Evasion of Deep Learning Detector for Malware C&C Traffic

The Palo Alto Networks Security AI research team tested a deep learning model for malware command and control (C&C) traffic detection in HTTP traffic. Based on the publicly available paper by Le et al., we built a model that was trained on a similar dataset as our production model and had similar performance. Then we crafted adversarial samples, queried the model, and adjusted the adversarial sample accordingly until the model was evaded.