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DevToolKit

PII Detector & Anonymizer

Detect and anonymize personally identifiable information in text. Finds emails, phone numbers, SSNs, credit cards, IPs, IBANs, and more — fully client-side with zero data transmission.

Paste text or click a sample to scan for personal data

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How to Use

Scan text for personal data in three steps:

  1. Paste your text — Enter logs, customer records, documents, or any text that might contain personal information. Click a sample button to try a pre-loaded example.
  2. Configure detection — Toggle individual PII categories on or off. Choose an anonymization mode: Mask (partial obscuring), Redact (block characters), or Label (category tags like [EMAIL]).
  3. Scan and review — Click "Scan for PII" to detect all matches. Review the risk assessment, category breakdown, highlighted original text, and anonymized output. Copy the sanitized text with the clipboard button.

About This Tool

Pattern-Based Detection

The detector uses regular expressions with validation logic to identify 10 categories of structured PII. Each pattern is tuned for precision over recall — it avoids false positives by applying secondary validation. Credit card numbers are verified with the Luhn algorithm (ISO/IEC 7812-1). Social Security Numbers are checked against IRS formatting rules (no 000/666/9xx area codes, no 00 groups, no 0000 serials). IBANs are validated for length and country code format per ISO 13616.

Phone number detection handles US formats (with or without country code, parenthesized area codes, dots/dashes/spaces) and international formats starting with +. Email detection follows RFC 5322 simplified patterns. IPv4 validation ensures each octet is 0-255. Date detection matches common formats (MM/DD/YYYY, DD-MM-YYYY, YYYY-MM-DD) with basic range checking.

Anonymization Modes

Mask mode preserves enough structure for the text to remain readable — email domains show first letters, phone numbers show area code and last four digits, credit cards show last four digits. This is useful for debugging and data sharing where context matters but specific values must be hidden. Redact mode replaces all PII with block characters (█), ensuring zero data leakage. Label mode substitutes category tags like [EMAIL], [SSN], [CREDIT CARD], which is ideal for annotation and training data preparation.

Limitations

Regex-based detection catches structured PII — data that follows predictable formatting patterns. It cannot detect unstructured PII such as person names ("John Smith"), physical addresses ("123 Elm Street"), or medical information. For those, NLP-based named entity recognition (NER) is required. The tool also focuses on English-language patterns; international ID formats beyond IBANs are not covered. For comprehensive data protection compliance, combine automated scanning with manual review. For password security, see Password Generator and Password Strength Tester.

Why Use This Tool

Instant Client-Side Scanning

All detection runs in your browser with zero network calls. This is critical for PII scanning — you should never send personal data to a third-party server just to check if it contains personal data. The regex patterns are embedded in the page code (~3KB). Processing is instantaneous for documents of any practical length.

Common Use Cases

  • Log sanitization: Clean server logs, error reports, and debug output before sharing with vendors, posting to Stack Overflow, or attaching to bug reports.
  • Document review: Scan contracts, spreadsheet exports, and customer correspondence before forwarding to ensure no SSNs, credit cards, or other sensitive data slip through.
  • Data pipeline QA: Verify that ETL pipelines and data exports have properly anonymized personal information before loading into analytics systems.
  • Compliance pre-check: Quickly assess PII exposure in text before a formal GDPR, CCPA, or HIPAA audit. The risk score provides a severity triage.
  • Training data preparation: Use Label mode to annotate text with PII category tags for building machine learning training datasets.

Privacy

100% client-side. Your text never leaves your browser. Related security tools: AES Encrypt/Decrypt, String Obfuscator, File Checksum, and Secure Notes.

FAQ

What types of PII does it detect?
The tool detects 10 categories of PII using regex pattern matching: email addresses, US and international phone numbers, US Social Security Numbers, credit card numbers (with Luhn validation), IPv4 and IPv6 addresses, dates, IBANs (international bank account numbers), URLs, and MAC addresses.
How does anonymization work?
Three modes are available. Mask mode partially obscures data while preserving format (e.g., j***@d***.com). Redact mode replaces data with block characters. Label mode substitutes category tags like [EMAIL] or [SSN]. The original text is never modified — a new anonymized copy is generated.
Does it use AI or machine learning?
No. Detection uses regex pattern matching with validation rules (like the Luhn algorithm for credit cards and SSN area/group validation). This approach catches structured PII patterns with near-zero false positives. It won't detect unstructured PII like person names or free-form addresses — those require NLP models.
Is my text sent to a server?
No. All detection and anonymization runs entirely in your browser using JavaScript. No text, no PII, and no data of any kind is transmitted over the network. The tool works fully offline after the page loads.
Can I use this for GDPR or HIPAA compliance?
The tool can help identify structured PII in documents as a first pass, but it is not a substitute for a comprehensive compliance audit. Regex-based detection cannot catch all PII types (e.g., names, physical addresses, medical record numbers without standard formatting). Always pair automated scanning with human review for compliance workflows.