Skip to content

Spam Guard is a hackathon project that integrates a chatbot to answer questions related to spam or ham classifications. It features a highly accurate pre-trained ML module that classifies spam and ham messages, texts, emails, and phone numbers. This ensures effective and reliable identification of spam across various communication channels.

Notifications You must be signed in to change notification settings

Blacksujit/SpamGuard

Repository files navigation

Spam Guard

image

Live Project Link :

https://spam-detection-tool-1.onrender.com

Youtube Link:

https://youtu.be/5uzirp4B6rI?si=CwZNA23-iHx6bHXB

Problem Statement:

Title: Develop Spam alert tool

Description: Develop a tool that can analyse and verify the source of any incoming call, link, SMS, mms and Email based on the inputs from the user. The solution should be able to check is source is genuine or spam

Solution : (Our Approach)

The Spam Detection and Prevention Tool is a project developed during a hackathon aimed at detecting and preventing spam across various communication channels. This tool provides users with the ability to detect spam messages, emails, multimedia messages (MMS), and short message service (SMS). Additionally, it includes functionality to determine whether phone numbers are associated with spam activity. Furthermore, the project integrates a chatbot where users can seek advice on how to stay safe from spam and fraud.

Features:

Spam Detection:

Utilizes machine learning models to detect spam messages, emails, MMS, and SMS.

Phone Number Analysis:

Determines whether phone numbers are spam or legitimate.

Chatbot Integration:

Includes a chatbot interface where users can inquire about spam prevention methods and safety tips.

API Integration:

Integrates APIs for data fetching, enabling real-time information retrieval for spam detection.

Twilio Integration:

Utilizes Twilio API for spam call detection and prevention.

Tech Stack:

Flask:

Python web framework used for building the application.

Python:

Programming language utilized for backend development and machine learning model implementation.

Machine Learning Model:

Implements machine learning algorithms for spam detection.

APIs:

Integrates APIs for fetching data and enhancing spam detection capabilities.

Twilio:

Utilizes Twilio API for spam call detection and prevention.

Getting Started:

To get started with the Spam Detection and Prevention Tool, follow these steps:

1.) Clone the repository:

git clone https://github.com/Blacksujit/spam-detection-tool.git

2.) Install Dependencies:

pip install -r requirements.txt

3.) Run the Flask application:

python wsgi.py

Product Overview and Features:

Home Page:

image

Result Page : (Showing the message was spam )

image

Phone Number Page Result Page (showing phone number was not spam):

image

ChatBot (Feature Adding):

image

Contributors:

1.) Sanskar Awati

2.) Abhishek Kute

License:

MIT

About

Spam Guard is a hackathon project that integrates a chatbot to answer questions related to spam or ham classifications. It features a highly accurate pre-trained ML module that classifies spam and ham messages, texts, emails, and phone numbers. This ensures effective and reliable identification of spam across various communication channels.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published