AI Security Testing
AI is changing how software is built, and increasingly how vulnerabilities are found. We help organisations on both sides: manual security reviews of applications built with AI tools, and AI working inside our own continuous penetration testing methodology — with a human tester validating what matters.
Request AI Security TestHow we help secure AI-built software
Code written with Copilot, Cursor, Claude Code or ChatGPT reaches production quickly, and AI agents are now effective at catching the obvious issues — SQL injection, known bad patterns, unsafe defaults. What they consistently miss are the issues that require understanding intent: business logic flaws, authorisation rules that only make sense in context, weaknesses chained across components, and edge cases that only surface with a specific user role or data shape. That is the gap a human tester is there to close.
The urgency is rising. AI models are now being used to find software vulnerabilities at a scale and speed that was not possible a year ago, and that capability will not stay on the defensive side alone. Organisations shipping AI-built software need to close the obvious gaps before someone else's AI does it for them.
On our side of the work, we use AI inside our own testing — for recon, triage, and continuous coverage between manual testing sessions. This capability is delivered as part of our continuous penetration testing engagement rather than as a separate product, because a human tester still validates every finding that matters.
Sawah Cyber Security's team follows market trends and technology closely, to see how both the attacker and defender sides of AI are evolving — and to make sure the methodology we offer keeps pace with what is actually possible.
When an AI-built Proof of Concept turns into a real product
A sales professional in the Netherlands approached Sawah Cyber Security with a scenario that is becoming increasingly common. Non-technical, without a single line of code ever written, this person had turned an idea into a working application purely through prompting an AI coding tool — and real customers were already signing up with their bank account number and personal data.
The core issue: there was no clear picture of what had been built beneath the surface. Which database the application used, where data was stored, whether any backups existed — none of it was known, while the product was on its way to handling payment details and other sensitive customer information.
In the Netherlands, the stakes are particularly high. Under GDPR, when an app is breached the owner is directly liable, with fines and reputational damage falling on the individual whose name is on the product.
It is the kind of situation this service exists for. AI lowers the barrier to shipping software enormously, but the people shipping it often have no reliable way to determine whether the result is safe to release — and need a human tester to work through the code and the architecture before the product moves forward.
Where AI fits in our work
A second opinion on your AI-built software
A manual security review of the code, architecture and data flows behind your application — the issues a tool on its own will not catch. Our team conducts an independent, security-focused assessment and gives you a clear view of what needs addressing before the product reaches real users.
AI inside our testing work
We use AI as part of our own testing methodology — for recon, triage, and continuous coverage between manual testing sessions. Delivered as part of our continuous penetration testing service, with a human tester validating every finding that matters. Aligned with the OWASP AI Testing Guide.
Speak to our team about AI security testing
Discuss your AI security testing needs with our specialists and find the right approach for your organisation.
Request AI Security Test