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I Built a Delhi Metro Route Planner In React with GSAP

I recently built a free Delhi Metro route planner: https://metro.coolhead.in/ The first version worked well as an interactive React app. You could pick a source station, pick a destination station, and see the route, estimated fare, stop…

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I recently built a free Delhi Metro route planner:



https://metro.coolhead.in/



The first version worked well as an interactive React app. You could pick a source station, pick a destination station, and see the route, estimated fare, stop count, travel time, interchanges, and line-color guidance on the metro map.



But there was a problem.



Most people do not search for "Delhi Metro route planner app". They search for very specific routes:




  • Rajiv Chowk to Kashmere Gate metro route

  • New Delhi to Airport T3 metro fare

  • Hauz Khas to Botanical Garden metro travel time

  • Dwarka Sector 21 to Rithala metro route



That meant a single-page app homepage was leaving a lot of useful search demand uncovered.



So I added programmatic SEO pages for every station-to-station combination.






What I Wanted



I wanted both of these URLs to show the same useful route:




https://metro.coolhead.in/routes/rajiv-chowk-to-kashmere-gate/
https://metro.coolhead.in/?from=RCK&to=KG






The first URL is clean and search-friendly.



The second URL is simple for app state and sharing.



Both should hydrate into the same React planner state with:





  • from auto-filled


  • to auto-filled

  • route searched automatically

  • fare/time/stops/interchanges visible






The Data Model



The app already had two useful datasets:





  • labels.json: station IDs and names


  • edge.json: graph edges between stations, with line colors and SVG paths



Each station has a compact ID:




{
"id": "RCK",
"text": "Rajiv Chowk"
}






The route page slug comes from the station names:




Rajiv Chowk -> rajiv-chowk
Kashmere Gate -> kashmere-gate






So this:




RCK -> KG






becomes:




/routes/rajiv-chowk-to-kashmere-gate/









Generating Every Route



There are 241 stations in the app data.



For every ordered source/destination pair, excluding same-station routes, the generator creates a static page:




241 * 240 = 57,840 route pages






Each generated route page includes:




  • a route-specific <title>

  • meta description

  • Open Graph metadata

  • Twitter metadata

  • canonical URL

  • JSON-LD

  • prerendered route text in the HTML

  • a hydration payload for the React app






Connect With Me



If you liked this project, want to collaborate, or need help building a web app, product prototype, internal tool, dashboard, interactive map, or AI-enabled application, feel free to connect with me.



I enjoy working on products that combine clean interfaces, practical user experience, and thoughtful engineering.



You can reach me here:



Website: https://metro.coolhead.in/

Hindi version: https://metro.coolhead.in/?lang=hi

LinkedIn: https://linkedin.com/in/biomathcode

GitHub: https://github.com/biomathcode

Email: [email protected]

I am open to freelance work, collaborations, product ideas, web development projects, and technical consulting.

CTI Threat Relationship Graph2 Knoten / 1 Relationen
CVE / Incident Software MITRE ATT&CK CWE Weakness IoC
SOC Incident Playbook: Remote Code Execution (RCE) Defense
title: Detect Exploitation - I Built a Delhi Metro Route Planner In React with GSAP
id: 1f916aba-f973-4a0d-bec9-e12244b4359d
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-24
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-24"
        description = "YARA Signature for "
    strings:
        $str = "I Built a Delhi Metro Route Pl" ascii wide
    condition:
        any of them
}
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich I Built a Delhi Metro Route Planner In R.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

Empfohlene Sofortmaßnahmen
  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
  • 2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
  • 3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.
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