Look carefully at both the specific detection as well as portions of the Event log entry, though you need to understand a bit more about how Defender actually works to see what I saw in an instant.
What you need to know about Defender is that for several years now, it has been one of the most advanced apps that Microsoft has created to take advantage of their ML.NET machine learning (i.e. Artificial Intelligence) abilities that have been created and advancing in parallel to Windows.
Microsoft Defender uses ML.NET to stop malware | .NET
Introduction to Windows Machine Learning | Microsoft Docs
Though this machine learning is really used throughout Defender's operation, it's most prevalent within certain specific detections which are designated by a suffix of "!ml" attached to the end of the detection name, which you should note is included in the one which detected your app.
Since these detections are related specifically to machine learning, they are inherently also found via real-time protection, so manual or automated scans will not find them.
The other clue to this within the Event log entry is the FastPath Detection type, which though maybe not obvious also implies machine learning as that's really how the dynamic, quick detection systems within Defender all truly operate.
I could now try to explain the potential reasons for this detection, but to a developer such as yourself this should be fairly obvious as a combination of a likely script within your code with a similarity to that found within the actual Wacatac malicious software that mis-triggered the machine learning and caused a false positive detection.
If this detection continues via real-time - machine learning, then you should manually submit your app using the WDSI Portal (under More pulldown) for developers to indicate it's a false positive, so it can be evaluated by first the machine learning system and then possibly a human to cause the detection to be tweaked to avoid this.
Antimalware and cybersecurity portal - Microsoft Security Intelligence