How to Secure Your Multi-Agent AI System: A Practical Checklist

Your AI agents trust each other by default. That's your biggest security hole. Picture this: Your research agent pulls data from an external source. That data contains a hidden instruction. Your research agent doesn't catch it — why would it? It passes the data to your planning agent. The planning agent treats it as legitimate context and adjusts its strategy. The execution agent follows the new strategy and performs an action you never authorized. Three agents. One poisoned input. Zero alerts. If you've read our previous article on monitoring AI agents in production, you know that observability is the foundation. But monitoring tells you what happened. Security determines what's allowed to happen in the first place. This is the security checklist we built after running a 12-agent team in production. Every item on this list exists because we learned the hard way. Why Multi-Agent Security Is Different When you secure a single AI model, you're protecting one endpoint. One input, one outp