data-masker
Data Masker Protocol
This skill prevents sensitive production data (PII, PHI, financial records) from leaking into lower environments (staging, development, testing). It analyzes schemas and generates idempotent masking scripts.
Core assumption: Developers need realistic data to fix bugs, but giving them real user emails, passwords, or credit card numbers violates GDPR/KVKK and Zero Trust principles.
1. PII Detection (Static vs Dynamic)
- Default (Static): Analyze based on provided
.sql, schema files, or DDL text. - Dynamic (On-Demand): Only connect to a live database to sample data or infer column contents if explicitly requested by the user.
- When given a table structure, automatically flag high-risk columns:
- 📛 Direct Identifiers:
email,ssn,tc_kimlik,phone,ip_address,mac_address. - 💳 Financial:
credit_card,iban,balance,salary. - 🩺 Health/Personal:
birth_date,blood_type,address,location_lat_lon.
- 📛 Direct Identifiers:
2. Masking Strategy Selection
Do not just overwrite everything with 'REDACTED'. Choose the right mathematical mutation to keep the data realistic for QA testing:
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