The OSINT Newsletter - Issue #20
A primer on geolocation for OSINT
👋 Hey, everyone. My writing is typically focused on the collection, enrichment, and analysis of unstructured data. I really enjoy searching for hard-to-find data and creating playbooks for new workflows and methodologies. What I haven’t focused a lot of my writing on is geolocation. There are a few reasons for that.
🏋️♂️ Geolocation is an OSINT skill that requires refining raw talent. Sure, there are tools that can assist you in finding the coordinates of an image and video, but unlike other OSINT workflows, there’s really no way to automate it. There’s no service out there that takes an image or video and returns a precise location. If there are features of tools that claim this, they aren’t as robust as what we’ve seen in reverse username, email, or phone number tools out there.
💪 It’s difficult to take a reader from zero to hero on a skill that requires focus, repetition, and creative, critical thinking skills to master; however, with the new format of this newsletter, I can at least create a primer to get you started. This will likely be part one of a multi-part series I’ll release over the next year.
⬇️ Let’s dig into this month’s OSINT newsletter… a primer for geolocation.
Google Maps + Street View + Reverse Image Search
Google Maps added a new feature that lets you split street view and map view on one screen. This used to be something you needed to use a third-party application for. Now that you can split the view, you can more easily walk the streets of an area of interest to pinpoint the exact location for geolocation.
There’s an issue, though. Google Maps doesn’t let you use Google Lens while on street view. If you find something that’s interesting, you’ll have to take a screenshot and then upload that image to do a reverse image search.
Fortunately, there’s a solution. A browser extension called Reverse Image Search allows you to take a screenshot on the page and it will automatically run a reverse image search for you. This saves you a few steps and lets you stay focused on your geolocation efforts.
Photo Location Finder - Github
One of the hardest things about geolocation is taking poor-quality images and trying to find unique characteristics that will help you narrow the scope of the world to a specific area and make it manageable for a human to investigate.
I’ve long said that data science and OSINT will converge pretty rapidly in the future. In this case, Google Cloud Vision helps identify possible landmarks, labels, and web entities automatically. This helps investigators enrich their images and videos of interest at scale.
Photo Location Finder is an open source application that will process an entire directory of images through Google Cloud Vision and return a JSON file of all matching landmarks, labels, and web entities.
Setting this up is as simple as getting a Google Cloud Vision API key and specifying the path to the directory all of your images are in.
OSINT Geo_Extractor - Github
It’s also a Python module, making it easy to develop other applications or utilities.
If you’re doing geolocation-specific investigations into the conflict in Ukraine and find yourself frequenting the previously mentioned websites often, consider setting this tool up and creating a combined map view for easier analysis.
✅ This is the end of the free subscription to The OSINT Newsletter. To see practical applications of OSINT tactics and techniques, please consider supporting this publication with a paid subscription.
🚀 Paid subscribers get access to practical OSINT tactics and techniques I haven’t published publicly online. This issue explores practical applications for geolocation in addition to step-by-step guides for OSINT techniques.
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