A curated collection of JSON files containing lists of websites associated with malicious activities.
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Updated
Jun 1, 2024 - JavaScript
A curated collection of JSON files containing lists of websites associated with malicious activities.
A script to that checks for active connections to known malicious foreign IP addresses.
Using Random Forest to detect Malicious attacks on the ES6 Website
🔐 Identifies dark patterns online, Summarizes the privacy policy of a website, Malicious URL detection, Multilingual support & more ...
Our project employs machine learning to pinpoint phishing URLs with 97.4% accuracy, leveraging HTTPS and website traffic as critical indicators. Insights into features like AnchorURL enhance cybersecurity strategies, showcasing the power of AI in combating online threats.
Phishers use the websites which are visually similar to those real websites. So, we developed this website so that user can know whether the URL is phishing or not before using it. URL -
TrustLink: Detect and safeguard against deceptive URLs. Real-time threat detection using browser extension and web application for enhanced online security.
Python-based tool for analyzing URLs and detecting potential threats using various cybersecurity services.
Detect whether a website is legitimate (or) phishing using machine learning techniques
ShotDroid is a pentesting tool for android. There are 3 tools that have their respective functions, Get files from Android directory, internal and external storage, Android Keylogger + Reverse Shell and Take a webcam shot of the face from the front camera of the phone and PC.
A Machine Learning Model to detect malicious urls which include Deep File Analysis on attributes as well dropped files.
Anomaly based Malware Detection using Machine Learning (PE and URL)
A python tool to detect malicios and phishing domains.
Malicious actors often reuse code to deploy their malware, phishing website or CNC server. As a result, similiaries can be found on URLs path by inspecting internet traffic. Moreover, deep learning models or even regular ML model do not fit for inline deployment in terms of running performance. However, regexes ( or YARA rules ) can be deployed …
Chrome extension for proactive detection of malicious websites
Associated-Threat-Analyzer detects malicious IPv4 addresses and domain names associated with your web application using local malicious domain and IPv4 lists.
Malicious URL Detection Model NN optimized by Genetic Algorithms 🧬
Phishers Develop the websites similar to those real websites. So, this project comes to know whether the URL is phishing or not.
Finds related domains and IPv4 addresses to do threat intelligence after Indicator-Intelligence collects static files.
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