The official repository for the paper "VulScribeR: Exploring RAG-based Vulnerability Augmentation with LLMs".
Reimplement partial implementation of Devign, a graph neural network-based model for identifying vulnerabilities in C code. Includes tools for data preparation, Joern integration, and model training for vulnerability detection.
Reimplement empirical study on deep learning-based vulnerability detection techniques using real-world datasets (Devign and Chrome+Debian). Includes tools for parsing, slicing, and analyzing C code with GGNN and ReVeal pipelines.
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