I've just published a new guide on securing RAG pipelines against data leaks. Originally published on devopsstart.com, this article explores why prompt hardening is not enough and how to implement identity-aware access controls at the data layer. Most security advice for LLM applications focuses on prompt injection, but this is a dangerous misdirection. The most critical and frequently overlooked vulnerability in a Retrieval-Augmented Generation (RAG) pipeline isn't the user's input; it's the uncontrolled access the system has to your internal data. Building strong defenses at the data retrieval layer is the only strategy that provides real security, while everything else is just a perimeter defense waiting to be breached. The Anatomy of a RAG Pipeline Before analyzing the vulnerabilities, let's quickly map the assembly line of a typical RAG application. Understanding this flow is key to seeing how a failure in one stage cascades into the next.…