On Sat, 2004-07-03 at 21:47, Mike McMullen wrote:
> The reason we have more ham than spam is because of the use of DNS-based
> blacklists like spamhaus, and spamcop to reject mail from reported spam sites.
> This way we stop them before they even get in the system.
>
> For us that meant in the last 70 days, we stopped 40k+ emails from even
> being seen by MailScanner, SA or ClamAV. When your mail system is
> an old box built out of pieces found in the PC "bone pile" that makes
> a big difference!
>
> So that 40k+ of known spam was stopped, leaving another just under 5k
> that got nabbed by SA. Thats the 6.4% I mentioned in my original post.
>
> The best thing you can do for bayes is to train it religiously each night.
> Since we only have 6-7 email users, I have a absurdly simple script
> that runs sa-learn on each user's Spam and Ham mailbox each night.
> I just name each person's mailbox explicitly in the shell script.
>
> Crude but effective.
>
> Hope this helps,
>
> Mike
We train it daily. :)
I have also been reading up on the sendmail rbl lists. I understand
that using the sorbl lists I have to accept the email upfront in order
to scan the content and run the search. At that point does it drop the
message or just apply a score to it?
Thanks for the ideas.
--
Scot L. Harris
[EMAIL PROTECTED]
QOTD:
"Say, you look pretty athletic. What say we put a pair of tennis
shoes on you and run you into the wall?"
