Your AI assistant can leak files people aren't allowed to see — here's how to fix it

AI can already help create new ideas, but truly revolutionary breakthroughs usually come from understanding a problem deeply, not just generating possibilities. My guess is that AI will become an incredible creative partner finding patterns and connections humans miss but the biggest leaps will still come from humans deciding which ideas are worth pursuing.

Excellent breakdown of a problem that's becoming increasingly common in enterprise AI systems. We've noticed many teams focus on prompt injection defenses while overlooking retrieval-level authorization. The "authorization before retrieval" approach makes a lot of sense, especially for multi-tenant SaaS platforms where document access policies can vary significantly between customers. Curious how this approach performs when permission graphs scale to thousands of users and documents.

Excellent write-up! I really liked the pre-filter approach with OpenFGA and Qdrant. Preventing unauthorized chunks from reaching the LLM is much safer than filtering after retrieval. We've been researching similar RAG security patterns and AI infrastructure on our blog , especially around secure vector search and permission-aware AI systems. It's great to see a practical implementation with real tests and a fail-closed approach. Thanks for sharing this detailed guide.

This makes perfect sense, love to see securities like this being engineered, kudos!

Permission-aware RAG is such a crucial pattern. It's wild how many AI projects skip authorization until it's too late.