Assessing Validity of Static Analysis Warnings using Ensemble Learning

no code implementations • 21 Apr 2021 • Anshul Tanwar, Hariharan Manikandan, Krishna Sundaresan, Prasanna Ganesan, Sathish Kumar Chandrasekaran, Sriram Ravi

Though the SA tools uncover many hidden bugs, they are lost in the volume of fake warnings reported.

Ensemble Learning

Multi-context Attention Fusion Neural Network for Software Vulnerability Identification

no code implementations • 19 Apr 2021 • Anshul Tanwar, Hariharan Manikandan, Krishna Sundaresan, Prasanna Ganesan, Sathish Kumar Chandrasekaran, Sriram Ravi

Besides a novel way of efficiently detecting code vulnerability, an additional novelty in this model is to exactly point to the code sections, which were deemed vulnerable by the model.

C++ code Vulnerability Detection

Predicting Vulnerability In Large Codebases With Deep Code Representation

no code implementations • 24 Apr 2020 • Anshul Tanwar, Krishna Sundaresan, Parmesh Ashwath, Prasanna Ganesan, Sathish Kumar Chandrasekaran, Sriram Ravi

Our results confirm that deep representation of source code and the active feedback loop is an assuring approach for predicting security and other vulnerabilities present in the code.