AI & LLM Penetration Testing
Security testing for LLM-powered features — prompt injection, data leakage, and model abuse, aligned to the OWASP LLM Top 10.
AI and LLM penetration testing secures LLM-powered features against prompt injection, data leakage, and model abuse — aligned to the OWASP LLM Top 10 and proven with working exploits.
Where attackers get in — and where we look.
Direct & indirect prompt injection
Sensitive-data leakage
Insecure output handling & XSS
Training-data & RAG exposure
Excessive agency & guardrail bypass
Model, plugin & supply-chain abuse
A proof-driven methodology.
Scope & recon
We agree objectives and rules of engagement, then map what you actually expose.
Map the attack surface
Enumerate entry points, roles, and trust boundaries a real attacker would target.
Manual exploitation
Certified testers exploit flaws by hand — chaining issues scanners never connect.
Prove impact
Every finding ships with a working, reproducible proof-of-exploit and business context.
Report & retest
Risk-ranked report with fixes, then a retest that confirms each issue is closed.
Proof you can act on.
Reproducible proof-of-exploit
Every finding ships with a working exploit and evidence.
Risk-ranked report
CVSS + business context, prioritized for your team.
Remediation guidance
Actionable fixes mapped to each finding.
Retest to verified fix
We confirm closure — proof it’s fixed, not assumed.
Make it continuous.
Pair this test with a program that keeps coverage live between engagements.
AI & LLM Penetration Testing — questions buyers ask.
What is prompt injection?
Prompt injection manipulates an LLM’s instructions — directly or through poisoned content it reads (indirect) — to make it leak data or take unintended actions. It is the top LLM risk we test.
Do you follow the OWASP LLM Top 10?
Yes — our testing maps to the OWASP Top 10 for LLM Applications, covering injection, data leakage, insecure output handling, and excessive agency.
Can you test RAG systems?
Yes — retrieval-augmented generation introduces training-data and context-exposure risks that we specifically target.
Prove what an attacker could actually do.
A short scoping call, no obligation.