Odd Services
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Pi.alert | 1,729 | 4 months ago | 121 | gpl-3.0 | JavaScript | |||||
| WIFI / LAN intruder detector. Check the devices connected and alert you with unknown devices. It also warns of the disconnection of "always connected" devices | ||||||||||
| Flightsim | 1,097 | 6 months ago | 15 | November 16, 2021 | 23 | other | Go | |||
| A utility to safely generate malicious network traffic patterns and evaluate controls. | ||||||||||
| Network Intrusion Detection | 195 | 5 years ago | 8 | Python | ||||||
| Network Intrusion Detection KDDCup '99', NSL-KDD and UNSW-NB15 | ||||||||||
| Nfr | 120 | 7 months ago | 36 | September 21, 2023 | 12 | other | Go | |||
| A lightweight tool to score network traffic and flag anomalies | ||||||||||
| Cyber Security | 89 | 2 years ago | 1 | Jupyter Notebook | ||||||
| Machine Learning for Network Intrusion Detection & Misc Cyber Security Utilities | ||||||||||
| Libellux Up And Running | 53 | 6 months ago | 13 | mit | JavaScript | |||||
| Libellux: Up & Running provides documentation on how-to install open-source software from source. The focus is Zero Trust Network to enhance the security for existing applications or install tools to detect and prevent threats. | ||||||||||
| Malicious Urls Detection With Autoencoder Neural Networks | 29 | 2 years ago | mit | Python | ||||||
| Detecting malicious URLs using an autoencoder neural network | ||||||||||
| Netmoth | 16 | 3 months ago | 4 | apache-2.0 | Go | |||||
| 🚀 A lightweight, fast, simple and complete solution for traffic analysis and intrusion detection. | ||||||||||
| Odd Services | 8 | 7 years ago | bsd-3-clause | Bro | ||||||
| Detect weird services on a network. | ||||||||||
| Aeids Py | 8 | 4 years ago | Python | |||||||
| AEIDS is a prototype of anomaly-based intrusion detection system which works by remembering the pattern of legitimate network traffic using Autoencoder. | ||||||||||
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