AI-Powered Password Strength Analyser Using Python, Django & Machine Learning
The Cyber Password Strength Analyzer Using Python Django & Machine Learning is a web-based cybersecurity application designed to analyze password strength and help users create more secure passwords.
The system uses a trained Random Forest Machine Learning model to evaluate different password characteristics such as length, uppercase and lowercase letters, numbers, special characters, entropy, repeated patterns, common passwords, and dictionary words.
Based on the analysis, passwords are classified as Weak, Medium, Strong, or Very Strong. The application also provides intelligent recommendations, a security score, estimated crack time, password history, reports, and a user dashboard.
Developed using Python, Django, SQLite, Bootstrap, JavaScript, and Machine Learning, this project is suitable for students looking for a practical Cyber Security, Python Django, or Machine Learning final-year project.
Main Features
- User Registration and Login
- Machine Learning Password Analysis
- Random Forest Prediction
- Password Strength Classification
- Password Entropy Calculation
- AI-Based Password Recommendations
- Estimated Password Crack Time
- Security Score
- User Dashboard
- Password Analysis History
- Date-Wise Reports
- Profile Management
- Secure Password Change
- Responsive User Interface
Technology Stack
| Technology | Used |
|---|---|
| Python | ✔ |
| Django | ✔ |
| SQLite | ✔ |
| HTML5 | ✔ |
| CSS3 | ✔ |
| Bootstrap | ✔ |
| JavaScript | ✔ |
Who Can Use This Project?
This project is suitable for students who are interested in Python, Django, Machine Learning, Artificial Intelligence, or Cyber Security.
It can be useful for students pursuing courses such as:
- BCA
- MCA
- B.Tech
- BE
- B.Sc Computer Science
- M.Sc Computer Science
- B.Sc IT
- M.Sc IT
- Cyber Security
- Python Programming
- Machine Learning
It can also be used as a Final Year Project, Major Project, Minor Project, College Project, Django Project, Machine Learning Project, or Cyber Security Project.
What You Will Learn
Working on this project can help students understand several practical concepts, including:
- Django web application development
- User authentication
- Database operations
- Password security concepts
- Machine Learning model integration
- Feature extraction
- Random Forest classification
- Password entropy calculation
- Reporting and data filtering
- Building responsive web interfaces
Project Package
The project package can include:
- Complete Python Django Source Code
- SQLite Database
- Project Documentation
- Project PPT
- Installation Guide
- Project Screenshots
Software Requirements
- Python 3.x
- Django
- SQLite
- Visual Studio Code
- PyCharm (Optional)
Project Screenshots
Home Page
User Registration
User Dashboard
Password Analysis
Report
How to Run the Project
Step 1: Download the project ZIP file.
Step 2: Extract the ZIP file.
Step 3: Copy the CyberPasswordStrengthAnalyzer folder and paste it on your Desktop.
Step 4: Open PyCharm.
Step 5: Open the terminal in PyCharm.
Step 6: Navigate to the project folder using the cd command.
cd project_pathExample:
cd C:\Users\your_computer_name\OneDrive\Desktop\CyberPasswordStrengthAnalyzerYou can also directly import the project folder into PyCharm.
Step 7: Now navigate to the cyberpassword
cd cyberpasswordStep 8: Run the Django project.
python manage.py runserverStep 9: Open your browser and visit:
http://127.0.0.1:8000/Now the Cyber Password Strength Analyser system will run successfully.
You can also register a new user from the registration page.
🚀 Buy the AI-Powered Password Strength Analyser Using Python, Django & Machine Learning
Get the complete source code, documentation, report, PPT, and installation guide with instant download.
🛒 Buy Now Get the Complete Project for Just ₹99 / $ 1.04Frequently Asked Questions (FAQs)
The project uses the Random Forest algorithm for password strength prediction. The trained model analyzes different password features and predicts the overall strength of the entered password.
The project uses the Random Forest algorithm for password strength prediction. The trained model analyzes different password features and predicts the overall strength of the entered password.
The project is developed using Python, Django, Machine Learning, Random Forest, SQLite, HTML, CSS, Bootstrap, and JavaScript.
The system analyzes password length, uppercase and lowercase characters, numbers, special characters, entropy, dictionary words, common passwords, repeated characters, and sequential patterns. These features are then processed by the Machine Learning model to predict password strength.
Yes. The system provides AI-assisted password recommendations based on the weaknesses detected in the password. It can suggest improvements such as increasing password length, adding special characters, avoiding common words, and reducing predictable patterns.
The Machine Learning model classifies passwords into four categories:
Weak
Medium
Strong
Very Strong
Yes. The project includes secure user registration, login, logout, session management, profile management, and change password functionality using Django.
Yes. This project is suitable for BCA, MCA, B.Tech, BE, B.Sc Computer Science, M.Sc Computer Science, B.Sc IT, M.Sc IT, Cyber Security, Python, and Machine Learning students looking for a final year, major, or minor project.
The project combines important concepts such as password security, entropy analysis, password pattern detection, Machine Learning classification, secure authentication, and AI-assisted recommendations, making it a practical cybersecurity academic project.
