AI/LLM Pentesting
Our AI/LLM penetration testing assesses the security of machine learning models and AI-powered apps against emerging threats.
The Challenge
AI features introduce new attack surface — prompt injection, data leakage and unsafe tool use — that traditional testing does not cover.
How We Help
We test LLM-powered applications against the OWASP Top 10 for LLMs, probing prompts, guardrails, tool integrations and data handling for real-world abuse.
- Prompt injection & jailbreak testing
- System-prompt & data leakage
- Insecure output handling
- Tool / function-calling abuse
- Training-data & RAG data exposure
- Access control around AI features
- Guardrail & filter bypass
- Prioritized report & remediation guidance
Typical project examples
Assessment of a customer-facing chatbot with tool access
RAG pipeline review for sensitive-data leakage
Guardrail bypass testing for an internal AI assistant
Frequently asked questions
What framework do you use?
The OWASP Top 10 for LLM Applications, extended with manual, application-specific testing.
Do you test the model or the application?
Primarily the application and how it uses the model — prompts, tools, data flows and access control.
Can you test agents with tool access?
Yes — tool and function-calling abuse is a key focus for agentic applications.