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BytesAgain β€Ί Skills β€Ί Security Checker
πŸ¦€ ClawHub

Security Checker

by @johstracke

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.

Versionv1.0.1
Downloads1,754
Installs2
#coding#legal
TERMINAL
clawhub install security-checker

πŸ“– About This Skill

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

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

    βœ… "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

    • πŸ”΄ "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: πŸ”΄ 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: βœ… 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=$1
    echo "πŸ”’ Running security scan..."
python3 /path/to/security_scan.py "$SKILL_PATH"
    if [ $? -ne 0 ]; then
    echo "❌ Cannot publish: Security scan failed"
    exit 1
fi
    echo "βœ… Security scan passed"
clawhub publish "$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

    βœ… All clear
    task-runner  
    
security_scan.py /home/ubuntu/.openclaw/workspace/skills/task-runner

    βœ… All clear
    security-checker
    
security_scan.py /home/ubuntu/.openclaw/workspace/skills/security-checker

    βœ… All clear

    All three skills passed security scans before publishing to ClawHub.

    πŸ’‘ 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: πŸ”΄ 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: βœ… No issues

    πŸ“‹ Tips & 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