This repository is an awesome-style curated list of adversarial machine learning resources, referencing foundational papers such as Goodfellow’s Explaining and Harnessing Adversarial Examples (2015) and Szegedy’s Intriguing properties of neural networks (2014). It aggregates blogs, papers, and talks covering attacks, defenses, and robust optimization for ML systems. The author notes it is now deprecated and no longer kept up-to-date, but it remains a reference starting point for the field.