Key Facts
- Category
- Data Processing
- Input Types
- textarea, select, checkbox, number
- Output Type
- json
- Sample Coverage
- 4
- API Ready
- Yes
Overview
The PII Finder scans text or log files to detect and annotate personally identifiable information (PII) such as email addresses, phone numbers, and credit card numbers. It outputs a JSON report with the positions and types of detected PII, aiding in redaction and compliance checks.
When to Use
- •When auditing text or logs for sensitive personal data before sharing or processing.
- •To ensure compliance with privacy regulations like GDPR by identifying PII in datasets.
- •When anonymizing data for testing or analysis to prevent exposure of real personal information.
How It Works
- •Input the text or log content into the text area.
- •Select the types of PII to scan for, such as emails, phones, or credit cards, from the dropdown.
- •Optionally, enable context inclusion to see surrounding characters for each match.
- •The tool processes the input and returns a JSON object listing all detected PII with their types and positions.
Use Cases
Scanning server logs to identify and redact IP addresses and API keys for security audits.
Checking customer support transcripts for email addresses and phone numbers before archiving.
Validating data exports to ensure no credit card numbers or SSNs are included for compliance.
Examples
1. Audit Email Logs for PII
Security Analyst- Background
- A security analyst needs to review email server logs to ensure no sensitive information is exposed.
- Problem
- Manually scanning logs for email addresses and phone numbers is time-consuming and error-prone.
- How to Use
- Paste the log content into the text input, select 'email' and 'phone' from the scan types, and include context for better analysis.
- Example Config
-
scanTypes: ["email", "phone"], includeContext: true - Outcome
- The tool returns a JSON report highlighting all email addresses and phone numbers found, with their positions and surrounding context.
2. Redact Credit Cards from Documents
Data Privacy Officer- Background
- Before sharing a document externally, a data privacy officer needs to remove any credit card numbers.
- Problem
- Credit card numbers might be embedded in text, and manual redaction risks missing some.
- How to Use
- Upload or paste the document text, choose 'creditCard' in the scan types, and run the scan.
- Outcome
- A list of credit card numbers with their locations is generated, allowing for precise redaction.
Try with Samples
textLog Files with Sensitive Data
Sample log files containing various types of PII (Personally Identifiable Information) for testing PII detection and log redaction tools
matched family text
Text with Sensitive Data Samples
Text containing various types of sensitive data for testing data masking (phones, emails, ID cards, bank cards)
matched family text
US SSN Samples
Collection of US Social Security Number formats for validation testing
matched family text
Web Data Serialization Rust Samples
Web Rust data serialization examples including JSON serialization, deserialization, and XML parsing
matched family text
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FAQ
What PII types can the tool detect?
It can detect emails, phone numbers, SSNs, credit cards, IPs, URLs, passports, ID cards, bank accounts, and API keys.
Is the text I input stored or shared?
The tool processes text locally in your browser and does not store or transmit your data.
Can I customize which PII types to scan?
Yes, you can select specific PII types from the dropdown to focus the scan on relevant data.
What does the output look like?
The output is a JSON array with objects containing the type, matched text, start and end positions, and optional context.
How accurate is the detection?
The tool uses pattern matching for common PII formats, but accuracy may vary based on text quality and format.