This module leverages advanced deep learning algorithms to identify and mitigate malicious Domain Generation Algorithm (DGA) domains used by cyber threats. By analyzing domain patterns and behavioral characteristics, it provides real-time detection of dynamically generated domains often employed in botnets and malware campaigns.
Key Functions:
✅ High-Precision DGA Detection – Utilizes deep learning models such as LSTM, CNN, and GRU to distinguish between legitimate and algorithmically generated domains.
✅ Adaptive Threat Intelligence – Continuously refines detection accuracy by learning from evolving attack patterns and newly discovered DGA techniques.
✅ Real-Time Monitoring & Response – Enables instant identification of suspicious domains, preventing unauthorized communication with command-and-control (C2) servers.
✅ Seamless Integration with Security Frameworks – Works alongside other security modules to enhance network protection, DNS filtering, and automated threat mitigation.
We welcome contributions and feedback. Please fork the repository and open a pull request with your suggested changes.
This project is licensed under the MIT License.
If you discover a vulnerability, please report it responsibly via GitHub Issues or contact the maintainers privately.