Security
AI code generation has transformed software development, but this scale introduces serious security risks. A Veracode 2025 benchmark found 45% of generated code samples failed security tests involving OWASP Top 10 vulnerabilities. A secure sandbox isolates code execution so that untrusted or AI-generated code cannot access host systems, other workloads, or sensitive data.
AI code generation has transformed software development, with Cursor's co-founder reportedly claiming Cursor writes almost 1 billion accepted lines of code daily, a self-reported figure not independently audited. But this scale introduces serious security risks: Veracode's 2025 benchmark of 100+ LLMs across 80 coding tasks found 45% of generated code samples failed security tests involving OWASP Top 10 vulnerabilities, and documented incidents include AI coding agents deleting local user files or home-directory contents, and separate incidents involving deletion of production databases or production data. Sandboxed environments have become essential infrastructure for running AI-generated code safely at scale. A secure sandbox isolates code execution so that untrusted or AI-generated code cannot access host systems, other workloads, or sensitive data. For teams building AI coding assistants, agents, or code generation pipelines, choosing the right sandboxed environment determines whether you can execute code securely, scale without manual intervention, and meet enterprise compliance requirements. This guide examines seven sandboxed environments serving different AI code generation needs in 2026, starting with Modal Sandboxes, a serverless platform built for secure code execution at massive scale.
Modal delivers serverless compute for secure code execution at scale, with sandboxes purpose-built for AI-generated code. The platform takes your code, containerizes it, and executes it in the cloud with automatic scaling, all defined through a code-first SDK available for Python, Go, and JavaScript/TypeScript.
modal.Sandbox.create(...). Code running inside a sandbox is not limited to one programming language; the sandbox can run whatever runtime or language the workload requiresModal has completed a SOC 2 Type II audit and supports HIPAA-compliant workloads on Enterprise plans via a BAA. The platform uses gVisor-based sandboxing for compute isolation, TLS 1.3 for public APIs, and encryption for data in transit and at rest. For teams with strict security requirements, Modal provides authenticated Sandbox connections and tunnel/port-forwarding primitives with connection tokens, with domain-level egress filtering actively in development.
Modal powers production workloads for AI companies running AI-generated code at scale:
Best For: Teams building AI coding assistants, agents, or code generation pipelines that need secure sandboxed execution at scale, with proven enterprise reliability and compliance certifications.
E2B specializes in secure sandboxes for AI agents, focusing on ephemeral code execution with Firecracker microVM isolation. E2B self-reports over 500 million started sandboxes and states it is used by 88% of Fortune 100 companies.
E2B excels at ephemeral code execution, spinning up isolated environments for agents to run generated code, then tearing them down. Perplexity implemented advanced data analysis in one week using E2B's runtime. E2B documents 1-hour continuous runtime on Base plans and 24-hour continuous runtime on higher-tier plans, with paused-state preservation available.
Best For: Teams building coding agents focused on ephemeral code execution and testing, particularly those needing fast sandbox cold starts and polished SDK design.
Northflank provides a complete cloud platform with sandbox capabilities. Northflank says it processes over 2 million isolated workloads monthly. The platform offers multiple isolation options and no forced time limits on sandbox sessions.
Northflank positions itself as a complete infrastructure platform rather than a sandbox-only tool. The platform's flexibility in isolation technology, offering both microVM and gVisor options, allows teams to choose the security boundary appropriate for their workloads.
Best For: Teams needing enterprise features like BYOC deployment, no forced session time limits, and flexible isolation options within a broader infrastructure platform.
Daytona provides AI agent infrastructure with fast documented sandbox creation times. Secondary coverage reports Daytona shifted toward AI agent infrastructure in early 2025 and the platform targets eval pipelines and agent workflows.
Daytona focuses on persistent workspaces that maintain state across sessions. This approach benefits agents that need to preserve context, cached dependencies, or intermediate results without recreation overhead.
Best For: Teams building coding agents that require fast sandbox creation, stateful persistence, and Docker compatibility for standard container workflows.
Together Code Sandbox extends Together AI's GPU cloud with sandboxed execution environments, offering snapshot-based startup and resume capabilities.
Together Code Sandbox is geared toward teams already using Together AI's ecosystem who need sandboxed development environments. The platform's snapshot feature is particularly useful for agents that need to maintain heavy IDE state.
Best For: Teams already using Together AI's platform who need integrated sandbox environments with snapshot capabilities.
Vercel Sandbox is an isolated code execution environment built for running untrusted code in temporary Linux microVMs. The platform uses Firecracker for isolation and integrates tightly with the Vercel deployment ecosystem.
Vercel Sandbox is best understood as an execution layer for secure, isolated code running within the Vercel ecosystem. Its fit is strongest for agent or developer workflows that involve repeated start-run-stop cycles or safe execution of generated code in Next.js applications.
Best For: Teams building within the Vercel ecosystem who need isolated environments for code execution, testing, or agent workflows with tight Next.js integration.
Blaxel is a sandbox platform built specifically for AI agents, with a focus on persistent "agent computers" that stay on standby and resume quickly.
Blaxel emphasizes persistent state rather than purely ephemeral execution. The platform is optimized for agents that need continuity across workflows, retaining shell history, installed dependencies, and context over time, rather than clean-room execution on every task.
Best For: Teams building coding agents that need persistent sandbox environments, fast standby resume times, and secure code execution with continuity across sessions.
Modal's AI-native runtime, filesystem, and multi-cloud capacity pool are optimized for the unique demands of sandboxed code execution: fast cold starts, elastic scaling, and secure isolation for AI-generated code.
Modal powers cloud infrastructure for over 10,000 teams, including AI companies running sandboxed code execution at massive scale. Production users like Lovable and Quora run millions of untrusted code snippets daily without pre-provisioning capacity, demonstrating enterprise-scale reliability for AI code generation workflows.
Modal's sandboxes support 50,000+ concurrent sessions with fast cold starts, gVisor isolation, and full observability. For AI coding assistants and agents that generate and execute untrusted code, this combination of scale, speed, and security is essential.
The code-first SDK eliminates infrastructure configuration complexity. Teams define sandbox environments, compute requirements, and scaling behavior directly in code. Modal's SDKs support Python, Go, and JavaScript/TypeScript. Modal Functions use decorators, while Sandboxes are created programmatically via modal.Sandbox.create(...). Sandboxes can run whatever runtime or language the workload requires. This code-first approach enables rapid iteration without YAML files or manual configuration.
With a completed SOC 2 Type II audit, HIPAA support via BAA for Enterprise customers (subject to product-scope limitations), and comprehensive security practices including gVisor sandboxing and TLS 1.3, Modal provides enterprise security features that support demanding AI code generation deployments.
For teams building AI coding assistants, code generation pipelines, or autonomous coding agents that require secure execution at scale, production-grade reliability, and enterprise compliance, Modal's combination of AI-native infrastructure and proven customer scale makes it the clear choice.
Explore the Modal documentation to get started.
Explore the Modal documentation to get started with secure AI code generation sandboxes.
View Modal DocsA sandboxed environment is an isolated execution space where AI-generated code runs without access to host systems, other workloads, or sensitive data. This isolation prevents malicious or buggy generated code from causing damage. Modal uses gVisor-based containers for isolation, while platforms like E2B and Vercel employ Firecracker microVMs.
AI code generation tools produce code autonomously, and Veracode's 2025 benchmark of 100+ LLMs across 80 coding tasks found 45% of generated code samples failed security tests involving OWASP Top 10 vulnerabilities. Documented incidents include AI coding agents deleting local user files or home-directory contents, and separate incidents involving deletion of production databases or production data. Sandboxed execution ensures that generated code runs in a controlled environment where failures cannot propagate to production systems.
Several platforms offer free tiers or credits for getting started. Modal provides free compute credits on its Starter plan, E2B offers one-time free credits, and platforms like Daytona and Blaxel provide initial credits for new users. Check each platform's current offerings for specific details.
Modal uses gVisor-based sandboxing for compute isolation, TLS 1.3 for public APIs, and encryption for data in transit and at rest. The platform has completed a SOC 2 Type II audit and supports HIPAA-compatible workloads for Enterprise customers through Business Associate Agreements, subject to product-scope limitations. Additional security features include authenticated Sandbox connections and tunnel/port-forwarding primitives with connection tokens, with domain-level egress filtering actively in development.
Cloud-based sandboxes eliminate infrastructure management overhead, provide instant scaling without capacity planning, and offer pay-per-use economics. Modal scales to 50,000+ concurrent sandboxes automatically, while E2B self-reports over 500 million started sandboxes, a scale that would be impractical to manage with self-hosted infrastructure.
Some enterprise-oriented sandbox providers disclose SOC 2 or SOC 2 Type II compliance, but certification status and scope vary by vendor and should be verified directly. Modal has completed a SOC 2 Type II audit and supports HIPAA-compatible workloads for healthcare applications through Business Associate Agreements on Enterprise, subject to current product-scope limitations. When evaluating platforms, verify current certifications and understand any scope limitations for specific features.