It’s a good idea to spend some time understanding the MXC policy schema. This is where you learn what MXC can do and what it can’t. It’s important to understand that MXC cannot provide more isolation than you get from a locked-down virtual environment, and that it can’t switch virtualization endpoints on the fly. The schema documentation shows the principles that are used by MXC’s development team. For example, they indicate that policies are an expression of intent, that the enforcement mechanisms are implemented in the tooling, and that the default position on any policy is “deny.” Thus, users need only define the policies they want to have a more permissive approach, as having no policy definition is by default an opt out.
Further, the tooling is designed to be cross-platform. You need only define policies once, and the Windows, macOS, and Linux versions of MXC will implement them on a target sandbox. How they are enforced will differ among the platforms and sandboxes, but whatever MXC does, it is driven by user intent. Putting the user requirements first is key, as the purpose of MXC is to provide a way for users to trust agents and to know that agents won’t run amuck and destroy data.
Using MXC to understand agent behavior
If you’re using MXC to develop agents and you want to tune the rules it uses, you can run MXC in audit and learning modes. This allows operations that would otherwise be blocked; instead of denying the operations, it logs them along with other operations, allowing you to tune your policies to actual agent behavior. Of course, it’s a good idea to run audit and learning modes on a virtual machine, or on a scratch test install, to ensure that your development systems are not impacted by an uncontrolled agent.
