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KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Coding Model Trained on 100,000+ Verifiable Repository Environments

Sun, 26 Jul 2026 12:55:17 +0200

The KwaiKAT Team at Kuaishou has published the KAT-Coder-V2.5 technical report, arguing that agentic coding capability is bottlenecked by training infrastructure rather than model scale. AutoBuilder raised environment construction success from 16.5% to 57.2%, producing over 100,000 verifiable environments across 12 languages, while a sandbox audit cut RL feedback errors from roughly 16% to below 2%.

The post KwaiKAT Team Releases KAT-Coder-V2.5: An Agentic Coding Model Trained on 100,000+ Verifiable Repository Environments appeared first on MarkTechPost.

Week in review: ServiceNow pre-auth RCE exploited in the wild, Hugging Face breached

Sun, 26 Jul 2026 10:02:10 +0200

Here’s an overview of some of last week’s most interesting news, articles, interviews and videos: AI agents are still logging in as humans Most large companies run more than one AI platform at the same time. Developers pull up coding assistants, marketing teams lean on writing tools, and analysts query enterprise search across separate vendors. Single-provider setups keep giving way to mixed stacks as companies keep their options open. PR3TACK preemptive framework maps threats before … More →

The post Week in review: ServiceNow pre-auth RCE exploited in the wild, Hugging Face breached appeared first on Help Net Security.

The AI coding tutor paradox grows as educators scramble to rethink how they test real skills

Sun, 26 Jul 2026 09:10:20 +0200

An ACM survey of 763 computer science educators from 49 countries shows that 68 percent have already changed their exams because of AI, shifting toward oral exams, proctored tests, and project-based work. Teaching is moving from writing code to understanding it. But nearly half of respondents say they lack proven examples for integrating AI into their courses.

The article The AI coding tutor paradox grows as educators scramble to rethink how they test real skills appeared first on The Decoder.

Anthropic's Claude Opus 5 costs well below Fable 5 while matching or beating it across most benchmarks

Sat, 25 Jul 2026 19:50:24 +0200

Anthropic's Claude Opus 5 leads the Artificial Analysis Intelligence Index with 61 points, edging out Claude Fable 5 and GPT-5.6 Sol. The model scores highest in analytical quality and coding, and costs up to half as much as Fable 5 at lower reasoning tiers. But the race at the top remains close.

The article Anthropic's Claude Opus 5 costs well below Fable 5 while matching or beating it across most benchmarks appeared first on The Decoder.

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

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

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

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

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

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

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

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

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

Transparency requirements

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

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

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

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

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

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

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

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

A consistent code of practice

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

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

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

Criteria for compliance

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

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

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

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

Creating a transparency pipeline

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

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

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

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

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

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

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

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

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

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

This article originally appeared on CIO.com.

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.

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Why Cognition bought Poke: AI personality is becoming a competitive advantage

Sat, 25 Jul 2026 19:49:45 +0200

The acquisition brings Poke’s conversational style and interaction model to Cognition’s coding agent Devin, reflecting a growing belief that how AI assistants interact with users is as important as the models powering them.

Prentis, new AI lab co-founded by Reid Hoffman, Mark Pincus in talks to raise $100M

Sat, 25 Jul 2026 19:49:41 +0200

The neolab is betting that automating routine computer tasks will soon outpace coding as AI's biggest use case.

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.

Pwn2Own Berlin 2026 - Day Two Results

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

Day Two of Pwn2Own Berlin 2026 and the stakes continue to rise! Security researchers are back on the Pwn2Own stage, pushing enterprise systems to their limits as the competition heats up. More exploits, more surprises, and more standout moments are unfolding, so follow along here for live updates as the race for Master of Pwn intensifies. There were plenty of big targets on the schedule today, including SharePoint, Exchange, and Safari.

Following an action-packed Day One where $523,000 was awarded for 24 unique 0-day vulnerabilities, Day Two added another $385,750 and 15 unique 0-days, bringing event totals to $908,750 with 39 unique vulnerabilities overall. DEVCORE holds a commanding lead for Master of Pwn with 40.5 points and $405,000, but with one day still to go, anything can happen. Here are the standings as of Day Two but we'll see what the final day of the contest brings. Stay tuned!

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

FAILURE - Unfortunately, Tao Yan & Edouard Bochin of Palo Alto Networks could not get their exploit of Apple Safari – Renderer Only working within the time allotted.

FAILURE - Unfortunately, Stephen Fewer of Rapid7 could not get their exploit of Microsoft SharePoint working within the time allotted.

SUCCESS - Ben Koo (@kiddo_pwn) of Team DDOS used a use-after-free bug to escalate privileges on Red Hat Enterprise Linux for Workstations in the second round, earning $10,000 and 1 Master of Pwn point.

SUCCESS - Dialed in! Nikolaos Mourousias (@deltaclock), Caue Obici (@caueobici) & Bruno Halltari (@BrunoModificato) of OtterSec used a Code Injection bug to exploit LM Studio in the second round, earning $20,000 and 4 Master of Pwn points. Full win!

COLLISON - Although successful on stage, Sina Kheirkhah (@SinSinology) of Summoning Team (@SummoningTeam) targeting Claude Desktop in the Coding Agent category used a bug that was previously known. They still earn $10,000 and 2 Master of Pwn points.

SUCCESS - Le Duc Anh Vu (@vulda17) of Viettel Cyber Security (@vcslab) exploited Cursor, earning $30,000 and 3 Master of Pwn points. Full win!

WITHDRAWAL - Kiyong Kwak of Kakaogames and Song Nuri of Samsung Electronics has withdrawn their entry for Apple Safari – Renderer Only in the Web Browser category.

FAILURE - Unfortunately, Ruitong of Abstract Team, University of Colorado Boulder could not get their exploit of Red Hat Enterprise Linux for Workstations working within the time allotted.

SUCCESS - Sina Kheirkhah (@SinSinology) of Summoning Team (@SummoningTeam) exploited OpenAI Codex in the second round, earning $20,000 and 4 Master of Pwn points.

COLLISON - Although successful on stage, Billy (@st424204), Bruce Chen (@bruce30262), Pan Zhenpeng (@Peterpan980927) & Weiming Shi (@bestswngs) of STARLabs SG (@starlabs_sg) targeting NVIDIA Megatron Bridge used a bug that was previously known. They still earn $2,500 and 1 Master of Pwn point.

WITHDRAWAL - Alon Ben Tsur (@iamgweej), Yahav Azran (@_yahav) have withdrawn their entry for Red Hat Enterprise Linux for Workstations in the Local Escalation of Privilege category.

SUCCESS - Orange Tsai (@orange_8361) of DEVCORE Research Team chained 3 bugs to achieve Remote Code Execution as SYSTEM on Microsoft Exchange, earning $200,000 and 20 Master of Pwn points.

SUCCESS / COLLISON - David Tae & Louis Hur of Out Of Bounds targeted Ollama, hitting a one-vulnerability collision with a previous attempt and earning $28,000 and 3 Master of Pwn points.

FAILURE - Nguyen Thanh Dat (@rewhiles) of Viettel Cyber Security (@vcslab) could not get their exploit of Mozilla Firefox – Renderer Only working within the time allotted.

SUCCESS - Cyrill Bannwart, Emanuele Barbeno, Yves Bieri, Lukasz D., Urs Mueller (@compasssecurity) of Compass Security exploited Cursor in the second round, earning $15,000 and 3 Master of Pwn points.

SUCCESS - Siyeon Wi used an integer overflow bug to escalate privileges on Microsoft Windows 11 in the fourth round, earning $7,500 and 3 Master of Pwn points.

SUCCESS / COLLISON - Byung Young Yi (@yibarrack) of Out Of Bounds targeted LiteLLM, hitting a one-vulnerability collision with a previous attempt and earning $17,750 and 3.75 Master of Pwn points.

SUCCESS - Confirmed! 0xDACA (@0xDACA) & Noam Trobishi (@NTrobishi) used a use-after-free bug to exploit NV Container Toolkit in the second round, earning $25,000 and 5 Master of Pwn points.

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.

The June 2026 Security Update Review

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

I’ve made it through Pwn2Own Berlin, had a little vacation, and now I’m back for Patch Tuesday. Microsoft and Adobe didn’t disappoint. In fact, they have heralded my return with the largest Patch Tuesday release ever. Thanks? Take a break from your regularly scheduled activities and let’s take a look at the latest security patches from Adobe and Microsoft. If you’d rather watch the full video recap covering the entire release, you can check it out here:

Adobe Patches for June 2026

For June, Adobe released 11 bulletins addressing 123 unique CVEs in Adobe Acrobat Reader, ColdFusion, Experience Manager, Experience Manager Forms, InDesign, InCopy, Substance 3D Sampler, Content Credentials SDK, Dreamweaver, Format Plugins, and Adobe Campaign Classic. A total of 11 of these CVEs were reported through the ZDI program.

Here’s this month’s overview table:

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

Obviously, the update for Campaign Classic should be on the top of your deployment list if you’re a user. A CVSS 10 is rare; two in the same bulletin is pretty much a unicorn. Adobe says there are no active attacks, but I would expect heavy research into creating one. The update for Coldfusion is also a Priority 1, but again, no known attacks is the wild. I suspect the Reader patch will also receive a lot of attention as malicious PDFs are common in ransomware attacks. The update for Experience Manager may be large, but it’s mostly just cross-site scripting (XSS) bugs.

Microsoft Patches for June 2026

This month, Microsoft released a new record 208 CVEs Windows and Windows components, Office and Office Components, Microsoft Edge (Chromium-based), Azure, .NET and Visual Studio, Github Copilot, Defender, Exchange Server, Hyper-V, Secure Boot, and BitLocker. At least, that’s my count. Microsoft’s tools seem to be having some issues, as they initially included a CVE from 2020 in this release. Regardless, the count is over 200, and I counted several times.

One of these bugs came through the ZDI program, but bugs submitted during Pwn2Own Berlin remain unpatched. If you include the Chromium and other third-party bugs, the total CVE count for June comes to a staggering 571 CVEs. 38 of these cases are rated Critical while the rest are rated Important in severity.

I’ve been counting CVEs on Patch Tuesday since 2017, and this is by far the largest monthly release in that time. The previous record was 177 set last year. It is extraordinary that Microsoft can produce so many patches in a single month, but it does raise concerns. How many of these cases were found using AI tools? How many patches were generated using AI to assist in coding or testing? What quality issues may exist in these patches? And likely most importantly, is this the new normal? The last two months were also large releases. Should sysadmins adjust their processes for prioritization and patch deployment based on this new volume of updates? Unfortunately, Microsoft is not providing those answers right now. Hopefully that changes in the future. BTW – just a note – the current number of CVEs shipped by Microsoft this year exceeds the total number of CVEs shipped in all of 2018.

One of the bugs patched by Microsoft this month is listed as under active exploitation and three others are listed as publicly known at the time of release. Let’s take a closer look at some of the more interesting updates for this month, starting with the bug being exploited in the wild.

- CVE-2026-41091 - Microsoft Defender Elevation of Privilege Vulnerability
Since Microsoft doesn’t provide info on how widespread exploitation is, we must read some tea leaves. For this patch, several different people were acknowledged, which indicates multiple parties say this is in the wild, meaning exploitation is likely significant. The good news is that most people won’t need to take action as Defender updates itself. However, if you don’t have this configured or are in an isolated environment, you’ll need to update to the latest version.

- CVE-2026-45657 - Windows Kernel Remote Code Execution Vulnerability
This CVSS 9.8 bug allows remote, unauthenticated attackers to execute code at SYSTEM level without user interaction. Yup – this is wormable. The problem lies in the way the kernel handles TCP/IP. This was listed as “Exploitation Less Likely” by Microsoft, but rest assured that every researcher and bug shop on the planet is reversing this patch right now trying to create an exploit. Test and deploy this patch quickly.

- CVE-2026-47291 - HTTP.sys Remote Code Execution Vulnerability
Our second CVSS 9.8 bug of the month, this also allows remote, unauthenticated attackers to execute code on affected systems without user interaction. However, there is a caveat. Systems using the default MaxRequestBytes registry value used by the Windows HTTP stack are not affected by this bug. You can edit your registry settings if you need protection while you test and deploy the patch. The bulletin includes instructions and even a PowerShell script for doing this action. Microsoft lists this as “Exploitation more likely”, so I would definitely check your registry settings.

- CVE-2026-44815 - DHCP Client Service Remote Code Execution Vulnerability
Here’s another CVSS 9.8 that has an odd incongruity. Although the CVSS says no permissions are required for exploitation, the write-up states it must be an “authenticated” user. I would err on the side of caution here and believe the CVSS. If that’s correct, then we have another bug where a remote, unauthenticated attacker could execute code on affected systems without user interaction. And since the DHCP client is on every OS, it’s a juicy target. This is another one to test and deploy with haste.

- CVE-2026-45585/CVE-2026-50507 - Windows BitLocker Security Feature Bypass Vulnerability
If you’ve followed the ongoing saga of Nightmare Eclipse vs. MSRC, the bugs should look familiar. One is definitely a fix for “YellowKey”, while the other appears to be a fix for “GreenPlasma”. The researcher has promised a “bone shattering” drop on June 14, so let’s hope Microsoft is able to reach some understanding with the researcher before more 0-days are released. Also, there is a script provided by Microsoft as a mitigation, but the better strategy is to test and deploy the updates.

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

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

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

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

Looking at the other Critical-rated bugs in this release, the scariest-looking one is actually nothing to concern yourself with at all. The CVSS 10 bug in Azure HorizonDB has already been addressed by Microsoft and is just being documented now. That’s also the case for five others. Of course, there wouldn’t be a release without Office bugs that have the Preview Pane as an attack vector. There are multiple in June. There’s a handful of bugs in the Remote Desktop Client, but these rely on connecting to a malicious RDP server. There are three patches for Hyper-V that allow for guest-to-host code execution. The bug in Active Directory requires authentication, but any authenticated user can hit it. For the Windows Directory Service vulnerability, it needs to be listening for TFTP. You have blocked that everywhere, right? The bug in Azure Network Adapter is somewhat unique as you need to update your Linux kernel to be protected. The bug in Azure Kubernetes allows an attacker to break out of a container and gain control of the AKS worker node. Finally, the bug in the Kerberos Key Distribution Center (KDC) seems unlikely, but if exploited, it could allow authenticated attackers to get code execution on affected systems.

Moving on to the other code execution bugs, there are the ubiquitous open-an-own bugs in Office components like Excel and Word. The code injection bug in Exchange Server looks troubling, but it requires a machine-in-the-middle (MiTM), so exploitation is unlikely. The bugs in SharePoint require authentication, but you should note that the patch applies to both SharePoint Server 2016 and SharePoint Enterprise Server 2016. The two bugs in UPnP are interesting. Both can lead to code execution by causing an error during the handling of specially crafted data, which could lead to a Use After Free (UAF) bug. The bugs in RDP Client all require connecting to a malicious RDP server, but it’s not clear why some are rated Critical and some are rated Important. The NTFS vulnerability requires a user to mount a virtual hard drive on an affected system. The last RCE bug this month is in Azure Stack Edge and requires the attacker to send a specially crafted file upload request that includes a manipulated file name or path, leading to code execution.

There are more than 60 Elevation of Privilege (EoP) bugs in this month’s release, and as usual, most simply lead to local attackers executing their code at SYSTEM-level privileges or administrative privileges, so there’s not much to add without further technical details about the bugs themselves. A notable exception is in Exchange Server, where a user on Outlook Web Access (OWA) could gain access to other mailboxes. The bug in Visual Studio Code could allow attackers to gain permissions associated with the MCP Server’s managed identity. The bugs in Windows SDK and Windows UI Automation Manager could let attacker go from low integrity up to medium integrity code execution. The bug in Bluetooth just allows “elevated” privileges without really describing what elevated might be.

Moving on to the more than 20 security feature bypass (SFB) bugs in the June release, there are a total of 10 that impact Secure Boot. All carry scope change (S:C) in the CVSS, meaning successful exploitation affects security boundaries beyond the vulnerable component itself — specifically the ability to load untrusted code at boot, bypass Virtual Secure Mode, and undermine boot integrity guarantees. CVE-2026-45654 explicitly calls out VSM exposure. The bulk of these are credited to Alon Leviev (STORM), which is notable given his prior BootKitty/BlackLotus-adjacent research. The bugs in the Windows Boot Manager have a similar impact as the Secure Boot bugs. The UEFI Secure Boot vulnerabilities go a layer deeper. They require either local admin or physical access but could allow for the running of untrusted code even before the OS loads. Rootkits anyone? The four bugs in BitLocker all require physical access but could yield encrypted data if exploited. The bug in Windows Administration Protection allows attackers to bypass the feature that prevents standard-user apps from performing admin-level actions. The bug in Visual Studio Copilot Chat could be the most interesting non-boot bug here as it allows authentication impersonation. Mark of the Web (MotW) and Excel vulns could bypass user warnings. Lastly, the bug in PC Manager bypasses expected user controls.

Turning our attention to the mass of spoofing bugs in the release, we instantly see 18 impacting SharePoint Server. Fortunately, these are simply cross-site scripting (XSS) bugs. It’s the Exchange bugs we should really watch for. One is an XSS that an attacker can exploit by convincing an Exchange administrator to open a malicious link or message, which then runs code in the admin's web session. That's a meaningful privilege escalation path. Another is listed as an SSRF-based attack, but no other details are available. The last is a lower-impact XSS with limited confidentiality/integrity loss. The bug in Bing Search (remember Bing?) is a classic search result spoofing. The bug in Azure Stack Edge is interesting as it could allow access to resources outside the vulnerable component's security boundary. The bug in Office for Android requires user interaction. The Office Project Server bug is an authenticated XSS with low impact. The final spoofing bug is in Azure Attestation but has already been addressed. You should still verify you are protected by following the instructions in the write-up from Microsoft.

There are 30 different information disclosure bugs in this release, and fortunately, the vast majority of these simply result in info leaks consisting of unspecified memory contents or memory addresses. The two bugs in Visual Studio require user interaction and could “disclose information over a network.” How obtuse. The bug in GitHub Copilot and Visual Studio Code could disclose discloses a sign-in access token for a user's work account. That's a meaningful credential exposure, not just random memory. That leaves the two bugs in Exchange Server. One could allow an authenticated user to gain information about which network services that the Exchange server can reach. The other sounds much like the spoofing bug in OWA as it allows attackers to see information in mailboxes they should not have access to.

I’ve never been a fan of the “tampering” category, as it could mean so many different things. For example, the bug in .NET simply says it could allow an unauthorized attacker to perform tampering locally. Similarly, the bug in Visual Studio says the same, expect here the tampering occurs over a network. Microsoft doesn’t even bother with a CWE for the tampering bug in the DHCP Server, so your guess is as good as mine.

There are seven DoS bugs in the June release, and as usual, Microsoft provides little to no actionable information about the vulnerabilities. The most interesting is the bug in HTTP.sys, which is listed as publicly known. This is an uncontrolled resource consumption, rated "Exploitation More Likely," and publicly disclosed. Since, HTTP.sys sits at the core of IIS and Windows web services, a network-accessible DoS here can take down any Windows server running HTTP-based services. Based on the Acknowledgement, it looks like this bug may have been found using AI. There are no real details for the other bugs, but based simply on the impact, I would focus on the Kerberos and TCP/IP bugs if you had to prioritize.

No new advisories are being released this month.

Looking Ahead

The next Patch Tuesday will be on July 14 and will be the last one before Black Hat/DEFCON. It’s usually a big release, so strap in and hang on. I’ll be back then to give you my full thoughts. Until then, stay safe, happy patching, and may all your reboots be smooth and clean!

Pwn2Own Ireland 2026 – New Targets and Categories

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

If you just want to read the rules, you can find them here.

Pwn2Own Ireland returns for 2026, and it’s the third year for this event in the Emerald Isle. Despite the dreary Irish skies (and the threat of a random banshee), we had an amazing event, even if we did end up in a jail at the end. With that in mind, we’re excited to return to Cork this fall for yet another great Pwn2Own event. We’ll also be returning to some of the great pubs Ireland has to offer in the evenings and wrapping the event up at a special location (stay tuned for that announcement).

As for the contest itself, it will run from October 6-9, 2026. As always, we’ll have a random drawing to determine the schedule of attempts on the first day of the contest, and we will proceed from there. Registration closes at 5:00 p.m. Irish Standard Time on Oct 1st, 2026. There are no exceptions for late entries, so if you have questions, please contact us at pwn2own@trendmicro.com (note the address). We will be happy to address your issues or concerns directly.

Due to the overwhelming amount of registrations and last-minute entries for our Pwn2Own Berlin event, we’re changing who can enter the contest a bit to ensure it’s fair for all researchers. To enter, you must have received an aggregate bounty payment totaling at least $15,000 during their life-time participation in ZDI. This includes past Pwn2Own events and our regular bug bounty program. We recognize there may be some who haven’t participated in the past with great exploits to demonstrate, so we will also accept up to 10 new contestants at our discretion. We’re capping the number of entries to 80 this year. Once we have 80 qualifying entries, we will close registration. That means if you want to enter, it is in your best interest to contact us sooner rather than later. Please read the rules thoroughly to ensure you meet all the requirements.

Now on to this year’s target categories. We’ll have seven different categories for this year’s event:

-- Mobile Phones
-- Smart Home Devices
-- Wellness
-- Printers
-- Messaging
-- AI Infrastructure
-- AI Coding Agents

Let’s take a look at each category in more detail, starting with mobile phones.

The Target Phones

Back in Amsterdam where this contest originated, it was originally dubbed “Mobile Pwn2Own” and our focus was strictly on phones. Mobile handsets remain at the heart of this event, and some of the Samsung entries from last year were absolutely smashing. As always, these phones will be running the latest version of their respective operating systems with all available updates installed. Last year we also introduced the USB attack vector, but no one submitted an entry for it. We’ll see if that changes this year.

Otherwise, contestants must compromise the device by browsing to content in the default browser for the target under test or by communicating with the following short-distance protocols: near field communication (NFC), Wi-Fi, or Bluetooth. The awards for this category are:

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Smart Home Devices

As you might have noticed, we have eliminated most of the consumer-related devices from this year’s event. However, there are still a few “pro-sumer” devices that still could have an impact on enterprises, and the first of these categories are the devices that control other devices and services. An attempt in this category must be launched against the target’s exposed network services, RF attack surface, or exposed features from the contestant’s laptop within the contest network.

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Wellness Category

This is one of the new categories this year and our first foray into the world of healthcare devices. However, we don’t intend to make this too easy. Entries that require physically pressing any button on the target, or the use of any information, code or PIN printed on the device, are out of scope. Entries that require the contestant to be paired to the target prior to the start of the attempt are not in scope. An attempt in this category must be launched against the target’s exposed network services, RF attack surface, or exposed features from the contestant’s laptop within the contest network.

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Rage Against the Printers

Printers have long been the source of jokes and memes, but they are also an often overlooked attack surface in your office. The printer category always produces some interesting results, often by playing music it shouldn’t or the occasional Rick Roll. We’ve reduced the number of targets in this category this year, but we still expect to see some interesting exploits in these oft unheralded targets.

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The Messaging Category

We introduced WhatsApp as a target last year and came close to seeing a functioning exploit. Sadly, that didn’t happen. However, WhatsApp is used by more than three billion people globally, and some of the messages transmitted can be quite sensitive. That’s why we are bringing it back and hoping for some better results. We know the bugs are out there. We’re just hoping the right researcher decides to show us an exploit that leads to code execution. All of the target handset will be available as clients. Here’s the full prize list for Messaging category:

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AI Infrastructure Category

We introduced these targets at Pwn2Own Berlin, and we saw such…uh…enthusiasm from the community that we decided to immediately bring them back for our Ireland event. An attempt in this category must be launched from the contestant’s laptop. Here’s a look at the targets and awards in the AI Infrastructure category:

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AI Coding Agent Category

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

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Master of Pwn

No Pwn2Own contest would be complete without crowning a Master of Pwn, which signifies the overall winner of the competition. Earning the title results in a slick trophy, a different sort of wearable, and brings with it an additional 65,000 ZDI reward points (instant Platinum status in 2027).

For those not familiar with how it works, points are accumulated for each successful attempt. While only the first demonstration in a category wins the full cash award, each successful entry claims the full number of Master of Pwn points. Since the order of attempts is determined by a random draw, those who receive later slots can still claim the Master of Pwn title – even if they earn a lower cash payout. As with previous contests, there are penalties for withdrawing from an attempt once you register for it. If the contestant decides to remove an Add-on Bonus during their attempt, the Master of Pwn points for that Add-on Bonus will be deducted from the final point total for that attempt. For example, someone registers for the Apple iPhone 15 with the Kernel Bonus Add-on. During the attempt, the contestant drops the Kernel Bonus Add-on but completes the attempt. The final point total will be 20 Master of Pwn points.

The Complete Details

The full set of rules for Pwn2Own Ireland 2026 can be found here. They may be changed at any time without notice. We highly encourage potential entrants to read the rules thoroughly and completely should they choose to participate. We also encourage contestants to read this blog covering what to expect when participating in Pwn2Own.

Registration is required to ensure we have sufficient resources on hand at the event. Please contact ZDI at pwn2own@trendmicro.com to begin the registration process. (Email only, please; queries via social media, blog post, or other means will not be acknowledged or answered.) If we receive more than one registration for any category, we’ll hold a random drawing to determine the contest order. Registration closes at 5:00 p.m. Irish Standard Time on Oct 1st, 2025.

The Results

We’ll be blogging and tweeting results in real-time throughout the competition. Be sure to keep an eye on the blog for the latest information. Follow us on Twitter at @thezdi and @trendaisecurity, and keep an eye on the #P2OIreland hashtag for continuing coverage.

We look forward to seeing everyone in Cork, and we look forward to seeing what new exploits and attack techniques they bring with them.

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

The July 2026 Security Update Review

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

Well folks. Here we are. The bug apocalypse has fully descended upon us. I’ll do my best to sort this out in some way meaningful, but this month’s release shows us the nay-sayers were right, and I’ve got to hand it to the nay-sayers here. Excellent call. Take an extended break from your regularly scheduled activities as we let’s take a look at the latest security patches from Adobe and Microsoft. If you’d rather watch the full video recap covering the entire release, you can check it out here:

Adobe Patches for July 2026

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

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

Here’s this month’s overview table:

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

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

Microsoft Patches for July 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

There are close to 260 EoP bugs in this month’s release. Microsoft could have just published the EoPs and still had a record-setting month. As usual, most simply lead to local attackers executing their code at SYSTEM-level privileges or administrative privileges, so there’s not much to add without further technical details about the bugs themselves. What’s really frustrating is that 94 have no explicit privilege statement at all. Microsoft just says “elevate privileges” with no detail. By my count, that leaves around 25 bugs to consider. Some don’t elevate at all. The FAQ literally says the attacker just gets “the rights of the user running the affected application.” That covers Win32k, Clip Service, Search Service, MSMQ, and SharePoint. A few get a Low-to-Medium integrity bump. There are also a couple that lead to downgraded service accounts or arbitrary file deletion, but nothing else I’ve seen really stands out too much.

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

Tego AI Discloses Second Claude Flaw in a Week: Hidden Link Silently Sends Files to Attackers

Sat, 25 Jul 2026 19:02:44 +0200

Tel Aviv, Israel, July 24th, 2026, CyberNewswire One week after disclosing that Anthropic’s Claude Tag Slack integration could be driven by plain “@Claude” text, Tego AI today published a second piece of research on the Claude ecosystem. This one focuses on Claude Code, Anthropic’s agentic command-line coding tool. Cloning an ordinary repository and starting Claude […]

The post Tego AI Discloses Second Claude Flaw in a Week: Hidden Link Silently Sends Files to Attackers appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.

What is an AI Code Generator? LLM Coding, Productivity, & Risk

Sat, 25 Jul 2026 19:02:24 +0200

YouTube Video

Announcing Pwn2Own Berlin for 2026

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

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

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

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

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

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

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

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

Virtualization Category

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

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

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Web Browser Category

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

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Enterprise Applications Category

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

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

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The Server Category

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

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Local Escalation of Privilege Category

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

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The Container Category

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

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AI Database Category

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

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The Coding Agent Category

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

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The Local Inference Category

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

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The NVIDIA Category

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

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Conclusion

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

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

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

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

ThreatsDay: Wie scheinbar harmlose Updates und KI-Input-Agenten missbraucht werden

Sat, 25 Jul 2026 19:00:31 +0200

LONDON (IT BOLTWISE) – Dieses ThreatsDay-Bulletin zeigt, wie Angreifer die „Gewohnheit“ der Nutzer ausnutzen: Updates, Berechtigungen, normale Installationswege und sogar KI-Bildreviews. Ein Beispiel ist eine PNG-Datei, die versteckte Anweisungen enthält und damit Coding-Agenten in Sessions mit scheinbar harmlosen Aufgaben lenken kann. Daneben stehen konkrete Änderungen an Plattformen wie GitHub Enterprise Server und PyPI, die genau […]

... den vollständigen Artikel »ThreatsDay: Wie scheinbar harmlose Updates und KI-Input-Agenten missbraucht werden« lesen

Dieser Beitrag ThreatsDay: Wie scheinbar harmlose Updates und KI-Input-Agenten missbraucht werden erschien als erstes auf IT BOLTWISE x Artificial Intelligence.

9 Kommandozeilen-Tools, die jeder Dev braucht

Sat, 25 Jul 2026 18:59:24 +0200

Selbst wenn Sie dieser Anblick nicht in Verzückung versetzt – ein Blick auf diese obligatorischen Kommandozeilen-Tools lohnt sich.

Foto: SkillUp | shutterstock.com

Manche Devs arbeiten mit der Kommandozeile (auch Command Line Interface; CLI), weil sie sie lieben – andere, weil ihnen nichts anderes übrig bleibt. Egal zu welcher Kategorie Sie sich zählen: Diese neun CLI-Tools helfen Ihrer Produktivität und Effizienz (zusätzlich) auf die Sprünge.

tldr

Keine Angst, wir ersparen Ihnen an dieser Stelle eine langwierige, faszinative Abhandlung über die ganz eigene Magie, die die Unix-Shell entfaltet. Fakt ist: Wenn man mit ihr arbeiten will, ist es manchmal erforderlich, vorher ein Handbuch zu lesen. Unix Docs (auch man- oder manual pages) sind diesbezüglich allerdings ein zweischneidiges Schwert: Die benötigte Information ist vorhanden – es ist nur die Frage, wo. Den Teil der Dokumentation aufzuspüren, den Sie gerade benötigen, kann ein entmutigender Task sein. Zwar kann die gute alte Befehlszeile dabei helfen – um ein offizielles Handbuch aufzurufen, genügt:

$ man

Allerdings zeichnen sich man-pages vor allem durch ihre Informationsdichte aus – und die Tatsache, dass sie manchmal aktuelle Informationen für neuere Tools vermissen lassen. Das CLI-Tool tldr versetzt Sie in die Lage, zielgerichteter zu suchen:

$ tldr

tldr in Aktion.

Foto: Matthew Tyson | IDG

Falls Sie npm installiert haben, ist die tldr-Installation nur einen kurzen Befehl entfernt:

npm install -g tldr

ngrok

Sobald Sie tldr installiert haben, können Sie damit viele weitere Befehle erkunden. Zum Beispiel:

$ tldr ngrok

Reverse proxy that creates a secure tunnel from a public endpoint to a locally running web service.

Mit ngrok eröffnet sich Ihnen eine stressfreie Möglichkeit, von einem Remote-Browser auf eine Entwicklungsmaschine zuzugreifen. Aber das Tool kann noch weit mehr. Sie können damit beispielsweise in der Cloud entwickeln und die Ergebnisse im Browser in Augenschein nehmen. Zudem können Sie mit ngrok auch schnell und einfach laufende Services über HTTPS veröffentlichen – ohne sich mit der Security-Infrastruktur herumschlagen zu müssen. Angenommen, Sie bauen einen Service Worker auf, der HTTPS benötigt, dann ist alles, was Sie für einen sicheren Kontext tun müssen, ngrok zu starten.

Das CLI-Tool ngrok macht Devs das Leben auf verschiedenen Ebenen leichter.

Foto: Matthew Tyson | IDG

Ein Beispiel, bei dem der HTTP-Port 8080 freigegeben wird:

$ ngrok http 8080

Der ngrok-Output sieht wie folgt aus:

https://f951-34-67-117-59.ngrok-free.app -> http://localhost:8080

Anschließend kann jedermann die zugewiesene URL aufrufen (machen Sie sich keine Mühe).

screen

Mit diesem Befehlszeilen-Tool können Sie eine Shell-Sitzung mit oder ohne laufenden Prozess “beiseite legen” und sie anschließend zu einem beliebigen Zeitpunkt fortsetzen – auch wenn Sie die ursprüngliche Session beenden.

$ tldr screen

Hold a session open on a remote server. Manage multiple windows with a single SSH connection.

Nehmen wir an, Sie starten ngrok, um remote auf eine Webanwendung zuzugreifen: Sie starten den Prozess, lassen diesen dann in screen laufen und programmieren so lange etwas. Währenddessen läuft ngrok die ganze Zeit weiter – Sie können über screen jederzeit wieder darauf zugreifen. Veranschaulicht in Code würde das wie folgt aussehen:

$ screen

// Now we are in a new session

$ ngrok http 8080

// Now ngrok is running, exposing http port 8080

Type ctrl-a

// Now we are in screen's command mode

Type the "d" key, to "detach".

// Now you are back in the shell that you started in, while screen is running your ngrok command in the background:

$ screen -list

There is a screen on:

128861.pts-0.dev3 (04/25/24 14:36:58) (Detached)

Tipp

Wenn Sie eine laufende Sitzung, in der Sie sich gerade befinden, benennen wollen, nutzen Sie die Tastenkombination Strg + A und geben :sessionname ein. Das ist besonders nützlich, wenn Sie mit mehreren Screen-Instanzen arbeiten wollen.

Screen ist ein umfangreiches und potentes CLI-Tool.

Foto: Matthew Tyson | IDG

Wenn wie im Beispiel nur eine screen-Instanz läuft, führt der Befehl $ screen -r (für “re-attach”) Sie zurück zu Ihrer ngrok-Sitzung. Im Fall mehrerer Screens können Sie diese mit Hilfe ihrer ID wieder aufrufen:

$ screen -r

Wenn Sie Ihre Session endgültig beenden wollen, beenden Sie ngrok mit Strg + C und geben anschließend exit in die Kommandozeile ein.

sdkman & nvm

Wenn Sie Java oder JavaScript auf einem Server verwenden, sollten Sie sich mit sdkman (für Java) und nvm (für Node) vertraut machen. Beide Kommandozeilen-Tools sind nützlich, wenn es darum geht, mit mehreren Programmiersprachenversionen auf dem selben Rechner zu jonglieren – und dabei sowohl Path Adjustment als auch Umgebungsvariablen überflüssig machen.

Mit sdkman können Sie beispielsweise neuere Java-Versionen erkunden und anschließend wieder zum aktuellen LTS-Release springen. Dieser Prozess wird durch das sdk-Kommando abstrahiert.

sdkman zeigt alle verfügbaren Java-Installationen auf einem lokalen Rechner an – inklusive derjenigen, die gerade in Benutzung ist.

Foto: Matthew Tyson | IDG

Zwischen den Versionen zu wechseln, gestaltet sich denkbar einfach – $ sdk use java 19-open führt Sie direkt zu JDK Version 19.

$ tldr sdk

Manage parallel versions of multiple Software Development Kits.

Supports Java, Groovy, Scala, Kotlin, Gradle, Maven, Vert.x and many others.

Die nvm-Utility funktioniert ganz ähnlich:

$ tldr nvm

Install, uninstall or switch between Node.js versions.

Supports version numbers like "12.8" or "v16.13.1", and labels like "stable", "system", etc.

Ein Blick auf nvm.

Foto: Matthew Tyson | IDG

fzf

Sowohl grep als auch find sind Standardbestandteile der Kommandozeilen-Befehlspalette. Allerdings sind beide Tools nicht so funktional, wie sie sein sollten. Das ruft fzf auf den Plan – einen “Fuzzy File Finder”. Mit “Fuzzy” ist dabei gemeint, dass die Details zu dem, was Sie suchen, nicht unbedingt klar definiert sein müssen. Ein Beispiel:

$ tldr fzf

Command-line fuzzy finder.

Similar to sk.

Sobald Sie fzf starten, indiziert das CLI-Tool umgehend das Dateisystem, um Ergebnisvorschläge für Ihre Suchen zu unterbreiten.

In diesem Beispiel suchen wir nach einem Projekt, an dem wir zuletzt gearbeitet haben.

Foto: Matthew Tyson | IDG

Aus 878.937 Möglichkeiten hat fzf die 25 Dateien und Verzeichnisse ausgewählt, die unseren Anforderungen entsprechen könnten – und das völlig ohne Umwege.

exa

Mit exa werden langweilige alte ls-Listings schöner und nützlicher:

$ tldr

A modern replacement for ls (List directory contents).

Für eine bessere Developer Experience ohne mentalen Overhead statten Sie ls einfach mit einem exa-Alias aus. Das Tool respektiert die meisten ls-Standardoptionen – exa -l funktioniert also (beispielsweise) genau so, wie Sie es erwarten würden.

Exa ist das neue ls.

Foto: Matthew Tyson | IDG

bat

Die bat-Utility ähnelt dem cat-Tool – ist aber besser:

$ tldr bat

Print and concatenate files.

A cat clone with syntax highlighting and Git integration.

Es handelt sich hierbei im Wesentlichen um eine Komfort- beziehungsweise Developer-Experience-Optimierung – ähnlich wie im Fall von exa. Wenn Sie bat verwenden, erwartet Sie ein vollwertiger File Viewer – inklusive Title, Borders, Line Numbers und insbesondere einer hilfreichen Syntax-Highlighting-Funktion für Programmiersprachen oder Konfigurationsdateien. Dabei reagiert bat auf less/more-Befehle – und wird mit “q” beendet. Die Navigation erfolgt über die Pfeiltasten.

Bat ist ein simples Dienstprogramm, das es zu einem echten Erlebnis macht, Dateien auf der Konsole zu durchsuchen.

Foto: Matthew Tyson | IDG

nethack

Ein absoluter Kommandozeilen-Klassiker ist nethack – der ursprüngliche, Konsolen-basierte ASCII Dungeon Crawler. Das CLI-Tool wird Ihre Produktivität zwar nicht direkt ankurbeln – kann aber durchaus dabei helfen, ein paar Minuten zur Ruhe zu kommen, um komplexe Dev-Probleme zu durchdringen.

Es gibt neuere Versionen des Nethack-Konzepts – manchmal fährt man jedoch mit dem Original am besten.

Foto: Matthew Tyson | IDG

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

Ultrahuman Ring Pro im Test: Ohne Abonnement und langlebig

Sat, 25 Jul 2026 18:59:22 +0200

Mike Sawh

Auf einen Blick

Pro

Insgesamt solide Tracking-Leistung
Ansprechende Begleit-App mit einigen nützlichen Modi
Beeindruckende Akkulaufzeit
Ohne Abonnement

Kontra

Hoher Preis
Klobiges Design
Softwarefunktionen entsprechen weitgehend denen des Air

Fazit

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

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

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

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

Design & Verarbeitung

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

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

Mike Sawh

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

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

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

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

Fitness & Tracking

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

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

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

Mike Sawh

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

Mike Sawh

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

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

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

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

Mike Sawh

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

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

Mike Sawh

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

Akkulaufzeit & Aufladen

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

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

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

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

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

Preis & Verfügbarkeit

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

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

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

Sollten Sie den Ultrahuman Ring Pro kaufen?

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

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

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

Technische Daten

Bis zu 15 Tage Akkulaufzeit
Kompatibel mit Android und iOS
Wasserdicht bis zu 100 Metern
2,65 mm dick
Gewicht: 3,3–4,8 g
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Der lange Abend des Vibe Coding (Tarpit Teil 2)

Sat, 25 Jul 2026 18:59:15 +0200

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Der lange Abend des Vibe Coding (Tarpit Teil 4)

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Der lange Abend des Vibe Coding (Tarpit Teil 3)

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Der lange Abend des Vibe Coding (Tipp-Spiel Teil 2)

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Der lange Abend des Vibe Coding (Fristenmanagement Teil 1)

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Der lange Abend des Vibe Coding (WM Sprücheklopfen Teil 2)

Sat, 25 Jul 2026 18:59:12 +0200

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Der lange Abend des Vibe Coding (WM Sprücheklopfen Teil 1)

Sat, 25 Jul 2026 18:59:12 +0200

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Der lange Abend des Vibe Coding (Fristenmanagement Teil 2)

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Der lange Abend des Vibe Coding (Fristenmanagement Teil 3)

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Der lange Abend des Vibe Coding (Fristenmanagement Teil 4)

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Google CEO distracts from Gemini 3.5 Pro delay with talk of Gemini 4 and monthly releases

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

Google CEO Sundar Pichai has sought to allay concerns over the delayed release of the Gemini 3.5 Pro large language model. He dodged questions about it in Google’s quarterly earnings call on Wednesday by focusing on the company’s next frontier AI model, Gemini 4, and plans to release subsequent LLMs at an almost monthly cadence.

His comments came a day after Google unveiled Gemini 3.6 Flash and 3.5 Flash Cyber but offered no update on the release of Gemini 3.5 Pro, the company’s delayed flagship reasoning model that many developers had expected to arrive weeks earlier.

Google introduced the Gemini 3.5 family at its annual I/O conference, promising to release the Pro model in June. That timeline has since slipped, with Bloomberg suggesting Gemini 3.5 Pro is months late because the model’s coding performance is falling short of internal expectations, especially when compared to better performance by similar models from OpenAI and Anthropic.

Instead of revisiting the Gemini 3.5 Pro timeline, Pichai used the earnings call to shift the discussion toward Gemini 4, when asked about how his company planned to navigate an increasingly competitive race to release frontier AI models by to Barclays Investment Bank analyst Ross Sandler.

“We are creating a baseline on top of which you will see us rapidly iterate on subsequent model releases. And so picking up pace and releasing models almost at a monthly cadence is part of our road map as we are building Gemini 4 as well,” Pichai said during the call.

Sandler’s question followed one from JPMorgan Chase & Co analyst Douglas Anmuth, who asked Pichai if Google was releasing frontier AI models frequently enough to keep pace with rivals OpenAI and Anthropic.

Pichai had responded to Anmuth’s question that Google remained confident of competing at the frontier and was investing heavily in a larger Gemini 4 base model.

Analysts, though, aren’t as confident as Pichai.

While delays to Google’s frontier model roadmap have not triggered an exodus of existing customers, either because of high switching costs or because many enterprises already running multi-model architectures, they have made CIOs evaluating AI platforms more cautious about making new commitments, said Bhupendra Chopra, chief revenue officer at IT consulting firm Kanerika.

A monthly model release cadence could prove to be a double-edged sword for enterprises and their CIOs.

While a monthly release cadence could help enterprises gain faster access to improvements in model performance, cost and capabilities, it will also require CIOs to invest more heavily in testing, governance and version management to safely adopt those updates, said Sanchit Vir Gogia, chief analyst at Greyhound Research.

Similarly, Pareekh Jain, principal analyst at Pareekh Consulting, said enterprises will embrace a faster release cadence only if each successive model delivers measurable improvements in performance, cost or safety, rather than simply changing version number.

The challenge for CIOs, Jain said, is not just keeping up with model releases; it’s deciding whether each new version is worth the cost of validating it.

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.

Claude Opus 5 arrives with near Fable performance at half the price

Sat, 25 Jul 2026 18:51:45 +0200

Anthropic's latest Claude upgrade targets developers and enterprises with stronger coding, better reasoning efficiency, prompt-cache-friendly tool changes, and near-Fable performance at Opus pricing.

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

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

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

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

Build High Quality Android Apps Using Agents

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

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

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

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

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

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

3: Accelerating AI coding assistance with Android Bench

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

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

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

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

Building AI Into Your Apps

5: Building Intelligent Apps with generative AI

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

6: Experiment with AppFunctions today

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

The Future is Adaptive

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

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

Build Android UI with Compose

8: Building seamless Android experiences across devices with Jetpack Compose

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

9: Create seamless experiences for Googlebook

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

New Desktop Android Emulator

10: Unified widget development experience with Jetpack Glance

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

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

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

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

12: Accelerate your development with Android XR Developer Preview 4

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

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

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

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

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

Low Light Boost and Magic Eraser in action

14: Increase app discovery and engagement on Google TV

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

15: Performance: the foundation of a great app experience

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

And The Latest on Driving Business Growth

16: What’s new in Google Play

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

Gemini will provide users with app suggestions during a search

17: And of course, Android 17

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

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

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

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

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

Datadog delivers millions of in-depth performance insights with ProfilingManager

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

Posted by Alice Yuan, Developer Relations Engineer at Google, Arti Arutiunov, Product Manager at Datadog and Nikita Ogorodnikov, Staff Software Engineer at Datadog

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

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

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

The impact of ProfilingManager

ProfilingManager is a system service introduced in Android 15 that enables apps to programmatically collect performance data such as call stack samples, field traces and memory heap dumps directly from production environments. This capability shifts the engineering paradigm from reactive manual reproduction to proactive field analysis.

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

Solving the Android code-level visibility challenge

Prior to the implementation of ProfilingManager, Datadog’s Real User Monitoring (RUM) focused on high-level application health and session-level telemetry to assess the user journey. Engineering teams could monitor Android performance signals like time to initial display, ANR rates, CPU load, and frozen frames. These insights extended to granular interactions, such as network latency, touch events, and main thread hangs. However, while this data effectively highlighted which performance bottlenecks were surfacing in the field, it provided no clear path to identifying the root cause of these failures.

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

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

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

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

Processing millions of weekly profiles to optimize real-world apps

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

Integrating a system-level profiling API into a global monitoring SDK required solving infrastructure challenges. Because ProfilingManager generates highly detailed performance traces, the Datadog engineering team had to build a pipeline capable of parsing and analyzing these profiles on the server side at scale. Beyond profile collection, Datadog also emphasizes the importance of balancing sampling frequency with collecting enough data to generate meaningful insights about your application. Datadog relies on ProfilingManager’s built-in rate limiting as a critical stability safeguard, preventing excessive telemetry requests from overburdening user devices.

The team has been profiling Datadog's own native Android application and a number of early adopters’ applications for months, gathering millions of profiles to ensure a fast, error-free launch experience and to refine their performance-detection algorithms. Today, the production integration seamlessly scales across a variety of Android devices.

Conclusion

By integrating Android’s ProfilingManager API, Datadog successfully closed the visibility gap between backend systems and mobile client applications for their customers. By processing millions of profiles weekly with negligible device overhead, Datadog equips Android developers with the code-level insights necessary to diagnose complex performance bugs instantly, helping developers build smoother applications and improve their app’s performance signals in the Play Store. To adopt the ProfilingManager API directly into your performance observability framework, check out our documentation.

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

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

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.

Android Studio Quail 2 is Stable: Multi-task with the Android Studio AI agent

Sat, 25 Jul 2026 10:15:29 +0200

Posted by Amman Asfaw, Product Manager, Android Studio

Android Studio Quail 2 is now stable and ready for you to use in production, bringing a shift to your IDE with concurrent agentic workflows, natively integrated memory leak profiling, and context-aware crash remediation. Whether you are performing a sweeping architectural overhaul, tracing a memory leak, or resolving a critical production crash, Android Studio keeps you anchored in your workspace by reducing manual friction.

Here’s a deep dive into what’s new:

Multi-tasking with parallel chats

In Android Studio Quail 2, we've been hard at work redesigning Agent Mode from the ground up. This new architecture provides better performance, offers more flexibility for decomposing complex tasks, and improves the suite of internal tools the agent uses to do its work.

In addition to these behind-the-scenes improvements, these changes also allow you to converse across multiple agent chats simultaneously. Waiting for the Android Studio agent to finish a task before you can ask another question or initiate a separate task in Agent Mode is a bottleneck of the past. You can multi-task seamlessly: kick off a UI refactor in one tab, fix a ProGuard rule in a second, and generate documentation in a third.

You can also change which models the agent uses from chat to chat based on the requests you have. Take a look at Android Bench for an analysis of how LLMs perform Android development tasks.

How to use: Click the "+" icon to start a new parallel conversation, and use the History icon to navigate between active tasks. Alternatively, select File > New > New Agent Tab to open a conversation in a dedicated tab.
Note: Worktree support is currently unavailable. Exercise caution when running concurrent chats that modify the same project files, which can potentially lead to editor conflicts.

Run multiple agent tasks in parallel with different models of your choice.

Use the History icon to navigate between active tasks.

Memory leak detection with LeakCanary

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

Hunting down memory leaks can be a tedious, manual task. Starting with Android Studio Quail 2, the popular open-source leak detector LeakCanary is natively integrated directly into the Profiler as a dedicated, first-class task.

This integration transforms your debugging performance by lifting and shifting the heap analysis off your resource-constrained testing phone, and onto your powerful development computer. By running the analysis on your computer, leak tracing is up to five times faster and jank-free, leaving your test app running smoothly on the device.

Once a leak is detected during a profiling session:

The Profiler renders an interactive, color-coded leak trace, grouping occurrences and estimating lost memory.
You can click Go to declaration on any leaking object in the trace to instantly jump to that exact line of code in your editor.
You can click Fix with Agent to have the Gemini agent ingest the trace, explain the root cause of the retained reference, and write the exact code change (such as unbinding a listener or clearing a static reference) to plug the leak.

Review memory leaks identified via LeakCanary through the Fix with Agent button.

App Quality Insights agent integration

Tracking down the root cause of an app crash can require manually synthesizing stack traces, device data, and source code. However Android Studio’s App Quality Insights (AQI) is now fully integrated with Agent Mode to do the heavy lifting for you.

When you click on a crash in the AQI panel, you immediately get a concise, high-level summary of the issue. If you need to dig deeper, simply click See more. This opens a dedicated chat where the agent uses your selected model and pulls in local source code and the full stack trace to deliver a comprehensive explanation of the failure.

With the new agent integration, you move directly from issue identification to resolution. By clicking Fix with AI, the agent will analyze the issue, propose a step-by-step fix plan, and—upon your approval—apply the necessary code changes directly to your project and verify the resulting fix

The Fix with AI button triggering the agent to analyze the issue, then propose the fix

Quality & stability improvements

Beyond new features, we’ve continued our focus on quality by addressing numerous bugs and incorporating the latest stability and performance improvements from the IntelliJ platform, making this a significant enhancement for your daily development.

Get Started

Ready to dive in and accelerate your development? Download Android Studio Quail 2 and start exploring these new features today! As always, your feedback is crucial to us. Check known issues, report bugs, and be part of our vibrant community on LinkedIn, Medium, YouTube, or X.

Decades-Old Bash Tricks Expose AI Coding Agents To Supply Chain Attacks

Sat, 25 Jul 2026 10:12:50 +0200

Slashdot reader wiredmikey writes: AI security researchers have uncovered a structural security flaw dubbed GuardFall that allows decades-old Bash shell tricks to bypass safeguards in most open source AI coding agents. By exploiting shell behaviors such as quote removal and variable expansion, attackers can hide malicious commands in repositories, README files, Makefiles, or other content consumed by AI agents. If executed — particularly in auto-approve or CI environments—the commands can steal credentials, compromise developer systems, or enable software supply chain attacks. According to researchers at Adversa AI, the 11 popular open source AI coding agents tested, only one successfully blocked all of the Bash trick techniques.

Read more of this story at Slashdot.

Linus Torvalds To Critics of AI Coding On Linux: 'Fork It. Or Just Walk Away.'

Sat, 25 Jul 2026 10:12:30 +0200

Linus Torvalds says the Linux kernel will not ban AI-assisted coding tools, and if anti-AI absolutists have a problem with that, they can "fork it" or "walk away." An anonymous reader quotes a report from Ars Technica: Writing in a lengthy post on the Linux kernel mailing list this week, Torvalds said that "Linux is not one of those anti-AI projects, and if somebody has issues with that, they can do the open-source thing and fork it. Or just walk away." The statement came amid a lengthy thread arguing about the use of Sashiko, an "agentic Linux kernel code review system" that its creators claim can, in tests, independently find 53.6 percent of the bugs that would end up being fixed by human coders in later commits. But the tool can also waste maintainers' time by sending "false positive" reports of bugs that don't exist, at a rate Sashiko's maintainers estimate is "well within [the] 20% range." In discussing whether maintainers should be subjected to a flood of these kinds of automated, AI-powered bug report emails (true or false), one poster cited the Software Freedom Conservancy's recent statement that the open source community "should support, not just tolerate, those who outright reject LLM-gen-AI systems" and that "every FOSS contributor deserves self-determination regarding LLM-gen-AI." In the face of that statement, Torvalds said that he rejects those who demand that their open source projects not accept any LLM-generated code or revisions. "We're not forcing anybody to use [LLM tools], but I will very loudly ignore people who try to argue against other people from using it," Torvalds said. Torvalds said his position on this is a pragmatic one that's "based on technical merit. Not fear of new tools." And when it comes to utility, Torvalds said that "AI is a tool, just like other tools we use. And it's clearly a useful one. It may not have been that 'clearly' even just a year ago, but it's no longer in question today. Anybody who doubts that clearly hasn't actually used it." [...] While Torvalds acknowledged that "AI isn't perfect," he urged detractors to compare the output of these tools to the performance of human code maintainers. "Anybody who points to the problems at AI had better be looking in the mirror and pointing at themselves at the same time," Torvalds wrote. "Because it's not like natural intelligence is always all that great either."

Read more of this story at Slashdot.

Rust Will Help Linux Succeed and Makes Coding Fun, Says Greg Kroah-Hartman

Sat, 25 Jul 2026 10:12:26 +0200

ZDNet reports on June's Open Source Summit India 2026 in Mumbai, where Linux stable kernel maintainer Greg Kroah-Hartman gave a talk titled "Rust and Linux: How the Rust Language is Going to Help Linux Succeed." Kroah-Hartman said in his keynote that "the [Linux] kernel is moving toward Rust. Git is moving toward Rust. Lots of projects are starting to move toward Rust." He didn't always feel that way. Kroah-Hartman added, "A number of years ago, when a friend of mine said, 'Ah, you got to try this new language. It's called Rust.' I was like, 'What? No, C is great.' His friend continued, "'No, no, no! It makes programming fun again.' I'm like, 'Nah, programming is fun in C.' He was right. I should have done it then. Rust is actually fun. It makes programming fun. It takes a lot of stuff away from having to worry about the compiler, which can fix a lot of your problems for you, and it makes code a little bit better." So, Kroah-Hartman has moved from being a Rust skeptic to one of its strongest champions inside the kernel. He now regards Rust as a permanent part of Linux, not an experiment. His case is straightforward: Rust's ownership and type system can eliminate most of the "stupid little tiny things" that dominate kernel Common Vulnerabilities and Exposures (CVEs), while making life easier for overworked maintainers. "Rust," in short, "makes my life so much easier...." In India, he said Linux sees "about 13 CVEs a day" and has been running at "almost nine changes an hour" for a decade or more. Most of those vulnerabilities, he argued, are not exotic attacks but simple C mistakes — unchecked pointers, forgotten unlocks, and sloppy cleanup paths: "This is what we're fixing 13 times a day. Small, trivial, little bugs like this all the time.... I've seen every CVE the kernel has done in the past 25 years. I think 80% would be gone, just because they would be caught by Rust." The remaining 20% are the logic bugs he'd prefer to focus on...." Moreover, Rust is becoming the default for new work in key subsystems. "New drivers for some subsystems are only going to be accepted in Rust...." he said. Binder, the Android IPC mechanism at the heart of billions of devices, now has parallel C and Rust implementations in the kernel. The C version "will go away soon," leaving the Rust version "as the bedrock of all Android devices going forward."

Read more of this story at Slashdot.

JetBrains TeamCity 2023.11.4 Authentication Bypass

Sat, 25 Jul 2026 10:04:56 +0200

Topic: JetBrains TeamCity 2023.11.4 Authentication Bypass Risk: High Text:#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ # Exploit Title: JetBrains TeamCity 2023.11.4 - Authentication Bypass # ...

Ghost CMS 5.59.1 Arbitrary File Read

Sat, 25 Jul 2026 10:04:50 +0200

Topic: Ghost CMS 5.59.1 Arbitrary File Read Risk: Medium Text:#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ # Exploit Title: Ghost CMS 5.59.1 - Arbitrary File Read # Date: 2023-09-...

10 Secret Bard Tips And Tricks (How To Use Google Bard)(Google Bard Tutorial)

Sat, 25 Jul 2026 09:05:25 +0200

Author: TheAIGRID - Bewertung: 486x - Views:35021

How To Use Google Bard)(Google Bard Tutorial)

Welcome to our channel where we bring you the latest breakthroughs in AI. From deep learning to robotics, we cover it all. Our videos offer valuable insights and perspectives that will expand your knowledge and understanding of this rapidly evolving field. Be sure to subscribe and stay updated on our latest videos.

All Bard Features
- Bard Can Make Charts - https://www.reddit.com/r/GoogleBard/comments/123s0yt/wow_google_bard_can_make_a_chart_bing_ai_used_to/
- Bard makes very big mistakes https://twitter.com/0xgaut/status/1638287359098716160
- Bard Cannot Help With Coding - https://twitter.com/iamnafets/status/1638232186649477120/photo/1
- Bard Actually has access to recent events
- Bard Cant Access Articles (Sometimes
- Bard Can Rewrite content
- Rewording Questions Helps https://www.reddit.com/r/GoogleBard/comments/11xoaw7/bard_can_actually_answer_code_questions_it_just/
- Bard Can write stories
- Bard is a confusing mix between ChatGPT + Bing
- Bard does have shorter answers
- Bard is quicker

Was there anything we missed?

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

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

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

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

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

Many paths to needing Rust

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

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

Rust learning resources

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

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

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

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

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

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

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

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

Beginner stumblings and unlearning habits

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

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

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

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

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

Learning to work with the borrow checker

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

The compiler as teacher

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

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

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

Learning by doing

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

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

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

Letting go of "clone guilt"

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

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

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

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

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

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

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

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

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

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

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

Teaching Rust in academia

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

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

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

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

Learning using LLMs

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

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

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

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

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

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

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

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

Organizational considerations for Rust learners

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

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

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

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

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

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

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

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

Silent attrition

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

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

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

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

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

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

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

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

Feedback on near-bounces from survey

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

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

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

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

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

Need more focused work on silent attritrion

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

Conclusions

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

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

What seems worth trying

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

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

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

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

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

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

What we still don't know

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

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

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

Der lange Abend des Vibe Coding (Tarpit Teil 1)

Sat, 25 Jul 2026 08:36:41 +0200

Author: SemperVideo - Bewertung: 461x - Views:13063

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Der lange Abend des Vibe Coding (Tipp-Spiel Teil 1)

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

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Der lange Abend des Vibe Coding (Tipp-Spiel Teil 3)

Sat, 25 Jul 2026 08:36:28 +0200

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

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

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

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

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

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

Claude Just Revealed AI's Biggest Problem

Sat, 25 Jul 2026 08:35:47 +0200

Author: Two Minute Papers - Bewertung: 3605x - Views:76846

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Der lange Abend des Vibe Coding (Next Project)

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Author: SemperVideo - Bewertung: 70x - Views:2470

Chasing new skills, going back to basics and pushing for collective action: how software engineers are adapting to AI

Sat, 25 Jul 2026 07:03:26 +0200

Software engineering was one of the best-paying professions in the US in 2022, but the advent of AI has disrupted it, leading to several layoffs and underemployment

Every weekday, Matt, a software engineer, looks forward to his four-hour train commute to Pawling, New York. It’s time he uses to work on his own project: a browser-based video game for which he writes every line of code himself.

“I am actively trying to keep my axe sharp,” said Matt, who did not want to use his actual name, to protect his employment. In the last six months, Matt’s job has increasingly shifted away from coding, problem solving and software architecture towards reviewing code generated by artificial intelligence. Convinced that the shift will weaken his skills, he’s doing what he can to keep them intact. “I am trying not to leverage AI where I can.”

Samsung Galaxy Z Flip 8 und Fold 8 (Ultra): Bei Vodafone bekommt ihr garantiert 500 Euro für euer altes Smartphone

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Samsung bringt mit dem Galaxy Z Flip 8, Galaxy Z Fold 8 und Galaxy Z Fold 8 Ultra seine neue Foldable-Generation auf den Markt. Parallel dazu hat Vodafone den offiziellen Vorverkauf gestartet.

Claude Opus 5 arrives with near Fable performance at half the price

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Anthropic's latest Claude upgrade targets developers and enterprises with stronger coding, better reasoning efficiency, prompt-cache-friendly tool changes, and near-Fable performance at Opus pricing.

Prentis, new AI lab co-founded by Reid Hoffman, Mark Pincus in talks to raise $100M

Sat, 25 Jul 2026 01:47:07 +0200

The neolab is betting that automating routine computer tasks will soon outpace coding as AI's biggest use case.

Prentis, new AI lab co-founded by Reid Hoffman, Marc Pincus in talks to raise $100M

Sat, 25 Jul 2026 00:32:12 +0200

The neolab is betting that automating routine computer tasks will soon outpace coding as AI's biggest use case.

5 endpoint blind spots your EDR/XDR was never built to see

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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.

Meet the New Claude Opus 5: Frontier-Class Agentic Coding and Computer Use at Unchanged Opus Pricing

Sat, 25 Jul 2026 00:03:51 +0200

Today, Anthropic released Claude Opus 5. It replaces Claude Opus 4.8 as the Opus-tier flagship. Pricing is unchanged at $5 per million input tokens and $25 per million output tokens. The Anthropic team positions Opus 5 as approaching the intelligence of Claude Fable 5 at half the price. It is now the default model on […]

The post Meet the New Claude Opus 5: Frontier-Class Agentic Coding and Computer Use at Unchanged Opus Pricing appeared first on MarkTechPost.

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

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

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

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

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

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

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

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

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

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

About this research

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

Anthropic's New Opus 5 Model Rivals Fable 5 For Half the Price

Fri, 24 Jul 2026 21:08:38 +0200

Anthropic has released Opus 5, a new Claude model that it says comes close to its higher-end Fable 5 model at half the price while improving on Opus 4.8 in knowledge work, coding, and scientific research tasks. "At the same time, Anthropic says it has managed to make the model more resistant to being tricked," notes Engadget. Additionally, the company says Opus 5 "exhibits the lowest rates of deceptive behavior." From the report: One important distinction between Opus 5 and Mythos, which is currently only available to a limited number of vetted organizations through Anthropic's Project Glasswing initiative, is that the company has specifically avoided training the new model on cyber-related tasks. Due to more its powerful capabilities, Opus 5 is broadly better at those tasks than its predecessor, making it more useful for finding cybersecurity vulnerabilities, but the company says Opus 5 is "substantially behind" its flagship model at exploiting those vulnerabilities. [...] Anthropic says "Claude Opus 5's safeguards are designed to allow beneficial uses of the model in both cybersecurity and biology." The company has strengthened some of the model's cyber-related guardrails, but notes it did so along a "narrow range" of specific tasks. "Based on our testing, we expect the classifiers to intervene around 85 percent less often than they do for Fable 5," Anthropic said. With Opus 5, Anthropic also isn't including it in its recently announced 30-day data retention policy, which the company introduced alongside Fable and Mythos 5. As for pricing. Anthropic says API costs for Opus 5 will remain at $5 per one million input tokens and $25 per one million output tokens. Anthropic has also added an "effort" menu for Opus that users can tweak to tell the model whether they want it to be more thorough or fast and efficient to conserve tokens.

Read more of this story at Slashdot.

Anthropic claims its new Claude Opus 5 delivers near-Fable 5 performance at half the token price

Fri, 24 Jul 2026 20:51:31 +0200

Anthropic's new flagship model Claude Opus 5 posts top scores in coding and knowledge work at half of Fable 5's token rates. On ARC-AGI-3, a benchmark for novel problem-solving, Opus 5 hits 30.2 percent, nearly four times higher than GPT-5.6 Sol.

The article Anthropic claims its new Claude Opus 5 delivers near-Fable 5 performance at half the token price appeared first on The Decoder.

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.

Why Cognition bought Poke: AI personality is becoming a competitive advantage

Fri, 24 Jul 2026 20:09:14 +0200

AI coding startup Cognition has acquired Poke, the AI assistant you text like a friend, in a deal valuing the startup in the low nine figures. The acquisition brings Poke’s conversational style and interaction model to Cognition’s coding agent Devin, reflecting a growing belief that how AI assistants interact with users is as important as the models powering them.

Bridging Innovation and Stability: The Risks of Vibe Coding

Fri, 24 Jul 2026 19:51:41 +0200

Vibe coding offers resource-limited organizations tools for rapid software development. But to build products that are sustainable and resilient, implementing a defined process is key to long-term success.

Tego AI Discloses Second Claude Flaw in a Week: Hidden Link Silently Sends Files to Attackers

Fri, 24 Jul 2026 19:24:53 +0200

The post Tego AI Discloses Second Claude Flaw in a Week: Hidden Link Silently Sends Files to Attackers appeared first on Cyber Security News.

Tego AI Discloses Second Claude Flaw in a Week: Hidden Link Silently Sends Files to Attackers

Fri, 24 Jul 2026 19:24:51 +0200

The post Tego AI Discloses Second Claude Flaw in a Week: Hidden Link Silently Sends Files to Attackers appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.

Claude Opus 5 arrives with near Fable performance at half the price

Fri, 24 Jul 2026 19:06:21 +0200

Anthropic's latest Claude upgrade targets developers and enterprises with stronger coding, better reasoning efficiency, prompt-cache-friendly tool changes, and near-Fable performance at Opus pricing.

Cloudflare Internal DNS puts public and private DNS on one policy engine

Fri, 24 Jul 2026 18:18:13 +0200

Enterprises typically operate separate systems for internal and external DNS because the two serve different audiences. Public DNS resolves names for services meant to be reached from the internet. Private DNS resolves internal resources, such as databases and internal applications, that should never be visible outside the corporate network.

While public DNS is usually a single system, private DNS is often scattered across on-premises appliances, cloud-native resolvers, and split-horizon setups, where the same hostname resolves to a different answer depending on whether the query comes from inside or outside the network. Coordinating those deployments across headquarters, branch offices, and multiple clouds means ongoing manual synchronization work for network teams.

Private DNS itself is not a new concept. It is already available from hyperscalers and established enterprise DNS vendors, but it typically runs apart from public DNS, with its own console, control plane and policy engine.

Cloudflare’s answer is a product it calls Internal DNS.

“Many organizations already use Cloudflare for their public DNS,” Enrique Somoza, product, performance and infrastructure at Cloudflare, told Network World. “Internal DNS extends that same platform to private DNS, so public and private are managed from the same global network and control plane.”

How it works

Query handling starts at the resolver, not at the zone. That consolidation extends to daily operations as well.

“Instead of operating two separate DNS systems, customers use one API, one audit trail, one dashboard, and one policy engine for every DNS query—whether it is for a public website or an internal application,” Somoza said.

Policy first. The resolver sits ahead of every lookup, not behind it. “Architecturally, Cloudflare Gateway becomes the resolver that customers connect to, and can use WARP, DNS over HTTPS, DNS over TLS, or traditional DNS,” Somoza said. “Gateway evaluates zero -trust policies first, then routes the query to the appropriate DNS view based on context, such as source IP, device posture, or network location.”

No public path in. Internal zones sit outside the public DNS hierarchy entirely. “Internal zones are never assigned public nameservers—they are only reachable through Gateway, so every query is evaluated before it is resolved,” Somoza said.

One hostname, multiple answers. Branch offices, data centers and cloud environments no longer each need their own resolver stack. “Operationally, this simplifies environments that span branch offices, data centers, and multiple clouds,” Somoza said. “The same internal hostname can return different answers depending on where the request originated without maintaining separate resolver infrastructure, conditional forwarders, or duplicate zone files.”

Somoza described the underlying objective in direct terms: “The goal is to make internal DNS behave like a single service instead of a collection of independent deployments,” he said.

View selection. The same hostname can resolve to different IP addresses depending on where the request comes from. Gateway makes that call using several client signals.

“View selection is policy driven,” Somoza said. “Gateway resolver policies evaluate the context of each DNS query, including attributes like source IP, device identity, or network location and determine which DNS view should answer the request.”

A view is a container, not a separate infrastructure stack. Somoza explained that a view is simply a logical grouping of internal zones. For example, a company could have separate views for Europe and North America, or for corporate users and operational technology networks.

Latency and resilience. Internal DNS inherits its performance characteristics from Cloudflare’s existing public network. “Internal DNS runs on Cloudflare’s global network, so queries are answered by the nearest available Gateway location, helping keep latency low for connected users,” Somoza said. “Because Internal DNS runs on the same global infrastructure as Cloudflare’s public DNS, it benefits from the same anycast architecture, geographic distribution, and resilient network design.”

How this differs from split-horizon DNS

Internal DNS replaces the duplicate-zone model traditional split-horizon setups depend on.

“Before migrating, many organizations maintain multiple versions of the same internal DNS zones across headquarters, branch offices, and cloud environments,” Somoza explained. “Conditional forwarders determine which resolver answers each query, and keeping those environments synchronized becomes an ongoing operational task.”

Internal DNS collapses those duplicate zones into a single authoritative copy split across views instead. “With Internal DNS, that configuration becomes much simpler,” Somoza said. “A customer might create a single corp.internal zone in Cloudflare and define multiple DNS views.”

For example, users in headquarters could receive one internal IP address for wiki.corp.internal, while branch offices receive a different address. Somoza emphasized that the zone itself only exists once. “Instead of maintaining multiple copies of the same configuration, administrators manage a single source of truth,” he said.

Early use cases and migration challenges

Not surprisingly, Somoza noted that the first use case Cloudflare sees for Internal DNS is for split-horizon DNS consolidation. There is also interest from organizations that operate across multiple cloud providers that want one consistent internal DNS service instead of managing separate DNS platforms in each environment.

Another common use case is extending zero-trust policies to internal name resolution. “Customers already use Gateway to control access to internet traffic, and Internal DNS lets them apply similar policy decisions before internal names are resolved,” Somoza said.

When it comes to migration, the friction customers report during migration is procedural rather than architectural.

“Customers need to think through API permissions, connectivity, and how existing local DNS forwarding rules interact with Gateway,” Somoza said. “Those are all well understood migration steps and customers often run both environments in parallel before completing the transition.”

Get started with OpenAI GPT-5.6 Sol, Terra, and Luna on Amazon Bedrock

Fri, 24 Jul 2026 17:50:42 +0200

OpenAI GPT-5.6 Sol, Terra, and Luna are now generally available on Amazon Bedrock. Learn how to select a model, run inference through the Responses API on the bedrock-mantle endpoint, reduce cost with prompt caching, connect the OpenAI Codex coding agent, and plan for quotas and scaling.

OneDrive: Microsoft stoppt Updates für Windows 10 ab August - ad-hoc-news.de

Fri, 24 Jul 2026 17:46:36 +0200

Parallel endet am 13. Oktober 2026 der Mainstream-Support für Windows Server 2022 und Windows 11 Version 24H2 (Home und Pro). Anzeige. Während ...

Visual Studio Code 1.130 dresses up Agents window

Fri, 24 Jul 2026 17:00:02 +0200

Microsoft has released Visual Studio Code 1.130, an update to the code editor that brings several improvements to the Agents window, along with enhancements to the agent host and the terminal.

VS Code 1.130 was released on July 22, one week after VS Code 1.129. Developers can access the release for Windows, Linux, or Mac from code.visualstudio.com.

With the new release, the Agents window gets updates that make it easier to review changes and manage chats. File-level diff statistics help users assess the size of each file’s changes when scanning a multi-file diff. The window also gets a more compact multi-file diff that makes it easier to review changes, Microsoft said. The Agents window is a dedicated window in VS Code that lets users run and track multiple agent sessions in parallel across their projects, without opening each workspace in a separate window.

Also with VS Code 1.130, assisted permissions for agent tool calls are available in the agent host. With assisted permissions, the LLM evaluates the risk of each tool call and decides whether the tool can run or should require the user’s approval. The setting to enable assisted permissions is chat.assistedPermissions.enabled. In another agent host improvement, quick chats running on the agent host now use compact, single-line rows in the sessions list. Regular sessions retain a second line with change statistics, status, and timestamps.

VS Code users now can open file links from Git diff output in the terminal when Git’s diff.mnemonicPrefix option is enabled. VS Code recognizes prefixes such as i/ for the index and w/ for the working tree, and removes the prefix from the link target so the correct file opens. When mnemonic prefixes are enabled, VS Code also recognizes the numeric prefixes produced by git diff --no-index.

Timestamps for chat requests and responses now are displayed when users hover over the message toolbar. You can disable this through the chat.verbose setting.

Slopsquatting, Phantom Domains, and HalluSquatting Are the Same AI Attack

Fri, 24 Jul 2026 16:10:23 +0200

Slopsquatting, phantom squatting, and HalluSquatting all exploit the same late-binding attack pattern, where AI coding agents trust hallucinated package, repo, or domain names. ActiveState explains how pre-fetch verification and governed dependency management can help stop these attacks before malicious code enters the pipeline. [...]

Updated Cyber Threat Actor Naming System

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

Introduction

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

Why are we Adopting a Different Naming System?

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

Our New Schema

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

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

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

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

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

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

A Work in Progress

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

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

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

Samsung Galaxy Z Flip 8 und Fold 8 (Ultra): Bei Vodafone bekommt ihr garantiert 500 Euro für euer altes Smartphone

Fri, 24 Jul 2026 15:14:37 +0200

Samsung bringt mit dem Galaxy Z Flip 8, Galaxy Z Fold 8 und Galaxy Z Fold 8 Ultra seine neue Foldable-Generation auf den Markt. Parallel dazu hat Vodafone den offiziellen Vorverkauf gestartet.

Wie mit KI aus Daten Entscheidungen werden | Computer Weekly

Fri, 24 Jul 2026 14:59:20 +0200

Sicherheit, Zugriffsrichtlinien und Überprüfbarkeit müssen parallel zur Demokratisierung selbst skalieren. Wenn dies geschieht, ist das Ergebnis nicht ...

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)

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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iPhone Ultra: Unstimmigkeiten über Apples Zeitplan

Fri, 24 Jul 2026 14:00:52 +0200

Eigentlich gehen wir von einem Start des iPhone Ultra parallel zum iPhone 18 Pro im Herbst 2026 aus. Ein Bericht nimmt nun erneut vermeintliche Unstimmigkeiten ... Weiterlesen ...

Der Beitrag iPhone Ultra: Unstimmigkeiten über Apples Zeitplan erschien zuerst auf Apfelpage.

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)

Top AIs invent same fake PyPl and npm package names

Fri, 24 Jul 2026 12:56:02 +0200

Enterprise software developers continue to be in danger of falling victim to slopsquatting, where AI coding tools hallucinate the existence of nonexistent libraries and hackers create malicious packages in response.

The top AI coding tools are remarkably consistent in their hallucinations: Researcher Aleksandr Churilov found the same 127 fake package names generated by five different LLMs.

Slopsquatting is a relatively new form of malware attack that involves the creation of malicious packages in response to the hallucinations of AI coding tools, causing the malicious packages to be incorporated into legitimate applications.

Churilov set out his findings in a research paper, The Range Shrinks, the Threat Remains: Re-evaluating LLM Package Hallucinations on the 2026 Frontier-Model Cohort, which is yet to be peer-reviewed. He found 127 hallucinated package names were shared across Claude Sonnet 4.6, Claude Haiku 4.5, GPT-5.4-mini, Gemini 2.5 Pro, and DeepSeek V3.2.

As of April this year, 53 of those names — 41 on the PyPI software repository and 12 on npm —are still available for registration.

According to the study, there are two reasons for this amount of conformity in the output of the models. First, models may learn the same incorrect package references from shared public training material, such as tutorials and documentation.

Second, they may independently extrapolate plausible names from ecosystem conventions. In this way, they could produce names that look correct, even if they don’t actually exist.

While Churilov’s research will worry CISOs and security-conscious developers, there is some relief. The research has not yet found any evidence that any of the remaining 53 names have been registered maliciously, nor used in an attack.

This article first appeared on InfoWorld.

Top AIs invent same fake PyPl and npm package names

Fri, 24 Jul 2026 12:51:25 +0200

The top AI coding tools are remarkably consistent in their hallucinations: Researcher Aleksandr Churilov found the same 127 fake package names generated by five different LLMs.

As of April this year, 53 of those names — 41 on the PyPI software repository and 12 on npm —are still available for registration.

Second, they may independently extrapolate plausible names from ecosystem conventions. In this way, they could produce names that look correct, even if they don’t actually exist.

New GENE 01 Bionic Humanoid Robot Teases AMD AI Game Changer (KIMI K3 VS FLASH 3.6)

Fri, 24 Jul 2026 12:34:40 +0200

Author: AI News - Bewertung: 7x - Views:48

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Generative Bionics just teased the Gene 01 humanoid robot to challenge Tesla and Boston Dynamics. In this video, we break down its groundbreaking multimodal tactile skin, 24 DoF hands, and open-source platform. We also see the new M1 hand from Mimic that can interchange with different robot models. AI News also compare the newly released Moonshot AI Kimmy K3 open-source 2.8T model against Google DeepMind’s closed-source Gemini 3.6 Flash API to see which reigns supreme in speed, cost, and coding performance.

Discover the AI agent economy: https://8004agents.ai

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4:56 Kimi K3
6:26 Gemini Flash 3.6

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Glaze AI: Glaze-Apps können nun native KI-Unterstützung bieten – ohne Setup & API-Schlüssel

Fri, 24 Jul 2026 11:49:44 +0200

Erst zum Anfang des Monats hat das Raycast-Team sein Portfolio um die Vibe-Coding-App Glaze aufgestockt. Nutzer können beschreiben, was sie gerne von der App benötigen, und...

Zum Beitrag: Glaze AI: Glaze-Apps können nun native KI-Unterstützung bieten – ohne Setup & API-Schlüssel

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How to execute queries in parallel using EF Core

Fri, 24 Jul 2026 11:04:59 +0200

EF Core is Microsoft’s flagship ORM (object-relational mapper), the software layer that allows .NET developers to work with relational databases. The DbContext class is the core component of the EF Core framework for managing database operations. However, the DbContext class in EF Core is not thread-safe. Hence, if you share DbContext instances between multiple threads, you will often encounter data corruption issues and the InvalidOperationException.

In this article, we’ll learn how we can execute queries in parallel in EF Core by handling thread-safety issues to avoid concurrency errors. To work with the code examples provided in this article, you should have Visual Studio 2026 installed in your system. You can download Visual Studio 2026 here.

Executing EF Core queries in parallel – the problem

When working in today’s data-driven applications, you will often need to fetch data from multiple unrelated datasets. In applications that use concurrency, thread-safety is critical to guaranteeing correct execution, avoiding data corruption and race conditions, and ensuring data consistency. Let’s understand this with an example.

Let’s say we want to populate a dashboard that displays all recently processed orders, metrics, logs, and traces, as well as your application’s performance metadata. We might write the following code.

public class Dashboard
{
    public List Orders { get; set; } = new();
    public Metrics Metrics { get; set; } = new();
    public List Logs { get; set; } = new();
    public List Traces { get; set; } = new();
}
public static async Task LoadDashboardAsync(ProductService productService)
{
    Task    ordersTask  = productService.GetProcessedOrdersAsync();
    Task        metricsTask = productService.GetMetricsAsync();
    Task logsTask    = productService.GetRecentLogsAsync();
    Task    tracesTask  = productService.GetTracesAsync();
    await Task.WhenAll(ordersTask, metricsTask, logsTask, tracesTask);
    return new Dashboard
    {
        Orders  = await ordersTask,
        Metrics = await metricsTask,
        Logs    = await logsTask,
        Traces  = await tracesTask
    };
}

In the preceding code snippet, there are four read operations that are executed by four different Task instances. Our objective is to ensure that the database round trips run in parallel instead of in sequence. We can accomplish this by usingTask.WhenAll, which starts the four tasks, waits for every task to finish, then returns the data wrapped inside a new Dashboard instance.

If we executed these queries sequentially, the user would have to wait until each query completed its execution in turn—for a total wait time equal to the sum of the times for all four queries. However, by running these queries in parallel, we reduce the wait time considerably. The user will need to wait only as long as it takes for the slowest of the four queries to complete its execution.

However, there is a danger with the above approach. If you run multiple operations on the same DbContext instance, you will see an InvalidOperationException with the following message:

A second operation started in this context before the previous operation was completed. This is usually caused by multiple threads using the same DbContext instance; instance members are not guaranteed to be thread-safe.

Databases such as SQL Server, PostgreSQL, and Oracle Database follow a request-response communication model at the connection level: a single connection can process only one command at a time. Hence, you cannot run multiple queries concurrently using the connection. If you await several operations using the same connection, EF Core detects the overlapping use of a non-thread-safe context and throws an InvalidOperationException. To run queries in parallel, you must give each task its own connection or context.

Why DbContext isn’t thread-safe – and how to work around it

The DbContext class in EF Core is designed to manage a single unit of work. To be more precise, EF Core does not provide support for running multiple operations on the same DbContext instance. This design approach creates inherent challenges when you use the same DbContext instance across multiple threads. If DbContext were thread-safe, extensive locking would be required, which would degrade data access performance.

This stateful design of DbContext makes it unsuitable for concurrent access patterns that involve loading, modifying, or tracking different sets of data simultaneously, because it needs to maintain the internal representation of database state.

The change tracker is one of the most important components of DbContext in EF Core. It monitors all entities loaded into memory and detects any changes made to them after they have been loaded. It keeps track of the original, current, and changed values of the entities, thereby enabling the EF Core runtime to know the current state of these entities when you call the SaveChanges() method on the DbContext instance.

To implement thread-safety when working with DbContext, we must write our code to ensure that each concurrent operation gets its own copy of a short-lived instance. Now, we could accomplish this by wrapping a shared DbContext instance inside a thread-safe block using the lock keyword, so that all calls to the database take place using one and only one thread at a time. This approach is illustrated in the code snippet below.

using Microsoft.EntityFrameworkCore;
public class Product
{
    public int Id { get; set; }
    public string Name { get; set; } = string.Empty;
    public decimal Price { get; set; }
    public int Quantity { get; set; }
}
public class AppDbContext : DbContext
{
    public AppDbContext(DbContextOptions options) : base(options) { }
    public DbSet Products => Set();
}

However, while the above approach gives us the thread-safety we need, it can degrade data access performance considerably. A better approach is to use IDbContextFactory , which creates fresh DbContext instances on demand. Calling its CreateDbContext() method is cheap and produces a fresh, isolated context every time.

The following code snippet shows how you can register an instance of type IDbContextFactory as a singleton. You can safely call this code from any thread.

builder.Services.AddDbContextFactory(options =>
    options.UseSqlServer(
        builder.Configuration.GetConnectionString("Default")));

Executing EF Core queries in parallel – the solution

Now let’s see how we can put IDbContextFactory to work. The following code illustrates a class named ProductService that uses a factory to create DbContext instances for each scope of work.

public class ProductService
{
    private readonly IDbContextFactory _factory;
    public ProductService(IDbContextFactory factory)
        => _factory = factory;
    public async Task GetByIdAsync(int id)
    {
        await using var context = await _factory.CreateDbContextAsync();
        return await context.Products.FindAsync(id);
    }
    public async Task UpdateStockQuantityAsync(int id, int updateQuantity)
    {
        await using var context = await _factory.CreateDbContextAsync();
        var product = await context.Products.FindAsync(id);
        if (product is null) return;
        product.Quantity += updateQuantity;
        await context.SaveChangesAsync();
    }
}

Note that ProductService has two methods, GetByIdAsync and UpdateStockQuantityAsync. An instance of the DbContext class is created locally in each of these methods. Now, suppose you have two threads, T1 and T2, that execute these methods concurrently. That is, thread T1 executes the GetByIdAsync method while thread T2 executes the UpdateStockQuantityAsync method. Because each of these methods is executed in isolation, they will have their own context, connection, and change-tracking information, and there will be no mutable state, so you don’t need to implement thread synchronization in either of these methods.

Consider the following code that executes a read operation and an update operation in two separate tasks.

public static async Task RunMethodsInParallelAsync(ProductService productService)
{
      Task readTask = productService.GetByIdAsync(1);
      Task updateTask = productService.UpdateStockQuantityAsync(3, 5);
      await Task.WhenAll(readTask, updateTask);
      Product? product = await readTask;
 }

The Task.WhenAll method runs the two tasks in parallel and waits until both have finished. The reason this approach is thread-safe, and will not create concurrency errors, is that each of these two methods creates its own DbContext instance internally. Therefore the read operation and the update operation use independent DbContext instances.

Use DbContext pooling to reduce allocation cost

Although creating DbContext instances is not that costly, you should consider using pooled contexts in applications that require high scalability and high performance. The following code snippet shows how you can register a pooled context.

builder.Services.AddPooledDbContextFactory(options =>
    options.UseSqlServer(connectionString));

A call to AddDbContext() will register a DbContext instance as scoped per HTTP request. Each request will run on a different thread and each will have its own context. However, keep in mind that the default scoped registration of the DbContext will not always suffice.

You will need a factory to create instances of DbContext when you’re using a background service, or performing some work inside a particular request, or running some business logic operation over multiple contexts.

Key takeaways

If you use EF Core in the data access layer of your application, you must implement thread safety measures whenever you run your queries in parallel.
You cannot execute multiple queries in parallel in EF Core using the same DbContext instance.
The IDbContextFactory enables you to create a DbContext instance for each thread, thereby enabling you to work with these instances in isolation.
Although using a DbContext pool involves a small allocation overhead, it becomes a non-issue if you need high throughput.

Governing Al agents at scale: Lessons from the leaders who’ve done it

Fri, 24 Jul 2026 08:10:06 +0200

Enterprise AI leaders from ZoomInfo, Docusign and AppViewX share what it took to build AI Centers of Excellence and govern agent identities inside two companies operating at scale. What you’ll take away: What an AI Center of Excellence looks like day to day at ZoomInfo and Docusign How to govern agent identities without standing up a parallel identity stack The traps both leaders worked hard to avoid, and what they’d do differently now What Venkat … More →

The post Governing Al agents at scale: Lessons from the leaders who’ve done it appeared first on Help Net Security.

Visual Studio Code 1.130 shines on Agents window

Fri, 24 Jul 2026 03:37:26 +0200

Microsoft has released Visual Studio Code 1.130, an update to the code editor that brings several improvements to the Agents window, along with enhancements to the agent host and the terminal.

VS Code 1.130 was released on July 22, one week after VS Code 1.129. Developers can access the release for Windows, Linux, or Mac from code.visualstudio.com.

Timestamps for chat requests and responses now are displayed when users hover over the message toolbar. You can disable this through the chat.verbose setting.

v17.1.0

Fri, 24 Jul 2026 03:09:44 +0200

test(coding-agent): aligned transcript compaction test with supersede…

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Seven years ago, Microsoft bet more than $13 billion that OpenAI would build the future of AI. Wednesday's announcement suggests the company has since learned a cheaper lesson: the future of AI may belong to whoever builds the frontier, but the profits belong to whoever makes it ordinary.

Best practices for applying Amazon Bedrock Guardrails to code generation workflows

Fri, 24 Jul 2026 01:23:12 +0200

In this post, we explain how Amazon Bedrock Guardrails can be configured for code generation workflows with coding assistants to overcome these constraints. With these best practices, you can build an efficient blueprint helping you with effective capacity planning with robust safety coverage.

Agentic coding goes hands free as OpenAI brings GPT-Live's full duplex voice control to Codex and ChatGPT on the desktop

Fri, 24 Jul 2026 00:20:42 +0200

Two weeks after debuting its more naturalistic GPT-Live audio AI model with full-duplex capabilities (listening and speaking at the same time), OpenAI is bringing it directly into developer workflows.

The company announced that GPT-Live now powers the ChatGPT desktop application on macOS and Windows, integrating directly with agentic systems like Codex and ChatGPT Work (which are separate experiences available in the ChatGPT desktop app).

When OpenAI initially launched GPT-Live on July 8, 2026, it introduced a continuous audio model capable of listening and speaking simultaneously—eliminating rigid turn-taking while delegating complex reasoning to background models like GPT-5.5.

Today's release expands that conversational layer to technical tasks, enabling software engineers to orchestrate multi-threaded coding jobs, review pull requests, and debug applications using natural voice commands.

As such, it could usher in a new era of "hands free" software development and even live, in-person group coding parties for Codex's more than 5 million weekly active users. Codex, of course, is the name given to OpenAI's models and harness focused on coding, but which the company has this year expanded into a more general productivity platform. An OpenAI spokesperson told VentureBeat this is the first time voice activation has been included natively with Codex on the desktop.

OpenAI posted a promotional video showing some of its employees, Codex developer experience engineer Jason Liu and Codex technical staffer Guinness Chen, speaking to the same ChatGPT desktop app session in the same room, each issuing different instructions and conversing with the same model.

New capabilities unlocked

At its core, this integration relies on decoupling the real-time voice layer from the underlying execution engines.

While GPT-Live maintains fluid conversation—inserting natural verbal acknowledgments like "got it" without interrupting the user—it passes heavy computational workloads to background reasoning models.

On macOS, the desktop application incorporates "Appshots" and screen context features, allowing ChatGPT Voice to analyze the frontmost window alongside local files, codebase structures, and active plugins.

This architecture creates a pair-programming dynamic where developers talk through problems conversationally while agents execute tasks asynchronously.

Rather than manually stopping coding sessions to type detailed instructions or switch windows, developers direct the system hands-free.

The full-duplex engine dynamically decides when to speak, pause, or invoke tools, maintaining conversational state even as background agents process complex code modifications.

Directing coding and complex builds with your voice alone

The central operational capability in this update centers on multi-task execution across Codex and ChatGPT Work environments.

Software engineers can initiate multiple concurrent task threads from a single spoken prompt. For instance, a developer preparing to ship a feature can instruct the system to investigate an open authentication bug, review a pending API migration pull request, and generate missing unit tests simultaneously.

The desktop application coordinates these actions across disparate contexts, tracing issues through Slack conversations, GitHub repositories, and local codebases.

Developers can also verbally convert design mockups into working code, splitting tasks across frontend, backend, and testing layers.

With support for multi-folder projects (build 26.715) and remote execution via iOS, engineers can check task progress, answer agent prompts, and redirect active jobs without switching applications or managing individual processes line by line.

Proprietary license

OpenAI’s voice-enabled desktop release operates under a proprietary, commercial enterprise model. Access is restricted to paid subscribers across Plus, Pro, Business, Enterprise, and Education plans.

For individual developers and corporate engineering departments, this commercial structure means the model weights, voice processing pipelines, and agent state architectures remain fully closed.

Organizations cannot modify or self-host the underlying systems. Furthermore, tasks initiated via ChatGPT Voice consume standard usage allocations directly from existing Codex and ChatGPT Work plan quotas, treating voice-triggered actions identically to standard agentic workloads.

Community reactions

Developer communities immediately noted the implications of bringing continuous full-duplex voice to autonomous coding workflows.

Reacting to the build 26.715 release announcement—which details voice integration and multi-folder project support—AI Insider journalist @ChrisGPT noted on X: "Today OpenAI will release voice and remote guidance for codex ! One step closer to personal AGI".

Early technical feedback highlights widespread enthusiasm for orchestrating complex agentic tasks hands-free, particularly when stepping away from the workstation or managing build pipelines remotely.

AMD Epyc CPU Roadmap: Auf Venice folgen Florence (Zen 7) und Ravenna (Zen 8)

Thu, 23 Jul 2026 21:52:23 +0200

Heute fällt der Startschuss für AMD Epyc Venice als neue Server-Prozessoren mit Zen-6-Architektur. Parallel gibt es einen Ausblick auf die Nachfolger. Laut Epyc-Roadmap folgt 2028 Florence mit Zen 7 und AI Compute Extensions. Zwei Jahre später soll bereits Ravenna mit Zen 8 im Jahr 2030 erscheinen.

NetworkManager update advances IPv6-only support, Wi‑Fi management, and security for Linux-based operating systems

Thu, 23 Jul 2026 21:34:46 +0200

Networking is core to any operating system, and when it comes to Linux, it’s actually a combination of several key components. The Linux kernel handles the data plane, moving packets, and holding live device state. NetworkManager is the network configuration service, operating as the control plane, deciding what a device’s configuration should be.

NetworkManager 1.58 was released this week, following more than five months of development and 407 commits since version 1.56. The release covers three areas: expanded support for IPv6-only networks, a set of Wi-Fi management updates, and a round of security hardening.

IPv4 address exhaustion remains the pressure behind the first of those areas, pushing more networks toward IPv6-only operation every year.

“More networks, mobile carriers, cloud providers, and anyone squeezed by IPv4 exhaustion are running IPv6-only by default,” Chris Van Hoof, director of Linux engineering, platform enablement at Red Hat, told Network World.

Advancing IPv6-only support

Dual stack networking, running IPv4 and IPv6 in parallel, has been the default IPv6 transition strategy for years. Dual stack networking, however, has a structural problem in that it still requires an IPv4 address on every device, so it does nothing to relieve address exhaustion pressure.

An alternative model called IPv6-mostly addresses that gap. It is defined in RFC 8925, “IPv6-Only-Preferred Option for DHCPv4,” and lets capable clients drop IPv4 entirely while legacy hosts that still need it keep receiving it on the same network segment.

“NetworkManager can also now auto-signal RFC 8925’s IPv6-only-preferred option, telling the network a host is fine skipping an IPv4 lease entirely,” Van Hoof said.

For the traffic that still needs IPv4, NetworkManager 1.58 adds support for CLAT, short for customer-side translator. CLAT is the client-side half of 464XLAT, a mechanism defined in RFC 6877, “464XLAT: Combination of Stateful and Stateless Translation.”

464XLAT pairs CLAT on the endpoint, which performs stateless header translation, with a stateful NAT64 translator on the provider side, letting IPv4-only apps keep functioning on a network that has no IPv4 of its own.

“CLAT is the translation layer that lets legacy IPv4-only apps and services keep working on those networks without bolt-on middleware,” Van Hoof said.

Wi-Fi management updates

NetworkManager 1.58 also brings a set of changes to how the daemon handles Wi-Fi connections and configuration.

Band selection: The band property of Wi-Fi connections now accepts a 6GHz value, and a Wi-Fi scan run through nmcli, NetworkManager’s command line tool, now shows each access point’s band as well.
Credential handling: WPS credentials with a 64 character hex PSK are now accepted, matching what some access points return.
Text interface improvements: nmtui, NetworkManager’s menu driven text interface, picked up several usability additions. A new device select button lets you choose a physical interface from a list instead of typing its name. The activation screen gained a rescan Wi-Fi button, and secret prompts now include a show password checkbox. There is also a share QR code option, mirroring the existing nmcli device wifi show-password command.

Security hardening

The release fixes vulnerabilities and tightens several defaults tied to DHCP handling and connection permissions.

CVE-2026-10805: Hostnames and MUD URLs are now validated before being written to the dhclient configuration file, rejecting characters that could alter the config syntax.
DHCPv4 client fix: An out-of-bounds read in the internal DHCPv4 client, triggerable by an on-link attacker with a malformed UDP packet, has been fixed.
Router option validation: The internal DHCPv4 client now ignores DHCP option 3, the Router option, when a lease also contains option 121, the Classless Static Route option, following the recommendation in RFC 3442.
Permission checks and deprecations: For private connections that restrict access to specific users, NetworkManager now verifies that the user can access the referenced 802.1X certificates and keys.

Tunneling and automation updates

Two smaller but practical additions round out this release: a new tunnel type for virtualized networks, and a fix that closes a gap in how NetworkManager’s state survives a reboot.

NetworkManager 1.58 also adds support for creating and managing GENEVE tunnel interfaces. GENEVE, short for Generic Network Virtualization Encapsulation, is a tunneling protocol that wraps Ethernet frames inside UDP packets, letting virtualized or overlay networks run on top of physical Layer 3 infrastructure. It shows up mainly in virtualization and cloud environments, where a hypervisor or container networking layer needs to build a virtual network segment across physical hosts. Previously, NetworkManager could not create or manage these interfaces directly.

The release also adds persisted managed state. NetworkManager tracks whether it is responsible for a given network device, a setting called its managed state. Until now, that setting reset on every reboot, so provisioning tools had to reapply it each time a system restarted. NetworkManager 1.58 lets the managed state survive a reboot when it is set through nmcli or the D-Bus API.

“It’s a small change but closes a real automation gap: Provisioning tools and cloud-init style workflows can set a device’s state once via D-Bus or nmcli and trust it survives a reboot, instead of reapplying config every time,” Van Hoof said.

AMD raises the AI stakes with Helios, Venice and robotics

Thu, 23 Jul 2026 20:48:09 +0200

AMD’s MI455X targets the AI memory wall

AMD

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

AMD’s Helios rack takes aim at Vera Rubin

Dave Altavilla

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

AMD

Pensando networking and ROCm software advance

Customer commitments underscore rack-scale confidence

AMD expands its robotics and embedded foundation

Execution for AMD is now the test

This article is published as part of the Foundry Expert Contributor Network.
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The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix

Thu, 23 Jul 2026 19:19:42 +0200

Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define the category — yet a majority of enterprises have already watched their agents produce confident, wrong answers traced to missing or inconsistent context. A governed semantic layer is emerging as the fix, but most are still building it; the field is converging on hybrid retrieval; and even as provider-native tools lead in practice, a plurality say they intend to keep best-of-breed. The result is a context gap — agents that sound authoritative running on a foundation their owners do not yet fully trust.

This wave of VentureBeat Pulse Research examines the enterprise RAG and context layer: what feeds AI agents their business context, which retrieval systems enterprises run, how they buy and measure them, where the architecture is heading, and — most revealingly — how often that context is already failing them.

The central finding is a context gap — the distance between how confidently enterprise agents answer and how reliable the context beneath them actually is. A majority of enterprises (57%) report that in the past six months their AI agents produced confident but wrong answers they traced to missing or inconsistent business context, and more than half of those said it happened more than once. This is not a fringe failure: retrieval is the primary context source for 38% of enterprises, more than any other approach, so when retrieval is thin or inconsistent, the errors it produces are wearing the agent’s authority. The infrastructure to fix it is being built — 58% already run or are building a governed semantic layer — but for most it is not yet in production.

Underneath, the market is consolidating in a direction that surprises. Provider-native retrieval — OpenAI’s file search (40%) and Google’s Vertex AI Search (38%) — already leads every dedicated vector database, and enterprises expect hybrid retrieval to dominate by the end of 2026 (34%). Yet a plurality (36%) say they intend to keep best-of-breed standalone tools rather than consolidate onto a provider’s native context stack, and a majority (57%) plan to switch or add a provider within the year. Stated preference and actual usage are pulling in opposite directions — the market is buying provider-native while insisting it wants independence.

Methodology

VentureBeat fielded this survey as part of its ongoing Pulse Research series. This survey focused on enterprise RAG infrastructure and the context layer — the retrieval systems, semantic layers, and context sources that feed AI agents. Responses are filtered to organizations with more than 100 employees (n=101); the survey drew no responses from organizations of 100 or fewer, so the full sample qualifies. All responses are from a single Q2 2026 (June) wave, so the report reads cross-sectionally and does not infer month-over-month trends. Several questions were multiple-select, so those shares can sum to more than 100%.

By organization size the sample concentrates in the mid-market: 251–1,000 employees (31%) and 101–250 (31%) lead, with 1,001–5,000 (20%), 5,001–10,000 (12%), and 10,001+ (7%) above them. By role it spans managers (39%), individual contributors (27%), the C-suite (16%), and VPs and directors (14%); on purchasing authority it is buyer-credible, with 46% final decision-makers and another 26% recommenders or influencers. Technology/Software is the largest industry at 20%, followed by Healthcare/Life Sciences (11%) and a broad spread across retail, transportation, financial services, manufacturing, and education.

At 101 respondents this is a modest sample and should be read as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It is best read as the view from organizations actively standing up RAG and context infrastructure rather than from the largest operators.

Finding 1: Confident and wrong

More than half have traced agent errors to bad context

We asked whether, in the past six months, enterprises had traced a confident but wrong agent answer to missing or inconsistent business context. Most had.

This is the report’s defining number. A majority of enterprises (57%) have already had an AI agent produce a confident, wrong answer they traced to bad context — wrong metrics, stale definitions, or missing documents — and more than half of those have seen it happen more than once. Only 28% report no such failure, and a small remainder either don’t run agents on enterprise data or don’t trace root cause closely enough to know.

The failure mode is specific and dangerous: the model is not obviously hallucinating; it is confidently wrong because the context feeding it was thin or inconsistent. Everything else in this report — what enterprises retrieve, how they govern it, and what they plan to build — is downstream of this problem.

Finding 2: RAG is the default context source

Retrieval feeds more agents than any other method

We asked what an enterprise’s AI agents primarily use to understand its data. Retrieval leads by a wide margin.

Retrieval is the backbone of enterprise context. For 38% of organizations, RAG over documents or a vector index is the primary way agents understand the business — nearly twice the share of the next approach, a governed semantic layer or ontology (21%). Mixed approaches (14%), direct live-system queries (10%), and long-context loading (6%) fill out the rest, and only 2% let agents run on the model’s general knowledge alone. The concentration matters in light of Finding 1: because so much enterprise context flows through retrieval, the quality of that retrieval is the quality of the answer. When RAG is the default source, thin retrieval is not an edge case — it is the main failure surface.

One approach is notable for its absence from these answers: customizing model weights, also known as fine-tuning. Every leading source of business context is injected at run time. Our most recent direct measurement of fine-tuning comes from our April–May survey wave (a separate survey, n=136), where fine-tuning capabilities ranked last of six factors in model selection at 5% — even as 26% of that sample still named fine-tuning and customization an investment they expect to grow. Fine-tuning has fallen out of the primary selection conversation; context injection is how enterprises make agents knowledgeable about their business.

Finding 3: Provider-native retrieval already leads the vector databases

OpenAI file search and vertex AI search top the dedicated tools

We asked which retrieval systems enterprises run in production today. The answer favors the model providers and hyperscalers over the specialists.

The dedicated vector database is no longer the center of the RAG stack. OpenAI’s file search (40%) and Google’s Vertex AI Search (38%) lead — provider-native and hyperscaler-native retrieval — ahead of every purpose-built vector database. Among the specialists, the most-used is the one enterprises already run for other reasons (Elasticsearch/OpenSearch, 20%) and the open, embedded option (pgvector, 12%); the pure-play vector databases that define the category — Weaviate, Qdrant, Pinecone, Milvus — each sit in single digits to low double digits. Notably, 13% of enterprises say they still run no production RAG at all. As with the platforms in the parallel infrastructure wave, enterprises are gravitating to retrieval that comes bundled with tools they already buy.

The shape of this finding held across both Q2 waves. In April–May (n=161), provider-built retrieval led usage there too, while every dedicated vector database remained marginal — the most-used standalone vector database peaked at 8% of that sample — and the hybrid, pluralistic future was already the consensus expectation (34% expected hybrid retrieval to dominate, with another 29% expecting multiple architectures by use case). Two waves, consistent picture: the category that coined the “vector database” term is being collected by the platforms enterprises already buy from.

Finding 4: But they say they want to keep best-of-breed

A plurality resist consolidating onto a provider’s native stack

We asked how enterprises will respond as model providers bundle retrieval, memory, and orchestration into their platforms. Their stated intent cuts against their current usage.

Here is the tension at the heart of the stack. Even as provider-native retrieval leads in practice (Finding 3), a plurality of enterprises (36%) say they intend to keep best-of-breed standalone tools rather than consolidate onto a provider’s native context stack — well ahead of the 21% who plan to consolidate. Another 21% expect a mix, and 9% intend to build and own the layer themselves. The gap between what enterprises run and what they say they want is the strategic question of the category: they are adopting bundled retrieval for convenience while asserting they will preserve independence. Which impulse wins — the pull of the provider bundle or the stated preference for modular control — will shape the retrieval market more than any single tool.

Finding 5: Hybrid retrieval is the consensus bet

Vector-only retrieval is already seen as insufficient

We asked which retrieval architecture enterprises expect to dominate their production RAG systems by the end of 2026. The field is converging — with a large share still unsure.

The architecture is settling on hybrid. A third (34%) expect hybrid retrieval — embeddings combined with reranking and access controls — to dominate their production systems by the end of 2026, three times the 11% who expect vector-only retrieval to prevail. That is a notable signal: the pure vector-search approach that launched the category is already viewed as insufficient on its own, superseded by pipelines that add reranking for accuracy and access controls for governance — the very access controls whose absence produces the failures in Finding 1. Tellingly, the second-largest answer is uncertainty: 17% simply don’t know, and another 14% expect to move beyond a dedicated vector layer entirely toward tool-first or long-context retrieval. The consensus is not a single tool but a layered pipeline — and it is not yet fully formed.

Finding 6: The governed context layer is being built now

Most run or are building a semantic layer — few in production

We asked whether enterprises use a governed semantic or context layer to give agents and BI a shared understanding of their data. Most are on the path; fewer have arrived.

The fix for the context gap is under construction. Well over half of enterprises (58%) either run a governed semantic layer in production (25%) or are piloting and building one (34%), and a further 17% are actively evaluating — meaning three-quarters are engaged with the idea in some form. But the balance is telling: more are building than have shipped, so for most enterprises the shared, governed definition layer that would prevent the "confident but wrong" failures of Finding 1 is still a work in progress. The semantic layer is the industry’s answer to inconsistent context; this wave catches it mid-construction, ambition well ahead of production.

Finding 7: Bought on ingestion and simplicity, watched for correctness

Selection favors operability; monitoring favors correctness and security

We asked what matters most when enterprises choose a retrieval system, and what they track once it is running. Both answers lean practical.

Enterprises choose retrieval systems on operability. Ease of data ingestion (36%), latency and performance (32%), and operational simplicity (29%) lead the selection criteria — ahead of retrieval accuracy and access control (23% each), the two factors most directly tied to the failures in Finding 1. Once systems are running, the emphasis shifts toward trust: the most-tracked metrics are response correctness (42%) and security and access control (38%), ahead of latency (28%), operational stability (27%), and answer relevance (23%).

Satisfaction with current systems is moderately positive but not enthusiastic — on a five-point scale, overall satisfaction averages 4.0, with ease of implementation and value for money both near 3.9. Enterprises buy for how easily a system runs and watch it for whether it can be trusted.

Finding 8: A retrieval reshuffle is coming

A majority plan to change providers — and the vector specialists are gaining interest

We asked whether enterprises plan to change or add a retrieval provider, and which they are considering. The consideration set differs from today’s stack.

The retrieval stack is not settled. While 43% have no plans to change, a small majority (57%) intend to switch or add a provider within twelve months, and a quarter (26%) within the next quarter. The consideration set is where it gets interesting: provider-native retrieval still leads what enterprises are evaluating (OpenAI 22%, Vertex AI Search 21%), but the open-source vector specialists punch above their current footprint — Qdrant (14%) and Milvus (13%) draw more switching interest than their present usage (10% and 6%) would suggest. Read with Finding 4, the picture is a market in flux: enterprises run provider-native today, are evaluating a broader field, and say they want to keep their options open. The reshuffle ahead will test whether best-of-breed intent survives contact with the convenience of the bundle.

The bottom line: A context gap that more retrieval alone won’t close

Organizations with more than 100 employees are wiring agents into their business faster than they can guarantee the context those agents run on. Retrieval is the default source of enterprise context, and it increasingly comes from the model providers and hyperscalers rather than the dedicated vector databases — yet a majority of enterprises have already watched agents answer confidently and wrongly because that context was thin or inconsistent. The failure is not exotic; it is the predictable result of pointing authoritative-sounding agents at an unreliable foundation.

The industry’s answer — a governed semantic layer, hybrid retrieval with reranking and access controls — is being built but is mostly not yet in production, and enterprises are pulled between the convenience of provider-native bundles and a stated preference for best-of-breed independence. At 101 respondents in a single Q2 wave this is a directional read, skewed toward the mid-market — but the direction is clear: the context layer is the next contested tier of the AI stack, and right now agents are running ahead of it. The context gap is not a retrieval-volume problem that more documents or bigger indexes will solve on their own; it is a problem of governed, consistent, access-aware context. The open question for later waves is whether enterprises finish building that layer before the confident-but-wrong failures move from the lab into decisions that matter.

Based on survey responses from 101 qualified enterprise respondents (100+ employees), drawn from a single Q2 2026 (June) wave. At this sample size the results should be read as a directional signal rather than a precise measurement — it's a self-selected sample, not a probability sample, and skews toward the mid-market. Respondents include managers, individual contributors, VPs/directors, and the C-suite, with strong purchasing authority, across technology, healthcare, retail, transportation, financial services, manufacturing, and education.

Google CEO distracts from Gemini 3.5 Pro delay with talk of Gemini 4 and monthly releases

Thu, 23 Jul 2026 18:38:04 +0200

Pichai had responded to Anmuth’s question that Google remained confident of competing at the frontier and was investing heavily in a larger Gemini 4 base model.

Analysts, though, aren’t as confident as Pichai.

A monthly model release cadence could prove to be a double-edged sword for enterprises and their CIOs.

The challenge for CIOs, Jain said, is not just keeping up with model releases; it’s deciding whether each new version is worth the cost of validating it.

Google CEO distracts from Gemini 3.5 Pro delay with talk of Gemini 4 and monthly releases

Thu, 23 Jul 2026 18:35:20 +0200

Pichai had responded to Anmuth’s question that Google remained confident of competing at the frontier and was investing heavily in a larger Gemini 4 base model.

Analysts, though, aren’t as confident as Pichai.

A monthly model release cadence could prove to be a double-edged sword for enterprises and their CIOs.

The challenge for CIOs, Jain said, is not just keeping up with model releases; it’s deciding whether each new version is worth the cost of validating it.

This article first appeared on InfoWorld.

Google CEO distracts from Gemini 3.5 Pro delay with talk of Gemini 4 and monthly releases

Thu, 23 Jul 2026 18:35:14 +0200

Pichai had responded to Anmuth’s question that Google remained confident of competing at the frontier and was investing heavily in a larger Gemini 4 base model.

Analysts, though, aren’t as confident as Pichai.

A monthly model release cadence could prove to be a double-edged sword for enterprises and their CIOs.

The challenge for CIOs, Jain said, is not just keeping up with model releases; it’s deciding whether each new version is worth the cost of validating it.

This article first appeared on InfoWorld.

Startup Founders Urge Trump Not to Shut Off Chinese Open Weight AI

Thu, 23 Jul 2026 18:18:19 +0200

Nearly 200 Silicon Valley companies, including Proton and Y Combinator, are urging the Trump administration not to block U.S. access to Chinese open-weight AI models or risk crippling the next generation of U.S. startups. Politico reports: On Wednesday, the newly-formed Little Tech Association sent letters to President Donald Trump, Commerce Secretary Howard Lutnick and others in the administration with its appeal, marking the first coordinated effort by Silicon Valley's wider influential startup community to weigh in on one of the Trump administration's most closely watched AI debates. At issue: whether Washington should restrict access to increasingly powerful open-weight -- meaning, AI models whose weights are publicly available -- AI models released by Chinese companies such as Moonshot AI and Alibaba. "American leadership requires two things: world-leading American open-weight models and continued access for U.S. builders to open models already available worldwide," the startup founders wrote in the letter (PDF) obtained by POLITICO, also sent to Office of Science and Technology Policy Director Michael Kratsios. Instead of broad prohibitions, they argue the government should adopt targeted safeguards. And they warn that banning Americans from downloading Chinese open-weight models wouldn't stop their proliferation -- but would weaken U.S. startups. "There'll be hundreds of companies that instantly die," said Suhail Doshi, founder of AI infrastructure startup Particle and a member of the association, which POLITICO first wrote about exclusively, in an interview. "It's great for Anthropic. We're all going to have to spend money on Anthropic." Last week, the Beijing-based AI company "Moonshot" released a massive new model that reset the AI race overnight, immediately vaulting into the top tier of global AI, beating Anthropic's Fable 5 and OpenAI's GPT-5.6 Sol in front-end coding tests. China's Xi Jinping also used his first appearance at China's World AI Conference to promote a vision of low-cost, broadly accessible AI and call for international cooperation rather than technological rivalry.

Read more of this story at Slashdot.

v0.32.3

Thu, 23 Jul 2026 17:47:58 +0200

agent: import skills from coding agents (#17294)

Zwei RTX 5090 für die HMX 6 und Zeitreise zur Höllenmaschine 4 mit vier GPUs

Thu, 23 Jul 2026 17:32:54 +0200

Hallo, ich bin der Michi, willkommen zur vierten Ausgabe des HMX-6-Newsletters. Diese Woche erfahrt ihr, welche Grafikkarten wir in der HMX 6 verbauen. Außerdem verraten wir, warum Halo das Design der HMX 6 prägen wird. Außerdem reisen wir zurück ins Jahr 2012 zur Höllenmaschine 4, die mit vier Grafikprozessoren neue Maßstäbe beim Gaming setzte. Wenn ihr keine Ausgabe verpassen wollt, könnt ihr den Newsletter kostenlos abonnieren – aber vergesst nicht, die Anmeldung via E-Mail zu bestätigen. Viel Spaß beim Lesen!

Hier geht es direkt zum Gewinnspiel der HMX 6 im Gesamtwert von 40.000 Euro.

HMX 6: 2x RTX 5090 von ZOTAC GAMING und Halo-Design

Jetzt können wir endlich verraten, welche Grafikkarten in der HMX 6 stecken: Als primäre Gaming-Grafikkarte der HMX 6 ist die RTX 5090 AMP Extreme INFINITY gedacht, während wir parallel dazu die RTX 5090 ARCTICSTORM AIO für verlustfreie Skalierung verwenden, um Bildqualität und -wiederholrate in praktisch jedem Videospiel zu verbessern. Natürlich könnt ihr die gebündelte Kraft der zwei 5090 auch im kreativen Einsatz nutzen, etwa beim 3D-Rendering oder KI-Berechnungen. Hier findet ihr alle Informationen zu den zwei ZOTAC-Grafikkarten.

ZOTAC

Eigentlich wollten Kris und ich euch diese Woche schon den aktuellen Stand des Casecon im Halo-Design zeigen. Doch unserem Modder Stefan Ulrich fehlen noch diverse Materialien. Jetzt fahren wir wahrscheinlich nächste Woche, doch die Zeit drängt schon wieder, denn wir wollen ja auf die Gamescom mit der HMX 6.

Rückblick: Die Höllenmaschine 4 setzte technische und optische Maßstäbe

Neue Maßstäbe setzten wir 2012 auch bei der Vermarktung der Höllenmaschine 4 – zumindest für unsere Verhältnisse: vier aufwendig produzierte Teaser-Videos mit Engelchen und Teufelsdamen sowie Fritz als Padawan von Obi-Wan Michi. Das hat riesigen Spaß gemacht und uns als Team Hölle zusammengeschweißt – und war der Beginn einer wunderbaren Freundschaft.

PC-WELT

Technisch auf der Höhe der Zeit waren wir mit den beiden Grafikkarten ASUS GTX690-4GD5, die jeweils zwei 915 MHz schnelle Nvidia Geforce GTX 690 beherbergten. Vier Grafikprozessoren gleichzeitig waren damals absoluter Wahnsinn und sorgten regelmäßig für offene Münder. Dazu gab es den Sechskerner Intel Core i7-3960X, 64 GB RAM im Vierkanalmodus, mit der OCZ RevoDrive die erste PCIe-SSD in einer Höllenmaschine und mit 10 Terabyte natürlich auch wieder verrückt viel HDD-Speicherplatz.

Sein höllisch gutes Aussehen verdankt das Gehäuse den international bekannten Casemoddern Martin und Stefan Blass. Sie haben ins Cooler Master Cosmos II ein Sichtfenster gefräst und per Airbrush lodernde Flammen auf die beiden Flügeltüren gezaubert. ARGB war damals noch kein Thema, aber mit dem Multidimmer von Richter waren immerhin individuelle Farbtöne und -wechsel per IR-Fernbedienung möglich. Hier geht es zum liebevoll restaurierten Artikel zur Höllenmaschine 4 aus 2012.

Maus mit Noctua-Lüfter und Steam Machine im Praxis-Test

Diese Woche ist eine skurrile Mail in meinem Postfach gelandet: Pulsar und Noctua präsentieren stolz die Früchte ihrer Zusammenarbeit: die Feinmann F01 Noctua Edition, eine Gaming-Maus mit aktiver Belüftung der Handflächen. Ich bin gespannt, wer sich über kühlere Handflächen beim Zocken freut.

Noctua/Pulsar

Mein Kollege und Namensvetter Michael Crider hat sich die kostspielige (ab 1.039 Euro) Steam Machine gekauft und einem ausführlichen Praxistest unterzogen. Sein Fazit fällt allerdings ernüchternd aus: Ein günstiger Mini-PC mit selbst installiertem SteamOS bietet derzeit nahezu denselben Nutzen für deutlich weniger Geld.

Warum es ein Problem ist, dass in neuen Laptops alte CPUs zum Einsatz kommen, erklärt mein Kollege Mark Hachman.

Vielen Dank fürs Lesen!

ommende Woche besuchen Kris und ich endlich unseren Modder Stefan, der uns dann hoffentlich schon das fast fertige Tisch-PC-Gehäuse für die Build-Week präsentiert – immer optimistisch bleiben, denn langsam drängt die Zeit. Außerdem reisen wir zurück ins Jahr 2013 zur legendären Höllenmaschine 5 mit den vielen Totenköpfen. Wenn ihr nichts verpassen wollt, abonniert den kostenlosen HMX-6-Newsletter – und denkt daran, eure Anmeldung per E-Mail zu bestätigen. Ich freue mich schon auf nächste Woche – bis dann! Euer Michi.

Q&A: Google’s AI and computing chief talks about its shapeshifting data centers

Thu, 23 Jul 2026 14:55:21 +0200

Google’s AI offerings span its internal and cloud offerings. Its data centers are processing seven times more AI tokens compared to last year. To keep up, Google is upgrading its data-center hardware and software technologies at a faster clip. It plans to raise $80 billion to build new data centers. (See related story: Google transforms its data center architecture for agent era)

Network World spoke with Mark Lohmeyer, vice president and general manager of AI and computing at Google, about how the company’s infrastructure is keeping pace with AI demand.

Network World: What is the primary shift in infrastructure needs?

Mark Lohmeyer: We’ve seen the rise of agents and agentic use cases. Years ago, it was the chat phase: Ask a question, get an answer. Now we’re in the agentic era, where you express your intent, agents spin off multiple sub-agents, working in parallel, preserving state. This is a radical shift in what infrastructure needs to do; make them fast, cost effective, secure, reliable. We’re delivering infrastructure optimized for the age of agents.

NW: What’s the goal of the infrastructure buildout, and what should customers expect regarding costs?

ML: Ultimately, it’s about enabling customers with leading-edge capabilities and models at scale cost-effectively. With agents, inference transactions increase by 50x, 100x versus non-agentic workloads. We’re driving the cost per transaction down exponentially. In our latest platforms, we reduce the cost by almost 2x for the same work. Customers serve twice the number of users at the same cost, directly driving profitability.

NW: How are you addressing energy efficiency?

ML: Energy is a critical resource, and Google has optimized for years. We design data centers and compute [to drive] high PUE (power usage effectiveness). We introduced liquid cooling over five years ago, and these latest systems are all liquid cooled. For agentic workloads, CPUs come to the forefront… orchestrating agents, calling tools, doing evaluation loops in reinforcement learning. Our latest Axion-based CPU platform called N4A has energy efficiency and is significantly better than the prior generation and x86 comparables.

NW: How do you think about token efficiency as you build-out systems?

ML: Performance and efficiency gains are powered by co-design of the model and infrastructure. Gemini is trained on TPUs, primarily served on TPUs with high frontier model capability, in a token and cost-efficient way. This stems from co-design across the full stack.

NW: How do you project what infrastructure will be needed years in advance?

ML: Hardware cycles deliver a new next generation roughly every year, but design cycles are two years or more in advance. We work with DeepMind doing core research, to application teams taking models into production, to billions of users, to our team building infrastructure. We work upstream with DeepMind and application teams to understand what’s coming. Agents weren’t being broadly spoken of externally, but internally we had those insights around what they would need. That shows up in hardware design. We hit the timing right — these platforms are built for agents.

NW: What’s the eighth generation TPU platform?

ML: We deliver new platforms every year, and ones launched years ago are close to 100% utilized because demand for AI-optimized compute is high. The eighth-generation TPU platform is the first delivering two complete systems, from the chip all the way up to the network and storage and software, that are optimized.

TPU-8t is optimized for training, and TPU-8i is optimized for inference. For TPU-8i, we increased SRAM on the chip to 384MB — three times the prior generation — and increased the HBM by 50%.

NW: How are you approaching GPU and TPU compatibility?

ML: People in a single cluster do not commingle GPUs and TPUs. We offer both options based on specific workload needs. We’ve been investing on the TPU side in using software frameworks customers are comfortable with on GPUs and enabling those on TPUs. For example, PyTorch and vLLM. Customers could have a pool of GPUs and TPUs, running vLLM on top of that. Start with a workload on TPUs, but if the TPU pool is fully utilized, spill to GPUs or vice versa. This works because it’s all leveraging the same compatible software layer on top.

NW: How has the orchestration platform changed for agents?

ML: Kubernetes is becoming the orchestration platform of choice for AI. Google is transforming GKE [Google Kubernetes Engine] into an agent-native orchestration solution. When expressing intent to an agent and it spins up multiple sub-agents, compute needs to spin up rapidly — TPUs or GPUs — without long delays, then run and spin back down. We’re optimizing at every layer of the GKE stack: significantly improving node startup time and how rapidly we start and stop containers. Lovable demonstrates this with GKE, spinning up hundreds of sandboxes for live coding sessions on their platform in parallel, paying for infrastructure when needed.

NW: What is the role of the network and storage infrastructure?

ML: The network is critical for AI. This requires creating large-scale clusters of GPUs or TPUs and enabling them to talk to each other in a high-performance way. We created the Virgo network — a collapsed network architecture, non-blocking within a data center, where multiple pods or NVLink72 domains connect together.

In TPU8T, we can connect over a million TPUs together leveraging Virgo, creating large-scale, high-performance, reliable clusters that shrink innovation cycles. Storage is equally critical. In large-scale clusters, something is always failing. The ability to take snapshots and go back to a checkpoint is important.

We’ve introduced Managed Lustre 10T, with 10 terabytes per second of bandwidth, 18 petabytes of storage in single clusters. This is 10 times faster than last year and 20 times faster than competition. We have Rapid Bucket, low-latency storage backed by Google storage systems. Both are impactful in large-scale training environments.

NW: How does KV cache strategy differ between training and inference?

ML: For TPU-8i, we increased SRAM on the chip to 384 megabytes — three times the prior generation — and increased the HBM by 50%. Storing KV cache directly in chip memory allows responding to inference requests much more rapidly and cost-effectively than going to an external system. For inference workloads, storing as much KV cache as possible on-chip is critical.

We’re introducing a dedicated KV cache storage subsystem that works across GPUs and TPUs. As KV caches get larger, being able to fall back to this dedicated subsystem becomes critical. Loading model weights rapidly is important in dynamic inference environments where accelerators switch between models hour by hour.

Poolside's Laguna S 2.1 is a small open-weight coding model that punches well above its size

Thu, 23 Jul 2026 14:36:22 +0200

Poolside has released Laguna S 2.1, its third coding model in three months. Rather than rely on raw scale, the company trained it to keep checking its work, revise failed approaches, and avoid giving up too soon during long agentic sessions. The compact model beats several much larger rivals in benchmarks. Poolside says it also solved a math problem that had been open since 1975 for under 10 cents.

The article Poolside's Laguna S 2.1 is a small open-weight coding model that punches well above its size appeared first on The Decoder.

Tech layoffs: A 2026 timeline

Thu, 23 Jul 2026 14:35:03 +0200

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Feb. 21, 2025: CISA lays off 130

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

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

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

Tech layoffs in 2024

Equinix
AMD
Freshworks
Cisco
General Motors
Intel
OpenText
Microsoft
AWS
Dell

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

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

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

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

August 1, 2024: Intel removes 15,000 roles

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

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

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

See news of earlier layoffs.

Poolside: US-Start-up setzt mit Laguna S 2.1 auf Modellverhalten statt Skalierung

Thu, 23 Jul 2026 14:18:27 +0200

Transparenz bei Reward-Hacking; Verfügbarkeit und strategische Ausrichtung. Poolside veröffentlicht mit Laguna S 2.1 das dritte Coding-Modell ...

7 Best Claude Code Alternatives for CLI Agentic Coding

Thu, 23 Jul 2026 14:06:21 +0200

Discover seven cheaper, faster Claude Code alternatives for CLI agentic coding, with open-source tools, local models, MCP support, and better context control.

Ganz ohne Chemie: Weltgrößte Testanlage für Schwungrad-Speicher entsteht in Shanghai

Thu, 23 Jul 2026 13:50:34 +0200

Qnetic baut in Shanghai eine Testanlage für Schwungrad-Energiespeicher, die nach eigenen Angaben die größte ihrer Art werden soll. Parallel dazu montiert das Team den ersten Prototypen der Baureihe Pulsar, einen Schwungradspeicher mit 200 Kilowattstunden Kapazität. Beide Vorhaben markieren einen wichtigen Schritt auf dem Weg von der Entwicklung zur kommerziellen Vermarktung der Technologie. Kinetische Energie statt …

Determining the ROI of AI requires data that most companies lack

Thu, 23 Jul 2026 11:07:22 +0200

Leadership wants to scale AI. Budgets are tripling. Adoption is up.

Then the CFO asks the question every board now asks: which of these initiatives is actually profitable?

Most organizations cannot answer that question, not because they lack visibility into cost, but because the cost data they have was never designed to produce that answer.

Applying lessons learned from managing cloud spend won’t be a fix for the AI and ROI quandary. True, cloud taught a generation of CFOs that billing without business context is noise. So to get cloud ROI, they stitched two data sources together: cost data plus business data. AWS reveals which account, which region, which tag, which resource. Merge in customer and product mappings on top and the ROI of the cloud spend comes into focus.

But AI is harder. It requires three data sources: cost, business, and telemetry—the automatic collection of data from disparate sources that helps to clarify the whole picture of what happened and why. An executive or engineering lead can have AI invoices and customer revenue. But they have no way to connect them to business value. The token count on the OpenAI invoice does not specify which customer triggered which call, which feature it served, or whether the prompt produced a business outcome. That data does not exist in the provider’s billing.

AI providers won’t fix this problem

The situation is not likely to change anytime soon because AI providers are not in the business of attributing an enterprise’s costs to that enterprise’s customers. Instead, AI providers are in the business of selling tokens. The granularity they expose is the granularity their billing systems require, not the granularity a CFO requires.

Not convinced? Compare what AWS gives you to what an AI provider gives you.

AWS billing exposes resource IDs, account hierarchies, region, SKU, tag metadata, usage by the minute. Every dollar can be attributed to a workload, a team, a customer segment if it was tagged correctly. The data is rich enough that mature FinOps teams built unit economics on top of it years ago.

An AI provider invoice gives you tokens consumed by model, with optional grouping by API key. That is the resolution. No request-level attribution. No customer ID. No feature mapping. No prompt outcome. No retry identification. Multi-step agent workflows collapse into a token count. Imagine a large bank receives a multi-million dollar AI invoice each month. But it has no visibility into what parts of the business were responsible for what parts of the cost so cannot allocate them.

If an enterprise wants to know what AI cost drove which customer or feature, it has to capture that data itself, inside an application, before the call leaves it.

Three required sources

Building AI ROI measurement requires three data sources, stitched together in a single model.

Cost data, normalized across providers. Every AI provider delivers cost differently. OpenAI invoices in one taxonomy, Anthropic in another, fine-tuning vendors and inference platforms each in their own. Cloud GPU costs sit in AWS or Azure billing. Vector database costs land in Pinecone or Snowflake invoices. None interoperate by default. Normalization is necessary but not sufficient. It will put all your AI costs in one schema. It does not tell you what they produced.
Application-layer telemetry. This is the source most organizations are missing, and the one that makes AI ROI structurally different from cloud ROI. It requires instrumenting AI calls inside your application across six categories: request-level tracing tied to a customer or session ID; feature attribution tied to the product surface that triggered the call; agent-step capture for multi-step workflows; retry and fallback identification so recovery costs don’t get attributed to primary calls; model selection logging that records which model was chosen and why; and outcome capture that ties each call to whether it produced business value. None of this data exists in the provider’s billing. All of it has to be captured at the moment the call is made and stored in a system that can be stitched to the cost data.
Business data. Revenue, customer segments, product hierarchies, and feature usage. The same business data already feeding your CRM and analytics stack, mapped to the customers and features the telemetry layer attributes calls to.

Stitched together, the three sources produce the unit economics every AI investment decision now requires: cost per customer interaction, margin per feature, profitability per agent workflow, ROI per model choice. None of these can be calculated from billing data alone. None can be calculated from telemetry alone. They require all three sources, modeled together in a way that maps cost to outcome.

Why agentic AI makes this urgent

Single-call inference is the easy case. One request, one cost, one customer, one outcome.

Agentic workflows are different. An agent decomposes a task into multiple steps. Each step calls a model. Some steps fall back to a different model when the first fails. Some steps retry on a poor result. Some steps invoke external tools that themselves cost money. A single user request can produce dozens of inference calls across multiple providers, with the cost compounding in ways the provider invoice cannot disaggregate.

If telemetry does not capture agent-step granularity, no one will know which steps are profitable. Aggregate costs will show up three weeks later in the invoice. By then, the workflow has been running at scale, customers are onboarded, and unprofitable paths have been retried thousands of times.

When agents make the calls, the volume of cost-generating events without business context attached grows by an order of magnitude. The window for instrumenting this before it becomes unmanageable is closing.

What changes when the three sources come together

Once the three sources are stitched together, the AI investment conversation changes.

Five different ways to build the same AI capability stop looking equivalent. They converge on adoption metrics and diverge by 10x on cost. The team picks the approach that delivers a similar business outcome at one-fifth the cost, because the team can finally see the difference. Product teams design features with margin awareness from the architecture phase, not from the post-launch budget review. Engineering teams choose model architectures with cost-per-outcome data alongside latency and quality. Leadership evaluates AI initiatives the way they evaluate any other capital allocation: on unit economics, not on the engagement chart. Aggregated invoices track the cost per customer interaction. Engagement metrics reveal margin per feature. Gut-instinct model selection is checked against real cost-per-outcome model selection results.

Within seconds, everyone can see which AI features are profitable, which should scale, and which should be killed. This is the insight everyone is looking for and companies that achieve it will optimize the benefits of AI.

The build trap

AI costs are compounding now. The board is not waiting 18 months for an internal project to reach production.

The temptation to build it anyway has never been sharper. AI coding tools have changed what a small engineering team can ship in a quarter. The instrumentation layer looks tractable. The cost normalization looks like a weekend project. The semantic model feels like something a senior engineer could draft over a sprint.

It is a trap. Three reasons.

Volume is the first. A production AI footprint generates millions of telemetry events per hour, and that volume scales with agentic adoption. Real-time ingestion, correlation, and attribution at that scale is not the same problem as vibe coding a prototype in an afternoon. It is a permanent operational system that has to be right every minute of every day.

The vendor landscape is the second. Cost data arrives in delayed billing windows from providers with non-interoperable schemas. Schemas change without notice. New AI providers enter the landscape monthly, each with its own taxonomy and metering. The system is not built once. It is maintained against a moving target that moves faster than most internal release cycles.

The third is what the first two add up to: this is business-critical infrastructure. The CFO and the board are going to make capital allocation decisions on the data this system produces. When schema drift goes unnoticed for two weeks, when an agent telemetry stream stops correlating to a vendor that quietly changed its billing API, the cost of being wrong is not a sprint of cleanup. It is a quarter of misallocated capital.

The build-vs.-buy question for engineering leaders has changed. It’s not “can we build this?” The honest answer is yes. The real question is whether the marginal hour of your strongest engineers is best spent stitching cost data to telemetry to business outcomes, or building the AI products that produce the revenue the cost data is measuring.

The capability is reproducible in weeks. The choice is whether to spend the next 18 months building it, or the next 18 months acting on it.

—

New Tech Forum provides a venue for technology leaders—including vendors and other outside contributors—to explore and discuss emerging enterprise technology in unprecedented depth and breadth. The selection is subjective, based on our pick of the technologies we believe to be important and of greatest interest to InfoWorld readers. InfoWorld does not accept marketing collateral for publication and reserves the right to edit all contributed content. Send all inquiries to doug_dineley@foundryco.com.

WSL container: A quiet revolution for Windows development

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

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

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

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

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

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

Getting started with WSL container

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

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

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

Calling Linux containers from Windows applications

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

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

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

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

Manage Linux containers from Windows

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

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

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

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

Run Kubernetes inside Windows for cloud-native development

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

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

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

Drei GTA-Spiele in einem: So hat ein Modder die Spielwelten per Vibe-Coding verbunden

Thu, 23 Jul 2026 11:06:12 +0200

Ein Modder zeigt ein beeindruckendes Projekt für eine Reihe von GTA-Titeln. Er hat drei der Spiele durch Portale miteinander verbunden. Wie die Technik dahinter funktioniert und wie dabei KI zum Einsatz kam. weiterlesen auf t3n.de

USN-8595-1: Linux kernel (Oracle) vulnerabilities

Thu, 23 Jul 2026 10:20:43 +0200

USN-8596-1: Linux kernel (NVIDIA) vulnerabilities

Thu, 23 Jul 2026 10:20:28 +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-2026-23226, CVE-2026-23227, CVE-2026-23244, CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255, CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285, CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303, CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308, CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315, CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321, CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340, CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361, CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370, CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378, CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383, CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389, CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412, CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419, CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448, CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461, CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465, CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475, CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393, CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429, CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434, CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441, CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480, CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487, CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494, CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498, CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503, CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31634, CVE-2026-31638, CVE-2026-31639, CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648, CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31689, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046, CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057, CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43084, CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089, CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43119, CVE-2026-43120, CVE-2026-43129, CVE-2026-43162, CVE-2026-43245, CVE-2026-43252, CVE-2026-43265, CVE-2026-43281, CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355, CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361, CVE-2026-43362, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368, CVE-2026-43370, CVE-2026-43371, CVE-2026-43372, CVE-2026-43373, CVE-2026-43377, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397, CVE-2026-43405, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43415, CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43499, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45855, CVE-2026-45858, CVE-2026-45899, CVE-2026-45911, CVE-2026-45920, CVE-2026-45924, CVE-2026-45942, CVE-2026-45943, CVE-2026-45956, CVE-2026-45958, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987, CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996, CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015, CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026, CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037, CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114, CVE-2026-46116, CVE-2026-46117, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46136, CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193, CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241, CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282, CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296, CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314, CVE-2026-46319, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53354, CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865, CVE-2026-64164)

USN-8574-2: Linux kernel vulnerabilities

Thu, 23 Jul 2026 10:01:06 +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-2026-43362, 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-8593-1: Linux kernel vulnerabilities

Thu, 23 Jul 2026 09:46:45 +0200

It was discovered that some AMD Zen 2 processors did not properly isolate shared resources in the operation cache. A local attacker could possibly use this issue to corrupt instructions executed at a higher privilege level, resulting in privilege escalation. (CVE-2025-54518) Several security issues were discovered in the Linux kernel. An attacker could possibly use these to compromise the system. This update corrects flaws in the following subsystems: - x86 platform drivers; - PSP security protocol; - ARM32 architecture; - ARM64 architecture; - MIPS architecture; - PowerPC architecture; - RISC-V architecture; - S390 architecture; - User-Mode Linux (UML); - x86 architecture; - Block layer subsystem; - Cryptographic API; - Intel NPU Driver; - Compute Acceleration Framework; - ACPI drivers; - Auxiliary display drivers; - Drivers core; - DRBD Distributed Replicated Block Device drivers; - Rados block device (RBD) driver; - Ublk userspace block driver; - Compressed RAM block device driver; - Bluetooth drivers; - Bus devices; - Character device driver; - Clock framework and drivers; - CPU frequency scaling framework; - Hardware crypto device drivers; - Buffer Sharing and Synchronization framework; - DPLL subsystem; - EDAC drivers; - Arm Firmware Framework for ARMv8-A(FFA); - EFI core; - FWCTL subsystem; - GPIO subsystem; - GPU drivers; - HID subsystem; - Hardware monitoring drivers; - I2C subsystem; - I3C subsystem; - IIO ADC drivers; - IIO subsystem; - InfiniBand drivers; - Input Device core drivers; - IOMMU subsystem; - Mailbox framework; - Multiple devices driver; - Media drivers; - NVIDIA Tegra memory controller driver; - MTD block device drivers; - Network drivers; - Ethernet bonding driver; - Mellanox network drivers; - Microsoft Azure Network Adapter (MANA) driver; - STMicroelectronics network drivers; - Texas Instruments network drivers; - MediaTek network drivers; - NVME drivers; - Parport drivers; - PCI subsystem; - Pin controllers subsystem; - Chrome hardware platform drivers; - ACPI WMI driver; - Generic PM domains; - MediaTek PM domains; - Power supply drivers; - MPAM driver; - Amlogic Meson reset controller drivers; - S/390 drivers; - SCSI subsystem; - NVIDIA Tegra Control Backbone (CBB) driver; - SPI subsystem; - Greybus lights staging drivers; - Media staging drivers; - Realtek RTL8723BS SDIO drivers; - TCM subsystem; - Thunderbolt and USB4 drivers; - TTY drivers; - Userspace I/O drivers; - USB Device Class drivers; - ULPI bus; - DesignWare USB2 driver; - USB Gadget drivers; - USB Dual Role (OTG-ready) Controller drivers; - USB Serial drivers; - USB Type-C support driver; - USB Type-C Port Controller Manager driver; - TI TPS6598x USB Power Delivery controller driver; - USB Type-C Connector System Software Interface driver; - USB over IP driver; - vDPA drivers; - VFIO drivers; - Framebuffer layer; - TSM AMD SEV Guest driver; - Xen hypervisor drivers; - 9P distributed file system; - File systems infrastructure; - AFS file system; - BTRFS file system; - Ceph distributed file system; - EROFS file system; - F2FS file system; - FUSE (File system in Userspace); - GFS2 file system; - HFS+ file system; - HugeTLB file system; - Network file systems library; - Network file system (NFS) server daemon; - NILFS2 file system; - File system notification infrastructure; - NTFS3 file system; - OCFS2 file system; - Overlay file system; - Diskquota system; - SMB network file system; - Tracing file system; - UDF file system; - DRM TTM subsystem; - Control group (cgroup); - Kernel CPU control infrastructure; - Tracing infrastructure; - QorIQ DPAA2 FSL-MC bus driver; - Freescale ENETC Ethernet drivers; - Memory management; - Memory Management; - Linked list library; - Netfilter; - padata parallel execution mechanism; - PPP protocol drivers and compressors; - Bluetooth subsystem; - Networking core; - Network shaper API; - Network traffic control; - TCP network protocol; - XFRM subsystem; - io_uring subsystem; - IPC subsystem; - Audit subsystem; - BPF subsystem; - DMA mapping infrastructure; - Kernel exit() syscall; - Kernel fork() syscall; - Kernel futex primitives; - IRQ subsystem; - Kexec HandOver (KHO); - Padata parallel execution mechanism; - Scheduler infrastructure; - Cryptographic library; - KProbes tracing; - 802.1Q VLAN protocol; - B.A.T.M.A.N. meshing protocol; - Ethernet bridge; - Ceph Core library; - Distributed Switch Architecture; - Ethtool driver; - Handshake API; - HSR network protocol; - IPv4 networking; - IPv6 networking; - IUCV driver; - L2TP protocol; - MAC80211 subsystem; - Multipath TCP; - NFC subsystem; - Open vSwitch; - Phonet protocol; - RDS protocol; - RxRPC session sockets; - SCTP protocol; - SMC sockets; - TIPC protocol; - TLS protocol; - Unix domain sockets; - VMware vSockets driver; - Wireless networking; - Integrity Measurement Architecture(IMA) framework; - Key management; - Linux Security Modules (LSM) Framework; - SELinux security module; - ALSA framework; - HD-audio driver; - AudioScience HPI driver; - FourSemi audio codecs; - Texas InstrumentS Audio (ASoC/HDA) drivers; - QCOM ASoC drivers; - Renesas ASoC drivers; - SOF drivers; - STI ASoC drivers; - USB sound devices; - KVM subsystem; (CVE-2026-43490, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43498, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45837, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-46104, CVE-2026-46105, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46109, CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114, CVE-2026-46116, CVE-2026-46117, CVE-2026-46118, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46130, CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46134, CVE-2026-46136, CVE-2026-46138, CVE-2026-46139, CVE-2026-46140, CVE-2026-46141, CVE-2026-46142, CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46147, CVE-2026-46148, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46153, CVE-2026-46154, CVE-2026-46156, CVE-2026-46157, CVE-2026-46158, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46162, CVE-2026-46163, CVE-2026-46164, CVE-2026-46165, CVE-2026-46166, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46170, CVE-2026-46171, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46175, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180, CVE-2026-46181, CVE-2026-46182, CVE-2026-46183, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46188, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46192, CVE-2026-46193, CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46202, CVE-2026-46203, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46210, CVE-2026-46211, CVE-2026-46212, CVE-2026-46213, CVE-2026-46214, CVE-2026-46215, CVE-2026-46216, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46221, CVE-2026-46222, CVE-2026-46223, CVE-2026-46224, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46228, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46239, CVE-2026-46240, CVE-2026-46241, CVE-2026-46242, CVE-2026-46273, CVE-2026-46274, CVE-2026-46275, CVE-2026-46290, CVE-2026-46291, CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46295, CVE-2026-46296, CVE-2026-46297, CVE-2026-46298, CVE-2026-46299, CVE-2026-46301, CVE-2026-46302, CVE-2026-46303, CVE-2026-46304, CVE-2026-46305, CVE-2026-46306, CVE-2026-46307, CVE-2026-46308, CVE-2026-46309, CVE-2026-46310, CVE-2026-46311, CVE-2026-46312, CVE-2026-46313, CVE-2026-46314, CVE-2026-46315, CVE-2026-46317, CVE-2026-46318, CVE-2026-46319, CVE-2026-46320, CVE-2026-46321, CVE-2026-46322, CVE-2026-46324, CVE-2026-52911, CVE-2026-52912, CVE-2026-52913, CVE-2026-52914, CVE-2026-52915, CVE-2026-52916, CVE-2026-52918, CVE-2026-52919, CVE-2026-52920, CVE-2026-52921, CVE-2026-52922, CVE-2026-52923, CVE-2026-52925, CVE-2026-52926, CVE-2026-52927, CVE-2026-52928, CVE-2026-52931, CVE-2026-52932, CVE-2026-52934, CVE-2026-52936, CVE-2026-52937, CVE-2026-52941, CVE-2026-52943, CVE-2026-52944, CVE-2026-52949, CVE-2026-52950, CVE-2026-52951, CVE-2026-52952, CVE-2026-52953, CVE-2026-52954, CVE-2026-52955, CVE-2026-52956, CVE-2026-52957, CVE-2026-52958, CVE-2026-52959, CVE-2026-52960, CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52965, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52971, CVE-2026-52973, CVE-2026-52974, CVE-2026-52975, CVE-2026-52976, CVE-2026-52977, CVE-2026-52978, CVE-2026-52979, CVE-2026-52980, CVE-2026-52981, CVE-2026-52982, CVE-2026-52983, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52987, CVE-2026-52988, CVE-2026-52989, CVE-2026-52990, CVE-2026-52991, CVE-2026-52992, CVE-2026-52993, CVE-2026-52994, CVE-2026-52995, CVE-2026-52996, CVE-2026-52997, CVE-2026-52998, CVE-2026-52999, CVE-2026-53000, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53005, CVE-2026-53006, CVE-2026-53007, CVE-2026-53008, CVE-2026-53009, CVE-2026-53010, CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015, CVE-2026-53016, CVE-2026-53017, CVE-2026-53018, CVE-2026-53019, CVE-2026-53020, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53024, CVE-2026-53025, CVE-2026-53026, CVE-2026-53027, CVE-2026-53028, CVE-2026-53029, CVE-2026-53030, CVE-2026-53031, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53038, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53042, CVE-2026-53043, CVE-2026-53044, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53051, CVE-2026-53052, CVE-2026-53053, CVE-2026-53054, CVE-2026-53055, CVE-2026-53056, CVE-2026-53057, CVE-2026-53058, CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53067, CVE-2026-53068, CVE-2026-53069, CVE-2026-53070, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53078, CVE-2026-53079, CVE-2026-53080, CVE-2026-53081, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086, CVE-2026-53087, CVE-2026-53088, CVE-2026-53089, CVE-2026-53090, CVE-2026-53091, CVE-2026-53092, CVE-2026-53093, CVE-2026-53094, CVE-2026-53095, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53099, CVE-2026-53100, CVE-2026-53101, CVE-2026-53102, CVE-2026-53103, CVE-2026-53104, CVE-2026-53105, CVE-2026-53106, CVE-2026-53107, CVE-2026-53108, CVE-2026-53109, CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53113, CVE-2026-53114, CVE-2026-53115, CVE-2026-53116, CVE-2026-53117, CVE-2026-53118, CVE-2026-53119, CVE-2026-53120, CVE-2026-53121, CVE-2026-53122, CVE-2026-53123, CVE-2026-53124, CVE-2026-53125, CVE-2026-53126, CVE-2026-53127, CVE-2026-53128, CVE-2026-53129, CVE-2026-53130, CVE-2026-53174, CVE-2026-53277, CVE-2026-53278, CVE-2026-53279, CVE-2026-53280, CVE-2026-53281, CVE-2026-53282, CVE-2026-53283, CVE-2026-53284, CVE-2026-53285, CVE-2026-53286, CVE-2026-53287, CVE-2026-53288, CVE-2026-53289, CVE-2026-53290, CVE-2026-53291, CVE-2026-53292, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296, CVE-2026-53297, CVE-2026-53298, CVE-2026-53299, CVE-2026-53300, CVE-2026-53301, CVE-2026-53302, CVE-2026-53303, CVE-2026-53304, CVE-2026-53305, CVE-2026-53306, CVE-2026-53307, CVE-2026-53308, CVE-2026-53309, CVE-2026-53310, CVE-2026-53311, CVE-2026-53312, CVE-2026-53313, CVE-2026-53314, CVE-2026-53315, CVE-2026-53316, CVE-2026-53317, CVE-2026-53318, CVE-2026-53319, CVE-2026-53320, CVE-2026-53321, CVE-2026-53322, CVE-2026-53323, CVE-2026-53324, CVE-2026-53357, CVE-2026-53358, CVE-2026-53360, CVE-2026-53364, CVE-2026-53365, CVE-2026-53367, CVE-2026-53368, CVE-2026-53369, CVE-2026-53370, CVE-2026-53371, CVE-2026-53372, CVE-2026-53373, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53377, CVE-2026-53378, CVE-2026-53379, CVE-2026-53380, CVE-2026-63837, CVE-2026-63838, CVE-2026-63839, CVE-2026-63840, CVE-2026-63841, CVE-2026-63842, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63849, CVE-2026-63850, CVE-2026-63851, CVE-2026-63852, CVE-2026-63853, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856, CVE-2026-63857, CVE-2026-63858, CVE-2026-63859, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63863, CVE-2026-63864, CVE-2026-63865, CVE-2026-63866, CVE-2026-63875, CVE-2026-63876, CVE-2026-63877, CVE-2026-63878, CVE-2026-63879, CVE-2026-63880, CVE-2026-63881, CVE-2026-63882, CVE-2026-63883, CVE-2026-63884, CVE-2026-63886, CVE-2026-63887, CVE-2026-63888, CVE-2026-63889, CVE-2026-63890, CVE-2026-63891, CVE-2026-63892, CVE-2026-63893, CVE-2026-63894, CVE-2026-63895, CVE-2026-63896, CVE-2026-63897, CVE-2026-63898, CVE-2026-63899, CVE-2026-63900, CVE-2026-63901, CVE-2026-63902, CVE-2026-63903, CVE-2026-63904, CVE-2026-63905, CVE-2026-63906, CVE-2026-63907, CVE-2026-63908, CVE-2026-63909, CVE-2026-63910, CVE-2026-63911, CVE-2026-63912, CVE-2026-63913, CVE-2026-63914, CVE-2026-63915, CVE-2026-63916, CVE-2026-63917, CVE-2026-63918, CVE-2026-63919, CVE-2026-63920, CVE-2026-63921, CVE-2026-63922, CVE-2026-63923, CVE-2026-63924, CVE-2026-63925, CVE-2026-63926, CVE-2026-63927, CVE-2026-63928, CVE-2026-63929, CVE-2026-63930, CVE-2026-63931, CVE-2026-63932, CVE-2026-63933, CVE-2026-63934, CVE-2026-63935, CVE-2026-63936, CVE-2026-63937, CVE-2026-63938, CVE-2026-63939, CVE-2026-63940, CVE-2026-63941, CVE-2026-63942, CVE-2026-63943, CVE-2026-63944, CVE-2026-63945, CVE-2026-63946, CVE-2026-63947, CVE-2026-63948, CVE-2026-63949, CVE-2026-63950, CVE-2026-63951, CVE-2026-63952, CVE-2026-63953, CVE-2026-63954, CVE-2026-63955, CVE-2026-63956, CVE-2026-63957, CVE-2026-63958, CVE-2026-63959, CVE-2026-63960, CVE-2026-63961, CVE-2026-63962, CVE-2026-63963, CVE-2026-63964, CVE-2026-63965, CVE-2026-63966, CVE-2026-63967, CVE-2026-63968, CVE-2026-63969, CVE-2026-63970, CVE-2026-63971, CVE-2026-63972, CVE-2026-63973, CVE-2026-63974, CVE-2026-63975, CVE-2026-63976, CVE-2026-63977, CVE-2026-63978, CVE-2026-63979, CVE-2026-63980, CVE-2026-63981, CVE-2026-63982, CVE-2026-63983, CVE-2026-63984, CVE-2026-63985, CVE-2026-63986, CVE-2026-63987, CVE-2026-63988, CVE-2026-63989, CVE-2026-63990, CVE-2026-63991, CVE-2026-63992, CVE-2026-63993, CVE-2026-63994, CVE-2026-63995, CVE-2026-63996, CVE-2026-63997, CVE-2026-63998, CVE-2026-63999, CVE-2026-64000, CVE-2026-64001, CVE-2026-64002, CVE-2026-64003, CVE-2026-64004, CVE-2026-64005, CVE-2026-64006, CVE-2026-64007, CVE-2026-64008, CVE-2026-64009, CVE-2026-64010, CVE-2026-64011, CVE-2026-64012, CVE-2026-64013, CVE-2026-64014, CVE-2026-64015, CVE-2026-64017, CVE-2026-64018, CVE-2026-64019, CVE-2026-64020, CVE-2026-64021, CVE-2026-64022, CVE-2026-64023, CVE-2026-64024, CVE-2026-64025, CVE-2026-64026, CVE-2026-64027, CVE-2026-64029, CVE-2026-64030, CVE-2026-64031, CVE-2026-64032, CVE-2026-64033, CVE-2026-64034, CVE-2026-64035, CVE-2026-64036, CVE-2026-64037, CVE-2026-64038, CVE-2026-64039, CVE-2026-64040, CVE-2026-64041, CVE-2026-64042, CVE-2026-64043, CVE-2026-64044, CVE-2026-64045, CVE-2026-64046, CVE-2026-64047, CVE-2026-64048, CVE-2026-64049, CVE-2026-64050, CVE-2026-64051, CVE-2026-64052, CVE-2026-64053, CVE-2026-64054, CVE-2026-64055, CVE-2026-64056, CVE-2026-64057, CVE-2026-64058, CVE-2026-64059, CVE-2026-64060, CVE-2026-64061, CVE-2026-64062, CVE-2026-64063, CVE-2026-64064, CVE-2026-64065, CVE-2026-64066, CVE-2026-64067, CVE-2026-64068, CVE-2026-64069, CVE-2026-64070, CVE-2026-64071, CVE-2026-64072, CVE-2026-64073, CVE-2026-64074, CVE-2026-64075, CVE-2026-64076, CVE-2026-64077, CVE-2026-64078, CVE-2026-64079, CVE-2026-64080, CVE-2026-64081, CVE-2026-64082, CVE-2026-64083, CVE-2026-64084, CVE-2026-64085, CVE-2026-64086, CVE-2026-64087, CVE-2026-64088, CVE-2026-64089, CVE-2026-64090, CVE-2026-64091, CVE-2026-64093, CVE-2026-64094, CVE-2026-64095, CVE-2026-64096, CVE-2026-64097, CVE-2026-64098, CVE-2026-64099, CVE-2026-64100, CVE-2026-64101, CVE-2026-64102, CVE-2026-64103, CVE-2026-64104, CVE-2026-64105, CVE-2026-64106, CVE-2026-64107, CVE-2026-64108, CVE-2026-64109, CVE-2026-64110, CVE-2026-64111, CVE-2026-64112, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115, CVE-2026-64116, CVE-2026-64117, CVE-2026-64118, CVE-2026-64119, CVE-2026-64120, CVE-2026-64121, CVE-2026-64122, CVE-2026-64123, CVE-2026-64124, CVE-2026-64125, CVE-2026-64126, CVE-2026-64127, CVE-2026-64128, CVE-2026-64129, CVE-2026-64130, CVE-2026-64131, CVE-2026-64132, CVE-2026-64133, CVE-2026-64134, CVE-2026-64135, CVE-2026-64136, CVE-2026-64137, CVE-2026-64138, CVE-2026-64139, CVE-2026-64140, CVE-2026-64141, CVE-2026-64142, CVE-2026-64143, CVE-2026-64144, CVE-2026-64145, CVE-2026-64146, CVE-2026-64147, CVE-2026-64148, CVE-2026-64149, CVE-2026-64150, CVE-2026-64151, CVE-2026-64152, CVE-2026-64153, CVE-2026-64154, CVE-2026-64155, CVE-2026-64156, CVE-2026-64157, CVE-2026-64158, CVE-2026-64159, CVE-2026-64160, CVE-2026-64161, CVE-2026-64162, CVE-2026-64163, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166, CVE-2026-64167, CVE-2026-64168, CVE-2026-64169, CVE-2026-64170, CVE-2026-64171, CVE-2026-64172, CVE-2026-64173, CVE-2026-64174, CVE-2026-64175, CVE-2026-64176, CVE-2026-64177, CVE-2026-64178, CVE-2026-64179, CVE-2026-64180, CVE-2026-64181, CVE-2026-64182, CVE-2026-64183, CVE-2026-64184, CVE-2026-64185, CVE-2026-64186)

Kommentar: Wie wollen wir in Zukunft noch Sicherheit lernen? - Heise

Thu, 23 Jul 2026 09:42:41 +0200

Jede Hochschule, die IT-Security lehrt, hat ein Hacking Lab oder zumindest CTF-artige Aufgaben in den Übungen ihrer Sicherheitsmodule. Parallel dazu ...

This Week In Rust: This Week in Rust 661

Thu, 23 Jul 2026 07:18:12 +0200

Hello and welcome to another issue of This Week in Rust! Rust is a programming language empowering everyone to build reliable and efficient software. This is a weekly summary of its progress and community. Want something mentioned? Tag us at @thisweekinrust.bsky.social on Bluesky or @ThisWeekinRust on mastodon.social, or send us a pull request. Want to get involved? We love contributions.

This Week in Rust is openly developed on GitHub and archives can be viewed at this-week-in-rust.org. If you find any errors in this week's issue, please submit a PR.

Want TWIR in your inbox? Subscribe here.

Updates from Rust Community

Official

Announcing Rust 1.97.1

Newsletters

The Embedded Rustacean Issue #76

Project/Tooling Updates

Observations/Thoughts

Rust Walkthroughs

Crate of the Week

This week's crate is xan, a TUI toolkit to work with CSV files.

Thanks to Simeon H.K. Fitch for the suggestion!

Please submit your suggestions and votes for next week!

Calls for Testing

An important step for RFC implementation is for people to experiment with the implementation and give feedback, especially before stabilization.

If you are a feature implementer and would like your RFC to appear in this list, add a call-for-testing label to your RFC along with a comment providing testing instructions and/or guidance on which aspect(s) of the feature need testing.

No calls for testing were issued this week by Rust, Cargo, Rustup or Rust language RFCs.

Let us know if you would like your feature to be tracked as a part of this list.

Call for Participation; projects and speakers

CFP - Projects

Always wanted to contribute to open-source projects but did not know where to start? Every week we highlight some tasks from the Rust community for you to pick and get started!

Some of these tasks may also have mentors available, visit the task page for more information.

No Calls for participation were submitted this week.

If you are a Rust project owner and are looking for contributors, please submit tasks here or through a PR to TWiR or by reaching out on Bluesky or Mastodon!

CFP - Events

Are you a new or experienced speaker looking for a place to share something cool? This section highlights events that are being planned and are accepting submissions to join their event as a speaker.

No Calls for papers or presentations were submitted this week.

If you are an event organizer hoping to expand the reach of your event, please submit a link to the website through a PR to TWiR or by reaching out on Bluesky or Mastodon!

Updates from the Rust Project

576 pull requests were merged in the last week

Compiler

Library

Cargo

Rustdoc

Clippy

Rust-Analyzer

Rust Compiler Performance Triage

The two most notable changes this week were #159115, which resulted in pretty nice instruction count wins for full incremental builds on several benchmarks, and #159091, which enabled PGO for rustdoc, which makes it ~3-4% faster across the board.

There were two large rollups with tiny performance regressions, which made it difficult to find the offending PRs.

Triage done by @Kobzol. Revision range: 5503df87..d527bc9b

Summary:

(instructions:u)	mean	range	count
Regressions ❌ (primary)	0.4%	[0.2%, 1.0%]	40
Regressions ❌ (secondary)	0.7%	[0.2%, 4.6%]	69
Improvements ✅ (primary)	-2.0%	[-6.2%, -0.2%]	136
Improvements ✅ (secondary)	-2.6%	[-8.4%, -0.2%]	119
All ❌✅ (primary)	-1.4%	[-6.2%, 1.0%]	176

2 Regressions, 3 Improvements, 6 Mixed; 4 of them in rollups 34 artifact comparisons made in total

Full report here.

Approved RFCs

Changes to Rust follow the Rust RFC (request for comments) process. These are the RFCs that were approved for implementation this week:

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Compiler Team (MCPs only)

Leadership Council

Deallocate post-2026 funds from PM and compiler-ops

Unsafe Code Guidelines

Do the bytes of a pointer have to stay in the same order?

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RFC: Refactor the libs team

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Quote of the Week

We were planning on publishing a blog post announcing this at the same time as making the repo public, but ran out of private repo CI usage 😭.

– Carl Lerche on r/rust about the launch of topcoat

Despite a lamentable lack of suggestions, llogiq is glad to have found this quote.

Please submit quotes and vote for next week!

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The AI code vulnerabilities that grow with your app

Thu, 23 Jul 2026 07:16:19 +0200

Theori built 28 apps with AI coding agents and scanned each one through its pentesting platform. Five models did the building, split between Anthropic and OpenAI, across apps written from a spec, thrown together from a casual prompt, and rewritten from an aging PHP codebase. The team went in expecting injection everywhere. SQL injection, cross-site scripting, the bugs that fill security tutorials. Those barely showed up. The models reached for prepared statements and ORMs on … More →

The post The AI code vulnerabilities that grow with your app appeared first on Help Net Security.

The AI code vulnerabilities that grow with your app

Thu, 23 Jul 2026 07:12:52 +0200

The post The AI code vulnerabilities that grow with your app appeared first on IT Security News.

HPR4689: Cheap Yellow Display Project Part 8: Writing the code

Thu, 23 Jul 2026 02:06:01 +0200

This show has been flagged as Clean by the host.

Hello, again. This is Trey.

Welcome to part 8 in my Cheap Yellow Display (CYD) Project series.

If you wish to catch up on earlier episodes, you can find them on my HPR profile page https://www.hackerpublicradio.org/correspondents/0394.html

It is hard to believe that I started this project and the HPR series to document it more than a year ago. Time flies. Life happens. I spent the last 8 months so focused on work related activities that I had to set the project aside. And once I set it aside, it was difficult to get back to again. The one time I tried, I found that my son's old Windows laptop, which I had commandeered to use for the project, was once and truly dead.

We live in a different world now than we did when I began this project. Today, everything is about AI – how it is changing our world, increasing efficiencies, and even displacing certain types of jobs. "Vibe coding" is transforming the way we make software, and now everyone is a developer.

Within my organization, we are all being strongly encouraged to learn more about AI and apply it in our daily work. We are blessed to have access to a wide range of training and to powerful tools which support the process. Several colleagues within my organization and outside my organization have recommended Claude Code -- for development, for organization, for brainstorming, and for much more. My role is not that of a developer, and I have had no need for Claude Code at work. There are plenty of other tools for me to use.

But at home, I thought... I could install Claude Code at home to experiment with and to learn. And then it hit me. I wonder if I could use Claude Code to help me with my stalled CYD project.

"Hello, my name is Trey, and I am a fraud."

OK. I don't think I am a fraud, but having never used such a powerful tool to help me code, I feel a little bit like a fraud, with Claude doing the work for me. Let's talk through what we did.

As I mentioned, I was unable to use the laptop on which I created the original GUI code. But no worries, because It was all on GitHub, right?

So, I began by trying to install Claude Code on one of my Ubuntu machines. That failed miserably, and all the instructions I found online recommended running it on Windows. So I transitioned to installing Claude Code on a freshly built Windows 10 system using some old hardware which will not support Windows 11. Surprisingly, It seems that Claude wants to run within Ubuntu on Windows Subsystem for Linux (WSL).

Once I went through all the hoops for installing and setting up my basic subscription, I got to work. I created a new directory to use for all my project files, and another one for Claude to write all its output files to.

Everything I have read and heard about using Claude Code for a project like this recommended beginning by using Claude to create the project plan. So my first prompt was as follows:

"I am building a project using an ESP32 cheap yellow display. The final goal is to have a device with a graphical user interface which will allow me store several text messages, each assigned to their own specific button. Then, when one of the buttons is pressed, the message will be converted into morse code, and the message will be sent by blinking an onboard LED. I already have the initial design for the GUI coded in my github repository. Please construct a detailed step by step plan for building this application"

I wanted to keep it simple at the beginning, so even though I plan to use an opto-isolated relay for the output, I am starting out using the built in LED.

Claude asked me for the URL for my Github repository, and I provided it. After thinking for a bit, it produced a project plan.

CYD Morse Sender — Step-by-Step Build Plan

What You Already Have

- 3 fully designed LVGL screens (Send, Config, Keyboard)

- 7 send buttons with green styling on the Send Screen

- Speed slider (5–30 WPM) and program slot dropdown on Config Screen

- Text area + LVGL keyboard widget on Keyboard Screen

- Display driver and touchscreen hardware initialized (but touch read was stubbed out)

---

Phase 1: Fix Touchscreen Input

Initialize the XPT2046 on VSPI, replace the hardcoded touched = false with real touch data, calibrate raw ADC coordinates to screen pixels, and verify all three nav buttons transition screens correctly.

Phase 2: Persistent Message Storage

Use Preferences.h / NVS to store 7 messages ("msg0" – "msg6") that survive power cycles. Load on boot and populate send button labels.

Phase 3: Config Screen — Slot Selection & Speed

Wire the Program dropdown to g_selectedSlot, wire the Speed slider to g_wpm with a live WPM label, and wire the Set button to clear the text area and navigate to the Keyboard Screen.

Phase 4: Keyboard Screen — Capture and Save Text

On keyboard OK (LV_EVENT_READY): read the text area, save to NVS, update the send button label, navigate back. On Cancel: navigate back without saving.

Phase 5: Morse Code Engine

Build morse.h with the full A–Z / 0–9 lookup table, a textToMorse() converter, and Paris-standard timing (unit_ms = 1200 / wpm).

Phase 6: Non-Blocking LED Transmission

State machine (IDLE / LED_ON / LED_OFF) driven by millis() in a morseUpdate() function called every loop — no delay(). LED on GPIO 17 (blue).

Phase 7: Wire the Send Buttons

Each button calls startMorse(getMessage(slot)) if not already transmitting. Disable all send buttons during TX; re-enable when the state machine reaches the end.

Phase 8: Integration & Polish

Stop button, WPM persistence, empty-slot guard, serial debug output, final touch calibration, end-to-end test checklist.

---

Recommended order: Phase 1 → 2 → 7 (partial) → 5 → 6 → 7 (full) → 3 → 4 → 8

This was wild! Claude determined exactly how far along I was in the project, and also alerted me to the fact that the "touch read was stubbed out". Ugh. This means that the files I had uploaded to GitHub were my original GUI files (Episode 05 – HPR4532 - https://hackerpublicradio.org/eps/hpr4532/index.html ) and not the ones that I finally got working properly (Episode 07 – HPR4624 - https://hackerpublicradio.org/eps/hpr4624/index.html ). That was my own fault. Did I mention that I don't get Git? I REALLY need to learn to properly use Git!

But, we have a plan, broken down by eight numbered phases. And they seem to address all the functionality I wanted with a few additional things I had not thought about. Interestingly, even though these phases are sequentially numbered, Claud recommended that we approach them in a bizarre order: Phase 1 → 2 → 7 (partial) → 5 → 6 → 7 (full) → 3 → 4 → 8 .

Alright. Let's see what we can do. The first phase is to fix the touchscreen input.

Claude took me through it step-by-step, asking as it needed to read specific project files.

Finally, it wrote a new ui.ino code file to my speficied output directory for me to test. I copied it into the correct file location, said a quick prayer, compiled in Arduino IDE, and downloaded to the CYD.

Well, that is... interesting. The display looked nothing like it was supposed to. There were vertical green bars with smaller dashed green vertical stripes in them. I will include a picture in the show notes so that you can see what it looked like and why it was so difficult to describe.

I spent the next hour or so trying to explain what I was seeing to a chat bot. Claude recommended potential fixes which either did nothing or made the situation worse. I began questioning whether this was a good idea, how people actually gained efficiencies talking to a bot, and even several life choices.

Then I had a thought. I prompted Claude:

If I were to take a picture of the screen on the cheap yellow display and copy it into the output folder, would you be able to analyze it to better determine what is wrong and how to fix it?

Shockingly, Claude answered in the affirmative, and told me to copy the picture to the output folder and let it know when to proceed. It analyzed the picture and more of the supporting files it had copied from my GitHub, asking each time if it could access that file. It determined that my original code was written for a flavor of LVGL version 8 and I was now using LVGL 9.5.

It recommended changes, and then asked permission to make those changes, file by file. .h files & .c files, Finally, I just gave it permission to edit the files in the project folder without asking for permission for each file each time. Claude was still explaining each change, showing me exactly what would be changed, and asking for permission, so that I could review all of the changes. But now it was not asking additional permission to write to each of the impacted files.

Next, Code compiled and downloaded. Different screen, but not right. Again, I took a picture and gave it to Claude to analyze. So, Claude paused and altered the code to generate a specific test pattern overtop of the GUI.

The test pattern was supposed to cover the entire rectangular screen. But parts of the pattern were in a square on the screen and parts were not. Another photograph and analysis, told Claude that there were some rotation/screensize issues.

We repeated this several times. Some resulted in improvement, and others did not.

This is the point where I noticed something interesting. Not about Claude, specifically, or about the app. But I noticed something interesting about myself and about the process.

Previously, when I was working through some of these challenges without Claud, I found myself becoming more and more stressed, frustrated, and angry, until I found a solution. Then another problem would repeat the cycle. Success in the end was great, but the emotional extremes during the process were not always pleasant.

Now, I was effectively managing the project, and relaying information to the resource responsible for fixing the problems -- a very different experience.

But I also ran into another issue. Claude became absolutely certain that the problem revolved around the device not accurately knowing where the 4 corners of the screen were. But in reality, the output of the test pattern was rotated 90 degrees from the actual screen. It took several iterations of me insisting that the problem had to do with screen orientation and not corner coordinates. It was interesting to experience the tool doubling down on an obvious mistake, but we finally resolved that.

Again, while it was frustrating, it was much less stressful.

We proceeded to Phase 2: Persistent Message Storage where we ensured that the button labels on the send screen were stored in the devices persistent storage, so that, when they are edited to contain the message they should send, that information would survive a reboot.

Next, we combined elements of Phase 5: Morse Code Engine , Phase 6: Non-Blocking LED Transmission , and Phase 7: Wire the Send Buttons together. Building the morse code engine was an area I had been thinking about for a while. I already had working parts of something similar in the Arduino practice oscillator I have referenced a few times in this series. The code for the practice oscillator may be found on my GitHub, but it was all based on original code from jmharvey1, with my only contribution being making pin assignments variables so that the code could easily be ported to different devices.

So, I was happy that we were building the morse code engine directly. The code for it may be found in morse.h, which uses a constant character lookup table to define each character. Without any specific direction from me, Claude used the PARIS timing methods I have already described within Episode 6 of this series. It defines timing for DOT, DASH, LETTER_GAP, and WORD_GAP, and all are based on a simple calculation of 1200 ms / the number of words per minute (WPM) we wish to transmit.

Along the way, we discovered that, if we tried to use the delay() function, it would crash the program due to a conflict with the LVGL timer used for touchscreen inputs. Claude altered all the delays accordingly.

Then, Phase 3: Config Screen — Slot Selection & Speed allowed us to configure the WPM we wished to use in addition to selecting a specific Send button to reconfigure. This forced us to work on Phase 4: Keyboard Screen — Capture and Save Text which is used to type the entries for each Send button. At this point, I also decided that we would want to also use the Keyboard Screen to send ad hoc morse as we typed it.

During this phase we discovered several bugs which seemed to cause random freezes. Careful troubleshooting with messages output to the Arduino IDE's serial console helped us narrow down the causes and remedy them.

Finally all the tests worked and I am able to merrily pre-configure macro buttons with custom messages and use the CYD to send the morse code for those messages to the on-board LED at whichever rate I specify.

I have noticed in my presentation of this narrative that I repeatedly slip into the first person plural terms "we" and "us" instead of the first person singular terms "I" and "me". I have unconsciously personified Claud and recognized it as an integral part of my (formerly one person) development team.

I finally configured Claude to connect to my GitHub repo and upload all the files and documentation. We additionally created a CYD-Narrative.md file which describes in more detail all the work which was done on the project. I still do not 100% get git, but we are successfully using it.

You can find all these files in my GitHub repo ( https://github.com/jttrey3/CYD_MorseSender ) where they are shared under a GPL 3.0 license.

There are still several additional steps I plan to complete in the next few months.

1. I will be integrating an opto-isolated relay which will allow me to plug the device into the straight key input on any amateur radio. This will require a battery power source, charge controller, and more hardware.

I... make that "We" (Claude & I) will be modifying the code to support an audio side tone through an attached speaker when sending code
We will add an output selection switch to the config page to choose any combination of speaker, relay, or LED as output.
We will develop a downloadable firmware which I hope to share with the Cheap Yellow Display community.

If you can think of any additional features you would like to see integrated, please drop me an email using the address in my HPR profile.

I may also work with a friend to attempt to 3d print a case for the entire contraption, and I will be sure to record additional episodes sharing the process.

I have learned so much throughout this project, about the CYD, ESP32, GUIs, Claude Code, GitHub, and most of all, about myself.

Does using AI to develop this code make me a fraud? It still feels like it in some ways.

Does it make me more productive? ABSOLUTELY! I made consistent forward progress when I only had 30-60 minutes each day to work on it, and everything discussed in this episode was completed in less than a week. If I had been able to work on it for a few hours uninterrupted, it may have only taken me 3-5 hours.

Does it empower and inspire me to do more projects like this? 100% I feel like I had support working with me the whole way. I was less stressed overall, and it had less of an impact on the amount of and quality of time I spent with my family.

I will be wrapping up this series soon, without any more 6 month gaps, I hope.

Until next time...

Provide feedback on this episode.

Startup Spotlight: MediaPact wants to reinvent digital ads for the AI era

Thu, 23 Jul 2026 00:52:58 +0200

As AI reshapes online search and advertising, Seattle startup MediaPact is building a marketplace to help brands and publishers strike direct sponsorship deals. Founder Lacie Thompson discusses launching the company, using AI to build without coding experience, and spotting a new opportunity in a rapidly changing digital media landscape. Read More

Cursor Releases Cursor Router: A Request-Level Classifier Delivering Frontier Coding Quality at 30–50% Lower Cost

Thu, 23 Jul 2026 00:47:23 +0200

Cursor has made Cursor Router generally available for Teams and Enterprise plans. The system classifies each request on query, context, task complexity and domain, then routes it to the most suitable model. Cursor reports frontier-quality output at 60% savings in online A/B tests, and 30–50% savings for three early-access enterprise accounts measured against Opus 4.8 rates.

The post Cursor Releases Cursor Router: A Request-Level Classifier Delivering Frontier Coding Quality at 30–50% Lower Cost appeared first on MarkTechPost.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Can a diminished Inflection compete with AI giants spending billions?

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

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

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

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

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

Google Drops Gemini Flash 3.6 on Us Teases Gemini 4

Wed, 22 Jul 2026 21:03:16 +0200

If you happen to be into AI and models, dancing between them depending on the task, and keeping up with the latest in Gemini, then we have news for you today in the Gemini Flash realm. Google has announced (and released) Gemini 3.6 Flash, which is their “workhouse model” that does coding, knowledge work, and...

Read the original post: Google Drops Gemini Flash 3.6 on Us Teases Gemini 4

Two Ways To Mess Up Your JWT Safety Net In Your Own Lab.

Wed, 22 Jul 2026 20:59:45 +0200

In the lab we’re going to build today, we’ll talk about JWTs and how they can affect the security of your website. This is a lab that’s been requested, and I could not be happier that the community is actually suggesting things for me to build. It’s a privilege to do this.

JWT As Security Measure

JSON Web Tokens are used a lot by developers. They provide a way to send ‘data’ with them (e.g., a role from a user), to check for authorization. A JWT consists of 3 parts, separated by a ..

Let’s take this JWT as an example.

eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiYWRtaW4iOnRydWUsImlhdCI6MTUxNjIzOTAyMn0.KMUFsIDTnFmyG3nMiGM6H9FNFUROf3wh7SmqJp-QV30

The first part eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9 is called 'the header'. It holds information on the type of the JWT. The second part eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiYWRtaW4iOnRydWUsImlhdCI6MTUxNjIzOTAyMn0 is the payload, which holds the claims. This is where that 'data' lives. If you decode this with Base64url you'll learn that this token belongs to John Doe and that he is an administrator. The last part is the important part. This is the signature. Each JWT should be signed with a strong password. Ideally that password is saved in a .env file on the server and not in the code.

So now you might wonder, well if it’s signed, nothing can go wrong right? Well, if that were true, I wouldn’t spend my evenings writing these kinds of blog posts now would I 😅.

Let’s Build The Lab Already

You’re right to think this by now. Enough theory, let’s do some hands on keyboard. As always in this series, I’ll provide you with the lab structure and some code to get us started.

Lab Tree

/mediumLabs
└── /JWT
    ├── server.js
    ├── login.html
    ├── index.html
    ├── admin.html
    ├── /node_modules
    ├── /package-lock.json
    └── /package.json

Code

server.js

const express = require('express');
const jwt = require('jsonwebtoken');
const path = require('path');
const Database = require('better-sqlite3');
const app = express();
const JWT_SECRET = 'secret';
const db = new Database(':memory:');
db.exec(`
  CREATE TABLE users (
    id INTEGER PRIMARY KEY,
    username TEXT,
    password TEXT,
    role TEXT
  )
`);
db.prepare("INSERT INTO users (username, password, role) VALUES ('user', 'password', 'user')").run();
app.use(express.urlencoded({ extended: false }));

app.get('/', (req, res) => res.sendFile(path.join(__dirname, 'login.html')));
function getToken(req) {
  const match = (req.headers.cookie || '').match(/token=([^;]+)/);
  return match ? match[1] : null;
}
app.post('/login', (req, res) => {
  const { username, password } = req.body;
  const user = db.prepare('SELECT * FROM users WHERE username = ? AND password = ?').get(username, password);
  if (!user) return res.redirect('/?error=Invalid+credentials');
  const token = jwt.sign({ username: user.username, role: user.role }, JWT_SECRET);
  res.setHeader('Set-Cookie', `token=${token}; Path=/`);
  res.redirect('/index.html');
});
app.get('/index.html', (req, res) => {
  try {
    res.sendFile(path.join(__dirname, 'index.html'));
  } catch {
    res.redirect('/');
  }
});
app.get('/admin', (req, res) => {
});

app.listen(3000, () => console.log('Listening on http://localhost:3000'));

login.html




    
    
    Login


    Login

    
        
            Username: 
        

        
            Password:

index.html

Home

Welcome!

You are logged in as .

Go to Admin Panel

admin.html

Admin Panel

Welcome, admin. Here is the secret flag:

FLAG{JWT}

Back to Home

Let’s Add Some Vulnerabilities

Ok, so now we have our base code, and we need to implement the functionality that will make sure only people with the role admin can navigate to /admin. First off, run npm run dev to see your code actually start.

In a very, very wrong way we already tried implementing security in admin.html. When you look inside the