So now i guess my question is. How can i prevent this type of thing in the future? I dont want a message that hits a mess of other positive rules to be autolearned. Im afraid ham messages of this spammy nature are going to influence my bayes database in a negative way.
What's so spammy about the message that bayes will notice? clearly the INVALID_MSGID is irrelevant here, and that's the only thing you can point out that's even remotely "spammy" about the message.
Quite frankly, I use fool's mailing lists as part of my forced-training on ham. Every day I pump their messages into my ham training as a part of an automated cron job. I do the same for CNN and several other news sites that my users use.
(that said, I've not seen any of the fool messages trigger INVALID_MSGID on my system)
I think you're being massively over-paranoid. Bayes isn't poisoned so easily, and quite frankly, the message IS nonspam and IS very typical of real-world html newsletters sent out by legitimate companies all the time.
If SA's bayes engine would be so radically upset by real-world email, it wouldn't work at all well. It's actually important to feed your bayes DB "spammy ham", otherwise your bayes database is not going to work very well when it comes to distinguishing such subtleties.
It's like training a security guard to recognize criminals by only showing them pictures of suit wearing accountants and prison inmates. What are they going to do when they see a construction worker? Looks more like an inmate than an accountant, must be a criminal. Come to think of it, which do YOU look more like?
Don't isolate your bayes database from reality by giving it false impressions of spam and ham. This does much more harm than good. Teach it everything you can about ham and spam, and keep it realistic. The bayes DB will be able to make much better decisions if you do.
