Profile of Vulnerability Remediations in Dependencies Using Graph Analysis

arXiv:2403.04989v1 Announce Type: cross
Abstract: This research introduces graph analysis methods and a modified Graph Attention Convolutional Neural Network (GAT) to the critical challenge of open source package vulnerability remediation by analyzing control flow graphs to profile breaking changes in applications occurring from dependency upgrades intended to remediate vulnerabilities. Our approach uniquely applies node centrality metrics -- degree, norm, and closeness centrality -- to the GAT model, enabling a detailed examination of package code interactions with a focus on identifying …

analysis applications arxiv attention breaking challenge control critical cs.cr cs.se dependencies dependency flow graph graphs network neural network open source package profile remediation research vulnerabilities vulnerability vulnerability remediation