Made under 36 hours for Hack the North 2024

• Demo: https://goose-guard.vercel.app
• Devpost: https://devpost.com/software/gooseguard
• Hugging Face: https://huggingface.co/harrumnoor/scam-detection

Protect yourself from scam emails, texts, and calls with our AI-powered cybersecurity platform. GooseGuard helps identify fraudulent communication using AI to analyze and detect suspicious patterns in emails, text messages, and phone calls!

• The core of the GooseGuard platform, a full-stack web application built with Next.js on top of Convex

• Interfaces Python scripts responsible for transcribing and detecting suspicious activity via the LLM Bert (featuring 460,000,000+ parameters)

• Clone this repository
• Instructions diverge below for Next.js application and BERT model:
• goose-guard - Next.js
  1. Setup virtual environment: python -m venv .venv, then pip install -r requirements.txt
     • To enter the virtual environment: ./venv/Scripts/activate
     • To leave the virtual environment: deactivate
  2. .env variables: HF_API_KEY - Hugging Face API key
• goose-guard-model - BERT:
  1. Setup environment: npm install
  2. Setup Convex: npx convex dev
  3. .env variables: HF_API_KEY - Hugging Face API key, GROQ_API_KEY - Groq API key