Re: spam scores being neutralized by bayes

Blake Hudson <[email protected]>
Newsgroups gmane.mail.virus.maiamailguard
Message-ID <[email protected]>
Jason, it sounds like your Bayes database has learned SPAM. This could 
be from incorrect user reports (messages were reported as NOT SPAM when 
they were SPAM) or from auto learning.

My suggestion is to turn off auto learning (bayes_auto_learn 0 in 
local.cf) and use Maia's digest function to confirm HAM/SPAM daily in 
order to train bayes. To help speed up the learning you may want to 
clear out your current bayes db. You can do this with the maiadbtool.pl 
script and the --clear-bayes option.

--Blake

Jason Street wrote on 7/7/2015 4:43 AM:
> I hope are small group of Maia users are keeping well.
>
> I am slowly getting to grips with Maia one problem I am having is with 
> the scores being assigned to email and as a result a lot of genuine 
> spam is reaching inboxes.
>
> The problem seems to be that Bayes (?) is neutralizing the scoring and 
> as a result email that would have been spam is allowed through.
>
> For example this scoring for spam that reached inbox
>
>   1.700     URIBL_DBL_SPAM     Contains an URL listed in the DBL 
> blocklist
>   1.449     RCVD_IN_BRBL_LASTEXT     (No description provided)
>   0.437     HTML_IMAGE_RATIO_02     HTML has a low ratio of text to 
> image area
>   0.100     DKIM_SIGNED     Domain Keys Identified Mail: message has a 
> signature
>   0.001     HTML_MESSAGE     HTML included in message
>   -0.001     SPF_PASS     SPF: sender matches SPF record
>   -0.100     DKIM_VALID     Message has at least one valid DKIM or DK 
> signature
>   -0.100     DKIM_VALID_AU     Message has a valid DKIM or DK 
> signature from author's domain
>   -1.900     BAYES_00     Bayesian spam probability is 0 to 1%:)
>
> What is the best way to resolve this?
>
> ¬¬JS
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