At BlackHat: Hell is Other People’s Machine Learning

The article reports on Endgame and University of Virginia research demonstrating that an AI agent can be trained via a game-like process to produce functionally equivalent malware variants that evade machine-learning-based detectors by exploiting model blind spots (e.g., unpacking, adding extraneous sections); the researchers plan to open-source the training code to help improve detection robustness.