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Agent Skill · 研究检索

security-checker(安全检查员)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

security-checker 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 3,391。

总安装 44,628周安装 1,788GitHub Stars 公开资料未说明下载 14,447核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.1

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:security-checker(安全检查员)
来源仓库:https://github.com/johstracke/security-checker
安装命令:
openclaw skills install security-checker
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install security-checker

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

在发布到 ClawHub 之前对 Python 技能进行安全扫描。在发布任何技能之前使用它来检查危险的导入、硬编码的机密、不安全的文件操作以及 eval/exec/subprocess 等危险函数。对于维护信任和确保已发布的技能可供其他人安全安装和运行至关重要。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install security-checker;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

security-checker 怎么安装?

在终端执行 openclaw skills install security-checker。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

security-checker 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

security-checker 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

security-checker 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

security-checker 用的人多吗?

公开数据是累计安装 44,628 次,近一周安装 1,788 次,下载 14,447 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

security-checker 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
security-checker

安全检查员 · 本页

44,628—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
security-checker
description
Security scanner for Python skills before publishing to ClawHub. Use before publishing any skill to check for dangerous imports, hardcoded secrets, unsafe file operations, and dangerous functions like eval/exec/subprocess. Essential for maintaining trust and ensuring published skills are safe for others to install and run.

Security Checker

Security scan Python skills before publishing to ensure code safety.

Quick Start

security_scan.py <file_or_directory>

Examples:

# Scan a single Python file
security_scan.py scripts/my_script.py

# Scan an entire skill directory
security_scan.py /path/to/skill-folder

# Scan multiple skills
security_scan.py skills/

What It Checks

Dangerous Imports

Detects imports that could be used maliciously:

  • os - System-level operations
  • subprocess - Command execution
  • shutil - File operations
  • socket - Network operations
  • urllib / requests - HTTP requests

Why dangerous? These imports enable system command execution, file manipulation, and network access that could be exploited.

Dangerous Functions

Detects potentially unsafe function calls:

  • os.system() - Executes shell commands
  • subprocess.call(), subprocess.run(), subprocess.Popen() - Command execution
  • eval() - Executes arbitrary code
  • exec() - Executes arbitrary code

Why dangerous? These can execute arbitrary commands or code, leading to remote code execution vulnerabilities.

Hardcoded Secrets

Detects tokens, keys, and passwords:

  • API keys
  • Auth tokens (including ClawHub tokens)
  • Passwords
  • Private keys
  • JWT-like tokens

Why dangerous? Secrets leaked in published code can be stolen and abused.

Unsafe File Operations

Detects risky file access patterns:

  • Absolute file paths outside expected directories
  • Parent directory traversal (..)
  • Writing to system directories

Why dangerous? Could lead to unintended file access, data loss, or system modification.

Usage Pattern: Pre-Publish Checklist

Before publishing any skill:

# 1. Run security scan
security_scan.py /path/to/skill

# 2. Review any warnings
# If warnings appear, fix the code or document why it's safe

# 3. Re-scan after fixes
security_scan.py /path/to/skill

# 4. Only publish if scan passes
clawhub publish /path/to/skill --slug my-skill ...

Interpretation of Results

✅ "No security issues found"

Code appears safe. Proceed with publishing.

⚠️ "Warning" (Yellow)

Potentially risky pattern detected. Review the specific line and decide:

  • Is it legitimate? Document why in code comments or SKILL.md
  • Can it be avoided? Refactor to safer alternatives
  • Is it necessary? Clearly document the risk and purpose

🔴 "Possible hardcoded secret"

Secret detected. Before publishing:

  • Remove the secret
  • Use environment variables instead: os.getenv('API_KEY')
  • Document required env variables in SKILL.md
  • Never commit real secrets

Examples

Legitimate os module usage (documented)

import os  # Used only for path.join() - safe file path construction
workspace = os.path.join(os.path.expanduser("~"), ".openclaw", "workspace")

Scan result: ⚠️ Warning about os import Action: Document safe usage pattern in code comments

Hardcoded secret (must fix)

API_KEY = "sk-1234567890abcdef"  # DON'T DO THIS

Scan result: 🔴 Possible hardcoded secret Action: Remove and use environment variable:

API_KEY = os.getenv("MY_SKILL_API_KEY")
# Document in SKILL.md: Requires MY_SKILL_API_KEY environment variable

Safe pattern (no issues)

# JSON storage for local data only
data = {"notes": [], "metadata": {}}
with open("data.json", "w") as f:
    json.dump(data, f)

Scan result: ✅ No issues

Best Practices

  1. Always scan before publishing - Make it part of your workflow
  2. Review warnings manually - The scanner can't judge context
  3. Use environment variables for secrets - Never hardcode
  4. Prefer json over eval - Safe parsing vs code execution
  5. Document necessary risks - If dangerous code is required, explain why
  6. Minimize dangerous imports - Only use what's truly necessary
  7. Keep code simple - Complex code is harder to audit

Integration with Development Workflow

Before committing to repo

# Pre-commit hook concept
python3 /path/to/security_scan.py scripts/
if [ $? -ne 0 ]; then
    echo "❌ Security scan failed. Fix issues before committing."
    exit 1
fi

Automated pre-publish check

#!/bin/bash
# publish-safe.sh

SKILL_PATH=$1

echo "🔒 Running security scan..."
python3 /path/to/security_scan.py "$SKILL_PATH"

if [ $? -ne 0 ]; then
    echo "❌ Cannot publish: Security scan failed"
    exit 1
fi

echo "✅ Security scan passed"
clawhub publish "$SKILL_PATH"

Limitations

This scanner:

  • Can't judge context - Some dangerous code may be legitimate
  • Static analysis only - Doesn't execute code
  • Python-focused - Other languages need different tools
  • Basic patterns - Sophisticated obfuscation may evade detection

Complement with:

  • Manual code review
  • Testing in isolated environment
  • Reading through all code before publishing
  • Using additional tools: bandit, safety

Trust Building

Publishing skills that pass security scans builds trust in the community:

  • Users know you care about safety
  • Your reputation improves
  • Skills get adopted more readily
  • ClawHub may highlight safe skills

Examples of Published Skills (All Scanned)

# research-assistant
security_scan.py /home/ubuntu/.openclaw/workspace/skills/research-assistant
# ✅ All clear

# task-runner  
security_scan.py /home/ubuntu/.openclaw/workspace/skills/task-runner
# ✅ All clear

# security-checker
security_scan.py /home/ubuntu/.openclaw/workspace/skills/security-checker
# ✅ All clear

All three skills passed security scans before publishing to ClawHub.

平台分布

OpenClaw

88.55%
按下载量换算12,793

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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