fraud

Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!

Image copy-move detector

"Very simple but works well" Computer Vision based ID verification solution provided by LibraX.

Implementation of an intelligence system to detect the fraud cases on the basis of classification.

Music and text generation with Transformer-XL.

Web Scraping, Document Deduplication & GPT-2 Fine-tuning with a newly created scam dataset.

Anomaly Detection Pipeline with Isolation Forest model and Kedro framework

Python SDK for Fingerprint Server API

AI-powered KYC automation platform with adaptive risk scoring, multi-layer biometrics, OCR, deepfake detection, and cryptographic credentialing. Reduces verification time from 48–72 hours to 8–12 minutes while improving fraud detection to 98.5%.

A small guide on credit card security, and ways hackers exploit them

Plundergram: A Telegram OSINT and recon tool (for research use only).

A curated list of tools, datasets and resources for financial crime compliance, AML, fraud, sanctions, KYC and surveillance.

Python script created for educational purposes. Chromium browsers cookies and passwords stealer, send via telegram

Open fraud monitoring: An open source platform that helps domain administrators monitor the behavior of users on their domain to identify malicious usages.

This project intends to solve the house hunt problem by sending the updates of new listings as per the selection criteria of the user by filtering spam in housing listings using NLP. It uses SMTP to send emails, nltk for NLP and tkinter for creating UI

using HMM to detect credit card fraudulent transaction

🪪 Identity forgery toolkit | Document & credential creation | NullSec Framework | @anonantics

The TE-925 (Truth Engine) is a one-stop, interactive truth-learning hub designed to reveal the hidden mechanics of the legal name fraud deception thrust upon humanity. Powered by a retro Pygame dashboard, it delivers over 90 original essays, custom searches, an expandable context window + more

It is a ML based model to detect fake URLs and QR codes, using adv. data cleaning to improve accuracy. Built a Flask-based RESTful API for real-time fraud checks, allowing easy use in web and web apps. Designed a responsive JS front end to connect with the backend, showing fraud risk scores, confidence levels, and key risk factors for users

A PySpark fraud detection project on AWS EMR