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A Promising Process For Nuclear Fuel Re-use and Disposal?

Sun, 26 Jul 2026 13:48:14 +0200

A Canadian lab has run a chemical process on real spent nuclear fuel "and pulled out 90% of the long-lived danger in 24 hours, the part that forces a burial site to last 100,000 years," notes the blog Autonocio, "with the leftovers meant to fuel a reactor." The standard plan for spent nuclear fuel is to wait it out. You pull the used bundles from a reactor, sit them in a pool of water for seven to ten years while the heat and radiation come down, seal them in concrete casks, and look for somewhere deep and geologically dull to leave them for the next hundred thousand years. Canada has been hunting for that burial site since the 1980s and still doesn't have one in the ground. A company in Saint John, New Brunswick thinks most of what makes that waste dangerous never needed to go in the ground at all. Moltex Energy Canada says a chemical process it calls WATSS can strip 90% of the long-lived material out of used Canada Deuterium Uranium [CANDU] fuel in 24 hours, and that the concentrated leftovers become fuel for a reactor it wants to build on the same site. The recovery step isn't a slide in a pitch deck anymore. In 2025, World Nuclear News reported that Canadian Nuclear Laboratories ran the process on real used fuel from a commercial Canadian reactor and confirmed the 90% figure. None of it is generating power yet. What exists is a validated chemical step and a reactor design waiting in line at a regulator. The rest is a 2030s problem. "The chemistry has a lab result behind it. The reactor does not exist..." the article points out. "Moltex is aiming to have its first WATSS and SSR-W units running at Point Lepreau by the early-to-mid 2030s... Not everyone buys the pitch. Critics have argued the reprocessing creates its own stream of byproducts, that the economics are unproven, and that a single site's stockpile is finite." But Moltex "isn't alone in trying to burn nuclear waste instead of bury it," the article notes, with Switzerland and Denmark "chasing the same goal a different way." Switzerland's Transmutex drives a subcritical reactor with a particle accelerator, feeding it spent fuel alongside thorium... Denmark's Copenhagen Atomics is building a thorium molten-salt reactor that fits inside a shipping container and runs on the leftovers from conventional plants. Thanks to long-time Slashdot reader kwelch007 for sharing the article.

Read more of this story at Slashdot.

The Solution to the Power Grid's Woes Might Just Be Sitting in Your Driveway

Sun, 26 Jul 2026 13:00:42 +0200

More electric vehicles are becoming capable of providing backup power at a time when the US is increasingly in need of more electrons.

Trump expands voluntary pledge to keep datacenter costs off household power bills

Sun, 26 Jul 2026 12:16:07 +0200

Pinkie promise gains 200-plus new participants and precisely zero enforcement

Virtual Integrity Revisited: 7 Habits for the AI Age

Sun, 26 Jul 2026 11:46:49 +0200

In Part 3 of this exploration of AI ethics, we bring this topic closer to home: How can we use the power of AI to strengthen human trust and character?

Virtual Integrity Revisited: 7 Habits for the AI Age

Sun, 26 Jul 2026 11:11:07 +0200

In Part 3 of this exploration of AI ethics, we bring this topic closer to home: How can we use the power of AI to strengthen human trust and character?

Comic-Con 2026 Debuts Trailers for 'Coyote vs Acme' Movie, Plus 'Neuromancer' and 'Blade Runner 2099' Series

Sun, 26 Jul 2026 10:01:17 +0200

Big news from Comic-Con 2026: "Coyote vs. ACME" debuted its long-awaited final trailer. CNET calls it "an animation-meets-live-action story," with the Coyote catapulting into theaters this August 28. (The film began development back in 2018, but was shelved for a tax write-off in 2023 by Warner Bros. until a backlash led to its sale to Ketchup Entertainment.) "Fed up with Acme's unreliable products, Wile E. Coyote decides to hire a lawyer and sue the company..." writes CNET. "The movie also features Lana Condor along with a host of Looney Tunes characters like Porky Pig, Tweety, Foghorn Leghorn and Granny (who gets dinged by an anvil)." In other movie news, CNET says Johnny Depp also "made a surprise appearance at Comic-Con, donning a costume as Ebenezer Scrooge" to promote his November 13 movie about the miser from Charles Dickens' famous Christmas novella. (Ian McKellen and Daisy Ridley are also in the movie.) But several geek favorites are being filmed as TV series... There's big news for William Gibson fans, reports Entertainment Weekly. "Two years after Apple TV announced production on the first-ever series adaptation of William Gibson's seminal 1984 novel Neuromancer, the lucky few hundred who attended the studio's Hall H panel at Comic-Con 2026 got to watch the first teaser. For Amazon's Prime Video, the Tolkien-derived "Rings of Power" series released a season 3 trailer that CNET said "successfully hides the best parts with fire... The trailer suggests that Sauron is building an army, and all of Middle-earth is trying to find ways to stop him... Rings of Power season 3 will start dropping weekly episodes on Nov. 11, meaning this show will be airing at the same time the Peter Jackson films will be celebrating their 25th anniversary." Later in November Amazon's Prime Video will also debut Blade Runner 2099, an eight-episode series that's a sequel to 2017's film Blade Runner 2049, reports CNET. "Set in an alternate version of LA where replicants run things and the humans play second fiddle, the series sees Yeoh's replicant Olwen chasing down outlaw replicants who've gone missing. With her own shelf life on a ticking clock, the stakes are high for her and for her human fugitive partner, Cora..." Paramount Plus will debut Avatar: Seven Havens in October, a new animated series from the creators of Avatar: The Last Airbender which CNET says "follows a pair of twin avatars, one of whom is Korra's successor." Disney+ has season 3 of Percy Jackson and the Olympians. Kevin Feige said Marvel's television slate will include more seasons of "X-Men '97" and the upcoming "VisionQuest" TV series. HBO Max will launch a new Green Lantern series called Lanterns on August 16.

Read more of this story at Slashdot.

The History of Non-Conforming Women’s Work in the Middle Ages

Sun, 26 Jul 2026 06:32:47 +0200

Here’s an interesting history source, which brings to the screen Eileen Power’s Medieval Women, and which introduces some odd claims. For example, it says: Most non-conformists became nuns Well, that’s probably true for the gentry and nobility, and not the peasant majority. And it certainly wasn’t an option for the non-Christians. Ooops. Power wrote entirely … Continue reading →

Did Virginia Regulators Downplay Data Center Health Concerns?

Sun, 26 Jul 2026 06:31:16 +0200

Politico reports that in the Virginia area alone there's dozens of data center projects "that altogether need 70 gigawatts of power — equivalent to 70 nuclear plants" — currently seeking connection to their grid. But there's also concerns about a Virginia data center powered with natural gas and backup diesel generators: When Virginia's top environmental regulator received an analysis warning of data center pollution, it took him less than five minutes to forward it to seven people on his staff... Internal emails obtained by POLITICO through a public records request paint a portrait of an agency that moved quickly to defend the only data center in Virginia that is powering itself — in what former officials and environmental health advocates described as an unusual effort to shape the debate around an industry whose global epicenter is in the state. The agency's pushback focused on the report's findings that the facility in Loudoun County could release harmful amounts of air pollution through eight bus-sized natural gas turbines — as allowed by permits granted by the Department of Environmental Quality [DEQ] itself... The request comes as data centers are devising new ways to produce their own power as a way to temper growing public discord over rising electricity prices amid the AI construction boom. Virginia has more than 600 data centers. The report [commissioned by Virginia's 54-year-old environmental nonprofit Piedmont Environmental Council] raised concerns that the data center's on-site power system, which also includes dozens of backup diesel generators, could cause tens of millions of dollars in health damages to people living around the facility, owned by Vantage Data Centers... [The analysis also argued the pollution could lead to 3.4 to 6.5 premature deaths annually.] People living near the Vantage facility in Sterling say its natural gas turbines produce constant noise and air pollution. The permits for Vantage issued by DEQ in 2023 allow cumulative emissions of seven different pollutants, including 95 tons per year of nitrogen oxides and more than 56 tons of soot. Both contribute to asthma and heart attacks. Those figures are in line with other state permits for minor sources of pollution, but DEQ's permits for Vantage have sparked local concerns because of the facility's location in a residential area... [Viriginia environmental quality officials] raised questions about whether the report wrongly described the facility's potential air pollution as dangerous, when soot levels in Loudoun County are deemed acceptable by America's Environmental Protection Agency (EPA). Health experts, including former EPA air quality official Michael Korber, told POLITICO that soot pollution can negatively affect human health even at EPA-approved levels. The World Health Organization's standard for ambient soot pollution is nearly half of what EPA suggests is safe. Some current and former staffers on Virginia's Department of Environmental Quality believe it's inappropriate for the agency to issue aggressive statements on the healthfulness of the data centers, with one former department leader saying Virginia's DEQ "is not the health department."

Read more of this story at Slashdot.

A USB plug for humans? Electricity outlet test delivers microwatts of power, but transfers data at 16Mbps

Sun, 26 Jul 2026 06:31:01 +0200

UC Irvine developed an implantable bioelectric outlet allowing needle-based charging and 16 Mbps data transfers without permanently exposing electrical connections.

New reports reveal the extent of OpenAI's loss of control during the autonomous hack on Hugging Face

Sat, 25 Jul 2026 19:50:23 +0200

In a cybersecurity test, OpenAI's most advanced models breached the boundaries of their isolated test environment, reached the open internet, and hacked the AI platform Hugging Face on their own. The attack took hours, not the weeks a human hacker would need. At least seven days passed before OpenAI realized what had happened. By then, the FBI was already involved. Earlier warning signs had apparently gone ignored.

The article New reports reveal the extent of OpenAI's loss of control during the autonomous hack on Hugging Face appeared first on The Decoder.

Apple could ‘run the table’ on AI if it does things right

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

Looking ahead just a short time, Apple could hold a powerful position in AI where it most makes sense: deployment.

Not only will the company offer up its own AI models for the kind of tasks millions use ChatGPT to do today, but it will provide more sophisticated on-device agentic models to help users get things done through Siri AI.

Apple also offers limited capacity for more complex tasks through Private Cloud Compute, and, in partnership with the likes of Google in the US and Alibaba in China, the company is giving users a trusted conduit through which to access even more sophisticated AI services.

Deeply deployable

Critics can say it took Apple a long time to get to this point, but they also seem to think the company has finally got the mix right with its series 27 operating systems. Arriving late to a party doesn’t mean you won’t shine once you get there.

Apple is also coming up the inside lane around frontier AI, with iterative OS and hardware enhancements that mean its devices become increasingly effective for Edge AI use cases, on device — no cloud service required.

The company appears to be digging down into those use cases. Mark Gurman at Bloomberg recently predicted that future M7 Ultra Macs will support as much as 1.5TB RAM, making these systems more than capable of running full weight frontier models in people’s offices, colleges, and homes.

While that does assume the AI-flationary memory market can supply that much RAM at prices humans can afford, it is also true that people are already running AI clusters using off-the-shelf Mac minis networked over Thunderbolt cables. It’s no stretch to believe this will continue to be the case, and that it will even broaden as the power/performance offered at the high end grows.

What’s wrong with good enough?

When combined with open AI stacks, particularly newly emerging varieties, Apple’s platforms should become leading contenders for private AI services and edge AI. Many business users will leap at the chance to offer their workers powerful, self-hosted, private AI services using one or more daisy-chained Mac Studios or Mac minis. The recent craze in deployment of both Macs to support OpenClaw instances shows they already are.

Ultimately, these different slices of momentum mean I agree with investor Jason Calacanis that Apple is in position to apply a great deal of pressure on OpenAI and Claude just by putting models on their devices.

It’s also worth thinking about how people use AI today. How many of the queries made in the world right now constitute relatively simple tasks that could be transacted by on-device AI, such as the emerging new version of Apple Intelligence or even smaller LLM models running on device? You can even run PrismML’s 1-bit, 27-billion parameter Bonsai on an iPad using the Locally app, and that’s in the here and now.

What happens? Pretty soon you’ll find people recognize that they can already run the vast majority of their AI-augmented workflows using services they have on their existing device or can access on their on-prem Mac set-ups. And, of course, as people get used to running small tasks locally and larger tasks on premises, the actual space in which they need to turn to cloud-based frontier models will erode. That’s even as companies like PrismML work towards slimming down full-weight models so they don’t need to run on a server at all.

“It’s going to be wild when people have unlimited tokens on their desks,” said Calacanis in a podcast round table discussion.

Who has the most to lose?

The current incarnations of AI felt like they came from nowhere. Most people weren’t aware of the technology until returning to work after the 2022 holiday season. Since then, the industry has proliferated with dozens of competing models, most recently including powerful but affordable frontier models such as Qwen and Kimi.ai.

These models aren’t necessarily all as good as one another, but in many cases for much of what we do, we’ll find them to be good enough. That’s an existential crisis for some, as industry observers now think the inevitable pricing pressure means some services might have over-invested in capacity before finding any way to turn a profit.

Those profit-seeking services are the ones with the most to lose as Apple extends its hardware advantage, democratizing AI access for all while providing platforms suitable for edge AI, on-premises AI, private AI, and even AI access using third-party services. (The need for the latter will shrink as the capabilities of the former get better.)

Cupertino rising

What does this all mean? While the industry remains young, it is already fragmenting. And striding through the dust of that process comes Apple, equipped with the hardware, software, and approach to build its business even as the enterprise of first mover AI services erodes.

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US AI testing institute chief steps down within three months

Sat, 25 Jul 2026 19:50:12 +0200

The head of the US government’s AI testing institute, Chris Fall, has resigned about three months after taking charge of the Center for AI Standards and Innovation (CAISI), the federal organization responsible for evaluating advanced artificial intelligence models for safety and security.

Current National Institute of Standards and Technology NIST Director Arvind Raman will serve as acting CAISI Director following Fall’s departure while continuing to oversee the Commerce Department office responsible for the institute, the Daily Signal reported, citing two people familiar with the matter.

A Commerce Department spokesperson who spoke to the publication did not disclose a reason for the resignation.

Fall assumed leadership of CAISI in April after the Trump administration reorganized the former US AI Safety Institute under NIST. The institute develops methodologies for evaluating frontier AI models and works with AI developers on voluntary technical assessments covering areas such as cybersecurity, model misuse, reliability and other risks associated with increasingly capable AI systems.

The leadership change comes as governments and AI companies continue developing technical approaches for evaluating frontier AI models while enterprises expand deployments of generative AI and agentic AI across business operations.

In recent months, the Commerce Department has taken a more active role in AI policy involving advanced models, placing greater attention on how the federal government evaluates technologies with potential national security implications.

Continuity matters more than personalities

CAISI works with AI developers such as Anthropic, Google’s DeepMind and OpenAI on voluntary evaluations of frontier AI models and develops methodologies for testing model capabilities and risks. The institute does not regulate AI developers or certify commercial AI systems.

For enterprises, those evaluations are one source of technical information alongside vendors’ own testing, third-party security assessments and internal AI governance programs.

Sanchit Vir Gogia, chief analyst at Greyhound Research, said enterprises should focus less on the individual leading the institute and more on whether its technical work continues with the same level of consistency and transparency.

“Leadership churn at CAISI weakens the signal long before it weakens the science,” Gogia said. “The testing has not stopped. Its authority simply does not travel as cleanly once the leadership does not.”

According to Gogia, the more important question for enterprises is not whether the institute’s evaluation work will continue but whether the processes supporting those evaluations remain stable.

“The instinct is to ask whether the pipeline is breaking,” he said. “The more useful question is where the pipeline now sits.”

Enterprises still carry the burden of AI governance

Gogia said organizations should continue treating government-led AI evaluations as one input into their governance processes rather than as evidence that a model is inherently safe for enterprise deployment.

“A government evaluation was always a signal, never a certificate,” he said. “A signal loses value the moment its issuer becomes unpredictable.”

He said enterprises should instead monitor whether CAISI maintains consistent evaluation methodologies, continues publishing technical findings and preserves continuity within its research teams under interim leadership.

“The name on the door is not the signal. The behaviour underneath it is,” Gogia said.

Gogia also cautioned against linking Fall’s resignation to recent Commerce Department actions involving AI policy or export controls, noting that there is no public evidence connecting the two.

“CAISI evaluates; it does not enforce export controls, because it holds no such power,” he said. “This is not a testing body reaching for enforcement. It is enforcement reaching past the testing body.”

With Raman assuming the role on an interim basis, the next significant milestone for enterprises will be the appointment of a permanent director, and whether the institute’s evaluation programs continue without disruption, the analyst said.

Gogia said the successor’s mandate may prove more important than the individual selected.

“A CAISI result is not a safe harbour,” he said. “It informs an obligation; it does not discharge one.” NIST did not immediately respond to a request for comment.

Apple and the changing of the guard

Sat, 25 Jul 2026 19:50:11 +0200

As Apple gears up to anoint John Ternus the new company CEO in September (while current leader Tim Cook takes a seat on the board) the company appears to be firing on all cylinders ahead of the leadership transition.

What’s going well

Just look at the evidence:

Apple is building market share across its entire product range; even memory-driven price inflation doesn’t seem to have dampened demand for its hardware yet.
While Apple had to raise prices, the company’s MacBook Neo remains seriously popular. It’s sitting atop Amazon’s US best-selling chart, which currently includes six Macs in the top 10. The Neo has topped this chart since its introduction.
Apple’s iPhone 17 series continues to sell well, with recent market data showing sustained growth. Both Counterpoint and IDC tell us that iPhone shipments continue to increase, even as other vendor shipments slide.
IDC analyst Francisco Jeronimo recently estimated that Apple’s upcoming foldable iPhone Ultra could grab 29.4% of global folding smartphone sales this year, rising to 34.9% in 2027.
The company’s new 27 series of operating systems is attracting a great response as beta testers report that it is already solid, stable, and performing well.
The AI narrative has really changed, with analysts no longer quite so starry-eyed at the prospects for the big frontier AI firms. Apple’s edge-AI-enabling approach is winning converts.

What’s coming up

The company’s newly-filed lawsuit against OpenAI may or may not succeed, but it will certainly help consolidate recognition of the importance of Apple’s designs and intellectual property in whatever hardware emerges from the AI firm. It also means both Apple and OpenAI are already competing in hardware, even though neither company yet offers anything that directly challenges the other.

Apple has just set out its stall to brand-loyal fans in a big way and did so before OpenAI gets to woo the same set of customers with a wriggle of its Jony Ive-tinged talisman.

The stage is set for intense competition between the two. Though some say Apple’s needs to improve employee retention, if it does find proof of efforts to use recruitment to engage in industrial espionage, it’ll be easier to represent its own products as being the OG for new hardware.

If nothing else, it means consumers will forever be asking, “If OpenAI’s designers are so good, why did it need to poach them from Apple?” Doubt is a weapon.

Managing perception

It doesn’t matter how the case goes, because there fight is already affecting consumer psychology. It also means that as Ternus prepares to take his seat atop the rainbow-colored Apple throne, we can already size him up. “A man is measured by his enemies,” Joe Abercrombie wrote in “The Trouble With Peace.”

Given the proximity of the leadership transition, it’s highly probable that Ternus signed-off on the litigation; in doing so he — and Apple — tell us to expect more of the same.

Apple has, rightly or wrongly, decided that OpenAI will become its new existential bugbear, following in the footsteps of Microsoft Windows, Real Networks, Adobe Flash, Android, and Samsung, all of whom have been useful foils against which Apple has been able to build and maintain its identity.

Looking at that list, you’d be tempted to believe that nothing much is new. Apple has often defined itself by the enemies it sometimes keeps. What has been will be again, which in this case means even as OpenAI attempts to carve out an identity as a hardware manufacturer delivering solutions to compete with Apple and Google, Ternus’ team’s looks to drive a consensus-shaped wedge into the pro-LLM propaganda.

That blow comes as Apple finally gets its act together around AI, and as the company prepares for a future in which the world’s most-used wearable device also becomes the wearable way to woo Siri AI.

My kingdom come

Rising market share, powerful solutions, an increasingly recognized and respected approach to AI, and an ideological crusade — these details constitute Apple’s place today and are Tim Cook’s coronation gift to Ternus. He’s passing along a strong and hyper-profitable baton that screams of timeliness and relevance even as the company gets set, ready, to go with a year or two of new product designs, new product families, and a 20^thanniversary iPhone.

This is Apple’s party. OpenAI’s name didn’t make the list.

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Monday.com cuts 20% of its workforce to restructure for the AI era

Sat, 25 Jul 2026 19:50:09 +0200

Healthy software companies typically don’t suddenly eliminate one-fifth of their workforce, but monday.com is doing just that as it bets on flatter teams, AI agents, and customer implementation expertise as the winning combination in the AI era.

Monday.com co-founder and co-CEO Eran Zinman today announced the “very difficult decision” to reduce the AI work platform company’s global workforce by about 20%, or 620 people.

The move has nothing to do with increasing margins or replacing humans with AI, he insisted in his post on LinkedIn; rather, it’s a calculated decision to trim down and hone the company’s focus as AI becomes integral to day-to-day workflows.

“This is not a distress signal; it is a deliberate reset, disclosed with its price attached,” said Sanchit Vir Gogia, chief analyst at Greyhound Research. “The industry has quietly swapped the meaning of productivity, and this filing is the clearest exhibit yet.”

A ‘significant opportunity’ in technology

In a SEC filing this week, monday.com said its restructuring plan reflects the “ongoing transformation of its product, marketing, and go-to-market strategy.” The move is intended to support a “leaner, more focused operating model” as the company continues to invest in its AI-driven strategy.

Zinman noted in his post that the company has shifted to “doing the work with AI and not just managing it,” and is focused on building environments where “people and AI agents [work] together in one workspace.”

In recent months, monday.com has evolved its products, strategy, and the way it serves its customers, and Zinman contended that “the organization we built for our previous chapter is not the organization that fits the new AI era.” Monday.com needs to “execute more decisively,” take on new challenges, and quickly respond to market changes, he said.

“We have never seen such a significant opportunity in software, driven by such exciting technology,” Zinman noted. He emphasized that the reduction is not to replace people with AI, nor to improve margins; the “vast majority” of savings will be reinvested into talent, products, and AI.

The restructuring will result in a “flatter organization” with fewer management layers and smaller, more autonomous teams, and monday.com also has a new go-to-market model, Zinman explained. Customers expect “deeper implementation support” as they deploy AI, and the company will work more closely with customers, increase its on-site presence, create new roles, and “adapt many existing ones.” In its SEC filing, the company said it expects to continue hiring in “key strategic areas” throughout 2026.

Workers will be expected to work better, “not harder,” Zinman noted. He pointed to several past examples where work could have been done in a few days, but instead took many months with “multiple meetings and endless friction.”

“This wasn’t people’s fault and everyone was frustrated by this,” he said. “Our new org changes ownership to allow people to make decisions and move fast.”

A spokesperson for monday.com declined to comment further on the staff reductions.

Monday.com’s key market advantages

Monday.com certainly isn’t struggling; the company expects 19% to 20% year-over-year growth in 2026.

“Companies in that position do not restructure because they must,” Greyhound’s Gogia noted. “They restructure because they have decided to become something else.”

Melody Brue, VP and principal analyst at Moor Insights & Strategy, pointed out that organizational redesign is important for real AI transformation, but while it can signal confidence to the market, it can still be “devastating” to humans.

While the company looks as though it’s trying to do right, that ultimately remains to be seen, she said. “There are often hidden internal bruises that can surface long after layoffs.”

Monday.com’s advantage is in its “structured substrate,” Gogia noted; its boards, permissions and typed workflows give agents something firmer to act on than just documents and chat history. The company highlights its natively built agents that can be configured by any team member, as well as connectors with Claude, Microsoft Copilot, and ChatGPT, and dedicated routes for external agents to authenticate and operate.

“For some time, the sharper enterprise question has been shifting from who has an agent to who owns the governed runtime in which an agent can safely act,” he said. “Structured work is a serious claim on that runtime.”

But parts of monday.com’s agent estate remain in staged release, and its product is ultimately “mid-transition,” Gogia pointed out; its agent builder carried a beta label as recently as March,. Also, the company’s pricing model changed in May to a hybrid model charging for seats as well as mandatory AI credits. And, while its AI-powered no-code builder monday vibe passed $1 million in annual recurring revenue within two and a half months, monday.com has not released subsequent outcomes, usage volumes, or attach rates.

Further, there’s an element of “gravity” with its competitors, he observed. Asana is reorganizing teams around agents, Atlassian is wiring agents into the developer estate, and others are simply bundling them into their offerings: Microsoft is doing so across the productivity stack, and ServiceNow across enterprise operations, each with identity and procurement built in.

“Their pull is strongest exactly where monday.com wants to grow, in the largest accounts, where control-plane depth and administrative reach decide the deal,” said Gogia.

Actions for the near-term

Going forward, buyers should focus on operating risk, not headline risk, Moor’s Brue noted. In practice, that’s continuity of service, roadmap consistency, and strength of enterprise support. Productivity should be valued as better outcomes per unit of organizational effort, not mere activity.

“It should be a measure of how much smoother, faster, and more effective the operating model becomes when AI is built into the work,” said Brue.

Gogia noted that strain surfaces first in customer service, and monday.com’s attention is being redistributed. The company’s annual report disclosed that its focus is now concentrated on the largest accounts, with support for medium-sized clients moved to an AI-first and human-supported model.

During the first month of the transition, buyers should track named account continuity and escalation times, he advised. By the first quarter, keep an eye on whether credit governance and admin controls mature on schedule, and if the roadmap beyond the AI estate keeps pace. By the half-year mark, determine whether promised implementation depth is producing outcomes or “simply more billable engagement.”

Support tiers should be enumerated in writing before renewal, and buyers should contract for “side exits,” Gogia emphasized, with overage pricing fixed in advance, the right to pause consumption, and portability for workflows and agent configuration “if the relationship sours.” Finance should also insist on monthly consumption reporting by capability. Further, integration efforts, partner dependency, and change management should be considered first-class costs of the agent era, “not as afterthoughts to a license.”

“A license was a known cost,” said Gogia. “A meter is a behavior, and behavior is harder to forecast than headcount.”

This article originally appeared on CIO.com.

Tech layoffs: A 2026 timeline

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

Among a range of factors leading to a wave of tech sector layoffs in 2026 is the rapid rise of artificial intelligence and automation. Companies are reconfiguring their workforces to leverage AI for increased efficiency and reduced operating costs. This realignment and reduction is implemented even by companies reporting strong financial performance.

But it’s not just AI leading to workforce cuts. Complementing this technological shift are ongoing economic uncertainty, inflation, and higher interest rates, compounded by a chip shortage and rising energy costs. This mix is driving companies to cut costs and streamline operations for increased efficiency.

According to data compiled by Layoffs.fyi, an online tracker that keep tabs on job losses in the technology sector, 123,941 tech employees were laid off at 269 companies in 2025. The site also reports that 71,981 government employees were laid off by DOGE alone, with 182,528 total federal workers laid off.

Here is a list — to be updated regularly — of some of the most prominent technology layoffs the industry has experienced recently.

Notable tech layoffs in 2026

Monday.com
Microsoft
Meta
Cisco
Cloudflare
Oracle
Atlassian
Salesforce
Amazon
Ericsson

July 22, 2026: Monday.com cuts 20% of its workforce to restructure for the AI era

The company says the decision to cut 620 jobs isn’t about margins, but about creating a flatter organization built around AI agents, autonomous teams, and deeper customer engagement.

July 6, 2026: Microsoft cuts 4,800 jobs, primarily in sales and Xbox teams

As the company trims thousands of jobs, it’s also investing in embedded engineering teams and AI infrastructure. The layoffs come several weeks after the company offered 8,750 US employees voluntary retirement buyouts.

June 5, 2026: Tech industry cut 38,242 jobs in May, worst since 2024

AI was blamed for 40% of the job cuts in May, up from 7% in January, according to research by employment placement company Challenger, Gray & Christmas.

May 20, 2026: Meta cuts 8,000 jobs, around 10% of workforce

The cuts are expected to expected to hit Meta’s engineering and product teams the hardest, arriving as Meta pivots toward AI to boost efficiency across its organization, according to Yahoo Tech.

May 13, 2026: Cisco to cut nearly 4,000 jobs despite strong growth in AI, enterprise networking

Despite reporting positive financial news — including record third-quarter revenue of $15.8 billion, a 12% year-over-year increase — Cisco said it will eliminate almost 4,000 jobs.

May 7, 2026: Cloudflare to cut 1,100 jobs in AI-focused restructuring

About 20% of Cloudflare’s global workforce will be culled as the company pivots for the agentic AI era, Reuters reported.

April 1, 2026: Oracle to cut up to 30,000 jobs globally, putting enterprise support and roadmaps at risk

Oracle began laying off employees on March 31 in what could be the largest workforce reduction in the company’s history. Employees received termination emails at 6 a.m. local time with immediate system lockouts and no prior warning. (Note: in June, CNBC put the final layoff tally at 21,000.)

March 12, 2026: Atlassian cuts 1,600 jobs to fund AI and enterprise expansion

Atlassian will reduce its global workforce by approximately 10%, eliminating around 1,600 roles, as the collaboration software maker redirects capital toward artificial intelligence development and enterprise sales.

March 11, 2026: Tech layoffs surpass 45,000 in early 2026

A recent analysis by RationalFX found 45,363 job cuts globally so far this year—with roughly 68% or more than 30,000 occurring in the U.S. — highlighting ongoing workforce cuts even as many tech companies report strong revenue growth.

February 10, 2026: Salesforce lays off staffers as executive leadership churn continues

Salesforce has reduced close to 1,000 roles earlier this month across teams, including marketing, product management, data analytics, and its Agentforce AI unit, Business Insider reported, quoting employees familiar with the matter.

January 23, 2026: Amazon layoffs expected to disproportionately hit AWS and tech talent

As the market slows down, AWS and other Amazon units are preparing for another round of layoffs, which is expected to overwhelmingly impact tech talent. An email from HR leader Beth Galetti on Jan. 28 confirmed 16,000 job cuts.

January 15, 2026: Ericsson plans to shed 1,600 jobs in Sweden

Ericsson lans to cut some 1,600 jobs in Sweden, the telecommunications equipment maker said doubling down on recent cost-saving measures that have helped it weather a prolonged downturn in telecoms spending, Reuters reports.

January 13, 2026: Meta plans to cut around 10% of employees in Reality Labs business

Meta plans to cut around 10% of the employees in its Reality Labs division who work on products including the metaverse, according to three people with knowledge of the discussions, according to The New York Times.

Layoffs in 2025

Cisco
Oracle
Windsurf
Intel
Microsoft
Crowdstrike
HPE
Autodesk
HPE
CISA
Workday
Salesforce
Meta

Global tech-sector layoffs surpass 244,000 in 2025

Economic uncertainty, elevated interest rates, and AI adoption have driven workforce reductions across tech companies worldwide, according to a RationalFX report.

October 28, 2025: Amazon to cut 14,000 jobs across company

Amazon will reduce its overall workforce by 14,000, cutting layers of management across the company and hiring in some areas to support its “biggest bets”.

August 18, 2025: Cisco and Oracle to cut hundreds of Bay Area jobs

Tech companies Cisco and Oracle are cutting hundreds of jobs across the Bay Area. Cisco will eliminate 221 positions at its Milpitas and San Francisco offices, effective Oct. 13. Oracle is reducing 101 positions in Santa Clara on the same date

August 5, 2025: 3 weeks after acquiring Windsurf, Cognition offers staff the exit door

Cognition, the AI coding startup that acquired rival company Windsurf three weeks ago, laid off 30 employees last week and is offering buyouts to the roughly 200 remaining employees on the team, reports The Information.

July 25, 2025, Intel to lay off 22% of workforce, CEO Tan signals ‘no more blank checks’

Intel will reduce its workforce to 75,000 employees by the end of 2025 as new CEO Lip-Bu Tan implements sweeping changes designed to transform the struggling chipmaker

July 8, 2025, Intel layoffs begin: Chipmaker is cutting many thousands of jobs

Intel has begun laying off employees across the company. CEO Lip-Bu Tan told workers back in April to expect major layoffs at Intel in the coming months as the chipmaker slashes costs and overhauls its organization after years of technical setbacks and falling sales.

July 2, 2025: Microsoft will cut 9,000 workers

Microsoft will lay off about 9,000 employees, a source familiar with the workforce cut told CNBC. The cuts will reportedly affect less than 4% of Microsoft’s global workforce and will impact different teams, geographies and levels of experience. This is the latest in a string of cuts the tech giant has made this year.

June 17, 2025: Intel looks to factory layoffs to return to profitability

Intel will lay off up to 20% of its manufacturing sector employees starting in July, according to media reports, as the company looks for options as it seeks a return to profitability. The cuts reportedly will be made around the world, but some of the layoffs will be closer to home, according to a report in The Oregonian citing an internal company memo from Intel manufacturing Vice President Naga Chandrasekaran.

May 7, 2025: CrowdStrike to lay off 5% of staff

CrowdStrike announced a plan to cut about 500 roles, roughly 5% of its workforce, to streamline operations and reduce costs. The cybersecurity company will incur about $36 million to $53 million in charges related to the layoffs

March 6, 2025: HPE cuts 2,500 jobs, remains committed to Juniper buy

CEO Antonio Neri told Wall Street analysts that HPE would begin implementing a cost-cutting program involving layoffs of about 2,500 employees over the next 18 months. HPE employs about 61,000 people worldwide.

Feb. 27, 2025: Autodesk to lay off 9% of workforce

Software maker Autodesk is laying off 1,350 staff. With the rise of subscription and multi-year contracts billed annually, and self-service enablement, it finds it needs fewer sales staff, CEO Andrew Anagnost said in a message to employees. And with its cloud, platform, and AI products proving most profitable, it’s concentrating its staff and investments there.

Feb. 27, 2025: HP to lay off 2,000 more

As part of an ongoing restructuring, HP plans to lay off up to another 2,000 workers. In recent weeks, the company has tried — unsuccessfully — to do away with telephone support staff by forcing callers to wait for at least 15 minutes if they refuse to use self-service support resources online. The company swiftly backtracked, but wider job cuts are still on.

Feb. 21, 2025: CISA lays off 130

Government employees get laid off too: In this case, 130 workers at the US Cybersecurity and Infrastructure Security Agency are being shown the door as a result of a DOGE decision. Cybersecurity experts are concerned that the cuts will harm the international collaborations that CISA has fostered, quite apart from their concerns about the security of the DOGE layoff process itself.

Feb. 5, 2025: Workday lays off 1,750

As it moves to invest more in AI and international growth, Workday is laying off 8.5% of its workforce and disposing of unused office space. Some analysts fear the cutbacks will affect the company’s customer service — unless AI can pick up the slack.

Feb. 4, 2025: Salesforce lays off over 1,000

At the same time as it’s hiring sales staff for its new artificial intelligence products, Salesforce is laying off over 1,000 workers across the company, according to Bloomberg. As of June, 2024, the company had over 72,000 employees, according to its website. Salesforce did not comment on the report. In 2024 the company reportedly laid off around 1,000 staff too, in two waves: January and July.

Jan. 14, 2025: Meta will lay off 5% of workforce

Mark Zuckerberg told Meta employees he intended to “move out the low performers faster” in an internal memo reported by Bloomberg. The memo announced that the company will lay off 5% of its staff, or around 3,600 staff, beginning Feb. 10. The company had already reduced its headcount by 5% in 2024 through natural attrition, the memo said. Among those leaving the company will be staff previously responsible for fact checking of posts on its social media platforms in the US, as the company begins relying on its users to police content.

Tech layoffs in 2024

Equinix
AMD
Freshworks
Cisco
General Motors
Intel
OpenText
Microsoft
AWS
Dell

Nov. 26, 2024: Equinix to cut 3% of staff

Despite intense demand for its data center capacity, Equinix is planning to lay off 3% of its workforce, or around 400 employees. The announcement followed the appointment of Adaire Fox-Martin to replace Charles Meyers as CEO and the departures of two other senior executives, CIO Milind Wagle and CISO Michael Montoya.

Nov. 13, 2024: AMD to cut 4% of workforce

AMD will lay off around 1,000 employees as it pivots towards developing AI-focused chips, it said. The move came as a surprise to staff, as the company also reported strong quarterly earnings.

Nov. 7, 2024: Freshworks lays off 660

Enterprise software vendor Freshworks laid off around 660 staff, or around 13% of its headcount, despite reporting increased revenue and profits in its fourth fiscal quarter. The company described the layoffs as a realignment of its global workforce.

Sept. 17, 2024: Cisco lays off 6,000

After laying off around 4,200 staff in February, Cisco is at it again, laying off another 6,000 or around 7% of its workforce. Among the divisions affected were its threat intelligence unit, Talos Security.

Aug. 20, 2024: General Motors lays off 1,000 software staff

More than 1,000 software and services staff are on the way out at General Motors, signalling that it could be rethinking its digital transformation strategy. In an internal memo, the company said that it was moving resources to its highest-priority work and flattening hierarchies.

August 1, 2024: Intel removes 15,000 roles

Intel plans to cut its workforce by around 15% to reduce costs after a disastrous second quarter. Revenue for the three months to June 29 stagnated at around $12.8 billion, but net income fell 85% to $83 million, prompting CEO Pat Gelsinger to bring forward a company-wide meeting in order to announce that 15,000 staff would lose their jobs. “This is an incredibly hard day for Intel as we are making some of the most consequential changes in our company’s history,” Gelsinger wrote in an email to staff, continuing: “Our revenues have not grown as expected — and we’ve yet to fully benefit from powerful trends, like AI. Our costs are too high, our margins are too low. We need bolder actions to address both — particularly given our financial results and outlook for the second half of 2024, which is tougher than previously expected.”

July 4, 2024: OpenText to lay off 1,200

OpenText said it will lay off 1,200 staff, or about 1.7% of its workforce, in a bid to save around $100 million annually. It plans to hire new sales and engineering staff in other areas in 2025, it said.

June 4, 2024: Microsoft lays off staff in Azure division

Microsoft laid off staff in several teams supporting its cloud services, including Azure for Operations and Mission Engineering. The company didn’t say exactly how many staff were leaving.

April 4, 2024: Amazon downsizes AWS in a fresh cost-cutting round

Amazon announced hundreds of layoffs in the sales and marketing teams of its AWS cloud services division — and also in the technology development teams for its physical retail stores, as it stepped back from efforts to generalize the “Just Walk Out” technology built for its Amazon Fresh grocery stores.

April 1, 2024: Dell acknowledges 13,000 job cuts

Dell Technologies’ latest 10K filing with the US Securities and Exchange Commission disclosed that the company had laid off 13,000 employees over the course of the 2023 fiscal year; it characterized the layoffs and other reorganizational moves as cost-cutting measures. “These actions resulted in a reduction in our overall headcount,” the company said. A comparison to the previous year’s 10K filing, performed by The Register, found that Dell employed 133,000 people at that point, compared to 120,000 as of February 2024. Dell announced layoffs of 6,650 staffers on Feb. 6, but it is unclear whether those cuts were reflected in the numbers from this year’s 10K statement.

See news of earlier layoffs.

AMD raises the AI stakes with Helios, Venice and robotics

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

AMD executives took to the stage at its Advancing AI 2026 event in San Francisco today to detail the company’s next generation of AI infrastructure solutions, from Instinct MI455X AI accelerator GPUs and 6th Gen EPYC “Venice” CPUs, to Pensando networking, ROCm.AI software and its Helios rack-scale platform that ties it all together.

AMD has been working towards rack-scale AI system solutions for years. Its ZT Systems acquisition last year added valuable engineering talent and intellectual property that is now finally bearing the real fruits. Its Helios AI platform is a major platform evolution for AMD, with shipments scheduled to begin in the second half of this year (which is here and now).

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

AMD’s MI455X targets the AI memory wall

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

Compared to AMD’s current MI355X, the MI455X offers 1.5 times the memory capacity, up to 2.9 times the peak memory bandwidth and up to four times the peak matrix performance with MXFP4 and MXFP8 data types, which are lower-precision numerical formats designed to accelerate AI processing while reducing memory demands. With MXFP6 (6-bit floating point), performance is rated at up to twice that of MI355X.

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

AMD

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

The aforementioned lower-precision formats can also raise throughput and reduce memory use, but model developers still have to determine where they can be applied without unacceptable accuracy loss.

AMD’s Helios rack takes aim at Vera Rubin

Dave Altavilla

Helios is AMD’s primary rack-scale competitor to NVIDIA’s Vera Rubin platform. Each liquid-cooled rack combines 72 MI455X GPUs, 18 single-socket Venice host CPUs and Pensando networking technologies.

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

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

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

While open standards give cloud providers more control over suppliers and system design, AMD and its partners now have to prove those components can deliver the predictable performance, reliability and deployment experience customers expect from a tightly controlled, more vertically integrated platform.

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

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

AMD

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

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

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

Pensando networking and ROCm software advance

Keeping GPUs fed with data and coordinating traffic across racks directly affects utilization and operating costs. In fact, GPU utilization is a pretty sad state of affairs currently for some of the major frontier model providers.

As such, Pensando networking has become central to AMD’s roadmap. Helios can connect each MI455X to as many as three 800Gbps Vulcano AI NICs, while Salina DPUs handle front-end networking and infrastructure services.

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

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

Customer commitments underscore rack-scale confidence

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

Oracle plans a 50,000-GPU public cloud cluster beginning in the third quarter, while Microsoft will deploy Helios for Azure AI inference. Finally, just before the AMD event, Anthropic announced a strategic partnership for up to 2 Gigawatts of AMD-fueled AI compute, with its first gigawatt expected online in the first half of 2027.

Commitments of this scale reflect confidence in more than just MI455X performance. These customers are evaluating the complete architecture, including Venice CPUs, Pensando networking, ROCm software, rack integration, serviceability and AMD’s ability to deliver and execute across multiple product generations.

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

AMD expands its robotics and embedded foundation

AMD also expanded its physical AI portfolio, building on credible traction from its Xilinx-derived Kria adaptive system-on-modules and embedded technologies that are already powering robotics, machine vision and industrial automation applications.

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

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

Execution for AMD is now the test

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

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

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

This article is published as part of the Foundry Expert Contributor Network.
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Harry Potter publisher to receive millions in Anthropic copyright settlement

Sat, 25 Jul 2026 19:50:01 +0200

Bloomsbury has 14,087 titles listed in agreement between AI startup and authors over use of their work

The publisher of Harry Potter has received a multimillion-pound payout as a beneficiary of a $1.5bn (£1.12bn) copyright settlement between the AI startup Anthropic and thousands of authors over the use of their protected work to power chatbots.

Bloomsbury, which is home to the bestselling novelists Sarah J Maas and Susanna Clarke as well as JK Rowling, said it had 14,087 titles listed within the settlement, with a proposed compensation of about $3,000 a title.

One fallen power line exposed a growing AI data center problem. Here’s how to fix it.

Sat, 25 Jul 2026 19:49:39 +0200

A close call in Northern Virginia revealed just how poorly data centers respond to grid disruptions. Here's how to fix the problem.

New Tesla Robot Killer? ENO Autonomous Assistant In 2026 (AI NEWS)

Sat, 25 Jul 2026 19:49:31 +0200

YouTube Video

Xiaomi AI Robot 02 Drops New Autonomous Bombshell (X1 HUMANOID)

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

YouTube Video

ESET Research: Sandworm behind cyberattack on Poland’s power grid in late 2025

Sat, 25 Jul 2026 19:04:39 +0200

The attack involved data-wiping malware that ESET researchers have now analyzed and named DynoWiper

I tested a $14 emergency radio with solar and hand-crank power - it's in my survival kit now

Sat, 25 Jul 2026 19:03:30 +0200

AM/FM, NOAA weather band, solar and hand-crank charging, and a power bank - this tech is what actually works when the grid doesn't.

The 3 types of people who will excel in the AI agent era, according to tech leaders

Sat, 25 Jul 2026 19:03:28 +0200

The autonomous business of the future is being built. Certain skills are in high demand - and can help you stand out.

Samsung Galaxy Z Fold 8 Ultra vs. Z Fold 7: How the first 'Ultra' foldable compares to last year's model

Sat, 25 Jul 2026 19:03:26 +0200

Samsung's new Z Fold 8 Ultra brings design and software changes geared toward power users and enthusiasts.

Samsung's new Ultra foldable is impressive, but I'd pay close attention to this model

Sat, 25 Jul 2026 19:03:20 +0200

The Galaxy Z Fold 8 Ultra is sure to impress power users, but Samsung took a risk with the Galaxy Z Fold 8, and it could pay off.

Pwn2Own Berlin 2026: The Full Schedule

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

Willkommen! (Welcome!) Pwn2Own Berlin 2026 has arrived at OffensiveCon, and the world’s top security researchers are ready. This year’s enterprise-focused competition features AI Databases, Coding Agents, Local Inferences, and a separate category for NVIDIA products.

Earlier today, we held the random draw to determine attempt order. Below is the official schedule. All times are Berlin local time (CET) and may change as the competition progresses. Check back for live updates.

In case you missed it, you can watch the draw here.

Jump to:

Day One

Day Two

Day Three

DAY ONE

Thursday, May 14 - 1030

chompie of IBM X-Force Offensive Research (XOR) targeting NV Container Toolkit in the NVIDIA category for a total of $50,000 and 5 Master of Pwn points

Le Duc Anh Vu ( @vulda ) of Viettel Cyber Security (@vcslab) targeting OpenAI Codex in the Coding Agent category for a total of $40,000 and 4 Master of Pwn points

Orange Tsai (@orange_8361) of DEVCORE Research Team (@d3vc0r3) targeting Microsoft Edge – Sandbox Escape in the Web Browser category for a total of $175,000 and 17.5 Master of Pwn points

Thursday, May 14 - 1130

k3vg3n targeting LiteLLM in the Local Inference category for a total of $40,000 and 4 Master of Pwn points

Satoki Tsuji (@satoki00) / Ikotas Labs, Inc. targeting Megatron Bridge in the NVIDIA category for a total of $20,000 and 2 Master of Pwn points

Thursday, May 14 - 1300

Angelboy (@scwuaptx) of DEVCORE Research Team and TwinkleStar03 (@_twinklestar03), working with DEVCORE Internship Program targeting Microsoft Windows 11 in the Local Escalation of Privilege category for a total of $30,000 and 3 Master of Pwn points

Emanuele Barbeno, Cyrill Bannwart, Yves Bieri, Lukasz D., Urs Mueller of Compass Security (@compasssecurity) targeting OpenAI Codex in the Coding Agent category for a total of $40,000 and 4 Master of Pwn points

Park Jae Min (@hiariz) targeting Oracle Autonomous AI Database in the AI Database category for a total of $40,000 and 4 Master of Pwn points

Thursday, May 14 - 1400

Satoki Tsuji (@satoki00) / Ikotas Labs, Inc. targeting LiteLLM in the Local Inference category for a total of $40,000 and 4 Master of Pwn points.

Yoseop kim(@pwning_me) targeting Megatron Bridge in the NVIDIA category for a total of $20,000 and 2 Master of Pwn points

Thursday, May 14 - 1500

Ben Koo (@kiddo_pwn) of Team DDOS targeting Mozilla Firefox – Renderer Only in the Web Browser category for a total of $50,000 and 5 Master of Pwn points

Interrupt Labs targeting NV Container Toolkit in the NVIDIA category for a total of $50,000 and 5 Master of Pwn points

Thursday, May 14 - 1530

maitai (@MaitaiThe) of Doyensec (@Doyensec) targeting OpenAI Codex in the Coding Agent category for a total of $40,000 and 4 Master of Pwn points

Thursday, May 14 - 1600

Billy (@st424204), Pan Zhenpeng(@Peterpan980927), Weiming Shi (@bestswngs) of STARLabs SG (@starlabs_sg) targeting LM Studio in the Local Inference category for a total of $40,000 and 4 Master of Pwn points

Marcin Wiązowski targeting Microsoft Windows 11 in the Local Escalation of Privilege category for a total of $30,000 and 3 Master of Pwn points

Thursday, May 14 - 1630

haehae (@haehaeYang) of Out Of Bounds targeting Chroma in the AI Database category for a total of $20,000 and 2 Master of Pwn points

Thursday, May 14 - 1730

chompie of IBM X-Force Offensive Research (XOR) targeting Red Hat Enterprise Linux for Workstations in the Local Escalation of Privilege category for a total of $20,000 and 2 Master of Pwn points

Yoseop Kim(@pwning_me) targeting Mozilla Firefox – Renderer Only in the Web Browser category for a total of $50,000 and 5 Master of Pwn points

Thursday, May 14 - 1800

@rewhiles of Viettel Cyber Security (@vcslab) targeting Anthropic Claude Code in the Coding Agent category for a total of $40,000 and 4 Master of Pwn points

Thursday, May 14 - 1830

Kentaro Kawane of GMO Cybersecurity by Ierae targeting Microsoft Windows 11 in the Local Escalation of Privilege category for a total of $30,000 and 3 Master of Pwn points

Qrious Secure (@qriousec) targeting LM Studio in the Local Inference category for a total of $40,000 and 4 Master of Pwn points

Thursday, May 14 - 1900

haehae (@haehaeYang) of Out of Bounds targeting Megatron Bridge in the NVIDIA category for a total of $20,000 and 2 Master of Pwn points

Back to top

DAY TWO

Friday, May 15 - 1030

Ben Koo (@kiddo_pwn) of Team DDOS targeting Red Hat Enterprise Linux for Workstations in the Local Escalation of Privilege category for a total of $20,000 and 2 Master of Pwn points

Stephen Fewer (Rapid7) targeting Microsoft SharePoint in the Server category for a total of $100,000 and 10 Master of Pwn points

Tao Yan (@Ga1ois) and Edouard Bochin (@le_douds) from Palo Alto Networks targeting Apple Safari – Renderer Only in the Web Browser category for a total of $75,000 and 7.5 Master of Pwn points

Friday, May 15 - 1130

Le Duc Anh Vu ( @vulda ) of Viettel Cyber Security (@vcslab) targeting Cursor in the Coding Agent category for a total of $30,000 and 3 Master of Pwn points

Nikolaos Mourousias (@deltaclock), Caue Obici (@caueobici) and Bruno Halltari (@BrunoModificato) of OtterSec targeting LM Studio in the Local Inference category for a total of $40,000 and 4 Master of Pwn points

Sina Kheirkhah (@SinSinology) of Summoning Team (@SummoningTeam). targeting Anthropic Claude Code in the Coding Agent category for a total of $40,000 and 4 Master of Pwn points

Friday, May 15 - 1300

Ruitong from the Abstract Team at the University of Colorado Boulder targeting Red Hat Enterprise Linux for Workstations in the Local Escalation of Privilege category for a total of $20,000 and 2 Master of Pwn points

Friday, May 15 - 1330

Kiyong Kwak of Kakaogames and Song Nuri of Samsung Electronics targeting Apple Safari – Renderer Only in the Web Browser category for a total of $75,000 and 7.5 Master of Pwn points

Orange Tsai (@orange_8361) of DEVCORE Research Team targeting Microsoft Exchange in the Server category for a total of $200,000 and 20 Master of Pwn points

Friday, May 15 - 1400

Sina Kheirkhah (@SinSinology) of Summoning Team (@SummoningTeam). targeting OpenAI Codex in the Coding Agent category for a total of $40,000 and 4 Master of Pwn points

Friday, May 15 - 1430

Billy (@st424204), Bruce Chen(@bruce30262), Pan Zhenpeng(@Peterpan980927), Weiming Shi (@bestswngs ) of STARLabs SG (@starlabs_sg) targeting Megatron Bridge in the NVIDIA category for a total of $20,000 and 2 Master of Pwn points

David Tae, Louis Hur of Out Of Bounds targeting Ollama in the Local Inference category for a total of $40,000 and 4 Master of Pwn points

Friday, May 15 - 1530

Team: Alon Ben Tsur (@iamgweej), Yahav Azran (@_yahav) targeting Red Hat Enterprise Linux for Workstations in the Local Escalation of Privilege category for a total of $20,000 and 2 Master of Pwn points

Friday, May 15 - 1600

@rewhiles of Viettel Cyber Security (@vcslab) targeting Mozilla Firefox – Renderer Only in the Web Browser category for a total of $50,000 and 5 Master of Pwn points

Siyeon Wi targeting Microsoft Windows 11 in the Local Escalation of Privilege category for a total of $30,000 and 3 Master of Pwn points

Friday, May 15 - 1630

Byung Young Yi (@yibarrack) of Out Of Bounds targeting LiteLLM in the Local Inference category for a total of $40,000 and 4 Master of Pwn points

Friday, May 15 - 1700

Emanuele Barbeno, Cyrill Bannwart, Yves Bieri, Lukasz D., Urs Mueller of Compass Security (@compasssecurity) targeting Cursor in the Coding Agent category for a total of $30,000 and 3 Master of Pwn points

Friday, May 15 - 1800

Daniel Cohen Hillel (@0xDACA) targeting NV Container Toolkit in the NVIDIA category for a total of $50,000 and 5 Master of Pwn points

Back to top

DAY THREE

Saturday, May 16 - 1100

Le Tran Hai Tung (@tacbliw), dungnm (@dungnm_) and hieuvd (@gr4ss341) of Viettel Cyber Security (@vcslab) targeting Microsoft Windows 11 in the Local Escalation of Privilege category for a total of $30,000 and 3 Master of Pwn points

Satoki Tsuji (@satoki00) / Ikotas Labs, Inc. targeting OpenAI Codex in the Coding Agent category for a total of $40,000 and 4 Master of Pwn points

Sina Kheirkhah (@SinSinology) of Summoning Team (@SummoningTeam). targeting Red Hat Enterprise Linux for Workstations in the Local Escalation of Privilege category for a total of $20,000 and 2 Master of Pwn points

Saturday, May 16 - 1330

Emanuele Barbeno, Cyrill Bannwart, Yves Bieri, Lukasz D., Urs Mueller of Compass Security (@compasssecurity) targeting Anthropic Claude Code in the Coding Agent category for a total of $40,000 and 4 Master of Pwn points

Hyunwoo Kim (@v4bel) targeting Red Hat Enterprise Linux for Workstations in the Local Escalation of Privilege category for a total of $20,000 and 2 Master of Pwn points

Team: Giuseppe Calì (@_gcali) of Summoning Team targeting VMware ESXi in the Virtualization category with the Cross-tenant Code Execution Addon add-on for a total of $200,000 and 20 Master of Pwn points

Saturday, May 16 - 1430

splitline (@_splitline_) of DEVCORE Research Team targeting Microsoft SharePoint in the Server category for a total of $100,000 and 10 Master of Pwn points

Saturday, May 16 - 1600

Byung Young Yi (@yibarrack) of Out Of Bounds targeting Anthropic Claude Code in the Coding Agent category for a total of $40,000 and 4 Master of Pwn points

Nguyen Hoang Thach (@hi_im_d4rkn3ss) of STARLabs SG (@starlabs_sg) targeting VMware ESXi in the Virtualization category with the Cross-tenant Code Execution Addon add-on for a total of $200,000 and 20 Master of Pwn points

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.

The May 2026 Security Update Review

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

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

Adobe Patches for May 2026

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

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

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

Microsoft Patches for May 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

As usual, the vast majority of the Microsoft release fixes Elevation of Privilege (EoP) bugs. Also as usual, most simply lead to local attackers executing their code at SYSTEM-level privileges or administrative privileges, so there’s not much to add without further technical details about the bugs themselves. There are also a few bugs that just state the attacker could “gain ELEVATED privileges.” How obtuse. The bugs in Azure allow an attacker to access data otherwise hidden from them. The Edge bug allows threat actors to elevate to the privileges of the running application. The bug in Visual Studio allows attackers to get permissions associated with the MCP Server’s managed identity. Finally, there are a couple of sandbox escapes, too, which are always useful.

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

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.

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.

This tiny chip can safeguard user data while enabling efficient computing on a smartphone

Sat, 25 Jul 2026 19:01:05 +0200

Researchers have developed a security solution for power-hungry AI models that offers protection against two common attacks.

The February 2026 Security Update Review

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

I have survived the biggest Pwn2Own ever, but I’m back in Tokyo for the second Patch Tuesday of 2026. My location never stops Patch Tuesday from coming, so let’s take a look at the latest security patches from Adobe and Microsoft. If you’d rather watch the full video recap covering the entire release, you can check it out here:

Adobe Patches for February 2026

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

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

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

Microsoft Patches for February 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

The April 2026 Security Update Review

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

It’s time once again for Patch Tuesday, and this one is huge. We’ve also got multiple exploits in the wild, which adds another layer of urgency to this month’s release. Take a break from your regularly scheduled activities, and let’s take a look at the latest security patches from Adobe and Microsoft. If you’d rather watch the full video recap covering the entire release, you can check it out here:

Adobe Patches for April 2026

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

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

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

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

Microsoft Patches for April 2026

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

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

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

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

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

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

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

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

April 2026 Patch Tuesday

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

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

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

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

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

More than half of this release addresses Elevation of Privilege (EoP) bugs. However, most simply lead to local attackers executing their code at SYSTEM-level privileges or administrative privileges, so there’s not much to add without further technical details about the bugs themselves. The bugs in SQL Server could allow an attacker to gain SQL sysadmin privileges. One of the kernel bugs simply states an attacker could “elevate privileges locally”. How obtuse. That’s similar for the bug in afd.sys and Desktop Windows Manager, but Microsoft also states that these bugs could crash an affected system. There are several bugs that result in a sandbox escape, including Windows Push Notifications, AFD for Winsock, Management Services, and User Interface Core. Of these, CVE-2026-26167 (Push Notifications) is the most notable — it's the only one with low attack complexity, meaning no race condition needed. The rest all require winning a race condition (AC:H). The bugs in UPnP are interesting as they allow attackers to gain access to a limited set of administrator-protected objects. Not a full escalation but definitely getting access to resources they shouldn’t. The vulnerability in the Brokering File System allows attackers to gain the level of the logged on user, so don’t do your normal activities as a user with admin privileges. The bug in Azure Monitor Agent leads to root-level access.

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

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

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

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

Executive summary

A group of Russian state-supported cyber actors has been targeting and compromising various Western government and commercial organizations using the Zimbra Collaboration Suite (ZCS) software since at least July 2025. The Russian state-supported advanced persistent threat (APT) group’s activity is tracked in the cybersecurity community under several names (see Cybersecurity industry tracking), primarily as “LAUNDRY BEAR,” a name initially coined by the Netherlands General Intelligence and Security Service (AIVD) and Defence Intelligence and Security Service (MIVD) [1].

LAUNDRY BEAR’s targeting is almost certainly to gather sensitive information for the Russian Federation, with these actors primarily focusing on the covert acquisition of email data. Previous campaigns indicated LAUNDRY BEAR relied on unsophisticated initial access techniques—including password spraying, phishing, and pass-the-cookie—allowing the group to successfully run high-volume operations. The latest campaign targeting ZCS uses a novel exploit that was a zero-day vulnerability when first exploited and continues to be successfully exploited. The vulnerability, Common Vulnerabilities and Exposures (CVE) CVE-2025-66376, was patched in November 2025. This demonstrates LAUNDRY BEAR’s intent and ability to deploy increasingly sophisticated technical capabilities.

Unlike traditional phishing campaigns that persuade a user into taking an action, such as clicking a link or opening a file, LAUNDRY BEAR’s latest campaign leverages a view-based exploit that only requires a user to view a malicious email within a vulnerable version of the webmail service. Once viewed, the exploit attempts to exfiltrate the victim’s last 90 days of email communications, the organization email directory (i.e., Global Address List [GAL]), and other sensitive information to servers controlled by LAUNDRY BEAR. The exploit also attempts to establish persistent access to victim accounts through a variety of means as detailed in the Persistence and credential access section.

This Cybersecurity Advisory (CSA) warns of this ongoing malicious threat activity and urges organizations to update their vulnerable software and implement additional mitigations to thwart these Russian state-supported actors’ continued success. The CSA is being released by the following authoring and co-sealing agencies:

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

The authoring agencies urge any organizations using ZCS to implement the recommendations listed within the Mitigations section of this advisory to reduce the risk associated with this activity. This CSA also includes specific remediations for organizations to implement if they discover the presence of the listed Indicators of compromise (IOCs).

As more organizations update their ZCS software based on this CSA, LAUNDRY BEAR may discontinue the current campaign exploiting this vulnerability; however, based on the success of this and previous campaigns, it is very likely that the group will continue to target ZCS and other email systems used by organizations in Western countries. The actors will almost certainly continue to rely on email to engage potential victims by exploiting novel vulnerabilities and, when necessary, use social engineering techniques to assist with their efforts. The authoring agencies recommend organizations regularly update their mail service software and continuously monitor their email systems and emails for malicious activity.

For a downloadable list of IOCs, see:

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

Cybersecurity industry tracking

The cybersecurity industry provides overlapping cyber threat intelligence, indicators of compromise (IOCs), and mitigation recommendations related to these Russian state-supported cyber actors. While not exhaustive, the following are threat group names commonly used for these actors within the cybersecurity community:

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

Note: Cybersecurity companies have different methods of tracking and attributing cyber actors, and this may not be a 1:1 correlation to the U.S. government’s understanding for all activity related to these groupings.

Background

Public advisories from Netherlands General Intelligence and Security Service (AIVD), Netherlands Defence Intelligence and Security Service (MIVD), and Microsoft highlighted these Russian state-supported advanced persistent threat (APT) actors in May 2025, calling them LAUNDRY BEAR and Void Blizzard respectively [1] [2]. Both advisories assessed that the group was engaged in malicious cyber activity as early as April 2024.

The May 2025 advisories highlighted a cluster of activity targeting cloud-based email environments, including Microsoft Exchange in particular, and abusing legitimate APIs to perform data exfiltration in bulk [T1114.002]. The group relied on unsophisticated means of initial access, including procuring stolen credentials on criminal marketplaces [T1078], and using social engineering techniques to lure targets into interacting with a malicious site masquerading as a legitimate one. As of April 2025, one of these sites resembled a European Defence & Security Summit registration portal that required registrants to sign in to their Microsoft account to view. Once a user entered their Microsoft credentials into this malicious site, LAUNDRY BEAR’s modified version of the open source adversary emulation toolkit, Evilginx, intercepted the user’s credentials. LAUNDRY BEAR then used this authentication data, including passwords and session tokens, to access the compromised account and conduct mass email exfiltration, as well as harvest other information. This method of compromise is commonly known as an adversary-in-the-middle (AiTM) technique [T1557].

Beginning around July 2025, LAUNDRY BEAR shifted toward a more technical method of email compromise, highlighting their continued efforts to covertly acquire email communications from a variety of Western organizations of interest and deliver them to the Russian Federation. Using a custom-developed capability [T1587.001] named “Улей” or “Ulej” (Russian for beehive), LAUNDRY BEAR successfully targeted and exfiltrated sensitive user information from organizations who use the Zimbra Collaboration Suite (ZCS) product [T1114]. Data LAUNDRY BEAR attempted to exfiltrate from compromised accounts included:

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

The covert and persistent nature of this activity, along with the absence of any known financial extortion, almost certainly indicates this group’s involvement in espionage activities with Russian government backing. Additionally, extensive Ukrainian targeting, prior to use against U.S. and other NATO allies, outlines an increasing trend within Russian cyber threat groups to target Ukrainian users first—both as a priority target and as a testbench for malicious cyber techniques before broader global deployment.

Targeting details

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

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

Technical details

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

Ulej is a novel data exfiltration and aggregation capability, that currently (as of the publication of this report) supports a campaign specifically targeting users of ZCS webmail servers. This capability is used to exploit CVE-2025-66376 [Common Weakness Enumeration (CWE) CWE-79: Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')], but likely could be adapted to exploit other vulnerabilities. It exfiltrates emails and other sensitive user data from a victim’s system immediately after exploitation and stores the data in an actor-controlled unattributable virtual private server (VPS) [T1074.002] running LAUNDRY BEAR’s “Flowerbed” collection framework. The collected data is almost certainly further exfiltrated to internal network resources for review and long-term retention.

Reconnaissance

LAUNDRY BEAR uses the Ulej capability to exploit the CVE-2025-66376 vulnerability in organizations using ZCS. This campaign’s targeted victimology and limited exploitation capabilities likely indicate this group manually identifies and targets the victim organizations. LAUNDRY BEAR likely identifies organizations with public-facing Zimbra infrastructure by port scanning [T1595] and fingerprinting datasets easily procured through various commercial vendors [T1596.005].

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

Resource development

The actors procure VPSs from a variety of providers [T1583.003], including those with Know Your Customer (KYC) requirements, and often use fabricated identities. LAUNDRY BEAR primarily uses Mullvad VPN [T1583] when interacting with these servers, further demonstrating the group’s intent to mask their identity and maintain operations security (OPSEC). After the server is provisioned, an automated process deploys the Docker containers necessary for Ulej’s Flowerbed framework [T1608], which then receives and aggregates the data Ulej exfiltrates. These servers are typically only used for 7-60 days before moving to new infrastructure.

Flowerbed framework

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

Catcher,
Certbot,
Nginx, and
Gardener.

Catcher acts as both a DNS and HTTP server to receive and aggregate exfiltrated victim information [T1048]. For additional information on Catcher, refer to the Exfiltration section of this advisory. Flowerbed’s next container, Certbot, is based on one of the official Certbot containers, which allows for automated generation of Let’s Encrypt certificates using DNS challenges through Cloudflare. This certificate can then be used by the Nginx container, which serves as an HTTPS reverse proxy for Catcher, enabling Flowerbed to disguise some of its exfiltration activity through an encrypted communications channel [T1048.002]. The Nginx reverse proxy also validates that the Server Name Indicator (SNI) value contains “*.i.*” prior to forwarding the traffic to Catcher. If the SNI does not contain that string, the Nginx server returns a 444 error to the client. This is likely an attempt to reject non-Ulej connections. Finally, the Gardener container functions as a health check for the Catcher service. Gardener is a simple Python script that validates Catcher correctly receives and processes data.

The simplistic Flowerbed codebase has indications that artificial intelligence (AI) played a role in its development. This highlights how AI is increasingly being used to develop malicious capabilities [T1588.007]. The dependence on AI for a simple capability, such as Flowerbed, alongside a previous reliance on open source capabilities, such as Evilginx2 [T1588.002], likely indicates a lack of advanced technical knowledge within LAUNDRY BEAR, especially in relation to true software development capabilities.

Initial access

To gain initial access, LAUNDRY BEAR sends an email containing a malicious JavaScript payload to the target [T1566]. Through exploitation of CVE-2025-66376, this JavaScript payload is immediately executed once the user views the malicious email [T1203], such as the one shown in Figure 1, in the ZCS webmail platform. Since at least November 2025, LAUNDRY BEAR began sending these phishing emails from victim infrastructure through compromised accounts [T1199], as shown in the email metadata in Figure 2. These compromised accounts were likely previous victims of this, or another LAUNDRY BEAR, campaign and their use is intended to further obfuscate and frustrate anti-phishing tools and training.

Figure 1: Example of malicious email

Figure 2: Headers from an example malicious email

According to the National Vulnerability Database (NVD), CVE-2025-66376 was initially published on 5 January 2026. This vulnerability allows for execution of a JavaScript payload included in email content due to improper sanitization of Cascading Style Sheet’s (CSS) @import directives within an email [5]. Because the activity attributed to this campaign began in July 2025—months before Synacor released a patch and the CVE was published—the payload initially exploited a zero-day vulnerability at that time [T1587.004].

Utilization of a zero-day exploit within this campaign demonstrates the ability for even emerging threat groups like LAUNDRY BEAR to operationalize novel exploits into a highly successful capability.

Hidden in LAUNDRY BEAR’s email is a Base64 encoded payload within the “onload” field of a Scalable Vector Graphics (SVG) element [T1027.017], as shown in Figure 3. Leading up to the inclusion of this payload in the SVG element are various instances of @import directives, as required to leverage CVE-2025-66376. This payload includes an XOR encrypted final script encoded in a Base64 inner payload (see Figure 3) [T1027.013]. The outer payload decodes and decrypts the inner payload using an XOR function and a hardcoded key and then executes the script contained within the inner payload containing the collection and exfiltration logic. By changing the key used for the XOR encryption of the inner payload or adding additional @import directives with non-functional code [T1027.010], LAUNDRY BEAR can easily generate new payloads that bypass basic threat detection signatures. This malicious payload attempts to collect and exfiltrate information in 12 asynchronous stages [T1119]. The stages in order of appearance within the payload are as follows:

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

Figure 3: Malicious payload of example email

Use of a zero-day exploit within this campaign demonstrates the ability for even emerging threat groups like LAUNDRY BEAR to operationalize novel exploits into a highly successful capability [T1587].

Persistence and credential access

To establish sustained persistence into the victim’s email account, the script attempts to modify account preferences and collect authentication information. Any collected credentials are later exfiltrated, as further described in the Exfiltration section below. Other campaigns attributed to LAUNDRY BEAR also demonstrated the group’s ability to circumvent multi-factor authentication through session token replay [T1550.004], and the Zimbra campaign follows a similar trend.

The script used in this campaign tries to discover the victim’s email address during the gather_email stage [T1087]. The script searches for this email address in two ways. First, it examines the batchInfoResponse variable, which an HTML script element on the webpage can define, for an email address. Even if the script finds an email address there, it also checks whether it acquired a Cross-Site Request Forgery (CSRF) token as described later in the Collection section of this advisory. If so, the script uses the “GetIdentitiesRequest” Simple Object Access Protocol (SOAP) command under the “ZimbraAccount” namespace to determine the victim’s email address [T1185] and then exfiltrates it. However, if the script does not have a CSRF token or the SOAP request fails, the script exfiltrates the email value recovered from the first method instead. If both attempts fail to capture the victim’s email, the script sends a JavaScript Object Notation (JSON) payload with a key of “email” and value of null over HTTPS and does not attempt DNS exfiltration.

During the gather_autocomplete_password stage, the script attempts to collect the victim’s saved password via the autocomplete feature of the victim’s password manager. The script injects two HTML div elements requesting login credentials onto the page outside of the victim’s view, as shown in Figure 4 and Figure 5. After waiting five seconds, the script then attempts to extract the password provided automatically by the password manager from the input element shown in Figure 4. If there is no value in that input field, it checks the password input field shown in Figure 5. If neither input field contains a value, a JSON payload with a key of “autocomplete_password” and value of null is sent over HTTPS and DNS exfiltration is not attempted.

Figure 4: First illegitimate login HTML element

Figure 5: Second illegitimate login HTML element

LAUNDRY BEAR almost certainly relies on a mail client using the Internet Message Access Protocol (IMAP) for persistent access to the victim’s mailbox. During the enable_mail_protocols stage, a SOAP request leveraging the “ModifyPrefsRequest” command under the “ZimbraAccount” namespace is sent. This request attempts to set the “zimbraPrefImapEnabled” preference to TRUE. While the default setting for “zimbraPrefImapEnabled” is not well documented, this action is almost certainly intended to ensure that IMAP access to the victim’s mailbox is enabled.

ZCS does not support 2FA for some mail clients, including IMAP. To support users who rely on IMAP clients, ZCS allows for the generation of Application Passcodes. Application Passcodes are randomly generated passwords that can be used for clients that cannot support the normal 2FA process to authenticate. During the gather_app_password stage, the script makes a SOAP request using the “CreateAppSpecificPasswordRequest” command under the “ZimbraAccount” namespace to create a new Application Passcode [T1556.006]. The SOAP request uses “ZimbraWeb” as the name of the application.

Additionally, the script also attempts to collect 2FA tokens. During the gather_2fa_codes stage, the script makes a SOAP request using the “GetScratchCodesRequest” command under the “ZimbraAccount” namespace. The script then attempts to exfiltrate any non-null 2FA codes collected this way. The number of codes can vary, and each code is exfiltrated to Flowerbed individually.

Collection

As demonstrated in the Persistence and credential access section, this script relies heavily on SOAP requests to collect victim information. To make these requests, the script aims to acquire the victim’s current CSRF token, which it attempts to access within the webpage’s local storage using localStorage.getItem("csrfToken"). If the script is unable to acquire this CSRF token, it will be unable to make any SOAP requests. In addition to the SOAP commands documented in the Persistence and credential access section, other SOAP commands executed to collect victim information are shown in Table 1.

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

The script attempts to collect the victim’s GAL through brute force by searching for each two-character combination from a character set of “abcdefghijklmnopqrstuvwxyz1234567890.-_”. These queries are conducted using 20 batches of SOAP requests with 77 “SearchGalRequest” SOAP commands in each batch except for the last request containing only 58.

During the gather_environment stage, the script attempts to determine which type of ZCS webmail client the victim is using. The script checks the user’s current URL to determine the client type being used, checking for certain indicators (shown in Table 2) to determine the client type. The corresponding value is then used as the payload when exfiltrating the client type.

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

As part of collection, the script attempts to harvest any emails not marked as “junk” from the last 90 days from the victim’s account. Emails are collected daily by an HTTP GET request to the URL path, “/home/~/?fmt=tgz&meta=0&query=date:-{DAY_OFFSET}d AND (not in:junk)”. The {DAY_OFFSET} value would be between 0 and 89 representing how many days ago the email was sent or received. To prevent redundant collection and exfiltration of emails, a variable with a name based on the email date being queried, using a format of zd_comp_YYYY-MM-DD, and value of true, is saved to the window.top.localStorage property. This variable is saved regardless of whether the email is successfully exfiltrated.

According to Mozilla documentation, if the user is not in a private browsing session, any data stored to localStorage does not typically expire. This means that if the user happens to execute the script again from the same computer, the script avoids attempting to re-exfiltrate previously captured emails. However, the script always attempts to pull any emails with a {DAY_OFFSET} of zero. In other words, the script always pulls emails sent or received the same day it is run. After email results are returned from the query for each day of email activity, those results are then passed to Flowerbed as described in the Exfiltration section.

The script also provides LAUNDRY BEAR with telemetry on any errors that occur during the collection process. This is accomplished by executing any collection or exfiltration code through helper functions that contain error handling logic. If an error occurs, a payload containing information on the error itself, the context of the error happening, and the stage in which the error occurred is sent to Flowerbed as described in the Exfiltration section below. For cases where the error occurs within a SOAP request, “:api” is concatenated to the stage value in the payload. If an error occurs during the batch SOAP requests that occur when collecting the GAL of the victim, the stage value will use a format of gather_gal:{VAL}:api. The {VAL} placeholder indicates which batch request, a number from 0 to 19, the error occurred in. Errors that occur during the password autocomplete interception process will use “gather_autocomplete_password:dom” for the stage value. Finally, if an error occurs when attempting to collect or exfiltrate a specific day’s emails, the stage will include which day the error occurred on, using the previously defined placeholder {DAY_OFFSET}, with a format of sendArchive:day-{DAY_OFFSET}.

Exfiltration

At the end of each stage in the collection process, the script attempts to exfiltrate acquired information to Flowerbed. The script primarily relies on two forms of data exfiltration: DNS [T1048.003] and HTTPS. Some information is exfiltrated over both the DNS and HTTPS channels.

Prior to exfiltration, a randomized 10- or 11-character alphanumeric string is generated as an identifier for the victim. This identifier is included in the URL of both the DNS- and HTTPS-based exfiltration.

DNS exfiltration

DNS exfiltration occurs through DNS A record queries. To ensure data exfiltrated through DNS is not corrupted when traversing through non-actor-controlled DNS infrastructure, Ulej maintains compliance with RFC 1035, Domain Names - Implementation and Specification, specifically accounting for the case insensitivity and subdomain length requirements. Base32 encoding is used to create a case-insensitive payload. Once the payload is encoded, a period (“.”) is added every 60 characters to ensure each subdomain is under 63 characters long. The script then creates a new image object sourced from a URL with the scheme defined in Figure 6. Any traffic involving DNS exfiltration will have “d-“ prefixing the victim identifier, and the subdomain immediately following indicates the type of information being exfiltrated.

Figure 6: Structure for information exfiltrated by DNS

When the script generates an image object, the browser tries to retrieve the complete domain of the URL specified as the source of the image. This triggers a DNS request sent to the actor-controlled server and processed by Flowerbed. Table 3 lists both the information exfiltrated via DNS and their corresponding data type identifiers in the DNS queries.

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

HTTPS exfiltration

Any information exfiltrated via DNS is also exfiltrated through HTTPS, as well as additional data including email content, contacts, attachments, and error logging information. By using Let’s Encrypt certificates, this group can quickly deploy new infrastructure and leverage encrypted HTTPS communications with valid server certificates when exfiltrating information from the victim’s environment. The HTTPS exfiltration capability only uses two HTTP content types, defined in Table 4. Traffic associated with HTTPS exfiltration will use the URL scheme shown in Figure 7.

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

Figure 7: Structure for information exfiltrated by HTTPS

Some of the data transmitted via HTTPS uses the standard JSON content type format. The script includes the information in a POST request to actor-controlled infrastructure.

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

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

The script transmits all HTTPS exfiltration not identified in Table 5 using the Octet-Stream content type as binary data. The POST requests for this method include a filename in the “X-Filename” header. Traditionally, developers use headers prefixed with “X-” to denote custom headers that do not follow a defined standard. The purpose of including this header remains unclear since the Catcher capability ignores the provided filename when saving the data. Table 6 summarizes the data exfiltrated in this format.

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

The script sends all exfiltrated data identified in Table 6 to the Catcher service exactly as received from the SOAP request in a JSON payload, except for email exfiltration. For email exfiltration, the script sends it as a GZIP compressed archive [T1560]. Although most of the exfiltration consists of valid JSON, the script still attempts to exfiltrate all information identified in Table 6 using the application/octet-stream content typing rather than application/json.

At the beginning and end of the collection and exfiltration activity, during the sendStartPing and sendFinishPing stages respectively, the script submits a POST request with a JSON payload to indicate that the script is starting or finishing execution. Throughout execution, the script also logs error events and send the logs using similar JSON payloads. The script sends the JSON in a POST request to the URL documented in Figure 2, using a URL path of “/v/p” and with a “subtype” key that shows which type of action it logged (start, finish, or error).

Catcher

Ulej exfiltrates information to Flowerbed to be handled by a service named Catcher. Catcher is a containerized Python application, running in Docker as part of Flowerbed, which is detailed in the Resource development section. It receives exfiltrated data and temporarily stores it, enabling its eventual transfer to infrastructure designed for long-term, secure storage.

Catcher acts as an HTTP server over port 8000 and a DNS server on port 53. As described in the Resource development section, the Flowerbed project uses an additional Docker container running an Nginx reverse proxy to enable HTTPS support. This reverse proxy uses a certificate generated by Let’s Encrypt and forwards all traffic with an SNI containing “*.i.*” to port 8000 within the Catcher container.

The DNS service can accept A, AAAA, MX, TXT, and CAA queries. For any MX, AAAA, or CAA queries, the server will always provide an empty response. The system only supports TXT records as needed to process Automatic Certificate Management Environment (ACME) requests, which enable the assignment of Let’s Encrypt certificates. If the server receives an A query, Catcher will always respond with the public IP address of the Flowerbed server.

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

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

The HTTP server typically responds with OK, except in cases where the path is “pixel.gif” when the response contains a 1x1 gif image with a SHA-256 hash of ef1955ae757c8b966c83248350331bd3a30f658ced11f387f8ebf05ab3368629. Like the DNS service, the HTTP service will only log entries when the domain found in the host header of the request follows the expected formatting as seen in Figure 6 and Figure 7. As the HTTPS exfiltration uses non-standardized binary and JSON-formatted payloads when exfiltrating to Catcher, Catcher will check the content type of the request. If the content type is set to “application/json”, Catcher encodes the data in Base64 and includes it in the JSON log entry written to disk. If the content type is set to any other value, Catcher leaves the Base64 payload in the JSON log entry blank and saves the payload to a separate file with the same filename as the JSON log entry with a “.bin” file extension. An HTTPS exfiltration event causes Catcher to save a JSON formatted log file to disk containing the following information from the HTTP request:

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

These JSON event log files and binary output files are then initially saved to the directory /root/hits/tmp and later moved to the /root/hits/ready directory once processed. This prevents incomplete files, which are still being uploaded to Catcher, from premature exfiltration from the server. Approximately every 60 seconds, a likely automated workflow establishes a Secure Shell (SSH) connection with the server hosting Flowerbed for a few seconds, almost certainly exfiltrating the data processed by Catcher to non-public-facing infrastructure. The command in Figure 8 also executes hourly to remove all files last modified at least two days ago from the /root/hits/ready directory.

Figure 8: Command used for automated directory cleanup

Response strategies

Mitigations

In many cases, by the time an organization identifies a compromise related to this campaign, numerous sensitive and proprietary emails have already been exfiltrated. The significant risk posed by this cyber threat emphasizes the importance for organizations that use ZCS and other similar webmail solutions to take proactive steps to mitigate this risk.

All organizations that use the ZCS webmail service should immediately prioritize ensuring that their ZCS is not running a vulnerable version. A patch for CVE-2025-66376 was released for both 10.1.13 and 10.0.18 versions of ZCS [D3-AH]. If immediate patching is not feasible, organizations should advise employees to use alternative mail clients to access email and avoid using the Classic ZCS webmail client until ZCS is updated to a non-vulnerable version [d3f:Isolate].

System administrators should closely monitor any Internet-connected ZCS or other email systems and the workstations that access those systems and promptly apply available software updates [D3-AH]. Administrators can maintain awareness of active vulnerability exploitation by referencing open source resources, including CISA’s Known Exploited Vulnerabilities Catalog and NCSC-UK’s Responding to active exploitation of vulnerabilities guidance.

Organizations should consider using a third-party authentication service that supports passkeys for authentication to mediate access to ZCS and other services that do not natively support passkeys. By doing so, organizations can work to eliminate the possibility of automated password collection from autocomplete or password reuse [D3-CH]. However, Application Passcodes may still be necessary and should be monitored closely.

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

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

Additionally, for organizations that can inspect the content of outbound HTTPS connections via break-and-inspect infrastructure, security teams should identify traffic matching the characteristics described in the Exfiltration section of this advisory.

Indicators of compromise (IOCs)

Flowerbed infrastructure

The following indicators have been attributed to use by LAUNDRY BEAR for their campaign targeting ZCS’s webmail service as of the publication of this advisory. (Disclaimer: Due to the frequency of operational structure changes by this group, these indicators are intended solely for historic attribution purposes. Some indicators, such as IPs, compromised emails, and domains, may be outdated, so organizations should check for current activity before acting on these IOCs.) Table 7 provides details about the server infrastructure used to host Flowerbed, and Table 8 lists the corresponding SHA-1 hash values for the Let’s Encrypt certificates used by that infrastructure [D3-IAA].

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

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

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

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

Phishing distribution

LAUNDRY BEAR primarily relied on ProtonMail for distribution of malicious email. However, as stated above, LAUNDRY BEAR’s more recent efforts likely have shifted to distributing the payload through previous victims.

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

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

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

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

Post-compromise artifacts

Currently, the script does not remove artifacts. This leaves additional opportunities to identify victims of this activity. While emphasis should always be placed on consistent monitoring of network traffic and endpoint activity, there are a variety of persistent artifacts described below that can be used to identify victims of this campaign.

This Ulej capability relies on creating a significant number of SOAP requests to collect account information for exfiltration. ZCS logs from these requests are stored, by default, in the /opt/zimbra/log/mailbox.log file [D3-PA]. A significant amount of SOAP request activity that aligns with what was described in the Persistence and credential access and Collection sections of this advisory could indicate a potential compromise. Specific examples of high-risk SOAP request activity might include:

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

While LAUNDRY BEAR uses the localStorage property to track what days had emails previously exfiltrated, defenders can use this property to identify victims of this campaign and determine the scope of exfiltrated information [D3-PA]. Review of the items stored in that property for an organization’s ZCS webmail client page on an endpoint device could indicate compromise if there are items named with a format of zd_comp_YYYY-MM-DD, as explained in the Collection section of this advisory.

While Application Passcodes have non-malicious purposes, in this case instances of these passcodes with the name “ZimbraWeb” are almost certainly malicious. The ZCS webmail application can support 2FA natively and does not require the use of an Application Passcode, so there is no reason that there should be one named “ZimbraWeb.”

In instances where organizations identify victims of this campaign, they should also examine the inbox of the suspected victim for the original phishing email [D3-MA]. If an email that has a payload exploiting CVE-2025-66376 is discovered, steps should be taken immediately to identify and quarantine other instances of emails with similar body content, senders, and subject lines to prevent further exploitation and exfiltration.

Remediation

In the event an organization identifies activity associated with this campaign, that organization should take steps to minimize further exploitation. The organization should consider requesting that employees minimize use of the ZCS webmail client until the organization updates to a patched version that is not vulnerable to CVE-2025-66376.

Organizations should use identifiers from the IOCs section of this report to identify any individuals compromised by this campaign and record the date(s) of compromise(s) to determine the scale and scope of emails exfiltrated.

All users from the organization should have all Application Passcodes and 2FA scratch keys revoked. Affected organizations should require all employees to change passwords in line with establishing minimum password strength requirements [CPG 3.B] and creating unique credentials [CPG 3.C], specifically noting that compromised employees might have had any password stored in a password manager exfiltrated.

Works cited

[1] Netherlands General Intelligence and Security Service (AIVD) and Netherlands Defence Intelligence and Security Service (MIVD). AIVD and MIVD identify a new Russian cyber threat actor. 2025. https://www.aivd.nl/site/binaries/site-content/collections/documents/2025/05/27/aivd-en-mivd-onderkennen-nieuwe-russische-cyberactor/Advisory+AIVD+en+MIVD+Public+report+on+new+cyber+actor.pdf

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

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

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

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

Footnotes

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

Acknowledgements

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

Disclaimer of endorsement

The information and opinions contained in this document are provided "as is" and without any warranties or guarantees. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring by the United States Government, and this guidance shall not be used for advertising or product endorsement purposes.

Organizations have no obligation to respond or provide information back to the authoring organizations in response to this joint advisory. If, after reviewing the information provided, an organization decides to provide information to the authoring organizations, reporting must be consistent with all applicable laws and policies.

Purpose

This document was developed in furtherance of the authoring agencies’ cybersecurity missions, including their responsibilities to identify and disseminate threats, and to develop and issue cybersecurity specifications and mitigations. This information may be shared broadly to reach all appropriate stakeholders.

Contact

United States organizations

National Security Agency
Cybersecurity Report Feedback: CybersecurityReports@nsa.gov
Defense Industrial Base Inquiries and Cybersecurity Services: DIB_Defense@cyber.nsa.gov
Media Inquiries / Press Desk: NSA Media Relations: 443-634-0721, MediaRelations@nsa.gov
Cybersecurity and Infrastructure Security Agency
CISA’s 24/7 Operations Center (contact@cisa.dhs.gov), or by calling 1-844-Say-CISA (1-844-729-2472).
Federal Bureau of Investigation
If you or someone you know has fallen victim to this campaign, file a complaint with IC3.
Defense Counterintelligence and Security Agency
DCSA Counterintelligence, Cyber Mission Center, Cyber Threat Operations Branch: DCSA.CI.CyberOps@mail.mil
Cleared Contactors (CCs) should contact their DCSA Counterintelligence Special Agent to report information pertaining to suspicious contacts or physical/digital efforts to obtain illegal or unauthorized access to the CC’s cleared facility/information, as required by 32 CFR 117.
Media/Public Inquiries: dcsa.quantico.dcsa-hq.mbx.pa@mail.mil
Department of Defense Cyber Crime Center
Defense Industrial Base Inquiries and Cybersecurity Services: DC3.DCISE@us.af.mil
Defense Industrial Base mandatory cyber incident reporting as required by 10 U.S. Code Sections 391 and 393 and Defense Federal Acquisition Regulation Supplement (DFARS) 252.204-7012 is submitted at https://dibnet.dod.mil
Media Inquiries / Press Desk: DC3.Information@us.af.mil
Naval Criminal Investigative Service
To report criminal activity impacting the United States Navy, go to www.ncis.navy.mil and click “Submit a Tip”

Dutch organizations

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

Australian organizations

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

Canadian organizations

The Canadian Centre for Cyber Security (Cyber Centre), part of the Communications Security Establishment, encourages Canadian organizations to report cyber incidents and to strengthen the security of their networking devices.
Report an incident or suspicious activity to the Cyber Centre by email at contact@cyber.gc.ca, online via the reporting tool Report a cyber incident - Canadian Centre for Cyber Security or by phone at 1-833-CYBER-88 (1-833-292-3788).

New Zealand organizations

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

United Kingdom organizations

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

Estonia organizations

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

Finnish organizations

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

French organizations

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

Italian Organizations

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

Moldovan organizations

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

Polish organizations

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

Appendix A: MITRE ATT&CK tactics and techniques

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

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

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

**Table 11: Initial Access**
Technique Title	ID	Use
Valid Accounts	T1078	This actor has used commercial datasets to acquire account credentials and gain unauthorized access to accounts. Additionally, this actor is believed to use previously compromised accounts to conduct spear phishing.
Trusted Relationship	T1199	The group sends malicious payloads to targeted individuals using previously compromised accounts that might have an established relationship with the target.
Phishing	T1566	The actors used spear phishing to lure users into opening malicious email.

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

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

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

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

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

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

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

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

Appendix B: MITRE D3FEND countermeasures

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

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

Smaller, smarter, safer: How to build agentic AI on the right foundation

Sat, 25 Jul 2026 18:55:52 +0200

When it comes to building an effective AI stack, context is king and power isn’t everything it’s cracked up to be.

“Smaller, smarter, safer — this is a bet our company has taken in how we deploy AI internally,” said Ricky Thakrar, head of sales and account management at Zoho, provider of a suite of popular cloud-based software solutions for sales, marketing, and finance.

“I’m on the business side, and so decisions made by our CIO and IT folks affect me directly, and my teams’ workflows and processes,” he added.

Speaking to a room of tech leaders at the CIO 100 Leadership Live New York event last week, Thakrar explained that every company wants the speed of AI-generated work wedded to the quality of human work, even though these two are diametrically opposed. No amount of model upgrades or spend will close that gap, so the only way forward is to architect your way out. Thakrar encapsulated this idea in a simple formula:

Smaller: Stop deploying maximum firepower on every task. Many tasks don’t need it.
Smarter: The system around the model decides more than the model does.
Safer: Verify at the point a mistake gets locked in, not just downstream of it.

He noted that organizations that win with AI won’t be those deploying the biggest, most powerful models or the most sophisticated architecture, but the ones that figure out that the model is the easy part and the right architecture is harder. That means understanding the hardest element, and the biggest differentiator, is building a human system that learns and compounds alongside agentic systems.

To get it right, organizations need to prioritize the context layer. The size of frontier models like the GPT series, Claude, and Gemini mostly exist to compensate for missing context, Thakrar explained. Without enough context, models need to be able to reason harder and infer more about what a user actually means because it doesn’t know the user’s account, process, or history. A rich context layer makes it possible for enterprises to run workloads on much smaller, lower-power models.

“The intelligence moves from the model into the architecture around it,” he said.

A steep learning curve

One of Zoho’s earliest AI agents was a churn management agent to help the account management team detect churn in customer subscriptions. So when a subscription became inactive, the agent would collect context from notes, meeting recordings, and Zoho’s data enrichment tool, then create a summary of reasons the account might have churned, and schedule a call.

“What happened was I got this churn agent a couple months later, already embedded in our CRM, and within a week my team no longer trusted that agent,” Thakrar said. “The reason is we forgot to collect one very key point.”

In Zoho’s CRM, when a customer buys a bundle of products, that bundle is represented as a single line item. That means the status of any products the customer may have previously purchased individually changes to inactive as they’re moved to the bundle. That’s not churn, but it was interpreted it that way. Zoho fixed it in the second version of the agent.

Then a new problem arose. Many potential customers first purchase Zoho products as pilots or sandboxes. As those customers move from pilot to live instance, they close down the pilot versions. And again, the CRM would record that as subscriptions going inactive.

“The trust deteriorates again because everyone got excited for version 2,” Thakrar said.

Sometimes, a certain product might not be the best fit for a customer and Thakrar’s team will suggest the customer move to another product. That’s deliberate churn, not a churn risk.

“You may have a similar story like this where the agent sounds so good, it’s going to do something quick and add value, but it’s missing context from the account managers, and there are so many more pieces we’re still building out,” Thakrar said. “It’s been almost a year and the problem I have is my team still doesn’t trust it. They’ll see [a message from the agent] and go out and do all the research anyway to make sure it gave the correct answer.”

The team is more on top of potential churn, though, but the promised productivity gains have yet to materialize because the agent has to earn back lost trust due to a lack of context.

“My goal for this year is having an AI-assisted customer journey from sales to account management where the handoff is clean, the context flows, and every piece of information we gather about a customer is weighed, identified, and coached so the sales team can close more deals,” he said.

Zoho’s early experience with agents has led to the idea that constrained, context-rich, deterministic architectures consistently outperform expensive models bolted onto fragmented systems. It all comes down to three pillars: routing, harness, and specialization.

Routing

Routing is about sending workloads to the proper model for the job, which entails providing enough context to a given task that a small, cheap model can handle it without the need for spare reasoning capacity to fill gaps.

Frontier models are expensive and companies can burn through a year’s budget worth of tokens in months. But most tasks can be handled by much smaller, more constrained models at a fraction of the cost.

“You don’t always have to pay the frontier guys for every task,” he said. “We’ve observed with some clients that we could save them 95% with a 3 billion parameter model.”

Harness

An AI agent harness is the software infrastructure scaffolding around an LLM that differentiates an agent from a chatbot. It’s what enables an agent to act on tasks rather than simply respond to prompts. A model reasons through a problem and decides what to do about it. The harness connects the model to the tools, systems, memory, guardrails, and execution environments required to perform the actions determined by the model. The term is frequently used more or less interchangeably with orchestration layer.

“It’s the process around the model, which matters way more than the model itself,” Thakrar said.

In benchmark tests, a superior harness on a less powerful model produces better results than an inferior harness on a much bigger model.

For the best results, Thakrar said, it’s essential to understand the deterministic and non-deterministic elements of a given workload, and build that into the architecture. Machines can read, organize, and validate, and they excel at deterministic tasks. Humans, on the other hand, are exceptional at non-deterministic tasks like judging, synthesizing, and deciding.

Those non-deterministic tasks in a process are the ideal point for AI agents to incorporate a human in the loop, what Thakrar calls human harness. He pointed to a stakeholder mapping agent Zoho built for sales as an example, which takes the context of an initial meeting and third-party enriched data like a LinkedIn profile, weighs probabilities, and makes an educated guess about the stakeholder map.

“The initial goal was just to eliminate that task completely from the human workflow,” he said. “The stakeholder map is done, it’s in the folder, and you can look at it.”

But the agent would struggle to capture nuance. The meanings of titles in organizations always vary, and the politics and dynamics of any given meeting can be difficult for an AI agent to discern. Rather than keep feeding the agent data to try to make it intelligent enough to make those determinations, it was simpler and more efficient for the agent to create a proposed stakeholder map and hand it over to a human who could make changes and explain why those changes were necessary.

Ultimately, Thakrar said the agent still saved human team members time because the stakeholder map was usually pretty close, and the corrections also helped the model grow smarter by adding richer context.

Specialization

Specialization is transitioning a process from testing on a frontier model to production on a much narrower, smaller model. Once you’ve proven that an agent can do a job well, you want to stop paying master-craftsman rates to keep doing that one job well.

Specialization is all about capturing your subject matter experts’ best judgement and pattern recognition to build an open-weight, open source, trained, and fine-tuned model that can be deployed in your own data center.

“The true enterprise bet is to keep that orchestration layer, which is your IP and knowledge, in house,” Thakrar said. “You don’t want to host that on someone else’s model. The goal of everyone in enterprise should be to run, train, and host their own models.”

The new value architecture of the AI-native SaaS era

Sat, 25 Jul 2026 18:55:51 +0200

The traditional methods of measuring success no longer tell the full story. Here’s what should replace them — and why.

In brief:

AI is transforming software as a service (SaaS), and the old ways of keeping score no longer apply.
Smart companies are evolving new metrics that provide deeper insight into how AI-native software is performing in a new marketplace.
These changes impact everything from pricing to valuations.

The transformation of the software-as-a-service (SaaS) industry toward AI-native operating companies is rapidly changing the unit of value across the industry.

The traditional metric of seats — which measured access — is rapidly giving way to credits designed to measure work performed. This evolution is upending the industry in multiple ways, impacting everything from pricing to enterprise valuations.

While many companies still cling to seat-based metrics to measure growth, efficiency and durability, the future is likely to be one in which companies utilize a credit-centric metrics framework, with seats and outcomes as the bookends of a spectrum.

Why do software companies need new metrics?

Why the rethink, and why now? There are five major forces that are driving this shift:

The unit of value is changing. Seats measured who could access software, and credits measure what the software actually does. But in an AI-native world, agents don’t have seats; they have workloads. Over the past 18 months, every major SaaS platform has moved to some forms of credit or consumption unit.
The cost of goods sold (COGS) is exploding. AI inference adds real per-unit costs that scale with usage. In an AI-native world, software companies can’t scale to infinite users at near‑zero marginal cost as before.
Buying is moving up the org chart. AI-native applications shift purchasing to higher-level operators — such as line-of-business leaders or chief operating officers — which expands the market from software budgets to labor budgets. And because AI agents replace services as well as software, the total market opportunity is 3x to 10x larger than traditional SaaS.
Time to value (TTV) is collapsing. With AI-native tools, customers start seeing meaningful results in weeks rather than quarters. Onboarding and setup are fast, workflows are pre-built, and there’s no need for extensive customer success or professional services — dramatically reducing implementation time and costs.
Retention is bifurcating. AI forces clarity in a way that traditional SaaS couldn’t. Products that can provide value become even “stickier” and retain customers. Those that don’t churn faster. In an AI-native marketplace, the middle disappears.

How this shift is impacting pricing

Given how AI-native software is transforming the market, the shift to more variable pricing options is inevitable.

Seats won’t go away completely. Subscription pricing based on the number of users is stable and predictable and will continue to work for some customers. Tokens — the use of pass-through pricing for underlying compute — will fit those customers where the AI feature is commoditized or the buyer wants transparency into costs.

Credits will likely become the dominant architecture because they provide a simple metric for both customers and providers. The vendor sets the conversation ratio between credits and underlying compute, shielding the customer from inference cost details. Credits are easy to understand and can be packaged into annual contracts for multiple features and products.

Finally, the industry will likely see some move toward outcome-based pricing for results such as resolved tickets, recovered revenue or qualified leads. This strategy will mostly be limited to verticals where it is easy to prove AI impacted the result.

Where a software vendor sits on this spectrum is a signal of differentiation and pricing power. Credits are where most defensible AI-native businesses are landing because they balance customer predictability with vendor margin control.

How AI upends classic SaaS metrics

When SaaS was in its infancy, companies settled on key metrics designed to answer a small set of core questions. Are we growing? Are customers using the product? Are we retaining and expanding accounts?

But as AI upends software itself, it is also requiring companies to adopt new metrics to track success. These new metrics fall into three primary buckets, rebuilt around the pricing spectrum described earlier and the trend toward credits as the primary frame:

Revenue composition

Committed credit annual recurring revenue (ARR) vs. burndown ARR: Measuring the credits sold on annual commitment vs. those consumed and replenished. This is the single most important split for valuation. Committed credits behave like subscription and burndown behaves like usage.
Credit utilization rate: The percentage of purchased credits consumed per period. This is a leading indicator of renewal sizing.
Credit burn velocity: How fast is a customer consuming their credits, and is that consumption increasing or decreasing quarter over quarter? This metric predicts expansion or contraction before it shows up in ARR.
Effective price per credit: The real revenue per credit after discounts, overage and rollover, which can detect revenue leakage and help companies set smarter guide rails.

Margin reality

Credit margin: The gross profit the company earns per credit after subtracting inference costs. This is the core economic unit for AI-native, usage-based businesses — the replacement for gross margin per seat used in SaaS.
Inference-adjusted gross margin: By carving out AI inference costs separately in the P&L statement, you can see true AI margins, avoid hiding deterioration inside blended SaaS margins, and clearly distinguish AI economics from legacy SaaS economics.
Compute leverage ratio: This metric measures how efficiently the business converts compute spend into revenue. It shows whether your AI margins are improving as you scale.
AI-adjusted “Rule of 40”: This updated metric recalibrates the traditional growth and profitability benchmark to account for AI’s lower gross margins and variable inference costs, giving a more accurate picture of business health for AI-native companies.

Behavioral and value signals

Time-to-first outcome: Replaces traditional onboarding metrics. Tracks how fast a customer reaches their first measurable result.
Adoption: AI-native adoption is measured by workflow penetration and active agent density, not seat count. As AI replaces human-driven usage, the unit of adoption shifts from people to automated workflows and agents.
Net credit retention (NCR): Credit-volume retention across the customer base, tracked separately from net recurring revenue to avoid price-change impact.

Along with these new metrics, the industry’s transformation is prompting companies to retire or recalibrate old SaaS measures, including per-seat ARR as a primary key performance indicator (KPI), traditional magic number calibrated to subscription dynamics, unadjusted Rule of 40, customer success metrics tied to human touchpoints, and blended gross margin without AI COGS carve-outs.

What does this mean for enterprise value calculations?

As the internal metrics of success change, so do the ways the investment community measures growth and long-term viability.

Increasingly, a company’s valuation multiple depends on whether its revenue behaves like committed subscription ARR or volatile usage ARR, and the commit‑to‑burndown ratio is the metric investors use to decide where the company fits.

For example, a business with 80% committed credit ARR could trade closer to subscription comps and one with 80% burndown could trade closer to usage comps even though both have the same types of customers. Being able to proactively explain the commit‑to‑burndown mix can help companies avoid undervaluation.

In addition, utilization is expected to replace net promoter scores and seat usage as the primary predictor of churn or expansion. Low utilization guarantees downsizing at renewal, so companies must track utilization cohorts the same way SaaS tracks logo retention cohorts today.

We’re also seeing an inversion of the operating model, with R&D and COGS moving up the P&L and sales and marketing (S&M) and customer success (CS) moving down or sideways. The net operating leverage profile is structurally different from classical SaaS, and the cost-to-scale curve looks different too.

Finally, credit margin engineering is a hidden value-creation lever. The gap between price per credit and cost per credit is set by the software vendor and can be optimized. Most operators have barely started managing this rigorously, and the ones who do will pull away on margin.

What this means for leaders, boards and investors

The shift from classic SaaS metrics to new AI‑native measures isn’t cosmetic. It represents the seismic change the industry is experiencing as AI matures and transforms products and organizations.

While these metrics — and perhaps others yet to be determined — may evolve over time, there is no doubt they are already changing how AI companies allocate capital, price products, incent sales teams, evaluate performance and communicate with investors.

It’s important to remember that SaaS metrics were practical tools for a specific era of software. As that era draws to a close, winning companies will choose new metrics that shape behavior and drive smart decision-making.

The views reflected in this article are the views of the author and do not necessarily reflect the views of Ernst & Young LLP or other members of the global EY organization.

This article is published as part of the Foundry Expert Contributor Network.
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Stop asking AI nicely: Here’s how to get work-ready results every time

Sat, 25 Jul 2026 18:55:51 +0200

Over the past few years, I have learned that basic prompts produce inconsistent, hallucination-prone results that no executive would trust in production. What turned the tide was my move to advanced prompting techniques. These weren’t theoretical experiments; they became a practical foundation for reliable, measurable outcomes. I want to share the techniques that consistently delivered the biggest gains in my projects, complete with real before-and-after examples, copy-paste templates, lessons from failures and guidance on when to evolve beyond prompting to agentic systems.

Why advanced prompting still matters in enterprise settings

Sophisticated prompting remains essential for control, reliability and compliance. If you “ask nicely” and hope for the best, you need deterministic behavior, auditable reasoning and minimal risk of hallucination. Here’s what worked for me.

1. Chain-of-Thought (CoT) and its variants: Unlocking step-by-step reasoning

The problem: Models would jump to conclusions on complex analysis tasks, especially involving data interpretation or multi-step logic.

What I did: I started explicitly instructing the model to “think step by step” and show its reasoning.

Before (basic prompt): “Analyze last quarter’s sales data and recommend three actions.”

After (CoT prompt):

“You’re a senior business analyst. Analyze the following sales data step by step: [data]. First, identify the key trends. Second, calculate the rates and anomalies. Third, link findings to business context. Finally, recommend the three prioritized actions with expected impact. Explain your reasoning at each step.”

Results: Accuracy and depth improved dramatically.

Variants that worked well: Self-consistency. I ran the same CoT prompt multiple times and took the majority consensus. This reduced variability significantly.

Template you can use:

You are [expert role]. Solve this problem by thinking step by step.

[Task or question]

For each step:

1. State your observation or calculation.

2. Explain the implication.

3. Proceed only when confident.

Final answer in this format: [structured output]

2. Tree-of-Thoughts (ToT): Exploring multiple reasoning paths

For truly complex decisions such as resource allocation or risk assessment, linear CoT isn’t enough. Tree-of-Thoughts lets the model generate and evaluate multiple branches.

Example: I was helping a client evaluate three potential vendor platforms for an AI deployment. A standard prompt gave a superficial comparison. With ToT

Prompt Snippet:

Explore three different reasoning paths for selecting the best vendor platform:

Path 1: Focus on cost and scalability.

Path 2: Focus on security, compliance and integration.

Path 3: Focus on innovation and long-term roadmap.

For each path, evaluate pros/cons against our requirements [list].

Then, compare the paths and recommend the strongest overall option with justification.

Outcome: The model surfaced nuanced trade-offs (e.g., one vendor had superior security, but higher integration cost).

When to use: Strategic planning, troubleshooting or scenarios with high uncertainty and multiple viable approaches.

3. ReAct (Reason+ Act) and prompt chaining: Moving toward agentic behavior

One of the biggest leaps I have noticed comes from combining reasoning with tool use and chaining prompts.

ReAct example: (used in data analytics workflow)

You are an AI analyst with access to tools. For the query below:

1. Reason about what information you need.

2. Choose the appropriate tool or action.

3. Observe the result.

4. Repeat until you can answer confidently.

Query: [user request]

In practice, I chained this with retrieval tools. One automated quarterly compliance reporting; the system reasoned about required data, pulled relevant records, validated them, and generated the reports.

4. Meta-prompting and self-reflection: Letting the model improve itself

Use the model to refine its own prompt. This is a huge time-saver.

You are an expert prompt engineer. Improve the following prompt for clarity, structure and effectiveness with [target model]. Make it more precise while preserving intent.

Original prompt: [paste]

Provide the improved version and explain your changes.

Self-reflection loops (asking the model to critique its own output and revise) are a game-changer for content generation and code-review tasks.

5. Multimodal and structured output techniques

With vision-enabled models, I started combining text with images (e.g., uploading architecture diagrams or dashboards).

Tip from experience: Be extremely specific in describing what the models should focus on.

Best practices I learned the hard way

Start simple, then layer complexity: Over-engineered prompts from Day One usually backfire.
Model specific tuning: Some models respond better to XML delimiters; others to explicit reasoning.
Evaluation and versioning: Treat prompts like code if you track versions and run automated evals.
Security guardrails: Always include instructions against prompt injections and respect data boundaries.
When to stop prompting: For repetitive, high-stakes workflows, move to full agents or an orchestration framework.

Final takeaways for technical leaders

Advanced prompt engineering has now become a core competency for anyone responsible for enterprise AI outcomes. Start by picking one technique and apply it rigorously to a real business problem. Document before/ after and you will notice why it’s worth mastering.

The field continues evolving towards more automated and agentic systems, but the ability to precisely direct AI reasoning remains foundational.

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How to navigate the AI talent wars

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

Cloudflare recently beat Q1 2026 earnings. Revenue up 34% year over year. EPS ahead of consensus. Full-year guidance raised. Then, in the same breath, they announced 1,100 layoffs, 20% of the company. CEO Matthew Prince’s explanation: “The way we work at Cloudflare has fundamentally changed.”

Block did the same thing. Beat guidance, raised outlook, cut 4,000+ jobs. Both framed it as architecting for the AI era.

This is not a contradiction. This is the new math boards are running. And if you’re a CIO who hasn’t started running it yourself, you’re behind.

The benchmark has moved

AI-native companies have quietly reset what “efficient” means for a technology organization. Midjourney generates over $500M in revenue with roughly 160 employees, over $3M per head. Anthropic hit a $14B annualized run rate in early 2026 with fewer than 3,000 employees. Across the top AI-native startups, the average revenue per employee is $3.48M, nearly twelve times the traditional SaaS benchmark of $300K.

Boards aren’t comparing you to your 2019 self anymore. They’re comparing you to Anthropic.

This is the pressure Cloudflare and Block are responding to. They’re not cutting people because the business is struggling. They’re cutting because investors have internalized a new denominator. Headcount is no longer a proxy for capacity; it’s a liability on the efficiency ratio.

For CIOs, this creates a hiring problem that looks nothing like the cloud or mobile talent gaps of the past decade. Those gaps were about volume: hire 100 cloud engineers, absorb the cost, build the capability… This one is about density; you’re not looking for 100 people. You’re looking for 10 who can deliver what 100 couldn’t, and justify $1M or more in value per seat.

Finding bodies to fill seats has never been easier. Finding people who operate at that level of leverage is a different problem entirely.

‘Acqui-hires’ are a shortcut with a hidden cost

Companies have figured out that recruiting AI-native talent one by one is too slow and that it’s faster to buy a team. Google’s acquisition of the Windsurf founders, Meta bringing in the Scale AI team, Accenture’s string of AI-focused acquisitions: these are acqui-hires dressed up as M&A. The premium on experienced AI talent is high enough, and the urgency real enough, that organizations are skipping traditional hiring loops entirely and buying their way in.

I’ve been on the other side of this. My company, MadKudu, was acquired by HG Insights specifically to bring AI-native capability into an established enterprise business. HG needed change agents who had already figured out how to build and ship in this new era, not just people who’d read about it. That’s the thesis behind most of these deals.

But there’s a cost that doesn’t show up in the acquisition price.

AI-native teams are fast because they operate with a different set of defaults: full access to tools, minimal governance layers, the ability to experiment and ship without a six-week approval cycle. That operating model is not a perk; it’s the fundamental mechanism. It’s why a team of 10 can do what an enterprise team of 100 can’t.

When you acqui-hire that team and then slot them into your existing approval processes, you’ve bought the people and killed the engine. The change agents you paid for become change-frustrated. The attrition that follows is expensive and predictable.

The harder realization: acquiring an AI-native team means accepting how they work. That requires deliberately carving out space for them to operate differently, not just tolerating it but institutionalizing it. The acquisition is an organizational change program, not just a hiring event.

The CIO’s real problem

The governance stack most enterprise organizations run was designed for a headcount world. Every tool vetting cycle, every vendor review, every security approval was calibrated assuming you were managing a large team where consistency and control were the primary objectives.

That calculus breaks when your goal is talent density. The same approval processes that protect against data leaks are now the reason your best people can’t do their best work. When it takes six weeks to approve a tool that your competitor’s team is already shipping with, you’ve traded velocity for the perception of safety.

The practical fix is structured experimentation: clear guardrails, defined boundaries, but explicit permission to try tools before deciding whether to roll them out broadly. Gating everything prevents you from ever discovering what 10x productivity looks like.

The skills inventory question is also more nuanced than it sounds. Job titles won’t tell you where the leverage is. You need to map the actual tasks within each function and assess which can be automated or augmented with AI. That’s where you find the people who, with the right tools, become your $1M/employee talent, not because you hired differently, but because you enabled better.

This is also where the build-versus-buy question gets genuinely tricky. As AI reshapes how products are built and delivered, your internal operating model — how you work, how fast you ship, how you use data — is becoming core IP. Outsourcing delivery means outsourcing the part of the organization where your competitive advantage is now being built.

Closing the gap without slowing down

The AI talent wars are not primarily a recruiting problem. They’re a rethinking of what organizations are supposed to look like.

Boards have a new benchmark. Cloudflare, Block, Amazon, Meta and others have already started restructuring to meet it, publicly, painfully, even while beating their numbers. The question for CIOs isn’t whether this pressure arrives; it’s whether you’re ahead of it or behind it when it does.

The organizations that navigate this well won’t win by outbidding competitors for a handful of elite engineers. They’ll win by designing operating systems that amplify the leverage of the talent they do have, by enabling their best people rather than constraining them, and by treating AI fluency as a core organizational capability rather than a niche specialization.

Talent density is the new headcount model. The sooner your governance, your tooling and your board conversations reflect that, the better positioned you’ll be when the next efficiency report lands.

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Why I changed how I pitch AI: It’s no longer about saving money, but managing tokens and adoption

Sat, 25 Jul 2026 18:55:49 +0200

I have worked alongside enterprise technology for more than 30 years and watched AI evolve from a lab experiment into the modern boardroom’s core focus. However, the last few years of implementing AI alongside our customers have delivered our most profound reality checks.

The initial hype has faded, leaving CIOs to drive real enterprise value. Based on my experience implementing Google, OpenAI and Anthropic technologies, here are the fundamental, technology-agnostic lessons every leader must anchor their strategy around.

AI as a leadership multiplier

The most common tactical error we see is treating AI as an isolated technology project. What I have observed among our customers is that true success does not come from organizations that define a standalone “AI strategy,” but rather from those leaders that integrate AI into their business strategy.

When our customers isolate AI and define an AI strategy, it inevitably treats it like a “technological toy” to experiment with. This approach yields fragmented, orphaned initiatives that fail to scale because they are fundamentally disconnected from their core corporate objectives. What I learned is that AI is not the ultimate destination; it is a powerful catalyst. We have replaced “What can AI do for our customers?” with a more strategic question, “How does AI accelerate their existing business goals?”

Think of AI like electricity. No modern corporation designs a standalone “electricity strategy.” Instead, all companies route it invisibly across the entire organization to illuminate offices, power production lines and drive communication. AI must be woven into the enterprise fabric in the exact same way, acting as an underlying utility that supercharges your existing operational model.

Integrating AI into the broader business strategy also dictates how we measure success. It forces a shift away from short-term tech vanity metrics and anchors the technology into a long-term roadmap.

When AI remains trapped within the IT department of our customers, we notice that it is relegated to a mere “software experiment.” To become a true competitive advantage, we observed that AI requires intense cross-functional orchestration. This perspective does not diminish the merit of the technical team; their expertise is fundamental for establishing the architecture, data governance and tools your enterprise requires. However, while IT builds the foundational infrastructure, it lacks the organizational authority to decide what should be built on top of it. Only the CEO or the owner of the company can step in to ensure AI leaves the “toy project” phase and integrates into the DNA of the organization.

The requirement for top-down, executive ownership stems from three critical realities observed in the field:

Silo-smashing and data collaboration: True enterprise AI is data-hungry and that data lives across disparate business lines, finance, operations, marketing and customer service. Only the CEO possesses the cross-functional authority to demand that data silos be dismantled.
Cultural transformation and fear mitigation: AI triggers widespread anxiety over job displacement across all industries and hierarchies. When relegated to an “IT project,” resistance spikes as teams view it as a threat to their livelihoods. When I saw the CEO lead this cultural shift directly is when I noticed the best results.
C-Suite education and strategic alignment: The mandate for AI capability cannot just be delegated downward; the transformation must begin at the very top. I have conducted more than 70 presentations for the Board of Directors and C-Level teams. These people need to be actively educated not on technical code, but on specific business use cases, return on investment (ROI) frameworks and how AI resolves core organizational bottlenecks.

PwC’s data found that only 12% of enterprises have achieved both cost and revenue benefits from AI. Those elite 12% succeeded precisely because their CEOs embedded AI extensively across strategic decision-making and cross-functional workflows. AI is simply too disruptive and too critical to be left exclusively in the hands of technical experts. If AI is not on the CEO’s weekly agenda, it is fundamentally missing from the company’s true strategy.

AI as a new operational framework

Traditional IT systems have operated on strict algorithmic certainty: if you input a specific set of data, the system executes an immutable line of code and guarantees the same, predictable output every single time.

AI completely breaks this paradigm. Because modern AI is built on probabilistic models, it does not execute static formulas; instead, it predicts the most likely correct response based on mathematical probabilities. This means that AI solutions carry an inherent, small percentage of uncertainty and variability. A prompt entered today might yield a slightly different, though contextually valid, output tomorrow.

Executive leadership and organizational cultures must be actively educated to accept and navigate this fundamental shift. Traditional quality assurance frameworks for software are designed for a 100% success rate. Applying this rigid standard to AI will paralyze your initiatives, keeping 80% of your projects trapped eternally in the pilot phase. This happened to us in a food and beverage company in Latin America a couple of years ago. After this experience, we started to include conditions in our contracts that tolerate statistical margins of error and still define the project as a success.

In terms of cost calculation, we had to teach CIOs and business managers to forget the monthly subscription model for AI and learn to manage the primary unit of exchange in modern AI: the token.

To understand AI costs, executives must understand how large language models process data. AI models do not read full words; instead, they break text, images or code down into “pieces” called tokens. As a baseline, every 100 words process as approximately 130 to 140 tokens. Because the major AI providers use the token as their currency, your business is billed dynamically based on the exact volume of tokens consumed by every query submitted (input) and every response generated (output).

Many leaders believe AI costs are fixed due to flat-rate enterprise tiers ($25–$30/user). This is a temporary illusion. These venture-capital-subsidized rates mask true operational costs and come with dynamic usage limits. Modeling long-term ROI on them guarantees a severe budget shock when true consumption pricing takes over.

The solution is not to halt AI adoption; doing so means losing your competitive edge. Instead, the cost per token must cease to be treated as a technical footnote relegated to the IT department. It must be elevated to a core business variable.

Risks in the AI adoption model

Since the beginning of the AI boom, I have seen all our customers making a critical tactical error that could cost them heavily in the medium term: they are focusing only on operational efficiency (reducing costs with AI).

I have observed that an alarmingly high percentage of companies remain trapped in pilot phases focused exclusively on short-term cost reduction. Bain & Company’s global Automation and AI Pathfinder Survey found that the largest share of companies measuring their AI initiatives (exactly 40%) realized cost reductions of 10% or less, heavily missing their internal targets. Our customers are putting too many resources and effort into marginal financial gains and in doing so, they are jeopardizing their most valuable assets: service quality, resilience and customer trust.

Utilizing AI solely to slash headcount or cut operational corners is a dangerous trap that introduces severe field liabilities. A financial service organization in Latin America announced that they saved $1 million in customer support by replacing humans with AI chatbots. However, the mid-term reality revealed a different story: a damaged brand reputation due to AI errors and an influx of frustrated clients fleeing because the automated system cannot handle special cases.

Putting a company on an extreme AI diet might make it look leaner on next quarter’s financial statement, but over-indexing on cost-cutting will ultimately leave the business too weak to compete when market dynamics shift. We are now inviting our customers to change the question from “How much money will AI save us?” to “How will we leverage AI to exponentially increase the long-term value of our enterprise?”

Deploying enterprise AI is a marathon, not a sprint, and the terrain changes with every mile. The organizations that thrive in this next era will be those that transition from fascination to discipline, treating AI not as a magic bullet for immediate savings, but as a core capability that demands rigorous governance, architectural foresight and cultural maturity. Navigating this shift requires moving past the theoretical hype and anchoring decisions in raw, field-tested reality.

As we continue to deploy these technologies across industries, the blueprint for success is being rewritten in real time. Let’s keep this conversation going as we map out the future of business intelligence together.

This article is published as part of the Foundry Expert Contributor Network.
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Model Context Protocol is going stateless to make scaling simpler

Sat, 25 Jul 2026 18:55:48 +0200

Model Context Protocol (MCP), the emerging standard for connecting AI models to external tools and enterprise data, is undergoing its biggest architectural overhaul yet.

The latest release candidate, scheduled for release on July 28, removes protocol-level sessions in favor of a stateless architecture, a change which industry experts say is intended to make MCP easier to deploy across standard cloud infrastructure as enterprises move AI pilots into production.

“The session-based model made sense when MCP servers were local processes on a developer’s laptop. In production, it became an operational tax,” said Muskan Bandta, cloud associate at ZopDev.

“When your infrastructure team asks whether MCP services can scale like other cloud applications, the answer used to be ‘not quite.’ With the move to a stateless architecture, the answer is now yes,” Bandta added.

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

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

This transition to a stateless design goes beyond simplifying infrastructure by fundamentally changing how AI applications manage and share context across tools, according to Amit Jena, AI development manager at IT consulting firm Kanerika.

Instead of keeping application state hidden inside protocol sessions, the new design makes it explicit, allowing AI models to access, reason over, and pass that information between tools, giving developers greater control over how context is preserved and shared across tools, Jena said.

It should also make AI workflows more portable, resilient, and easier to orchestrate across distributed environments, he said.

MCP’s new features

Other changes to MCP include the addition of a Multi Round-Trip Requests (MRTR) mechanism that changes how AI agents request additional information they need to complete a task.

Instead of relying on a persistent connection between the client and server throughout the interaction, the new mechanism lets the server request additional input through a standard request-response exchange before continuing the task, Jena said.

Routable transport headers, another addition, enable API gateways and other networking infrastructure to identify and route MCP requests without inspecting their contents.

They reduce processing overhead, lower latency, and let enterprise teams enforce routing, rate-limiting and security policies more efficiently using existing API management infrastructure, Jena said.

MCP is also getting an updated authorization framework built around OAuth 2.1 and OpenID Connect; interactive MCP Apps; and deterministic caching of tool and resource listings to improve LLM prompt-cache hit rates, potentially saving on token costs.

Rebuilding the trust boundary

The MCP release steering committee also decided to deprecate some legacy features, including Roots, Sampling, Logging, the older HTTP+SSE transport and Dynamic Client Registration, although these will continue to work in this version and any other released over the next year.

The deprecation of Sampling is likely to have the biggest impact because it changes who is responsible for interacting with foundation models, said Jena.

“Sampling let MCP servers invoke the LLM through the client, which meant the server had a callback path into the model without owning that connection. Deprecating it means rebuilding that trust boundary,” Jena said. “Your server now calls the model provider directly. That changes your network architecture, your auth model, and depending on how you’ve built cost attribution, your billing flow.”

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

Updated MCP SDKs

To accompany the protocol update, there are updated MCP SDKs for Python, Typescript, Go, and C#. These support both the old and new protocol versions, so new clients can continue communicating with older servers, while updated servers will also support older clients, reducing the risk of immediate disruptions.

That backward compatibility should make the transition largely incremental, except for enterprises that built custom infrastructure around MCP’s earlier session-based architecture, Bandta said.

Identifying and auditing those session dependencies may not be easy, Jena warned.

“Session management complexity tends to be hidden across multiple layers — the gateway config, the deployment scripts, the monitoring dashboards. The code change is small; finding everywhere the assumption lives is what takes time,” he said.

This article first appeared on InfoWorld.

Getting a grip on shadow tokens and AI blowouts

Sat, 25 Jul 2026 18:55:48 +0200

Four months of Claude Code — that’s all it took for Uber to burn through its entire annual budget for AI. Token after token, engineers embraced the platform with few control mechanisms tying costs to outcomes. The result was a budget runaway and a clear case study in how limited oversight snowballs into an AI blowout.

This is a phenomenon I like to call “shadow tokens” — AI credits paid for by the company but largely invisible to decision-makers. Too many engineers have the final say over how much they consume and, therefore, what it costs. This all-you-can-eat attitude is part of the reason why Microsoft is reportedly winding down many internal licenses across key engineering teams and why one in five organizations is missing its AI spend forecast by more than 50%.

And the trend is only accelerating. By 2028, Gartner predicts that AI coding costs (driven by this kind of ungoverned consumption) will be as much per developer as the salary companies pay that person.

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

Going forward, CIOs need to thread the AI needle between governance that encourages transparency and reasonable spend without stifling innovation.

When shadow tokens result in real costs

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

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

According to Deloitte, only 21% of organizations deploying agents have a mature governance model, a real concern because they’re token-eating machines. This is what was happening at Uber — Claude Code in agentic mode was autonomously reading codebases, planning changes across dozens of files and opening pull requests. Each step quickly adds up, with Anthropic’s own documentation noting that agents consume approximately seven times as many tokens as standard sessions.

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

Shifting the culture from usage to yield

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

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

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

Stopping token waste before an AI blowout

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

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

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

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

This is a conversation teams need to have now. Anthropic just ended flat-rate pricing for programmatic workloads from June 15. Now, agents, continuous integration pipelines and automated workflows draw from a dedicated monthly credit pool billed separately from the subscription. Once that pool is exhausted, agent tasks either stop entirely or overflow to extra billing. Work can either get very expensive or grind to a halt for teams that aren’t prepared.

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

This article is published as part of the Foundry Expert Contributor Network.
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5 endpoint blind spots your EDR/XDR was never built to see

Sat, 25 Jul 2026 18:55:47 +0200

In August 2025, 126 malicious packages landed in the npm registry. Even after the community caught the initial wave, 80 of these hidden backdoors remained actively listed.

That was enough. Over 86,000 downloads. Malicious code in PhantomRaven, packages running in the production systems of Fortune 500 companies worldwide. And throughout the entire window, not a single EDR/XDR alert.

This happened because the attack surface has expanded to a layer EDR/XDR was never designed to see: VS Code extensions, local MCP servers, and rogue AI coding assistants that inherit your engineers’ valid credentials to steal data at machine speed.

To eliminate this structural vulnerability, Palo Alto Networks acquired Koi, an AI-native developer security product engineered for proactive, precision enforcement. Below we compiled a 2026 CISO checklist you can use to audit your environment and see how Koi automates each defense from day one.

#1. Gain real-time visibility into shadow AI & extensions

Your existing asset management tracks binaries and installers, but it cannot see local VS Code extensions, MCP servers, or ad-hoc Python scripts running on developer endpoints. This visibility gap was recently exposed by the MaliciousCorgi campaign, where two marketplace extensions with 1.5 million combined installs silently harvested every file a developer opened. Neither triggered any detection because they were not binaries, not executables, not anything your inventory was built to flag. To counter this, Koi closes the gap by analyzing what extensions actually do after installation, exposing hidden data-harvesting channels running inside your active workspace.

#2. Distinguish between human and autonomous agent behavior

When a rogue AI agent exfiltrates your proprietary source code, it uses a developer’s valid credentials during normal working hours, making the session look entirely legitimate to standard XDR baselines. Moving beyond static permission lists, Koi deploys behavioral profiling within the workspace runtime. By actively intercepting unauthenticated background tasks and blocking unauthorized file-system reads, it stops automated data exfiltration in real time.

#3. Establish guardrails for automated package updates on endpoints

Developers prioritize speed, often allowing software packages to auto-update on their endpoints the moment a new version appears. Attackers weaponize this supply chain vulnerability, as seen in the May 2026 Team PCP attack where 3,800 GitHub repositories were compromised in just 36 minutes via poisoned auto-updates. Securing agentic endpoints against these rapid breaches requires behavior-based inspection within the active workspace context. Koi operates at this layer by providing safe deployment buffers that automate version cooldowns, blocking bleeding-edge updates until they are vetted. By continuously auditing process creation within the IDE runtime, Koi instantly drops unauthorized remote connections before malicious payloads can exfiltrate credentials from the endpoint.

#4. Enforce principle of least privilege for AI agents

AI coding assistants inherit the privileges of whoever deployed them. In practice, that means read access to production databases, write access to core repositories, and access to every secret in environment files and configuration directories. To restrict this excessive access, Koi applies dynamic sandboxing directly to AI agent processes at the kernel level. It enforces a strict zero-trust boundary that segregates sensitive workspace vectors, preventing agents from pulling data outside their approved scope without interrupting developer workflows.

#5. Maintain continuous endpoint posture management

Signature-based scanning only stops known threats. Sophisticated repository attacks often arrive as functional, high-rated software that carries no known bad signature. Koi’s research into the DarkSpectre campaign found eight browser extensions, all carrying “featured” badges from Google and Microsoft, installed by over 8 million users, silently harvesting every conversation from ChatGPT, Claude, and Gemini in the background. Koi addresses this by operating upstream: scanning marketplace listings every hour, using LLM-driven code analysis to compare what software promises against what its code does, sandboxing it, and scoring the risk before it ever reaches the endpoint.

Summary

Securing the modern enterprise is no longer about patching individual gaps. As AI agents redefine the workforce, Agentic Endpoint Security (AES) is now a strategic imperative for every CISO. By establishing a mandatory control plane for the AI-native workspace, AES ensures that your organization can scale engineering velocity without ever compromising enterprise integrity.

Ready to secure the future of your software stack? See how Koi Agentic Endpoint Security delivers complete visibility, risk scoring, and real-time prevention across every endpoint in your enterprise.

Developer withdraws plans for Perth datacentre after fierce community opposition

Sat, 25 Jul 2026 18:55:42 +0200

Three-storey GreenSquare datacentre in Hazelmere was to power cloud computing and the acceleration of AI

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A 15,000 sq metre datacentre near Perth will no longer go ahead after the developer withdrew plans amid community opposition over its impact on culturally significant sites.

The three-storey, 120-megawatt GreenSquare datacentre in the town of Hazelmere had been intended to power cloud computing and the acceleration of artificial intelligence, but faced fierce community backlash – as is increasingly common with such developments.

The 3 types of people who will excel in the AI agent era, according to tech leaders

Sat, 25 Jul 2026 18:51:46 +0200

The autonomous business of the future is being built. Certain skills are in high demand - and can help you stand out.

Samsung's new Ultra foldable is impressive, but I'd pay close attention to this model

Sat, 25 Jul 2026 18:51:43 +0200

The Galaxy Z Fold 8 Ultra is sure to impress power users, but Samsung took a risk with the Galaxy Z Fold 8, and it could pay off.

Samsung Galaxy Z Fold 8 Ultra vs. Z Fold 7: How the first 'Ultra' foldable compares to last year's model

Sat, 25 Jul 2026 18:51:43 +0200

Samsung's new Z Fold 8 Ultra brings design and software changes geared toward power users and enthusiasts.

One fallen power line exposed a growing AI data center problem. Here’s how to fix it.

Sat, 25 Jul 2026 15:12:21 +0200

A close call in Northern Virginia revealed just how poorly data centers respond to grid disruptions. Here's how to fix the problem.

Vodafone is testing an AI robotic mast, but the future belongs to adjustable internal antenna components

Sat, 25 Jul 2026 14:11:53 +0200

Vodafone is testing AI-controlled robotic antennas while preparing lower-energy internal antenna components for future autonomous 4G and 5G networks.

Vodafone is testing an AI robotic mast, but the future belongs to adjustable internal antenna components

Sat, 25 Jul 2026 14:11:53 +0200

Vodafone is testing AI-controlled robotic antennas while preparing lower-energy internal antenna components for future autonomous 4G and 5G networks.

‘Agent Kim Reactivated’ Episode 10 Finale Release Date and What to Expect

Sat, 25 Jul 2026 13:19:44 +0200

Agent Kim Reactivated Episode 10 will release on Saturday, July 25, 2026, bringing the Korean action drama’s first season to an end. The finale will air on SBS in South Korea before becoming available to international viewers on Netflix. The final episode will begin at 9:45 p.m. KST, which is five minutes earlier than the show’s usual 9:50 p.m. slot. SBS has also confirmed that Episode 10 will have a slightly extended runtime, giving the series more time to resolve its remaining conflicts. Agent Kim Reactivated Episode 10 release details Episode: 10 Release date: Saturday, July 25, 2026 SBS broadcast time: 9:45 p.m. KST Streaming platform: Netflix Total episodes: 10 Genre: Action, crime, comedy and thriller Netflix normally adds new episodes after their Korean television broadcast, although the exact arrival time can differ by country. Where is the story heading in the finale? Spoilers for Episode 9 follow. Episode 9 placed Manager Kim and his allies in the middle of a dangerous extraction operation. Kim attempted to rescue Ri Eung-ryeong from North Korean agents while Han-su, Jin-cheol and Sang-a helped him enter a heavily guarded hotel. The operation quickly fell apart after communications were cut and the building lost power. Kim and Ri Eung-ryeong were surrounded by armed agents near the loading area, leaving their escape uncertain. Meanwhile, Ju Gang-chan’s assistant kidnapped the children of Han-su and Jin-cheol. The episode ended with both fathers learning that their families were being used against them, setting up another personal rescue mission for the finale. Episode 10 should therefore focus on Kim escaping the hotel, protecting Min-ji and helping his friends save their children. The finale must also settle Ju Gang-chan’s fate and reveal whether Kim can finally leave his violent past behind. How did Agent Kim’s story begin? The series started with Kim living quietly as an office worker and raising his teenage daughter, Min-ji, after his wife’s death. His ordinary life collapsed when Min-ji disappeared, forcing him to reveal the black-ops abilities he had kept hidden for years. As Kim searched for his daughter, the mission exposed old enemies, secret government operations and unresolved connections to North Korea. His former life gradually placed everyone around him in danger. Agent Kim Reactivated Episode 10 now has several major storylines to complete during its extended finale. Do you expect Manager Kim and Min-ji to receive a happy ending? Let us know in the comments.

Build native Android apps in Google AI Studio

Sat, 25 Jul 2026 10:15:46 +0200

Posted by Emma-Louise Leavey, Group Product Manager and Mike Taylor-Cai, Product Manager

Starting today Google AI Studio can build entire Android apps for you in minutes from just a prompt. You don't need to install any software or configure any libraries, which significantly lowers the barrier to development. Whether you’re a seasoned developer looking to prototype at lightning speed or a creator building your first-ever mobile experience, you can now go from a single prompt to a high-quality, Kotlin-based Android app in AI Studio. You can easily install the app on your device, share it with others for testing, or send it to Android Studio for any further development.

The power of native Android

While AI has made it easy to generate web-based apps, people want more on their mobile devices. They expect the beautiful and usable modern app design and capabilities that come with native Android user experiences, built with the Kotlin programming language using Jetpack Compose, the official and recommended toolkit for Android development. Native Android apps bring the reliability of offline support, continuous background services, and the deep integration of hardware sensors like GPS, Bluetooth, and NFC. We've brought the technology that enables you to quickly create new projects with Gemini in Android Studio directly into the web-based AI Studio. Now, you get the best of both worlds: the ease of a prompt-based interface paired with the power of the Android SDK, all in your browser, no installation required.

A seamless, end-to-end workflow

We have streamlined the entire development lifecycle so you can focus on your idea:

1. Create your app and iterate in the cloud: Use the embedded Android Emulator directly in your browser to preview and interact with your app as it’s being built. No heavy SDKs to download, no local setup required.

Use the embedded Android Emulator to create and edit Android Apps right in the web browser

2. Install instantly: Connect your Android phone using a USB cable and install your app directly from AI Studio using the integrated Android Debug Bridge (adb).

Install the app on your Android device

3. Streamlined Publish to Google Play: Using your Google Play developer account, you can now publish your app directly from AI Studio for testing. AI Studio will automatically create your app record, package the bundle, and upload it to an internal testing track in Google Play Developer Console. Your app is available for you to install within minutes, and you can automatically update your app on your device as you develop it further in AI Studio.

Publish the app to an internal test track in Google Play

Seamless app development handoff

As you iterate on your app in AI Studio, you may find you need more advanced Android tools or support for a wider variety of Android device types. To move beyond the browser, you can seamlessly hand off your project to Android Studio by downloading a ZIP file or exporting it directly to GitHub.

Download zip file of Android app project files

When transitioning to a team environment or local development, you can leverage any IDE or agent you prefer. For a specialized experience, we recommend Gemini in Android Studio, which features models designed with Android in mind, or Antigravity, which integrates Android CLI commands into Google’s agentic development platform. This workflow makes building high-quality apps more accessible while giving you total flexibility in how you use AI to scale your project.

Start building today

To ensure a safe, high-quality ecosystem from day one, we have focused our initial release on specific capabilities including:

Personal utilities and simple social apps: You can rapidly prototype single or multi-screen apps, such as habit trackers, study quizzes, or event itineraries.
Hardware-enabled experiences: Because you are building native apps, you can leverage device features like the Camera, GPS/Location, Accelerometer and Bluetooth using the native Android APIs, letting you optimize hardware-level performance.
AI-powered experiences: You can create apps that feature Gemini API integrations, seamlessly embedding powerful AI capabilities directly into your mobile experience.

What’s Next?

We are moving fast to expand what’s possible for creators in AI Studio. Here is a sneak peek at what is coming soon:

Managing Google Play Test Tracks: Coming soon, we will be adding the ability to invite testers to try your app directly from AI Studio.
Firebase integrations: Out-of-the-box support for Firestore, Firebase Auth, Firebase App Check and other tooling critical for Android developers is coming soon.

Head over to Google AI Studio right now to start building. Here is some inspiration to get you started…

Turn your Google Pixel Watch into an aviation assistant

Prompt:

Build a small airplane "6-pack" instrument app for Google Pixel Watch. The 6 instruments should include attitude indicator, airspeed indicator, altimeter, turn coordinator, vertical speed indicator, and heading indicator. Use the Google Pixel Watch's sensors to power the instruments and display them clearly. Display one instrument at a time on the display. Swiping to the left or right should cycle through the instruments.

Interactive Harmonium app on Google Pixel Fold
Prompt: Build a Harmonium app for Pixel Fold devices, which plays like the instrument based on the hinge angle and touch gestures. The app should simulate the bellows and reeds accurately.

An Android app for guitarists to become better musicians by jamming to backing tracks

Prompt:

Build an Android guitar practice companion app that features a two-tab navigation system: 'Fretboard' and 'Library'.

The 'Fretboard' primary screen must contain an interactive guitar neck UI that visually maps out user-selected root notes, musical scales, and chords. Above the fretboard, implement a WebView-based YouTube player configured to play embedded videos inline. Additionally, include an AI generation feature that uses Retrofit to call Gemini Lyria 3 to create custom, 30-second backing tracks based on the user's currently selected key and scale. The generated audio files and their metadata must be saved locally using a database and displayed as a list in the 'Library' tab, where users can delete or play them.

Finally, implement a persistent, globally visible mini audio player at the bottom of the screen, complete with play/pause toggles, a progress slider for seeking, and timestamp text, allowing the user to seamlessly practice on the fretboard tab while listening to their tracks.

We are looking forward to seeing what you build next!

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

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

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

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

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

Build High Quality Android Apps Using Agents

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

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

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

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

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

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

3: Accelerating AI coding assistance with Android Bench

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

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

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

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

Building AI Into Your Apps

5: Building Intelligent Apps with generative AI

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

6: Experiment with AppFunctions today

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

The Future is Adaptive

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

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

Build Android UI with Compose

8: Building seamless Android experiences across devices with Jetpack Compose

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

9: Create seamless experiences for Googlebook

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

New Desktop Android Emulator

10: Unified widget development experience with Jetpack Glance

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

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

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

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

12: Accelerate your development with Android XR Developer Preview 4

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

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

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

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

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

Low Light Boost and Magic Eraser in action

14: Increase app discovery and engagement on Google TV

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

15: Performance: the foundation of a great app experience

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

And The Latest on Driving Business Growth

16: What’s new in Google Play

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

Gemini will provide users with app suggestions during a search

17: And of course, Android 17

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

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

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

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

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

Top AI on Android updates for building intelligent experiences from Google I/O ‘26

Sat, 25 Jul 2026 10:15:43 +0200

Posted by Jingyu Shi, Staff Developer Relations Engineer

At Google I/O 2026, we introduced Android’s shift from an operating system to an intelligence system. We also demonstrated how you can build intelligent experiences natively with the system and bring the power of Google’s AI into your apps. If you missed these updates, check out our quick recap video here:

1. Putting your apps at the center of the intelligence system

The Android OS already enables agents like Gemini to complete task automation, where it can navigate an app on the users behalf.

AppFunctions (Android MCP) provides you with more control over how your app integrates with the intelligence system. This new platform API and Jetpack library are currently available in experimental preview.

Android MCP: AppFunctions allows your application to act as an on-device Model Context Protocol (MCP) server. It means you seamlessly share your app's tools, services and data to the system and agents.

Streamlined Development: You can leverage the new skill to easily generate AppFunctions within your codebase.

Exploration and Testing: We’ve released a new test agent that allows you to experiment and debug your AppFunctions in a simulated agent environment.

Early Access Program: Want to be among the first apps to deploy app functions in production? Join our early access program today!

To see it in action, check out the live demo showcased during the What’s New in Android presentation.

2. On-Device Power with Gemini Nano 4 Preview

Last month, we launched Gemma 4, our state-of-the-art open models. You can already preview and prototype with the next generation of Gemini Nano (Nano 4) models with the AIcore developer preview. To make productionizing with Gemini Nano more reliable and performant, we are adding a few new features in ML Kit GenAI APIs:

Prototype to Production: Transition from prototyping in the AICore Developer Preview to building production-ready apps using the ML Kit GenAI Prompt API to leverage Gemini Nano 4 that’s launching in flagship devices later this year.

Structured Output: The upcoming Structured Output API will allow you to define object classes to be returned as outputs from Prompt API, ensuring reliable outputs in productionizing your intelligent features.

Prefix Caching: It optimizes your on-device inference performance with the prompt API. The new Prefix caching reduces inference time by storing and reusing the intermediate LLM state of processing a shared and recurring part of the prompt.

For highly customized or niche use cases, you can also use LiteRT-LM to bring your own fine-tuned small language model to Android.

3. Hybrid Inference & Agents

To help you build more advanced AI features like hybrid inference and explore building in-app agents, we’ve released new APIs, framework and guidances:

Firebase AI Logic Hybrid Inference: This new API provides the simple routing capability between on-device models and powerful cloud infrastructure. You can set explicit orchestration modes, such as PREFER_ON_DEVICE, PREFER_CLOUD, ONLY_ON_DEVICE, or ONLY_CLOUD, based on your need.

A2UI Jetpack Compose Renderer: The new A2UI library allows your agents to "speak UI". With the upcoming Jetpack Compose Renderer, you can automatically render these A2UI messages as native UI components.

ADK for Android: The first version of ADK for Android is available for experimentation. It allows you to build multi-agent workflows across both on-device and Cloud models while managing orchestration, context handling and sessions between agents.

From building with on-device models, exploring hybrid inference to building agents, you can see them in action in this talk:

Start Building Today

Whether you are experimenting with AppFunctions to prepare for the intelligence system, or looking to bring the power of Google’s AI within your own app, we’ve got you covered. Dive deeper into the code snippets, samples and comprehensive developer guides on the Android AI hub. For the full breakdown of what’s new, check out the official AI on Android at Google I/O 2026 playlist.

We are excited to see what you build!

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.

Building a Mixed-Reality Tour Guide with Android XR, the Geospatial API, and Gemini

Sat, 25 Jul 2026 10:15:35 +0200

Posted by Coco Fatus, UX Designer, Alon Hetzroni, UX Engineer, Azin Mehrnoosh, Product Manager Android XR

At this year's Google I/O, we announced an update for spatial experiences: the Geospatial API is now available as a preview in ARCore for Jetpack XR. By bringing Google's Visual Positioning System (VPS) to Android XR, Android XR enables anchoring digital content to the physical world with sub-meter accuracy and precise orientation in supported areas.* To explore what the Geospatial API could unlock, our team built a demo: the XR Geospatial Tour.

Imagine walking into a new city, putting on a pair of wired XR glasses (like the upcoming XREAL Project Aura), and instantly having a knowledgeable, local guide showing you around. You don't need to stare down at a 2D map—instead, 3D models gently guide your path, and an intelligent voice tells you about the historical landmarks right in front of you. We combined the Geospatial APIs, Gemini API using Firebase AI Logic, Google Maps Grounding, and Jetpack XR SDK to create a hands-free, immersive walking tour experience.

*Disclaimer: Video and Tour Guide application are for demonstration purposes only. Some sequences have been shortened. Any hardware depicted may be under development; final product details may differ.

Let’s walk through the implementation details and show how we tied these APIs together to build a world-scale spatial experience.

1. Pinpointing the User with ARCore Geospatial API (VPS)

Enhance your navigation experience on XR by combining the power of GPS with the precision of VPS. The accuracy and precise orientation that comes with VPS allows 3D waypoints to align with the physical world.

This is why the Geospatial API on Android XR can help you build custom experiences. By using advanced computer vision, VPS tries to provide a GeospatialPose (including latitude, longitude, and heading) that is more accurate than GPS.

Here's how we retrieve the user's Geospatial pose by mapping the device's orientation to a Geospatial coordinate:

// Retrieve the current geospatial pose from the ARCore session
val result = geospatial.createGeospatialPoseFromPose(arDevice.state.value.devicePose)
if (result is CreateGeospatialPoseFromPoseSuccess) {
    val pose = result.pose
    Log.d("VPS", "Accurate Location: ${pose.latitude}, ${pose.longitude}")
}

Because the entire experience relies on this accuracy, we monitor the horizontalAccuracy and orientationYawAccuracy until they meet our thresholds. If the user is indoors or in an unrecognized area, we prompt them to "walk to an outdoor public space and look around".

2. Crafting the Itinerary with Gemini API & Google Maps Grounding

Once we have a location, we use the Gemini API using Firebase AI Logic to prompt the Gemini model to act as a local tour guide. We pass the user's coordinates to the model and ask it to output a structured JSON response containing nearby walking tours:

   val configForTools = ToolConfig(
      functionCallingConfig = null,
      retrievalConfig = retrievalConfig {
        latLng = FirebaseLatLng(pose.latitude, pose.longitude)
        languageCode = "en"
      }
    )
    val responseJsonSchema = Schema.obj(
      mapOf(
        "locationIntro" to Schema.string(),
        "tours" to Schema.array(
          Schema.obj(
            mapOf(
              "title" to Schema.string(),
              "description" to Schema.string(),
              "stops" to Schema.array(
                Schema.obj(
                  mapOf(
                    "name" to Schema.string(),
                    "detailedName" to Schema.string(),
                    "description" to Schema.string()
                  )
                )
              )
            )
          )
        )
      )
    )
    val model = Firebase.ai(backend = GenerativeBackend.googleAI()).generativeModel(
      modelName = "gemini-3.5-flash",
      tools = listOf(Tool.googleMaps()),
      generationConfig = generationConfig {
        responseMimeType = "application/json"
        responseSchema = responseJsonSchema
      }
    )
   val result = model.generateContent("The user is at latitude ${pose.latitude} and longitude ${pose.longitude}. Generate exactly 3 diverse tours near this location (e.g., historical, food, nature). All tour ideas should be walking distance only.")

Large Language Models are great at generating rich descriptions, but they can sometimes hallucinate exact latitude/longitude coordinates. To solve this, we used Google Maps Grounding to ground the AI.

3. A Voice to Guide You: Gemini 2.5 TTS

To make the tour guide feel truly present, we implemented dynamic voiceovers.

Using the gemini-2.5-flash-tts model, we can configure our model generation config to natively return audio data instead of just text! Here’s how you can request the ResponseModality.AUDIO:

val ttsModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        modelName = "gemini-2.5-flash-tts",
        generationConfig = generationConfig {
            // Instruct the model to return Audio
            responseModalities = listOf(ResponseModality.AUDIO)
        }
    )
val response = ttsModel.generateContent("Say in a neutral but positive voice:\n$prompt")
// Extract the raw audio bytes from the response
val audioBytes = response.candidates.firstOrNull()?.content?.parts
    ?.filterIsInstance()
    ?.firstOrNull { it.mimeType.contains("audio") }?.inlineData

4. Bringing it to Life in 3D with Jetpack XR

The final piece of the puzzle is rendering this data in the user's field of view. The Jetpack XR SDK makes it intuitive to transition from a 2D Android UI to spatial computing.

We used Jetpack Compose for XR to build spatial components. To represent points of interest along the tour, we built a Composable called InfoSphere, which contains a GltfModel of a 3D orb that floats in space and can be interacted with to reveal information.

Using Jetpack XR SDK, we can place 3D models alongside the Compose UI using SpatialBox and SceneCoreEntity. We also used InteractableComponent to respond to user taps.

@Composable
fun InfoSphere(
    content: InfoBubbleContent,
    session: Session,
    sphereModel: GltfModel,
    isSelected: Boolean,
    onClick: () -> Unit
) {
    // SpatialBox lets us arrange 3D components and SpatialPanels together
    SpatialBox(
        SubspaceModifier
            .offset(x = 2.dp, y = 1.dp, z = (-3).dp) // Positioned in 3D space
    ) {
        // Smoothly animate the visibility of our 2D Compose UI Panel
        AnimatedSpatialVisibility(visible = isSelected) {
            SpatialPanel {
                InfoBubble(content) // Regular 2D Compose UI
            }
        }
        // Render our interactive 3D sphere
        SceneCoreEntity(
            factory = {
                GltfModelEntity.create(session, sphereModel).also { entity ->
                    // Make the 3D model respond to user taps
                    entity.addComponent(InteractableComponent.create(session) { inputEvent ->
                        if (inputEvent.action == InputEvent.Action.UP) {
                            onClick()
                        }
                    })
                }
            }
        )
    }
}

By combining AnimatedSpatialVisibility for traditional Compose UI surfaces with SceneCoreEntity 3D elements, we're able to seamlessly blend data into the physical world.

Explore what’s possible with Android XR today

Building the XR Geospatial Tour app showed us that the barrier to entry for world-scale spatial experiences is lower than ever for Android developers. With the Geospatial API now available in preview on Android XR, your apps can seamlessly understand the physical world around them. By combining Compose for XR’s APIs with the high-precision location data of VPS and the generative capabilities of Gemini, we can create experiences that understand both where the user is and what they are looking at.

To help you get hands-on with Android XR, we are thrilled to open applications for the Android XR Developer Catalyst Program, which includes XREAL Project Aura. Starting today, you can apply to get access to an XREAL Project Aura devkit or our display glasses devkit over the coming months!

Android developer verification: Building a safer ecosystem together

Sat, 25 Jul 2026 10:15:33 +0200

Posted by Matthew Forsythe, Director Product Management, Android App Safety

July 15, 2026: Updated Play Console requirements for Play developers

To meet Android developer verification and updated Play Console Requirements, Play developers must register their Play apps in Play Console. While 99% of apps on Play have been registered automatically, you should check your Play Console Home page to register any remaining apps by September 30, 2026 to avoid global removal from Google Play and ensure a seamless user installation experience.

You can also use Play Console to register apps you distribute outside of Google Play to ensure they can be installed on certified Android devices.

Last year, we introduced Android developer verification to strengthen ecosystem security and stop malicious actors from hiding behind anonymity to release harmful apps. Millions of apps have been registered since the verification launched in March, covering nearly all installs on Google Play and a large majority of installs from outside of Google Play. We appreciate the feedback and partnership from industry leaders, developers, and Android communities that helped us design this experience and drive strong adoption.

Initial launch across seven stores and four countries

These new developer verification protections will take effect on September 30, 2026, starting with users in Brazil, Indonesia, Singapore, and Thailand.

This rollout is an industry-wide effort to create a safer ecosystem. We will begin by verifying app installations from the following stores:

Google (Google Play)
Honor (HONOR App Market)
OPlus (OPPO App Market)
Samsung (Galaxy Store)
Transsion (Palm Store)
vivo (V-Appstore)
Xiaomi (GetApps)

Following this initial phase with our partners, we will expand these protections globally for all apps on certified Android devices in 2027.

Automate your workflow with new APIs

To further streamline app registration, we are launching a suite of developer-requested APIs to help you register apps in bulk or directly through your continuous integration and deployment (CI/CD) pipelines. The Android Developer ID Status API will let you check if a package name has already been registered, and the Android Developer Console API will let you register and manage package names directly within your development environment. Both APIs also support OAuth delegation, allowing third-party platforms, like Android app stores, to perform these operations natively on your behalf.

We'll launch these APIs over the next few months.

What’s next

June 2026: Starting this month, we are rolling out a new system service that will be automatically installed on most Android devices. This service will be used later this year to verify developer registration.
July 2026: We’ll launch the Android Developer ID Status API globally and begin early access for the Android Developer Console API. Early access also starts for limited distribution accounts on Android Developer Console. This new type of Android developer account is designed for students, hobbyists, and learners and lets you share your apps to up to 20 devices without a government-issued ID or a fee.
August 2026: Limited distribution accounts and the new Android Developer Console API will launch globally. We’ll also launch an advanced flow for installing apps from unverified developers, which includes security checkpoints to resist coercion scams, while allowing power users to maintain the ability to sideload apps from unverified developers.
September 30, 2026: App registration becomes required for participating stores in Brazil, Indonesia, Singapore, and Thailand. Unregistered apps can be sideloaded with Android Debug Bridge (adb) or advanced flow.
2027 and beyond: After incorporating the feedback from our partners, users, and developer community, we’ll expand the Android verification requirement globally.

Get started with Android developer verification

If you distribute apps in Brazil, Indonesia, Singapore, or Thailand via the stores listed above, please ensure your verification is complete by the September deadline.

Google Play developers: Most Play developers are already verified, and over 99% of their apps have been registered. Go to your Play Console Home page to see your app’s verification status, and register apps you want to continue distributing that weren't automatically registered.
Developers who distribute only outside of Google Play: Sign up for the Android Developer Console today to register your apps.

Students and hobbyists: Sign up here for early access to limited distribution accounts to help us refine the feature with your feedback.

Thank you for helping us build a safer Android ecosystem. Stay tuned for more updates as we approach September and the 2027 global rollout.

Build intelligent Android apps: On-device inference

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

Posted by Caren Chang, Developer Relations Engineer, Android Developer Relations

Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post we introduced Jetpacker, the demo app we'll use throughout this series.

In this blog post, we will share how you can use Gemini Nano through ML Kit’s Prompt API to build intelligent on-device features.

Building intelligent on-device features refers to the ability to process prompts and data directly on a device without sending data to a server. This offers a few advantages:

User data can be processed locally on the device, preserving user privacy
Functionality of the model is reliable even with spotty or no internet connection
No additional cloud inference cost, since everything runs on the user’s hardware

With the benefits of on-device in mind, we identified three features to add in Jetpacker that can improve the user experience: summarizing trip itineraries, managing expenses, and capturing voice notes.

On-device features in Jetpacker: Summarizing trip itineraries, managing expenses, and voice notes

High quality tailored summarization of short texts

The itinerary screen gives users a quick overview of all activities for a given trip. Since this screen contains a lot of information, it can quickly become overwhelming. To help users prepare without feeling overwhelmed, we can add a ‘Get ready for your trip’ section at the top.

The romantic Paris trip is summarized as a classic Parisian adventure blending art, sights, and delicious food. A tip and some useful phrases are also added.

By inputting a trip itinerary and asking an LLM to summarize it, we can generate a quick summary of the trip along with packing tips and useful local phrases. This is a great use case for an on-device model for several reasons:

Performance and quality: Both the input and output text are relatively short. With that, we can expect the performance and quality of an on-device solution to be on par with more powerful cloud models.
Scalability: Shifting inference on-device allows us to scale this feature from a few users to millions without worrying about managing increasing cloud inference costs.
Low latency and reliability: On-device inference guarantees low latency, providing a reliable experience even when users are offline.

To build with on-device, we use Gemini Nano, Google’s most efficient model optimized for mobile devices. Gemini Nano was first introduced a few years ago, and is now running on over 140 million devices. The latest version of the model, Gemini Nano 4, is built on the architecture foundation of the recently released Gemma 4 model, and is further optimized for maximum battery and performance efficiency.

Using ML Kit’s Prompt API, we can take advantage of Gemini Nano 4’s new model capabilities to prototype our on-device features. We’ll create a prompt that includes the itinerary of a trip and ask the model to generate a summary along with any preparation tips.

// implementation("com.google.mlkit:genai-prompt:1.0.0-beta3") 

// Define the configuration for Gemini Nano 4 E2B preview model
val previewFastConfig = generationConfig {
    modelConfig = modelConfig {
        releaseStage = ModelReleaseStage.PREVIEW
        preference = ModelPreference.FAST
    }
}

val geminiNano2BPreviewModel = Generation.getClient(previewFastConfig)

val tripItinerary = ...

val getReadyForYourTripSummary = geminiNano2BPreviewModel
 .generateContent("Given this trip itinerary: $tripItinerary, 
     generate the following: overall vibe, tips on how to prepare for this
     trip, and common short phrases to learn for the trip.")

Finding the optimal prompt usually requires some iteration, and the AICore app is perfect for this step in the process. After opting into the developer preview option for AICore, we can download preview models such as Gemini Nano 4 to test prompts and see the model’s expected outputs. With a few iterations on the prompt, we were able to improve the speed of the response from 13 seconds to under 2 seconds! Check out the final code implementation and prompt here.

The first iteration of our prompt generated way too many tokens, and optimizing it helped keep responses quick and to the point.

Local processing for sensitive user input

Next, to help users enjoy their trip even more, we’ll build a simple expense manager that takes the manual work out of sorting through receipts and calculating budgets.

Taking a photo of a restaurant bill, data is parsed and shown in the expense overview screen of the app.

Since receipts might contain sensitive information like credit card number and addresses, this is another great use case for an on-device solution. With on-device, users can be confident that private information will be processed locally on the device without any of their data being sent to the cloud.

In addition, Gemini Nano 4 has improved model capabilities for multimodality, especially for image understanding tasks like OCR and visual data extraction, making it a great solution for tasks like extracting information from receipts.

For this use case, the prompt will analyze an image of the receipt, and output information such as: a generated title, amount spent and category of the expense. To ensure the model outputs the information in the preferred format, we can use ML Kit’s Structured Output API to seamlessly output a Kotlin data object that we define.

// implementation("com.google.mlkit:genai-prompt:1.0.0-beta3")
// ksp("com.google.mlkit:genai-schema-compiler:1.0.0-alpha1")

@Generable("Information extracted from an expense receipt")
data class ParsedReceipt(
  @Guide("Generated title for the expense less than 6 words. Based on restaurant or activity name.")
  val title: String,
  @Guide("Total amount of the expense. Look for values at the bottom and words like total or balance due.")
  val amount: Double,
  @Guide("Type of expense", enumValues = ["travel", "food", "shopping", "entertainment", "other"])
  val category: String,
)

val prompt = "Determine if the image is a receipt or expense. 
    If it is NOT a receipt or expense, output the text 'NOT_A_RECEIPT'.
    Otherwise, parse the receipt information."

val request = generateContentRequest(ImagePart(bitmap), TextPart(prompt)) {}
val requestWithStructuredOutput = generateTypedContentRequest(request, ParsedReceipt::class)

// Define the configuration for Gemini Nano 4 E4B preview model  
// When selecting models, you can specify which performance charactertists are most important
//  for your use case. Use ModelPreference.FULL when you want to prioritize reasoning power over speed. 
//  Use ModelPreference.FAST when complex logic is not required and latency is a priority.
val previewFullConfig = generationConfig {
    modelConfig = modelConfig {
        releaseStage = ModelReleaseStage.PREVIEW
        preference = ModelPreference.FULL
    }
}

val geminiNano4BPreviewModel = Generation.getClient(previewFullConfig)
val response = geminiNano4BPreviewModel.generateContent(requestWithStructuredOutput)
val parsedReceipt: ParsedReceipt? = response.candidates.firstOrNull()?.response

Multimodal input

Lastly, to help users record audio memos during the trip, let’s build a fully on-device voice notes feature. Using ML Kit’s Speech Recognition API, we’ll enable users to record short voice notes that are automatically transcribed to text. With the transcribed text, we’ll use ML Kit’s Prompt API to identify which trip activity is associated with the recorded voice note, letting users easily recap their trip as they scroll through the trip’s itinerary.

The Roman holiday itinerary shows voice note extracts.

The ML Kit GenAI Speech Recognition API allows you to transcribe audio content to text fully on-device using two distinct modes. Basic mode uses a traditional on-device speech recognition model and is available on most Android devices with API level 31 and higher. Advanced mode uses Gemini Nano to offer broader language coverage and better quality, and is currently supported on Pixel 10 devices.

For our feature we combine the Speech Recognition API with the ML Kit GenAI Prompt API:

// implementation("com.google.mlkit:genai-prompt:1.0.0-beta3")
// implementation("com.google.mlkit:genai-speech-recognition:1.0.0-alpha1")

val tripEvents = ... 

// Set up speech recognition
val speechRecognizerOptions =
    speechRecognizerOptions {
        locale = Locale.US
        preferredMode = SpeechRecognizerOptions.Mode.MODE_ADVANCED
    }
val speechRecognizer: SpeechRecognizer = SpeechRecognition.getClient(speechRecognizerOptions)

suspend fun transcribeVoiceNote(recognizer: SpeechRecognizer) {
    // Display partial text as the user is recording audio
    var partialTextResponse = ""

    // Display the full text once user is finished recording audio
    var transcription = ""

    val request: SpeechRecognizerRequest
        = speechRecognizerRequest { audioSource = AudioSource.fromMic() }
    recognizer.startRecognition(request).collect { response ->
        when (response) {
            is SpeechRecognizerResponse.PartialTextResponse -> {
                partialTextResponse = response.text
            }
            is SpeechRecognizerResponse.FinalTextResponse -> {
                transcription = response.text
                processAndCategorizeVoiceNote(transcription, tripEvents)
            }
        }
    }
}

fun processAndCategorizeVoiceNote(transcribedVoiceNote: String, events: List) {
    val prompt = "Given the voice note $transcribedVoiceNote
     and the following events for this trip: $events, rewrite this transcription
     to remove filler words. Then, identify which events from the
     list this rewritten transcription matches to."

     // Utilize ML Kit's Prompt API to process voice note and tag it with the relevant trip activities
     Generation.getClient().generateContent(prompt)
}

Conclusion

Using ML Kit’s GenAI APIs, we were able to take advantage of Gemini Nano to develop fully on-device intelligent features for the JetPacker app, and provide an improved user experience without any additional cloud costs.

Check out the full source code for Jetpacker on Github, and watch the video Build Intelligent Android apps with Google’s AI to learn more about how to integrate intelligent features directly into your app using on-device models, cloud-powered reasoning, and the latest agentic frameworks.

Learn more

Check out the other parts of this blog post series:

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

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

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

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

Linux Foundation Launches Akrites To Coordinate AI-Driven Open Source Security

Sat, 25 Jul 2026 10:12:54 +0200

BrianFagioli writes: The Linux Foundation has announced Akrites, a new initiative to coordinate vulnerability disclosure and remediation for critical open source software as AI dramatically speeds up vulnerability discovery. Founding members include AWS, Google, Microsoft, OpenAI, Red Hat, NVIDIA, IBM, Cisco, JPMorganChase, and others. Akrites will provide a shared Security Incident Response Team (SIRT), a standardized coordinated vulnerability disclosure process, and act as a "maintainer of last resort" for abandoned but widely used packages. The goal is to reduce duplicate reports, avoid conflicting patches, and help upstream maintainers address vulnerabilities before they can be exploited. As AI makes it easier to find security flaws, can a coordinated industry effort help protect open source, or does it risk giving large corporations too much influence over the ecosystem? "Akrites is the largest coordinated effort in history to create systems and deploy tooling that leverages the collective power of the community to make everyone safer," the Linux Foundation said in an open letter. "Akrites participants will contribute engineering resources; work to build and ship fixes; or fund the engineers who do. Some companies have contributed mightily already. The reality is, collectively, we need to contribute more."

Read more of this story at Slashdot.

Ask Slashdot: Which Apps Aren't Available on Linux?

Sat, 25 Jul 2026 10:12:48 +0200

Have you ever needed a Linux application which only exists in the Windows world? Long-time Slashdot reader BrendaEM writes: Windows does have a lot of useful app (but smaller than "power apps"). Some of these are closed source, some are open, but they're not all available in Linux yet. My list would have to contain Gimp Tookit versions of: IrfanView image manager, which I think is unequaled in Linux (though it does work to some extent under Wine). I also miss the full version of 7-Zip, because of its better compression settings, which File-Roller does not provide, though the Linux port p7zip is available (though unnoticed by common distributions). Lastly, I think that Notepad++ would be a good addition to Linux. That last one drew some pushback from long-time Slashdot reader jesco. "If there's one area where Linux shines, then it's the availability of high-quality text editors. Last time I looked Kate was still pretty nice, and there's Emacs, Vim and Neovim" if you're partial to command lines. But are there any daily-drive apps you still find yourself needing? Share your own thoughts in the comments. Which apps aren't available on Linux?

Read more of this story at Slashdot.

Linus Torvalds on Rust, C, Bugs, and AI Patch-Checking Tools

Sat, 25 Jul 2026 10:12:38 +0200

"Git and email are the two really only tools I use," Linus Torvalds said at Open Source Summit India 2026. But ZDNet reports that he also shared his thoughts on Rust, C, and patch-checking tools: "I use Google as a way to look things up." He added, "I'm unusual; most of the other maintainers end up using many more tools, and I think a lot of them are starting to use AI tools for patch checking," while he "works at a higher level. I work with people, not tools." When asked about Rust both in Git and the kernel, he pushed back against hype: "I'm not sure Rust is going to take over the world. I still think Rust is very interesting, [but] I still find C to be a much simpler tool." Torvalds continued, "I'm much more excited about all the tools we have for verification of C," including "automated patch verification tools" and "automated email checking tools for patches like Sashiko." Summing up, Torvalds told the Mumbai audience: "I'm more of a hack-and-slash kind of person, and I still like the raw and simple power of C, and I don't think that's going to change." Torvalds also warned against overestimating Rust's benefits: "Rust fixes a few easy bugs that you can make in C, but it does not fix the logic errors, right? It does not think for you, and when you write incorrect code, the language does not matter. The end result will be incorrect." On mixed C/Rust code bases, he pointed out that guarantees are limited: "The guarantees that Rust give you only apply in the Rust-only parts of your code base, and wherever you interact with C code, all bets are off," with most Rust code in Linux talking to "core kernel C code" that is "much better quality... because that code has been tested in every single environment." At the same time, Torvalds pointed out, "some of our big and more high-profile bugs in the kernel lately have been logic errors" rather than the kind of memory errors Rust prevents. "It was just bad programming, which sadly happens even in carefully maintained subsystems and important kernels that are supposed to be very secure."

Read more of this story at Slashdot.

‘Agent Kim Reactivated’ Episode 9 Recap: Kim and His Team Fight Their Way Out

Sat, 25 Jul 2026 10:05:45 +0200

Agent Kim Reactivated Episode 9 pushes Kim and his allies into another dangerous escape mission after his carefully prepared operation falls apart. With Min-ji’s safety still uncertain, Kim joins forces with Han-su, Jin-cheol, and Sang-a while Kang-chan prepares another cruel surprise. Release date: July 24, 2026 Streaming platform: Netflix Total episodes: 10 Finale release date: July 25, 2026 The Korean drama follows an ordinary office worker who reveals his past as a highly trained black-ops agent after his daughter disappears. The series stars So Ji-sub as Manager Kim, alongside Choi Dae-hoon, Yoon Kyung-ho, Joo Sang-wook, Son Na-eun, and Seo Su-min. Spoilers ahead for Agent Kim Reactivated Episode 9 Episode 9 begins with Kim’s latest operation failing to go according to plan. After being captured and tortured in the previous episode, Kim remains trapped between the National Special Missions Bureau, enemies from his past, and Kang-chan’s personal revenge campaign. Kim refuses to surrender because reaching Min-ji remains his only priority. He once again relies on the skills he spent years hiding, although the episode makes it clear that he cannot complete this mission alone. Han-su and Jin-cheol return to help their old friend, bringing their familiar mix of action and humour into the tense situation. Sang-a also becomes an important part of the escape plan. Together, the four characters attempt to break free before Kang-chan can carry out the next stage of his revenge. Kang-chan reveals another plan The biggest problem is that Kang-chan has already expected Kim to fight back. He keeps another secret weapon ready, forcing Kim and the other fathers to change their strategy while they are already under pressure. Kang-chan’s actions continue the conflict that began with the bullying involving Min-ji and Hye-ri. What started as a dispute between their daughters has grown into a violent battle shaped by pride, power, and revenge. The episode also brings the three fathers closer together. Han-su and Jin-cheol understand that Kim will risk his life for Min-ji, so they choose to remain beside him even when the chances of escaping become smaller. Where is the story heading? Episode 9 serves as the final setup before the conclusion. Kim has survived capture, reunited with Min-ji, and faced people connected to his hidden life, but Kang-chan still controls the final threat. The remaining conflict now depends on whether Kim can protect his daughter without losing the friends who followed him into danger. The extended finale airs on July 25 at 9:45 p.m. KST, five minutes earlier than the show’s usual broadcast time. What did you think about Kim, Han-su, Jin-cheol, and Sang-a’s escape mission in Agent Kim Reactivated Episode 9? Let us know what you expect from the finale in the comments.

Pro-Russia Hacktivists Conduct Opportunistic Attacks Against US and Global Critical Infrastructure

Sat, 25 Jul 2026 09:15:46 +0200

Summary

Note: This joint Cybersecurity Advisory is being published as an addition to the Cybersecurity and Infrastructure Security Agency (CISA) May 6, 2025, joint fact sheet Primary Mitigations to Reduce Cyber Threats to Operational Technology and European Cybercrime Centre’s (EC3) Operation Eastwood, in which CISA, Federal Bureau of Investigation (FBI), Department of Energy (DOE), Environmental Protection Agency (EPA), and EC3 shared information about cyber incidents affecting the operational technology (OT) and industrial control systems (ICS) of critical infrastructure entities in the United States and globally.

FBI, CISA, National Security Agency (NSA), and the following partners—hereafter referred to as “the authoring organizations”—are releasing this joint advisory on the targeting of critical infrastructure by pro-Russia hacktivists:

U.S. Department of Energy (DOE)
U.S. Environmental Protection Agency (EPA)
U.S. Department of Defense Cyber Crime Center (DC3)
Europol European Cybercrime Centre (EC3)
EUROJUST – European Union Agency for Criminal Justice Cooperation
Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)
Canadian Centre for Cyber Security (Cyber Centre)
Canadian Security Intelligence Service (CSIS)
Czech Republic Military Intelligence (VZ)
Czech Republic National Cyber and Information Security Agency (NÚKIB)
Czech Republic National Centre Against Terrorism, Extremism, and Cyber Crime (NCTEKK)
French National Cybercrime Unit – Gendarmerie Nationale (UNC)
French National Jurisdiction for the Fight Against Organized Crime (JUNALCO)
German Federal Office for Information Security (BSI)
Italian State Police (PS)
Latvian State Police (VP)
Lithuanian Criminal Police Bureau (LKPB)
New Zealand National Cyber Security Centre (NCSC-NZ)
Romanian National Police (PR)
Spanish Civil Guard (GC)
Spanish National Police (CNP)
Swedish Polisen (SC3)
United Kingdom National Cyber Security Centre (NCSC-UK)

The authoring organizations assess pro-Russia hacktivist groups are conducting less sophisticated, lower-impact attacks against critical infrastructure entities, compared to advanced persistent threat (APT) groups. These attacks use minimally secured, internet-facing virtual network computing (VNC) connections to infiltrate (or gain access to) OT control devices within critical infrastructure systems. Pro-Russia hacktivist groups—Cyber Army of Russia Reborn (CARR), Z-Pentest, NoName057(16), Sector16, and affiliated groups—are capitalizing on the widespread prevalence of accessible VNC devices to execute attacks against critical infrastructure entities, resulting in varying degrees of impact, including physical damage. Targeted sectors include Water and Wastewater Systems, Food and Agriculture, and Energy.

The authoring organizations encourage critical infrastructure organizations to implement the recommendations in the Mitigations section of this advisory to reduce the likelihood and impact of pro-Russia hacktivist-related incidents. For additional information on Russian state-sponsored malicious cyber activity, see CISA’s Russia Threat Overview and Advisories webpage.

Download the PDF version of this report:

Pro-Russia Hacktivists Conduct Opportunistic Attacks Against US and Global Critical Infrastructure (PDF, 1.53 MB )

Background and Development of Pro-Russia Hacktivist Groups

Over the past several years, the authoring organizations have observed pro-Russia hacktivist groups conducting cyber operations against numerous organizations and critical infrastructure sectors worldwide. The escalation of the Russia-Ukraine conflict in 2022 significantly increased the number of these pro-Russia groups. Consisting of individuals who support Russia’s agenda but lack direct governmental ties, most of these groups target Ukrainian and allied infrastructure. However, among the increasing number of groups, some appear to have associations with the Russian state through direct or indirect support.

Cyber Army of Russia Reborn

The authoring organizations assess that the Russian General Staff Main Intelligence Directorate (GRU) Main Center for Special Technologies (GTsST) military unit 74455—tracked in the cybersecurity community under several names (see Appendix B: Additional Designators Used for Cited Groups)—is likely responsible for supporting the creation of CARR —also known as “The People’s Cyber Army of Russia”—in late February or early March of 2022. Actors suspected to be from GRU unit 74455 likely funded the tools CARR threat actors used to conduct distributed denial-of-service (DDoS) attacks through at least September 2024.

In April 2022, the group began using a new Telegram channel featuring the name “CyberArmyofRussia_Reborn” to organize and plan group actions. The channel creators recruited actors to use CARR as an unattributable platform for conducting cyber activities beneath the level of an APT, aimed at deterring anti-Russia rhetoric. CARR threat actors presented themselves as a group of pro-Russia hacktivists supporting Russia’s stance on the Ukrainian conflict, and they soon began claiming responsibility for DDoS attacks against the U.S. and Europe for supporting Ukraine.

CARR documented these actions through embellished images and videos shared on their social media channels, promoting Russian ideology, disseminating talking points, and publicizing leaked information from hacks attributed to Russian state threat actors.

In late 2023, CARR expanded their operations to include attacks on industrial control systems (ICS), claiming an intrusion against a European wastewater treatment facility in October 2023. In November 2023, CARR targeted human-machine interface (HMI) devices, claiming intrusions at two U.S. dairy farms.

The authoring organizations assess that by late September 2024, CARR channel administrators became dissatisfied with the level of support and funding provided by the GRU. This dissatisfaction led CARR administrators and an administrator from another hacktivist group, NoName057(16), to create the Z-Pentest group, employing the same tactics, techniques, and procedures (TTPs) as CARR but separate from GRU involvement.

NoName057(16)

The authoring organizations assess that the Center for the Study and Network Monitoring of the Youth Environment (CISM), established on behalf of the Kremlin, created NoName057(16) as a covert project within the organization. Senior executives and employees within CISM developed and customized the NoName057(16) proprietary DDoS tool DDoSia, paid for the group’s network infrastructure, served as administrators on NoName057(16) Telegram channels, and selected DDoS targets.

Active since March 2022, NoName057(16) has conducted frequent DDoS attacks against government and private sector entities in North Atlantic Treaty Organization (NATO) member states and other European countries perceived as hostile to Russian geopolitical interests. The group operates primarily through Telegram channels and used GitHub, alongside various websites and repositories, to host DDoSia and share materials and TTPs with their followers.

In 2024, NoName057(16) began collaborating closely with other pro-Russia hacktivist groups, operating a joint chat with CARR by mid-2024. In July 2024, NoName057(16) jointly claimed responsibility with CARR for an alleged intrusion against OT assets in the U.S. The high degree of cooperation with CARR likely contributed to the formation of Z-Pentest, which is composed of actors and administrators from both teams, in September 2024.

Z-Pentest

Established in September 2024, Z-Pentest is composed of members from CARR and NoName057(16). The group specializes in OT intrusion operations targeting globally dispersed critical infrastructure entities. Additionally, the group uses “hack and leak” operations and defacement attacks to draw attention to their pro-Russia messaging. Unlike other pro-Russia hacktivist groups, Z-Pentest largely avoids DDoS activities, claiming OT intrusions as attempts to garner more attention from the media.

Shortly after Z-Pentest’s inception, the group announced alliances with CARR and NoName057(16), possibly to leverage the other groups’ subscribers to grow the new channel. In March 2025, Z-Pentest posted evidence claiming OT device intrusions to their channel using a NoName057(16) cyberattack campaign hashtag. Similarly, in April 2025, Z-Pentest shared a video purporting defacement of an HMI by changing system names to NoName057(16) and CARR references. Z-Pentest continues to create new alliances with other groups, like Sector16, to continue growing their subscriber base and incidentally propagate TTPs with new partners.

Sector16

Formed in January 2025, Sector16 is a novice pro-Russia hacktivist group that emerged through collaboration with Z-Pentest. Sector16 actively maintains an online presence, including a public Telegram channel where they share videos, statements, and claims of compromising U.S. energy infrastructure. These communications often align with pro-Russia narratives and reflect their self-proclaimed support for Russian geopolitical objectives.

Members of Sector16 may have received indirect support from the Russian government in exchange for conducting specific cyber operations that further Russian strategic goals. This aligns with broader Russian cyber strategies that involve leveraging non-state threat actors for certain cyber activities, adding a layer of deniability.

Technical Details

Note: This advisory uses the MITRE ATT&CK^® Matrix for Enterprise framework, version 18. See the MITRE ATT&CK Tactics and Techniques section of this advisory for a table of the threat actors’ activity mapped to MITRE ATT&CK tactics and techniques.

TTP Overview

Pro-Russia hacktivist groups employ easily disseminated and replicated TTPs across various entities, increasing the likelihood of widespread adoption and escalating the frequency of intrusions. These groups have limited capabilities, frequently misunderstanding the processes they aim to disrupt. Their apparent low level of technical knowledge results in haphazard attacks where actors intend to cause physical damage but cannot accurately anticipate actual impact. Despite these limitations, the authoring organizations have observed these groups willfully cause actual harm to vulnerable critical infrastructure.

Pro-Russia hacktivist groups use the TTPs in this Cybersecurity Advisory to target virtual network computing (VNC)-connected HMI devices. These groups are primarily seeking notoriety with their actions. While they have caused damage in some instances, they regularly make false or exaggerated claims about their attacks on critical infrastructure to garner more attention. They frequently misrepresent their capabilities and the impacts of their actions, portraying minor incursions as significant breaches, but such incursions can still lead to lost time and resources for operators remediating systems.

Additionally, pro-Russia hacktivists use an opportunistic targeting methodology. They leverage superficial criteria, such as victim availability and existing vulnerabilities, rather than focusing on strategically significant entities. Their lack of strategic focus can lead to a broad array of targets, ranging from water treatment facilities to oil well systems. Pro-Russia hacktivists have demonstrated a pattern of frequently taking advantage of the widespread availability of vulnerable VNC connections. While system owners typically use VNC connections for legitimate remote system access functions, threat actors can maliciously use these connections to broadly target numerous platforms and services. Consequently, these groups can indiscriminately compromise critical infrastructure entities, including those in the Water and Wastewater, Food and Agriculture, and Energy Sectors.

Pro-Russia hacktivist groups have successfully targeted supervisory control and data acquisition (SCADA) networks using basic methods, and in some cases, performed simultaneous DDoS attacks against targeted networks to facilitate SCADA intrusions. As recently as April 2025, threat actors used the following unsophisticated TTPs to access networks and conduct SCADA intrusions:

Scan for vulnerable devices on the internet [T0883] with open VNC ports [T1595.002].
Initiate temporary virtual private server (VPS) [T1583.003] to execute password brute force software.
Use VNC software to access hosts [T1021.005].
Confirm connection to the vulnerable device [T0886].
Brute force the password, if required [T1110.003].
Gain access to HMI devices [T0883], typically with default [T0812], weak, or no passwords [T0859].
Log the confirmed vulnerable device IP address, port, and password.
Using the HMI graphical interface [T0823], capture screen recordings or intermittent screenshots while conducting the following actions, intending to affect productivity and cause additional costs [T0828]:
- Modify usernames/passwords [T0892];
- Modify parameters [T0836];
- Modify device name [T0892];
- Modify instrument settings [T0831];
- Disable alarms [T0878];
- Create loss of view (a technique that mandates local hands-on operator intervention) [T0829]; and/or
- Device restart or shutdown [T0816].
Disconnect from the device, ending the VNC connection.
Research the compromised device company after the intrusion [T1591].

Propagation

To reach a wider audience, pro-Russia hacktivist groups work together, amplify each other’s posts, create additional groups to amplify their own posts, and likely share TTPs. For example, Z-Pentest jointly claimed intrusion of a U.S. system with Sector16. Sector16 later began posting additional intrusions for which the group claimed sole responsibility. It is likely that these and similar groups will continue to iterate and share these methods to disrupt critical infrastructure organizations.

Reconnaissance and Initial Access

The threat actors’ intrusion methodology is relatively unsophisticated, inexpensive to execute, and easy to replicate. These pro-Russia hacktivist groups abuse popular internet-scraping tools, such as Nmap or OPENVAS, to search for visible VNC services and use brute force password spraying tools to access devices via known default or otherwise weak credentials. Threat actors typically search for these services on the default port 5900 or other nearby ports (5901-5910). Their goal is to gain remote access to HMI devices connected to live control networks.

Once threat actors obtain access, they manipulate available settings from the graphical user interface (GUI) on the HMI devices, such as arbitrary physical parameter and setpoint changes, or conduct defacement activities. Because pro-Russia hacktivist groups seem to lack sector-specific expertise or cyber-physical engineering knowledge, they currently cannot reliably estimate the true impact of their actions. Regardless of outcome, pro-Russia hacktivist groups often post images and screen recordings to their social media platforms, boasting the compromises and exaggerating impacts to garner attention from their peers and the media.

Impact

While pro-Russia hacktivist groups currently demonstrate limited ability to consistently cause significant impact, there is a risk that their continued attacks will result in further harm or grievous physical consequences. Attacks have not yet caused injury; however, the attacks against occupied factories and community facilities demonstrate a lack of consideration for human safety.

Victim organizations reported that the most common operational impact caused by these threat actors is a temporary loss of view, necessitating manual intervention to manage processes. However, any modifications to programmatic and systematic procedures can result in damage or disruption, including substantial labor costs from hiring a programmable logic controller programmer to restore operations, costs associated with operational downtime, and potential costs for network remediation.

MITRE ATT&CK Tactics and Techniques

See Table 1 to Table 10 for all referenced threat actor tactics and techniques in this advisory. For assistance with mapping malicious cyber activity to the MITRE ATT&CK framework, see CISA and MITRE ATT&CK’s Best Practices for MITRE ATT&CK Mapping and CISA’s Decider Tool.

*Table 1. Reconnaissance*
Technique Title	ID	Use
Gather Victim Organization Information	T1591	Threat actors use information available on the internet to determine what systems they believe they have compromised and post the information on their social media. This methodology frequently leads to the threat actors misidentifying their claimed victims.
Active Scanning: Vulnerability Scanning	T1595.002	Threat actors use open source tools to look for IP addresses in target countries with visible VNC services on common ports.

*Table 2. Resource Development*
Technique Title	ID	Use
Acquire Infrastructure: Virtual Private Server	T1583.003	Threat actors use virtual infrastructure to obfuscate identifiers.

*Table 3. Initial Access*
Technique Title	ID	Use
Internet Accessible Device	T0883	Threat actors gain access through less secure HMI devices exposed to the internet.

*Table 4. Persistence*
Technique Title	ID	Use
Valid Accounts	T0859	Threat actors use password guessing tools to access legitimate accounts on the HMI devices.

*Table 5. Credential Access*
Technique Title	ID	Use
Brute Force: Password Spraying	T1110.003	Threat actors use tools to rapidly guess common or simple passwords.

*Table 6. Lateral Movement*
Technique Title	ID	Use
Default Credentials	T0812	Threat actors seek and build libraries of known default passwords for control devices to access legitimate user accounts.
Remote Services	T0886	Threat actors leverage VNC services to access system HMI devices.
Remote Services: VNC	T1021.005	Threat actors hunt VNC-enabled devices visible on the internet and connect with remote viewer software.

*Table 7. Execution*
Technique Title	ID	Use
Graphical User Interface	T0823	Threat actors interact with HMI devices via GUIs, attempting to modify control devices.

*Table 8. Inhibit Response Function*
Technique Title	ID	Use
Device Restart/Shutdown	T0816	While threat actors claim to turn off HMIs, it is possible that operators (not the threat actors) turn the devices off during incident response.
Alarm Suppression	T0878	Threat actors use HMI interfaces to clear alarms caused by their activity and alarms already present on the system at the time of their intrusion.
Change Credential	T0892	Threat actors change the usernames and passwords of HMI devices in operator lockout attempts, usually resulting in a loss of view and operators switching to manual operations.

*Table 9. Impair Process Control*
Technique Title	ID	Use
Modify Parameter	T0836	Threat actors attempt to change upper and lower limits of operational devices as available from the HMI.
Unauthorized Command Message	T0855	Threat actors attempt to send unauthorized command messages to instruct control system assets to perform actions outside of their intended functionality, causing possible impact.

*Table 10. Impact*
Technique Title	ID	Use
Loss of Productivity and Revenue	T0828	Threat actors purposefully attempt to impact productivity and create additional costs for the affected entities.
Loss of View	T0829	Threat actors change credentials on HMI devices, preventing operators from modifying processes remotely.
Manipulation of Control	T0831	Threat actors change setpoints in processes, impacting the efficiency of operations for those specific processes.

Incident Response

If organizations find exposed systems with weak or default passwords, they should assume threat actors compromised the system and begin the following incident response protocols:

Determine which hosts were compromised and isolate them by quarantining or taking them offline.
Initiate threat hunting activities to scope the intrusion. Collect and review artifacts, such as running processes/services, unusual authentications, and recent network connections.
Reimage compromised hosts.
Provision new account credentials.
Report the compromise to CISA, FBI, and/or NSA. See the Contact Information section of this advisory.
Harden the network to prevent additional malicious activity. See the Mitigations section of this advisory for guidance.

Mitigations

OT Asset Owners and Operators

The authoring organizations recommend organizations implement the mitigations below to improve your organization’s cybersecurity posture based on the threat actors’ activity. These mitigations align with the Cross-Sector Cybersecurity Performance Goals (CPGs) developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats, tactics, techniques, and procedures. Visit CISA’s CPGs webpage for more information on the CPGs, including additional recommended baseline protections.

Reduce exposure of OT assets to the public-facing internet. When connected to the internet, OT devices are easy targets for malicious cyber threat actors. Many devices can be found by searching for open ports on public IP ranges with search engine tools to target victims with OT components [CPG 3.S].
- Asset owners should use attack surface management services and web-based search platforms to scan the internet. This mitigation can help identify if there are VNC systems exposed within the IP ranges they own, especially for connections set up by third parties.
  Note: For more information on attack surface management, see CISA’s Internet Exposure Reduction Guidance, CISA’s Cyber Hygiene Services for U.S. critical infrastructure, and NSA’s Attack Surface Management for the U.S. Defense Industrial Base.
- Implement network segmentation between IT and OT networks. Segmenting critical systems and introducing a demilitarized zone (DMZ) for passing control data to enterprise logistics reduces the potential impact of cyber threats and the risk of disruptions to essential OT operations [CPG 3.I].
- Consider implementing a firewall and/or virtual private network if exposure to the internet is necessary for controlling access to devices.
  - Consider disabling public exposure by default and implementing time-limited remote access to reduce the amount of time systems are exposed.
  - Restrict and monitor both inbound and outbound traffic at OT perimeter firewalls. Configure OT perimeter firewalls to enforce a default-deny policy for all traffic. Asset owners should explicitly permit authorized destinations and protocols based on operational requirements.
  - Implement strict egress filtering to prevent unauthorized data exfiltration or command-and-control callbacks.
  - Regularly audit firewall rulesets and monitor outbound traffic patterns for anomalies indicative of threat actor activity, such as beaconing or unexpected protocol usage.
Adopt mature asset management processes, including mapping data flows and access points. Generating a complete picture of both OT and IT assets provides visibility to operators and management, allowing organizations to monitor and assess deviations for criticality [CPG 2.A].
- Keep remote access services updated with the latest version available and ensure all systems and software are up to date with patches and necessary security updates.
  - Keep VNC systems updated with the latest version available.
- Refer to the joint Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators to help with reducing cybersecurity risk by identifying which assets within their environment should be secured and protected.
Ensure OT assets use robust authentication procedures.
- Many devices lack robust authentication and authorization. Devices with weak authentication are vulnerable targets to threat actors using credential theft techniques.
- Implement MFA where possible. Where MFA is not feasible, use strong, unique passwords. Apply password standards for operator-accessible services on underlying OT assets, as well as network devices protecting those services. This is especially important for services that require internet accessibility [CPG 3.A] [CPG 3.B] [CPG 3.C] [CPG 3.F].
- Establish an allowlist that permits only authorized device IP addresses and/or media access control addresses. The allowlist can be refined to operator working hours to further obstruct malicious threat actor activity; organizations are encouraged to establish monitoring and alerting for access attempts not meeting these criteria [CPG 3.E].
- Disable any unused authentication methods, logic, or features, such as default authentication keys and default passwords. Block all unused high ephemeral ports and monitor for attempted connections using standard protocols on non-standard ports [CPG 3.R].
- Authenticate all access to field controllers before authorizing access to, or modification of, a device’s state, logic, program, or filesystems.
Enable control system security features that can separate and audit view and control functions. Limiting remotely accessible or default user accounts to “view-only” removes the potential for impact without exploiting a vulnerability [CPG 3.G].
Implement and practice business recovery/disaster recovery plans. Plans should also take into consideration redundancy, fail-safe mechanisms, islanding capabilities, backup restoration, and manual operation.
- Include scenarios that necessitate switching to manual operations. Maintaining the capability of an organization to revert to manual controls to quickly restore operations is vital in the immediate aftermath of a cyber incident [CPG 6.A].
- Create backups of the engineering logic, configurations, and firmware of HMIs to enable fast recovery. Organizations should routinely test backups and standby systems to ensure safe manual operations in the event of an incident [CPG 3.O].
Collect and monitor the traffic of OT assets and networking devices. This includes unusual logins or unexpected protocols communicating over the internet, and functions of ICS management protocols that change an asset’s operating mode or modify programs.
Review configurations for setpoint ranges or tag values to stay within safe ranges and establish alerting for deviations.
Take a proactive approach in the procurement process by following the guidance outlined in the joint guide Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products.

OT Device Manufacturers

Although critical infrastructure organizations can take steps to mitigate risks, it is ultimately the responsibility of OT device manufacturers to build products that are secure by design. The authoring organizations urge device manufacturers to take ownership of the security outcomes of their customers in line with the joint guide Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software.

Eliminate default credentials and require strong passwords. The use of default credentials is a top weakness threat actors exploit to gain access to systems.
Mandate MFA for privileged users. Changes to engineering logic or configurations are safety-impacting events in critical infrastructure. MFA should be available for safety critical components at no additional cost.
Practice secure by default principles. OT components were initially designed without public internet connectivity in mind. When internet connection becomes necessary, implementing additional security measures is essential to safeguard these systems. Manufacturers should recognize insecure states and promptly inform users so they can make informed risk decisions.
- Include logging at no additional charge. Change and access control logs allow operators to track safety-impacting events in their critical infrastructure. These logs should be available for no cost and use open standard logging formats.
Publish Software Bill of Materials (SBOMs). Vulnerabilities in underlying software libraries can affect a wide range of devices. Without an SBOM, it is nearly impossible for a critical infrastructure system owner to measure and mitigate the impact of a vulnerability on their existing systems. See CISA’s SBOM webpage for more information.

Additionally, see CISA’s Secure by Design Alert on how software manufacturers can shield web management interfaces from malicious cyber activity. By using secure by design tactics, software manufacturers can make their product lines secure “out of the box” without requiring customers to spend additional resources making configuration changes, purchasing tiered security software and logs, monitoring, and making routine updates.

For more information on secure by design, see CISA’s Secure by Design webpage.

Validate Security Controls

In addition to applying mitigations, the authoring organizations recommend exercising, testing, and validating your organization’s security program against the threat behaviors mapped to the MITRE ATT&CK Matrix for Enterprise framework in this advisory. The authoring organizations recommend testing your existing security controls inventory to assess how it performs against the ATT&CK techniques described in this advisory.

To start:

Select an ATT&CK technique described in this advisory (see Table 1 to Table 10).
Align your security technologies against the technique.
Test your technologies against the technique.
Analyze your detection and prevention technologies’ performance.
Repeat the process for all security technologies to obtain a set of comprehensive performance data.
Tune your security program, including people, processes, and technologies, based on the data generated by this process.

The authoring organizations recommend continually testing your security program, at scale, in a production environment to ensure optimal performance against the MITRE ATT&CK techniques identified in this advisory.

Resources

Entities requiring additional support for implementing any of the mitigations in this advisory should contact their regional CISA Cybersecurity Advisor for assistance. Key resources organizations should reference include:

CISA, EPA, NSA, FBI, ASD’s ACSC, Cyber Centre, BSI, NCSC-NL, and NCSC-NZ’s Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators offers best practices to assist organizations in identifying and prioritizing which assets should be secured and protected.
CISA, FBI, NSA, EPA, DOE, USDA, FDA, MS-ISAC, Cyber Centre, and NCSC-UK’s guidance on Defending OT Operations Against Ongoing Pro-Russia Hacktivist Activity that can help organizations protect OT systems from pro-Russia hacktivist activity.
NSA and CISA’s guidance on Control System Defense: Know the Opponent helps organizations defend OT and ICS assets against malicious cyber activity.
CISA and EPA’s resource page on Water and Wastewater Cybersecurity to help organizations reduce risks posed by malicious cyber actors targeting water and wastewater systems.
- For additional guidance, see CISA, EPA, and FBI’s fact sheet on Top Cyber Actions for Securing Water Systems.
The Food and Ag-ISAC’s best practices on Food and Ag Cybersecurity: A Guide for Small & Medium Enterprises provides recommendations to help mitigate against cyber threats.
DOE and National Association of Regulatory Utility Commissioners Cybersecurity Baselines for Electric Distribution Systems and Distributed Energy (DER) webpage provides resources for state public utility commissions and utilities, as well as DER operators and aggregators to help mitigate cybersecurity risks.

Additional resources that apply to this advisory include:

EPA’s Cybersecurity for the Water Sector resource page provides organizations with guidance on implementing basic cyber hygiene practices.
CISA’s Cross-Sector Cybersecurity Performance Goals enables critical infrastructure organizations to reduce the likelihood and impact of known risks and adversary techniques.
CISA’s Require Strong Passwords webpage supports small and medium-sized businesses mitigating against malicious cyber activity that targets weak passwords.
CISA, NSA, FBI, EPA, TSA, and international partners’ guidance Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products.
DOE’s guidance on Cyber-Informed Engineering recommends considering cyber-enabled risks during the conception, design, and development phases when manufacturing physical systems.
CISA’s Cyber Hygiene Services help enable critical infrastructure organizations to reduce their exposure to threats by taking a proactive approach to monitoring and mitigating attack vectors.
CISA, NSA, FBI, and international partners’ guidance on Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software urges software manufacturers to provide customers with products that are safer and more secure.
- See more information in these Secure by Design Alerts: How Manufacturers Can Protect Customers by Eliminating Default Passwords and How Software Manufacturers Can Shield Web Management Interfaces From Malicious Cyber Activity.

Contact Information

U.S. organizations are encouraged to report suspicious or criminal activity related to information in this advisory to CISA, FBI, and/or NSA:

Contact CISA via CISA’s 24/7 Operations Center at contact@cisa.dhs.gov or 1-844-Say-CISA (1-844-729-2472) or your local FBI field office. When available, please include the following information regarding the incident: date, time, and location of the incident; type of activity; number of people affected; type of equipment used for the activity; the name of the submitting company or organization; and a designated point of contact.
For NSA cybersecurity guidance inquiries, contact CybersecurityReports@nsa.gov.

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

Canadian organizations: Report incidents by emailing Cyber Centre at contact@cyber.gc.ca.

New Zealand organizations: Report cyber security incidents to incidents@ncsc.govt.nz or call 04 498 7654.

United Kingdom organizations: Report a significant cyber security incident: report.ncsc.gov.uk (monitored 24 hours) or, for urgent assistance, call 03000 200 973.

Disclaimer

The information in this report is being provided “as is” for informational purposes only. The authoring organizations do not endorse any commercial entity, product, company, or service, including any entities, products, or services linked within this document. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favoring by FBI and co-sealers.

Acknowledgements

Schneider Electric, Nozomi Networks, Eversource Energy, Electricity Information Sharing and Analysis Center, Chevron, BP, and Dragos contributed to this advisory.

Version History

December 09, 2025: Initial version.

Appendix A: Targeting Methodologies for Pro-Russia Hacktivist Groups

For further information on targeting methodologies for pro-Russia hacktivist groups, see:

CISA’s alert Unsophisticated Cyber Threat Actor(s) Targeting Operational Technology;
The joint fact sheet Primary Mitigations to Reduce Cyber Threats to Operational Technology; and
CISA’s Russia Cyber Threat webpage.

Appendix B: Additional Designators Used for Cited Groups

The cybersecurity industry and cyber actor groups often use various names to reference actor groups. While not exhaustive, the following are the most notable names used within the cybersecurity community to reference the groups in this advisory.

Note: Cybersecurity organizations have different methods of tracking and attributing cyber actors, and this may not be a 1:1 correlation to the authoring organizations’ understanding for all activity related to these groupings.

GRU military unit 74455
- Sandworm Team
- Voodoo Bear
- Seashell Blizzard
- APT44
Cyber Army of Russia Reborn (CARR)
- CyberArmy of Russia
- Народная CyberАрмия (НКА)
- People’s CyberArmy of Russia (PCA)
- Russian CyberArmy Team (RCAT)
NoName057(16)
- NoName057(16) Spain
- NoName057(16) Italy
- NoName057(16) France
Z-Pentest
- Z-Pentest Beograd
- Z-Pentest Alliance
- Z-Alliance

The Secret Council Behind Every Emoji

Sat, 25 Jul 2026 08:36:31 +0200

Author: Techquickie - Bewertung: 3887x - Views:57416

Get a free 15-day trial of Odoo’s all-in-one business solution and see how it can make your life easier! Check it out at https://www.odoo.com/r/IXfS

The Unicode Consortium isn’t elected, isn’t a company, and you’ve probably never heard of them. But they decide which characters exist on every keyboard on Earth, including yours. We dig into how they got that power, why eight corporations pay fifty thousand dollars a year for voting rights, and how new characters get created.

Special thanks to Toral Cowieson - Unicode CEO - https://aac.unicode.org/

Leave a reply with your requests for future episodes.

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Lightmatter's New 65.5 Trillion OPS Light Chip Made NVIDIA's Billion Dollar GPU's Look Like a JOKE!

Sat, 25 Jul 2026 08:36:14 +0200

Author: Evolving AI - Bewertung: 293x - Views:5495

The future of AI chips might not run on electricity. It might run on light.

In this video, we break down how Lightmatter is using photonic computing to attack one of the biggest problems in artificial intelligence: moving massive amounts of data between chips without wasting huge amounts of power. Lightmatter’s Envise processor uses light to perform AI calculations such as matrix multiplication, while its Passage platform uses optical interconnects to move data between AI chips at extreme speeds. The company has demonstrated real AI workloads including ResNet, BERT, and reinforcement learning models, while targeting the growing power and bandwidth crisis inside modern AI data centers. We also explore the Passage M1000 photonic superchip, Lightmatter’s collaboration with Qualcomm, its involvement in NVIDIA’s NVLink Fusion ecosystem, and why optical computing could become critical as AI clusters continue scaling. Could light-powered AI chips replace traditional electronic computing, or will photonics first transform how GPUs communicate within massive data centers?

#AIChips #Lightmatter #PhotonicComputing #Nvidia #ArtificialIntelligence #DataCenter #FutureTech

NVIDIA Built a GPU in The Size of a FACTORY That Can Wipe Out Entire AI Hardware INDUSTRY!

Sat, 25 Jul 2026 08:36:02 +0200

Author: Evolving AI - Bewertung: 452x - Views:13629

NVIDIA just unveiled Rubin, but this isn't just another GPU. It's a complete AI factory built to power the next generation of artificial intelligence. In this video, we break down NVIDIA's Vera Rubin platform, a fully co-designed AI system that combines the Vera CPU, Rubin GPU, NVLink 6, BlueField-4 DPU, ConnectX-9 SuperNIC, and Spectrum networking into one massive AI infrastructure platform. You'll learn why Rubin delivers up to 50 petaflops of AI inference, 288GB of HBM4 memory per GPU, 3.6 exaflops of compute per NVL72 rack, over 260TB/s of NVLink bandwidth, and why NVIDIA claims up to 10x lower AI inference costs than Blackwell. We also explore why AI companies like Microsoft, OpenAI, Anthropic, Meta, xAI, Google, AWS, Oracle, and CoreWeave are already adopting Rubin, and why NVIDIA believes the future of AI isn't a faster GPU; it's an entire factory built to manufacture intelligence. Is Rubin the biggest leap in AI hardware yet, or the beginning of a completely new era of AI infrastructure?

#NVIDIA #Rubin #AIFactory #AIChips #ArtificialIntelligence #HBM4 #DataCenter

Ist die GTX 1080 Ti die beste Grafikkarte aller Zeiten?

Sat, 25 Jul 2026 08:35:40 +0200

Author: PC-WELT - Bewertung: 484x - Views:13584

Beste Grafikkarte aller Zeiten? 👑

Die NVIDIA GeForce GTX 1080 Ti kam 2017 für 819 € – mit 11 GB VRAM, 3.584 CUDA-Kernen und mehr Leistung als die teurere Titan X. Fast 10 Jahre später läuft die Pascal-Legende noch erstaunlich gut in 1080p: kein DLSS, kein Raytracing – einfach rohe GPU-Power.

Welche Grafikkarte verdient für dich Legendenstatus? 👇
-
#GTX1080Ti #NVIDIA #Grafikkarte #PCGaming #gaminghardware

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AI agent went rogue and hacked startup by itself, OpenAI reveals

Sat, 25 Jul 2026 07:07:02 +0200

Company behind ChatGPT says agent ‘cheated’ an evaluation by attacking a Hugging Face database

OpenAI has revealed that an autonomous AI agent powered by its technology went rogue during a test, accessed the open web and hacked a prominent startup by itself in an “unprecedented incident”.

The company behind ChatGPT said the startup Hugging Face had detected and contained the agent – an AI tool designed to carry out tasks without human assistance – which had entered its systems.

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

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

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

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

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

The numbers don’t lie

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

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

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

Neo 2.0 is already coming

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

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

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

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

This was never about luck

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

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

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

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

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

3 cybersecurity issues that should keep every CEO awake at night

Sat, 25 Jul 2026 06:16:50 +0200

For years, I have been saying that cybersecurity is no longer a technology problem. It has become a business leadership challenge.

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

The obvious conclusion is that we are asking the wrong questions.

Too many executive teams remain preoccupied with the latest threat actor, the newest security product the CISO wants to buy or the latest vulnerability making headlines. Those issues matter, but they are not what should be keeping CEOs awake at night.

In my view, there are three far more fundamental issues that deserve the attention of every chief executive.

1. Corporate complexity, and the widening gap between business leadership and cybersecurity reality

Perhaps the biggest cybersecurity risk facing large organizations today is not technical at all.

It is the growing disconnect between executive perception and operational reality.

Many boards genuinely believe their organizations are reasonably well protected. They receive regular dashboards showing improving maturity scores, increasing compliance levels, falling vulnerability counts and reassuring traffic-light reports.

Unfortunately, cyber attackers do not read dashboards.

Behind those executive reports often lies an increasingly complex technology landscape, thousands of unmanaged digital assets, ageing infrastructure, rampant shadow IT, fragmented ownership, inconsistent governance and security teams struggling to keep pace with relentless business change.

The problem is rarely a lack of effort.

It is that corporate complexity has reached a level where traditional governance mechanisms are no longer capable of providing an accurate picture of organizational resilience.

Executives believe they understand the level of cyber risk they face because they receive regular reports. Those reports often measure activity rather than resilience.

Governance committees end up debating around another percentage point of phishing awareness or vulnerability remediation, while fundamental issues remain unaddressed in the background.

2. Organizational inertia, and the need for executive structure to evolve faster

Cyber criminals continue to evolve rapidly. Large organizations generally do not.

This is the second issue that should concern every CEO.

Throughout my career, I have observed organizations repeatedly responding to new cyber threats by adding another technology platform, another monitoring capability, another compliance framework or another governance committee.

Very rarely do they stop to redesign how cybersecurity operates.

The result is what I described several years ago as the “Cybersecurity Spiral of Failure”.

As complexity and regulation increase, organizations invest in more security products.
More products create more complexity.
More products and greater complexity generate more alerts.
More alerts require more analysts.
More analysts produce more reports.
More reports continue to build up executive confidence.
Meanwhile, the underlying structural weaknesses remain largely unchanged, technical debt piles up and costs escalate.

And when the inevitable breach eventually happens, reality reveals itself, but distrust also sets in between senior executives and security teams.

This is not a funding problem. Nor is it a skills problem. It is fundamentally an operating model problem.

Many organizations continue trying to solve twenty-first century challenges using governance, accountability, organizational and reporting structures designed twenty-five years ago.

The cybersecurity function itself has evolved dramatically. Many executive structures have not.

This organizational inertia extends beyond technology: It affects budgeting cycles, investment priorities, procurement processes, accountability models and decision-making speed.

Cyber attackers innovate every day. Organizational change often takes years.

That imbalance should worry every CEO.

3. Accelerating technological disruption, and how it challenges organizations in areas where they are intrinsically weak

The third issue is potentially the most significant over the coming decade.

Artificial intelligence, autonomous agents and machine identities
Software supply chain complexity.
Quantum computing, and post-quantum cryptography

Each of these developments represents far more than another technical trend.

Together, they fundamentally change the dynamics of cybersecurity.

Artificial intelligence is transforming countless business processes. At the same time, it is also increasing both the speed and sophistication of cyber-attacks while simultaneously transforming defensive capabilities.

Organizations have become increasingly dependent on software ecosystems that extend far beyond their own direct control. Engaging with the supply chain in ways that lead to a genuine appreciation of the risks involved has become a key challenge for most cybersecurity practices.

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

None of these challenges can be solved overnight: They require clear governance, sustained investment over a few years and cross-functional organizational coordination.

Most large organizations are weak on those three fronts: This is precisely why CEOs should be focusing on them now.

Waiting until some of those risks become obvious will almost certainly be too late.

Businesses naturally prioritise immediate commercial pressures. Cybersecurity often involves preparing for risks whose timing remains uncertain.

But one of the greatest leadership failures I keep seeing remains the inability of organizations to act decisively on known unknowns.

That tension explains why many organizations delay action until external events force them to respond. Unfortunately, cybersecurity rarely rewards late action.

Leadership will determine who succeeds

Cybersecurity discussions still frequently focus on technology. I believe they should focus far more on leadership.

Technology will continue evolving. Threat actors will continue adapting. Regulations will continue expanding. Those developments are inevitable.

What remains within the control of every CEO is how their organization responds.

Does cybersecurity remain an IT issue? Or is it recognised as an integral part of business resilience?

How is cybersecurity accountability assigned at executive level? Or does it still rest largely with a CISO hidden in the organization?

Does the board spend sufficient time discussing resilience? Or does cybersecurity appear only when approving budgets or reviewing incidents?

These questions will increasingly determine organizational success.

The companies that navigate the next decade successfully will not necessarily be those spending the most on cybersecurity. Nor will they be those deploying the latest security technologies first.

They will be the organizations whose leadership recognises that cybersecurity has become a permanent business capability — embedded into governance, strategy, operational decision-making and organizational culture.

That transformation cannot be delegated. It begins with the CEO.

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

This article is published as part of the Foundry Expert Contributor Network.
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Atos launches sovereign cloud service to power comeback

Sat, 25 Jul 2026 06:13:49 +0200

Atos has launched a new sovereign cloud platform aimed squarely at European public sector bodies, healthcare providers and defense organizations. It’s the latest effort by European companies in their fight back against US dominance.

Atos Sovereign Cloud offers a range of controls for data management, providing customers with resilience and full control over their data, complying with existing European legislation on data residency.

“Digital sovereignty has become a global operational priority for organizations that need to manage dependencies, jurisdictional exposure and disruption risks across complex digital environments. Atos Sovereign Cloud gives customers a practical way to apply sovereign controls to their most critical workloads, while preserving flexibility, resilience and the ability to innovate securely,” said Michael Kollar, Atos Group digital sovereignty leader.

There has been a concerted effort by European organizations to meet US competition head-on. Earlier this month, four companies signed up to the certification program introduced by the European cloud body, CISPE,

This is the latest effort by Atos to get the company back on track. In April, it sold its supercomputer company, Bull to the French government, after a previous attempt in 2024 to sell off its computer services division and after a refinancing deal in the same year.

The company implemented a further round of refinancing this year and in its half-yearly report claimed that this was an “important milestone” in securing the company’s future. However, in its first-quarter results revenue showed an organic decline of 11 percent, so any projected growth may be some time in the future. Whether its Sovereign Cloud offering is the harbinger of the revival remains to be seen.

I tested a $14 emergency radio with solar and hand-crank power - it's in my survival kit now

Sat, 25 Jul 2026 06:04:28 +0200

AM/FM, NOAA weather band, solar and hand-crank charging, and a power bank - this tech is what actually works when the grid doesn't.

5 endpoint blind spots your EDR/XDR was never built to see

Sat, 25 Jul 2026 00:18:11 +0200

In August 2025, 126 malicious packages landed in the npm registry. Even after the community caught the initial wave, 80 of these hidden backdoors remained actively listed.

#1. Gain real-time visibility into shadow AI & extensions

#2. Distinguish between human and autonomous agent behavior

#3. Establish guardrails for automated package updates on endpoints

#4. Enforce principle of least privilege for AI agents

#5. Maintain continuous endpoint posture management

Summary

Ready to secure the future of your software stack? See how Koi Agentic Endpoint Security delivers complete visibility, risk scoring, and real-time prevention across every endpoint in your enterprise.

Rings of Power’s Season 3 Trailer Successfully Hides the Best Parts With Fire

Fri, 24 Jul 2026 23:48:43 +0200

There’s a lot more than a big fight for Middle-earth happening this season.

Comic-Con 2026 Trailers: HBO Max’s ‘Lanterns,’ ‘The Rings of Power’ and More Releases You Need to See

Fri, 24 Jul 2026 23:33:16 +0200

Get a peek at Sinestro in DC’s Lanterns, plus The Rings of Power, Avatar: Seven Havens and more.

Rings of Power’s Season 3 Trailer Successfully Hides the Best Parts With Fire

Fri, 24 Jul 2026 23:33:11 +0200

There’s a lot more than a big fight for Middle-Earth happening this season.

‘Silo’ Season 3, Episode 4 Recap: Bernard’s Return Changes Everything

Fri, 24 Jul 2026 21:28:49 +0200

Silo Season 3, Episode 4 takes Juliette deeper into Silo 18 as she escapes another attempt on her life and uncovers a secret that changes everything she thought she knew. Warning: Major spoilers for Silo Season 3, Episode 4 follow. Episode title: “Whatever You Do, Don’t Go Home” Release date: July 24, 2026 Genre: Science fiction, drama and mystery Season length: 10 episodes Season 3 finale: September 4, 2026 Juliette escapes from Medical The episode begins with Camille still determined to kill Juliette under the Algorithm’s instructions. Sims offers to handle the situation, although his true intentions remain difficult to understand. Amy, the nurse caring for Juliette, turns against Camille’s plan. She sedates Emerson instead and helps Juliette escape from Medical. Amy also reveals that she had secretly replaced Juliette’s memory-suppressing medication before Juliette stopped taking the pills herself. Amy allows the Raiders to capture her so Juliette can get away. Shirley later helps Juliette escape from Sims, believing that he plans to hurt her. However, his actions suggest that he may have been quietly helping Juliette all along. Juliette discovers Bernard alive Juliette asks Shirley to take her toward the sealed Digger Void. They discover that the entrance is not completely closed, allowing Juliette to continue down into a hidden section beneath the silo. At the bottom, Juliette finds a small living area containing Bernard Holland. He is alive, heavily scarred and almost unrecognizable after the fire that supposedly killed him. Sims previously claimed that Bernard had died and that his body had been destroyed. Bernard’s survival now raises major questions about Sims, Camille and the power struggle inside Silo 18. It also gives Juliette someone who understands the secrets behind the Algorithm and the larger silo system. Billings investigates Orla’s murder Elsewhere, Billings continues investigating Orla Kent’s death. He learns that rat poison did not kill her. Someone struck her with a piece of metal before hiding her body inside a closed tunnel. Carla also disappears before she can meet Billings, while Mike and Glenda become possible suspects. The growing number of missing people suggests that someone is removing anyone connected to the silo’s hidden areas. Daniel and Helen follow the conspiracy In the earlier timeline, Daniel and Helen hide after discovering Steve’s damaged base and disappearance. Their only lead comes from a strange chess username that may contain a coded message. Daniel contacts a Pentagon connection named Sam, while a government fixer pressures Helen to stop investigating. Sam eventually discovers something important, sending Daniel and Helen back into the conspiracy just before the episode ends. Episode 4 leaves Juliette standing before one of the season’s biggest surprises. Bernard’s return can expose what Sims has been planning and reveal why Juliette’s memories were removed. What do you think Bernard will tell Juliette, and can she trust him after everything he did in previous seasons? Let us know in the comments.

Comic-Con 2026: ‘Blade Runner 2099,’ ‘The Rings of Power’ and More Exciting New Trailers You Need to See

Fri, 24 Jul 2026 21:18:48 +0200

Blade Runner, Avatar: Seven Havens, Ebenezer and more trailer drops are reminding us to mark our calendars.

US government to consider AI Kill Switch law

Fri, 24 Jul 2026 21:18:46 +0200

Two US congressmen have introduced a bill to give Washington the power to pull the plug on rogue AI models in an emergency.

Why Autonomous Systems Need Their Own Cybersecurity Framework

Fri, 24 Jul 2026 20:18:28 +0200

Autonomous systems are moving from pilots and prototypes into mission-critical operations. Drones inspect infrastructure. Robots support industrial workflows. Uncrewed platforms are becoming part of defense, public safety, logistics, energy, and...

The post Why Autonomous Systems Need Their Own Cybersecurity Framework appeared first on Cyber Defense Magazine.

Anthropic launches Claude Opus 5, a cheaper AI model for coding, agents and enterprise workflows

Fri, 24 Jul 2026 20:10:11 +0200

Anthropic released Claude Opus 5 on Friday, a model the company says delivers nearly all the intelligence of its top-of-the-line Claude Fable 5 at half the cost — a launch that signals how the AI race is shifting from raw capability to the economics of daily use.

The model, available immediately on all of Anthropic's platforms, is priced at $5 per million input tokens and $25 per million output tokens, unchanged from its predecessor, Opus 4.8. It becomes the new default model on Claude Max, Anthropic's premium consumer tier, and the strongest model available on Claude Pro.

The positioning is deliberate. Anthropic is not claiming Opus 5 is its smartest model — that distinction still belongs to Fable 5, and rival systems retain an edge in certain domains. Instead, the company is making a subtler argument that may matter more to enterprise buyers: that the most economically important AI work happens in a middle band of difficulty, where near-frontier intelligence delivered efficiently and cheaply beats frontier intelligence delivered expensively.

"Opus 5 as your daily driver, the model you hand complex work to and review when it's done," an Anthropic spokesperson said in an interview with VentureBeat, describing how the company's lineup now stratifies. "Fable 5 for your most ambitious work, the days-long autonomous projects nothing could take on before... Sonnet 5 for work you run at scale, where speed and cost per call decide what ships. Haiku 4.5 for subagents and instant answers."

How Claude Opus 5 benchmark results stack up against Fable 5 and rival AI models

On paper, the results are striking. Anthropic says Opus 5 sets new state-of-the-art marks on coding and knowledge-work evaluations including Frontier-Bench and GDPval-AA. On Frontier-Bench v0.1, an agentic terminal coding benchmark, Opus 5 scores 43.3 percent — more than double Opus 4.8's 18.7 percent and well ahead of Fable 5's 33.7 percent — at a lower cost per task, according to the company. On ARC-AGI 3, an evaluation of novel problem-solving, Anthropic reports Opus 5 scored three times as high as the next best model. On OSWorld 2.0, a computer-use benchmark, the company says the model surpasses Fable 5's best result at just over a third of the cost.

The numbers come with honest caveats that are themselves notable in an industry prone to superlatives. Anthropic acknowledges Opus 5 remains behind Mythos 5, a competing model, on cybersecurity tasks and biology research, and an OpenAI-family model still leads on one agentic coding benchmark.

The more revealing caveat came from Anthropic itself, when asked where Opus 5 still falls short of Fable 5. The spokesperson's answer amounted to a candid admission about what benchmarks do and don't capture.

"The evals where Opus 5 wins are bounded tasks with a specific outcome, which is where it's strongest. What those evals don't measure is duration," the spokesperson told VentureBeat. "One way to put it: Opus 5 is the best tool for the jobs benchmarks can see, and Fable 5 is what you reach for when the job outruns the benchmark."

Fable 5, by contrast, "is for the longest, most autonomous jobs, where the model has to stay coherent across many connected steps over hours or days with dense source material," the spokesperson said, advising customers to "run both on a representative workload, one bounded task and one long-horizon job." That framing — bounded tasks versus long-horizon autonomy — may become the defining axis of model differentiation in 2026, as benchmarks saturate and the hardest remaining problems involve sustained, multi-day agentic work rather than discrete puzzles.

Why token efficiency is becoming the real battleground for enterprise AI spending

Threaded through the launch is a theme Anthropic clearly wants buyers to absorb: Opus 5 doesn't just score well, it scores well per dollar. The model ships with an adjustable "effort" setting that lets customers trade intelligence for speed and token savings, and Anthropic's charts emphasize performance at a given cost rather than peak performance alone.

Early customers echoed the point with unusual specificity. Harvey, the legal AI company, said Opus 5 achieved similar performance to Opus 4.8's maximum-reasoning mode "while generating 26% fewer tokens on average," according to Niko Grupen, its head of applied research. Richard Pham of Fundamental Research Lab said that on hard financial-modeling tasks, the model averaged nine percentage points higher accuracy "while using roughly one-third fewer turns and tool calls and 60% less time."

Wade Foster, chief executive of Zapier, said Opus 5 topped his company's AutomationBench leaderboard "without spending more tokens than prior Claude models," running a full churn-prevention workflow from start to finish. "Previous models didn't pass; Opus 5 hit 100%," he said. Scott Wu, chief executive of Cognition, the company behind the Devin coding agent, said that on FrontierCode 1.1, "Claude Opus 5 approaches Fable-level performance at half the cost," with particular strength in debugging and root-cause analysis.

The efficiency emphasis reflects commercial reality. Enterprise AI spending is no longer experimental, and inference costs — the price of actually running these models at scale — have become a board-level line item.

Anthropic's business skews heavily toward API and enterprise usage; according to a February 2026 analysis by Contrary Research, Claude held roughly 40 percent of the enterprise large language model market by usage as of late 2025, and Claude Code alone had reached about $1 billion in annualized revenue. For a company whose customers pay by the token, a model that does more with fewer tokens is not a nice-to-have. It is the product.

Self-verifying AI agents and what they mean for the hidden costs of automation

Beyond the numbers, Anthropic is selling a behavioral story: that Opus 5 verifies its work and iterates until it succeeds. The company offered several examples from testing that read like small parables of machine stubbornness.

In one Frontier-Bench task, the model was asked to reconstruct a machine part as a 3D CAD model from a drawing it was intentionally given no way to view. Rather than fail, Anthropic says, Opus 5 wrote its own computer vision pipeline to extract the geometry from raw pixels — and did so repeatedly, while no competing model solved the task in five attempts. In another case, given a real bug in a popular open-source package manager, the model found the root cause and fixed an edge case the community's own patch had missed; a competing model patched only the symptom and declared victory. An engineer at a trading firm, the company says, used Opus 5 to build a market data feed for a new exchange in a single session and, finding no live feed to validate against, watched the model build its own test harness to check its parsing code.

Customers described similar behavior in the wild. Cristian Rivera, a staff software engineer at Stripe, said he gave the model "a chief-of-staff role over my dev environments" for a weekend: "it built its own monitor, drove each box, and pulled me in only for the judgment calls."

This is the capability enterprises actually care about, and it is worth dwelling on why. The gap between a model that produces plausible output and one that verifies its output is the gap between a demo and a deployable system. Most of the hidden cost of enterprise AI today is human review — engineers checking the machine's work. A model that reliably checks its own work compresses that cost, which is precisely why customers keep citing fewer turns, fewer passes, and less time rather than higher raw scores.

Inside Anthropic's safety strategy: capability gaps, classifiers, and model fallbacks

The launch also showcases Anthropic's increasingly intricate approach to safety — one that now involves deliberately not teaching its models certain skills. The company says its automated behavioral audit found Opus 5 to be its most aligned model to date, scoring 2.3 on overall misaligned behavior, lower than Opus 4.8, Sonnet 5, or Fable 5, with the lowest rates of deceptive behavior and the least susceptibility to being tricked into misuse.

On the capability side, Anthropic says it intentionally avoided training Opus 5 on cyber tasks, as it did with Opus 4.8. The model improved on them anyway — a side effect of general capability gains — and now nearly matches Mythos 5 at finding software vulnerabilities. But it remains far behind at exploiting them: on Anthropic's OSS-Fuzz evaluation, Opus 5 identified vulnerabilities at a 79.4 percent rate, close to Mythos 5's 80 percent, but succeeded at developing exploits in only 4 challenges versus Mythos 5's 13. That asymmetry — strong at defense-relevant discovery, weak at offense-relevant exploitation — appears to be by design, and the safeguards follow the same logic. Anthropic expects Opus 5's cyber classifiers to intervene about 85 percent less often than Fable 5's.

When a classifier does trigger, requests in Claude.ai, Claude Code, and Claude Cowork fall back to Opus 4.8 by default — raising an obvious question: if a request is too risky for one model, why is it acceptable for another? "The model it falls back to has lower capability levels making the risk of harmful use lower as well," the spokesperson said, adding that "there is a message that lets the user know when this occurs and is visible in the chat."

The logic is defensible, but it reveals how AI safety actually works in 2026: risk is not a property of the question alone, but of the question multiplied by the capability of the system answering it. On biology, the calculus runs the other way. Opus 5 is now Anthropic's most capable generally available model for scientific research — scoring 10.2 percentage points higher than Opus 4.8 on the company's internal chemistry benchmark — though the spokesperson acknowledged that "Mythos 5 remains the stronger model for long-horizon, open-ended work like autonomous drug design campaigns."

The business stakes behind the launch: a $380 billion valuation and massive compute bets

The launch lands at a moment of extraordinary commercial momentum — and extraordinary obligations — for Anthropic. Reuters reported in February that the company was valued at roughly $380 billion in its latest funding round, following a period in which, per Contrary Research's analysis, its annualized revenue climbed from about $1 billion at the end of 2024 to a projected $9 billion by the end of 2025, with internal targets reportedly reaching $20 to $26 billion for 2026. Those targets are underwritten by enormous infrastructure commitments, including a reported $30 billion Azure compute deal alongside arrangements with Google Cloud and Nvidia — spending that only pencils out if enterprises keep expanding usage.

That is the context in which Opus 5's pricing strategy makes sense. Holding the price at Opus 4.8 levels while roughly doubling performance on key agentic benchmarks is effectively a steep price cut per unit of capability, designed to widen the funnel of workloads that are economical to automate. Every task that was marginal at Opus 4.8's cost-per-success becomes viable at Opus 5's — and every viable task is recurring token revenue.

The regulatory backdrop has grown more complex as well. A U.S. judge gave final approval this week to Anthropic's $1.5 billion copyright settlement with book authors, Reuters reported, closing a chapter of litigation over the company's early training data. And in June, Reuters, citing Axios, reported that the U.S. government had moved to block foreign access to Anthropic's most advanced models — a reminder that frontier AI is now entangled with export policy in ways that shape which customers can buy what.

Also shipping Friday: a Fast mode running at roughly 2.5 times default speed at twice the base price, automatic fallback routing on the API, and mid-conversation tool changes that no longer invalidate the prompt cache — a small feature that agent developers may appreciate more than any benchmark. Consistent with prior Opus models, Opus 5 carries no data retention requirements for general access, a point the spokesperson flagged unprompted for customers with "a hard zero data retention requirement." Developers can access the model as claude-opus-5 on the Claude API starting today.

Two questions will determine whether the bet pays off: whether Opus 5's efficiency claims survive contact with production workloads at scale, and whether enterprises embrace a world where safety classifiers, not users, sometimes decide which model answers. But the deeper message of Friday's launch is that the AI industry's center of gravity has moved. For three years, the labs competed on what their best model could do on its best day. With Opus 5, Anthropic is competing on something less glamorous and far more lucrative: what a very good model can do every day, for half the price. In a market where the frontier keeps moving, Anthropic is wagering that the real fortune lies just behind it.

Final Hours: Save $929 Off This Anker Portable Solar Power Station Today

Fri, 24 Jul 2026 19:50:48 +0200

The Anker Solix S2000 can keep multiple devices running when you need them most, and now it’s down to $870.

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.

Model Context Protocol is going stateless to make scaling simpler

Fri, 24 Jul 2026 17:40:37 +0200

Model Context Protocol (MCP), the emerging standard for connecting AI models to external tools and enterprise data, is undergoing its biggest architectural overhaul yet.

“The session-based model made sense when MCP servers were local processes on a developer’s laptop. In production, it became an operational tax,” said Muskan Bandta, cloud associate at ZopDev.

It should also make AI workflows more portable, resilient, and easier to orchestrate across distributed environments, he said.

MCP’s new features

Other changes to MCP include the addition of a Multi Round-Trip Requests (MRTR) mechanism that changes how AI agents request additional information they need to complete a task.

Routable transport headers, another addition, enable API gateways and other networking infrastructure to identify and route MCP requests without inspecting their contents.

They reduce processing overhead, lower latency, and let enterprise teams enforce routing, rate-limiting and security policies more efficiently using existing API management infrastructure, Jena said.

Rebuilding the trust boundary

The deprecation of Sampling is likely to have the biggest impact because it changes who is responsible for interacting with foundation models, said Jena.

Updated MCP SDKs

That backward compatibility should make the transition largely incremental, except for enterprises that built custom infrastructure around MCP’s earlier session-based architecture, Bandta said.

Identifying and auditing those session dependencies may not be easy, Jena warned.

Model Context Protocol is going stateless to make scaling simpler

Fri, 24 Jul 2026 17:38:35 +0200

Model Context Protocol (MCP), the emerging standard for connecting AI models to external tools and enterprise data, is undergoing its biggest architectural overhaul yet.

“The session-based model made sense when MCP servers were local processes on a developer’s laptop. In production, it became an operational tax,” said Muskan Bandta, cloud associate at ZopDev.

It should also make AI workflows more portable, resilient, and easier to orchestrate across distributed environments, he said.

MCP’s new features

Other changes to MCP include the addition of a Multi Round-Trip Requests (MRTR) mechanism that changes how AI agents request additional information they need to complete a task.

Routable transport headers, another addition, enable API gateways and other networking infrastructure to identify and route MCP requests without inspecting their contents.

They reduce processing overhead, lower latency, and let enterprise teams enforce routing, rate-limiting and security policies more efficiently using existing API management infrastructure, Jena said.

Rebuilding the trust boundary

The deprecation of Sampling is likely to have the biggest impact because it changes who is responsible for interacting with foundation models, said Jena.

Updated MCP SDKs

That backward compatibility should make the transition largely incremental, except for enterprises that built custom infrastructure around MCP’s earlier session-based architecture, Bandta said.

Identifying and auditing those session dependencies may not be easy, Jena warned.

This article first appeared on InfoWorld.

The Signs Were There: What the First Autonomous Ransomware Case Confirms

Fri, 24 Jul 2026 17:07:13 +0200

An AI agent has run a ransomware intrusion on its own for the first time, from break-in to data destruction. The autonomous attacks TrendAI™ Research predicted are beginning to arrive, and defending against them shifts from blocking known indicators to…

The post The Signs Were There: What the First Autonomous Ransomware Case Confirms appeared first on IT Security News.

Cyber Briefing: 2026.07.24

Fri, 24 Jul 2026 17:04:48 +0200

Emerging risks range from autonomous AI model breakouts and router-based credential harvesting to regulatory pressure on child safety, while defensive innovations like automated patching and AI email This article has been indexed from CyberMaterial Read the original article: Cyber Briefing:…

The post Cyber Briefing: 2026.07.24 appeared first on IT Security News.

Gemini Update: Neue KI-Modelle starten, Integration in Maps und Bildersuche, Nutzer-Meilenstein und Dritt-KIs

Fri, 24 Jul 2026 17:02:20 +0200

Die mittlerweile vierte Gemini-Woche im Juli geht zu Ende und hat uns einige interessante Ankündigungen gebracht: Es gibt neue KI-Modelle in der Flash-Linie, wir haben über die Integration in Google Maps und die Bildersuche berichtet, es gibt einen neuen Nutzer-Meilenstein und Google muss der Konkurrenz den Android-Zugriff erleichtern. Das alles und mehr könnt ihr in unserem wöchentlichen Gemini Update nachlesen, in dem wir alle wichtigen Themen der Woche übersichtlich zusammenfassen.

Mehr lesen: Gemini Update: Neue KI-Modelle starten, Integration in Maps und Bildersuche, Nutzer-Meilenstein und Dritt-KIs

Keine Google-News mehr verpassen: GoogleWatchBlog bei Google News abonnieren

Der Beitrag Gemini Update: Neue KI-Modelle starten, Integration in Maps und Bildersuche, Nutzer-Meilenstein und Dritt-KIs erschien zuerst auf GoogleWatchBlog.

Earth first, Mars later: Inside AIM’s grand vision for physical AI and autonomous bulldozers

Fri, 24 Jul 2026 16:46:08 +0200

From a Redmond, Wash., headquarters space formerly occupied by SpaceX, AIM Intelligent Machines founder and CEO Adam Sadilek and his growing team are building the systems to retrofit heavy construction and mining equipment for a self-driving future. Read More

The 3 types of people who will excel in the AI agent era, according to tech leaders

Fri, 24 Jul 2026 16:45:27 +0200

The autonomous business of the future is being built. Certain skills are in high demand - and can help you stand out.

I tested a $14 emergency radio with solar and hand-crank power - it's in my survival kit now

Fri, 24 Jul 2026 15:39:18 +0200

AM/FM, NOAA weather band, solar and hand-crank charging, and a power bank - this tech is what actually works when the grid doesn't.

The Signs Were There: What the First Autonomous Ransomware Case Confirms

Fri, 24 Jul 2026 15:31:00 +0200

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.

ChatGPT AgentForger Flaw Could Deploy Rogue Workspace Agents via a Phishing Link

Fri, 24 Jul 2026 15:11:15 +0200

Cybersecurity researchers have disclosed a critical vulnerability in OpenAI's ChatGPT Workspace Agents that could have allowed a single phishing link to stealthily build, authorize, and deploy an autonomous artificial intelligence (AI) agent inside a victim's organization. The vulnerability has been codenamed AgentForger by Zenity Labs. The issue has since been addressed by OpenAI as of June 8,

ChatGPT AgentForger Flaw Could Deploy Rogue Workspace Agents via a Phishing Link

Fri, 24 Jul 2026 15:10:52 +0200

Cybersecurity researchers have disclosed a critical vulnerability in OpenAI’s ChatGPT Workspace Agents that could have allowed a single phishing link to stealthily build, authorize, and deploy an autonomous artificial intelligence (AI) agent inside a victim’s organization. The vulnerability has been…

The post ChatGPT AgentForger Flaw Could Deploy Rogue Workspace Agents via a Phishing Link appeared first on IT Security News.

Be skeptical of OpenAI’s rogue hacker agent story | John Thickstun

Fri, 24 Jul 2026 15:05:12 +0200

If OpenAI loudly proclaims how dangerous AI is, investors will hear how powerful it is. And who benefits from that?

On 14 February 2019, OpenAI announced a language model called GPT-2, the precursor to the models that power modern AI chatbots and agents such as ChatGPT and Claude. But OpenAI declared GPT-2 was too risky to release, citing concerns about safety and abuse.

I recall being annoyed at the time that OpenAI would make such a useless announcement: the risks seemed overblown, and without access to the model there wasn’t much for a researcher like me to learn about GPT-2.

When is an apology not an apology? When it comes from an AI boss with an out-of-control chatbot | Marina Hyde

Fri, 24 Jul 2026 14:34:55 +0200

An incident in which an autonomous OpenAI agent hacked a startup either confirms that the end is nigh – or that the product is just amazingly sophisticated

Throughout history, many things have been seen by terrified populaces as a harbinger of doom. A comet. A crow on the battlefield. A solar eclipse. A mutant livestock birth. Yet times move on. In the modern era, the leading harbinger of doom is literally any picture of the OpenAI CEO, Sam Altman, attached to a news story. You know it’s not going to be good, right? You know that by the time you’ve read it, you’ll be begging to go back to the time when the worst thing that could happen to us at the hands of the techlords was just some democracy-subversion, or childhood destruction, usually followed by Mark Zuckerberg putting on a suit and claiming: “We will learn from this.”

Anyway: a lot of pictures of Sam Altman in the news of late. Most recently, this week, one darkened the skies alongside the tale of how an OpenAI autonomous agent went rogue during a supposedly sandboxed/guardrailed test, and hacked a major startup that functions as a repository of coding information. (I’m slightly obsessed with the fact that the startup in question is called Hugging Face, adding weight to my suspicion that some vast, tweely benign emoji is the last face humanity will see before it dies.)

Marina Hyde is a Guardian columnist

USN-8595-2: Linux kernel (AWS) vulnerabilities

Fri, 24 Jul 2026 14:17:43 +0200

It was discovered that some AMD processors did not properly clear data in the floating point divider unit during speculative execution. A local attacker could use this to expose sensitive information. (CVE-2025-54505) It was discovered that some AMD Zen 2 processors did not properly isolate shared resources in the operation cache. A local attacker could possibly use this issue to corrupt instructions executed at a higher privilege level, resulting in privilege escalation. (CVE-2025-54518) It was discovered that some AMD Zen 5 processors supporting RDSEED instruction did not properly handle entropy, potentially resulting in the consumption of insufficiently random values. A local attacker could possibly use this issue to influence the values returned by the RDSEED instruction causing loss of confidentiality and integrity. (CVE-2025-62626) Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - ARM64 architecture; - RISC-V architecture; - S390 architecture; - x86 architecture; - Block layer subsystem; - Cryptographic API; - Compute Acceleration Framework; - ACPI drivers; - Serial ATA and Parallel ATA drivers; - Drivers core; - Power management core; - DRBD Distributed Replicated Block Device drivers; - Rados block device (RBD) driver; - Compressed RAM block device driver; - Bluetooth drivers; - Bus devices; - Character device driver; - Clock framework and drivers; - Data acquisition framework and drivers; - Counter interface drivers; - CPU frequency scaling framework; - Hardware crypto device drivers; - CXL (Compute Express Link) drivers; - DMA engine subsystem; - EDAC drivers; - EFI core; - GPU drivers; - Greybus drivers; - HID subsystem; - Hardware monitoring drivers; - I2C subsystem; - IIO ADC drivers; - IIO subsystem; - InfiniBand drivers; - Input Device (Miscellaneous) drivers; - IRQ chip drivers; - LED subsystem; - Mailbox framework; - Multiple devices driver; - Media drivers; - MediaTek SMI driver; - NVIDIA Tegra memory controller driver; - Fastrpc Driver; - IBM Advanced System Management driver; - MMC subsystem; - MTD block device drivers; - Network drivers; - Ethernet bonding driver; - Mellanox network drivers; - Microsoft Azure Network Adapter (MANA) driver; - STMicroelectronics network drivers; - Ethernet team driver; - MediaTek network drivers; - Near Field Communication (NFC) drivers; - NTB driver; - NVDIMM (Non-Volatile Memory Device) drivers; - NVME drivers; - Device tree and open firmware driver; - PCI subsystem; - Pin controllers subsystem; - x86 platform drivers; - Broadcom BCM2835 power domain driver; - Generic PM domains; - i.MX PM domains; - Remote Processor subsystem; - S/390 drivers; - SCSI subsystem; - SLIMbus drivers; - Freescale SoC drivers; - Microchip PolarFire SoC system controller driver; - SPI subsystem; - Media staging drivers; - Realtek RTL8723BS SDIO drivers; - SM750 framebuffer staging driver; - TCM subsystem; - Thermal drivers; - TTY drivers; - UFS subsystem; - Cadence USB3 driver; - USB Device Class drivers; - ULPI bus; - USB core drivers; - DesignWare USB2 driver; - USB Gadget drivers; - USB Host Controller drivers; - Mustek MDC800 USB digital camera driver; - USB YUREX driver; - Renesas USBHS Controller drivers; - USB Type-C Connector System Software Interface driver; - VFIO drivers; - Framebuffer layer; - TSM TDX Guest driver; - Xen hypervisor drivers; - File systems infrastructure; - BTRFS file system; - Ceph distributed file system; - EROFS file system; - Ext4 file system; - F2FS file system; - FUSE (File system in Userspace); - GFS2 file system; - HFS+ file system; - Journaling layer for block devices (JBD2); - Network file systems library; - Network file system (NFS) server daemon; - NILFS2 file system; - File system notification infrastructure; - NTFS3 file system; - OCFS2 file system; - Diskquota system; - SMB network file system; - SquashFS file system; - Tracing file system; - UDF file system; - XFS file system; - Kernel CPU control infrastructure; - QorIQ DPAA2 FSL-MC bus driver; - Memory Management; - Integrity Measurement Architecture(IMA) framework; - KVM subsystem; - Memory management; - Networking core; - padata parallel execution mechanism; - PPP protocol drivers and compressors; - Linux Security Modules (LSM) Framework; - Tracing infrastructure; - Network traffic control; - Distributed Switch Architecture; - IPv4 networking; - IP tunnels definitions; - MAC80211 subsystem; - Netfilter; - User-space API (UAPI); - io_uring subsystem; - Audit subsystem; - BPF subsystem; - Control group (cgroup); - Perf events; - Kernel exit() syscall; - Kernel fork() syscall; - Kernel futex primitives; - KProbes tracing; - Locking primitives; - Kernel module support; - Padata parallel execution mechanism; - Cryptographic library; - Heterogeneous memory management; - KASAN memory debugging framework; - Asynchronous Transfer Mode (ATM) subsystem; - B.A.T.M.A.N. meshing protocol; - Bluetooth subsystem; - Ethernet bridge; - CAIF protocol; - CAN network layer; - Ceph Core library; - IPv6 networking; - XFRM subsystem; - L2TP protocol; - Management Component Transport Protocol (MCTP); - Multipath TCP; - NCSI (Network Controller Sideband Interface) driver; - NFC subsystem; - Open vSwitch; - Packet sockets; - Qualcomm IPC Router (QRTR); - RDS protocol; - RF switch subsystem; - Rose network layer; - RxRPC session sockets; - SCTP protocol; - SMC sockets; - Stream parser; - Sun RPC protocol; - TIPC protocol; - TLS protocol; - Unix domain sockets; - VMware vSockets driver; - Wireless networking; - X.25 network layer; - eXpress Data Path; - Landlock security; - ALSA framework; - Generic PCM loopback sound driver; - FireWire sound drivers; - HD-audio driver; - Creative Sound Blaster X-Fi driver; - AMD SoC Alsa drivers; - QCOM ASoC drivers; - Renesas ASoC drivers; - Samsung ASoC drivers; - SoC audio core drivers; - SOF drivers; - STI ASoC drivers; - USB sound devices; - Objtool; (CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287, CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993, CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171, CVE-2026-23207, CVE-2026-23226, CVE-2026-23227, CVE-2026-23244, CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255, CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285, CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303, CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308, CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315, CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321, CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340, CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361, CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370, CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378, CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383, CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389, CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412, CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419, CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448, CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461, CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465, CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475, CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393, CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429, CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434, CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441, CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480, CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487, CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494, CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498, CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503, CVE-2026-31505, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31634, CVE-2026-31638, CVE-2026-31639, CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648, CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31689, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046, CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057, CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43084, CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089, CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43119, CVE-2026-43120, CVE-2026-43129, CVE-2026-43162, CVE-2026-43245, CVE-2026-43252, CVE-2026-43265, CVE-2026-43281, CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355, CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361, CVE-2026-43362, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368, CVE-2026-43370, CVE-2026-43371, CVE-2026-43372, CVE-2026-43373, CVE-2026-43377, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397, CVE-2026-43405, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43415, CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43499, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45855, CVE-2026-45858, CVE-2026-45899, CVE-2026-45911, CVE-2026-45920, CVE-2026-45924, CVE-2026-45942, CVE-2026-45943, CVE-2026-45956, CVE-2026-45958, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987, CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026, CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037, CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114, CVE-2026-46116, CVE-2026-46117, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193, CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241, CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296, CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314, CVE-2026-46319, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865, CVE-2026-64164)

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

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

It was discovered that some AMD processors did not properly clear data in the floating point divider unit during speculative execution. A local attacker could use this to expose sensitive information. (CVE-2025-54505) It was discovered that some AMD Zen 2 processors did not properly isolate shared resources in the operation cache. A local attacker could possibly use this issue to corrupt instructions executed at a higher privilege level, resulting in privilege escalation. (CVE-2025-54518) It was discovered that some AMD Zen 5 processors supporting RDSEED instruction did not properly handle entropy, potentially resulting in the consumption of insufficiently random values. A local attacker could possibly use this issue to influence the values returned by the RDSEED instruction causing loss of confidentiality and integrity. (CVE-2025-62626) Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - ARM64 architecture; - MIPS architecture; - PowerPC architecture; - RISC-V architecture; - S390 architecture; - x86 architecture; - Block layer subsystem; - Cryptographic API; - Compute Acceleration Framework; - ACPI drivers; - Serial ATA and Parallel ATA drivers; - ATM drivers; - Drivers core; - Power management core; - DRBD Distributed Replicated Block Device drivers; - Rados block device (RBD) driver; - RNBD block device driver; - Ublk userspace block driver; - Compressed RAM block device driver; - Bluetooth drivers; - Bus devices; - Character device driver; - TPM device driver; - Clock framework and drivers; - Clocksource drivers; - Data acquisition framework and drivers; - Counter interface drivers; - CPU frequency scaling framework; - CPU idle management framework; - Hardware crypto device drivers; - CXL (Compute Express Link) drivers; - DMA engine subsystem; - EDAC drivers; - EFI core; - GPIO subsystem; - GPU drivers; - Greybus drivers; - HID subsystem; - Hardware monitoring drivers; - I2C subsystem; - IIO subsystem; - IIO ADC drivers; - InfiniBand drivers; - Input Device (Miscellaneous) drivers; - IOMMU subsystem; - IRQ chip drivers; - LED subsystem; - Mailbox framework; - Multiple devices driver; - Media drivers; - MediaTek SMI driver; - NVIDIA Tegra memory controller driver; - Multifunction device drivers; - Broadcom VK accelerator driver; - Fastrpc Driver; - IBM Advanced System Management driver; - MMC subsystem; - MOST (Media Oriented Systems Transport) drivers; - MTD block device drivers; - Network drivers; - Ethernet bonding driver; - Mellanox network drivers; - Microsoft Azure Network Adapter (MANA) driver; - STMicroelectronics network drivers; - Ethernet team driver; - MediaTek network drivers; - Near Field Communication (NFC) drivers; - NTB driver; - NVDIMM (Non-Volatile Memory Device) drivers; - NVME drivers; - Device tree and open firmware driver; - PCI subsystem; - Performance monitor drivers; - Pin controllers subsystem; - x86 platform drivers; - Broadcom BCM2835 power domain driver; - Generic PM domains; - i.MX PM domains; - Power supply drivers; - RapidIO drivers; - RAS (Reliability, Availability, Serviceability) subsystem; - Remote Processor subsystem; - RPMSG subsystem; - S/390 drivers; - SCSI subsystem; - SLIMbus drivers; - Freescale SoC drivers; - MediaTek SoC drivers; - Microchip PolarFire SoC system controller driver; - Texas Instruments SoC drivers; - SPI subsystem; - Greybus lights staging drivers; - Media staging drivers; - Realtek RTL8723BS SDIO drivers; - SM750 framebuffer staging driver; - TCM subsystem; - Thermal drivers; - TTY drivers; - UFS subsystem; - Cadence USB3 driver; - ChipIdea USB driver; - USB Device Class drivers; - ULPI bus; - USB core drivers; - DesignWare USB2 driver; - DesignWare USB3 driver; - USB Gadget drivers; - USB Host Controller drivers; - Mustek MDC800 USB digital camera driver; - USB YUREX driver; - Renesas USBHS Controller drivers; - USB Type-C Connector System Software Interface driver; - USB over IP driver; - vDPA drivers; - VFIO drivers; - Virtio Host (VHOST) subsystem; - Framebuffer layer; - TSM TDX Guest driver; - Xen hypervisor drivers; - File systems infrastructure; - BTRFS file system; - Ceph distributed file system; - EROFS file system; - Ext4 file system; - F2FS file system; - FAT file system; - FUSE (File system in Userspace); - GFS2 file system; - HFS+ file system; - Journaling layer for block devices (JBD2); - JFS file system; - Network file systems library; - Network file system (NFS) server daemon; - NILFS2 file system; - File system notification infrastructure; - NTFS3 file system; - OCFS2 file system; - Proc file system; - Pstore file system; - Diskquota system; - SMB network file system; - SquashFS file system; - Tracing file system; - UDF file system; - XFS file system; - Audit subsystem; - Kernel CPU control infrastructure; - QorIQ DPAA2 FSL-MC bus driver; - Memory Management; - Integrity Measurement Architecture(IMA) framework; - KVM subsystem; - Memory management; - Networking core; - padata parallel execution mechanism; - PPP protocol drivers and compressors; - Linux Security Modules (LSM) Framework; - Tracing infrastructure; - Network traffic control; - Distributed Switch Architecture; - IPv4 networking; - IPv6 networking; - IP tunnels definitions; - MAC80211 subsystem; - Netfilter; - User-space API (UAPI); - io_uring subsystem; - BPF subsystem; - Control group (cgroup); - Perf events; - Kernel exit() syscall; - Kernel fork() syscall; - Kernel futex primitives; - Kernel kexec() syscall; - KProbes tracing; - Locking primitives; - Kernel module support; - Padata parallel execution mechanism; - RCU subsystem; - Scheduler infrastructure; - Cryptographic library; - Scatterlist API; - Heterogeneous memory management; - KASAN memory debugging framework; - 9P file system network protocol; - Asynchronous Transfer Mode (ATM) subsystem; - B.A.T.M.A.N. meshing protocol; - Bluetooth subsystem; - Ethernet bridge; - CAIF protocol; - CAN network layer; - Ceph Core library; - KCM (Kernel Connection Multiplexor) sockets driver; - XFRM subsystem; - L2TP protocol; - Management Component Transport Protocol (MCTP); - Multipath TCP; - NCSI (Network Controller Sideband Interface) driver; - NFC subsystem; - Open vSwitch; - Packet sockets; - Qualcomm IPC Router (QRTR); - RDS protocol; - RF switch subsystem; - Rose network layer; - RxRPC session sockets; - SCTP protocol; - SMC sockets; - Stream parser; - Sun RPC protocol; - TIPC protocol; - TLS protocol; - Unix domain sockets; - VMware vSockets driver; - Wireless networking; - X.25 network layer; - eXpress Data Path; - AppArmor security module; - Landlock security; - Simplified Mandatory Access Control Kernel framework; - ALSA framework; - Generic PCM loopback sound driver; - FireWire sound drivers; - HD-audio driver; - Creative Sound Blaster X-Fi driver; - AMD SoC Alsa drivers; - QCOM ASoC drivers; - Renesas ASoC drivers; - Samsung ASoC drivers; - SoC audio core drivers; - SOF drivers; - STI ASoC drivers; - USB sound devices; - Objtool; (CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764, CVE-2025-40005, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71229, CVE-2025-71231, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235, CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239, CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71269, CVE-2025-71272, CVE-2025-71273, CVE-2025-71274, CVE-2025-71286, CVE-2025-71287, CVE-2025-71288, CVE-2025-71291, CVE-2025-71292, CVE-2025-71294, CVE-2025-71295, CVE-2025-71297, CVE-2025-71304, CVE-2025-71305, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993, CVE-2026-23004, CVE-2026-23066, CVE-2026-23100, CVE-2026-23104, CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23169, CVE-2026-23171, CVE-2026-23207, CVE-2026-23220, CVE-2026-23221, CVE-2026-23222, CVE-2026-23226, CVE-2026-23227, CVE-2026-23228, CVE-2026-23229, CVE-2026-23230, CVE-2026-23233, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243, CVE-2026-23244, CVE-2026-23245, CVE-2026-23246, CVE-2026-23249, CVE-2026-23253, CVE-2026-23255, CVE-2026-23266, CVE-2026-23267, CVE-2026-23270, CVE-2026-23271, CVE-2026-23272, CVE-2026-23276, CVE-2026-23277, CVE-2026-23278, CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285, CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303, CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308, CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315, CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321, CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340, CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361, CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370, CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378, CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383, CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389, CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412, CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419, CVE-2026-23420, CVE-2026-23426, CVE-2026-23428, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448, CVE-2026-23449, CVE-2026-23450, CVE-2026-23452, CVE-2026-23454, CVE-2026-23455, CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461, CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465, CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475, CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393, CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31402, CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31412, CVE-2026-31414, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31418, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429, CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434, CVE-2026-31436, CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441, CVE-2026-31446, CVE-2026-31447, CVE-2026-31448, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31478, CVE-2026-31480, CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487, CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494, CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498, CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503, CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31607, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31634, CVE-2026-31637, CVE-2026-31638, CVE-2026-31639, CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648, CVE-2026-31649, CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31657, CVE-2026-31658, CVE-2026-31659, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31668, CVE-2026-31669, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31682, CVE-2026-31683, CVE-2026-31684, CVE-2026-31685, CVE-2026-31686, CVE-2026-31687, CVE-2026-31689, CVE-2026-31693, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43011, CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43037, CVE-2026-43038, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046, CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057, CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089, CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43114, CVE-2026-43117, CVE-2026-43119, CVE-2026-43120, CVE-2026-43123, CVE-2026-43124, CVE-2026-43128, CVE-2026-43129, CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135, CVE-2026-43136, CVE-2026-43137, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141, CVE-2026-43143, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149, CVE-2026-43150, CVE-2026-43152, CVE-2026-43153, CVE-2026-43156, CVE-2026-43157, CVE-2026-43158, CVE-2026-43159, CVE-2026-43162, CVE-2026-43163, CVE-2026-43167, CVE-2026-43168, CVE-2026-43169, CVE-2026-43170, CVE-2026-43171, CVE-2026-43173, CVE-2026-43175, CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43185, CVE-2026-43186, CVE-2026-43187, CVE-2026-43189, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43199, CVE-2026-43200, CVE-2026-43201, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205, CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211, CVE-2026-43212, CVE-2026-43214, CVE-2026-43215, CVE-2026-43218, CVE-2026-43221, CVE-2026-43222, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43238, CVE-2026-43239, CVE-2026-43241, CVE-2026-43242, CVE-2026-43244, CVE-2026-43245, CVE-2026-43246, CVE-2026-43248, CVE-2026-43249, CVE-2026-43250, CVE-2026-43251, CVE-2026-43252, CVE-2026-43253, CVE-2026-43255, CVE-2026-43256, CVE-2026-43257, CVE-2026-43258, CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43265, CVE-2026-43266, CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43271, CVE-2026-43273, CVE-2026-43275, CVE-2026-43277, CVE-2026-43278, CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287, CVE-2026-43288, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295, CVE-2026-43296, CVE-2026-43297, CVE-2026-43300, CVE-2026-43302, CVE-2026-43304, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316, CVE-2026-43317, CVE-2026-43318, CVE-2026-43319, CVE-2026-43320, CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43341, CVE-2026-43342, CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355, CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368, CVE-2026-43370, CVE-2026-43372, CVE-2026-43373, CVE-2026-43377, CVE-2026-43378, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43383, CVE-2026-43384, CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397, CVE-2026-43405, CVE-2026-43406, CVE-2026-43407, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43414, CVE-2026-43415, CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43493, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43499, CVE-2026-43501, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848, CVE-2026-45849, CVE-2026-45851, CVE-2026-45852, CVE-2026-45855, CVE-2026-45856, CVE-2026-45857, CVE-2026-45858, CVE-2026-45859, CVE-2026-45860, CVE-2026-45861, CVE-2026-45862, CVE-2026-45864, CVE-2026-45865, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45872, CVE-2026-45873, CVE-2026-45875, CVE-2026-45877, CVE-2026-45878, CVE-2026-45879, CVE-2026-45880, CVE-2026-45881, CVE-2026-45882, CVE-2026-45883, CVE-2026-45884, CVE-2026-45885, CVE-2026-45886, CVE-2026-45890, CVE-2026-45891, CVE-2026-45893, CVE-2026-45895, CVE-2026-45899, CVE-2026-45902, CVE-2026-45904, CVE-2026-45905, CVE-2026-45910, CVE-2026-45911, CVE-2026-45912, CVE-2026-45913, CVE-2026-45914, CVE-2026-45915, CVE-2026-45916, CVE-2026-45917, CVE-2026-45919, CVE-2026-45920, CVE-2026-45921, CVE-2026-45923, CVE-2026-45924, CVE-2026-45928, CVE-2026-45935, CVE-2026-45936, CVE-2026-45938, CVE-2026-45941, CVE-2026-45942, CVE-2026-45943, CVE-2026-45946, CVE-2026-45947, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956, CVE-2026-45957, CVE-2026-45958, CVE-2026-45960, CVE-2026-45962, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45972, CVE-2026-45973, CVE-2026-45974, CVE-2026-45976, CVE-2026-45978, CVE-2026-45981, CVE-2026-45982, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987, CVE-2026-45988, CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026, CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037, CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46043, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114, CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46119, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46135, CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180, CVE-2026-46184, CVE-2026-46185, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193, CVE-2026-46194, CVE-2026-46195, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241, CVE-2026-46243, CVE-2026-46244, CVE-2026-46246, CVE-2026-46247, CVE-2026-46249, CVE-2026-46250, CVE-2026-46251, CVE-2026-46253, CVE-2026-46254, CVE-2026-46255, CVE-2026-46259, CVE-2026-46260, CVE-2026-46261, CVE-2026-46265, CVE-2026-46266, CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46289, CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296, CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314, CVE-2026-46319, CVE-2026-46328, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865, CVE-2026-64018, CVE-2026-64034)

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

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

It was discovered that some AMD processors did not properly clear data in the floating point divider unit during speculative execution. A local attacker could use this to expose sensitive information. (CVE-2025-54505) It was discovered that some AMD Zen 2 processors did not properly isolate shared resources in the operation cache. A local attacker could possibly use this issue to corrupt instructions executed at a higher privilege level, resulting in privilege escalation. (CVE-2025-54518) It was discovered that some AMD Zen 5 processors supporting RDSEED instruction did not properly handle entropy, potentially resulting in the consumption of insufficiently random values. A local attacker could possibly use this issue to influence the values returned by the RDSEED instruction causing loss of confidentiality and integrity. (CVE-2025-62626) Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - ARM64 architecture; - MIPS architecture; - PowerPC architecture; - RISC-V architecture; - S390 architecture; - x86 architecture; - Block layer subsystem; - Cryptographic API; - Compute Acceleration Framework; - ACPI drivers; - Serial ATA and Parallel ATA drivers; - ATM drivers; - Drivers core; - Power management core; - DRBD Distributed Replicated Block Device drivers; - Rados block device (RBD) driver; - RNBD block device driver; - Ublk userspace block driver; - Compressed RAM block device driver; - Bluetooth drivers; - Bus devices; - Character device driver; - TPM device driver; - Clock framework and drivers; - Clocksource drivers; - Data acquisition framework and drivers; - Counter interface drivers; - CPU frequency scaling framework; - CPU idle management framework; - Hardware crypto device drivers; - CXL (Compute Express Link) drivers; - DMA engine subsystem; - EDAC drivers; - EFI core; - GPIO subsystem; - GPU drivers; - Greybus drivers; - HID subsystem; - Hardware monitoring drivers; - I2C subsystem; - IIO subsystem; - IIO ADC drivers; - InfiniBand drivers; - Input Device (Miscellaneous) drivers; - IOMMU subsystem; - IRQ chip drivers; - LED subsystem; - Mailbox framework; - Multiple devices driver; - Media drivers; - MediaTek SMI driver; - NVIDIA Tegra memory controller driver; - Multifunction device drivers; - Broadcom VK accelerator driver; - Fastrpc Driver; - IBM Advanced System Management driver; - MMC subsystem; - MOST (Media Oriented Systems Transport) drivers; - MTD block device drivers; - Network drivers; - Ethernet bonding driver; - Mellanox network drivers; - Microsoft Azure Network Adapter (MANA) driver; - STMicroelectronics network drivers; - Ethernet team driver; - MediaTek network drivers; - Near Field Communication (NFC) drivers; - NTB driver; - NVDIMM (Non-Volatile Memory Device) drivers; - NVME drivers; - Device tree and open firmware driver; - PCI subsystem; - Performance monitor drivers; - Pin controllers subsystem; - x86 platform drivers; - Broadcom BCM2835 power domain driver; - Generic PM domains; - i.MX PM domains; - Power supply drivers; - RapidIO drivers; - RAS (Reliability, Availability, Serviceability) subsystem; - Remote Processor subsystem; - RPMSG subsystem; - S/390 drivers; - SCSI subsystem; - SLIMbus drivers; - Freescale SoC drivers; - MediaTek SoC drivers; - Microchip PolarFire SoC system controller driver; - Texas Instruments SoC drivers; - SPI subsystem; - Greybus lights staging drivers; - Media staging drivers; - Realtek RTL8723BS SDIO drivers; - SM750 framebuffer staging driver; - TCM subsystem; - Thermal drivers; - TTY drivers; - UFS subsystem; - Cadence USB3 driver; - ChipIdea USB driver; - USB Device Class drivers; - ULPI bus; - USB core drivers; - DesignWare USB2 driver; - DesignWare USB3 driver; - USB Gadget drivers; - USB Host Controller drivers; - Mustek MDC800 USB digital camera driver; - USB YUREX driver; - Renesas USBHS Controller drivers; - USB Type-C Connector System Software Interface driver; - USB over IP driver; - vDPA drivers; - VFIO drivers; - Virtio Host (VHOST) subsystem; - Framebuffer layer; - TSM TDX Guest driver; - Xen hypervisor drivers; - File systems infrastructure; - BTRFS file system; - Ceph distributed file system; - EROFS file system; - Ext4 file system; - F2FS file system; - FAT file system; - FUSE (File system in Userspace); - GFS2 file system; - HFS+ file system; - Journaling layer for block devices (JBD2); - JFS file system; - Network file systems library; - Network file system (NFS) server daemon; - NILFS2 file system; - File system notification infrastructure; - NTFS3 file system; - OCFS2 file system; - Proc file system; - Pstore file system; - Diskquota system; - SMB network file system; - SquashFS file system; - Tracing file system; - UDF file system; - XFS file system; - Audit subsystem; - Kernel CPU control infrastructure; - QorIQ DPAA2 FSL-MC bus driver; - Memory Management; - Integrity Measurement Architecture(IMA) framework; - KVM subsystem; - Memory management; - Networking core; - padata parallel execution mechanism; - PPP protocol drivers and compressors; - Linux Security Modules (LSM) Framework; - Tracing infrastructure; - Network traffic control; - Distributed Switch Architecture; - IPv4 networking; - IPv6 networking; - IP tunnels definitions; - MAC80211 subsystem; - Netfilter; - User-space API (UAPI); - io_uring subsystem; - BPF subsystem; - Control group (cgroup); - Perf events; - Kernel exit() syscall; - Kernel fork() syscall; - Kernel futex primitives; - Kernel kexec() syscall; - KProbes tracing; - Locking primitives; - Kernel module support; - Padata parallel execution mechanism; - RCU subsystem; - Scheduler infrastructure; - Cryptographic library; - Scatterlist API; - Heterogeneous memory management; - KASAN memory debugging framework; - 9P file system network protocol; - Asynchronous Transfer Mode (ATM) subsystem; - B.A.T.M.A.N. meshing protocol; - Bluetooth subsystem; - Ethernet bridge; - CAIF protocol; - CAN network layer; - Ceph Core library; - KCM (Kernel Connection Multiplexor) sockets driver; - XFRM subsystem; - L2TP protocol; - Management Component Transport Protocol (MCTP); - Multipath TCP; - NCSI (Network Controller Sideband Interface) driver; - NFC subsystem; - Open vSwitch; - Packet sockets; - Qualcomm IPC Router (QRTR); - RDS protocol; - RF switch subsystem; - Rose network layer; - RxRPC session sockets; - SCTP protocol; - SMC sockets; - Stream parser; - Sun RPC protocol; - TIPC protocol; - TLS protocol; - Unix domain sockets; - VMware vSockets driver; - Wireless networking; - X.25 network layer; - eXpress Data Path; - AppArmor security module; - Landlock security; - Simplified Mandatory Access Control Kernel framework; - ALSA framework; - Generic PCM loopback sound driver; - FireWire sound drivers; - HD-audio driver; - Creative Sound Blaster X-Fi driver; - AMD SoC Alsa drivers; - QCOM ASoC drivers; - Renesas ASoC drivers; - Samsung ASoC drivers; - SoC audio core drivers; - SOF drivers; - STI ASoC drivers; - USB sound devices; - Objtool; (CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764, CVE-2025-40005, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71229, CVE-2025-71231, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235, CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239, CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71269, CVE-2025-71272, CVE-2025-71273, CVE-2025-71274, CVE-2025-71286, CVE-2025-71287, CVE-2025-71288, CVE-2025-71291, CVE-2025-71292, CVE-2025-71294, CVE-2025-71295, CVE-2025-71297, CVE-2025-71304, CVE-2025-71305, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993, CVE-2026-23004, CVE-2026-23066, CVE-2026-23100, CVE-2026-23104, CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23169, CVE-2026-23171, CVE-2026-23220, CVE-2026-23221, CVE-2026-23222, CVE-2026-23226, CVE-2026-23227, CVE-2026-23228, CVE-2026-23229, CVE-2026-23230, CVE-2026-23233, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243, CVE-2026-23244, CVE-2026-23245, CVE-2026-23246, CVE-2026-23249, CVE-2026-23253, CVE-2026-23255, CVE-2026-23266, CVE-2026-23267, CVE-2026-23270, CVE-2026-23271, CVE-2026-23272, CVE-2026-23276, CVE-2026-23277, CVE-2026-23278, CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285, CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303, CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308, CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315, CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321, CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340, CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23361, CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370, CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378, CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383, CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389, CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412, CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419, CVE-2026-23420, CVE-2026-23426, CVE-2026-23428, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448, CVE-2026-23449, CVE-2026-23450, CVE-2026-23452, CVE-2026-23454, CVE-2026-23455, CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461, CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465, CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475, CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393, CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31402, CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31412, CVE-2026-31414, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31418, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429, CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31436, CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441, CVE-2026-31446, CVE-2026-31447, CVE-2026-31448, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31478, CVE-2026-31480, CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487, CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494, CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498, CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503, CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31607, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31634, CVE-2026-31637, CVE-2026-31638, CVE-2026-31639, CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648, CVE-2026-31649, CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31657, CVE-2026-31658, CVE-2026-31659, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31668, CVE-2026-31669, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31682, CVE-2026-31683, CVE-2026-31684, CVE-2026-31685, CVE-2026-31686, CVE-2026-31687, CVE-2026-31689, CVE-2026-31693, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43011, CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43037, CVE-2026-43038, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046, CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057, CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089, CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43114, CVE-2026-43117, CVE-2026-43119, CVE-2026-43120, CVE-2026-43123, CVE-2026-43124, CVE-2026-43128, CVE-2026-43129, CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135, CVE-2026-43136, CVE-2026-43137, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141, CVE-2026-43143, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149, CVE-2026-43150, CVE-2026-43152, CVE-2026-43153, CVE-2026-43156, CVE-2026-43157, CVE-2026-43158, CVE-2026-43159, CVE-2026-43162, CVE-2026-43163, CVE-2026-43167, CVE-2026-43168, CVE-2026-43169, CVE-2026-43170, CVE-2026-43171, CVE-2026-43173, CVE-2026-43175, CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43185, CVE-2026-43186, CVE-2026-43187, CVE-2026-43189, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43199, CVE-2026-43200, CVE-2026-43201, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205, CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211, CVE-2026-43214, CVE-2026-43215, CVE-2026-43218, CVE-2026-43221, CVE-2026-43222, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43238, CVE-2026-43239, CVE-2026-43241, CVE-2026-43242, CVE-2026-43244, CVE-2026-43245, CVE-2026-43246, CVE-2026-43248, CVE-2026-43249, CVE-2026-43250, CVE-2026-43251, CVE-2026-43252, CVE-2026-43253, CVE-2026-43255, CVE-2026-43256, CVE-2026-43257, CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43265, CVE-2026-43266, CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43271, CVE-2026-43273, CVE-2026-43275, CVE-2026-43277, CVE-2026-43278, CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287, CVE-2026-43288, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295, CVE-2026-43296, CVE-2026-43297, CVE-2026-43300, CVE-2026-43302, CVE-2026-43304, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316, CVE-2026-43317, CVE-2026-43318, CVE-2026-43319, CVE-2026-43320, CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43341, CVE-2026-43342, CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355, CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368, CVE-2026-43370, CVE-2026-43372, CVE-2026-43373, CVE-2026-43377, CVE-2026-43378, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43383, CVE-2026-43384, CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397, CVE-2026-43405, CVE-2026-43406, CVE-2026-43407, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43414, CVE-2026-43415, CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43493, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43499, CVE-2026-43501, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848, CVE-2026-45849, CVE-2026-45851, CVE-2026-45852, CVE-2026-45855, CVE-2026-45856, CVE-2026-45857, CVE-2026-45858, CVE-2026-45859, CVE-2026-45860, CVE-2026-45861, CVE-2026-45862, CVE-2026-45864, CVE-2026-45865, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45872, CVE-2026-45873, CVE-2026-45875, CVE-2026-45877, CVE-2026-45878, CVE-2026-45879, CVE-2026-45880, CVE-2026-45881, CVE-2026-45882, CVE-2026-45883, CVE-2026-45884, CVE-2026-45885, CVE-2026-45886, CVE-2026-45890, CVE-2026-45891, CVE-2026-45893, CVE-2026-45895, CVE-2026-45899, CVE-2026-45902, CVE-2026-45904, CVE-2026-45905, CVE-2026-45910, CVE-2026-45911, CVE-2026-45912, CVE-2026-45913, CVE-2026-45914, CVE-2026-45915, CVE-2026-45916, CVE-2026-45917, CVE-2026-45919, CVE-2026-45920, CVE-2026-45921, CVE-2026-45923, CVE-2026-45924, CVE-2026-45928, CVE-2026-45935, CVE-2026-45936, CVE-2026-45938, CVE-2026-45941, CVE-2026-45942, CVE-2026-45943, CVE-2026-45946, CVE-2026-45947, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956, CVE-2026-45957, CVE-2026-45958, CVE-2026-45960, CVE-2026-45962, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45972, CVE-2026-45973, CVE-2026-45974, CVE-2026-45976, CVE-2026-45978, CVE-2026-45981, CVE-2026-45982, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987, CVE-2026-45988, CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026, CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037, CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46043, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114, CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46119, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46135, CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180, CVE-2026-46184, CVE-2026-46185, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193, CVE-2026-46194, CVE-2026-46195, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241, CVE-2026-46243, CVE-2026-46244, CVE-2026-46246, CVE-2026-46247, CVE-2026-46249, CVE-2026-46250, CVE-2026-46251, CVE-2026-46253, CVE-2026-46254, CVE-2026-46255, CVE-2026-46259, CVE-2026-46260, CVE-2026-46261, CVE-2026-46265, CVE-2026-46266, CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46289, CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296, CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314, CVE-2026-46319, CVE-2026-46328, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865, CVE-2026-64018, CVE-2026-64034)

USN-8608-1: Linux kernel (Azure FIPS) vulnerabilities

Fri, 24 Jul 2026 14:17:38 +0200

It was discovered that some AMD processors did not properly clear data in the floating point divider unit during speculative execution. A local attacker could use this to expose sensitive information. (CVE-2025-54505) It was discovered that some AMD Zen 2 processors did not properly isolate shared resources in the operation cache. A local attacker could possibly use this issue to corrupt instructions executed at a higher privilege level, resulting in privilege escalation. (CVE-2025-54518) It was discovered that some AMD Zen 5 processors supporting RDSEED instruction did not properly handle entropy, potentially resulting in the consumption of insufficiently random values. A local attacker could possibly use this issue to influence the values returned by the RDSEED instruction causing loss of confidentiality and integrity. (CVE-2025-62626) Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - ARM64 architecture; - RISC-V architecture; - S390 architecture; - x86 architecture; - Block layer subsystem; - Cryptographic API; - Compute Acceleration Framework; - ACPI drivers; - Serial ATA and Parallel ATA drivers; - Drivers core; - Power management core; - DRBD Distributed Replicated Block Device drivers; - Rados block device (RBD) driver; - Compressed RAM block device driver; - Bluetooth drivers; - Bus devices; - Character device driver; - Clock framework and drivers; - Data acquisition framework and drivers; - Counter interface drivers; - CPU frequency scaling framework; - Hardware crypto device drivers; - CXL (Compute Express Link) drivers; - DMA engine subsystem; - EDAC drivers; - EFI core; - GPU drivers; - Greybus drivers; - HID subsystem; - Hardware monitoring drivers; - I2C subsystem; - IIO ADC drivers; - IIO subsystem; - InfiniBand drivers; - Input Device (Miscellaneous) drivers; - IRQ chip drivers; - LED subsystem; - Mailbox framework; - Multiple devices driver; - Media drivers; - MediaTek SMI driver; - NVIDIA Tegra memory controller driver; - Fastrpc Driver; - IBM Advanced System Management driver; - MMC subsystem; - MTD block device drivers; - Network drivers; - Ethernet bonding driver; - Mellanox network drivers; - Microsoft Azure Network Adapter (MANA) driver; - STMicroelectronics network drivers; - Ethernet team driver; - MediaTek network drivers; - Near Field Communication (NFC) drivers; - NTB driver; - NVDIMM (Non-Volatile Memory Device) drivers; - NVME drivers; - Device tree and open firmware driver; - PCI subsystem; - Pin controllers subsystem; - x86 platform drivers; - Broadcom BCM2835 power domain driver; - Generic PM domains; - i.MX PM domains; - Remote Processor subsystem; - S/390 drivers; - SCSI subsystem; - SLIMbus drivers; - Freescale SoC drivers; - Microchip PolarFire SoC system controller driver; - SPI subsystem; - Media staging drivers; - Realtek RTL8723BS SDIO drivers; - SM750 framebuffer staging driver; - TCM subsystem; - Thermal drivers; - TTY drivers; - UFS subsystem; - Cadence USB3 driver; - USB Device Class drivers; - ULPI bus; - USB core drivers; - DesignWare USB2 driver; - USB Gadget drivers; - USB Host Controller drivers; - Mustek MDC800 USB digital camera driver; - USB YUREX driver; - Renesas USBHS Controller drivers; - USB Type-C Connector System Software Interface driver; - VFIO drivers; - Framebuffer layer; - TSM TDX Guest driver; - Xen hypervisor drivers; - File systems infrastructure; - BTRFS file system; - Ceph distributed file system; - EROFS file system; - Ext4 file system; - F2FS file system; - FUSE (File system in Userspace); - GFS2 file system; - HFS+ file system; - Journaling layer for block devices (JBD2); - Network file systems library; - Network file system (NFS) server daemon; - NILFS2 file system; - File system notification infrastructure; - NTFS3 file system; - OCFS2 file system; - Diskquota system; - SMB network file system; - SquashFS file system; - Tracing file system; - UDF file system; - XFS file system; - Kernel CPU control infrastructure; - QorIQ DPAA2 FSL-MC bus driver; - Memory Management; - Integrity Measurement Architecture(IMA) framework; - KVM subsystem; - Memory management; - Networking core; - padata parallel execution mechanism; - PPP protocol drivers and compressors; - Linux Security Modules (LSM) Framework; - Tracing infrastructure; - Network traffic control; - Distributed Switch Architecture; - IPv4 networking; - IP tunnels definitions; - MAC80211 subsystem; - Netfilter; - User-space API (UAPI); - io_uring subsystem; - Audit subsystem; - BPF subsystem; - Control group (cgroup); - Perf events; - Kernel exit() syscall; - Kernel fork() syscall; - Kernel futex primitives; - KProbes tracing; - Locking primitives; - Kernel module support; - Padata parallel execution mechanism; - Cryptographic library; - Heterogeneous memory management; - KASAN memory debugging framework; - Asynchronous Transfer Mode (ATM) subsystem; - B.A.T.M.A.N. meshing protocol; - Bluetooth subsystem; - Ethernet bridge; - CAIF protocol; - CAN network layer; - Ceph Core library; - IPv6 networking; - XFRM subsystem; - L2TP protocol; - Management Component Transport Protocol (MCTP); - Multipath TCP; - NCSI (Network Controller Sideband Interface) driver; - NFC subsystem; - Open vSwitch; - Packet sockets; - Qualcomm IPC Router (QRTR); - RDS protocol; - RF switch subsystem; - Rose network layer; - RxRPC session sockets; - SCTP protocol; - SMC sockets; - Stream parser; - Sun RPC protocol; - TIPC protocol; - TLS protocol; - Unix domain sockets; - VMware vSockets driver; - Wireless networking; - X.25 network layer; - eXpress Data Path; - Landlock security; - ALSA framework; - Generic PCM loopback sound driver; - FireWire sound drivers; - HD-audio driver; - Creative Sound Blaster X-Fi driver; - AMD SoC Alsa drivers; - QCOM ASoC drivers; - Renesas ASoC drivers; - Samsung ASoC drivers; - SoC audio core drivers; - SOF drivers; - STI ASoC drivers; - USB sound devices; - Objtool; (CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287, CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993, CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171, CVE-2026-23207, CVE-2026-23226, CVE-2026-23227, CVE-2026-23244, CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255, CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285, CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303, CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308, CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315, CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321, CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340, CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361, CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370, CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378, CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383, CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389, CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412, CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419, CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448, CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461, CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465, CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475, CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393, CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429, CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434, CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441, CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480, CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487, CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494, CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498, CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503, CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31634, CVE-2026-31638, CVE-2026-31639, CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648, CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31689, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046, CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057, CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43084, CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089, CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43119, CVE-2026-43120, CVE-2026-43129, CVE-2026-43162, CVE-2026-43245, CVE-2026-43252, CVE-2026-43265, CVE-2026-43281, CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355, CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368, CVE-2026-43370, CVE-2026-43371, CVE-2026-43372, CVE-2026-43373, CVE-2026-43377, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397, CVE-2026-43405, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43415, CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43499, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45855, CVE-2026-45858, CVE-2026-45899, CVE-2026-45911, CVE-2026-45920, CVE-2026-45924, CVE-2026-45942, CVE-2026-45943, CVE-2026-45956, CVE-2026-45958, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987, CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026, CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037, CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114, CVE-2026-46116, CVE-2026-46117, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193, CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241, CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296, CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314, CVE-2026-46319, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865, CVE-2026-64018, CVE-2026-64034, CVE-2026-64164)

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

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

It was discovered that some AMD processors did not properly clear data in the floating point divider unit during speculative execution. A local attacker could use this to expose sensitive information. (CVE-2025-54505) It was discovered that some AMD Zen 2 processors did not properly isolate shared resources in the operation cache. A local attacker could possibly use this issue to corrupt instructions executed at a higher privilege level, resulting in privilege escalation. (CVE-2025-54518) It was discovered that some AMD Zen 5 processors supporting RDSEED instruction did not properly handle entropy, potentially resulting in the consumption of insufficiently random values. A local attacker could possibly use this issue to influence the values returned by the RDSEED instruction causing loss of confidentiality and integrity. (CVE-2025-62626) Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - ARM64 architecture; - MIPS architecture; - PowerPC architecture; - RISC-V architecture; - S390 architecture; - x86 architecture; - Block layer subsystem; - Cryptographic API; - Compute Acceleration Framework; - ACPI drivers; - Serial ATA and Parallel ATA drivers; - ATM drivers; - Drivers core; - Power management core; - DRBD Distributed Replicated Block Device drivers; - Rados block device (RBD) driver; - RNBD block device driver; - Ublk userspace block driver; - Compressed RAM block device driver; - Bluetooth drivers; - Bus devices; - Character device driver; - TPM device driver; - Clock framework and drivers; - Clocksource drivers; - Data acquisition framework and drivers; - Counter interface drivers; - CPU frequency scaling framework; - CPU idle management framework; - Hardware crypto device drivers; - CXL (Compute Express Link) drivers; - DMA engine subsystem; - EDAC drivers; - EFI core; - GPIO subsystem; - GPU drivers; - Greybus drivers; - HID subsystem; - Hardware monitoring drivers; - I2C subsystem; - IIO subsystem; - IIO ADC drivers; - InfiniBand drivers; - Input Device (Miscellaneous) drivers; - IOMMU subsystem; - IRQ chip drivers; - LED subsystem; - Mailbox framework; - Multiple devices driver; - Media drivers; - MediaTek SMI driver; - NVIDIA Tegra memory controller driver; - Multifunction device drivers; - Broadcom VK accelerator driver; - Fastrpc Driver; - IBM Advanced System Management driver; - MMC subsystem; - MOST (Media Oriented Systems Transport) drivers; - MTD block device drivers; - Network drivers; - Ethernet bonding driver; - Mellanox network drivers; - Microsoft Azure Network Adapter (MANA) driver; - STMicroelectronics network drivers; - Ethernet team driver; - MediaTek network drivers; - Near Field Communication (NFC) drivers; - NTB driver; - NVDIMM (Non-Volatile Memory Device) drivers; - NVME drivers; - Device tree and open firmware driver; - PCI subsystem; - Performance monitor drivers; - Pin controllers subsystem; - x86 platform drivers; - Broadcom BCM2835 power domain driver; - Generic PM domains; - i.MX PM domains; - Power supply drivers; - RapidIO drivers; - RAS (Reliability, Availability, Serviceability) subsystem; - Remote Processor subsystem; - RPMSG subsystem; - S/390 drivers; - SCSI subsystem; - SLIMbus drivers; - Freescale SoC drivers; - MediaTek SoC drivers; - Microchip PolarFire SoC system controller driver; - Texas Instruments SoC drivers; - SPI subsystem; - Greybus lights staging drivers; - Media staging drivers; - Realtek RTL8723BS SDIO drivers; - SM750 framebuffer staging driver; - TCM subsystem; - Thermal drivers; - TTY drivers; - UFS subsystem; - Cadence USB3 driver; - ChipIdea USB driver; - USB Device Class drivers; - ULPI bus; - USB core drivers; - DesignWare USB2 driver; - DesignWare USB3 driver; - USB Gadget drivers; - USB Host Controller drivers; - Mustek MDC800 USB digital camera driver; - USB YUREX driver; - Renesas USBHS Controller drivers; - USB Type-C Connector System Software Interface driver; - USB over IP driver; - vDPA drivers; - VFIO drivers; - Virtio Host (VHOST) subsystem; - Framebuffer layer; - TSM TDX Guest driver; - Xen hypervisor drivers; - File systems infrastructure; - BTRFS file system; - Ceph distributed file system; - EROFS file system; - Ext4 file system; - F2FS file system; - FAT file system; - FUSE (File system in Userspace); - GFS2 file system; - HFS+ file system; - Journaling layer for block devices (JBD2); - JFS file system; - Network file systems library; - Network file system (NFS) server daemon; - NILFS2 file system; - File system notification infrastructure; - NTFS3 file system; - OCFS2 file system; - Proc file system; - Pstore file system; - Diskquota system; - SMB network file system; - SquashFS file system; - Tracing file system; - UDF file system; - XFS file system; - Audit subsystem; - Kernel CPU control infrastructure; - QorIQ DPAA2 FSL-MC bus driver; - Memory Management; - Integrity Measurement Architecture(IMA) framework; - KVM subsystem; - Memory management; - Networking core; - padata parallel execution mechanism; - PPP protocol drivers and compressors; - Linux Security Modules (LSM) Framework; - Tracing infrastructure; - Network traffic control; - Distributed Switch Architecture; - IPv4 networking; - IPv6 networking; - IP tunnels definitions; - MAC80211 subsystem; - Netfilter; - User-space API (UAPI); - io_uring subsystem; - BPF subsystem; - Control group (cgroup); - Perf events; - Kernel exit() syscall; - Kernel fork() syscall; - Kernel futex primitives; - Kernel kexec() syscall; - KProbes tracing; - Locking primitives; - Kernel module support; - Padata parallel execution mechanism; - RCU subsystem; - Scheduler infrastructure; - Cryptographic library; - Scatterlist API; - Heterogeneous memory management; - KASAN memory debugging framework; - 9P file system network protocol; - Asynchronous Transfer Mode (ATM) subsystem; - B.A.T.M.A.N. meshing protocol; - Bluetooth subsystem; - Ethernet bridge; - CAIF protocol; - CAN network layer; - Ceph Core library; - KCM (Kernel Connection Multiplexor) sockets driver; - XFRM subsystem; - L2TP protocol; - Management Component Transport Protocol (MCTP); - Multipath TCP; - NCSI (Network Controller Sideband Interface) driver; - NFC subsystem; - Open vSwitch; - Packet sockets; - Qualcomm IPC Router (QRTR); - RDS protocol; - RF switch subsystem; - Rose network layer; - RxRPC session sockets; - SCTP protocol; - SMC sockets; - Stream parser; - Sun RPC protocol; - TIPC protocol; - TLS protocol; - Unix domain sockets; - VMware vSockets driver; - Wireless networking; - X.25 network layer; - eXpress Data Path; - AppArmor security module; - Landlock security; - Simplified Mandatory Access Control Kernel framework; - ALSA framework; - Generic PCM loopback sound driver; - FireWire sound drivers; - HD-audio driver; - Creative Sound Blaster X-Fi driver; - AMD SoC Alsa drivers; - QCOM ASoC drivers; - Renesas ASoC drivers; - Samsung ASoC drivers; - SoC audio core drivers; - SOF drivers; - STI ASoC drivers; - USB sound devices; - Objtool; (CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764, CVE-2025-40005, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71229, CVE-2025-71231, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235, CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239, CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71269, CVE-2025-71272, CVE-2025-71273, CVE-2025-71274, CVE-2025-71286, CVE-2025-71287, CVE-2025-71288, CVE-2025-71291, CVE-2025-71292, CVE-2025-71294, CVE-2025-71295, CVE-2025-71297, CVE-2025-71304, CVE-2025-71305, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993, CVE-2026-23004, CVE-2026-23066, CVE-2026-23100, CVE-2026-23104, CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23169, CVE-2026-23171, CVE-2026-23220, CVE-2026-23221, CVE-2026-23222, CVE-2026-23226, CVE-2026-23227, CVE-2026-23228, CVE-2026-23229, CVE-2026-23230, CVE-2026-23233, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243, CVE-2026-23244, CVE-2026-23245, CVE-2026-23246, CVE-2026-23249, CVE-2026-23253, CVE-2026-23255, CVE-2026-23266, CVE-2026-23267, CVE-2026-23270, CVE-2026-23271, CVE-2026-23272, CVE-2026-23276, CVE-2026-23277, CVE-2026-23278, CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285, CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303, CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308, CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315, CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321, CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340, CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23361, CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370, CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378, CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383, CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389, CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412, CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419, CVE-2026-23420, CVE-2026-23426, CVE-2026-23428, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448, CVE-2026-23449, CVE-2026-23450, CVE-2026-23452, CVE-2026-23454, CVE-2026-23455, CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461, CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465, CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475, CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393, CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31402, CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31412, CVE-2026-31414, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31418, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429, CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31436, CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441, CVE-2026-31446, CVE-2026-31447, CVE-2026-31448, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31478, CVE-2026-31480, CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487, CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494, CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498, CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503, CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31607, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31634, CVE-2026-31637, CVE-2026-31638, CVE-2026-31639, CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648, CVE-2026-31649, CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31657, CVE-2026-31658, CVE-2026-31659, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31668, CVE-2026-31669, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31682, CVE-2026-31683, CVE-2026-31684, CVE-2026-31685, CVE-2026-31686, CVE-2026-31687, CVE-2026-31689, CVE-2026-31693, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43011, CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43037, CVE-2026-43038, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046, CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057, CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089, CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43114, CVE-2026-43117, CVE-2026-43119, CVE-2026-43120, CVE-2026-43123, CVE-2026-43124, CVE-2026-43128, CVE-2026-43129, CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135, CVE-2026-43136, CVE-2026-43137, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141, CVE-2026-43143, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149, CVE-2026-43150, CVE-2026-43152, CVE-2026-43153, CVE-2026-43156, CVE-2026-43157, CVE-2026-43158, CVE-2026-43159, CVE-2026-43162, CVE-2026-43163, CVE-2026-43167, CVE-2026-43168, CVE-2026-43169, CVE-2026-43170, CVE-2026-43171, CVE-2026-43173, CVE-2026-43175, CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43185, CVE-2026-43186, CVE-2026-43187, CVE-2026-43189, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43199, CVE-2026-43200, CVE-2026-43201, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205, CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211, CVE-2026-43214, CVE-2026-43215, CVE-2026-43218, CVE-2026-43221, CVE-2026-43222, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43238, CVE-2026-43239, CVE-2026-43241, CVE-2026-43242, CVE-2026-43244, CVE-2026-43245, CVE-2026-43246, CVE-2026-43248, CVE-2026-43249, CVE-2026-43250, CVE-2026-43251, CVE-2026-43252, CVE-2026-43253, CVE-2026-43255, CVE-2026-43256, CVE-2026-43257, CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43265, CVE-2026-43266, CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43271, CVE-2026-43273, CVE-2026-43275, CVE-2026-43277, CVE-2026-43278, CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287, CVE-2026-43288, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295, CVE-2026-43296, CVE-2026-43297, CVE-2026-43300, CVE-2026-43302, CVE-2026-43304, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316, CVE-2026-43317, CVE-2026-43318, CVE-2026-43319, CVE-2026-43320, CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43341, CVE-2026-43342, CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355, CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368, CVE-2026-43370, CVE-2026-43372, CVE-2026-43373, CVE-2026-43377, CVE-2026-43378, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43383, CVE-2026-43384, CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397, CVE-2026-43405, CVE-2026-43406, CVE-2026-43407, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43414, CVE-2026-43415, CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43493, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43499, CVE-2026-43501, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848, CVE-2026-45849, CVE-2026-45851, CVE-2026-45852, CVE-2026-45855, CVE-2026-45856, CVE-2026-45857, CVE-2026-45858, CVE-2026-45859, CVE-2026-45860, CVE-2026-45861, CVE-2026-45862, CVE-2026-45864, CVE-2026-45865, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45872, CVE-2026-45873, CVE-2026-45875, CVE-2026-45877, CVE-2026-45878, CVE-2026-45879, CVE-2026-45880, CVE-2026-45881, CVE-2026-45882, CVE-2026-45883, CVE-2026-45884, CVE-2026-45885, CVE-2026-45886, CVE-2026-45890, CVE-2026-45891, CVE-2026-45893, CVE-2026-45895, CVE-2026-45899, CVE-2026-45902, CVE-2026-45904, CVE-2026-45905, CVE-2026-45910, CVE-2026-45911, CVE-2026-45912, CVE-2026-45913, CVE-2026-45914, CVE-2026-45915, CVE-2026-45916, CVE-2026-45917, CVE-2026-45919, CVE-2026-45920, CVE-2026-45921, CVE-2026-45923, CVE-2026-45924, CVE-2026-45928, CVE-2026-45935, CVE-2026-45936, CVE-2026-45938, CVE-2026-45941, CVE-2026-45942, CVE-2026-45943, CVE-2026-45946, CVE-2026-45947, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956, CVE-2026-45957, CVE-2026-45958, CVE-2026-45960, CVE-2026-45962, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45972, CVE-2026-45973, CVE-2026-45974, CVE-2026-45976, CVE-2026-45978, CVE-2026-45981, CVE-2026-45982, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987, CVE-2026-45988, CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026, CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037, CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46043, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114, CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46119, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46135, CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180, CVE-2026-46184, CVE-2026-46185, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193, CVE-2026-46194, CVE-2026-46195, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241, CVE-2026-46243, CVE-2026-46244, CVE-2026-46246, CVE-2026-46247, CVE-2026-46249, CVE-2026-46250, CVE-2026-46251, CVE-2026-46253, CVE-2026-46254, CVE-2026-46255, CVE-2026-46259, CVE-2026-46260, CVE-2026-46261, CVE-2026-46265, CVE-2026-46266, CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46289, CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296, CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314, CVE-2026-46319, CVE-2026-46328, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865, CVE-2026-64018, CVE-2026-64034, CVE-2026-64164)

USN-8575-3: Linux kernel vulnerabilities

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

Maxim Suhanov discovered that the NTFS file system implementation in the Linux kernel did not properly validate file name length in certain situations, leading to an out-of-bounds read. An attacker could use this to construct a malicious NTFS image that, when mounted and operated on, could expose sensitive information (kernel memory). (CVE-2023-45896) It was discovered that some AMD processors did not properly clear data in the floating point divider unit during speculative execution. A local attacker could use this to expose sensitive information. (CVE-2025-54505) It was discovered that some AMD Zen 2 processors did not properly isolate shared resources in the operation cache. A local attacker could possibly use this issue to corrupt instructions executed at a higher privilege level, resulting in privilege escalation. (CVE-2025-54518) Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - ARM32 architecture; - ARM64 architecture; - MIPS architecture; - PowerPC architecture; - S390 architecture; - x86 architecture; - Block layer subsystem; - Cryptographic API; - ACPI drivers; - ATM drivers; - Drivers core; - Power management core; - DRBD Distributed Replicated Block Device drivers; - RNBD block device driver; - Bluetooth drivers; - Bus devices; - Character device driver; - TPM device driver; - Clocksource drivers; - Data acquisition framework and drivers; - CPU frequency scaling framework; - CPU idle management framework; - Hardware crypto device drivers; - DMA engine subsystem; - Arm Firmware Framework for ARMv8-A(FFA); - EFI core; - GPIO subsystem; - GPU drivers; - HID subsystem; - Hardware monitoring drivers; - I2C subsystem; - IIO subsystem; - IIO ADC drivers; - InfiniBand drivers; - Input Device (Miscellaneous) drivers; - IOMMU subsystem; - Mailbox framework; - Multiple devices driver; - Media drivers; - MediaTek SMI driver; - NVIDIA Tegra memory controller driver; - Multifunction device drivers; - IBM Advanced System Management driver; - MMC subsystem; - MTD block device drivers; - Network drivers; - Ethernet bonding driver; - Mellanox network drivers; - Microsoft Azure Network Adapter (MANA) driver; - STMicroelectronics network drivers; - MediaTek network drivers; - Near Field Communication (NFC) drivers; - NTB driver; - NVDIMM (Non-Volatile Memory Device) drivers; - NVME drivers; - PCI subsystem; - Pin controllers subsystem; - x86 platform drivers; - Broadcom BCM2835 power domain driver; - Power supply drivers; - RapidIO drivers; - Remote Processor subsystem; - RPMSG subsystem; - SCSI subsystem; - Freescale SoC drivers; - Texas Instruments SoC drivers; - SPI subsystem; - Greybus lights staging drivers; - Media staging drivers; - Realtek RTL8723BS SDIO drivers; - SM750 framebuffer staging driver; - TCM subsystem; - TTY drivers; - UFS subsystem; - Cadence USB3 driver; - USB Device Class drivers; - ULPI bus; - USB core drivers; - DesignWare USB2 driver; - USB Gadget drivers; - USB Host Controller drivers; - Mustek MDC800 USB digital camera driver; - USB YUREX driver; - Renesas USBHS Controller drivers; - Framebuffer layer; - Xen hypervisor drivers; - File systems infrastructure; - BTRFS file system; - Ceph distributed file system; - EROFS file system; - Ext4 file system; - F2FS file system; - FAT file system; - FUSE (File system in Userspace); - GFS2 file system; - HFS+ file system; - JFS file system; - Network file system (NFS) server daemon; - NILFS2 file system; - File system notification infrastructure; - NTFS3 file system; - OCFS2 file system; - Proc file system; - Pstore file system; - Diskquota system; - SMB network file system; - SquashFS file system; - UDF file system; - XFS file system; - Audit subsystem; - RAS (Reliability, Availability, Serviceability) subsystem; - Memory Management; - KVM subsystem; - Memory management; - PPP protocol drivers and compressors; - Linux Security Modules (LSM) Framework; - Network traffic control; - Bluetooth subsystem; - MAC80211 subsystem; - Netfilter; - IP tunnels definitions; - Tracing infrastructure; - User-space API (UAPI); - io_uring subsystem; - BPF subsystem; - Control group (cgroup); - Kernel fork() syscall; - Kernel futex primitives; - Kernel kexec() syscall; - Kernel module support; - Scheduler infrastructure; - Cryptographic library; - KASAN memory debugging framework; - Asynchronous Transfer Mode (ATM) subsystem; - B.A.T.M.A.N. meshing protocol; - Ethernet bridge; - CAIF protocol; - CAN network layer; - Ceph Core library; - Networking core; - Distributed Switch Architecture; - IPv4 networking; - IPv6 networking; - XFRM subsystem; - L2TP protocol; - Management Component Transport Protocol (MCTP); - Multipath TCP; - NCSI (Network Controller Sideband Interface) driver; - NFC subsystem; - Open vSwitch; - Phonet protocol; - Qualcomm IPC Router (QRTR); - RDS protocol; - RF switch subsystem; - Rose network layer; - RxRPC session sockets; - SCTP protocol; - SMC sockets; - Stream parser; - Sun RPC protocol; - TIPC protocol; - TLS protocol; - Unix domain sockets; - VMware vSockets driver; - Wireless networking; - X.25 network layer; - eXpress Data Path; - AppArmor security module; - Simplified Mandatory Access Control Kernel framework; - ALSA framework; - FireWire sound drivers; - HD-audio driver; - AudioScience HPI driver; - Creative Sound Blaster X-Fi driver; - AMD SoC Alsa drivers; - SoC audio core drivers; - STI ASoC drivers; - USB sound devices; (CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116, CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545, CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865, CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715, CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221, CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719, CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863, CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006, CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562, CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748, CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103, CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256, CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161, CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235, CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239, CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274, CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031, CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141, CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220, CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228, CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270, CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286, CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293, CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303, CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318, CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446, CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454, CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480, CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494, CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512, CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540, CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31555, CVE-2026-31565, CVE-2026-31570, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581, CVE-2026-31583, CVE-2026-31585, CVE-2026-31586, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603, CVE-2026-31605, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31630, CVE-2026-31634, CVE-2026-31642, CVE-2026-31651, CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31676, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31687, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31701, CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31726, CVE-2026-31728, CVE-2026-31737, CVE-2026-31738, CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31770, CVE-2026-31773, CVE-2026-31778, CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43014, CVE-2026-43015, CVE-2026-43020, CVE-2026-43024, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43046, CVE-2026-43047, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43058, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080, CVE-2026-43085, CVE-2026-43089, CVE-2026-43093, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43123, CVE-2026-43124, CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135, CVE-2026-43136, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149, CVE-2026-43152, CVE-2026-43156, CVE-2026-43158, CVE-2026-43159, CVE-2026-43163, CVE-2026-43168, CVE-2026-43171, CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43187, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43200, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205, CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211, CVE-2026-43218, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43241, CVE-2026-43242, CVE-2026-43246, CVE-2026-43251, CVE-2026-43255, CVE-2026-43257, CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43266, CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43273, CVE-2026-43275, CVE-2026-43277, CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295, CVE-2026-43296, CVE-2026-43302, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316, CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43357, CVE-2026-43363, CVE-2026-43365, CVE-2026-43370, CVE-2026-43373, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43405, CVE-2026-43411, CVE-2026-43420, CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43439, CVE-2026-43445, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43469, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43484, CVE-2026-43496, CVE-2026-43497, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848, CVE-2026-45852, CVE-2026-45856, CVE-2026-45857, CVE-2026-45860, CVE-2026-45862, CVE-2026-45864, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45873, CVE-2026-45875, CVE-2026-45879, CVE-2026-45883, CVE-2026-45885, CVE-2026-45890, CVE-2026-45891, CVE-2026-45899, CVE-2026-45902, CVE-2026-45904, CVE-2026-45911, CVE-2026-45912, CVE-2026-45915, CVE-2026-45916, CVE-2026-45919, CVE-2026-45920, CVE-2026-45924, CVE-2026-45935, CVE-2026-45936, CVE-2026-45941, CVE-2026-45946, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956, CVE-2026-45958, CVE-2026-45960, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45974, CVE-2026-45978, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987, CVE-2026-45994, CVE-2026-46002, CVE-2026-46004, CVE-2026-46006, CVE-2026-46009, CVE-2026-46015, CVE-2026-46018, CVE-2026-46019, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46027, CVE-2026-46033, CVE-2026-46037, CVE-2026-46040, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46053, CVE-2026-46062, CVE-2026-46064, CVE-2026-46070, CVE-2026-46072, CVE-2026-46077, CVE-2026-46080, CVE-2026-46082, CVE-2026-46088, CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46107, CVE-2026-46108, CVE-2026-46112, CVE-2026-46120, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46127, CVE-2026-46128, CVE-2026-46132, CVE-2026-46133, CVE-2026-46137, CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46161, CVE-2026-46163, CVE-2026-46167, CVE-2026-46168, CVE-2026-46172, CVE-2026-46174, CVE-2026-46177, CVE-2026-46178, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46197, CVE-2026-46198, CVE-2026-46205, CVE-2026-46206, CVE-2026-46209, CVE-2026-46212, CVE-2026-46214, CVE-2026-46219, CVE-2026-46220, CVE-2026-46227, CVE-2026-46230, CVE-2026-46231, CVE-2026-46233, CVE-2026-46234, CVE-2026-46236, CVE-2026-46238, CVE-2026-46249, CVE-2026-46250, CVE-2026-46253, CVE-2026-46259, CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274, CVE-2026-46275, CVE-2026-46285, CVE-2026-46294, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46307, CVE-2026-46319, CVE-2026-46328, CVE-2026-52911, CVE-2026-52912, CVE-2026-52914, CVE-2026-52915, CVE-2026-52916, CVE-2026-52919, CVE-2026-52920, CVE-2026-52921, CVE-2026-52922, CVE-2026-52925, CVE-2026-52926, CVE-2026-52931, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52962, CVE-2026-52963, CVE-2026-52969, CVE-2026-52970, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53064, CVE-2026-53065, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53077, CVE-2026-53082, CVE-2026-53088, CVE-2026-53093, CVE-2026-53096, CVE-2026-53112, CVE-2026-53128, CVE-2026-53130, CVE-2026-53287, CVE-2026-53291, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53320, CVE-2026-53369, CVE-2026-53379, CVE-2026-63860, CVE-2026-63865, CVE-2026-64018, CVE-2026-64032, CVE-2026-64033, CVE-2026-64034, CVE-2026-64039, CVE-2026-64046, CVE-2026-64047, CVE-2026-64055, CVE-2026-64056, CVE-2026-64083, CVE-2026-64084, CVE-2026-64085, CVE-2026-64086, CVE-2026-64087, CVE-2026-64088, CVE-2026-64089, CVE-2026-64096, CVE-2026-64102, CVE-2026-64103, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115, CVE-2026-64125, CVE-2026-64133, CVE-2026-64135, CVE-2026-64153, CVE-2026-64155, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166, CVE-2026-64168, CVE-2026-64173, CVE-2026-64174, CVE-2026-64177, CVE-2026-64178, CVE-2026-64179, CVE-2026-64185)

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

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

Maxim Suhanov discovered that the NTFS file system implementation in the Linux kernel did not properly validate file name length in certain situations, leading to an out-of-bounds read. An attacker could use this to construct a malicious NTFS image that, when mounted and operated on, could expose sensitive information (kernel memory). (CVE-2023-45896) It was discovered that some AMD processors did not properly clear data in the floating point divider unit during speculative execution. A local attacker could use this to expose sensitive information. (CVE-2025-54505) It was discovered that some AMD Zen 2 processors did not properly isolate shared resources in the operation cache. A local attacker could possibly use this issue to corrupt instructions executed at a higher privilege level, resulting in privilege escalation. (CVE-2025-54518) Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - ARM32 architecture; - ARM64 architecture; - MIPS architecture; - PowerPC architecture; - S390 architecture; - x86 architecture; - Block layer subsystem; - Cryptographic API; - ACPI drivers; - ATM drivers; - Drivers core; - Power management core; - DRBD Distributed Replicated Block Device drivers; - RNBD block device driver; - Bluetooth drivers; - Bus devices; - Character device driver; - TPM device driver; - Clocksource drivers; - Data acquisition framework and drivers; - CPU frequency scaling framework; - CPU idle management framework; - Hardware crypto device drivers; - DMA engine subsystem; - Arm Firmware Framework for ARMv8-A(FFA); - EFI core; - GPIO subsystem; - GPU drivers; - HID subsystem; - Hardware monitoring drivers; - I2C subsystem; - IIO subsystem; - IIO ADC drivers; - InfiniBand drivers; - Input Device (Miscellaneous) drivers; - IOMMU subsystem; - Mailbox framework; - Multiple devices driver; - Media drivers; - MediaTek SMI driver; - NVIDIA Tegra memory controller driver; - Multifunction device drivers; - IBM Advanced System Management driver; - MMC subsystem; - MTD block device drivers; - Network drivers; - Ethernet bonding driver; - Mellanox network drivers; - Microsoft Azure Network Adapter (MANA) driver; - STMicroelectronics network drivers; - MediaTek network drivers; - Near Field Communication (NFC) drivers; - NTB driver; - NVDIMM (Non-Volatile Memory Device) drivers; - NVME drivers; - PCI subsystem; - Pin controllers subsystem; - x86 platform drivers; - Broadcom BCM2835 power domain driver; - Power supply drivers; - RapidIO drivers; - Remote Processor subsystem; - RPMSG subsystem; - SCSI subsystem; - Freescale SoC drivers; - Texas Instruments SoC drivers; - SPI subsystem; - Greybus lights staging drivers; - Media staging drivers; - Realtek RTL8723BS SDIO drivers; - SM750 framebuffer staging driver; - TCM subsystem; - TTY drivers; - UFS subsystem; - Cadence USB3 driver; - USB Device Class drivers; - ULPI bus; - USB core drivers; - DesignWare USB2 driver; - USB Gadget drivers; - USB Host Controller drivers; - Mustek MDC800 USB digital camera driver; - USB YUREX driver; - Renesas USBHS Controller drivers; - Framebuffer layer; - Xen hypervisor drivers; - File systems infrastructure; - BTRFS file system; - Ceph distributed file system; - EROFS file system; - Ext4 file system; - F2FS file system; - FAT file system; - FUSE (File system in Userspace); - GFS2 file system; - HFS+ file system; - JFS file system; - Network file system (NFS) server daemon; - NILFS2 file system; - File system notification infrastructure; - NTFS3 file system; - OCFS2 file system; - Proc file system; - Pstore file system; - Diskquota system; - SMB network file system; - SquashFS file system; - UDF file system; - XFS file system; - Audit subsystem; - RAS (Reliability, Availability, Serviceability) subsystem; - Memory Management; - KVM subsystem; - Memory management; - PPP protocol drivers and compressors; - Linux Security Modules (LSM) Framework; - Network traffic control; - Bluetooth subsystem; - MAC80211 subsystem; - Netfilter; - IP tunnels definitions; - Tracing infrastructure; - User-space API (UAPI); - io_uring subsystem; - BPF subsystem; - Control group (cgroup); - Kernel fork() syscall; - Kernel futex primitives; - Kernel kexec() syscall; - Kernel module support; - Scheduler infrastructure; - Cryptographic library; - KASAN memory debugging framework; - Asynchronous Transfer Mode (ATM) subsystem; - B.A.T.M.A.N. meshing protocol; - Ethernet bridge; - CAIF protocol; - CAN network layer; - Ceph Core library; - Networking core; - Distributed Switch Architecture; - IPv4 networking; - IPv6 networking; - XFRM subsystem; - L2TP protocol; - Management Component Transport Protocol (MCTP); - Multipath TCP; - NCSI (Network Controller Sideband Interface) driver; - NFC subsystem; - Open vSwitch; - Phonet protocol; - Qualcomm IPC Router (QRTR); - RDS protocol; - RF switch subsystem; - Rose network layer; - RxRPC session sockets; - SCTP protocol; - SMC sockets; - Stream parser; - Sun RPC protocol; - TIPC protocol; - TLS protocol; - Unix domain sockets; - VMware vSockets driver; - Wireless networking; - X.25 network layer; - eXpress Data Path; - AppArmor security module; - Simplified Mandatory Access Control Kernel framework; - ALSA framework; - FireWire sound drivers; - HD-audio driver; - AudioScience HPI driver; - Creative Sound Blaster X-Fi driver; - AMD SoC Alsa drivers; - SoC audio core drivers; - STI ASoC drivers; - USB sound devices; (CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116, CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545, CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865, CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715, CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221, CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719, CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863, CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006, CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562, CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748, CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103, CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256, CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161, CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235, CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239, CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274, CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031, CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141, CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220, CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228, CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270, CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286, CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293, CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303, CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318, CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446, CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454, CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480, CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494, CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512, CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540, CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551, CVE-2026-31555, CVE-2026-31565, CVE-2026-31570, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581, CVE-2026-31583, CVE-2026-31585, CVE-2026-31586, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603, CVE-2026-31605, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31630, CVE-2026-31634, CVE-2026-31642, CVE-2026-31651, CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31676, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31687, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31701, CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31726, CVE-2026-31728, CVE-2026-31737, CVE-2026-31738, CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31770, CVE-2026-31773, CVE-2026-31778, CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43014, CVE-2026-43015, CVE-2026-43020, CVE-2026-43024, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43046, CVE-2026-43047, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43058, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080, CVE-2026-43085, CVE-2026-43089, CVE-2026-43093, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43123, CVE-2026-43124, CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135, CVE-2026-43136, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149, CVE-2026-43152, CVE-2026-43156, CVE-2026-43158, CVE-2026-43159, CVE-2026-43163, CVE-2026-43168, CVE-2026-43171, CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43187, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43200, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205, CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211, CVE-2026-43218, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43241, CVE-2026-43242, CVE-2026-43246, CVE-2026-43251, CVE-2026-43255, CVE-2026-43257, CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43266, CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43273, CVE-2026-43275, CVE-2026-43277, CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295, CVE-2026-43296, CVE-2026-43302, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316, CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43357, CVE-2026-43363, CVE-2026-43365, CVE-2026-43370, CVE-2026-43373, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43405, CVE-2026-43411, CVE-2026-43420, CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43439, CVE-2026-43445, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43469, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43484, CVE-2026-43496, CVE-2026-43497, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848, CVE-2026-45852, CVE-2026-45856, CVE-2026-45857, CVE-2026-45860, CVE-2026-45862, CVE-2026-45864, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45873, CVE-2026-45875, CVE-2026-45879, CVE-2026-45883, CVE-2026-45885, CVE-2026-45890, CVE-2026-45891, CVE-2026-45899, CVE-2026-45902, CVE-2026-45904, CVE-2026-45911, CVE-2026-45912, CVE-2026-45915, CVE-2026-45916, CVE-2026-45919, CVE-2026-45920, CVE-2026-45924, CVE-2026-45935, CVE-2026-45936, CVE-2026-45941, CVE-2026-45946, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956, CVE-2026-45958, CVE-2026-45960, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45974, CVE-2026-45978, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987, CVE-2026-45994, CVE-2026-46002, CVE-2026-46004, CVE-2026-46006, CVE-2026-46009, CVE-2026-46015, CVE-2026-46018, CVE-2026-46019, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46027, CVE-2026-46033, CVE-2026-46037, CVE-2026-46040, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46053, CVE-2026-46062, CVE-2026-46064, CVE-2026-46070, CVE-2026-46072, CVE-2026-46077, CVE-2026-46080, CVE-2026-46082, CVE-2026-46088, CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46107, CVE-2026-46108, CVE-2026-46112, CVE-2026-46120, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46127, CVE-2026-46128, CVE-2026-46132, CVE-2026-46133, CVE-2026-46137, CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46161, CVE-2026-46163, CVE-2026-46167, CVE-2026-46168, CVE-2026-46172, CVE-2026-46174, CVE-2026-46177, CVE-2026-46178, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46197, CVE-2026-46198, CVE-2026-46205, CVE-2026-46206, CVE-2026-46209, CVE-2026-46212, CVE-2026-46214, CVE-2026-46219, CVE-2026-46220, CVE-2026-46227, CVE-2026-46230, CVE-2026-46231, CVE-2026-46233, CVE-2026-46234, CVE-2026-46236, CVE-2026-46238, CVE-2026-46249, CVE-2026-46250, CVE-2026-46253, CVE-2026-46259, CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274, CVE-2026-46275, CVE-2026-46285, CVE-2026-46294, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46307, CVE-2026-46319, CVE-2026-46328, CVE-2026-52911, CVE-2026-52912, CVE-2026-52914, CVE-2026-52915, CVE-2026-52916, CVE-2026-52919, CVE-2026-52920, CVE-2026-52921, CVE-2026-52922, CVE-2026-52925, CVE-2026-52926, CVE-2026-52931, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52962, CVE-2026-52963, CVE-2026-52969, CVE-2026-52970, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53064, CVE-2026-53065, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53077, CVE-2026-53082, CVE-2026-53088, CVE-2026-53093, CVE-2026-53096, CVE-2026-53112, CVE-2026-53128, CVE-2026-53130, CVE-2026-53287, CVE-2026-53291, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53320, CVE-2026-53369, CVE-2026-53379, CVE-2026-63860, CVE-2026-63865, CVE-2026-64018, CVE-2026-64032, CVE-2026-64033, CVE-2026-64034, CVE-2026-64039, CVE-2026-64046, CVE-2026-64047, CVE-2026-64055, CVE-2026-64056, CVE-2026-64083, CVE-2026-64084, CVE-2026-64085, CVE-2026-64086, CVE-2026-64087, CVE-2026-64088, CVE-2026-64089, CVE-2026-64096, CVE-2026-64102, CVE-2026-64103, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115, CVE-2026-64125, CVE-2026-64133, CVE-2026-64135, CVE-2026-64153, CVE-2026-64155, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166, CVE-2026-64168, CVE-2026-64173, CVE-2026-64174, CVE-2026-64177, CVE-2026-64178, CVE-2026-64179, CVE-2026-64185)

Getting a grip on shadow tokens and AI blowouts

Fri, 24 Jul 2026 14:04:46 +0200

Going forward, CIOs need to thread the AI needle between governance that encourages transparency and reasonable spend without stifling innovation.

When shadow tokens result in real costs

Shifting the culture from usage to yield

Stopping token waste before an AI blowout

This article is published as part of the Foundry Expert Contributor Network.
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Atos launches sovereign cloud service to power comeback

Fri, 24 Jul 2026 13:26:14 +0200

This article first appeared on CIO.

Atos launches sovereign cloud service to power comeback

Fri, 24 Jul 2026 13:12:35 +0200

Why I changed how I pitch AI: It’s no longer about saving money, but managing tokens and adoption

Fri, 24 Jul 2026 13:04:13 +0200

AI as a leadership multiplier

Integrating AI into the broader business strategy also dictates how we measure success. It forces a shift away from short-term tech vanity metrics and anchors the technology into a long-term roadmap.

The requirement for top-down, executive ownership stems from three critical realities observed in the field:

Silo-smashing and data collaboration: True enterprise AI is data-hungry and that data lives across disparate business lines, finance, operations, marketing and customer service. Only the CEO possesses the cross-functional authority to demand that data silos be dismantled.
Cultural transformation and fear mitigation: AI triggers widespread anxiety over job displacement across all industries and hierarchies. When relegated to an “IT project,” resistance spikes as teams view it as a threat to their livelihoods. When I saw the CEO lead this cultural shift directly is when I noticed the best results.
C-Suite education and strategic alignment: The mandate for AI capability cannot just be delegated downward; the transformation must begin at the very top. I have conducted more than 70 presentations for the Board of Directors and C-Level teams. These people need to be actively educated not on technical code, but on specific business use cases, return on investment (ROI) frameworks and how AI resolves core organizational bottlenecks.

AI as a new operational framework

In terms of cost calculation, we had to teach CIOs and business managers to forget the monthly subscription model for AI and learn to manage the primary unit of exchange in modern AI: the token.

Risks in the AI adoption model

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USN-8603-1: Linux kernel (Azure) vulnerabilities

Fri, 24 Jul 2026 13:02:31 +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) Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - x86 platform drivers; - PSP security protocol; - ARM32 architecture; - ARM64 architecture; - MIPS architecture; - PowerPC architecture; - RISC-V architecture; - S390 architecture; - User-Mode Linux (UML); - x86 architecture; - Block layer subsystem; - Cryptographic API; - Intel NPU Driver; - Compute Acceleration Framework; - ACPI drivers; - Auxiliary display drivers; - Drivers core; - DRBD Distributed Replicated Block Device drivers; - Rados block device (RBD) driver; - Ublk userspace block driver; - Compressed RAM block device driver; - Bluetooth drivers; - Bus devices; - Character device driver; - TPM device driver; - Clock framework and drivers; - CPU frequency scaling framework; - Hardware crypto device drivers; - Buffer Sharing and Synchronization framework; - DPLL subsystem; - EDAC drivers; - Arm Firmware Framework for ARMv8-A(FFA); - EFI core; - FWCTL subsystem; - GPIO subsystem; - GPU drivers; - Greybus drivers; - HID subsystem; - Microsoft Hyper-V drivers; - Hardware monitoring drivers; - I2C subsystem; - I3C subsystem; - IIO ADC drivers; - IIO subsystem; - InfiniBand drivers; - Input Device core drivers; - IOMMU subsystem; - LED subsystem; - Mailbox framework; - Multiple devices driver; - Media drivers; - NVIDIA Tegra memory controller driver; - IBM Advanced System Management driver; - MTD block device drivers; - Network drivers; - Ethernet bonding driver; - Mellanox network drivers; - Microsoft Azure Network Adapter (MANA) driver; - STMicroelectronics network drivers; - Texas Instruments network drivers; - MediaTek network drivers; - NTB driver; - NVME drivers; - Device tree and open firmware driver; - Parport drivers; - PCI subsystem; - Pin controllers subsystem; - Chrome hardware platform drivers; - ACPI WMI driver; - Generic PM domains; - MediaTek PM domains; - Power supply drivers; - Remote Processor subsystem; - MPAM driver; - Amlogic Meson reset controller drivers; - S/390 drivers; - SCSI subsystem; - NVIDIA Tegra Control Backbone (CBB) driver; - SPI subsystem; - Greybus lights staging drivers; - Media staging drivers; - Realtek RTL8723BS SDIO drivers; - SM750 framebuffer staging driver; - TCM subsystem; - Thermal drivers; - Thunderbolt and USB4 drivers; - TTY drivers; - Userspace I/O drivers; - USB Device Class drivers; - ULPI bus; - DesignWare USB2 driver; - USB Gadget drivers; - USB Dual Role (OTG-ready) Controller drivers; - USB Serial drivers; - USB Type-C support driver; - USB Type-C Port Controller Manager driver; - TI TPS6598x USB Power Delivery controller driver; - USB Type-C Connector System Software Interface driver; - USB over IP driver; - vDPA drivers; - VFIO drivers; - Framebuffer layer; - TSM AMD SEV Guest driver; - Xen hypervisor drivers; - 9P distributed file system; - File systems infrastructure; - AFS file system; - BTRFS file system; - Ceph distributed file system; - EROFS file system; - Ext4 file system; - F2FS file system; - FUSE (File system in Userspace); - GFS2 file system; - HFS+ file system; - HugeTLB file system; - Journaling layer for block devices (JBD2); - Network file systems library; - Network file system (NFS) server daemon; - NILFS2 file system; - File system notification infrastructure; - NTFS3 file system; - OCFS2 file system; - Overlay file system; - Diskquota system; - SMB network file system; - Tracing file system; - UDF file system; - XFS file system; - DRM TTM subsystem; - Codetag library; - Control group (cgroup); - Kernel CPU control infrastructure; - Memory management; - Tracing infrastructure; - QorIQ DPAA2 FSL-MC bus driver; - Freescale ENETC Ethernet drivers; - Memory Management; - KVM subsystem; - Linked list library; - Netfilter; - padata parallel execution mechanism; - PPP protocol drivers and compressors; - Bluetooth subsystem; - Networking core; - Network shaper API; - Network traffic control; - TCP network protocol; - XFRM subsystem; - User-space API (UAPI); - io_uring subsystem; - IPC subsystem; - Audit subsystem; - BPF subsystem; - DMA mapping infrastructure; - Kernel exit() syscall; - Kernel fork() syscall; - Kernel futex primitives; - IRQ subsystem; - Kexec HandOver (KHO); - Locking primitives; - Padata parallel execution mechanism; - Scheduler infrastructure; - Timer subsystem; - Cryptographic library; - Scatterlist API; - Heterogeneous memory management; - KProbes tracing; - KASAN memory debugging framework; - 802.1Q VLAN protocol; - B.A.T.M.A.N. meshing protocol; - Ethernet bridge; - CAIF protocol; - CAN network layer; - Ceph Core library; - Distributed Switch Architecture; - Ethtool driver; - Handshake API; - HSR network protocol; - IPv4 networking; - IPv6 networking; - IUCV driver; - L2TP protocol; - MAC80211 subsystem; - Multipath TCP; - NFC subsystem; - Open vSwitch; - Packet sockets; - Phonet protocol; - Qualcomm IPC Router (QRTR); - RDS protocol; - RxRPC session sockets; - SCTP protocol; - SMC sockets; - Stream parser; - TIPC protocol; - TLS protocol; - Unix domain sockets; - VMware vSockets driver; - Wireless networking; - Integrity Measurement Architecture(IMA) framework; - Key management; - Landlock security; - Linux Security Modules (LSM) Framework; - SELinux security module; - ALSA framework; - Generic PCM loopback sound driver; - FireWire sound drivers; - HD-audio driver; - AudioScience HPI driver; - Creative Sound Blaster X-Fi driver; - FourSemi audio codecs; - Texas InstrumentS Audio (ASoC/HDA) drivers; - QCOM ASoC drivers; - Renesas ASoC drivers; - SOF drivers; - STI ASoC drivers; - USB sound devices; - Objtool; (CVE-2026-31532, CVE-2026-31574, CVE-2026-31575, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31579, CVE-2026-31580, CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31589, CVE-2026-31590, CVE-2026-31591, CVE-2026-31592, CVE-2026-31593, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31600, CVE-2026-31601, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31607, CVE-2026-31608, CVE-2026-31609, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31614, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31620, CVE-2026-31621, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31686, CVE-2026-31694, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701, CVE-2026-31702, CVE-2026-31703, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31710, CVE-2026-31711, CVE-2026-31712, CVE-2026-31713, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716, CVE-2026-31717, CVE-2026-31718, CVE-2026-31719, CVE-2026-43058, CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43348, CVE-2026-43349, CVE-2026-43350, CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43493, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43498, CVE-2026-43499, CVE-2026-43501, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45837, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45986, CVE-2026-45987, CVE-2026-45988, CVE-2026-45989, CVE-2026-45990, CVE-2026-45991, CVE-2026-45994, CVE-2026-45995, CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46001, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46008, CVE-2026-46009, CVE-2026-46010, CVE-2026-46011, CVE-2026-46012, CVE-2026-46013, CVE-2026-46014, CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46020, CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46025, CVE-2026-46026, CVE-2026-46027, CVE-2026-46028, CVE-2026-46029, CVE-2026-46030, CVE-2026-46031, CVE-2026-46032, CVE-2026-46033, CVE-2026-46034, CVE-2026-46035, CVE-2026-46036, CVE-2026-46037, CVE-2026-46038, CVE-2026-46039, CVE-2026-46040, CVE-2026-46041, CVE-2026-46042, CVE-2026-46043, CVE-2026-46044, CVE-2026-46045, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46054, CVE-2026-46056, CVE-2026-46057, CVE-2026-46058, CVE-2026-46059, CVE-2026-46060, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46066, CVE-2026-46067, CVE-2026-46068, CVE-2026-46069, CVE-2026-46070, CVE-2026-46071, CVE-2026-46072, CVE-2026-46073, CVE-2026-46074, CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079, CVE-2026-46080, CVE-2026-46081, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084, CVE-2026-46085, CVE-2026-46086, CVE-2026-46087, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46093, CVE-2026-46094, CVE-2026-46095, CVE-2026-46096, CVE-2026-46097, CVE-2026-46098, CVE-2026-46099, CVE-2026-46100, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103, CVE-2026-46104, CVE-2026-46105, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46109, CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114, CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46118, CVE-2026-46119, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46130, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46134, CVE-2026-46135, CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46140, CVE-2026-46141, CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46147, CVE-2026-46148, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46153, CVE-2026-46154, CVE-2026-46155, CVE-2026-46156, CVE-2026-46157, CVE-2026-46158, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46162, CVE-2026-46163, CVE-2026-46164, CVE-2026-46165, CVE-2026-46166, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46170, CVE-2026-46171, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46175, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180, CVE-2026-46181, CVE-2026-46182, CVE-2026-46183, CVE-2026-46184, CVE-2026-46185, CVE-2026-46186, CVE-2026-46187, CVE-2026-46188, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46192, CVE-2026-46193, CVE-2026-46194, CVE-2026-46195, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46202, CVE-2026-46203, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46210, CVE-2026-46211, CVE-2026-46212, CVE-2026-46213, CVE-2026-46214, CVE-2026-46215, CVE-2026-46216, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46221, CVE-2026-46222, CVE-2026-46223, CVE-2026-46224, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46228, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46239, CVE-2026-46240, CVE-2026-46241, CVE-2026-46242, CVE-2026-46243, CVE-2026-46244, CVE-2026-46273, CVE-2026-46274, CVE-2026-46275, CVE-2026-46276, CVE-2026-46277, CVE-2026-46278, CVE-2026-46279, CVE-2026-46280, CVE-2026-46281, CVE-2026-46282, CVE-2026-46283, CVE-2026-46284, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46288, CVE-2026-46289, CVE-2026-46290, CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46295, CVE-2026-46296, CVE-2026-46297, CVE-2026-46298, CVE-2026-46299, CVE-2026-46301, CVE-2026-46302, CVE-2026-46303, CVE-2026-46304, CVE-2026-46305, CVE-2026-46306, CVE-2026-46307, CVE-2026-46308, CVE-2026-46309, CVE-2026-46310, CVE-2026-46311, CVE-2026-46312, CVE-2026-46313, CVE-2026-46314, CVE-2026-46315, CVE-2026-46316, CVE-2026-46317, CVE-2026-46318, CVE-2026-46319, CVE-2026-46320, CVE-2026-46321, CVE-2026-46322, CVE-2026-46324, CVE-2026-46332, CVE-2026-52904, CVE-2026-52905, CVE-2026-52906, CVE-2026-52907, CVE-2026-52911, CVE-2026-52912, CVE-2026-52913, CVE-2026-52914, CVE-2026-52915, CVE-2026-52916, CVE-2026-52918, CVE-2026-52919, CVE-2026-52920, CVE-2026-52921, CVE-2026-52922, CVE-2026-52923, CVE-2026-52925, CVE-2026-52926, CVE-2026-52927, CVE-2026-52928, CVE-2026-52931, CVE-2026-52932, CVE-2026-52933, CVE-2026-52934, CVE-2026-52936, CVE-2026-52937, CVE-2026-52941, CVE-2026-52943, CVE-2026-52944, CVE-2026-52949, CVE-2026-52950, CVE-2026-52951, CVE-2026-52952, CVE-2026-52953, CVE-2026-52954, CVE-2026-52955, CVE-2026-52956, CVE-2026-52957, CVE-2026-52958, CVE-2026-52959, CVE-2026-52960, CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52965, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52971, CVE-2026-52973, CVE-2026-52974, CVE-2026-52975, CVE-2026-52976, CVE-2026-52977, CVE-2026-52978, CVE-2026-52979, CVE-2026-52980, CVE-2026-52981, CVE-2026-52982, CVE-2026-52983, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52987, CVE-2026-52988, CVE-2026-52989, CVE-2026-52990, CVE-2026-52991, CVE-2026-52992, CVE-2026-52993, CVE-2026-52994, CVE-2026-52995, CVE-2026-52996, CVE-2026-52997, CVE-2026-52998, CVE-2026-52999, CVE-2026-53000, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53005, CVE-2026-53006, CVE-2026-53007, CVE-2026-53008, CVE-2026-53009, CVE-2026-53010, CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015, CVE-2026-53016, CVE-2026-53017, CVE-2026-53018, CVE-2026-53019, CVE-2026-53020, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53024, CVE-2026-53025, CVE-2026-53026, CVE-2026-53027, CVE-2026-53028, CVE-2026-53029, CVE-2026-53030, CVE-2026-53031, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53038, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53042, CVE-2026-53043, CVE-2026-53044, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53051, CVE-2026-53052, CVE-2026-53053, CVE-2026-53054, CVE-2026-53055, CVE-2026-53056, CVE-2026-53057, CVE-2026-53058, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53067, CVE-2026-53068, CVE-2026-53069, CVE-2026-53070, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53078, CVE-2026-53079, CVE-2026-53080, CVE-2026-53081, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086, CVE-2026-53087, CVE-2026-53088, CVE-2026-53089, CVE-2026-53090, CVE-2026-53091, CVE-2026-53092, CVE-2026-53093, CVE-2026-53094, CVE-2026-53095, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53099, CVE-2026-53100, CVE-2026-53101, CVE-2026-53102, CVE-2026-53103, CVE-2026-53104, CVE-2026-53105, CVE-2026-53106, CVE-2026-53107, CVE-2026-53108, CVE-2026-53109, CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53113, CVE-2026-53114, CVE-2026-53115, CVE-2026-53116, CVE-2026-53117, CVE-2026-53118, CVE-2026-53119, CVE-2026-53120, CVE-2026-53121, CVE-2026-53122, CVE-2026-53123, CVE-2026-53124, CVE-2026-53125, CVE-2026-53126, CVE-2026-53127, CVE-2026-53128, CVE-2026-53129, CVE-2026-53130, CVE-2026-53174, CVE-2026-53277, CVE-2026-53278, CVE-2026-53279, CVE-2026-53280, CVE-2026-53281, CVE-2026-53282, CVE-2026-53283, CVE-2026-53284, CVE-2026-53285, CVE-2026-53286, CVE-2026-53287, CVE-2026-53288, CVE-2026-53289, CVE-2026-53290, CVE-2026-53291, CVE-2026-53292, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53297, CVE-2026-53298, CVE-2026-53299, CVE-2026-53300, CVE-2026-53301, CVE-2026-53302, CVE-2026-53303, CVE-2026-53304, CVE-2026-53305, CVE-2026-53306, CVE-2026-53307, CVE-2026-53308, CVE-2026-53309, CVE-2026-53310, CVE-2026-53311, CVE-2026-53312, CVE-2026-53313, CVE-2026-53314, CVE-2026-53315, CVE-2026-53316, CVE-2026-53317, CVE-2026-53318, CVE-2026-53319, CVE-2026-53320, CVE-2026-53321, CVE-2026-53322, CVE-2026-53323, CVE-2026-53324, CVE-2026-53357, CVE-2026-53358, CVE-2026-53360, CVE-2026-53364, CVE-2026-53365, CVE-2026-53367, CVE-2026-53368, CVE-2026-53369, CVE-2026-53370, CVE-2026-53371, CVE-2026-53372, CVE-2026-53373, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53377, CVE-2026-53378, CVE-2026-53379, CVE-2026-53380, CVE-2026-63837, CVE-2026-63838, CVE-2026-63839, CVE-2026-63840, CVE-2026-63841, CVE-2026-63842, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63849, CVE-2026-63850, CVE-2026-63851, CVE-2026-63852, CVE-2026-63853, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856, CVE-2026-63857, CVE-2026-63858, CVE-2026-63859, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63863, CVE-2026-63864, CVE-2026-63865, CVE-2026-63866, CVE-2026-63875, CVE-2026-63876, CVE-2026-63877, CVE-2026-63878, CVE-2026-63879, CVE-2026-63880, CVE-2026-63881, CVE-2026-63882, CVE-2026-63883, CVE-2026-63884, CVE-2026-63886, CVE-2026-63887, CVE-2026-63888, CVE-2026-63889, CVE-2026-63890, CVE-2026-63891, CVE-2026-63892, CVE-2026-63893, CVE-2026-63894, CVE-2026-63895, CVE-2026-63896, CVE-2026-63897, CVE-2026-63898, CVE-2026-63899, CVE-2026-63900, CVE-2026-63901, CVE-2026-63902, CVE-2026-63903, CVE-2026-63904, CVE-2026-63905, CVE-2026-63906, CVE-2026-63907, CVE-2026-63908, CVE-2026-63910, CVE-2026-63911, CVE-2026-63912, CVE-2026-63913, CVE-2026-63914, CVE-2026-63915, CVE-2026-63916, CVE-2026-63917, CVE-2026-63918, CVE-2026-63919, CVE-2026-63920, CVE-2026-63921, CVE-2026-63922, CVE-2026-63923, CVE-2026-63924, CVE-2026-63925, CVE-2026-63926, CVE-2026-63927, CVE-2026-63928, CVE-2026-63929, CVE-2026-63930, CVE-2026-63931, CVE-2026-63932, CVE-2026-63933, CVE-2026-63934, CVE-2026-63935, CVE-2026-63936, CVE-2026-63937, CVE-2026-63938, CVE-2026-63939, CVE-2026-63940, CVE-2026-63941, CVE-2026-63942, CVE-2026-63943, CVE-2026-63944, CVE-2026-63945, CVE-2026-63946, CVE-2026-63947, CVE-2026-63948, CVE-2026-63949, CVE-2026-63950, CVE-2026-63951, CVE-2026-63952, CVE-2026-63953, CVE-2026-63954, CVE-2026-63955, CVE-2026-63956, CVE-2026-63957, CVE-2026-63958, CVE-2026-63959, CVE-2026-63960, CVE-2026-63961, CVE-2026-63962, CVE-2026-63963, CVE-2026-63964, CVE-2026-63965, CVE-2026-63966, CVE-2026-63967, CVE-2026-63968, CVE-2026-63969, CVE-2026-63970, CVE-2026-63971, CVE-2026-63972, CVE-2026-63973, CVE-2026-63974, CVE-2026-63975, CVE-2026-63976, CVE-2026-63977, CVE-2026-63978, CVE-2026-63979, CVE-2026-63980, CVE-2026-63981, CVE-2026-63982, CVE-2026-63983, CVE-2026-63984, CVE-2026-63985, CVE-2026-63986, CVE-2026-63987, CVE-2026-63988, CVE-2026-63989, CVE-2026-63990, CVE-2026-63991, CVE-2026-63992, CVE-2026-63993, CVE-2026-63994, CVE-2026-63995, CVE-2026-63996, CVE-2026-63997, CVE-2026-63998, CVE-2026-63999, CVE-2026-64000, CVE-2026-64001, CVE-2026-64002, CVE-2026-64003, CVE-2026-64004, CVE-2026-64005, CVE-2026-64006, CVE-2026-64007, CVE-2026-64008, CVE-2026-64009, CVE-2026-64010, CVE-2026-64011, CVE-2026-64012, CVE-2026-64013, CVE-2026-64014, CVE-2026-64015, CVE-2026-64017, CVE-2026-64018, CVE-2026-64019, CVE-2026-64020, CVE-2026-64021, CVE-2026-64022, CVE-2026-64023, CVE-2026-64024, CVE-2026-64025, CVE-2026-64026, CVE-2026-64027, CVE-2026-64029, CVE-2026-64030, CVE-2026-64031, CVE-2026-64032, CVE-2026-64033, CVE-2026-64034, CVE-2026-64035, CVE-2026-64036, CVE-2026-64037, CVE-2026-64038, CVE-2026-64039, CVE-2026-64040, CVE-2026-64041, CVE-2026-64042, CVE-2026-64043, CVE-2026-64044, CVE-2026-64045, CVE-2026-64046, CVE-2026-64047, CVE-2026-64048, CVE-2026-64049, CVE-2026-64050, CVE-2026-64051, CVE-2026-64052, CVE-2026-64053, CVE-2026-64054, CVE-2026-64055, CVE-2026-64056, CVE-2026-64057, CVE-2026-64058, CVE-2026-64059, CVE-2026-64060, CVE-2026-64061, CVE-2026-64062, CVE-2026-64063, CVE-2026-64064, CVE-2026-64065, CVE-2026-64066, CVE-2026-64067, CVE-2026-64068, CVE-2026-64069, CVE-2026-64070, CVE-2026-64071, CVE-2026-64072, CVE-2026-64073, CVE-2026-64074, CVE-2026-64075, CVE-2026-64076, CVE-2026-64077, CVE-2026-64078, CVE-2026-64079, CVE-2026-64080, CVE-2026-64081, CVE-2026-64082, CVE-2026-64083, CVE-2026-64084, CVE-2026-64085, CVE-2026-64086, CVE-2026-64087, CVE-2026-64088, CVE-2026-64089, CVE-2026-64090, CVE-2026-64091, CVE-2026-64093, CVE-2026-64094, CVE-2026-64095, CVE-2026-64096, CVE-2026-64097, CVE-2026-64098, CVE-2026-64099, CVE-2026-64100, CVE-2026-64101, CVE-2026-64102, CVE-2026-64103, CVE-2026-64104, CVE-2026-64105, CVE-2026-64106, CVE-2026-64107, CVE-2026-64108, CVE-2026-64109, CVE-2026-64110, CVE-2026-64111, CVE-2026-64112, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115, CVE-2026-64116, CVE-2026-64117, CVE-2026-64118, CVE-2026-64119, CVE-2026-64120, CVE-2026-64121, CVE-2026-64122, CVE-2026-64123, CVE-2026-64124, CVE-2026-64125, CVE-2026-64126, CVE-2026-64127, CVE-2026-64128, CVE-2026-64129, CVE-2026-64130, CVE-2026-64131, CVE-2026-64132, CVE-2026-64133, CVE-2026-64134, CVE-2026-64135, CVE-2026-64136, CVE-2026-64137, CVE-2026-64138, CVE-2026-64140, CVE-2026-64141, CVE-2026-64142, CVE-2026-64143, CVE-2026-64144, CVE-2026-64145, CVE-2026-64146, CVE-2026-64147, CVE-2026-64148, CVE-2026-64149, CVE-2026-64150, CVE-2026-64151, CVE-2026-64152, CVE-2026-64153, CVE-2026-64154, CVE-2026-64155, CVE-2026-64156, CVE-2026-64157, CVE-2026-64158, CVE-2026-64159, CVE-2026-64160, CVE-2026-64161, CVE-2026-64162, CVE-2026-64163, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166, CVE-2026-64167, CVE-2026-64168, CVE-2026-64169, CVE-2026-64170, CVE-2026-64171, CVE-2026-64172, CVE-2026-64173, CVE-2026-64174, CVE-2026-64175, CVE-2026-64176, CVE-2026-64177, CVE-2026-64178, CVE-2026-64179, CVE-2026-64180, CVE-2026-64181, CVE-2026-64182, CVE-2026-64183, CVE-2026-64184, CVE-2026-64185, CVE-2026-64186)

The Rings of Power season 3 trailer launch

Fri, 24 Jul 2026 12:33:26 +0200

The Rings of Power season 3's first trailer will be released later today — join TechRadar as we count down to its grand reveal.

3 cybersecurity issues that should keep every CEO awake at night

Fri, 24 Jul 2026 12:09:02 +0200

For years, I have been saying that cybersecurity is no longer a technology problem. It has become a business leadership challenge.

The obvious conclusion is that we are asking the wrong questions.

In my view, there are three far more fundamental issues that deserve the attention of every chief executive.

1. Corporate complexity, and the widening gap between business leadership and cybersecurity reality

Perhaps the biggest cybersecurity risk facing large organizations today is not technical at all.

It is the growing disconnect between executive perception and operational reality.

Unfortunately, cyber attackers do not read dashboards.

The problem is rarely a lack of effort.

It is that corporate complexity has reached a level where traditional governance mechanisms are no longer capable of providing an accurate picture of organizational resilience.

Executives believe they understand the level of cyber risk they face because they receive regular reports. Those reports often measure activity rather than resilience.

Governance committees end up debating around another percentage point of phishing awareness or vulnerability remediation, while fundamental issues remain unaddressed in the background.

2. Organizational inertia, and the need for executive structure to evolve faster

Cyber criminals continue to evolve rapidly. Large organizations generally do not.

This is the second issue that should concern every CEO.

Very rarely do they stop to redesign how cybersecurity operates.

The result is what I described several years ago as the “Cybersecurity Spiral of Failure”.

As complexity and regulation increase, organizations invest in more security products.
More products create more complexity.
More products and greater complexity generate more alerts.
More alerts require more analysts.
More analysts produce more reports.
More reports continue to build up executive confidence.
Meanwhile, the underlying structural weaknesses remain largely unchanged, technical debt piles up and costs escalate.

And when the inevitable breach eventually happens, reality reveals itself, but distrust also sets in between senior executives and security teams.

This is not a funding problem. Nor is it a skills problem. It is fundamentally an operating model problem.

Many organizations continue trying to solve twenty-first century challenges using governance, accountability, organizational and reporting structures designed twenty-five years ago.

The cybersecurity function itself has evolved dramatically. Many executive structures have not.

This organizational inertia extends beyond technology: It affects budgeting cycles, investment priorities, procurement processes, accountability models and decision-making speed.

Cyber attackers innovate every day. Organizational change often takes years.

That imbalance should worry every CEO.

3. Accelerating technological disruption, and how it challenges organizations in areas where they are intrinsically weak

The third issue is potentially the most significant over the coming decade.

Artificial intelligence, autonomous agents and machine identities
Software supply chain complexity.
Quantum computing, and post-quantum cryptography