Using ML models to detect and stop authorization bypass vulnerabilities | Juan Berner | NULLCON

This talk addresses authorization bypass vulnerabilities, a prevalent issue in web applications. The speaker, Juan Berner, discusses how these vulnerabilities can arise from inadequate authorization controls, allowing unauthorized users to access sensitive data. He emphasizes the importance of mitigating alert fatigue in detection systems and introduces techniques for leveraging open-source machine learning tools to enhance vulnerability detection and prevention. With over nine years of experience in security, Berner focuses on developing strategies that can effectively block unauthorized access before data breaches occur.