Deep Learning-Based Binary Analysis for Vulnerability Detection in X86-64 Machine Code

While much of the current research in deep learning-based vulnerability detection relies on disassembled binaries, this paper explores the feasibility of extracting features directly from raw x86-64 machine code. Although assembly language is more interpretable for humans, it requires more comple...

MAYA: Addressing Inconsistencies in Generative Password Guessing through a Unified Benchmark

Recent advances in generative models have led to their application in password guessing, with the aim of replicating the complexity, structure, and patterns of human-created passwords. Despite their potential, inconsistencies and inadequate evaluation methodologies in prior research have hindered...