OpenSandbox - Alibaba's open-source general-purpose AI application sandbox platform

What is OpenSandbox?

OpenSandbox is an open-source, general-purpose AI application sandbox platform from Alibaba, licensed under the Apache 2.0 license. It is specifically designed for secure execution of AI-generated code and automated tasks. It provides multi-language SDKs (Python, Java/Kotlin, JavaScript/TypeScript) and a unified sandbox API, with built-in Docker and Kubernetes runtime support, enabling rapid deployment of various isolated execution environments such as code interpreters, browser automation, and desktop environments (VNC/VS Code). OpenSandbox primarily addresses the security isolation issue when AI agents (such as Claude Code and Gemini CLI) execute arbitrary code. Through fine-grained network policy control and resource isolation, it allows developers to securely run LLM-generated code, third-party plugins, or automation scripts in a controlled environment, while maintaining context persistence and efficient task scheduling capabilities.

Main functions of OpenSandbox

• Multi-language SDK supportIt provides client SDKs in three languages: Python, Java/Kotlin, and JavaScript/TypeScript, and adopts a unified API design to facilitate developers to quickly integrate it into various AI applications.
• code interpreterIt features a built-in Code Interpreter function, supports secure execution of code in multiple languages such as Python and JavaScript, and has persistent context capabilities, allowing for the continuous execution of multiple code segments while preserving their state.
• Browser automationSupports automation scenarios in mainstream browsers such as Chrome and Playwright, and is suitable for tasks such as web page data collection, automated testing, and RPA.
• Desktop Environment SandboxIt provides VNC remote desktop and VS Code online development environment, supporting the isolated execution of GUI applications and complex interactive tasks.
• Network policy controlA unified entry gateway enables multiple routing policies, supports fine-grained control of outbound traffic at the sandbox level, and ensures network security for the execution environment.
• Multi-runtime supportIt has built-in Docker and Kubernetes runtimes, which support both quick local startup of a single sandbox and large-scale distributed sandbox cluster scheduling.
• MCP Protocol Integration:supply opensandbox-mcp-serverIt supports calling sandbox capabilities via Model Context Protocol and can be seamlessly integrated into AI tools such as Cursor and Claude Desktop.
• Resource isolation and restrictionsIt supports the isolation and quota limits of resources such as CPU, memory, disk, and network to prevent malicious or abnormal code from affecting the host machine.
• Unified Sandbox APIIt provides a standardized sandbox lifecycle management interface, including operations such as creation, execution, monitoring, and destruction, simplifying the cost of adapting to multiple environments.

OpenSandbox Technical Principles

• Containerization isolationLightweight sandbox containers are built based on Docker and Kubernetes, and process, network, and file system isolation is achieved based on Linux namespaces and Cgroups, ensuring that AI-generated code runs in a restricted environment.
• Unified Sandbox RuntimeDesign an abstract runtime interface layer that supports local Docker single-node operation and distributed scheduling in Kubernetes clusters, shielding underlying differences through a unified API.
• Ingress Gateway ArchitectureIt adopts a unified ingress gateway to handle all sandbox traffic, supports multiple routing policy configurations, and realizes network egress control and traffic auditing at the sandbox granularity.
• Multi-language SDK wrapperIt encapsulates underlying sandbox capabilities through gRPC/HTTP protocols, providing idiomatic client SDKs for Python, Java/Kotlin, and JavaScript/TypeScript, thus lowering the integration threshold.
• Persistence Context MechanismThe code interpreter maintains the code execution state and environment variables by mounting persistent storage volumes, supporting continuous code execution in multi-turn conversations.
• Resource quota managementIt integrates Kubernetes ResourceQuota and LimitRange to hard limit the CPU, memory, disk, and network bandwidth of the sandbox, preventing resource exhaustion attacks.
• Security Policy EngineBuilt-in Linux security modules such as Seccomp and AppArmor restrict system call permissions for processes within the sandbox, minimizing the attack surface.
• MCP Protocol AdaptationImplement the Model Context Protocol server to expose sandbox capabilities as standardized tool interfaces, enabling LLM to call functions such as code execution and browser operations through structured protocols.
• Image layered constructionIt adopts a layered image design, with the base image providing the runtime environment and the application image stacking business dependencies, supporting fast startup and elastic scaling.

OpenSandbox project address

• Github repositoryhttps://github.com/alibaba/OpenSandbox

Application scenarios of OpenSandbox

• AI Programming AssistantIt provides a secure code execution environment for AI programming tools such as Claude Code, GitHub Copilot, and Cursor, and verifies the correctness of the code logic generated by LLM in real time.
• Agent Evaluation and BenchmarkingProvides a standardized, isolated evaluation environment for AI agents, supporting the secure and automated execution of benchmark tests such as SWE-bench and WebArena.
• Browser Automation AgentIt supports GUI agents such as WebAgent and Operator to perform automated tasks such as web browsing, form filling, and data scraping in an isolated sandbox.
• Third-party plugin executionIt enables secure operation of untrusted third-party code or plugins, preventing malicious code from accessing host system resources. It is suitable for plugin marketplaces and code hosting platforms.
• Reinforcement learning trainingProvides an isolated computing environment for RL training, supporting secure distributed training tasks using frameworks such as OpenAI Gym and Gymnasium.
• Online Education and Code EvaluationIt provides a secure code execution environment for programming education platforms, supports automatic evaluation and real-time feedback of student code, and prevents malicious code from damaging the system.