A public repository dedicated to exploring the intersection of Machine Learning (ML) and AI security. This project contains implementations, research, and experiments on how ML can be used for cyber defense, as well as how ML systems themselves can be vulnerable to attacks.
The repository is organized into the following key areas:
| Directory | Description |
|---|---|
Adversarial_Attack/ |
Code and resources related to generating adversarial examples to fool ML models. |
DDOS_Attack/ |
Projects focused on using ML for Distributed Denial-of-Service (DDoS) detection and mitigation. |
Malicious_URL/ |
ML models and datasets for classifying and detecting malicious URLs. |
SMS_Spam_Classification/ |
A classic NLP project to identify and filter spam text messages. |
Trojan_Horse/ |
Research and code exploring Trojan attacks (backdoors) in neural networks. |
White_Box_Attack/ |
Implementations of white-box adversarial attacks where the attacker has full knowledge of the model. |
This repository is actively evolving. In the future, we plan to expand its scope to include cutting-edge topics in AI security and safety, such as:
- More LLM Attacks: Exploring prompt injection, jailbreaking, model theft, and other vulnerabilities specific to Large Language Models.
- AI Safety Research: Investigating topics like model alignment, robustness, interpretability, and the prevention of unintended behaviors in advanced AI systems.
- Model Extraction & Inversion
- Data Poisoning Techniques
- Federated Learning Security
Contributions are welcome! If you have a new project, improvement, or bug fix related to ML and Cybersecurity, please feel free to open a Pull Request or an Issue.
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature) - Commit your Changes (
git commit -m 'Add some AmazingFeature') - Push to the Branch (
git push origin feature/AmazingFeature) - Open a Pull Request
This repository is for educational and research purposes only. The techniques and code provided here should not be used for any malicious or unlawful activities. The contributors are not responsible for any misuse of the information.
Let's build a more secure AI-powered future, together.