FA-PengFei/NGWAF

First iteration of ML based Feedback WAF

36
/ 100
Emerging

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.

No commits in the last 6 months.

Use this if you manage web applications and want an automated, adaptive system to detect and respond to cyber threats without immediately blocking them.

Not ideal if you need a production-ready, fully supported Web Application Firewall solution right now, as this is an experimental proof of concept.

cybersecurity web-application-security threat-detection security-operations incident-response
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 12 / 25

How are scores calculated?

Stars

59

Forks

7

Language

Jupyter Notebook

License

MIT

Last pushed

Mar 20, 2024

Commits (30d)

0

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