RAG Privacy Attacks: How Retrieval-Augmented Generation Pipelines Leak Private Documents
RAG makes LLMs accurate by indexing private documents — but the retrieval pipeline introduces a new attack surface. Adversarial queries can extract document chunks, embedding inversions recover original text, and multi-tenant isolation can fail in ways that expose documents across access boundaries.