
RAG security: risks, controls and a practical threat model
Threat-model a RAG system across documents, indexing, retrieval and generation, then apply layered controls for permissions, provenance and testing.
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Assessment, supplier review and assurance records for defined AI uses.
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Threat-model a RAG system across documents, indexing, retrieval and generation, then apply layered controls for permissions, provenance and testing.
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Evaluate a RAG system with test sets, retrieval and answer metrics, security tests, release gates and regression monitoring tied to real user tasks.
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Build a practical AI governance framework covering ownership, inventory, risk tiers, approval, monitoring, incidents and improvement.
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Use this AI risk assessment template to assess a use case, record evidence, rate risks, assign controls and decide whether to proceed.
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Assess an AI supplier's data handling, security, model controls, incident response and contract terms with this practical checklist and template.
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Learn how to identify and classify sensitive data using content, context, legal duties, aggregation risk and the likely impact of compromise.
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