I'm using. But, maybe with some Bayesian work... it would be possible.
But,
as I said, I'm a bit risk averse and Bayesian poisoning is so easy,
especially at this volume.
I would turn off AWL I think in your situation. But by and large Bayes
poisioning is a myth, at least for the vast majority of people. The junk
spammers stick in seems better at identifying spam than poisioning it. If
you are concered about getting false passes from Bayes, just set the scores
for bayes < 50 to zero, or to some smaller value than the default. If you
get bayes FNs, that is just more work for your customer service types, and
will be self-correcting if they submit them as 'learn as ham'.
Hum. In your case network checks aren't going to help very much, since you
are doing the original sending. So you are going to have to depend a lot
more on rules than most people will. You can/should use the clam
integration to catch the vast majority of the phish messages and actual
virui that spammers will probably try to send. URIBL will probably also be
very helpful, since it checks the target domains referenced in the email
messages.
Loren
