Your AI apps have new attack surfaces.
We test them, then patch them.
Prompt injection, data leakage, tool misuse, jailbreaks. AI applications fail in ways traditional security testing never looks for. We attack your AI apps and agents the way adversaries will, document what breaks, and fix it. Patches shipped into your codebase, not a PDF of findings.
Your pen test never looked for prompt injection.
Traditional security testing hunts known vulnerability classes in known places. AI applications break differently. A carefully worded input can override system instructions, pull confidential data out of the context window, or trick an agent into misusing the tools it is connected to, and none of it shows up in a standard scan or pen test.
When you own your AI systems you also own their failure modes, which is exactly why you want them tested honestly rather than described in a vendor's security whitepaper. Most teams shipping AI features have never been attacked this way, so the first adversary to try will be a real one. Better that it is us: the same techniques, under controlled conditions, ending in a fix instead of an incident.
We break it, we document it,
we fix it.
One engagement covers the full loop: adversarial testing across your AI surface, findings ranked by real-world exploitability, and patches implemented in your codebase.
Adversarial testing engagement
We attack your AI apps and agents the way adversaries will, using prompt injection, jailbreaks, data leakage, and tool misuse, across every interface your users and attackers can reach. Each finding comes with a working reproduction, an impact rating, and a recommended fix, so nothing lands as a vague warning.
Scope a test →- Adversarial testing of AI apps and agents
- Prompt injection and jailbreak testing
- Data leakage analysis across context and retrieval
- Tool and agent misuse scenarios
- Findings prioritized by exploitability and impact
- Patches implemented, not just reported
Patching, not just reporting
Most security reports die in a backlog. We implement the fixes with your team, including input hardening, output filtering, permission scoping, and guardrail layers, so the engagement ends with closed holes rather than open tickets.
Book a scoping call →Retest and handoff
After patching we re-run the full attack suite to confirm each exploit no longer lands, then hand your team the test cases. Every future release gets checked against the same attacks, by your own engineers, without calling us.
Talk it through →Built for teams shipping AI to real users.
If your AI features touch customers, data, or tools, this is for you.
Testing is one layer.
Here is the rest.
Find out what breaks before an attacker does.
Fixed scope, fast turnaround, patches included. Tell us what you have shipped and we will scope the test.
