Ways of filtering erronous email addresses using NLP? Background:

I have a database of user information, in which they registered through a website. 

Objective:

I would like to filter out erroneous emails, not by if it is malformed (i.e. it's missing an @-sign), but rather by "weird strings" in the "local-part" of the address. So examples of erroneous email address are things like: 


zzzzzzzzzzzzzzzzz@gmail.com
asdfasdfasdf@gmail.com
yourenotgettingmyrealemail@gmail.com
123@yahoo.com
test@test.com


I know most of these require some "human" interpretation to figure that they're probably not real, but I was wondering if there are any algorithms that can help me out.
More important than the algorithm is having an existing corpus of labeled data.  Most ML algorithms need to train on a huge amount of text before they start producing useful results (for example a NLP algorithm was trained to generate fiction by reading the entire Harry Potter series).  

Do you have a list of known good and bad e-mail addresses?  

You can still try to group email addresses even if your data isn’t labeled, but it’s harder.