How to use this image

All examples in this guide use the public image. If you've mirrored the repository for your own use (for example, to your Docker Hub namespace), update your commands to reference the mirrored image instead of the public one.

For example:

• Public image: dhi.io/sbx-templates:<tag>
• Mirrored image: <your-namespace>/dhi-sbx-templates:<tag>

For the examples, you must first use docker login dhi.io to authenticate to the registry to pull the images.

These images are the agent templates used by Docker Sandboxes to run AI coding agents inside isolated containers. Each agent is published as a separate tag of the single sbx-templates repository (for example claude-code, codex, or shell). They are meant to be launched by the sbx CLI (docker sandbox), which pulls the right tag, mounts your workspace, and runs the agent for you—you normally do not start them with a bare docker run.

What's included in this image

Every sbx-templates tag builds on a common base that includes:

• docker — Docker CLI for container management
• git — version control
• gh — GitHub CLI for repository management
• uv — fast Python package installer and resolver

Full-tier tags additionally bundle language toolchains (Go, Node.js, Python, and a JDK) along with common shell utilities. All tags run as the nonroot agent user, use /home/agent/workspace as the working directory, and use tini as the entrypoint so agents launched with docker exec are reaped correctly.

Run agents with the sbx CLI

These images are launched by Docker Sandboxes, not started by hand. Install the sbx CLI plugin (invoked as docker sandbox, or as the standalone sbx binary), then let it create the sandbox, pull the correct tag, mount your workspace, and run the agent.

Enable the hardened (DHI) templates

By default the sbx CLI pulls the standard docker/sandbox-templates images. Point it at the hardened dhi.io/sbx-templates equivalents by turning on the platform.images.useDHI setting:

docker sandbox settings set platform.images.useDHI true

Or enable it for a single shell session with an environment variable:

export DOCKER_SANDBOXES_USE_DHI=1

With the toggle on, sbx swaps docker/sandbox-templates:<tag> for dhi.io/sbx-templates:<tag> (same tag) when it resolves an agent's default template image. The daemon pulls the image the first time you run the agent; authenticate to the registry with docker login dhi.io if the pull requires it.

Run an agent

Create and run a sandbox for an agent in a workspace directory:

docker sandbox run claude /path/to/workspace

Run the same command again to reuse the existing sandbox, so your session and files persist. To open a plain sandbox with no preinstalled agent, use the shell agent:

docker sandbox run shell /path/to/workspace

Agent-to-tag mapping

Each sbx agent resolves to a tag of this repository. The CLI selects the Docker-in-Docker (-docker) variant by default so the agent can build and run containers inside its sandbox:

Non--docker tags (for example claude-code or shell) provide the same environment without the bundled Docker Engine, and a -minimal tag (for example claude-code-minimal) omits the bundled language toolchains for a smaller image.

Extend an agent with kits

Agents can be composed with additional kits at run time using --kit (a local directory or a packaged kit):

docker sandbox run claude --kit ./my-extension/ /path/to/workspace

Image variants

Docker Hardened Images come in different variants depending on their intended use. Image variants are identified by their tag.

• Runtime variants are designed to run your application in production. These images are intended to be used either directly or as the FROM image in the final stage of a multi-stage build. These images typically:

  • Run as a nonroot user
  • Do not include a shell or a package manager
  • Contain only the minimal set of libraries needed to run the app

• Build-time variants typically include dev in the tag name and are intended for use in the first stage of a multi-stage Dockerfile. These images typically:

  • Run as the root user
  • Include a shell and package manager
  • Are used to build or compile applications

To view the image variants and get more information about them, select the Tags tab for this repository, and then select a tag.

Migrate to a Docker Hardened Image

To migrate your application to a Docker Hardened Image, you must update your Dockerfile. At minimum, you must update the base image in your existing Dockerfile to a Docker Hardened Image. This and a few other common changes are listed in the following table of migration notes.

The following steps outline the general migration process.

1. Find hardened images for your app.

   A hardened image may have several variants. Inspect the image tags and find the image variant that meets your needs.

2. Update the base image in your Dockerfile.

   Update the base image in your application's Dockerfile to the hardened image you found in the previous step. For framework images, this is typically going to be an image tagged as dev because it has the tools needed to install packages and dependencies.

3. For multi-stage Dockerfiles, update the runtime image in your Dockerfile.

   To ensure that your final image is as minimal as possible, you should use a multi-stage build. All stages in your Dockerfile should use a hardened image. While intermediary stages will typically use images tagged as dev, your final runtime stage should use a non-dev image variant.

4. Install additional packages

   Docker Hardened Images contain minimal packages in order to reduce the potential attack surface. You may need to install additional packages in your Dockerfile. Inspect the image variants to identify which packages are already installed.

   Only images tagged as dev typically have package managers. You should use a multi-stage Dockerfile to install the packages. Install the packages in the build stage that uses a dev image. Then, if needed, copy any necessary artifacts to the runtime stage that uses a non-dev image.

   For Alpine-based images, you can use apk to install packages. For Debian-based images, you can use apt-get to install packages.

Troubleshooting migration

The following are common issues that you may encounter during migration.

General debugging

The hardened images intended for runtime don't contain a shell nor any tools for debugging. The recommended method for debugging applications built with Docker Hardened Images is to use Docker Debug⁠ to attach to these containers. Docker Debug provides a shell, common debugging tools, and lets you install other tools in an ephemeral, writable layer that only exists during the debugging session.

Permissions

By default image variants intended for runtime, run as the nonroot user. Ensure that necessary files and directories are accessible to the nonroot user. You may need to copy files to different directories or change permissions so your application running as the nonroot user can access them.

Privileged ports

Non-dev hardened images run as a nonroot user by default. As a result, applications in these images can't bind to privileged ports (below 1024) when running in Kubernetes or in Docker Engine versions older than 20.10. To avoid issues, configure your application to listen on port 1025 or higher inside the container, even if you map it to a lower port on the host. For example, docker run -p 80:8080 my-image will work because the port inside the container is 8080, and docker run -p 80:81 my-image won't work because the port inside the container is 81.

No shell

By default, image variants intended for runtime don't contain a shell. Use dev images in build stages to run shell commands and then copy any necessary artifacts into the runtime stage. In addition, use Docker Debug to debug containers with no shell.

Entry point

Docker Hardened Images may have different entry points than images such as Docker Official Images. Use docker inspect to inspect entry points for Docker Hardened Images and update your Dockerfile if necessary.