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#

malicious-url-detection

Here are 86 public repositories matching this topic...

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.

  • UpdatedApr 21, 2024
  • Java

Automated OWASP CRS and Bad Bot Detection for Nginx, Apache, Traefik and HaProxy

  • UpdatedNov 15, 2025
  • Python

Phishers use the websites which are visually and semantically similar to those real websites. So, we develop this website to come to know user whether the URL is phishing or not before using it. URL -http://phishing-url-detector-api.herokuapp.com/

  • UpdatedJul 11, 2024
  • Jupyter Notebook

Anomaly based Malware Detection using Machine Learning (PE and URL)

  • UpdatedFeb 1, 2025
  • Jupyter Notebook

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 …

  • UpdatedOct 30, 2023
  • Python

detect malicious URL and Request (Bi-LSTM、Bi-LSTM + CNN、CNN + Bi-LSTM、CNN + Bi-LSTM + CNN)

  • UpdatedMar 18, 2019
  • Jupyter Notebook

Associated-Threat-Analyzer detects malicious IPv4 addresses and domain names associated with your web application using local malicious domain and IPv4 lists.

  • UpdatedAug 31, 2023
  • Python
url_genie

Malicious URL Detection Model NN optimized by Genetic Algorithms 🧬

  • UpdatedAug 20, 2023
  • Jupyter Notebook

A list of malicious IP addresses associated with botnets, cyberattacks, and the generation of artificial traffic on websites. Useful for network administrators and security companies to block threats and protect against DDoS attacks.

  • UpdatedNov 29, 2025
  • JavaScript

Detecting malicious URLs using Machine Learning

  • UpdatedOct 30, 2018
  • Jupyter Notebook

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 -

  • UpdatedMay 9, 2024
  • Jupyter Notebook
thedartproject.github.io

In this project, we have detected the malicious URLs using lexical features and boosted machine learning algorithms

  • UpdatedAug 19, 2020
  • Jupyter Notebook

An Open-source project for One-Stop-Shop content moderation, it is technology agnostic and provides various communication strategies out of the box!

  • UpdatedOct 29, 2021
  • JavaScript

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