The ISC International Journal of Information Security

Abstract In 2023, Zhang et al. introduced the lightweight block cipher family GFRX-b/k, offering various versions with different block (b) and key (k) lengths. Due to the similarity of the GFRX’s round function to that of the SIMON, the designers referenced the cryptanalysis conducted on the SIMON-32 and claimed that the GFRX-64/128, with higher than 19 and 13 rounds, is resistant to differential and linear cryptanalysis, respectively. In this paper, we examine the differential and linear cryptanalysis of GFRX-64/96 and GFRX-64/128. We first introduce baseline neural distinguishers for up to 7 rounds of the GFRX-64/96. Subsequently, we extend a 6-round neural distinguisher by adding 2 rounds to perform a key recovery attack, achieving an 8-round key rank analysis through a deep learning-based approach. Furthermore, we conduct an automated cryptanalysis of GFRX-64 using a SAT/SMT-based framework, identifying an 11-round differential distinguisher with a probability of 2−62, a 15-round linear distinguisher with a correlation of 2−30, and a 17-round linear hull with a correlation of 2−31.61. These results indicate that reducing the differential and linear cryptanalysis of the GFRX block cipher to the differential and linear cryptanalysis of the SIMON block cipher cannot yield accurate results or bounds. To the best of our knowledge, this work represents the first third-party cryptanalysis of the GFRX block cipher, offering new insights into its security.