Introduction to Docker Sandboxes with Go
AI coding agents are at their best when we let them work on their own, installing packages, running tests, building images, and trying things out without asking for permission every step of the way. But that's also when they're the most dangerous. An agent running on our laptop can do anything we can, including reading our SSH keys or wiping our home directory. Docker Sandboxes tries to solve…
Docker Sandboxes provide isolated environments for running potentially untrusted code, such as AI coding agents. Each sandbox is a lightweight virtual machine with its own kernel, filesystem, and Docker Engine. Sandboxes come in two types: local, managed by a CLI tool called sbx, and cloud sandboxes created via the Sandboxes API.
The key advantages of sandboxes over regular containers are that they run in their own isolated environment, have their own Docker Engine, and have finer-grained network policies. Sandboxes use microVMs to provide an additional layer of isolation compared to containers, which only use kernel namespaces and cgroups. Each sandbox has its own Docker Engine with a separate image cache, allowing agents to build images and run containers without affecting the host.
There are three ways to provide access to files and directories within a sandbox: direct mode mounts the host directory at the same path inside the sandbox, clone mode mounts a read-only host repository and creates a private clone inside the sandbox, and no workspace mounts nothing from the host. Network access from sandboxes is controlled through a proxy that checks outbound traffic against a network policy.
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