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Paper · arXiv

The Price of Safety: Benign-Case Utility and Token Overhead of Memory-Poisoning Defenses in LLM Agents

Memory-poisoning defenses for LLM agents are typically evaluated by their ability to prevent attacks. However, the traffic they process is rarely adversarial. The cost of implementing a defense is paid with each interaction, while its benefits are only seen in a small percentage of cases. We developed a measurement setup that keeps the memory backend, retrieval process, and judge consistent across different conditions, changing only the defense itself. We test each condition three times across five conversations to distinguish the defense's real effects from noise inherent in the pipeline's runs, which remains significant even at temperature zero. Across three write-time defenses (input s...

AuthorsPritom Bhowmik
Primary categorycs.CR
Published19 September 2026
Last updated at source19 September 2026
cs.CRcs.AI
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