How do you enforce access control in a RAG pipeline?
Filter at retrieval time, against the identity of the requesting user, before any chunk reaches the model. Once text is in the context window it has already leaked — filtering the model's output afterwards is damage limitation, not access control. The retriever is the enforcement point.
The failure mode is structural. Enterprise sources — document stores, wikis, ticketing systems — already carry identity-based permissions, but a naive RAG pipeline indexes their contents into a vector store that has none. Every user then queries a corpus flattened to the union of everyone's access.
The fix is to carry the source permissions into the index and apply them as a pre-retrieval filter bound to the caller's identity. Daxa's TwinGuard architecture does exactly this: SafeConnectors generate a live data bill-of-materials, and SafeRetriever wraps the retrieval call to apply identity-aware filtering before chunks are returned.
Audit the filter, not just the answer. You want a log showing which chunks were withheld for which principal, because that is the artefact a compliance review asks for.
Written by Binary AI Labs · Reviewed