CloakClaw

cloakclaw

by canonflip-git

>

3.9k其他未扫描2026年3月30日

安装

npm install -g cloakclaw

文档

CloakClaw — Always-On Privacy Proxy

Prerequisites

bash
# Required
npm install -g cloakclaw

# Optional but recommended
brew install poppler       # Better PDF text extraction
ollama pull qwen2.5:7b     # AI-powered name/company detection

Verify: cloakclaw --version should return 0.1.2 or higher.

How It Works

  1. Detect: When user sends a document or sensitive text, auto-detect the document type
  2. Cloak: Run the cloaking engine (regex + local LLM) to replace sensitive entities with realistic fakes
  3. Send: Forward cloaked text to the cloud LLM for analysis
  4. Decloak: When response arrives, reverse all replacements to restore originals
  5. Deliver: Send the restored response to user with a privacy footer

Entity Types (24)

CategoryTypes
IdentityPeople, Companies, Passports, Drivers License
ContactEmails, Phones, Addresses
FinancialDollars, Percentages, Accounts, Banks, SSNs
LegalCase Numbers, Jurisdictions
TechIP Addresses, MAC Addresses, Passwords/Secrets, API Keys, URLs
OtherCrypto Wallets, GPS Coordinates, VIN Numbers, Medical IDs, Dates

Profiles (6)

  • general — all 24 types (default for unknown documents)
  • legal — contracts, NDAs, filings (10 types)
  • financial — bank statements, P&L, investor docs (11 types)
  • email — correspondence (10 types)
  • code — .env files, configs, infra docs (9 types)
  • medical — HIPAA-adjacent records (11 types)

Auto-Detection Rules

Always cloak (document attached):

  • PDF, TXT, MD, CSV, JSON, YAML, code files → auto-detect profile from content
  • Legal keywords (agreement, contract, whereas, hereby) → legal profile
  • Financial keywords (revenue, P&L, balance sheet, quarterly) → financial profile
  • Code files (.env, .yaml, .json with secrets) → code profile
  • Default for unrecognized → general profile

Always cloak (sensitive content in text):

  • Contains SSN patterns (###-##-####)
  • Contains dollar amounts > $1,000
  • Contains multiple proper names + company names
  • Contains IP addresses, API keys, or passwords
  • User explicitly says "cloak", "private", "redact", or "protect"

Skip cloaking:

  • Simple questions with no sensitive data
  • User says "raw", "uncloak", "no cloak", or "cloakclaw off"

Execution Flow

Step 1: Cloak the document

bash
node scripts/cloak.js --profile <general|legal|financial|email|code|medical> --input /path/to/file

Output JSON:

json
{
  "sessionId": "a5cc1496-15b9-4b43-8506-3ea75dfe1304",
  "cloaked": "...cloaked text...",
  "entityCount": 20,
  "profile": "legal"
}

Or use the CLI directly:

bash
cloakclaw cloak document.pdf --profile legal -o cloaked.txt

Step 2: Send cloaked text to cloud LLM

Use the cloaked text as the document content. The user's question stays unchanged — only the document data is cloaked.

Step 3: Decloak the response

bash
node scripts/decloak.js --session <sessionId> --input /path/to/response.txt

Or CLI:

bash
cloakclaw decloak -s <sessionId> -f response.txt

Output: restored text with original entities.

Step 4: Deliver with privacy footer

Append to the response:

code
🔒 CloakClaw: {entityCount} entities protected | Profile: {profile} | Session: {sessionId_short}

User Commands

  • cloakclaw off — disable auto-cloaking for this session
  • cloakclaw on — re-enable auto-cloaking
  • cloakclaw status — show current settings and recent sessions
  • cloakclaw diff <sessionId> — show what was cloaked

Configuration

Config at ~/.cloakclaw/config.yaml:

yaml
ollama:
  url: http://localhost:11434
  model: qwen2.5:7b

Recommended Models by RAM

RAMModelQuality
8GBqwen2.5:3bBasic (regex does most work)
16GBqwen2.5:7bGood
32GB+qwen2.5:32bVery good
64GB+qwen2.5:72bExcellent

Security

  • AES-256-GCM encrypted mapping database
  • Optional password protection (cloakclaw password set)
  • Auto-expiry: sessions purged after 7 days
  • Zero telemetry, zero cloud dependency for cloaking
  • All processing runs locally

⚠️ Disclaimer

CloakClaw is NOT HIPAA, GDPR, SOC 2, PCI-DSS, or CCPA compliant. It is a best-effort privacy tool. Users are responsible for reviewing cloaked output before sharing.

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