This project aims to detect malware embedded within QR codes, assisting law enforcement in scanning public QR codes, such as those found in subways and other public areas. It enhances public safety by identifying potentially malicious QR codes before they can cause harm.

1. Initial Detection: Utilizes the TotalVirus API for the first layer of detection.
2. AI Model: Employs an AI model for a second layer of detection, providing robust security.

• Pre-trained Models: Access and deploy pre-trained models quickly.

• 📱 Cross-Platform Application: A Flutter-based application (QR Malware Detection) for seamless interaction with the model.

• 🌐 Server Backend: A Flask server (server_Qr/server.py and server_Qr/test.py) that handles the malware detection process.

To set up the project, follow these steps:

1. Clone the Repository:

2. Create a Virtual Environment:

   # Create a new conda environment with Python 3.12.3
   conda create --name myenv python=3.12.3
   
   # Activate the conda environment
   conda activate myenv

3. Install Python Dependencies:

   pip install -r requirements.txt

4. Download the Model: Download the model and add it to the Server_Qr folder.

5. Install Flutter Dependencies: Navigate to the qr_code_malw directory and run:

   flutter pub get

1. Start the Server: Navigate to the Server_Qr directory and run:

   python server.py

   Open another terminal and run:

   python test.py

2. Run the Flutter Application: Navigate to the qr_code_malw directory and execute:

   flutter run

This project is licensed under the MIT License - see the LICENSE file for details.

• Thanks to the Flutter and PyTorch communities for their invaluable resources.