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Risks of Knowledge Poisoning in AI Security Agents Using RAG
AI security agents using Retrieval-Augmented Generation (RAG) face risks from poisoned external knowledge that can lead to incorrect exploit behavior. This study highlights a gap in understanding how knowledge poisoning affects action-taking security agents beyond QA systems.
As AI security agents increasingly rely on external data for vulnerability analysis, poisoned inputs could cause harmful operational decisions. Understanding these risks is critical to improving AI security agent reliability and safety.
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Score 80
Source Type arxiv
Reposts 0
Topic Quality 52
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