RAG security posture management: are your retrieval controls enough?

TL;DR: RAG expands the AI data surface by turning enterprise content into retrievable prompt context, which creates new leakage, injection and logging risks, according to LEVO. Effective RAG security posture management depends on governing ingestion sources, vector store access, retrieval policy and output handling at runtime, not just at build time.

NHIMG editorial — based on content published by LEVO: LLMjacking: How Attackers Hijack AI Using Compromised NHIs

Questions worth separating out

Q: How should teams govern retrieval-augmented generation when enterprise data is relational?

A: Start by treating retrieval sources as governed assets, not just model inputs.

Q: Why do RAG systems increase data exfiltration risk?

A: RAG systems expand the trust boundary because the model can pull in external content, then transform that content into output or tool actions.

Q: What are the signs that a RAG system is failing its access controls?

A: Common warning signs include employees retrieving content outside their business function, sensitive documents appearing in shared search results, agents exposing credentials or confidential records, and retrieval results that ignore source level permissions.

Practitioner guidance

• Approve ingestion sources explicitly Maintain a source register for every corpus feeding RAG, including owner, timestamp, classification and retention policy.
• Segment vector stores by identity and sensitivity Separate embeddings and documents by tenant, environment, and data class.
• Cap retrieval scope and context growth Set top-k limits, maximum context size, and rate limits for repeated queries.

What's in the full article

LEVO's full article covers the operational detail this post intentionally leaves for the source:

• Layer-by-layer guidance on ingestion posture, vector store access and retrieval policy design
• Monitoring patterns for retrieval spikes, unusual query behaviour and cross-domain document access
• Testing approaches for prompt injection, instruction contamination and restricted-document retrieval
• Implementation detail on output redaction, logging retention and policy filtering in RAG workflows

👉 Read LEVO's analysis of RAG security posture management →

RAG security posture management: are your retrieval controls enough?

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