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+
+<h1 align="center">
+  <a href="https://github.com/athrvas017/Code_Guardians">
+    CoC Inheritance 2025
+  </a>
+  <br>
+  NetShield: AI-Powered Shield Against Digital Threats
+</h1>
+
+<div align="center">
+By Team Code Guardians
+</div>
+<hr>
+
+<details>
+<summary>Table of Contents</summary>
+
+- [Description](#-description)
+- [Links](#-links)
+- [Tech Stack](#-tech-stack)
+- [Progress](#-progress)
+- [Future Scope](#-future-scope)
+- [Applications](#-applications)
+- [Project Setup](#-project-setup)
+- [Team Members](#-team-members)
+- [Mentors](#-mentors)
+
+</details>
+
+## 📝 Description
+
+NetShield is a comprehensive cybersecurity command center designed to protect users from modern digital threats. It unifies advanced detection engines for identifying AI-generated deepfakes, phishing attacks, and malicious URLs into a single, intuitive platform, bridging the gap between sophisticated AI models and everyday user safety.
+
+## 🔗 Links
+
+- [GitHub Repository](https://github.com/athrvas017/Code_Guardians)
+- [Demo Video](https://drive.google.com/drive/folders/1dVyEsKwROaDJ4tRXqUwdbtWY4HUjXxSL?usp=sharing)
+- [Project Screenshots/Drive](https://drive.google.com/drive/folders/1HvrXofSExR4bGeJy7EzlTZEwDSUbz-35)
+- [Hosted Website](https://netshield-67le.onrender.com/)
+
+## 🤖 Tech-Stack
+
+### System Architecture
+
+```mermaid
+graph TD
+    User([User/Source]) --> WebUI[Frontend Static Pages]
+    User --> BrowserExt[Chrome Extension MV3]
+
+    WebUI --> API[Flask Backend]
+    BrowserExt --> API
+
+    API --> URLModel[URL ML Model - scikit-learn]
+    API --> PhishModel[Phishing Text Model - scikit-learn + TF-IDF]
+    API --> SafeBrowsing[Google Safe Browsing API]
+    API --> AIDetect[Hugging Face Inference via gradio_client]
+
+    WebUI --> PwnedAPI[HaveIBeenPwned Password API]
+
+    URLModel --> Out([Security Verdict & Risk Insights])
+    PhishModel --> Out
+    AIDetect --> Out
+```
+
+### Front-end (`frontend/`)
+- **HTML5 Pages**: Multi-page interface in `frontend/pages` (index, password toolkit, awareness, AI detection, command analysis).
+- **Vanilla JavaScript**: Feature logic in `frontend/js` (password generation, breach check, and utilities).
+- **CSS3**: Shared styles in `frontend/css/style.css` and assets in `frontend/assets`.
+
+### Browser Extension (`extension/`)
+- **Chrome Extension Manifest V3**: `extension/manifest.json` with service worker architecture.
+- **Extension Modules**: Background worker, content scripts, popup UI, and utility scripts under `extension/background`, `extension/content`, `extension/popup`, and `extension/utils`.
+
+### Back-end (`backend/`)
+- **Flask (Python 3)**: Central web server and routes in `backend/app.py` with modular services under `backend/services`.
+- **Gunicorn + Procfile**: Production serving and deployment support (`backend/gunicorn_config.py`, `backend/Procfile`, `backend/vercel.json`).
+- **Environment Configuration**: `python-dotenv` for API keys and runtime configuration.
+
+### ML / AI
+- **URL & Phishing Models**: scikit-learn models and vectorizers stored as `.pkl` files in `backend/model` and loaded via `joblib`.
+- **Feature/Training Utilities**: Model training scripts and feature engineering in `backend/utils`.
+- **AI Image Detection Service**: Hugging Face endpoint integration through `gradio_client` in `backend/services/ai_image_detection.py`.
+
+### External Integrations
+- **Google Safe Browsing API**: URL reputation verification in backend safety services.
+- **HaveIBeenPwned API (k-Anonymity range API)**: Password breach checks used by the password toolkit.
+## 📈 Progress
+
+### Fully Implemented Features
+
+* **AI Image Detection**  
+  Detects deepfake and AI-generated images using a ResNet-18 model by analyzing pixel artifacts and frequency patterns.
+
+* **URL Safety Scanner**  
+  Uses machine learning-based lexical analysis along with Google Safe Browsing API to identify malicious and phishing websites.
+
+* **Phishing Email Detector**  
+  Applies NLP techniques (TF-IDF + Naive Bayes) to detect social engineering attacks and automatically scans embedded links.
+
+* **Dangerous Command Analysis**  
+  Identifies harmful shell commands such as file deletion, privilege escalation, and fork bombs, and provides security warnings.
+
+* **Password Toolkit**  
+  Generates strong passphrases and checks password leaks securely using k-Anonymity and breach databases.
+
+* **Browser Extension**  
+  Real-time Chrome Extension that scans URLs, detects login fields, and provides instant security alerts.
+
+
+---
+
+### Partially Implemented Features / Work in Progress
+
+* **Database Layer Integration**: Migrating module outputs and user security events to a centralized database for reliable storage, querying, and analytics.
+* **Password Manager Module (In Progress)**: Building a secure vault workflow for storing, generating, and auto-filling credentials with encrypted persistence.
+
+## 🔮 Future Scope
+
+* **Advanced Password Manager**: Full-featured encrypted credential vault with breach alerts, password health scoring, and cross-device sync support.
+* **URL Model Enhancement**: Improving malicious URL detection with larger datasets, richer feature engineering, and continuous model retraining.
+* **AI Image Model Enhancement**: Upgrading deepfake detection with newer architectures, multimodal validation signals, and better robustness against adversarial manipulation.
+
+## 💸 Applications
+
+1. **Consumer Privacy** - Protecting individuals from identity theft and social engineering fraud.
+2. **Corporate Security** - Enhancing employee protection against sophisticated Business Email Compromise (BEC).
+3. **Media Verification** - Providing tools for journalists and users to verify the authenticity of online imagery.
+
+## 🛠 Project Setup
+
+1. Clone the GitHub repo.
+```bash
+git clone https://github.com/athrvas017/Code_Guardians.git
+```
+
+2. Create and activate a Virtual Environment.
+```bash
+python -m venv venv
+# Windows
+.\venv\Scripts\activate
+# Linux/macOS
+source venv/bin/activate
+```
+
+3. Install dependencies.
+```bash
+pip install -r requirements.txt
+```
+
+4. Download ML models and data.
+Place the `models` folder and relevant datasets in the `backend/` directory. (Link available in 🔗 Links).
+
+5. Start the Flask application.
+```bash
+cd backend
+python app.py
+```
+
+## 👨‍💻 Team Members
+
+* **Athrva Sarade**: [GitHub Profile](https://github.com/athrvas017)
+* **Niranjan patil**: [GitHub Profile](https://github.com/niranjanpatil1010)
+* **Ajay Payer**: [GitHub Profile](https://github.com/ajaypayer)
+* **Om chavarkar**: [GitHub Profile](https://github.com/Blaster1011)
+
+
+## 👨‍🏫 Mentors
+
+* **[Sarakshi Mamodia]**: [GitHub Profile](https://github.com/smamodia) [LinkedIn](https://www.linkedin.com/in/sarakshi-mamodia-6702682a3?utm_source=share&utm_campaign=share_via&utm_content=profile&utm_medium=ios_app)
+* **[Prachi Chavhan]**: [GitHub Profile](https://github.com/Pxchavhan) [LinkedIn](https://www.linkedin.com/in/pchavhan)
+
+
+
+