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Which compliance controls apply to OWASP LLM08 vector weaknesses

OWASP LLM08 covers weak access control, leaks and poisoning in RAG stores. This maps each risk to the control families auditors already ask about.

Safeguard Security Team
4 min read

OWASP LLM08 covers flaws in how embeddings are created, stored and retrieved in RAG systems. For compliance, it maps to controls you probably already own: access control, data classification, supplier vetting and logging. The work is applying them to the vector store, which often sits outside normal review.

What does LLM08 say?

OWASP describes vector and embedding weaknesses as flaws in generating, storing or retrieving embeddings that can be used, on purpose or by accident, to inject harmful content, manipulate output or expose sensitive information. Its listed risks are unauthorized access and data leakage, cross context leaks in multi tenant stores, embedding inversion, data poisoning and behavior alteration.

Its mitigations are plain: permission aware vector stores, partitioning by access level, validating pipelines and trusted sources, tagging and classifying data, and keeping detailed, immutable logs of retrieval.

How does each risk map to a control family?

This table is a working aid, not an official crosswalk. Check the exact control numbers against the framework versions you use.

  • Unauthorized access maps to logical access and least privilege. An auditor may ask who can query each index and whether that is enforced at retrieval.
  • Cross context leaks map to tenant isolation and segregation. Can one customer's chunks be returned to another?
  • Sensitive data embedded maps to data classification and privacy. What entered the index, and was it allowed to?
  • Poisoned source content maps to supplier and input integrity. Who can add documents, and are they reviewed?
  • Weak retrieval logging maps to logging and monitoring. Can you reconstruct what was retrieved for a given answer?

Frameworks that commonly come up here include ISO 27001 style access and supplier controls, SOC 2 criteria on logical access and monitoring, and the NIST AI Risk Management Framework for governance. The same evidence often serves more than one.

What does the evidence look like?

Auditors rarely want a policy alone. Useful artifacts are:

  • an inventory of every vector store and what it holds
  • the access model for each index, including service accounts
  • the ingestion path with who approved each source
  • retrieval logs with user, query time and returned document identifiers
  • a test record showing a user cannot retrieve chunks from a group they do not belong to

Where do teams slip?

Most gaps come from treating the vector database as a cache. It holds copies of sensitive documents, often with looser permissions than the originals. Another gap is ingestion: a shared drive connected to an index quietly imports whatever lands there, including files with hidden text.

What would a short audit conversation sound like?

Imagine an assessor asks, "Show me how a support agent is prevented from retrieving finance documents through your assistant." A weak answer is that the prompt tells the model not to. OWASP's guidance points the other way: enforce access in the retrieval layer, so the wrong chunks never reach the model at all.

A stronger answer walks through the identity passed to the vector store, the filter applied by group, the test that proves it, and the log line showing the filtered query. That is the same evidence pattern used for any data store, applied to a newer component.

The same logic holds for poisoning. "We trust our documents" is not evidence. A record of who can write to the source folder, plus a review step for new files, is.

What to do

  1. Inventory every vector store, embedding model and ingestion source.
  2. Classify the data in each index and remove what should not be there.
  3. Enforce document level permissions at query time, not only at upload.
  4. Partition indexes by tenant or sensitivity.
  5. Restrict who can add documents and review new sources.
  6. Log retrievals immutably and keep them for your retention period.
  7. Test cross user retrieval each release and file the result.

Quick check

Is embedding data personal data?

It can be. If the source text contains personal data and the embedding can be reversed, treat it as sensitive. OWASP lists embedding inversion as a risk.

Does a framework name LLM08 directly?

Generally no. Frameworks speak in control families, so you map the risk to the family, as above.

Sources

Last reviewed: 18 October 2026.

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