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Spoofing the Toolbox: Optimizing Tool Descriptions to Deceive LLM Agents
Large language model (LLM) agents are widely used in many applications and often rely on external tools. Tool information, such as function descriptions, helps agents determine which tools best suit a given context. However, attackers can manipulate this information to mislead LLM agents into using
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