Machine Learning Based Cross-Language Vulnerability Detection : How Far Are We

Abstract

This thesis concerns the study of Machine Learning based methods for detecting vulnerable code. Various Neural Network models have been trained to detect specific vulnerabilities on a programming language dataset. This work, entails an approach not targeting specific vulnerabilities. We also leverage the commonality among programming languages like JAVA and C# by training the model on both languages and detecting vulnerabilities.