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Clawsec Scanner

OrganizationPopular
prompt-security
clawsec-scanner

Automated vulnerability scanner for agent platforms. Performs dependency scanning (npm audit, pip-audit), multi-database CVE lookup (OSV, NVD, GitHub Advisory), SAST analysis (Semgrep, Bandit), and agent-specific static hook inspection for OpenClaw hooks.

Overview

Publisherprompt-security
Repositoryclawsec
Skill nameclawsec-scanner
Stars
1.1K
Forks
112
Bundled files
20
LicenseAGPL-3.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 20 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by prompt-security on GitHub. Read the source before you install it.

Installation

Install the Clawsec Scanner AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/prompt-security/clawsec/tree/main/skills/clawsec-scanner
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/prompt-security/clawsec.git /tmp/clawsec
mkdir -p .claude/skills
cp -r /tmp/clawsec/skills/clawsec-scanner .claude/skills/clawsec-scanner
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Clawsec Scanner in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Clawsec Scanner on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Clawsec Scanner is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ClawSec Scanner

Comprehensive security scanner for agent platforms that automates vulnerability detection across multiple dimensions:

  • Dependency Scanning: Analyzes npm and Python dependencies using npm audit and pip-audit with structured JSON output parsing
  • CVE Database Integration: Queries OSV (primary), NVD 2.0, and GitHub Advisory Database for vulnerability enrichment
  • SAST Analysis: Static code analysis using Semgrep (JavaScript/TypeScript) and Bandit (Python) to detect hardcoded secrets, command injection, path traversal, and unsafe deserialization
  • DAST Framework: Agent-specific static analysis of OpenClaw hook metadata and handler source without importing or invoking target code
  • Unified Reporting: Consolidated vulnerability reports with severity classification and remediation guidance
  • Continuous Monitoring: OpenClaw hook integration for automated periodic scanning

Vercel Skills Installation

Install with the Vercel Skills CLI for this harness:

bash
npx skills add prompt-security/clawsec --skill clawsec-scanner -a openclaw -y

Features

Multi-Engine Scanning

The scanner orchestrates four complementary scan types to provide comprehensive vulnerability coverage:

  1. Dependency Scanning

    • Executes npm audit --json and pip-audit -f json as subprocesses
    • Parses structured output to extract CVE IDs, severity, affected versions
    • Handles edge cases: missing package-lock.json, zero vulnerabilities, malformed JSON
  2. CVE Database Queries

    • OSV API (primary): Free, no authentication, broad ecosystem support (npm, PyPI, Go, Maven)
    • NVD 2.0 (optional): Requires API key to avoid 6-second rate limiting
    • GitHub Advisory Database (optional): GraphQL API with OAuth token
    • Normalizes all API responses to unified Vulnerability schema
  3. Static Analysis (SAST)

    • Semgrep for JavaScript/TypeScript: Detects security issues using --config auto or --config p/security-audit
    • Bandit for Python: Leverages existing pyproject.toml configuration
    • Identifies: hardcoded secrets (API keys, tokens), command injection (eval, exec), path traversal, unsafe deserialization
  4. Dynamic Analysis (DAST)

    • Static hook inspection for OpenClaw hook handlers discovered from HOOK.md metadata
    • Verifies coverage and source-level risk signals without importing, transpiling, or invoking target handlers
    • Note: Traditional web DAST tools (ZAP, Burp) do not apply to agent platforms - this provides agent-specific testing

Unified Reporting

All scan types emit a consistent ScanReport JSON schema:

typescript
{
  scan_id: string;         // UUID
  timestamp: string;       // ISO 8601
  target: string;          // Scanned path
  vulnerabilities: Vulnerability[];
  summary: {
    critical: number;
    high: number;
    medium: number;
    low: number;
    info: number;
  }
}

Each Vulnerability object includes:

  • id: CVE-2023-12345 or GHSA-xxxx-yyyy-zzzz
  • source: npm-audit | pip-audit | osv | nvd | github | sast | dast
  • severity: critical | high | medium | low | info
  • package: Package name (or 'N/A' for SAST/DAST)
  • version: Affected version
  • fixed_version: First version with fix (if available)
  • title: Short description
  • description: Full advisory text
  • references: URLs for more info
  • discovered_at: ISO 8601 timestamp

OpenClaw Integration

Automated continuous monitoring via hook:

  • Runs scanner on configurable interval (default: 86400s / 24 hours)
  • Triggers on agent:bootstrap and command:new events
  • Posts findings to event.messages array with severity summary
  • Rate-limited by CLAWSEC_SCANNER_INTERVAL environment variable

Installation

Prerequisites

Verify required binaries are available:

bash
# Core runtimes
node --version  # v20+
npm --version
python3 --version  # 3.10+

# Scanning tools
pip-audit --version  # Install: uv pip install pip-audit
semgrep --version    # Install: pip install semgrep OR brew install semgrep
bandit --version     # Install: uv pip install bandit

# Utilities
jq --version
curl --version

Option A: Via clawhub (recommended)

bash
npx clawhub@latest install clawsec-scanner

Option B: Manual installation with verification

bash
set -euo pipefail

VERSION="${SKILL_VERSION:?Set SKILL_VERSION (e.g. 0.1.0)}"
INSTALL_ROOT="${INSTALL_ROOT:-$HOME/.openclaw/skills}"
DEST="$INSTALL_ROOT/clawsec-scanner"
BASE="https://github.com/prompt-security/clawsec/releases/download/clawsec-scanner-v${VERSION}"

TEMP_DIR="$(mktemp -d)"
trap 'rm -rf "$TEMP_DIR"' EXIT

# Pinned release-signing public key
# Fingerprint (SHA-256 of SPKI DER): 711424e4535f84093fefb024cd1ca4ec87439e53907b305b79a631d5befba9c8
cat > "$TEMP_DIR/release-signing-public.pem" <<'PEM'
-----BEGIN PUBLIC KEY-----
MCowBQYDK2VwAyEAS7nijfMcUoOBCj4yOXJX+GYGv2pFl2Yaha1P4v5Cm6A=
-----END PUBLIC KEY-----
PEM

ZIP_NAME="clawsec-scanner-v${VERSION}.zip"

# Download release archive + signed checksums
curl -fsSL "$BASE/$ZIP_NAME" -o "$TEMP_DIR/$ZIP_NAME"
curl -fsSL "$BASE/checksums.json" -o "$TEMP_DIR/checksums.json"
curl -fsSL "$BASE/checksums.sig" -o "$TEMP_DIR/checksums.sig"

# Verify checksums manifest signature
openssl base64 -d -A -in "$TEMP_DIR/checksums.sig" -out "$TEMP_DIR/checksums.sig.bin"
if ! openssl pkeyutl -verify \
  -pubin \
  -inkey "$TEMP_DIR/release-signing-public.pem" \
  -sigfile "$TEMP_DIR/checksums.sig.bin" \
  -rawin \
  -in "$TEMP_DIR/checksums.json" >/dev/null 2>&1; then
  echo "ERROR: checksums.json signature verification failed" >&2
  exit 1
fi

EXPECTED_SHA="$(jq -r '.archive.sha256 // empty' "$TEMP_DIR/checksums.json")"
if [ -z "$EXPECTED_SHA" ]; then
  echo "ERROR: checksums.json missing archive.sha256" >&2
  exit 1
fi

ACTUAL_SHA="$(shasum -a 256 "$TEMP_DIR/$ZIP_NAME" | awk '{print $1}')"
if [ "$EXPECTED_SHA" != "$ACTUAL_SHA" ]; then
  echo "ERROR: Archive checksum mismatch" >&2
  exit 1
fi

echo "Checksums verified. Installing..."

mkdir -p "$INSTALL_ROOT"
rm -rf "$DEST"
unzip -q "$TEMP_DIR/$ZIP_NAME" -d "$INSTALL_ROOT"

chmod 600 "$DEST/skill.json"
find "$DEST" -type f ! -name "skill.json" -exec chmod 644 {} \;

echo "Installed clawsec-scanner v${VERSION} to: $DEST"
echo "Next step: Run a scan or set up continuous monitoring"

Usage

On-Demand CLI Scanning

bash
SCANNER_DIR="${INSTALL_ROOT:-$HOME/.openclaw/skills}/clawsec-scanner"

# Scan all skills with JSON output
"$SCANNER_DIR/scripts/runner.sh" --target ./skills/ --output report.json --format json

# Scan specific directory with human-readable output
"$SCANNER_DIR/scripts/runner.sh" --target ./my-skill/ --format text

# Check available flags
"$SCANNER_DIR/scripts/runner.sh" --help

CLI Flags:

  • --target <path>: Directory to scan (required)
  • --output <file>: Write results to file (optional, defaults to stdout)
  • --format <json|text>: Output format (default: json)
  • --check: Verify all required binaries are installed

OpenClaw Hook Setup (Continuous Monitoring)

Enable automated periodic scanning:

bash
SCANNER_DIR="${INSTALL_ROOT:-$HOME/.openclaw/skills}/clawsec-scanner"
node "$SCANNER_DIR/scripts/setup_scanner_hook.mjs"

This creates a hook that:

  • Scans on agent:bootstrap and command:new events
  • Respects CLAWSEC_SCANNER_INTERVAL rate limiting (default: 86400 seconds / 24 hours)
  • Posts findings to conversation with severity summary
  • Recommends remediation for high/critical vulnerabilities

Restart the OpenClaw gateway after enabling the hook, then run /new to trigger an immediate scan.

Environment Variables

bash
# Optional - NVD API key to avoid rate limiting (6-second delays without key)
export CLAWSEC_NVD_API_KEY="your-nvd-api-key"

# Optional - GitHub OAuth token for Advisory Database queries
export GITHUB_TOKEN="ghp_your_token_here"

# Optional - Scanner hook interval in seconds (default: 86400 / 24 hours)
export CLAWSEC_SCANNER_INTERVAL="86400"

# Optional - Allow unsigned advisory feed during development (from clawsec-suite)
export CLAWSEC_ALLOW_UNSIGNED_FEED="1"

Architecture

Modular Design

Each scan type is an independent module that can run standalone or as part of unified scan:

scripts/runner.sh              # Orchestration layer
├── scan_dependencies.mjs      # npm audit + pip-audit
├── query_cve_databases.mjs    # OSV/NVD/GitHub API queries
├── sast_analyzer.mjs          # Semgrep + Bandit static analysis
├── dast_runner.mjs            # Static hook inspection orchestration
└── dast_hook_executor.mjs     # Static hook source inspection helper

lib/
├── report.mjs                 # Result aggregation and formatting
├── utils.mjs                  # Subprocess exec, JSON parsing, error handling
└── types.ts                   # TypeScript schema definitions

hooks/clawsec-scanner-hook/
├── HOOK.md                    # OpenClaw hook metadata
└── handler.ts                 # Periodic scan trigger

Fail-Open Philosophy

The scanner prioritizes availability over strict failure propagation:

  • Network failures → emit partial results, log warnings
  • Missing tools → skip that scan type, continue with others
  • Malformed JSON → parse what's valid, log errors
  • API rate limits → implement exponential backoff, fallback to other sources
  • Zero vulnerabilities → emit success report with empty array

Critical failures that exit immediately:

  • Target path does not exist
  • No scanning tools available (all bins missing)
  • Concurrent scan detected (lockfile present)

Subprocess Execution Pattern

All external tools run as subprocesses with structured JSON output:

javascript
import { spawn } from 'node:child_process';

// Example: npm audit execution
const proc = spawn('npm', ['audit', '--json'], {
  cwd: targetPath,
  stdio: ['ignore', 'pipe', 'pipe']
});

// Handle non-zero exit codes gracefully
// npm audit exits 1 when vulnerabilities found (not an error!)
proc.on('close', code => {
  if (code !== 0 && stderr.includes('ERR!')) {
    // Actual error
    reject(new Error(stderr));
  } else {
    // Vulnerabilities found or success
    resolve(JSON.parse(stdout));
  }
});

Troubleshooting

Common Issues

"Missing package-lock.json" warning

  • npm audit requires lockfile to run
  • Run npm install in target directory to generate
  • Scanner continues with other scan types if npm audit fails

"NVD API rate limit exceeded"

  • Set CLAWSEC_NVD_API_KEY environment variable
  • Without API key: 6-second delays enforced between requests
  • OSV API used as primary source (no rate limits)

"pip-audit not found"

  • Install: uv pip install pip-audit or pip install pip-audit
  • Verify: which pip-audit
  • Add to PATH if installed in non-standard location

"Semgrep binary missing"

  • Install: pip install semgrep OR brew install semgrep
  • Requires Python 3.8+ runtime
  • Alternative: use Docker image returntocorp/semgrep

"DAST static coverage finding"

  • The DAST harness does not execute target hook handlers.
  • JavaScript and TypeScript hook files are read as source and reported with info-level static coverage findings.
  • Review any listed static signals manually when deciding whether a hook needs deeper sandboxed testing.

"Concurrent scan detected"

  • Lockfile exists: /tmp/clawsec-scanner.lock
  • Wait for running scan to complete or manually remove lockfile
  • Prevents overlapping scans that could produce inconsistent results

Verification

Check scanner is working correctly:

bash
# Verify required binaries
./scripts/runner.sh --check

# Run unit tests
node test/dependency_scanner.test.mjs
node test/cve_integration.test.mjs
node test/sast_engine.test.mjs
node test/dast_harness.test.mjs

# Validate skill structure
python ../../utils/validate_skill.py .

# Scan test fixtures (should detect known vulnerabilities)
./scripts/runner.sh --target test/fixtures/ --format text

Development

Running Tests

bash
# All tests (vanilla Node.js, no framework)
for test in test/*.test.mjs; do
  node "$test" || exit 1
done

# Individual test suites
node test/dependency_scanner.test.mjs  # Dependency scanning
node test/cve_integration.test.mjs     # CVE database APIs
node test/sast_engine.test.mjs         # Static analysis
node test/dast_harness.test.mjs        # DAST static hook inspection

Linting

bash
# JavaScript/TypeScript
npx eslint . --ext .ts,.tsx,.js,.jsx,.mjs --max-warnings 0

# Python (Bandit already configured in pyproject.toml)
ruff check .
bandit -r . -ll

# Shell scripts
shellcheck scripts/*.sh

Adding Custom Semgrep Rules

Create custom rules in .semgrep/rules/:

yaml
rules:
  - id: custom-security-rule
    pattern: dangerous_function($ARG)
    message: Avoid dangerous_function - use safe_alternative instead
    severity: WARNING
    languages: [javascript, typescript]

Update scripts/sast_analyzer.mjs to include custom rules:

javascript
const proc = spawn('semgrep', [
  'scan',
  '--config', 'auto',
  '--config', '.semgrep/rules/',  // Add custom rules
  '--json',
  targetPath
]);

Integration with ClawSec Suite

The scanner works standalone or as part of the ClawSec ecosystem:

  • clawsec-suite: Meta-skill that can install and manage clawsec-scanner
  • clawsec-feed: Advisory feed for malicious skill detection (complementary)
  • openclaw-audit-watchdog: Cron-based audit automation (similar pattern)

Install the full ClawSec suite:

bash
npx clawhub@latest install clawsec-suite
# Then use clawsec-suite to discover and install clawsec-scanner

Security Considerations

Scanner Security

  • No hardcoded secrets in scanner code
  • API keys read from environment variables only (never logged or committed)
  • Subprocess arguments use arrays to prevent shell injection
  • All external tool output parsed with try/catch error handling

Vulnerability Prioritization

Critical/High severity findings should be addressed immediately:

  • Known exploits in dependencies (CVSS 9.0+)
  • Hardcoded API keys or credentials in code
  • Command injection vulnerabilities
  • Path traversal without validation

Medium/Low severity findings can be addressed in normal sprint cycles:

  • Outdated dependencies without known exploits
  • Missing security headers
  • Weak cryptography usage

Info findings are advisory only:

  • Deprecated API usage
  • Code quality issues flagged by linters

Roadmap

v0.0.4 (Current)

  • Dependency scanning (npm audit, pip-audit)
  • CVE database integration (OSV, NVD, GitHub Advisory)
  • SAST analysis (Semgrep, Bandit)
  • Static OpenClaw hook inspection for DAST without target code execution
  • Unified JSON reporting
  • OpenClaw hook integration

Future Enhancements

  • Automatic remediation (dependency upgrades, code fixes)
  • SARIF output format for GitHub Code Scanning integration
  • Web dashboard for vulnerability tracking over time
  • CI/CD GitHub Action for PR blocking on high-severity findings
  • Container image scanning (Docker, OCI)
  • Infrastructure-as-Code scanning (Terraform, CloudFormation)
  • Comprehensive agent workflow DAST (requires deeper platform integration)

Contributing

Found a security issue? Please report privately to security@prompt.security.

For feature requests and bug reports, open an issue at: https://github.com/prompt-security/clawsec/issues

License

AGPL-3.0-or-later

See LICENSE file in repository root for full text.

Resources

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Clawsec Scanner AI skill do?

Automated vulnerability scanner for agent platforms. Performs dependency scanning (npm audit, pip-audit), multi-database CVE lookup (OSV, NVD, GitHub Advisory), SAST analysis (Semgrep, Bandit), and agent-specific static hook inspection for OpenClaw hooks.

Why use Clawsec Scanner on TypingMind?

Because you install it once and use it with any model. Clawsec Scanner is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Clawsec Scanner in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/prompt-security/clawsec/tree/main/skills/clawsec-scanner. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Clawsec Scanner?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Clawsec Scanner?

As many as you like. As long as a model supports skills, you can use Clawsec Scanner with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Clawsec Scanner AI skill free?

Yes. It is published on GitHub by prompt-security under the AGPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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