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security-checker安全检查员

Agent Skill

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。

总安装

44,628

周安装

1,788

GitHub Stars

公开资料未说明

下载量

14,447
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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