Open-source phishing detection engine with explainable verdict. Self-hostable alternative to VirusTotal, CheckPhish, URLScan.io
A strict iOS app that analyzes link safety like a nutrition label (no AI, offline)
An all in one tool for IP/URL/Domain analysis and enrichment - Apollo.py
SecQR is an AI-powered QR code scanner that identifies and warns users about malicious URLs. It uses a combination of machine learning and a database of known URLs to determine the safety of a link.
An AI-powered URL analyzer that assesses website security by integrating multiple threat intelligence APIs like VirusTotal and Google Safe Browsing.
A comprehensive toolkit for analyzing and downloading YouTube videos, playlists.
Phishing Detection & Threat Intelligence Dashboard built using Flask and Python. Detects suspicious URLs using SSL validation, WHOIS analysis, VirusTotal API integration, homograph detection, suspicious keyword analysis, and risk-based threat scoring with an interactive security dashboard UI.
A powerful Python URL parser & security analysis toolkit for developers, security researchers, and automation.
A Python-based cybersecurity tool that analyzes URLs for suspicious characteristics and detects potential phishing indicators using multiple security checks.
A Flask-based phishing URL detector
A powerful web-based utility for parsing, analyzing, and editing URLs with real-time encoding/decoding capabilities.
A Python-based cybersecurity tool that detects potential phishing URLs using risk analysis techniques.
A Python desktop application that detects potentially malicious URLs using rule-based phishing analysis with a modern CustomTkinter interface.
Isolated multi-browser URL inspection toolkit. Sandboxed sessions for security analysts, QA engineers, and developers. Cross-browser evidence capture with safety policies.
🎣 Advanced Phishing Detection & URL Analyzer — Detect phishing URLs, emails, and credential harvesting attempts
A Python Flask web app that analyzes URLs, detects phishing indicators, and provides risk-based recommendations.
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