SYSTEM AND METHODS FOR UNBIASED TRANSFORMER SOURCE CODE VULNERABILITY LEARNING WITH SEMANTIC CODE GRAPH

The present disclosure presents vulnerability code detection systems and related methods. One such method comprises executing, by a client computing device, a joint RoBERTa and graph convolutional neural network model that is configured to detect a code vulnerability attack on a computing device. The model can analyze the code structure and its connections and identify any irregularities or patterns that could be used to exploit vulnerabilities. Once the GCNN model has analyzed the code, it can provide insights to the user or system administrator about potential vulnerabilities and provide suggested actions to remediate them.