waf-brain and NGWAF
These are competitors: both implement machine learning-based Web Application Firewalls for network intrusion detection, with BBVA/waf-brain offering a more mature, actively maintained alternative to FA-PengFei/NGWAF's experimental feedback-driven approach.
About waf-brain
BBVA/waf-brain
Machine Learning WAF Based
This tool helps cybersecurity professionals protect web applications from common attacks like SQL injection. It acts as an intelligent firewall, analyzing incoming web requests (like login attempts or data queries) in real-time. By applying deep learning, it identifies and blocks malicious requests before they reach your application, safeguarding sensitive data and maintaining service availability. Security engineers and application owners responsible for web security would use this.
About NGWAF
FA-PengFei/NGWAF
First iteration of ML based Feedback WAF
This project offers a new way to protect web applications from cyberattacks. Instead of blocking malicious traffic outright, it uses machine learning to identify threats like SQL injection and then redirects attackers to a safe, emulated environment. This allows security teams to observe attacker behavior and gather data to automatically improve the system's detection capabilities over time.
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