Accelerated and Intelligent Password Cracking with Performance Optimization

: In the increasingly digitised world, security is a huge concern. Among all the security mechanisms, password authentication is the most popular one, however, weak or simple passwords are still susceptible to security attacks. This work introduces a system for distributed password cracking, for helping recover lost or forgotten passwords as well as to assess the weaknesses of current password management methodologies Furthermore, the system leverages cloud computing resources in order to allocate tasks towards workers, in-order to enhance productivity and scalability. The study also examines the efficacy of password strength, hashing algorithm, and encryption method in enhancing password security. The resulting system combines many attack tactics such as brute-force, dictionary, or hybrid approach as well as state-of-the-art optimization strategies. Anticipating passwords with heuristic-based predictions and machine learning model, and running upon GPU-accelerated parallel devices, the system is orders of magnitude faster than the approaches that try with candidate passwords alone. Ultimately, the project seeks to raise cybersecurity awareness by showing how weaknesses exist in password-based authentication and encourage the implementation of stronger, more secure authentication measures, such as multi-factor authentication (MFA) and biometrics.