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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 // HIGH AI Widens Skill-Ability Gap, Enabling Autonomous Cyberattacks // FIRST LOOK OpenAI Expands ChatGPT Into Family and Caregiver Households // FIRST LOOK Iroh Launches Mesh LLM for Distributed AI Across Peer Nodes //
CVE-2026: Google Antigravity Sandbox Escape via Prompt Injection

CVE-2026: Google Antigravity Sandbox Escape via Prompt Injection

ATLAS OWASP HIGH Significant risk · Prioritise patching ▲ 9.0 The Hacker News

A now-patched vulnerability in Google's agentic IDE Antigravity allowed attackers to achieve arbitrary code execution by injecting malicious flags into the find_by_name tool's Pattern parameter, bypassing the platform's Strict Mode sandbox before security constraints were enforced. The attack chain could be triggered entirely via indirect prompt injection—embedding hidden instructions in files pulled from untrusted sources—requiring no account compromise and no additional user interaction. This case exemplifies the systemic risk of insufficient input validation in AI agent tool interfaces, where autonomous execution removes the human oversight layer that traditional security models depend on.

CVE-2026: Anthropic MCP SDK Remote Code Execution

CVE-2026: Anthropic MCP SDK Remote Code Execution

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 9.4 The Hacker News

A systemic 'by design' vulnerability in Anthropic's Model Context Protocol (MCP) SDK enables arbitrary remote code execution across all supported language implementations via unsafe STDIO transport defaults, affecting over 7,000 publicly accessible servers and 150 million downloads. The flaw has been independently confirmed across 10+ popular AI frameworks including LiteLLM, LangChain, and Flowise, with Anthropic declining to modify the protocol's architecture. This represents a significant AI supply chain risk with cascading exposure to sensitive data, API keys, and internal systems.

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