How do I protect documents in RAG systems from privacy leaks?
Category:LLM Privacy & Compliance
Quick Answer
RAG creates specific risk: retrieved document chunks are sent to LLM as context. Protection layers: redact PII at indexing time, scan retrieved chunks before sending, scan LLM output for leaked PII. Also implement access controls on vector DB to prevent cross-tenant data leakage.
Detailed Answer
RAG (Retrieval-Augmented Generation) creates a specific risk: your vector database contains real documents, and retrieved chunks are sent to the LLM as context.
Protection layers:
- At indexing time: Redact PII before creating embeddings
- At retrieval time: Scan retrieved chunks for PII before sending
- At response time: Scan LLM output for leaked PII
Documents → PII Redaction → Embeddings → Vector DB │ User Query → Retrieval → PII Scan → LLM → PII Scan → Response
Additional measures:
- Implement access controls on vector DB (user A shouldnt retrieve user Bs docs)
- Tag documents with sensitivity levels
- Use metadata filtering to prevent cross-tenant data leakage
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