Creating a Sandbox for your Agent and Dev Environment (with opencode)

I have been using opencode (and other agent harnesses) on my local ubuntu machine. I usually give permission "always allow" once it asks for things like "ls" and "cat". Recently after doing this it went and read some personal documents and most definitely sent that over the internet to the model provider.

This is the risk and there is nothing stopping it from reading files that are unencrypted while logged in – such as ~/.ssh/id_ed25519 or finding some way to get the browser secrets.

The answer is isolating / sandboxing the place where the agent runs – so one can give it lenient permissions without it exposing data you do not want it to.

What agent sandbox options are there?

These are some sandboxes I could find with a google ai assisted search and looking at the awesome-agent-sandboxes readme, focusing on the self-hosted options.

Evaluated

Direct docker cli sandbox
Agentinfra all-in-one sandbox – All-in-One Sandbox for AI Agents that combines Browser, Shell, File, MCP and VSCode Server in a single Docker container
Arrakis – A fully customizable and self-hosted sandboxing solution for AI agent code execution and computer use
Bunkervm – Time-travel debugging for AI agent sandboxes with firecracker vm
Bouvet – Isolated code execution sandboxes for AI agents
Sandbox AI – Run AI generated code in isolated sandboxes
Microsandbox – easy, fast, programmable and local-first microVM runtime and library
nono – A Secure Sandbox for AI Agents
fence – Lightweight, container-free sandbox for running commands with network and filesystem restrictions
yolobox – Let your AI go full send. Your home directory stays home.
Mudroom – Run coding agents in a Linux VM on a clone of your project, then review and apply their changes like a pull request
Agentbox – Run multiple agents in parallel sandboxed VMs, with a single command, on your PC or in the cloud
Opensandbox – Secure, Fast, and Extensible Sandbox runtime for AI agents.
Opencode sandbox – Modified docker based sandbox specifically for opencode
cplt – Sandbox for AI coding agents. Runs Copilot CLI, Claude Code, OpenCode, Gemini CLI, Antigravity, Pi, goose or a plain shell inside a kernel-level sandbox, with git and gh guards and sandbox policy committed to the repository.
sandbase-harness – Local-first, self-hosted AI agent runtime and MCP bridge with sandboxed sessions, memory, credentials, audit/replay, and a local Console.

Skipped

Docker Sandboxes – skipped as it requires a docker account login to use them
DaytoneSandboxes – appears to require login
Flintlock – Not a sandbox, used to lifecycle management of microVMs.
Rivet agents – Not clear if it is fit for purpose from the readme.
Sandboxer – looks like a playground for a talk that has not been updated recently

Direct docker cli sandbox

Create a project folder and add 3 files…

Dockerfile:

# Use a lightweight, official Python runtime
FROM python:3.11-slim

# Set the working directory inside the container
WORKDIR /app

# Ensure standard system tools are available for Python development
RUN apt-get update && apt-get install -y --no-install-recommends \
    git \
    curl \
    ca-certificates \
    && rm -rf /var/lib/apt/lists/*

# Run the official installation script inside the container
RUN curl -fsSL https://opencode.ai/v2/install | bash

# Automatically map the custom installer binary directory to the global system PATH
ENV PATH="/root/.opencode/bin:${PATH}"

# Keep the container running in the background so you or your scripts can execute commands
CMD ["tail", "-f", "/dev/null"]

docker-compose.yml

services:
  opencode-sandbox:
    build: .
    container_name: opencode_python_sandbox
    # Vital flags for interactive command line interfaces (TUI)
    stdin_open: true
    tty: true
    # Mount ONLY the current directory into the container's /app folder
    volumes:
      - .:/app
    # Pass necessary OpenCode and LLM API environment variables from host to container
    environment:
      - OPENCODE_API_KEY
      - OPENCODE_MODEL
      - ANTHROPIC_API_KEY
      - OPENAI_API_KEY
    # Keeps network completely open for external API calls/installations
    network_mode: bridge
    # web ui ports
    ports:
    - "4096:4096"

and opencode.json (make edits where needed)

{
  "$schema": "https://opencode.ai/config.json",
  "disabled_providers": [
    "github-copilot",
    "anthropic",
    "openai"
  ],
  "enabled_providers": [
    "opencode",
    "opencode-go"
  ],
  "model": "opencode/space-bunny-free",
  "small_model": "opencode/space-bunny-free"
}

Steps:

Set your ai key on the host env

export OPENCODE_API_KEY="your-opencode-key"

Build and run the container
```
docker compose up -d
```

Run opencode

docker compose exec -it opencode-sandbox opencode

Rating 6/10 – Simple for simple tasks, more complex when needing skills and plugins for the agent, multiple services and more dependencies. Requires work and a unique set up.