ToolFence: Fine-Grained Authorization for Secure Tool-Using LLM Agents
Tool-using LLM agents remain vulnerable to indirect prompt injection because trusted instructions and untrusted observations share one context, allowing malicious content to steer consequential input-filtering defenses. Multi-path consensus defenses still leave a high attack success rate because they examine content or...
Yan-Jie Li, Xiang-Yu He, Xue-Long Dai et al.
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