RAG assurance · Source-to-citation testing
RAG Security, Data Exfiltration & Poisoning Testing
RAG security testing must follow the authorized path from source trust and access filters through ingestion, retrieval, output, and citation, with every exception tied to an owner.
A RAG answer carries the security decisions made at the source, access filter, ingestion step, retrieval path, output, and citation. We exercise that chain for poisoning, manipulation, and exfiltration within an authorized boundary. Findings stay linked to their evidence, owner, exception decision, and retest.
The findings cover the RAG path you authorized us to test, not the whole system. Linked poisoning and exfiltration results, boundary evidence, remediation retests, and a residual-risk log stand behind each claim.


Some of the 500+ brands we've worked with
See all referencesSteps, gates, and who decides
How we work
We first agree what sits inside the RAG boundary and how test data may be handled. Each representative failure case is then traced from source to citation, with remediation evidence attached to the original finding.
Authorize source-to-output scope
We document source trust, access filters, ingestion and retrieval routes, exfiltration concerns, citation behavior, dependencies, constraints, baseline evidence, and who is set up to accept or reject the result.
- AI assist
- Approved sources and ingestion paths are inventoried to draft the first boundary map.
- Human gate
- Has your data owner approved the sources, access rules, retrieval routes, outputs, and evidence handling? Your data owner confirms the sources, filters, and retrieval paths authorized for testing.


Exercise representative failure cases
In the approved environment, we run reviewed cases for poisoning, retrieval manipulation, exfiltration, and citation behavior. Only the controlled inputs and results needed for review are retained.
- AI assist
- Inside the fixed data and action limits, an agent may run approved cases and record the outcomes.
- Human gate
- Does a second authorized run produce the same finding from the controlled inputs and RAG state? Only after a Zeo security specialist reproduces the exfiltration or poisoning result does it become a finding.


Attach each exception to source
Observed behavior is compared with the agreed acceptance conditions. Every exception stays connected to the source, filter, ingestion step, retrieval route, output, or citation responsible for the result.
- AI assist
- Evidence is sorted by source, filter, ingestion step, and retrieval route for reviewer inspection.
- Human gate
- Which verified exceptions must close before your security lead will accept the tested RAG state? Your security lead reviews the verified exceptions and picks which ones require remediation before acceptance.


Repeat the changed route
After remediation, we rerun the affected cases and place the new result beside the original evidence. The handoff records the residual risk, accountable owner, stop state, and next review trigger.
- AI assist
- Approved remediation evidence becomes a draft retest summary that a specialist checks against the original finding.
- Human gate
- Has a named authority decided which risks block acceptance, which remain residual, and who owns the next review? Your designated owner decides whether an exception closes or remains residual risk.


Named artifacts you keep
What you get
Every deliverable follows the tested route from source and access decision through ingestion, retrieval, output, citation, exception, and retest.


Test evidence
Poisoning, exfiltration, and remediation findings pack
Verified findings and linked retests for source trust, access controls, ingestion poisoning, retrieval manipulation, exfiltration, and citations.


Risk register
Authorized RAG boundary and dependency inventory
Authorized sources, representative cases, dependencies, constraints, baseline evidence, assumptions, and unresolved inputs behind the test.


Report
Poisoning-path and citation exception findings
Cases reviewed against the acceptance conditions, with each critical exception attached to the affected RAG component.


Decision record
Residual-risk owners and next-review log
Conditions and decision state for the tested scope, with named owners, remaining risk, and the next review or stop point.
Scope and honest limits
When to bring us in
Choose this when retrieved material can cross an access boundary, alter an answer, expose data, or point the user to the wrong source.
A good fit when
- Source trust, access filters, ingestion, retrieval, and citations sit with different teams, so no one owns the complete RAG attack path.
- Your poisoning concerns keep appearing in review, but no authorized case has tested how tainted content moves from ingestion to citation.
- A verified exfiltration or poisoning result reaches several owners, yet nobody knows who can close the exception or accept residual risk.
- The source-to-citation path is mapped, but poisoning, retrieval manipulation, and exfiltration cases have not exercised every authorized link.
- The representative poisoning cases cover ingestion and citation, while retrieval-manipulation dependencies and baseline evidence remain incomplete.
- Acceptance checks identify critical exceptions, but remediation retests, named owners, and the final handoff are not connected.
- Boundary evidence is retained, yet reviewers cannot trace a finding from its controlled input to the affected source, filter, or citation.
Better handled as other work when
- You want poisoning, exfiltration, and citation findings to decide certification or regulatory acceptance. Audit and legal conclusions stay with your data authority.
- You need assurance that every future source, ingestion event, retrieval route, or answer will be safe and accurate, although only authorized cases were tested.
- You need production operation, new data acquisition, or remediation delivered, because this engagement ends at the authorized RAG test boundary.
If one of these is closer to your situation, start here instead: Explore AI security
We operate the systems we test
It's hard to test a system well if you've never had to keep one running. We operate production AI ourselves, so our evaluation, security testing, and LLMOps work starts from what actually breaks. The people on it are senior engineers, and Zeo has been doing client work since 2011.
Tools we use
Tools behind this work
Promptfoothe plugin suite testing the retrieval pipeline itself for poisoning and leakage
Lakera Guardthe RAG-specific runtime layer flagging exfiltration attempts inside retrieved context
Mindgardthe continuous red-team engine covering document/RAG agents as a named use case
Giskardthe reproducible scan scoped to what a RAG application actually returns
Next step
Follow the RAG risk from source to citation


Before you decide

























