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Introduction:
Open-Source Intelligence (OSINT) has evolved from manual data hunting to dynamic, geospatial real-time dashboards. The “GODEYE” project demonstrates how aggregating publicly available data sources—from aircraft transponders to live CCTV feeds—into a single interactive map creates unprecedented situational awareness. This article dissects the technical architecture, security considerations, and provides hands-on commands to build similar OSINT capabilities while highlighting the cybersecurity risks of exposed data layers.
Learning Objectives:
– Architect a browser-based OSINT platform using MapLibre GL JS and Node.js scrapers with parallel request batching.
– Implement dual-API fallback systems and progressive geocoding for robust data retrieval without paid cloud services.
– Apply Linux/Windows commands for data scraping, API security hardening, and geospatial visualization troubleshooting.
You Should Know:
1. Live Data Layer Acquisition: Scraping ADS-B, AIS, and Wildfire Feeds
GODEYE pulls real-time flight (ADS-B), maritime (AIS), and wildfire (NASA FIRMS) data from public endpoints. Below is a step-by-step guide to set up a Node.js scraper with parallel batching, mimicking the project’s core.
Step‑by‑step guide:
– Linux/macOS: Install Node.js and required packages.
sudo apt update && sudo apt install nodejs npm -y Debian/Ubuntu mkdir godeye-scraper && cd godeye-scraper npm init -y && npm install axios cheerio p-limit
– Windows (PowerShell as Admin):
winget install OpenJS.NodeJS mkdir godeye-scraper; cd godeye-scraper npm init -y; npm install axios cheerio p-limit
– Create `scraper.js`:
const axios = require('axios');
const pLimit = require('p-limit');
const limit = pLimit(5); // Max 5 parallel requests
const sources = [
'https://public-adsb-exchange.com/api/flights', // Example endpoint
'https://services.marinetraffic.com/ais/positions',
'https://firms.modaps.eosdis.nasa.gov/api/area/csv/'
];
async function fetchSource(url) {
try {
const response = await axios.get(url, { timeout: 10000 });
console.log(`Fetched ${url}: ${response.data.length} bytes`);
return response.data;
} catch (error) {
console.error(`Failed ${url}: ${error.message}`);
return null;
}
}
async function batchFetch() {
const promises = sources.map(url => limit(() => fetchSource(url)));
const results = await Promise.all(promises);
console.log('Batch completed');
}
batchFetch();
– Run: `node scraper.js`. This implements parallel HTTP batching with timeout handling.
2. Progressive Geocoding Fallback for Hyper‑Local Addresses
The project uses a 4‑stage geocoding fallback (e.g., for Indian addresses). This ensures location resolution even when primary APIs fail.
Step‑by‑step guide:
– Install geocoding libraries: `npm install node-geocoder`.
– Create `geocode-fallback.js`:
const NodeGeocoder = require('node-geocoder');
const providers = [
{ provider: 'openstreetmap', apiKey: null },
{ provider: 'google', apiKey: process.env.GOOGLE_API_KEY },
{ provider: 'here', apiKey: process.env.HERE_API_KEY }
];
async function progressiveGeocode(address) {
for (const cfg of providers) {
try {
const geocoder = NodeGeocoder(cfg);
const result = await geocoder.geocode(address);
if (result && result.length > 0) {
console.log(`Success with ${cfg.provider}:`, result[bash]);
return result[bash];
}
} catch (err) {
console.warn(`${cfg.provider} failed:`, err.message);
}
}
throw new Error('All geocoding providers failed');
}
progressiveGeocode("Connaught Place, New Delhi").then(console.log);
– Set API keys as environment variables (`export GOOGLE_API_KEY=”…”` on Linux; `set GOOGLE_API_KEY=…` on Windows CMD). This design prevents single‑point failure and avoids paid API overuse.
3. OSINT Lookup Engine with Dual‑API Automatic Fallback
GODEYE’s lookup engine queries phone numbers, IPs, domains, etc., using a primary + backup API architecture. Below is a hardened implementation with timeout handling.
Step‑by‑step guide:
– API security & configuration: Store keys in `.env` (use `npm install dotenv`).
.env file PRIMARY_OSINT_API=https://api.primary.com/v1/lookup PRIMARY_API_KEY=your_key FALLBACK_OSINT_API=https://api.fallback.com/v2/query FALLBACK_API_KEY=your_backup_key
– Create `osint-lookup.js`:
require('dotenv').config();
const axios = require('axios');
async function lookupWithFallback(query, type='ip') {
const endpoints = [
{ url: process.env.PRIMARY_OSINT_API, key: process.env.PRIMARY_API_KEY },
{ url: process.env.FALLBACK_OSINT_API, key: process.env.FALLBACK_API_KEY }
];
for (const ep of endpoints) {
try {
const response = await axios.get(`${ep.url}?${type}=${query}`, {
headers: { 'Authorization': `Bearer ${ep.key}` },
timeout: 5000 // 5 seconds timeout
});
console.log(`Success from ${ep.url}:`, response.data);
return response.data;
} catch (err) {
console.warn(`Fallback triggered: ${err.code || err.message}`);
}
}
return { error: 'All APIs failed' };
}
lookupWithFallback('8.8.8.8', 'ip');
– Windows command for environment variables:
setx PRIMARY_API_KEY "your_key" && setx FALLBACK_API_KEY "your_backup_key"
Then restart terminal. This architecture ensures high availability for OSINT lookups.
4. Live CCTV Camera Geolocation from Public IP Directories
Scraping 606 live CCTV cameras across 62 countries involves parsing public IP camera directories (e.g., Insecam). This raises ethical and security concerns—always respect robots.txt and local laws.
Step‑by‑step guide (educational only):
– Identify public camera index pages. Use `axios` + `cheerio` to extract IPs and coordinates.
const cheerio = require('cheerio');
async function scrapeCameras(url) {
const { data } = await axios.get(url);
const $ = cheerio.load(data);
const cameras = [];
$('div.camera-item').each((i, el) => {
const ip = $(el).find('.ip').text();
const lat = parseFloat($(el).attr('data-lat'));
const lon = parseFloat($(el).attr('data-lon'));
if (lat && lon) cameras.push({ ip, lat, lon });
});
return cameras;
}
– Mitigation for defenders: To prevent unauthorized camera scraping, implement IP whitelisting, HTTP authentication, or move cameras behind VPNs. Use `fail2ban` on Linux to block scrapers:
sudo apt install fail2ban sudo systemctl enable fail2ban Configure /etc/fail2ban/jail.local to monitor HTTP logs
5. MapLibre GL JS Custom SDF Icon System for Threat Overlays
GODEYE uses canvas-drawn Signed Distance Field (SDF) icons for 13 distinct overlays (aircraft, ships, conflict zones). This optimizes rendering performance.
Step‑by‑step guide:
– Include MapLibre GL JS in your HTML:
<link href="https://unpkg.com/[email protected]/dist/maplibre-gl.css" rel="stylesheet" /> <script src="https://unpkg.com/[email protected]/dist/maplibre-gl.js"></script>
– Add a custom SDF icon layer for cyber threat intelligence:
const map = new maplibregl.Map({ container: 'map', style: 'https://demotiles.maplibre.org/style.json' });
map.on('load', () => {
map.loadImage('https://raw.githubusercontent.com/maplibre/maplibre-gl-js/main/test/images/red-marker.png', (error, image) => {
if (error) throw error;
map.addImage('threat-icon', image, { sdf: true }); // SDF enables color tinting
map.addSource('threats', {
type: 'geojson',
data: { type: 'FeatureCollection', features: [] }
});
map.addLayer({
id: 'threats-layer',
type: 'symbol',
source: 'threats',
layout: { 'icon-image': 'threat-icon', 'icon-size': 0.8 }
});
});
});
– Update threats dynamically: `map.getSource(‘threats’).setData(geoJsonData)`. This technique is used for conflict zones and GPS jamming detection points.
6. API Security & Cloud Hardening for OSINT Dashboards
While GODEYE avoids cloud infra, deploying similar dashboards requires hardening against API abuse and data leakage.
Step‑by‑step guide:
– Rate limiting with Express (Node.js):
npm install express express-rate-limit
const rateLimit = require('express-rate-limit');
const limiter = rateLimit({ windowMs: 15601000, max: 100 }); // 100 req per 15 min
app.use('/api/', limiter);
– Linux firewall (UFW) to restrict access:
sudo ufw default deny incoming sudo ufw allow from 192.168.1.0/24 to any port 3000 proto tcp Allow only local network sudo ufw enable
– Windows Defender Firewall rule (PowerShell):
New-1etFirewallRule -DisplayName "Block Public OSINT" -Direction Inbound -Action Block -RemoteAddress Any -LocalPort 3000
– API key rotation & encryption: Use `crypto` module to encrypt stored keys; rotate every 90 days. Never hardcode keys in client-side JavaScript—proxy requests through your own backend.
7. Vulnerability Exploitation & Mitigation: GPS Jamming Detection
GODEYE includes GPS jamming/spoofing detection by analyzing ADS-B signal anomalies. Attackers may jam GPS to hide aircraft positions; defenders can implement consistency checks.
Step‑by‑step mitigation (Linux-based):
– Install `dump1090` to capture raw ADS-B messages:
sudo apt install dump1090-mutability dump1090 --1et --1et-http-port 8080
– Analyze timestamps and signal-to-1oise ratios. A sudden drop in visible satellites across multiple aircraft indicates jamming.
– Python script to detect spoofing (compare reported position vs expected trajectory):
import numpy as np def detect_spoofing(positions): velocities = np.diff(positions, axis=0) if np.any(np.linalg.norm(velocities, axis=1) > 600): >600 knots unrealistic return "Spoofing suspected" return "Normal"
– Hardening against GPS jamming: Use anti‑jamming antennas or switch to terrestrial navigation (e.g., eLoran) where available.
What Undercode Say:
– Key Takeaway 1: Open-source intelligence is not just about collecting data—it’s about resilient architecture. Dual-API fallbacks and progressive geocoding transform a fragile scraper into a production-ready OSINT engine.
– Key Takeaway 2: The GODEYE project exposes a critical cybersecurity paradox: the same geospatial visualization that aids threat hunters can leak sensitive infrastructure markers. Always implement rate limiting, IP whitelisting, and ethical use policies.
Analysis (10 lines):
The dashboard’s reliance on public ADS-B and AIS data is legally permissible but operationally risky; adversaries can similarly track military movements. The absence of cloud infrastructure reduces cost but shifts responsibility to local host hardening—many developers overlook firewall configurations, making their OSINT dashboards accessible to the open internet. Live CCTV scraping, while technically impressive, violates privacy norms in many jurisdictions and should be restricted to authorized penetration testing only. The dual-API fallback pattern is a best practice for any cybersecurity tool that depends on external data sources. GPS jamming detection is an emerging frontier; integrating machine learning on ADS-B anomaly scores could automate threat alerts. For defenders, similar dashboards can serve as blue-team situational awareness, but must be air-gapped or protected by mutual TLS. The use of MapLibre GL JS with SDF icons demonstrates that high‑performance geospatial intelligence is achievable without proprietary mapping SDKs. Finally, the project’s “no paid APIs” mantra is educational but not enterprise‑ready—critical alerts demand reliable, SLA-backed data feeds.
Prediction:
– +1 Real-time OSINT dashboards will become standard in Security Operations Centers (SOCs) within 24 months, merging physical threat intelligence (flights, ships, fires) with cyber threat feeds.
– -1 Adversaries will weaponize publicly scraped CCTV and infrastructure markers to plan kinetic attacks, prompting new regulations that restrict real-time geospatial data sharing.
– +1 Open-source mapping libraries (MapLibre, OpenLayers) will surpass proprietary GIS tools for threat visualization, driven by community-built threat intelligence layers.
– -1 GPS jamming attacks will increase in frequency, especially around critical infrastructure, as low‑cost software-defined radios become widely available.
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