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A quick python script to analyze a given set of passwords and give you some statistics. Used for identifying the most effective hashcat rules and masks, based on observed password trends.

Python 100.00%

password-analyzer.py's Introduction

password-analyzer.py

A quick python script to analyze a given set of passwords and give you some statistics. Used for identifying the most effective hashcat rules and masks, based on observed password trends. Run this against your dumped passwords, i.e. mimikatz and hashcat output, to identify trends. This will help you decide which rules and masks will most likely be effective in subsequent runs. Note, the script requires the passwords to be separated by new lines. CSVs wont work.

Usage:

python password-analyzer.py <password_file.txt>

Sample Output:

------------------------------------------------------------
 Starting Characters
------------------------------------------------------------
 182 of the 258 passwords start with an uppercase letter
  [ ~ 70 % ] 

 37 of the 258 passwords start with a lowercase letter
  [ ~ 14 % ] 

 24 of the 258 passwords start with a number
  [ ~ 9 % ] 

 15 of the 258 passwords start with a special character
  [ ~ 5 % ] 

------------------------------------------------------------
 Ending Characters
------------------------------------------------------------
 40 of the 258 passwords end with a letter
  [ ~ 15 % ] 

 160 of the 258 passwords end with a number
  [ ~ 62 % ] 

 58 of the 258 passwords end with a special character
  [ ~ 22 % ] 

------------------------------------------------------------
 Word Length
------------------------------------------------------------
 0 of the 258 passwords have 5 or fewer letters
  [ ~ 0 % ] 

 0 of the 258 passwords have 6 letters
  [ ~ 0 % ] 

 0 of the 258 passwords have 7 letters
  [ ~ 0 % ] 

 3 of the 258 passwords have 8 letters
  [ ~ 1 % ] 

 60 of the 258 passwords have 9 letters
  [ ~ 23 % ] 

 53 of the 258 passwords have 10 letters
  [ ~ 20 % ] 

 53 of the 258 passwords have 11 letters
  [ ~ 20 % ] 

 89 of the 258 passwords have 12 or more letters
  [ ~ 34 % ] 

------------------------------------------------------------
 Client Name
------------------------------------------------------------
 0 of the 258 passwords have the client's name
  [ ~ 0 % ] 

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