Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Streamingphish | 278 | 2 years ago | 13 | apache-2.0 | Jupyter Notebook | |||||
Python-based utility that uses supervised machine learning to detect phishing domains from the Certificate Transparency log network. | ||||||||||
Evilginx Course | 113 | 5 months ago | ||||||||
Repository for uploading all extra resources for students enrolled in Simpler Hacking's Evilginx3 Pro Course | ||||||||||
Url Classification | 98 | 3 years ago | 2 | Jupyter Notebook | ||||||
Machine learning to classify Malicious (Spam)/Benign URL's | ||||||||||
Phishing Website Detection | 78 | a year ago | Jupyter Notebook | |||||||
It is a project of detecting phishing websites which are main cause of cyber security attacks. It is done using Machine learning with Python | ||||||||||
Malicious Web Content Detection Using Machine Learning | 71 | 5 years ago | 3 | mit | Python | |||||
Chrome extension for detecting phishing web sites | ||||||||||
Ml_securityinformatics | 51 | 8 years ago | mit | Jupyter Notebook | ||||||
Short Course - Applied Machine Learning for Security Informatics | ||||||||||
Phishing Detection Plugin | 42 | 8 months ago | mit | JavaScript | ||||||
A lite chrome extension for detecting phishing sites using random forest classifier | ||||||||||
Malicious Urlv5 | 38 | a year ago | 3 | mit | Python | |||||
A multi-layered and multi-tiered Machine Learning security solution, it supports always on detection system, Django REST framework used, equipped with a web-browser extension that uses a REST API call. | ||||||||||
Phishing Dataset | 21 | a year ago | Svelte | |||||||
Phishing dataset with more than 88,000 instances and 111 features. Web application available at. https://gregavrbancic.github.io/Phishing-Dataset/ | ||||||||||
Url Feature Extractor | 18 | 5 years ago | Python | |||||||
Extracting features from URLs to build a data set for machine learning. The purpose is to find a machine learning model to predict phishing URLs, which are targeted to the Brazilian population. |