OSINT Tracing: Where Was This Photo Taken?

OSINT Tracking: Where Was This Photo Taken?

In this lab, you'll apply real OSINT (Open Source Intelligence) techniques to determine the geographic location of an image. There are no monuments, visible street names, or obvious clues—just an urban scene with architectural details, subtle signs, and some cultural hints.

The photo was anonymously shared on a server linked to suspicious activities. No EXIF data is directly accessible. Your mission as a cybersecurity analyst is to precisely identify the city and country where the image was taken.

In this lab you will learn:

• Strategic visual analysis of urban images
• Use of reverse image search and linguistic deduction
• Geolocation with OSINT tools
• Hypothesis validation from a forensic terminal

🌱 How to Start This Lab

👉 This challenge is solved from your browser, but the final validation is done inside the brokendb virtual machine.

1. If you don't have it yet, download the virtual machine from this link:

1https://storage.googleapis.com/cybersecurity-machines/brokendb-lab.ova

1. Import the virtual machine into VirtualBox or VMware.
2. Start the VM and log in as the user student:4geeks-lab.

📄 Instructions

This is the only trace left by the attacker:

Download it and study it carefully. Your task is to find the city and country where this image was taken. To do this, you can use:

1. Carefully observe the image. There is no clear text, but there are details that can help you.

2. Use OSINT tools:

   • Reverse image search on Google Images
   • Analysis with ExifTool (online) if you decide to examine metadata
   • Visual comparison on Google Maps or Street View

3. When you think you know the city and country, go to the virtual machine and run the validator in the console with the following command:

1validate-location

Enter the city and country in the following format:

1city,country

Example:

1paris,france

If your answer is correct, you will get the flag:

✅ Correct!
🎁 Flag: 4GEEKS{EXAMPLE_FLAG}

This exercise simulates a real analysis where you must extract geographic intelligence from an image without context. It's not enough to just look—you have to think like an analyst, deduce from visual language, and corroborate hypotheses with open tools.

Are you ready to look beyond the obvious?

Good luck, Analyst!