AI Chatbot Security Testing
Customer support bots, FAQ assistants, and internal knowledge chatbots tested for prompt injection, jailbreaks, system prompt leakage, sensitive data disclosure, and unsafe or off-policy responses.
Agentic AI Security Testing
Tool-using agents, autonomous workflows, and multi-agent systems, along with the MCP (Model Context Protocol) servers and clients that connect them to external tools and data sources, tested end to end. We assess excessive agency, goal hijacking, unsafe tool execution, and privilege abuse, together with authentication gaps, over-broad tool access, tool poisoning, confused-deputy flaws, and token handling.
AI RAG Security Testing
Retrieval-augmented generation pipelines, knowledge bases, and document Q&A systems tested for poisoned content, cross-user data leakage, weak access controls on embeddings, and indirect prompt injection.
AI Application Security Testing (Web/API)
AI-powered web applications, APIs, and enterprise integrations where AI is one component among many, covering authentication, authorization, output handling, and the surrounding application and cloud stack.
AI/ML Custom Model Security Testing
Testing of the model itself for adversarial inputs, model extraction, training data inference, data poisoning, and backdoored or tampered models.
Deliverables
Executive summary, technical findings with reproducible proof-of-concept, and a risk-rated remediation roadmap mapped to the OWASP Top 10 for LLM Applications and MITRE ATLAS.