anyone can help with the shortcircuit SA plugin?
Posted: 20 Jul 2016 14:24
I'd like to shortcircuit BAYES_999 so when an email is 99.9% SPAM it should be scored and classified as SPAM immediately bypassing all other tests BUT STILL be learned by BAYES as SPAM to keep the DB up to date.
Now this is what I have so far but no learning is happening. is this correct?
inside my local.shortcircuit.cf
Apparently the meaning of this directive:
is the following so I need to counter
Now this is what I have so far but no learning is happening. is this correct?
Code: Select all
tflags BAYES_999 learn
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# read for scores: /var/lib/spamassassin/3.004001/updates_spamassassin_org/60_shortcircuit.cf
# read for details: https://spamassassin.apache.org/full/3.4.x/doc/Mail_SpamAssassin_Plugin_Shortcircuit.html
# Shortcircuit - stop evaluation early if high-accuracy rules fire
#
loadplugin Mail::SpamAssassin::Plugin::Shortcircuit
# Some shortcircuiting, if the plugin is enabled
#
ifplugin Mail::SpamAssassin::Plugin::Shortcircuit
#
# default: strongly-whitelisted mails are *really* whitelisted now, if the
# shortcircuiting plugin is active, causing early exit to save CPU load.
# Uncomment to turn this on
#
# shortcircuit USER_IN_WHITELIST on
# shortcircuit USER_IN_DEF_WHITELIST on
# shortcircuit USER_IN_ALL_SPAM_TO on
# shortcircuit SUBJECT_IN_WHITELIST on
# the opposite; blacklisted mails can also save CPU
#
# shortcircuit USER_IN_BLACKLIST on
# shortcircuit USER_IN_BLACKLIST_TO on
# shortcircuit SUBJECT_IN_BLACKLIST on
# if you have taken the time to correctly specify your "trusted_networks",
# this is another good way to save CPU
#
# shortcircuit ALL_TRUSTED on
# and a well-trained bayes DB can save running rules, too
#
shortcircuit BAYES_999 spam
tflags BAYES_999 learn
# shortcircuit BAYES_99 spam
# shortcircuit BAYES_00 ham
endif # Mail::SpamAssassin::Plugin::Shortcircuit
# Not needed for now but no idea how exactly to change this.
# The default Shortcircuit spam score is 100 while ham is -100.
# These scores may be altered with the "shortcircuit_spam_score" and
# "shortcircuit_ham_score" variables.
Code: Select all
shortcircuit BAYES_999 spam
Code: Select all
tflags TEST noautolearn
spam
Shortcircuit the rule using a set of defaults; override the default score of this rule with the score from shortcircuit_spam_score, set the noautolearn tflag, and set priority to -100. In other words, equivalent to:
shortcircuit TEST on
priority TEST -100
score TEST 100
tflags TEST noautolearn