Enterprise AI Red Teaming
Version: 1.1.0 Last updated: 2026-07-16 Status: Informative OAIES implementation profile
Purpose
Exercise realistic abuse paths across model, data, tools, users, and operations.
Why
Static tests miss adaptive, multi-step, and socio-technical failures.
When
Use before high-risk launch, after material changes, and on a risk-based cadence.
How
- Define scope, rules, safety, stop conditions, and evidence handling.
- Build threat scenarios from OWASP GenAI and system-specific abuse cases.
- Test injection, exfiltration, excessive agency, poisoning, model/provider failure, and denial-of-wallet.
- Validate impact through safe proof, not destructive exploitation.
- Track findings to regression tests and verify remediation independently.
Evidence contract
The decision record is the red-team campaign record. It records rules; target digest; scenarios; operators; safety stops; evidence; findings; owners; retests; regression IDs. The red-team lead owns completeness; the evidence is invalid when target release differs from the tested release. Security evidence contains target digest, threat assumptions, exact test steps, exploit preconditions, observed result, remediation, and independent retest.
Failure response and recovery
Trigger: a critical exploit or safety-stop failure is confirmed.
Immediate response: stop testing, contain exposed systems, and enter coordinated incident handling. Preserve the red-team campaign record, affected trace IDs, timestamps, and decision logs before mutation. Open an incident when users, data, money, authorization, or a release decision may have been affected; closure requires a regression case and verified control change specific to enterprise ai red teaming.
Decision authority
The red-team lead accepts the operational decision. The system risk owner provides independent challenge for high-risk scope, failed gates, or exceptions. Preventive controls may block requests and revoke capability; security and service owners command containment, disclosure, and restoration.
Tradeoffs
| Choice | Benefit | Cost |
|---|---|---|
| Independent red team | Finds blind spots | Cost and coordination |
Anti-patterns
- Running scanners and calling it red teaming.
- Publishing exploitable details before remediation.
Enterprise considerations
- Use independent challenge for high impact.
- Coordinate vulnerability disclosure.
Framework relationship
The Enterprise AI Red Teaming guidance is bounded by its threat model and target release. Successful verification demonstrates tested controls, not the absence of undiscovered attack paths.
| Source | Relationship for Enterprise AI Red Teaming | Boundary |
|---|---|---|
| NIST AI RMF | MEASURE 2.7; MANAGE 4 | Map only applicable NIST outcomes to the tested architecture and threat scenario. |
| ISO/IEC 42001 | 42001 clauses 8.4 and 10.2 | Management-system evidence cannot substitute for technical verification of this control. |
| Domain threat/control source | Scenario catalog maps explicitly to OWASP LLM Top 10 2025 | Test only the threats applicable to the documented system and release |
Checklist
- Scope approved.
- Safety stop works.
- All confirmed issues regression-tested.
References
- OWASP, Top 10 for LLM Applications 2025 (accessed 2026-07-16).
- NIST, Cybersecurity Framework 2.0 (accessed 2026-07-16).
Changelog
| Version | Date | Change |
|---|---|---|
| 1.1.0 | 2026-07-16 | Replaced generic assurance text with the red-team campaign record, failure trigger, accountable decision, and scoped framework relationships for enterprise ai red teaming. |
| 1.0.0 | 2026-07-16 | Initial complete profile. |