Re: make bayes autolearn ignore specific scores
jdow writes: > From: "Alexander Piavka" <[EMAIL PROTECTED]> > > > On Sat, 15 Jul 2006, Magnus Holmgren wrote: > > > >> On Tuesday 11 July 2006 23:16, Alexander Piavka took the opportunity to > >> write: > >> > Hi , i'd like to know if its possbile and how, to ignore specific rule > >> > scores (like ALL_TRUSTED) then calculating the autolearn threshold for > >> > spam and ham? > >> > >> "Like" ALL_TRUSTED, eh? If you have a problem with ALL_TRUSTED you likely > >> have > >> a bad trusted_networks setting. Adding a host to trusted_networks means > >> that > >> you trust it not to forge headers and not to originate spam, meaning that > >> if > >> ALL_TRUSTED fires then the message *should* definitely be ham, otherwise > >> your > >> assumption that the host can be trusted is wrong. > > > > No i've no problem with ALL_TRUSTED , it's just i thoght it's not a good > > idea to learn every mail from trusted networks as ham, i wanted to make a > > bayes autolearn independent of the sending source and thus ignore > > ALL_TRUSTED > > and some more tests. Since this way bayes would learn from much more ham > > messages than spam messages,esspecialy since most spam messages we get are > > the same. Thus i thougth since the bayes databese size is limited it > > should have learn from at least as much spam mail as ham, to have more > > spam mails detected by bayes. > > But probably i'm wrong or not? > > One might say two things. The first is a startled "Well duh!" The second > is, "if you have ALL_TRUSTED" appear as a rule hit on every message then > you're being silly. > > ALL_TRUSTED does not mean a damn thing with respect to whether a message > is ham or spam. It just says that the received headers are likely to be > accurate in as much as "you" or a "trusted agent" oversees the header > generation. um, no, ALL_TRUSTED means that all of the hosts that relayed the mail were trusted -- including the very first, originating host. This should not happen unless you list a spammer's machine in trusted_networks. --j.
Re: make bayes autolearn ignore specific scores
From: "Alexander Piavka" <[EMAIL PROTECTED]>
On Sat, 15 Jul 2006, Magnus Holmgren wrote:
On Tuesday 11 July 2006 23:16, Alexander Piavka took the opportunity to write:
> Hi , i'd like to know if its possbile and how, to ignore specific rule
> scores (like ALL_TRUSTED) then calculating the autolearn threshold for
> spam and ham?
"Like" ALL_TRUSTED, eh? If you have a problem with ALL_TRUSTED you likely have
a bad trusted_networks setting. Adding a host to trusted_networks means that
you trust it not to forge headers and not to originate spam, meaning that if
ALL_TRUSTED fires then the message *should* definitely be ham, otherwise your
assumption that the host can be trusted is wrong.
No i've no problem with ALL_TRUSTED , it's just i thoght it's not a good
idea to learn every mail from trusted networks as ham, i wanted to make a
bayes autolearn independent of the sending source and thus ignore ALL_TRUSTED
and some more tests. Since this way bayes would learn from much more ham
messages than spam messages,esspecialy since most spam messages we get are
the same. Thus i thougth since the bayes databese size is limited it
should have learn from at least as much spam mail as ham, to have more
spam mails detected by bayes.
But probably i'm wrong or not?
One might say two things. The first is a startled "Well duh!" The second
is, "if you have ALL_TRUSTED" appear as a rule hit on every message then
you're being silly.
ALL_TRUSTED does not mean a damn thing with respect to whether a message
is ham or spam. It just says that the received headers are likely to be
accurate in as much as "you" or a "trusted agent" oversees the header
generation.
{o.o}
Re: make bayes autolearn ignore specific scores
On Sat, 15 Jul 2006, Magnus Holmgren wrote: > On Tuesday 11 July 2006 23:16, Alexander Piavka took the opportunity to write: > > Hi , i'd like to know if its possbile and how, to ignore specific rule > > scores (like ALL_TRUSTED) then calculating the autolearn threshold for > > spam and ham? > > "Like" ALL_TRUSTED, eh? If you have a problem with ALL_TRUSTED you likely have > a bad trusted_networks setting. Adding a host to trusted_networks means that > you trust it not to forge headers and not to originate spam, meaning that if > ALL_TRUSTED fires then the message *should* definitely be ham, otherwise your > assumption that the host can be trusted is wrong. No i've no problem with ALL_TRUSTED , it's just i thoght it's not a good idea to learn every mail from trusted networks as ham, i wanted to make a bayes autolearn independent of the sending source and thus ignore ALL_TRUSTED and some more tests. Since this way bayes would learn from much more ham messages than spam messages,esspecialy since most spam messages we get are the same. Thus i thougth since the bayes databese size is limited it should have learn from at least as much spam mail as ham, to have more spam mails detected by bayes. But probably i'm wrong or not? > > Even if your trusted_networks setting is correct and you feel that mail coming > through all trusted hosts isn't representative, I don't think it would hurt > learning it. > > But to answer your question - use the noautolearn flag, e.g. > > tflags DKIM_SIGNED net nice noautolearn > > Note that there is no way to set or clear a single flag; you have to list all > flags that should be set. Thanks for the solution > > -- > Magnus Holmgren[EMAIL PROTECTED] >(No Cc of list mail needed, thanks) > _.-.. ,'9 )\)`-.,.--. `-.| Piavlo `. \, Alexander \) `. )._\ (\ |// `-,// ]||//" "" ""
Re: make bayes autolearn ignore specific scores
On Tuesday 11 July 2006 23:16, Alexander Piavka took the opportunity to write: > Hi , i'd like to know if its possbile and how, to ignore specific rule > scores (like ALL_TRUSTED) then calculating the autolearn threshold for > spam and ham? "Like" ALL_TRUSTED, eh? If you have a problem with ALL_TRUSTED you likely have a bad trusted_networks setting. Adding a host to trusted_networks means that you trust it not to forge headers and not to originate spam, meaning that if ALL_TRUSTED fires then the message *should* definitely be ham, otherwise your assumption that the host can be trusted is wrong. Even if your trusted_networks setting is correct and you feel that mail coming through all trusted hosts isn't representative, I don't think it would hurt learning it. But to answer your question - use the noautolearn flag, e.g. tflags DKIM_SIGNED net nice noautolearn Note that there is no way to set or clear a single flag; you have to list all flags that should be set. -- Magnus Holmgren[EMAIL PROTECTED] (No Cc of list mail needed, thanks) pgpMPEAHCKhLh.pgp Description: PGP signature
RE: make bayes autolearn ignore specific scores
Alexander Piavka wrote: > > What is the difference between the check_rbl* and check_uridnsbl* > tests. They seem to be made for the same purpose? They are similar, but not the same. check_rbl is for checking MTA IP addresses found in the mail headers. check_uridnsbl is for checking URLs found in the body of the message. -- Bowie
RBL classes (was Re: make bayes autolearn ignore specific scores)
Alexander Piavka wrote: What is the difference between the check_rbl* and check_uridnsbl* tests. They seem to be made for the same purpose? check_rbl* tests look at the IP addresses of the systems that sent the mail -- basically, what shows up in the Received: lines once they get out of your trusted networks area. check_uridnsbl* tests look the domain names in URLs that appear in the body of the message -- in other words, they look at links. P.S. in the future, please start a new thread instead of replying to an old one with a completely different topic. -- Kelson Vibber SpeedGate Communications
Re: make bayes autolearn ignore specific scores
What is the difference between the check_rbl* and check_uridnsbl* tests. They seem to be made for the same purpose? Thanks.
