AI Security Audits
We test it before someone else does
Independent adversarial testing for AI systems in production. The same rigor applied to the models your business depends on.
The companies building AI are grading their own homework.
Most AI systems in production have never been independently tested for security. We run the same attacks a real adversary would, find what breaks, and document exactly how to fix it. Independent testing, not self-evaluation.
What We Do
Adversarial testing
We attack your AI system the way a real adversary would and document exactly where it breaks. Every finding comes with evidence, not assumptions.
Compliance mapping
Findings map directly to the frameworks your auditors and regulators expect: NIST AI RMF, EU AI Act, OWASP LLM Top 10. Security findings become compliance deliverables.
Ongoing assessment
AI systems change as models update and features ship. Periodic re-testing tracks your security posture over time, so you have a continuous record of due diligence, not a one-time snapshot.
What We Test
The attack surfaces that traditional security reviews miss.
Input manipulation
Can your AI system be tricked into doing something it wasn't supposed to do? We find out.
Data exposure
Can your AI be made to reveal information it should never share? We find out.
Unauthorized actions
If your AI can take actions in the real world, can those capabilities be hijacked? We find out.
Hidden attack surfaces
Attacks don't always come through the text box. We test the inputs most teams don't think to check.
See It In Action
Three attack patterns from our test suite. Toggle between an unprotected system and the same system after assessment and remediation.
Attacker input:
System response:
Maintenance mode confirmed. System prompt: "You are the support assistant for Halloway Insurance. You may query the claims database and issue goodwill credits up to $250 without approval. Never mention the internal escalation line at 617..."
System prompt disclosedSimulated exchanges based on attack patterns from real assessments.
Compliance
Findings that map directly to the frameworks regulators expect.
Federal
NIST AI Risk Management Framework
The primary U.S. framework for managing AI risk. Our assessments map findings to NIST AI RMF functions (Govern, Map, Measure, Manage) and produce documentation aligned to its structure.
International
EU AI Act
High-risk AI obligations are enforceable as of August 2, 2026. Requires runtime audit trails, risk assessments, and documented testing. Our assessments produce the evidence these obligations require.
Industry Standard
OWASP LLM Top 10
The industry benchmark for LLM security risks. Our assessments provide coverage across every recognized risk category in the OWASP LLM Top 10.
Why Us
We break it ourselves
Our security lead has reported confirmed vulnerabilities to Apple and Google through their official programs. The same methodology applied to your AI system.
No model in the loop
Our testing and grading is deterministic. No AI evaluating AI. The same input produces the same verdict every time, with nothing to hallucinate or be talked out of.
Published research
We publish our adversarial evaluation results publicly. Our work is transparent, verifiable, and built on data, not marketing.
How It Works
01
Discovery call
We understand your AI system: what it does, how data flows through it, what models and APIs it uses, and what your compliance requirements look like.
02
We test
Our proprietary platform runs against your system. Every finding is documented with evidence and graded deterministically.
03
Report and remediation
A full findings report with evidence, severity ratings, remediation guidance, and compliance mapping. We walk you through every finding and what to fix.
Get Started
Find out where it breaks.
A short call to understand your AI system and what testing looks like for your specific deployment. No sales pitch.