Prob-Hashcat: Accelerating Probabilistic Password Guessing with Hashcat by Hundreds of Times
Ziyi Huang, Ding Wang, Yunkai Zou · 2024
While the academic community has proposed dozens of probabilistic password guessing models to improve the success rate of password guessing, few studies have considered the speed of generating password guesses (which is a crucial factor in realistic password guessing scenarios). Real-world attackers often aim to crack more passwords in less time, and the speed of these models thus becomes a significant concern. Consequently, real-world attackers tend to prefer simple heuristic methods (such as Rule attack and Mask attack) and off-the-shelf password cracking tools (such as Hashcat and John the Ripper), over academic probabilistic password guessing models, despite the latter’s superior scientific flavor.