AI Security

 When AI or LLM functionality is embedded within web applications or APIs, we integrate targeted assessment into our structured web security methodology. 

This includes:

• AI-related endpoint exposure 
• API parameter manipulation
• Role-based access enforcement
• Conversation/session ID handling 
• Prompt boundary validation
• Authentication and authorisation controls
   

AI components are treated as part of the application attack surface, subject to the same structured testing discipline as any other 

externally accessible interface.

Beyond technical testing, AI adoption introduces governance challenges that traditional controls may not fully address. 

We evaluate:

• Backend data scoping within AI workflows
• RAG configuration and document segregation
• Tool execution permissions
• API key management practices
• Logging, monitoring, and audit visibility
   

AI systems amplify existing weaknesses in control design. Governance maturity determines operational resilience.