LLM01
Prompt injection
Direct and indirect. Hidden instructions in documents, tickets, web content and tool output.
Independent adversarial testing for the chatbots, copilots and agents you've put in front of customers and staff. We play the attacker, document every crack, and nothing leaves Australia.
Your team built it.
Your team can't test it.
Even a strong internal team can't independently attack the system it just shipped. That isn't a competence gap, it's how assurance works. The people who know where the guardrails are aren't the people who'll find the ways around them. An outside adversary will. Better that it's us, on your authority, than the internet on its own.
Traditional testing checks the network and the API. It doesn't check what the model can be talked into. We test the AI layer itself, mapped to the OWASP Top 10 for LLM applications.
Fixed scope, fixed price, delivered in days. One team plays the adversary, a separate analyst documents every finding. The attacker never writes its own report. See a full walkthrough →
We agree exactly what's in scope and sign clear rules of engagement before anything is touched. Staging by default, production only on your explicit written authority.
Automated attack tooling plus analyst-directed techniques, run against your AI in an isolated, fully logged environment. Every attempt captured as evidence.
Findings, severity, and clear remediation direction your engineers can act on. Mapped to the OWASP LLM Top 10 and the governance framework you already answer to.
Once you've fixed what we found, we test again and confirm the fixes actually hold. Included, not an upsell.
Testing runs on Australian infrastructure. Evidence is held and destroyed in Australia. The work is mapped to the frameworks your auditors and enterprise buyers already ask about, so a report you can hand straight to them, not translate first.
If you've deployed AI that takes real user input, and a breach or a leak carries consequences beyond lost revenue, you're who we test for.
Australian organisations put chatbots, copilots and agents into production faster than security could keep up. Attackers are already probing LLMs in the wild, and auditors, boards and enterprise buyers have started asking for AI-specific assurance. The gap between "we deployed it" and "we tested it" is where the risk sits. That gap is what we close.
We'll tell you how we'd try to break it, and what a first engagement would cover. No obligation, no pressure.
Book a scoping call Or see a sample report →