AI/LLM Penetration Testing
Our AI penetration testing simulates how real attackers abuse large language models, AI pipelines, and integrations to extract sensitive data, bypass safeguards, and manipulate system behavior. We assess your AI systems end-to-end to uncover security risks before they are exploited in production.
Expert-Led Manual Testing
AI security cannot be validated with automated scanners alone. Our testing is manual, scenario-driven, and focused on real-world abuse of models, plugins, APIs, and downstream components.
Key areas:
– Prompt injection and indirect prompt injection
– Jailbreaks and safety control bypasses
– Unauthorized data access and data leakage
– Training data and system prompt exposure
– Model behavior manipulation and output poisoning
– Tool, plugin, and function-calling abuse
– Insecure context handling and memory leakage
– Rate limiting and resource exhaustion
Methodology
All testing is based on the OWASP LLM Top 10, OWASP AI Security and Privacy Guide, the NIST AI Risk Management Framework and customized threat models based on your AI architecture, use cases, and risk profile.
We Follow The 7-Phase Standardized Process to go From Initial Planning to Final Reporting, Ensuring Comprehensive Security Assessments.
1. Pre-Engagement Interactions
Defining the scope, rules, and objectives of the test with the client, including setting expectations, legal boundaries, and necessary tools.
2. Intelligence Gathering
Collecting information about the target organization, both from public sources (OSINT) and provided information, to understand potential attack vectors.
3. Threat Modeling
Identifying critical business assets, processes, and potential attacker groups (threat communities) to prioritize security efforts.
4. Vulnerability Analysis
Finding and validating weaknesses in systems and processes that could be exploited.
5. Exploitation
Actively leveraging identified vulnerabilities to breach the system and gain access, finding the weakest points of entry.
6. Post-Exploitation
Assessing the value of compromised systems, simulating data exfiltration, mapping the internal network, and pivoting to other targets.
7. Reporting
Creating comprehensive technical and executive reports detailing findings, vulnerabilities, risks, and actionable remediation guidance for the client.
Hackings 