ScrubGuard - Deterministic PII & Secret Scrubber + Reversible LLM Tokenizer

ScrubGuard - Deterministic PII & Secret Scrubber + Reversible LLM Tokenizer

Sub-millisecond, zero-dependency PII & secret redaction with mathematical checksum verification (Luhn Credit Cards, ISO 7064 Mod-97 IBANs, SSA US SSN rules) and Reversible LLM Tokenization.

Strip sensitive data before sending prompts to OpenAI, Anthropic, or logs, and rehydrate [EMAIL_1] / [CREDIT_CARD_1] placeholders in the LLM's response automatically.

• Live API & Playground: https://scrubguard-api.scrubguard.workers.dev
• GitHub Repository: https://github.com/scrubguard-dev/scrubguard
• Support: [email protected]

Features

• Mathematical Checksum Validation: Cuts false positives on order IDs and random numbers using Luhn (Credit Cards), ISO 7064 Mod-97 (IBANs), and SSA Area/Group/Serial validation (US SSNs).
• Secret & API Key Detection: Scrubs leaked OpenAI (sk-proj-...), Anthropic (sk-ant-...), Stripe (sk_live_..., sk_test_..., whsec_...), AWS (AKIA...), GitHub PAT (ghp_..., github_pat_...), Slack, Google API, JWT, and PEM Private Keys.
• Reversible LLM Tokenization: Replaces PII with consistent placeholders ([EMAIL_1], [US_SSN_1]) and returns a vault map so LLM outputs can be restored via rehydrateText or POST /v1/rehydrate.
• Deep JSON Sanitizer: Recursively scrubs strings and sensitive keys (password, secret, api_key, ssn) up to 32 levels deep without breaking JSON schemas.
• Linear-Time Regex Engine: Disjoint character classes and bounded repetitions prevent catastrophic backtracking (ReDoS).

Quick Start (Hosted Edge API)

1. Scrub & Tokenize Prompt Before Sending to an LLM (POST /v1/scrub)

curl -X POST https://scrubguard-api.scrubguard.workers.dev/v1/scrub \
  -H "Content-Type: application/json" \
  -d '{
    "text": "Refund customer [email protected] on card 4532 0151 1283 0366 (SSN 412-55-9821)",
    "mode": "tokenize"
  }'

Response:

{
  "output": "Refund customer [EMAIL_1] on card [CREDIT_CARD_1] (SSN [US_SSN_1])",
  "findings_count": 3,
  "findings_by_type": {
    "CREDIT_CARD": 1,
    "US_SSN": 1,
    "EMAIL": 1
  },
  "vault": {
    "[CREDIT_CARD_1]": "4532 0151 1283 0366",
    "[US_SSN_1]": "412-55-9821",
    "[EMAIL_1]": "[email protected]"
  }
}

2. Rehydrate LLM Output (POST /v1/rehydrate)

curl -X POST https://scrubguard-api.scrubguard.workers.dev/v1/rehydrate \
  -H "Content-Type: application/json" \
  -d '{
    "text": "Processed refund for [EMAIL_1] ending in [CREDIT_CARD_1].",
    "vault": {
      "[CREDIT_CARD_1]": "4532 0151 1283 0366",
      "[EMAIL_1]": "[email protected]"
    }
  }'

Node.js / Edge SDK (ScrubGuardClient)

import { ScrubGuardClient } from 'scrubguard-mcp'; // npm install scrubguard-mcp

const guard = new ScrubGuardClient({
  apiKey: process.env.SCRUBGUARD_API_KEY, // Optional: uses hosted Pro Edge API (100k req/mo)
});

// 1. Scrub user prompt
const { output: safePrompt, vault } = await guard.scrub(
  'Email [email protected] with key AKIAIOSFODNN7EXAMPLE'
);

// 2. Send `safePrompt` to OpenAI / Anthropic...
const llmResponse = `Sent confirmation to ${safePrompt.match(/\[EMAIL_\d+\]/)[0]}.`;

// 3. Restore original values
const { output: finalReply } = await guard.rehydrate(llmResponse, vault);

Model Context Protocol (MCP) Server for Claude Desktop & Cursor

ScrubGuard runs locally by default with no network calls. Add it to your claude_desktop_config.json or .cursor/mcp.json:

{
  "mcpServers": {
    "scrubguard": {
      "command": "npx",
      "args": ["-y", "scrubguard-mcp"]
    }
  }
}

To use the optional hosted Pro API, or to run from a local clone:

{
  "mcpServers": {
    "scrubguard": {
      "command": "node",
      "args": ["/path/to/scrubguard/mcp/index.js"],
      "env": {
        "SCRUBGUARD_API_KEY": "sg_live_optional_pro_key"
      }
    }
  }
}

Exposes three MCP tools to your AI assistant:

• scrub_text: Scrub or reversibly tokenize PII & secrets in text.
• rehydrate_text: Restore [TOKEN_1] placeholders using the vault map.
• scrub_json: Recursively sanitize nested JSON objects and logs.

Support & Contact

Questions, bug reports, or higher volume plans: [email protected]