AI Security
AI Security Testing
Conventional application testing covers the surface around the model and stops there. We test the system as a whole against prompt injection, data exfiltration, tool abuse and poisoned retrieval.
The business problem
Your existing testing does not cover this
A penetration test finds injection in a parameter, not instructions embedded in a document the assistant will later read. It checks authorisation on endpoints, not whether the model can be persuaded to use a tool on someone else's behalf. These are different vulnerability classes and they are not covered by scope you already buy.
What we do
Test against realistic abuse
We work from a threat model rather than a checklist: what an attacker would want and what the system makes reachable. Testing covers injection through every content path the model can read, exfiltration via output, tool abuse and privilege escalation, and retrieval poisoning. Findings come with reproduction steps, severity and a fix, ranked by exploitability, and we retest after remediation and leave the tests behind.
AI Security Testing
Capabilities
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Prompt Injection Testing
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Jailbreak Testing
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AI Data Leakage Testing
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Agent Security Testing
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RAG Poisoning Testing
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Tool Abuse Testing
Common use cases
Common use cases
- Test an AI application before it reaches production or a customer.
- Assess an assistant that already has system access nobody has reviewed.
- Establish evidence of testing for a customer security questionnaire or an auditor.
- Validate that guardrails added after an incident actually hold.
How we deliver
How we deliver
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Threat model
Establish what an attacker would target, and what they would gain by reaching it.
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Test
Adversarial testing against realistic abuse, not a checklist of known strings.
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Report
Findings with reproduction steps, severity and the fix, ranked by exploitability.
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Retest
Verify the fixes hold, and leave the tests behind so regressions surface.
Technology
Technology
- OWASP LLM Top 10
- MITRE ATLAS
- Garak
- Burp Suite
- ISO/IEC 27001
Security & governance
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.
Engagement models
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 test the system, not the model
A model in isolation has limited attack surface. The exposure comes from what it is connected to, so testing has to include the tools, the retrieval and the permissions. Because we build these systems, we know where the seams are.
Selected clients
Frequently asked questions
Frequently asked questions
How is this different from a penetration test?
Do you test against production?
What do we receive?
How long does an assessment take?
Related capabilities
Related capabilities
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AI Red Teaming
Adversarial testing of AI applications and agents against realistic abuse scenarios.
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AI Agents
Software that completes multi-step work inside your systems, under your access controls and your approval rules.
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AI Security Consulting
Threat-model AI systems and design the architecture, controls and boundaries that contain their risk.
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Test AI applications for the failure modes conventional application testing does not cover.