberattack Contained, Investigation Underway

According to the company's official notice, the Craneware cyberattack prompted the activation of its incident response plan immediately after the unauthorized access was identified. The Board appointed external cybersecurity and forensic specialists, who are working alongside Craneware's internal IT team and retained security providers to determine the full scope of the incident. The company stated that investigators have found no remaining indicators of compromise within its systems. Despite the data breach at Craneware, normal operations have continued without interruption.

Data Breach at Craneware Exposed Employee and Customer Records

Initial findings indicate that attackers viewed and exfiltrated a significant volume of file names. Craneware's current assessment suggests that much of the affected information consists of non-sensitive or publicly available regulatory data. However, the investigation has also confirmed that a percentage of employee data, along with a subset of customer and partner records, was accessed and exfiltrated during the Craneware data breach. The organization is continuing to examine the precise nature and extent of the compromised data. It is also working with advisers to identify affected individuals and organizations, prepare notifications where necessary, and meet all applicable regulatory obligations. Craneware added that it will provide further updates to the market as additional information becomes available. As part of its response to the data breach at Craneware, the company has notified relevant regulators and law enforcement agencies. These include the UK's Information Commissioner's Office (ICO) and the US Federal Bureau of Investigation (FBI).

Craneware to Notify Affected Parties as Assessment Continues

In its official announcement, Craneware said: "The incident has been contained, and there has been no disruption to customer services or to the Company's operations. The external specialists have confirmed that there are no residual indicators of compromise arising from the cybersecurity incident in the Company's systems." The company further stated: "Investigations so far have established that a significant volume of file names were viewed and exfiltrated. The current assessment is that a large element of the data involved is non-sensitive or already public regulatory data. A percentage of Craneware employee data as well as a subset of customer and partner records, have been accessed and exfiltrated." The notice also stated: "This announcement contains inside information as stipulated under the UK version of the Market Abuse Regulation No 596/2014, which is part of English Law by virtue of the European (Withdrawal) Act 2018, as amended. On publication of this announcement via a Regulatory Information Service, this information is considered to be in the public domain." While the investigation into the cyberattack on Craneware remains ongoing, the company said it will continue assessing the impact of the cyberattack and issue further updates as appropriate.

Vibe Coding erklärt

Mon, 20 Jul 2026 07:54:16 +0200

Vibe Coding verspricht viele KI-getriebene Vorteile, macht Softwareentwickler jedoch nicht überflüssig – eher im Gegenteil.

Fit Ztudio | shutterstock.com

Im Dev-Umfeld verschwimmt die Grenze zwischen Programmieren und Prompten schon seit einigen Jahren. Auf die Spitze getrieben wird diese Entwicklung vom Vibe-Coding-Trend: Frühe KI-Entwickler-Tools wie GitHub Copilot waren vornehmlich darauf ausgelegt, Devs zu unterstützen. Etwa, indem sie Funktionen und Syntax ergänzten oder Boilerplate-Code aus Kommentaren generierten. Kommt ein Vibe-Coding-Ansatz zum Zug, beginnen menschliche Entwickler hingegen gar nicht erst damit, Code zu schreiben.

Dieses Konzept führt nicht nur zu veränderten Workflows, sondern erfordert auch, ein neues Mindset. Schließlich wird die Programmierarbeit mit Vibe Coding eher zu einer Art Live-Prototyping. In diesem Artikel lesen Sie:

warum Vibe Coding Vibe Coding heißt,
inwieweit sich dieser Ansatz für Unternehmen eignet,
wie Vibe-Coding-Workflows konkret aussehen (können),
welche Tools in diesem Bereich zu empfehlen sind,
welche Risiken Sie dabei auf dem Schirm haben sollten, sowie
Tipps dazu, wie Sie Vibe Coding effektiv in der Praxis umsetzen.

Vibe Coding – Begriffsdefinition

Der Begriff Vibe Coding wurde Anfang 2025 vom OpenAI-Mitbegründer Andrej Karpathy geprägt. Der KI-Experte trat den Trend mit einem Post auf dem Kurznachrichtendienst X los.

There's a new kind of coding I call "vibe coding", where you fully give in to the vibes, embrace exponentials, and forget that the code even exists. It's possible because the LLMs (e.g. Cursor Composer w Sonnet) are getting too good. Also I just talk to Composer with SuperWhisper…
— Andrej Karpathy (@karpathy) February 2, 2025

In diesem beschreibt Karpathy die Vibe-Coding-Methodik als eine neue Coding-Form, bei der man sich ganz den “Vibes” hingibt und vergisst, dass der Code überhaupt existiert. Amy Mortlock, Vice President of Marketing beim OSINT-Spezialisten ShadowDragon, erklärt das Konzept etwas weniger kryptisch: “Beim Vibe Coding beschreibt man in natürlicher Sprache, was man möchte, und die KI generiert dann die gesamte Anwendung und kümmert sich um alle technischen Details.”

Vibe Coding setzt also darauf, die traditionelle Programmierarbeit durch dialogorientierte Anweisungen und Kooperation mit einem KI-Assistenten zu ersetzen. Statt detaillierte Spezifikationen zu entwerfen und diese an die Engineers weiterzugeben, können Produktmanager, Fachexperten – oder jeder andere, der eine Idee hat – in einfacher Sprache beschreiben, wie das Ergebnis aussehen soll. Die KI-Software erledigt dem Rest in Echtzeit. Allerdings geht es dabei weniger darum, die Softwareentwicklung durchgängig zu automatisieren.

Vielmehr stehen Mindset-Veränderungen im Fokus: Warum sollte man nicht der KI die Mechanik überlassen und sich stattdessen auf die Ausrichtung, das Feedback, den Flow und die “Vibes” konzentrieren? Schließlich werden die Modelle, die Tools wie Cursor oder GitHub Copilot zugrunde liegen, immer performanter. Deswegen sehen auch viele Developer ihre Arbeit inzwischen vorwiegend als einen Dialog mit der KI – statt sich zeilenweise selbst durch Syntax zu wühlen.

Und obwohl auch bei einem Vibe-Coding-Ansatz diverse Probleme und Herausforderungen auf den Plan treten können (dazu später mehr): Die Technik gewinnt zunehmend an Popularität – auch im Unternehmensumfeld.

Vibe Coding im Unternehmen

Wie das in der Praxis konkret aussieht, beschreibt Charles Ma, Softwareentwickler beim Observability-Spezialisten Chronosphere: “Viele unserer Entwickler nutzen Tools wie Cursor und Claude Code. Wir fördern deren Einsatz sogar über ein Nutzungs-Leaderboard. Dabei betrachten wir die Tools jedoch als Assistenten, nicht als Dev-Ersatz. Unser Code-Review-Prozess ist weiterhin Pflicht für jeden Produktionscode – und wir sehen eher davon ab, viele unserer oder gar externe Tools mit KI zu verbinden.”

In der Perspektive von Achint Agarwal, Vice President of Product beim KI-Anbieter Pramata, hat Vibe Coding vor allem die Art und Weise verändert, wie Teams vom Konzept zum Prototyp gelangen: “Früher mussten UI/UX-Designer und Entwickler zusammenarbeiten, um eine Idee in etwas zu verwandeln, mit dem Kunden interagieren konnten. Dieser Prozess konnte leicht mehrere Wochen dauern und diverse Überarbeitungsrunden umfassen.”

Heute, so Agarwal, könne ein Produktmanager oder Fachexperte einfach in natürlicher Sprache formulieren, was er sich vorstellt, und die KI generiere funktionierenden Code in Prototyp-Qualität. “Bei dieser Veränderung geht es um mehr als nur Geschwindigkeit: Auch die Qualität der Ergebnisse ist besser, weil die Person, die den Anforderungen am nächsten steht, während des gesamten Prozesses die Kontrolle behält und es keine Reibungsverluste durch Übergaben gibt”, fügt der Manager hinzu.

Auch Agarwal sieht in Vibe Coding kein Substitut für die traditionelle Softwareentwicklung, sondern vor allem ein Explorations- und Validierungs-Tool: “Dev-Teams ist es damit möglich, in kurzer Zeit funktionierende Prototypen zu erstellen, diese mit Kunden zu testen und zu überprüfen, ob die Idee sinnvoll ist. Fällt diese Prüfung positiv aus, kann der Prototyp an die Engineers gehen, die ihn mit Blick auf Skalierbarkeit, Sicherheit und langfristige Integrationen weiter ausbauen.”

Wie sieht ein Vibe-Coding-Workflow aus?

Es gibt keine allgemeingültige Blaupause für Vibe Coding. Entsprechend gehen auch die Ansichten darüber auseinander, wie ein typischer Vibe-Coding-Workflow aussieht. Kostas Pardalis, Data Infrastructure Engineer beim KI-Lösungsanbieter Typedef, beschreibt diesen als agilen, vierstufigen Prozess:

die Erkundungsphase, in der der “Vibe”, der Zweck und die Einschränkungen definiert werden.
die Gestaltungsphase, in der ein funktionierender Prototyp erstellt und verfeinert wird.
die Grounding-Phase, die genutzt wird, um Struktur und Datenintegrität hinzuzufügen.
die Operationalisierungsphase, in der Versionierung, Evaluierung und Governance hinzukommen.

Steve Croce, Field CTO beim Open-Source-Unternehmen Anaconda, steht hingegen auf dem Standpunkt, dass der Vibe-Coding-Workflow davon abhängig ist, ob ein Prototyp, eine Zwischenlösung oder eine vollständige Produktionsapplikation entwickelt werden soll. Basierend darauf, orientiert sich der Vibe-Coding-Workflow in der Vision des Technologieentscheiders eher am traditionellen Software Development Lifecycle – fußt jedoch ebenfalls auf vier Stufen:

In der Phase der Planungs- und Anforderungsanalyse könnten Produktmanager und UX-Teams demnach voll und ganz auf Vibe Coding setzen und so vor der formellen Entwicklung klickbare Prototypen und Machbarkeitstests erstellen.
Im Rahmen der Design-Phase kann KI laut Croce dabei unterstützen, Architekturen und Dokumentationen zu erstellen. Der Manager weist allerdings darauf hin, dass es in dieser Phase auch hilfreich sein könne, erfahrene Engineers oder Architekten hinzuziehen, um die Einhaltung von Standards und die Reusability interner Systeme zu gewährleisten.
Als Kernbereich der Vibe-Coding-Experience sieht Croce die Implementierungs- und Testphase: Ein KI-Agent könne an dieser Stelle die gesamte Anwendung erstellen und darüber hinaus auch Repositories strukturieren und Tests durchführen. Der Experte rät Unternehmens-Teams jedoch mit Blick auf die Testabdeckung und Konformitätsprüfungen auch in dieser Phase dazu, menschliche Profis hinzuzuziehen.
In der Bereitstellungs- und Wartungsphase könne KI laut dem CTO dazu genutzt werden, Apps bereitzustellen und zu warten. Dieser Part könne jedoch auch vollständig außerhalb der Vibe-Coding-Erfahrung abgewickelt werden, um den Unternehmensanforderungen zu entsprechen, so Croce.

Empfehlenswerte Vibe-Coding-Tools

Vibe-Coding-Tools decken ein breites Spektrum ab: Vom leicht zugänglichen, dialogorientierten Builder für nicht-technische Teams, bis hin zu integrierten Entwicklungsumgebungen (IDEs), die Engineers umfassende Kontrollmöglichkeiten bieten und zuverlässige Anwendungen gewährleisten. Die Wahl des richtigen Tools hängt von den Fähigkeiten des Teams, dem Projektziel und dem benötigten Maß an Governance ab.

Eine kleine Auswahl empfehlenswerter Tools für Vibe-Coding-Zwecke:

Cursor ist eine KI-integrierte IDE, mit der sich mehrere Dateien bearbeiten lassen.
Replit ist eine gute Wahl für Browser-basierte Entwicklungsarbeit.
Bolt und Lovable sind Builder, eignen sich vor allem für schnelles Brainstorming und zeichnen sich durch überschaubaren technischen Aufwand aus. Diese Tools sind daher auch für Einsteiger geeignet.
Windsurf und Zed sind vollständige IDEs, die darauf ausgelegt sind, Vibe-Coding-Funktionen in traditionelle Dev-Umgebungen zu integrieren.

Diese Risiken birgt Vibe Coding

Trotz der genannten Vorteile birgt der Vibe-Coding-Ansatz auch diverse Risiken mit Blick auf die Wartbarkeit und Anfälligkeit der generierten Logik. So warnt etwa ShadowDragon-Managerin Mortlock: “Sicherheitslücken und technische Schulden sind die Hauptprobleme in Zusammenhang mit Vibe Coding. KI kann manchmal unsichere Pattern oder auch veraltete Bibliotheken einbinden.”

Zudem sei KI-generierter Code in den meisten Fällen auch länger, was das Debugging langwierig und mühsam gestalten könne, erklärt Mortlock. Sie fügt hinzu: “KI verweist unter Umständen auch auf nicht existierende Packages, was auch böswillige Akteure ausnutzen könnten. Was wie funktionierender Code aussieht, kann versteckte Fallen bergen.”

Charles Ma, Software Engineer beim Observability-Spezialisten Chronosphere, sieht ein weiteres Problem, das die Angriffsfläche potenziell vergrößert: “Selbst erfahrene Engineers können selbstzufrieden werden und dann Probleme übersehen, die ihnen sonst nicht entgangen wären. Sobald KI-Tools mit externen Systemen verbunden sind oder Websuchen durchführen, besteht außerdem das Risiko von Prompt Injections und Toolchain-Exploits.”

Infrastruktur-Profi Pardalis fokussiert mit Blick auf die Risiken von Vibe Coding vor allem die Bereiche Volatilität und Sichtbarkeit: Weil dieser Ansatz für schnelle Iterationen und Modellautonomie förderlich sei, bestünden die Hauptrisiken in unkontrollierter Variabilität und undurchsichtigen Quellen. Um diese Probleme zu bekämpfen, appelliert Pardalis für:

Lineage Tracking: Jede Version wird committet und verwendet Frameworks mit integrierter Traceability.
Evaluierungsschleifen: Qualitäts- und Regressionsprüfungen werden automatisiert durchgeführt.
Governance-Layer: Prompt-Historien werden auditiert und sensible Daten gefiltert.

Der Engineering-Profi ist der Ansicht, dass eine expressive, modellgesteuerte Softwareentwicklung und eine deterministische Infrastruktur unter disziplinierten Rahmenbedingungen koexistieren können: “Letztendlich verspricht Vibe Coding kein Chaos, sondern strukturierte Kreativität. Sie entwickeln Ideen schnell, setzen sie aber sicher um. Mit anderen Worten: Freiheit am Anfang, Disziplin im weiteren Verlauf – so kann Vibe Coding tatsächlich in Produktionsumgebungen skaliert werden.”

6 Tipps für effektives Vibe Coding

Da Sie nun umfassend über alle Aspekte des Vibe-Coding-Ansatzes informiert sind, geben wir Ihnen abschließend noch ein paar Tipps an die Hand, um Ihre eigene Initiative erfolgreich umzusetzen. Diese haben wir aus unseren Gesprächen mit den im Artikel zitierten Spezialisten zum Thema extrahiert

Beginnen Sie mit Zielen, nicht mit Funktionen: Beschreiben Sie zunächst die gewünschte User Experience und die wesentlichen Geschäftsprobleme, die mit der Initiative gelöst werden sollen. Dabei müssen Sie es nicht übertreiben und jeden Button oder Screen definieren – für relevante Lösungen ist es entscheidend, der KI so genau wie möglich zu beschreiben, was erreicht werden soll.
Planen Sie voraus: Vibe Coding ist nicht in der Lage, eine gute Architektur zu ersetzen. Bevor Sie KI hinzuziehen, sollten Sie deshalb sicherstellen, dass Design und Spezifikationen stimmen. Das erleichtert es der KI, “Intent” in kohärente Systeme zu übersetzen.
Verstehen Sie KI als Partner: Es gilt, mit Vibe-Coding-Tools zu kollaborieren. Diese Werkzeuge brauchen Anleitung und ihre Ergebnisse müssen überprüft werden. Blindes Vertrauen kann an dieser Stelle kontraproduktiv sein. Sie sollten deshalb nicht zögern, die KI-generierte Logik in Frage zu stellen.
Nutzen Sie Frameworks, Kontext und Beispiele: Etablierte Frameworks zu nutzen, erspart es Ihnen alles von Grund auf neu zu entwickeln. Die KI mit Beispielanwendungen zu füttern oder (vertrauenswürdige) MCP-Server hinzuzuziehen, um Kontext in größeren Projekten zu managen, kann ihre Fähigkeiten erweitern.
Halten Sie Menschen – und Security – im Loop: Setzen Sie auch bei Vibe- respektive KI-Coding-Tools auf das Least-Privilege-Prinzip – und Review-Prozesse. Engineering Best Practices anzuwenden, empfiehlt sich ebenfalls: Generieren Sie Tests, verifizieren Sie Funktionalitäten. Und betrachten Sie die Tools als Kreativitäts- und Produktivitäts-Support. Nicht als Substitut für Skills und Knowhow.
Iterieren und verfeinern Sie: Nehmen Sie mit Blick auf Vibe Coding Abstand vom Streben nach Perfektion (auch wenn es Ihnen widerstrebt) und finden Sie sich möglichst frühzeitig mit unvollkommenen Ergebnissen ab. Tracken Sie Prompts, cachen Sie Checkpoints und verfeinern Sie die Ergebnisse – solange, bis der “Flow” zu einer zuverlässigen Funktionalität wird.

(fm)

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

UK’s Largest Cybercrime Case Ends in Prison for Spider Hacker

Mon, 20 Jul 2026 02:13:59 +0200

Scattered Spider Hackers Sentenced over Mass-Affecting Transit Attack Two well-known members of the notorious hacking group Scattered Spider were sentenced to prison in the UK on July 16, 2026. Owen...

The post UK’s Largest Cybercrime Case Ends in Prison for Spider Hacker appeared first on Cyber Defense Magazine.

James Webb Space Telescope Discovers How Black Holes Feed Themselves

Sun, 19 Jul 2026 21:23:13 +0200

"Thanks to the James Webb Space Telescope, astronomers have been given a glimpse of the mechanisms that supermassive black holes use to feed themselves," reports Space.com: The powerful cosmic titans get really puzzling when astronomers using the JWST spot them before the universe was even 1 billion years old. That's because the mechanisms by which black holes devour matter to grow and then merge to create even more massive black holes should take at least 1 billion years to achieve supermassive status. This is even more confusing because theories also say the most ravenously feeding black holes (and thus the fastest growing) should also push the matter they use for this growth away, in effect putting themselves on a diet. So, with all this in mind, how did supermassive black holes grow so rapidly in the early universe? One explanation suggests supermassive black holes push away gas, starving themselves as predicted, but also that this matter eventually cools and falls back to the black hole. That would allow for another period of feeding and thus growth. This explanation further suggests that as this gas cools down, it forms "streamers," or filaments, of gas just a few hundred light-years wide but which stretch thousands of light-years long. These would fall back to the center of the galaxy and form a swirling disk around its incumbent black hole, once again feeding it and triggering a new period of growth. This would then restart the jets from the black hole, which would again cut off the cosmic titan's food supply, allowing the whole process to begin once more. The process would in essence be a self-regulating cycle of feasting followed by fasting. However, the connection between these filaments and supermassive black holes has been elusive, meaning this mechanism has resisted confirmation. To solve the mystery of feasting black holes, the JWST turned its attention to a relatively close AGN situated at the heart of the central galaxy of the Centaurus Cluster, NGC 4696, located just 145 million light-years from Earth. The Hubble Space Telescope previously studied this galaxy, uncovering a strange, hook-shaped swirl of gas near the central supermassive black hole of NGC 4696. The JWST followed up this discovery by producing a detailed map of gas flowing at the heart of the galaxy. This revealed the hook-shaped feature is around 800 light-years wide and is composed of gas moving at incredible speeds of around 1.3 million miles per hour (600 kilometers per second). More excitingly, the swirl of gas appears to be connected to a vast filament of material falling in toward the central supermassive black hole. The team tested the JWST observations against a computer simulation, finding gas in the infalling filament scenario would indeed take a shape similar to that seen in NGC 4696. "JWST is now showing us the final link of this closed loop," team member Helen Russell of the School of Physics and Astronomy at the University of Nottingham in the U.K. said in the statement. "The vast filamentary network of gas flows ultimately funnels gas down to a disk that fuels the black hole." The team's research was published on Wednesday (July 16) in the Astrophysical Journal Letters. "We are finally seeing this self-sustaining cycle in action," team leader Julie Hlavacek-Larrondo of the Université de Montréal said in a statement.

Read more of this story at Slashdot.

Life on a Pale Red Dot (emf2026)

Sun, 19 Jul 2026 20:18:10 +0200

What could other worlds look like? Exoplanetology — the study of planets orbiting stars other than our sun — is rapidly progressing, and researchers are discovering increasing numbers of planets. Little is known about these distant worlds — perhaps their mass, or their radius, but conditions on the surface are still left somewhat to our imagination. The nearest star to the Earth after the Sun is Proxima Centauri, a mere four light years away, and we now know it too hosts a planet. Much smaller and redder than our Sun, Proxima emits most of its light in the infrared part of the electromagnetic spectrum, rather than the visible range. Life on Earth has evolved to make the most of the Sun’s energy — but how would life have evolved on a planet with a very different kind of light available? Our project explores this idea using Kodak Aerochrome, a false-colour infrared film. Sensitive to light extending into the infrared regime, where foliage reflects strongly, it produces images that mimic the red hued plant life that we might find on other planets. Through this series of photographs we explore the story of an astronaut visiting one of these distant worlds. See the exhibition of photographs in the Robot Arms and on Sunday from 1pm in the Arts tent. Licensed to the public under https://creativecommons.org/licenses/by-sa/4.0/ about this event: https://www.emfcamp.org/schedule/2026/435-life-on-a-pale-red-dot

Life on a Pale Red Dot (emf2026)

Sun, 19 Jul 2026 19:08:44 +0200

Apple probably won't add Jony Ive to OpenAI trade secret theft suit

Sun, 19 Jul 2026 17:08:02 +0200

Four years ago, Jony Ive left Apple, and joined OpenAI, yet he isn't named in the intellectual property theft suit. The reasons for that are myriad, ranging from the personal to practical.

Jony Ive & OpenAI's Sam Altman | Image Credit: OpenAI

On July 10, Apple launched what looks to become a major lawsuit against OpenAI, accusing ex-Apple employees of stealing intellectual property. However, despite former Apple design chief's links to OpenAI, he isn't in the crosshairs of Apple's lawyers.

In Sunday's "Power On" newsletter for Bloomberg, Mark Gurman writes about the lawsuit and the oddity. He believes there are two big reasons for Apple not to implicate Ive in the lawsuit at all.

Continue Reading on AppleInsider | Discuss on our Forums

Government use of automated AI decision-making to be curbed under new Australian rules

Sun, 19 Jul 2026 14:03:38 +0200

New national plan accompanied by Labor push for digital duty of care legislation

Get our breaking news email, free app or daily news podcast

The use of AI in automated decision-making by government departments and agencies will be subject to tough rules under a new national plan, expected to extend to consumer protections, workplace safety and privacy.

As the Albanese government grapples with the rapid growth in the use of artificial intelligence and a boom in datacentre construction, senior ministers have begun work to draw up new rules to ensure safety is built into AI processes inside government, prioritising fairness, accuracy and transparency.

Some Xbox studio leads reportedly "detest" Game Pass — so why did Xbox push ahead with it? "It felt like a race to zero."

Sun, 19 Jul 2026 13:41:03 +0200

In a new podcast, Bloomberg's Jason Schreier shared thoughts from Xbox Game Studios leaders, who reportedly "detest" Game Pass and its impact on perception of value.

Europe's push for space sovereignty.

Sun, 19 Jul 2026 07:20:48 +0200

As space becomes an increasingly critical part of modern infrastructure, governments are reevaluating decades of policy to ensure reliable, secure, and independent access to the systems they are increasingly relying on. In this week’s episode, host Maria Varmazis sits down with producer Ethan Cook⁠⁠⁠ to explore Europe's evolving space strategy and how it is increasingly prioritizing space sovereignty. During the conversation, they examine the EU's proposed Space Act and how it aims to improve the region's space security, sustainability, and reliability for years to come.

CVE-2026-44800 | Microsoft Windows up to Server 2025 Push Notifications race condition

Sun, 19 Jul 2026 04:09:02 +0200

A vulnerability was found in Microsoft Windows 11 23H2/11 24H2/11 25H2/11 26H1/Server 2025. It has been rated as problematic. This affects an unknown function of the component Push Notifications. Performing a manipulation results in race condition. This vulnerability is identified as CVE-2026-44800. The attack is only possible with local access. There is not any exploit available.

Building a tiny paging network (emf2026)

Sat, 18 Jul 2026 19:22:53 +0200

Beep! A Brief History of UK Paging — and How to Build Your Own Transmitter Before smartphones, before SMS, before push notifications — there was the pager. For three decades, paging networks formed the invisible backbone of British communications, keeping doctors on call, field engineers reachable, and a generation of teenagers mysteriously popular. This talk traces the arc of paging in the UK, from the launch of the first commercial paging service by British Telecom in the 1950s through to the golden era of consumer paging in the 1980s and 90s. We'll look at the major networks — PageOne, Vodafone & BT — and the protocols that underpinned them: POCSAG, the workhorse standard developed at the Post Office Research Centre, and FLEX, Motorola's higher-speed successor. We'll touch on why paging quietly outlasted the first wave of mobile phones in critical sectors, and why a small but dedicated community still relies on them today. Then we get hands-on. Using an ESP32 and an SX1262 LoRa module — total cost under £15 — I'll demonstrate a working POCSAG transmitter built entirely with open-source tools like RadioLib. We'll send a real message, to a 30 year old pager and show how it can be useful today. Licensed to the public under https://creativecommons.org/licenses/by-sa/4.0/ about this event: https://www.emfcamp.org/schedule/2026/47-building-a-tiny-paging-network

Building a tiny paging network (emf2026)

Sat, 18 Jul 2026 18:48:40 +0200

How I Abused a Group Policy Object (GPO) in Active Directory (And How to Fix It)

Sat, 18 Jul 2026 11:39:16 +0200

Group Policy Objects (GPOs) are one of the most powerful features in Active Directory. They allow administrators to manage settings across computers and users.

But if the wrong user has control over a GPO, it can become an easy privilege escalation path.

In this lab, I’ll use BloodHound to identify a dangerous GPO permission and then show how to fix it.

Lab Setup

Domain: LAB.LOCAL
Domain Controller: 192.168.56.104
Attacker: Kali Linux
User: bob

Step 1 — Collect Active Directory Data

First, I collected information from Active Directory using BloodHound.py.

bloodhound-python -u bob -p 'password@123' -d lab.local -ns 192.168.56.104 -c All --zip

BloodHound successfully collected:

8 Users
55 Groups
3 GPOs
2 OUs
1 Computer

Step 2 — Import into BloodHound

Next, I uploaded the generated ZIP file into BloodHound Community Edition.

BloodHound maps relationships between users, groups, computers, OUs, and GPOs, making it much easier to spot privilege escalation paths.

Step 3 — Finding the Misconfiguration

BloodHound showed that Bob had WriteDacl, WriteOwner, and GenericWrite permissions over the Employees Policy GPO.

These permissions are dangerous because they allow a user to modify who controls the GPO or change its configuration.

Why Is This Dangerous?

If an attacker can edit a GPO linked to an Organizational Unit (OU), they may be able to:

Execute scripts on domain computers
Deploy scheduled tasks
Add users to local Administrators
Push malicious registry changes
Gain higher privileges across the domain

A single misconfigured GPO can impact many systems at once.

Step 4 — Fixing the Issue

On the Domain Controller:

Group Policy Management
        ↓
Employees Policy
        ↓
Delegation

Review who has permissions on the GPO.

Remove unnecessary permissions such as:

GenericWrite
misconfiguredWriteDacl
WriteOwner

Only trusted administrators should have these rights.

Verify the Fix

Run BloodHound again after updating the permissions.

bloodhound-python -u bob -p 'password@123' -d lab.local -ns 192.168.56.104 -c All --zip

Re-import the ZIP into BloodHound.

The dangerous permission edges should no longer appear for Bob.

Key Takeaways

1.Regularly audit GPO permissions.

2. Use the principle of least privilege.

3. Review BloodHound findings periodically.

4. Remove unnecessary GenericWrite, WriteDacl, and WriteOwner permissions.

Disclaimer: The techniques demonstrated in this article were performed in a private Active Directory lab for learning purposes. Always obtain proper authorization before testing any production environment.

— Written by

Aruvasaga Chithan A

Ethical Hacker & Cyber Security Researcher.

Thanks for reading — your support keeps me writing.
See you in the next article…

Linkedin.

How I Abused a Group Policy Object (GPO) in Active Directory (And How to Fix It) was originally published in InfoSec Write-ups on Medium, where people are continuing the conversation by highlighting and responding to this story.

From SQL Injection to Infrastructure-Level RCE: A PostgreSQL Superuser Compromise

Sat, 18 Jul 2026 11:39:13 +0200

Imagine finding a backdoor that gives you absolute superuser access to a state infrastructure network, documenting the exploit chain perfectly, and submitting it—only to be met with total bureaucratic silence.

While auditing a financial management web portal (vsswb), I discovered a single unparameterized parameter that ultimately resulted in unauthenticated Remote Code Execution (RCE). This is the technical walkthrough of the exploit chain.

1. The Entry Point

The vulnerable endpoint was responsible for processing the pJobNumber parameter.

vss00CvStatusData.php

Appending a single quote (') immediately triggered a raw PostgreSQL error:

pg_query(): Query failed: ERROR: unterminated quoted string at or near "## order by wcs.fdate ;"

Observation

User-controlled input was being directly concatenated into a SQL statement without parameterization.

2. Fingerprinting the Database

Using UNION SELECT with NULL placeholders to align the three-column query structure, I extracted the PostgreSQL version and execution context.

curl -k -s "https://[TARGET_URL]/vsswb/vss00CvStatusData.php?pAction=LoadTypeCombo&pJobNumber=nonexistent'+UNION+SELECT+NULL,version(),current_user--&pSelection=1"

Response:

[
  {
    "wbid": null,
    "job": "PostgreSQL 13.1, compiled by Visual C++ build 1914, 64-bit",
    "wodetails": "postgres"
  }
]

Finding

The web application connected directly as the native PostgreSQL postgres account.

This is the database superuser, effectively eliminating privilege boundaries.

3. Mass Data Exposure

With superuser privileges, PostgreSQL system catalogs became fully accessible.

Enumeration quickly revealed employee records stored in:

public.vss01tpemployee

The table contained personally identifiable information (PII), including employee names, PAN numbers, and financial records.

From SQL Injection to Infrastructure-Level RCE: A PostgreSQL Superuser Compromise was originally published in InfoSec Write-ups on Medium, where people are continuing the conversation by highlighting and responding to this story.

Device Code Phishing: How Attackers Abuse Microsoft’s Legitimate Authentication Page Without…

Sat, 18 Jul 2026 11:39:11 +0200

Device Code Phishing: How Attackers Abuse Microsoft’s Legitimate Authentication Page Without Stealing Your Password

The most convincing Microsoft phishing attack yet. Learn how attackers abuse Microsoft’s trusted device authentication process, obtain access tokens instead of passwords, and why traditional MFA awareness alone is no longer enough.

Have You Ever Come Across a Website Like This Below Screenshot? No fake Microsoft login pages. No stealing of passwords. No cloned authentication forms. No obvious browser warnings. Yes that’s device code phishing

At first glance, this page looks completely legitimate.

It carries Microsoft’s branding, displays a verification code, and instructs users to continue their sign-in using the official Microsoft Device Login page. Unlike traditional phishing websites, there are no fake Microsoft login forms, no requests for your password, and no obvious signs that something is wrong.

So, it must be safe… right?

Not necessarily.

Device Code Phishing has become one of the most effective phishing techniques because it abuses Microsoft’s legitimate authentication workflow instead of attempting to steal usernames and passwords. Since users authenticate directly with Microsoft, many of the traditional warning signs associated with phishing are absent, making these attacks significantly more convincing.

In this article, the ThreatWatch360 team explains how Device Code Phishing works, why it is dangerous, and how attackers leverage this technique to gain unauthorized access to Microsoft 365 accounts without ever asking victims for their credentials.

What is Device Code Authentication?

Before understanding Device Code Phishing, it’s important to understand Device Code Authentication.

Microsoft introduced the Device Code Flow to allow devices with limited input capabilities, such as smart TVs, conference room devices, IoT devices, and command-line applications, to authenticate users.

Instead of entering credentials directly on the device, Microsoft generates a short verification code.

The user then visits Microsoft’s official Device Login page, enters the code, signs in with their Microsoft account, and authorizes the request.

The authenticated session is then linked back to the requesting application.

This workflow is completely legitimate and is widely used by Microsoft-supported applications.

Unfortunately, threat actors discovered they could abuse this authentication flow for phishing.

How Device Code Phishing Works

Unlike traditional phishing attacks, Device Code Phishing does not steal passwords.

Instead, it tricks victims into authorizing an attacker-controlled application using Microsoft’s own authentication infrastructure.

The result is that the attacker receives a valid Microsoft access token after the victim successfully authenticates.

Stage 1 — The Phishing Email

Initial Phishing Email

The attack usually begins with a convincing phishing email.

In our demonstration, the victim receives an email claiming that Microsoft detected unusual sign-in activity and encourages them to secure their account immediately.

The email closely resembles legitimate Microsoft security notifications, making it difficult for many users to distinguish between genuine and malicious messages.

Instead of directing users to a fake Microsoft login page, the email redirects them to an attacker-controlled website.

This subtle difference is what makes Device Code Phishing particularly dangerous.

Stage 2 — The Fake Verification Portal

Device Code Phishing Page

After clicking the email link, the victim is presented with what appears to be a Microsoft verification portal.

The page displays:

A Microsoft verification code
Instructions explaining how to complete authentication
A button that automatically opens Microsoft’s legitimate Device Login page

Everything appears authentic.

Unlike credential phishing pages, this website never asks the user for their Microsoft username or password.

Instead, it simply instructs the user to authenticate through Microsoft itself.

This dramatically increases trust.

Stage 3 — Redirecting to Microsoft’s Official Login Page

Official Microsoft Device Login

Clicking the verification button redirects the victim to Microsoft’s official Device Login page.

Notice the URL.

The browser clearly displays Microsoft’s legitimate domain: login.microsoftonline.com

This is not a fake login page.

This is Microsoft’s real authentication portal.

Since users are interacting directly with Microsoft, many security-conscious individuals believe the request is legitimate.

Stage 4 — Entering the Device Code

Microsoft Device Authentication

The victim enters the code displayed on the phishing website into Microsoft’s official authentication page.

At this point, everything still appears normal.

The authentication process is entirely handled by Microsoft.

No passwords have been stolen.

No fake login page has been displayed.

Yet the attacker is already one step closer to gaining access.

Stage 5 — Microsoft Requests Account Authorization

Account Selection

Once the code is accepted, Microsoft asks the victim to select the account they wish to authorize.

Again, this occurs entirely on Microsoft’s legitimate infrastructure.

Nothing appears suspicious.

Most users assume they are completing a routine Microsoft verification process.

Stage 6 — Granting Access

Authorization Prompt

Microsoft now asks the user to confirm the authentication request.

The victim clicks Continue, believing they are protecting or verifying their Microsoft account.

Instead, they are unknowingly authorizing an attacker-controlled application.

Stage 7 — Authentication Complete

Successful Authorization

Microsoft confirms that authentication has completed successfully.

From the victim’s perspective, everything appears perfectly normal.

There are no error messages.

No warnings.

No indication that their Microsoft session has now been shared with someone else.

Stage 8 — The Attacker Receives the Access Token

Attacker Token Captured dashboard

Behind the scenes, the attacker’s phishing infrastructure immediately receives the Microsoft access token generated during the authentication process.

Unlike traditional phishing attacks, the attacker never needed the victim’s password.

Instead, they now possess a valid Microsoft authentication token issued directly by Microsoft.

Stage 9 — Accessing Microsoft Resources

Searching Microsoft Graph Data

Using the captured token, the attacker can begin interacting with Microsoft Graph APIs according to the permissions granted during authentication.

Depending on the permissions available, this may allow access to resources such as:

Outlook email
OneDrive files
SharePoint data
Microsoft Teams information
Other Microsoft 365 resources

In our demonstration, the captured token is used to search mailbox content, illustrating how quickly authenticated access can be abused after the victim completes the authorization process.

Why Device Code Phishing Is So Effective

Traditional phishing relies on fake login pages.

Device Code Phishing is different.

The victim authenticates directly with Microsoft.

Every important step occurs on Microsoft’s legitimate domain.

This removes many of the indicators users have been trained to recognize.

There are:

No fake Microsoft login pages.
No stealing of passwords.
No cloned authentication forms.
No obvious browser warnings.

Instead, attackers exploit the trust users place in Microsoft’s legitimate authentication process.

Why This Matters

Modern phishing campaigns are evolving beyond simple credential theft. By abusing legitimate authentication workflows, attackers can obtain valid access tokens without ever knowing a user’s password. This makes Device Code Phishing particularly attractive because it blends legitimate authentication with social engineering. Organizations relying solely on user awareness around fake login pages may find these attacks significantly more difficult to detect.

How to Protect Yourself

Although Device Code Authentication is a legitimate Microsoft feature, there are several ways users can protect themselves from Device Code Phishing attacks.

Never authenticate unless you initiated the request.

If you receive an unexpected email asking you to verify your Microsoft account using a device code, stop and verify the request before proceeding.

Check why you are being asked to authenticate.

Ask yourself:

Did I start this login?
Am I trying to sign in on another device?
Was I expecting this authentication request?

If the answer is no, do not continue.

Be cautious of urgent security emails.

Threat actors frequently use messages about unusual sign-in activity, account suspension, or urgent verification to pressure victims into acting quickly.

Review recently authorized applications.

Regularly review the applications connected to your Microsoft account and remove any unfamiliar or unnecessary authorizations.

Revoke active sessions if you suspect compromise.

If you believe you accidentally completed a Device Code Phishing request:

Immediately sign out of all active Microsoft sessions.
Revoke recently granted application permissions.
Change your Microsoft account password.
Inform your organization’s IT or Security team.
Review your recent sign-in activity for any suspicious access.

Acting quickly can significantly reduce the impact of token-based attacks.

Conclusion

Device Code Phishing demonstrates that modern phishing attacks no longer need to steal passwords to be successful.

By abusing Microsoft’s legitimate Device Code authentication workflow, attackers can trick users into authorizing malicious applications while every authentication step takes place on Microsoft’s official infrastructure.

This makes the attack highly convincing, difficult for users to recognize, and increasingly relevant in modern phishing campaigns.

Understanding how this technique works is the first step toward recognizing suspicious authentication requests and preventing unauthorized access to Microsoft 365 environments.

As attackers continue to shift toward token-based authentication abuse, user awareness remains one of the most effective defenses against these evolving phishing techniques.

Device Code Phishing: How Attackers Abuse Microsoft’s Legitimate Authentication Page Without… was originally published in InfoSec Write-ups on Medium, where people are continuing the conversation by highlighting and responding to this story.

Decoding the Obfuscated Layer: A Playbook Walkthrough of Command-Line Forensics

Sat, 18 Jul 2026 11:21:48 +0200

A full and detailed insight into CLI forensics, going into depth following a TryHackMe lab

Source: TechFusion

For incident responders, security analysts, and threat hunters, discovering an unknown script execution running on an enterprise workstation triggers an immediate race against time. Is it a harmless administrative automation tool, or is it an advanced information stealer scraping the credential caches of every corporate browser?

I recommend you first walk through this article and afterwards complete the TryHackMe lab Obfuscation: The Egg Shell File.

The core purpose of this tactical playbook is to provide you with a highly comprehensive, real-world analytical framework so you can confidently dive into the live lab environment (don’t, i say DON’T worry about committing every single execution flag or decoding syntax to memory; the structural muscle memory will lock in during the hands-on exercises).

Let’s cut the fluff and begin:

In modern security operations, the discipline of malware analysis bridges the gap between passive defense and active threat hunting. Using TryHackMe’s foundational lab featuring real-world PowerShell obfuscation strings, this walkthrough guides defenders through the surgical progression required to size up a hostile payload, calculate its technical attributes, map its internal compiled structure, and decrypt its runtime behavior safely.

📋 The Script Triage Checklist

Source: BitLyft

When you capture a suspicious script execution string from your SIEM (Security Information and Event Management) logs, proceed with these steps immediately:

Isolate and Copy Safely: Transfer the raw text string into a completely disconnected text editor inside a designated analysis virtual machine.
Identify the Execution Flags: Search for evasion switches like -NoP (No Profile), -W Hidden (Window Hidden), or -Enc (Encoded Command), which indicate deliberate bypass actions.
Locate Network Anchors: Scan the text string for markers like DownloadString, DownloadFile, curl, or iwr that hint at secondary external downloads.
Preserve Casing: Do not run lowercase or uppercase find-and-replace scripts across your sample yet; case variance is often structurally critical to decoding algorithms.

Deep Dive: Stripping the Camouflage

https://www.researchgate.net/figure/The-obfuscation-techniques-of-code-element-layer_fig2_340401812

Let’s look at an actual example of an obfuscated script layer captured directly from an initial access vector payload log.

What to look for in the image: Notice how the raw command string uses a combination of string splitting, character swapping, and nested script blocks. Threat actors do this to bypass static string matching (signatures) used by endpoint detection engines. By analyzing the structural markers, we can map out the exact unpacking routine.

Layer 1: Undoing String Concatenation

GPT Images 2.0 generated photo

Attackers frequently break apart their critical strings using addition operators or variable insertions to stop simple pattern scanners.

# Obfuscated string snippet
$a = "Down"; $b = "load"; $c = "String"
. ( $ExecutionContext.InvokeCommand.ExpandString('$' + 'a' + '$' + 'b' + '$' + 'c') )

The Fix: You don’t have to guess what this does. By loading the script into an isolated PowerShell CLI and replacing the aggressive execution operator (like . or Invoke-Expression / IEX) with a safe print directive like Write-Output, the environment itself will assemble the string for you:

# Safe evaluation technique
Write-Output ( $ExecutionContext.InvokeCommand.ExpandString('$' + 'a' + '$' + 'b' + '$' + 'c') )
# Output result: DownloadString

Layer 2: Demangling Character Shuffling

GPT Images 2.0 generated image

Another popular mechanism involves using format strings to re-order components out of sequence at runtime:

"{2}{0}{1}" -f 'Net.','WebClient','New-Object

The -f operator acts as an indexing map. To decrypt it manually:

Position {2} grabs the 3rd element: New-Object
Position {0} grabs the 1st element: Net.
Position {1} grabs the 2nd element: WebClient

When evaluated sequentially by the command pipeline, it structures clean and functional telemetry: New-Object Net.WebClient.

Layer 3: Defeating Base64 and XOR Rings

GPT Images 2.0 generated figure

The final boss of script obfuscation is almost always an encoded byte block. Base64 is easily recognizable by its standard alphanumeric character set and trailing padding markers (=).

To quickly unwrap these blocks without running the malicious code:

Copy the raw payload block inside the command string.
Load the payload directly into CyberChef (the open-source utility for security operations).
Chain together the From Base64 recipe followed by Decode Text (UTF-16LE).

Input:  aAB0AHQAcAA6AC8ALwBtAGEAbAB3AGEAcgBlAC4AbgBlAHQALwBwAGEAeQBsAG8AYQBkAC4AZQB4AGUA
Output: http://malware.net/payload.exe

By working backward through these layers, you quickly isolate the final Indicators of Compromise (IoCs) — such as the secondary payload download URL or target staging paths — allowing your security infrastructure to immediately blacklist the server across the enterprise.

🧠 Strategic Takeaway

(yayy)

The Obfuscation: The Egg Shell File analysis framework underscores a foundational truth of computer network defense: Malware cannot accomplish its mission without leaving a structural or behavioral footprint inside operational logs.

Whether it is a distinct jump in character selection counts, an unexpected system variable concatenation flag, or a sudden burst of hidden network invocation arguments executed entirely from background windows, an obfuscated script pipeline will always reveal its true payload target under systematic scrutiny.

By utilizing platforms like CyberChef to strip back multi-layered Base64 and XOR encoding architectures and verifying those outputs within isolated environments, defenders completely eliminate the guesswork from administrative code reviews.

Go log into the TryHackMe room, reverse the nested string layout structures of the script sample, map out the true operational strings, and transform your defensive triage into an optimized playbook.

📈 Master the Art of System Forensics & Threat Intelligence

The author

Generic security training completely collapses when sophisticated threat groups deploy obfuscated, packed, and tailored payloads across your endpoints.

To ensure you never miss an in-depth threat intelligence playbook pulling back the curtain on advanced binary analysis, active threat hunting, and modern defense frameworks:

Follow Pop123 on Medium for immediate notifications on all newly published technical deep-dives, infrastructure hardening playbooks, and reverse-engineering guides.
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Thank you for reading. This article was entirely written by Pop123. If you found this technical breakdown of the malware analysis matrix valuable, consider leaving a clap and sharing your thoughts, configuration questions, or analytical feedback in the responses below, I am as always open to further discussing the interesting topics!

For collaborations and inquiries: alexandrupp55@gmail.com

Decoding the Obfuscated Layer: A Playbook Walkthrough of Command-Line Forensics was originally published in InfoSec Write-ups on Medium, where people are continuing the conversation by highlighting and responding to this story.

EY Data Breach – Hackers Access Third-Party IT Support Platform and Steal Client Tax Documents

Sat, 18 Jul 2026 10:38:58 +0200

Ernst & Young LLP (EY) has confirmed a data security incident in which an unauthorized third party breached a third-party IT service management platform used by its tax practice, exfiltrating documents containing client personal and financial information. The Big Four firm filed formal breach notifications with the California Attorney General’s office on July 15, 2026, […]

The post EY Data Breach – Hackers Access Third-Party IT Support Platform and Steal Client Tax Documents appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.

Alien World Chemistry Found Inside Meteorite That Struck New Jersey Home

Sat, 18 Jul 2026 09:08:16 +0200

Researchers say a meteorite that crashed through the roof of a Hillsborough, New Jersey, home in 2024 contains unusually pristine evidence of salty fluids and organic chemistry from near the surface of a primitive asteroid. "A forensic study of the fragments revealed that they contained preserved bits from near the surface of a primitive asteroid, where it experienced concentrated salty fluids -- a process not previously known from this type of protoplanet world," said lead author and meteor astronomer Peter Jenniskens of the SETI Institute and NASA's Ames Research Center in California's Silicon Valley. Phys.org reports: According to paper co-author Mike Zolensky, a meteoriticist at NASA's Johnson Space Center in Houston, analysis of the Hillsborough meteorite found fragments that were more extensively altered by water on the meteorite's parent asteroid than is typically seen in CM2 carbonaceous chondrites. The analysis classified the specimen as a CM1/2 carbonaceous chondrite, an intermediate classification between petrographic types CM1 and CM2. [...] Zolensky and colleague JangMi Han found small salt-rich CM1 fragments within the Hillsborough meteorite, suggesting they originated from a near-surface region of the parent asteroid where liquid water evaporated and concentrated salts. They are now working to identify the salt minerals for comparison with similar phases found among samples returned to Earth from asteroids Ryugu and Bennu. The high concentration of salt in briny fluids can potentially create molecules crucial to life on Earth. Brines allow phosphate to remain in solution and can catalyze chemical reactions between organics and precipitate minerals. "Isotope studies of carbon and nitrogen suggest that primitive carbonaceous chondrites, including CM types, delivered organic matter to the early Earth," said cosmochemist Queenie Chan of Royal Holloway University of London, England, and biogeochemist Nana Ogawa of the Biogeochemistry Research Center at the Japan Agency for Marine-Earth Science and Technology. "The Hillsborough meteorite contained 1.8% by weight of carbon and 0.07% of nitrogen, and had carbon and nitrogen isotopes typical for CM-type meteorites." The meteorite contained a wide variety of soluble organic compounds, and its compositional range confirms that the Hillsborough meteorite was more altered by water than most other CM-type meteorites. "A high fraction of compounds were the product of organic chemistry with minerals," said organic mass spectrometry specialist Phil Schmitt-Kopplin of Technical University Munich. "We do not know if these magnesium organic compounds were contributed by brine chemistry or were simply left over from earlier impact shock processes." In living organisms, organometallic compounds are found in blood and used in photosynthesis. Among the soluble organic compounds were many amino acids, similar to those found in more moderately altered CM2 chondrites. Astrobiologist Danny Glavin of NASA's Goddard Space Flight Center in Greenbelt, Maryland, and his team in Goddard's Astrobiology Analytical Lab concluded that the delivery of amino acids, carboxylic acids and other soluble organic molecules by CM-type bodies may have contributed to the prebiotic organic inventory that preceded the emergence of life on Earth. Their analysis suggests the complex distribution of amino acids observed in the Hillsborough meteorite formed within the parent body, likely assisted by brine fluid chemistry. The findings have been published in the journal Science Advances.

Read more of this story at Slashdot.

Hackers Breach EY Third-Party IT Support Platform and Steal Client Tax Documents

Sat, 18 Jul 2026 08:23:46 +0200

Ernst & Young LLP, one of the world’s Big Four professional services firms, has disclosed a data breach in which an unauthorized third party infiltrated a vendor-managed IT service platform and exfiltrated documents containing client tax data. The firm filed formal breach notifications with the California Attorney General’s office on July 15, 2026, and with […]

The post Hackers Breach EY Third-Party IT Support Platform and Steal Client Tax Documents appeared first on Cyber Security News.

Microsoft schickt jetzt eine Mail an Windows-10-Nutzer: Das steht drin

Sat, 18 Jul 2026 08:02:17 +0200

Microsoft verschickt jetzt an Windows-10-Nutzer eine Mail, in der das Unternehmen darüber informiert, dass es den Support für Windows 10 um ein weiteres Jahr verlängert. Windows 10 gehört also nicht zu den zahlreichen Programmen, die Microsoft in diesem Jahr ausmustert. Das steht in der Mail, die zumindest in den USA an Windows-10-Nutzer geht:

Die Mail beginnt mit der Überschrift “Bleiben Sie ein weiteres Jahr sicher” (in englischer Sprache). Danach erklärt Microsoft, dass die Windows 10 Extended Security Updates (ESU) bis zum 12. Oktober 2027 verlängert werden. Und somit anders als ursprünglich geplant nicht bereits am 12. Oktober 2026 auslaufen. Voraussetzung ist natürlich, dass Sie sich für die Windows 10 Extended Security Updates (ESU) angemeldet haben.

Wie das US-amerikanische IT-Nachrichtenportal Windowslatest anmerkt, landet diese Mail in Outlook im “Sonstige”-Ordner und nicht im “Relevant”-Ordner. Es besteht also das Risiko, dass viele Outlook-Nutzer diese offizielle Microsoft-Mail übersehen.

Microsoft zeigt plötzlich Verständnis

Im Text der Mail erklärt Microsoft sein (plötzliches) Verständnis dafür, dass der Umzug zu einem neuen PC oder einem neuen Notebook Zeit braucht. In den vergangenen Jahren hatte es Microsoft an diesem Verständnis fehlen lassen. Immerhin sollte der Support für Windows 10 ja bereits im Oktober 2025 enden. Dann kam die erste Verlängerung bis Oktober 2026 und kürzlich die bis Oktober 2027. Vermutlich waren es die nach wie vor hohen Marktanteile von Windows 10, die Microsoft so verständnisvoll werden ließen.

Über einen “Mehr erfahren”-Button gelangt der interessierte Nutzer zu einer Webseite mit weiteren Informationen. Dabei handelt es sich um die offizielle Info-Seite von Microsoft zu den ESU-Updates für Windows 10.

Wer erhält diese Mail?

Diese Mail geht laut Windowslatest nur an Nutzer, die sich bereits für das ESU-Programm für Windows 10 angemeldet haben. Wer sich aber noch nicht für das ESU-Programm angemeldet hat, erhält diese Mail nicht. Diese Mail dient also nicht dazu, überhaupt erst über das ESU-Programm zu informieren, sondern nur dazu, dass alle ESU-Nutzer von der Verlängerung um ein weiteres Jahr erfahren. Wobei man zu Microsofts Ehrenrettung sagen muss, dass es im Juli 2026 fahrlässig ist, Windows 10 ohne ESU-Updates zu verwenden: In so einem Windows-10-System wurden seit Oktober 2025 keine Lücken mehr geschlossen.

Sie müssen auf diese Mail in keiner Weise reagieren oder aktiv werden. Anders sieht es aus, wenn Sie Windows 10 tatsächlich noch ohne ESU-Updates nutzen sollten: Hier erklären wir, wie Sie sich dafür anmelden. Das sollten Sie jetzt sofort machen.

PC-Upgrade statt Neukauf: So sparen Sie Hunderte Euro

When trusted sites turn.

Sat, 18 Jul 2026 07:22:09 +0200

Lauren Fievisohn⁠, Ph.D, Senior Threat Researcher from ⁠Silent Push⁠, is sharing their work on "Meet DriveSurge: A New Threat Actor Using ClickFix and Fake Update Drive-By Attacks in Thousands of Compromised Sites." Silent Push researchers have identified a newly named threat actor, DriveSurge, which has compromised thousands of legitimate websites and uses ClickFix and fake browser update lures to distribute malware at scale through a pay-per-install operation. The group leverages a traffic distribution system called zTDS to silently redirect visitors from trusted websites to malicious payloads, while employing sophisticated infrastructure, obfuscation, and fingerprinting techniques to evade detection. The report also details how DriveSurge targets both Windows and macOS users and provides defenders with eight infrastructure fingerprints to help identify and disrupt the campaign.

v2.1.214

Sat, 18 Jul 2026 03:46:25 +0200

What's changed

Fixed single-segment dir/** allow rules like Edit(src/**) auto-approving writes to nested dir/ directories anywhere in the tree instead of only /dir
Fixed a permission-check bypass affecting commands run in Windows PowerShell 5.1 sessions
Fixed Bash permission checks to fail closed on file-descriptor redirect forms that bash parses differently than the permission analyzer
Fixed Bash permission checks misjudging very long commands — commands over 10,000 characters now always prompt instead of running automatically
Fixed Bash permission checks treating zsh variable subscripts and modifiers in [[ ]] comparisons as inert text — these commands now prompt for approval
Fixed Bash permission checks to no longer auto-approve certain help and man commands that could run unsafe options, command substitutions, or backslash paths
Fixed permission prompts on remote sessions that could proceed before the local confirmation dialog
Added the EndConversation tool: Claude can end sessions with highly abusive users or jailbreak attempts, as on claude.ai since 2025 — see https://www.anthropic.com/research/end-subset-conversations
Added a periodic progress heartbeat for long-running tool calls that previously went silent
Added an ISO modified timestamp to memory file frontmatter
Added message.uuid, client_request_id, and tool_source attributes to OpenTelemetry log events for message-level correlation and tool provenance
Added CLAUDE_CODE_OTEL_CONTENT_MAX_LENGTH to configure the 60 KB truncation limit on OpenTelemetry content attributes
Added reasoning effort to the subagentStatusLine payload, so custom agent rows can render model and effort
Added permission prompts for docker commands (including the Podman docker shim) carrying daemon-redirect flags (--url, --connection, --identity, and Podman's remote mode) that previously ran without one
Fixed a crash when a GrowthBook feature evaluates to null, and a bug where a malformed flag payload could wipe the cached feature flags
Fixed Bash tool killing the Claude session when a pkill -f pattern accidentally matched the CLI's own process (Linux)
Fixed unbounded memory growth when --settings points at a device file or multi-GB file; oversized (>2 MiB) settings files now fail at startup with a clear error
Fixed streaming turns failing with "Socket is closed" behind corporate proxies on Windows
Fixed stream-json output truncation at exit for slow-reading SDK/pipeline consumers; the exit drain now scales with queued bytes instead of a flat 2s cap
Fixed scheduled tasks refusing their own configured prompt as untrusted input — the fired prompt is now delivered as the session's assigned task
Fixed PowerShell tool commands hanging until timeout when a child process waited on standard input (Windows)
Fixed Python scripts under the PowerShell tool crashing with UnicodeDecodeError when reading non-UTF-8 data from standard input (Windows)
Fixed Python scripts run via the PowerShell tool crashing with UnicodeEncodeError on non-ASCII output, and PowerShell 7 error messages containing raw ANSI escape sequences (Windows)
Fixed the PowerShell tool reporting where.exe, fc.exe, and diff.exe as errors when they return a valid negative answer (Windows)
Fixed > and >> under the PowerShell tool on Windows PowerShell 5.1 writing UTF-16LE files that other tools couldn't read as UTF-8
Fixed a displaced background daemon deleting its successor's control socket on shutdown, which made the next client kill the healthy replacement daemon
Fixed background sessions parked with ← or /background and left idle keeping the background daemon and a worker process alive indefinitely
Fixed completed background sessions being impossible to remove via claude rm or the agent view once the background service had gone idle
Fixed background sessions dispatched from a non-git folder being impossible to delete from the agents view
Fixed reopening a stopped background session failing to restore its saved conversation when an unreadable folder exists in the session store
Fixed the Remote Control "session ready" push notification firing for sessions where Remote Control was not explicitly enabled
Fixed /install-github-app and the /mcp settings menu being blocked in agent-view sessions — they're now refused only in background sessions with no terminal attached
Fixed plugins enabled via the --settings CLI flag not loading (regression since v2.1.181)
Fixed feature flags going stale in long-running sessions after the OAuth token rotates
Fixed /ultrareview refusing to run in repos with no merge base — it now offers to review all tracked files
Fixed claude update and claude doctor hanging silently, and the /status System diagnostics section going blank, when a shell-config path is a directory
Fixed memory frontmatter values being silently truncated at an inline # when memory files are saved
Fixed session cost and token telemetry double-counting on streams that emit multiple cumulative message_delta frames
Fixed a spurious "check your network" warning that appeared while the advisor was thinking
Fixed hooks with exit code 2 not blocking as documented when the hook's stdout JSON fails schema validation
Fixed OTel log events emitted outside the turn's async context missing the interaction span's trace context
Fixed MCP transient errors during prompts/resources refresh clearing the server's slash commands and resources
Improved the claude rc workspace-trust error in the home directory to say trust there is never saved and to suggest running from a project directory
Changed single-segment dir/** hook if: conditions to match only /dir; write **/dir/** for any-depth matching. deny/ask permission rules keep their any-depth match.
Changed file commands using -m/--magic-file or -f/--files-from to require permission instead of being auto-allowed as read-only
Changed keep-alive connection pooling to disable after a stale-connection error, so retries open a fresh socket
Changed SessionStart hooks to report source "fork" when a session begins as a fork instead of "resume"

Intuit scrapped its own AI agent architecture twice in four months. At VB Transform 2026, its AI VP called that the fast path

Fri, 17 Jul 2026 23:02:41 +0200

Intuit was an early pioneer in the usage of agentic AI, but its path to success has hardly been a straight line.

At VB Transform 2026, Intuit VP of AI Nhung Ho described how the company rebuilt its agent architecture twice in the span of about four months, first moving from a fleet of specialist agents to a central orchestration layer, then abandoning that layer for a skills and tools based system once the orchestrator itself started failing under its own complexity. The full second rebuild took 60 days, with a first working version in under 20.

The failure mode that forced the second rewrite was specific. Agents in the orchestrated system passed results to each other in natural language, and each handoff lost context the next agent needed to act correctly.

"If you have 10 agents and they all are passing to each other, every time that pass happens, error compounds," Ho said.

Why the orchestration layer broke down

Ho said the original push toward specialist agents came from a straightforward customer complaint. A fleet of capable agents is still something a customer has to manage, deciding which agent to use for which task. Intuit's answer was a system that could take a task and route it internally, without asking the customer to pick an agent themselves.

That orchestration layer held up for about three months, which Ho described only half joking as roughly a year in the compressed timeline of agent development in 2026.

It broke for a structural reason rather than a capacity one. Passing outcomes between agents in natural language meant each downstream agent had to infer how the upstream agent reached its conclusion, and that inference degraded with each additional hop. A ten agent chain did not fail occasionally, it compounded errors by design.

That diagnosis is what sent Intuit back to a skills and tools architecture.

The 60-day rebuild, and what it took to get engineering buy-in

Rebuilding a production agent system in 60 days required more than an architectural decision. Ho said the harder problem was internal, convincing both leadership and the engineers who had built the original agents that scrapping recent work was the right call.

The pitch to leadership relied on evidence rather than argument. Ho's team built a demo of the new architecture using real customer queries pulled from production, then showed it performing better than the existing system on the same tasks.

"The best proof, at least my belief, is what are customers trying to do? And whatever system you build needs to address those problems," Ho said.

Winning over engineering required a different case. Hundreds of engineers outside Ho's core team had built the specialist agents being retired, and the ask was to take their agents apart into individual skills and tools instead.

Ho said the motivating argument was scale. A standalone agent solved one narrow problem, while a shared skill or tool built into the new architecture could serve every customer who touched that part of the product. That shift also changed what partner teams were responsible for day to day, moving their focus from building agents to running evals, since evals became the only way to measure whether the new architecture was actually working.

Bringing a human into the loop, and feedback at a different scale

The clearest customer facing result of the rebuild is a feature that lets a live agent conversation pull in a human — though it's currently in early testing, live to about 1% of Intuit's customer base. "We're going to be scaling it up in the next few weeks," she said.

Ho said a customer can bring in an Intuit product support person mid conversation, or their own accountant, or one of Intuit's own bookkeepers, and that person joins with the full context of what the agent has already done.

Ho drew a direct contrast with how most AI chat products handle the same situation. A general purpose assistant answering a tax question typically ends with a disclaimer to consult a professional. Intuit's system is built to connect the customer to that professional directly, inside the same conversation.

That human handoff sits alongside a permissions model built for financial data specifically. Every action an agent takes on a customer's financial data requires explicit permission first, though Ho said that requirement can ease over time as customers build trust in the system. Intuit keeps an audit log of everything an agent does that can be reversed if needed.

Feedback in the agentic AI era

The rebuild also changed how Intuit gathers and uses feedback, a shift Ho said is qualitatively different from what came before.

"Feedback in the past used to be very, very sparse, and it was also very bimodal," Ho said. "Either they loved it or they hated it, and usually it tends towards the negative."

In a chat based system, every conversation functions as feedback, which Ho said moved the company from roughly 0.3% of customers ever giving explicit feedback to something close to 100%.

Ho said she has returned to writing code herself specifically to build models that analyze that feedback volume systematically, looking for where the system is falling short at a scale no manual review process could keep up with.

That volume comes with a tone most product teams aren't used to hearing directly. Customers tell the agent exactly where it failed, in plain terms.

"They straight up tell you, 'You suck. I hate this. This is not right,'" Ho said. "But they're also willing to give the systems grace and correct it as well, and so the onus is on all of us to harvest this new piece of feedback and type of feedback, and actually improve the system."

Capital One releases VulnHunter, an open-source AI tool that finds software flaws before hackers do

Fri, 17 Jul 2026 23:02:38 +0200

Capital One on Thursday released VulnHunter, an open-source, agentic AI security tool that scans source code for exploitable vulnerabilities, maps out how an attacker would reach them, and proposes targeted fixes — all before a single line ships to production. The tool, built internally and now available on GitHub under an Apache 2.0 license, is one of the most ambitious attempts by a major financial institution to turn offensive AI capabilities into a public defensive resource.

The move marks a striking philosophical turn for a company still defined, in many boardrooms, by a 2019 data breach that compromised the personal information of roughly 106 million people across the United States and Canada and ultimately cost the bank an $80 million federal fine.

Capital One is not simply releasing another vulnerability scanner. VulnHunter introduces what the company calls an "attacker-first forward analysis" — a workflow in which the tool begins at the points where a real adversary would enter a system, such as APIs, network messages, or file uploads, and reasons forward through the application's logic to determine whether an exploit path actually survives the code's existing defenses. Conventional scanners typically work in reverse, flagging a dangerous-looking code pattern and then searching backward for a hypothetical attacker. That approach, security practitioners widely acknowledge, buries engineering teams under avalanches of false positives.

VulnHunter attacks that problem head-on with a second innovation: a built-in "falsification engine" that tries to disprove its own findings before a developer ever sees them. After the tool surfaces a potential vulnerability, a structured reasoning workflow hunts for logical gaps, unsupported assumptions, and conditions that would prevent the attack from succeeding. Only findings the engine fails to rule out reach a human reviewer — and when they do, VulnHunter delivers not just an alert but a full explanation of the exploit path and a proposed code fix ready for engineering review.

The tool currently runs on Anthropic's Claude Opus 4.8 model inside a Claude Code environment, though Capital One says the framework has the potential to work across other foundation models and coding harnesses.

The 2019 breach that reshaped how Capital One thinks about cybersecurity

To understand why Capital One chose to open-source a tool this consequential, you have to understand the scar tissue.

On July 19, 2019, Capital One disclosed that an outside individual — later identified as a former Amazon Web Services employee named Paige Thompson — had gained unauthorized access to names, addresses, self-reported income, Social Security numbers, and linked bank account numbers belonging to credit card customers and applicants. The breach, which Capital One says occurred on March 22 and 23, 2019, was discovered only after an external security researcher flagged a configuration vulnerability through the company's Responsible Disclosure Program on July 17 of that year.

The damage was sweeping. Approximately 100 million people in the United States and 6 million in Canada were affected. Roughly 140,000 Social Security numbers, about 80,000 linked bank account numbers, and approximately 1 million Canadian Social Insurance Numbers were compromised. The FBI arrested Thompson, and the government stated it believed the data had been recovered with no evidence of fraud. But the reputational and regulatory toll was enormous.

In August 2020, the Office of the Comptroller of the Currency fined Capital One $80 million, finding that the bank had failed to adequately identify and manage risks as it migrated significant technology operations to the cloud. As Reuters reported at the time, the OCC's consent order cited insufficient network security controls, inadequate data loss prevention measures, and a board that failed to hold management accountable when internal auditing surfaced problems. The OCC also ordered Capital One to overhaul its operations and submit new cybersecurity plans for regulatory review.

The incident became an industry case study in the dangers of moving fast with new technology. As CyberScoop reported in July 2019, a cybersecurity executive at a competing financial company observed that the breach "could be the result of trying too many new things and forcing them through." Capital One's own CEO, Richard D. Fairbank, acknowledged the gravity of the moment. "While I am grateful that the perpetrator has been caught, I am deeply sorry for what has happened," Fairbank said at the time. "I sincerely apologize for the understandable worry this incident must be causing those affected and I am committed to making it right."

How Capital One rebuilt its security reputation through open-source investment

What followed was not a retreat from technology but a doubling down — with security explicitly at the center.

Capital One had declared itself an "open-source first" company in 2015 as part of a broader technology transformation that began over a decade ago. After the breach, the company accelerated its investments in software supply chain security, open-source governance, and AI-driven defense. In August 2022, Capital One joined the Open Source Security Foundation as a premier member, earning a seat on the organization's Governing Board. Chris Nims, then EVP of Cloud & Productivity Engineering, framed the move as a natural extension of the company's operating philosophy. "As a highly-regulated company, we are seasoned in managing compliance and governance and advocate for standardization, automation and collaboration," Nims said in the OpenSSF announcement.

Behind that public commitment lay a substantial operational apparatus. Capital One's Open Source Program Office, now in its third iteration, manages open-source usage, contributions, and community building across the enterprise. The company has released more than 25 open-source projects and made over 2,000 contributions to approximately 135 external open-source projects, according to the company's own disclosures. Those efforts address not just code dependencies but the entire software development lifecycle — DevSecOps tools, infrastructure, and the collaborative environments, both internal and external, that shape how software gets built and shipped.

Nureen D'Souza, the director who leads Capital One's OSPO, has spoken publicly about the philosophy underpinning this work. At cdCon 2022, D'Souza described a "company-wide culture with security ingrained" that allows developers to focus on innovation rather than maintenance chores, as reported by SD Times. The OSPO's charter emphasizes three pillars: standardization of open-source processes, automation of security policies throughout the delivery pipeline, and ecosystem sustainability through upstream contributions to the foundations and projects the company depends on.

VulnHunter is the most consequential product of that multi-year effort — and the clearest signal yet that Capital One views open-source collaboration not as charity but as a competitive security strategy. The company argues that modern software supply chains are so deeply interconnected that a single vulnerability in a widely used open-source component can cascade across thousands of enterprises simultaneously. Proprietary defenses, no matter how sophisticated, cannot address a problem that is fundamentally communal. By releasing VulnHunter under a permissive license, Capital One invites the global security research community to stress-test, extend, and improve the tool — effectively crowdsourcing its own defense infrastructure while strengthening the broader ecosystem.

Inside VulnHunter's three-stage AI engine for finding exploitable code

For engineering leaders evaluating VulnHunter, the technical architecture is where the tool's ambitions become concrete. The workflow unfolds in three distinct stages.

In the first stage — attacker-first forward analysis — VulnHunter begins at the points where an external adversary would interact with a system: API endpoints, network message handlers, file upload interfaces. From each entry point, the tool reasons forward through application logic, tracing data flows, transformations, and internal security checkpoints to determine whether an attacker can actually reach a dangerous code path. This approach mirrors how a skilled penetration tester would probe a system, but automates the process at a scale no human team could match.

The second stage is where VulnHunter departs most sharply from conventional scanners. After identifying a potential vulnerability, the falsification engine runs a structured reasoning workflow designed to disprove its own conclusion. It searches for assumptions that do not hold, logical gaps in the exploit path, and environmental conditions that would prevent an attack from succeeding. Findings that fail this internal challenge are discarded before any developer sees them. Capital One's explicit goal is to shift the developer's burden away from triaging false alarms — a perennial pain point that erodes trust in security tooling and slows development velocity.

In the third stage, vulnerabilities that survive the falsification engine trigger an evidence-backed remediation workflow. VulnHunter gathers supporting evidence across the codebase, maps the complete surviving exploit path, explains the defect and the specific capabilities an attacker would gain, and generates targeted code changes for engineering review. The output is not a generic advisory but a concrete, context-aware patch proposal.

Capital One says it validated VulnHunter internally before release, running it across thousands of repositories spanning tens of business areas. The company reports that the tool identified and remediated vulnerabilities with speed and efficiency that far exceeded what its teams previously achieved through manual triage.

Why AI-powered attacks are forcing banks to rethink traditional cyber defenses

VulnHunter arrives at a moment when the cybersecurity landscape is shifting beneath the feet of every enterprise. Capital One's announcement frames the urgency in stark terms: advanced AI models have "dramatically lowered the barrier for bad actors to discover and exploit vulnerabilities in software," and the window before sophisticated AI attack capabilities become affordable and accessible to virtually every adversary is shrinking rapidly.

The company's own AI security researchers have been tracking these trends closely. At NeurIPS 2024 in Vancouver, Capital One's team presented research and curated a list of nearly 100 papers spanning LLM safety, adversarial resilience, jailbreak attacks, and synthetic data generation. The papers they highlighted — including work on multi-agent defense frameworks, automated red-teaming, and guardrail classifiers — paint a picture of an arms race in which offensive and defensive AI capabilities are co-evolving at breakneck speed.

Several of those research themes map directly onto VulnHunter's architecture. The falsification engine echoes the adversarial defense strategies explored in papers like "BackdoorAlign," which demonstrated that embedding a structured safety mechanism into a small number of training examples could recover a model's safety alignment without degrading performance. The attacker-first forward analysis reflects the philosophy of "WildTeaming," a framework that collects and analyzes real-world jailbreak attempts to build more resilient models. And VulnHunter's emphasis on minimizing false positives parallels the goals of "GuardFormer," a guardrail classifier that outperformed GPT-4 on safety benchmarks while running 14 times faster.

The thread connecting all of this work is a conviction that traditional, reactive security — monitoring networks, patching known vulnerabilities, responding to incidents after they occur — is no longer sufficient when adversaries can use AI to discover and exploit zero-day vulnerabilities at machine speed. The only durable defense, Capital One argues, is to find and fix the vulnerabilities in your own code before attackers find them first.

What Capital One's cloud security journey reveals about the entire banking industry

Capital One's arc from breach victim to open-source security contributor also illuminates a broader reckoning across financial services. When Capital One moved aggressively to Amazon Web Services in the mid-2010s, it was a rarity among major banks. Most financial institutions simply did not trust third parties to store their most sensitive data. Capital One's CIO at the time, Rob Alexander, publicly championed the cloud as more secure than the bank's own data centers — a claim that the 2019 breach complicated considerably.

The CyberScoop report from that period captured the tension within the industry. W. Patrick Opet, managing director of cybersecurity at JP Morgan Chase, described a cultural shift in banking from prioritizing traders to prioritizing developers: "Now, it's 'Focus on the developer, turn everything into code, and automate everything.'" Mark Nicholson, Deloitte's cyber leader for the financial industry, noted that the pressure to move quickly was exposing "weaknesses in the development methodology." And the breach itself was a reminder that even as Chase spent $600 million annually on cybersecurity, relatively simple vulnerabilities — like the Apache Struts bug that enabled the Equifax breach — could undercut massive investments in data protection.

Seven years later, the industry has largely followed Capital One into the cloud, and the security challenges have only intensified. The question is no longer whether to use cloud infrastructure but how to secure the software that runs on it. VulnHunter represents Capital One's answer: rather than relying solely on network-level controls and perimeter defenses, push security directly into the code itself, at the moment it is written. The open-source release also carries implicit competitive pressure. If VulnHunter gains traction among developers and security teams, it could set a new baseline for what enterprise security tooling is expected to do — and force rival banks, fintechs, and cloud providers to match or exceed its capabilities.

Whether VulnHunter lives up to that ambition will depend on adoption, community engagement, and the tool's real-world performance against the increasingly sophisticated AI-powered attacks it was designed to counter. But the release itself tells a story that extends well beyond any single tool or any single company. In 2019, a misconfigured firewall exposed 100 million records and turned Capital One into a cautionary tale about the cost of moving fast without moving carefully. In 2026, the same institution is open-sourcing the kind of AI-driven defense it wishes it had built sooner — and betting that the best way to protect its own code is to help the entire industry protect theirs.

Internet of Baby - the privacy implications of a smart nursery. (emf2026)

Fri, 17 Jul 2026 22:48:23 +0200

IoT baby monitors, smart bassinets, connected toys, and AI-powered parenting apps promise peace of mind and convenience for tired parents of wee children. But behind the reassuring notifications and cutesy designs lies an ever expanding ecosystem of microphones, cameras, biometric sensors, cloud analytics, and behaviour profiling systems collecting data about children - before they even have started solids! This talk explores the privacy implications of modern baby IoT devices: what data is collected, where it goes, who profits from it. I will examine real-world breaches, insecure ecosystems, children's data gathering, and the consequences of normalising surveillance from infancy. Licensed to the public under https://creativecommons.org/licenses/by-sa/4.0/ about this event: https://www.emfcamp.org/schedule/2026/220-internet-of-baby-the-privacy-implications-of-a-smart-nursery

Meta In Talks To Lease Computing Power To Anthropic In Potential $10 Billion Deal

Fri, 17 Jul 2026 19:51:00 +0200

Anthropic is reportedly in very early talks to lease computing power from Meta in a potential deal worth around $10 billion. The discussions follow Anthropic's recent compute deal with SpaceX and come as Meta explores selling excess AI capacity as part of a broader push to turn its massive infrastructure spending into a cloud business. CNBC reports: Access to enough AI chips remains a challenge for firms like Anthropic, which places usage limits on its most advanced models like Fable. [...] Meta could spend as much as $145 billion on capital expenditures, including for AI infrastructure, in 2026. Last October, Zuckerberg said that companies are regularly "asking if we have compute that they could buy from us at some premium to what we've bought it at."

Read more of this story at Slashdot.

EY Data Breach – Hackers Gain Access to IT Support System and Download Documents

Fri, 17 Jul 2026 19:38:59 +0200

Ernst & Young LLP (EY) is notifying clients that an unauthorized third party breached a support ticket platform used by its IT staff, downloading documents containing client tax data during a roughly two-week window this spring. The Big Four accounting and consulting giant filed breach notifications with the California Attorney General’s office on July 15, […]

The post EY Data Breach – Hackers Gain Access to IT Support System and Download Documents appeared first on Cyber Security News.

OpenAI’s new hardware is a $230, 13-switch keyboard for Codex

Fri, 17 Jul 2026 19:19:49 +0200

OpenAI is selling its first hardware — without any help from Jony Ive. It describes the Codex Micro as a “command center for agentic work” but it’s really a 13-switch wireless keyboard customized to help developers keep tabs on what their Codex agents are doing. It costs $230.

The keyboard has 13 mechanical switches (one keycap covers two of them by default), a rotary encoder, joystick, and RGB backlighting around the whole keypad and individual keys. It comes with 32 customizable icon keycaps.

OpenAI claims that the Codex Micro is a serious business tool: The command keys enable Codex users accept changes, reject outputs, push-to-talk, start new chats, and trigger custom actions. The rotary encoder can be used to dial up the “brainpower” allocated to tasks — or in more conventional terms, how many tokens to allocate to reasoning on a task. And the RGB lighting can provide feedback on how various tasks are progressing. And the RGB lighting under the “agent” keys can provide feedback on how various tasks are progressing.

The Codex Micro’s manufacturer, Work Louder, already has a similar device on the market, the Creator Micro, which offers similar functionality, but without the colorful keys. It costs $56 less than the Codex Micro, however.

The Codex Micro will fit in snugly with OpenAI’s other merchandise, where using Codex is as much about a fashion statement as a technological choice.

OpenAI’s new hardware is a $230, 13-switch keyboard for Codex

Fri, 17 Jul 2026 19:18:22 +0200

The Codex Micro will fit in snugly with OpenAI’s other merchandise, where using Codex is as much about a fashion statement as a technological choice.

This article first appeared on InfoWorld.

UK’s Largest Cybercrime Case Ends in Prison for Spider Hacker

Fri, 17 Jul 2026 17:39:25 +0200

The post UK’s Largest Cybercrime Case Ends in Prison for Spider Hacker appeared first on IT Security News.

Bethesda teases Fallout 5 soon after Xbox’s mass layoffs

Fri, 17 Jul 2026 16:02:39 +0200

Xbox is currently in a "reset" period that includes laying off around 3,200 employees over the next year, involving deep cuts at beloved studios like id Software and Obsidian Entertainment. Now, in an attempt to show that things are still running fine, the company has announced a slate of upcoming projects at Bethesda Game Studios […]

Key Trump Deportation Strategies: Removing, Replacing, and Pressuring Immigration Judges

Fri, 17 Jul 2026 15:38:09 +0200

New data shows how mass firings, loyalist replacements, and pressure tactics are turning U.S. immigration courts into a deportation enforcement arm.

The post Key Trump Deportation Strategies: Removing, Replacing, and Pressuring Immigration Judges appeared first on Just Security.

TSMC Plans Up To 12 Arizona Chip Factories, But You Should Be Skeptical

Fri, 17 Jul 2026 15:06:52 +0200

The chipmaker TSMC recently made a major announcement regarding its manufacturing efforts in the United States. While the company originally planned to build eight plants in Arizona, a new wave of investment might push that number up to 12. This expansion could mean more chips for Apple devices will be made domestically, but there are plenty of reasons to hold off on celebrating just yet. The new investment plan promises four more factories in Arizona The government announced that the chipmaker agreed to invest an additional $100 billion in its domestic facilities. This brings its total planned spending to $265 billion. With this added cash, the total number of Arizona sites would grow to 12. These new additions would include both actual chip production sites and dedicated packaging facilities. Adding local packaging is a big step. Previously, experts pointed out that making raw chips in the US was only half the job. Without domestic packaging, the raw materials would just have to be shipped back to Taiwan anyway. Building out the full production line in Arizona helps solve that problem. The actual timeline remains unclear and depends on market conditions However, the company itself is painting a slightly different picture. While government officials confidently announced 12 facilities, the chip manufacturer simply stated that the extra funding would likely result in four new plants. More importantly, it did not provide any specific timeline for when these new factories will actually be built. Leadership noted that future construction is entirely based on the current market situation. This brings a layer of uncertainty to the whole project. Additionally, key customers are keeping their options open. Competitors like Intel and Samsung are also aggressively pushing their own production services. If major buyers decide to spread their orders out to these alternative suppliers, the market situation could change. That shift could delay or cancel the need for all 12 planned locations. Ultimately, these expansion plans look great on paper, but the reality is much less guaranteed. Until the company breaks ground and confirms a strict building schedule, these extra factories are just possibilities rather than facts.

Silo Season 3 Episode 4 Release Date, Time, and What to Expect

Fri, 17 Jul 2026 14:10:37 +0200

Silo Season 3 Episode 4 will arrive on Apple TV on Friday, July 24, 2026. The next chapter will continue Juliette Nichols’ fight to recover her memories while the Before Times storyline reveals more about the events that led to the creation of the silos. Season 3 began on July 3 and follows a weekly Friday release schedule. The ten-episode season will run through September 4, 2026. Silo Season 3 Episode 4 release details Release date: Friday, July 24, 2026 Release time: 12 a.m. PT and 3 a.m. ET India release time: Around 12:30 p.m. IST Streaming platform: Apple TV Genre: Science fiction, dystopian drama and mystery Expected duration: Around 45 to 60 minutes Season episode count: 10 episodes Season finale: September 4, 2026 Main cast: Rebecca Ferguson, Common, Harriet Walter, Chinaza Uche, Avi Nash, Alexandria Riley, Shane McRae and Remmie Milner Ashley Zukerman, Jessica Henwick, Laura Innes, Jessica Brown Findlay, Morven Christie, Reed Birney, Matt Craven and Colin Hanks are among the major additions to the Season 3 cast. Steve Zahn also returns after playing Solo in Season 2. What happened before Episode 4? Spoilers ahead for Silo Season 3 Episodes 1 to 3. Season 3 follows two connected timelines. Inside Silo 18, Juliette has returned after surviving her journey outside, but her damaged memories have left her vulnerable. Camille Sims and Nurse Amy have been using memory-altering drugs as part of a wider attempt to control her and weaken any resistance inside the silo. Juliette gradually learns that other residents have also lost parts of their memories. Patrick Kennedy tells her about the drugs being used to make people forget, while Juliette continues searching for Lukas Kyle and the truth hidden from her. Meanwhile, the Before Times storyline follows journalist Helen Drew and pilot Charlotte Keene. Helen investigates secret memory-erasure experiments connected to Dr. Crnkovich, while Charlotte begins recovering memories of a suspicious military operation. Their story appears closely tied to the political crisis and possible attack that eventually forced humanity underground. What to expect from Silo Season 3 Episode 4 Episode 4 will likely push Juliette closer to discovering who altered her memories and why the Algorithm considers her dangerous. Her growing resistance to the medication also puts Camille, Sims and Nurse Amy under pressure, since they can no longer assume that Juliette will remain confused or obedient. Patrick’s information about the forgetfulness drugs may help Juliette identify more people who were secretly controlled. Lukas could also return to the main storyline, especially because his knowledge of the Legacy and Salvador Quinn’s message makes him important to understanding the silos. The Before Times plot should continue exploring Helen’s investigation and Charlotte’s recovered memories. Charlotte’s mission may reveal who planned the disaster, what the strange substance was and whether powerful officials helped create the conditions that led to the silo project. As both timelines develop, Episode 4 should make the connection between Juliette’s present-day struggle and the original architects of the silo system much clearer. Silo Season 3 Episode 4 streams on Apple TV on July 24. What do you think Juliette will remember next, and how deeply is Camille involved in the plan to control Silo 18? Let us know in the comments.

Smart glasses are deeply creepy. Why are celebrities like Kylie Jenner endorsing them?

Fri, 17 Jul 2026 14:04:31 +0200

Meta touts safety features – but for women, the dangers of these recording devices are obvious

Imagine if every time you left the house, you couldn’t be sure that the stranger you met at a bar – or even the person walking by you in the street – wasn’t secretly recording you. It sounds like something out of a Black Mirror episode, but let’s face it, the era of wearable technology is fully upon us as everyday accessories have been developed to help track health and fitness data, receive smartphone notifications, and provide hands-free accessibility.

So when Meta announced their AI glasses a few years ago, it wasn’t too surprising that one of the biggest (and most embattled) tech companies on earth had begun cashing in on our obsession with watching others. And their AI glasses have already raised serious concerns over privacy, personal safety and even our sense of agency.

OpenAI and Apple legal battle escalates, poached employees warned about data deletion

Fri, 17 Jul 2026 13:55:50 +0200

Apple has reportedly sent legal letters to former staffers now working at OpenAI, warning them against deleting data that could be used in the brewing legal battle over OpenAI's alleged theft of company secrets.

Sam Altman of OpenAI

Apple filed a lawsuit in early July, 2026, arguing that OpenAI received trade secrets from its former employees. Former executives Tang Tan and Chang Liu were also named in the lawsuit.

Now, The Financial Times reports that Apple has sent letters to approximately 40 former employees. The legal communications require the preservation of all relevant documentation, ensuring that it can be called upon when required.

Continue Reading on AppleInsider | Discuss on our Forums

"There have been reports that we've been nerfed into the ground and gutted, and we are not": id Software proclaims it's alive and well, making more DOOM games

Fri, 17 Jul 2026 13:13:18 +0200

id Software recently discussed the future of the company following Microsoft's mass wave of layoffs during a DOOM: The Dark Ages | Revelation livestream, and it reassured fans it's not going anywhere anytime soon.

Mozilla Privacy Blog: Beyond technical fixes: Protecting kids online without breaking the internet

Fri, 17 Jul 2026 13:10:44 +0200

This is part one of a two-part series in which we explore approaches to protecting children online while safeguarding privacy, security and the open web. Part one covers our concerns regarding age gates, and alternative policy proposals that address the root causes of online harms.

Young people today have unprecedented opportunities to learn, connect, and explore — not just the web and the world, but also themselves. With the increased ubiquity of digital technologies and devices, worries around the relationship between these technologies and young people’s well-being have grown, too. While concerns about the societal implications of new technologies is not a new phenomenon, experts argue that the accelerating speed of deployment of new technologies has outpaced scientists’ capacity to feed into policy recommendations addressing risks. A growing body of research documents the harms experienced by young people online and the challenges reported by parents attempting to mediate their kids’ technology use. At the same time, experts highlight the importance of contextual factors like existing mental health conditions, socio-economic circumstances and parental mediation to understand the real-world effects of digital technologies.

Faced with this complexity, and mounting public pressure, policymakers around the world are urgently seeking ways to improve child safety online. Driven by a sense of time running out and promises of new technical solutions to difficult questions, this has led, across jurisdictions, to proposals to restrict young people’s access to certain technologies or platforms by introducing age assurance mandates.

Privacy and user empowerment have always formed a core part of Mozilla’s mission. As we have said before, we support safer spaces for minors, but we caution against approaches that rely on identity checks, surveillance-based enforcement, or exclusionary defaults. Such interventions rely on the collection of personal and sensitive data and, thus, introduce major new privacy and security risks.

While many technologies exist to verify, estimate, or infer users’ ages, fundamental tensions around accessibility, their effectiveness and effects on user’s privacy, security and free expression remain. Technological approaches must be part of wider efforts to address the root causes of online harms. However, the deployment of age assurance technologies will not solve the complex challenge of preparing young people to navigate an increasingly online world and ensure their wellbeing. That will require more holistic approaches: offering education and support to navigate the web safely, addressing harmful business practices and acknowledging the offline factors shaping children’s lives including social inequality, poverty or disparate access to (mental) health care services.

Ineffective age-gating mandates and the dangerous shift toward VPN restrictions

As jurisdictions around the world gain experience with government-mandated age gates for certain services, evidence is mounting that age restrictions are not an effective policy tool. Avoiding age gates is widespread and trivially easy: In Australia, where minors under 16 year of age have been banned from certain social media platforms since December 2025, the government’s Compliance Update reports that seven out of ten young Australians remain online, often skirting age checks by simply entering a fake birthdate. A recent study on the implementation of the UK’s Online Safety Act found that a third of children have bypassed age gates with fairly trivial steps like faking their birthdate, borrowing someone else’s login credentials, or even drawing on facial hair, and that a quarter of parents have helped their children to bypass age assurance systems. In the US, studies indicate that as far back as 2011, 64% of parents who were aware their child under 13 had a social media account were also ones who helped them create that account.

Confronted with the apparent ineffectiveness of age gates, policymakers around the world seem to be shifting their attention to alleged circumvention tools. While research shows that many young people bypass age barriers by using other people’s devices and accounts or tricking age estimation tools by making themselves look older, virtual private networks (VPNs) are increasingly framed as primarily a “loophole” to age gates. VPNs create encrypted “tunnels” between a user’s device and the internet, protecting all internet traffic from that device and concealing users’ IP addresses. VPNs are an essential privacy and security resource for millions of users worldwide, including young people.

Utah’s recent age verification law holds websites hosting age-restricted content liable for verifying the age of anyone physically located in Utah, including individuals using VPNs or proxies. While the law does not ban VPNs outright, it forces websites to either block known VPN IP addresses or verify the age of every visitor globally. In the UK, policymakers debated age gates for VPNs extensively, but stopped short of restricting VPNs after new evidence confirmed that VPNs are not a relevant pathway for children seeking to bypass age checks. In Brazil, the ECA Digital law empowers the regulatory authority to order technical countermeasures against circumvention tools such as VPNs. These developments suggest a worrying trend: well-meaning but ineffective attempts to protect children risk undermining the fundamental rights to privacy, security, and free expression of all users, as well as the health and openness of the web itself.

We are convinced, however, that there are rights-respecting alternatives policymakers can pursue to empower young people online and improve their safety and well-being.

Moving beyond access bans

We strongly believe that online safety frameworks should be grounded in children’s rights, striking a balance between their right to protection and their right to participate in society, express themselves freely, and access media and information. Such frameworks must also be proportionate and should not undermine the fundamental rights and access to tools like VPNs for all users.

Rather than focusing on limiting access, we believe that policymakers should prioritize interventions that tackle the root causes of online harm. Before considering new instruments, this work starts with ensuring that independent regulatory authorities have the necessary resources to enforce existing online safety frameworks. In Europe, preliminary findings against Meta and TikTok find these companies’ addictive design features to be in breach of the Digital Services Act, underlining the potential of frameworks like the DSA to address key concerns.

The design of online interfaces, and the affordances and constraints they offer, significantly influences users’ interactions, decisions and overall wellbeing. ‘Dark patterns’ or deceptive interfaces are key drivers of harms experienced by users, and especially young people: they can compel people to consent to extensive data collection and processing, resulting in hyper-personalized feeds, personalized ads that may exploit cognitive vulnerabilities and promote unhealthy or excessive consumer choices, and an overall erosion of privacy.

This is why we support proposals like EU Digital Fairness Act (DFA) and the American Innovation and Choice Online Act (AICOA) that could fill regulatory gaps. Specifically, we advocate for the prohibition of harmful design, guided by harmonized definitions of core concepts like “dark patterns”, “deceptive design,” and “addictive design” and anti-circumvention clauses to prevent companies from avoiding regulation through small tweaks. Platforms should be responsible for demonstrating that their design choices are fair, non-manipulative and non-exploitative. And services that are likely to be accessed by children should be required to refrain from enabling certain design features, including excessive notifications, endless feeds and gambling-like features by default, and only with parental consent.

Further, we urge policymakers to adopt a privacy-first approach to online harms. Many of the risks encountered by young people online are related to the collection and processing of personal data. Platforms collect enormous amounts of personal data, including sensitive data, to personalize and target services, ranging from algorithmic recommender systems to online ads. While the systems that target and display ads and curate online content are distinct, both are based on the surveillance and profiling of users.

Such profiling is the basis for young people being targeted with personalized ads and content recommendations, which can segment, exclude, or steer people into inequitable options and towards harmful content. Providers should thus be prohibited from using sensitive personal data (e.g. ethnicity, religious belief, health status, sexual orientation, political affiliation) to personalize content recommendations or ads, and they should be mandated to enable privacy-protective settings by default, including restricting access to users’ location, camera, microphone, contacts, and camera roll. Policymakers should also extend the fairness and transparency obligations to personalization systems and advertising actors, including intermediaries and data brokers.

Additionally, everyone online, including families and young people, should be fully in control of their online experiences and navigate the web according to their preferences and needs. There is a significant opportunity to empower users with easy, effective opt-out rights and granular user controls. In practice, users should have the right to opt out of personalized content and targeting without being penalized with a downgraded version of the service. Some frameworks already strengthen choice – in those cases, we advocate for their robust enforcement.

Across jurisdictions, choice can be strengthened by ensuring that preferences explicitly expressed (e.g. settings selected, feedback signals, customization choices made, survey responses) are respected and “sticky”, so do not get reset without being explicitly requested by the user. Interoperability mandates should let people integrate third-party content moderation systems or recommendation algorithms that better match their preferences and help them break out of the walled gardens of a few dominant companies. Parental controls are another important lever to operationalize user controls: Providers should deploy easy-to-use and effective parental controls that allow families to tailor online experiences to their preferences, across platforms.

We appreciate that this is a long list of complex policy recommendations which are also impacted by broader (geo)political developments. The fact remains that current age assurance approaches are not a silver bullet, and will create more, rather than solve, problems in the long term.

Where policymakers consider age signals as necessary to ensure age-appropriate online experiences, we believe that there are technical approaches better suited to balance users’ rights than those currently pursued. We will explore these developments and approaches in the second part of this series.

The post Beyond technical fixes: Protecting kids online without breaking the internet appeared first on Open Policy & Advocacy.

OpenAI Is Selling $230 Codex Micro Hardware Product With Work Louder

Fri, 17 Jul 2026 12:53:59 +0200

OpenAI recently teamed up with Work Louder to release a physical tool for developers. Reports show OpenAI is selling $230 Codex Micro hardware product units on its website now. The keyboard brings your digital agent workspace straight to your desk. It helps users manage active chats and keep track of tasks through live lighting feedback. Buyers can pick between a clicky or silent switch version when ordering the device. The device offers physical controls for common coding workflow tasks The gadget maps your most used actions to physical buttons. This release shows its push into the physical world of artificial intelligence tools. It connects directly with the desktop app to provide high customization. You can reassign any key or change how the agent buttons work to fit your specific needs. Each key lights up with a status indicator so you can see if the program is thinking, running, waiting, or done before you even open a chat window. Here is a look at the specific features built into this product: Trigger skills instantly: Users can flick the built-in joystick to launch common workflows. This includes reviewing a pull request, debugging a coding error, or refactoring text. Keep core actions close: The command keys give you a dedicated shortcut for accepting, rejecting, or starting a new chat. Set the brainpower: You can turn a physical dial to adjust the reasoning level of the AI on the fly. This lets you stay fast for simple tasks or turn it up for heavier thinking. This hardware release marks a big shift in how developers interact with digital models. Moving software controls to a physical keypad saves time by reducing screen switching. It also makes working with smart agents feel much more natural and direct. The release points to a future where physical devices bridge the gap between human input and complex background processing.

Behind the Refund: From GST Phishing to Remcos RAT Through a Multi-Stage .NET Infection Chain

Fri, 17 Jul 2026 12:39:20 +0200

Introduction Seqrite Labs recently identified a malware distribution campaign that abused the credibility of government institutions to increase infection success rates. The threat actors impersonated legitimate government departments and distributed malicious emails disguised as official notifications related to taxation, refunds, compliance requirements, and regulatory matters. By leveraging recognizable government branding, urgency, and financial incentives, the […]

The post Behind the Refund: From GST Phishing to Remcos RAT Through a Multi-Stage .NET Infection Chain appeared first on Seqrite Labs.

Xi Jinping of China Pitches ‘Openness’ in Push to Shape the Path of A.I.

Fri, 17 Jul 2026 12:34:37 +0200

Xi Jinping said that the development of artificial intelligence systems should be a “symphony of global collaboration.”

How to add XLAs to your outsourcing contract

Fri, 17 Jul 2026 12:17:06 +0200

Organizations usually face the same questions concerning XLAs: What should we measure, who owns the data, how should incentives work, and how will this change provider behavior after signature.

There are no easy answers either, but after advising clients in MSP relationships with major providers, I’ve seen what works and what doesn’t. Successful XLA programs rarely start with massive transformation, nor rely on perfection before adding experience accountability to the contract.

Start with the right metrics

The first concern I hear is what to measure. MSPs often steer that discussion toward metrics already in their reporting stack. That’s a trap.

Unlike SLAs, which measure operational outputs, XLAs should focus on employee experience and business outcomes. The strongest programs start with three to five high-signal metrics tied to the employee journeys creating the most friction. More than that and the program loses focus before it gains traction.

I typically recommend starting with employee satisfaction scores, perceived lost productivity time, repeat incident rates, task completion success, and ease of getting support. Then focus early measurement on common employee experiences like service desk interactions, employee onboarding, application reliability, and device performance.

Trying to measure everything is understandable, but it’s also one of the fastest ways to stall an XLA program.

Precisely define roles and responsibilities

This is the part of XLA contract design where I spend the most time with clients, and it’s the part that major MSPs are most likely to leave vague if you let them. Accenture and TCS both have mature commercial teams skilled at agreeing to things in principle while avoiding specific accountability in writing. Don’t let that happen here.

Employee experience isn’t solely the vendor’s responsibility. It’s genuinely shared, which is a more productive framing than pure vendor accountability, but only if the split is clearly spelled out. This is what I’ve found works in practice.

Customer responsibilities

Selecting tools and platforms
Managing data infrastructure
Sharing experience data openly with the provider
Supporting internal improvement initiatives that the provider flags

Vendor responsibilities

Running the measurement cadence
Delivering monthly experience reporting
Identifying and surfacing improvement opportunities from the data
Executing operational improvements within agreed timelines

Without this level of specificity, XLA programs almost always become reporting exercises. The data gets collected, the scorecard gets presented, and nothing actually changes.

Build flexible targets

One of the biggest mistakes in XLA design is treating experience targets like traditional SLAs, setting once at contract signing and left unchanged for years. Employee expectations, workforce patterns, and technology environments, after all, evolve constantly. A target that feels ambitious in year one may become meaningless by year three.

The strongest XLA contracts include formal reviews every three to six months to recalibrate targets, align with business priorities, and raise expectations as experience improves. This prevents providers from locking in easy wins and coasting. When providers resist review cycles, it’s often a sign they believe the targets can be met on autopilot, a red flag in any XLA program.

Use the right scoring method

One overlooked XLA best practice is how experience scores are calculated. Point-in-time scores can be distorted by outages, isolated incidents, or low survey participation, and providers sometimes exploit that volatility.

I advise clients to calculate official XLA scores using rolling two-month averages instead of snapshots. It creates a more stable and accurate view of experience trends, and makes operational timing games much harder. Most importantly, define the scoring methodology explicitly in the contract. Don’t leave it to be worked out operationally after signing.

Structure incentives carefully

Relying on penalty-only incentives is one of the most expensive XLA mistakes. On paper, the model is simple: miss the target, pay the penalty. In practice, it drives the wrong behavior. Providers focus on protecting themselves instead of improving employee experience, optimizing survey timing, and managing averages rather than solving problems collaboratively.

I’ve seen this repeatedly in Infosys, HCL, and TCS relationships. The strongest XLA structures combine risk and reward where providers earn meaningful upside for exceeding targets, innovating, and improving outcomes. Penalties still matter, especially in mature programs, but they can’t be the only lever otherwise the contract becomes another SLA model with better branding.

Define escalation processes

When experience scores fall below threshold, the contract needs to specify what happens next. This sounds obvious, but I’ve reviewed many service delivery measurement frameworks in clients’ incumbent MPS contracts that specify financial consequences without defining any collaborative process to address the underlying problem.

The escalation language I push clients to include specifies:

a joint review process triggered when scores fall below threshold.
root cause analysis expectations and timelines.
remediation planning requirements with named owners on both sides.
timelines for corrective action and progress reporting.

The framing matters as much as the mechanics. Escalation should be positioned as collaborative problem-solving, not blame assignment. Contracts that turn every missed score into a commercial dispute damage the relationship when provider engagement matters most. The best MSPs treat escalation as a shared diagnostic exercise, not a contractual confrontation.

Establish an operating rhythm

Signing the contract is the beginning, not the end. In my experience, the organizations that get the most out of XLA programs are those that build a disciplined operating cadence and stick to it. The ones that treat XLAs as a reporting exercise almost never see meaningful improvement.

This is the cadence I recommend:

Daily: Both parties maintain live dashboards showing experience trends, application performance, regional issues, and persona-specific insights to catch emerging issues.

Weekly: Customer and vendor teams hold focused working sessions to determine what improved experience this week, what hurt it, which remediation actions were completed, and what’s the priority for next week.

Monthly: Formal governance meetings to review experience scores, improvement actions, root cause discussions, and cross-functional issues that need escalation.

Biannually: Leadership steering meetings to assess overall experience performance, recalibrate targets, and align the XLA program with evolving business priorities to honestly evaluate whether or not the program is driving the outcomes the organization actually cares about.

Common mistakes organizations make

After working through XLA design and implementation with clients across their MSP relationships, the failure modes are predictable. Here’s what to watch for.

Setting targets before establishing a baseline
Rushing into targets before understanding your current state is one of the fastest ways to create disputes. Spend the first three to six months gathering baseline data, then negotiate targets based on evidence rather than guesswork.

Measuring too much
More metrics don’t create more insight. Frameworks with 20 data points rarely survive operational reality. Start focused and expand gradually.

Hiding the data
Transparency is foundational to XLAs. Providers who obscure poor scores, especially when controlling the measurement platform, undermine the entire model. Clients who weaponize the data create the same problem. Build mutual transparency obligations into the contract.

Over-relying on penalties
Penalty-only structures recreate legacy SLA behaviors. Balanced incentives drive better long-term outcomes.

Treating XLAs as static
Employee expectations, technology, and business priorities evolve constantly. Without formal review cycles, XLA programs quickly become irrelevant.

Start smaller than you think you need to

The organizations that get XLAs right are rarely the ones with the most sophisticated tooling. They’re the ones that stopped waiting for a perfect program and introduced real accountability into the contract with what they had.

The most effective starting points are often simple: agree on a focused set of experience metrics, establish a six-month review cycle, commit to shared visibility and data transparency, and create joint accountability for continuous improvement.

From there, maturity develops over time. Governance builds trust, data becomes more actionable, and targets evolve alongside business priorities. The relationship shifts from compliance management to outcome-driven partnership.

In my experience, the organizations that succeed are the ones that stopped accepting green scorecards at face value and demanded something more meaningful.

Airbus announces cloud deal with Scaleway in digital sovereignty push

Fri, 17 Jul 2026 12:08:25 +0200

The move by Airbus comes amidst growing concerns about digital sovereignty and the influence of US-based hyperscalers

CVE-2026-47081 | cyrusimap Cyrus IMAP up to 3.12.2 Apple Push Notification Service access control (WID-SEC-2026-2387)

Fri, 17 Jul 2026 11:57:10 +0200

A vulnerability categorized as problematic has been discovered in cyrusimap Cyrus IMAP up to 3.12.2. Impacted is an unknown function of the component Apple Push Notification Service. Such manipulation leads to improper access controls. This vulnerability is traded as CVE-2026-47081. The attack may be launched remotely. There is no exploit available.

Linus Torvalds Rejects Anti-AI Push and Defends LLM Tools in Linux Development

Fri, 17 Jul 2026 09:39:12 +0200

Linux creator Linus Torvalds has issued a forceful public rebuke to kernel developers pushing an anti-AI stance, declaring unequivocally that large language model tools have a permanent place in Linux kernel development. The exchange unfolded on July 14, 2026, in a Linux Media Mailing List thread that was originally about linking the Patchwork patch-tracking system […]

The post Linus Torvalds Rejects Anti-AI Push and Defends LLM Tools in Linux Development appeared first on Cyber Security News.

Salesforce’s Agentforce product maturity questioned as KeyBanc cites weak customer traction

Fri, 17 Jul 2026 09:03:12 +0200

Salesforce’s AI agent platform, Agentforce, is seeing weaker-than-expected customer traction, according to a recent KeyBanc Capital Markets investment research note, which attributed the slowdown in part to the product itself, stating that “Agentforce, as a product, just isn’t there” yet, following customer checks and a CIO survey.

“Our checks and customer conversations have not been strong, nor has the feedback been on Agentforce. What we can piece together in the disclosed numbers does not signal building momentum and, most recently, our CIO survey delivered another blow with Salesforce being a standout for the wrong reasons,” according to a Seeking Alpha that quoted a KeyBanc research note.

“We attend more Salesforce partner and customer events than any other company in our coverage, and feedback from those customers has been consistent in two ways: 1) customers’ data is not in order to do meaningful AI work; and 2) Agentforce, as a product, just isn’t there,” Seeking Alpha reported, quoting the KeyBanc note.

The KeyBanc note quoted by Seeking Alpha also pointed out that conversations with Salesforce “partners” indicate that Agentforce proof-of-concept deployments are only now starting to generate pipeline opportunities, while its CIO survey found more respondents expecting to deprioritize Salesforce within their IT budget than the other way around over the coming 12 months.

The findings in the research note stand in contrast to Salesforce’s sustained push to position Agentforce as its flagship enterprise AI platform. Since introducing the offering nearly two years back, the company has expanded it with new foundation models, integrations, deployment options, and pricing initiatives, most recently introducing its Headless 360 strategy to make Agentforce available beyond conventional CRM workflows through a more flexible consumption model.

Parts of that flexible consumption model and Agentforce pricing, which Salesforce is still evolving, have already come under scrutiny with industry analysts expressing concern that Headless 360’s monetization model could create budgeting headaches for CIOs by making AI spending less predictable and increasing pressure on IT leaders to demonstrate measurable business outcomes and return on investment before expanding deployments.

Concerns over product maturity

Those concerns around Agentforce’s evolving pricing model appear to be intersecting with the latest concerns about product maturity that KeyBanc analysts mention in their report.

“Three pricing model changes in roughly 18 months make procurement committees nervous, and if the commercial model keeps shifting, buyers question whether the product has stabilized either,” said Bhupendra Chopra, chief revenue officer at IT consulting firm Kanerika.

Salesforce’s latest consumption-based pricing model, Chopra pointed out, is a bigger concern: “It is harder to budget for than seat-based licensing. CIOs want a clearer line between spend and outcome. That line isn’t clear enough yet.”

Greyhound Research Chief Analyst Sanchit Vir Gogia, too, said that the pricing model is a fundamental issue for enterprises.

While Salesforce’s pricing model charges enterprises for AI activity, it leaves customers to determine whether those interactions ultimately translate into meaningful business outcomes, Gogia said.

That, according to Gaurav Parab, principal research analyst at NelsonHall, is slowing adoption because enterprise leaders, such as CIOs, are under pressure to evaluate TCO and expected ROI.

“Most enterprises first want confidence that AI deployments will generate measurable business outcomes before committing to broader rollouts,” he said.

Data Cloud and data readiness remain as challenges

Pricing, though, is just one piece of the equation.

The discussion about Agentforce adoption, analysts said, cannot be separated from Salesforce’s broader product strategy, which positions Agentforce alongside Data Cloud as the foundation for enterprise AI deployments.

“Data modernization has become one of the biggest determinants of adoption. Agentforce depends on trusted, unified enterprise data to generate reliable outcomes. For many organizations, preparing that data foundation through Data 360, integration, governance, and data quality initiatives represents a significant part of the implementation effort,” Purab said, backing the KeyBanc research note.

Chopra seconded that assessment, saying Data Cloud has effectively become a prerequisite for production-grade Agentforce: “We worked with a private equity fund administrator where the AI layer only became reliable once we had clean, structured data feeding into Salesforce consistently. Before that, even well-configured automation produced inconsistent outputs.”

In practice, that means many enterprises need to invest separately in Data Cloud, data integration, governance, and cleanup before Agentforce can be deployed reliably at scale, Chopra said.

Implementation challenges are slowing adoption

Product maturity aside, those implementation challenges, Purab pointed out, are also contributing to a slower pace of Agentforce adoption in enterprises than anticipated.

While interest in Agentforce continues to grow, enterprises, according to the analyst, are largely limiting deployments to targeted, high-value use cases while they establish trusted data foundations, integrate with existing systems, and demonstrate measurable business value.

More so because Data Cloud accelerates Agentforce once the foundation is coherent, it cannot make incoherence disappear, Gogia pointed out.

Chopra, too, said his conversations with enterprise customers closely mirror Purab and KeyBanc’s findings: “The issue isn’t appetite. The issue is that their CRM data is fragmented, partially duplicated, and inconsistently structured. You can’t put an AI agent on top of that and expect reliable outputs.”

“Cleaning that up takes months. That work doesn’t show in a vendor’s deal count, which is why signed agreements and actual production deployments are two very different numbers right now.”

Timing issue or execution gap?

Despite all the challenges, though, Purab said that the slower pace of current adoption is not necessarily indicative of a long-term problem.

“I see it as a timing issue, but it has always been the case. Enterprise AI adoption has consistently followed the maturity of data, governance, and operating models. Salesforce will undoubtedly continue refining the product, pricing, and go-to-market approach, but the larger challenge lies in enterprise readiness,” Purab said.

“As organizations strengthen their data foundations and gain confidence in deploying AI responsibly, Agentforce adoption is likely to broaden significantly,” Purab added.

Chopra, in contrast, offered a more nuanced view: “While data readiness, which is a customer issue, will improve with time, Salesforce needs to fix its go-to-market strategy.”

“Three pricing changes in 18 months, a product that requires significant pre-investment before it delivers value, and implementation complexity that most mid-market buyers aren’t resourced for is definitely a positioning gap Salesforce needs to close,” Chopra said.

Regardless of whether the current slowdown proves temporary or structural, both analysts agreed that the next six to twelve months should provide a clearer picture of Agentforce’s trajectory.

For CIOs evaluating the platform, they said, the focus should be less on headline product announcements and more on tangible indicators of enterprise adoption and operational maturity.

“The key indicators will be an increase in enterprise-scale production deployments rather than pilots, broader adoption beyond customer service into other business functions, stronger customer references demonstrating measurable business outcomes, continued simplification of pricing and deployment models, and greater maturity around governance, security, and operating models for AI agents,” Purab said.

For Chopra, CIOs should go a step further by measuring how AI agents perform in production rather than simply tracking deployment numbers: “Containment rate in production — what percentage of agent interactions are resolved without human escalation — is the real performance signal, not token volume or deal count.”

Salesforce did not immediately respond to a request for comment.

Linux Creator Linus Torvalds Rejects Anti-AI Push and Defends LLM Tools

Fri, 17 Jul 2026 08:38:58 +0200

Linux creator and top-level kernel maintainer Linus Torvalds has made it clear that the Linux kernel project will not adopt an anti-AI stance. He believes that large language models and related tools should be assessed based on their technical value…

The post Linux Creator Linus Torvalds Rejects Anti-AI Push and Defends LLM Tools appeared first on IT Security News.

Linux Creator Linus Torvalds Rejects Anti-AI Push and Defends LLM Tools

Fri, 17 Jul 2026 07:53:51 +0200

The post Linux Creator Linus Torvalds Rejects Anti-AI Push and Defends LLM Tools appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.

Truth Social To Sell Wall Street Firms the 'Fastest' Access To Trump's Post

Fri, 17 Jul 2026 05:52:57 +0200

An anonymous reader quotes a report from NBC News: Trump Media & Technology Group has unveiled a paid-for, licensed data feed that will give banks and trading firms "the fastest" access to posts from influential Truth Social accounts, such as President Donald Trump's, whose posts often move global markets. The product, called 'Truth API,' will deliver posts from the 10 most influential accounts to customers at a significantly faster pace than a regular push notification on the Truth Social platform, a spokesperson said. The feed is designed for organizations "most impacted by the cost of a delay in information," such as algorithmic trading firms, the company said in a statement. "Until now... firms that prioritize tracking influential Truth posts have relied on manual monitoring. Truth API closes the gap." "Markets already move on Truth Social posts ... As adoption grows, we expect Truth API to become a meaningful, ongoing source of revenue for the company," TMTG's interim CEO Kevin McGurn said.

Read more of this story at Slashdot.

Xi Jinping spearheads China’s AI push

Fri, 17 Jul 2026 04:48:57 +0200

A new body is set to strengthen Beijing’s influence over international standard-setting

Chinese memory ban would cut off RAMpocalypse relief

Fri, 17 Jul 2026 02:47:23 +0200

Two US lawmakers push tighter curbs on chipmakers from the Middle Kingdom

v2.1.212

Fri, 17 Jul 2026 02:31:39 +0200

What's changed

/fork now copies your conversation into a new background session (its own row in claude agents) while you keep working; the in-session subagent it used to launch is now /subtask
Added claude auto-mode reset to restore the default auto-mode configuration, with a confirmation prompt (pass --yes to skip)
Added a session-wide limit on WebSearch tool calls (default 200, tunable via CLAUDE_CODE_MAX_WEB_SEARCHES_PER_SESSION) to stop runaway search loops
Added a per-session cap on subagent spawns (default 200, override with CLAUDE_CODE_MAX_SUBAGENTS_PER_SESSION) to stop runaway delegation loops; /clear resets the budget
MCP tool calls running longer than 2 minutes now move to the background automatically so the session stays usable; configure the threshold or disable with CLAUDE_CODE_MCP_AUTO_BACKGROUND_MS
Typing /resume in the agent view now opens a picker of past sessions — including sessions deleted from the list — and resumes your pick as a background session
Fixed plan mode auto-running file-modifying Bash commands (e.g. touch, rm) without a permission prompt or SDK canUseTool callback
Fixed worktree creation following a repository-committed symlink at .claude/worktrees, which could create files outside the repository
Fixed a continue:false hook's halt being dropped when the tool fails or completes mid-stream, and hook infrastructure errors being misreported as user rejections
Fixed SIGTERM during a running Bash tool orphaning the command's process tree in print/SDK mode; the CLI now aborts the turn, kills the tree, and exits 143
Fixed /background and claude --bg failing with "EUNKNOWN: unknown error, uv_spawn" on Windows when Group Policy blocks PowerShell 5.1; the daemon now prefers PowerShell 7
Fixed shell mode (!) not executing commands containing file paths while the path autocomplete popup was open
Fixed auto-mode denial notifications rendering broken characters when a long denial reason was truncated mid-emoji
Fixed Ctrl+J not inserting a newline in the agent view dispatch input on terminals with extended key reporting, and surfaced the newline shortcut in the ? help overlay
Fixed /ultrareview rejecting PR references like #123, PR 123, and pasted PR URLs; error hints now name the command you actually typed
Fixed /ultrareview not fetching the branch from origin when it exists remotely; it now suggests the closest branch name on typos
Fixed /ultrareview skipping the billing confirmation in a new conversation after /clear
Fixed /ultrareview's "not a git repository" error on Claude Desktop now suggesting the project's repository folder instead of terminal commands
Fixed hosted (host-managed) sessions failing at startup when repository settings configured mTLS certs, extra CA bundles, or OAuth scopes; these transport settings are now ignored with a warning
Fixed a spurious "File has not been read yet" error when editing a file that had been read with offset/limit before resuming a session
Fixed ExitWorktree failing with "no active EnterWorktree session" after resuming a session with --continue/--resume in print/SDK mode
Fixed the workflow agent grid staying empty for Remote Control clients that join a session mid-run
Fixed streaming-mode control requests being marked complete before their handler finished, which could lose the request on session restart
Fixed background sessions created with /fork losing their live-parent protection after a state write failure
Fixed reopening a stopped background session from the agent view failing silently — it now resumes the session, or shows why it can't and lets you force a restart
Fixed agent teams: a stopping teammate could send the leader duplicate idle notifications when team initialization re-ran within a session
Fixed the plan-approval dialog footer splitting "ctrl+g to edit in " apart when the file path is long
Fixed the welcome banner keeping its old panel widths after a combined width+height terminal resize in fullscreen mode
Fixed diff previews losing their line numbers and +/- markers in narrow layouts
Fixed @-mentions attaching nothing after a partial file read, plugin uninstall targeting the wrong marketplace, and false "Command timed out" on exit code 143
Fixed OpenTelemetry HTTP exports being rejected with 411/400 by Azure Monitor and other endpoints that don't accept chunked transfer encoding
Fixed OTLP event log records missing trace_id/span_id when TRACEPARENT is set in SDK/headless mode
Fixed conversations with many images incorrectly failing with "Request too large" errors, and improved the error message to explain the actual cause
Fixed web search and web fetch returning "API Error" text as search results or page content when the API was overloaded
Improved web search and web fetch reliability by retrying 529 errors and rate-limited requests with bounded backoff
Improved prompt caching: the mid-conversation system block now works behind LLM gateways and custom base URLs (Bedrock, Vertex, 1P)
Improved background agent attach: cold-attaching now instantly shows the formatted transcript while the session boots, instead of a blank wait
Reduced token usage in inter-agent messaging: SendMessage bodies are no longer duplicated into replayed history and tool results
Changed /fork to name the copy after your prompt when the session has no title, so the row is recognizable in the agent view
Changed bare /btw to reopen the side-question panel on your most recent exchange so you can browse earlier answers
Changed the ← footer hint to pulse N done for a moment when a background agent finishes while nothing needs your input
Deprecated the Task tool's mode parameter (now ignored); subagents inherit the parent session's permission mode by default
Changed Enterprise forceLoginMethod to be enforced for VS Code extension, SDK, setup-token, and install-github-app logins, not just the terminal
Changed session transcripts to record the reasoning effort level on each assistant message
Changed headless/SDK sessions to apply a set_model control request mid-turn; the next model round-trip uses the new model instead of waiting for the next turn
Changed agent view / claude agents --json: sessions waiting on a sandbox, MCP-input, or managed-settings prompt now show as "Needs input" instead of "Working"
Updated the auth status panel title from "Cloud authentication" to "Authentication"
Corrected an earlier release note (2.1.200): tmux through the 3.6 series lacks synchronized output; newer tmux with support is detected automatically

Galaxy S25 Lineup Gets July Update (Update: More Devices)

Thu, 16 Jul 2026 23:32:34 +0200

Samsung continues its push of July security patch updates to its long list of devices. Galaxy S25 series is the latest, but we’ll be updating this post as more devices receive it. Galaxy S25 joins Galaxy S26 in being updated to the latest software, but beyond the security patch, nothing else is noted in the...

Read the original post: Galaxy S25 Lineup Gets July Update (Update: More Devices)

How to eject water from the MacBook speaker with a shortcut

Thu, 16 Jul 2026 19:24:50 +0200

Spilled water on your MacBook? Use a water eject shortcut to push moisture out of your speakers fast. Here's how to set it up and what else actually helps.

Huawei eying possible DRAM market entry

Thu, 16 Jul 2026 19:23:28 +0200

Chinese tech giant Huawei is reportedly entering the DRAM manufacturing business in a bid to cash in on the insane profitability of memory sales.

Three firms – Micron Technology, SK hynix, and Samsung Electronics — account for 95% of the DRAM on the market worldwide. The rest is small players, mostly in China. One of them, CXMT, is gearing to make a run for the market and try and take a little bit of their business. But it is a small player, especially compared to Huawei.

Huawei’s strategy is complex. It is working with various entities to circumvent the U.S. trade sanctions specifically targeting it. According to SemiconductorInsider on X.com, the Chinese government and DRAM chip maker Swaysure (formed in 2022) are planning to introduce a DRAM manufacturing plant with a capacity of 140,000 wafers per month.

For perspective, Samsung manufacturers approximately 500,000 wafers per month, and Micron makes about 250,000 wafers per month.

It all fits in perfectly with Beijing’s drive for semiconductor self-reliance uh especially after all of the U.S. sanctions. And it would be US interference, not Huawei’s inexperienced with making memory that will be its greatest challenge, says one analyst.

“Their biggest problem will be tooling up, since the US has a lot of sway over the world’s semiconductor equipment makers, and it’s using that sway to prevent tools from being shipped to China,” said Jim Handy, president of Objective Analysis.

Handy said he hears that Huawei and Swaysure are working to produce DRAM starting at 28nm. With that process they ought to be able to make 8Gb chips that yield reasonably but he doubts that they will be able to make HBM with that process, though.

Since he doesn’t know how far along they are in the process, Handy doesn’t know when something could come to market. “They may be on the cusp of shipping something, or they may be a couple of years away, but I don’t think they will wait any longer than that, so let’s say 2028. If there’s still a shortage in 2028, they are likely to ramp as hard as they can to get to something like 2-5% of the market by 2030. If the shortage ends before then, they will probably take a much longer time,” he said.

Examining Google DeepMind’s AI bioresilience push

Thu, 16 Jul 2026 19:04:26 +0200

Google DeepMind and Isomorphic Labs outlined a bioresilience program to curb AI misuse in biology while aiding outbreak response. The two organisations published an update on a joint initiative that began quietly and has now built out more than 15 partnerships with government bodies, biosecurity organisations, and research groups over the past 12 months. The […]

The post Examining Google DeepMind’s AI bioresilience push appeared first on AI News.

Airbus migrating 70 critical apps from AWS to France's Scaleway amid digital sovereignty push

Thu, 16 Jul 2026 17:18:27 +0200

Total of 900 applications including ERP, CRM, and manufacturing systems going to be kept 'under European control'

iPad mini with OLED release imminent, pricing unclear

Thu, 16 Jul 2026 16:10:07 +0200

While the rumor that the next iPad mini would have an expensive OLED screen is not new, what is, is that in all likelihood it will ship very shortly after the iPhone 18 Pro release.

iPad mini 7 running Assassin's Creed

The unit, said to be codenamed J510, is very late in the development process. While Thursday's report by Bloomberg's Mark Gurman doesn't explicitly say that it is in mass production, it will have to be by now to make Apple's rumored timetable for release.

A release for the new unit is expected as soon as October, following the iPhone 18 Pro release cycle. What is not clear is pricing for the unit.

Rumor Score: 🤯 Likely

Continue Reading on AppleInsider | Discuss on our Forums

Mass production of folding iPhone vapor cooling system has begun

Thu, 16 Jul 2026 13:54:23 +0200

Apple has reportedly increased the number of vapor chamber coolers it has ordered from its suppliers, with the company likely to use them in its first foldable iPhone as well as the 20th-anniversary celebration model.

The iPhone 17 Pro uses a vapor chamber for cooling purposes - Image Credit: iFixit

The report doesn't go into detail, but it's claimed that Apple has "significantly increased" the total vapor chamber cooling plates on order. It's thought that the first phone to benefit from the new plates will be the oft-rumored foldable device, commonly called iPhone Ultra or iPhone Fold.

This report comes from the Weibo account "Fixed Focus Digital," the same leaker who claimed the iPhone Ultra would benefit from a new cooling system. However, the anonymous leaker is so far the only one to have made such a claim.

Rumor Score: 🤯 Likely

Continue Reading on AppleInsider | Discuss on our Forums

Russian hackers trojanize WebEx, Zoom apps to push Starland malware

Thu, 16 Jul 2026 12:23:31 +0200

A financially motivated Russian threat actor tracked as UAT-11795 is using trojanized software to steal credentials and cryptocurrency by deploying a new backdoor called Starland RAT. [...]

When AI gets a body, it inherits an attack surface

Thu, 16 Jul 2026 12:09:41 +0200

Most security leaders I know working on AI robotics are being shown the same kind of video. A humanoid folds a shirt, sorts a bin, walks a warehouse aisle and a vendor uses the clip to move an embodied AI system from pitch to purchase order. Someone then has to sign off. Robot demos create procurement momentum before security teams receive the artifacts needed to evaluate the system as cyber-physical infrastructure.

Before the book, I prepared cloud infrastructure operating in China and the United States for cybersecurity compliance audits and for the Multi-Level Protection Scheme, China’s mandatory security-grading regime that determines whether a system is allowed to operate. That work taught me a lesson I carry into every AI conversation now. You cannot secure what you cannot see into, and the buyer rarely sees in. A demo makes it worse. It shows one task, completed once, under conditions the vendor chose. None of what a security team must evaluate is on screen.

This used to be a research-lab problem. It is now a procurement line item. The risk changed when embodied AI moved from a research demo to a purchase order. Vendors are asking security teams to approve embodied AI before the category has audit evidence, logging norms, supplier transparency or a shared-responsibility model.

Embodied AI puts a model inside a machine that operates in the physical world: a robot, an arm, a humanoid. Once a model gains motors, sensors and a body, it ceases to be a software endpoint and becomes a cyber-physical system. It inherits hardware, firmware, a supply chain, an installer and a set of remote-access paths. Every one of those is an attack surface that the demo video doesn’t show. An embodied system is sold like software and behaves like a fleet of networked machinery on your floor.

Evaluate these systems across five questions: provenance, access, integrity, evidence and accountability. Here is what each means.

Evaluation question #1: Provenance

What is inside, and who controls it? A humanoid is an assembly of actuators, lidar units, battery packs, joint modules and controllers, most from a supply chain the buyer never vetted, each running firmware the buyer cannot read. Software teams already fought this fight, which is why the software bill of materials became standard practice. Lack of transparency creates systemic risk. Embodied systems raise the stakes because the firmware now lives in dozens of parts that move. The risk does not depend on whether the robot is Chinese, American, German or Japanese. It depends on how much of the system the buyer can see: the hardware, firmware, remote-access paths and maintenance relationships behind it. China installs more industrial robots than any other country and sits near the center of the battery supply chain, as well as parts of the lidar and machine-vision supply base, which these systems draw on. Lidar, short for Light Detection and Ranging, uses pulsed laser beams to map an environment in 3D; machine vision handles optical inspection and guidance. Much of that lineage traces to suppliers your team has no relationship with. This is the hardware and firmware version of the third-party risk NIST’s supply chain guidance was written for, except that the component has motors. Demand a hardware and firmware bill of materials, then use it. Flag unsigned firmware. Map which supplier holds update authority for each part. Require a way to verify integrity, and treat any component you cannot identify as unmanaged.

Evaluation question #2: Access

Who can reach the fleet? Someone installs these machines, someone services them and the vendor pushes software updates. Where teleoperation is part of the support model, treat it as a privileged remote-access path, not a convenience feature. Each is a standing path into a machine that moves and lifts. Security teams have seen this story before. Operational Technology (OT) security went mainstream once industrial systems joined IT networks, and the recurring failure is unmanaged remote access that nobody inventoried. According to one industry survey, roughly half of attacks on OT assets originate in an IT network breach. SolarWinds showed why a trusted update channel deserves scrutiny when one delivered a backdoor to thousands of networks. Embodied systems add the harder part. The compromised endpoint can move. A remote operator on that channel can drive a machine and push code to every unit at once. Treat the fleet like high-value OT. Inventory every remote path, segment it from the production network, default to deny, require signed and verified updates, apply privileged-access controls to vendor maintenance, and treat an always-on teleoperation link as a backdoor until it is governed.

Evaluation question #3: Integrity

Whether the machine can be made to misperceive or misbehave. Researchers have shown that lidar spoofing can cause an autonomous system to brake for an obstacle that is not there or miss one that is. The same class of sensor and model manipulation, on a humanoid sharing a floor with people, produces motion, not a wrong answer on a screen. This is where safety engineering and security part ways. Functional safety stops hazardous motion when a component fails. It plans for accidents. Security plans for an adversary. A hardwired safety circuit can stay independent of the control plane, and a good one does. What it does not tell you is how an attacker reached that control plane, altered the model’s inputs or seized the fleet-management path. Ask the vendor to threat-model sensor spoofing and model manipulation as a path to physical motion. Then ask how you will even know it happened. A spoofed sensor does not announce itself. It shows up as a machine acting incorrectly with confidence.

Picture the failure in plain terms. A warehouse robot takes a routine vendor update that changes how it navigates. The buyer cannot verify the firmware, cannot identify the supplier of the sensor module and has no logs to distinguish a spoofed sensor from a model error. The machine keeps moving, and no one can say why.

Evaluation question #4: Evidence

Whether the claims are true. You have not found an independent audit of embodied-AI field performance, so the uptime and reliability numbers come from the vendor. You are buying a claim, not a track record. Require independently verified uptime, intervention rate and incident history from a named deployment you can call. “Cutting-edge” is not a control.

Evaluation question #5: Accountability

Who owns the risk when it fails? Cloud taught security teams shared responsibility the hard way, after years of arguing which side of the line a breach fell on. Embodied AI arrives without that model, and the stakes are physical: the machine can injure someone. In my compliance work, the question that decided everything was always who is accountable when this thing breaks. Put it in the contract. Define the responsibility boundary, an incident-disclosure timeline, a right to audit and liability for physical harm. A vendor who will not commit in writing is showing you who bears the risk.

These five questions share one root. For a decade, the security question was whether you could trust what a model generates. The embodied question is who can reach the machine and what they can make it do. A demo answers neither.

Before any embodied system reaches your floor, make these five demands of the vendor.

Provenance. A hardware and firmware bill of materials with named suppliers, integrity verification and a vulnerability-disclosure record. No bill of materials, no deal.
Access. A full map of who installs, who services and every update and teleoperation path, with segmentation, default-deny and signed updates required.
Integrity. A threat model for sensor spoofing and model manipulation that treats the failure as physical motion, plus logging that a defender can use.
Evidence. Independently verified uptime, intervention and incident history from a named deployment you can call.
Accountability. A contract that defines the responsibility boundary, incident-disclosure timelines, audit rights and liability for physical harm.

The robot demo is built to make you feel the future has arrived. My job, and now yours, is the unglamorous question behind it. Ask what the machine’s attack surface looks like once it is bolted to your floor, wired to your network and updated by someone you have never met.

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Partnered Health Cyberattack Exposes Patient Data Across Australia

Thu, 16 Jul 2026 11:09:28 +0200

The Partnered Health cyberattack has exposed sensitive patient information across multiple Australian clinics, raising fresh concerns about healthcare cybersecurity. The Partnered Health data breach, involving clinics owned by healthcare provider Partnered Health, a company backed by Quadrant, affected facilities in New South Wales, Victoria, Queensland, Western Australia, and the ACT. The incident has also renewed scrutiny of the growing number of cyberattacks targeting Australia's healthcare sector.

Partnered Health Data Breach Impacted Medical and Personal Information

Partnered Health confirmed that a malicious actor accessed its systems on 23 June, compromising data from 21 clinics across cities, including Sydney, Melbourne, and Canberra. The healthcare provider disclosed the breach more than three weeks later, informing patients that investigations had confirmed personal and health information had been taken from some clinics within its network. "Our investigations to date have confirmed that personal information (including health information) was taken from some of the clinics in our network," the company said. It added, "As a health services provider, we know our patients and our people trust us with personal and medical information, and we sincerely apologise for any concern and inconvenience this may cause them." The stolen information includes names, dates of birth, addresses, contact details, Medicare information, private health insurance details, concession card information, consultation notes, referral letters, pathology reports, diagnostic results, and other treatment records maintained by general practitioners.

Investigation into the Partnered Health Cyberattack Continues

Partnered Health said the cyberattack has been reported to the Australian Cyber Security Centre, the Office of the Australian Information Commissioner, and law enforcement authorities. The company has also secured an interim injunction from the NSW Supreme Court preventing the stolen information from being used or published. While investigations remain ongoing, the provider said the extent of the breach is still being determined at five clinics, including three in Western Australia and two in Victoria. "While there is no direct evidence that patient records have been viewed, as a precaution we have written to patients from these clinics to make them aware of this and provide details of steps that can be taken to protect their information," a Partnered Health spokesperson said. The spokesperson added, "We understand that this sort of news can cause concern. We sincerely apologize for any distress this may have caused our patients."

Quadrant-backed Healthcare Provider Faces Growing Scrutiny

Established in 2013, Partnered Health operates more than 60 medical centres, along with skin cancer, allied health, and mental health clinics, providing services to more than 5 million people nationwide. The company is owned by Quadrant, while Bupa announced in June that it would acquire the healthcare provider. The Partnered Health data breach comes amid a record year for cybersecurity incidents in Australia. According to the Office of the Australian Information Commissioner, 1,205 data breach notifications were recorded in 2025, marking an 8% increase compared with 2024. Among the year's largest incidents was the cyberattack on Qantas, which compromised the information of 5.7 million customers and was reportedly leaked on the dark web. A spokesperson for the Department of Home Affairs said the federal government is aware of the Partnered Health cyberattack and confirmed that relevant agencies are engaged as investigations continue. Authorities have not yet disclosed how many patients were affected or the full scope of the stolen data.