CoolFace
Apppublic

Eason918/malicious-email-and-url-detector-v2

sourceHugging Faceupdated 1y agoView on Hugging Face
1likes
App README

Malicious Email & URL Detector v2

A lightweight Streamlit web application that utilizes a fine-tuned deep learning model to detect malicious content in emails and URLs. The app helps individuals and organizations identify threats such as phishing and malware before any harm can occur.

Key Features

  • —Real-Time Detection Quickly classifies emails or URLs as malicious or benign using a fine-tuned transformer model.
  • —User-Friendly Interface Paste the email text or URL, then click a button—no advanced knowledge required.
  • —Lightweight & Fast Built on Streamlit for a snappy, interactive experience.

How It Works

  1. 1.Model A fine-tuned variant of distilroberta-base trained on a curated dataset of phishing, malware, and legitimate examples.
  2. 2.Input Users provide either an email’s textual content or a single URL. The app normalizes and processes the input.
  3. 3.Inference The model returns a label (malicious/benign) and a confidence score, enabling quick decisions on blocking or flagging potential threats.

Quickstart

  1. 1.Clone the Repository
bash
   git clone https://huggingface.co/spaces/your-username/Malicious-Email-and-URL-Detector-v2
   cd Malicious-Email-and-URL-Detector-v2

2. **Install Dependencies**
   pip install -r requirements.txt

3. **Run the App**  
   streamlit run app.py

4. **Use It**

   Step 1: Paste the email content or URL into the input box.

   Step 2: Click Analyze.

   Step 3: View the output displaying the classification (malicious or benign) and the confidence score.

6. **Example**

   Input:

   "Hello, your account has been locked. Please verify at http://suspicious-link.com"

   Output:

   Malicious (Confidence: 0.95)


## Limitations
Limitations
False Positives/Negatives: No model is perfect. Always combine with other security measures.

Dataset Bias: Performance depends on how well the training data represents real-world threats.

Evolving Threats: Regular updates are recommended to keep pace with new phishing or malware tactics.

## Contact
Author: Eason Liu