RAG Tutorials don't teach you this | Must Watch

The tutorial addresses the often-overlooked security implications within Retrieval-Augmented Generation (RAG) systems. It focuses specifically on authorization risks in AI applications, noting that RAG systems, such as internal AI copilots and enterprise chatbots, can unintentionally expose sensitive documents to unauthorized users.

The content explains the fundamentals of RAG, emphasizing why standard Role-Based Access Control (RBAC) is frequently insufficient for securing these architectures. The discussion introduces Relationship-Based Access Control (ReBAC) as an alternative approach for managing access rights in complex AI environments. A demonstration illustrating a secure RAG pipeline using Auth0's tooling is included to show practical implementation details, clarifying that vector search operations themselves do not constitute security against unauthorized data access.

This presentation is relevant for developers building secure RAG systems, multi-tenant AI platforms, and enterprise copilots where data governance and authorization are critical concerns.