targeting developers and DevOps engineers building privacy-compliant systems.
The Challenge
Application and API logs frequently capture personal data incidentally: user IDs, email addresses, IP addresses, partial account numbers, names from user input validation errors, and session identifiers. Developers need these logs for debugging but cannot share raw logs with third-party support providers, external contractors, or even internal teams without appropriate access — all of whom may not have legal basis to access user personal data. The GDPR principle of data minimization applies to log data as much as to application data. The challenge: JSON log structures are deeply nested and variable — PII entities appear at different paths depending on the API endpoint and error type.
By the Numbers
- The GDPR principle of data minimization applies to log data as much as to application data.
Real-World Scenario
A SaaS company shares application logs with an external penetration testing firm. Raw logs contain 4,200 unique user email addresses and IP addresses. anonym.legal processes 180MB of JSON logs in batch, replacing all email addresses with consistent fake addresses (user1@example.com, user2@example.com) and IP addresses with anonymized IPs. The pen test firm receives logs with full technical context but zero real user data. GDPR compliance for third-party data sharing achieved in 25 minutes.
Technical Approach
Native JSON support with nested structure traversal detects PII at any depth within JSON documents. Email addresses, IPs, names, and other entities are detected by content, not path — so the same configuration works across variable log schemas. Technical metadata (timestamps, error codes, stack traces, technical IDs) is preserved. The Replace method substitutes PII with consistent fake values, preserving referential integrity within log files (the same user email replaced with the same fake email across all log entries).
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