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Skills/aradotso/trending-skills/zeroboot-vm-sandbox
zeroboot-vm-sandbox logo

zeroboot-vm-sandbox

aradotso/trending-skills
1K installs40 stars
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Installation

npx skills add https://github.com/aradotso/trending-skills --skill zeroboot-vm-sandbox

Summary

Sub-millisecond VM sandboxes for AI agents using copy-on-write KVM forking via Zeroboot

SKILL.md

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)
  1. Template: Firecracker boots once, pre-loads your runtime, snapshots memory + CPU state
  2. Fork (~0.8ms): New KVM VM maps snapshot memory as CoW, restores CPU state
  3. 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

Execute 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

MetricValue
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 (/dev/kvm accessible)
  • 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): mmap(MAP_PRIVATE) on snapshot file → kernel handles CoW page faults per VM
  • 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

/dev/kvm not found (self-hosted)

# Enable KVM kernel module
sudo modprobe kvm
sudo modprobe kvm_intel  # or kvm_amd

API returns 401 Unauthorized

  • Verify ZEROBOOT_API_KEY is set and starts with zb_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

Resources

  • API Reference
  • Architecture Docs
  • Deployment Guide
  • Homepage
  • GitHub

Score

0–100
63/ 100

Grade

C

Popularity15/30

1,207 installs — growing adoption.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Zeroboot Vm Sandbox skill score badge previewScore badge

Markdown

[![Zeroboot Vm Sandbox skill](https://www.remoteopenclaw.com/skills/aradotso/trending-skills/zeroboot-vm-sandbox/badges/score.svg)](https://www.remoteopenclaw.com/skills/aradotso/trending-skills/zeroboot-vm-sandbox)

HTML

<a href="https://www.remoteopenclaw.com/skills/aradotso/trending-skills/zeroboot-vm-sandbox"><img src="https://www.remoteopenclaw.com/skills/aradotso/trending-skills/zeroboot-vm-sandbox/badges/score.svg" alt="Zeroboot Vm Sandbox skill"/></a>

Zeroboot Vm Sandbox FAQ

How do I install the Zeroboot Vm Sandbox skill?

Run “npx skills add https://github.com/aradotso/trending-skills --skill zeroboot-vm-sandbox” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Zeroboot Vm Sandbox skill do?

Sub-millisecond VM sandboxes for AI agents using copy-on-write KVM forking via Zeroboot The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Zeroboot Vm Sandbox skill free?

Yes. Zeroboot Vm Sandbox is a free, open-source skill published from aradotso/trending-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Zeroboot Vm Sandbox work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Zeroboot Vm Sandbox works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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