AI-Augmented Testing
We use AI in our testing, and we research how AI systems are attacked and secured.
In our testing
We build and run our own testing tooling that pairs established security tools with multiple language models for analysis. Feeding into it is a private corpus of vulnerability research and findings that we build and maintain ourselves. It informs what we test for on a given target and helps separate real issues from scanner noise.
Rather than running everything at everything, testing is scoped to the technology actually in front of us. That keeps false positives down and keeps findings backed by evidence.
AI handles the breadth: the high-volume reconnaissance and surface mapping that is slow to do by hand. The operator handles the rest. Exploitation, judgment, and validation stay with an experienced tester, and every finding is checked by hand before it goes in a report. The tooling makes a tester faster. It does not replace one, and it does not sit between you and a person who is accountable for the result.
AI Research
We also work the other direction, on how these systems break and how to secure them. Our published research covers LLM architecture and the techniques that get past current defences.
Security assessment of AI-integrated applications (LLM deployments, RAG pipelines, agentic workflows) is a core service. See Services for detail.
Interested in AI-augmented security assessments or need assurance your AI system is secure? Contact us to discuss your requirements.