This article discusses a new paper outlining design patterns for mitigating prompt injection attacks in LLM agents. It details six patterns – Action-Selector, Plan-Then-Execute, LLM Map-Reduce, Dual LLM, Code-Then-Execute, and Context-Minimization – and emphasizes the need for trade-offs between agent utility and security by limiting the ability of agents to perform arbitrary tasks.
Researchers at HiddenLayer have developed a novel prompt injection technique that bypasses instruction hierarchy and safety guardrails across all major AI models, posing significant risks to AI safety and requiring additional security measures.
