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🚨 LureBuster - Anti-Phishing Flood | Endpoint Stress Test

Python Matplotlib license

Designed to combat phishing by flooding scam sites with deceptive data, LureBuster's configurable traffic engine also serves as a tool for teams to test their own endpoints against high-volume requests.

image

🎯 Features

  • Data Flood: Generates a huge amount of data
  • Random Data: Mimics real user data using Faker
  • Parametrized Data: Dynamically change payloads, using predefined placeholders
    • Example: 'Her first name is {{PERSON_first_name_female}}, and her last name is {{PERSON_last_name_female}}'
    • Result: 'Her first name is Michelle, and her last name is Gardner'
    • Internally this will call Faker's Providers methods.
  • Multi-Threaded: Concurrent request engine
  • JSON Templates: Save/load attack profiles
  • Metrics: Check realtime requests per second, error rates, attack duration, successful requests

Can be used for:

🛡️Anti-Phishing:

  • Generate fake data at scale
  • Mimic organic user data patterns
  • Degrades phishing database utility

🧪Endpoint Testing:

  • Multi-threaded load simulation
  • Custom payload injection
  • Performance metric collection
  • Stress test

🛡️ Compliance Note

This tool is designed for:

  • Authorized security testing (with permission)
  • Ethical phishing disruption (targeting confirmed scam sites)
  • Legitimate load testing of owned infrastructure

⚠️ Never test systems without explicit authorization.

📐 Placeholder Structure

Text placeholders follow Providers method structure:

  • Wrapped with double curly brackets: {{...}}
  • Starts with an uppercase provider class: {{USER_AGENT...}}
  • Followed by an existing method for that provider:
    • Method without parameters: {{USER_AGENT_android_platform_token}}
    • Method with positional parameters: {{USER_AGENT_chrome(13,63,800,899)}}
    • Method with keyword parameters: {{USER_AGENT_chrome(version_from=13,version_to=63,build_from=800,build_to=899)}}
    • Method with default parameters: {{USER_AGENT_chrome}}

🐳 Example Endpoint with Docker

Creating the Image

sudo docker build -t example-api-image example-api/.

Running the Container

sudo docker run -p 8000:8000 -d --name "lurebuster-example-api" "example-api-image"

Testing the Endpoints

If everything ran properly, you should see Hello, LureBuster! at http://localhost:8000, and since I chose FastAPI to host this test endpoint, you can also access swagger docs

Checking Endpoint logs

sudo docker logs -f "lurebuster-example-api"

This will open a terminal with all the traffic in the 2 example endpoints.

🐱 Code Reviews by Haxi

Our Chief Meowker Officer ensures:

  • Readable, maintainable code
  • No hairball-inducing complexity
  • Bug-free merges (when not napping on the keyboard)

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A Python desktop application that floods phishing websites with indistinguishable fake data

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