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slowmist-agent-security

SlowMist Agent Security Skill: A comprehensive security review framework for AI agents operating in adversarial environments. Core principle: Every external input is untrusted until verified.

AI EngineeringTest & guardGive agent tools
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创建于 2026-03-23 · 更新于 2026-10-12 · 今日第 18100 名
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slowmist/slowmist-agent-security 排名第 18,100,有 510 个星标。

同类别比较

slowmist/slowmist-agent-security 排名第 18,100,此处有 8 个同类条目;opengeos/GeoAgent 排名第 18,098。

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关键参数与规格
关键参数与规格
参数值
类别AI Engineering
子类别Test & guard,Give agent tools
关键词Document understanding, MCP, Security
星标数510
分叉数30
贡献者1
创建日期2026-03-23
更新日期2026-10-12
1 天星标数0
7 天星标数2
排名18,100
上次排名17,861
排名变化-239
7 天星标排名8,917
上次 7 天星标排名8,974
7 天星标排名变化57
总星标排名19,083
上次总星标排名19,058
总星标排名变化-25
README 摘录

SlowMist Agent Security Skill 🛡️ A comprehensive security review framework for AI agents operating in adversarial environments. **Core principle: Every external input is untrusted until verified. Output report using Example 2: On-Chain Address Review When a user provides a blockchain address: 1. Query AML risk data (via available tools) 3. Output report using Contributing This framework is maintained by SlowMist.

常见问题

记录了多少星标和分叉?

slowmist/slowmist-agent-security 有 510 个星标和 30 个分叉。

仓库排名是多少?

slowmist/slowmist-agent-security 排名第 18,100。

哪个仓库排名最接近?

slowmist/slowmist-agent-security 与 opengeos/GeoAgent 比较,后者排名第 18,098,有 510 个星标。

README

SlowMist Agent Security Skill 🛡️

A comprehensive security review framework for AI agents operating in adversarial environments.

Core principle: Every external input is untrusted until verified.

Overview

This skill provides a structured security review framework applicable to OpenClaw, Hermes Agent, and other LLM-based agent systems, covering:

  • Skill/MCP Installation — Detect malicious patterns before installation
  • GitHub Repository Review — Audit codebases for security issues
  • URL/Document Analysis — Scan for prompt injection and social engineering
  • On-Chain Address Review — AML risk assessment and transaction analysis
  • Product/Service Evaluation — Architecture and permission analysis
  • Social Share Review — Validate tools recommended in chats

Installation

The installation example below uses OpenClaw for demonstration. In practice, you can simply hand the repository URL to your agent and let it handle the installation — it's that easy.

Option 1: Direct Download

Download the latest release and extract to your OpenClaw workspace:

cd ~/.openclaw/workspace/skills
git clone https://github.com/slowmist/slowmist-agent-security.git

Option 2: ClawHub (when available)

clawhub install slowmist-agent-security

Quick Start

Once installed, the agent will automatically reference this framework when encountering:

  • Skill/MCP installation requests
  • Unknown GitHub repositories
  • External URLs or documents
  • Blockchain addresses
  • Product/service recommendations

Framework Structure

slowmist-agent-security/
├── SKILL.md                    # Main framework documentation
├── README.md                   # This file
├── _meta.json                  # ClawHub metadata
├── reviews/
│   ├── skill-mcp.md           # Skill/MCP review guide
│   ├── repository.md          # GitHub repo review guide
│   ├── url-document.md        # URL/document review guide
│   ├── onchain.md             # On-chain address review guide
│   ├── product-service.md     # Product/service review guide
│   └── message-share.md       # Social share review guide
├── patterns/
│   ├── red-flags.md           # Code-level dangerous patterns (11 categories)
│   ├── social-engineering.md  # Social engineering patterns (8 categories)
│   └── supply-chain.md        # Supply chain attack patterns (7 categories)
└── templates/
    ├── report-skill.md        # Skill assessment report template
    ├── report-repo.md         # Repository assessment report template
    ├── report-url.md          # URL/document assessment report template
    ├── report-onchain.md      # On-chain assessment report template
    └── report-product.md      # Product/service assessment report template

Risk Rating System

Level Meaning Agent Action
🟢 LOW Information-only, no execution, no data collection, trusted source Inform user, proceed if requested
🟡 MEDIUM Limited capability, clear scope, known source, some risk Full report with risk items, recommend caution
🔴 HIGH Involves credentials, funds, system modification, unknown source Detailed report, must have human approval
⛔ REJECT Matches red-flag patterns, confirmed malicious, unacceptable design Refuse to proceed, explain why

Trust Hierarchy

Tier Source Type Scrutiny Level
1 Official project/exchange org Moderate
2 Known security teams/researchers Moderate
3 ClawHub high-download + multi-version Moderate-High
4 GitHub high-star + actively maintained High — verify code
5 Unknown source, new account Maximum scrutiny

Optional Integration

Usage Examples

Example 1: Skill Review

When a user asks to install a skill:

  1. Reference reviews/skill-mcp.md
  2. Scan files using patterns/red-flags.md
  3. Output report using templates/report-skill.md

Example 2: On-Chain Address Review

When a user provides a blockchain address:

  1. Validate address format
  2. Query AML risk data (via available tools)
  3. Output report using templates/report-onchain.md

Contributing

This framework is maintained by SlowMist. Contributions welcome:

  • New attack patterns
  • Improved detection rules
  • Additional review templates

Credits

License

MIT License — Free to use, modify, and distribute.


Security is not a feature — it's a prerequisite. 🛡️

SlowMist · https://slowmist.com

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