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Cross-platform Flutter app for capturing or selecting images, detecting QR codes, and analyzing them with OpenAI. Reveals QR contents (URL, Wi-Fi, etc.) and potential security risks in a user-friendly interface. Perfect for quick, secure QR scanning.
AI-Powered Quishing Detection API: Detects malicious QR codes in emails, including advanced evasion techniques like Split-QR, CSS obfuscation, and url shortener. Extracts URLs and classifies threats using XGBoost ML model. Returns JSON-ready threat intelligence
A security advisory on the growing, but overlooked threat of malicious QR code overlays targeting industries such as travel, hotel, personal banking, restaurant, clinics, and more.
Offline-first QR-code phishing (quishing) analyzer: decodes QR images, PDFs and emails and explains the risk of URLs, payment, Wi-Fi and MFA payloads, with no external APIs.
Browser-based QR security scanner that analyzes links for phishing and quishing signals before they are opened, with offline heuristics and optional Google Safe Browsing checks.
Forensic desktop tool (PyQt6, OpenCV) that decodes QR codes and PDFs and shows where they really lead: UPI payment scams, redirect tracing, credential-harvesting pages, risky PDF features, explained threat scores.
Treinamento interativo de Segurança da Informação sobre quishing, phishing, deepfake, senhas, vazamentos de dados, LGPD e boas práticas, com simulação educativa e quiz de 15 perguntas.
Herramienta open source y gratuita para analizar el riesgo de phishing (quishing) de un código QR sin visitar la URL: suplantación de marca, trucos de URL, TLDs sospechosos y más.
Reproducible, confound-controlled benchmark for payload-free QR-phishing (quishing) detection — uncovering a URL-length confound that inflated prior reported accuracy by up to 0.24 AUC.