Hi everyone!

In this blog post, we’ll see an example of how to solve an interesting GEOINT challenge based on observations from a photo, without using any reverse image search tools or IA things. Only our marvellous brain.

This challenge is proposed by Sector035 on his Twitter account.

I encourage you to first try yourself and attempt to solve this challenge before looking at this solution.

This is by experiencing and trying different approaches that you’ll improve your OSINT skills.

Link to the challenge: https://x.com/Sector035/status/1882394303873638407

So here we go!

We start with a photo posted on Sector035’s Twitter account:

As always, when doint GEOINT, we must focus on ALL the details, whenever they are in background or foreground.

The most obvious thing is that the picture was taken in a coffee shop or a restaurant. In a place where there are tables and chairs.

In front of that place, there’s another store with the end of a word : "PH" and a last word "LAURE?". On the right there’s also the brand’s logo:

Between these two elements, we can also identify another sign with the word "Polo".

At this point, if you still don’t know what this brand is, you can simply Google what we already have:

So the store on the other side is a Ralph Lauren one.

We must determine where the photographer was when he took the photo.
There is a reflection on the window that displays the storefront’s name:

Unfortunately, we’re not able to read what’s written. I decided to use a tool like GIMP to
reverse the image:

Thanks to this manipulation, we can now read a part of the storefront:
"NERO" and "Coffee Roasters"

With only these two pieces of information, we are able to determine the coffee we’re in:

At this point, I tried to use Overpass Turbo with a request to locate a Caffè Nero near a Ralph Lauren store but it eventually failed.
We’ll see why, at the end of this article…

Here is the request:

[out:json][timeout:25];

(
  nwr["brand"="Caffè Nero"];  
)->.caffeNero;

(
  nwr["brand"="Polo Ralph Lauren"](around.caffeNero:30);
);

out body;
>;
out skel qt;

This article is not about Overpass Turbo so we won’t discuss in detail about this request but in short: it finds all "Ralph Lauren" stores that are at 30 meters (maximum) in range of any "Caffè Nero".

But this request ended up with no result (as said, we’ll talk about that at the end).

Let’s try to reduce our search area with clues from the photo. This can be anywhere in the world.

If we look at the floor between the two stores, this is not concrete (maybe tiles?), so we are likely to be inside or in a mall:

This can narrow down our searches to only places inside a building.

Another very useful clue is the emergency exit sign at the top:

These signs are mandatory in public areas in Europe in order to indicate where people should exit in case of emergency.

Looking at the ones used in the USA, they are different:

We could follow this logic on multiple continents to exclude them. I let you do the job 😀

So, we’ll mainly focus on Europe.

One other observation to rely on that sign is the electrical plug just under the bench:

As shown in this screenshot, I added a schema of what the plug looks like (or at least what it seems to look like with the 3 pixels fighting).

According to Wikipedia, these plug types are only found in specific countries:

If we scroll down the Wikipedia page, we eventually find a plug type matching ours:

These are mainly used in UK and in some other Asian countries.

Another interesting thing is the presence of switches to activate/deactivate the plugs, which confirms this socket type.

Let’s move on something else.
The front sign near the entrance contains the word "New" (thanks Captain Obvious). But this small clue gives us the hint that this is an english speaking country:

This is not likely to be in France or Greece or any other country with a first language that is not english.

So far, our observations lead us to an english speaking country with specific electrical plugs and with a Caffè Nero near a Ralph Lauren store located indoors (probably a mall.

This is a lot of clues but not enough to pinpoint a location.

We can then look at the location where the two stores are mainly implemented.

For Ralph Lauren: https://www.ralphlauren.com/locations

For Caffè Nero: https://www.caffenero.com/

Now, if you want, you can play the "find 7 differences" game 😀

With all the elements so far, we can be very confident that the location is likely to be in the UK.

The "Caffè Nero" company is based in London (according to Wikipedia)

There are hundred of them all around the country, so we’ll focus on the Ralph Lauren stores instead ("only" 27 of them in the UK).

That’s the funniest part: we’ll try to look at each Ralph Lauren store in the UK to identify one which could match the view we have of it with the photo.

Reminder:

• RED: The store name, followed by a sign and the logo
• GREEN: A gray metal separator under the sign and between the name and logo with a light attached to it.
• BLUE: Some big window showing the inside of the store.

Let’s search on Google Maps:

It shouldn’t take that long because there are only 27 of them in the country.

One location seems to match:

Let’s look closer and check with Google Street View:

The logo on the sign seems a bit different as the name on the left. But everything else matches.

The big issue here, is that there is no Caffè Nero in front of that Ralph Lauren store:

But if we search on Google Maps for "Caffè Nero" in this area:

It magically appears while it was not there by default when we zoomed in.

Maybe if you read this article in a few weeks, months… this will be updated but for now we don’t see it by default.

We’ll see that this is because it is a new shop that has been opened for a month (at the time of writting this article). So it is not correctly referenced yet.

If we look at the Google Maps page:

We can easily determine where the photographer was when he took that photo.

The location of this Caffè Nero is: Unit 136, McArthur Glen Designer Outlet, York YO19 4TA, United Kingdom

So now, why didn’t Overpass Turbo find this location?

Overpass Turbo runs requests by using the OpenStreetMap project. Unfortunately, the map hasn’t been updated yet, so the objects are not matching: the Ralph Lauren store exists but not the Caffè Nero.

We can go further and try to find the opening date of this coffee shop on the Internet:

In these videos, we learn that the shop’s location has changed over the past few months and is now located in York Designer Outlet.

Some other articles talk about this change:

And that’s all!

I hope you enjoyed your reading and that you’ve learnt some new things about the reasearch methodology.

Don’t hesitate to contact me directly on my Twitter if you have any suggestions.

Mea culpa if there are mistakes, English is not my first language :p

See you!