Web Vulnerabilities Incidents Monitoring Service using Machine Learning
Using ML models with 99.5% accuracy - %99.2 F1 Score, we are able to detect different web attack variants like (XSS,SQLi,CSRF,Open Redirect,etc..). The developer of a certain website could add our JS code, that routes all query params and submitted forms to our core Microservice that parses this data and then communicates to the ML microservice to get confidence results and then through a secure websockets connection send those results to a dashboard that has informative and attractive Widgets and Charts and Incoming Incidents alerts written in React and Redux.
- Using ML models with 99.5% accuracy - %99.2 F1 Score
- Microservice architecture design
- Scalable
- Easy to deploy
- Test different attack variants (XSS,CSRF,SQL,Bruteforce)
- Setup in under 1 min
- Attractive & informative dashboard
- Secure communication protocols (SSL,WSS + Encryption)
- Python
- Tornado
- Scipy Kit
- Numpy
- Asyncio
- React
- Redux
- JQuery
- Digital Ocean
- Zeyad Khaled
- Hikmet Demir
- [Abdurahman Atakishiyev](https://www.linkedin.com/in/abd/ "Abdurahman Atakishiyev"
- [Ping Cheng](https://www.linkedin.com/in/ping-cheng/ "Ping Cheng"