Analyzes URLs to determine whether they are phishing attempts, while offering a clean and simple UI. The app supports full CRUD operations: creating new URL checks, viewing paginated results, updating feedback, deleting entries, and re-analyzing URLs.

The app allows a user to:

1. Submit a URL for analysis;
2. Send the URL to a server hosting an intelligent phishing detection model;
3. Analyze the URL and store the results for future use (training and fine-tuning);
4. Receive a clear verdict on whether the URL is safe or a phishing attempt;
5. Browse results from previous analyses;
6. Update feedback on an analyzed URL and re-analyze it if needed;
7. See a pie chart that shows the report between phishing and legitimate URLs.

1. Angular
2. PrimeNG
3. Django
4. Django REST Framework
5. SQLite
6. PyTorch
7. PyTorch Lightning
8. python-dotenv
9. ChatGPT

1. The LLM was pointing to a path that didn't exist in my Angular Project (src/app/app.module.ts) because I defined the component to be standalone. This makes to each component handles its dependencies alone. So, what I did? I explained to him in greater detail that my components were as he defined them, but created using ng g c <nume> --standalone. After this explanation, he understood and we moved on;

2. Another thing was that it generated some CSS code that had classes/ids that weren't defined in HTML. This was a simple fix, seeing as I only repaired the references between the files.

cd Backend
python manage.py makemigrations
python manage.py migrate
python manage.py runserver

• The backend runs at http://localhost:8000 and serves the API endpoints.
• It is intended to be accessed only through the frontend running on http://localhost:4200.
• All interactions with the URL analysis model, feedback, deletion, and re-analyze features go through the frontend UI.

cd Frontend
ng serve

It will run on browser at localhost:4200.