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State information in LLM-driven agents can be exploited, turning their task execution capabilities into a potential attack surface.
Security vulnerabilities in embodied agents are more complex than previously understood, with critical gaps in defenses against long-term attack propagation and multi-agent interactions.
AgentSentry stops indirect prompt injection attacks in LLM agents by pinpointing when the attack takes hold using causality, then surgically removing the malicious influence.
