AI Agent Security: Identity & Access Management in the AI Era

AI agents are changing how we think about security. The good news is that basic security principles remain the same. What's interesting is that AI agents don't have their own unique identities. They use the identities of the applications or humans they work for. This means if an agent can attack a system, its human counterpart could too. However, three key attributes of AI agent deployments require adjustments to security planning. First, agents are unpredictable. Unlike traditional applications with defined paths, agents make decisions, and the same prompt can lead to different results. This is like sending a small child with your credit card to the store; the outcome isn't guaranteed. Second, agent platforms often come with excessive privileges by default. Many platforms, like Microsoft Copilot, were designed for functionality first, with security as an afterthought. They frequently require administrative rights or privileged access and lack granular permission controls. Some even elevate privileges behind the scenes, giving the agent more power than the user who created it. For example, creating an API key in AWS Bedrock can secretly create a highly privileged user with a powerful policy. This happens automatically when you click a button. The bottom line is that while core security principles hold, the unpredictable nature and default high privileges of AI agents demand careful attention to identity and access management.