Low False Positive Token Identification in Source Code Repositories using Machine Learning
AssigneeSap SE
InventorsSlim Trabelsi, Sofiane Lounici, Marco Rosa, Carlo Maria Negri
Life of this patent
Estimating the term…
Abstract
Source code is scanned to generate a list of vulnerable tokens. Thereafter, the list of vulnerable tokens is inputted into a machine learning model to identify false positives in the list of vulnerable tokens. Based on this identification, the list of vulnerable tokens can be modified to remove the identified false positives. Related apparatus, systems, techniques and articles are also described.
Claims20
A computer-implemented method comprising:
- scanning source code to generate a list of vulnerable tokens;
- inputting, the list of vulnerable tokens, into a machine learning model to identify false positives in the list of vulnerable tokens;
- and
- modifying the list of vulnerable tokens to remove the identified false positives.
A system comprising:
- at least one data processor;
- and
- memory storing instructions which, when executed by the at least one data processor, result in operations comprising:
- scanning source code to generate a list of vulnerable tokens;
- inputting, the list of vulnerable tokens, into a machine learning model to identify false positives in the list of vulnerable tokens;
- and
- modifying the list of vulnerable tokens to remove the identified false positives.
A non-transitory computer program product storing instructions which, when executed by at least one computing device, result in operations comprising:
- scanning source code to generate a list of vulnerable tokens;
- inputting, the list of vulnerable tokens, into a machine learning model to identify false positives in the list of vulnerable tokens;
- and
- modifying the list of vulnerable tokens to remove the identified false positives.
Dependencies are inferred from the claim text.