adversarial-attacks

A Google Deepmind paper introduces the first systematic framework for 'AI agent traps'—attacks that exploit autonomous agents' vulnerabilities to external tools and internet access. The researchers identify six attack categories targeting perception, reasoning, memory, actions, multi-agent networks, and human supervisors, with proof-of-concept demonstrations for each.

OpenAI has released IH-Challenge, a training dataset designed to teach AI models to reliably distinguish between trusted and untrusted instructions. Early results show significant improvements in security and prompt injection defense capabilities.