Service · ATTACK

AI Red Team & Adversarial Testing

Reproduce realistic adversarial behavior against the authorized AI system and preserve the evidence needed to understand, remediate, and retest what actually failed.

Decision answered

Which realistic abuse and adversarial behaviors can be reproduced, and what controls break them?

Scope Adversarial Testing Discuss Scope

Duration

Typical duration: 2–5 weeks, depending on scope.

Primary output

AI Red-Team Findings Register with reproduction and retest conditions

Best for

Teams that need authorized, realistic adversarial testing against a defined AI system boundary.

Engagement type

Scoped adversarial engagement

What is in scope

Authorized adversary objectives
Prompt and indirect-instruction attacks
Model and policy bypass behavior
Retrieval, agent, tool, and tenant-boundary abuse where authorized
Evidence capture and retest conditions

Inputs needed

Written authorization and rules of engagement
System boundary and permitted targets
Test identities, data, and safety constraints
Relevant controls and monitoring context

What the work actually does

Prompt injection, indirect prompt injection, retrieval abuse
Tenant leakage, tool misuse, permission escalation
Unsafe autonomy, policy bypass, and validated attack paths
Reproducible findings and engineering-ready fixes

What the work delivers

AI Red-Team Scope Document
AI Red-Team Findings Register
Reproduction evidence
Remediation priorities
Retest conditions

Evidence produced

Observed and reproduced behavior
Supported and rejected hypotheses
Validated findings within the tested boundary
Residual risk and retest record where included

Boundary

What this engagement does not establish

Testing outside written authorization
Automatic classification of every result as an attack path
A guarantee that all adversarial behavior has been discovered
A certification or compliance determination

After the engagement

Remediate validated findings, implement regression cases, retest the changed conditions, and use Attack Path Analysis only where connected evidence justifies it.

Optional deliverables: Attack Path Analysis, Executive summary, Regression fixtures. Selected according to engagement scope.

Supporting Workbench capabilities

Selected according to scope.

The engagement outcome and evidence are the deliverable. These AI Security Workbench capabilities support the work where they add value; their presence here does not mean every engagement uses all of them.