modbender guard-scanner 🛡️
Static + runtime security scanner for AI agent skills. 135 static patterns + 26 runtime patterns (5 layers) across 22 categories — zero dependencies. 0.016ms/scan.
When To Use This Skill
- Before installing a new skill from ClawHub or any external source
- After updating skills to check for newly introduced threats
- Periodically to audit your installed skills
- In CI/CD to gate skill deployments
Quick Start
1. Static Scan (Immediate)
Scan all installed skills:
node skills/guard-scanner/src/cli.js ~/.openclaw/workspace/skills/ --verbose --self-exclude
Scan a specific skill:
node skills/guard-scanner/src/cli.js /path/to/new-skill/ --strict --verbose
2. Runtime Guard (OpenClaw Plugin Hook)
Blocks dangerous tool calls in real-time via before_tool_call hook. 26 patterns, 5 layers, 3 enforcement modes.
openclaw hooks install skills/guard-scanner/hooks/guard-scanner
openclaw hooks enable guard-scanner
openclaw hooks list
3. Recommended order
# Pre-install / pre-update gate first
node skills/guard-scanner/src/cli.js ~/.openclaw/workspace/skills/ --verbose --self-exclude --html
# Then keep runtime monitoring enabled
openclaw hooks install skills/guard-scanner/hooks/guard-scanner
openclaw hooks enable guard-scanner
Runtime Guard Modes
Set in openclaw.json → hooks.internal.entries.guard-scanner.mode:
| Mode | Intended Behavior | Current Status |
|---|---|---|
monitor |
Log all, never block | ✅ Fully working |
enforce (default) |
Block CRITICAL threats | ✅ Fully working |
strict |
Block HIGH + CRITICAL | ✅ Fully working |
Threat Categories
| # | Category | What It Detects |
|---|---|---|
| 1 | Prompt Injection | Hidden instructions, invisible Unicode, homoglyphs |
| 2 | Malicious Code | eval(), child_process, reverse shells |
| 3 | Suspicious Downloads | curl|bash, executable downloads |
| 4 | Credential Handling | .env reads, SSH key access |
| 5 | Secret Detection | Hardcoded API keys and tokens |
| 6 | Exfiltration | webhook.site, DNS tunneling |
| 7 | Unverifiable Deps | Remote dynamic imports |
| 8 | Financial Access | Crypto wallets, payment APIs |
| 9 | Obfuscation | Base64→eval, String.fromCharCode |
| 10 | Prerequisites Fraud | Fake download instructions |
| 11 | Leaky Skills | Secret leaks through LLM context |
| 12 | Memory Poisoning* | Agent memory modification |
| 13 | Prompt Worm | Self-replicating instructions |
| 14 | Persistence | Cron jobs, startup execution |
| 15 | CVE Patterns | Known agent vulnerabilities |
| 16 | MCP Security | Tool/schema poisoning, SSRF |
| 17 | Identity Hijacking* | SOUL.md/IDENTITY.md tampering |
| 18 | Sandbox Validation | Dangerous binaries, broad file scope, sensitive env |
| 19 | Code Complexity | Excessive file length, deep nesting, eval density |
| 20 | Config Impact | openclaw.json writes, exec approval bypass |
External Endpoints
| URL | Data Sent | Purpose |
|---|---|---|
| (none) | (none) | guard-scanner makes zero network requests. All scanning is local. |
Security & Privacy
- No network access: guard-scanner never connects to external servers
- Read-only scanning: Only reads files, never modifies scanned directories
- No telemetry: No usage data, analytics, or crash reports are collected
- Local reports only: Output files (JSON/SARIF/HTML) are written to the scan directory
- No environment variable access: Does not read or process any secrets or API keys
- Runtime Guard audit log: Detections logged locally to
~/.openclaw/guard-scanner/audit.jsonl
Model Invocation Note
guard-scanner does not invoke any LLM or AI model. All detection is performed through static pattern matching, regex analysis, Shannon entropy calculation, and data flow analysis — entirely deterministic, no model calls.
Trust Statement
guard-scanner was created by Guava 🍈 & Dee after experiencing a real 3-day identity hijack incident in February 2026. A malicious skill silently replaced an AI agent's SOUL.md personality file, and no existing tool could detect it.
- Open source: Full source code available at https://github.com/koatora20/guard-scanner
- Zero dependencies: Nothing to audit, no transitive risks
- Test suite: 134 tests across 24 suites, 100% pass rate
- Taxonomy: Based on Snyk ToxicSkills (Feb 2026), OWASP MCP Top 10, and original research
- Complementary to VirusTotal: Detects prompt injection and LLM-specific attacks that VirusTotal's signature-based scanning cannot catch
Output Formats
# Terminal (default)
node src/cli.js ./skills/ --verbose
# JSON report
node src/cli.js ./skills/ --json
# SARIF 2.1.0 (for CI/CD)
node src/cli.js ./skills/ --sarif
# HTML dashboard
node src/cli.js ./skills/ --html
License
MIT — LICENSE