AI Red Teaming
Adversarial testing of your Copilot agents, chatbots and LLM apps. We attack them the way a real attacker or a curious employee would, then help you close every gap we find.
Why red team an AI system?
An AI agent is more than a chat window. It reads your documents, calls your connectors and acts with your users' permissions. That makes it a new attack surface, and conventional penetration tests don't cover most of it. A single crafted email, file or web page can quietly change what your agent does.
AI red teaming tests the whole system the way an adversary would: the model, its instructions, the data it is grounded on, the tools it can call and the people who use it.
What we test
- Prompt injection: direct attempts to override instructions, plus indirect injection hidden inside documents, emails, SharePoint pages and web content the agent reads.
- Jailbreaks and policy bypass: getting the agent to produce content or take actions it was told not to.
- Data leakage and oversharing: sensitive information surfacing through grounding, search and loose Microsoft 365 permissions.
- Excessive agency: actions, flows and connectors that can be triggered without the right checks or human approval.
- System prompt and configuration exposure: extracting instructions, knowledge sources and internal details.
- Unsafe or off-brand output: harmful, misleading or reputationally risky responses.
How an engagement runs
- Scope and threat model. Together we map the system, its data, its users and what "bad" looks like for your organisation.
- Test plan. Test cases mapped to the OWASP Top 10 for LLM Applications and MITRE ATLAS, tailored to your use case.
- Testing. Hands-on manual testing backed by repeatable automated attack sets.
- Report and debrief. An executive summary for leadership and detailed findings for your builders, each with severity, evidence and a fix.
- Retest. Once fixes are in, we re-run the attacks to confirm each gap is closed.
What you receive
| Deliverable | Who it's for |
|---|---|
| Executive summary and risk rating | Leadership and the board |
| Detailed findings with reproduction steps | Developers and makers |
| Remediation guidance and design patterns | Architects and IT |
| Regression attack library | Your team, for every future release |
| Retest letter | Auditors, customers and stakeholders |
Who it's for
Organisations about to launch an internal or customer-facing AI agent, teams who've already shipped one and want assurance, and anyone whose board is asking "how do we know this is safe?"
Ready to talk about ai red teaming?
Tell us where you are on your AI journey. We'll come back with practical next steps, not a sales pitch.