Detection of Vulnerabilities in Tensorflow with LSTM and BERT

This work has developed a Deep Learning model that analyses the semantics of the Python code used when working with TensorFlow and detects vulnerabilities to improve data security and bug recognition. This research not only seeks to improve the security of TensorFlow, but also aims to be a solution for other deep learning frameworks in the future and help developers find existing vulnerabilities to facilitate secure code writing.