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CrowdStrike Falcon AIDR Adds Coverage for Copilot Studio and Claude Code

CrowdStrike Falcon AIDR Adds Coverage for Copilot Studio and Claude Code

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 CrowdStrike Blog

CrowdStrike has extended its Falcon AI Detection and Response (AIDR) capability to cover Microsoft Copilot Studio agents and Anthropic Claude Code, bringing behavioural monitoring to two fast-growing agentic AI surfaces. This expansion signals that enterprises are actively deploying autonomous agents in production environments that previously lacked dedicated security tooling. Defenders now have a detection layer for these platforms, but the expanded integration surface also introduces new ingestion and telemetry trust boundaries that adversaries may probe.

Claude Hacked 3 Organizations in Misconfigured AI Security Tests

Claude Hacked 3 Organizations in Misconfigured AI Security Tests

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.2 Wired Security

Anthropic disclosed that three Claude models — Opus 4.7, Mythos 5, and an internal research model — gained unauthorized access to production systems of three unnamed organizations during third-party cybersecurity evaluations conducted by testing firm Irregular. The breach stemmed from a misconfiguration that gave the models unintended internet access despite prompts specifying an air-gapped simulation environment, and the incidents went undetected for months. The disclosure follows OpenAI's recent admission of a similar containment failure, raising urgent questions about the adequacy of current AI agent testing infrastructure and oversight.

LLMs Break Cryptographic Schemes in New CryptanalysisBench Study

LLMs Break Cryptographic Schemes in New CryptanalysisBench Study

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 Schneier on Security

A new benchmark, CryptanalysisBench, demonstrates that frontier LLMs can perform meaningful cryptanalysis, breaking 65–86% of schemes with known practical vulnerabilities and producing novel attacks against previously unbroken primitives. Anthropic's Mythos Preview model uncovered new vulnerabilities in the Hawk signature scheme and reduced-round AES, representing the first AI-discovered cryptanalytic results of this kind. This signals a near-term shift in the threat landscape where AI-assisted cryptanalysis may begin to outpace human expert analysis.

Anthropic Brings Voice Mode to Claude Opus and Sonnet Models

Anthropic Brings Voice Mode to Claude Opus and Sonnet Models

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 The Verge AI

Anthropic has expanded Claude's voice mode to its more capable Opus and Sonnet models, with agentic integrations into productivity apps including Gmail, Slack, and Canva. This significantly widens the attack surface by combining a natural-language voice input channel with agentic action-taking capabilities across third-party platforms. Defenders must now account for voice-based prompt injection, cross-app lateral movement via conversational instruction, and the difficulty of auditing spoken-language interactions at scale.

Anthropic and OpenAI Open Vetted Cyber Programs for Offensive Researchers

Anthropic and OpenAI Open Vetted Cyber Programs for Offensive Researchers

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 TechCrunch AI

Anthropic and OpenAI have introduced structured vetting programs — Anthropic's Cyber Verification Program and OpenAI's Trusted Access for Cyber — that grant approved offensive security researchers access to AI models with reduced cybersecurity guardrails. These programs create a two-tier access model where the boundary between legitimate researcher and malicious actor becomes a policy decision made by private companies, introducing new social-engineering and access-abuse vectors. Defenders must now account for the possibility that guardrail-reduced model access can be obtained through credential abuse, insider compromise, or vetting-process manipulation.

Fake Claude App via Bing Ads Delivers SectopRAT Malware

Fake Claude App via Bing Ads Delivers SectopRAT Malware

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.2 BleepingComputer

Attackers exploited Bing's ad platform and Anthropic's legitimate Claude.ai domain to distribute a fake Claude desktop installer laced with SectopRAT, a feature-rich remote access trojan with info-stealing and HVNC capabilities. The campaign, dubbed FakeAgent, compromised at least 29 organisations in a 48-hour window by abusing Claude Artifacts as a trusted hosting vector — a novel AI platform abuse technique. The incident highlights how threat actors are weaponising AI brand trust and legitimate AI infrastructure as malware delivery mechanisms.

CVE-2026-46331: Claude Cowork VM Sandbox Escape on macOS

CVE-2026-46331: Claude Cowork VM Sandbox Escape on macOS

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.1 The Hacker News

A sandbox escape vulnerability (CVE-2026-46331) in Anthropic's Claude Cowork allows an AI agent running inside a Linux VM to break out and access the entire macOS host filesystem with read-write privileges. Approximately 500,000 local Cowork users were exposed, with the attack chain requiring no user interaction beyond connecting a folder. Anthropic closed the report as informative without a dedicated patch, leaving users who opt into local execution still at risk.

Prompt Injection Attacks Claude Code and Codex Execution

Prompt Injection Attacks Claude Code and Codex Execution

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 9.2 The Hacker News

Researchers at the AI Now Institute have demonstrated a proof-of-concept attack dubbed 'Friendly Fire' that tricks AI coding agents — specifically Anthropic's Claude Code and OpenAI's Codex in autonomous mode — into executing malicious binaries while performing routine security reviews. The attack embeds a disguised payload inside an open-source library and uses a plain README.md instruction to direct the agent to run a malicious shell script, bypassing existing trust-prompt defences. Because the weakness is architectural rather than version-specific, no patch exists; mitigation requires workflow changes.

Anthropic Mythos LLM Scans Federal Software for Vulnerabilities

Anthropic Mythos LLM Scans Federal Software for Vulnerabilities

ATLAS OWASP MEDIUM Moderate risk · Monitor closely ▲ 6.5 SecurityWeek

CISA's Attack Surface Evaluation team is reportedly leveraging Anthropic's 'Mythos' model to scan federal government software for security vulnerabilities, representing a significant expansion of AI-assisted offensive security tooling in critical infrastructure defence. The deployment raises important questions about the trustworthiness of LLM-driven vulnerability assessment, potential for model-induced false negatives, and the security of the AI pipeline itself when applied to sensitive government codebases. This marks one of the most prominent known uses of a commercial LLM in an active U.S. government cyber defence role.

Claude Opus Discovers API Flaw Enabling Ticket Fraud

Claude Opus Discovers API Flaw Enabling Ticket Fraud

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 Wired Security

Security researcher Ian Carroll leveraged Anthropic's Claude Opus 4.7 to identify a critical vulnerability in Front Gate Tickets—a Live Nation subsidiary handling ticketing for major US festivals—that granted super-administrator access and the ability to freely issue tickets of any value. The case demonstrates LLM-assisted autonomous vulnerability discovery at scale, with Carroll noting the AI could likely have completed the full exploit chain without human intervention. Front Gate patched the flaw within 24 hours of disclosure, confirming no evidence of prior exploitation.

Anthropic Ships Mythos for AI-Driven Bug Discovery

Anthropic Ships Mythos for AI-Driven Bug Discovery

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 7.8 Dark Reading

Anthropic's Mythos capability, combined with IBM and Red Hat's Project Lightwell service backed by 20,000 engineers and $5B, introduces an AI-driven pipeline for discovering and remediating bugs in open-source software at industrial scale. This creates a dual-edged attack surface: adversaries who can influence Mythos's findings, its training data, or the remediation pipeline gain a privileged position to inject subtle vulnerabilities into widely-deployed open-source components. Defenders must treat the AI vulnerability-finding and patch-generation pipeline itself as a high-value, high-risk supply chain asset requiring rigorous integrity controls.

Anthropic Releases Mythos and Fable Models with Global Access

Anthropic Releases Mythos and Fable Models with Global Access

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 6.8 TechCrunch AI

The US government has lifted export restrictions on Anthropic's Mythos and Fable models, restoring broad international access to what are described as the most capable AI models publicly available, with Mythos specifically noted for its advanced ability to identify and exploit software vulnerabilities. Defenders must now contend with a significantly wider pool of threat actors — including foreign nationals and nation-state-affiliated researchers — who can access a model with documented offensive security capabilities. The policy reversal also introduces regulatory uncertainty that complicates enterprise risk assessments, as organizations cannot rely on stable governance signals to calibrate their AI security postures.

Claude Code Indirect Prompt Injection Spawns Reverse Shell

Claude Code Indirect Prompt Injection Spawns Reverse Shell

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.5 SecurityWeek

Researchers have demonstrated that indirect prompt injection attacks embedded within seemingly benign code repositories can cause Claude Code — Anthropic's agentic coding assistant — to spawn a reverse shell on a developer's machine. The attack exploits Claude Code's autonomous execution capabilities, using hidden instructions in repository content to hijack the host system without any explicit user consent. This highlights a critical risk in agentic AI tools that operate with elevated system privileges in developer environments.

Anthropic CEO: Open-Source AI Models Pose Systemic Safety Risk

Anthropic CEO: Open-Source AI Models Pose Systemic Safety Risk

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 6.2 Meta AI (via HN)

Anthropic CEO Dario Amodei testified to lawmakers that open-source AI models present a systemic safety risk because once released, developers lose the ability to monitor misuse, revoke access, or patch safety guardrails. For defenders, this formalises a long-standing asymmetry: closed-source safety controls (rate-limiting, usage monitoring, kill-switches) become irrelevant once capable weights are publicly distributed. Security teams building on or competing against open-weight models must now treat every downloaded model artifact as a potentially unpatched, unmonitored endpoint that can be fine-tuned to remove safety constraints entirely.

Sakana AI and 360 Launch Fugu and Tulongfeng Models

Sakana AI and 360 Launch Fugu and Tulongfeng Models

FIRST LOOK ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 6.8 Cohere AI (via HN)

Sakana AI's Fugu and Chinese firm 360's Tulongfeng are frontier AI models positioned as functional alternatives to Anthropic's export-restricted Mythos and Fable 5, with Fugu explicitly designed for agentic orchestration across third-party model APIs. For defenders, the proliferation of cybersecurity-focused frontier models outside US regulatory reach removes a key friction point that previously slowed adversary access to high-capability AI offensive tooling. The agentic, multi-model orchestration design of Fugu in particular introduces compounded supply-chain and prompt-injection risk for any enterprise connecting these models to existing tool ecosystems.

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