MAVIS: Machine Assisted Vulnerability Identification System
12Code review has become what log review was a few years ago; everyone knows they should do it, everyone says they are doing something, but everybody knows they aren't doing enough. In this talk David covers the highlights of MAVIS, a new open source project that can be used to supplement or even guide code review of internal projects. MAVIS is an ML/AI based tool that can be hooked into your CI pipeline to flag code commits that deserve "special attention."
Learn more about SEC595 Applied Data Science and AI/Machine Learning for Cybersecurity Professionals: https://www.sans.org/u/1vzR
About the Speaker
David Hoelzer, a SANS Fellow and author of more than twenty days of SANS courseware, is an expert in a variety of information security fields, having served in most major roles in the IT and security industries over the past twenty-five years. Currently, David serves as the principal examiner and director of research for Enclave Forensics, a New York/Las Vegas based incident response and forensics company. He also serves as the chief information security officer for Cyber-Defense, an open-source security software solution provider.