Data Anonymizer
OrtasecurityEn az 16K bağlam
Detects and redacts personally identifiable information (PII) and sensitive data from text, logs, and structured datasets. Recommends anonymization techniques such as masking, tokenization, pseudonymization, k-anonymity, and differential privacy, and generates reusable redaction code while preserving analytical utility and referential integrity.
Kullanım alanları
- Redacting PII from application logs before sharing
- Anonymizing datasets for analytics and ML training
- Choosing between masking, tokenization, and pseudonymization
- Building GDPR/HIPAA-compliant data export pipelines
- Generating reusable PII detection and redaction code
Örnek prompt
Anonymize the following customer dataset for use in an analytics environment. Columns: full_name, email, phone, ip_address, date_of_birth, city, purchase_amount Requirements: - Preserve ability to join records across tables (consistent pseudonyms) - Keep city and purchase_amount usable for analysis - Comply with GDPR Provide: 1. Classification of each column by sensitivity 2. Recommended anonymization technique per column 3. Implementation code 4. Residual re-identification risk assessment
Önerilen modeller
Uyumlu araçlar
claude-codecursorkiroany
Modaliteler
Giriş: text, code
→Çıkış: text, code
İlgili Skills
Yazar
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