| wesleyraptor/streamingphish |
278 |
|
0 |
0 |
over 4 years ago |
0 |
|
13 |
apache-2.0 |
Jupyter Notebook |
| Python-based utility that uses supervised machine learning to detect phishing domains from the Certificate Transparency log network. |
| simplerhacking/Evilginx-Course |
113 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
|
|
| Repository for uploading all extra resources for students enrolled in Simpler Hacking's Evilginx3 Pro Course |
| surajr/URL-Classification |
98 |
|
0 |
0 |
almost 5 years ago |
0 |
|
2 |
|
Jupyter Notebook |
| Machine learning to classify Malicious (Spam)/Benign URL's |
| chamanthmvs/Phishing-Website-Detection |
78 |
|
0 |
0 |
about 3 years ago |
0 |
|
0 |
|
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 |
| philomathic-guy/Malicious-Web-Content-Detection-Using-Machine-Learning |
71 |
|
0 |
0 |
over 6 years ago |
0 |
|
3 |
mit |
Python |
| Chrome extension for detecting phishing web sites |
| albahnsen/ML_SecurityInformatics |
51 |
|
0 |
0 |
over 9 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| Short Course - Applied Machine Learning for Security Informatics |
| picopalette/phishing-detection-plugin |
42 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
JavaScript |
| A lite chrome extension for detecting phishing sites using random forest classifier |
| abhisheksaxena1998/Malicious-Urlv5 |
38 |
|
0 |
0 |
about 3 years ago |
0 |
|
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. |
| GregaVrbancic/Phishing-Dataset |
21 |
|
0 |
0 |
over 3 years ago |
0 |
|
0 |
|
Svelte |
| Phishing dataset with more than 88,000 instances and 111 features. Web application available at. https://gregavrbancic.github.io/Phishing-Dataset/ |
| lucasayres/url-feature-extractor |
18 |
|
0 |
0 |
over 6 years ago |
0 |
|
0 |
|
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. |
