I test LLM applications, chatbots, AI assistants, and prompt-based systems for weaknesses such as prompt injection, jailbreaks, system prompt leakage, data exposure, unsafe responses, weak guardrails, and instruction bypasses.

This service is useful before launch, after adding new AI features, or when a business wants to understand how its AI system behaves under adversarial user input.

The review may include direct prompt attacks, indirect prompt injection, retrieval/RAG abuse, unsafe completion testing, sensitive data exposure checks, policy bypass attempts, and practical recommendations for safer design.

You receive a structured report explaining what was tested, what failed, what risk it creates, and how to improve the system.

Client Requirements: Provide app access, model/provider details, system purpose, sensitive data boundaries, guardrails already in place, and approved testing scope.