July 25, 2022, 1:20 a.m. | Clemens-Alexander Brust, Bernd Gruner, Tim Sonnekalb

cs.CR updates on arXiv.org arxiv.org

Automatic vulnerability detection on C/C++ source code has benefitted from
the introduction of machine learning to the field, with many recent
publications considering this combination. In contrast, assembly language or
machine code artifacts receive little attention, although there are compelling
reasons to study them. They are more representative of what is executed, more
easily incorporated in dynamic analysis and in the case of closed-source code,
there is no alternative. We propose ROMEO, a publicly available, reproducible
and reusable binary vulnerability …

assembly language

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