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RAG Security Controls

RAG security controls protect source ingestion, indexing, retrieval, context assembly, and grounded response generation.

What it means

RAG security controls protect source ingestion, indexing, retrieval, context assembly, and grounded response generation.

Why it matters

A secure model can still be compromised by poisoned documents, broken authorization, stale indexes, or context that contains executable instructions.

Practical focus

  • Define the approved purpose, accountable owner, users, operating environment, and acceptable risk for rag security controls before implementation or procurement
  • Implement source validation, malware and instruction scanning, tenant isolation, authorization-aware retrieval, context filtering, citations, and index rollback through documented architecture, policy, configuration, and change control
  • Collect ingestion provenance, index versions, permission tests, poisoned-document exercises, grounding scores, and rollback records and compare the results with approved requirements, risk thresholds, and expected outcomes
  • Exercise this failure scenario as a planned test: an attacker uploads a document that ranks highly and instructs the model to ignore policy or expose another tenant's data

Common mistakes

  • Using the label rag security controls without defining the exact system boundary, decision, data, and people in scope
  • Treating a model response or vendor claim as sufficient evidence without testing the surrounding application and operating process
  • Failing to preserve ingestion provenance, index versions, permission tests, poisoned-document exercises, grounding scores, and rollback records in a form that lets reviewers reconstruct decisions and changes
  • Testing only the normal path and never rehearsing what happens when an attacker uploads a document that ranks highly and instructs the model to ignore policy or expose another tenant's data

Certification relevance

This subject appears in or supports the following certification bodies of knowledge:

AI SecurityAdvanced AIResponsible AI

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