🛡️ Real-Time Security Alert and Response System

A proactive, intelligent security monitoring platform for digital retail, inspired by real-world enterprise needs.
Built with Django and pure Python for both clarity and rapid prototyping.

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🚀 Overview

Modern e-commerce and fintech platforms face constant threats—fraud, account takeovers, payment abuse—that cost millions. Most existing systems detect these after the damage is done.

This project provides a real-time, automated security alert and response platform, featuring:

• Live activity monitoring
• Rule-based and AI-driven threat detection
• Instant admin/user notifications
• Automated account lockdown and self-service unlock via OTP
• Rich dashboards for both users and admins

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🎯 Features

1. Activity Monitoring

• Tracks critical user actions: logins, password changes, transactions, failed payments, and browsing.
• Data sources: frontend/backend webhooks, logs, session metadata, and payment events.

2. Threat Detection Engine

• Rule-based detection (e.g., multiple failed logins, large transactions from new devices, suspicious browsing).
• (Optional) AI anomaly detection (Isolation Forest, One-Class SVM—see roadmap).
• Each event gets a severity score and full context for triage.

3. Real-Time Alerts

• Admins see a live feed of security alerts (with filter/search).
• Alerts contain: user/session/device, geo-IP, summary, severity, and suggested actions.
• User-facing alerts: Users see their own flagged events and can dispute ("This wasn't me!").

4. Automated Response System

• For high-severity threats:
  • User account is temporarily locked (sensitive actions blocked).
  • User is notified and offered self-service unlock via OTP (simulated or real email/SMS).
  • Admin can override or escalate, all with one click.

5. Security Health and Transparency

• Every user sees a dynamic “Security Health” bar—higher if their account is clean, lower if alerts exist.
• Users get actionable suggestions (enable 2FA, review recent activity).
• Full transparency: users can see what happened, when, and why.

6. Modern, Minimal Dashboard

• Responsive home page, member, and admin dashboards (basic Django templates—easy to style for your hackathon!).
• Instant event simulation from the UI (no Postman needed!).
• Admins have instant “resolve” and “unblock” options.

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🛠️ Tech Stack

• Backend: Django (API, business logic, admin, ORM)
• Frontend: Django Templates (minimal, pure HTML/CSS, ready for customization)
• Database: SQLite/PostgreSQL (via Django ORM)
• Alerting: Email (console for demo, extendable to SMTP/SMS)
• Anomaly Detection: Python (Scikit-learn, PyOD ready for ML integration)
• Other: Docker-ready, cross-platform

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📸 Screenshots

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💡 Key Innovations

• Proactive security: Alerts + actions happen before damage, not after.
• User empowerment: End users can self-verify suspicious events via OTP.
• Business value: Reduces fraud losses and support costs, boosts customer trust.
• Hackathon-ready: Fast, clear UI for demo. All testing via web—no extra tools needed.

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⚡ How It Works (Quick Walkthrough)

1. Monitor: Every critical user event is sent to the backend (via form, API, or real app).
2. Detect: Rules/ML flag anything suspicious, assigning a severity and full context.
3. Alert: Admins get instant alerts in dashboard and (simulated) email; users see flagged events and “This wasn’t me!” button.
4. Respond: High-severity? The user is locked out of sensitive actions until they confirm via OTP, or admin reviews/unlocks.
5. Recover: User or admin unlocks, health bar rises, account is safe again.

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🚦 Demo/Test Cases

No need for Postman! Test everything in the web UI:

• Trigger a large transaction to see a lock and OTP flow.
• Trigger failed logins, password changes, etc., to see medium/low severity alerts.
• Use "This wasn't me" and unlock actions as both user and admin.

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🔒 Security & Extensibility

• OTP via email/SMS: Can be integrated with Twilio, Sendgrid, etc.
• Role-based access: Members and admins have totally different views and privileges.
• Extensible rules: Add new detection rules in a single place.
• ML anomaly detection: Hooks in place for advanced detection.
• Rate limiting, geo-IP, and blockchain-ready: Easy to add.

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🏗️ Roadmap

• Add full ML anomaly detection.
• Slack/Telegram alert integration.
• Advanced search/filter on alert feed.
• User-facing notification history.
• Audit log hardening (blockchain or append-only).
• Theme/UI polish.

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🚀 Quickstart

1. Clone & Install

   git clone https://github.com/EclipseZoro/SecureRetailSystem.git
   cd security-alert-system
   pip install -r requirements.txt

2. Set up DB and Admin

   python manage.py migrate
   python manage.py createsuperuser
   python manage.py runserver

3. Go to:

   • http://localhost:8000/ – Home
   • http://localhost:8000/login/ – Member/Admin Login
   • http://localhost:8000/member/ – Member Dashboard (test alerts/events)
   • http://localhost:8000/admin_dashboard/ – Admin Alert Feed

4. Simulate events from the dashboard to see everything in action!

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🤝 Contributing

Pull requests and feature suggestions are always welcome.
Please open an issue or PR with your ideas or improvements.

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📣 Credits

Created by Astubh Mishra for Walmart Hackathon 2025.
Inspired by real-world threats and a passion for smarter, safer digital commerce.

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For questions or demo requests, feel free to contact or open an issue!