Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Sniffnet | 12,766 | 3 months ago | 21 | August 08, 2023 | 32 | apache-2.0 | Rust | |||
Application to comfortably monitor your Internet traffic 🕵️♂️ | ||||||||||
Scapy | 9,725 | 814 | 206 | 3 months ago | 25 | December 25, 2022 | 158 | gpl-2.0 | Python | |
Scapy: the Python-based interactive packet manipulation program & library. Supports Python 2 & Python 3. | ||||||||||
Ivre | 3,167 | 3 months ago | 43 | gpl-3.0 | Python | |||||
Network recon framework. Build your own, self-hosted and fully-controlled alternatives to Shodan / ZoomEye / Censys and GreyNoise, run your Passive DNS service, collect and analyse network intelligence from your sensors, and much more! Uses Nmap, Masscan, Zeek, p0f, etc. | ||||||||||
Nettacker | 2,915 | 24 days ago | 15 | October 29, 2023 | 35 | apache-2.0 | Python | |||
Automated Penetration Testing Framework - Open-Source Vulnerability Scanner - Vulnerability Management | ||||||||||
Flowmeter | 1,058 | 5 months ago | 1 | apache-2.0 | Go | |||||
⭐ ⭐ Use ML to classify flows and packets as benign or malicious. ⭐ ⭐ | ||||||||||
Lme | 616 | 3 months ago | 49 | other | Shell | |||||
Logging Made Easy (LME) is a free and open logging and protective monitoring solution serving all organizations. | ||||||||||
Hellraiser | 545 | a year ago | 16 | Ruby | ||||||
Vulnerability scanner using Nmap for scanning and correlating found CPEs with CVEs. | ||||||||||
Picosnitch | 529 | 4 months ago | 43 | October 23, 2023 | 3 | gpl-3.0 | Python | |||
Monitor Network Traffic Per Executable, Beautifully Visualized | ||||||||||
Nmapgui | 443 | 4 years ago | n,ull | gpl-3.0 | Java | |||||
Advanced Graphical User Interface for NMap | ||||||||||
Poseidon | 405 | 2 | a month ago | 25 | September 19, 2022 | 1 | apache-2.0 | Python | ||
Poseidon is a python-based application that leverages software defined networks (SDN) to acquire and then feed network traffic to a number of machine learning techniques. The machine learning algorithms classify and predict the type of device. |