This document provides a comprehensive, curated list and analysis of modern code sandboxing solutions. It is designed to help developers, architects, and engineering leaders navigate the complex landscape of secure code execution, from foundational technologies to full-fledged platforms.
- 1. Why Secure Code Execution Matters Now
- 2. Sandboxing Technologies
- 3. Feature Matrix: At-a-Glance Comparison
- 4. In-Depth Platform Profiles
- 4.1. e2b: The AI Agent Sandbox Runtime
- 4.2. Daytona: Secure & Elastic Infrastructure for AI Code
- 4.3. microsandbox: Self-Hosted MicroVMs for Untrusted Code
- 4.4. WebContainers: Browser-Native Development Runtime
- 4.5. Replit: Collaborative Browser-Based Development
- 4.6. Cloudflare Workers: Edge Computing with V8 Isolates
- 4.7. Fly.io: Modern Application Hosting with MicroVMs
- 4.8. Kata Containers: Secure Container Runtime
- 4.9. YepCode: Enterprise Automation with AI Code Execution
- 4.10. Other Notable Platforms & Cloud Development Environments (CDEs)
- 6. Docker vs MicroVM for Sandboxing
- 7. Choosing Your Sandbox: A Decision Framework
- 8. Contributing
Code sandboxing has moved from a niche security tool to essential infrastructure for modern applications. Originally, sandboxing was mainly used by security teams to safely analyze suspicious files without risking production systems. While this remains important, two major trends have made sandboxing essential for product development.
AI and LLM Applications: Large Language Models now generate code that needs to run safely. AI agents, data analysis tools, and UI frameworks must execute untrusted, dynamically generated code. This requires secure runtime environments. For example, Hugging Face uses e2b's sandboxing for reinforcement learning pipelines, and Groq uses e2b for Compound AI systems that combine LLMs with live code execution.
User-Programmable Platforms: Many SaaS applications, data tools, and developer platforms now let users submit their own code through plugins, custom scripts, or data transformations. This requires secure isolation to prevent security vulnerabilities. The same need exists for Cloud Development Environments (CDEs) and online IDEs like GitHub Codespaces, Gitpod, and Coder, which must isolate each user's environment from the host infrastructure and other users.
Sandboxing has changed from a security-only tool to a platform feature that enables new capabilities. The focus has shifted from just preventing attacks to safely enabling powerful functionality. This means sandboxes must be fast, reliable, and easy to use - not just secure. Modern solutions are judged by their SDKs, execution speed, and integration ease, because sandboxes are now part of core product functionality.
Different sandboxing technologies make different trade-offs between three key factors: Security Isolation, Performance & Startup Speed, and Compatibility (how closely the sandbox behaves like a real machine). No approach is perfect - each makes different compromises.
The following table provides a comparative overview of the core sandboxing technologies, highlighting their key characteristics and trade-offs:
| Technology | Isolation Level | Startup Time | Resource Overhead | Hardware Requirements | Compatibility | Primary Use Cases |
|---|---|---|---|---|---|---|
| Firecracker ↓ | Hardware-Level | ~125ms | Low (5MB per VM) | KVM/Hardware Virtualization | Full Linux | Serverless, AI agents, ephemeral workloads |
| libkrun ↓ | Hardware-Level | ~Container-speed | Low | KVM/Hardware Virtualization | Full Linux | Embedded sandboxing, self-hosted platforms |
| gVisor ↓ | Application Kernel | ~100ms | Medium | Any Linux host | High (Linux API subset) | Multi-tenant containers, cloud services |
| nsjail ↓ | Process-Level | ~50ms | Very Low | Any Linux host | High (filtered syscalls) | Code execution, long-running processes |
| Docker/OCI ↓ | Namespace-Level | ~10-50ms | Very Low | Any Linux host | Full Linux | Development, CI/CD, application deployment |
| WebAssembly ↓ | Runtime-Level | ~10ms | Very Low | Any platform | Limited (WASM modules) | Edge computing, plugin systems |
| V8 Isolates ↓ | Runtime-Level | ~1ms | Very Low | Any platform | JavaScript only | Edge functions, serverless JavaScript |
- Isolation Level: The strength of security boundaries between sandboxed processes
- Startup Time: Time to initialize and start executing code in the sandbox
- Resource Overhead: Memory and CPU overhead per sandbox instance
- Hardware Requirements: Dependencies on specific hardware or virtualization features
- Compatibility: How closely the sandbox environment matches a full operating system
- Primary Use Cases: Most common scenarios where each technology excels
MicroVMs provide the strongest security isolation. They use hardware virtualization to give each sandbox its own kernel, memory space, and virtual devices. This creates a hardware-enforced boundary between guest code and the host operating system, avoiding the shared kernel vulnerabilities of containers. The key innovation is dramatically faster boot times, making VMs practical for short-lived workloads.
- GitHub: firecracker-microvm/firecracker
- Website: firecracker-microvm.github.io
Developed and open-sourced by Amazon Web Services (AWS), Firecracker is a virtual machine monitor (VMM) that uses the Linux Kernel Virtual Machine (KVM) to create and manage lightweight microVMs. Its design philosophy is minimalist. It intentionally excludes all non-essential devices like USB controllers, graphics cards, and sound cards, which drastically reduces the potential attack surface and lowers the memory overhead of each microVM to less than 5 MiB.
- Mechanism: Firecracker runs as a user-space process on a host machine and is controlled via a RESTful API. This API allows for the programmatic configuration of the microVM, including setting the number of vCPUs, memory size, and attaching network interfaces or block devices. This API-driven approach is crucial for automating the lifecycle of sandboxes in cloud-native applications.
- Performance: Firecracker's defining feature is its startup speed. It can launch a microVM and initiate user-space code in as little as 125 milliseconds, with a creation rate of up to 150 microVMs per second on a single host. This performance bridges the gap between the slow boot times of traditional VMs (often 10+ seconds) and the fast startup of containers, making it suitable for high-throughput, on-demand workloads like serverless functions. This capability is what enables services like AWS Lambda and AWS Fargate to provide isolated execution environments at scale.
- Security Model: For defense-in-depth, Firecracker employs a companion "jailer" process. The jailer sets up a secure environment using Linux cgroups and namespaces to isolate the Firecracker VMM process itself before dropping its privileges. This provides a second layer of containment in the unlikely event that the virtualization barrier is compromised.
- Adoption: This technology is the foundation for many major platforms:
- e2b ↓ - leverages Firecracker for secure, fast-starting sandboxes for AI agents
- Fly.io ↓ - uses Firecracker microVMs for modern application hosting
- YepCode ↓ - uses Firecracker microVMs for enterprise-grade code execution and automation
- AWS Lambda - Amazon's serverless computing service runs on Firecracker
- AWS Fargate - Amazon's container hosting service uses Firecracker for isolation
- GitHub: containers/libkrun
- Website: github.com/containers/libkrun/wiki
Similar to Firecracker, libkrun is a library-based virtualization solution designed to create lightweight, KVM-based virtual machines with minimal overhead. It is the core technology powering microsandbox. By providing virtualization as a library, it allows applications to embed high-security sandboxing directly, achieving genuine hardware-level isolation with its own kernel and memory space, while maintaining startup times competitive with containers.
- Adoption: This technology is primarily used by:
- microsandbox ↓ - uses libkrun as its core virtualization technology for self-hosted sandboxing
- Podman - Red Hat's rootless container engine can use libkrun for VM-level isolation while maintaining container compatibility
- crun - OCI runtime that can use libkrun for enhanced security
The emergence of microVM technologies like Firecracker and libkrun has rendered the old dichotomy of "slow, secure VMs versus fast, insecure containers" largely obsolete. They offer a compelling "best of both worlds" approach that has become the new standard for high-security, ephemeral code execution.
This approach offers an intermediate level of isolation between microVMs and standard containers. Instead of running a full guest kernel, an "application kernel" runs in user-space and intercepts all system calls made by the sandboxed process. It fulfills these requests itself, making only a limited and carefully vetted set of its own system calls to the true host kernel.
- GitHub: google/gvisor
- Website: gvisor.dev
Developed and used extensively by Google, gVisor is an open-source application kernel written in the memory-safe language Go.
- Mechanism: When an application inside a gVisor sandbox attempts to perform an operation like opening a file or sending a network packet, it issues a standard Linux system call. gVisor intercepts this call before it reaches the host kernel. gVisor's user-space kernel then processes the request according to its own implementation of the Linux API. This architecture dramatically reduces the host kernel's attack surface, as the sandboxed application can no longer directly exploit vulnerabilities in the host's syscall interface.
- Advantages: gVisor provides significantly stronger isolation than standard containers and has the major advantage of not requiring hardware virtualization support, meaning it can run on any Linux host, whether bare-metal or a VM. It is used in production to secure Google services like Cloud Run, App Engine, and Cloud Functions. It also offers advanced features like the ability to checkpoint and restore a running container's state.
- Disadvantages: This interception layer can introduce performance overhead compared to running directly on the host kernel. Furthermore, because gVisor re-implements the Linux API, there can be compatibility issues if an application uses obscure or newly introduced syscalls that gVisor does not yet support.
- Adoption: This technology is used by:
- Google Cloud Run - Google's serverless container platform uses gVisor for isolation
- Google App Engine - Google's platform-as-a-service uses gVisor for security
- Google Cloud Functions - Google's serverless functions use gVisor
- Kata Containers - can optionally use gVisor as a runtime
- Various Kubernetes clusters for enhanced container security
- GitHub: google/nsjail
- Website: github.com/google/nsjail
nsjail is a process isolation tool that leverages Linux namespaces and seccomp-bpf filters to create secure sandboxed environments. Originally developed by Google and used in production environments, it provides a lightweight alternative to full virtualization when strong isolation is needed.
- Mechanism: nsjail creates isolated environments by combining multiple Linux security features: namespaces (PID, mount, network, user), seccomp-bpf system call filtering, and resource limits via cgroups. Unlike gVisor's approach of reimplementing syscalls, nsjail uses kernel-level filtering and namespace isolation to restrict what the sandboxed process can access.
- Advantages: Extremely lightweight with minimal overhead compared to VMs or application kernels. Provides fine-grained control over system resources, file access, and network capabilities. Well-suited for scenarios where you need to run potentially untrusted code with specific resource constraints. Used successfully in production by platforms like Windmill for sandboxing Python and TypeScript execution.
- Use Cases: Particularly effective for long-running processes that need computational isolation without the overhead of full virtualization. According to community discussions, it's recommended for scenarios involving WebSocket data processing and light computational tasks where container-level isolation might be insufficient but VM overhead is undesirable.
- Configuration: Supports extensive configuration options for runtime restrictions, including CPU limits, memory constraints, filesystem access controls, and network isolation policies. Can be integrated into worker processes via languages like Rust for programmatic control.
- Adoption: This technology is used by:
- Windmill - uses nsjail for sandboxing Python and TypeScript execution
- Google - uses nsjail internally for various sandboxing needs
- Security research - widely used in malware analysis and security research
- CTF platforms - used by competitive programming and security challenge platforms
This is the most lightweight form of sandboxing, where isolation is enforced by the language runtime itself rather than the operating system or hardware. This approach offers the fastest startup times and lowest resource overhead but is the most restrictive in terms of compatibility.
- GitHub: WebAssembly/spec
- Website: webassembly.org
WebAssembly is a binary instruction format designed as a portable compilation target for a stack-based virtual machine. Its security model is built on two fundamental principles:
- Memory Safety: WASM code executes in a linear memory space that is completely isolated from the host process's memory. Every memory access is automatically bounds-checked by the runtime, preventing buffer overflows from affecting the host or other WASM modules. The call stack is also managed by the runtime and is inaccessible to the WASM code, which neutralizes traditional stack-smashing attacks.
- Capability-Based Security: A WASM module is inert by default. It has no intrinsic ability to access the file system, network, or any other external resource. To perform any I/O, the host environment must explicitly provide these capabilities by passing in functions (known as "imports") during instantiation. This "default-deny" posture ensures that a module can only do what it has been explicitly permitted to do.
- Adoption: This technology is used across many platforms:
- WebContainers ↓ - uses WASM for browser-based Node.js runtime
- Shopify Scripts - uses WASM for safe execution of custom scripts
- Fastly Compute@Edge - uses WASM for edge computing
- Wasmtime - server-side WASM runtime
- Docker+WASM - Docker Desktop now supports WASM containers
- Kubernetes - supports WASM workloads through various runtimes
V8 Isolates are a core feature of Google's V8 JavaScript engine. An Isolate represents a completely independent instance of the V8 engine, with its own memory heap, garbage collector, and execution state.
- Mechanism: When multiple scripts run in different V8 Isolates within the same process (e.g., multiple tabs in a web browser), their objects, variables, and code are completely separate. One isolate cannot directly access the memory or state of another. This is the fundamental technology that enables platforms like Cloudflare Workers and Deno Deploy to securely run code from thousands of different customers on the same physical servers with extremely low overhead.
- Language-Specific Limitations: While V8 Isolates excel at JavaScript execution, they are not well-suited for Python workloads. The V8 engine is specifically designed and optimized for JavaScript's execution model, memory management, and runtime characteristics. Python applications require different runtime environments and cannot benefit from V8's isolation technology. For Python sandboxing, alternative approaches like nsjail, gVisor, or microVMs are more appropriate choices.
- The V8 Sandbox: It is important to distinguish V8 Isolates from the newer V8 Sandbox. The V8 Sandbox is a further defense-in-depth measure that operates within an isolate. It reserves a large region of virtual address space and ensures that all V8 heap pointers are confined to that space. This is designed to mitigate the impact of potential vulnerabilities within the V8 engine itself, preventing an exploit from achieving arbitrary memory read/write capabilities outside the sandboxed region. This demonstrates a multi-layered approach to security, even within the runtime.
- Adoption: This technology powers major edge computing platforms:
- Cloudflare Workers ↓ - uses V8 Isolates for edge computing
- Deno Deploy - uses V8 Isolates for serverless JavaScript
- Shopify Scripts - uses V8 Isolates for safe script execution
- Chrome Browser - uses V8 Isolates for tab isolation
- Node.js Worker Threads - uses V8 Isolates for thread isolation
- Vercel Edge Runtime - uses V8 Isolates for edge functions
Containerization represents the most widely adopted approach to application isolation, using Linux namespaces and control groups (cgroups) to create isolated environments that share the host kernel. While not providing the strongest security boundaries, containers offer an excellent balance of compatibility, performance, and operational simplicity.
- GitHub: docker/docker, opencontainers
- Website: docker.com, opencontainers.org
Docker and the broader Open Container Initiative (OCI) ecosystem represent the de facto standard for containerization. Containers package applications with their dependencies while providing process-level isolation through kernel features.
- Mechanism: Containers use multiple Linux kernel features for isolation: namespaces (PID, mount, network, user, UTS, IPC) separate process trees, filesystems, and network stacks; cgroups limit and monitor resource usage (CPU, memory, I/O); and security modules like AppArmor or SELinux provide additional access controls. Unlike VMs, containers share the host kernel, making them lightweight but potentially less secure.
- Advantages: Extremely fast startup times (10-50ms), minimal resource overhead, extensive ecosystem of tools and images, excellent compatibility with existing applications, and mature orchestration platforms like Kubernetes. The shared kernel model enables efficient resource utilization and makes containers ideal for microservices architectures.
- Security Considerations: The shared kernel creates potential attack vectors, as demonstrated by container escape vulnerabilities. However, most security incidents (69% according to industry reports) result from misconfigurations rather than kernel exploits. Proper configuration, avoiding privileged containers, and using minimal base images significantly reduce risks. As noted in security discussions, "the Linux kernel has far too large of an attack surface to be trusted as a hard security boundary" - this is why platforms running hostile code prefer microVMs or specialized runtimes.
- Rootless vs Root-based Runtimes: Container security varies significantly between implementations:
- Podman - Rootless by design, no daemon, better user namespace support, fork/exec model provides stronger isolation
- Docker - Default daemon runs as root, creating privileged attack surface; Docker socket access equals root access
- For hostile code: Rootless runtimes like Podman offer significantly better security than daemon-based Docker setups
- Use Cases: Ideal for trusted application deployment, development environments, CI/CD pipelines, and microservices architectures. Less suitable for running untrusted code from external sources or scenarios requiring the strongest security isolation.
- Enhanced Security Options: Technologies like gVisor provide additional security layers for containers, while Kata Containers offer VM-level isolation with container compatibility.
- Adoption: This technology is ubiquitous across the industry:
- Daytona ↓ - uses containers for development environments
- Replit ↓ - uses containers for coding environments
- Gitpod ↓ - uses containers for development workspaces
- Coder ↓ - uses containers for development environments
- Kubernetes - the foundation of modern container orchestration
- Docker Hub - the largest container registry with billions of downloads
The following table provides a high-level, comparative overview of the leading code sandboxing solutions, allowing for a quick assessment of their core attributes and positioning.
| Solution | Primary Technology | Launch Date | GitHub Stars | License | Self-Hosted | SaaS Available | Filesystem Access | Network Access | Workload Suitability |
|---|---|---|---|---|---|---|---|---|---|
| e2b ↓ | Firecracker (MicroVM) | Nov 2023 | 8.9k+ | Apache-2.0 | Yes | Yes | Persistent | Full | Short & Long-Running |
| Daytona ↓ | Containers (OCI/Docker) | 2023 | 21k+ | AGPL-3.0 | Yes | Yes | Persistent, Archivable | Full | Long-Running & Stateful |
| microsandbox ↓ | libkrun (MicroVM) | May 2025 | 3.3k+ | Apache-2.0 | Yes (Primary) | No | Persistent & Ephemeral | Full | Short & Long-Running |
| WebContainers ↓ | Browser-based Node.js/Wasm | 2021 | N/A | Proprietary | No | Yes | Ephemeral | Browser-limited | Short & Medium-Running |
| Replit ↓ | Containers/VMs | 2016 | N/A | Proprietary | No | Yes | Persistent | Full | Short & Long-Running |
| Cloudflare Workers ↓ | V8 Isolates | 2017 | N/A | Proprietary | No | Yes | Ephemeral | Edge-limited | Short-Running |
| Fly.io ↓ | MicroVMs (Firecracker) | 2017 | N/A | Proprietary | No | Yes | Persistent | Full | Short & Long-Running |
| Kata Containers ↓ | MicroVM Containers | 2017 | 5.2k+ | Apache-2.0 | Yes | No | Persistent | Full | Long-Running & Stateful |
| YepCode ↓ | Firecracker (MicroVM) | 2021 | N/A | Proprietary | Yes | Yes | Persistent | Full | Short & Long-Running |
| CodeSandbox ↓ | MicroVM & Browser | 2017 | 13.4k+ | Proprietary / OSS Parts | No | Yes | Persistent | Full | Short & Long-Running |
| Gitpod ↓ | Containers | 2020 | 12.9k+ | AGPL-3.0 | Yes | Yes | Persistent | Full | Long-Running & Stateful |
| Coder ↓ | Containers / VMs | 2019 | 8.1k+ | AGPL-3.0 | Yes | Yes | Persistent | Full | Long-Running & Stateful |
This section provides a detailed, structured analysis of each major platform, expanding on the data presented in the feature matrix.
- Overview: e2b is an open-source, secure cloud runtime explicitly engineered for the needs of AI applications and autonomous agents. It provides developers with sandboxed cloud environments powered by Firecracker microVMs, enabling the safe execution of AI-generated code. The platform is heavily focused on providing a seamless developer experience through its SDKs and is designed to be the backend infrastructure for agentic workflows.
- GitHub: e2b-dev/E2B
- Website: e2b.dev
- Launch Date: The "Custom Sandboxes" feature, a core part of its offering, was launched on November 7, 2023. The project has been active for longer, with notable partnerships like the one with Groq announced in April 2025, indicating its adoption in production systems.
- GitHub Stars: The project has garnered significant community interest, with approximately 8,900 stars.
- License: e2b is licensed under the permissive Apache-2.0 License, which allows for broad use and modification without the copyleft restrictions of licenses like AGPL.
- Hosting:
- SaaS: Yes. The primary offering is a fully managed cloud service with a tiered pricing model (Hobby and Pro). Pricing is based on a monthly subscription plus usage-based costs for CPU and memory, metered per second of runtime.
- Self-Hosted: Yes. e2b provides a self-hosting guide and Terraform scripts for deploying the infrastructure on your own cloud provider account. It currently supports GCP, with support for AWS in progress.
- Capabilities:
- Filesystem Access: The sandboxes provide full filesystem I/O capabilities. The SDKs for Python and JavaScript allow for programmatic uploading and downloading of files, making it easy to provide context to or retrieve artifacts from an agent. The environments are persistent, meaning filesystem changes and installed packages can be maintained across multiple execution calls within a single session.
- Network Access: Sandboxes have full, unrestricted internet access by default. Furthermore, any service running inside the sandbox (e.g., a web server) can be exposed to the public internet via a unique, secure URL provided by the e2b platform, facilitating use cases like hosting generated web apps or providing APIs from within the sandbox.
- Workload Suitability: e2b is highly versatile and well-suited for both short-lived and long-running workloads. The fast startup time (~150-200ms) is ideal for ephemeral tasks like running a single code snippet for data analysis. The Pro plan supports sessions up to 24 hours long, making it robust enough for complex, stateful agentic tasks, development environments, or demanding reinforcement learning training loops that require persistent state.
- Overview: Daytona positions itself as a comprehensive platform for both secure AI code execution and enterprise development environment management. It emphasizes lightning-fast sandbox startup times (under 200ms), stateful persistence, and a robust SDK for programmatic control. It aims to provide a secure, elastic runtime for AI agents while also serving as a full-featured Cloud Development Environment (CDE). For a detailed comparison with other AI sandboxing solutions, see this analysis of Daytona vs microsandbox.
- GitHub: daytonaio/daytona
- Website: daytona.io
- Launch Date: The company was founded in 2023, and its open-source version gained significant community traction and funding in mid-2024.
- GitHub Stars: The project has achieved remarkable popularity, with over 21,000 stars.
- License: The main open-source repository is licensed under the AGPL-3.0. This is a critical distinction, as this strong copyleft license has specific requirements for modifications that are made available over a network. Other parts of the ecosystem, like the documentation, use the more permissive Apache-2.0 license.
- Hosting:
- SaaS: Yes. Daytona offers a managed cloud platform with a usage-based, pay-as-you-go pricing model for compute, memory, and storage resources.
- Self-Hosted: Yes. Self-hosting is a core part of Daytona's offering. The project provides installers and detailed guides for setting up a Daytona instance on your own infrastructure, giving organizations full control over their environments.
- Capabilities:
- Filesystem Access: Daytona provides a full, persistent filesystem within its sandboxes. A key feature is the ability to archive inactive sandboxes, which moves the entire filesystem state to cost-effective object storage for long-term preservation and later retrieval. The SDK includes a filesystem API for programmatic file operations.
- Network Access: Sandboxes are equipped with network access. They can expose services running on specific ports via a public preview link. For private sandboxes, this link is secured with an access token to ensure controlled access.
- Workload Suitability: Daytona is explicitly designed for long-running, stateful workloads. Features like automatically stopping inactive sandboxes and archiving them after a configurable period are tailored to optimize costs for persistent environments that are not always in active use. This makes it ideal for full-fledged development workspaces and complex, multi-step agentic tasks that require state to be preserved indefinitely.
- Underlying Technology: Daytona uses container-based isolation with OCI/Docker compatibility. The platform supports any OCI/Docker image for sandbox creation and achieves sub-90ms startup times through optimized container orchestration rather than microVM technology.
The choice of the AGPL-3.0 license for Daytona's core product is a significant strategic decision. This license generally requires that any modifications to the software, if made accessible over a network, must also be released under the same license. For many large enterprises, this creates legal and compliance friction, as it could compel them to open-source proprietary integrations. This dynamic often serves to steer such customers towards a commercial enterprise license, which is offered under different, non-copyleft terms. This contrasts sharply with the permissive Apache-2.0 licenses of e2b and microsandbox, which remove this friction and signal a different business strategy focused on widespread adoption and SaaS conversion.
- Overview: microsandbox is a self-hosted platform singularly focused on providing maximum security for untrusted code execution. Its core value proposition is combining the hardware-level isolation of microVMs (powered by libkrun) with the sub-200ms startup speed of containers and the complete control afforded by a self-hosted model. It is designed to solve the security-speed-control trade-off without compromise.
- GitHub: microsandbox/microsandbox
- Website: docs.microsandbox.dev
- Launch Date: The initial public release (v0.1.0) was on May 20, 2025.
- GitHub Stars: The project has accumulated approximately 3,300 stars since its launch.
- License: microsandbox uses the permissive Apache-2.0 License, making it straightforward for companies to adopt and integrate into commercial products.
- Hosting:
- SaaS: No. The platform is explicitly and exclusively a self-hosted solution. This is a core part of its identity, emphasizing "Your Infrastructure" and giving users full control and data privacy.
- Self-Hosted: Yes, this is the only deployment model. Users install and run the msb server component on their own hardware or cloud instances.
- Capabilities:
- Filesystem Access: The platform supports both persistent and ephemeral filesystems. When using the project-based workflow (msr), file changes and installations within a sandbox are automatically persisted to a local ./menv directory on the host. This allows a developer to stop and restart a sandbox without losing their work. For one-off tasks, it also supports fully temporary sandboxes (msx) that leave no trace after execution.
- Network Access: The microsandbox core server is responsible for managing networking for the sandboxes. While detailed network configuration guides are not present in the primary documentation snippets, use cases such as "Web Browsing Agent" and "Instant App Hosting" strongly imply that sandboxes can be configured with controlled network access to fulfill these roles.
- Workload Suitability: microsandbox is highly flexible, catering to both short-lived, stateless tasks and long-running, stateful workloads. The msx command is designed for quick, ephemeral executions, while the project-based msr command with its persistent state is ideal for ongoing development work or complex, multi-step processes where context must be maintained.
- Overview: WebContainers represents a fundamentally different approach to code sandboxing by bringing server-side development entirely into the browser. Developed by StackBlitz, this technology creates a browser-based Node.js runtime using WebAssembly that can run package managers, development servers, and full-stack frameworks without any remote infrastructure.
- GitHub: N/A (proprietary)
- Website: webcontainers.io, stackblitz.com
- Technology: The platform leverages Browser-based Node.js/WebAssembly to create isolated execution environments that run entirely within the browser's security sandbox. This approach eliminates the need for remote servers while providing genuine Node.js compatibility.
- Launch Date: WebContainers technology was first introduced in 2021 as part of StackBlitz's browser-based IDE platform.
- License: Proprietary technology with enterprise licensing options available for embedding in other platforms.
- Hosting:
- SaaS: Yes. The primary offering is integrated into StackBlitz's cloud IDE platform, with enterprise licensing available for custom integrations.
- Self-Hosted: No. The technology runs in browsers but requires StackBlitz's proprietary runtime.
- Capabilities:
- Filesystem Access: Ephemeral - provides a virtual filesystem that exists only during the browser session. Files can be persisted through browser storage mechanisms or exported.
- Network Access: Browser-limited - can make HTTP requests subject to browser CORS policies and security restrictions. Cannot run traditional server applications accessible from external networks.
- Workload Suitability: Ideal for short to medium-running development tasks, prototyping, tutorials, and educational environments. Performance claims of up to 10x faster package installation than local development make it suitable for rapid iteration workflows.
- Unique Value Proposition: WebContainers eliminates server infrastructure costs entirely while providing instant, disposable development environments. This makes it particularly valuable for interactive tutorials, low-code platforms, and AI development environments where traditional server-based sandboxes would be cost-prohibitive at scale.
- Overview: Replit is a browser-based development platform that emphasizes collaboration, education, and rapid prototyping. Founded in 2016, it has become one of the most popular platforms for learning to code and building quick prototypes. The platform provides instant development environments without any local setup, supporting dozens of programming languages and frameworks.
- GitHub: replit
- Website: replit.com
- Technology: Replit uses container and VM-based isolation to provide secure, isolated development environments. Each "Repl" (development environment) runs in its own sandboxed container with full filesystem access and network capabilities.
- Launch Date: 2016 - Originally founded as a simple online code editor, it has evolved into a comprehensive development platform.
- License: Proprietary platform with both free and paid tiers.
- Hosting:
- SaaS: Yes. Replit is primarily a cloud-based SaaS platform with tiered pricing based on usage and features.
- Self-Hosted: No. The platform is exclusively cloud-based.
- Capabilities:
- Filesystem Access: Persistent - Each Repl maintains its filesystem state between sessions, allowing for ongoing project development.
- Network Access: Full - Repls can make external network requests and can expose web services via public URLs.
- Workload Suitability: Ideal for short to long-running development tasks, particularly educational projects, collaborative coding, and rapid prototyping. The platform excels at quick iterations and sharing code with others.
- Unique Features: Real-time collaboration, integrated AI coding assistance, one-click deployment, and strong community features make it particularly popular for education and team development.
- Overview: Cloudflare Workers represents the edge computing paradigm, running code across Cloudflare's global network of 275+ data centers. Launched in 2017, it uses V8 Isolates to provide extremely fast cold starts and global distribution, making it ideal for serverless functions that need to run close to users worldwide.
- GitHub: N/A (proprietary)
- Website: workers.cloudflare.com, developers.cloudflare.com/workers
- Technology: V8 Isolates - Uses the same isolation technology as web browsers to provide lightweight, secure execution environments with near-zero cold start times.
- Launch Date: 2017 - Introduced as part of Cloudflare's expansion into edge computing services.
- License: Proprietary platform with usage-based pricing.
- Hosting:
- SaaS: Yes. Exclusively a managed service running on Cloudflare's global edge network.
- Self-Hosted: No. The value proposition is entirely based on Cloudflare's global infrastructure.
- Capabilities:
- Filesystem Access: Ephemeral - No persistent filesystem. State can be maintained using Workers KV (key-value storage) or Durable Objects.
- Network Access: Edge-limited - Can make HTTP requests but operates within browser-like security constraints. Optimized for HTTP request/response patterns.
- Workload Suitability: Exclusively for short-running tasks (10ms-30s execution time). Perfect for API endpoints, edge logic, and request transformation.
- Performance: Exceptional performance with 0ms cold starts and sub-100ms global latency. Claims to be up to 10x less expensive than traditional serverless platforms.
- Overview: Fly.io is a developer-focused cloud platform that runs applications using hardware-virtualized containers (microVMs) across 35 global regions. Founded in 2017, it bridges the gap between traditional VPS hosting and modern serverless platforms, offering the flexibility of VMs with the convenience of containerized deployment.
- GitHub: N/A (proprietary)
- Website: fly.io, fly.io/docs
- Technology: MicroVMs (Firecracker) - Uses Firecracker microVMs to provide hardware-level isolation while maintaining fast boot times (250ms or less).
- Launch Date: 2017 - Initially focused on CDN services, evolved into a full application hosting platform.
- License: Proprietary platform with transparent, usage-based pricing.
- Hosting:
- SaaS: Yes. Fully managed platform running on Fly.io's own hardware infrastructure.
- Self-Hosted: No. The platform is built around Fly.io's specific hardware and network infrastructure.
- Capabilities:
- Filesystem Access: Persistent - Applications can use persistent volumes and maintain state between deployments.
- Network Access: Full - Complete network access with automatic global load balancing and zero-config private networking between instances.
- Workload Suitability: Supports both short and long-running workloads. Can scale from single request handling to always-on applications with thousands of instances.
- Unique Value Proposition: Combines the isolation benefits of microVMs with a developer-friendly deployment experience. Particularly strong for applications that need global distribution but require more than what edge computing platforms can provide.
- Overview: Kata Containers is an open-source container runtime that delivers the speed of containers with the security of virtual machines. Launched in 2017 by the Open Infrastructure Foundation, it represents a unique approach to container security by running each container in its own lightweight virtual machine. This hybrid approach addresses the fundamental security concerns of traditional container runtimes while maintaining container ecosystem compatibility.
- GitHub: kata-containers/kata-containers
- Website: katacontainers.io
- Technology: MicroVM Containers - Kata Containers creates lightweight virtual machines for each container, providing hardware-enforced isolation while maintaining compatibility with the container ecosystem. It supports multiple hypervisors including QEMU, Cloud-Hypervisor, and Firecracker.
- Launch Date: December 2017 - Emerged from the merger of Intel Clear Containers and Hyper runV projects.
- License: Apache-2.0 - Fully open-source with permissive licensing.
- Hosting:
- SaaS: No. Kata Containers is infrastructure software that cloud providers and enterprises deploy in their own environments.
- Self-Hosted: Yes. This is the primary deployment model, integrated into container orchestration platforms like Kubernetes.
- Capabilities:
- Filesystem Access: Persistent - Full filesystem capabilities within the container/VM hybrid, with standard container volume mounting and storage options.
- Network Access: Full - Complete networking capabilities with container-standard networking models and Kubernetes networking integration.
- Workload Suitability: Ideal for long-running, stateful workloads that require strong security isolation. Perfect for multi-tenant environments, untrusted code execution, and compliance-heavy workloads where container escape vulnerabilities are unacceptable.
- Unique Value Proposition: Kata Containers solves the "container vs. VM" dilemma by providing both. Organizations get the operational benefits of containers (fast startup, density, orchestration) with the security guarantees of VMs (hardware isolation, dedicated kernel). This makes it particularly valuable for production environments running untrusted workloads or requiring regulatory compliance.
- Overview: YepCode is an enterprise-ready integration and automation platform that provides secure, sandboxed code execution powered by Firecracker microVMs. Founded in 2021, it positions itself as "The Zapier for developers," offering full programming capabilities within a serverless environment. YepCode's defining feature is its automatic dependency detection and installation, eliminating the complexity of manual dependency management that plagues other platforms. It excels at short-lived executions, enterprise automation, and AI-generated code execution with comprehensive process management and audit capabilities.
- GitHub: yepcode
- Website: yepcode.io, YepCode Run
- Launch Date: 2021 - Founded with the mission to enable developers to automate tasks through source code rather than drag-and-drop interfaces.
- GitHub Stars: N/A (proprietary platform with some open-source components)
- License: Proprietary with freemium pricing model and enterprise options.
- Hosting:
- SaaS: Yes. The primary offering is YepCode Cloud with a usage-based pricing model called "Yeps" (executions), ranging from a free developer plan to enterprise solutions.
- Self-Hosted: Yes. YepCode offers on-premise deployment options available on Growth and Enterprise plans, including executors on-premise and full-stack on-premise deployments.
- Capabilities:
- Filesystem Access: Persistent - YepCode provides a robust storage system that handles file operations within processes. Users can upload, download, and manage files through both the platform interface and programmatic access via the
yepcode.storagehelper. File persistence is maintained across process executions. - Network Access: Full - Sandboxes have complete network access with the ability to connect to any external service. YepCode also provides a tunneling system for accessing private infrastructure behind firewalls, making it suitable for enterprise environments with strict network policies.
- Workload Suitability: YepCode is optimized for short-lived executions and serverless automation scenarios. While it supports longer processes, it excels at quick data transformations, API integrations, and ephemeral tasks. The platform supports processes written in JavaScript (Node.js v22) and Python (v3.13).
- Filesystem Access: Persistent - YepCode provides a robust storage system that handles file operations within processes. Users can upload, download, and manage files through both the platform interface and programmatic access via the
- Key Advantages:
- Automatic Dependency Management: YepCode's standout feature is its ability to automatically detect and install any NPM or PyPI dependency that code includes, eliminating the need for manual dependency configuration.
- Process Management & Versioning: Full process lifecycle management with source code versioning, execution tracking, and comprehensive audit trails for every change.
- Flexible Execution Triggers: Processes can be started manually, via scheduling system, through webhooks, or programmatically via API.
- Enterprise Audit & Compliance: Complete audit module tracking all modifications, executions, and system changes for regulatory compliance.
- MCP Integration: Offers an MCP (Model Context Protocol) server that allows both using the run_code tool for dynamic execution and exposing any pre-created process as MCP tools for AI agents.
- Unique Value Proposition: YepCode combines the ease of a SaaS platform with enterprise-grade security and the full power of programming languages. Its automatic dependency detection sets it apart from other platforms, while its comprehensive process management, audit capabilities, and MCP integration make it particularly valuable for AI agents and enterprise automation workflows that require both dynamic code execution and established process orchestration.
While the platforms above are specialized sandboxing runtimes, the broader category of Cloud Development Environments (CDEs) also relies heavily on sandboxing technology to function. They provide a useful point of comparison.
- CodeSandbox: A pioneer in the online IDE space, CodeSandbox provides a complete development experience in the browser. It cleverly uses two different sandboxing technologies. For lightweight frontend prototyping, it uses Browser Sandboxes, where code is executed directly in the browser. For more complex, full-stack development, it uses powerful VM Sandboxes built on microVMs, offering a backend environment with full terminal access. While it has open-source components, its core platform is a SaaS offering.
- Gitpod & Coder: These are leading open-source CDEs that focus on creating ephemeral, reproducible development environments directly from a Git repository context. Their primary goal is to solve the "works on my machine" problem by standardizing environments using configuration files like
.gitpod.yml or devcontainer.json.
- Sandboxing Approach: Their isolation is typically based on containers (e.g., Docker). However, their architectures are sophisticated. Gitpod employs a zero-trust model with a central management plane and runners that deploy environments within a customer's own cloud infrastructure, ensuring source code never leaves the network perimeter. Coder uses Terraform as its provisioning engine, which provides immense flexibility. A Coder template can define a workspace as a Docker container, a Kubernetes pod, or even a full VM on a cloud provider, allowing administrators to choose the appropriate level of isolation for their needs. Both projects use the AGPL-3.0 license for their open-source editions and offer enterprise versions with commercial licenses.
When evaluating sandboxing solutions, one of the most fundamental architectural decisions is choosing between container-based isolation (Docker/OCI) and microVM-based isolation. This choice significantly impacts performance, security, and operational complexity.
Containers (Docker) Performance Advantages:
- Startup Speed: OCI runtimes can spawn containers orders of magnitude faster than Firecracker microVMs
- Resource Overhead: Minimal overhead when sharing kernel and base container layers
- Memory Efficiency: Shared kernel and base layers reduce overall memory footprint
- Mature Ecosystem: Extensive tooling and optimization for long-running deployments
MicroVMs Performance Considerations:
- Cold Start Latency: Higher initial startup cost compared to containers
- Resource Isolation: Each VM requires its own kernel and memory space
- Hardware Requirements: Depends on hardware virtualization support
Containers Security Model:
- Containers are "basically fancy processes" with namespace-based isolation
- Shared kernel creates potential attack surface
- Suitable for trusted, homogeneous workloads
- Enhanced security available through technologies like gVisor (application kernels)
Real-World Container Escape Statistics:
- 94% of organizations reported serious container security incidents in the last 12 months
- 69% of incidents involved misconfigurations rather than vulnerabilities
- 87% of container images in production contain critical or high-severity vulnerabilities
- 60% of organizations were vulnerable to the major 2024 "Leaky Vessels" container escape vulnerabilities
- Most container escapes occur through misconfigurations (privileged containers, sensitive mounts) rather than novel CVE exploits
MicroVMs Security Advantages:
- Hardware-Level Isolation: Dedicated guest kernel per sandbox
- Stronger Boundaries: Hardware-enforced isolation between workloads
- Reduced Attack Surface: Host kernel not directly accessible to guest code
- Multi-Tenancy: Superior isolation for untrusted code from different sources
- Escape Mitigation: Hardware virtualization makes container escape techniques ineffective
Choose Containers When:
- Running internal, trusted applications
- Deploying homogeneous workloads that benefit from shared base layers
- Startup performance is critical
- Operating within a mature container ecosystem
- Managing long-running, stateful services
Choose MicroVMs When:
- Executing untrusted code from external sources
- Providing multi-tenant sandboxing services
- Security isolation is paramount
- Running diverse OS/kernel requirements
- Building hosting platforms or serverless infrastructure
Some platforms combine both approaches:
- Kata Containers: Provides container-compatible API with VM-level isolation
- gVisor: Application kernel approach offering intermediate security
- Platform-Specific: Many cloud providers use MicroVMs for hosting but containers for application deployment
Most organizations currently prefer containers because:
- Established tooling and operational expertise
- Simpler deployment and management workflows
- Better resource utilization for trusted workloads
- More mature monitoring and debugging capabilities
However, the emergence of fast-booting microVM technologies like Firecracker has made the performance gap less significant, making security considerations more important in the decision matrix.
Container Escape Risk Assessment:
- Low Risk: Internal development environments, trusted CI/CD pipelines, homogeneous application stacks
- Medium Risk: Multi-tenant SaaS platforms with authenticated users, plugin systems with code review
- High Risk: Public code execution services, AI agent sandboxes, untrusted user-generated code
Mitigation Strategies:
- For Containers: Use security-focused configurations, avoid privileged containers, implement least-privilege access, consider gVisor for additional isolation
- For MicroVMs: Accept higher resource overhead for stronger isolation guarantees, ideal for zero-trust environments
Key Takeaway: Use containers for internal, trusted applications where performance and ecosystem maturity matter most. Use MicroVMs for untrusted code execution, multi-tenant platforms, or when security isolation is non-negotiable. Given that 69% of container incidents involve misconfigurations rather than vulnerabilities, proper operational security practices are crucial regardless of the technology choice.
Choosing the right sandboxing solution depends on your specific requirements. Consider your project's security needs, workload types, operational preferences, and primary use case. This framework provides decision criteria to guide your selection.
This is the most important trade-off. Your choice depends on your threat model.
- For Maximum Security: If your application runs highly untrusted or potentially malicious code from the public internet, and you need the strongest possible isolation, choose a microVM-based solution. The hardware-enforced boundary from a dedicated guest kernel provides the best defense against container escape vulnerabilities.
- Recommended: microsandbox, e2b, YepCode.
- For Balanced Security and Compatibility: If you need stronger isolation than standard containers but can't use hardware virtualization, an application kernel is a good choice. It reduces the attack surface without requiring hardware virtualization.
- Recommended: gVisor.
- For Maximum Performance and Speed: If your workload is well-defined, you have some trust in the code, and startup time and resource overhead are most critical (e.g., high-volume, short-lived edge functions), a language-runtime-based sandbox is most efficient.
- Recommended: A platform built on WebAssembly (WASM) or V8 Isolates.
The nature of your workload - whether it's a one-off task or a long-running process - is important.
- For Stateless/Ephemeral Tasks: If you need to run quick, isolated tasks that don't require preserved state (e.g., grading code submissions, data transformations), most solutions work. However, those optimized for fast, ephemeral execution are better.
- Recommended: microsandbox in its temporary mode (msx) is explicitly designed for this. e2b's fast startup also makes it a strong contender. YepCode is specifically optimized for short-lived executions with automatic dependency management.
- For Stateful/Long-Running Processes: If your use case requires a persistent environment where the filesystem can be modified, dependencies can be installed, and state is preserved across multiple interactions (e.g., an interactive AI coding assistant, a full development workspace, a multi-step agent), you need a platform with robust persistence features.
- Recommended: Daytona, e2b (Pro plan), and microsandbox (project mode) are all explicitly designed to support long-running, stateful workloads. CDEs like Gitpod and Coder also excel at this.
Your organization's operational model and compliance requirements will determine your hosting strategy.
- For a Managed Service (SaaS): If you want to accelerate development and offload the operational burden of managing sandboxing infrastructure, a SaaS platform is the best choice. These platforms offer usage-based pricing and handle all the scaling, maintenance, and security of the underlying infrastructure.
- Recommended: e2b, Daytona, and YepCode provide mature, feature-rich SaaS offerings.
- For Full Control (Self-Hosted): If you have strict data sovereignty, regulatory compliance (e.g., GDPR), or security policies that mandate running all infrastructure within your own network perimeter, a self-hosted solution is necessary.
- Recommended: microsandbox is self-hosted by design and is the most straightforward choice for this model. Daytona, e2b, YepCode, Gitpod, and Coder also offer robust self-hosting options, typically as part of their enterprise offerings.
Finally, consider whether you need a tool tailored for a specific domain or a more general-purpose platform.
- For AI-Centric Workflows: If you are building AI agents, code interpreters, or other LLM-powered applications, choosing a platform that is explicitly optimized for this domain can provide significant advantages. Their SDKs and features are often designed to solve common problems in agentic development.
- Recommended: e2b, YepCode, and Daytona are heavily focused on the AI and agent use case.
- For General-Purpose Execution/Development: If your needs are broader, such as providing general-purpose development environments or a secure runtime for a variety of applications, a more general platform may be a better fit.
- Recommended: microsandbox is a powerful, general-purpose secure execution engine. Coder and Gitpod are leading general-purpose Cloud Development Environments.
This is a living document. The field of code sandboxing is evolving rapidly. If you see inaccuracies, have experience with these or other platforms, or want to suggest additions, please open an issue or submit a pull request. Your contributions are welcome!