SOURCE-LINKED INTELLIGENCE
Micro-Collaborative Poisoning: A Distributed Attack on RAG Systems
Retrieval-Augmented Generation (RAG) improves large language models by grounding outputs in external knowledge sources, but this dependency also creates a surface for poisoning attacks. This paper introduces Micro-Collaborative Poisoning, a distributed attack in which a false target claim is divided across multiple locally plausible documents instead of being concentrated in a single malicious passage. We evaluate the attack across 108 RAG configurations by varying dataset, retriever architecture, retrieval depth, database composition, number of poisoned databases, and generator model. The res
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T10:03:33.000Z
First collected: 2026-09-23T13:51:27.104Z. This is not the publication date.