AIBearisharXiv – CS AI · 9h ago7/10
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Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain Points
A comprehensive survey of 87 machine learning vulnerability detection studies reveals that the field has stalled despite a decade of research, trapped in self-reinforcing feedback loops that optimize for narrow, artificial problems. Researchers identify twelve interconnected pain points spanning datasets, formulations, metrics, and evaluation approaches that perpetuate focus on binary C/C++ function-level classification while neglecting vulnerability type prediction, multilingual support, and broader detection granularities.