A professional anti-phishing research tool 🔐 that serves scammers a tasty dish of millions of seeds 🍽️ while you sit back and watch the chaos 💥 . Generate payloads automatically ⚡ and log every move 📊 while testing your defenses 🛡️. Time to own those phishers and make them cry 🦸‍♂️💀!

Detect Phishing Websites with the power of Artificial Intelligence (AI)

Filter of daily fake new domains

Python-based application designed to scan URLs and assess website risks through an API

Hands on analysis and defending against phishing emails. Investigating real-world phishing attempts using a variety of techniques.

Bulk domain email security lockdown tool that prevents email phishing and spoofing attacks by automatically configuring SPF hard fail, null MX records, and DMARC rejection policies on unused Cloudflare-managed domains.

SPF, DKIM, DMARC configuration guide with real DNS record examples. Covers MTA-STS, BIMI, DANE, anti-phishing, and anti-spoofing controls.

Open-source cybersecurity tip repository delivering actionable guidance to help users and administrators prevent account hacking, covering authentication best practices, phishing mitigation, and access control hardening for individual and organizational digital accounts.

A professional reminder to stay vigilant against phishing scams, specifically focusing on the technology industry.... | View more at LaravelMail.com

Comprehensive phishing analysis project covering fundamentals to advanced investigations using real-world scenarios, SOC methodologies, and industry tools.

Open-source reference gateway for Trust-First Email Protocol (TFEP) — cryptographic sender identity via Ed25519 + DID:web, spam/phishing prevention, verified webhooks, B2B document exchange, and non-repudiable legal notices. SMTP-compatible. Written in Go.

Advanced multimodal AI agent for real-time zero-day phishing detection in the browser

Lists of domain's and other data around known phishing operations

A machine learning–based web application designed to identify and prevent phishing attacks by analyzing website URLs and behavioral patterns. The system detects malicious websites using feature extraction techniques and predictive models to enhance user security and prevent credential theft.