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

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• 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.

這是一個用於釋出程式碼前做安全檢查的工具，能發現金鑰洩露、危險函式等問題。文件詳細、使用簡單是主要優點，質量表現中規中矩。不足之處在於：只能檢查 Python 程式碼，容易誤報正常功能，複雜場景下檢測能力有限，且無法靈活調整檢測規則。對於需要深度安全檢測的使用者來說，這個工具可能不夠滿足需求。