AI Agent Hacking & Security

AI Agent Hacking & Security Testing

Explored how an AI agent can be manipulated through adversarial interactions, with a focus on AI agent hacking, prompt injection, sensitive data exposure, and unsafe agent behavior.

The lab uses an AI agent connected to controlled internal data and tools, creating a realistic environment for testing how the agent responds when an attacker attempts to bypass its instructions, access information it should not reveal, or influence how it uses its capabilities.

The assessment demonstrates the practical attack surface of modern AI agents and how seemingly simple interactions can become security issues when an agent has access to sensitive data or external capabilities. The testing was performed against fictional data in an isolated environment for authorized security research.