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MemPot: Defending against Memory Extraction Attack with Optimized Honeypots
Large Language Model LLM-based agents employ external and internal memory systems to handle complex, goal-oriented tasks, yet this exposes them to severe extraction attacks, and effective defenses remain lacking. In this paper, we propose MemPot, the first theoretically verified defense framework...
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