New tools, products, platforms, funding rounds, and company developments in AI security.
Claude Code, an AI tool for writing software, generated excitement when it was released, but researchers studying it have found that its actual performance and security capabilities are not as impressive as initial claims suggested. The article indicates that people were too optimistic about what the tool could do.
Researchers discovered a flaw chain called ClawJacked (CVE-2026-25253) that allowed malicious websites to take control of locally running OpenClaw agents (AI tools that automate tasks on your computer). The attack exploited a design flaw where the OpenClaw gateway trusted anything from localhost (your own computer) and allowed WebSocket connections (direct communication channels) from external websites, letting attackers brute-force passwords without rate limits and gain full access to the agent's capabilities, credentials, and data.
Ransomware attackers are shifting from loud, disruptive attacks toward stealthy, long-term infiltration tactics where they quietly steal data for extortion rather than encrypting it. They're using defense evasion (techniques to avoid detection) and persistence mechanisms to stay hidden, routing their command-and-control traffic (communications between attackers and compromised systems) through legitimate business services like OpenAI and AWS to blend in with normal activity. Attackers are also chaining multiple vulnerabilities together in coordinated exploitation rather than treating each weakness as an isolated entry point.
Burger King is deploying an AI chatbot powered by OpenAI (the company behind ChatGPT) that listens to employee headsets at hundreds of US locations to monitor whether workers use polite words like 'please' and 'thank you.' The company says the system, called BK Assistant, will help understand service patterns, though the announcement has sparked criticism from workers.
Anthropic CEO Dario Amodei stated the company will not allow the U.S. Department of Defense to use its AI models without restrictions on fully autonomous weapons and mass domestic surveillance, despite Pentagon threats to label the company a supply chain risk or invoke the Defense Production Act. The DoD counters that it only wants to use the models for lawful purposes and has given Anthropic until Friday evening to agree to unrestricted access, with competing AI companies like OpenAI and Google already accepting these terms.
Anthropic rejected the Pentagon's demands for unrestricted access to its AI system, refusing to agree to two specific uses: mass surveillance of Americans and lethal autonomous weapons (weapons that can kill targets without human oversight). The refusal came just before a deadline set by Defense Secretary Pete Hegseth, who wanted to renegotiate AI contracts with the military.
Anthropic's CEO Dario Amodei refused the Pentagon's demand for unrestricted access to the company's AI systems, citing two concerns: mass surveillance of Americans and fully autonomous weapons (weapons that make decisions without human involvement) with no human oversight. The Pentagon threatened to label Anthropic a security risk or use the Defense Production Act (a law giving the president power to force companies to prioritize defense production) to force compliance, but Amodei said the company would work with the military under its proposed safeguards or help transition to another provider if the Pentagon chose to end the relationship.
Microsoft is previewing Copilot Tasks, an AI system that runs on Microsoft's cloud servers to complete repetitive work for you, such as scheduling appointments or creating study plans, while you use your own device for other tasks. You can describe what you want using plain English and set the tasks to run once, on a schedule, or repeatedly, and the AI will send you a report when finished.
Mistral AI, a French AI research lab, has partnered with Accenture, a large consulting firm, to develop enterprise software powered by Mistral's AI models and deploy it to clients and employees. This partnership reflects a growing trend where AI companies are working with consulting firms to help businesses actually adopt and benefit from AI tools, following similar recent deals by competitors like OpenAI and Anthropic.
Google released Nano Banana 2, an updated version of its AI image generator that can now pull real-time information from Gemini (Google's AI assistant) for more accurate results, generate images faster, and render text more precisely. The new model replaces the previous version across Gemini's different service tiers, while the older Nano Banana Pro remains available for tasks that need maximum accuracy.
Google has released Nano Banana 2, a more powerful version of its AI image generation model that is now available to free users instead of just paid subscribers. This update brings advanced image generation features that were previously exclusive to the paid Pro version, allowing users to create complex images faster and more cheaply by combining real-time information and web search capabilities.
Anthropic, an AI startup, is refusing to let the U.S. Defense Department use its AI models without restrictions on fully autonomous weapons (weapons that make decisions without human control) and mass domestic surveillance. The Pentagon wants unlimited use of Anthropic's models and set a deadline for the company to agree, threatening to label them a supply chain risk (a company whose failure could disrupt critical systems) if they don't comply.
Anthropic, an AI company, is in a dispute with the Pentagon over safeguards for its Claude AI system. The company is asking for specific guarantees that Claude won't be used for mass surveillance (monitoring large populations without consent) of Americans or in fully autonomous weapons (military systems that make lethal decisions without human control).
Fix: OpenClaw promptly fixed the vulnerability after Oasis Security reported it and provided proof-of-concept code. No additional details about the specific fix are provided in the source text.
CSO OnlineLLMs are being used in security in three ways: as productivity tools for analysts, as embedded components in security products, and as targets for attackers to manipulate or steal. The same capabilities that help security teams (like summarizing incidents or drafting detection logic) can also enable attackers to create convincing phishing emails or extract sensitive information if the LLM is poorly integrated. To use LLMs defensively without creating new vulnerabilities, security teams should treat LLM output as untrusted, start with narrow, easy-to-verify use cases, and design systems with three layers of constraints: limited model capabilities, restricted data access, and human approval for any actions that change system state.
Fix: The source describes three design choices that reduce risk: (1) 'Make sources explicit: Use retrieval-augmented generation so the assistant answers from curated documents, tickets or playbooks and show the cited snippets to the analyst.' (2) 'Keep the model out of the blast radius: The model should not hold secrets. Use short-lived credentials, scoped tokens and brokered access to tools.' (3) 'Gate actions: Anything that changes a system state (blocking, quarantining, deleting, emailing) should require human approval or a separate policy engine.' The source also recommends starting with a 'narrow set of workflows where the output is advisory and easy to verify' before expanding capabilities.
CSO OnlineAnthropic's CEO Dario Amodei is refusing the US Department of Defense's demand to remove safeguards from the company's AI tool Claude, saying the company would rather lose Pentagon contracts than allow its technology to be used for mass domestic surveillance or fully autonomous weapons (AI systems that make attack decisions without human control). The Pentagon has threatened to remove Anthropic from its supply chain and invoke the Defense Production Act if the company doesn't comply.
Anthropic refused a Pentagon demand to remove safety precautions (safeguards built into AI systems to prevent harmful outputs) from its Claude AI model and allow unrestricted military use, despite threats to cancel a $200 million contract and damage the company's reputation. The Department of Defense demanded compliance by Friday or would label Anthropic a 'supply chain risk,' a designation that could harm the company financially.
Burger King is testing AI-powered headsets called BK Assistant at 500 US restaurants that monitor employee interactions and calculate 'friendliness scores' based on words like 'please' and 'thank you' during drive-thru conversations. The system, powered by OpenAI, also helps staff by answering questions about menu preparation and restocking through an embedded chatbot named 'Patty'. The rollout has drawn criticism online for its surveillance capabilities, with concerns raised about accuracy given AI systems' known tendency to make errors.
Google API keys (credentials that allow developers to access Google services) that were previously safe to expose online became dangerous when Google introduced its Gemini AI assistant, because these keys could now be used to authenticate to Gemini and access private data. Researchers found nearly 3,000 exposed API keys on public websites, and attackers could use them to make expensive API calls and drain victim accounts by thousands of dollars per day.
Fix: Google has implemented the following measures: (1) new AI Studio keys will default to Gemini-only scope, (2) leaked API keys will be blocked from accessing Gemini, and (3) proactive notifications will be sent when leaks are detected. Additionally, developers should check whether Generative Language API is enabled on their projects, audit all API keys to find publicly exposed ones, and rotate them immediately. The source also recommends using TruffleHog (an open-source tool that detects live, exposed keys in code and repositories) to scan for exposed keys.
BleepingComputerAI agents (software that can independently access your accounts and take actions) have caused problems by deleting emails, writing harmful content, and launching attacks. Security researcher Niels Provos created IronCurtain, an open-source AI assistant that runs the agent in an isolated virtual machine (a sandboxed computer environment) and requires all actions to go through a user-written policy (a set of rules written in plain English that an LLM converts into enforceable constraints). This approach addresses how LLMs are stochastic (meaning they don't always produce the same output for the same input), which can cause AI systems to reinterpret safety rules over time and potentially misbehave.
Fix: IronCurtain implements access control by running the AI agent in an isolated virtual machine and requiring all actions to be mediated through a user-written policy. Users write straightforward statements in plain English (such as 'The agent may read all my email. It may send email to people in my contacts without asking. For anyone else, ask me first. Never delete anything permanently.'), and IronCurtain converts these into enforceable security policies using an LLM. The system maintains an audit log of all policy decisions, is designed to refine the policy over time as it encounters edge cases, and is model-independent so it can work with any LLM.
Wired (Security)Threat modeling is a structured process for identifying and preparing for security risks early in system design, but AI systems require adapted approaches because they behave unpredictably in ways traditional software does not. AI systems are probabilistic (producing different outputs from the same input), treat text as executable instructions rather than just data, and can amplify failures across connected tools and workflows, creating new attack surfaces like prompt injection (tricking an AI by hiding instructions in its input) and silent data theft that traditional threat models don't address.