Secure your AI
AI Red Teaming
Adversarial testing of LLM applications, copilots, agents and models. We find the jailbreaks, injections and data leaks before someone else does.
Why it matters
Traditional penetration tests were not designed for systems that take instructions from natural language. A model that behaves in a demo can still be talked into leaking data, ignoring its policy or misusing the tools it has been given.
Mapped to
- OWASP Top 10 for LLM Applications
- MITRE ATLAS
- NIST AI 600-1
What we cover
- Direct and indirect prompt injection, including payloads hidden in documents, web pages and emails
- Jailbreaks and safety-policy bypass for your specific use case
- System prompt, training data and sensitive information extraction
- Tool and plugin abuse: forcing agents to take actions they should not
- Cross-tenant and cross-user data leakage in retrieval (RAG) pipelines
- Denial-of-wallet and unbounded consumption scenarios
How an engagement runs
- 01
Scope
Agree targets, threat actors, data sensitivity and rules of engagement.
- 02
Model threats
Map trust boundaries, inputs, tools and the paths an attacker would take.
- 03
Attack
Manual and automated adversarial testing against your real deployment.
- 04
Report and retest
Walk your team through findings, then verify every fix.
What you receive
Clear outputs your engineers, leadership and auditors can each use.
- Findings report with severity, business impact and reproducible attack transcripts
- Each finding mapped to the OWASP Top 10 for LLM Applications and MITRE ATLAS
- Prioritised remediation guidance written for engineers
- Retest of fixed findings and an executive summary
Open-source first
We start with proven open-source tools to keep costs down, and recommend commercial options only when they add real value. How we choose
- garak
- PyRIT
- promptfoo
Related services
LLM Application Security
Architecture and code review for RAG apps, chatbots and copilots, so security is designed in rather than bolted on.
Learn moreAgent and MCP Security
Least privilege, sandboxing and human checkpoints for AI agents and the tools and MCP servers they connect to.
Learn moreAI Supply Chain Security
Know where your models, datasets and AI vendors come from, and what they could bring into your environment.
Learn moreReady to talk about AI Red Teaming?
Tell us what you are building. We will come back with a short, honest view of where the risk is and what it would take to test it.