You're assuming malice, but in this case there's a much more simple explanation: indifference.
VMware want to keep bad stuff off of their customers' machines, and they want to do so without pissing off their customers too much. Carbon Black is a "next gen" endpoint solution, meaning essentially that it uses some kind of ML model in addition to classic AV signatures. I don't know anything about their ML model, but I would guess that it is very probably tuned to slightly prefer false positives to false negatives.
With that background, imagine that a new language called FooBar gets invented. FooBar doesn't get a huge amount of traction for Windows and OSX apps, but pentesters take to it and FooBarRed becomes super popular. That means that the dataset that the ML model is being trained on doesn't contain a lot of FooBar, but when it does, the FooBar is always bad. Naturally, the model decides that as it has only ever tasted bad FooBar, all FooBar is bad.
That's "wrong" from a fairness standpoint, and the solution is for VMware to manually tune the model. But without customer complaints, they are not likely to do so. They're not acting maliciously; they just aren't incentivised to care.