International Association
for Cryptologic Research

We introduce an efficient SAT-based space partitioning technique that enables systematic exploration of large search spaces in cryptanalysis. The approach divides complex search spaces into manageable subsets through combinatorial necklace generation, allowing precise tracking of explored regions while maintaining search completeness.We demonstrate the technique’s effectiveness through extensive cryptanalysis of Ascon-Hash256. For differential-based collision attacks, we conduct an exhaustive search of 2-round collision trails, proving that no collision trail with weight less than 156 exists. Through detailed complexity analysis and parameter optimization, we present an improved 2-round collision attack with complexity 261.79. We also discover new Semi-Free-Start (SFS) collision trails that enable practical attacks on both 3-round and 4-round Ascon-Hash256, especially improving the best known 4-round SFS trail from weight 295 to 250.Furthermore, applying the technique to Meet-in-the-Middle structure search yields improved attacks on 3-round Ascon-Hash256. We reduce the collision attack complexity from 2116.74 to 2114.13 with memory complexity 2112 (improved from 2116), and the preimage attack complexity from 2162.80 to 2160.75 with memory complexity 2160 (improved from 2162).

Ascon is the final winner of the lightweight cryptography standardization competition (2018 − 2023). In this paper, we focus on preimage attacks against round-reduced Ascon. The preimage attack framework, utilizing the linear structure with the allocating model, was initially proposed by Guo et al. at ASIACRYPT 2016 and subsequently improved by Li et al. at EUROCRYPT 2019, demonstrating high effectiveness in breaking the preimage resistance of Keccak. In this paper, we extend this preimage attack framework to Ascon from two aspects. Firstly, we propose a linearize-and-guess approach by analyzing the algebraic properties of the Ascon permutation. As a result, the complexity of finding a preimage for 2-round Ascon-Xof with a 64-bit hash value can be significantly reduced from 239 guesses to 227.56 guesses. To support the effectiveness of our approach, we find an actual preimage of all ‘0’ hash in practical time. Secondly, we develop a SAT-based automatic preimage attack framework using the linearize-and-guess approach, which is efficient to search for the optimal structures exhaustively. Consequently, we present the best theoretical preimage attacks on 3-round and 4-round Ascon-Xof so far.