scam-detection

There are 0 repository under scam-detection topic.

• crypto-firewall

  chartingshow / crypto-firewall

  🎁 Blocks browser-based crypto mining, cryptojacking, banking and crypto malware, infostealers, phishing websites, malicious apps and hackers command-and-control (C2) servers.

  adblockerfilterlisthostsublockublock-filters-rulesublock-originadblockcrypto-minercryptocurrenciescryptocurrencyprivacyfirewallcryptojackingabuse-detectionfraud-detectionmalware-detectionphishing-detectiontracking-detectionscam-detectionransomware-detection
  Language:Python 17
• AI-Crypto-Scam-Detector

  jonesterrance / AI-Crypto-Scam-Detector

  AI Crypto Scam Detector

  crypto-phishing-detectcrypto-scam-detectorcrypto-scannerphishing-detectionscam-detectscam-detectionscam-scanner
  11

• BothBosu / Synthetic-Data-for-Scam-Detection-Leveraging-LLMs-to-Train-Deep-Learning-Models

  This repository contains the source code and synthetic datasets used in the research on scam detection using deep learning models trained on data generated by Large Language Models (LLMs).

  deep-learningfraud-detectionlarge-language-modelsmulti-agent-systemsnatural-language-processingscam-detectionsynthetic-datatext-classification
  Language:Jupyter Notebook 3

• ccan23 / rugcheck

  Python wrapper for RugCheck API

  cryptocurrencydecentralized-exchangedexliquiditymemecoinmemecoinsrugcheckrugpullscam-detectionscam-tokensolana
  Language:Python 1

• eddieoz / atproto-scam-detector

  Crypto-Labeler is an advanced, AI-powered labeling and moderation tool dedicated to protecting the BlueSky community. By identifying and addressing crypto spammers, scammers, phishing attempts, and other malicious activities, it fosters a safer, more trustworthy, and transparent online environment for all users.

  atprotoatproto-labeleratprotocolbskybsky-botfirehoselabelermoderationmoderation-botmoderation-botsozonescam-detectionspam-detection
  Language:TypeScript 1
• Philippine-Scam-Analysis-ML

  HiroshiJoe / Philippine-Scam-Analysis-ML

  This repository includes analysis and models for distinguishing "Scam" from "Non-scam" messages. The data, originally extracted from images via OCR for the ScamGuard project, is used here to apply sentiment analysis and machine learning techniques to improve scam detection.

  data-scienceexploratory-data-analysismachine-learning-algorithmsscam-detection
  Language:Jupyter Notebook 1

• neupgroup / trustcheck.base

  Open-source Tool. Uses reputation to find outliers among entities.

  fraud-detectionscam-detectionfalse-positive-detection

• tgum / villager-scam

  a tiny web app to tell if a villager from minecraft is scamming you

  htmljavascriptmathminecraftminimalscamscam-detectiontradingvillager
  Language:HTML