mrm8488/codebert-base-finetuned-detect-insecure-code

CodeBERT is a bimodal pre-trained model for programming language (PL) and nat-ural language (NL) It learns general-purpose representations that support downstream NL-PL applications such as natural language codesearch, code documentation generation, etc. The dataset used comes from the paper Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks . The task is to identify whether it is an insecure code that may attack software systems, such as resource leaks, use-after-free vulnerabilities and DoS attack . We treat the task as binary classification (0/1), where 1 stands for insecure code and 0 for secure code . Data statistics of the,