External Data Extraction Attacks Against Retrieval-Augmented Large Language Models

Retrieval-augmented generation (RAG, a technique where AI systems pull in external documents to answer questions) enhances large language models but introduces a new security risk: external data extraction attacks (EDEAs), where attackers can trick the system into revealing sensitive or copyrighted information from its knowledge base. Researchers developed an attack called Secret that uses AI-optimized prompts and adaptive strategies to extract data from RAG systems, successfully extracting data from commercial models where previous attacks failed.