Too high performances on a classification problem
As noted by Peter, you should split your data into test and train
sets before fitting the TfidfVectorizer to the training set (not to
all the data).

Pandas read_json() is not reading your data from file the way you
want. You are expecting df[&quot;lista_asm&quot;] to be a Series of list
objects (each containing strings). This Series is instead a  Series
of strings (formatted to appear like a list of strings). You must
parse the strings into a list, if that is what you want. But I
believe that the TfidfVectorizer().fit method wants strings, not a
list of strings. (This issue was apparent before your edit)

Similar to the first issue, you should avoid using the
RandomOverSampler() on the test data. If you want to use it, apply it
only to the training data. I suspect that it may be creating
duplicates or near-duplicate records, some of which are later split
into the test set. Try not oversampling at all and evaluate the
performance.