Pre-Retrieval vs Post-Retrieval Authorization
A RAG pipeline can enforce access inside the vector query or in the app after results return. Each has a distinct failure mode. Here is what breaks.
15 posts
A RAG pipeline can enforce access inside the vector query or in the app after results return. Each has a distinct failure mode. Here is what breaks.
Embeddings throw away the permissions your source systems already track. Here is the recipe to carry document-level permissions into a RAG pipeline.
Gateco supports role, attribute, and relationship-based access control, and you can mix them in one policy set. Here is which model fits which pattern.
An orchestrator decides which agents and steps run. Gateco decides what an agent can retrieve. Different layers, and retrieval is where RAG leaks.
Gateco now supports per-org OpenAI keys for Grounded Answers, encrypted with AES-256-GCM and per-tenant KMS binding. Here is how the credit model works.
When policy evaluation hits an error, Gateco denies the retrieval and logs it. Here is why fail-closed is the right default, and when fail-open fits.
Gateco now supports 1-hop relationship-based access control: policies can check whether a principal owns or is assigned to a resource. How and when to use it.
Every RAG pipeline your team ships creates an access surface that bypasses application-layer authorization. Here is how to close the gap, in security terms.
A summary of everything that shipped this month: relationship-based access control, API key authentication, SDK v1.0, and our new Trust Center.
Azure AI Search gives you hybrid retrieval. Gateco decides who can see the results. Why enterprise RAG needs both, and how they compose.
Azure AI Search has powerful retrieval, but for compliance it leaves three gaps: no dynamic ABAC, no deny-by-default, and no audit trail.
A step-by-step guide to connecting your identity provider to Gateco for policy-enforced AI retrievals.
Metadata filters are the most common approach to RAG access control, and fundamentally insufficient. Why they can't replace a dedicated permission layer.
Four approaches to RAG authorization compared: no auth, metadata filters, app-layer RBAC, and a dedicated permission layer. Pros, cons, and when each fits.
Vector databases retrieve by embedding similarity. They don't know who's asking or check permissions. That is the RAG security gap, and it is wide.