Explore an innovative approach to dynamic taint analysis using neural networks in this IEEE conference talk. Delve into the limitations of traditional rule-based DTA and discover how Neutaint offers a more efficient method for tracking taint information. Learn about data collection techniques, influence analysis through gradient computation, and the evaluation process. Examine case studies on overtaint and runtime overhead, and understand the application of this technology in exploit analysis and fuzzing. Investigate the performance of different ML models and the impact of training data on information loss. Gain insights into this cutting-edge technique that promises to revolutionize dynamic taint analysis in the field of computer security.