Matt Kettler wrote to Gustafson, Tim:
At 12:08 PM 8/26/2004, Gustafson, Tim wrote:
This is what makes me thing it's auto-learning in this case:
Aug 26 14:58:33 maze sm-mta[4231]: i7QEwVOQ004231: Milter add: header:
X-Spam-Status: No, hits=-104.9 required=5.0
tests=BAYES_00,\n\tUSER_IN_ALL_SPAM_TO autolearn=ham version=2.64
well, yes, but it doesn't need USER_IN_ALL_SPAM_TO to autolearn that
message as ham, so that's hardly a suggestion that the all_spam_to is
involved.
If you take away the BAYES and USER_IN_ALL_SPAM_TO, which it should,
the score of the email is 0.
By default SA autolearns anything under 0.1. 0 is less than 0.1,
learn as ham by default.
Hi Matt,
You're right. I think what Tim is getting at is (and he can correct me
if I'm wrong) that, sometimes, when folks use all_spam_to, they also
want to ensure that those messages don't get autolearned *at all*,
regardless of their spaminess or haminess. Traffic from this mailing
list is a good example.
Tim, what you want can be done with 3.0 and the bayes_ignore_to
directive. It works like a charm. However, you're using 2.64, which
doesn't support bayes_ignore_to.
Unfortunately, you're kind of out of luck doing this with 2.64. I'd
suggest upgrading if possible. If you happen to be using something like
MIMEDefang or procmail, you could hack a solution to prevent scanning
certain mail, but I really believe upgrading to 3.0 is the easier and
safer route. We've been using it in production for more than a month.
- Ryan
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