
Real‑time detection of malicious (phishing) URLs using classical ML and deep‑learning models with a Flask REST API and a lightweight web UI.
The Url Classification System offers a robust solution for identifying malicious URLs in real-time, effectively safeguarding users from phishing attacks. By combining classical machine learning techniques with advanced deep learning models, it presents a powerful tool for enhancing web security, making it crucial for both individual users and organizations.
With its user-friendly design, including a lightweight web UI and a Flask REST API, the system is not only efficient but also accessible. This innovative approach to URL classification ensures that users can rely on a sophisticated mechanism to filter harmful content while enjoying a seamless experience.
Real-Time Detection: Instantly identifies and alerts users about phishing URLs, ensuring immediate protection against threats.
Classical ML and Deep Learning Models: Utilizes a combination of proven techniques for higher accuracy and reliability in detecting malicious links.
Flask REST API: Seamlessly integrates with other applications and services, enabling easy access to the detection capabilities.
Lightweight Web UI: Offers an intuitive interface for users to easily interact with the system without compromising performance.
Enhanced Security: Designed to provide real-time defenses against web-based threats, boosting overall cybersecurity measures.
Scalability: Capable of handling a growing amount of URLs, making it suitable for both small-scale and large-scale environments.
User-Friendly Design: Prioritizes simplicity and ease of use while maintaining powerful functionalities, appealing to a wide audience.
