SuchetSanjeev/EncryptedTrafficAttackClassifierLLMs

This cybersecurity classifier integrates a lightweight LLM with a Random Forest model to analyze encrypted network traffic, achieving 90% accuracy across nine cyberattack categories. It delivers actionable threat intelligence through an intuitive Streamlit interface, enhancing security without compromising data privacy

20
/ 100
Experimental
No License No Package No Dependents
Maintenance 6 / 25
Adoption 1 / 25
Maturity 1 / 25
Community 12 / 25

How are scores calculated?

Stars

1

Forks

1

Language

Python

License

Last pushed

Oct 28, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/llm-tools/SuchetSanjeev/EncryptedTrafficAttackClassifierLLMs"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.