A deep learning-based application for detecting malware by analyzing binary files converted to images.
- Converts binary files to grayscale images
- Uses CNN for malware detection
- Simple GUI interface
- Batch processing support
- Python 3.8+
- TensorFlow 2.x
- OpenCV
- NumPy
- Pandas
- Matplotlib
- ttkbootstrap (for GUI)
- Clone the repository:
git clone https://github.com/ThaRealJozef/MalwareDetectionSystem.git
cd MalwareDetectionSystem- Create and activate a virtual environment:
python -m venv venv
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate- Install dependencies:
pip install -r requirements.txt- Download the latest release from the Releases page
- Extract the downloaded ZIP file
- Run
MalwareDetectionSystem.exefrom the extracted folder
If you want to build the executable yourself:
- Follow the "From Source" installation steps above
- Install PyInstaller:
pip install pyinstaller
- Run the build script:
# On Windows: .\build.bat # On macOS/Linux: chmod +x build.sh ./build.sh
- The executable will be created in the
distfolder
Run the application:
python app.pymalware-image-detector/
├── src/ # Source code
│ ├── models/ # Model definitions
│ ├── preprocessing/ # Data preprocessing
│ └── utils/ # Utility functions
├── data/ # Data directory (not included in git)
├── app.py # Main application
├── requirements.in # Direct dependencies
├── requirements.txt # Pinned dependencies
└── README.md # This file
Big Thanks to these fellows for providing the datasets used in this project.
- DikeDataset - Malware samples dataset
- Benign-NET - Benign software dataset
Please refer to their respective repositories for usage terms and conditions.