04 / ORBITA MORE SECURE TOMORROW
17 / AI red teaming

Challenge the assumptions behind your AI.

Run a structured adversarial exercise against the misuse scenarios that matter to your AI product and its users.

Discuss your requirements

Specialist delivery and availability are confirmed during scoping.

Adversarial AI

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.

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

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

FROM FIRST CONVERSATION TO FOLLOW-THROUGH
01

Understand

Start with your business, environment, and the decisions you need to make.

02

Assess

Agree the scope and examine the controls, configurations, and exposures that matter.

03

Prioritize

Translate findings into clear actions, accountable owners, and realistic next steps.

04

Improve

Support remediation, review the evidence, and keep the programme moving forward.

START A CONVERSATION

Let’s talk about ai red teaming.

Tell us what you need to protect. We’ll help turn the question into a clear scope of work.

Get in touch