AI Security

AI Red Teaming

Structured adversarial testing against realistic abuse scenarios: what a motivated attacker, a hostile user or a careless one can make the system do.

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The business problem

Nobody attacked it before it shipped

Systems are tested against how they are meant to be used. Real users are more inventive than test plans, and some are hostile. For anything customer-facing, the first genuinely adversarial interaction happens in production, in public, with a screenshot.

What we do

Attack it with objectives, not prompts

We work to objectives rather than a wordlist: extract data the user should not reach, make it act outside its remit, get it to produce something reputationally damaging, drive cost through resource abuse. Each success is documented with the exact path, so it is reproducible and fixable. We also test the boring failures, degradation under load, behaviour when a tool errors, since those cause more incidents than clever attacks.

AI Red Teaming

Capabilities

Adversarial AI Testing
Agent Red Teaming
LLM Red Teaming
Abuse Scenario Testing
AI Attack Simulation

Common use cases

Assess a customer-facing assistant before launch.
Test an agent with write access to production systems.
Provide independent assurance for a board or a regulator.
Establish an ongoing testing cadence rather than a one-off exercise.

How we deliver

Threat model

Establish what an attacker would target, and what they would gain by reaching it.
Test

Adversarial testing against realistic abuse, not a checklist of known strings.
Report

Findings with reproduction steps, severity and the fix, ranked by exploitability.
Retest

Verify the fixes hold, and leave the tests behind so regressions surface.

Technology

OWASP LLM Top 10
MITRE ATLAS
Garak
Burp Suite
ISO/IEC 27001

Security & governance

Testing is authorised in writing, scoped to agreed targets and run against a non-production environment unless you decide otherwise. Findings are handled as confidential and disclosed to you before anyone else. Nothing is retained beyond the engagement except the report and the regression tests you asked us to leave behind.

Independently audited against

Engagement models

AI Advisory

Expert consultants provide strategy, architecture, assessment and transformation guidance.

AI Project

We take responsibility for designing and delivering a defined AI solution.

Managed AI

We operate, monitor and continuously improve production AI systems.

Why TeamExtension.ai

We report what it means, not just what worked

A list of successful jailbreaks is not useful on its own. What matters is which ones reach something valuable, and which architectural change closes a class of them at once rather than one at a time.

Selected clients

Frequently asked questions

How is this different from security testing?

Security testing works systematically through known vulnerability classes. Red teaming works to objectives and uses whatever path succeeds, including social and multi-step approaches. Both are useful; they answer different questions.

Will you find something?

Almost certainly. The useful question is whether what we find reaches anything that matters, which is what the report is organised around.

Can this run continuously?

Yes. Automated adversarial suites run in the pipeline, with periodic human-led exercises for the creative attacks automation does not find.

What authorisation do you need?

Written authorisation from someone empowered to give it, with agreed scope, timing and escalation. We do not test systems without it.

Related capabilities

AI Security

AI Security Testing

Test AI applications for the failure modes conventional application testing does not cover.

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AI Security

AI Security Consulting

Threat-model AI systems and design the architecture, controls and boundaries that contain their risk.

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Agentic AI & Automation

AI Agents

Software that completes multi-step work inside your systems, under your access controls and your approval rules.

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Discuss Your AI Initiative

Adversarial testing of AI applications and agents against realistic abuse scenarios.

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