Doesn’t surprise me. Yesterday I learned that people run AI agents on their system with full admin rights. No containerisation or anything. Wild. Like we forgot 50 years of computer security overnight.
That's because sandboxing is quite hard. I use `cco`, but even then, the home folder is exposed. You are one prompt away from the agent sending the browser passwords with curl. To prevent this, you need a fake home and a networking whitelist for the agent to access the provider (llama cpp, OpenAI, etc.) There is no cross-platform solution that is easy to use for this. And no, a Linux box with Docker won't do. I devel…
- Sandbox on Linux using Docker, Podman, containerd, gVisor, Kata, Firecracker
- Sandbox on Mac using Docker (Docker Desktop or Orbstack), Podman, Apple containers, Seatbelt, Tart (Tart lets you run simulators).
- Network control
- Secrets control (file mounts or credentials broker)
- NO ambient data (ENV is replaced with a minimal and local-to-sandbox one)
- NO access to your homedir. You have to explicitly mount things you want.
- NO direct access to your workdir: Your work dir is never modified until you apply the changes, either standalone or as a git commit. You can also diff before applying. Git runs sandbox side in case the repo has filters.
- gitignored files never get copied in. The agent never sees them.
- Has built-in support for claude, codex, gemini, aider, and opencode, but you can also launch it in "shell" mode and run whatever you want.
- Supports VS code tunnels, so you can remotely access in VS code if you don't want to use the terminal.
- Full lifecycle support: Launch, attach, stop, restart, wait, one-shot, clone, destroy
- MCP passthrough
- Layered API (golang) if you want to sandbox other things
- Self-contained binary. No external requirements other than the backends you want to use. Defaults to a ~/.yoloai dir for config/data, but you can point it anywhere.
- FOSS