# LitterBox — Self-Hosted Payload Sandbox (MCP)

> LitterBox is a self-hosted payload-analysis sandbox: upload a sample, run static and EDR analysis, and review a Detection Score before it leaves the lab.

## Install

Merge the JSON below into your `.mcp.json`:

## Quick Use

```bash
git clone https://github.com/BlackSnufkin/LitterBox.git

# Windows (Python 3.11+)
cd LitterBox
python -m venv venv
pip install -r requirements.txt
python litterbox.py

# Linux (Docker): see LitterBox/Docker/setup.sh
```

## Intro

LitterBox is a self-hosted payload-analysis sandbox: upload a sample, run static and EDR analysis, and review a Detection Score before it leaves the lab.

- **Best for:** Red/blue teams who need a repeatable lab sandbox to measure detection before live engagements
- **Works with:** Python 3.11+; Windows and Docker (Linux); optional EDR profiles; includes a wiki-linked MCP integration (per README)
- **Setup time:** 30–90 minutes (Docker build can take ~1 hour)

## Practical Notes

- GitHub: 1,416 stars · 161 forks; pushed 2026-05-05 (verified via GitHub API).
- README states Docker setup provisions a Windows 10 container with KVM and exposes UI at `http://127.0.0.1:1337`.
- README lists bundled scanners with versions/dates (e.g., PE-Sieve 0.4.1.2 updated 2026-05-02; Elastic YARA rules commit `d131ea8`).

## Main

If you use LitterBox in a real workflow, keep it disciplined:

1. Treat it as a **staging gate**: every payload must pass the same pipeline before it leaves the lab.
2. Keep EDR profiles and scanner versions under change control; the README’s scanner table makes drift visible.
3. Use the results to decide between:
   - *rewrite/refactor* (reduce detections)
   - *environmental changes* (different execution context)
   - *abandon* (too risky)
4. Run it isolated. The README’s advisory calls out VM isolation and “development use only”.

Even if you never use the MCP path, the “Detection Score + indicators breakdown” framing is a strong way to standardize review discussions.

### FAQ

**Q: Is this safe to run on a workstation?**
A: Only in isolated environments. The README warns against production use and recommends VM/dedicated lab setups.

**Q: Where do EDR profiles live?**
A: README says to drop YAML profiles under `Config/edr_profiles/` so the upload page picks them up at boot.

**Q: Does it support MCP?**
A: README links to a wiki page named `LitterBoxMCP` under its documentation table.

## Source & Thanks

> Source: https://github.com/BlackSnufkin/LitterBox
> License: GPL-3.0
> GitHub stars: 1,416 · forks: 161

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## 快速使用

```bash
git clone https://github.com/BlackSnufkin/LitterBox.git

# Windows（Python 3.11+）
cd LitterBox
python -m venv venv
pip install -r requirements.txt
python litterbox.py

# Linux（Docker）：参考 LitterBox/Docker/setup.sh
```

## 简介

LitterBox 是自建的 payload 分析沙箱：上传样本后可跑静态/动态/EDR 分析，输出 Detection Score 与触发指标，支持用 profile 接入 EDR，用于出手前的实验室验证。

- **适合谁：** 红蓝对抗团队：想在实验室先量化检测风险，再决定是否进入真实环境
- **可搭配：** Python 3.11+；Windows 与 Docker（Linux）；可选 EDR profiles；README 链接到 MCP 集成说明（Wiki）
- **准备时间：** 30–90 分钟（Docker 初次构建约 1 小时）

## 实战建议

- GitHub：1,416 stars · 161 forks；最近更新 2026-05-05（GitHub API 验证）。
- README 表示 Docker 安装会拉起带 KVM 的 Windows 10 容器，完成后 UI 在 `http://127.0.0.1:1337`。
- README 给出内置扫描器版本与日期（例如 PE-Sieve 0.4.1.2 更新至 2026-05-02；Elastic YARA 规则 commit `d131ea8`）。

## 主要内容

把 LitterBox 用成“可落地的门禁”：

1. 作为 **出手前的关卡**：每个样本都走同一套 pipeline，别靠拍脑袋放行。
2. EDR profiles 与扫描器版本做变更管理；README 的 scanner 表让漂移一眼可见。
3. 用结果推动决策：是 *重写/降噪*、还是 *换环境*，还是 *直接放弃*。
4. 一定要隔离运行。README 的安全提示强调只在隔离 VM/专用测试环境中使用。

即便不走 MCP，单靠 “Detection Score + 触发指标拆解” 也足以把评审讨论标准化。

### FAQ

**能在日常工作机上跑吗？**
答：建议只在隔离环境跑。README 提示不要用于生产，推荐隔离 VM/实验室环境。

**EDR profiles 放哪？**
答：README 说把 YAML profile 放到 `Config/edr_profiles/`，启动时会自动加载。

**支持 MCP 吗？**
答：README 的文档表格链接到 `LitterBoxMCP`（Wiki 页面）。

## 来源与感谢

> Source: https://github.com/BlackSnufkin/LitterBox
> License: GPL-3.0
> GitHub stars: 1,416 · forks: 161


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Source: https://tokrepo.com/en/workflows/litterbox-self-hosted-payload-sandbox-mcp
Author: MCP Hub