Trending-skills zeroboot-vm-sandbox
Sub-millisecond VM sandboxes for AI agents using copy-on-write KVM forking via Zeroboot
install
source · Clone the upstream repo
git clone https://github.com/Aradotso/trending-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/Aradotso/trending-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/zeroboot-vm-sandbox" ~/.claude/skills/aradotso-trending-skills-zeroboot-vm-sandbox && rm -rf "$T"
manifest:
skills/zeroboot-vm-sandbox/SKILL.mdsource content
Zeroboot VM Sandbox
Skill by ara.so — Daily 2026 Skills collection.
Zeroboot provides sub-millisecond KVM virtual machine sandboxes for AI agents using copy-on-write forking. Each sandbox is a real hardware-isolated VM (via Firecracker + KVM), not a container. A template VM is snapshotted once, then forked in ~0.8ms per execution using
mmap(MAP_PRIVATE) CoW semantics.
How It Works
Firecracker snapshot ──► mmap(MAP_PRIVATE) ──► KVM VM + restored CPU state (copy-on-write) (~0.8ms)
- Template: Firecracker boots once, pre-loads your runtime, snapshots memory + CPU state
- Fork (~0.8ms): New KVM VM maps snapshot memory as CoW, restores CPU state
- Isolation: Each fork is a separate KVM VM with hardware-enforced memory isolation
Installation
Python SDK
pip install zeroboot
Node/TypeScript SDK
npm install @zeroboot/sdk # or pnpm add @zeroboot/sdk
Authentication
Set your API key as an environment variable:
export ZEROBOOT_API_KEY="zb_live_your_key_here"
Never hardcode keys in source files.
Quick Start
REST API (cURL)
curl -X POST https://api.zeroboot.dev/v1/exec \ -H 'Content-Type: application/json' \ -H "Authorization: Bearer $ZEROBOOT_API_KEY" \ -d '{"code":"import numpy as np; print(np.random.rand(3))"}'
Python
import os from zeroboot import Sandbox # Initialize with API key from environment sb = Sandbox(os.environ["ZEROBOOT_API_KEY"]) # Run Python code result = sb.run("print(1 + 1)") print(result) # "2" # Run multi-line code result = sb.run(""" import numpy as np arr = np.arange(10) print(arr.mean()) """) print(result)
TypeScript / Node.js
import { Sandbox } from "@zeroboot/sdk"; const apiKey = process.env.ZEROBOOT_API_KEY!; const sb = new Sandbox(apiKey); // Run JavaScript/Node code const result = await sb.run("console.log(1 + 1)"); console.log(result); // "2" // Run async code const output = await sb.run(` const data = [1, 2, 3, 4, 5]; const sum = data.reduce((a, b) => a + b, 0); console.log(sum / data.length); `); console.log(output);
Common Patterns
AI Agent Code Execution Loop (Python)
import os from zeroboot import Sandbox def execute_agent_code(code: str) -> dict: """Execute LLM-generated code in an isolated VM sandbox.""" sb = Sandbox(os.environ["ZEROBOOT_API_KEY"]) try: result = sb.run(code) return {"success": True, "output": result} except Exception as e: return {"success": False, "error": str(e)} # Example: running agent-generated code safely agent_code = """ import json data = {"agent": "result", "value": 42} print(json.dumps(data)) """ response = execute_agent_code(agent_code) print(response)
Concurrent Sandbox Execution (Python)
import os import asyncio from zeroboot import Sandbox async def run_sandbox(code: str, index: int) -> str: sb = Sandbox(os.environ["ZEROBOOT_API_KEY"]) result = await asyncio.to_thread(sb.run, code) return f"[{index}] {result}" async def run_concurrent(snippets: list[str]): tasks = [run_sandbox(code, i) for i, code in enumerate(snippets)] results = await asyncio.gather(*tasks) return results # Run 10 sandboxes concurrently codes = [f"print({i} ** 2)" for i in range(10)] outputs = asyncio.run(run_concurrent(codes)) for out in outputs: print(out)
TypeScript: Agent Tool Integration
import { Sandbox } from "@zeroboot/sdk"; interface ExecutionResult { success: boolean; output?: string; error?: string; } async function runInSandbox(code: string): Promise<ExecutionResult> { const sb = new Sandbox(process.env.ZEROBOOT_API_KEY!); try { const output = await sb.run(code); return { success: true, output }; } catch (err) { return { success: false, error: String(err) }; } } // Integrate as a tool for an LLM agent const tool = { name: "execute_code", description: "Run code in an isolated VM sandbox", execute: async ({ code }: { code: string }) => runInSandbox(code), };
REST API with fetch (TypeScript)
const API_BASE = "https://api.zeroboot.dev/v1"; async function execCode(code: string): Promise<string> { const res = await fetch(`${API_BASE}/exec`, { method: "POST", headers: { "Content-Type": "application/json", Authorization: `Bearer ${process.env.ZEROBOOT_API_KEY}`, }, body: JSON.stringify({ code }), }); if (!res.ok) { const err = await res.text(); throw new Error(`Zeroboot error ${res.status}: ${err}`); } const data = await res.json(); return data.output; }
Health Check
curl https://api.zeroboot.dev/v1/health
API Reference
POST /v1/exec
POST /v1/execExecute code in a fresh sandbox fork.
Request:
{ "code": "print('hello')" }
Headers:
Authorization: Bearer <ZEROBOOT_API_KEY> Content-Type: application/json
Response:
{ "output": "hello\n", "duration_ms": 0.79 }
Performance Characteristics
| Metric | Value |
|---|---|
| Spawn latency p50 | ~0.79ms |
| Spawn latency p99 | ~1.74ms |
| Memory per sandbox | ~265KB |
| Fork + exec Python | ~8ms |
| 1000 concurrent forks | ~815ms |
- Each sandbox is a real KVM VM — not a container or process jail
- Memory isolation is hardware-enforced (not software)
- CoW means only pages written by your code consume extra RAM
Self-Hosting / Deployment
See docs/DEPLOYMENT.md in the repo. Requirements:
- Linux host with KVM support (
accessible)/dev/kvm - Firecracker binary
- Rust 2021 edition toolchain
# Check KVM availability ls /dev/kvm # Clone and build git clone https://github.com/adammiribyan/zeroboot cd zeroboot cargo build --release
Architecture Notes
- Snapshot layer: Firecracker VM boots once per runtime template, memory + vCPU state saved to disk
- Fork layer (Rust):
on snapshot file → kernel handles CoW page faults per VMmmap(MAP_PRIVATE) - Isolation: Each fork has its own KVM VM file descriptors, vCPU, and page table — fully hardware-separated
- No shared kernel: Unlike containers, each sandbox runs its own kernel instance
Troubleshooting
(self-hosted)/dev/kvm not found
# Enable KVM kernel module sudo modprobe kvm sudo modprobe kvm_intel # or kvm_amd
API returns 401 Unauthorized
- Verify
is set and starts withZEROBOOT_API_KEYzb_live_ - Check the key is not expired in your dashboard
Timeout on execution
- Default execution timeout is enforced server-side
- Break large computations into smaller chunks
- Avoid infinite loops or blocking I/O in sandbox code
High memory usage (self-hosted)
- Each VM fork starts at ~265KB CoW overhead
- Pages are allocated on write — memory grows with sandbox activity
- Tune concurrent fork limits based on available RAM