The invention discloses a graph neural network-based vulnerability identification and prediction method and system, computer equipment and a storage medium. The method comprises the following steps: constructing a vulnerability data set; dividing the vulnerability data set into a training set and a test set; expressing a vulnerability file code graph; vulnerability feature extraction; and constructing a predictor, and predicting vulnerabilities in the code file by utilizing the predictor. The system is used for realizing the process of the method, and the computer equipment and the storage medium can realize the process of the method by executing computer programs. According to the method, the grammar and semantic information of the vulnerability codes can be better utilized, the relationship between the vulnerability codes and the context is fully mined, one type of vulnerability is effectively identified, the universality and universality are higher, the link of manually formulatingvulnerability indexes in actual code auditing can be replaced, the actual use cost is lower, the application field is wider, and the precision is higher.