Re: Remove SA tagging when learning as ham
On Wed, 20 Jun 2018 09:20:56 +0200
Matus UHLAR - fantomas wrote:
> >> >> > On Mon, 18 Jun 2018 06:13:06 -0600 @lbutlr wrote:
> >> >> >> I have a script that runs when a mail is moved out of the
> >> >> >> Junk folder to pass the mail through sa-learn --ham,
>
> >> >You can work around the plugin's deficiencies by using
> >> >autotraining or doing some additional training, but then the
> >> >plugin is of limited relevance.
>
> >On Tue, 19 Jun 2018 10:41:51 +0200 Matus UHLAR - fantomas wrote:
> >> Of course, both autotraining AND the fixing errors are required to
> >> work properly.
>
> On 19.06.18 22:27, RW wrote:
> >Then you have worst of both worlds. I'm not saying the plugin is
> >completely useless for Bayes, but 'not completely useless' is not
> >much of a recommendation.
>
> I'd say the best, or nearly the best:
>
> - autolearning works
> - user can correct mistakes.
SA autotraining is can be too selective, and both the plugin and
autotraining are poor at learning ham. And many users wont correct all
mistakes.
It seem inferior to simple manual imap training folders, or webmail
training.
> do you know of better way than manual reviewing all BAYES scores for
> all mail?
I do, but I wouldn't recommend it for general users.
I use training folders and have a sieve script that does something
like this:
if score >= 15 && sanity-checks {
# definitely spam (zero FPs)
file into
if needs-training-as-spam {
file into
}
}
elsif score >= 5 {
# low-scoring spam or spam that need inspection
file into
}
else {
if needs-training-as-ham {
file a copy into
}
# start of filing rules
...
}
Anything in or gets
manually moved to a training folder. I occasionally copy some manually
selected ham as well, to keep up the numbers.
Almost all my ham hits BAYES_00 these days, and with local rules >99%
of spam is over the 15 points needed for automated handling. It
requires very little effort.
Re: CVE-2018-12558: DOS in perl module Email::Address
On 6/20/2018 1:30 PM, Bill Cole wrote: http://www.openwall.com/lists/oss-security/2018/06/19/3 SpamAssassin does not use Email::Address. Thanks, Bill, for clarifying that. I've been concerned about this for hours - but too busy today research it myself. -- Rob McEwen
Re: CVE-2018-12558: DOS in perl module Email::Address
On 20 Jun 2018, at 11:11, Ian Zimmerman wrote: > This is probably of interest to readers of this list. Only very tangentially. > http://www.openwall.com/lists/oss-security/2018/06/19/3 SpamAssassin does not use Email::Address.
Fwd: CVE-2018-12558: DOS in perl module Email::Address
This is probably of interest to readers of this list. http://www.openwall.com/lists/oss-security/2018/06/19/3 -- Please don't Cc: me privately on mailing lists and Usenet, if you also post the followup to the list or newsgroup. To reply privately _only_ on Usenet and on broken lists which rewrite From, fetch the TXT record for no-use.mooo.com.
Re: Remove SA tagging when learning as ham
>> > On Mon, 18 Jun 2018 06:13:06 -0600 @lbutlr wrote: >> >> I have a script that runs when a mail is moved out of the Junk >> >> folder to pass the mail through sa-learn --ham, >You can work around the plugin's deficiencies by using autotraining >or doing some additional training, but then the plugin is of limited >relevance. On Tue, 19 Jun 2018 10:41:51 +0200 Matus UHLAR - fantomas wrote: Of course, both autotraining AND the fixing errors are required to work properly. On 19.06.18 22:27, RW wrote: Then you have worst of both worlds. I'm not saying the plugin is completely useless for Bayes, but 'not completely useless' is not much of a recommendation. I'd say the best, or nearly the best: - autolearning works - user can correct mistakes. one downside is that users will corerct only in case of score mismatch, not bayes mismatch (so, even BAYES_999 won't be reported when not causing FP). do you know of better way than manual reviewing all BAYES scores for all mail? -- Matus UHLAR - fantomas, uh...@fantomas.sk ; http://www.fantomas.sk/ Warning: I wish NOT to receive e-mail advertising to this address. Varovanie: na tuto adresu chcem NEDOSTAVAT akukolvek reklamnu postu. My mind is like a steel trap - rusty and illegal in 37 states.
