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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 //
Anthropic Launches Claude Cowork Mobile with Remote Control

Anthropic Launches Claude Cowork Mobile with Remote Control

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

Anthropic is expanding its Claude Cowork agentic desktop feature to mobile, enabling users to remotely initiate, monitor, and steer long-running AI tasks on their PC from a smartphone — with background task execution persisting even after the mobile app is closed. This cross-device architecture introduces a new attack surface: a mobile application acting as a command-and-control interface for an agent with local filesystem access, expanding the blast radius of device compromise, session hijacking, and prompt injection attacks. Defenders must now account for a persistent, background-running agentic process on employee endpoints that can be triggered or manipulated via a separate, potentially less-secured mobile channel.

Google Patches Prompt Injection RCE in Agentic AI

Google Patches Prompt Injection RCE in Agentic AI

ATLAS OWASP CRITICAL Active exploitation · Immediate action required ▲ 8.5 Dark Reading

Google has patched a critical prompt injection vulnerability in an agentic AI tool designed for filesystem operations, where insufficient input sanitisation enabled sandbox escape and arbitrary code execution. The flaw highlights the compounding risk surface of agentic AI systems that interface directly with operating system resources. This is a significant example of how LLM-native vulnerabilities can translate into traditional high-severity RCE outcomes.

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