ExoPassword is a Password Strength Analyzing module that combines Machine Learning, rule-based scoring, and breach detection to provide detailed insight regarding your passwords.
- Supports password strength evaluation by 4 Machine Learning models
- Rule based password scoring
- Password breach status and breach count
Python3 is required.
Open terminal
and execute:
pip install exopassword
Open terminal
and execute:
git clone https://github.com/owaspvit/exo.git
cd exo
pip install --editable .
from exo.exocore import ExoCore
API_KEY = "" #Enzoic API Key here
SECRET_KEY = "" #Enzoic Secret Key here
exo = ExoCore(API_KEY, SECRET_KEY)
result = exo.results("abc123@12")
print(result)
{
"password": "abc123@12",
"score": 80,
"DecisionTree": {
"score": 1,
"response": "Moderate"
},
"LogisticRegression": {
"score": 1,
"response": "Moderate"
},
"NaiveBayes": {
"score": 1,
"response": "Moderate"
},
"NeuralNetwork": {
"score": 2,
"response": "Strong"
},
"Breached": True,
"BreachCount": 11
}
Model | Training Accuracy | Testing Accuracy |
---|---|---|
Decision Tree | 0.981 | 0.926 |
Logistic Regression | 0.819 | 0.818 |
Naive Bayes | 0.812 | 0.812 |
Neural Network | 0.991 | 0.989 |
Before creating an issue, please ensure that it hasn't already been reported/suggested.
The issue tracker is only for bug reports and enhancement suggestions. If you have a question, please ask it in the Discord server instead of opening an issue – you will get redirected there anyway.
If you wish to contribute to the ExoPassword codebase or documentation, feel free to fork the repository and submit a pull request.
If you don't understand something in the documentation, you are experiencing problems, or you just need a gentle nudge in the right direction, please don't hesitate to join our Discord Server.