title: Malicious Email & Url Detector
emoji: 📊
colorFrom: red
colorTo: yellow
sdk: streamlit
sdk_version: 1.43.2
app_file: app.py
pinned: false
short_description: A web app for detecting malicious Email and URL
Malicious Email & URL Detector
This is the first version of Malicious-URL-Detector, a web application built using Streamlit that leverages a fine-tuned deep learning model to detect malicious emails and URLs. The application analyzes input text—whether it’s the content of an email or a URL string—and classifies it as either malicious (e.g., phishing or malware) or benign.
How It Works
Model Integration:
The app uses a model fine-tuned from distilbert/distilbert-base-uncased for text classification. The model has been trained on a curated dataset comprising phishing, malware, and legitimate examples, enabling it to recognize suspicious patterns and linguistic cues.User Interface:
Built with Streamlit, the web app offers a simple and intuitive interface where users can paste the content of an email or a URL. Upon submission, the model processes the input and returns a prediction indicating whether the text is malicious or benign, along with a confidence score.Real-Time Detection:
Designed for real-time threat detection, the application helps organizations and individual users quickly identify potentially harmful links before they are accessed, thereby contributing to enhanced cybersecurity defenses.
Getting Started
To run the application locally or deploy it on Hugging Face Spaces, follow these steps:
- Clone the Repository:
Clone this repository to your local machine.git clone https://huggingface.co/spaces/your-username/Malicious-URL-Detector cd Malicious-URL-Detector