Dynamic Neural Control Flow Execution: An Agent-Based Deep Equilibrium Approach for Binary Vulnerability Detection

arXiv:2404.08562v1 Announce Type: cross
Abstract: Software vulnerabilities are a challenge in cybersecurity. Manual security patches are often difficult and slow to be deployed, while new vulnerabilities are created. Binary code vulnerability detection is less studied and more complex compared to source code, and this has important practical implications. Deep learning has become an efficient and powerful tool in the security domain, where it provides end-to-end and accurate prediction. Modern deep learning approaches learn the program semantics through sequence and graph …

abstract agent arxiv binary challenge code control cs.ai cs.cr cs.lg cybersecurity detection dynamic equilibrium flow security software type vulnerabilities vulnerability