AI Agent Security
Best Practices
Cheat Sheet

AI agent security focuses on protecting systems that can take actions on their own, like calling APIs, accessing data, or triggering workflows. Unlike traditional applications, AI agents operate dynamically, so security needs to account for real-time behavior, not just static configuration.

AI agents can access multiple systems, make decisions, and execute actions automatically. If permissions are too broad or inputs are manipulated, they can perform unintended actions, access sensitive data, or trigger downstream systems without clear visibility.

Securing AI agents starts with visibility into where they run and what they do. From there, teams should define clear identities, enforce least privilege, monitor runtime behavior, and detect unexpected or unintended actions as they happen.

Key best practices include maintaining an inventory of agents, monitoring behavior in real time, assigning unique identities, limiting permissions, detecting abnormal actions, and isolating agents to reduce blast radius.