PrivGuard – AI Personal Privacy Risk Analyzer

PrivGuard is a mobile-first, privacy-focused app that helps users detect oversharing risks in their digital content. Whether it’s social media posts, images, or bios, PrivGuard uses custom on-device AI to analyze content and flag potential privacy threats, ensuring your data never leaves your phone or trusted backend.

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🌐 Real-World Use Case

Over 90% of digital threats begin with publicly available data.

PrivGuard educates and protects users by identifying:

• Posts that reveal personal details
• Real-time travel or location risks
• Information linked to password recovery
• IDs, documents, tickets captured in photos

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📱 Core Features

Upload & Local Scan

• Capture or upload media/text posts
• Securly save to local storage
• Long-press to run on-device scan

AI Privacy Analysis

• Text classifier: NER-based risk labeling with DistilBERT
• Risk Score: 0–100 with 🟢 Low, 🟡 Medium, 🔴 High tag
• Smart Tips: Context-aware advice (e.g., mask phone numbers, generalise location)
• Image Scanning: Object detection to extract and detect any risky details from image post (AVAILABLE IN FUTURE VERSIONS)

Social Profile Risk Scanner (AVAILABLE IN FUTURE VERSIONS)

• Input Instagram/Twitter handle + email
• Uses Instaloader / snscrape to fetch data
• NLP analysis of bio, captions, hashtags
• Auto-rescan every 30 days with push alerts

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App Architecture/Tech Stack

Phase	Feature	Stack
1	Upload UI + Gallery	Flutter, path_provider, image_picker
2	AI Risk Detection	DistilBERT, tflite_flutter,HuggingFace Transformers
3	Security	flutter_secure_storage, encrypt

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Custom AI Module

• Fine-tuned DistilBERT to detect Personally Identifiable Information present in given text
• Detects terms like:
  1. Names
  2. Dates
  3. Locations
  4. Phone numbers
  5. Credit card details
  6. Date of birth and other personal details

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App Screens (UI Flow)

1. Gallery Screen

   • Grid view of all uploaded content
   • Scan option on long-press

2. Scan Result Screen

   • Risk tag + reason: "Passport detected" or "Location inferred"
   • Actionable suggestions

3. Social Media Scanner

   • Input handle + email
   • View/email detailed report
   • Enable auto-scan mode

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Data Privacy & Ethics

• 💡 All analysis is performed locally
• 🚫 No 3rd-party cloud APIs (e.g., Google Vision, Gemini)
• 🗑️ All posts, media files stored securly in local storage

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Colab Notebook for AI Model

📎 Google Colab Notebook

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Getting Started

To Run the application locally-

1. This repo uses Git LFS to store large model files. Before cloning, install Git LFS
   git lfs install.
2. Clone the repository
   git clone https://github.com/Shaurya-Saini/Priv_Guard.git
cd Priv_Guard
git lfs pull
3. Create project
   flutter create .
4. Run the application using an emulator from Android studio
   flutter run

A few resources to get you started if this is your first Flutter project:

• Lab: Write your first Flutter app
• Cookbook: Useful Flutter samples

For help getting started with Flutter development, view the online documentation, which offers tutorials, samples, guidance on mobile development, and a full API reference.