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MCP and security

PII Masker

Automatically detect and redact personally identifiable information (PII) from AI prompts before sending to external LLM APIs. Detects names, emails, phone numbers, SSNs, credit card numbers, addresses, and custom PII patterns. Essential for GDPR, HIPAA, and SOC 2 compliance in AI applications.

Run PII Masker Interactively 100% client-side execution in your browser. Zero data retention.
Open Interactive Tool

What Problem Does This Solve?

Transmitting user PII (names, SSNs, credit cards, emails, medical IDs) to third-party foundation models creates severe GDPR, HIPAA, and CCPA compliance violations.

Technical Methodology & How It Works

Identifies sensitive entity types using client-side regex and heuristic NER, replacing them with reversible cryptographic tokens before model ingestion.

Primary Production Use Cases

  • Remove PII from customer support prompts before sending to OpenAI
  • HIPAA-compliant AI deployment

Engineering Limitations & Scope

Designed for structured and semi-structured PII entities; highly ambiguous context-dependent entities should be verified with secondary checks.

Data Privacy & Cryptographic Isolation

100% client-side redaction. Sensitive text never leaves the developer's device unmasked.

Frequently Asked Questions

Can masked tokens be de-anonymized after model completion?

Yes, the tool generates a reversible mapping dictionary kept exclusively in local memory.

Does it support custom regex patterns?

Yes, you can define custom regex rules for proprietary internal ID formats.

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