smishing-detection

Smishing Botnets Going Viral in Iran

Proof of concept Android application for detecting smishing messages

Dacon Mission 14. 금융문자 분석 경진대회

사회적 이슈 기반 컨텍스트를 활용해 스미싱을 탐지하는 AI 시스템 AI-based smishing detection system using social issue-driven context for identifying context-aware phishing attacks

FraudGuard AI is a real-time, multi-channel fraud detection platform. Powered by FastAPI, scikit-learn, React 19, and Kubernetes, it analyzes SMS smishing, phishing emails, and malicious URLs with confidence scoring and community-driven threat sharing.

AI-powered phishing detection and awareness tool for users, students, and cybersecurity analysts.

Deep Learning based Smishing Detection System using CNN, LSTM and Bidirectional LSTM with 98.96% accuracy.

An AI-drive model driven to discern the legitimacy of SMS messages.

Smish hunter is an android application with the purpose of real-time prevention of smishing.

smishing internship project

New Zealand-localized phishing and smishing detection with selective abstention. Combines a localized feature set (IRD, NZ Post, banks, te reo cues, .govt.nz lookalikes) with classical baselines, fine-tuned transformers, and LLM-as-classifier (Gemini), under a class-conditional deferral layer for human review. Independent research.

Este repositório contém um script em Python que detecta mensagens suspeitos de phishing, verificando palavras-chave comuns em mensagens fraudulentas, como "Ganhe", "Prêmio", "Urgente" e "Promoção". Se alguma dessas palavras for encontrada, o e-mail é classificado como "Phishing"; caso contrário, é classificado como "Seguro".

Offline, deterministic synthetic dataset generator and validator for multilingual scam-message and smishing research: 50 languages, 60 scam families. Research data, not a live detector.

Business Website