Nigel Frankcom wrote:
On Sat, 05 Aug 2006 14:08:45 +0200, Arik Raffael Funke
<[EMAIL PROTECTED]> wrote:
how to I get spamd/spamc to always add the spamassassin report headers?
I.e. also to ham messages...
I have the following in my local.cf and user_pref.cf but to no apparent use:
use_auto_whitelist 0
use_bayes 0
add_header all Report _REPORT_
add_header all Status _YESNO_, hits=_HITS_ required=_REQD_ tests=_TESTS_
autolearn=_AUTOLEARN_ version=_VERSION_
I am using version 3.1.4.
report_safe 1
That wasn't it either. As I understand the documentation this config
variable is supposed to attach the original message unmodified to a
spamassassin spam report message. This is not what I was looking for.
For me the usual X-Spam-Status headers suffice, but I also want them in
ham. As a call with "spamassassin ham.txt" would produce... just I want
them also with "less ham.txt | spamc".
I attach my local.cf below to avoid any uncertainties.
Thanks for the help.
- Arik
-------- File: local.cf -----------
# This is the right place to customize your installation of SpamAssassin.
#
# See 'perldoc Mail::SpamAssassin::Conf' for details of what can be
# tweaked.
#
# Only a small subset of options are listed below
#
###########################################################################
# Add *****SPAM***** to the Subject header of spam e-mails
#
# rewrite_header Subject *****SPAM*****
# Save spam messages as a message/rfc822 MIME attachment instead of
# modifying the original message (0: off, 2: use text/plain instead)
#
# report_safe 1
# Set which networks or hosts are considered 'trusted' by your mail
# server (i.e. not spammers)
#
# trusted_networks 212.17.35.
# Set file-locking method (flock is not safe over NFS, but is faster)
#
# lock_method flock
# Set the threshold at which a message is considered spam (default: 5.0)
#
# required_score 5.0
# Use Bayesian classifier (default: 1)
#
use_bayes 0
# Bayesian classifier auto-learning (default: 1)
#
bayes_auto_learn 0
# Set headers which may provide inappropriate cues to the Bayesian
# classifier
#
# bayes_ignore_header X-Bogosity
# bayes_ignore_header X-Spam-Flag
# bayes_ignore_header X-Spam-Status
use_auto_whitelist 0
use_bayes 0
add_header all Report _REPORT_
add_header all Status _YESNO_, hits=_HITS_ required=_REQD_ tests=_TESTS_
autolearn=_AUTOLEARN_ version=_VERSION_
report_safe 1
