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<p>Binary Code Similarity Detection (BCSD) plays a critical role in software security. However, accurately measuring the similarity between binaries compiled from the same source code under different compilation configurations remains a major challenge. To address this issue, we propose BinEncoder, a novel BCSD framework that extracts high-level semantics of binary functions through a microcode-based representation. Specifically, BinEncoder lifts binary code into Hex-Rays microcode, an intermediate representation, and decomposes composite instructions into nested instructions to expose fine-grained semantics. It then employs a Transformer model pre-trained on three tailored tasks to capture structural and contextual information. Extensive experiments demonstrate that BinEncoder achieves superior performance over representative BCSD baselines across multiple BCSD tasks and shows promising potential for retrieval-based vulnerability detection.</p>

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BinEncoder: Binary code similarity detection across compilation configurations via microcode

  • 期刊论文

  • 发表日期：

    2026年7月29日

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  • Zheng Zhao,
  • Tianhao Zhang,
  • Qian Mao,
  • Qi Zhao,
  • Xiangyang Luo,
  • Xiaoya Fan

摘要

Binary Code Similarity Detection (BCSD) plays a critical role in software security. However, accurately measuring the similarity between binaries compiled from the same source code under different compilation configurations remains a major challenge. To address this issue, we propose BinEncoder, a novel BCSD framework that extracts high-level semantics of binary functions through a microcode-based representation. Specifically, BinEncoder lifts binary code into Hex-Rays microcode, an intermediate representation, and decomposes composite instructions into nested instructions to expose fine-grained semantics. It then employs a Transformer model pre-trained on three tailored tasks to capture structural and contextual information. Extensive experiments demonstrate that BinEncoder achieves superior performance over representative BCSD baselines across multiple BCSD tasks and shows promising potential for retrieval-based vulnerability detection.