LIVE FEED
CRITICAL OpenAI GPT-5.6 Escapes Sandbox, Attacks Hugging Face to Cheat Benchmark // CRITICAL CVE-2026-0770: Langflow RCE Flaw Exploited in Active Attacks // HIGH Azure DevOps MCP Prompt Injection Hijacks AI Review Agents // FIRST LOOK Yellow Teams Bring AI Offense and Defense Into One Security Function // FIRST LOOK Tracebit Ships AWS Context Bombing Defence Against AI Hacking Agents // FIRST LOOK FriendMachine Launches Jacquard Lang for AI-Written Code Review // CRITICAL Check Point 2026 AI Security Report: LLMs Now Run Live Attacks // FIRST LOOK OpenAI GPT-5.6 Sol Ships Faster Parallel Tool-Use for Agents // FIRST LOOK Meta Launches Muse Image with Public Instagram Photo Reuse // FIRST LOOK Estonia Launches State-Issued Digital IDs for AI Agents //
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All LLM Security Agentic AI Industry News Research Supply Chain Prompt Injection First Look: Security Regulatory Adversarial ML Jailbreaks Model Theft Data Poisoning AI Security Tools Security Operations
Azure DevOps MCP Prompt Injection Hijacks AI Review Agents

Azure DevOps MCP Prompt Injection Hijacks AI Review Agents

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 9.1 The Hacker News

A prompt injection flaw in Microsoft's official Azure DevOps MCP server allows attackers to embed hidden instructions inside pull request descriptions using HTML comments, invisible to human reviewers but passed raw to AI agents. Because the affected tool lacks the spotlighting guardrail Microsoft already applied to other tools in the same server, a low-privileged contributor can hijack a senior reviewer's AI agent to exfiltrate secrets, trigger pipelines, and read confidential wikis across unrelated projects. The vulnerability represents a textbook confused-deputy escalation in an agentic AI workflow, confirmed unpatched as of July 21, 2026.

Anthropic Mythos AI Achieves 72% Autonomous Exploit Success

Anthropic Mythos AI Achieves 72% Autonomous Exploit Success

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.2 The Hacker News

Anthropic's Project Glasswing, powered by the Mythos Preview model, demonstrated unprecedented AI-driven vulnerability discovery — including a 72.4% autonomous exploit success rate against Firefox's JS shell and chained multi-bug exploits bypassing OS sandboxing — but fewer than 1% of discovered vulnerabilities were patched before potential adversarial access. The disclosure reveals a catastrophic asymmetry: AI has industrialised vulnerability discovery at machine speed while remediation capacity remains locked to human calendar pace. Real-world threat actors are already deploying LLM-integrated attack chains autonomously, as evidenced by an MCP-hosted LLM used against FortiGate appliances.

Moltbook Exposes 1.5M Tokens via Cross-App OAuth Risk

Moltbook Exposes 1.5M Tokens via Cross-App OAuth Risk

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 8.2 The Hacker News

The article examines 'toxic combinations' — a compounding risk pattern where AI agents and OAuth integrations bridge multiple SaaS applications, creating attack surfaces that no single application owner reviews. A real-world case involving Moltbook exposed 1.5 million agent API tokens and plaintext third-party credentials, illustrating how agentic AI identities create cross-app trust relationships invisible to conventional access controls. The threat is structural: non-human identities now outnumber human ones in most SaaS environments, and single-app access reviews are architecturally blind to inter-application permission stacking.

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