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As an ISO/IEC standard, RIPEMD-160 has been extensively studied for (Semi-Free-Start) collision attacks. A significant breakthrough was achieved at FSE 2024 with the first 41-, 42-, and 43-step SFS collision attacks, which leveraged an automatic search model (EUROCRYPT 2023) and a message modification strategy (FSE 2020). However, these attacks are limited by reliance on heuristic objective functions and suboptimal message modification techniques. This paper enhances the existing framework from two perspectives. Firstly, we refine the automatic search model by incorporating a holistic objective function that considers all critical probability components, moving beyond simple Hamming weight. Secondly, we introduce two generic techniques to further improve (SFS) collision attacks: the first application of differential clustering and a dedicated message modification strategy. As a result, we present the first valid SFS collision attack on 44-step RIPEMD-160. Additionally, we significantly reduce the time complexities of existing attacks on 41-, 42-, and 43-step variants, making it feasible to find colliding message pairs for 41- and 42-step versions within practical time for the first time.

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Improved Semi-Free-Start Collision Attacks on RIPEMD-160

  • 会议论文

  • 发表日期：

    2026年

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  • Zhuolong Zhang,
  • Muzhou Li,
  • Haoyang Wang,
  • Shiqi Hou,
  • Wei Wang,
  • Meiqin Wang

摘要

As an ISO/IEC standard, RIPEMD-160 has been extensively studied for (Semi-Free-Start) collision attacks. A significant breakthrough was achieved at FSE 2024 with the first 41-, 42-, and 43-step SFS collision attacks, which leveraged an automatic search model (EUROCRYPT 2023) and a message modification strategy (FSE 2020). However, these attacks are limited by reliance on heuristic objective functions and suboptimal message modification techniques. This paper enhances the existing framework from two perspectives. Firstly, we refine the automatic search model by incorporating a holistic objective function that considers all critical probability components, moving beyond simple Hamming weight. Secondly, we introduce two generic techniques to further improve (SFS) collision attacks: the first application of differential clustering and a dedicated message modification strategy. As a result, we present the first valid SFS collision attack on 44-step RIPEMD-160. Additionally, we significantly reduce the time complexities of existing attacks on 41-, 42-, and 43-step variants, making it feasible to find colliding message pairs for 41- and 42-step versions within practical time for the first time.