DetectBERT: Code Vulnerability Detection
Shantanu Sudhir Gujar
Abstract
DetectBERT is a deep learning approach for identifying vulnerabilities in source code at the statement level. Utilizing transformer encoder models extracts features and learns complex relationships without predefined graph structures. DetectBERT addresses data distribution challenges using real-world code and normalizing user-defined names. Demonstrated effectiveness in Python using public datasets like CVEFixes and VUDENC, DetectBERT offers scalable, robust, and granular vulnerability detection.
Topics & Concepts
Computer scienceVulnerability (computing)Code (set theory)Computer securityProgramming languageSet (abstract data type)Software Reliability and Analysis ResearchWeb Application Security VulnerabilitiesAdvanced Malware Detection Techniques