An Implementation and Evaluation of PDF Password Cracking Using John the Ripper And Crunch

Abstract: It can be challenging to choose the most effective word-mangling rules to apply while undertaking a dictionary-based password cracking attempt. We discuss a new method for generating password structures in the highest possible order in this work. Based on a training set of previously revealed passwords, we first build an artificial probabilistic context-free grammar. As a result of this grammar, we can generate word-mangling rules and, as a result, password guesses for password cracking. By putting our tools and strategies to the test on genuine password sets, we will show that this strategy appears to be a more effective way to crack passwords than traditional methods. Our approach cracked 28 percent to 129 percent more passwords than John the Ripper, a publicly available standard password cracking software, in one set of testing. We'll construct a wordlist for dictionary attacks using the Crunch tool