Listen to this Post
Introduction:
In the world of Open Source Intelligence (OSINT), the line between casual observation and critical data gathering is often thinner than a pizza crust. A recent social media post by Sylvain HAJRI, founder of the OSINT tool Epieos, humorously tests the “Pentagon Pizza Meter” from a location near the Pentagon. While the post is lighthearted, it underscores a fundamental truth in cybersecurity and intelligence: publicly shared information, from GPS coordinates to restaurant check-ins, can be exploited to track individuals, verify movements, and build detailed profiles. This article dissects the technical methodologies behind such geolocation OSINT, providing a roadmap for both understanding the risk and conducting ethical reconnaissance.
Learning Objectives:
- Understand the principles of geolocation OSINT and how metadata from social media can be used to pinpoint locations.
- Learn to utilize command-line tools and online platforms to extract and verify geographic data.
- Master the techniques of cross-referencing visual cues with satellite imagery for precise location analysis.
You Should Know:
- Decoding the Coordinates: From Social Banter to Actionable Intel
The post’s comment section is a goldmine for an OSINT practitioner. Users casually drop what appear to be GPS coordinates in response to the “Pizza Meter” test.
– `38°53’25.4″N 77°05’19.0″W` (provided by James A.)
– `38.921081, -77.032357` (provided by Lionel Mouchabac)
Step‑by‑step guide: What this does and how to use it.
These are two different formats of geographic coordinates. The first is in Degrees, Minutes, Seconds (DMS) , while the second is in Decimal Degrees (DD) . Your first step is to normalize and analyze these points.
– Step 1: Conversion and Verification. Use a command-line tool like `proj` (part of the PROJ library on Linux) or an online converter to see if they point to the same location.
– Linux Command: To convert the DMS to DD, you can use a simple `bc` calculation or a dedicated tool. For a quick check, use gpsbabel:
Convert DMS to Decimal echo "38°53'25.4\"N 77°05'19.0\"W" | gpsbabel -i nmea -f - -o kml -F - | grep -o "<coordinates>.</coordinates>"
(Note: This requires `gpsbabel` installed: sudo apt-get install gpsbabel).
– Manual Calculation: Decimal Degrees = Degrees + (Minutes/60) + (Seconds/3600). For the latitude: 38 + (53/60) + (25.4/3600) = 38.890389. For the longitude: -(77 + (5/60) + (19.0/3600)) = -77.088611.
– Step 2: Visual Confirmation. Paste the coordinates into a mapping service like Google Earth or Google Maps.
– `38.890389, -77.088611` (Converted from DMS) places you at the intersection of S Oak St and Army Navy Dr, directly adjacent to the Pentagon. This is a logical, publicly accessible point for a photo.
– `38.921081, -77.032357` places you further north, near the Arlington National Cemetery and the Netherlands Carillon. This shows how different coordinates in the same thread can provide multiple points of interest (POIs) for an investigator mapping an individual’s potential movements.
2. Utilizing OSINT Frameworks and Tools for Geolocation
Beyond raw coordinates, the post hints at the use of tools like “Epieos,” which is a professional OSINT tool for email and phone number lookups. However, for geolocation, we rely on imagery analysis and metadata.
Step‑by‑step guide: Reverse Image Searching and Visual Analysis
Assuming Sylvain took a photo with his smartphone and posted it, the image itself could contain Exif data (though LinkedIn strips most of it). However, the visual elements in the picture are the primary vector.
– Step 1: Identify Visual Cues. In the described image (though not visible here), one would look for storefronts (Papa John’s), street signs, unique architecture, or landscaping.
– Step 2: Execute a Reverse Image Search. On Linux, you can use tools like `exiftool` to check local images for metadata, but for online images, use `curl` to grab the image URL and feed it into a reverse search API or website.
– Linux Command: Use `curl -O
` to download the image. Then, use a CLI tool like `sift` (a Go implementation of the TinEye API) or simply open Firefox with a search URL. [bash] Example using curl and a generic reverse search (conceptual) wget [bash] -O pizza_shop.jpg Then manually upload to images.google.com or use a script with the Google Vision API
– Step 3: Correlate with Mapping Tools. Use Google Earth Pro (free on Windows/Linux) to view historical imagery. If the Papa John’s has a specific sign or awning color visible in the photo, you can scroll through years of satellite history to see when that branding was installed, narrowing down the time the photo could have been taken.
- The “Pizza Meter” as a Social Engineering & Surveillance Concept
The “Pentagon Pizza Meter” is a pop culture reference suggesting that a high volume of pizza deliveries to specific government buildings (like the Pentagon or the White House) indicates late-night work, potentially signaling a crisis or imminent military action. From a cybersecurity perspective, this is a form of logistics intelligence.
Step‑by‑step guide: Simulating Traffic and Delivery Pattern Analysis
While we cannot tap into pizza delivery logs without a warrant, we can model the concept using publicly available traffic and crowd-sourced data to understand patterns around sensitive sites.
– Step 1: API Collection. Use the Google Maps Places API or the Yelp Fusion API to search for “pizza” near a specific coordinate (e.g., the Pentagon).
– Linux Command: Use `curl` to query the API.
curl -X GET -H "Authorization: Bearer YOUR_YELP_API_KEY" "https://api.yelp.com/v3/businesses/search?term=pizza&latitude=38.890389&longitude=-77.088611&radius=1000" | jq '.'
(The `jq` tool parses the JSON output, install with sudo apt-get install jq).
– Step 2: Traffic Pattern Analysis. Use the Google Maps Distance Matrix API to estimate travel times from these pizza shops to the target building during different times (e.g., 12:00 PM vs. 10:00 PM). A sudden decrease in travel time (less traffic) combined with consistent orders could be a proxy for identifying late-night activity spikes.
4. Defensive Measures: Protecting Your Digital Location Footprint
For security professionals, understanding these OSINT techniques is crucial for defensive purposes. The playful post by Sylvain is a reminder that even harmless check-ins can be dangerous for personnel working at or near sensitive locations.
Step‑by‑step guide: Hardening Your Digital Presence
- Step 1 (Mobile – Android/iOS): Disable Geotagging for your camera app. On Android, go to Camera Settings > Location tags (disable). On iOS, go to Settings > Privacy & Security > Location Services > Camera > Never.
- Step 2 (Windows 11): For photos taken with a Windows tablet or phone, you must strip metadata before sharing.
- Command Line: Use a PowerShell command to remove Exif data from a batch of photos.
Get-ChildItem -Path "C:\Users\YourName\Pictures" -Filter .jpg | ForEach-Object { Add-Type -AssemblyName System.Drawing; $img = [System.Drawing.Image]::FromFile($<em>.FullName); $img.RemovePropertyItem(0x9286); $img.Save($</em>.FullName + "_stripped.jpg"); $img.Dispose() }(Note: This is a simplified example; robust tools like `exiftool` are recommended for production use).
- Step 3 (Linux): Use `mat2` (Metadata Anonymisation Toolkit) to clean files before distribution.
sudo apt install mat2 mat2 -v my_photo.jpg This creates a clean version: my_photo.cleaned.jpg
What Undercode Say:
- Key Takeaway 1: OSINT is not just about hacking databases; it is the art of aggregating publicly available data—from GPS coordinates in comments to the geometry of a pizza shop sign—to build a compelling intelligence picture.
- Key Takeaway 2: The “Pentagon Pizza Meter” meme, while humorous, represents a real-world attack vector: logistics and pattern-of-life analysis. If you can track pizza deliveries, you can track the people eating them.
Analysis:
This seemingly trivial social media interaction is a masterclass in modern intelligence gathering. It demonstrates that security clearances and physical fences are rendered moot by the metadata and visual data we willingly publish. For the red teamer, it highlights the importance of “doxing” oneself to find leaks. For the blue teamer, it is a stark warning that operational security (OpSec) training must extend to personal social media habits. The use of multiple coordinate formats in the comments shows a diverse technical understanding among the community, but also reveals a lack of OpSec, as they essentially published the exact rooftop from which an operative was observing the Pentagon. In the future, we can expect AI tools to automatically scrape such comment sections, correlate the coordinates with satellite imagery, and instantly profile the individual based on the location history of their social media connections, all without human intervention.
Prediction:
As AI-driven visual analysis matures, the manual “spot the sign” OSINT of today will evolve into automated, real-time geolocation. We will see the rise of defensive “location spoofing” tools becoming standard for high-risk personnel, not just for their devices but for their digital personas, creating a new cyber-arm’s race between OSINT aggregators and privacy advocates.
▶️ Related Video (80% Match):
🎯Let’s Practice For Free:
IT/Security Reporter URL:
Reported By: Shajri Pentagonpizzameter – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
