
AI Spots Critical Microsoft Security Bugs 97% of the Time (venturebeat.com) 41
Microsoft claims to have developed a system that correctly distinguishes between security and non-security software bugs 99% of the time, and that accurately identifies the critical, high-priority security bugs on average 97% of the time. From a report: In the coming months, it plans to open-source the methodology on GitHub, along with example models and other resources. Their work suggests that such a system, which was trained on a data set of 13 million work items and bugs from 47,000 developers at Microsoft stored across AzureDevOps and GitHub repositories, could be used to support human experts. It's estimated that developers create 70 bugs per 1,000 lines of code and that fixing a bug takes 30 times longer than writing a line of code, and that in the U.S., $113 billion is spent annually on identifying and fixing product defects. In the course of architecting the model, Microsoft says that security experts approved the training data and that statistical sampling was used to provide those experts a manageable amount of data to review. The data was then encoded into representations called feature vectors and Microsoft researchers designed the system using a two-step process, in which the model first learned to classify security and non-security bugs and then to apply severity labels -- critical, important, low-impact -- to the security bugs.