AI Agent Security

AI Agent Security is the security architecture for AI agents that do more than generate text. These systems can call tools, change files, run code, use APIs, inspect data, or prepare actions in external systems. The term covers the technical and organizational controls around that runtime: sandboxes for risky execution, explicit permissions, approval workflows, network policies, secret and credential isolation, logging, telemetry, and emergency shutdown paths. Compared with traditional application security, AI Agent Security has to account for a non-deterministic actor. An agent can derive new steps from prompts, tool results, memory, and surrounding context, so securing only the model is not enough. The whole operating environment matters, from the system prompt and tool scopes to the audit trail. In companies, AI Agent Security becomes critical as soon as coding agents open pull requests, analyze sensitive data, process tickets, or touch production-adjacent workflows. Strong controls separate experiments from production rights, limit blast radius, and make important actions reviewable. It is the foundation for using autonomous or semi-autonomous AI systems in real business processes without turning every agent into an uncontrolled admin user.