June 11, 2024, 4:42 a.m. | Avital Shafran, Roei Schuster, Vitaly Shmatikov

cs.CL updates on arXiv.org arxiv.org

arXiv:2406.05870v1 Announce Type: cross
Abstract: Retrieval-augmented generation (RAG) systems respond to queries by retrieving relevant documents from a knowledge database, then generating an answer by applying an LLM to the retrieved documents.
We demonstrate that RAG systems that operate on databases with potentially untrusted content are vulnerable to a new class of denial-of-service attacks we call jamming. An adversary can add a single ``blocker'' document to the database that will be retrieved in response to a specific query and, furthermore, …

abstract arxiv cs.cl cs.cr cs.lg database databases documents knowledge llm machine queries rag retrieval retrieval-augmented systems type vulnerable

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