OpenSSL implements crypto primitives, which, as far as we currently know, are mathematically safe. It's clear cut, black and white, it either is implemented correctly and (as far as we know) safe, or it isn't.
Snort works based on fixed rules. It's black and white, either traffic is logged and / or blocked, or it isn't. Basic rules log entire classes of traffic, the ability to engineer around them is very limited. Specialized Snort rules are a cat and mouse game, though.
At least two of the three things ROOST wants to do are machine learning models. They are not black and white, they are fuzzy. Minor changes can be enough to fool a classifier without changing the real semantic meaning for humans.
I have very, very hard doubts Google, OpenAI et al. will release Open Source classifiers which they will actually also use themselves.
Either they will try to get perfect recall, then it certainly will have (probably massive) overreach. Or there will always be false negatives. In the latter case, ML classifiers are IMO the one thing where security through obscurity not only actually works, but is the only thing which keeps them working at all. If you can freely train on an imperfect classifier, you can fool it, no?
I would love this, I like the Open Source approach a lot, but I cannot imagine how this should work in practice.
Also: How should third-party companies be able to reliably "set their own rules" on a probabilistic ML model, anyway, without training it themselves? The thing Roblox published[1] is a classifier for 6 categories. Sure, it's nice that you can e.g. say "I only want to filter profanity" this way - but what constitutes profanity is not controlled by you, but by the whims of a US company, even though this very much is not a globally homogeneous standard.