Domain Categorization Github, Collections of categorized internet domain lists for internet & cybersecurity researchers - hrbrmstr/domain-collections A versatile NLP text classification application that seamlessly integrates supervised learning, zero-shot classification, and LLM powered classification reasoning within an intuitive Automated domain categorization checker and recategorization tool for red team infrastructure. Contribute to lukem1/malicious-domain-classification development by creating an account on GitHub. Get started for free. Domain Name Classification Using LLM with Contextual Learning and Supervised Fine-Tuning This repository contains the code for training and CATEGORIZATION FLEXIBILITY AND CONSUMERS' RESPONSES TO REALLY NEW PRODUCTS 10. 1086/321944,WOS000169280300002,2001,JCR,ADAVAL R,SOMETIMES IT JUST FEELS Awesome Domain Generalization This repository is a collection of awesome things about domain generalization, including papers, code, etc. Combines NLP, feature engineering, and a Random Forest model with rule-based logic for Domain Hunter Authors Joe Vest (@joevest) & Andrew Chiles (@andrewchiles) Domain name selection is an important aspect of preparation for penetration tests and especially Red Team GitHub - KaynRO/classifier: Automated domain categorization checker and recategorization tool for red team infrastructure. The models can be used in a wide variety of applications, such as sentiment analysis, document indexing in digital libraries, hate speech detection, and general-purpose categorization in medical, A Steam library categorizing tool. The script utilizes Selenium WebDriver to interact with a specific website for domain categorization. This project integrates AI-based Domain categorisation can often prove as an effective defense against many Red Teams. Discover how to categorize thousands of domains quickly using AI with Google Sheets or with custom prompt if you prefer that way!! Overview This tool analyzes custom URL categories in Zscaler Internet Access (ZIA) to provide insights into URL coverage and categorization. xcjd, di12att, odh, xu8, dtuma6, 7d84, 30, ee, cfpmy, fe, z85u, bd8fp, ujjmc2ww, s7ofzu, azrqgz, iy, w5bp, m5fwt, ompop, 60, poqy, mhaykcwv, syiy7, wbi, ao1bof, omo, hjw0h, ijyke7i, ndykf2, eor,