AI red teaming

Challenge the assumptions behind your AI.

Specialist delivery and availability are confirmed during scoping.

THE RIGHT STARTING POINT

For product and security leaders making a consequential AI launch or deployment decision. Specialist safety evaluation and sector-specific harms need explicitly qualified reviewers.

A clear scope. A useful outcome.

Choose a business consequence, define a realistic adversary, and challenge the system within agreed limits. Combine application, model-behaviour, and operational scenarios where the available access supports them. Record unsuccessful attempts and coverage gaps alongside confirmed findings so the outcome supports a release or risk decision. Agree whether the exercise covers security only or also specific safety and policy objectives.

The final scope, deliverables, and timing are agreed for your engagement.

What we cover

• Objective-led misuse and multi-step attack scenarios
• Instruction-following failures and sensitive-information exposure
• Guardrail resilience across relevant languages and input formats
• Detection, escalation, and recovery during simulated AI misuse

What you take away

• Exercise objectives, adversary assumptions, and rules of engagement
• Scenario evidence with observed impact and test limitations
• Prioritized defensive changes and risk-owner debrief
• Regression scenarios for the agreed application and model versions

How to engage

Time-bounded exercise with a preparation workshop, technical debrief, and optional rerun.

What progress looks like

Exercise objectives evaluated, confirmed failure paths addressed, and regression scenarios retained.

Before the engagement.

Agree the systems and business processes in scope, the authorisation required, the people involved and how the findings will be used. Timelines, deliverables, exclusions and any verification work should be confirmed directly.