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