Explore a groundbreaking machine learning classifier for data-driven vulnerability prioritization in this Black Hat conference talk. Delve into the complexities of modern technology stacks, increasing vulnerability volumes, and the challenges of effective remediation strategies. Learn about measuring coverage and efficiency in vulnerability management, current attacker velocities, and the case for predictive approaches. Gain insights into machine learning applications for cybersecurity, including data sources, algorithm types, and supervised classification. Discover how probability can be leveraged to improve decision-making in vulnerability and risk management, and witness live predictions and fulfillments during this 50-minute session presented by Kenna researchers Michael Roytman and Jonathan Cran.