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Digit Semantics based Optimization for Practical Password Cracking Tools
Users usually create their passwords with meaningful digits, i.e. digit semantics, which can be partially exploited by probabilistic password guessing models with a data-driven methodology for better efficiency. However, these semantics are largely ignored by current practical password cracking tools, like John the Ripper (JtR) and Hashcat. In this paper, we are motivated to study the digit semantics in passwords and exploit them to optimize the guessing efficiency of practical password cracking tools. We first design a practical extraction tool of digit semantics in passwords. Then we conduct a comprehensive empirical analysis of the digit semantics in four large-scale password sets leaked from the real world. Based on the analysis results, we further propose two new operations (the basic unit to construct mangling rules), then generate 1,974 digit semantics rules constructed from them. Moreover, in order to enforce semantics rules in JtR and Hashcat, we optimize their rule engines and running logic with the compatibility of the original built-in operations. The evaluation on the real password sets shows the significant advantage of digit semantics rules to extend current typical rule sets when we crack both Chinese and English (two of the biggest user groups) passwords with digit strings.