> Hi,
> I am losing confident in SA, the training process is
> pretty slow or it doesn't seem to be learning.
> I am training SA with around 30-50 manually identified
> spam (moving spam mails to and spam folder created in
> squirrelmail and crond the sa-train command on that
> folder every hour to train and delete them).
>
> The script is tested to be working on the shell before I
> put it on crond
>
> However, I found that the learning process is either not
> right or it is rather slow.
>
> I gone through the headers of the spams and found that
> even almost identical (in content) spams always got a
> score 0.1 and these spams are received on separated
> occasions across several days. This had made me losing
> confident on SA.
>
> I wonder if had it setup correct to detect and learn
> spams . I am using a default setup from qmail-toaster
> cnt50 , do I need more filters to harden my defense? Any
> recommendations you will be appreciated.
>
> Here are sample samples I taken from my mailbox on this
> server,
> (eg, sample spam 1 and 8 are almost identical in content
> but they are both scored with only 0.1 . : (
>
> http://www.keac.com/id3303/spam-egs.txt
Mail #1 here
Content preview: == US Drugstore == Voted as No.1 US pharmacy on Internet
Over 80 meds on our online store We accept Visa, Master Card, JCB, Dinner
& eCheck [...]
Content analysis details: (17.4 points, 5.0 required)
pts rule name description
---- ---------------------- --------------------------------------------------
3.0 RCVD_IN_XBL RBL: Received via a relay in Spamhaus XBL
[68.243.81.116 listed in zen.spamhaus.org]
0.9 RCVD_IN_PBL RBL: Received via a relay in Spamhaus PBL
2.0 RCVD_IN_BL_SPAMCOP_NET RBL: Received via a relay in bl.spamcop.net
[Blocked - see <http://www.spamcop.net/bl.shtml?68.243.81.116>]
1.2 INVALID_DATE Invalid Date: header (not RFC 2822)
1.2 TO_MALFORMED To: has a malformed address
4.0 BOTNET Relay might be a spambot or virusbot
[botnet0.8,ip=68.243.81.116,rdns=68-243-81-116.area7.spcsdns.net,maildomain=mediafutures.org,client,ipinhostname]
1.0 BAYES_60 BODY: Bayesian spam probability is 60 to 80%
[score: 0.6572]
0.1 RDNS_NONE Delivered to trusted network by a host with no rDNS
4.0 JM_SOUGHT_2 JM_SOUGHT_2
