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Americká firma Hadron Energy vyvinula mikromodulární jaderný reaktor Halo • Zařízení využívá lehkovodní technologii schválenou regulačními úřady • Hotové moduly najdou uplatnění v datových centrech i těžkém průmyslu

107 °C, 112 °C, ale i 117 °C. Takové hodnoty hlásí uživatelé GeForce RTX 5000 poté, co se vrátila možnost monitorovat nejvyšší teplotu grafického jádra (hotspot) karet generace Blackwell…

OpenAI says its AI models, including GPT‑5.6 Sol and a pre-release model, hacked into the Hugging Face artificial intelligence repository while being tested in a sandboxed testing environment. [...]

A single invisible comment in an Azure DevOps pull request can turn a reviewer's own AI coding agent against them, driving it into projects the attacker has no rights to reach and quietly leaking what it finds. The flaw is in Microsoft's official Azure DevOps MCP server, and it works because one of its tools returns pull request descriptions without a prompt-injection guardrail the company had

A single invisible comment in an Azure DevOps pull request can turn a reviewer's own AI coding agent against them, driving it into projects the attacker has no rights to reach and quietly leaking what it finds. The flaw is in Microsoft's official Azure DevOps MCP server, and it works because one of its tools returns pull request descriptions without a prompt-injection guardrail the company had Swati Khandelwalhttp://www.blogger.com/profile/[email protected]

OpenAI has admitted that it was the operator of the autonomous agents that attacked model-mart Hugging Face last week, and that they did so after a research project escaped a sandbox by finding and exploiting a zero-day flaw, then used another zero-day flaw to launch an attack. The attack saw agents achieve “unauthorized access to a limited set of internal datasets and to several credentials” used by Hugging Face, which said its infosec teams observed an autonomous agent framework “executing many thousands of individual actions across a swarm of short-lived sandboxes, with self-migrating command-and-control staged on public services.” “This matches the ‘agentic attacker’ scenario the industry has been forecasting.” On Tuesday, OpenAI admitted it was the attacker and that its models went rogue. “This incident occurred during an internal evaluation which prompts models to pursue advanced exploitation using complex attack paths, in an effort to quantify their cyber capabilities,” the startup confessed. The models that conducted the attack included GPT‑5.6 Sol and what OpenAI described as “an even more capable pre-release model” that like the other involved used “reduced cyber refusals for evaluation purposes.” OpenAI thought its models were “hyperfocused on finding a solution for ExploitGym” – a benchmark that measures how effective AIs are at finding security exploits. OpenAI says it runs these tests “in a highly isolated environment, with network access constrained to the ability to install packages through an internally hosted third-party software that acts as a proxy and cache for package registries.” The company’s models decided not to be bound by those constraints. “The models identified and exploited a zero-day vulnerability in the package registry cache proxy. With this access, our models performed a series of privilege escalation and lateral movement actions in our research testing environment until the models reached a node with Internet access,” OpenAI admitted. “After gaining Internet access, the models inferred that Hugging Face potentially hosted models, datasets and solutions for ExploitGym. Knowing this, the model searched for and successfully found ways to gain access to secret information that it could use to cheat the evaluation,” OpenAI explained. “In one example, the model chained together multiple attack vectors, including using stolen credentials and zero-day vulnerabilities to find a remote code execution path on the Hugging Face servers.” Hugging Face’s assessment of the incident was that it represented the moment at which “Autonomous, AI-driven offensive tooling is no longer theoretical.” OpenAI reached a similar conclusion. “The incident also makes clear that advanced models can discover and exploit novel attack paths in real-world systems without source-code access. It highlights that advanced cyber capabilities must be developed alongside stronger safeguards and defensive tools,” the company wrote, without a trace or hint of contrition about the fact its own safeguards didn’t work. Which rather begs the question: If one of the prime movers of the AI boom can’t get this stuff right, what chance do the rest of us have? OpenAI has done the usual Big Tech thing of apologizing for the mess, and promising that its new guardrails and industry collaborations will hopefully prevent this sort of thing from happening again. History suggests those are very hollow sentiments. ®

Ve spolupráci společností OpenAI a Work Louder byla představena (𝕏) hardwarová klávesnice Codex Micro pro práci s AI agenty. Cena klávesnice je 230 dolarů.

Authorities in Germany and the U.S. dismantled the central infrastructure of Kratos, a phishing-as-a-service (PhaaS) platform with global reach, and its developer was arrested in Indonesia. [...]

A large-scale operation dubbed 'FakeGit' is pushing SmartLoader and StealC malware through 7,600 malicious GitHub repositories that accumulated more than 14 million downloads. [...]

Znovuzavedení evidence tržeb s sebou přinese i řadu nesouvisejících daňových novinek, které se schvalují v rámci jedné předlohy. Jaké novinky se chystají?

AI tento rok naplno vtrhla do vývoje softwaru a výrazně ovlivňuje také open-source projekty. V open source v poslední době v souvislosti s AI pozoruji některé trendy, které svět otevřeného softwaru mění.

Uklidíme dotfiles do profilů, necháme si vygenerovat čerstvý mirrorlist pro pacman, vytiskneme zdrojáky s náhledem přímo v terminálu, dáme čtyřem AI agentům jednu společnou paměť a nakonec proměníme terminál v hackerskou scénu z filmu.

Zmrazení optického vlákna s kapalným jádrem (LiCOF) v kapalném dusíku při teplotě mínus 195 °C mu nadělí podivuhodné vlastnosti, včetně mimořádně intenzivní vazby mezi světelnými a zvukovými vlnami. Mohlo by z toho být dramatické snížení nároků na energii fotonických neuromorfních počítačů.

Stotunová bóje C4 švédských CorPower Ocean získala plnou certifikaci od norské společnosti DNV, zlatý standard v certifikaci offshore energetických technologií. Jde o zásadní milník na cestě ke komerčnímu využití technologií tohoto typu. První komerční soustavy bójí C4 vyrostou v Portugalsku a ve Skotsku.

Samsungu se sice podařilo vyžehlit situaci ve výrobě pamětí, kde nespokojení zaměstnanci hrozili stávkou, pokud nedostanou víc z vysokých firemních zisků. Vyvolalo to ale nespokojenost ve výrobě čipů…

Who needs expensive frontier models to find software vulns? Cisco has just released two open-weight models that specialize in finding known bugs in existing codebases. The models, Antares-350M and Antares-1B, are part of Cisco’s new Antares family of security small language models (SLMs), and are now available on Hugging Face - but only to vetted users. “We’re making sure we’re gating that and appropriately granting access,” DJ Sampath, Cisco's senior vice president and general manager of AI software and platform, told The Register. The company is working with academic and nonprofit organizations, as well as smaller and public organizations’ security teams, to ensure they have access to the vulnerability-hunting models. Plus, because both are small models designed to run locally, “you also need the keys to the source code” to scan for and find vulnerabilities, Sampath said. “This means an attacker is going to be able to exploit an endpoint or a service that you have.” It also means that proprietary code never leaves the organization’s machines, compared to cloud-based LLMs that send code to the AI providers’ external servers for processing and analysis. This enables security analysis in environments with strict privacy or compliance requirements, according to the networking and security giant. And yes, it's named after the massive red super-giant star. “It's almost 1,000 times bigger than the sun, even though the sun dominates the sky, and that is the analogy that we're using here for vulnerability detection and localization,” Cisco VP and chief AI scientist Amin Karbasi told The Register. “The impact of vulnerabilities in your codebase is huge, but it might be only a single file or a few lines of code in a million lines of code.” A future, 3-billion-parameter model in the Antares family won’t be released to the public, Karbasi added. “We are completely gating the 3B model to make sure that we responsibly release it to communities that need it,” he said. Small yet mighty Cisco claims that its models perform as well as or better than dozens of larger models in its new benchmark test that measures how efficiently AI models identify security flaws in codebases. Antares-1B outperforms Google’s Gemini 3 Pro and is comparable to Z.ai's GLM-5.2, we’re told, while the yet-to-be-released Antares-3B does a better job at finding vulnerabilities than GLM-5.2 and OpenAI’s GPT-5.5. Plus, we’re told that the small models scan code much faster and at a fraction of the cost of larger, token-gobbling AI systems. “If you look at the performance, in terms of the time it takes to finish 500 repositories, Antares finishes the entire cohort of repositories in 15 minutes, whereas frontier models take five hours,” Karbasi said, adding that this translates to significantly less cost. “It takes like less than $1 whereas frontier models are above $100 into $150 of cost,” he added. The difference, Karbasi explained, is that Cisco took a “fundamentally different approach” to building Antares. “These models have been trained in a very different way,” he said. “Antares is inherently not a chatbot. It is an investigator. It is a search engine. It has to find a very specific thing that might be a needle in a haystack, and it goes and finds that.” This required training the model on several different ways to search for vulnerabilities “because one way of search may not actually be fruitful, then it has to change its strategy, do it another way, and then do it another way,” Karbasi said. “Because it is very nimble and it’s very small, it can actually do a lot of search at the same time, which is very different from bigger models.” Karbasi likened it to a bicycle on a busy London street: “You can go much faster than the biggest truck.” Or, to use Sampath’s favorite analogy for the benefits of using a small, security-focused model to find bugs in code: “Sometimes you don't need a private jet to go to a corner store, right?”®

Hackers are actively exploiting the critical CVE-2026-50522 vulnerability in Microsoft SharePoint to steal machine keys and maintain access even after affected servers are patched. [...]

AI models will do just about anything to complete the task you ask, including cheating to get there, according to new cybersecurity evaluations from the UK government's AI Security Institute (AISI). The group found that leading models often take shortcuts to achieve a particular result and then misrepresent how they obtained that result. And they won't always admit it when asked. "Every model we have tested for this behaviour attempted to cheat," AISI said in a blog post on Tuesday. "Models did not reliably report this behaviour when asked, and often did not reason about it in their chain-of-thought, suggesting that detecting cheating will likely require robust monitoring methods." Infractions included searching the internet for the answer, bypassing sandbox network restrictions, probing the evaluation harness, attacking a system other than the target, and guessing an answer. Cheating in this manner – employing a workaround or gaming a reward function to score better on a benchmark test, for example – has been widely documented by machine learning researchers. It doesn't necessarily imply malicious intent, AISI said, but it's nonetheless troublesome because it can produce misleading assessments of model capabilities. When AISI conducted evaluated five leading models, it found that all of them cheated. The results were as follows: GPT-5.4 cheated 67 times in 475 test runs (14.1 percent). GPT-5.5 cheated 54 times in 475 test runs (11.4 percent). GPT-5.6-Sol cheated 60 times in 475 test runs (12.6 percent). Claude 4.7 Opus cheated 43 times in 475 test runs (9.1 percent). Claude Mythos Preview cheated 37 times in 475 test runs (7.8 percent). Asking models whether they cheated or did anything wrong proved an unreliable auditing mechanism because the models didn't always admit wrongdoing. "In our experiments, models did not consistently acknowledge attempted cheating when asked, and described it as wrong less than 50 percent of the time," said AISI. Existing vetting methods, such as self-reporting and chain-of-thought logs, proved similarly dicey because models don't always report their chain-of-thought. And there were instances where a model would consider whether a proposed action amounted to cheating and then decided to take the action anyway. Given the absence of reliable model cheating detection methods, AISI warns that its current approach – manual review coupled with LLM monitoring – may not be sufficient to catch deception, particularly as models become more sophisticated. "A more fundamental fix would be to train the models not to cheat in the first place – but given this kind of behaviour was reported in frontier models more than a year ago, robustly aligning it away may not be easy," AISI concludes. ®

The Anubis ransomware gang has claimed responsibility for the cyberattack on Coca-Cola's Fairlife dairy subsidiary, threatening to publish allegedly stolen corporate data unless the company pays a ransom. [...]

Apple has moved to address a security flaw in its Hide My Email service that enabled users' real email addresses to be unmasked, effectively undermining the feature's privacy guarantees. 404 Media reported Tuesday that a fix for the issue was deployed by Apple on July 3, 2026, after more than a year, when it was disclosed to the company by Tyler Murphy, co-founder of EasyOptOuts. Hide My Email