There are 0 repository under malicious-url topic.
Associated-Threat-Analyzer detects malicious IPv4 addresses and domain names associated with your web application using local malicious domain and IPv4 lists.
Malicious URL detector using keras recurrent networks and scikit-learn classifiers
Embed malware, apks, executables or any other binary file into a PDF, or generate a PDF with malicious link encrusted.
Detecting malicious URLs using Machine Learning
Malicious Domain Blocklist, suitable for use in Pi-hole or similar applications which accept domain based lists..
A DNS blocklist repo. Lists in various formats like AdGuard/Easylist, Pi-hole, HOSTS. Includes regex and wiki
Protect your computer / rooted-smartphone !
Curated block list including IPs, FQDNs, Domains, JA3, etc. Tailored for utmost precision to minimize false positives in personal or non-commercial environments. Updated regularly. For assistance or to support our initiatives, please reach out or consider participating in our sponsorship program
A curated collection of JSON files containing lists of websites associated with malicious activities.
Chrome extension for proactive detection of malicious websites
Python-based tool for analyzing URLs and detecting potential threats using various cybersecurity services.
A Machine Learning Model to detect malicious urls which include Deep File Analysis on attributes as well dropped files.
List of phishing URLs/Domains
The project focuses on detecting malicious URLs, a critical problem in today's digital landscape.
A repository with source code for the detection of malicious domain.
Cyberus is a tool to check the generic and sentimental legitimacy of the message, and it gives an approximate idea of the risk, based on the dataset, on which it has trained, and some machine learning models for predicting the risk quantitatively.
free-nitro.club detection api; /links returns all links and /links/<link> checks if the link is malicious
Cyber Security Project (College Project 6 month training)
Malicious Url Detection
Hackers attacks intercepted
Machine Learning Based Ransomware generated Command and Control Domain Detector.
Malicious URL Detection is designed to identify potentially harmful URLs using machine learning techniques. The model leverages various features of URLs to classify them as malicious or benign, providing an essential prediction for cybersecurity.