Above and Beyond

Ready for takeoff? Let’s tackle May’s aviation challenges!

Galen Reich & Merel Zoet
May 04, 2026

Hi everyone!

Welcome to May’s Bellingcat Open Source Challenge!

With five brand new exercises, our researcher Logan Williams will introduce you to flight tracking. We’ll also share the solutions to last month’s challenges.

May Challenge - Above and Beyond

Did you know there’s around 100 000 flights worldwide, every day? Some of these flights may reveal important information for open source research work. Several free and open source tools allow you to track aircraft on their journeys.

In a recent investigation we used flight-tracking data to verify whether a story in the Dutch newspaper De Telegraaf was legitimate. The largest newspaper in the country published an interview with a woman claiming she organised evacuation flights from Dubai after Iranian attacks on the city began, selling seats at €1,600 (US$ 1,850) each. Bellingcat found that the photo included in the interview was AI-generated, and that according to Flightradar24, no such flight ever departed to the Netherlands.

Our researcher Logan Williams recently built a tool that allows you to visualise historical trends in flight data and spot unusual patterns, like the unusually high US aerial tanker activity before the strikes on Iran for example.

Get started with flight tracking with these five challenges that Logan created - good luck! Challenge.bellingcat.com

As always, our Discord server is the place to find others working on the challenges. Join us in the #bellingcat-challenge channel!

April’s Acoustic Adventures

SPOILER ALERT: From this point on, we’ll be discussing last month’s challenges. If you still plan to complete them, you may want to skip this section.

Screenshot of last month’s challenges

Here are the answers to the ‘Acoustic Adventures’ challenges:

Munttoren
14/02/1976
caravan routes in 1973 Germany and Brazil
Shoebill
Goh Chok Tong

The first challenge featured the soundscape of a city. Writing on their blog, Field Notes, Nezr Kaan began by identifying acoustic details that could point to a specific city. They heard church chimes, bicycle sounds and public service announcements at a station. The announcements are in English, but it doesn’t sound like a native English accent. Searching for the exact phrase that can be heard in the announcement led to a Reddit thread about Amsterdam. This was enough for Nezr to start the search for the churches and bell towers in this city. On towerbells.org, a database of bell towers worldwide, they compared the tempo, the interval pattern as well as the the weight and timbre of each set of bells. One recording of the Munttoren, a tower located in central Amsterdam, perfectly matched the audio in the challenge.

To start solving ‘A Very Cold Case’ you needed to identify the national anthems heard within the clip. Marco Dalla Stella recognised those of the USSR/Russia and Germany. But to identify the third he had to go through a list of prize winning countries at the Winter Olympics. He found the anthem matched that of Czechoslovakia. All three countries underwent major changes in the late 20th century. But the audio clip would have had to have been played before the the dissolution of Czechoslovakia.. Marco looked at the results of Czechoslovakia at the different Olympic Games until he found a podium shared by the USSR, West Germany and Czechoslovakia at the 1976 Winter Olympics in Innsbruck.

‘Synthetic Signals’ was a crash course in identifying deepfake audio for many of you! In the voice recording, there were a few words replaced with deepfake audio - but how to determine which ones? In audio editing software like Audacity, it is possible to generate a spectrogram of the audio fragment. Audio deepfakes are often distinguishable from real human speech by analyzing specific frequency inconsistencies. In the spectrogram below you can see that there are some words where the high frequencies tail off faster. In this case, the absence of higher frequencies helps identify the words in the text that were generated using AI.

Spectogram made in Audacity

In their Field Notes blog, Nezr Kaan explains how they tackled ‘Rapid Fire’. The challenge description discussed unrest in South Sudan, which led Nezr to interpret the audio recording as containing gunshots or combat sounds. However, an animal sound in the background challenged that assumption. Simply googling “South Sudan animal sounds like gunshot” proved sufficient. Recordings of the shoebill, a bird native to South Sudan, matched the sound heard in the challenge audio.

For the last challenge ‘Trace the Call’, the clue lies in the keypad tones. Each number on a keypad produces a unique sound created by combining two specific frequencies, making it possible to distinguish between them using a DTMF decoder. The ringing tone that can be heard also helps to identify the country that the call is being made this Wikipedia article helpfully shares some examples of ringing tones that can be heard in different parts of the world. A Bellingcat Discord member ended up finding the phone number derived from the keypad tones in a press release, linking it to the office of former Singapore prime minister Goh Chok Tong.

That’s it for this month’s Bellingcat Challenge Newsletter. We’d love to hear your feedback on the challenges. You can also join us on Discord and let us know if you have ideas for future challenges.

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Elsewhere on Bellingcat

Before we go, here are some links to other exciting projects from Bellingcat:

See you next month!