Tom Lane heads up

[DeJuan Jackson]

Just dropping a quick not for Tom Lane. I sent a personal message
today, but I wasn't sure if you'd get it after I remembered all of the
spam filters you've got set up.

Sorry for the off topic post.

---------------------------(end of broadcast)---------------------------
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[Mike Mascari]

Bruce Momjian wrote:

Joe Conway wrote:

The one thing I had *not* been doing, but started to do as of last
night, is to use the false-negatives to explicitly train the Bayesian
filter. It was easy enough to set up. I created an hourly cron job as
follows:

/usr/bin/sa-learn --mbox --spam /path/to/false-neg.mbox

Now I just drop all false negatives into that mailbox, and clean them
out periodically. Hopefully that will make a significant improvement.

I can tell you it certainly will.

Doesn't sa-learn also require you to teach it Ham as well? My
problem has been that sa-learn appears to ignore white-listed emails
and therefore can't learn from 90% of my Ham. Meanwhile, I get spam
that slips through SA that my Mozilla client *correctly* identifies
as Junk. Once a week, I take that Junk email, along with all Ham and
run sa-learn with the appropriate --spam/--ham switch. But it
doesn't seem to be improving. I still get spam which SA fails to
identify but which, 95% of the time, Mozilla correctly identifies.

Mike Mascari

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[Marc G. Fournier]

On Wed, 21 Apr 2004, Joe Conway wrote:

The one thing I had *not* been doing, but started to do as of last
night, is to use the false-negatives to explicitly train the Bayesian
filter. It was easy enough to set up. I created an hourly cron job as
follows:

/usr/bin/sa-learn --mbox --spam /path/to/false-neg.mbox

Now I just drop all false negatives into that mailbox, and clean them
out periodically. Hopefully that will make a significant improvement.

This, for me, has made the big difference, since the false-negatives don't
get autolearned :(

----
Marc G. Fournier Hub.Org Networking Services (http://www.hub.org)
Email: sc*****@hub.org Yahoo!: yscrappy ICQ: 7615664

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[Marc G. Fournier]

On Wed, 21 Apr 2004, Joe Conway wrote:

The one thing I had *not* been doing, but started to do as of last
night, is to use the false-negatives to explicitly train the Bayesian
filter. It was easy enough to set up. I created an hourly cron job as
follows:

/usr/bin/sa-learn --mbox --spam /path/to/false-neg.mbox

Now I just drop all false negatives into that mailbox, and clean them
out periodically. Hopefully that will make a significant improvement.

This, for me, has made the big difference, since the false-negatives don't
get autolearned :(

----
Marc G. Fournier Hub.Org Networking Services (http://www.hub.org)
Email: sc*****@hub.org Yahoo!: yscrappy ICQ: 7615664

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[Joe Conway]

Marc G. Fournier wrote:

On Wed, 21 Apr 2004, Joe Conway wrote:

/usr/bin/sa-learn --mbox --spam /path/to/false-neg.mbox

Now I just drop all false negatives into that mailbox, and clean them
out periodically. Hopefully that will make a significant improvement.

This, for me, has made the big difference, since the false-negatives don't
get autolearned :(

Actually, even much of what does (correctly) get marked as spam, ends up
with autolearn=no, because it seems SpamAssassin is somewhat
conservative with autolearning. I just sent this off list to Michael Chaney:
---------------------------------------------------------------------

I've noticed that the threshold for autolearn seems too high, i.e. a
high proportion of email correctly marked as spam, has autolearn=no.
Here's an example:

X-Spam-Status: Yes, hits=3.7 required=2.5
tests=BAYES_44,HTML_FONT_INVISIBLE, HTML_IMAGE_ONLY_04,
HTML_MESSAGE,MIME_HTML_NO_CHARSET,MIME_HTML_ONLY,
MIME_HTML_ONLY_MULTI autolearn=no version=2.63

Now in /etc/mail/spamassassin/local.cf I have this setting:

# Enable Bayes auto-learning
auto_learn 1
bayes_auto_learn_threshold_spam 6

From the SA docs, I get the impression that autolearn cannot be made
more aggressive.

So in order to counteract that, I just made an additional change -- I
put in a mail filter rule that automatically forwards any mail marked as
spam, but with autolearn=no, to false-neg.mbox. This should help too, I
think.

Joe
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[Joe Conway]

Marc G. Fournier wrote:

On Wed, 21 Apr 2004, Joe Conway wrote:

/usr/bin/sa-learn --mbox --spam /path/to/false-neg.mbox

Now I just drop all false negatives into that mailbox, and clean them
out periodically. Hopefully that will make a significant improvement.

This, for me, has made the big difference, since the false-negatives don't
get autolearned :(

Actually, even much of what does (correctly) get marked as spam, ends up
with autolearn=no, because it seems SpamAssassin is somewhat
conservative with autolearning. I just sent this off list to Michael Chaney:
---------------------------------------------------------------------

I've noticed that the threshold for autolearn seems too high, i.e. a
high proportion of email correctly marked as spam, has autolearn=no.
Here's an example:

X-Spam-Status: Yes, hits=3.7 required=2.5
tests=BAYES_44,HTML_FONT_INVISIBLE, HTML_IMAGE_ONLY_04,
HTML_MESSAGE,MIME_HTML_NO_CHARSET,MIME_HTML_ONLY,
MIME_HTML_ONLY_MULTI autolearn=no version=2.63

Now in /etc/mail/spamassassin/local.cf I have this setting:

# Enable Bayes auto-learning
auto_learn 1
bayes_auto_learn_threshold_spam 6

From the SA docs, I get the impression that autolearn cannot be made
more aggressive.

So in order to counteract that, I just made an additional change -- I
put in a mail filter rule that automatically forwards any mail marked as
spam, but with autolearn=no, to false-neg.mbox. This should help too, I
think.

Joe
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[Jim Seymour]

Joe Conway <ma**@joeconway.com> wrote:

[snip]
The one thing I had *not* been doing, but started to do as of last
night, is to use the false-negatives to explicitly train the Bayesian
filter.

[snip]

As you've discovered, the hard way, one must constantly train Bayesian
filters. This means that every false positive has to be fed back
through it with whatever means your version uses to tell it "No, this
was *not* spam," and every false negative, the converse.

--
Jim Seymour | Spammers sue anti-spammers:
js******@LinxNet.com | http://www.LinxNet.com/misc/spam/slapp.php
http://jimsun.LinxNet.com | Please donate to the SpamCon Legal Fund:
| http://www.spamcon.org/legalfund/

---------------------------(end of broadcast)---------------------------
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[Jim Seymour]

Joe Conway <ma**@joeconway.com> wrote:

[snip]
The one thing I had *not* been doing, but started to do as of last
night, is to use the false-negatives to explicitly train the Bayesian
filter.

[snip]

As you've discovered, the hard way, one must constantly train Bayesian
filters. This means that every false positive has to be fed back
through it with whatever means your version uses to tell it "No, this
was *not* spam," and every false negative, the converse.

--
Jim Seymour | Spammers sue anti-spammers:
js******@LinxNet.com | http://www.LinxNet.com/misc/spam/slapp.php
http://jimsun.LinxNet.com | Please donate to the SpamCon Legal Fund:
| http://www.spamcon.org/legalfund/

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[Marc G. Fournier]

On Wed, 21 Apr 2004, Mike Mascari wrote:

Doesn't sa-learn also require you to teach it Ham as well? My problem
has been that sa-learn appears to ignore white-listed emails and
therefore can't learn from 90% of my Ham. Meanwhile, I get spam that
slips through SA that my Mozilla client *correctly* identifies as Junk.
Once a week, I take that Junk email, along with all Ham and run sa-learn
with the appropriate --spam/--ham switch. But it doesn't seem to be
improving. I still get spam which SA fails to identify but which, 95% of
the time, Mozilla correctly identifies.

I'm finding it gets better over time ... a few always slip through the
crack, but not near as many today as yesterday ... as for Ham, I have a
mailbox that I save all my 'Answered Emails' to (from friends, lists, etc)
that I periodically run through as --ham

----
Marc G. Fournier Hub.Org Networking Services (http://www.hub.org)
Email: sc*****@hub.org Yahoo!: yscrappy ICQ: 7615664

---------------------------(end of broadcast)---------------------------
TIP 7: don't forget to increase your free space map settings

[Marc G. Fournier]

On Wed, 21 Apr 2004, Mike Mascari wrote:

Doesn't sa-learn also require you to teach it Ham as well? My problem
has been that sa-learn appears to ignore white-listed emails and
therefore can't learn from 90% of my Ham. Meanwhile, I get spam that
slips through SA that my Mozilla client *correctly* identifies as Junk.
Once a week, I take that Junk email, along with all Ham and run sa-learn
with the appropriate --spam/--ham switch. But it doesn't seem to be
improving. I still get spam which SA fails to identify but which, 95% of
the time, Mozilla correctly identifies.

I'm finding it gets better over time ... a few always slip through the
crack, but not near as many today as yesterday ... as for Ham, I have a
mailbox that I save all my 'Answered Emails' to (from friends, lists, etc)
that I periodically run through as --ham

----
Marc G. Fournier Hub.Org Networking Services (http://www.hub.org)
Email: sc*****@hub.org Yahoo!: yscrappy ICQ: 7615664

---------------------------(end of broadcast)---------------------------
TIP 7: don't forget to increase your free space map settings

[Lincoln Yeoh]

At 10:08 AM 4/20/2004 +0200, Karel Zak wrote:

4. Very long list of procmail filters on header and body patterns.

It must be pretty difficult maintain these header and body patterns
and the others lists. I had same problem and I resolve if by
"spamassassin", it knows learn and it's more simple than procmailrc
coding. Now I have cca 5% of all spams in my INBOX.

My spam:ham ratio is about 98:2 (98% spam), excluding mailing lists.

So far its manageable though rather annoying - fortunately in my situation
I can regard as spam emails that are in html (or have HTML) and not in my
whitelist. That gets rid of about 50% of the spam, the other 40% or so get
filtered via another simple filter.

My situation=I don't really have to answer messages to my personal email
account from ignorant strangers that send me html email. Your situation may
be different.

So far I haven't seen any html emails that were really worth reading, even
the one or two from relatives (who I white-list to not be rude ;) ). I go
through that folder once in a while and it works for me - so far I don't
recall having HTML emails from strangers that weren't spam.

I've had plain text messages from silly strangers (and a silly colleague)
that used lots of !!!! and stupid subject lines - actual content barely
worth replying to. e.g. Help!!!!!

Situation is different at work. But company pays for antispam software.
Ironically while we sell Sophos Puremessage (which seems to be pretty
good), it's for larger companies/orgs than us (>1000 users). ;).

The backup MX thing is not very useful in most cases. Seems similar for DNS
- doesn't appear that useful to have your names resolvable while your site
is unreachable. OK the error messages may be slightly less embarassing?

Regards,
Link.

---------------------------(end of broadcast)---------------------------
TIP 9: the planner will ignore your desire to choose an index scan if your
joining column's datatypes do not match

[Lincoln Yeoh]

At 10:08 AM 4/20/2004 +0200, Karel Zak wrote:

4. Very long list of procmail filters on header and body patterns.

It must be pretty difficult maintain these header and body patterns
and the others lists. I had same problem and I resolve if by
"spamassassin", it knows learn and it's more simple than procmailrc
coding. Now I have cca 5% of all spams in my INBOX.

My spam:ham ratio is about 98:2 (98% spam), excluding mailing lists.

So far its manageable though rather annoying - fortunately in my situation
I can regard as spam emails that are in html (or have HTML) and not in my
whitelist. That gets rid of about 50% of the spam, the other 40% or so get
filtered via another simple filter.

My situation=I don't really have to answer messages to my personal email
account from ignorant strangers that send me html email. Your situation may
be different.

So far I haven't seen any html emails that were really worth reading, even
the one or two from relatives (who I white-list to not be rude ;) ). I go
through that folder once in a while and it works for me - so far I don't
recall having HTML emails from strangers that weren't spam.

I've had plain text messages from silly strangers (and a silly colleague)
that used lots of !!!! and stupid subject lines - actual content barely
worth replying to. e.g. Help!!!!!

Situation is different at work. But company pays for antispam software.
Ironically while we sell Sophos Puremessage (which seems to be pretty
good), it's for larger companies/orgs than us (>1000 users). ;).

The backup MX thing is not very useful in most cases. Seems similar for DNS
- doesn't appear that useful to have your names resolvable while your site
is unreachable. OK the error messages may be slightly less embarassing?

Regards,
Link.

---------------------------(end of broadcast)---------------------------
TIP 9: the planner will ignore your desire to choose an index scan if your
joining column's datatypes do not match

[Joe Conway]

Marc G. Fournier wrote:

On Mon, 19 Apr 2004, Joe Conway wrote:

Marc G. Fournier wrote:

Huh? I just use Spamassassin myself, with Razor/Pyzor/DCC and Bayes all
enabled ...

I use exactly the same setup. But recently I've noticed that the
spammers are getting smarter -- I think 20% of it is slipping by the
filters. I'm going to need something better.

do you force learn those spam that get through the cracks? I get about 20
or 30 messages that slip through the cracks, which I process through with
sa-learn nightly ...

Sorry to drag this OT thread on even longer, but it seems to be a topic
many are interested in ;-)

I wanted to report back that after just 2 days of forced (supervised)
learning, the bayesian filter is now nailing about 99% of all spam.
*Many, many, thanks* for the suggestion.

But I wonder why the autolearn feature is so conservative? At this point
I'm getting lots of stuff like this:

X-Spam-Status: Yes, hits=5.8 required=2.5 tests=BAYES_99,HTML_FONT_BIG,
HTML_MESSAGE autolearn=no version=2.63
X-Spam-Report:
* 0.1 HTML_MESSAGE BODY: HTML included in message
* 0.3 HTML_FONT_BIG BODY: HTML has a big font
* 5.4 BAYES_99 BODY: Bayesian spam probability is 99 to 100%
* [score: 1.0000]

Notice that, even though I get a hit on BAYES_99, I still get
autolearn=no. Ah well, I guess I should be asking that question of the
SpamAssassin guys. Also notice that this sucker would have gotten
through with a score of only 0.4 had it not been for the bayesian filter.

Again, thanks.

Joe
---------------------------(end of broadcast)---------------------------
TIP 9: the planner will ignore your desire to choose an index scan if your
joining column's datatypes do not match

[Joe Conway]

Marc G. Fournier wrote:

On Mon, 19 Apr 2004, Joe Conway wrote:

Marc G. Fournier wrote:

Huh? I just use Spamassassin myself, with Razor/Pyzor/DCC and Bayes all
enabled ...

I use exactly the same setup. But recently I've noticed that the
spammers are getting smarter -- I think 20% of it is slipping by the
filters. I'm going to need something better.

do you force learn those spam that get through the cracks? I get about 20
or 30 messages that slip through the cracks, which I process through with
sa-learn nightly ...

Sorry to drag this OT thread on even longer, but it seems to be a topic
many are interested in ;-)

I wanted to report back that after just 2 days of forced (supervised)
learning, the bayesian filter is now nailing about 99% of all spam.
*Many, many, thanks* for the suggestion.

But I wonder why the autolearn feature is so conservative? At this point
I'm getting lots of stuff like this:

X-Spam-Status: Yes, hits=5.8 required=2.5 tests=BAYES_99,HTML_FONT_BIG,
HTML_MESSAGE autolearn=no version=2.63
X-Spam-Report:
* 0.1 HTML_MESSAGE BODY: HTML included in message
* 0.3 HTML_FONT_BIG BODY: HTML has a big font
* 5.4 BAYES_99 BODY: Bayesian spam probability is 99 to 100%
* [score: 1.0000]

Notice that, even though I get a hit on BAYES_99, I still get
autolearn=no. Ah well, I guess I should be asking that question of the
SpamAssassin guys. Also notice that this sucker would have gotten
through with a score of only 0.4 had it not been for the bayesian filter.

Again, thanks.

Joe
---------------------------(end of broadcast)---------------------------
TIP 9: the planner will ignore your desire to choose an index scan if your
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[Alvar Freude]

-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA1

Hi,

- -- Joe Conway <ma**@joeconway.com> wrote:

I use exactly the same setup. But recently I've noticed that the spammers
are getting smarter -- I think 20% of it is slipping by the filters. I'm
going to need something better.

I recently rebuild by bayes database because it was corrupted; feeded it with
about 1000 low-point-spam and nowabout two spams slipping by the filter in
one day while 200 to 300 are catched.
Ciao
Alvar

- --
** Alvar C.H. Freude -- http://alvar.a-blast.org/ -- http://odem.org/
** Berufsverbot? http://odem.org/aktuelles/staatsanwalt.de.html
** ODEM.org-Tour: http://tour.odem.org/
***5 Jahre Blaster:*http://www.a-blast.de/ | http://www.a-blast.de/statistik/

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Version: GnuPG v1.2.3 (FreeBSD)

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KVN3aQfw34S+IWokGX60OFA=
=hkKo
-----END PGP SIGNATURE-----
---------------------------(end of broadcast)---------------------------
TIP 7: don't forget to increase your free space map settings

[Alvar Freude]

-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA1

Hi,

- -- Joe Conway <ma**@joeconway.com> wrote:

I use exactly the same setup. But recently I've noticed that the spammers
are getting smarter -- I think 20% of it is slipping by the filters. I'm
going to need something better.

I recently rebuild by bayes database because it was corrupted; feeded it with
about 1000 low-point-spam and nowabout two spams slipping by the filter in
one day while 200 to 300 are catched.
Ciao
Alvar

- --
** Alvar C.H. Freude -- http://alvar.a-blast.org/ -- http://odem.org/
** Berufsverbot? http://odem.org/aktuelles/staatsanwalt.de.html
** ODEM.org-Tour: http://tour.odem.org/
***5 Jahre Blaster:*http://www.a-blast.de/ | http://www.a-blast.de/statistik/

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Version: GnuPG v1.2.3 (FreeBSD)

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KVN3aQfw34S+IWokGX60OFA=
=hkKo
-----END PGP SIGNATURE-----
---------------------------(end of broadcast)---------------------------
TIP 7: don't forget to increase your free space map settings

[Marc G. Fournier]

On Fri, 23 Apr 2004, Joe Conway wrote:

Marc G. Fournier wrote:

On Mon, 19 Apr 2004, Joe Conway wrote:

Marc G. Fournier wrote:
Huh? I just use Spamassassin myself, with Razor/Pyzor/DCC and Bayes all
enabled ...

I use exactly the same setup. But recently I've noticed that the
spammers are getting smarter -- I think 20% of it is slipping by the
filters. I'm going to need something better.

do you force learn those spam that get through the cracks? I get about 20
or 30 messages that slip through the cracks, which I process through with
sa-learn nightly ...

Sorry to drag this OT thread on even longer, but it seems to be a topic
many are interested in ;-)

I wanted to report back that after just 2 days of forced (supervised)
learning, the bayesian filter is now nailing about 99% of all spam.
*Many, many, thanks* for the suggestion.

But I wonder why the autolearn feature is so conservative? At this point
I'm getting lots of stuff like this:

X-Spam-Status: Yes, hits=5.8 required=2.5 tests=BAYES_99,HTML_FONT_BIG,
HTML_MESSAGE autolearn=no version=2.63
X-Spam-Report:
* 0.1 HTML_MESSAGE BODY: HTML included in message
* 0.3 HTML_FONT_BIG BODY: HTML has a big font
* 5.4 BAYES_99 BODY: Bayesian spam probability is 99 to 100%
* [score: 1.0000]

Notice that, even though I get a hit on BAYES_99, I still get
autolearn=no. Ah well, I guess I should be asking that question of the
SpamAssassin guys. Also notice that this sucker would have gotten
through with a score of only 0.4 had it not been for the bayesian filter.

BAYES_99 means that its already been found in the bayes filter, so why
would it once more autolearn it? :)
----
Marc G. Fournier Hub.Org Networking Services (http://www.hub.org)
Email: sc*****@hub.org Yahoo!: yscrappy ICQ: 7615664

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[Marc G. Fournier]

On Fri, 23 Apr 2004, Joe Conway wrote:

Marc G. Fournier wrote:

On Mon, 19 Apr 2004, Joe Conway wrote:

Marc G. Fournier wrote:
Huh? I just use Spamassassin myself, with Razor/Pyzor/DCC and Bayes all
enabled ...

I use exactly the same setup. But recently I've noticed that the
spammers are getting smarter -- I think 20% of it is slipping by the
filters. I'm going to need something better.

do you force learn those spam that get through the cracks? I get about 20
or 30 messages that slip through the cracks, which I process through with
sa-learn nightly ...

Sorry to drag this OT thread on even longer, but it seems to be a topic
many are interested in ;-)

I wanted to report back that after just 2 days of forced (supervised)
learning, the bayesian filter is now nailing about 99% of all spam.
*Many, many, thanks* for the suggestion.

But I wonder why the autolearn feature is so conservative? At this point
I'm getting lots of stuff like this:

X-Spam-Status: Yes, hits=5.8 required=2.5 tests=BAYES_99,HTML_FONT_BIG,
HTML_MESSAGE autolearn=no version=2.63
X-Spam-Report:
* 0.1 HTML_MESSAGE BODY: HTML included in message
* 0.3 HTML_FONT_BIG BODY: HTML has a big font
* 5.4 BAYES_99 BODY: Bayesian spam probability is 99 to 100%
* [score: 1.0000]

Notice that, even though I get a hit on BAYES_99, I still get
autolearn=no. Ah well, I guess I should be asking that question of the
SpamAssassin guys. Also notice that this sucker would have gotten
through with a score of only 0.4 had it not been for the bayesian filter.

BAYES_99 means that its already been found in the bayes filter, so why
would it once more autolearn it? :)
----
Marc G. Fournier Hub.Org Networking Services (http://www.hub.org)
Email: sc*****@hub.org Yahoo!: yscrappy ICQ: 7615664

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[Gregory Wood]

Marc G. Fournier wrote:

BAYES_99 means that its already been found in the bayes filter, so why
would it once more autolearn it? :)

To add more spam words to its vocabulary of course. Learning works both
ways...

Greg

---------------------------(end of broadcast)---------------------------
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[Gregory Wood]

Marc G. Fournier wrote:

BAYES_99 means that its already been found in the bayes filter, so why
would it once more autolearn it? :)

To add more spam words to its vocabulary of course. Learning works both
ways...

Greg

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[Martijn van Oosterhout]

On Tue, Apr 20, 2004 at 01:06:18AM -0400, Tom Lane wrote:

3. I have noticed that bouncing any machine that sends "HELO
sss.pgh.pa.us" gets rid of a ton of spam and viruses. I don't know of
any real clean way to do this, but I have a sendmail.cf hack for it.
By the way, thanks very much for this tip. This almost in one hit made
a many of our spam and virus filters redundant. Very nice on the load.
I'd noticed that some perl mail modules appear to get this wrong but it
efficiently catches our customers sending viruses and spam through our
relay too.

I'm using Exim 3 so I can only pick this up after the mail has been
received but with Exim 4 I should be able to kill the email in SMTP
stage.

--
Martijn van Oosterhout <kl*****@svana.org> http://svana.org/kleptog/ Patent. n. Genius is 5% inspiration and 95% perspiration. A patent is a
tool for doing 5% of the work and then sitting around waiting for someone
else to do the other 95% so you can sue them.

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