Traditional security controls like MFA and PAM are bypassed easily by threat actors on a regular basis. Threat actors prefer breaking into organizations using legitimate credentials so they can achieve their goals undetected, often until it is too late. To combat this growing threat, organizations now need to find a way to accurately detect and respond to identity threats targeting their applications beyond the point of login.

Reveal Security recently spoke with cybersecurity expert and veteran CISO Jim Routh, who led security at numerous companies including MassMutual, Aetna, and American Express where he built custom solutions to address this very issue. Jim explains how unsupervised machine learning-based behavioral analytics can reduce risk by delivering the most accurate threat detection possible.