zeroboot-vm-sandbox
提供基于 KVM 的硬件隔离虚拟机沙盒,采用写时复制技术,毫秒级启动,为 AI 代理提供安全隔离的执行环境
npx skills add aradotso/trending-skills --skill zeroboot-vm-sandboxBefore / After 效果对比
1 组使用 Docker 容器运行不受信任的代码,启动时间较长且只提供进程级隔离,存在逃逸风险,无法保证硬件级别的安全
使用 Firecracker + KVM 虚拟机,提供硬件级隔离,通过写时复制毫秒级启动,每个沙盒是完全独立的 VM,确保最高级别的安全性
description SKILL.md
zeroboot-vm-sandbox
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
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
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 (
/dev/kvmaccessible) -
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_KEYis set and starts withzb_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
Weekly Installs269Repositoryaradotso/trending-skillsGitHub Stars10First Seen6 days agoSecurity AuditsGen Agent Trust HubPassSocketPassSnykWarnInstalled ongithub-copilot268codex268amp268cline268kimi-cli268gemini-cli268
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