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Local IP scanner with geolocation alerts

Why Choose This Project

In corporate networks, cyberattacks often start with internal reconnaissance, where malicious actors scan local IP ranges to find vulnerable devices. Traditional monitoring tools can miss unauthorized scanning activity. This project provides a web-based local IP scanning system that identifies active devices on a network, tracks their IP addresses, and triggers geolocation-based alerts for suspicious activity. It is ideal for network administrators, IT security teams, and enterprises seeking enhanced internal security.

What You Get

  • A dashboard to scan local IP ranges and detect active devices.

  • Geolocation mapping of detected devices.

  • Alerts for unknown or suspicious IPs, highlighting potential threats.

  • Exportable scan reports for audit purposes.

  • Optional user authentication for secure access.

  • Real-time monitoring of connected devices on a network.

Key Features

Feature Description
Local IP Scanning Scan defined IP ranges to detect active devices.
Device Detection Identify devices by IP, MAC address, hostname (if available).
Geolocation Mapping Map detected IPs to geographic locations using IP geolocation APIs.
Suspicious IP Alerts Flag IPs not recognized or outside expected geolocation.
Dashboard Visualization Real-time view of scanned devices and their locations.
Exportable Reports Export scan results in CSV or PDF format.
User Authentication (Optional) Secure login for network administrators.
Scheduled Scans Automate periodic scanning for continuous monitoring.

Technology Stack

Frontend Layer

  • HTML, CSS, JavaScript

  • Bootstrap for responsive UI

  • Optional: React or Vue.js for dynamic dashboard

Backend Layer

  • Node.js (Express) / Java Spring Boot / Python Flask

  • Responsible for scanning IPs, fetching geolocation data, and triggering alerts

Database Layer

  • MongoDB / MySQL / PostgreSQL to store scan history, alerts, and device metadata

Security Layer

  • HTTPS for secure dashboard access

  • Role-based access for admins

  • Input validation to prevent injection attacks

Optional Libraries & APIs

  • Node net or Python socket for IP scanning

  • IP Geolocation APIs (ipinfo.io, ipstack, or MaxMind GeoIP)

  • Chart.js / D3.js for dashboard visualization

Working Flow

  1. Define IP Range

    • Admin/user specifies local network IP range (e.g., 192.168.0.1 – 192.168.0.254).

  2. IP Scanning

    • Backend scans each IP in the range to detect live devices.

    • Collects metadata: hostname, MAC address, OS (if detectable).

  3. Geolocation Mapping

    • Each detected IP is mapped to geographic coordinates using geolocation APIs.

    • Highlights unexpected or external locations.

  4. Alerts & Notifications

    • Flag devices outside expected range or unauthorized devices.

    • Send notifications via email or dashboard alerts.

  5. Dashboard Visualization

    • Map detected devices with geolocation markers.

    • Display device details in a table.

  6. Reporting & Export

    • Export scan results, alerts, and historical data for audit purposes.

Main Modules

  • User Module → Optional authentication and session management

  • IP Scanning Module → Scan local IP ranges and detect active devices

  • Geolocation Module → Map IP addresses to geographic locations

  • Alert Module → Notify admin of suspicious or unauthorized devices

  • Dashboard Module → Visualize active devices and geolocation data

  • Reporting Module → Export scan and alert logs

Security Features

  • HTTPS encryption for dashboard and data transfer

  • Input validation for IP range and scan configuration

  • Role-based access control for admins

  • Logging of scanned IPs, alerts, and actions for audit

  • Optional alert escalation for suspicious devices

This Course Fee:

₹ 2499 /-

Project includes:
  • Customization Icon Customization Fully
  • Security Icon Security High
  • Speed Icon Performance Fast
  • Updates Icon Future Updates Free
  • Users Icon Total Buyers 500+
  • Support Icon Support Lifetime
Secure Payment:
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