Predicting Exploitability - Forecasts for Vulnerability Management

Explore predictive models for vulnerability management in this 42-minute RSA Conference talk. Learn how to forecast which vulnerabilities are likely to be exploited using open-source data and machine learning. Discover the speaker's 90% accurate model for predicting exploitability on the day a vulnerability is released. Gain insights into evaluating machine learning models in the context of vulnerabilities and exploits, selecting appropriate models, and asking the right questions. Witness live forecasts and understand the future of data-driven security. Delve into topics such as CVSS, positive predictive value of remediation, and the role of AWS ML in vulnerability prediction. Examine various models, including the "Highly Likely" and "Most Likely" approaches, and understand how to measure their performance. Explore the importance of patches, affected software, and vulnerability prevalence in predicting exploitability. Gain valuable takeaways on leveraging machine learning for more effective vulnerability management and staying ahead of fast-moving attackers.