Safeclaw

Universal outbound data guard for AI agents.

Safeclaw catches sensitive data (API keys, passwords, emails, credit cards) before an AI agent accidentally leaks it. Runs on-premise with zero external calls — works for local dev, CI/CD pipelines, and enterprise deployments alike.

Works with any AI agent: Claude Code, OpenClaw, ClaudeClaw, Codex, and more!

pip install safeclaw-guard

Why This Exists

AI agents have access to your codebase, .env files, databases, and configs. When they generate output — a shell command, a file, an API call — they can accidentally include secrets in plaintext. The agent doesn't know it's leaking. Safeclaw stops that at the exit.

In plain English: The AI agent reads your secrets to do its job. Safeclaw makes sure those secrets don't appear in the output.

Block vs Redact

Input:  "Deploy with key sk-ant-api03-realkey123..."
Output: "[SAFECLAW BLOCKED] contains sensitive data: Anthropic API Key"

Input:  "Send report to john@acme.com and call 555-867-5309"
Output: "Send report to [REDACTED:EMAIL] and call [REDACTED:PHONE]"

Configurable per entity type — API keys block, emails redact. Your call.

Get Started

Safeclaw supports multiple integration methods depending on your agent and workflow:

🤖 MCP-Compatible Agents (Claude Code, OpenClaw, ClaudeClaw, etc.)

pip install safeclaw-guard
safeclaw install --mcp

Your MCP-compatible agent can now use Safeclaw's safeclaw_scan and safeclaw_detect tools automatically.

🐍 Python Code (Any Python Agent)

from safeclaw import guard

result = guard("Contact john@acme.com with key sk-ant-api03-abc123...")
print(result.safe)      # False
print(result.blocked)   # True — API key detected
print(result.text)      # [SAFECLAW BLOCKED] ...

🌐 HTTP API (Any Language, Any Agent)

safeclaw serve   # starts on localhost:18791

curl -X POST http://127.0.0.1:18791/scan \
  -H "X-Safeclaw-Secret: <secret>" \
  -d '{"text": "your text here"}'

💻 CLI Tool (Shell Scripts, CI/CD, Hooks)

pip install safeclaw-guard
safeclaw install  # For Claude Code specifically

# Or use directly:
echo "some text" | safeclaw scan
safeclaw scan < file.txt

What It Detects

Architecture

• Pipeline pattern (spaCy/sklearn-inspired) — pluggable detectors. Ships with RegexDetector, drop in an ML model later without changing any code.
• Pydantic v2 models — typed Span, Entity, GuardResult following NER conventions.
• Confidence scoring — every match has a score (0.0–1.0). Only flags above your threshold.
• Overlap resolution — when two patterns match the same span, highest confidence wins.

Configuration

safeclaw init    # creates .safeclaw.yaml

threshold: 0.75       # confidence cutoff
fail_open: true       # if error: pass through (true) or block (false)

rules:
  api_key:    { action: block,  enabled: true }
  email:      { action: redact, enabled: true }
  phone:      { action: redact, enabled: true }
  ip_address: { action: redact, enabled: false }  # too noisy

Commands

Try It

git clone https://github.com/wassupjay/SafeClaw.git && cd SafeClaw
python -m venv .venv && source .venv/bin/activate
pip install -e .
python demo.py

  Clean text          → ✅ PASS
  Email               → 🟡 REDACT  [REDACTED:EMAIL]
  Phone               → 🟡 REDACT  [REDACTED:PHONE]
  JWT                 → 🟡 REDACT  [REDACTED:JWT]
  OpenAI key          → 🔴 BLOCK
  Anthropic key       → 🔴 BLOCK
  AWS key             → 🔴 BLOCK
  GitHub token        → 🔴 BLOCK
  Stripe key          → 🔴 BLOCK
  Password            → 🔴 BLOCK
  Credentials in URL  → 🔴 BLOCK
  SSN                 → 🔴 BLOCK
  Credit card         → 🔴 BLOCK
  PEM private key     → 🔴 BLOCK
  16/16 tests passed

License

MIT