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CVE-2026-17459 | perwendel spark up to 2.9.4 SparkJava ExternalResourceHandler.jav staticFiles.externalLocation symlink (Issue 1296 / EUVD-2026-49054)

Sun, 26 Jul 2026 14:29:46 +0200

A vulnerability classified as critical was found in perwendel spark up to 2.9.4. This vulnerability affects the function staticFiles.externalLocation of the file src/main/java/spark/resource/ExternalResourceHandler.jav of the component SparkJava. Executing a manipulation can lead to symlink following. This vulnerability is registered as CVE-2026-17459. It is possible to launch the attack remotely. Furthermore, an exploit is available. The project was informed of the problem early through an issue report but has not responded yet.

CVE-2026-17458 | mf-yang openclaw-cn up to 0.2.1 Browser Control HTTP API agent.act.ts clickViaPlaywright server-side request forgery (Issue 562 / EUVD-2026-49053)

Sun, 26 Jul 2026 14:29:45 +0200

A vulnerability classified as critical has been found in mf-yang openclaw-cn up to 0.2.1. This affects the function clickViaPlaywright of the file src/browser/routes/agent.act.ts of the component Browser Control HTTP API. Performing a manipulation results in server-side request forgery. This vulnerability is cataloged as CVE-2026-17458. It is possible to initiate the attack remotely. Furthermore, there is an exploit available. The project was informed of the problem early through an issue report but has not responded yet.

CVE-2026-17457 | mf-yang openclaw-cn up to 0.2.1 Scheme navigation-guard.ts assertBrowserNavigationAllowed url information disclosure (Issue 561 / EUVD-2026-49052)

Sun, 26 Jul 2026 13:38:14 +0200

A vulnerability described as problematic has been identified in mf-yang openclaw-cn up to 0.2.1. Affected by this issue is the function assertBrowserNavigationAllowed of the file src/browser/navigation-guard.ts of the component Scheme Handler. Such manipulation of the argument url leads to information disclosure. This vulnerability is listed as CVE-2026-17457. The attack may be performed from remote. In addition, an exploit is available. The project was informed of the problem early through an issue report but has not responded yet.

Induction Labs Photon-1 Simulates Desktops, Plays Checkers, and Models Billiard Physics From One Pretraining Run

Sun, 26 Jul 2026 11:24:52 +0200

Most agents that learn from video need to know what action produced each frame. Induction Labs is arguing that this requirement is the bottleneck. Last week, they released imagination models, a foundation model architecture that pretrains on raw video with no action labels at all. Their test system is Photon-1, a sparse 106B-A5B mixture-of-experts (MoE) […]

The post Induction Labs Photon-1 Simulates Desktops, Plays Checkers, and Models Billiard Physics From One Pretraining Run appeared first on MarkTechPost.

CVE-2026-17433 | nanocoai NanoClaw up to 2.0.64 MCP Server Approval chat-sdk-bridge.ts createChatSdkBridge.setup improper authorization (Issue 2761 / EUVD-2026-49048)

Sun, 26 Jul 2026 09:19:21 +0200

A vulnerability was found in nanocoai NanoClaw up to 2.0.64. It has been classified as critical. This impacts the function createChatSdkBridge.setup of the file src/channels/chat-sdk-bridge.ts of the component MCP Server Approval. Performing a manipulation results in improper authorization. This vulnerability was named CVE-2026-17433. The attack needs to be approached locally. In addition, an exploit is available. The project was informed of the problem early through an issue report but has not responded yet.

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

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

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

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

A Debian general resolution on LLM usage

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

The Debian project is considering a general resolution on the use of large language models in the creation of the distribution. There are three alternatives to consider: a total ban on LLM usage, rejecting LLMs "as far as practical", or explicitly allowing LLM usage subject to a set of conditions. The discussion period has just begun; the beginning of the voting period does not yet appear to have been set. Those who want to look over the discussion ahead of the inevitable LWN article can find it over here.

Ghost Font Exposes a Blind Spot in AI Vision by Hiding Text in Motion-Based Optical Illusions

Sun, 26 Jul 2026 06:34:11 +0200

Artificial intelligence has made significant progress in reading documents, recognizing handwritten text and interpreting low-quality images. However, a new experimental typography project called Ghost Font is revealing an unexpected limitation in how many AI vision systems process visual information.Created by…

The post Ghost Font Exposes a Blind Spot in AI Vision by Hiding Text in Motion-Based Optical Illusions appeared first on IT Security News.

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."

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.

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.

10 cool things Copilot can do in PowerPoint

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

Building a presentation can take lots of time. There are design choices to figure out: the slide layouts, fonts, theme colors, and so on. You can use a template to skip this hassle, but you still have to paste your text and other content into the slides and edit it all so that the results are visually appealing.

In PowerPoint, Microsoft’s Copilot AI assistant can now automate the heavy lifting of presentation creation. It can generate a first-draft presentation in minutes, then help you edit it. You can also prompt Copilot to help you quickly understand the contents of a presentation and glean insights from it. Use the tips in this guide to save oodles of time as you create and work with presentations.

Who can use Copilot in PowerPoint

Individuals with a Microsoft 365 Personal, Family, or Premium subscription have access to Copilot from within PowerPoint and other Microsoft 365 apps. Users with a Premium plan have higher Copilot usage allowances and access to advanced AI features.

For business users, it’s more complicated. Organizations with more than 2,000 users must pay for Microsoft 365 Copilot licenses for their users in addition to their regular Microsoft 365 licenses. Users at organizations with fewer than 2,000 users can use Copilot within M365 apps even without the M365 Copilot add-on licenses, but there are limitations in usage, speed, and feature availability.

To see what kind of access you have, log in to Microsoft’s Copilot Chat web hub and look for your name in the lower left corner. If you see “M365 Copilot (Premium)” under your name, you can use Copilot in M365 apps with priority access and advanced features. “M365 Copilot (Basic)” means you can use Copilot in M365 apps with lower-priority access and limited features. If you see “Copilot Chat (Basic)” or nothing below your name, you can’t use Copilot in M365 apps.

(Copilot Chat Basic users do get some Copilot functionality, including the ability to generate presentations, via the Copilot Chat hub. See our Copilot Chat tutorial for details.)

Working with Copilot in PowerPoint

First, let’s quickly go over the notable settings of the Copilot sidebar.

When you have a presentation open in PowerPoint, click the Copilot icon; it may be floating at the lower-right corner of your PowerPoint window or parked at the right end of the Ribbon toolbar. The Copilot sidebar will open along the right of the page. You’ll type your prompts to Copilot inside the chat window in this pane.

The sidebar on the right is where you interact with Copilot in PowerPOint.

Howard Wen / Foundry

Agent mode: By default, Copilot can build a new presentation or make changes to an existing one in the main PowerPoint window. This is known as “agent mode.” To change this so that Copilot can’t take direct action on a presentation (all its responses appear in the sidebar), click the Allow editing button above the chat window and change it to Chat only.

The tips in this guide require that Copilot be in agent mode, so make sure you see Allow editing above the chat window.

Choice of AI model: Behind the scenes, Copilot has access to various genAI models, including different versions of Anthropic Claude and OpenAI GPT. By default, it decides which model to use based on your prompt. You can set it to use a particular model: click Auto at the upper right of the Copilot pane and select a model from the dropdown that opens.

You can choose which AI model you want Copilot to use for a request.

Howard Wen / Foundry

The tips in this guide should work fine on the default Auto setting. But feel free to experiment switching to specific models to see which give you the best results for particular tasks.

Important: Remember that generative AI output often includes errors, so always check Copilot’s output for accuracy. (Also see our tips for reducing hallucinations in Copilot.) You’ll likely want to rewrite it in your own voice as you’re reviewing it.

1. Create a presentation template

For many people, the hardest part of creating a presentation is getting started. What types of information should be included on the slides, and in what order? Copilot can give you a leg up by creating the type of presentation you need, with placeholder data that you can later replace with your own.

Start a new presentation, open the Copilot sidebar, and type your prompt into the chat window. It’s best to provide very specific details in your prompt. The more context or details you provide, the more likely Copilot will generate a presentation template that suits your needs.

A good prompt should contain the slide count, subject, audience, and tone. Example:

Create a 6-slide presentation for a sales meeting focusing on Q1 revenue. The audience is the sales team, so keep the tone professional and focused on the sales data.

Copilot may ask a series of follow-up questions, such as your preferred visual style and desired level of detail. Then it will generate a presentation template.

Copilot generates a presentation with placeholder data and explains its elements.

Howard Wen / Foundry

You can optionally prompt Copilot for revisions, and when you’re happy with the template, swap in your own data.

2. Create a presentation from a document

You can attach a document (such as a Word document, Excel spreadsheet, or PDF) and prompt Copilot to generate a presentation based on its contents. This works best with a structured-format document (such as a business plan, project proposal, or summary report) that contains sections with headings.

Copilot can extract the document’s text and structure to generate the slide content for the new presentation. This can especially be useful for quickly turning a long report into a visually appealing presentation.

In the Copilot pane, click the + icon at the bottom of the chat window. A list of documents that you’ve recently accessed appears. Select the one that you want Copilot to use. Alternatively, click the magnifying glass icon and inside its search box, type a few letters of the filename for the document you want. (Business users with an M365 Copilot license can select up to five files for Copilot to pull from when creating a presentation.)

Attaching a document for Copilot to base a presentation on.

Howard Wen / Foundry

Then in the chat window, you can enter a prompt that’s as simple as “Create a presentation,” although as always, providing more details and context is better. This is especially important for corporate users who reference multiple source files. It’s useful to tell Copilot what data to pull from each document.

Answer any follow-up questions that Copilot asks, and it will then generate the presentation.

Copilot has generated a professional presentation from a social media marketing campaign document.

Howard Wen / Foundry

Note: Your marketing department may have created one or more branded company templates for Copilot to work from. If that’s the case at your organization, simply open the appropriate company template as your first step. Then you can upload docs and type a prompt as described above. Copilot will create a presentation using the branded template.

3. Add content from a document to a slide

Manually copying text or other content from a document and pasting it into a new slide is a chore. Instead, you can prompt Copilot to extract information directly from a Word document, Excel spreadsheet, or PDF to create new slides.

In the Copilot pane, attach the document using the same steps described in tip 2, then tell Copilot to create a slide from the document. As always, it helps to provide details such as the new slide’s focus or what data to include:

Add a slide based on the attached document.
Use the attached file to add a slide about the project budget that focuses on Q1 projections.
Summarize only the financial section of the attached document as a slide.

A new Copilot-generated slide based on data from an Excel spreadsheet.

Howard Wen / Foundry

4. Refine your slide text

A presentation should be visual and display only the core message. Conciseness and proper writing tone are essential for your slides, so that they don’t lose the attention of your audience.

You can prompt Copilot to refine text on an individual slide in various ways, such as rewriting it in a more professional tone or making it more concise. Highlight the text inside a text box on the slide. On the toolbar that appears over the highlighted text, click Edit with Copilot.

On the menu that opens, you can select a preset prompt to refine the text, such as Condense or Make professional. Or, at the top of this menu, you can type a prompt to rewrite the highlighted text.

Choose a preset prompt for refining text on a slide or type in your own prompt.

Howard Wen / Foundry

Note that this feature affects all the text inside the text box. To rewrite only a portion of text inside a text box, you must split that portion out into a separate text box.

Alternatively, you can prompt Copilot to analyze your entire presentation and tighten up the wording throughout all of its slides. For example:

Make these slides more visual and use less text.

5. Find or create an image

If you have Copilot generate a presentation from an existing Word document that contains images, it will incorporate those images into the presentation. If there are no images in the source document, you can ask Copilot to find or create one and add it to a slide.

To add a stock image or an image from your organization’s brand library, tell Copilot what you’re looking for:

Add a stock photo of young adults in a cafe drinking boba tea.
Add a photo from our asset library of young adults in a cafe drinking boba tea.

To have Copilot create an image using Microsoft’s Designer image generation tool, describe your desired image. As always, specificity is helpful:

Create a photorealistic image of a diverse group of 5 or 6 fashionable young adults sitting in a cafe drinking boba tea. They’re smiling or laughing, and some are looking at their phones.

Copilot in PowerPoint hooks into Microsoft’s Designer tool for image generation.

Howard Wen / Foundry

Just as you need to review any text output from Copilot, take a close look at generated images to be sure nothing looks off.

Also note that Copilot image generation isn’t always reliable in PowerPoint. For some time during our testing for this story, Copilot said it couldn’t create an image because “the image generation service is returning a server error on every attempt.” After about a day and a half, the service began working again.

6. Expand your presentation with relevant slides

As you’re building your presentation, you may find that it’s become text heavy. Or perhaps it could use more visually oriented slides to break things up and make its progression flow better. Copilot can generate and insert new slides that are based on the content of the slides already in the presentation.

In the Copilot pane, specify exactly where you want the new slide to go. This helps Copilot to analyze the content of the slides before and after where you want the new slide. Then it can generate a slide to bridge between the two slides. Examples:

Add a slide after slide 3 about our competitive advantages.
Add a slide after slide 11 that transitions to slide 12.

Need a transition slide? Just ask!

Howard Wen / Foundry

7. Summarize a presentation

Maybe you need a quick refresh of your presentation before an important meeting. Or maybe a co-worker has sent you a presentation that’s packed with lots of slides. You can prompt Copilot to generate a summary of the presentation’s overall messaging.

In the Copilot pane, just type “summarize this presentation.” You can also have Copilot flag key slides that contain important information: “show me key slides.”

Ask Copilot to summarize a presentation or flag key slides.

Howard Wen / Foundry

8. Answer questions about a presentation

As you’re reviewing a presentation, especially one that you didn’t create and are not familiar with, you can get Copilot to pull key data points from its slides.

In the Copilot pane, type specific informational questions. Examples:

What are the action items in this deck?
What is the proposed budget mentioned here?

If Copilot can’t find the exact answer to the question you ask, it will provide related information from the presentation.

Ask Copilot specific questions about the contents of a presentation.

Howard Wen / Foundry

This method can also help you validate that your presentation includes everything you want it to. If you ask Copilot about the action items in a presentation and it can’t find any, you know you need to add them. (Copilot will likely offer to generate them for you based on the rest of the slides.)

You can even take this tactic a step further and ask Copilot if the presentation is missing any important data, if any slides are weak or confusing, if there are any awkward transitions, if there are key points that should be better emphasized, and so on.

9. Help you navigate a large presentation

In the business world, presentations with dozens of slides are not uncommon, such as for financial reports or project documentation. Trying to find a specific slide or multiple slides can be tough. Copilot can help you navigate such a presentation.

In the Copilot pane, prompt Copilot to find slides based on specific topics. Example:

Show me the slides about the project timeline.

Copilot will analyze the presentation and reply with a list of links to the relevant slides. Click one of these to jump directly to that slide.

Copilot can help you zoom directly to a slide that covers a particular topic or shows specific data.

Howard Wen / Foundry

10. Generate speaker notes and/or an FAQ

Here’s a great timesaver when you’re preparing to show your presentation to an audience: Copilot can automatically generate suggested speaker notes for you, based on the content of your slides. Example prompt:

Write speaker notes for every slide with one talking point per slide.

Copilot can create speaker notes in seconds.

Howard Wen / Foundry

In a related feature, Copilot can create a frequently asked questions list (FAQ) for you to consult in your speaker notes or to present as a slide:

Write an FAQ for these slides.

Copilot will ask where you want the questions and answers added — as a new slide at the end, integrated into the speaker notes of relevant slides, or somewhere else that you designate. Make a selection, and Copilot will generate the FAQ based on the content of your presentation.

A Copilot-generated FAQ slide.

Howard Wen / Foundry

AMD raises the AI stakes with Helios, Venice and robotics

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

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

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

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

AMD’s MI455X targets the AI memory wall

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

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

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

AMD

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

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

AMD’s Helios rack takes aim at Vera Rubin

Dave Altavilla

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

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

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

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

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

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

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

AMD

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

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

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

Pensando networking and ROCm software advance

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

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

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

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

Customer commitments underscore rack-scale confidence

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

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

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

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

AMD expands its robotics and embedded foundation

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

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

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

Execution for AMD is now the test

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

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

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

This article is published as part of the Foundry Expert Contributor Network.
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Sam Altman’s biometric startup World raises $52.5M via crypto sale

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

Sam Altman's side project — which seeks to scan the world's eyeballs and turn them into unique digital identifiers — has raised some fresh cash through a crypto sale.

Dyson Clean+Wash Hygiene angewischt

Sat, 25 Jul 2026 19:36:33 +0200

Der Name Dyson im Zusammenhang mit nassen Böden ist inzwischen kein komplett neues Thema mehr. Der V15s Detect Submarine war der erste Schritt, der Wash G1...

Zum Beitrag: Dyson Clean+Wash Hygiene angewischt

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Fügt uns doch bei Google als bevorzugte Quelle hinzu!

New Project CAV3RN module abuses Outlook calendar events for C2 and DNS AAAA records for configuration recovery

Sat, 25 Jul 2026 19:04:16 +0200

Kaspersky GReAT experts describe a new Project CAV3RN C2 module. It uses Outlook calendar for communication via Microsoft Graph and has a backup connection via DNS AAAA responses.

The Spy Hack That Made US a Superpower: Project Gunman

Sat, 25 Jul 2026 19:03:51 +0200

YouTube Video

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

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 June 2026 Security Update Review

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

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

Adobe Patches for June 2026

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

Here’s this month’s overview table:

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

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

Microsoft Patches for June 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

The July 2026 Security Update Review

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

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

Adobe Patches for July 2026

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

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

Here’s this month’s overview table:

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

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

Microsoft Patches for July 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

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The February 2026 Security Update Review

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

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

Adobe Patches for February 2026

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

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

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

Microsoft Patches for February 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

The 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!

Foxit Updater Vulnerability Gives Standard Users SYSTEM-Level Control of Windows Devices

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

Foxit PDF Reader has been found vulnerable to a local privilege escalation flaw that allows standard Windows users to gain full SYSTEM-level control under specific conditions. The issue, tracked as CVE-2026-57239, was disclosed following research into Foxit’s updater and service architecture and represents a high-impact post-exploitation pathway, although it requires prior code execution on the […]

The post Foxit Updater Vulnerability Gives Standard Users SYSTEM-Level Control of Windows Devices appeared first on Cyber Security News.

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.

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.
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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.

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Stop asking AI nicely: Here’s how to get work-ready results every time

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

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

Why advanced prompting still matters in enterprise settings

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

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

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

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

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

After (CoT prompt):

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

Results: Accuracy and depth improved dramatically.

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

Template you can use:

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

[Task or question]

For each step:

1. State your observation or calculation.

2. Explain the implication.

3. Proceed only when confident.

Final answer in this format: [structured output]

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

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

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

Prompt Snippet:

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

Path 1: Focus on cost and scalability.

Path 2: Focus on security, compliance and integration.

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

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

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

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

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

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

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

ReAct example: (used in data analytics workflow)

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

1. Reason about what information you need.

2. Choose the appropriate tool or action.

3. Observe the result.

4. Repeat until you can answer confidently.

Query: [user request]

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

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

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

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

Original prompt: [paste]

Provide the improved version and explain your changes.

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

5. Multimodal and structured output techniques

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

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

Best practices I learned the hard way

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

Final takeaways for technical leaders

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

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

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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.

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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.

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Model Context Protocol is going stateless to make scaling simpler

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

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

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

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

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

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

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

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

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

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

MCP’s new features

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

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

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

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

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

Rebuilding the trust boundary

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

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

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

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

Updated MCP SDKs

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

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

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

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

This article first appeared on InfoWorld.

Getting a grip on shadow tokens and AI blowouts

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

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

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

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

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

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

When shadow tokens result in real costs

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

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

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

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

Shifting the culture from usage to yield

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

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

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

Stopping token waste before an AI blowout

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

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

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

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

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

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

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Private health records of half a million Britons offered for sale on Chinese website

Sat, 25 Jul 2026 18:55:43 +0200

Technology minister tells Commons ‘de-identified’ information from UK Biobank advertised for sale on Alibaba

The confidential health records of half a million British volunteers have been offered for sale on Chinese website Alibaba, the UK government has confirmed.

The “de-identified” data, belonging to participants in the UK Biobank project, was found for sale on three separate listings last week. Ian Murray, the technology minister, told the Commons on Thursday that, after working with the Chinese government and Alibaba, the records had now been removed. It is not believed any sales were made.

CVE-2022-3602 and CVE-2022-3786: OpenSSL 3.0.7 patches Critical Vulnerability

Sat, 25 Jul 2026 18:52:21 +0200

On Tuesday, November 1 2022 between 1300-1700 UTC, the OpenSSL project announced the release of a new version of OpenSSL (version 3.0.7) that will patch a critical vulnerability in OpenSSL version 3.0 and above. Only OpenSSL versions between 3.0 and 3.0.6 are affected at the time of writing. At this moment the details of this [...]

The post CVE-2022-3602 and CVE-2022-3786: OpenSSL 3.0.7 patches Critical Vulnerability appeared first on Hacking Tutorials.

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

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

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

CVE-2026-5203 | CMS Made Simple up to 2.2.22 UserGuide Module XML Import class.UserGuideImporterExporter.php _copyFilesToFolder path traversal

Sat, 25 Jul 2026 17:03:04 +0200

A vulnerability was found in CMS Made Simple up to 2.2.22 and classified as critical. This impacts the function _copyFilesToFolder in the library modules/UserGuide/lib/class.UserGuideImporterExporter.php of the component UserGuide Module XML Import. The manipulation results in path traversal. This vulnerability is known as CVE-2026-5203. It is possible to launch the attack remotely. Furthermore, an exploit is available. This issue has been reported early to the project. They confirmed, that "this has already been discovered and fixed for the next release."

How AI drove Shopify back to clean code

Sat, 25 Jul 2026 15:12:13 +0200

Turns out, agents just want the same things as humans: easily-readable code, explicit contracts, and helpful feedback

Build for the future with the Android XR Developer Catalyst Program — Apply now!

Sat, 25 Jul 2026 10:15:51 +0200

Posted by Android XR Team

The Android XR ecosystem is expanding, and we’re committed to supporting developers who will build its next great experiences. Today, we’re opening applications for the Android XR Developer Catalyst Program, a dedicated initiative to accelerate the development of Android XR apps ready to launch within the next year.

This program is designed to provide the resources, hardware, and grants to help you build and scale innovative experiences across wired XR glasses, like XREAL’s Project Aura, and intelligent eyewear (audio and display glasses). We are especially interested in seeing innovative experiences across media, gaming, productivity, and health, but we welcome any unique use case that helps users expand what's possible.

Why join the catalyst program?

We want to help developers navigate common barriers to entry for XR development by providing:

Development Kits: Get early access to hardware development kits for wired XR glasses (XREAL’s Project Aura) and / or intelligent eyewear (audio and display glasses).
Technical support: Gain access to specialized technical resources and support forums specifically designed to help you prepare your app for Google Play.
Grant Opportunities: Submit a request and you may be eligible to receive a non-recoupable grant to accelerate your development.

Ready to start building?

Applications are open to developers looking to publish apps for the Android XR ecosystem in the next 6-12 months. You can build with Kotlin and the Jetpack XR SDK, or with Unity, Unreal Engine or Godot. If you need a spark of inspiration, you can check out existing XR Experiments and Samples to see how you can use the SDK for everything from spatial music to navigation.

Once you have your concept ready, be sure to submit your application by June 30th by 11:59PM PDT. We can’t wait to see what you build.

Start Your Application

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

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

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

Posted by Simona Milanovic and Ben Trengrove, Developer Relations Engineers

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

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

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

Android development unlocked for Antigravity

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

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

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

Unlocking Android Studio capabilities for any agent

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

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

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

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

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

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

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

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

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

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

More ways to get started

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

winget install -e --id Google.AndroidCLI

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

Support for Journeys

Journeys are natural language descriptions of core user experiences.

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

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

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

Expanding Android skills

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

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

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

android init

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

android skills list

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

android skills add –skill=

Get started today

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

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

Build native Android apps in Google AI Studio

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

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

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

The power of native Android

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

A seamless, end-to-end workflow

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

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

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

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

Install the app on your Android device

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

Publish the app to an internal test track in Google Play

Seamless app development handoff

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

Download zip file of Android app project files

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

Start building today

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

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

What’s Next?

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

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

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

Turn your Google Pixel Watch into an aviation assistant

Prompt:

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

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

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

Prompt:

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

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

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

We are looking forward to seeing what you build next!

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

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

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

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

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

Build High Quality Android Apps Using Agents

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

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

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

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

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

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

3: Accelerating AI coding assistance with Android Bench

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

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

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

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

Building AI Into Your Apps

5: Building Intelligent Apps with generative AI

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

6: Experiment with AppFunctions today

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

The Future is Adaptive

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

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

Build Android UI with Compose

8: Building seamless Android experiences across devices with Jetpack Compose

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

9: Create seamless experiences for Googlebook

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

New Desktop Android Emulator

10: Unified widget development experience with Jetpack Glance

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

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

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

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

12: Accelerate your development with Android XR Developer Preview 4

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

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

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

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

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

Low Light Boost and Magic Eraser in action

14: Increase app discovery and engagement on Google TV

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

15: Performance: the foundation of a great app experience

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

And The Latest on Driving Business Growth

16: What’s new in Google Play

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

Gemini will provide users with app suggestions during a search

17: And of course, Android 17

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

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

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

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

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

Prioritizing Memory Efficiency: Essential Steps for Android 17

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

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

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

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

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

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

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

Understanding Android 17 app memory limits

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

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

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

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

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

Maximize bytecode optimization with R8

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

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

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

To properly configure R8 in your build.gradle file:

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

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

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

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

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

Library Developer R8 Best Practices

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

R8 Configuration Analyzer

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

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

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

R8 Agent Skill

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

Optimize image loading

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

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

Adopt these five best practices

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

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

Android Studio tooling

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

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

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

Detect and fix memory leaks with Android Studio

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

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

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

LeakCanary memory leak analysis contextualized with Go to declaration for debugging

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

Examples of common memory leaks

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

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

Here are a few example scenarios:

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

Trim memory when app leaves visible state

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

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

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

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

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

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

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

class MainActivity : AppCompatActivity(), ComponentCallbacks2 {

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

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

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

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

Advanced memory observability with ProfilingManager

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

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

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

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

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


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

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

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

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

Conclusion

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

Top 3 updates for Android developer productivity

Sat, 25 Jul 2026 10:15:38 +0200

Posted by Simona Milanovic, Developer Relations Engineer

Every year, Google I/O brings new announcements and resources across ecosystems and products, including Android development. As development shifts toward AI and agent-assisted tooling, we’ve expanded our offerings to better support you, however you decide to build for Android.

To help you stay up to date, here is a summary of the top 3 announcements for Android Developer Productivity at I/O.

1. Android CLI is now stable

Android CLI is now stable at version 1.0, with more capabilities and integrations.

The latest version of Android CLI introduces many new features, like programmatic version lookup and support for Journeys, and bridging capability to allow agents to integrate directly with Android Studio, via the studio command.

Running Android Studio alongside the agent and Android CLI enables more efficient navigation in your project, more precise output, and access to Android Studio’s unique tooling, such as performance profilers, Compose Previews, and Android Device Streaming.

Android CLI now integrates seamlessly with Android Studio

Additionally, Google Antigravity now officially supports Android development, with the Android resources bundle, which includes the Android CLI and skills.

You can either install the bundle during onboarding after installation, or later from the Settings > Customizations > Build With Google Plugins menu. This provides Antigravity with all the powerful tools and knowledge of Android CLI to enable it to perform core tasks—from creating projects to deploying your app on a new virtual device—much more easily and efficiently.

Google Antigravity now offers the Android resources bundle

Android CLI is now available through more package managers: like npm and homebrew. For more information, check out the Android CLI blog post and official documentation.

2. Android skills keep growing

To help models gain expertise for specific development patterns that follow our best practices, we are continuing to expand our repository of Android skills, available through Android CLI and GitHub.

Android skills ground LLMs in specialized workflows and domain knowledge, for the most common and more complex user journeys they might struggle with. We’ve shipped a fresh new batch of skills, with now more than 17 skills for areas such as:

Adaptive UI
Display Glasses and Jetpack Compose Glimmer for XR
Migration to CameraX
Perfetto SQL and Trace Analysis
Jetpack Compose Styles API
AppFunctions
Verified email retrieval with Android Credential Manager
Engage SDK integration
Testing setup
Wear OS Jetpack Compose Material3

Android skills keep growing

You can browse skills and install using the Android CLI commands:

android skills list
android skills add –skill=

For more information, check out the official documentation.

3. Android Bench adds new models

Earlier this year, we launched Android Bench - our leaderboard for testing LLMs on real-world Android development challenges and tasks, with the goal of accelerating model improvements, so you have more helpful options for AI assistance.

Latest results from Android Bench leaderboard

You asked us to evaluate open models. So, at I/O, we added more commonly used ones, including our local model Gemma 4, to the leaderboard. We also added the latest models including Gemini 3.5 Flash.

We are also working on increasing the difficulty of challenges we’re giving LLMs, including creating long running tasks, to continue encouraging improvements. These tasks will be coming soon to Android Bench. Check out the Android Bench leaderboard to see the latest results.

Android development anywhere

By expanding our AI-assisted Android development offerings to Antigravity, through Android CLI and Android skills, and solidifying with the pro capabilities and production grade polish of Android Studio, we’re supporting Android developers wherever they choose to build.

Have fun bringing your ideas to life faster and easier than ever before - we’re excited to see what you build in this new era of agentic development.

Check out the full Developer productivity at Google I/O 2026 YouTube playlist for more information.

Android 17 is here

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

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

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

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

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

Let's dive deeper into Android 17.

An intelligence system

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

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

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

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

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

Adaptive-first

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

No resizability/orientation restrictions on large screens

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

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

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

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

App Bubbles and Bubble Bar in action

Activity recreation updates

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

Continue On

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

Handoff Suggestion on a Tablet

class MyHandoffActivity : Activity() {

    ...

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

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

Go adaptive-first with Jetpack Compose

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

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

Android is Compose-first

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

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

Performance & efficiency

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

App memory limits

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

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

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

The R8 Configuration Analyzer

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

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

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

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

Generational garbage collection

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

Lock-Free MessageQueue

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

Static final fields now truly final

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

Custom notification view restrictions

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

Privacy & Security

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

Privacy-preserving choices

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

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

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

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

Local network access

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

SMS OTP protection

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

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

Post-Quantum Cryptography (PQC)

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

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

Safer native dynamic code loading

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

Smarter password protection for physical inputs

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

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

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

Smarter password protection for physical inputs

Media and camera features that empower creators and delight users

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

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

Better support for hearing aids

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

CameraX and Media3

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

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

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

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

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

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

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

Get started with Android 17

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

Getting the Android 17 beta on partner devices

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

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

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

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

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

Building a Mixed-Reality Tour Guide with Android XR, the Geospatial API, and Gemini

Sat, 25 Jul 2026 10:15:35 +0200

Posted by Coco Fatus, UX Designer, Alon Hetzroni, UX Engineer, Azin Mehrnoosh, Product Manager Android XR

At this year's Google I/O, we announced an update for spatial experiences: the Geospatial API is now available as a preview in ARCore for Jetpack XR. By bringing Google's Visual Positioning System (VPS) to Android XR, Android XR enables anchoring digital content to the physical world with sub-meter accuracy and precise orientation in supported areas.* To explore what the Geospatial API could unlock, our team built a demo: the XR Geospatial Tour.

Imagine walking into a new city, putting on a pair of wired XR glasses (like the upcoming XREAL Project Aura), and instantly having a knowledgeable, local guide showing you around. You don't need to stare down at a 2D map—instead, 3D models gently guide your path, and an intelligent voice tells you about the historical landmarks right in front of you. We combined the Geospatial APIs, Gemini API using Firebase AI Logic, Google Maps Grounding, and Jetpack XR SDK to create a hands-free, immersive walking tour experience.

*Disclaimer: Video and Tour Guide application are for demonstration purposes only. Some sequences have been shortened. Any hardware depicted may be under development; final product details may differ.

Let’s walk through the implementation details and show how we tied these APIs together to build a world-scale spatial experience.

1. Pinpointing the User with ARCore Geospatial API (VPS)

Enhance your navigation experience on XR by combining the power of GPS with the precision of VPS. The accuracy and precise orientation that comes with VPS allows 3D waypoints to align with the physical world.

This is why the Geospatial API on Android XR can help you build custom experiences. By using advanced computer vision, VPS tries to provide a GeospatialPose (including latitude, longitude, and heading) that is more accurate than GPS.

Here's how we retrieve the user's Geospatial pose by mapping the device's orientation to a Geospatial coordinate:

// Retrieve the current geospatial pose from the ARCore session
val result = geospatial.createGeospatialPoseFromPose(arDevice.state.value.devicePose)
if (result is CreateGeospatialPoseFromPoseSuccess) {
    val pose = result.pose
    Log.d("VPS", "Accurate Location: ${pose.latitude}, ${pose.longitude}")
}

Because the entire experience relies on this accuracy, we monitor the horizontalAccuracy and orientationYawAccuracy until they meet our thresholds. If the user is indoors or in an unrecognized area, we prompt them to "walk to an outdoor public space and look around".

2. Crafting the Itinerary with Gemini API & Google Maps Grounding

Once we have a location, we use the Gemini API using Firebase AI Logic to prompt the Gemini model to act as a local tour guide. We pass the user's coordinates to the model and ask it to output a structured JSON response containing nearby walking tours:

   val configForTools = ToolConfig(
      functionCallingConfig = null,
      retrievalConfig = retrievalConfig {
        latLng = FirebaseLatLng(pose.latitude, pose.longitude)
        languageCode = "en"
      }
    )
    val responseJsonSchema = Schema.obj(
      mapOf(
        "locationIntro" to Schema.string(),
        "tours" to Schema.array(
          Schema.obj(
            mapOf(
              "title" to Schema.string(),
              "description" to Schema.string(),
              "stops" to Schema.array(
                Schema.obj(
                  mapOf(
                    "name" to Schema.string(),
                    "detailedName" to Schema.string(),
                    "description" to Schema.string()
                  )
                )
              )
            )
          )
        )
      )
    )
    val model = Firebase.ai(backend = GenerativeBackend.googleAI()).generativeModel(
      modelName = "gemini-3.5-flash",
      tools = listOf(Tool.googleMaps()),
      generationConfig = generationConfig {
        responseMimeType = "application/json"
        responseSchema = responseJsonSchema
      }
    )
   val result = model.generateContent("The user is at latitude ${pose.latitude} and longitude ${pose.longitude}. Generate exactly 3 diverse tours near this location (e.g., historical, food, nature). All tour ideas should be walking distance only.")

Large Language Models are great at generating rich descriptions, but they can sometimes hallucinate exact latitude/longitude coordinates. To solve this, we used Google Maps Grounding to ground the AI.

3. A Voice to Guide You: Gemini 2.5 TTS

To make the tour guide feel truly present, we implemented dynamic voiceovers.

Using the gemini-2.5-flash-tts model, we can configure our model generation config to natively return audio data instead of just text! Here’s how you can request the ResponseModality.AUDIO:

val ttsModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        modelName = "gemini-2.5-flash-tts",
        generationConfig = generationConfig {
            // Instruct the model to return Audio
            responseModalities = listOf(ResponseModality.AUDIO)
        }
    )
val response = ttsModel.generateContent("Say in a neutral but positive voice:\n$prompt")
// Extract the raw audio bytes from the response
val audioBytes = response.candidates.firstOrNull()?.content?.parts
    ?.filterIsInstance()
    ?.firstOrNull { it.mimeType.contains("audio") }?.inlineData

4. Bringing it to Life in 3D with Jetpack XR

The final piece of the puzzle is rendering this data in the user's field of view. The Jetpack XR SDK makes it intuitive to transition from a 2D Android UI to spatial computing.

We used Jetpack Compose for XR to build spatial components. To represent points of interest along the tour, we built a Composable called InfoSphere, which contains a GltfModel of a 3D orb that floats in space and can be interacted with to reveal information.

Using Jetpack XR SDK, we can place 3D models alongside the Compose UI using SpatialBox and SceneCoreEntity. We also used InteractableComponent to respond to user taps.

@Composable
fun InfoSphere(
    content: InfoBubbleContent,
    session: Session,
    sphereModel: GltfModel,
    isSelected: Boolean,
    onClick: () -> Unit
) {
    // SpatialBox lets us arrange 3D components and SpatialPanels together
    SpatialBox(
        SubspaceModifier
            .offset(x = 2.dp, y = 1.dp, z = (-3).dp) // Positioned in 3D space
    ) {
        // Smoothly animate the visibility of our 2D Compose UI Panel
        AnimatedSpatialVisibility(visible = isSelected) {
            SpatialPanel {
                InfoBubble(content) // Regular 2D Compose UI
            }
        }
        // Render our interactive 3D sphere
        SceneCoreEntity(
            factory = {
                GltfModelEntity.create(session, sphereModel).also { entity ->
                    // Make the 3D model respond to user taps
                    entity.addComponent(InteractableComponent.create(session) { inputEvent ->
                        if (inputEvent.action == InputEvent.Action.UP) {
                            onClick()
                        }
                    })
                }
            }
        )
    }
}

By combining AnimatedSpatialVisibility for traditional Compose UI surfaces with SceneCoreEntity 3D elements, we're able to seamlessly blend data into the physical world.

Explore what’s possible with Android XR today

Building the XR Geospatial Tour app showed us that the barrier to entry for world-scale spatial experiences is lower than ever for Android developers. With the Geospatial API now available in preview on Android XR, your apps can seamlessly understand the physical world around them. By combining Compose for XR’s APIs with the high-precision location data of VPS and the generative capabilities of Gemini, we can create experiences that understand both where the user is and what they are looking at.

To help you get hands-on with Android XR, we are thrilled to open applications for the Android XR Developer Catalyst Program, which includes XREAL Project Aura. Starting today, you can apply to get access to an XREAL Project Aura devkit or our display glasses devkit over the coming months!

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

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

Posted by Amman Asfaw, Product Manager, Android Studio

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

Here’s a deep dive into what’s new:

Multi-tasking with parallel chats

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

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

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

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

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

Use the History icon to navigate between active tasks.

Memory leak detection with LeakCanary

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

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

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

Once a leak is detected during a profiling session:

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

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

App Quality Insights agent integration

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

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

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

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

Quality & stability improvements

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

Get Started

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

Build intelligent Android apps: Introduction to Jetpacker

Sat, 25 Jul 2026 10:15:26 +0200

Posted by Jolanda Verhoef, Senior Developer Relations Engineer, Android Developer Relations

Building GenAI features in your app usually means navigating through various models, APIs and architecture choices:

Execution location: Where does your model run? On device, in the cloud, or both?
Complexity: How complex is your setup? Are you doing a single inference call or do you need a more agentic flow?
In-app or Android System: Should your feature be built into your Android app or does it fit better as an Android system integration?

In this blog post series we'll navigate these choices with you. We will take you along on a journey, starting with a basic mobile app and transforming it into a personalized, intelligent, and agentic experience.

Jetpacker: a demo travel app

Jetpacker is a technical showcase app that our team built from the ground up for this year's Google I/O (built using Antigravity). At its core, Jetpacker helps users plan, explore, and enjoy their next big adventure. It shows an overview of your trips, the itinerary of each trip, and details of each event on that trip. Of course following all best practices of Android development, including a beautifully expressive Material UI design.

And best of all? It's fully open source!

Today we are publishing a series of technical blog posts diving deep into each of these features. We’ll provide detailed implementation steps, code snippets, and architectural insights to help you build your own intelligent Android applications.

On-device intelligence

On-device features in Jetpacker: Summarizing trip itineraries, managing expenses, and voice notes

Using an on-device model comes with no additional cloud inference costs, means you don't have to worry about internet connectivity, and lets users be confident that private information will be processed locally, on the device, without any of their data being sent to the cloud.

In Jetpacker, we chose on-device inference for three of our features:

The trip overview feature transforms a messy, multi-day itinerary into a concise, actionable summary. It leverages Gemini Nano through the ML Kit GenAI APIs to process data locally on the device. We consider this a nice-to-have feature where we don't want to incur extra cloud costs, making on-device inference the right choice.
The expense tracker automatically extracts structured data from receipt images to help users track their travel spending. It uses the multimodal capabilities of Gemini Nano 4 through the ML Kit GenAI APIs. We choose an on-device solution so that any privacy-sensitive information on the receipt images never leaves the user's device.
The audio diary records, transcribes, and categorizes voice notes into relevant trip activities. It is powered by the ML Kit Speech Recognition and GenAI Prompt APIs. We chose an on-device solution for privacy and connectivity reasons.

Cloud & hybrid inference

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

Sometimes your use-case requires AI models with greater world knowledge or a much larger context window and with greater ability in handling complex tasks. In that case, we can switch from running an on-device model to using a cloud model instead.

Or, if you want to get the best of both worlds, you can use hybrid inference to dynamically choose either a cloud or on-device model at runtime. This allows us to lower costs by moving inference to the device when it is available, but at the same time support all Android devices running the app.

In Jetpacker, we implemented several features using cloud or hybrid inference:

The place Q&A feature answers user questions about specific locations by grounding responses in real-world data. It uses Firebase AI Logic integrated with Google Maps and web context. Using a cloud model is necessary here for its greater world knowledge.
The review drafting feature helps users compose detailed reviews for the places they have visited. It leverages both on-device and cloud models through Firebase AI Logic's new Hybrid inference API. This is a feature we wanted to make available to all app users, so we're using a cloud model as a fallback when an on-device model is unavailable.
The automatic chat translation dynamically translates chat messages in real time to facilitate seamless communication, demonstrating custom hybrid inference logic. Again, we want this feature to be available to all app users, but at the same time have some specific considerations on when to choose on-device versus cloud.

System integration

While not a feature you see in the app itself, the Android system integration opens up the app's core capabilities directly to the Android operating system. It uses the AppFunctions API to integrate with system-level intelligence.

In-app agentic workflows (coming soon!)

The booking assistant shows several in-progress flight bookings, asking the user for input before making a final booking.

Agenticness introduces a higher level of autonomy, enabling models to act as agents. Instead of a single inference call, an agent works towards a specific goal via an orchestration loop that allows it to reason, use tools, and adapt its path. Depending on your requirements, these intelligent agents can run either in the cloud, directly on-device, or in a hybrid setup.

For Jetpacker we added a booking assistant that automates end-to-end booking workflows directly within the application to streamline reservations. It is built using A2UI and ADK running in the cloud. The Android app functions as a front-end to the multi-agentic system running in the cloud.

Learn more

Check out the other parts of this blog post series:

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

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

Build intelligent Android apps: On-device inference

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

Posted by Caren Chang, Developer Relations Engineer, Android Developer Relations

Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post we introduced Jetpacker, the demo app we'll use throughout this series.

In this blog post, we will share how you can use Gemini Nano through ML Kit’s Prompt API to build intelligent on-device features.

Building intelligent on-device features refers to the ability to process prompts and data directly on a device without sending data to a server. This offers a few advantages:

User data can be processed locally on the device, preserving user privacy
Functionality of the model is reliable even with spotty or no internet connection
No additional cloud inference cost, since everything runs on the user’s hardware

With the benefits of on-device in mind, we identified three features to add in Jetpacker that can improve the user experience: summarizing trip itineraries, managing expenses, and capturing voice notes.

On-device features in Jetpacker: Summarizing trip itineraries, managing expenses, and voice notes

High quality tailored summarization of short texts

The itinerary screen gives users a quick overview of all activities for a given trip. Since this screen contains a lot of information, it can quickly become overwhelming. To help users prepare without feeling overwhelmed, we can add a ‘Get ready for your trip’ section at the top.

The romantic Paris trip is summarized as a classic Parisian adventure blending art, sights, and delicious food. A tip and some useful phrases are also added.

By inputting a trip itinerary and asking an LLM to summarize it, we can generate a quick summary of the trip along with packing tips and useful local phrases. This is a great use case for an on-device model for several reasons:

Performance and quality: Both the input and output text are relatively short. With that, we can expect the performance and quality of an on-device solution to be on par with more powerful cloud models.
Scalability: Shifting inference on-device allows us to scale this feature from a few users to millions without worrying about managing increasing cloud inference costs.
Low latency and reliability: On-device inference guarantees low latency, providing a reliable experience even when users are offline.

To build with on-device, we use Gemini Nano, Google’s most efficient model optimized for mobile devices. Gemini Nano was first introduced a few years ago, and is now running on over 140 million devices. The latest version of the model, Gemini Nano 4, is built on the architecture foundation of the recently released Gemma 4 model, and is further optimized for maximum battery and performance efficiency.

Using ML Kit’s Prompt API, we can take advantage of Gemini Nano 4’s new model capabilities to prototype our on-device features. We’ll create a prompt that includes the itinerary of a trip and ask the model to generate a summary along with any preparation tips.

// implementation("com.google.mlkit:genai-prompt:1.0.0-beta3") 

// Define the configuration for Gemini Nano 4 E2B preview model
val previewFastConfig = generationConfig {
    modelConfig = modelConfig {
        releaseStage = ModelReleaseStage.PREVIEW
        preference = ModelPreference.FAST
    }
}

val geminiNano2BPreviewModel = Generation.getClient(previewFastConfig)

val tripItinerary = ...

val getReadyForYourTripSummary = geminiNano2BPreviewModel
 .generateContent("Given this trip itinerary: $tripItinerary, 
     generate the following: overall vibe, tips on how to prepare for this
     trip, and common short phrases to learn for the trip.")

Finding the optimal prompt usually requires some iteration, and the AICore app is perfect for this step in the process. After opting into the developer preview option for AICore, we can download preview models such as Gemini Nano 4 to test prompts and see the model’s expected outputs. With a few iterations on the prompt, we were able to improve the speed of the response from 13 seconds to under 2 seconds! Check out the final code implementation and prompt here.

The first iteration of our prompt generated way too many tokens, and optimizing it helped keep responses quick and to the point.

Local processing for sensitive user input

Next, to help users enjoy their trip even more, we’ll build a simple expense manager that takes the manual work out of sorting through receipts and calculating budgets.

Taking a photo of a restaurant bill, data is parsed and shown in the expense overview screen of the app.

Since receipts might contain sensitive information like credit card number and addresses, this is another great use case for an on-device solution. With on-device, users can be confident that private information will be processed locally on the device without any of their data being sent to the cloud.

In addition, Gemini Nano 4 has improved model capabilities for multimodality, especially for image understanding tasks like OCR and visual data extraction, making it a great solution for tasks like extracting information from receipts.

For this use case, the prompt will analyze an image of the receipt, and output information such as: a generated title, amount spent and category of the expense. To ensure the model outputs the information in the preferred format, we can use ML Kit’s Structured Output API to seamlessly output a Kotlin data object that we define.

// implementation("com.google.mlkit:genai-prompt:1.0.0-beta3")
// ksp("com.google.mlkit:genai-schema-compiler:1.0.0-alpha1")

@Generable("Information extracted from an expense receipt")
data class ParsedReceipt(
  @Guide("Generated title for the expense less than 6 words. Based on restaurant or activity name.")
  val title: String,
  @Guide("Total amount of the expense. Look for values at the bottom and words like total or balance due.")
  val amount: Double,
  @Guide("Type of expense", enumValues = ["travel", "food", "shopping", "entertainment", "other"])
  val category: String,
)

val prompt = "Determine if the image is a receipt or expense. 
    If it is NOT a receipt or expense, output the text 'NOT_A_RECEIPT'.
    Otherwise, parse the receipt information."

val request = generateContentRequest(ImagePart(bitmap), TextPart(prompt)) {}
val requestWithStructuredOutput = generateTypedContentRequest(request, ParsedReceipt::class)

// Define the configuration for Gemini Nano 4 E4B preview model  
// When selecting models, you can specify which performance charactertists are most important
//  for your use case. Use ModelPreference.FULL when you want to prioritize reasoning power over speed. 
//  Use ModelPreference.FAST when complex logic is not required and latency is a priority.
val previewFullConfig = generationConfig {
    modelConfig = modelConfig {
        releaseStage = ModelReleaseStage.PREVIEW
        preference = ModelPreference.FULL
    }
}

val geminiNano4BPreviewModel = Generation.getClient(previewFullConfig)
val response = geminiNano4BPreviewModel.generateContent(requestWithStructuredOutput)
val parsedReceipt: ParsedReceipt? = response.candidates.firstOrNull()?.response

Multimodal input

Lastly, to help users record audio memos during the trip, let’s build a fully on-device voice notes feature. Using ML Kit’s Speech Recognition API, we’ll enable users to record short voice notes that are automatically transcribed to text. With the transcribed text, we’ll use ML Kit’s Prompt API to identify which trip activity is associated with the recorded voice note, letting users easily recap their trip as they scroll through the trip’s itinerary.

The Roman holiday itinerary shows voice note extracts.

The ML Kit GenAI Speech Recognition API allows you to transcribe audio content to text fully on-device using two distinct modes. Basic mode uses a traditional on-device speech recognition model and is available on most Android devices with API level 31 and higher. Advanced mode uses Gemini Nano to offer broader language coverage and better quality, and is currently supported on Pixel 10 devices.

For our feature we combine the Speech Recognition API with the ML Kit GenAI Prompt API:

// implementation("com.google.mlkit:genai-prompt:1.0.0-beta3")
// implementation("com.google.mlkit:genai-speech-recognition:1.0.0-alpha1")

val tripEvents = ... 

// Set up speech recognition
val speechRecognizerOptions =
    speechRecognizerOptions {
        locale = Locale.US
        preferredMode = SpeechRecognizerOptions.Mode.MODE_ADVANCED
    }
val speechRecognizer: SpeechRecognizer = SpeechRecognition.getClient(speechRecognizerOptions)

suspend fun transcribeVoiceNote(recognizer: SpeechRecognizer) {
    // Display partial text as the user is recording audio
    var partialTextResponse = ""

    // Display the full text once user is finished recording audio
    var transcription = ""

    val request: SpeechRecognizerRequest
        = speechRecognizerRequest { audioSource = AudioSource.fromMic() }
    recognizer.startRecognition(request).collect { response ->
        when (response) {
            is SpeechRecognizerResponse.PartialTextResponse -> {
                partialTextResponse = response.text
            }
            is SpeechRecognizerResponse.FinalTextResponse -> {
                transcription = response.text
                processAndCategorizeVoiceNote(transcription, tripEvents)
            }
        }
    }
}

fun processAndCategorizeVoiceNote(transcribedVoiceNote: String, events: List) {
    val prompt = "Given the voice note $transcribedVoiceNote
     and the following events for this trip: $events, rewrite this transcription
     to remove filler words. Then, identify which events from the
     list this rewritten transcription matches to."

     // Utilize ML Kit's Prompt API to process voice note and tag it with the relevant trip activities
     Generation.getClient().generateContent(prompt)
}

Conclusion

Using ML Kit’s GenAI APIs, we were able to take advantage of Gemini Nano to develop fully on-device intelligent features for the JetPacker app, and provide an improved user experience without any additional cloud costs.

Check out the full source code for Jetpacker on Github, and watch the video Build Intelligent Android apps with Google’s AI to learn more about how to integrate intelligent features directly into your app using on-device models, cloud-powered reasoning, and the latest agentic frameworks.

Learn more

Check out the other parts of this blog post series:

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

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

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

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

Optimize your apps for the next generation of Samsung Galaxy devices

Sat, 25 Jul 2026 10:15:16 +0200

Posted by Fahd Imtiaz, Senior Product Manager and Miguel Montemayor, Developer Relations Engineer, Android Developer Experience

Today at Galaxy Unpacked, Samsung unveiled its latest lineup of foldable and wearable devices. For developers, this means that the variety of form factors, screen sizes, and device postures your app needs to support is expanding once again.

With devices like the Galaxy Z Fold8, the ecosystem is expanding to include hardware with a landscape-first natural orientation and a wider aspect ratio in its main display state. Whether a user is unfolding a large display, flipping open a cover screen, or glancing at their wrist, users expect a flawless experience. To help you meet this moment, we’re sharing actionable guidance and new tooling updates to enable you to build adaptively proactively.

Rethink layout architecture for dynamic displays, including ultra-wide foldables

Building for the latest foldables means dropping assumptions about display orientation and size. This is especially true for the Galaxy Z Fold8, which adopts an ultra-wide display, adding to the variety of aspect ratios to account for. Devices with this landscape-first natural orientation show the limitations of hardcoded layout rules when users unfold the device. That’s why we’ve introduced dedicated guidance for building for landscape foldables and trifolds.

To build a responsive UI that handles these physics seamlessly, focus on the following core pillars:

Build fluid, adaptive layouts: Wide aspect ratios and compact vertical heights require fluid UIs that scale responsively. Our updated adaptive design guidance advises considering the window class width first to determine layout changes, then adjusting for height. To let individual components fluidly adapt to the grid, structure your layout using flexible containers that allow your content to automatically wrap, span, and reflow. For design inspiration browse our adaptive sample app and dual-screen design galleries.
Track actual app space: Your app's display space rarely matches the physical device size, especially on an ultra-wide screen during multi-window, split-screen, or multitasking states. Sometimes even the orientations differ. Leverage Window Size Classes using the Jetpack Window Manager library to calculate the exact space your app occupies.

Leverage the latest Jetpack Compose Update: Start by adopting the stable Jetpack Compose April '26 release (Compose BOM version 2026.04.01).Take advantage of the new structural layout tools to manage complex architectures. The new Grid API allows you to define dynamic tracks and column spans without the performance overhead of a lazy list. Pair Grid with the new FlexBox layout API to easily handle multi-axis alignment and dynamic item wrapping. You can also use the new MediaQuery API to adapt your UI to its environment, using conditions to detect signals like device posture, window size, and keyboard types.
Make your app fold aware: Use the Jetpack WindowManager library, which provides an API surface for foldable device window features such as folds and hinges. When your app is fold aware, it can adapt its layout to avoid placing important content in the area of folds or hinges and use folds and hinges as natural separators.
Maintain app continuity: Avoid breaking the user journey when the device configuration shifts. Retain your UI state using ViewModel to ensure smooth transitions when a user folds or unfolds their device.

Ensure seamless camera capture on foldable devices

Camera implementation on foldables brings unique hardware quirks. Moving from a compact outer display to an expanded inner display introduces distinct layout aspect ratios while device rotation remains unchanged. If an app assumes a fixed portrait relationship between the camera sensor and the device layout, the app will likely suffer from sideways, stretched, or cropped previews during these folding transitions.

When optimizing your app's media pipeline, migrate your capture experiences to CameraX using the CameraX migration skill. The library’s PreviewView automatically handles sensor orientation, device rotation, and scaling behind the scenes. This guarantees a clean, stable preview regardless of how the user holds or positions the device. If you are maintaining an existing Camera2 codebase, integrate the CameraViewfinder library to apply these complex aspect ratio and rotation transformations automatically without needing a total architecture overhaul.

Extend glanceable interactions to Wear OS 7

The opportunity to build for this new generation of devices extends right to the wrist. Launching with Wear OS 7, Wear Widgets give you a fresh surface to provide users with instant, glanceable access to their essential updates. You can build these highly expressive experiences using Jetpack Glance and RemoteCompose. Crucially, Widgets built with this framework can now populate multi-widget tiles that were previously reserved for first-party widgets.

Build intelligent features

Gemini intelligence already completes tasks on users’ behalf, and you can experiment with the intelligence system by sharing your apps capabilities.

Samsung’s new foldable devices come with Gemini Nano 4, our latest on-device model. Nano 4 provides support for over 140 languages, better multimodal understanding, and much more. Use ML Kit’s Prompt API with advanced features like structured output and thinking mode to build intelligent features on-device.

Start optimizing today

The tools and frameworks are ready to help you optimize your app for all screen sizes. Begin by exploring our guidance for building adaptive apps to learn more about core adaptive design principles.

To dive deeper, check out our comprehensive YouTube playlist. Finally, ensure your app delivers a flawless, premium experience on the newest form factors by reviewing our dedicated quality guidelines for trifolds and landscape foldables and WearOS.

Unfold the future today!

Google Hands Open Health Stack To the Linux Foundation

Sat, 25 Jul 2026 10:12:42 +0200

BrianFagioli writes: The Linux Foundation intends to launch the Open Health Stack Software Foundation, a new vendor-neutral home for the Google Open Health Stack project. Google is contributing the project code and assets while Google.org is providing a $3 million grant. The initiative is also backed by Microsoft, Anthropic, and the World Health Organization, with the goal of building open source, AI-ready digital health infrastructure. Will moving the project under Linux Foundation governance accelerate adoption, or is this simply another foundation that most developers will never interact with? The new project will focus on core HL7 FHIR technologies for healthcare interoperability, the Open Health Stack Player deployment toolkit, and AI Commons -- a model-agnostic healthcare AI initiative being co-developed with the World Health Organization. A notable part of the announcement is its planned Implementer Program, which aims to give startups, small businesses, and local developers in low- and middle-income countries a formal role in governance. In other words, the effort is not just about building healthcare software standards, but about making sure the people implementing them in underserved markets help shape the project too.

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

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.


Defending Against China-Nexus Covert Networks of Compromised Devices
Sat, 25 Jul 2026 09:10:14 +0200


Defending against china-nexus covert networks of compromised devices
executive summary
Defending against China-nexus covert networks of compromised devices 
Explaining the widespread shift in tactics, techniques and procedures (TTPs) towards networks of compromised infrastructure, and how to defend against it 
Summary
With support from the UK Cyber League, this advisory has been jointly released by the National Cyber Security Centre (NCSC-UK) and international partners: 

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

Its purpose is to provide network defenders with the tools needed to defend against China-nexus cyber actors and their tactic of using large scale networks of compromised devices (covert networks) to route their cyber activity. 
Introduction  
Over the past few years there has been a major shift in the tactics, techniques and procedures (TTPs) used by China-nexus cyber actors, moving away from the use of individually procured infrastructure, and towards the use of externally provisioned, large-scale networks of compromised devices. 

The NCSC believes that the majority of China-nexus threat actors are using these networks (hereafter “covert networks”), that multiple covert networks have been created and are being constantly updated, and that a single covert network could be being used by multiple actors. These networks are mainly made up of compromised Small Office Home Office (SOHO) routers, as well as Internet of Things (IoT) and smart devices. 


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


The use of covert networks of compromised devices - also known as botnets - to facilitate malicious cyber activity is not new, but China-nexus cyber actors are now using them strategically, and at scale.  


This advisory describes the typical makeup of a covert network and what they are being used for. It also includes protective advice for organizations being targeted by cyber activity using a covert network as an access vector.
Covert Networks 
Covert networks are used to connect across the internet in a low-cost, low-risk, deniable way, disguising the origin and attribution of malicious activity. Actors have been observed using them for each phase of their Cyber Kill Chains, from performing scans as part of reconnaissance, to the delivery of malware, communicating with said malware, and exfiltrating stolen data from a victim. They can also be used for general deniable internet browsing, allowing threat actors to research exploitation techniques, new TTPs, and their victims without attribution. Some covert networks are also used by legitimate customers to browse the internet, making it challenging to attribute malicious activity. 

There is evidence that covert networks used by China-nexus actors are created and maintained by Chinese information security companies. A network known to network defenders as Raptor Train, which in 2024 infected more than 200,000 devices worldwide, was controlled and managed by the Chinese company, Integrity Technology Group. This company was also assessed by the FBI to be responsible for the computer intrusion activities attributed to China-based hackers known as Flax Typhoon. 



Botnet operations represent a significant threat to the UK by exploiting vulnerabilities in everyday internet-connected devices with the potential to carry out large-scale cyber attacks – NCSC Director of Operations, Paul Chichester 



Covert networks mostly consist of compromised SOHO routers, but they also pull in any vulnerable device they can exploit at scale. Raptor Train was made up of thousands of SOHO routers and IoT devices, such as web cameras and video recorders, as well as firewalls and Network Attached Storage (NAS) devices. The KV Botnet used by Volt Typhoon was mainly made up of vulnerable Cisco and NetGear routers. The edge devices were vulnerable because they were “end of life” – out of date and no longer receiving updates or security patches by their manufacturers. 


The cyber security industry has been aware of examples of these networks for some time and has publicly reported on the widespread scale of the threat and its implications. Mandiant Intelligence produced a public blog in May 2024 talking about covert networks in which they highlighted a key issue for defenders – indicator of compromise (IOC) Extinction. If a particular threat group could now come from one of many covert networks, each with potentially hundreds of thousands of endpoints, and each used by multiple threat actors, old network defense paradigms of static malicious IP block lists will be less effective. This is compounded by the dynamic nature of these networks where new nodes will be added as old devices are patched or removed from use. 
Typical Network Topology
The number of covert networks used by China-nexus cyber actors is large, with new networks regularly developed and deployed. The existing covert networks change too, either because of defensive or legal action, or simply as a result of software updates and new exploits being used to target different technologies for incorporation into the network. 

Because of this, a description of all known covert networks in detail, including how they are constructed and how they communicate, would immediately be out of date – and for most network defenders would not be practically useful. 


However, most covert networks of compromised devices use the same basic set up. Understanding this generalized structure can aid researchers and defenders by helping them to understand which part of a network they may have found, and how to defend against it. 




  
      




      A diagram illustrating the basic setup of a covert network.
  

The diagram above illustrates the basic setup of a covert network, where typically an actor will connect to the network via an on-ramp or entry node. Their traffic will be forwarded through multiple compromised devices, used as traversal nodes, before exiting the network from an exit node, usually in the same geographic region as the target. 
Protective Advice 
Defending from attackers using covert networks is not straightforward, and defensive tactics will be different based on the levels of resource and the nature of the target organization. General advice for good cyber security practice should be followed, and some key messages can be found in the appendix of this advisory.  


The following advice is specifically tailored to steps which can be taken to combat the risk of attacks coming from large, dynamic networks of compromised devices. 


Further guidance for all organizations facing cyber security threats is available on the NCSC website. 
This guidance should be considered alongside all applicable laws and regulations of the UK and co-sealing countries relating to the security of networks and data. It will be each organization’s responsibility to ensure compliance with any such laws and regulations. Organizations should note that following the recommended actions set out below will not remove all risks.
All organizations

The NCSC recommends the following steps for all affected organizations to either take themselves, or ask their managed service and/or security providers to investigate for them: 

Map and understand network edge devices, developing a clear understanding of organizational assets and what should be connecting to them.
Baseline normal connections, especially to corporate virtual private networks (VPNs) or other similar services.

Would you expect connections from consumer broadband ranges?


Leverage available dynamic threat feeds which include covert network infrastructure.
Implement multifactor authentication for remote connections.

Smaller organizations should consider creating and actioning a free NCSC Cyber Action Toolkit. 
Larger or more at-risk organizations


Some more comprehensive measures may be appropriate if the risk to an organization is high enough, to be conducted either in-house or through a security provider:  

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

The NCSC's Cyber Essentials can help protect organizations of all sizes. 
Largest or most at-risk organizations 
If Advanced Persistent Threat (APT) tracking is part of an organization’s in-house capability, or if it is part of the service provided by a security vendor, consider tracking China-nexus covert networks as APTs in their own right.

Active hunting – look for connections from IP addresses likely to be part of a covert network of compromised devices, for instance those hosting SOHO routers or IoT devices.
Track and map covert networks reported by industry or government by looking at banners and certificates.
Use threat reporting and threat feeds to create and implement dynamic blocklists and create alert rules to detect incoming threats.
Consider using NetFlow feeds to look upstream and map covert networks to find new nodes. 

The NCSC Cyber Assessment Framework provides guidance for organizations under the highest levels of threat, including those operating essential services, in sectors such as energy, healthcare, transport, digital infrastructure and government.  
MITRE ATT&CK® 
This advisory has been compiled with respect to the MITRE ATT&CK® framework, a globally accessible knowledge base of adversary tactics and techniques based on real-world observations. 






Tactic 






ID 






Technique 






Procedure 










Resource Development 






T1584.005 






Compromise Infrastructure: Botnet 






Botnets are used as core components of covert networks 








Resource Development 






T1584.008 






Compromise Infrastructure: Network Devices 






Devices are compromised and added to botnets 








Resource Development 






T1583.003 






Acquire Infrastructure: Virtual Private Server 






Virtual private servers (VPS) are used in covert networks, typically as on-ramps 








Command and Control 






T1090.003 






Proxy: Multi-hop Proxy 






Used by China-nexus cyber actors to route traffic 










 Appendix: Cyber Security Best Practices 
In addition to the protective advice outlined in this advisory, a number of cyber security best practices will also be useful in defending against the activity described in this advisory. 

Protect your devices and networks by keeping them up to date: use the latest supported versions, apply security updates promptly, use antivirus and scan regularly to guard against known malware threats. See NCSC Guidance: https://www.ncsc.gov.uk/collection/device-security-guidance/policies-and-settings/antivirus-and-other-security-software
Prevent and detect lateral movement in your organization’s networks. See NCSC Guidance: https://www.ncsc.gov.uk/guidance/preventing-lateral-movement
Implement architectural controls for network segregation. See NCSC Guidance: https://www.ncsc.gov.uk/guidance/10-steps-network-security
Set up a security monitoring capability so you are collecting the data that will be needed to analyze network intrusions. See NCSC Guidance: https://www.ncsc.gov.uk/guidance/introduction-logging-security-purposes and https://www.ncsc.gov.uk/information/logging-made-easy
Use modern systems and software. These have better security built-in. If you cannot move off out-of-date platforms and applications straight away, there are short term steps you can take to improve your position. See NCSC Guidance:  https://www.ncsc.gov.uk/collection/mobile-device-guidance/managing-the-risks-from-obsolete-products
Restrict intruders' ability to move freely around your systems and networks. Pay particular attention to potentially vulnerable entry points such as third-party systems with onward access to your core network. During an incident, disable remote access from third-party systems until you are sure they are clean. See NCSC Guidance: https://www.ncsc.gov.uk/guidance/preventing-lateral-movement and https://www.ncsc.gov.uk/guidance/assessing-supply-chain-security.
Deploy a host-based intrusion detection system. A variety of products are available, free and paid-for, to suit different needs and budgets.
Further information: Invest in preventing malware-based attacks across various scenarios.  See NCSC Guidance: https://www.ncsc.gov.uk/guidance/mitigating-malware-and-ransomware-attacks 

Disclaimer  
This report draws on information derived from NCSC and industry sources. Any NCSC findings and recommendations made have not been provided with the intention of avoiding all risks and following the recommendations will not remove all such risk. Ownership of information risks remains with the relevant system owner at all times. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favoring by co-sealers. UK readers should refer to the NCSC website for information about NCSC assured services. 



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


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


All material is UK Crown Copyright © 










Matrix Live S12E09: The Matrix Spring Update 2026 from The Matrix Community Summit
Sat, 25 Jul 2026 08:42:18 +0200
Author: Matrixdotorg - Bewertung: 30x - Views:605 
In which Matthew gives an update on everything happening in Matrix as of May 2026, including the Spec Core Team and Foundation priorities, Project Hydra to improve federation robustness, how Hydra unlocks vanilla MLS on Matrix, and the resurgence of P2P Matrix!



Matrix Community Summit: https://matrix-community.events/conferences/2026-summit.html

Schedule: https://openki.matrix-community.events/event/eu43r8WTeHsCMEBsE/the-matrix-spring-update-2026



This Week in Matrix: https://matrix.org/twim



Find Matrix.org on the internet:

🐘 https://mastodon.matrix.org/@matrix

🤝 https://www.linkedin.com/company/matrix-org

🦋 https://bsky.app/profile/matrix.org

[m] Office of the Matrix Foundation https://matrix.to/#/%23foundation-office:matrix.org



CVE-2022-40482 | Laravel up to 9.31.x HTTP/2 hasValidCredentials timing discrepancy (EUVD-2022-43760)
Sat, 25 Jul 2026 08:42:06 +0200
A vulnerability classified as critical was found in Laravel up to 9.31.x. This affects the function hasValidCredentials of the component HTTP2 Handler. Executing a manipulation can lead to observable timing discrepancy.

This vulnerability is handled as CVE-2022-40482. The attack can only be done within the local network. There is not any exploit available.

Upgrading the affected component is advised.


Firefox Nightly: Backup for a Rainy Day – These Weeks in Firefox: Issue 202
Sat, 25 Jul 2026 08:37:35 +0200
Highlights

The profile backup mechanism has been enabled by default for all desktop platforms in Nightly, as well as Beta! The current plan is to have this ride out to Firefox 151 for Windows, macOS and Linux on May 18th!

This feature, when enabled, will create a copy of your profile data in the background and store it in a single file on your file system that you can restore from.
You will be able to manage this feature in Settings under Sync (for now)




You can read more about the feature here


As followups to the recent addition to the WebExtension tabs API to support the new SplitView tabs feature, tabs.group() and tabs.ungroup() have been fixed to work correctly with split view tabs, and fixed split views being prepended instead of appended to tab groups when adopted into a new window – Bug 2029099 / Bug 2029534
Adaptive autofill has been enabled on Nightly.

Previously, autofill only completed domains (e.g. typing red autofilled reddit.com). Now it can also complete full URLs for pages you visit often (e.g. red → reddit.com/r/firefox), learning from what you actually click in the address bar. If a suggestion isn’t helpful, you can now dismiss it so autofill learns what not to show you too.

If you run into issues or have feedback, you can file a bug here!




Markus Stange [:mstange] implemented dynamic toolbar on top in RDM (#1978145), but also implemented some static skeleton UI so it’s closer to what we actually have in Firefox for Android

dynamic toolbar is behind a pref: devtools.responsive.dynamicToolbar.enabled
it can be put on top by setting devtools.responsive.dynamicToolbar.onTop, otherwise it’s at the bottom




Friends of the Firefox team
Resolved bugs (excluding employees)
Script to find new contributors from bug list
Volunteers that fixed more than one bug

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

New contributors (🌟 = first patch)

 Anthony Mclamb: Disable the legacy Edge migrator
 Amin Amir

🌟Fix browsingContext.sys.mjs to assign to #contextCreatedHandled instead of contextCreatedHandled
Fix missing WITHOUT ROWID SQLite performance optimization in SERPCategorization.sys.mjs
🌟 Amine Zroual: Omitted maxResults property not handled correctly in getRecentlyClosed


any1here: install_sig_alt_stack incorrectly checks mmap’s return value
🌟 Armin Ulrich: Fix MessageHandlerRegistry.sys.mjs calling getExistingMessageHandler with an unused second argument
japandi

Cannot remove amazon.com from top sites list
The height of the pinned tabs area should be responsive to the number of pins
Use cenum for nsIHelperAppLauncherDialog reason constants to enable better typescript annotations


Nathan Johnson [:narjoDev]: Remove browser.display.use_system_colors pref
DrSeed

Firefox shows vertical tabs in new windows despite “Hide tabs and sidebar” setting
The “Expand sidebar on hover” option is not kept after the vertical tabs are disabled and enabled again


Keji Bakare:

Split view’s focus-outline is clipped on the right side of left tab
White space on the right side of left panel in split view


🌟 gotyaoi: Reload toolbar button is active on about:newtab
Itoro James: [A11y][Keyboard Navigation]Cancelling a note via Keyboard Navigation still saves it
John Iweh: The notification dot is not displayed if the tab is in a Split View
🌟 John Iweh: sidebar-shown attribute remains when sidebar.revamp is false
🌟 jonathancabera:

The Move tab to Split View option is also displayed for the tabs that are within the Split View
A Note with long text (1003 characters) is saved by pressing ENTER even if the “Save” button is disabled
Tab group guide line becomes disconnected under certain conditions related to split views in vertical tab mode


Aloys: Remove logic that forces distribution language packs to be reinstalled when upgrading from Firefoxes older than 67
liz:

Create test to ensure maxRenderCountEstimate is never being set to Infinity in virtual-list component in Fx View
Button accessible name does not convey its function: missing topic context (Settings dialog > Topics dialog > buttons Following/Unfollow/Blocked/Unblock)


Mary cathline: Tab Group Label does not respect touch density in vertical tab bar
🌟 Brandon Lucier: Popups opened with window.open give window type normal instead of popup
karan68: [dialog] New Shortcut dialog needs a label/accessible name
🌟 Vector: Button does not programmatically indicate that it opens a dialog (Recent activity section > story card > ••• disclosure > Delete from History button)
🌟 Osoble: Update font size and weight for synced tabs device name headers in Firefox View
konyhéa:

Add test for sync admin disabled to browser_syncedtabs_errors_firefoxview.js
Check all second paramaters for TestUtils.waitForCondition in Fx View test files
Recently Closed Tabs, Tabs from Other Devices, and History pages should have Cmd / Ctrl + Click on a link open the link in the new background tab.


Noble Chinonso: #shouldHandleEvent in SidebarTreeView.js compares event.keyCode to string values, causing Home/End keys to never be handled
Pranjali Srivastava: Add a test to verify that the space above tabs is consistent across PB, LWT and sizemode (where appropriate)
Okhuomon Ajayi:

More spacing is needed between the tab note icon and the close icon on the tab
The tabs in vertical mode collapsed state are positioned differently in Split View
Keep vertical split view tabs stacked vertically even when the sidebar is expanded when expand on hover is enabled
Vertical split view tabs can be too big or small when tabs are overflowing


🌟 Rishan: Fix duplicated arrow function in browser_history_sidebar.js
Chukwuka Rosemary:

“Forget About This Site” context menu option missing from Firefox View history
Long strings are not displayed properly on the about:opentabs page search filed
Add test for Forget This Site option in Fxview history context menu.


ROSHAAN:

🌟Tab note background colour is incorrect for default light theme
 [win/linux] The splitter between content areas does not match Figma spec
Fix typo in OpenInTabsUtils.confirmOpenInTabs()


Sameeksha: Disclosure button expanded/collapsed state not programmatically defined (Customize button)
kofoworola shonuyi:

🌟Actually hide or remove sidebar-shown attribute when in fullscreen.
Add a test for checking sidebar-shown attribute in fullscreen mode


🌟 Sayd Mateen: Page URL is displayed as tab name when page’s contains about:reader?
 


Oluwatobi:

Unable to delete selected history entries from sidebar
Incorrect Sidebar button state/tooltip hover text
The city name heading level doesn’t follow the correct heading level order


Nishchay [:nish]: Unable to add tabs to old closed tab groups (tabGroupState.splitViews is undefined)

 
Project Updates
Add-ons / Web Extensions
Addon Manager & about:addons

In preparation for the Project Nova restyling of the about:addons page, we have refactored about:addons into separate per-component ES modules, splitting the monolithic aboutaddons.js and aboutaddons.html into 16 dedicated component files under components/ (with no behavior or UI changes) – Bug 2032014

NOTE: if you have working on patches with changes to about:addons internals it is very likely you’ll need to rebase and solve merge conflicts hit on top of this refactoring, the internals are still largely the same as before but don’t hesitate to reach out to the Addons team if you have doubts / questions or need help to figure out how to adapt your patch of top of these changes



WebExtensions Framework

Fixed exportFunction to preserve the constructibility of the wrapped function instead of unconditionally making all exported functions implicitly as constructors – Bug 2033173

Thanks to Gregory Pappas for contributing this improvement to the Content Scripts’ Xray Wrappers helpers!


Fixed a Firefox 151 regression where extension content scripts accessing location.ancestorOrigins caused subsequent page script reads of the same property to fail with “Permission denied”, breaking sites like Gmail – Bug 2034329

Thanks to Simon Farre for promptly investigating and fixing this recent regression!



WebExtension APIs

Updated sessions.getRecentlyClosed() to remove the hardcoded cap when maxResults is omitted – Bug 1392125

Shoutout to Amine Zroual for contributing this enhancement to the sessions WebExtensions API!



DevTools

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




Hubert Boma Manilla (:bomsy) is making good progress on migrating the Console to CodeMirror 6 (#2032758, #2026569)

Fluent

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


Migration Improvements

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

New Tab Page

Nova for New Tab has ridden the trains to Beta! It will be enabled by default, globally, when Firefox 151 goes out to release on May 19th

It’s possible that we’ll do a train-hop coupled with an experiment to enable HNT Nova for a few clients a bit earlier.


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

Search and Urlbar

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

Smart Window

uplifted 10 bugs to 150.0.1 dot release addressing initial user feedback from diary study and Connect

jump to bottom of conversation 2028692
stop streaming button 2029204
back/forward navigation from assistant 2029229
dark mode for various chips 2024499


search engine switching from smart bar 2021973
Nova styling within smart window 2026794

Storybook/Reusable Components/Acorn Design System

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

UX Fundamentals

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

Settings Redesign

Tim converted settings related to Accessibility page to config-based pane Bug 1968116 – Convert settings related to Accessibility page to config-based settings
Benjamin converted Privacy & Security page to the config-based pane Bug 1968112 – Convert settings related to Privacy & Security page to config-based settings
Finn integrated Firefox Labs page into setting-pane config Bug 2021047 – Integrate Firefox Labs page into setting-pane config
Anna converted Firefox Updates section to config-based prefs Bug 1990961 – Convert Firefox Updates section to config-based prefs
Mark Kennedy added moz-promo, that is welcoming users to the redesigned settings Bug 2015093 – Add a moz-promo to welcome users to the redesign




Anna added possibility to search for actions in the redesigned “Applications” section Bug 2020370 – It’s no longer possible to search for actions in the new “Applications” section
Anna fixed the Settings navbar layout breakage



Firefox Nightly: More Kit, More Control – These Weeks in Firefox: Issue 203
Sat, 25 Jul 2026 08:37:32 +0200
Highlights

James enabled adaptive autofill in Nightly for testing, which we believe should provide better results in the URL bar when doing autocomplete!
Jack updated the illustrations shown on some of our error pages to match the latest approved designs, giving users more polished artwork when the browser encounters connection or security errors!



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


 

We’ve disabled the CSS filter implicitly applied to WebExtension pageAction SVG icons across all release channels starting in Firefox 152, completing the deprecation

NOTE: The blog post published at WebExtensions API changes in Firefox 149-152 provides to extensions developers more details about this deprecation and links to the related MDN docs.



Friends of the Firefox team
Resolved bugs (excluding employees)
Script to find new contributors from bug list
Volunteers that fixed more than one bug

Amin Amir
Pranjali Srivastava
Sam Johnson

New contributors (🌟 = first patch)

 🌟:23rd: Regression: The new swipe-to-navigation indicator stucks for a moment, when deciding not to navigate the other page
🌟Akeem Omosanya: Remove commented-out code in SearchService.sys.mjs
Amin Amir:

🌟Fix browsingContext.sys.mjs to assign to #contextCreatedHandled instead of contextCreatedHandled
Fix missing WITHOUT ROWID SQLite performance optimization in SERPCategorization.sys.mjs


🌟Sahaj: Suggest the default target language for translation after changing the detected source language
🌟JIANG Zhirui: Breakpad build failed on Windows using VS2026 due to removal of stdext
 John Iweh: Add “Open in New Tab” and “Open in New Container Tab” options to the context menu for Tabs from Other Devices
Jak: Bookmarks and History – should respect the “When you open a link, image or media in a new tab, switch to it immediately” setting
🌟Andy [:rgbcmy]: Autoplayed next video should also be PIP
 konyhéa: “Escape” key should collapse the expanded on hover sidebar launcher even if hover is still active.
 Pranjali Srivastava:

Remove icon property from sidebar extensions
Show language-agnostic SelectTranslations context menu item when the source and target languages are the same



Project Updates
Add-ons / Web Extensions
Addon Manager & about:addons

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

WebExtensions Framework

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

WebExtension APIs

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

DevTools

Andreas Farre improved the Session History tab in the Application panel (still behind devtools.application.sessionHistory.enabled)

added support for remote debugging (#2014064, #2016121)
made sure that calls to History.replaceState are reflected in the UI (#2037359)


Julian Descottes [:jdescottes] fixed the most frequent DevTools crash we were observing in Telemetry, adding a guard against IDBTransaction errors when retrieving breakpoints in the Debugger (#2030260)
Nicolas Chevobbe [:nchevobbe] fixed the image preview tooltip for relative URLs images in constructed stylesheet (#2035503)
Julian Descottes [:jdescottes] reduced the overhead we had because of network requests monitoring by only decoding response content when the user actually want to see the response (#2026228)

WebDriver

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

Lint, Docs and Workflow

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

https://arewemozsrcyet.com/



New Tab Page

We did our first region-specific trainhop on May 11th (just 15% of the US), and turned on HNT Nova (and sometimes Widgets) for those clients to get some advance-data of its behaviour in the wild! A note that HNT Nova gets turned on for everybody when Firefox 151 ships on May 19th.

We’ll be launching a similar experiment in the DE, probably on May 12th, also at 15% population.


Most of the team is heads down building out a sports-tracking widget, attempting to get that ready in time to be generally available for the upcoming World Cup event.
Dre landed a new world clock widget, which is currently off by default, but pretty snazzy!


Search and Urlbar

Nova (URL Bar Design Refresh)

Drew and Daisuke continued their work on Nova styling for the Address bar (input and view).


Search and Suggest

Drew finalized two bugs for World Cup and sports suggestions, which were landed and uplifted: one to update the localization string for scheduled games and another to show both teams’ icons in suggestions. Drew also landed and uplifted a fix for rich search suggestion icons being forced into a square aspect ratio.
Standard8 updated Ecosia favicons to the latest branding, including QA testing and publishing.


Settings Redesign (SRD)

Stephanie landed a test to ensure search suggestion settings are hidden when quicksuggest is disabled, as well as a patch to resolve TypeScript issues in search.mjs, and is adding test coverage to confirm removed search engines are not displayed in the default engines dropdown.


General URL Bar and Component Updates

Daisuke landed implementation of the context menu on URL bar results, and a fix to show the loading URL in the URL bar when starting up with a homepage.

Marco is working on several tasks, including a PDF download / focus stealing issue and allowing arrays to be bound in Sqlite.sys.mjs. Marco also worked on fixes related to Places, such as avoiding replacing the favicons database if it is not corrupt.


Standard8 finalized the URL bar test manifest split. Standard8 also upgraded us to TypeScript 6.
Moritz landed a fix for URL bar abandonment telemetry being recorded when clicking an engine in the unified search button popup (Bug 2032973), which was also uplifted. Moritz also simplified search mode switcher item activation in tests, and made it so that the unified search button popup closes when installing an open search engine.



Smart Window

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



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

Storybook/Reusable Components/Acorn Design System

Nova token updates occasionally, focused on SRD

UX Fundamentals

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

Settings Redesign

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






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



Hacks.Mozilla.Org: PACT: Anonymous Credentials for the Web
Sat, 25 Jul 2026 08:37:27 +0200
This is the technical companion to our update on Distilled, “Keeping the web open and private in the bot era.” Here we take a deeper look at the problem space, the design we’re proposing, and the problems still left to solve. 
Bots (and privacy-preserving browsers) not welcome 
Browse a news site in a private window. Shop at a major retailer with a VPN. Visit a video streaming platform with anti-fingerprinting defenses tuned up. You’ll see the same responses: registration walls, block pages, and endless CAPTCHAs. The message is clear: if we think you might be a bot, you’re not welcome. 
Websites have valid reasons for wanting to block bots. Bots enable volumetric abuse, abuse that wouldn’t otherwise be feasible if they had to be carried out by humans.  For example: SEO comment spam, credential stuffing and DDoSing. Consequently many sites employ dedicated anti-abuse tooling which aims to keep the bots out whilst minimizing friction for human visitors. 
Unfortunately, that tooling is increasingly failing at both tasks. Browser privacy protections are dismantling the passive signals that anti-abuse systems depended on to identify and distinguish visitors. Meanwhile advances in generative AI have rendered CAPTCHAs ineffective: bots now solve them faster and more reliably than humans. 
Many sites are switching to more invasive mechanisms and now ask visitors to disclose identifying information, e.g. an email address, a federated login or disabling their VPN. This means greater friction for users, since providing these details on a first visit takes time. It also compromises their privacy, since these details enable the same kinds of cross-site tracking that browser privacy protections were intended to mitigate. 
This leaves users with a dilemma. The more effectively they protect their privacy, the harder it is for websites to distinguish them from bots and the worse the treatment they receive. Website operators are also suffering. The additional friction they inflict upon well-behaved visitors harms their site, but many are willing to pay the costs if it mitigates volumetric abuse. 
Browser-based AI agents make this tension more acute. Sites may want to allow agents which are acting on behalf of individual users while blocking agents engaged in volumetric abuse. However, with no effective mechanisms to distinguish the two, websites are opting to block both. That hurts users, who should be free to choose the user agent they use to access the web; it hurts new browsers and agents, which struggle to interoperate; and it hurts sites, which lose legitimate visitors.
The consequence is that the web gets worse for everyone. Users get more friction or less privacy or both. Website operators see more volumetric abuse and the friction they add drives away users who would otherwise want to consume their content or services. New user agents struggle to access the same content as conventional browsers. 
The Costs of Convenient Solutions
Some large ecosystem players have put forward solutions that leverage their control of the dominant operating systems and their deep integration with consumer hardware. These rely on device attestation: identifiers and privileged code baked into devices at the hardware level, which let manufacturers prove what software is running on a user’s device. Exposing this functionality to the web means attesting to sites that the user is running approved software with trusted hardware and therefore isn’t a bot. There have been two substantive proposals.
Google’s Web Environment Integrity, abandoned in 2023, was the blunt version. It attested to the user agent itself, as well as the operating system and device in use. Users would have lost control in two ways: once to the attester, which would decide which operating systems and devices could be blessed, and again to the website, which would decide which software to accept. If sites had adopted allow-lists of approved user agents, building a new browser would have become virtually impossible, and sites could have withdrawn access from any user agent they chose.
Apple’s Private Access Tokens, deployed across their ecosystem in 2022, have more subtle issues. Built on the Privacy Pass protocol standardized at the IETF, they get a lot right: a user receives a renewed, limited batch of one-time tokens that can be presented to websites without linking their visits together. This provides privacy for users and has shown rate limits to be an effective tool for sites – both points we’ll return to later in this post.
However, Private Access Tokens rely on device attestation, requiring that the hardware manufacturer be in overall control of the user’s device. Presenting a PAT tells a website you are locked into Apple’s rules for what counts as acceptable software. Due to PAT’s technical design^[1], there’s no way to open the system to other sources of scarcity without compromising the system’s privacy properties, meaning that if more widely deployed, access to the web would become tied to having bought expensive hardware from a small, hard to change set of vendors. 
Both approaches are ultimately hostile to users and to the openness of the web. Both are premised on parts of a user’s device that sit within the manufacturer’s control and beyond the user’s own. Were they widely deployed, the web would become just another walled garden with centralized gatekeepers controlling acceptable hardware, operating systems and software. As convenient as these solutions are for the players who already dominate the ecosystem, we think there’s a better path.
A Better Path Forward 
Bots’ harms arise from their ability to operate beyond human scale. For sites to prevent volumetric abuse they don’t actually need to know the user’s identity or receive cryptographic proof that they’re running approved software. If sites knew their visitors were restricted to a rate limit set by a site, that would be enough.  
Rate limits only make sense if they’re tied to something scarce; something an attacker can’t cheaply replicate to evade the limit. Without anchoring to a scarce resource, like the trusted hardware used in Private Access Tokens, attackers can generate as many fresh identities as they need to bypass the rate limit. 
However, hardware is just one option for scarcity. Anything a user already has that an attacker can’t trivially spin up at scale will work: email addresses and phone numbers are naturally scarce. A paid subscription costs an attacker the same as a real user.  Even maintaining an account on a free service requires some non-trivial work. 
What if we could use these scarce signals across the web? We could build an open ecosystem with many parties offering scarcity signals, each site choosing which to accept. By opening up who can provide a signal, and letting sites choose which to accept, we can avoid transferring control to device manufacturers and the resulting harms. 
As a concrete example of who might be well positioned to provide such a signal, we can consider VPN providers acting as a subscription service. Sites routinely block VPN users indiscriminately, whether through a deliberate policy choice or through an indirect consequence of rate limiting visitors per IP address. But a VPN subscription is a perfect source of scarcity. If the VPN provider could vouch for its users so that sites could rate limit each user individually – then users would be able to browse the web with less friction and without giving up their VPN usage. 
The catch is that building a system that can enable this on the open web whilst maintaining user’s privacy is genuinely difficult. It requires that we take information from one site — that this user holds some scarce thing — and expose it to other sites so that they can use that as the basis for their rate limiting. Letting one site verify a signal from another is the sort of information flow that privacy-preserving browsers have spent the last decade locking down to prevent cross-site tracking. 
Our goal would be that no more than the minimum information gets through: a single bit communicating whether the user is below the rate limit set by the site. Leaking anything more – like the source of the scarcity that the rate limit is anchored to – would be unacceptable. Enabling a new cross-site information flow might feel like compromising privacy to gain better access, but reality is more nuanced. If a new system moves sites away from demanding that visitors be identifiable (whether through fingerprinting or login forms), it can be a win for both privacy and access.
The Foundations 
The good news is that the cryptographic foundations for a privacy preserving approach already exist. The Privacy Pass protocol, originally developed in 2018 to reduce the friction of Cloudflare CAPTCHAs for Tor users, introduced the core primitive: a token that is unlinkable between issuance and redemption. You prove something to an issuer (e.g. by solving a CAPTCHA), receive some tokens, and later present a token to a website. The website can verify the token is legitimate, but can’t link it to the user it was issued to. 

Figure 1: In Privacy Pass, a CAPTCHA provider can issue tokens to a client which can then be used to bypass challenges for future site visits. Even if the CAPTCHA provider and sites collude, they can’t use the tokens to identify the user or their browsing history. 
Privacy Pass has gone on to be successfully deployed in systems where the issuer and verifier have a prior trust relationship: Apple uses it to authenticate users of Private Cloud Compute and Private Relay without linking their activity to their identity, Chrome uses it for two-hop IP protection, and Kagi uses it to provide private search. These deployments work in part because a small number of parties have agreed in advance on who issues tokens and who accepts them. 
Applying this approach to an open system where any site can act as an issuer brings real challenges. Firstly, even though tokens are unlinkable, knowing a user has access to a specific issuer is a privacy leak on its own, because you can infer that the user meets the relevant issuance criteria. If one site can learn that you have a token from another site, that reveals that you have been to that site, which can be a major privacy problem. This compounds if sites can learn the set of issuers you have visited, since it becomes a fingerprint which can be used to identify you. 
Generic techniques exist for proving a statement in zero knowledge: we can prove that a client has a token from a set of acceptable issuers without revealing which specific issuer it is. We’ll call this issuer blinding. The generic approach is often slow, but bespoke approaches tailored to the underlying cryptography can improve this considerably. 
Another challenge is how sites using rate limits decide who to trust to issue tokens. If an issuer misbehaves then the site’s rate limits become ineffective, enabling volumetric abuse. However, if we need to prevent the site from learning which issuers a user has access to, the site is only going to know that one of its trusted issuers was used, not which one. This makes mistakes or misbehaviour by an issuer difficult to detect, and makes it hard for sites to evaluate new issuers. Solving this challenge is essential for openness. Without adequate information, sites are likely to lean towards conservative issuer selection. That could lead to less choice between Anchors, which in turn could lead to a new form of gatekeeper being created. 
To solve this, sites at least need a way to calculate an aggregate score for each issuer they use. This should roughly correspond to how much of the traffic it considers abusive to have come from users using that particular issuer. Mozilla has long invested in systems like Prio which use multiparty computation (MPC) to protect user privacy whilst enabling aggregate measurements of system behaviour. 
Privacy Pass also struggles to handle dynamic adjustments to rate limits. Once tokens have been issued, they’re difficult to invalidate without either revoking all active tokens or risking attacks which can compromise the privacy of users. It’s also beneficial if sites can adjust rate limits on a per client basis, for example by increasing rate limits where they become more confident the client is benign and withdrawing access when abuse is detected. 
Anonymous Credit Tokens offer a useful building block to solve this problem. Conventional Privacy Pass schemes rely on issuing a bucket of tokens but ACT works differently by enabling the use of a credential with state. For example, an ACT credential can hold an internal counter. When the credential is presented, the site can check the counter is over some threshold and mutate it, increasing or decreasing the counter whenever the site’s perception of the holder has improved or worsened. Critically, the exact value is never leaked to the site, preventing the site from tracking the holder and ensuring successive presentations of the same credential can’t be linked. 
Putting it together 
So how can we combine these techniques to build a system which can enable privacy-preserving rate limiting on the open web? In May 2026, we participated in a W3C CG Meeting in collaboration with Cloudflare, Chrome and other web stakeholders in which we started sketching out a design we’re calling PACT – Private Access Control Tokens. 
Rate limits need a starting point, a source of scarcity to anchor on. We’ll call an entity that provides such a source an Anchor. To a user who meets the Anchor’s criteria, like having a subscription, an account in good standing, or a verified phone number, an Anchor issues a batch of Endorsement tokens, following the Privacy Pass model. In practice, Anchors could be any website which has access to this kind of signal. An Endorsement conveys scarcity to other sites. 
That’s enough for a simple system where access is either granted or denied. But as we discussed earlier, we also want the ability to increase access where a visitor behaves benignly and decrease it where they don’t. The state needed to enforce a rate limit can’t live in the Endorsement, because Endorsements cross trust boundaries between unrelated sites. We need a second object that can hold that state, scoped to the party that maintains it. 
We’ll call that the party that handles rate limiting for a site a Moderator and the stateful object a Credential. A Credential is specific to a Moderator and, unlike endorsements, we limit each site to nominating a single Moderator. In the common case the site itself plays the Moderator role, so there’s no new entity or trust boundary. A Moderator can also be a third-party service shared across many sites, allowing those sites to cooperatively share a rate limit. 
In the terminology of the previous section, the Anchor is the issuer of Endorsements, and the Moderator both verifies Endorsements and issues Credentials. A Moderator manages rate-limit policy: it decides which Anchors it trusts, accepts their Endorsements, and issues a Credential in return.

Figure 2: (1) Clients acquire Endorsements from Anchors in the course of normal browsing to sites they have relationships with. (2) Clients can exchange Endorsements for a stateful Credential from a Moderator. (3) Credentials can be used to access sites which use that Moderator. Credentials can be updated over time. 
Directly revealing which Anchor backed an Endorsement would leak a lot of information about the user. The issuer blinding techniques from the previous section solve this: when an Endorsement is redeemed, the Moderator only learns that it came from one of the Anchors it trusts, but not which one. 
When a Moderator covers more than one site, we let Credentials be presented across all of them but partition cookies and storage as we would for any other third party site. The unlinkability of Credential presentations keeps this from creating a new cross-site identifier. The benefit is that good behaviour on one site improves access on every site the Moderator covers, and bad behaviour cuts it everywhere. Websites can already build the same capability with a shared account system, so this doesn’t create a new way to lock users out, but it does provide a new way to grant access without requiring users to give up their privacy. 
Enabling Moderators that cover many sites carries a centralisation risk, similar to the concentration we see today in anti-abuse providers. The mitigation is that the choice of Moderator stays with each site, and the choice of trusted Anchors stays with each Moderator. This can’t reverse the centralisation pressure the web already faces, but it ensures this system won’t lead to additional lock-in: a new Anchor or a new Moderator can be adopted without coordinating with a dominant vendor. 
The system then has three flows. First, the user receives Endorsements from an Anchor in the course of normal interaction, based on the Anchor’s positive view of the user. This is a relatively rare operation for any given user and Anchor. After all, as our source of scarcity, Endorsements should not be too easy to accumulate.

Figure 3: In the course of normal browsing, clients browse to websites they have a relationship with. These sites can act as Anchors by issuing Endorsements to clients.
Second, when the user arrives at a site that works with a Moderator, the browser spends an Endorsement from an Anchor the Moderator trusts and receives a Credential in return. The presentation hides which Anchor was used, and neither the Anchor nor the Moderator can trace the Endorsement back to where it was issued. The Moderator decides what initial balance the Credential starts with. If the user has no Endorsements from suitable Anchors at all, existing mechanisms (CAPTCHAs, account creation, federated login) could be used to bootstrap a Credential the same way, so the system degrades to today’s experience rather than locking the user out.

Figure 4: When the client browses to a site, it can prompt the client for a Credential from the Moderator it uses. If the Client doesn’t have a suitable Credential, but does have a suitable Endorsement, it can exchange it for a Credential with the Moderator. In practice, the Moderator and the Site might be the same server.  
Third, as the user browses, the browser presents the Credential and the Moderator updates the internal state of the Credential. The Moderator can reward behaviour that looks benign and penalize suspicious activity, but can’t track the use of the Credential or identify it if it’s used on other sites the Moderator covers. Revocation falls out of the same mechanism: a Moderator can refuse to return an updated Credential. 

Figure 5: The Client can present the Credential on sites which use the matching Moderator. Sites can check if the Credential is in good standing. The sites can then adjust the access the Credential has in response to behaviour. E.g. increasing it when they gain confidence in the client or reducing it in response to malicious behaviour.
In practice, all of this would happen transparently to the user through a WebAPI that sites acting as Anchors or Moderators would call from JavaScript. In an ideal ecosystem, users would accumulate Endorsements through normal browsing, just by virtue of the sites they already visit, and the rest of the flow would happen in the background as they move around the web, leaving users with meaningfully less friction. 
AI agents acting on behalf of a user slot into the same flow. An agent can carry its user’s Credentials, in which case the user remains accountable for how the agent behaves. Sites would not need to grant any more access than they would to the user themselves. Alternatively, the operator of an agent can run its own Anchor and vouch for its agents the way other Anchors vouch for human users. Sites retain control over which Anchors they accept, so they can choose how to treat agent traffic without needing a separate detection mechanism. 
Several mechanisms combine to keep the information about a user that flows out close to a single bit. Cryptographic unlinkability ensures successive Credential presentations cannot be tied to each other or to the original issuance, so a user’s visits cannot be joined into a history. Each site is bound to a single Moderator, so the set of Moderators a user has Credentials with never becomes a cross-site fingerprint. The Anchor-to-Credential exchange happens in an isolated browsing context, so during ordinary browsing the only thing the site or its Moderator ever observes is a Credential presentation: the site only learns if the user has a valid Credential below the rate limit, or nothing. When the Moderator updates a Credential, it adjusts the credentials state without learning what it is.
The additional privacy given to users from Issuer blinding makes participating in the system more challenging for Moderators. Because the Moderator can’t see which Anchor backed a Credential at issuance, it can’t give a Credential from a strong Anchor more access than one from a weak Anchor: doing so would itself leak which Anchor was used. The initial access has to be uniform across the Moderator’s whole pool of Anchors, which in practice means setting it at the strength of the weakest. However, this is only relevant for that initial access, the Moderator can update credentials according to the holder’s behavior, enabling Credential’s to accrue access over time.
Building an open ecosystem also requires that sites can make effective decisions about the Anchors they choose to trust. Multiparty computation systems like Prio enable aggregate scoring without compromising privacy. When users present Credentials, they can provide an encrypted share which identifies the anchor they used and can be privately aggregated to compute the quality of an issuer.
Next Steps 
We think the architecture we’ve sketched for PACT has the right shape, but many of the details still need to be worked out and the entire system needs rigorous privacy and security analysis.
We want to do that work in the open. The IETF is the natural venue for the cryptographic protocols underneath, and the W3C for the WebAPI surface that sits on top. We’ll be bringing draft specifications to these bodies as soon as they’re ready, and we welcome collaborators from across the ecosystem: browser vendors, site operators, anti-abuse providers, and the cryptography community. 
If successful, we think we can provide a system which will keep the web open and private, while still giving sites the rate-limiting signal they need. 
Acknowledgements
The ideas described here are the result of collaboration and conversations with many people, including: Watson Ladd, Thibault Meunier, Michele Orrù, Trevor Perrin, Eric Rescorla, Samuel Schlesinger, Martin Thomson, Eric Trouton, Benjamin Vandersloot & Cathie Yun.  


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

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


The Rust Programming Language Blog: The many journeys of learning Rust
Sat, 25 Jul 2026 08:37:24 +0200
This is another post in our series covering what we learned through the Vision Doc process. We previously described the overall approach and what we learned about doing user research, we explored what people love about Rust, dug into what it takes to ship safety-crticial Rust, and described some of the major challenges that people face when using Rust.
In this post we walk through what folks have found on their journey to learn the Rust programming language with ups and downs covered.
As a disclaimer, LLMs (Large Language Models) come up in this post because our interviewees brought them up. We're scoping discussion to their use as a learning tool, covering research and example generation, not broader questions about AI (Artificial Intelligence) in software development.

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

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


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

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

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

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


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

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

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

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

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

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


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

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

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


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

The compiler as teacher
Rust's diagnostics did the teaching on their own, especially around lifetimes.

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


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


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

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


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


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

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

The experienced Rust developers we spoke with consistently said the same thing: clone freely while you're learning, then optimize when you understand the problem. Rust's reputation for performance and correctness feeds this. Newcomers assume anything less than optimal is wrong before they've written a first working program, and clone guilt is how that shows up.
We think it could be an interesting area of future study to check into the patterns Rust programmers employ at different levels of experience and under which circumstances. One member of the Rust Vision doc team that's very experienced with Rust noted that there's kind of an "expected shape" they understand as passing the compiler. This knowledge influences how they approach writing code which wouldn't take that shape and they naturally find themselves understanding when to use so-called workarounds, such as passing around indices into arrays or Vecs.

Multi-paradigm, but not the OOP some are used to
The Rust programming language is multi-paradigm, and how that lands depends on what you're coming from. We heard some that came from a functional background were delighted with digging into learning how much Rust inherits from that lineage. Some others noted that they and others on their teams struggled to unlearn the object-oriented style they'd come to use heavily in other languages like C++ and Java.

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


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

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

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


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


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

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

The C cohort leaned on LLMs for the project in ways the Rust cohort couldn't. We don't yet have a clear answer for why.
What did come through clearly was the Rust cohort's experience with the community. Some students needed to figure out which drivers to use for the embedded project and how to use them. Their professor encouraged them to open issues and ask questions directly on GitHub, and the maintainers responded. Students who had never contributed to open source before were getting answers from the people who wrote the code.

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

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


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

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

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

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

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

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

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

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


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


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

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

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

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

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


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

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

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

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

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

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

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

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


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

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

Survey Respondent A went on to share in a more detailed response about a perceived weakness in Rust learning materials related to lifetimes and the borrow checker are explained. There was an observation that it's fairly easy to run into more complex situations with lifetimes and the borrow checker. They felt that the current state of this sort of material and tutorials is fairly superficial and can leave learners stuck when they run into those more complex situations.
One respondent that bounced once and came back shared challenges around usage of async. In concert with Rust's memory-safety and the borrow checker, they found some of the nitty-gritty details of async were difficult to learn. While we're aware of the Rust Project's continuous efforts to improve Rust's async story, this is another data point of a user that faced challenges.
Another survey respondent shared how they had multiple times bounced in trying to learn Rust. They returned after a year or so and found Rustlings to be highly motivating. We note that having multiple pathways for folks to learn Rust opens up more possibilities for those that nearly bounced, just like this person.

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

Conclusions
Across these conversations, the experience of learning Rust depended heavily on context. Why someone was learning and what support they had mattered as much as the borrow checker. The same kinds of examples kept coming up: a training course that got a team to a shared baseline, a maintainer answering a student's first GitHub issue, and a colleague whose code showed that cloning was okay.
That context is largely something the community has a hand in. With that in mind, here is what we take away from what we heard, and what we still don't know.

What seems worth trying
Learning materials aimed at unlearning. Syntax barely came up when people described their struggles. People struggled with unlearning habits from previous languages, whether OOP structuring from C++ and Java or the instinct to grab a raw pointer to a peripheral. Most of our learning materials teach Rust from first principles, and that works. What we didn't come across is much written for, say, the engineer with ten years of Java who lands on a Rust team after a reorg: material that names the patterns they'll reach for that won't transfer, and shows what to do instead. The professor we spoke with did a version of this in the classroom, leaning on "traits are like interfaces in Java" and saving generics for later in the course, and the students did fine. Something similar could work outside the classroom too.
Put the "clone freely while you're learning" advice somewhere official. Every experienced developer we spoke with gave the same advice, but learners seem to mostly pick it up by accident, like the researcher who happened to see someone else cloning the struct they had been carefully threading lifetimes through. Saying it early in official materials would take some of the steepness out of the curve. The broader version belongs there too: idiomatic Rust doesn't have to mean optimal Rust, especially on a first project.
Diagnostics are already a primary learning resource: several people told us the compiler taught them lifetimes before any documentation did. Diagnostics reach learners right at the moment they're stuck. When writing new ones, it seems worth keeping the confused newcomer in mind alongside the expert, because for a lot of people this is where the learning happens.
Is "the book" actually out of date? Whether or not The Rust Programming Language or other materials are actually behind, a team evaluating Rust looked at its repository, saw unresolved issues and unmerged PRs, and moved on. As more companies evaluate adoption, more people will look at these materials with the same fresh eyes. Visible issue triage and some communication about what's current and what's planned would address the perception, separately from whatever content work may or may not be needed.
How stuck learners get treated is shaping who stays. We heard about students getting answers on GitHub from the maintainers who wrote the code, and we heard about learners being told their struggles were a skill issue. The first group came away with a lasting good impression of Rust. Some of the second group walked away entirely, and because they leave quietly, it's easy to underestimate how many of them there are. The welcoming side of the community came up unprompted as a reason people stayed, so we know it makes a difference when we get this right.
Every organization we spoke with described essentially the same ramp-up for bringing a team to Rust. Teams that brought groups of developers to Rust described roughly the same approach: get everyone to a shared baseline with a training course or with The Rust Programming Language and Rustlings, start people on lower-risk tickets, and give them somewhere internal to ask questions. Several organizations also found that hiring developers without Rust experience and ramping them up worked out better than continuing to search for rare expertise in another language. None of this is complicated, and teams weighing adoption don't need to invent a training program from scratch.

What we still don't know
The biggest gap is the people we didn't reach. Nearly everyone we spoke with stuck with Rust long enough to be reachable through Rust channels, so the stories of bouncing off came to us second-hand: a friend who walked away from embedded Rust, colleagues who quietly stopped after the responses they got. As we wrote in our first post, finding people who decided against Rust takes targeted outreach. If the proposed User Research team comes together, talking with learners who bounced would make a good early project, and learning is probably the area where that research would teach us the most.
We also don't know what to make of LLMs as a learning tool yet. They came up as a search engine, as an example generator, and in one organization's case as something that makes training high school graduates into working Rust developers possible. We saw a classroom where the C cohort leaned on LLMs in ways the Rust cohort couldn't, and we don't have an explanation for it. All of this comes from a handful of conversations, so we treat it as a set of leads to follow up on. Given how quickly the tools are changing, it seems better to study this deliberately than to wait and see what folklore develops.
The folks we spoke with showed that people do get there: with enough passes through the materials and enough code written, it eventually clicks. The opportunities above are mostly about making it work for the people who didn't pick Rust on purpose, and for the ones who would have stuck around if their early experience had gone a little differently.


The Rust Programming Language Blog: crates.io: development update
Sat, 25 Jul 2026 08:37:18 +0200
Another six months have passed since our last development update, and the crates.io team has been busy. Here's a summary of the most notable changes and improvements made to crates.io since then.

Source Code Viewer
Crate pages now have a "Code" tab that lets you browse the contents of published crate versions directly on crates.io. This shows you the exact files that cargo downloads when you add a crate as a dependency, which might differ from the linked repository. This makes it much easier to audit your dependencies, including files that never appear in the repository, like the normalized Cargo.toml files that cargo generates.

The viewer comes with a file tree sidebar with search functionality, syntax highlighting, and GitHub-style line selection, where clicking or dragging line numbers produces shareable #L10-L20 URLs.
Under the hood, the server now builds a zip file for every published version. Since the .crate files that cargo consumes are gzipped tarballs without random access support, a background job re-packs each of them into a seekable zip archive plus a JSON manifest describing the contained files. Both are served from our static CDN. The frontend then fetches only the manifest and loads each file on demand with an HTTP range request. Because of this architecture, browsing crate sources essentially adds no load on the crates.io API servers. Existing crate versions have been backfilled, so this works for old releases too.
The rendering library behind the code viewer is a diff renderer at heart, and that's no accident: a version-to-version diff viewer built on the same infrastructure is currently in the works. This will allow you to review exactly what changed between two published versions, right on crates.io. Stay tuned!

Untangling crates.io Accounts from GitHub
At the end of May, the crates.io team accepted RFC #3946. Crates.io accounts always have been tightly coupled to GitHub: signing in means "Log in with GitHub", and your crates.io identity is your GitHub username. The RFC changes that. It introduces usernames that are native to crates.io and independent of linked GitHub accounts, as a prerequisite for eventually supporting login via other identity providers.
The implementation of crates.io usernames has started, but there is still a lot left to do, most visibly the ability to change your crates.io username. After that is complete, there will be future RFCs and implementation for signing in with identity providers other than GitHub. Since all of this touches authentication and account security, we are deliberately taking it slow and rolling these changes out in small, carefully reviewed steps.

Advisories and Suggestions
In our January update we introduced the "Security" tab, which shows security advisories from the RustSec database. We have since taken this integration one step further: crates that RustSec has flagged as unmaintained now show a warning banner directly on their crate pages, linking to the corresponding advisory for details and possible alternatives. Thanks to Dirkjan Ochtman for implementing this feature!

Related to this, some popular crates have been largely absorbed into the Rust standard library over the years, like lazy_static, which has been superseded by std::sync::LazyLock since Rust 1.80. Crate pages of such crates now show a friendly "You might not need this dependency" banner describing the standard library replacement, and superseded crates in dependency lists get a small light bulb icon with a similar hint.

The dataset behind this feature lives in the new rust-lang/std-replacement-data repository, together with a documented inclusion policy: standard library replacements only, every entry must cite the stable std, core, or alloc API and Rust version, and crate maintainers get a notice-and-comment window before an entry is added. New entries can be proposed upstream and can benefit other tools too.

Ferris
The most delightful change of this cycle: the Ferris on our error pages now follows your mouse cursor with its eyes:

Getting a 404 error on crates.io is now slightly less sad.

Svelte Frontend Migration Completed
In our January update, we announced that we were experimenting with porting the crates.io frontend from Ember.js to Svelte. This experiment has concluded successfully: the new frontend reached feature parity, went through a public testing phase in April, became the default at the beginning of May, and the Ember.js app has been removed from our repository.
We designed this change to be invisible for our users, since the new frontend is a 1:1 port of the previous design and functionality. For the team and our contributors, however, it is a big deal: the frontend is now built on a more modern framework, which should make it easier for new contributors to get started. It also allows us to iterate faster, as the source code viewer above demonstrates.
We want to thank the Ember.js team for a framework that served crates.io well for many years, and the Svelte team for making the transition so enjoyable.

Miscellaneous
These were some of the more visible changes to crates.io over the past six months, but a lot has happened "under the hood" as well:


Search performance: Relevance-sorted search queries previously ranked every crate matching the query, which could take 1-2 seconds for short or common search terms. Ranking is now bounded to the 1,000 matching crates with the highest recent download counts.


Reverse dependencies performance: The reverse dependencies endpoint no longer recomputes the full dependent set on every request. It is now served from a precomputed table kept in sync by database triggers, turning an expensive join into a bounded index scan and greatly reducing the chance of getting a timeout error.


New ARCHITECTURE.md: If you've ever wondered how crates.io actually works, our ARCHITECTURE.md document got a complete rewrite. It is now organized around the high-level systems that make up crates.io and how they fit together, and includes walkthroughs of what happens when you run cargo publish, why a typical crate download never touches our API servers, and how download counts are derived from CDN access logs.


Definition lists: READMEs now render Markdown definition lists, a widely used Markdown extension. Our markdown renderer comrak already supported them, the extension just wasn't enabled yet. Thanks to @mistaste for this contribution!


CDN cache tags: Files uploaded to our static CDN now carry cache-tag metadata, allowing us to invalidate all cached files of a crate or a specific release in a single operation, instead of issuing one invalidation per file URL.


Caching improvements: We removed a global Vary: Cookie response header that was preventing our CDNs from caching public API responses and frontend assets effectively. Per-user responses now use Cache-Control: no-store instead, resulting in better cache hit rates at the CDN edge.


Accessibility: We have made crates.io friendlier to screen readers: decorative icons are now hidden from the accessibility tree, heading hierarchies have been fixed, and lists are marked up as proper lists. ARIA snapshot tests now ensure that regressions can't slip in unnoticed. We plan to continue to improve crates.io accessibility over the coming months.


Git index performance: The background worker's local clone of the git index is now a bare and shallow repository, eliminating roughly 250,000 checked-out files and the full commit history from its disk, improving its performance as we see increased rates of crate publication. The periodic index squashing now goes through the GitHub API instead of generating large git packs locally, which had previously caused out-of-memory failures on the production worker.



Feedback
We hope you enjoyed this update on the development of crates.io. If you have any feedback or questions, please let us know on Zulip or GitHub. We are always happy to hear from you and are looking forward to your feedback!


Details of Alan Turing’s Voice Encryption System
Sat, 25 Jul 2026 08:37:05 +0200
Really interesting piece of cryptographic history:
In November 2023, a large cache of his wartime papers—nicknamed the “Bayley papers”—was auctioned in London for almost half a million U.S. dollars. The previously unknown cache contains many sheets in Turing’s own handwriting, telling of his top-secret “Delilah” engineering project from 1943 to 1945. Delilah was Turing’s portable voice-encryption system, named after the biblical deceiver of men. There is also material written by Bayley, often in the form of notes he took while Turing was speaking. It is thanks to Bayley that the papers survived: He kept them until he died in 2020, 66 years after Turing passed away...


Matrix 2.0 — How we're making Matrix go voom!
Sat, 25 Jul 2026 08:36:49 +0200
Author: Matrixdotorg - Bewertung: 395x - Views:15995 
NOTE: we'll update the FOSDEM 2023 playlist as we gather all the talks. Stay tuned for more Matrix content.



This video was recorded during FOSDEM 2023, and can also be found here: https://fosdem.org/2023/schedule/event/matrix20/



Matrix is an open standard for secure, decentralised communication, which may be familiar from powering the online editions of FOSDEM in 2021 and 2022 (and hybrid-FOSDEM this year!).



In this talk we will explain the fundamental changes which are landing in Matrix 2.0, which speeds up Matrix to be at least as snappy as the fastest proprietary messaging apps - all while handling thousands of rooms spanning millions of users.



During 2022 we've been on a mission to completely rework the slowest bits of Matrix, aiming that nobody can ever complain about Matrix being sluggish again. In practice this means fundamental changes in:



- How Matrix syncs data - "sliding sync", where servers only sync the bare minimum data to clients required to render the UI, providing instant login and instant sync (MSC3575)



- How room joins work over federation - "faster joins", where servers only sync the bare minimum data such that clients can start participating in the room as soon as possible (MSC3902)



- How auth works - switching Matrix to use OIDC natively for all authentication, registration and account management (MSC3861)



- How VoIP works - switching Matrix to natively support multiparty decentralised E2EE VoIP as the primary calling mechanism (MSC3401 and MSC3898)



The end result is transformational, and by far the biggest change to Matrix since the project began in 2014. So, we're calling it Matrix 2.0, and this talk will give a guided tour of everything that's changed - and show off the new reference matrix-rust-sdk client SDK, which powers the new flagship mobile Matrix client, codenamed Element X.



00:00 Hello!

00:41 Matrix and its ecosystem

06:33 Spec update

08:10 Matrix is taking over the world

09:26 Demo: Element X is blazing fast

13:25 Behind the scenes of the demo

15:02 How sliding sync works

21:20 One matrix-rust-sdk to rule them all

23:45 Faster remote room joins

25:12 MatrixRTC, Element Call, Matryoshka Widgets

26:37 Demo: Element Call!

28:34 Demo: raiding Element Call with waterfall — Selective Forwarding Units for Matrix

31:02 OpenID Connect: authentication done right

32:04 The future: Digital Markets Act, MIMI, MLS, P2P Matrix

36:32 Demo: P2P Matrix

40:31 Demo: ThirdRoom — Matrix beyond chat and voice

47:16 What's next?



Support Matrix!

🪙 Donorbox for individuals - https://donorbox.org/keep-matrix-exciting

💶 Matrix Foundation (paid) membership for orgs - https://forms.gle/Yy345QkB5pifJJNy6



(This Week in) Matrix

🐘 https://mastodon.matrix.org/@matrix

🐦️ https://twitter.com/matrixdotorg

[m] https://matrix.to/#/#thisweekinmatrix:matrix.org



Why Gaming on Linux Suddenly Matters
Sat, 25 Jul 2026 08:36:39 +0200
Author: Techquickie - Bewertung: 24191x - Views:665011 
Click this link https://boot.dev/?promo=TECHQUICKIE and use my code TECHQUICKIE to get 25% off your first payment for boot.dev. Thank you Boot.Dev for Sponsoring! 



From broken drivers to the Steam Deck selling millions, Linux gaming has gone from "is this the year?" to "wait, it actually works now." But getting here took a decade of tinkering, a billion-dollar bet from Valve, and an open-source community that refused to quit. In this video we talk to Valve and the Batocera project about how Linux quietly became a real threat to Windows - and why Microsoft is playing catch-up.



Leave a reply with your requests for future episodes.



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Purchases made through some store links may provide some compensation to Linus Media Group. Affiliate links powered in part by https://affilimate.com/



Linus Sebastian is an investor in Framework Computer, Inc and HexOS by Eshtek.



Chapters

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0:01 Is this the year of Linux gaming?

0:43 Why Microsoft is usually better

2:03 How Valve is fighting back

3:37 Sponsor 

4:14 Steamdeck saved the day

4:50 Windows claps back 

6:27 Valve is putting up a fight 

7:40 Watch another video



Why PC Memory is Stuck in 1995 (Unified Memory Explained)
Sat, 25 Jul 2026 08:36:06 +0200
Author: Techquickie - Bewertung: 10104x - Views:195333 
Play War Thunder for FREE on PC, PlayStation, Xbox, and mobile using the links below! New to the game, or returning after six months? You'll get a massive bonus pack on PC and consoles packed with vehicles, boosters, and more. Claim your bonus and start playing today!



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Computer memory is officially worth more than gold, thanks to AI. So why do our CPUs and GPUs still act like selfish jerks and refuse to share it? They can and it's called Unified Memory, and in this video we’re breaking down the physical bottlenecks of traditional PC architecture and explaining how Apple - and now AMD and NVIDIA - are rewriting the rules of hardware efficiency. Special thanks to Professor Prashant Nair from UBC for lending his engineering expertise!



Leave a reply with your requests for future episodes.



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Google’s New Dual-TPU Chip Made The Most Advanced AI GPUs Look Like a JOKE!
Sat, 25 Jul 2026 08:36:03 +0200
Author: Evolving AI - Bewertung: 328x - Views:12498 
Google just revealed two brand-new AI chips—and they could change the future of artificial intelligence. Instead of building one GPU to handle everything, Google introduced its 8th-generation Tensor Processing Units: TPU 8t for AI training and TPU 8i for AI inference and reasoning. The company believes future AI infrastructure needs specialized hardware rather than one general-purpose accelerator. In this video, we break down Google's new TPU architecture, including 121 exaflops of compute, superpods with up to 9,600 chips, 2 petabytes of shared memory, Virgo networking, TPUDirect, Boardfly topology, Axion CPUs, and next-generation liquid cooling. We also explain why Google optimized TPU 8i for reasoning models, AI agents, and massive inference workloads with 288GB of HBM and dramatically improved memory performance. Could Google's specialized TPU strategy become the future of AI computing? And is this the first real architectural challenge to NVIDIA's GPU dominance?



#Google #TPU #NVIDIA #AIChips #ArtificialIntelligence #GoogleCloud #Semiconductors



AMD's 19.6 TB/s Monster AI-Chip Just Made NVIDA's VERA RUBIN Look Like a JOKE!
Sat, 25 Jul 2026 08:35:56 +0200
Author: Evolving AI - Bewertung: 614x - Views:23208 
AMD may have finally built a real challenger to NVIDIA’s AI empire. In this video, we break down the AMD Instinct MI400 series and the flagship MI455X AI accelerator, featuring 432GB of HBM4 memory, 19.6TB/s of memory bandwidth, up to 40 petaflops of FP4 compute, and an advanced chiplet architecture designed for next-generation AI training and inference. But AMD’s real weapon is bigger than one chip. The Helios rack-scale AI platform combines 72 MI455X GPUs with next-generation AMD EPYC “Venice” CPUs, massive HBM4 capacity, high-speed networking, ROCm software, and open technologies like UALink to challenge NVIDIA’s tightly integrated AI infrastructure. We also explore how AMD plans to compete with NVIDIA Vera Rubin, the importance of ROCm versus CUDA, and why major AI companies and cloud providers are increasingly looking for alternatives to NVIDIA. Could AMD finally turn the AI accelerator market into a real two-company war?



#AMD #NVIDIA #MI455X #AIChips #InstinctMI400 #Helios #ArtificialIntelligence



NVIDA's New DGX Stations Destroying The Entire AI INDUSRTY!
Sat, 25 Jul 2026 08:35:45 +0200
Author: Evolving AI - Bewertung: 791x - Views:22194 
NVIDIA just revealed the most powerful AI workstation ever built—and it puts data center hardware on your desk. Powered by the new GB300 Grace Blackwell Ultra Superchip, the NVIDIA DGX Station combines a 72-core Grace CPU, a Blackwell Ultra GPU with 20,480 CUDA cores, 748GB of unified coherent memory, and up to 20 petaflops of AI compute. It's designed to run massive AI models locally, eliminating many of the memory limitations that force developers to rely on expensive cloud GPUs. In this video, we break down the DGX Station architecture, unified memory, NVLink C2C, HBM3e, local AI inference, trillion-parameter model claims, real-world pricing, and why NVIDIA believes desktop AI workstations are the future of artificial intelligence development. We also compare the DGX Station with DGX Spark, Apple’s Mac Studio, cloud GPU infrastructure, and explain why local AI could become the next major shift in computing.



Is NVIDIA reinventing the personal computer for the AI era?



#NVIDIA #DGXStation #Blackwell #AIWorkstation #ArtificialIntelligence #LocalAI #CUDA



Der lange Abend des Vibe Coding (Next Project)
Sat, 25 Jul 2026 08:35:31 +0200
Author: SemperVideo - Bewertung: 70x - Views:2470 
Vielen Dank für Ihre Unterstützung: 



http://SemperVideo.de/spende



Fragen und Antworten auf 

https://twitch.tv/sempervideo



http://www.patreon.com/sempervideo?ty=c



https://amzn.to/37WtJq5



https://github.com/RPiList/specials



Chasing new skills, going back to basics and pushing for collective action: how software engineers are adapting to AI
Sat, 25 Jul 2026 07:03:26 +0200
Software engineering was one of the best-paying professions in the US in 2022, but the advent of AI has disrupted it, leading to several layoffs and underemployment
Every weekday, Matt, a software engineer, looks forward to his four-hour train commute to Pawling, New York. It’s time he uses to work on his own project: a browser-based video game for which he writes every line of code himself.
“I am actively trying to keep my axe sharp,” said Matt, who did not want to use his actual name, to protect his employment. In the last six months, Matt’s job has increasingly shifted away from coding, problem solving and software architecture towards reviewing code generated by artificial intelligence. Convinced that the shift will weaken his skills, he’s doing what he can to keep them intact. “I am trying not to leverage AI where I can.”
 Continue reading...


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.



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 […]


Monthly News – May 2026
Sat, 25 Jul 2026 05:09:34 +0200
Hi everyone, We’ve got a lot of exciting news this month! But first of all, let us thank everyone involved in helping our project. Many thanks for your support and your donations! Note that the improvements and features mentioned in this blog post are planned for the next version of Linux Mint, which is scheduled […]


Monthly News – June 2026
Sat, 25 Jul 2026 05:09:17 +0200
Hi everyone, Many thanks to all the people who donate and sponsor our project! Note: The improvements and features mentioned in this blog post are planned for the next version of Linux Mint, which is scheduled for Christmas this year. Wayland We worked really hard on Wayland and we got to the point where it […]


Colorado Names First Principal Director of AI Architecture
Sat, 25 Jul 2026 00:03:49 +0200
Jane Yang has joined the state Office of Information Technology in the newly created role. She was previously chief AI officer for the U.S. Administration for Children and Families.


Distribution Release: Helwan Linux 5.0
Fri, 24 Jul 2026 23:03:02 +0200
The DistroWatch news feed is brought to you by TUXEDO COMPUTERS.  Saeed Badreldin has announced the release of Helwan Linux 5.0, a significant update of the project's Arch-based distribution designed primarily for developers: "We are proud to announce the launch of Helwan Linux 5.0, a version that marks a qualitative leap in our distribution philosophy and development. What's new....


Anthropic's New Opus 5 Model Rivals Fable 5 For Half the Price
Fri, 24 Jul 2026 21:08:38 +0200
Anthropic has released Opus 5, a new Claude model that it says comes close to its higher-end Fable 5 model at half the price while improving on Opus 4.8 in knowledge work, coding, and scientific research tasks. "At the same time, Anthropic says it has managed to make the model more resistant to being tricked," notes Engadget. Additionally, the company says Opus 5 "exhibits the lowest rates of deceptive behavior." From the report: One important distinction between Opus 5 and Mythos, which is currently only available to a limited number of vetted organizations through Anthropic's Project Glasswing initiative, is that the company has specifically avoided training the new model on cyber-related tasks. Due to more its powerful capabilities, Opus 5 is broadly better at those tasks than its predecessor, making it more useful for finding cybersecurity vulnerabilities, but the company says Opus 5 is "substantially behind" its flagship model at exploiting those vulnerabilities.
 
[...] Anthropic says "Claude Opus 5's safeguards are designed to allow beneficial uses of the model in both cybersecurity and biology." The company has strengthened some of the model's cyber-related guardrails, but notes it did so along a "narrow range" of specific tasks. "Based on our testing, we expect the classifiers to intervene around 85 percent less often than they do for Fable 5," Anthropic said. With Opus 5, Anthropic also isn't including it in its recently announced 30-day data retention policy, which the company introduced alongside Fable and Mythos 5.
 
As for pricing. Anthropic says API costs for Opus 5 will remain at $5 per one million input tokens and $25 per one million output tokens. Anthropic has also added an "effort" menu for Opus that users can tweak to tell the model whether they want it to be more thorough or fast and efficient to conserve tokens.






Read more of this story at Slashdot.


v3.96.0
Fri, 24 Jul 2026 20:37:39 +0200
What's Changed

[INS-355] Added Hashicorp vault token detector by @MuneebUllahKhan222 in #4819
Tighten JiraToken v1 verification by @shahzadhaider1 in #5122
[INT-718] Add TargetNotFoundError for targeted scan targets missing from the source by @bill-rich in #5123
Fix GitLab project metadata cache and switch to LRU by @kashifkhan0771 in #4727
Log analyze errors for Anthropic Analyzer by @kashifkhan0771 in #5120
Add metrics for chunks and results by @mcastorina in #5128
Update Cloudflare detectors for 2026+ prefixed credential formats (include upstream PR changes) by @kashifkhan0771 in #5111
[INS-312] Duo API Secret Key Detector by @MuneebUllahKhan222 in #4771
[Feature] Added SonarQube Cloud "Scoped Organization Token" Detector by @nabeelalam in #4739
[INS-255] Updated datadog detector to set verificationError in case of a verification error by @MuneebUllahKhan222 in #4661
Log analyze errors for Postgres analyzer by @kashifkhan0771 in #5131
Log analyze errors for HuggingFace analyzer by @kashifkhan0771 in #5130
Engine - Config.SourceManager doc by @amanfcp in #5002
Update module github.com/go-git/go-git/v5 to v5.19.1 [SECURITY] by @renovate[bot] in #5034
Retry git clone on transient network errors by @shahzadhaider1 in #5132
Fix scan_all_installations Rejecting Org Member Personal Repos by @shahzadhaider1 in #5142
updated detector to include underscore char by @mattbrady-1 in #5121
[chore] Change job_id in metric to source_type by @mcastorina in #5149
Posthog regex update by @mattbrady-1 in #5133
fix(handlers): apk handler now doesnt check for apk extension since json-enumerator and other byte stream methods wouldnt have it by @johannestaas-trufflesec in #5151

New Contributors

@mattbrady-1 made their first contribution in #5121

Full Changelog: v3.95.9...v3.96.0


Linux Kernel 7.1.4 Released with Bug Fixes, Security Updates, and Hardware Improvements
Fri, 24 Jul 2026 20:32:46 +0200

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

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

Another Important Stable Maintenance Release

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

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

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

Bug Fixes Across Multiple Kernel Subsystems

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

The update addresses issues affecting:

Memory management
	File systems
	Networking
	Device drivers
	Architecture-specific code
	Core kernel infrastructure
	USB and storage subsystems
These targeted patches help eliminate crashes, improve compatibility with newer hardware, and resolve edge cases that may only appear under specific workloads.

Improved Hardware Compatibility

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

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

Graphics hardware
	Storage controllers
	Networking devices
	USB peripherals
	Laptop components
	ARM development boards
Although no major driver additions are expected in a maintenance release, incremental improvements like these often resolve hardware-specific bugs reported by users after earlier releases.

Security and Reliability Updates

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

      
    
  


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.



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.




Mobile OS Release: UBports 24.04-2.0
Fri, 24 Jul 2026 18:32:57 +0200
The DistroWatch news feed is brought to you by TUXEDO COMPUTERS.  The UBports project has published a new feature update, UBports 24.04-2.0 which introduces web browser updates and support for "notch" areas in output displays. "Ubuntu Touch 24.04-2.0 is a feature update under the same Ubuntu 24.04 base as the previous release. Nonetheless, this release contains exciting updates and....


Sam Altman’s biometric startup World raises $52.5 million via crypto sale
Fri, 24 Jul 2026 18:21:05 +0200
Sam Altman's side project — which seeks to scan the world's eyeballs and turn them into unique digital identifiers — has raised some fresh cash through a crypto sale.


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.”



Distribution Release: Shadowfetch Linux 2.0.0
Fri, 24 Jul 2026 18:02:21 +0200
The DistroWatch news feed is brought to you by TUXEDO COMPUTERS.  The Shadowfetch Linux distribution is a Debian-based project which features the Plasma desktop. The latest release of Shadowfetch, version 2.0.0, enables automatic Btrfs snapshots prior to package changes, making rolling back to working snapshots easier. The project has also revamped its welcome screen. "Boot straight into a working....


Build an explainable next-best-product recommendation system for banking on AWS
Fri, 24 Jul 2026 17:50:40 +0200
Learn the architecture and design decisions behind an explainable next-best-product recommendation system for banking, built with Amazon SageMaker AI and PyTorch. A multi-tower neural network with learned attention delivers accurate, per-customer recommendations while providing the explainability that banking regulators require.


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.



Which of your old cables are actually worth keeping?
Fri, 24 Jul 2026 17:38:40 +0200
Clean out that cable junk drawer every so often and keep only the things you actually need.


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.



De Vlieger: The Fedora 45 sausage factory
Fri, 24 Jul 2026 17:15:45 +0200
Fedora contributor Simon de Vlieger has published a blog
post with a walkthrough of how the project turns source code and
packages into the final release that users install on their systems.


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

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





The massive Project Zomboid 'Build 42' update confirmed for July 29
Fri, 24 Jul 2026 16:56:21 +0200
The incredibly detailed zombie survival game Project Zomboid is set to level up in a huge way with the proper release of Build 42 on July 29th.
Read the full article on GamingOnLinux.


New U.S. tariffs hit Apple's supply chain, with no clear exemptions
Fri, 24 Jul 2026 16:55:54 +0200
The United States has chosen to apply new 10% tariffs to goods imported from a total of 60 countries, including the countries where nearly every iPhone and Mac are assembled.


Apple's supply chain may be impacted by new tariffs. Image credit: Intel

The new tariffs went into effect on Friday, July 24, 2026. They come into force as a 10% blanket import tax imposed by the Trump administration lapsed following a Supreme Court ruling that it was unlawful.

The new action follows a months-long investigation by the U.S. Trade Representative into the possible use of forced labor in the production of goods in 60 countries.


 Continue Reading on AppleInsider | Discuss on our Forums


The tech-broification of American science has officially begun
Fri, 24 Jul 2026 16:47:48 +0200
The Trump administration unveiled the first "Genesis Mission" grants on Thursday, directing $5 billion toward hundreds of AI-driven science projects in an effort the White House has described as "comparable in urgency and ambition to the Manhattan Project." At roughly the same time, Trump's science adviser Michael Kratsios was on Capitol Hill selling lawmakers on […]


Scientists set off on RV Celtic Explorer to track ocean changes
Fri, 24 Jul 2026 16:45:57 +0200
The AR7E-2026 project aims to generate new insights into the links between ocean circulation, climate, carbon cycling and marine ecosystems.
Read more: Scientists set off on RV Celtic Explorer to track ocean changes


AI's Biggest Hidden Security Flaw
Fri, 24 Jul 2026 16:22:44 +0200
Author: Security Weekly - A CRA Resource - Bewertung: 2x - Views:12 
Modern LLMs process prompts by predicting the next token from context. They don't inherently distinguish system instructions from user instructions, and many "reasoning" models use the same underlying architecture while producing reasoning-style text.



That makes prompt or command injection a persistent security challenge and highlights an important limitation: fluent explanations aren't necessarily evidence of genuine reasoning or understanding. Developers need additional safeguards instead of assuming the model can reliably separate trustworthy instructions from malicious ones.



Should future AI models include stronger architectural separation between trusted instructions and user input, or can software safeguards solve the problem?



Subscribe to our podcasts: https://securityweekly.com/subscribe



#LLM #SecurityWeekly #Cybersecurity #InformationSecurity #AI #InfoSec



Rethinking the transport layer for AI-first architecture
Fri, 24 Jul 2026 16:20:27 +0200
The need to re-engineer the entire transport layer to support AI-first architecture.


CVE-2026-16767 | Ne-Lexa php-zip up to 4.0.2 ZIP src/ZipFile.php ZipFile::extractTo entryName path traversal (Issue 100 / EUVD-2026-48450)
Fri, 24 Jul 2026 16:08:02 +0200
A vulnerability marked as critical has been reported in Ne-Lexa php-zip up to 4.0.2. This affects the function ZipFile::extractTo of the file src/ZipFile.php of the component ZIP Handler. Performing a manipulation of the argument entryName results in path traversal.

This vulnerability is cataloged as CVE-2026-16767. It is possible to initiate the attack remotely. Furthermore, there is an exploit available.

The project was informed of the problem early through an issue report but has not responded yet.


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.




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)


CVE-2026-5671 | Cyber-III Student-Management-System up to 1a938fa61e9f735078e9b291d2e6215b4942af3f Class Schedule Deletion Endpoint delete_batch.php batch cross site scripting (Issue 242)
Fri, 24 Jul 2026 14:12:05 +0200
A vulnerability was found in Cyber-III Student-Management-System up to 1a938fa61e9f735078e9b291d2e6215b4942af3f and classified as problematic. Impacted is an unknown function of the file /admin/class%20schedule/delete_batch.php of the component Class Schedule Deletion Endpoint. Executing a manipulation of the argument batch can lead to cross site scripting.

This vulnerability is tracked as CVE-2026-5671. The attack can be launched remotely. Moreover, an exploit is present.

This product does not use versioning. This is why information about affected and unaffected releases are unavailable.

The project was informed of the problem early through an issue report but has not responded yet.


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.
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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.
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USN-8603-1: Linux kernel (Azure) vulnerabilities
Fri, 24 Jul 2026 13:02:31 +0200
It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - x86 platform drivers;
  - PSP security protocol;
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - RISC-V architecture;
  - S390 architecture;
  - User-Mode Linux (UML);
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - Intel NPU Driver;
  - Compute Acceleration Framework;
  - ACPI drivers;
  - Auxiliary display drivers;
  - Drivers core;
  - DRBD Distributed Replicated Block Device drivers;
  - Rados block device (RBD) driver;
  - Ublk userspace block driver;
  - Compressed RAM block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clock framework and drivers;
  - CPU frequency scaling framework;
  - Hardware crypto device drivers;
  - Buffer Sharing and Synchronization framework;
  - DPLL subsystem;
  - EDAC drivers;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - FWCTL subsystem;
  - GPIO subsystem;
  - GPU drivers;
  - Greybus drivers;
  - HID subsystem;
  - Microsoft Hyper-V drivers;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - I3C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - Input Device core drivers;
  - IOMMU subsystem;
  - LED subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - NVIDIA Tegra memory controller driver;
  - IBM Advanced System Management driver;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Texas Instruments network drivers;
  - MediaTek network drivers;
  - NTB driver;
  - NVME drivers;
  - Device tree and open firmware driver;
  - Parport drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - Chrome hardware platform drivers;
  - ACPI WMI driver;
  - Generic PM domains;
  - MediaTek PM domains;
  - Power supply drivers;
  - Remote Processor subsystem;
  - MPAM driver;
  - Amlogic Meson reset controller drivers;
  - S/390 drivers;
  - SCSI subsystem;
  - NVIDIA Tegra Control Backbone (CBB) driver;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - Thermal drivers;
  - Thunderbolt and USB4 drivers;
  - TTY drivers;
  - Userspace I/O drivers;
  - USB Device Class drivers;
  - ULPI bus;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Dual Role (OTG-ready) Controller drivers;
  - USB Serial drivers;
  - USB Type-C support driver;
  - USB Type-C Port Controller Manager driver;
  - TI TPS6598x USB Power Delivery controller driver;
  - USB Type-C Connector System Software Interface driver;
  - USB over IP driver;
  - vDPA drivers;
  - VFIO drivers;
  - Framebuffer layer;
  - TSM AMD SEV Guest driver;
  - Xen hypervisor drivers;
  - 9P distributed file system;
  - File systems infrastructure;
  - AFS file system;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - HugeTLB file system;
  - Journaling layer for block devices (JBD2);
  - Network file systems library;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Overlay file system;
  - Diskquota system;
  - SMB network file system;
  - Tracing file system;
  - UDF file system;
  - XFS file system;
  - DRM TTM subsystem;
  - Codetag library;
  - Control group (cgroup);
  - Kernel CPU control infrastructure;
  - Memory management;
  - Tracing infrastructure;
  - QorIQ DPAA2 FSL-MC bus driver;
  - Freescale ENETC Ethernet drivers;
  - Memory Management;
  - KVM subsystem;
  - Linked list library;
  - Netfilter;
  - padata parallel execution mechanism;
  - PPP protocol drivers and compressors;
  - Bluetooth subsystem;
  - Networking core;
  - Network shaper API;
  - Network traffic control;
  - TCP network protocol;
  - XFRM subsystem;
  - User-space API (UAPI);
  - io_uring subsystem;
  - IPC subsystem;
  - Audit subsystem;
  - BPF subsystem;
  - DMA mapping infrastructure;
  - Kernel exit() syscall;
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - IRQ subsystem;
  - Kexec HandOver (KHO);
  - Locking primitives;
  - Padata parallel execution mechanism;
  - Scheduler infrastructure;
  - Timer subsystem;
  - Cryptographic library;
  - Scatterlist API;
  - Heterogeneous memory management;
  - KProbes tracing;
  - KASAN memory debugging framework;
  - 802.1Q VLAN protocol;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Distributed Switch Architecture;
  - Ethtool driver;
  - Handshake API;
  - HSR network protocol;
  - IPv4 networking;
  - IPv6 networking;
  - IUCV driver;
  - L2TP protocol;
  - MAC80211 subsystem;
  - Multipath TCP;
  - NFC subsystem;
  - Open vSwitch;
  - Packet sockets;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - Integrity Measurement Architecture(IMA) framework;
  - Key management;
  - Landlock security;
  - Linux Security Modules (LSM) Framework;
  - SELinux security module;
  - ALSA framework;
  - Generic PCM loopback sound driver;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - FourSemi audio codecs;
  - Texas InstrumentS Audio (ASoC/HDA) drivers;
  - QCOM ASoC drivers;
  - Renesas ASoC drivers;
  - SOF drivers;
  - STI ASoC drivers;
  - USB sound devices;
  - Objtool;
(CVE-2026-31532, CVE-2026-31574, CVE-2026-31575, CVE-2026-31576,
CVE-2026-31577, CVE-2026-31578, CVE-2026-31579, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31582, CVE-2026-31583, CVE-2026-31584,
CVE-2026-31585, CVE-2026-31586, CVE-2026-31587, CVE-2026-31588,
CVE-2026-31589, CVE-2026-31590, CVE-2026-31591, CVE-2026-31592,
CVE-2026-31593, CVE-2026-31594, CVE-2026-31595, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31600,
CVE-2026-31601, CVE-2026-31602, CVE-2026-31603, CVE-2026-31604,
CVE-2026-31605, CVE-2026-31606, CVE-2026-31607, CVE-2026-31608,
CVE-2026-31609, CVE-2026-31610, CVE-2026-31611, CVE-2026-31612,
CVE-2026-31613, CVE-2026-31614, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31620,
CVE-2026-31621, CVE-2026-31622, CVE-2026-31623, CVE-2026-31624,
CVE-2026-31625, CVE-2026-31626, CVE-2026-31627, CVE-2026-31628,
CVE-2026-31629, CVE-2026-31686, CVE-2026-31694, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31700,
CVE-2026-31701, CVE-2026-31702, CVE-2026-31703, CVE-2026-31704,
CVE-2026-31705, CVE-2026-31706, CVE-2026-31707, CVE-2026-31708,
CVE-2026-31709, CVE-2026-31710, CVE-2026-31711, CVE-2026-31712,
CVE-2026-31713, CVE-2026-31714, CVE-2026-31715, CVE-2026-31716,
CVE-2026-31717, CVE-2026-31718, CVE-2026-31719, CVE-2026-43058,
CVE-2026-43071, CVE-2026-43072, CVE-2026-43073, CVE-2026-43348,
CVE-2026-43349, CVE-2026-43350, CVE-2026-43490, CVE-2026-43491,
CVE-2026-43492, CVE-2026-43493, CVE-2026-43495, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43498, CVE-2026-43499, CVE-2026-43501,
CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836,
CVE-2026-45837, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840,
CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844,
CVE-2026-45845, CVE-2026-45846, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45988, CVE-2026-45989, CVE-2026-45990, CVE-2026-45991,
CVE-2026-45994, CVE-2026-45995, CVE-2026-45996, CVE-2026-45997,
CVE-2026-45999, CVE-2026-46001, CVE-2026-46002, CVE-2026-46003,
CVE-2026-46004, CVE-2026-46005, CVE-2026-46006, CVE-2026-46007,
CVE-2026-46008, CVE-2026-46009, CVE-2026-46010, CVE-2026-46011,
CVE-2026-46012, CVE-2026-46013, CVE-2026-46014, CVE-2026-46015,
CVE-2026-46016, CVE-2026-46018, CVE-2026-46019, CVE-2026-46020,
CVE-2026-46021, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024,
CVE-2026-46025, CVE-2026-46026, CVE-2026-46027, CVE-2026-46028,
CVE-2026-46029, CVE-2026-46030, CVE-2026-46031, CVE-2026-46032,
CVE-2026-46033, CVE-2026-46034, CVE-2026-46035, CVE-2026-46036,
CVE-2026-46037, CVE-2026-46038, CVE-2026-46039, CVE-2026-46040,
CVE-2026-46041, CVE-2026-46042, CVE-2026-46043, CVE-2026-46044,
CVE-2026-46045, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049,
CVE-2026-46050, CVE-2026-46051, CVE-2026-46052, CVE-2026-46053,
CVE-2026-46054, CVE-2026-46056, CVE-2026-46057, CVE-2026-46058,
CVE-2026-46059, CVE-2026-46060, CVE-2026-46061, CVE-2026-46062,
CVE-2026-46063, CVE-2026-46064, CVE-2026-46065, CVE-2026-46066,
CVE-2026-46067, CVE-2026-46068, CVE-2026-46069, CVE-2026-46070,
CVE-2026-46071, CVE-2026-46072, CVE-2026-46073, CVE-2026-46074,
CVE-2026-46075, CVE-2026-46076, CVE-2026-46077, CVE-2026-46078,
CVE-2026-46079, CVE-2026-46080, CVE-2026-46081, CVE-2026-46082,
CVE-2026-46083, CVE-2026-46084, CVE-2026-46085, CVE-2026-46086,
CVE-2026-46087, CVE-2026-46088, CVE-2026-46089, CVE-2026-46090,
CVE-2026-46091, CVE-2026-46092, CVE-2026-46093, CVE-2026-46094,
CVE-2026-46095, CVE-2026-46096, CVE-2026-46097, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46100, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46103, CVE-2026-46104, CVE-2026-46105, CVE-2026-46106,
CVE-2026-46107, CVE-2026-46108, CVE-2026-46109, CVE-2026-46110,
CVE-2026-46111, CVE-2026-46112, CVE-2026-46113, CVE-2026-46114,
CVE-2026-46115, CVE-2026-46116, CVE-2026-46117, CVE-2026-46118,
CVE-2026-46119, CVE-2026-46120, CVE-2026-46121, CVE-2026-46122,
CVE-2026-46123, CVE-2026-46124, CVE-2026-46125, CVE-2026-46126,
CVE-2026-46127, CVE-2026-46128, CVE-2026-46129, CVE-2026-46130,
CVE-2026-46131, CVE-2026-46132, CVE-2026-46133, CVE-2026-46134,
CVE-2026-46135, CVE-2026-46136, CVE-2026-46137, CVE-2026-46138,
CVE-2026-46139, CVE-2026-46140, CVE-2026-46141, CVE-2026-46142,
CVE-2026-46143, CVE-2026-46144, CVE-2026-46145, CVE-2026-46146,
CVE-2026-46147, CVE-2026-46148, CVE-2026-46149, CVE-2026-46150,
CVE-2026-46151, CVE-2026-46152, CVE-2026-46153, CVE-2026-46154,
CVE-2026-46155, CVE-2026-46156, CVE-2026-46157, CVE-2026-46158,
CVE-2026-46159, CVE-2026-46160, CVE-2026-46161, CVE-2026-46162,
CVE-2026-46163, CVE-2026-46164, CVE-2026-46165, CVE-2026-46166,
CVE-2026-46167, CVE-2026-46168, CVE-2026-46169, CVE-2026-46170,
CVE-2026-46171, CVE-2026-46172, CVE-2026-46173, CVE-2026-46174,
CVE-2026-46175, CVE-2026-46176, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46179, CVE-2026-46180, CVE-2026-46181, CVE-2026-46182,
CVE-2026-46183, CVE-2026-46184, CVE-2026-46185, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46188, CVE-2026-46189, CVE-2026-46190,
CVE-2026-46191, CVE-2026-46192, CVE-2026-46193, CVE-2026-46194,
CVE-2026-46195, CVE-2026-46196, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46199, CVE-2026-46200, CVE-2026-46201, CVE-2026-46202,
CVE-2026-46203, CVE-2026-46204, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46207, CVE-2026-46208, CVE-2026-46209, CVE-2026-46210,
CVE-2026-46211, CVE-2026-46212, CVE-2026-46213, CVE-2026-46214,
CVE-2026-46215, CVE-2026-46216, CVE-2026-46218, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46221, CVE-2026-46222, CVE-2026-46223,
CVE-2026-46224, CVE-2026-46225, CVE-2026-46226, CVE-2026-46227,
CVE-2026-46228, CVE-2026-46229, CVE-2026-46230, CVE-2026-46231,
CVE-2026-46232, CVE-2026-46233, CVE-2026-46234, CVE-2026-46235,
CVE-2026-46236, CVE-2026-46238, CVE-2026-46239, CVE-2026-46240,
CVE-2026-46241, CVE-2026-46242, CVE-2026-46243, CVE-2026-46244,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46275, CVE-2026-46276,
CVE-2026-46277, CVE-2026-46278, CVE-2026-46279, CVE-2026-46280,
CVE-2026-46281, CVE-2026-46282, CVE-2026-46283, CVE-2026-46284,
CVE-2026-46285, CVE-2026-46286, CVE-2026-46287, CVE-2026-46288,
CVE-2026-46289, CVE-2026-46290, CVE-2026-46291, CVE-2026-46292,
CVE-2026-46293, CVE-2026-46294, CVE-2026-46295, CVE-2026-46296,
CVE-2026-46297, CVE-2026-46298, CVE-2026-46299, CVE-2026-46301,
CVE-2026-46302, CVE-2026-46303, CVE-2026-46304, CVE-2026-46305,
CVE-2026-46306, CVE-2026-46307, CVE-2026-46308, CVE-2026-46309,
CVE-2026-46310, CVE-2026-46311, CVE-2026-46312, CVE-2026-46313,
CVE-2026-46314, CVE-2026-46315, CVE-2026-46316, CVE-2026-46317,
CVE-2026-46318, CVE-2026-46319, CVE-2026-46320, CVE-2026-46321,
CVE-2026-46322, CVE-2026-46324, CVE-2026-46332, CVE-2026-52904,
CVE-2026-52905, CVE-2026-52906, CVE-2026-52907, CVE-2026-52911,
CVE-2026-52912, CVE-2026-52913, CVE-2026-52914, CVE-2026-52915,
CVE-2026-52916, CVE-2026-52918, CVE-2026-52919, CVE-2026-52920,
CVE-2026-52921, CVE-2026-52922, CVE-2026-52923, CVE-2026-52925,
CVE-2026-52926, CVE-2026-52927, CVE-2026-52928, CVE-2026-52931,
CVE-2026-52932, CVE-2026-52933, CVE-2026-52934, CVE-2026-52936,
CVE-2026-52937, CVE-2026-52941, CVE-2026-52943, CVE-2026-52944,
CVE-2026-52949, CVE-2026-52950, CVE-2026-52951, CVE-2026-52952,
CVE-2026-52953, CVE-2026-52954, CVE-2026-52955, CVE-2026-52956,
CVE-2026-52957, CVE-2026-52958, CVE-2026-52959, CVE-2026-52960,
CVE-2026-52961, CVE-2026-52962, CVE-2026-52963, CVE-2026-52964,
CVE-2026-52965, CVE-2026-52967, CVE-2026-52968, CVE-2026-52969,
CVE-2026-52970, CVE-2026-52971, CVE-2026-52973, CVE-2026-52974,
CVE-2026-52975, CVE-2026-52976, CVE-2026-52977, CVE-2026-52978,
CVE-2026-52979, CVE-2026-52980, CVE-2026-52981, CVE-2026-52982,
CVE-2026-52983, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986,
CVE-2026-52987, CVE-2026-52988, CVE-2026-52989, CVE-2026-52990,
CVE-2026-52991, CVE-2026-52992, CVE-2026-52993, CVE-2026-52994,
CVE-2026-52995, CVE-2026-52996, CVE-2026-52997, CVE-2026-52998,
CVE-2026-52999, CVE-2026-53000, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53005, CVE-2026-53006,
CVE-2026-53007, CVE-2026-53008, CVE-2026-53009, CVE-2026-53010,
CVE-2026-53011, CVE-2026-53012, CVE-2026-53013, CVE-2026-53014,
CVE-2026-53015, CVE-2026-53016, CVE-2026-53017, CVE-2026-53018,
CVE-2026-53019, CVE-2026-53020, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53024, CVE-2026-53025, CVE-2026-53026,
CVE-2026-53027, CVE-2026-53028, CVE-2026-53029, CVE-2026-53030,
CVE-2026-53031, CVE-2026-53032, CVE-2026-53033, CVE-2026-53034,
CVE-2026-53035, CVE-2026-53036, CVE-2026-53037, CVE-2026-53038,
CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53042,
CVE-2026-53043, CVE-2026-53044, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53051, CVE-2026-53052, CVE-2026-53053, CVE-2026-53054,
CVE-2026-53055, CVE-2026-53056, CVE-2026-53057, CVE-2026-53058,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53063, CVE-2026-53064, CVE-2026-53065, CVE-2026-53066,
CVE-2026-53067, CVE-2026-53068, CVE-2026-53069, CVE-2026-53070,
CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074,
CVE-2026-53075, CVE-2026-53076, CVE-2026-53077, CVE-2026-53078,
CVE-2026-53079, CVE-2026-53080, CVE-2026-53081, CVE-2026-53082,
CVE-2026-53083, CVE-2026-53084, CVE-2026-53085, CVE-2026-53086,
CVE-2026-53087, CVE-2026-53088, CVE-2026-53089, CVE-2026-53090,
CVE-2026-53091, CVE-2026-53092, CVE-2026-53093, CVE-2026-53094,
CVE-2026-53095, CVE-2026-53096, CVE-2026-53097, CVE-2026-53098,
CVE-2026-53099, CVE-2026-53100, CVE-2026-53101, CVE-2026-53102,
CVE-2026-53103, CVE-2026-53104, CVE-2026-53105, CVE-2026-53106,
CVE-2026-53107, CVE-2026-53108, CVE-2026-53109, CVE-2026-53110,
CVE-2026-53111, CVE-2026-53112, CVE-2026-53113, CVE-2026-53114,
CVE-2026-53115, CVE-2026-53116, CVE-2026-53117, CVE-2026-53118,
CVE-2026-53119, CVE-2026-53120, CVE-2026-53121, CVE-2026-53122,
CVE-2026-53123, CVE-2026-53124, CVE-2026-53125, CVE-2026-53126,
CVE-2026-53127, CVE-2026-53128, CVE-2026-53129, CVE-2026-53130,
CVE-2026-53174, CVE-2026-53277, CVE-2026-53278, CVE-2026-53279,
CVE-2026-53280, CVE-2026-53281, CVE-2026-53282, CVE-2026-53283,
CVE-2026-53284, CVE-2026-53285, CVE-2026-53286, CVE-2026-53287,
CVE-2026-53288, CVE-2026-53289, CVE-2026-53290, CVE-2026-53291,
CVE-2026-53292, CVE-2026-53293, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53297, CVE-2026-53298, CVE-2026-53299,
CVE-2026-53300, CVE-2026-53301, CVE-2026-53302, CVE-2026-53303,
CVE-2026-53304, CVE-2026-53305, CVE-2026-53306, CVE-2026-53307,
CVE-2026-53308, CVE-2026-53309, CVE-2026-53310, CVE-2026-53311,
CVE-2026-53312, CVE-2026-53313, CVE-2026-53314, CVE-2026-53315,
CVE-2026-53316, CVE-2026-53317, CVE-2026-53318, CVE-2026-53319,
CVE-2026-53320, CVE-2026-53321, CVE-2026-53322, CVE-2026-53323,
CVE-2026-53324, CVE-2026-53357, CVE-2026-53358, CVE-2026-53360,
CVE-2026-53364, CVE-2026-53365, CVE-2026-53367, CVE-2026-53368,
CVE-2026-53369, CVE-2026-53370, CVE-2026-53371, CVE-2026-53372,
CVE-2026-53373, CVE-2026-53374, CVE-2026-53375, CVE-2026-53376,
CVE-2026-53377, CVE-2026-53378, CVE-2026-53379, CVE-2026-53380,
CVE-2026-63837, CVE-2026-63838, CVE-2026-63839, CVE-2026-63840,
CVE-2026-63841, CVE-2026-63842, CVE-2026-63843, CVE-2026-63844,
CVE-2026-63845, CVE-2026-63846, CVE-2026-63847, CVE-2026-63848,
CVE-2026-63849, CVE-2026-63850, CVE-2026-63851, CVE-2026-63852,
CVE-2026-63853, CVE-2026-63854, CVE-2026-63855, CVE-2026-63856,
CVE-2026-63857, CVE-2026-63858, CVE-2026-63859, CVE-2026-63860,
CVE-2026-63861, CVE-2026-63862, CVE-2026-63863, CVE-2026-63864,
CVE-2026-63865, CVE-2026-63866, CVE-2026-63875, CVE-2026-63876,
CVE-2026-63877, CVE-2026-63878, CVE-2026-63879, CVE-2026-63880,
CVE-2026-63881, CVE-2026-63882, CVE-2026-63883, CVE-2026-63884,
CVE-2026-63886, CVE-2026-63887, CVE-2026-63888, CVE-2026-63889,
CVE-2026-63890, CVE-2026-63891, CVE-2026-63892, CVE-2026-63893,
CVE-2026-63894, CVE-2026-63895, CVE-2026-63896, CVE-2026-63897,
CVE-2026-63898, CVE-2026-63899, CVE-2026-63900, CVE-2026-63901,
CVE-2026-63902, CVE-2026-63903, CVE-2026-63904, CVE-2026-63905,
CVE-2026-63906, CVE-2026-63907, CVE-2026-63908, CVE-2026-63910,
CVE-2026-63911, CVE-2026-63912, CVE-2026-63913, CVE-2026-63914,
CVE-2026-63915, CVE-2026-63916, CVE-2026-63917, CVE-2026-63918,
CVE-2026-63919, CVE-2026-63920, CVE-2026-63921, CVE-2026-63922,
CVE-2026-63923, CVE-2026-63924, CVE-2026-63925, CVE-2026-63926,
CVE-2026-63927, CVE-2026-63928, CVE-2026-63929, CVE-2026-63930,
CVE-2026-63931, CVE-2026-63932, CVE-2026-63933, CVE-2026-63934,
CVE-2026-63935, CVE-2026-63936, CVE-2026-63937, CVE-2026-63938,
CVE-2026-63939, CVE-2026-63940, CVE-2026-63941, CVE-2026-63942,
CVE-2026-63943, CVE-2026-63944, CVE-2026-63945, CVE-2026-63946,
CVE-2026-63947, CVE-2026-63948, CVE-2026-63949, CVE-2026-63950,
CVE-2026-63951, CVE-2026-63952, CVE-2026-63953, CVE-2026-63954,
CVE-2026-63955, CVE-2026-63956, CVE-2026-63957, CVE-2026-63958,
CVE-2026-63959, CVE-2026-63960, CVE-2026-63961, CVE-2026-63962,
CVE-2026-63963, CVE-2026-63964, CVE-2026-63965, CVE-2026-63966,
CVE-2026-63967, CVE-2026-63968, CVE-2026-63969, CVE-2026-63970,
CVE-2026-63971, CVE-2026-63972, CVE-2026-63973, CVE-2026-63974,
CVE-2026-63975, CVE-2026-63976, CVE-2026-63977, CVE-2026-63978,
CVE-2026-63979, CVE-2026-63980, CVE-2026-63981, CVE-2026-63982,
CVE-2026-63983, CVE-2026-63984, CVE-2026-63985, CVE-2026-63986,
CVE-2026-63987, CVE-2026-63988, CVE-2026-63989, CVE-2026-63990,
CVE-2026-63991, CVE-2026-63992, CVE-2026-63993, CVE-2026-63994,
CVE-2026-63995, CVE-2026-63996, CVE-2026-63997, CVE-2026-63998,
CVE-2026-63999, CVE-2026-64000, CVE-2026-64001, CVE-2026-64002,
CVE-2026-64003, CVE-2026-64004, CVE-2026-64005, CVE-2026-64006,
CVE-2026-64007, CVE-2026-64008, CVE-2026-64009, CVE-2026-64010,
CVE-2026-64011, CVE-2026-64012, CVE-2026-64013, CVE-2026-64014,
CVE-2026-64015, CVE-2026-64017, CVE-2026-64018, CVE-2026-64019,
CVE-2026-64020, CVE-2026-64021, CVE-2026-64022, CVE-2026-64023,
CVE-2026-64024, CVE-2026-64025, CVE-2026-64026, CVE-2026-64027,
CVE-2026-64029, CVE-2026-64030, CVE-2026-64031, CVE-2026-64032,
CVE-2026-64033, CVE-2026-64034, CVE-2026-64035, CVE-2026-64036,
CVE-2026-64037, CVE-2026-64038, CVE-2026-64039, CVE-2026-64040,
CVE-2026-64041, CVE-2026-64042, CVE-2026-64043, CVE-2026-64044,
CVE-2026-64045, CVE-2026-64046, CVE-2026-64047, CVE-2026-64048,
CVE-2026-64049, CVE-2026-64050, CVE-2026-64051, CVE-2026-64052,
CVE-2026-64053, CVE-2026-64054, CVE-2026-64055, CVE-2026-64056,
CVE-2026-64057, CVE-2026-64058, CVE-2026-64059, CVE-2026-64060,
CVE-2026-64061, CVE-2026-64062, CVE-2026-64063, CVE-2026-64064,
CVE-2026-64065, CVE-2026-64066, CVE-2026-64067, CVE-2026-64068,
CVE-2026-64069, CVE-2026-64070, CVE-2026-64071, CVE-2026-64072,
CVE-2026-64073, CVE-2026-64074, CVE-2026-64075, CVE-2026-64076,
CVE-2026-64077, CVE-2026-64078, CVE-2026-64079, CVE-2026-64080,
CVE-2026-64081, CVE-2026-64082, CVE-2026-64083, CVE-2026-64084,
CVE-2026-64085, CVE-2026-64086, CVE-2026-64087, CVE-2026-64088,
CVE-2026-64089, CVE-2026-64090, CVE-2026-64091, CVE-2026-64093,
CVE-2026-64094, CVE-2026-64095, CVE-2026-64096, CVE-2026-64097,
CVE-2026-64098, CVE-2026-64099, CVE-2026-64100, CVE-2026-64101,
CVE-2026-64102, CVE-2026-64103, CVE-2026-64104, CVE-2026-64105,
CVE-2026-64106, CVE-2026-64107, CVE-2026-64108, CVE-2026-64109,
CVE-2026-64110, CVE-2026-64111, CVE-2026-64112, CVE-2026-64113,
CVE-2026-64114, CVE-2026-64115, CVE-2026-64116, CVE-2026-64117,
CVE-2026-64118, CVE-2026-64119, CVE-2026-64120, CVE-2026-64121,
CVE-2026-64122, CVE-2026-64123, CVE-2026-64124, CVE-2026-64125,
CVE-2026-64126, CVE-2026-64127, CVE-2026-64128, CVE-2026-64129,
CVE-2026-64130, CVE-2026-64131, CVE-2026-64132, CVE-2026-64133,
CVE-2026-64134, CVE-2026-64135, CVE-2026-64136, CVE-2026-64137,
CVE-2026-64138, CVE-2026-64140, CVE-2026-64141, CVE-2026-64142,
CVE-2026-64143, CVE-2026-64144, CVE-2026-64145, CVE-2026-64146,
CVE-2026-64147, CVE-2026-64148, CVE-2026-64149, CVE-2026-64150,
CVE-2026-64151, CVE-2026-64152, CVE-2026-64153, CVE-2026-64154,
CVE-2026-64155, CVE-2026-64156, CVE-2026-64157, CVE-2026-64158,
CVE-2026-64159, CVE-2026-64160, CVE-2026-64161, CVE-2026-64162,
CVE-2026-64163, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166,
CVE-2026-64167, CVE-2026-64168, CVE-2026-64169, CVE-2026-64170,
CVE-2026-64171, CVE-2026-64172, CVE-2026-64173, CVE-2026-64174,
CVE-2026-64175, CVE-2026-64176, CVE-2026-64177, CVE-2026-64178,
CVE-2026-64179, CVE-2026-64180, CVE-2026-64181, CVE-2026-64182,
CVE-2026-64183, CVE-2026-64184, CVE-2026-64185, CVE-2026-64186)


Tor pauses new feature development to perform privacy audit on Firefox 153
Fri, 24 Jul 2026 12:27:09 +0200
The Tor Project has paused new feature development for Tor Browser 16 as developers work through more than 250 changes inherited from Firefox ESR 153 to ensure they do not weaken the browser's privacy and anonymity protections. The announcement accompanied the release of Tor Browser 16.0a9, the latest alpha build intended for testing rather than …
The post Tor pauses new feature development to perform privacy audit on Firefox 153 appeared first on CyberInsider.


Critical IntelliJ IDEA Path Traversal Flaw Enables Code Execution
Fri, 24 Jul 2026 12:09:07 +0200
JetBrains has patched a critical path traversal vulnerability in IntelliJ IDEA that allows attackers to achieve arbitrary code execution simply by tricking a developer into opening a maliciously crafted project. Tracked as CVE-2026-59792, the flaw carries a CVSS score of 9.6 and was disclosed on July 10, 2026, alongside a broader batch of security fixes […]
The post Critical IntelliJ IDEA Path Traversal Flaw Enables Code Execution appeared first on Cyber Security News.


ISC2 seeks input from IT pros for AI security certification
Fri, 24 Jul 2026 12:09:03 +0200

		
					  
						




ISC2 has begun developing a vendor-neutral AI security certification aimed at cybersecurity professionals working to secure AI systems and manage emerging AI risks.



The nonprofit organization, best known for the CISSP certification, says it is seeking volunteers worldwide to help define the knowledge and skills that will shape the new credential. While ISC2 has not finalized the certification domains, the certification is expected to address both technical AI security and governance topics, with a pilot exam planned before the end of 2026.



According to Casey Marks, ISC2 chief operating officer, feedback from cybersecurity practitioners led ISC2 to conclude that AI security had grown beyond expanding AI content within existing certifications.



“AI has reached a tipping point,” Marks says. “AI no longer is just another tool; instead, it has fundamentally changed the cybersecurity practice itself.”



ISC2 already includes AI-related content in certifications including CISSP and CCSP, but Marks says practitioners have identified new responsibilities and risks that extend beyond those programs. “Enterprise security teams are currently grappling with significant knowledge gaps, particularly around securing model architectures against new vulnerabilities like prompt injection, data poisoning, and model inversion,” Marks adds.



Organizations are working to understand emerging governance frameworks, including the NIST AI Risk Management Framework and ISO/IEC 42001, while adapting traditional application security and security operations workflows to AI systems, he says.



ISC2 has not finalized the certification domains, but Marks says the organization expects the credential to address both technical controls and governance practices for securing AI systems and managing AI risk. The certification will use ISC2’s established certification development process, which relies on cybersecurity practitioners to define job roles, develop exam content, and validate competencies.



Marks says ISC2 will continue to update the certification through ongoing input from cybersecurity professionals, in addition to its regular certification review process.



The organization is also determining which professionals the certification will target. Marks says AI security responsibilities are emerging across security architecture, risk management, security operations, software development security, governance and compliance, communication and network security, and security assessment and testing. ISC2 says the certification will reflect how those roles are evolving.



For organizations that are building AI security programs now, Marks recommends using existing AI training resources, adopting established governance frameworks, creating cross-functional AI security working groups, and participating in the certification development process.



Marks says ISC2 expects AI knowledge to become part of most cybersecurity roles while a more specialized AI security discipline continues to develop. He says organizations will increasingly need professionals with foundational AI security knowledge, as well as specialists in areas such as adversarial machine learning, model architectures, and AI data pipelines.



Looking ahead, Marks says he expects AI security expertise to evolve into both a foundational skill for cybersecurity professionals and a specialized discipline of its own.



“At this time, we are seeing a hybrid evolution occurring in real time: AI security is simultaneously becoming a baseline expectation for all security roles, while also carving out a dedicated, highly specialized discipline,” Marks says.



CIOs beware: DNS KSK rollover could kick off wave of mysterious outages
Fri, 24 Jul 2026 12:09:00 +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.”



CVE-2026-5529 | Dromara lamp-cloud up to 5.8.1 DefUserController /defUser/pageUser improper authorization (Issue 403)
Fri, 24 Jul 2026 11:34:57 +0200
A vulnerability has been found in Dromara lamp-cloud up to 5.8.1 and classified as critical. This vulnerability affects the function pageUser of the file /defUser/pageUser of the component DefUserController. Performing a manipulation results in improper authorization.

This vulnerability is identified as CVE-2026-5529. The attack can be initiated remotely. Additionally, an exploit exists.

The project was informed of the problem early through an issue report but has not responded yet.


The Microsoft agent framework wars are over. The real architecture decision starts now
Fri, 24 Jul 2026 11:04:58 +0200

					  
						




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



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



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



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



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



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



It didn’t change the meal.



The framework was never the hard part



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



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



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



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



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



What building production agents actually taught me



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



Context beats model choice



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



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



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



Failure is where the real work is



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



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



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



Identity is the real security boundary



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



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



The surprises weren’t technical



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



Build for change, not for today’s winner



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



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



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



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



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



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



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



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



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



This article is published as part of the Foundry Expert Contributor Network.
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Sponsor mismatch is the silent killer of enterprise transformation
Fri, 24 Jul 2026 11:03:44 +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.
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Why enterprises should care about Nokia’s AI-RAN platform
Fri, 24 Jul 2026 10:13:45 +0200

		
					  
						




Earlier this month, Nokia provided an AI-RAN platform update that brings an AI-native and programmable compute which is projected to double spectral efficiency by 2028. This increases speed, but more importantly, it can allow mobile operators to create some actual monetization beyond connectivity.



With this release, Nokia is introducing what it calls the industry’s first commercial AI-RAN platform, built on its AI‑native anyRAN software and Nvidia’s Aerial AI-RAN stack running on merchant GPU-based accelerated computing. The company is already seeing more than 20% gains in spectral efficiency from AI-driven radio algorithms, with a roadmap to reach 50% by 2027 and more than 100% by 2028, effectively doubling capacity on existing spectrum in dense cells.



Legacy RAN infrastructure enables connectivity but not much beyond that. The AI-RAN makes the network intelligent and extends AI into the physical world, enabling telcos to get more from their infrastructure investments, including providing a path to 6G. The partnership with Nvidia brings CUDA and AI into mobile environments.



For Network World readers, the headline isn’t just that Nokia got to market first with AI‑RAN—it’s that the company is using AI and GPUs to break the historical coupling between radio performance and custom silicon refresh cycles, and to turn the RAN into an application platform.



What AI-RAN actually is



At a technical level, Nokia’s AI‑RAN is a software‑defined baseband architecture that runs Layer 1/Layer 2 RAN functions and AI models on accelerated compute, primarily GPUs, instead of being locked into fixed‑function ASICs. Udayan Mukherjee, Nokia’s CTO for RAN and core, summarized the vision in the analyst briefing: “AI‑RAN is essentially a platform that turns the radio network into a true AI‑native programmable platform… one software detached from the hardware, defining flexible hardware deployment configurations, including part of the AI grid.”



Several pillars stand out:




AI‑native design: Algorithms move from traditional linear models to increasingly nonlinear techniques (e.g., advanced channel estimation, deep receivers/transmitters, RKHS-based methods), which demand tensor-heavy compute best delivered by GPUs.



Software-defined RAN: The same anyRAN software stack runs across different hardware configurations—plug‑in cards, standalone AI‑RAN nodes, and COTS/cloud RAN—so innovation comes via software releases rather than baseband card swaps.



Programmable “D‑apps” layer: Nokia is pushing a new real‑time E3 interface from Layer 1/2 into an application layer for distributed apps (D‑apps) that can tap IQ samples, channel estimation and scheduling data for use cases such as sensing and location services.



Crucially, this isn’t meant to replace all custom silicon overnight. Mukherjee was explicit: “We are not dropping the purpose‑built product… but we want to also get to merchant silicon, because that’s the future as we want to develop bigger models and AI elements and value‑added services on top of it.” The result is a hybrid era where AI‑accelerated platforms coexist with existing basebands but begin to shoulder the most compute‑intensive workloads.




Why AI-RAN matters for operators



Nokia and its early operator partners are trying to solve three perennial problems: finite spectrum, changing traffic patterns, and the drag of hardware refresh cycles.



First, spectrum constraints. Aji Ed, Nokia’s head of AI‑RAN and cloud RAN, called spectrum “the first constraint everybody has,” noting that operators have paid “huge amount of money” for bands and now need to “get up to the 2x spectrum” in terms of usable capacity. By running more complex AI models for multi‑user MIMO pairing, channel estimation, carrier aggregation and deep receiver/transmitter functions on GPUs, Nokia believes it can unlock those gains where traditional platforms simply run out of compute headroom.



Second, traffic is shifting. Generative AI and distributed inference workloads are driving more uplink-heavy, latency‑sensitive patterns that current RANs weren’t designed for. AI‑RAN’s ability to adapt scheduling, beamforming and resource allocation dynamically via AI models deployed at the baseband is meant to keep up with this shift.



Third, innovation cadence. In Ed’s words, “hardware upgrades can’t keep up with the innovation… we can’t really have a silicon refresh cycle linked with every three‑year cycle.” Nokia’s subscription‑based software model is designed to deliver new AI algorithms, spectral‑efficiency improvements and network optimization features continuously, without requiring “forklift” hardware replacements.



For operators, the message is attractive: comparable TCO and power to existing basebands, “no hardware premium” for GPU adoption, but higher capacity and a path to new services. Nokia told analysts it has reached performance, price and energy efficiency parity between its custom GridShark silicon and GPU-based systems, while moving the baseband roadmap to merchant silicon.



Nokia’s differentiation strategy



Every major RAN vendor is talking about AI‑enhanced radio, but Nokia is drawing a line between incremental gains and what it claims is a platform shift. When asked why its 2x spectral efficiency ambition is so much higher than the ~20% numbers competitors discuss, Ed pointed to the underlying architecture: “We are able to bring much more complex algorithms into this compute infrastructure… all of these require much higher compute, which is exactly what is coming from the accelerated computing.”



Several differentiators emerge:




Aggressive spectral roadmap: Nokia is targeting 1.5x by 2027 and 2x by 2028, across TDD massive MIMO and FDD scenarios, with a feature roadmap built jointly with Nvidia and other partners.



Single code base, three deployment paths: The same anyRAN software stack runs on (1) a GPU‑powered AirScale capacity plug‑in card, (2) a high‑capacity standalone AI‑RAN node, and (3) GPU‑based COTS/cloud RAN servers. This lets operators modernize “at their own pace” and mix brownfield evolution with greenfield AI-native deployments.



Open ecosystem with D‑apps: Nokia is leaning into ORAN compliance (front‑haul, O1/O2) and actively championing the E3 interface and D‑apps concept within ORAN and AI‑RAN alliances, with Bell Labs and at least two external partners already building sensing and location applications on the platform.



Software subscription tied to value: The commercial model builds on existing software subscriptions but ties pricing more explicitly to delivered value, such as spectral efficiency improvements and new AI services, rather than pure license metrics.




Mukherjee emphasized the openness angle in the briefing: “We see a lot of third‑party applications, whether it’s improving spectral efficiency or location service or sensing, can be developed on this platform… any AI‑powered services from us in Nokia or from ecosystems can be actually developed on top of it.” For operators burned by closed optimization stacks, that’s a notable pivot.



How AI-RAN unlocks new revenue



Most operators will sign off on AI‑RAN if the capacity and TCO story holds, but the more strategic question is monetization beyond connectivity. Nokia’s spokespeople spent considerable time on this in the analyst call, pointing to several classes of services that are difficult or impossible to deliver without AI running in the RAN itself.



Examples include:




Integrated sensing: Turning the RAN into a distributed sensor grid that can support applications such as 3D mapping, gesture recognition and environmental monitoring, using the same RF infrastructure. Mukherjee noted, “We have at least two to three partners developing sensing applications on top of it… as well as two other companies developing location services.”



Physical AI and location services: For factories, logistics hubs and smart cities, AI‑RAN can provide high‑precision positioning and real‑time telemetry for robots, drones and autonomous systems by fusing radio data and AI models at the edge.



Distributed AI infrastructure: Operators exploring “AI‑native cities” can use AI‑RAN nodes and COTS GPU servers as a distributed inference fabric for applications that need tight latency to endpoints—think AR/VR offload, real‑time video analytics or interactive generative AI experiences.



Premium connectivity tiers: With fine‑grained, AI‑driven control over uplink/downlink scheduling and QoS, operators can create differentiated SLAs for enterprise slices, mission‑critical IoT and AI workloads, charging for guaranteed performance rather than best‑effort connectivity.




Ed framed the opportunity as a continuum: Superior connectivity from 2x spectral efficiency creates “space for new AI workloads and other use cases,” while the D‑apps ecosystem and subscription model provide a mechanism to package and sell those capabilities. In practice, that could look like:




Industrial sensing-as-a-service, where Nokia and partners supply D‑apps for integrated sensing and positioning, and operators monetize them per site or per device.



Network‑exposed APIs for inference, location and RF sensing, integrated into operators’ broader network API portfolios as they pursue “network-as-a-platform” strategies.



Sector‑specific AI‑native services, such as stadium analytics, transportation corridor monitoring, or drone traffic management, built by ISVs on top of Nokia’s exposed E3 data.




For operators that already use Nokia’s MantaRay and SMO stacks for cross‑network optimization, AI‑RAN essentially becomes the local real‑time execution environment, while R‑apps/X‑apps continue to orchestrate macro-level behaviors. Mukherjee described this layered architecture as “DU and CU on the platform running D‑apps using E3, interfacing to X‑apps and R‑apps through E2SM and connecting to the overall management system/SMO for lifecycle management.”



Adoption path and reality check



Nokia is not promising instant transformation. AI‑RAN pilots are slated for late 2026, with commercial availability on card‑based systems in 2027 and AirScale-based systems around 2028, all driven from a single software stack that supports 4G, 5G and is upgradable to 6G. The company already has trials and collaborations underway with T‑Mobile US, SoftBank, Indosat Ooredoo Hutchison, BT, Elisa, Vodafone, Orange, NTT Docomo, Deutsche Telekom and others.



There are still open questions around 3GPP vs ORAN standardization of E3, the maturity of the D‑apps ecosystem, and how operators will digest yet another subscription layer tied to radio software. But Nokia’s move puts a stake in the ground: in the AI era, the RAN is not just a throughput engine; it’s a programmable AI computer that can be monetized.



For Network World readers evaluating vendor roadmaps, this launch suggests a clear directional change. If Nokia hits its targets, AI‑RAN could mark the point where baseband becomes less about hardware SKUs and more about an AI platform strategy—one where spectral efficiency and new services are rolled out at “software speed,” as Ed described it, rather than at the pace of the next card generation.



CVE-2026-8223 | Open5GS up to 2.7.7 sm-policies Endpoint pcf_sess_sbi_discover_and_send denial of service (Issue 4438)
Fri, 24 Jul 2026 09:59:16 +0200
A vulnerability was found in Open5GS up to 2.7.7. It has been rated as problematic. Affected by this vulnerability is the function pcf_sess_sbi_discover_and_send of the component sm-policies Endpoint. Performing a manipulation results in denial of service.

This vulnerability is cataloged as CVE-2026-8223. It is possible to initiate the attack remotely. Furthermore, there is an exploit available.

The project was informed of the problem early through an issue report but has not responded yet.


CVE-2026-8222 | Open5GS up to 2.7.7 sm-policies Endpoint src/pcf/nbsf-handler.c pcf_nbsf_management_handle_register denial of service (Issue 4437)
Fri, 24 Jul 2026 09:59:11 +0200
A vulnerability was found in Open5GS up to 2.7.7. It has been declared as problematic. Affected is the function pcf_nbsf_management_handle_register of the file src/pcf/nbsf-handler.c of the component sm-policies Endpoint. Such manipulation leads to denial of service.

This vulnerability is listed as CVE-2026-8222. The attack may be performed from remote. In addition, an exploit is available.

The project was informed of the problem early through an issue report but has not responded yet.


CVE-2026-8225 | Open5GS up to 2.7.7 delete Endpoint src/pcf/sm-sm.c pcf_npcf_smpolicycontrol_handle_delete denial of service (Issue 4440)
Fri, 24 Jul 2026 09:59:02 +0200
A vulnerability identified as problematic has been detected in Open5GS up to 2.7.7. This affects the function pcf_npcf_smpolicycontrol_handle_delete of the file src/pcf/sm-sm.c of the component delete Endpoint. The manipulation leads to denial of service.

This vulnerability is documented as CVE-2026-8225. The attack can be initiated remotely. Additionally, an exploit exists.

The project was informed of the problem early through an issue report but has not responded yet.


CVE-2026-12877 | Project Management, Bug and Issue Tracking Plugin up to 5.0.x on WordPress Issue-Tracker Configuration improper authentication
Fri, 24 Jul 2026 09:40:17 +0200
A vulnerability was found in Project Management, Bug and Issue Tracking Plugin up to 5.0.x on WordPress. It has been classified as critical. This affects an unknown function of the component Issue-Tracker Configuration. Performing a manipulation results in improper authentication.

This vulnerability was named CVE-2026-12877. The attack may be initiated remotely. There is no available exploit.

Upgrading the affected component is recommended.


CW@60: The mirror and the machine - three decades on the frontlines of the tech revolution
Fri, 24 Jul 2026 09:17:01 +0200
Every technology innovation and every IT project is, at its heart, a human-interest story - and those delivering the IT should always remember that, says IT services veteran Sam Kingston


World's First Wave Power Generator Receives Certification For Regular Use
Fri, 24 Jul 2026 09:10:23 +0200
"The Norwegian certification agency DNV has certified the commercial wave-driven power generator Corpower C4 for regular use," writes Longtime Slashdot reader Qbertino. "German news site heise.de has a detailed write-up. See a CGI video of the power station and its internals, as well as the company's website [at their respective links]." From the report (translated to English): According to the manufacturer Corpower Ocean, it is the first DNV prototype certificate for a wave energy converter. The certificate confirms that Corpower's technology meets DNV's requirements for structural strength, reliability, and safety, Corpower Ocean announced. The certification process began in the design phase and lasted seven years. DNV oversaw the process from concept development through design, manufacturing, and assembly, to dry-running tests and subsequent operation.
 
This is an important step, said Patrik Moller, CEO and one of the founders of Corpower Ocean. With the certification, wave energy is no longer just a promising technology, but a proven and financially viable one. This opens up new opportunities for project financing, insurance, and investments in commercial applications. The Corpower C4 wave power plant looks like a normal buoy: It consists of a 19-meter-long floating body with a diameter of 9 meters and a weight of approximately 11 tons. The system is anchored to the seabed. A mechanism inside the buoy converts its up-and-down movements in the waves into a rotary motion. This, in turn, drives a generator that produces electricity. The report notes that the company is "planning the first two industrial-scale wave energy farms off the coasts of Portugal and Scotland," which are scheduled to begin operating sometime between 2027 and 2029.






Read more of this story at Slashdot.


Russian-Linked Hackers Target Zimbra Users With Zero-Day Exploit
Fri, 24 Jul 2026 08:25:49 +0200
A Zimbra phishing campaign attributed to Russian state-supported cyber actors has targeted Western government and commercial organizations, exploiting CVE-2025-66376 to access sensitive email data and other information, according to a joint cybersecurity advisory issued in July 2026.

The activity has been linked primarily to LAUNDRY BEAR, a Russian state-supported advanced persistent threat (APT) group tracked under several names across the cybersecurity industry. The advisory said the campaign has been active since at least July 2025 and has targeted organizations using the Zimbra Collaboration Suite (ZCS).

Unlike conventional phishing attacks that typically require victims to click a malicious link or open an attachment, the campaign uses a view-based exploit. A user only needs to view a malicious email in a vulnerable version of ZCS webmail for the exploit to attempt execution.
Zimbra Phishing Campaign Uses CVE-2025-66376
The campaign centers on CVE-2025-66376, a vulnerability that was initially exploited as a zero-day vulnerability before a patch was released. According to the advisory, the activity began in July 2025, months before the vulnerability was published and patched.

The vulnerability allows a JavaScript payload contained in email content to execute because of improper sanitization of CSS @import directives within an email. The malicious payload uses Base64 encoding and XOR encryption and can be modified to help bypass basic threat detection signatures.

Once triggered, the payload attempts to collect and exfiltrate information through 12 stages. These include gathering the victim's email address and environment information, collecting two-factor authentication codes and application passwords, attempting to capture saved passwords, enabling mail protocols, gathering the Global Address List (GAL), and sending archived email data.

The advisory said the campaign's use of a zero-day exploit demonstrates the ability of LAUNDRY BEAR to operationalize novel vulnerabilities into a successful attack capability.
LAUNDRY BEAR Targets Email and Sensitive Data
The primary objective of the Russian state-supported cyber actors appears to be the covert acquisition of email data. The campaign attempts to steal the last 90 days of email communications, email addresses, passwords, the organization's Global Address List, 2FA tokens and newly created application passcodes.

The actors have targeted organizations connected to the defense industrial base, government, education, energy, law enforcement, media, non-governmental organizations and technology sectors.

The advisory said LAUNDRY BEAR likely identifies organizations with publicly exposed Zimbra infrastructure through port scanning and commercially available datasets. It may then compile individual user email addresses using commercial data, open-source intelligence or previously exfiltrated information.

The group has also used compromised accounts to distribute phishing emails. Since at least November 2025, malicious emails were reportedly sent from victim infrastructure, potentially using previously compromised accounts to make the activity harder to detect and to bypass anti-phishing measures.
Ulej and Flowerbed Support Email Data Exfiltration
The campaign uses a custom capability called Ulej, which was developed to exploit ZCS and exfiltrate sensitive information. The collected data is sent to infrastructure associated with the Flowerbed framework.

Flowerbed is a Python project using Docker and includes four containers: Catcher, Certbot, Nginx and Gardener. Catcher receives and aggregates stolen information, while Nginx operates as an HTTPS reverse proxy. The framework uses DNS and HTTPS channels for email data exfiltration.

The advisory said the campaign can exfiltrate email content, contacts, attachments, authentication information and other data. The stolen information is initially stored by Catcher before being transferred to non-public-facing infrastructure.

The report also noted indications that artificial intelligence may have played a role in developing the Flowerbed codebase, highlighting the increasing use of AI in developing malicious capabilities.
Organizations Urged to Patch Vulnerable Zimbra Systems
The advisory urged organizations using ZCS to immediately ensure their systems are not running vulnerable versions. A patch for CVE-2025-66376 was released for ZCS versions 10.1.13 and 10.0.18.

If immediate patching is not possible, organizations are advised to have employees use alternative mail clients and avoid the Classic ZCS webmail client until the software is updated.

Security teams are also advised to monitor internet-connected ZCS systems, workstations accessing those systems and network traffic for signs of suspicious activity. Recommended monitoring includes looking for large outbound data transfers to unfamiliar VPS providers, unusual DNS queries with random subdomains, sudden connections to newly established domains and connections involving VPN providers such as Mullvad.

Organizations should also consider authentication services that support passkeys and maintain network monitoring, packet capture or NetFlow data and relevant logs.

The advisory further recommends that organizations identifying victims revoke Application Passcodes and 2FA scratch keys and require affected employees to change their passwords. Security teams should also investigate the original phishing email and quarantine similar messages to prevent further exploitation and data theft.


Fix App Not Installed As Package Appears To Be Invalid
Fri, 24 Jul 2026 07:15:26 +0200
Key TakeawaysIssue of 'App Not Installed As Package Appears To Be Invalid' arises from non-Play Store app installations on Android devices.Troubleshooting steps include restarting the device, checking storage availability, downloading the app again from a reliable source, verifying device architecture compatibility, disabling Google Play Protect temporarily, deleting existing app data, resetting app preferences, and trying […]
The post Fix App Not Installed As Package Appears To Be Invalid appeared first on iTech Hacks.


The race to collect every book ever written
Fri, 24 Jul 2026 06:21:26 +0200
When the FBI seized Z-Library, it looked like the end of illegal book sharing. Now, its pirate project is central to the AI revolution


Desktop v0.0.4
Fri, 24 Jul 2026 04:02:06 +0200

Start chatting without opening a project folder — the app now supports workspace-free chat sessions.
New first-run onboarding flow to get you set up on launch.
Drag and drop files directly onto the chat to attach them.
Image attachments now display inline in the chat transcript.
Schedule one-time routines (not just recurring ones), with navigation to jump to a routine's run.
New custom overlay title bar with in-app navigation.
Redesigned channel setup as expandable cards.
Added a setting to replay the new-user experience.
Cleaner chat markdown rendering, and external links now open correctly in your browser.
Agent sessions now use agentic compaction by default, keeping long conversations within context more intelligently.
Fixed the agent not finding gh and other CLI tools by resolving your login shell's PATH.
Headless routines now default to YOLO mode so they can run unattended.
Fixed request metering for the SAP AI Core provider.

Full Changelog: desktop-v0.0.3...desktop-v0.0.4


Microsoft launches new in-house AI models it says cut costs up to 89% versus OpenAI
Fri, 24 Jul 2026 02:50:17 +0200
Microsoft AI released two new in-house models into public preview on Wednesday — MAI-Image-2.5-Pro, its highest-fidelity image generator to date, and MAI-Voice-2-Flash, a speech model built for high-volume enterprise workloads — while publishing production data that amounts to the company's most aggressive argument yet that it can power its own products without leaning on OpenAI's frontier models.
The announcement, made by Microsoft AI's Superintelligence team, lands roughly a year after the company committed to building purpose-built models internally, and it arrives with an unusual level of specificity about where those models now run: Bing, PowerPoint, OneDrive, Dynamics 365, Excel, GitHub Copilot, and Azure. The message to enterprise buyers — and, implicitly, to OpenAI — is that Microsoft's homegrown models are no longer research projects. They are production infrastructure serving millions of users.
"Each of these enhancements is a step toward the same goal: Microsoft products, powered by Microsoft models," the company wrote in its announcement blog.
How MAI-Image-2.5-Pro and MAI-Voice-2-Flash stake out opposite ends of the AI cost curve
The two new releases occupy opposite ends of what Microsoft calls the quality-speed-cost curve, and the positioning is deliberate. MAI-Image-2.5-Pro targets the premium tier: hero imagery, detailed editing, and precise in-image text rendering — the last of which has long been a notorious weak spot for image generation models. Microsoft priced the model at $5 per million text input tokens, $8 per million image input tokens, and $106 per million image output tokens. The base MAI-Image-2.5 model recently launched at No. 2 for image editing on Arena, the community leaderboard that has become a de facto scoreboard for generative media.
The creative industry appears to be taking notice. Rob Reilly, global chief creative officer at advertising giant WPP, called the Pro model "a strong leap forward for GenMedia tools" in a statement included in Microsoft's announcement, adding that "Microsoft has firmly established itself among the leaders in generative AI."
MAI-Voice-2-Flash goes the other direction. First previewed at Microsoft's Build conference, Flash runs twice as fast as MAI-Voice-2 and costs 32% less, priced at $15 per million characters. It is designed for the unglamorous but enormous market of high-volume voice — call centers, voice agents, and real-time speech applications where latency and cost-per-call matter more than marginal gains in expressiveness. Together, the two models reflect a strategy of building families of models rather than a single flagship, because, as the company put it, a creative studio chasing maximum fidelity has very different needs from a customer service operation handling millions of calls a day.
Microsoft's production metrics show in-house models cutting GPU costs by up to 89%
The model launches are arguably less newsworthy than the deployment metrics Microsoft attached to them — numbers that read like a systematic case for swapping out third-party frontier models across its product portfolio. 
Bing Image Creator now runs entirely on MAI-Image-2.5, end to end, marking the first time the consumer image tool is fully in-house. In PowerPoint, Microsoft says MAI-Image-2.5 reduces GPU costs by up to 84% compared with GPT-Image-2, OpenAI's image model. In OneDrive, where MAI-Image-2.5 is now the default for key image-editing scenarios, the company reports a 26% increase in save rates, roughly 25% lower P95 latency, and 2.5 times greater efficiency under medium-utilization production workloads.
On the voice side, MAI-Voice-2-Flash now powers Dynamics 365 Contact Center — the platform used by customers including T-Mobile and EasyJet — where Microsoft claims GPU cost reductions of up to 89%. The model is also integrated into Azure Voice Live for developers building speech-to-speech agents.
Perhaps the most consequential deployment sits in healthcare. Microsoft's Dragon Copilot, used by 170,000 medical providers and responsible for processing 28 million patient encounters last quarter, now runs on MAI-Transcribe-1.5 for its multilingual workflow across 58 languages. Microsoft says internal evaluations show a 50% relative reduction in both transcription and language-identification error rates across most languages — a meaningful claim in a domain where transcription errors can propagate directly into clinical notes.
Inside the 'hill-climbing' strategy that lets small models beat GPT-5.6 in Excel
In a companion post published the same day, Microsoft detailed the methodology behind these results — what it calls its "hill-climbing machine," an integrated flywheel of data, models, and the product "harness" that surrounds them.
The clearest example is MAI-Code-1-Flash, the lightweight coding model launched in GitHub Copilot in June. Microsoft says the model achieves an approximately 10% higher code accept rate than GPT-5.4 Mini and Claude Haiku 4.5 in VS Code, while using 10% fewer median tokens. Developer retention tells a similar story: users were 6% more likely to return across multiple days than with GPT-5.4 Mini, and 11% more likely than with Claude Haiku 4.5.
Then Microsoft did something more interesting. It took the MAI-Code-1-Flash checkpoint and further trained it inside an Excel reinforcement learning environment, teaching a coding model the tools and workflows of spreadsheet knowledge work. The result, according to production user feedback, is a model on par with GPT-5.6 for the most common Excel tasks — while being small enough to run on Nvidia's older H100 and even A100 GPUs rather than requiring the latest-generation accelerators.
That hardware detail deserves emphasis. Every major AI company is fighting for allocation of cutting-edge chips, and a model that delivers frontier-adjacent quality on two-generation-old silicon fundamentally changes the deployment economics. It also frees the newest hardware — including Microsoft's now-operational GB200 cluster — for training rather than serving.
Satya Nadella's 'frontier diffusion' manifesto redraws the OpenAI relationship
Microsoft CEO Satya Nadella framed the announcements in a lengthy post on X titled "Frontier Diffusion & Control," which functions as something close to a strategic manifesto. "We can now take saturated frontier capabilities and deliver them at scale and at lower cost through models optimized for high-usage products, while continuing to use frontier models for frontier needs," Nadella wrote, adding that Microsoft is "beginning to route traffic across our first-party surfaces to MAI whenever our models match or outperform frontier alternatives."
Translated from executive prose: capabilities that were state-of-the-art a year ago are now table stakes, and Microsoft believes it can replicate them cheaply for the specific, repetitive tasks that dominate real product usage. Why pay frontier prices for a frontier model when a user just wants to reformat a spreadsheet column?
Nadella was careful to note that "frontier models from OpenAI and Anthropic are part of the orchestration system alongside MAI" — but he also articulated a pointed principle of model independence, arguing that a company's evaluations "should continue to hill climb even when any given model has been removed." 
“Keeping the harness, memory, context, and skills outside the model, he argued, is what gives Microsoft control. The subtext is hard to miss. Reuters reported in April that Microsoft’s exclusive license to OpenAI’s technology had been revised into a non-exclusive arrangement, and The Information reported last September that Microsoft had begun incorporating Anthropic models into some products. Wednesday’s announcement completes the triangle: Microsoft as orchestrator, with its partners’ frontier models as interchangeable components and its own models absorbing an ever-larger share of routine traffic.”
Developers cheer cheaper task-specific models while skeptics question Microsoft's track record
The response online captured both the appeal and the skepticism surrounding the strategy. "I love when people use small models for niche tasks," wrote one X user, @mavihsk, responding to Nadella's post. "Why do I have to use the all-knowing model just to change my field in Excel?" Another user, @nabu_lines, distilled the pitch neatly: "cost and performance both improve when you stop overusing the biggest model."
Others were less charitable about Microsoft's execution track record. "Microsoft is the worst when it comes to listening to user feedback," wrote designer @designedbyabin, arguing the company "will lose the AI race because they repeatedly failed to understand user needs." And one user, @tokenoverflow, offered a drier critique of the model-independence pitch: "i want it keep hill climbing after removing microsoft."
The skeptics raise a fair point. Microsoft's self-reported metrics — accept rates, save rates, GPU savings — come from its own internal evaluations, not independent benchmarks, and the company chooses which comparisons to publish.
But the strategy's logic does not depend on any single number. Nadella's framing that software now has "real marginal cost for the first time" explains why Microsoft is obsessive about tokens, GPUs, and serving costs: when AI features run on every keystroke across a billion-user product portfolio, an 84% GPU cost reduction is not an optimization. It is the difference between a viable business and a money pit.
Why Microsoft is turning its internal AI playbook into an Azure product
The final piece of the strategy is that Microsoft is selling the playbook, not just the models. Nadella explicitly positioned the hill-climbing approach as "a template for every other AI native, SaaS, or Enterprise company," and Microsoft is packaging the toolchain through Foundry and what it calls Frontier Tuning — letting enterprises train specialized models against their own proprietary evaluations and reinforcement learning environments. That turns Microsoft's internal cost-cutting exercise into an Azure product, and it gives enterprise customers a reason to run their AI workloads on Microsoft's cloud even if the models themselves come from elsewhere.
The company's emphasis on models trained "on clean, traceable, enterprise-grade data, without distillation from third-party models" serves the same commercial end. In an industry facing mounting scrutiny over training data provenance, Microsoft is betting that enterprise buyers — and courts — will care where model capabilities come from. Microsoft says it is now extending the hill-climbing approach to Copilot Chat, Outlook, and PowerPoint, and both new models are available in public preview through Microsoft Foundry and the MAI Playground. "None of this is an endpoint," the company wrote. "We're just getting started."
Seven years ago, Microsoft bet more than $13 billion that OpenAI would build the future of AI. Wednesday's announcement suggests the company has since learned a cheaper lesson: the future of AI may belong to whoever builds the frontier, but the profits belong to whoever makes it ordinary.


CVE-2026-8267 | Open5GS up to 2.7.7 SMF smf_nsmf_handle_created_data_in_vsmf denial of service (Issue 4448)
Fri, 24 Jul 2026 02:09:56 +0200
A vulnerability was found in Open5GS up to 2.7.7. It has been classified as problematic. This vulnerability affects the function smf_nsmf_handle_created_data_in_vsmf of the component SMF. This manipulation causes denial of service.

This vulnerability appears as CVE-2026-8267. The attack may be initiated remotely. In addition, an exploit is available.

The project was informed of the problem early through an issue report but has not responded yet.


CVE-2026-8266 | Open5GS up to 2.7.7 SMF /src/smf/gsm-build.c gsm_build_pdu_session_establishment_accept denial of service (Issue 4447)
Fri, 24 Jul 2026 02:09:55 +0200
A vulnerability was found in Open5GS up to 2.7.7 and classified as problematic. This affects the function gsm_build_pdu_session_establishment_accept of the file /src/smf/gsm-build.c of the component SMF. The manipulation results in denial of service.

This vulnerability is reported as CVE-2026-8266. The attack can be launched remotely. Moreover, an exploit is present.

The project was informed of the problem early through an issue report but has not responded yet.


CVE-2026-8268 | Open5GS up to 2.7.7 SMF OpenAPI_list_create denial of service (Issue 4449)
Fri, 24 Jul 2026 02:09:54 +0200
A vulnerability was found in Open5GS up to 2.7.7. It has been declared as problematic. This issue affects the function OpenAPI_list_create of the component SMF. Such manipulation leads to denial of service.

This vulnerability is traded as CVE-2026-8268. The attack may be launched remotely. Furthermore, there is an exploit available.

The project was informed of the problem early through an issue report but has not responded yet.


HPR4690: Playing Civilization V, Part 14
Fri, 24 Jul 2026 02:04:41 +0200
This show has been flagged as Clean by the host.

In our sample game we look at playing as Austria and aiming for a Diplomatic Victory. And our focus is on puppeting City-States, but I misunderstood and instead of making a Diplomatic Victory easier, it makes it harder. I still managed to get my Diplomatic Victory, but a Science or Domination Victory would definitely have been easier in this scenario.

Playing Civilization V, Part 14

Now I am at turn 340, I just puppeted another City-State, and I have one more on the way. I have sent a large number of military units, both land and sea, to the City-States that are on Japan’s border. If he tries anything now he will likely regret it. Now I am starting to build things I had not bothered with before, like Granaries and Amphitheaters. I got a couple of Great Engineers, and used them to rush build Wonders. I am nearly finished puppeting all of the City-States, and my Happiness and Income are both quite healthy. I am in such good shape I started to build the World’s Fair, which I initally proposed then ignored.

At this point I only have one more City-State to puppet, then I will have puppeted every City-State in the game. So it is time to put my large income to use in other ways by giving gifts to the other players. I may want to get a few more votes on my side to get over the top in the World Leader vote when it happens. On turn 357 I completed the puppeting of all of the City-States in the game. Meanwhile, I am building up my Science and building Wonders as they become available. I didn’t build any in the early game because I had other priorities, but now I have a strong military, high income, and no other pressing needs. My score on the Leader Board is now double that of my nearest competitor which is still Japan. And their denunciation me of just expired with them taking no action.

I used a Great Engineer to rush build the Porcelain Tower, earning me another Great Scientist, which I then used to build another Academy. At this point it is mostly a slog to the finish. Since I was so dominant and so wealthy I could afford to pursue a couple of other options just in case. One was a Science victory, which looked like a possibility, though it would be close. I had to be very focused in my Science Research. The other option was a Culture victory, and I had dominated two other empires culturally without half trying, and I was generating Great Artists, Great Musicians, and Great Writers pretty rapidly. So I built Museums, then Archeologists, and grabbed every artifact I find to stuff into the Museums. But the final Victory came when I researched Globalization. This tech allows you to get an extra vote in a World Council for every Spy you send to another empire’s capital and designate as an Ambassador. I immediately sent my spies out (they had previously been in my cities doing counter-espionage since I had a tech lead). And a few turns later a vote for World Leader came up and I won.

This was my first time using Maria Theresa of Austria as my leader, and it was fun, but in the end puppeting all of the City-Staters actually made it harder to win a Diplomatic victory. In other games I have played, every City-State that was an ally was an extra vote in the World Council, and I assumed that making them puppets would mean I would get that many votes. But that didn’t happen. Of course, if I had read more carefully in the Civilization Wiki I would have realized this, because it says there very clearly that Austria is one of the worst Empires to pick if you are going for a Diplomatic victory. So the fact that I managed it anyway is nice. I think I actually could have done a Science victory as I had my Spaceship half-built when I won the Diplomatic Victory. But I hope this analysis of how I actually played this game will be helpful to someone else.

Links

https://www.palain.com/gaming/civilization-v/playing-civilization-v-part-14/



Provide feedback on this episode.


CVE-2026-8261 | Squirrel up to 3.2 squirrel/sqobject.cpp SQFunctionProto::Load heap-based overflow (Issue 326)
Fri, 24 Jul 2026 01:44:08 +0200
A vulnerability classified as critical has been found in Squirrel up to 3.2. This affects the function SQFunctionProto::Load of the file squirrel/sqobject.cpp. This manipulation causes heap-based buffer overflow.

This vulnerability is tracked as CVE-2026-8261. The attack is restricted to local execution. Moreover, an exploit is present.

The project was informed of the problem early through an issue report but has not responded yet.


Agentic coding goes hands free as OpenAI brings GPT-Live's full duplex voice control to Codex and ChatGPT on the desktop
Fri, 24 Jul 2026 00:20:42 +0200
Two weeks after debuting its more naturalistic GPT-Live audio AI model with full-duplex capabilities (listening and speaking at the same time), OpenAI is bringing it directly into developer workflows. 
The company announced that GPT-Live now powers the ChatGPT desktop application on macOS and Windows, integrating directly with agentic systems like Codex and ChatGPT Work (which are separate experiences available in the ChatGPT desktop app). 
When OpenAI initially launched GPT-Live on July 8, 2026, it introduced a continuous audio model capable of listening and speaking simultaneously—eliminating rigid turn-taking while delegating complex reasoning to background models like GPT-5.5. 
Today's release expands that conversational layer to technical tasks, enabling software engineers to orchestrate multi-threaded coding jobs, review pull requests, and debug applications using natural voice commands.
As such, it could usher in a new era of "hands free" software development and even live, in-person group coding parties for Codex's more than 5 million weekly active users. Codex, of course, is the name given to OpenAI's models and harness focused on coding, but which the company has this year expanded into a more general productivity platform. An OpenAI spokesperson told VentureBeat this is the first time voice activation has been included natively with Codex on the desktop. 
OpenAI posted a promotional video showing some of its employees, Codex developer experience engineer Jason Liu and Codex technical staffer Guinness Chen, speaking to the same ChatGPT desktop app session in the same room, each issuing different instructions and conversing with the same model. 
New capabilities unlocked
At its core, this integration relies on decoupling the real-time voice layer from the underlying execution engines.
While GPT-Live maintains fluid conversation—inserting natural verbal acknowledgments like "got it" without interrupting the user—it passes heavy computational workloads to background reasoning models. 
On macOS, the desktop application incorporates "Appshots" and screen context features, allowing ChatGPT Voice to analyze the frontmost window alongside local files, codebase structures, and active plugins.
This architecture creates a pair-programming dynamic where developers talk through problems conversationally while agents execute tasks asynchronously. 
Rather than manually stopping coding sessions to type detailed instructions or switch windows, developers direct the system hands-free. 
The full-duplex engine dynamically decides when to speak, pause, or invoke tools, maintaining conversational state even as background agents process complex code modifications.
Directing coding and complex builds with your voice alone
The central operational capability in this update centers on multi-task execution across Codex and ChatGPT Work environments. 
Software engineers can initiate multiple concurrent task threads from a single spoken prompt. For instance, a developer preparing to ship a feature can instruct the system to investigate an open authentication bug, review a pending API migration pull request, and generate missing unit tests simultaneously.
The desktop application coordinates these actions across disparate contexts, tracing issues through Slack conversations, GitHub repositories, and local codebases.
Developers can also verbally convert design mockups into working code, splitting tasks across frontend, backend, and testing layers. 
With support for multi-folder projects (build 26.715) and remote execution via iOS, engineers can check task progress, answer agent prompts, and redirect active jobs without switching applications or managing individual processes line by line.
Proprietary license
OpenAI’s voice-enabled desktop release operates under a proprietary, commercial enterprise model. Access is restricted to paid subscribers across Plus, Pro, Business, Enterprise, and Education plans.
For individual developers and corporate engineering departments, this commercial structure means the model weights, voice processing pipelines, and agent state architectures remain fully closed. 
Organizations cannot modify or self-host the underlying systems. Furthermore, tasks initiated via ChatGPT Voice consume standard usage allocations directly from existing Codex and ChatGPT Work plan quotas, treating voice-triggered actions identically to standard agentic workloads.
Community reactions
Developer communities immediately noted the implications of bringing continuous full-duplex voice to autonomous coding workflows. 
Reacting to the build 26.715 release announcement—which details voice integration and multi-folder project support—AI Insider journalist @ChrisGPT noted on X: "Today OpenAI will release voice and remote guidance for codex ! One step closer to personal AGI". 
Early technical feedback highlights widespread enthusiasm for orchestrating complex agentic tasks hands-free, particularly when stepping away from the workstation or managing build pipelines remotely.


I built a Linux filesystem benchmark for corruption, snapshots, rebuilds and ENOSPC across 26 storage layouts
Fri, 24 Jul 2026 00:13:06 +0200
Most filesystem benchmarks measure throughput on a freshly formatted single device. That is useful, but it misses many of the reasons people choose btrfs, ZFS or bcachefs in the first place.
 I built modern-fs-benchmark to examine modern filesystems as complete storage systems, including their features, failure modes and behavior over time.
 The current matrix contains 26 configurations across btrfs, ZFS, bcachefs, ext4 and XFS over md/LVM, dm-integrity, native and LUKS encryption, parity layouts, and XFS on a ZFS zvol.
 Hosted CI dashboard:
 https://bartosz.fenski.pl/modern-fs-benchmark/
 Experimental real-hardware dashboard:
 https://bartosz.fenski.pl/modern-fs-benchmark/real-hw/
 Apache-2.0 licensed source and complete methodology:
 https://github.com/fenio/modern-fs-benchmark
 The raw benchmark datasets are published under CC BY 4.0. Every result records the kernel and filesystem tool/module versions. CI artifacts also contain a full command trace, so the exact workload is inspectable rather than hidden behind a chart.
 Why I started this project
 Many filesystem benchmarks follow a familiar pattern: create a filesystem with mostly default options, mount it, run fio or another generic workload, and compare throughput.
 General-purpose suites such as the Phoronix Test Suite are useful for conventional performance comparisons, but they do not focus on the machinery that makes modern copy-on-write filesystems interesting.
 I wanted a benchmark designed around btrfs, ZFS and bcachefs as multi-device storage systems rather than treating them as interchangeable replacements for ext4 on a single freshly formatted disk.
 That means testing behavior such as:
 - Redundancy and degraded operation
 - Snapshot aging, scaling and reclamation
 - Compression and encryption
 - Reflinks and clone divergence
 - Fsync tail latency and responsiveness under load
 - Rebuild and scrub behavior
 - Near-full and hard-ENOSPC behavior
 - Data integrity and recovery from corruption
 Ext4 and XFS over md, LVM and dm-integrity are included as classic-stack baselines so the costs and benefits of integrated CoW designs can be compared with layered alternatives.
 Silent corruption is one particularly important example. When one redundant copy is deliberately corrupted behind the filesystem, checksumming filesystems such as btrfs, ZFS and bcachefs can identify the damaged copy and recover from a valid replica.
 Traditional md/LVM redundancy without data checksums can notice during a scrub that its copies disagree, but it cannot determine which one is correct. In my tests, some classic configurations returned corrupted data successfully without an application-visible error.
 The dm-integrity configuration shows that a classic layered stack can obtain integrity protection too, with a measurable performance cost.
 An important limitation
 The main dashboard uses loop devices on GitHub-hosted VMs. Absolute throughput numbers and small differences between filesystems should not be interpreted as hardware rankings.
 The hosted runs are primarily useful for:
 - Correctness and integrity outcomes
 - Comparisons within the same job
 - Large behavioral differences
 - Snapshot-aging and near-full shapes
 - Trends across repeated runs
 Real disks are required for meaningful absolute performance, concurrency scaling, device parallelism and mixed-media topologies.
 I am aware of this limitation and do not want the hosted dashboard to suggest more precision than the underlying environment can provide.
 The real-hardware experiment
 Kent Overstreet, the creator of bcachefs, made one of his Hetzner machines available for a real-hardware experiment.
 The server had two physical NVMe devices. It completed three full benchmark runs, which are available in the separate real-hardware dashboard. These runs provided meaningful absolute measurements and exposed concurrency behavior that cannot be observed when several loop devices share one virtual disk.
 During the fourth run, one NVMe controller entered the kernel’s dead state. The existing machine environment had its operating system on RAID0 across the two NVMe devices, so the hardware failure also made part of /nix/store unreadable and eventually prevented new SSH sessions.
 The incomplete fourth run is not being published as benchmark data. This was a failure of the underlying hardware, not a result attributable to any filesystem being tested.
 I am grateful to Kent for providing the machine and making the real-hardware experiment possible. Without that access, the three existing hardware runs would not exist.
 Where I would like to take it
 Better hardware would not merely produce more reliable throughput numbers. It would enable an entirely new class of tests designed for multi-device and multi-tier filesystems.
 I would eventually like to run the suite on a machine containing several storage classes, for example two HDDs, two SSDs and an NVMe device.
 That could support scenarios such as:
 - HDD, SSD and NVMe baselines using identical workloads
 - bcachefs foreground and background targets
 - ZFS HDD data vdevs with SSD special vdevs
 - Separate ZFS L2ARC and SLOG experiments
 - LVM dm-cache in writeback and writethrough modes
 - Metadata and small-block placement on faster media
 - Foreground latency during background migration
 - Contention between fast and slow storage tiers
 - Degraded operation and rebuild under application load
 - Performance before, during and after promoting or evacuating a storage tier
 These are the kinds of scenarios for which multi-device and multi-tier filesystems are built, but they cannot be represented honestly when every “device” is a loop file backed by the same cloud disk.
 I am considering either renting a suitable dedicated server or eventually building and hosting my own machine. Providers such as Worldstream offer configurations close to what I need, but the recurring cost is currently outside the project’s budget.
 For now, the benchmark will remain in its hosted-CI form for an unknown amount of time. The existing dashboard will continue to be useful for correctness, behavioral comparisons and regression tracking, but it cannot answer every real-hardware performance question or model complex mixed-media topologies.
 I am also open to running the suite on hardware provided by someone else. A useful environment would need Linux root access, clearly identified block devices that may be wiped, and enough uninterrupted access to complete repeated runs. The hardware description, methodology and resulting data would remain public.
 I would appreciate technical feedback:
 - Which current tests are misleading or unfair?
 - Which failure scenarios are missing?
 - Which mixed-media topologies would be most useful?
 - Which additional filesystems or layered stacks should be included?
 - Which results deserve deeper investigation?
 The methodology, implementation and raw results are public. If a filesystem is being tested in a way that misrepresents it, I consider that a bug in the benchmark.
 
   submitted by    /u/bfenski  
 [link]   [comments]


Who Doesn’t Love a Clean Floor? Here Are 25+ Vacuum Deals to Make It Happen
Thu, 23 Jul 2026 23:34:14 +0200
Get clean floors without sacrificing your whole weekend or your whole paycheck with these top CNET picks.


EU Fines Google $1 Billion For Breaking Digital Antitrust Regulations
Thu, 23 Jul 2026 23:07:00 +0200
The European Union fined Google more than $1 billion for allegedly using Google Play and Search to steer users toward its own services and apps at the expense of competitors. The Associated Press reports: Google had recently lost its appeal of a $4.5 billion antitrust fine imposed by the EU for throttling competition and reducing consumer choice through the dominance of its mobile Android operating system. The European Commission, the bloc's executive branch and highest antitrust enforcer, said it was acting in the interest of consumers after an investigation of Google.
 
"The best products should succeed because they're better, not because they're owned by the company running the search engine. And European consumers have a right to be told by app developers where to sign up to the best offers, even when the app store owner does not get a cut," said Teresa Ribera, the commission's Executive Vice President for Clean, Just and Competitive Transition.
 
Google's President of Global Affairs Kent Walker blasted the fine as "product degradation driven by a small group of self-serving complainants" that will have a negative impact on European businesses and consumers. He said that the EU's Digital Markets Act forces Google "to strip away real-time search features Europeans love -- like instant pricing and direct availability for hotels, flights, and restaurants -- and dismantle safety protections on Google Play."






Read more of this story at Slashdot.


Check Point hole grants unauthenticated attackers full SmartConsole admin privileges
Thu, 23 Jul 2026 22:25:55 +0200

		
					  
						




Check Point has confirmed that a critical security hole in its SmartConsole management tool, one that allows unauthenticated attackers to assume full admin privileges, is now being exploited in the wild. The vulnerability, CVE-2026-16232, was given a CVSS score of 9.3.



In its security alert, Check Point described the bug as one allowing an unauthenticated attacker to “obtain an application login token and use it to login via SmartConsole with full admin privileges and apply changes to the security policy and security configuration.”



The company has released a patch for the bug and also recommends that users “limit Trusted Clients, GUI clients, to trusted IP addresses/subnets.” That approach has always been a best practice, but practical networking realities today make it challenging to maintain. Check Point said that the exploit has impacted ten of its customers, all of whom it had notified directly.



Far worse than most



Frank Dickson, group VP for security at IDC, said this security hole is far worse than most.



“This hits harder than your average CVE because of where it lives,” he said. “The CVE targets the SmartConsole login on Check Point’s Security Management Server, the console that pushes policy to every gateway underneath it. Popping a gateway gets you one lock picked. Popping the management server is more like finding the One Ring: one stolen token to rule every gateway it manages, no need to fight each one individually. The attacker can rewrite policy, open new VPN paths and kill the logging.”



In an interview with CSO Online, Lotem Finkelstein, vice president of research at Check Point, said that the company learned of the vulnerability on Sunday, emailed customers the same day, and released the patch within 72 hours.



But when his team re-reviewed earlier logs, knowing what to look for, they spotted this hole being attacked as early as April, Finkelstein said.



The fact that, over the course of three months, the team only found ten organizations under attack, indicated that it has been very difficult for the attacker to find vulnerable systems, he noted; customers were, in the main, using secure settings to protect themselves.



Nonetheless, Finkelstein said, Check Point considers this hole to be “a severe vulnerability.”



Challenges of IP address restrictions



While it can be technically challenging to keep the IP address allowlists that Check Point recommends current, given DHCP’s ability to easily change those addresses, Assaf Morag, a cybersecurity researcher at Flare, noted that specifically limiting access to a management console is far more critical than limiting overall external access.



“Implementing Trusted Clients as a per-IP allowlist is impractical,” he said, but that is not the case with restricting management access. “The more scalable solution is to restrict access based on trusted administrative network segments such as VPN pools, management VLANs, or jump hosts rather than maintaining lists of individual DHCP-assigned client addresses,” he explained. “That gives you the security benefit without creating a full-time administrative task. Maintaining allowlists for individual hosts is much more practical when those hosts have stable, predictable IP addresses, rather than dynamically assigned DHCP addresses.”



Pieter Arntz, malware intelligence researcher at Malwarebytes, also noted that the constantly changing nature of global IP addresses can prove annoying to IT teams. Stressing that he is not familiar with Check Point’s specific settings, he noted, “Certain settings are a nuisance when applied strictly, and at some point the IT staff gets tired of constantly tweaking and they abandon the most secure path.”



Ideal platform for long-term attacks



Mike Wilkes, enterprise CISO at Aikido Security,  agreed that the severity and exposure of this hole is alarming.



“This is exactly the kind of vulnerability that keeps CISOs awake at night because it strikes at the one system that is supposed to stand between the attacker and everything else. An authentication bypass that grants administrative control of a perimeter firewall isn’t just another CVE to patch. It’s an invitation for an adversary to rewrite the rules of the network itself,” he said. “The uncomfortable reality is that nobody runs a CrowdStrike agent on their firewall. Once an attacker owns an edge device, they gain a uniquely privileged position that often falls outside the visibility of traditional endpoint security, making it an ideal platform for persistence, credential theft, traffic manipulation, and long-term espionage.”



IDC’s Dickson strongly encouraged CISOs to deploy the patch, not to just change settings to mitigate the issue. 



“Apply the actual hotfix,” he said. “Don’t just restrict Trusted Client IPs and call it done. That’s a stopgap, not a fix. Any internet-facing management console, Check Point or otherwise, is a five-alarm architecture problem independent of this CVE.”



And, he added, “since attackers here can disable logging, audit admin activity going back before the bug surfaced. Quiet logs aren’t proof nothing happened. This is the recurring theme with ‘single pane of glass’ security tools: the console built to make everything easier to run is also the one thing you really don’t want someone else driving.”



‘The Java Story’ recounts the rise, fall, and rise again of Java
Thu, 23 Jul 2026 22:04:52 +0200

		
					  
						




The evolution of Java is the subject of a just-released documentary about the programming language and development platform. “The Java Story: The Official Documentary” tells the story of Java through interviews with the engineers who created it and shepherded it through three decades.



Produced by CultRepo and sponsored by Oracle, JetBrains, IBM, and Azul, the documentary follows Java from its set-top box and browser-based origins at Sun Microsystems in the 1990s and through its rise to dominate server-side computing in the 2000s, the “dark ages” and resurgence with Java 8 under Oracle in the 2010s, and its continuing modernization and promising role in AI today. “From its humble beginnings as a project code-named ‘Oak’ at Sun Microsystems to becoming a global standard for enterprise software and billions of devices, Java’s journey is one of radical innovation, strategic pivots, and enduring community strength,” said Cult.Repo. 



The documentary also delves into Sun’s bitter Java licensing dispute with Microsoft, Oracle’s suit of Google over its use of Java APIs Android (Google won), the creation of the Java Community Process, Sun’s open-sourcing of Java, and Oracle’s switch to the six-month release cycle. Technical enhancements such as lambda expressions in Java 8, virtual threads in Java 21 (Project Loom), and the ongoing refactor to bring value objects to the Java object model (Project Valhalla) also get attention. 



Technical experts and other Java figures interviewed in the documentary include James Gosling, creator of Java; Kim Polese, Java’s first product manager; Carla Schroer, director of Java compatibility at Sun Microsystems; James Duncan Davidson, creator of Apache Tomcat; Mark Reinhold, chief architect of the Java Platform Group at Oracle; Brian Goetz, Java language architect in the Java Platform Group at Oracle; Rod Johnson, creator of Spring; and Gavin King, creator of Hibernate. 



Meta drops out of a major clean energy pact as its natural gas buildout accelerates
Thu, 23 Jul 2026 21:52:26 +0200
Meta has made significant investments in natural gas over the past year. Now, it's dropping out of an industry renewable energy group.


4 ways AI-driven defense is rewriting the cybersecurity playbook
Thu, 23 Jul 2026 21:34:50 +0200

		
					  
						




The cybersecurity landscape has evolved beyond human scale. Today’s adversaries have replaced predictable, manual playbooks with machine-generated attack chains that can breach traditional controls in seconds. To bridge the gap, organizations must move past legacy, reactive controls and embrace a fundamentally different, AI-driven architecture: Agentic Endpoint Security (AES). 



AES represents a paradigm shift, moving security from a passive monitor to an active participant in the defense lifecycle. It provides the visibility and automated guardrails necessary to govern autonomous AI agents and agentic tools, ensuring that as your workforce scales with AI, your security posture remains unbreakable. 



With autonomous AI agents now capable of planning and executing multi-stage attacks at machine speed, the pressure on traditional security operations (SOC) has reached a breaking point. To survive this shift, the strategy is clear: we must fight AI with AI. 



Here is how AI-driven defense, pioneered by Cortex XDR and the era of Agentic Endpoint Security, is fundamentally rewriting the cybersecurity playbook.




From reactive patching to proactive prevention 




For decades, the industry lived in a “wait-and-see” mode waiting for a vulnerability to surface, waiting for a signature, and then rushing to patch the hole. But reactive methods just don’t hold up against modern “frontier” AI attacks that are constantly morphing. 



AI-driven defense changes the game by shifting to a prevention-first architecture. Rather than relying on historical signatures, modern platforms deploy localized, ML-driven analysis to evaluate the intent and behavior of an active process, stopping threats pre-execution. Cortex XDR leads with a strict prevention-first approach by using AI-driven local analysis and behavioral threat protection; the XDR agent stops sophisticated threats pre-impact and pre-execution. This proactive stance reduces the overall risk profile by blocking malicious chains of events in real time across network, process, file, and registry activity. 



2. Eliminating the “agentic blind spot” 



As we all rush to adopt generative AI and automated workflows, a new gap has appeared: the “agentic blind spot.” Adversaries are now targeting AI assistants and automated scripts to bypass defenses. Since these digital agents often have deep access to enterprise data, a compromise here lets attackers move completely under the radar. 



The new playbook requires securing this entire ecosystem. By combining the distinct capabilities of Cortex XDR and Koi Security, organizations can effectively close this gap. Koi Agentic Endpoint Security tracks everything from shell commands to prompts in real time, while Cortex XDR adds a layer of defense that identifies and neutralizes behavioral anomalies unique to these automated threats. 



3. Machine-speed detection and “attack storylines” 



When an attacker can move through your network in seconds, human-led teams can’t keep up. To make matters worse, most systems just flood analysts with low-quality, isolated alerts, leading to major burnout. 



AI-driven defense fixes the investigation process by automatically stitching separate data points into a single, high-fidelity “attack storyline.” Cortex XDR uses thousands of machine learning detectors across endpoint, network, and cloud sources to group related signals into one cohesive case. This reveals the full story of an attack, letting your analysts focus on fast remediation instead of digging through piles of data, reducing alert noise by up to 98%. 



4. Surgical and autonomous response 



The final piece of the puzzle is moving from manual remediation to autonomous action. AI-driven response lets your SOC handle threats in minutes, not hours. The platform can automatically revoke compromised tokens or isolate endpoints at machine speed. 



Cortex XDR delivers built-in enterprise-grade automation at no additional cost, providing over 120 out-of-the-box playbooks and 18 quick actions to handle up to 99% of incidents without manual intervention. Crucially, this level of automation requires an unbreakable foundation of agent resilience. To ensure the defense cannot be disabled by an adversary, Cortex XDR is certified in both the AVC EDR Detection and Anti-Tampering tests, successfully blocking all attempts to disable or modify the agent. 



Summary



The threat landscape is changing faster than ever, driven by AI-powered attackers who exploit even the smallest gaps. But you don’t have to stay on the defensive. By shifting to a proactive, AI-driven architecture like the one built into Cortex XDR, you can stop threats before they happen, secure your agentic workflows, and automate away the noise that leads to analyst burnout. 



The journey to a more resilient, AI-powered SOC doesn’t have to be daunting. With the right foundation in place, you’re not just keeping pace with the new threat landscape; you’re staying one step ahead. It’s time to move beyond the old manual playbook and embrace the future of security operations. 



To learn more about Palto Alto Networks, visit https://www.paloaltonetworks.com.



New pip flag fixes longstanding Python frustration
Thu, 23 Jul 2026 21:27:38 +0200

		
					  
						




A new version of Python’s native package management tool, pip, will remove a limitation that has frustrated Python developers for years. If you wanted to install the dependencies for a given package, but not install the package itself, you were stuck. Either you had to extract the dependency list from the package and install it by hand, or you had to build the whole package anyway.



Why was this a problem? Sometimes, you want only the dependencies for a package—for instance, as a way to create a separate environment for testing or another project. If you’re making source distributions via CI, some requirements might be needed to make the source distribution but aren’t actually included in it (e.g., Cython). You would need to install these requirements somewhere—apart from the project itself—to perform the build step.



A dependencies-only install mode for packages is a long-requested feature. Developer James O’Claire found many examples of such requests, along with various workarounds. Most of those involved third-party solutions of some sort.



Now, a new feature set to land in pip version 26.2 will fix this problem from the inside. The command pip install --only-deps will install only the dependencies for a given package. Note that it will not install build dependencies for the package, but only runtime dependencies.



Note that you can accomplish this with existing third-party tools. For instance, uv sync --no-install-project has the same behavior. But having this functionality right inside pip means you don’t have to turn to external tooling—or ugly hacks—to solve the problem. This may be an example of how third-party projects like uv (a superfast Python package installer) are inspiring native Python features where they make sense.



pip 26.2 is scheduled to be released by the end of July 2026.



Multi-turn attacks broke AI models 88% of the time — single-turn testing missed it, Cisco AI security lead warns at VB Transform 2026
Thu, 23 Jul 2026 20:48:24 +0200
When Cisco ran 6,986 multi-turn attacks against 15 flagship models, attackers who adapted across the conversation broke through as often as 88.3% of the time. Amy Chang, Cisco's head of AI threat intelligence and security research, brought that finding to the agentic security panel at VB Transform 2026; the number should worry anyone still running single-turn red-teaming programs.
VentureBeat's June 2026 Pulse survey of 107 enterprise respondents explains why the room was full. More than half, 54%, have already had a confirmed agent security incident (18%) or a near-miss caught before harm (36%). Just 32% give every agent its own scoped, managed identity, and fewer still, 30%, isolate their highest-risk agents in sandboxes. Provider-native and hyperscaler controls remain the primary agent security layer at 82% of companies surveyed. The world's largest security vendors have done the same math. 
Palo Alto Networks closed its $25 billion acquisition of CyberArk in February, CrowdStrike agreed in January to pay $740 million for SGNL, and Cisco announced its intent to acquire Astrix Security for a reported $400 million, all of it aimed at the identity and isolation layer most enterprises have not finished building.
Chang came to the panel with almost two decades of experience spanning cybersecurity operations, government, and the military. She ran global cybersecurity operations as an executive director at JPMorgan Chase, where she led the bank's cyber threat intelligence teams, and served as a senior staffer on the House Foreign Affairs Committee and as a U.S. Navy Reserve officer. She also teaches cybersecurity and emerging threats as adjunct faculty at the Middlebury Institute of International Studies.
Chang's 88.3% number comes from a study she co-authored with Nicholas Conley, built on 30,090 single-turn prompts and 6,986 multi-turn attacks against those 15 closed and proprietary flagship models. Multi-turn success rates ranged from 7.89% to 88.3%, every model tested showed non-trivial multi-turn exposure, and the two testing styles did not even rank the models in the same order. Cisco publishes adversarial evaluation signals for what is now 105 models on its LLM Security Leaderboard, she told the audience.
"If you don't understand how models are susceptible to different types of attacks, then you are unable to account for how that model that is powering your agent, that is powering your application, to understand where those failure points are," Chang said. Single-turn testing is the one-shot malicious prompt, she explained, while extending an attack into a longer conversation "is more realistic of how we are actually engaging with our models, with our agents, with our applications." That longer arc surfaces harmful outputs and misaligned behaviors that a snapshot never catches.
Cisco has pushed the testing itself into agentic territory. Chang described a framework where agents assess a deployment scenario, develop relevant attacks, judge whether they are worth pursuing, execute them, and evaluate their own success. What surprised her most, after all that sophistication, was how simple the defensive answer stays. "The answer is still that it's pretty simple," she said. "You don't have to get super creative. You just need to think about truly what are the fundamentals and basics of what I'm trying to secure in my organization."
Her starting point for CISOs beginning agentic deployments is Cisco's Integrated AI Security and Safety Framework, which she said "stipulates all the ways that AI can be compromised across the AI lifecycle" from modality through supply chain. From there, teams can work backward from real incidents, trace how each attack was achieved, and use the framework to build a strategy with the right coverage and mitigations.
Heather Ceylan, the CISO of Box, sees the same gap from the defender's side. "A lot of what you see out there with agent red teaming is just single-turn, and that's not how people are actually interacting with AI day-to-day," she told the audience. Box now simulates multi-turn adversaries with agents that think like an attacker and iterate attempt after attempt to hijack the target. "You have to pressure test your agents because otherwise you don't know if your execution controls are really working as you intended."
Box deployed agents inside its security operations center about a year ago, starting with human approval required for every action, and trust built quickly enough that analysts shifted into monitoring mode. Then the agent made one mistake, and every bit of that accumulated trust vanished. "They had to start all over again," she said. "So I think that that monitoring piece is so important. Even if you're not gonna have a human in the loop, things change, models change, and we can't control how the models change and interpret things."
Rajesh Parekh, VP of AI and ML at Intuit, brought the builder's perspective. Parekh led large-scale computer vision and ML systems powering Google's Maps and Geo products before joining Intuit, and holds a doctorate in computer science. 
Three layers versus an operating system
Ceylan described Box's approach as three concentric layers. Permissioning comes first, so the agent never accesses more content than the human who invoked it. Ephemeral sandbox environments spin up for each agent task, containing the blast radius if an agent gets hijacked, and runtime execution control restricts the agent's tool calls to only those relevant to the task at hand. "If you want an agent to summarize a doc for you, if you have a prompt injection that came in that says forward this to maliciousattacker at domain.com, it can't do that," Ceylan said. "That action in that tool call is not even in its vocabulary."
She classified agent actions into three oversight categories. Actions that are not sensitive, like read and summarize, need no human in the loop. Moderately sensitive actions skip human approval but get logged and monitored, while destructive actions like mass deletion of files always require a human. "Things are gonna shift between those three categories quite a bit," she acknowledged, "but setting those types of categories up front allows you to have a principled framework."
Rather than layering controls onto agents one at a time, Intuit has built a central platform called GenOS, short for generative AI operating system, which abstracts security, risk, and fraud modeling so individual agent developers never reinvent protection. "Permissioning is not about giving access to AI," Parekh said. "Instead, it is defining very tightly scoped and clearly auditable authority to the agent to perform very specific tasks." Intuit evolved from agents inheriting user permissions to each agent carrying its own identity, and the company is now investigating mid-session permission changes tied to the specific task underway.
Parekh calls the broader model an AI-powered expert platform, one where the human expert is built into the trust architecture rather than bolted on as a gate. "The paradigm that we are pursuing is where the user, the AI agent, and the human expert are collaborating to solve the user problem," he said.
The end of human code review
Ceylan took on the tension between security testing and development velocity without hedging. "The days of secure code reviews where a human's looking at the code and we're looking at security architecture reviews, design docs, those are done," she said. "If you keep trying to do security that way, you're gonna get left behind." Box is building toward a fully agentic development lifecycle where agents review design documents, apply security requirements, and review the code for vulnerabilities. "I'm very optimistic that we will get to a point where we will write code without security vulnerabilities because agents and the models are going to get so good at writing code without vulnerabilities," she said. "We're still a long way away from that."
Her advice for development teams skips the advanced AI concepts entirely and returns to basics that predate agents. "It comes down to very basic least privilege access," she said. "If you start giving your agents overly broad permissions at the beginning, it's really hard to comb that back and build an infrastructure that allows for those ephemeral credentials and only those narrowly scoped tasks."
Parekh explained why the red teaming surface has expanded so quickly. "These agents have skills, and skills could become vulnerabilities," he said. "Agents have access to certain data, they have access to tools, and there could be threats that are lurking within those tools as well. So suddenly the blast radius of the malicious code or the intent increases dramatically." When Intuit identifies common vulnerability patterns from its manual red teaming exercises, it automates those tests back into the GenOS harness so future agents inherit protection and red teamers stay focused on new threat vectors. Runtime scanning of prompts and responses adds a final layer that can stop a suspect response and escalate to a human expert, he said.
"You need to continuously test to ensure that those remain robust to the protections that you have built, as well as to account for any sort of drift or any other types of dependencies that you introduce into your scenario that can create novel vulnerabilities," she said.
Intent versus probability
An audience question about intent detection set off the sharpest exchange of the session. Ceylan noted that when Box's own agent operates, the system always knows the user's intent because it controls the prompt, which means guardrails and tool-call restrictions can be engineered around it. The harder challenge, which she admitted Box is still trying to solve, arrives when external agents connect and the context behind the request is opaque.
That exchange exposed a split running through the wider industry. Mastercard, in the fireside chat immediately preceding the panel, came down on the side of quantifying intent, building an open-source framework to propagate it as a standard because complex B2B procurement cannot work without that trust. Endpoint security CTOs, in briefings with VentureBeat, have gone the other way, saying they will bet on probability rather than intent inference for production workloads. Chang explained why models, as they are trained today, cannot reliably derive intent from a prompt, which is why deterministic controls and behavioral proxies remain necessary. Ceylan agreed that both are required. "If you're not doing anything deterministic, you're really relying heavily on that intent, and I haven't seen programs that are there yet," she said.
Ceylan's story about trust collapsing after a single agent mistake landed as the panel's most memorable moment because enterprise agentic security is not a problem that gets solved and stays solved. Models change, permissions drift, and adversaries adapt across multi-turn conversations that snapshot tests never capture.
For the 82% of enterprises relying on provider-native controls as their primary security layer, and the 59% shopping for agent security tooling over the next 12 months, the panel's takeaway was blunt. Test the way attackers attack, across full conversations and continuously, or find out in production what your single-turn red teaming missed.


Black Forest Labs launches FLUX 3 capable of generating images and 20-second video with audio — but in limited release to start
Thu, 23 Jul 2026 20:48:22 +0200
Black Forest Labs (BFL) is expanding its FLUX family beyond image generation with today's launch of FLUX 3, a multimodal frontier model trained to understand and generate images, or combined audio/video clips up to 20 seconds from a single prompt — and to extend the same underlying architecture to robotic vision and actions.
The Freiburg, Germany-based AI lab says FLUX 3 is jointly trained across those modalities rather than assembling separate image, video and audio models behind a common interface. 
That distinction is central to the company's pitch: BFL wants enterprises to think about creative generation, simulation, computer use and robotics as connected applications of a single capability it calls visual intelligence — models, in the company's words, "that can perceive, predict, and act across physical and digital environments." This release marks BFL's first public video generation model. 
FLUX 3 will be offered through four product lines: FLUX 3 Video, FLUX 3 Image, FLUX 3 Action and the upcoming, open source FLUX 3 Dev. FLUX 3 Video, with optional native audio generation, and FLUX 3 Action are entering a gated "Early Access" program now, to which anyone can apply, but which BFL must approve. 
There is presently no public access through BFL's application programming interface (API) or those of partners yet, but the company says FLUX 3 Image will roll out in the coming weeks, followed by general availability. The limited initial availability rollout echoes the release strategies of new models from other frontier labs in the U.S. lately, including Anthropic and OpenAI, though those were ostensibly for security concerns and due to government request. 
What the company has not announced is pricing, production service-level commitments, evaluation methodology, sample sizes, rater counts or any image-model benchmarks at all. Enterprise buyers therefore cannot yet calculate total cost of ownership or independently reproduce the video comparisons.
Another big notable omission: FLUX 3 is not launching with downloadable weights at this time, nor an open source license. BFL says faster and open-weight versions will arrive later this year, and its technical blog names FLUX 3 Dev as "open-weight access to a multimodal backbone, for content creation (video, audio and image) and action prediction" — a considerably broader commitment than any previous FLUX Dev release, all of which covered images only.
But it arrives last in the sequence. Developers accustomed to receiving a locally deployable FLUX variant alongside — or soon after — a major model announcement will have to wait. That delay does not negate the company's commitment, but it is disappointing given the role open weights have played in FLUX's adoption thus far. 
Flux 3 is rated higher than the competition, but missing pricing and benchmarking details may prevent rapid enterprise adoption
BFL has published several benchmark comparisons, but they're qualified as preliminary — with full benchmark results and methodology to be published later during broader general availability. 
In early head-to-head preference testing on 10-second, 720p text-to-video clips with audio, the company says FLUX 3 was preferred over Luma Ray 3.2 in 93% of comparisons, Runway Gen-4.5 in 77%, Grok Imagine Video in 69%, Kling v3 Pro in 60%, Happy Horse v1 in 59%, Happy Horse 1.1 in 57%, and both Seedance 2.0 and Google's Gemini Omni Flash in 52%.
One caveat travels with every one of those figures, and it comes from BFL itself. The chart carrying the results is labeled a "preliminary evaluation of an early FLUX 3 candidate" — meaning the numbers describe a pre-release checkpoint rather than the model now entering early access. That cuts both ways: the shipping model may perform better, but nothing published today measures what customers will actually call.
Luma Ray 3.2 and Runway Gen-4.5, where FLUX 3 posted 93% and 77%, are the softest comparisons on the list — established products, but not the models currently setting the pace in independent video rankings. Those are real wins, and they are the ones least likely to change an enterprise shortlist.
Seedance 2.0, at 52%, is a statistical coin flip against a model most Western enterprises cannot currently procure. ByteDance indefinitely postponed Seedance 2.0's international rollout after Netflix, Warner Bros., Disney, Paramount and Sony sent legal threats over alleged systematic copyright infringement, and that suspension remains in place. Tying a frozen product is neither a strong claim nor a damaging one.
Gemini Omni Flash, also at 52%, matters much more. Omni is the closest large-platform analogue to what FLUX 3 is attempting — multimodal input, video and audio-aware creation, conversational editing — and by BFL's own measurement, the two are indistinguishable on 10-second text-to-video quality. 
Google's advantage in that matchup is that Omni is generally available via Google's Gemini API for $0.10 per second of generated 720p video, or a 10-second clip for around.
One regional wrinkle matters for a German company's home market. Editing uploaded video is unavailable to Omni Flash users in the European Economic Area, Switzerland and the United Kingdom, though editing video the model itself generated is permitted. A European enterprise that wants to run its existing footage through a generative editing pass cannot currently do so on Omni Flash.
Here's a rough guide for enterprises considering which video models to rely upon: 
Model Max single-generation duration Max resolution Key constraints Price per 10-second clip (720p) Price per 10-second clip (1080p) Price per 10-second clip (4K)
FLUX 3 Video 20 seconds Not stated; evaluations run at 720p Early access; no published SLA or pricing Not announced Not announced Not announced 
HappyHorse 1.1 15 seconds 1080p No 4K; closed weights Not published (v1.0 reseller rate is ~$1.82) Not published (v1.0 reseller rate is ~$3.12) n/a 
Veo 3.1 Per-second billing 4K Supports clip extension; preview $4.00 $4.00 $6.00 
Veo 3.1 Fast Per-second billing 4K Preview $1.00 $1.20 $3.00 
Veo 3.1 Lite Per-second billing 1080p No 4K, no clip extension; preview $0.50 $0.80 n/a 
Gemini Omni Flash 10 seconds (3s minimum) 720p at 24 FPS Preview abd no EU access $1.00 n/a n/a 
One architecture for media generation and physical action
FLUX 3 builds on Self-Flow, BFL's method for aligning multimodal understanding and generation within one architecture, publicized back in March 2026. 
The company says it significantly scaled up compute and data to train across video, images and audio simultaneously, and that testing showed video generation and action prediction do not require separate foundations — the same architecture could be extended to action prediction without sacrificing what it learned from video.
"We place vision at the center of our approach because it is the most signal-rich medium of the physical world. Images convey structure, images and video teach spatial relationships, video teaches dynamics, and actions reveal causal relationships. But vision alone is not the complete picture," said Robin Rombach, co-founder and CEO of BFL, in a pre-release statement provided to VentureBeat. "True intelligence means perceiving the world: predicting how it will change, taking action, and learning from the results. Joint training within one unified architecture is what will get us there, because each training modality strengthens the others. Audio conveys timing, prosody, and physical events that elude vision. Language conveys goals, abstractions, and instructions that pixels cannot easily express."
He put the case more bluntly elsewhere in the announcement: "You can't cheat reality. A model that only learns images can only generate images. But the world is not made of still frames. It moves, sounds, changes, and responds."
BFL says FLUX 3 targets creative tooling, media, design, e-commerce and physical AI, supporting video generation with synchronized audio, precise image editing, product and material consistency across motion, multilingual generation and robotic action prediction. It is already being tested by Canva, Burda, Magnific (formerly Freepik), Krea and Picsart.
For creative software companies, the appeal is consolidation. A single foundation could potentially support storyboarding, image editing, product rendering, video variation and localization without repeatedly translating assets and instructions between disconnected models.
For robotics teams, the potential value is data efficiency. Models that already encode motion, object behavior and physical change may need less task-specific robot training than systems starting from raw demonstrations.
What FLUX 3 Video can actually do
The video tier is the most concretely specified part of the launch, and it settles a question that had been circulating as rumor: FLUX 3 generates clips of up to 20 seconds with audio in a single generation. 
Every video output comes with native audio. For comparison, HappyHorse 1.0 tops out at 15 seconds of 1080p with synchronized audio — though BFL has not stated what resolution its 20-second clips run at, and its published evaluations were conducted at 720p. Still, a 20-second long clip from a single prompt is among the longest yet achieved, matching OpenAI's discontinued Sora model.
The capability list BFL published covers:
Text-to-video generation.
Image-to-video generation, either animating from a starting frame or using images as visual references.
Video-to-video generation from a reference clip, carrying elements such as a specific character into a new scene or context.
Generative video-audio continuation from existing video and audio input.
Keyframe-to-video generation for controlled transitions between defined moments.
 Multilingual dialogue.
A broad range of visual styles and aspect ratios, from candid camcorder footage to animation and cinematics.
Typography generation and animated design.
Agentic chaining of individual clips into longer, multi-shot sequences.
That last item is the one enterprise video teams should look at hardest. BFL claims the capabilities combine to produce sequences lasting several minutes, with visual references keeping characters consistent across scenes. If that holds up under production conditions, it addresses the constraint that has kept generative video out of most commercial pipelines: not clip quality, but continuity across shots.
It is also the capability where competition is most direct. HappyHorse 1.1's headline upgrade is R2V, or Reference-to-Video, which accepts multiple character reference images to hold identity stable across generated footage — the same problem, approached at the input layer rather than through agentic clip chaining. Alibaba also claims zero-drift lip sync and has specifically targeted the artifacts that mark commercial AI video as synthetic, including facial oiliness and over-sharpening. Character consistency is where this category is being contested, and both companies know it.
BFL says FLUX 3 Video is already particularly strong at human facial expressions, associating sounds with physical events, and multilingual output. On the image side, the company says preliminary evaluations conducted during midtraining show significant improvement over earlier FLUX versions in complex prompt handling and text generation, including high-accuracy text in multiple languages. It published no image benchmarks or win rates.
FLUX-mimic tests whether video models can become robot models
BFL is applying its unified-architecture thesis through FLUX-mimic, a video-action model built on FLUX 3 and developed with Swiss firm Mimic Robotics, one of the first partners to receive early access.
The technical blog describes two distinct routes to action prediction: integrating native action prediction directly into FLUX 3, scaling up the initial Self-Flow work; and using the pretrained video backbone as a dynamics-aware foundation from which specialized action models can be finetuned with limited task-specific data. FLUX-mimic is the second route — the FLUX 3 backbone combined with mimic's robot-learning and production-deployment expertise in dexterous manipulation.
FLUX-mimic is designed for general-purpose robotic manipulation: helping robots understand a visual scene, predict the consequences of an action, and adapt to new tasks with far less task-specific data. 
BFL and Mimic Robotics say that depending on task difficulty, the model can be finetuned for a specific manipulation task with as little as 30 minutes of robot data, where prior approaches have required 30 or more hours.
"The hardest part of robotics is data," said Elvis Nava, CTO of Mimic Robotics, in a statement provided to VentureBeat. "Every new task normally means hours of a robot repeating itself. Because FLUX-mimic is built on top of frontier video models that already understand how the physical world behaves, it picks up a new task in minutes, not days. This way, we can leapfrog the current state of the art in robot learning."
BFL argues that a model trained only on images cannot understand a world that "moves, sounds, changes, and responds," and that physical understanding is what produces convincing generated footage. Google makes a nearly identical claim for Gemini Omni. 
Its developer documentation cites "world knowledge" that combines "an understanding of physics" with Gemini's grasp of history, science and cultural context. Its marketing is blunter still: "Most AI models just predict the next pixel to build a narrative or an image. Gemini Omni is different," the company posted in June, crediting the model with "an intuitive understanding of forces like gravity, kinetic energy, and fluid dynamics for more realistic movements that follow real-world logic." 
The practical consequence for enterprise buyers is that world-model language is not a differentiator. Two of the three leading video systems now market physical understanding as their central advantage, and neither has published a benchmark that measures it. 
There is no standard test for whether generated water behaves like water, whether a dropped object falls at a plausible rate, or whether a sound arrives when the impact does. Human preference ratings capture some of it indirectly. Nothing else on offer captures it at all.
Open weights helped make FLUX an industry standard
BFL officially launched in summer 2024 and gained a name for itself in the AI industry in the intervening two years for its commitment to open sourcing high-quality AI image models beloved by developers, creatives, and enterprises. 
The company's founders, including Rombach, Andreas Blattmann and Patrick Esser, previously helped create VQGAN, latent diffusion and Stable Diffusion, the latter the open source technology that kicked off broad AI generation capabilities for the masses and currently used by many AI image generators and companies. 
That reach translated into commercial distribution. FLUX models now power generative features inside Adobe Photoshop, Picsart and Nous Research's Hermes Agent, among other platforms, and the company cites film director Martin Scorsese among professional users.
Wired magazine described Black Forest Labs as a relatively small company that nevertheless became a leading competitor to Silicon Valley's largest AI labs, with FLUX models ranking near the top of image benchmarks and becoming some of the most downloaded text-to-image models on AI code sharing community Hugging Face. The company says it now runs a 100-person team across Freiburg and San Francisco.
FLUX.1 Dev, FLUX.1 Kontext Dev, FLUX.1 Fill Dev and related control models, released shortly after the firm's launch,  gave researchers and creative-tool developers access to downloadable checkpoints, local inference and integrations with frameworks including Hugging Face Diffusers and ComfyUI. FLUX.1 Kontext Dev, for example, was released as an open-weight model for research and noncommercial use, with generated outputs permitted for commercial purposes under the applicable license.
The company continued that pattern with FLUX.2 Dev in late 2025, a 32-billion-parameter open-weight model combining generation and multi-reference editing. Black Forest Labs called it the strongest open-weight image generation and editing model available at launch and released weights, reference inference code and optimized implementations for consumer Nvidia GPUs.
FLUX 3 Dev raises the stakes on that evaluation. Previous Dev releases were image models. This one is described as a multimodal backbone spanning video, audio, image and action prediction — meaning a single license will govern whether a company can locally deploy a model that touches both content production and physical machinery.  BFL hasn't yet shared information about its license, the parameter count, quantizations or hardware requirements.
The company frames open weights as an enterprise feature rather than a community gesture, arguing they enable secure, low-latency local deployment for applications like robotic control systems and let teams adapt FLUX 3 to their own data, products and workflows. 
The financial backing behind FLUX 3 is worth noting alongside the technical claims. Black Forest Labs is valued at $3.25 billion and has raised more than $450 million from investors including a16z, AMP, Salesforce Ventures, Nvidia, General Catalyst, Adobe Ventures, Figma Ventures, Canva and Deutsche Telekom's T.Capital.

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`.

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

Model	Max single-generation duration	Max resolution	Key constraints	Price per 10-second clip (720p)	Price per 10-second clip (1080p)	Price per 10-second clip (4K)
FLUX 3 Video	20 seconds	Not stated; evaluations run at 720p	Early access; no published SLA or pricing	Not announced	Not announced	Not announced
HappyHorse 1.1	15 seconds	1080p	No 4K; closed weights	Not published (v1.0 reseller rate is ~$1.82)	Not published (v1.0 reseller rate is ~$3.12)	n/a
Veo 3.1	Per-second billing	4K	Supports clip extension; preview	$4.00	$4.00	$6.00
Veo 3.1 Fast	Per-second billing	4K	Preview	$1.00	$1.20	$3.00
Veo 3.1 Lite	Per-second billing	1080p	No 4K, no clip extension; preview	$0.50	$0.80	n/a
Gemini Omni Flash	10 seconds (3s minimum)	720p at 24 FPS	Preview abd no EU access	$1.00	n/a	n/a

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Executive summary

Cybersecurity industry tracking

Background

Targeting details

Technical details

Reconnaissance

Resource development

Flowerbed framework

Initial access

Persistence and credential access

Collection

Exfiltration

DNS exfiltration

HTTPS exfiltration

Catcher

Response strategies

Mitigations

Indicators of compromise (IOCs)

Flowerbed infrastructure

Phishing distribution

Post-compromise artifacts

Remediation

Works cited

Footnotes