LLM Application Security Penetration Testing

Our AI/LLM Application Security Penetration Testing service tests both agentic and non-agentic behaviours, with test scenarios tailored to the way application is implemented - from simple prompt-handling flows to multi-step autonomous agents. We check for ways the model can be pushed outside its intended boundaries, whether by input manipulation, prompt chaining, or API abuse, and verify it does not leak sensitive data or perform unintended actions. Additionally, we assess how those weaknesses could be misused to cause real business impact (unintended data leakage, excessive agency, mis-information, brand impact), and risk rate the vulnerabilities accordingly. This helps strike the right balance between usability and safety. This specialized, human-driven testing can help deploy AI with confidence.

AI Model Interpretation

Gather information (AI models/services)
Understanding core algorithms, input data, and anticipated outcomes

Scenario-Specific Testing

Develop test scenarios that simulate real-world situations including OWASP LLM Top 10
Execute real-world threats such as phishing attacks, malware distribution, and theft of Personally Identifiable Information (PII)
Uncover traditional attacks like RCE, SQLi, Authorization Bypass etc. through LLM-based vulnerabilities like "Prompt Injection" and "LLM Excessive Agency"

Risk/Impact Assessment

Understand both the intended and unintended behaviour of AI-based application
Evaluate risk based on various aspects like business operations, user trust, regulatory compliance, brand image, and societal impacts