🗣️ Tool to generate adversarial text examples and test machine learning models against them

A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X

An Unsupervised Graph-based Toolbox for Fraud Detection

Code for KDD 2020 paper Robust Spammer Detection by Nash Reinforcement Learning

A list of disposable email domains, cleaned and validated by scanning MX records.

LLM for Email Spam Detection

A collection of static files maintained by the Sublime team, primarily used for phishing defense.

Anti Spam/NSFW Telegram Bot Written In Python With Pyrogram.

Spam Detection Project for college students with PPT, Report, Code, Datasets and Research papers

Asynchronous Python Wrapper For A.R.Q API.

This is a Text Analysis App which can be used to find a detailed analysis of a particular text. This includes 5 main types of Analysis - Spam/Ham Detection, Sentiment Analysis, Stress Detection, Hate & Offensive Content Detection, Sarcasm Detection

Detects cyber threats to the end user with machine learning. This tool can do malware analysis of given exe file, spam analysis of given url and mail.

Implementing a machine learning algorithm(Neural Network with logistic activation function) to detect if an email is a spam email or a ham.

Group Guardian is a Telegram bot for admins to maintain a safe community.

Mail Header Detective is a powerful tool that can help dissect complex email headers, providing useful insights and valuable information about the provided email.

A Python interface to the Akismet spam-filtering service.

Spam Slayer is a web app used to detect deceptions from Amazon products' reviews. Users can copy a link to the product and paste directly paste it to my page. Using my trained deep learning model, Spam Slayer will distinguish between true/fake reviews and show them an adjusted rating without fake reviews.

Opinion mining on seller's reviews to check if the seller sells fake products

Protect your forms with a honeypot field

WhiteLightning distills massive, state-of-the-art language models into lightweight, hyper-efficient text classifiers. It's a command-line tool that lets you create specialized models that run anywhere—from the cloud to the edge—using the universal ONNX format for maximum compatibility.