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InfoResearchPeer-reviewed

Vul-CTG: A Multimodal Framework for Software Vulnerability Detection via Code Text and Graph Integration

Source
IEEE Xplore (Security & AI Journals)(opens in a new tab)
Published
Record updated

Summary

Vul-CTG is a multimodal framework for software vulnerability detection that combines code text and program graph representations. It builds enriched graphs from statement-level source code graphs and abstract code property graphs, aligns them with code text through a new architecture called CTG-Former, and uses contrastive learning and pre-training to resist noisy labels. On recent function-level datasets it reports an approximate 3% F1-score improvement over state-of-the-art methods.