AI apps fail secure logging, authors propose spec

The author argues that AI-generated applications frequently lack proper logging and error tracking, often failing to record critical security events like failed authorization checks. Standard twelve-factor logging recommendations focus on routing streams to standard output without specifying payload contents, while platform log retention periods are typically far too short to catch breaches discovered months later. To address this, the article outlines a standardized logging specification detailing specific event groups, required fields, data sanitization rules, and acceptance checks. Open article →