FAQ

FAQ

General

What is ClawMoat?

ClawMoat is a security layer for AI agents. It scans inputs for prompt injection, detects jailbreak attempts, prevents credential exfiltration, and enforces tool-use policies — all at runtime, with zero dependencies.

Why do AI agents need security?

Modern AI agents have access to shell commands, file systems, browsers, email, and APIs. A prompt injection in an email or web page can hijack an agent into running malicious commands, exfiltrating secrets, or impersonating the user. ClawMoat prevents this.

Is ClawMoat only for OpenClaw?

No. ClawMoat works as a standalone CLI tool and Node.js library. It has first-class OpenClaw integration via the skill system, but you can use it with any AI agent framework — LangChain, AutoGPT, CrewAI, or custom agents.

Does ClawMoat require an API key or cloud service?

No. ClawMoat runs entirely locally with zero external dependencies. The Layer 1 (pattern matching) and Layer 2 (heuristic/ML) detection work offline. Layer 3 (LLM judge) optionally uses your existing LLM API for edge cases.

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Detection

What types of attacks does ClawMoat detect?

• Prompt injection — Attempts to override agent instructions
• Jailbreak — DAN, developer mode, dual persona, and other LLM bypass techniques
• Secret exfiltration — API keys, tokens, credentials in outbound text (30+ patterns)
• PII leakage — Emails, SSNs, phone numbers, credit cards, addresses
• Data exfiltration — curl/wget uploads, DNS tunneling, paste service uploads
• Phishing URLs — Suspicious TLDs, shorteners, typosquatting
• Memory poisoning — Attempts to manipulate agent memory files
• Supply chain — Malicious patterns in third-party agent skills

What is the false positive rate?

ClawMoat is tuned for high precision. Layer 1 pattern matching has near-zero false positives for critical/high severity findings. Medium/low severity findings are intentionally more sensitive and may produce some false positives — these are logged as warnings, not blocks.

Can attackers bypass ClawMoat?

No security tool is 100% effective. ClawMoat significantly raises the bar for attacks. The 3-layer pipeline means an attacker needs to evade pattern matching, ML classification, AND the LLM judge simultaneously. Novel attacks may initially bypass Layer 1, but Layers 2-3 provide defense in depth.

Does ClawMoat slow down my agent?

Layer 1 runs in under 1ms. Layer 2 adds ~50ms. Layer 3 (LLM judge) adds 200ms-2s but is only invoked for ~5% of inputs. For most inputs, total overhead is under 5ms.

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Configuration

Where does ClawMoat look for config?

1. ./clawmoat.yml in the current directory
2. ~/.clawmoat.yml in your home directory
3. Programmatic config via createPolicy()

What's the minimum useful config?

version: 1
detection:
  prompt_injection: true
  secret_scanning: true
policies:
  exec:
    block_patterns: ["rm -rf", "curl * | bash"]
  file:
    deny_read: ["~/.ssh/*", "~/.aws/*"]

Can I use ClawMoat without a config file?

Yes. Without a config file, ClawMoat runs all scanners with default settings. The policy engine is inactive (all tool calls allowed) — only content scanning is performed.

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Integration

How do I use ClawMoat with LangChain?

const { scan } = require('clawmoat');

// Wrap your agent's input processing
function secureInput(text) {
  const result = scan(text);
  if (!result.safe) {
    throw new Error(`Blocked: ${result.findings.map(f => f.type).join(', ')}`);
  }
  return text;
}

// Use in your LangChain chain
const chain = new LLMChain({
  llm,
  prompt,
  inputModifier: secureInput,
});

How do I add ClawMoat to my CI/CD pipeline?

# In your CI script
clawmoat audit --badge
# Exit code 1 if threats found — fails the build

Does ClawMoat work with TypeScript?

ClawMoat is written in JavaScript but includes JSDoc type annotations. TypeScript projects can use it directly. Full .d.ts type definitions are planned for v0.3.

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Project

What's the license?

MIT — free forever, for any use.

How do I contribute?

Open an issue or submit a PR. All contributions welcome.

What's on the roadmap?

• v0.2 — TypeScript rewrite, plugin API
• v0.3 — Behavioral anomaly detection, ML classifier models
• v0.4 — Multi-agent delegation policies, real-time dashboard
• v1.0 — Stable API, comprehensive test suite, full OWASP coverage

How do I report a security vulnerability?

See our Security Policy. Email security@clawmoat.com for responsible disclosure.