Redroom: The Open‑Source Geopolitical Intelligence Platform That Puts SIGINT In Your Browser + Video

Introduction:

Open‑source intelligence (OSINT) has long been the domain of fragmented command‑line tools and manual data sifting. Redroom changes that by delivering a unified, real‑time OSINT workstation that fuses AI‑classified news, live SIGINT feeds, satellite tracking, and a 3D threat globe into a single web interface—no security clearance required. This article explores the technical layers of Redroom, from its open‑source architecture to the underlying data streams, and provides a hands‑on guide to replicating its core capabilities using Linux commands, Python, and other free tools.

Learning Objectives:

Understand how Redroom aggregates and visualises real‑time OSINT, SIGINT, and satellite data.
Learn to deploy equivalent OSINT pipelines using command‑line tools and Python libraries.
Apply ethical OSINT principles to collect, correlate, and analyse public‑source intelligence.

You Should Know:

1. Aggregating Live Geopolitical Data Feeds

Redroom’s intelligence portal pulls from 100+ global news sources, performs entity extraction and sentiment analysis, and maps relationships between events. To build a similar pipeline, start by collecting RSS feeds and applying NLP for classification.

Step‑by‑step guide (Linux/macOS):

Collect RSS feeds – Use `feedparser` in Python to fetch and parse news.
```
pip install feedparser
```
Extract entities & sentiment – Leverage `spaCy` or transformers.
```
pip install spacy
python -m spacy download en_core_web_sm
```

Example script:

import feedparser, spacy
nlp = spacy.load("en_core_web_sm")
news = feedparser.parse("http://rss.cnn.com/rss/edition.rss")
for entry in news.entries[:5]:
doc = nlp(entry.title + " " + entry.summary)
print("Entities:", [ent.text for ent in doc.ents])

3. Automate collection – Use `cron` (Linux) or Task Scheduler (Windows) to run the script periodically.

For Windows, you can run the same Python script using PowerShell; use `Schedule-Task` to automate it.

2. Real‑Time Threat Visualization on a 3D Globe

Redroom’s 3D threat globe uses WebGL to display live aircraft, vessels, seismic events, and fires. You can replicate a basic threat globe using `react-globe.gl` or a standalone Three.js setup.

Step‑by‑step guide (web development):

Set up a Three.js globe – Install Node.js and create a new project.
```
npm init -y
npm install three globe.gl
```

Fetch live threat data – Use public APIs (e.g., NASA FIRMS for active fires).

// Fetch fire data (simplified)
fetch('https://firms.modaps.eosdis.nasa.gov/api/area/csv/...')
.then(response => response.text())
.then(csv => {
// Parse CSV and add markers to globe
});

Render interactive globe – Use `Globe` component from globe.gl.
```
const Globe = require('globe.gl');
const myGlobe = Globe()(document.getElementById('globe'))
.globeImageUrl('//unpkg.com/three-globe/example/img/earth-blue-marble.jpg');
```
For offline or local deployment, you can also use CesiumJS, which provides high‑fidelity 3D maps with satellite imagery.
SIGINT from Open Sources – From RTL‑SDR to Dashboard
While Redroom’s SIGINT portal aggregates public signals (aircraft, vessels, etc.), true signal intelligence involves capturing raw radio data. Use an RTL‑SDR dongle and open‑source tools to build your own SIGINT feed.

Step‑by‑step guide (Linux):

Install SIGINT toolkit – Use SIGpi, a bash script that installs popular SIGINT tools.
```
git clone https://github.com/joecupano/SIGpi
cd SIGpi
./install.sh
```
Capture aircraft ADSB‑B – Run `dump1090` to decode ADS‑B signals.
```
dump1090 --interactive --1et
```
Consolidate into a dashboard – Use INTERCEPT, a web dashboard that unifies multiple SIGINT tools.
```
git clone https://github.com/smittix/intercept
cd intercept && ./intercept.sh
```
On Windows, you can use SDR (SDRSharp) with a RTL‑SDR driver, then feed data into a local visualization tool.

4. Satellite Tracking and Orbital Intelligence

Redroom’s Orbit portal provides real‑time satellite tracking using Two‑Line Element (TLE) data. You can build a similar tracker with Python and the `skyfield` library.

Step‑by‑step guide (cross‑platform Python):

1. Install dependencies

pip install skyfield requests

2. Fetch and parse TLEs – Download the latest NORAD TLE set from CelesTrak.

from skyfield.api import load, EarthSatellite
url = 'https://celestrak.org/NORAD/elements/gp.php?CATNR=25544'
data = requests.get(url).text
lines = data.splitlines()
satellite = EarthSatellite(lines[bash], lines[bash], lines[bash])

3. Compute current position – Use SGP4 propagation to get latitude/longitude.

ts = load.timescale()
t = ts.now()
geocentric = satellite.at(t)
subpoint = geocentric.subpoint()
print(f"Lat: {subpoint.latitude.degrees}, Lon: {subpoint.longitude.degrees}")

4. Visualise on a map – Use `folium` to plot the ground track.

5. Ethical OSINT and Responsible Data Handling

Redroom explicitly mandates ethical OSINT principles: minimise harm, verify before publishing, protect privacy, and respect legal boundaries. These principles are critical when handling live data from public sources.

Step‑by‑step guide to ethical automation:

Anonymise your requests – Use Tor or VPN to avoid exposing your real IP.
```
sudo apt install tor
proxychains4 python your_osint_script.py
```
Respect rate limits – Implement delays (time.sleep()) between API calls.
Document sources – Keep a log of every data source and the date/time of collection.
Encrypt sensitive findings – Use `gpg` or `openssl` to protect stored intelligence.
Correlating Multiple Domains – The Analyst’s Power Move
Redroom’s main value is multi‑domain correlation: linking news events with SIGINT map data. You can achieve this by storing all collected data in a SQLite database and writing simple correlation queries.

Example correlation query (SQLite):

-- Find news articles mentioning "Houthi" that occurred within 1 hour of a vessel being within 50km of Yemen.
SELECT news.headline, news.timestamp, vessels.name
FROM news
JOIN vessels ON ABS(JULIANDAY(news.timestamp) - JULIANDAY(vessels.timestamp)) < 0.0417
WHERE news.entity = 'Houthi' AND vessels.region = 'Yemen Coast';

Run this periodically using a cron job to automatically surface actionable intelligence.

What Undercode Say:

Redroom lowers the barrier to entry for geopolitical OSINT by packaging multiple complex data streams into an accessible, open‑source interface.
The platform’s true innovation is not just data aggregation but the contextual correlation it enables, turning raw public signals into structured intelligence.
However, the ease of use also raises ethical concerns; without proper training, analysts might inadvertently violate privacy or legal norms.
The inclusion of SIGINT and satellite tracking in a browser‑based tool democratises capabilities once reserved for nation‑states, which could empower both defenders and adversaries.
Future iterations might incorporate deep learning for pattern‑of‑life analysis and predictive threat modelling, moving from real‑time awareness to proactive alerting.
Overall, Redroom exemplifies the shift toward “OSINT as a platform” – a trend that will likely accelerate as AI and cloud APIs lower development costs.
For cybersecurity professionals, Redroom offers a free sandbox to practice multi‑source intelligence correlation without expensive commercial solutions.
The community should contribute additional data sources and correlation modules to enhance its value while maintaining strict ethical guidelines.
Redroom’s MIT license encourages forking and customisation, making it a foundation for specialised intelligence dashboards in corporate or academic settings.
Finally, always remember: open source does not mean open season – ethical OSINT is a discipline, not a loophole.

Prediction:

+1 Redroom and similar platforms will accelerate the commoditisation of real‑time OSINT, enabling smaller organisations and individual researchers to compete with state‑level intelligence capabilities.
-1 The proliferation of easy‑to‑use OSINT dashboards will inevitably lead to misuse by hostile actors, including targeting of critical infrastructure and mass surveillance of activists.
+1 AI‑driven correlation and anomaly detection will become standard features, automatically alerting analysts to hidden patterns across disparate public data sets.
-1 Governments may respond by tightening regulations on public data access or imposing licensing requirements for OSINT platforms, potentially fragmenting the open‑source ecosystem.
+1 The open‑source nature of Redroom will foster a community‑driven intelligence sharing model, similar to MISP but for geopolitical and SIGINT data, enhancing collective security.

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