Securing Retrieval-Augmented Generation: A Taxonomy of Attacks, Defenses, and Future Directions 事件

Securing Retrieval-Augmented Generation: A Taxonomy of Attacks, Defenses, and Future Directions arXiv:2604.08304v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) extends large language models (LLMs) with external knowledge, but this access path also introduces security risks that existing work often conflates with inherent LLM flaws. We frame secure RAG as securing external knowledge access and organize the literature with SLOT, a taxonomy along four axes: the attac