Author

Kaan Sulkalar

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Preprint Sep 2026

SEMA-GUARD: Semantic and Graph-Based Vulnerability Detection in Assembly Code

This article presents SEMA-GUARD, a framework that uses semantic analysis and graph neural networks to identify flaws in assembly code, and results imply that including semantic information in graph-based models may be a successful method for identifying vulnerabilities in compiled code.

H. Dursunoglu, Kaan Sulkalar · 0 citations