Secure, local and programmable sandboxes for AI agents — launch hardware-isolated microVMs in sub-100ms to execute untrusted code
microsandbox is a secure sandbox runtime designed for AI agents, leveraging microVM technology for hardware-level isolation where each sandbox runs its own independent Linux kernel, protecting against namespace escape vulnerabilities while achieving sub-100ms startup times.
Core Isolation & Security
- microVM virtualization via libkrun with per-sandbox independent kernels, fully isolated from the host kernel
- Non-leaking secret mechanism: secret values never enter the VM; random placeholders are used internally, with real values substituted by the host side only when requests target allowed destinations. Automatically blocks DNS rebinding and cloud metadata endpoints (169.254.169.254)
- Programmable networking: user-space network stack based on smoltcp where every packet leaving the sandbox passes through a host-side controllable stack, supporting IP/DNS/HTTP-level policy control
Image & Filesystem
- OCI compatible: supports standard container images from Docker Hub, GHCR, ECR, GCR and any OCI-compatible registry with automatic shared layer deduplication
- Image storage uses VMDK + EROFS fsmeta for block-device-backed rootfs
- Supports host directory mounts, managed volumes, and custom filesystem backends
- Snapshot & reuse: capture stopped sandbox writable layers as portable artifacts; subsequent sandboxes boot from snapshots skipping the installation phase
Deployment Model
- Runtime embeds directly as a child process of the host application — no daemon architecture, no root required, no background services
- Supports Linux (KVM) and macOS (Apple Silicon)
- Detached mode available for long-running sessions
Developer Experience
- Multi-language SDKs (Rust, TypeScript, Python) with consistent APIs
- Full-featured CLI tool
msbcovering sandbox/image/volume lifecycle management - AI Agent integration: MCP Server (
microsandbox-mcp) and Agent Skills compatible with Claude Code, Cursor, Codex, Gemini CLI, GitHub Copilot and other mainstream AI coding assistants
Typical Use Cases
- AI Agent code execution sandbox: run untrusted code in isolated VMs, preventing prompt injection from compromising the host
- Zero-leak credential management: Agent calls external APIs without exposing secrets to sandbox-internal code
- Local isolated dev & test: quickly spin up isolated environments from OCI images
- CI/CD lightweight parallel builds: sub-100ms microVM startup for parallelized build tasks
- Multi-agent collaboration: each agent gets an isolated environment with snapshot-based reuse of pre-configured setups
Current Status: Beta (v0.4.5); programmable networking and extensible filesystem backends marked as coming soon; Windows support status unconfirmed.