Security vulnerability analysis of code based on machine learning and variable usage
AssigneeInternational Business Machines Corporation
InventorsLi Bo Zhang, Zhuo Zhao, Ming Qian Wang, Jia Ning Li
Life of this patent
Estimating the term…
Loading patent…
AssigneeInternational Business Machines Corporation
InventorsLi Bo Zhang, Zhuo Zhao, Ming Qian Wang, Jia Ning Li
Estimating the term…
According to a present invention embodiment, software is analyzed for security vulnerabilities. Information from a security scan of code is analyzed to identify a security issue pertaining to a code portion. A machine learning model determines an initial risk factor score for the security issue based on a history of information pertaining to one or more prior security scans. The initial risk factor score is refined to produce an overall risk factor score for the security issue based on a confidence of the initial risk factor score. The initial risk factor score is refined based on one or more risk factor scores for operations within the code applied to a variable of the code portion. A classification of the security issue is determined as one of a valid security issue and a false positive based on the overall risk factor score.
A method of analyzing software for security vulnerabilities comprising:
A system for analyzing software for security vulnerabilities comprising:
A computer program product for analyzing software for security vulnerabilities, the computer program product comprising one or more computer readable storage media having program instructions collectively stored on the one or more computer readable storage media, the program instructions executable by at least one processor to cause the at least one processor to:
Dependencies are inferred from the claim text.