Phishing-Attack-Domain-Detection and Phishing-Website-Detection

Both tools are direct competitors, each offering an independent machine learning-based solution for detecting phishing URLs using Python, differing mainly in their popularity as indicated by GitHub stars.

Maintenance 0/25
Adoption 8/25
Maturity 16/25
Community 20/25
Maintenance 2/25
Adoption 10/25
Maturity 8/25
Community 23/25
Stars: 56
Forks: 23
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: GPL-2.0
Stars: 190
Forks: 72
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About Phishing-Attack-Domain-Detection

deepeshdm/Phishing-Attack-Domain-Detection

Identifying Malicious Phishing URLs through Machine Learning

This tool helps individuals and organizations detect malicious phishing URLs before they can cause harm. You input a website address, and it tells you whether the URL is legitimate or a fraudulent phishing attempt. It is designed for anyone who needs to verify the safety of a link, from cybersecurity professionals to everyday internet users.

cybersecurity fraud-prevention website-safety link-verification internet-security

About Phishing-Website-Detection

chamanthmvs/Phishing-Website-Detection

It is a project of detecting phishing websites which are main cause of cyber security attacks. It is done using Machine learning with Python

This tool helps cybersecurity professionals and IT administrators identify deceptive websites designed to steal personal information. It takes the URL of a website and determines whether it's a legitimate site or a phishing attempt. The output helps protect users from financial fraud and data theft.

cybersecurity fraud-prevention IT-security threat-detection website-security

Scores updated daily from GitHub, PyPI, and npm data. How scores work