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Plant, Persist, Trigger: Sleeper Attack on Large Language Model Agents

Li, Yongxiang et al.
arXiv (All) · Papers
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artificial-intelligence
Large Language Model (LLM) agents remain vulnerable to safety threats from the external environment, where attackers inject adversarial content into external observations such as tool-returned data, webpages, or MCP context, causing harmful agentic behaviors such as unsafe actions or incorrect outpu
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