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Password Cracker program coded in C++ language by applying brute force algorithm and parallelizing it using MPI and OpenMP

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Distributed Password Cracker Using MPI and OpenMP

Description

Password Cracker program coded in C++ Language by applying Brute Force Algorithm and Parallelizing it using MPI and OpenMP. You can look at detailed description Here.

Manual

  1. Copy the content of /etc/shadow into a file shadow.txt and place it into your current working directory:

    sudo cat /etc/shadow > shadow.txt
    
  2. Use following command to Compile the Code:

    mpic++ -fopenmp main.cpp -lcrypt -o main
    
  3. Create a file named as machinefile in your current working directory:

    touch machinefile
    
  4. The machinefile should have the hostname of your pc and the number of processes you want to run on it in parallel i.e, sameet is the hostname of my pc and I want to run 5 processes in parallel. So, its format should be like:

    sameet:5
    
  5. Use following commands to Execute the Code. Here 5 represents total number of processes to create:

    mpiexec -n 5 -f machinefile ./main
    

Working Screenshots



Side Notes

  • The /etc/shadow file stores all the users of the pc and their respective passwords in encryped form.
  • The encryption of their passwords are done using SHA-512 Algorithm in Ubuntu Linux.
  • We can encrypt any string using the crypt() function from crypt.h Library. It returns us Salt and Encyrpted Password both in a single appended string. It requires two arguments:
    • The string to encrypt.
    • The salt used to encrypt the string.
  • We can extract the salt used to encrypt the password from shadow file and then use it to encrypt all the strings obtained from brute force and compare with the password.
  • In shadow file, the username, salt, and password are stored in the following format:
    • Username before first :
    • Then Salt until three $ signs
    • And Encrypted Password after that

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Password Cracker program coded in C++ language by applying brute force algorithm and parallelizing it using MPI and OpenMP

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