AI Agent Security Cheat Sheet
Get the 5-step framework for discovering, governing, and recovering AI agents before they put your data at risk.
AI agents don’t wait for permission, and that’s exactly the challenge. The moment an agent can act on your data rather than simply answering questions about it, gaps in access controls, inventory management, and approval processes can quickly become security risks.
Data leakage is already the most common agent breach type, and one in five organizations can’t say for certain whether unsanctioned agents are running in their environment at all.
This cheat sheet outlines the four key risks organizations face as AI agents evolve from chat-based assistants to autonomous actors: data leakage, shadow agents, input manipulation, and governance gaps. You'll find practical guidance for securing agent access, questions to help shape governance decisions, and a five-step framework for putting effective controls in place.
What you’ll learn:
- Identify the four most common ways AI agents put data and operations at risk.
- Apply practical do’s and don’ts for defining agent permissions and approval processes.
- Align governance decisions to how agents are actually being used across your business.
- Implement a 5-step framework: discover, identify, guard, audit, recover.
AI agent sprawl rarely announces itself. It may lack a clear owner, retain permissions beyond its intended purpose, or take actions without consistent review.
This cheat sheet gives security and IT leaders a practical, actionable approach to staying ahead of those risks — starting visibility into every agent in the environment and ending with a recovery strategy when something goes wrong.
