The reason "Apoploe vesrreaitais" is detected as Greek is because the first "word" is "phonetically" similar to the word απόπλους, which means sailing/shipping and it is rooted in ancient Greek. If we were to write Αποπλοuς using roman characters, we would write apoplous or apoloi (plural, in Greek is αποπλοΐ). So I think that the model understands that "oe" suffix is used to represent the Greek suffix "οι" that is used for plurals. The rest of the word is rather close phonetically, so there is some model that maps phonetic representations to the correct word.
The other phrase seems to be combined of words classified as Portuguese, Spanish, Lithuanian, and Luxembourgish.
My hypothesis here is more that these models are trained more on western languages than others and thus our latent representation of "language" is going to appear like Latin gibberish due to a combination of the evolution of these languages as well as human bias. ("It's all Greek to me")
Regardless, here is me, a native speaker, disproving your hypothesis.
I tried the following words in google translate elefantas ailaifantas ailaiphantas elaiphandas elaiphandac.
The suggested detections are ελέφαντας, αιλαιφάντας, αιλαιφάντας, ελαϊφάντας, ελαϊφάντας, however, the translations are elephant, illuminated, illuminated, elephant, elephant respectively. The first is correct. When mapping the roman characters back to greek, there is loss of information, this is seen in the umlaut above iota which makes the pronunciation from ε [e] - like to αϊ [ai̯], and the emphasis denoted via the mark above epsilon (έ).
Notice that all all the words have an edit distance of >=4, a soundex distance of at most 1, and a metaphone distance of at most 1 [1]. The suggested words as I said above are near homophones of the correct word bar a few minor details.
I guess that says more about you than about my reply. Also, I'm a native speaker as well. That doesn't really have any bearing, my comment above comes from what I know about common implementations of language detection algorithms, not so much from looking at how Google Translate behaves.
It does have a lot of bearing actually. While I am a native speaker, my spelling skills are atrocious as everything is a sequence of sounds in my head more so than a sequence of letters. To get around my spelling issues I frequently use homophones to find the correct spelling of a word which uses soundex or similar algorithms to find the correct word along with character mappings between the two languages.
Regardless, I believe I have proved the hypothesis to not be true.