Subscriptos | AI-Powered Subscription Protection

Built With

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Description

Subscriptos protects consumers from predatory subscription services. Paste in any Terms of Service and our AI analyzes it for red flags, scores it on privacy, integrity, and fairness, and translates the legalese into casual, easy-to-understand language. Users can also generate virtual cards with spending limits through Stripe to control subscription costs. Available as both a web dashboard and a Chrome extension.

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Installation

Prerequisites

• Node.js 18+
• Python 3.11+
• Supabase project
• Google AI API Key (Gemini)
• Stripe API Key (Issuing)

Steps

1. Clone the Repository

git clone https://github.com/your-org/SASEHacksCFF
cd SASEHacksCFF

2. Install Frontend Dependencies

cd frontend
npm install

3. Install Backend Dependencies

cd backend
pip install -r requirements.txt

4. Configure Environment Variables

cp backend/.env.example backend/.env

Required variables:

# Supabase
SUPABASE_URL=https://your-project.supabase.co
SUPABASE_SERVICE_KEY=your-service-role-key

# Google AI
GEMINI_API_KEY=your-gemini-api-key

# Stripe
STRIPE_API_KEY=your-stripe-api-key
STRIPE_WEBHOOK_SECRET=your-webhook-secret

Also configure the frontend Supabase client in frontend/src/supabase.js with your project URL and anon key.

5. Run the Backend

cd backend
uvicorn main:app --reload

6. Run the Frontend

cd frontend
npm run dev

7. Access the Application Open http://localhost:5173 in your browser.

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Tech Stack

Category	Technologies
Frontend	React 19, Vite 7, Tailwind CSS 4, Framer Motion, React Router v7
Chrome Extension	Manifest v3, @crxjs/vite-plugin
Backend	FastAPI, Uvicorn, Python 3.11+
AI	Google Gemini 2.5 Flash
Database	Supabase (PostgreSQL)
Auth	Supabase Auth (JWT)
Payments	Stripe Issuing API
PDF Processing	PyMuPDF

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Architecture

Subscriptos follows a client-server architecture with a React frontend, FastAPI backend, Gemini-powered AI analysis layer, and Supabase for auth and data persistence.

AI Layer

The AI layer uses Google Gemini 2.5 Flash to analyze Terms of Service documents through three specialized modules.

AI Modules:

Module	File	Purpose
ToS Report	tosreport.py	Scores the ToS on data privacy, integrity, and consumer fairness (0-100) with justifications
ToS Translate	tostranslate.py	Summarizes red flags in casual Gen-Z language for accessibility
ToS Chat	toschat.py	Interactive Q&A chatbot that answers user questions about specific clauses
PDF Parser	pdfparser.py	Extracts text from uploaded PDF contracts for analysis

Scoring Scale:

Range	Meaning
80-100	Gold standard — nothing blatantly predatory
50-79	At least one clause is a point of contention
30-49	At least one clause is blatantly wrong or predatory
0-29	Multiple clauses are blatantly wrong or predatory

Analysis Flow:

1. User submits ToS text via dashboard or Chrome extension
2. Backend checks if the company has already been scanned (cached by company name)
3. If new, Gemini extracts the company name, generates scores with justifications
4. Translation module produces a casual red flag summary
5. All results are saved to the scans table in Supabase
6. User can ask follow-up questions via the chat module

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API Endpoints

Method	Endpoint	Description
POST	/ai/tos	Save raw ToS text to database
POST	/ai/report	Analyze ToS and return scores (cached by company)
POST	/ai/translate	Get casual brainrot red flag summary
POST	/ai/chat	Ask questions about the ToS
POST	/ai/chat/reset	Reset chat session
GET	/cards/	List user's virtual cards
POST	/cards/create/	Create a new virtual card with spending limit
DELETE	/cards/{card_id}	Cancel a virtual card

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Database Schema

scans table:

Column	Type	Description
id	int (PK)	Auto-incrementing primary key
tos	text	Full Terms of Service text
source_name	text	Company name (extracted by AI)
translation	text	Casual red flag summary
data_privacy_score	int	0-100 privacy score
data_privacy_just	text	Score justification
integrity_score	int	0-100 integrity score
integrity_just	text	Score justification
consumer_fairness_score	int	0-100 fairness score
consumer_fairness_just	text	Score justification

profiles table:

Column	Type	Description
id	uuid (PK)	User ID from Supabase Auth
stripe_id	text	Stripe cardholder ID

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Project Structure

SASEHacksCFF/
├── frontend/
│   ├── src/
│   │   ├── pages/
│   │   │   ├── Landing.jsx          # Marketing landing page
│   │   │   ├── Login.jsx            # Auth page
│   │   │   ├── Dashboard.jsx        # ToS analysis interface
│   │   │   ├── VirtualCards.jsx     # Card management
│   │   │   └── Popup.jsx           # Chrome extension popup
│   │   ├── components/
│   │   │   ├── Navbar.jsx           # Navigation bar
│   │   │   ├── Sidebar.jsx          # Dashboard sidebar
│   │   │   ├── CardWindow.jsx       # Card display
│   │   │   └── VirtualCardForm.jsx  # Card creation form
│   │   ├── contexts/
│   │   │   └── AuthContext.jsx      # Supabase auth (web + extension)
│   │   ├── layouts/
│   │   │   └── DashboardLayout.jsx  # Dashboard wrapper
│   │   ├── App.jsx                  # Router
│   │   ├── supabase.js              # Supabase client
│   │   └── contentWorker.jsx        # Extension content script
│   ├── manifest.json                # Chrome Extension v3 manifest
│   ├── vite.config.js
│   └── package.json
│
├── backend/
│   ├── main.py                      # FastAPI entry point
│   ├── auth.py                      # JWT token verification
│   ├── db.py                        # Supabase client
│   ├── routes/
│   │   ├── ai.py                    # ToS analysis endpoints
│   │   ├── cards.py                 # Stripe virtual card endpoints
│   │   └── scans.py                 # Scan history endpoints
│   ├── LLMs/
│   │   ├── tosreport.py             # Gemini scoring analysis
│   │   ├── tostranslate.py          # Gemini casual summary
│   │   ├── toschat.py               # Gemini interactive chat
│   │   └── pdfparser.py             # PDF text extraction
│   ├── requirements.txt
│   └── .env.example
│
└── README.md

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Subscriptos - Protecting consumers from predatory subscriptions with AI