AI Tool

Docker Sandboxes Review

Docker Sandboxes provides isolated environments for coding AI agents, leveraging microVMs to offer hardware-level isolation for untrusted code execution.

shipped Sep 17, 2026codefreemium

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code

Why it matters

1Utilizes microVMs for hardware-level isolation, providing a strong security boundary for untrusted code.

2Supports secure execution of AI coding agents like Claude Code, Codex CLI, and Gemini CLI.

3Offers network and filesystem policy enforcement, along with secure credential handling via host keychain integration.

4Allows 'Docker-in-Docker' functionality within sandboxes, enabling agents to build and run containers in isolation.

Specs

API Docs

View Documentation →

API Available

Yes, public API

overview

What is Docker Sandboxes?

Docker Sandboxes is an AI tool developed by Docker that enables developers and teams to run AI coding agents and other untrusted code in secure, isolated environments. It leverages microVMs to provide hardware-level isolation for untrusted code execution, ensuring that autonomous agents can perform tasks like installing packages, running services, and modifying files without compromising the host machine or sensitive data. This platform is designed to package applications and their dependencies into containers for consistent execution, integrating with systems that prioritize strong isolation.

features

Key Features of Docker Sandboxes

Docker Sandboxes offers a suite of features designed to provide robust security and control for running AI agents and untrusted code. These capabilities ensure strong isolation, policy enforcement, and secure operations within development workflows.

MicroVM-based hardware-level isolation for every agent session, providing a dedicated Linux kernel.
Secure execution for AI coding agents, including support for Claude Code, Codex CLI, and Gemini CLI.
Network isolation with configurable allow and deny lists, enforced at runtime.
Filesystem lockdown and policy enforcement to prevent unauthorized data access or exfiltration.
Secure credential handling, injecting credentials into outbound network requests from the host keychain without exposing values inside the sandbox.
Ability for agents to build and run Docker containers within the sandbox, isolated from the host's Docker daemon.
Identity-bound audit logs for enhanced traceability and compliance.
OCI-compliant and platform-independent container image creation and deployment.

use cases

Who Should Use Docker Sandboxes?

Docker Sandboxes is primarily designed for developers, teams, and enterprises that require secure and isolated environments for running AI agents and other untrusted code. Its robust security features make it suitable for scenarios where host machine integrity and data protection are paramount.

AI Developers: For safely running AI coding agents (e.g., Claude Code, Copilot CLI) that perform autonomous tasks like package installation, service execution, and file modification.
Experimentation and Development Teams: For developers who need to experiment with untrusted code, install various packages, run databases, or compile code without risking their host system.
Enterprises with Strict Security Requirements: For organizations prioritizing strong isolation, control, and compliance features for their AI agent runtimes and development workflows.
Teams Prioritizing Data Security: For scenarios requiring secure credential handling and policy enforcement to prevent data leakage or unauthorized network connections.

how to use

How to Use Docker Sandboxes

To use Docker Sandboxes, developers typically interact with the sbx command-line interface to create, manage, and run isolated environments. A Docker runtime is required on the target machine for deployment.

1Install Docker Desktop (which includes Docker Sandboxes) on macOS or Windows.
2Utilize the sbx create command to provision a new sandbox environment, optionally specifying a 'kit' for pre-configured tools.
3Run AI agents or untrusted code within the created sandbox using sbx run.
4Define network and filesystem policies for the sandbox to control its access and behavior.
5Manage sandbox lifecycle with commands like sbx daemon restart and sbx prune for cleanup.
6Integrate with AI agent platforms like NanoClaw for secure, agentic workflows.

pricing

Docker Sandboxes Pricing & Plans

Docker Sandboxes is available through Docker's freemium model, offering various tiers that cater to individual developers and large enterprises. The pricing structure provides access to essential tools and scales up to include advanced security, control, and compliance features.

Docker Personal: $0 – Provides essential tools for building and deploying containers, suitable for individual developers.
Docker Pro: $11 per user/month – Offers advanced features and additional resources for professional developers.
Docker Team: $16 per user/month – Includes collaborative tools designed for small teams.
Docker Business: $24 per user/month – Delivers robust security, control, and compliance features for enterprise-level requirements.

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Pros

+Provides strong hardware-level isolation using microVMs, significantly enhancing security for untrusted code execution.
+Enables AI coding agents to operate autonomously without compromising the host machine or sensitive data.
+Offers robust security features including network isolation, filesystem lockdown, and secure credential handling.
+Supports 'Docker-in-Docker' functionality within sandboxes, allowing agents to build and run containers in isolation.
+Features identity-bound audit logs and policy enforcement, aiding in compliance and control.
+Continuously updated with new features like microVM-based isolation for macOS/Windows and improved CLI commands.

Cons

−Some users desire more generalization beyond AI agents, wishing for compatibility with arbitrary docker-compose files or orchestration images.
−Base images for sandboxes can be large (e.g., ~1.5GB for claude-code), potentially including unnecessary tools for specific use cases.
−The current implementation can feel tightly coupled to a hardcoded list of AI agents, limiting flexibility for broader development tasks.
−Performance on macOS, particularly regarding host file system access, has been a general concern for some Docker users, though microVMs aim to mitigate this for sandboxes.

Policies

Pricing Page

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Similar Tools

Docker Sandboxes vs Competitors

Docker Sandboxes differentiates itself in the secure execution landscape by providing an integrated platform specifically tailored for AI agent development, leveraging microVMs for hardware-level isolation. While other tools offer components of secure execution, Docker Sandboxes aims for a more complete, out-of-the-box solution.

Firecracker↗

It's a lightweight virtual machine monitor (VMM) specifically designed for serverless workloads, providing minimal overhead and fast startup times for microVMs.

Firecracker provides the underlying microVM technology for hardware-level isolation, which is a core component of Docker Sandboxes. However, it is a lower-level building block that requires more manual setup and integration to create a complete development environment compared to Docker Sandboxes' more integrated platform.

gVisor↗

It's an application kernel that intercepts system calls from containerized applications and handles them in userspace, providing a stronger isolation boundary than traditional containers.

gVisor offers enhanced security for existing container runtimes by operating as an application kernel, providing a different layer of isolation compared to Docker Sandboxes' focus on hardware-level microVMs. While both aim for secure execution, gVisor integrates with standard container workflows to harden them, rather than providing a microVM-based runtime directly.

Kata Containers↗

It combines the speed and manageability of containers with the security advantages of virtual machines, running containers inside lightweight virtual machines.

Kata Containers directly addresses the need for running containers with VM-level isolation, similar to the microVM approach of Docker Sandboxes. However, Kata provides the container runtime and requires integration into your existing container orchestration or development workflow, whereas Docker Sandboxes aims to offer a more complete, integrated platform for AI agent development.

Podman↗

It's a daemonless container engine that allows users to run and manage OCI containers and pods, offering a Docker-compatible command-line interface.

Podman serves as a direct, daemonless alternative to Docker for managing containers, which is a fundamental part of Docker Sandboxes' functionality. While Podman itself doesn't inherently provide microVM-level isolation, it can be configured to use secure runtimes like Kata Containers or gVisor for enhanced security, requiring additional setup compared to Docker Sandboxes' integrated isolation.

See every Docker Sandboxes alternative, compared→