Tady通过结构约束正则化，解决神经反汇编器的错误输出问题。
Tady: A Neural Disassembler without Structural Constraint Violations
- 基于后支配关系构建结构约束，限制反汇编解空间。
- 在多种二进制上消除结构违规，保持指令级准确率。
- 适合需要可靠反汇编结果的安全分析与逆向工程人员。
反汇编是二进制分析中关键但具挑战性的步骤。尽管新兴的神经反汇编器在效率和准确性方面展现出潜力，但其输出常违反基本的结构约束，严重影响实际可用性。为此，我们通过形式化并应用基于后支配关系的关键结构约束，对反汇编解空间进行正则化，系统性地检测出现有神经反汇编器输出中的广泛错误。这些错误通常源于模型对上下文建模能力有限以及指令级解码忽略全局结构完整性。我们提出 Tady，一种新型神经反汇编器，具备改进的模型架构和专用后处理算法，专门针对上述缺陷设计。在多种二进制上的全面评估表明，Tady能有效消除结构约束违规，同时保持高效性和指令级准确性。
原文摘要 · Abstract (English)
Disassembly is a crucial yet challenging step in binary analysis. While emerging neural disassemblers show promise for efficiency and accuracy, they frequently generate outputs violating fundamental structural constraints, which significantly compromise their practical usability. To address this critical problem, we regularize the disassembly solution space by formalizing and applying key structural constraints based on post-dominance relations. This approach systematically detects widespread errors in existing neural disassemblers' outputs. These errors often originate from models' limited context modeling and instruction-level decoding that neglect global structural integrity. We introduce Tady, a novel neural disassembler featuring an improved model architecture and a dedicated post-processing algorithm, specifically engineered to address these deficiencies. Comprehensive evaluations on diverse binaries demonstrate that Tady effectively eliminates structural constraint violations and functions with high efficiency, while maintaining instruction-level accuracy.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。