Poisoning the Context: Securing RAG Pipelines Against Knowledge Injection Attacks

Originally published on tamiz.pro. The Silent Vulnerability in Retrieval-Augmented Generation Retrieval-Augmented Generation (RAG) has become the de facto standard for grounding Large Language Models (LLMs) in proprietary data. By fetching relevant documents from a vector database and injecting them into the model's context window, RAG mitigates... Weiterlesen