PlanFlip: Attacking Multi-Agent LLM Systems via Planning-Phase Prompt Injection

Explain Like I'm Normal

Researchers discovered a critical vulnerability in multi-agent systems where compromising the 'Planner' agent causes a cascade of failure across all downstream 'Executor' agents. Using a method called PlanFlip, attackers can disguise malicious instructions as tool outputs to bypass filters and hijack complex workflows. This suggests that as AI systems become more autonomous and hierarchical, their centralized planning logic becomes a single point of failure.