🔐 Password Tester

A mini project that allows users to test password strength, estimate crack time, and receive feedback for improvement with information,simulation thinking of hacker in real life

🚀 Features

• Real-time password strength analysis
• Estimated crack time calculation
• Helpful suggestions to improve weak passwords
• Modern, responsive UI

🛠️ Tech Stack

🖥️ Front-End

• React – UI framework
• Vite – Fast bundler and dev server
• TypeScript – Type-safe development
• Mantine – UI component library
• TsParticles - UI Animation Library

⚙️ Back-End

-JavaScript

🚀 Deployment

• Vercel - Deploy front-end
• Render - Deploy back-end

LIBARY

• zxcvbn – Password strength estimation,you can learn about operating principle in this link

🔍 How It Works

Almost app test password usually just exam length or need special character(#,%,@@),this is good but not safety in real life.Once password is 'An2007@" meet all the need of one strength password but we can crack it easily with infomation I collect . The project use zxcvbn library(one libary in DropBox) and custom dictionary is created by PII(name,birthday,nickname) to evaluate strength of password.It simulation a hacker attack in real life

🔄 Flow

1. User enters a password in the input field.
2. Frontend sends the password to zxcvbn for analysis.
3. The result is displayed instantly with strength level and suggestions.

📦 Installation

Clone the repository:

git clone https://github.com/ry2811/Password-Strength
npm install

Run front-end

cd password
npm run dev

Run back-end

cd password-tester-be
node index.js

🌐Website : https://password-strength-navy.vercel.app/

Screenshots :

🌱Future Plans

• Add API "I have PWNED" to check password leak
• Export strength reports as PDF
• Mobile-first redesign
• Localization (English + Vietnamese)

🤝 Contributing

Contributions are welcome!
Feel free to open issues or submit pull requests.
If you find this project useful, please ⭐ the repository to support its development.

📬 Contact

Email: nguyendangkhoi2811@gmail.com

📄 License

This project is licensed under the MIT License.

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