# <@LICENSE>
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to you under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# </@LICENSE>
=head1 NAME
Mail::SpamAssassin::Plugin::Bayes - determine spammishness using a Bayesian classifier
=head1 DESCRIPTION
This is a Bayesian-style probabilistic classifier, using an algorithm based on
the one detailed in Paul Graham's I<A Plan For Spam> paper at:
http://www.paulgraham.com/spam.html
It also incorporates some other aspects taken from Graham Robinson's webpage
on the subject at:
http://radio.weblogs.com/0101454/stories/2002/09/16/spamDetection.html
And the chi-square probability combiner as described here:
http://www.linuxjournal.com/print.php?sid=6467
The results are incorporated into SpamAssassin as the BAYES_* rules.
=head1 METHODS
=cut
package Mail::SpamAssassin::Plugin::Bayes;
use strict;
use warnings;
use bytes;
use re 'taint';
BEGIN {
eval { require Digest::SHA; import Digest::SHA qw(sha1 sha1_hex); 1 }
or do { require Digest::SHA1; import Digest::SHA1 qw(sha1 sha1_hex) }
}
use Mail::SpamAssassin;
use Mail::SpamAssassin::Plugin;
use Mail::SpamAssassin::PerMsgStatus;
use Mail::SpamAssassin::Logger;
use Mail::SpamAssassin::Util qw(untaint_var);
# pick ONLY ONE of these combining implementations.
use Mail::SpamAssassin::Bayes::CombineChi;
# use Mail::SpamAssassin::Bayes::CombineNaiveBayes;
our @ISA = qw(Mail::SpamAssassin::Plugin);
use vars qw{
$IGNORED_HDRS
$MARK_PRESENCE_ONLY_HDRS
%HEADER_NAME_COMPRESSION
$OPPORTUNISTIC_LOCK_VALID
};
# Which headers should we scan for tokens? Don't use all of them, as it's easy
# to pick up spurious clues from some. What we now do is use all of them
# *less* these well-known headers; that way we can pick up spammers' tracking
# headers (which are obviously not well-known in advance!).
# Received is handled specially
$IGNORED_HDRS = qr{(?: (?:X-)?Sender # misc noise
|Delivered-To |Delivery-Date
|(?:X-)?Envelope-To
|X-MIME-Auto[Cc]onverted |X-Converted-To-Plain-Text
|Subject # not worth a tiny gain vs. to db size increase
# Date: can provide invalid cues if your spam corpus is
# older/newer than ham
|Date
# List headers: ignore. a spamfiltering mailing list will
# become a nonspam sign.
|X-List|(?:X-)?Mailing-List
|(?:X-)?List-(?:Archive|Help|Id|Owner|Post|Subscribe
|Unsubscribe|Host|Id|Manager|Admin|Comment
|Name|Url)
|X-Unsub(?:scribe)?
|X-Mailman-Version |X-Been[Tt]here |X-Loop
|Mail-Followup-To
|X-eGroups-(?:Return|From)
|X-MDMailing-List
|X-XEmacs-List
# gatewayed through mailing list (thanks to Allen Smith)
|(?:X-)?Resent-(?:From|To|Date)
|(?:X-)?Original-(?:From|To|Date)
# Spamfilter/virus-scanner headers: too easy to chain from
# these
|X-MailScanner(?:-SpamCheck)?
|X-Spam(?:-(?:Status|Level|Flag|Report|Hits|Score|Checker-Version))?
|X-Antispam |X-RBL-Warning |X-Mailscanner
|X-MDaemon-Deliver-To |X-Virus-Scanned
|X-Mass-Check-Id
|X-Pyzor |X-DCC-\S{2,25}-Metrics
|X-Filtered-B[Yy] |X-Scanned-By |X-Scanner
|X-AP-Spam-(?:Score|Status) |X-RIPE-Spam-Status
|X-SpamCop-[^:]+
|X-SMTPD |(?:X-)?Spam-Apparently-To
|SPAM |X-Perlmx-Spam
|X-Bogosity
# some noisy Outlook headers that add no good clues:
|Content-Class |Thread-(?:Index|Topic)
|X-Original[Aa]rrival[Tt]ime
# Annotations from IMAP, POP, and MH:
|(?:X-)?Status |X-Flags |X-Keywords |Replied |Forwarded
|Lines |Content-Length
|X-UIDL? |X-IMAPbase
# Annotations from Bugzilla
|X-Bugzilla-[^:]+
# Annotations from VM: (thanks to Allen Smith)
|X-VM-(?:Bookmark|(?:POP|IMAP)-Retrieved|Labels|Last-Modified
|Summary-Format|VHeader|v\d-Data|Message-Order)
# Annotations from Gnus:
| X-Gnus-Mail-Source
| Xref
)}x;
# Note only the presence of these headers, in order to reduce the
# hapaxen they generate.
$MARK_PRESENCE_ONLY_HDRS = qr{(?: X-Face
|X-(?:Gnu-?PG|PGP|GPG)(?:-Key)?-Fingerprint
|D(?:KIM|omainKey)-Signature
)}ix;
# tweaks tested as of Nov 18 2002 by jm posted to -devel at
# http://sourceforge.net/p/spamassassin/mailman/message/12977556/
# for results. The winners are now the default settings.
use constant IGNORE_TITLE_CASE => 1;
use constant TOKENIZE_LONG_8BIT_SEQS_AS_TUPLES => 0;
use constant TOKENIZE_LONG_8BIT_SEQS_AS_UTF8_CHARS => 1;
use constant TOKENIZE_LONG_TOKENS_AS_SKIPS => 1;
# tweaks by jm on May 12 2003, see -devel email at
# http://sourceforge.net/p/spamassassin/mailman/message/14844556/
use constant PRE_CHEW_ADDR_HEADERS => 1;
use constant CHEW_BODY_URIS => 1;
use constant CHEW_BODY_MAILADDRS => 1;
use constant HDRS_TOKENIZE_LONG_TOKENS_AS_SKIPS => 1;
use constant BODY_TOKENIZE_LONG_TOKENS_AS_SKIPS => 1;
use constant URIS_TOKENIZE_LONG_TOKENS_AS_SKIPS => 0;
use constant IGNORE_MSGID_TOKENS => 0;
# tweaks of 12 March 2004, see bug 2129.
use constant DECOMPOSE_BODY_TOKENS => 1;
use constant MAP_HEADERS_MID => 1;
use constant MAP_HEADERS_FROMTOCC => 1;
use constant MAP_HEADERS_USERAGENT => 1;
# tweaks, see http://issues.apache.org/SpamAssassin/show_bug.cgi?id=3173#c26
use constant ADD_INVIZ_TOKENS_I_PREFIX => 1;
use constant ADD_INVIZ_TOKENS_NO_PREFIX => 0;
# We store header-mined tokens in the db with a "HHeaderName:val" format.
# some headers may contain lots of gibberish tokens, so allow a little basic
# compression by mapping the header name at least here. these are the headers
# which appear with the most frequency in my db. note: this doesn't have to
# be 2-way (ie. LHSes that map to the same RHS are not a problem), but mixing
# tokens from multiple different headers may impact accuracy, so might as well
# avoid this if possible. These are the top ones from my corpus, BTW (jm).
%HEADER_NAME_COMPRESSION = (
'Message-Id' => '*m',
'Message-ID' => '*M',
'Received' => '*r',
'User-Agent' => '*u',
'References' => '*f',
'In-Reply-To' => '*i',
'From' => '*F',
'Reply-To' => '*R',
'Return-Path' => '*p',
'Return-path' => '*rp',
'X-Mailer' => '*x',
'X-Authentication-Warning' => '*a',
'Organization' => '*o',
'Organisation' => '*o',
'Content-Type' => '*c',
'x-spam-relays-trusted' => '*RT',
'x-spam-relays-untrusted' => '*RU',
);
# How many seconds should the opportunistic_expire lock be valid?
$OPPORTUNISTIC_LOCK_VALID = 300;
# Should we use the Robinson f(w) equation from
# http://radio.weblogs.com/0101454/stories/2002/09/16/spamDetection.html ?
# It gives better results, in that scores are more likely to distribute
# into the <0.5 range for nonspam and >0.5 for spam.
use constant USE_ROBINSON_FX_EQUATION_FOR_LOW_FREQS => 1;
# How many of the most significant tokens should we use for the p(w)
# calculation?
use constant N_SIGNIFICANT_TOKENS => 150;
# How many significant tokens are required for a classifier score to
# be considered usable?
use constant REQUIRE_SIGNIFICANT_TOKENS_TO_SCORE => -1;
# How long a token should we hold onto? (note: German speakers typically
# will require a longer token than English ones.)
use constant MAX_TOKEN_LENGTH => 15;
###########################################################################
sub new {
my $class = shift;
my ($main) = @_;
$class = ref($class) || $class;
my $self = $class->SUPER::new($main);
bless ($self, $class);
$self->{main} = $main;
$self->{conf} = $main->{conf};
$self->{use_ignores} = 1;
$self->register_eval_rule("check_bayes");
$self;
}
sub finish {
my $self = shift;
if ($self->{store}) {
$self->{store}->untie_db();
}
%{$self} = ();
}
###########################################################################
# Plugin hook.
# Return this implementation object, for callers that need to know
# it. TODO: callers shouldn't *need* to know it!
# used only in test suite to get access to {store}, internal APIs.
#
sub learner_get_implementation { return shift; }
###########################################################################
# Plugin hook.
# Called in the parent process shortly before forking off child processes.
sub prefork_init {
my ($self) = @_;
if ($self->{store} && $self->{store}->UNIVERSAL::can('prefork_init')) {
$self->{store}->prefork_init;
}
}
###########################################################################
# Plugin hook.
# Called in a child process shortly after being spawned.
sub spamd_child_init {
my ($self) = @_;
if ($self->{store} && $self->{store}->UNIVERSAL::can('spamd_child_init')) {
$self->{store}->spamd_child_init;
}
}
###########################################################################
# Plugin hook.
sub check_bayes {
my ($self, $pms, $fulltext, $min, $max) = @_;
return 0 if (!$self->{conf}->{use_learner});
return 0 if (!$self->{conf}->{use_bayes} || !$self->{conf}->{use_bayes_rules});
if (!exists ($pms->{bayes_score})) {
my $timer = $self->{main}->time_method("check_bayes");
$pms->{bayes_score} = $self->scan($pms, $pms->{msg});
}
if (defined $pms->{bayes_score} &&
($min == 0 || $pms->{bayes_score} > $min) &&
($max eq "undef" || $pms->{bayes_score} <= $max))
{
if ($self->{conf}->{detailed_bayes_score}) {
$pms->test_log(sprintf ("score: %3.4f, hits: %s",
$pms->{bayes_score},
$pms->{bayes_hits}));
}
else {
$pms->test_log(sprintf ("score: %3.4f", $pms->{bayes_score}));
}
return 1;
}
return 0;
}
###########################################################################
# Plugin hook.
sub learner_close {
my ($self, $params) = @_;
my $quiet = $params->{quiet};
# do a sanity check here. Weird things happen if we remain tied
# after compiling; for example, spamd will never see that the
# number of messages has reached the bayes-scanning threshold.
if ($self->{store}->db_readable()) {
warn "bayes: oops! still tied to bayes DBs, untying\n" unless $quiet;
$self->{store}->untie_db();
}
}
###########################################################################
# read configuration items to control bayes behaviour. Called by
# BayesStore::read_db_configs().
sub read_db_configs {
my ($self) = @_;
# use of hapaxes. Set on bayes object, since it controls prob
# computation.
$self->{use_hapaxes} = $self->{conf}->{bayes_use_hapaxes};
}
###########################################################################
sub ignore_message {
my ($self,$PMS) = @_;
return 0 unless $self->{use_ignores};
my $ig_from = $self->{main}->call_plugins ("check_wb_list",
{ permsgstatus => $PMS, type => 'from', list => 'bayes_ignore_from' });
my $ig_to = $self->{main}->call_plugins ("check_wb_list",
{ permsgstatus => $PMS, type => 'to', list => 'bayes_ignore_to' });
my $ignore = $ig_from || $ig_to;
dbg("bayes: not using bayes, bayes_ignore_from or _to rule") if $ignore;
return $ignore;
}
###########################################################################
# Plugin hook.
sub learn_message {
my ($self, $params) = @_;
my $isspam = $params->{isspam};
my $msg = $params->{msg};
my $id = $params->{id};
if (!$self->{conf}->{use_bayes}) { return; }
my $msgdata = $self->get_body_from_msg ($msg);
my $ret;
eval {
local $SIG{'__DIE__'}; # do not run user die() traps in here
my $timer = $self->{main}->time_method("b_learn");
my $ok;
if ($self->{main}->{learn_to_journal}) {
# If we're going to learn to journal, we'll try going r/o first...
# If that fails for some reason, let's try going r/w. This happens
# if the DB doesn't exist yet.
$ok = $self->{store}->tie_db_readonly() || $self->{store}->tie_db_writable();
} else {
$ok = $self->{store}->tie_db_writable();
}
if ($ok) {
$ret = $self->_learn_trapped ($isspam, $msg, $msgdata, $id);
if (!$self->{main}->{learn_caller_will_untie}) {
$self->{store}->untie_db();
}
}
1;
} or do { # if we died, untie the dbs.
my $eval_stat = $@ ne '' ? $@ : "errno=$!"; chomp $eval_stat;
$self->{store}->untie_db();
die "bayes: (in learn) $eval_stat\n";
};
return $ret;
}
# this function is trapped by the wrapper above
sub _learn_trapped {
my ($self, $isspam, $msg, $msgdata, $msgid) = @_;
my @msgid = ( $msgid );
if (!defined $msgid) {
@msgid = $self->get_msgid($msg);
}
foreach my $msgid_t ( @msgid ) {
my $seen = $self->{store}->seen_get ($msgid_t);
if (defined ($seen)) {
if (($seen eq 's' && $isspam) || ($seen eq 'h' && !$isspam)) {
dbg("bayes: $msgid_t already learnt correctly, not learning twice");
return 0;
} elsif ($seen !~ /^[hs]$/) {
warn("bayes: db_seen corrupt: value='$seen' for $msgid_t, ignored");
} else {
# bug 3704: If the message was already learned, don't try learning it again.
# this prevents, for instance, manually learning as spam, then autolearning
# as ham, or visa versa.
if ($self->{main}->{learn_no_relearn}) {
dbg("bayes: $msgid_t already learnt as opposite, not re-learning");
return 0;
}
dbg("bayes: $msgid_t already learnt as opposite, forgetting first");
# kluge so that forget() won't untie the db on us ...
my $orig = $self->{main}->{learn_caller_will_untie};
$self->{main}->{learn_caller_will_untie} = 1;
my $fatal = !defined $self->{main}->{bayes_scanner}->forget ($msg);
# reset the value post-forget() ...
$self->{main}->{learn_caller_will_untie} = $orig;
# forget() gave us a fatal error, so propagate that up
if ($fatal) {
dbg("bayes: forget() returned a fatal error, so learn() will too");
return;
}
}
# we're only going to have seen this once, so stop if it's been
# seen already
last;
}
}
# Now that we're sure we haven't seen this message before ...
$msgid = $msgid[0];
my $msgatime = $msg->receive_date();
# If the message atime comes back as being more than 1 day in the
# future, something's messed up and we should revert to current time as
# a safety measure.
#
$msgatime = time if ( $msgatime - time > 86400 );
my $tokens = $self->tokenize($msg, $msgdata);
{ my $timer = $self->{main}->time_method('b_count_change');
if ($isspam) {
$self->{store}->nspam_nham_change(1, 0);
$self->{store}->multi_tok_count_change(1, 0, $tokens, $msgatime);
} else {
$self->{store}->nspam_nham_change(0, 1);
$self->{store}->multi_tok_count_change(0, 1, $tokens, $msgatime);
}
}
$self->{store}->seen_put ($msgid, ($isspam ? 's' : 'h'));
$self->{store}->cleanup();
$self->{main}->call_plugins("bayes_learn", { toksref => $tokens,
isspam => $isspam,
msgid => $msgid,
msgatime => $msgatime,
});
dbg("bayes: learned '$msgid', atime: $msgatime");
1;
}
###########################################################################
# Plugin hook.
sub forget_message {
my ($self, $params) = @_;
my $msg = $params->{msg};
my $id = $params->{id};
if (!$self->{conf}->{use_bayes}) { return; }
my $msgdata = $self->get_body_from_msg ($msg);
my $ret;
# we still tie for writing here, since we write to the seen db
# synchronously
eval {
local $SIG{'__DIE__'}; # do not run user die() traps in here
my $timer = $self->{main}->time_method("b_learn");
my $ok;
if ($self->{main}->{learn_to_journal}) {
# If we're going to learn to journal, we'll try going r/o first...
# If that fails for some reason, let's try going r/w. This happens
# if the DB doesn't exist yet.
$ok = $self->{store}->tie_db_readonly() || $self->{store}->tie_db_writable();
} else {
$ok = $self->{store}->tie_db_writable();
}
if ($ok) {
$ret = $self->_forget_trapped ($msg, $msgdata, $id);
if (!$self->{main}->{learn_caller_will_untie}) {
$self->{store}->untie_db();
}
}
1;
} or do { # if we died, untie the dbs.
my $eval_stat = $@ ne '' ? $@ : "errno=$!"; chomp $eval_stat;
$self->{store}->untie_db();
die "bayes: (in forget) $eval_stat\n";
};
return $ret;
}
# this function is trapped by the wrapper above
sub _forget_trapped {
my ($self, $msg, $msgdata, $msgid) = @_;
my @msgid = ( $msgid );
my $isspam;
if (!defined $msgid) {
@msgid = $self->get_msgid($msg);
}
while( $msgid = shift @msgid ) {
my $seen = $self->{store}->seen_get ($msgid);
if (defined ($seen)) {
if ($seen eq 's') {
$isspam = 1;
} elsif ($seen eq 'h') {
$isspam = 0;
} else {
dbg("bayes: forget: msgid $msgid seen entry is neither ham nor spam, ignored");
return 0;
}
# messages should only be learned once, so stop if we find a msgid
# which was seen before
last;
}
else {
dbg("bayes: forget: msgid $msgid not learnt, ignored");
}
}
# This message wasn't learnt before, so return
if (!defined $isspam) {
dbg("bayes: forget: no msgid from this message has been learnt, skipping message");
return 0;
}
elsif ($isspam) {
$self->{store}->nspam_nham_change (-1, 0);
}
else {
$self->{store}->nspam_nham_change (0, -1);
}
my $tokens = $self->tokenize($msg, $msgdata);
if ($isspam) {
$self->{store}->multi_tok_count_change (-1, 0, $tokens);
} else {
$self->{store}->multi_tok_count_change (0, -1, $tokens);
}
$self->{store}->seen_delete ($msgid);
$self->{store}->cleanup();
$self->{main}->call_plugins("bayes_forget", { toksref => $tokens,
isspam => $isspam,
msgid => $msgid,
});
1;
}
###########################################################################
# Plugin hook.
sub learner_sync {
my ($self, $params) = @_;
if (!$self->{conf}->{use_bayes}) { return 0; }
dbg("bayes: bayes journal sync starting");
$self->{store}->sync($params);
dbg("bayes: bayes journal sync completed");
}
###########################################################################
# Plugin hook.
sub learner_expire_old_training {
my ($self, $params) = @_;
if (!$self->{conf}->{use_bayes}) { return 0; }
dbg("bayes: expiry starting");
my $timer = $self->{main}->time_method("expire_bayes");
$self->{store}->expire_old_tokens($params);
dbg("bayes: expiry completed");
}
###########################################################################
# Plugin hook.
# Check to make sure we can tie() the DB, and we have enough entries to do a scan
# if we're told the caller will untie(), go ahead and leave the db tied.
sub learner_is_scan_available {
my ($self, $params) = @_;
return 0 unless $self->{conf}->{use_bayes};
return 0 unless $self->{store}->tie_db_readonly();
# We need the DB to stay tied, so if the journal sync occurs, don't untie!
my $caller_untie = $self->{main}->{learn_caller_will_untie};
$self->{main}->{learn_caller_will_untie} = 1;
# Do a journal sync if necessary. Do this before the nspam_nham_get()
# call since the sync may cause an update in the number of messages
# learnt.
$self->_opportunistic_calls(1);
# Reset the variable appropriately
$self->{main}->{learn_caller_will_untie} = $caller_untie;
my ($ns, $nn) = $self->{store}->nspam_nham_get();
if ($ns < $self->{conf}->{bayes_min_spam_num}) {
dbg("bayes: not available for scanning, only $ns spam(s) in bayes DB < ".$self->{conf}->{bayes_min_spam_num});
if (!$self->{main}->{learn_caller_will_untie}) {
$self->{store}->untie_db();
}
return 0;
}
if ($nn < $self->{conf}->{bayes_min_ham_num}) {
dbg("bayes: not available for scanning, only $nn ham(s) in bayes DB < ".$self->{conf}->{bayes_min_ham_num});
if (!$self->{main}->{learn_caller_will_untie}) {
$self->{store}->untie_db();
}
return 0;
}
return 1;
}
###########################################################################
sub scan {
my ($self, $permsgstatus, $msg) = @_;
my $score;
return unless $self->{conf}->{use_learner};
# When we're doing a scan, we'll guarantee that we'll do the untie,
# so override the global setting until we're done.
my $caller_untie = $self->{main}->{learn_caller_will_untie};
$self->{main}->{learn_caller_will_untie} = 1;
goto skip if ($self->{main}->{bayes_scanner}->ignore_message($permsgstatus));
goto skip unless $self->learner_is_scan_available();
my ($ns, $nn) = $self->{store}->nspam_nham_get();
## if ($self->{log_raw_counts}) { # see _compute_prob_for_token()
## $self->{raw_counts} = " ns=$ns nn=$nn ";
## }
dbg("bayes: corpus size: nspam = $ns, nham = $nn");
my $msgtokens;
{ my $timer = $self->{main}->time_method('b_tokenize');
my $msgdata = $self->_get_msgdata_from_permsgstatus ($permsgstatus);
$msgtokens = $self->tokenize($msg, $msgdata);
}
my $tokensdata;
{ my $timer = $self->{main}->time_method('b_tok_get_all');
$tokensdata = $self->{store}->tok_get_all(keys %{$msgtokens});
}
my $timer_compute_prob = $self->{main}->time_method('b_comp_prob');
my $probabilities_ref =
$self->_compute_prob_for_all_tokens($tokensdata, $ns, $nn);
my %pw;
foreach my $tokendata (@{$tokensdata}) {
my $prob = shift(@$probabilities_ref);
next unless defined $prob;
my ($token, $tok_spam, $tok_ham, $atime) = @{$tokendata};
$pw{$token} = {
prob => $prob,
spam_count => $tok_spam,
ham_count => $tok_ham,
atime => $atime
};
}
my @pw_keys = keys %pw;
# If none of the tokens were found in the DB, we're going to skip
# this message...
if (!@pw_keys) {
dbg("bayes: cannot use bayes on this message; none of the tokens were found in the database");
goto skip;
}
my $tcount_total = keys %{$msgtokens};
my $tcount_learned = scalar @pw_keys;
# Figure out the message receive time (used as atime below)
# If the message atime comes back as being in the future, something's
# messed up and we should revert to current time as a safety measure.
#
my $msgatime = $msg->receive_date();
my $now = time;
$msgatime = $now if ( $msgatime > $now );
my @touch_tokens;
my $tinfo_spammy = $permsgstatus->{bayes_token_info_spammy} = [];
my $tinfo_hammy = $permsgstatus->{bayes_token_info_hammy} = [];
my %tok_strength = map( ($_, abs($pw{$_}->{prob} - 0.5)), @pw_keys);
my $log_each_token = (would_log('dbg', 'bayes') > 1);
# now take the most significant tokens and calculate probs using
# Robinson's formula.
@pw_keys = sort { $tok_strength{$b} <=> $tok_strength{$a} } @pw_keys;
if (@pw_keys > N_SIGNIFICANT_TOKENS) { $#pw_keys = N_SIGNIFICANT_TOKENS - 1 }
my @sorted;
foreach my $tok (@pw_keys) {
next if $tok_strength{$tok} <
$Mail::SpamAssassin::Bayes::Combine::MIN_PROB_STRENGTH;
my $pw_tok = $pw{$tok};
my $pw_prob = $pw_tok->{prob};
# What's more expensive, scanning headers for HAMMYTOKENS and
# SPAMMYTOKENS tags that aren't there or collecting data that
# won't be used? Just collecting the data is certainly simpler.
#
my $raw_token = $msgtokens->{$tok} || "(unknown)";
my $s = $pw_tok->{spam_count};
my $n = $pw_tok->{ham_count};
my $a = $pw_tok->{atime};
push( @{ $pw_prob < 0.5 ? $tinfo_hammy : $tinfo_spammy },
[$raw_token, $pw_prob, $s, $n, $a] );
push(@sorted, $pw_prob);
# update the atime on this token, it proved useful
push(@touch_tokens, $tok);
if ($log_each_token) {
dbg("bayes: token '$raw_token' => $pw_prob");
}
}
if (!@sorted || (REQUIRE_SIGNIFICANT_TOKENS_TO_SCORE > 0 &&
$#sorted <= REQUIRE_SIGNIFICANT_TOKENS_TO_SCORE))
{
dbg("bayes: cannot use bayes on this message; not enough usable tokens found");
goto skip;
}
$score = Mail::SpamAssassin::Bayes::Combine::combine($ns, $nn, \@sorted);
undef $timer_compute_prob; # end a timing section
# Couldn't come up with a probability?
goto skip unless defined $score;
dbg("bayes: score = $score");
# no need to call tok_touch_all unless there were significant
# tokens and a score was returned
# we don't really care about the return value here
{ my $timer = $self->{main}->time_method('b_tok_touch_all');
$self->{store}->tok_touch_all(\@touch_tokens, $msgatime);
}
my $timer_finish = $self->{main}->time_method('b_finish');
$permsgstatus->{bayes_nspam} = $ns;
$permsgstatus->{bayes_nham} = $nn;
## if ($self->{log_raw_counts}) { # see _compute_prob_for_token()
## print "#Bayes-Raw-Counts: $self->{raw_counts}\n";
## }
$self->{main}->call_plugins("bayes_scan", { toksref => $msgtokens,
probsref => \%pw,
score => $score,
msgatime => $msgatime,
significant_tokens => \@touch_tokens,
});
skip:
if (!defined $score) {
dbg("bayes: not scoring message, returning undef");
}
undef $timer_compute_prob; # end a timing section if still running
if (!defined $timer_finish) {
$timer_finish = $self->{main}->time_method('b_finish');
}
# Take any opportunistic actions we can take
if ($self->{main}->{opportunistic_expire_check_only}) {
# we're supposed to report on expiry only -- so do the
# _opportunistic_calls() run for the journal only.
$self->_opportunistic_calls(1);
$permsgstatus->{bayes_expiry_due} = $self->{store}->expiry_due();
}
else {
$self->_opportunistic_calls();
}
# Do any cleanup we need to do
$self->{store}->cleanup();
# Reset the value accordingly
$self->{main}->{learn_caller_will_untie} = $caller_untie;
# If our caller won't untie the db, we need to do it.
if (!$caller_untie) {
$self->{store}->untie_db();
}
$permsgstatus->set_tag ('BAYESTCHAMMY',
($tinfo_hammy ? scalar @{$tinfo_hammy} : 0));
$permsgstatus->set_tag ('BAYESTCSPAMMY',
($tinfo_spammy ? scalar @{$tinfo_spammy} : 0));
$permsgstatus->set_tag ('BAYESTCLEARNED', $tcount_learned);
$permsgstatus->set_tag ('BAYESTC', $tcount_total);
$permsgstatus->set_tag ('HAMMYTOKENS', sub {
my $pms = shift;
$self->bayes_report_make_list
($pms, $pms->{bayes_token_info_hammy}, shift);
});
$permsgstatus->set_tag ('SPAMMYTOKENS', sub {
my $pms = shift;
$self->bayes_report_make_list
($pms, $pms->{bayes_token_info_spammy}, shift);
});
$permsgstatus->set_tag ('TOKENSUMMARY', sub {
my $pms = shift;
if ( defined $pms->{tag_data}{BAYESTC} )
{
my $tcount_neutral = $pms->{tag_data}{BAYESTCLEARNED}
- $pms->{tag_data}{BAYESTCSPAMMY}
- $pms->{tag_data}{BAYESTCHAMMY};
my $tcount_new = $pms->{tag_data}{BAYESTC}
- $pms->{tag_data}{BAYESTCLEARNED};
"Tokens: new, $tcount_new; "
."hammy, $pms->{tag_data}{BAYESTCHAMMY}; "
."neutral, $tcount_neutral; "
."spammy, $pms->{tag_data}{BAYESTCSPAMMY}."
} else {
"Bayes not run.";
}
});
return $score;
}
###########################################################################
# Plugin hook.
sub learner_dump_database {
my ($self, $params) = @_;
my $magic = $params->{magic};
my $toks = $params->{toks};
my $regex = $params->{regex};
# allow dump to occur even if use_bayes disables everything else ...
#return 0 unless $self->{conf}->{use_bayes};
return 0 unless $self->{store}->tie_db_readonly();
my @vars = $self->{store}->get_storage_variables();
my($sb,$ns,$nh,$nt,$le,$oa,$bv,$js,$ad,$er,$na) = @vars;
my $template = '%3.3f %10u %10u %10u %s'."\n";
if ( $magic ) {
printf($template, 0.0, 0, $bv, 0, 'non-token data: bayes db version')
or die "Error writing: $!";
printf($template, 0.0, 0, $ns, 0, 'non-token data: nspam')
or die "Error writing: $!";
printf($template, 0.0, 0, $nh, 0, 'non-token data: nham')
or die "Error writing: $!";
printf($template, 0.0, 0, $nt, 0, 'non-token data: ntokens')
or die "Error writing: $!";
printf($template, 0.0, 0, $oa, 0, 'non-token data: oldest atime')
or die "Error writing: $!";
if ( $bv >= 2 ) {
printf($template, 0.0, 0, $na, 0, 'non-token data: newest atime')
or die "Error writing: $!";
}
if ( $bv < 2 ) {
printf($template, 0.0, 0, $sb, 0, 'non-token data: current scan-count')
or die "Error writing: $!";
}
if ( $bv >= 2 ) {
printf($template, 0.0, 0, $js, 0, 'non-token data: last journal sync atime')
or die "Error writing: $!";
}
printf($template, 0.0, 0, $le, 0, 'non-token data: last expiry atime')
or die "Error writing: $!";
if ( $bv >= 2 ) {
printf($template, 0.0, 0, $ad, 0, 'non-token data: last expire atime delta')
or die "Error writing: $!";
printf($template, 0.0, 0, $er, 0, 'non-token data: last expire reduction count')
or die "Error writing: $!";
}
}
if ( $toks ) {
# let the store sort out the db_toks
$self->{store}->dump_db_toks($template, $regex, @vars);
}
if (!$self->{main}->{learn_caller_will_untie}) {
$self->{store}->untie_db();
}
return 1;
}
###########################################################################
# TODO: these are NOT public, but the test suite needs to call them.
sub get_msgid {
my ($self, $msg) = @_;
my @msgid;
my $msgid = $msg->get_header("Message-Id");
if (defined $msgid && $msgid ne '' && $msgid !~ /^\s*<\s*(?:\@sa_generated)?>.*$/) {
# remove \r and < and > prefix/suffixes
chomp $msgid;
$msgid =~ s/^<//; $msgid =~ s/>.*$//g;
push(@msgid, $msgid);
}
# Modified 2012-01-17 per bug 5185 to remove last received from msg_id calculation
# Use sha1_hex(Date: and top N bytes of body)
# where N is MIN(1024 bytes, 1/2 of body length)
#
my $date = $msg->get_header("Date");
$date = "None" if (!defined $date || $date eq ''); # No Date?
#Removed per bug 5185
#my @rcvd = $msg->get_header("Received");
#my $rcvd = $rcvd[$#rcvd];
#$rcvd = "None" if (!defined $rcvd || $rcvd eq ''); # No Received?
# Make a copy since pristine_body is a reference ...
my $body = join('', $msg->get_pristine_body());
if (length($body) > 64) { # Small Body?
my $keep = ( length $body > 2048 ? 1024 : int(length($body) / 2) );
substr($body, $keep) = '';
}
#Stripping all CR and LF so that testing midstream from MTA and post delivery don't
#generate different id's simply because of LF<->CR<->CRLF changes.
$body =~ s/[\r\n]//g;
unshift(@msgid, sha1_hex($date."\000".$body).'@sa_generated');
return wantarray ? @msgid : $msgid[0];
}
sub get_body_from_msg {
my ($self, $msg) = @_;
if (!ref $msg) {
# I have no idea why this seems to happen. TODO
warn "bayes: msg not a ref: '$msg'";
return { };
}
my $permsgstatus =
Mail::SpamAssassin::PerMsgStatus->new($self->{main}, $msg);
$msg->extract_message_metadata ($permsgstatus);
my $msgdata = $self->_get_msgdata_from_permsgstatus ($permsgstatus);
$permsgstatus->finish();
if (!defined $msgdata) {
# why?!
warn "bayes: failed to get body for ".scalar($self->get_msgid($self->{msg}))."\n";
return { };
}
return $msgdata;
}
sub _get_msgdata_from_permsgstatus {
my ($self, $pms) = @_;
my $t_src = $self->{conf}->{bayes_token_sources};
my $msgdata = { };
$msgdata->{bayes_token_body} =
$pms->{msg}->get_visible_rendered_body_text_array() if $t_src->{visible};
$msgdata->{bayes_token_inviz} =
$pms->{msg}->get_invisible_rendered_body_text_array() if $t_src->{invisible};
$msgdata->{bayes_mimepart_digests} =
$pms->{msg}->get_mimepart_digests() if $t_src->{mimepart};
@{$msgdata->{bayes_token_uris}} =
$pms->get_uri_list() if $t_src->{uri};
return $msgdata;
}
###########################################################################
# The calling functions expect a uniq'ed array of tokens ...
sub tokenize {
my ($self, $msg, $msgdata) = @_;
my $t_src = $self->{conf}->{bayes_token_sources};
my @tokens;
# visible tokens from the body
if ($msgdata->{bayes_token_body}) {
my(@t) = map($self->_tokenize_line ($_, '', 1),
@{$msgdata->{bayes_token_body}} );
dbg("bayes: tokenized body: %d tokens", scalar @t);
push(@tokens, @t);
}
# the URI list
if ($msgdata->{bayes_token_uris}) {
my(@t) = map($self->_tokenize_line ($_, '', 2),
@{$msgdata->{bayes_token_uris}} );
dbg("bayes: tokenized uri: %d tokens", scalar @t);
push(@tokens, @t);
}
# add invisible tokens
if ($msgdata->{bayes_token_inviz}) {
my $tokprefix;
if (ADD_INVIZ_TOKENS_I_PREFIX) { $tokprefix = 'I*:' }
if (ADD_INVIZ_TOKENS_NO_PREFIX) { $tokprefix = '' }
if (defined $tokprefix) {
my(@t) = map($self->_tokenize_line ($_, $tokprefix, 1),
@{$msgdata->{bayes_token_inviz}} );
dbg("bayes: tokenized invisible: %d tokens", scalar @t);
push(@tokens, @t);
}
}
# add digests and Content-Type of all MIME parts
if ($msgdata->{bayes_mimepart_digests}) {
my %shorthand = ( # some frequent MIME part contents for human readability
'da39a3ee5e6b4b0d3255bfef95601890afd80709:text/plain'=> 'Empty-Plaintext',
'da39a3ee5e6b4b0d3255bfef95601890afd80709:text/html' => 'Empty-HTML',
'da39a3ee5e6b4b0d3255bfef95601890afd80709:text/xml' => 'Empty-XML',
'adc83b19e793491b1c6ea0fd8b46cd9f32e592fc:text/plain'=> 'OneNL-Plaintext',
'adc83b19e793491b1c6ea0fd8b46cd9f32e592fc:text/html' => 'OneNL-HTML',
'71853c6197a6a7f222db0f1978c7cb232b87c5ee:text/plain'=> 'TwoNL-Plaintext',
'71853c6197a6a7f222db0f1978c7cb232b87c5ee:text/html' => 'TwoNL-HTML',
);
my(@t) = map('MIME:' . ($shorthand{$_} || $_),
@{ $msgdata->{bayes_mimepart_digests} });
dbg("bayes: tokenized mime parts: %d tokens", scalar @t);
dbg("bayes: mime-part token %s", $_) for @t;
push(@tokens, @t);
}
# Tokenize the headers
if ($t_src->{header}) {
my(@t);
my %hdrs = $self->_tokenize_headers ($msg);
while( my($prefix, $value) = each %hdrs ) {
push(@t, $self->_tokenize_line ($value, "H$prefix:", 0));
}
dbg("bayes: tokenized header: %d tokens", scalar @t);
push(@tokens, @t);
}
# Go ahead and uniq the array, skip null tokens (can happen sometimes)
# generate an SHA1 hash and take the lower 40 bits as our token
my %tokens;
foreach my $token (@tokens) {
# skip empty tokens
$tokens{substr(sha1($token), -5)} = $token if $token ne '';
}
# return the keys == tokens ...
return \%tokens;
}
sub _tokenize_line {
my $self = $_[0];
my $tokprefix = $_[2];
my $region = $_[3];
local ($_) = $_[1];
my @rettokens;
# include quotes, .'s and -'s for URIs, and [$,]'s for Nigerian-scam strings,
# and ISO-8859-15 alphas. Do not split on @'s; better results keeping it.
# Some useful tokens: "$31,000,000" "www.clock-speed.net" "f*ck" "Hits!"
### (previous:) tr/-A-Za-z0-9,\@\*\!_'"\$.\241-\377 / /cs;
### (now): see Bug 7130 for rationale (slower, but makes UTF-8 chars atomic)
s{ ( [A-Za-z0-9,@*!_'"\$. -]+ |
[\xC0-\xDF][\x80-\xBF] |
[\xE0-\xEF][\x80-\xBF]{2} |
[\xF0-\xF4][\x80-\xBF]{3} |
[\xA1-\xFF] ) | . }
{ defined $1 ? $1 : ' ' }xsge;
# should we also turn NBSP ( \xC2\xA0 ) into space?
# DO split on "..." or "--" or "---"; common formatting error resulting in
# hapaxes. Keep the separator itself as a token, though, as long ones can
# be good spamsigns.
s/(\w)(\.{3,6})(\w)/$1 $2 $3/gs;
s/(\w)(\-{2,6})(\w)/$1 $2 $3/gs;
if (IGNORE_TITLE_CASE) {
if ($region == 1 || $region == 2) {
# lower-case Title Case at start of a full-stop-delimited line (as would
# be seen in a Western language).
s/(?:^|\.\s+)([A-Z])([^A-Z]+)(?:\s|$)/ ' '. (lc $1) . $2 . ' ' /ge;
}
}
my $magic_re = $self->{store}->get_magic_re();
# Note that split() in scope of 'use bytes' results in words with utf8 flag
# cleared, even if the source string has perl characters semantics !!!
# Is this really still desirable?
foreach my $token (split) {
$token =~ s/^[-'"\.,]+//; # trim non-alphanum chars at start or end
$token =~ s/[-'"\.,]+$//; # so we don't get loads of '"foo' tokens
# Skip false magic tokens
# TVD: we need to do a defined() check since SQL doesn't have magic
# tokens, so the SQL BayesStore returns undef. I really want a way
# of optimizing that out, but I haven't come up with anything yet.
#
next if ( defined $magic_re && $token =~ /$magic_re/ );
# *do* keep 3-byte tokens; there's some solid signs in there
my $len = length($token);
# but extend the stop-list. These are squarely in the gray
# area, and it just slows us down to record them.
# See http://wiki.apache.org/spamassassin/BayesStopList for more info.
#
next if $len < 3 ||
($token =~ /^(?:a(?:ble|l(?:ready|l)|n[dy]|re)|b(?:ecause|oth)|c(?:an|ome)|e(?:ach|mail|ven)|f(?:ew|irst|or|rom)|give|h(?:a(?:ve|s)|ttp)|i(?:n(?:formation|to)|t\'s)|just|know|l(?:ike|o(?:ng|ok))|m(?:a(?:de|il(?:(?:ing|to))?|ke|ny)|o(?:re|st)|uch)|n(?:eed|o[tw]|umber)|o(?:ff|n(?:ly|e)|ut|wn)|p(?:eople|lace)|right|s(?:ame|ee|uch)|t(?:h(?:at|is|rough|e)|ime)|using|w(?:eb|h(?:ere|y)|ith(?:out)?|or(?:ld|k))|y(?:ears?|ou(?:(?:\'re|r))?))$/i);
# are we in the body? If so, apply some body-specific breakouts
if ($region == 1 || $region == 2) {
if (CHEW_BODY_MAILADDRS && $token =~ /\S\@\S/i) {
push (@rettokens, $self->_tokenize_mail_addrs ($token));
}
elsif (CHEW_BODY_URIS && $token =~ /\S\.[a-z]/i) {
push (@rettokens, "UD:".$token); # the full token
my $bit = $token; while ($bit =~ s/^[^\.]+\.(.+)$/$1/gs) {
push (@rettokens, "UD:".$1); # UD = URL domain
}
}
}
# note: do not trim down overlong tokens if they contain '*'. This is
# used as part of split tokens such as "HTo:D*net" indicating that
# the domain ".net" appeared in the To header.
#
if ($len > MAX_TOKEN_LENGTH && $token !~ /\*/) {
if (TOKENIZE_LONG_8BIT_SEQS_AS_UTF8_CHARS && $token =~ /[\x80-\xBF]{2}/) {
# Bug 7135
# collect 3- and 4-byte UTF-8 sequences, ignore 2-byte sequences
my(@t) = $token =~ /( (?: [\xE0-\xEF] | [\xF0-\xF4][\x80-\xBF] )
[\x80-\xBF]{2} )/xsg;
if (@t) {
push (@rettokens, map('u8:'.$_, @t));
next;
}
}
if (TOKENIZE_LONG_8BIT_SEQS_AS_TUPLES && $token =~ /[\xa0-\xff]{2}/) {
# Matt sez: "Could be asian? Autrijus suggested doing character ngrams,
# but I'm doing tuples to keep the dbs small(er)." Sounds like a plan
# to me! (jm)
while ($token =~ s/^(..?)//) {
push (@rettokens, "8:$1");
}
next;
}
if (($region == 0 && HDRS_TOKENIZE_LONG_TOKENS_AS_SKIPS)
|| ($region == 1 && BODY_TOKENIZE_LONG_TOKENS_AS_SKIPS)
|| ($region == 2 && URIS_TOKENIZE_LONG_TOKENS_AS_SKIPS))
{
# if (TOKENIZE_LONG_TOKENS_AS_SKIPS)
# Spambayes trick via Matt: Just retain 7 chars. Do not retain the
# length, it does not help; see jm's mail to -devel on Nov 20 2002 at
# http://sourceforge.net/p/spamassassin/mailman/message/12977605/
# "sk:" stands for "skip".
# Bug 7141: retain seven UTF-8 chars (or other bytes),
# if followed by at least two bytes
$token =~ s{ ^ ( (?> (?: [\x00-\x7F\xF5-\xFF] |
[\xC0-\xDF][\x80-\xBF] |
[\xE0-\xEF][\x80-\xBF]{2} |
[\xF0-\xF4][\x80-\xBF]{3} | . ){7} ))
.{2,} \z }{sk:$1}xs;
## (was:) $token = "sk:".substr($token, 0, 7); # seven bytes
}
}
# decompose tokens? do this after shortening long tokens
if ($region == 1 || $region == 2) {
if (DECOMPOSE_BODY_TOKENS) {
if ($token =~ /[^\w:\*]/) {
my $decompd = $token; # "Foo!"
$decompd =~ s/[^\w:\*]//gs;
push (@rettokens, $tokprefix.$decompd); # "Foo"
}
if ($token =~ /[A-Z]/) {
my $decompd = $token; $decompd = lc $decompd;
push (@rettokens, $tokprefix.$decompd); # "foo!"
if ($token =~ /[^\w:\*]/) {
$decompd =~ s/[^\w:\*]//gs;
push (@rettokens, $tokprefix.$decompd); # "foo"
}
}
}
}
push (@rettokens, $tokprefix.$token);
}
return @rettokens;
}
sub _tokenize_headers {
my ($self, $msg) = @_;
my %parsed;
my %user_ignore;
$user_ignore{lc $_} = 1 for @{$self->{main}->{conf}->{bayes_ignore_headers}};
# get headers in array context
my @hdrs;
my @rcvdlines;
for ($msg->get_all_headers()) {
# first, keep a copy of Received headers, so we can strip down to last 2
if (/^Received:/i) {
push(@rcvdlines, $_);
next;
}
# and now skip lines for headers we don't want (including all Received)
next if /^${IGNORED_HDRS}:/i;
next if IGNORE_MSGID_TOKENS && /^Message-ID:/i;
push(@hdrs, $_);
}
push(@hdrs, $msg->get_all_metadata());
# and re-add the last 2 received lines: usually a good source of
# spamware tokens and HELO names.
if ($#rcvdlines >= 0) { push(@hdrs, $rcvdlines[$#rcvdlines]); }
if ($#rcvdlines >= 1) { push(@hdrs, $rcvdlines[$#rcvdlines-1]); }
for (@hdrs) {
next unless /\S/;
my ($hdr, $val) = split(/:/, $_, 2);
# remove user-specified headers here, after Received, in case they
# want to ignore that too
next if exists $user_ignore{lc $hdr};
# Prep the header value
$val ||= '';
chomp($val);
# special tokenization for some headers:
if ($hdr =~ /^(?:|X-|Resent-)Message-Id$/i) {
$val = $self->_pre_chew_message_id ($val);
}
elsif (PRE_CHEW_ADDR_HEADERS && $hdr =~ /^(?:|X-|Resent-)
(?:Return-Path|From|To|Cc|Reply-To|Errors-To|Mail-Followup-To|Sender)$/ix)
{
$val = $self->_pre_chew_addr_header ($val);
}
elsif ($hdr eq 'Received') {
$val = $self->_pre_chew_received ($val);
}
elsif ($hdr eq 'Content-Type') {
$val = $self->_pre_chew_content_type ($val);
}
elsif ($hdr eq 'MIME-Version') {
$val =~ s/1\.0//; # totally innocuous
}
elsif ($hdr =~ /^${MARK_PRESENCE_ONLY_HDRS}$/i) {
$val = "1"; # just mark the presence, they create lots of hapaxen
}
if (MAP_HEADERS_MID) {
if ($hdr =~ /^(?:In-Reply-To|References|Message-ID)$/i) {
$parsed{"*MI"} = $val;
}
}
if (MAP_HEADERS_FROMTOCC) {
if ($hdr =~ /^(?:From|To|Cc)$/i) {
$parsed{"*Ad"} = $val;
}
}
if (MAP_HEADERS_USERAGENT) {
if ($hdr =~ /^(?:X-Mailer|User-Agent)$/i) {
$parsed{"*UA"} = $val;
}
}
# replace hdr name with "compressed" version if possible
if (defined $HEADER_NAME_COMPRESSION{$hdr}) {
$hdr = $HEADER_NAME_COMPRESSION{$hdr};
}
if (exists $parsed{$hdr}) {
$parsed{$hdr} .= " ".$val;
} else {
$parsed{$hdr} = $val;
}
if (would_log('dbg', 'bayes') > 1) {
dbg("bayes: header tokens for $hdr = \"$parsed{$hdr}\"");
}
}
return %parsed;
}
sub _pre_chew_content_type {
my ($self, $val) = @_;
# hopefully this will retain good bits without too many hapaxen
if ($val =~ s/boundary=[\"\'](.*?)[\"\']/ /ig) {
my $boundary = $1;
$boundary = '' if !defined $boundary; # avoid a warning
$boundary =~ s/[a-fA-F0-9]/H/gs;
# break up blocks of separator chars so they become their own tokens
$boundary =~ s/([-_\.=]+)/ $1 /gs;
$val .= $boundary;
}
# stop-list words for Content-Type header: these wind up totally gray
$val =~ s/\b(?:text|charset)\b//;
$val;
}
sub _pre_chew_message_id {
my ($self, $val) = @_;
# we can (a) get rid of a lot of hapaxen and (b) increase the token
# specificity by pre-parsing some common formats.
# Outlook Express format:
$val =~ s/<([0-9a-f]{4})[0-9a-f]{4}[0-9a-f]{4}\$
([0-9a-f]{4})[0-9a-f]{4}\$
([0-9a-f]{8})\@(\S+)>/ OEA$1 OEB$2 OEC$3 $4 /gx;
# Exim:
$val =~ s/<[A-Za-z0-9]{7}-[A-Za-z0-9]{6}-0[A-Za-z0-9]\@//;
# Sendmail:
$val =~ s/<20\d\d[01]\d[0123]\d[012]\d[012345]\d[012345]\d\.
[A-F0-9]{10,12}\@//gx;
# try to split Message-ID segments on probable ID boundaries. Note that
# Outlook message-ids seem to contain a server identifier ID in the last
# 8 bytes before the @. Make sure this becomes its own token, it's a
# great spam-sign for a learning system! Be sure to split on ".".
$val =~ s/[^_A-Za-z0-9]/ /g;
$val;
}
sub _pre_chew_received {
my ($self, $val) = @_;
# Thanks to Dan for these. Trim out "useless" tokens; sendmail-ish IDs
# and valid-format RFC-822/2822 dates
$val =~ s/\swith\sSMTP\sid\sg[\dA-Z]{10,12}\s/ /gs; # Sendmail
$val =~ s/\swith\sESMTP\sid\s[\dA-F]{10,12}\s/ /gs; # Sendmail
$val =~ s/\bid\s[a-zA-Z0-9]{7,20}\b/ /gs; # Sendmail
$val =~ s/\bid\s[A-Za-z0-9]{7}-[A-Za-z0-9]{6}-0[A-Za-z0-9]/ /gs; # exim
$val =~ s/(?:(?:Mon|Tue|Wed|Thu|Fri|Sat|Sun),\s)?
[0-3\s]?[0-9]\s
(?:Jan|Feb|Ma[ry]|Apr|Ju[nl]|Aug|Sep|Oct|Nov|Dec)\s
(?:19|20)?[0-9]{2}\s
[0-2][0-9](?:\:[0-5][0-9]){1,2}\s
(?:\s*\(|\)|\s*(?:[+-][0-9]{4})|\s*(?:UT|[A-Z]{2,3}T))*
//gx;
# IPs: break down to nearest /24, to reduce hapaxes -- EXCEPT for
# IPs in the 10 and 192.168 ranges, they gets lots of significant tokens
# (on both sides)
# also make a dup with the full IP, as fodder for
# bayes_dump_to_trusted_networks: "H*r:ip*aaa.bbb.ccc.ddd"
$val =~ s{\b(\d{1,3}\.)(\d{1,3}\.)(\d{1,3})(\.\d{1,3})\b}{
if ($2 eq '10' || ($2 eq '192' && $3 eq '168')) {
$1.$2.$3.$4.
" ip*".$1.$2.$3.$4." ";
} else {
$1.$2.$3.
" ip*".$1.$2.$3.$4." ";
}
}gex;
# trim these: they turn out as the most common tokens, but with a
# prob of about .5. waste of space!
$val =~ s/\b(?:with|from|for|SMTP|ESMTP)\b/ /g;
$val;
}
sub _pre_chew_addr_header {
my ($self, $val) = @_;
local ($_);
my @addrs = $self->{main}->find_all_addrs_in_line ($val);
my @toks;
foreach (@addrs) {
push (@toks, $self->_tokenize_mail_addrs ($_));
}
return join (' ', @toks);
}
sub _tokenize_mail_addrs {
my ($self, $addr) = @_;
($addr =~ /(.+)\@(.+)$/) or return ();
my @toks;
push(@toks, "U*".$1, "D*".$2);
$_ = $2; while (s/^[^\.]+\.(.+)$/$1/gs) { push(@toks, "D*".$1); }
return @toks;
}
###########################################################################
# compute the probability that a token is spammish for each token
sub _compute_prob_for_all_tokens {
my ($self, $tokensdata, $ns, $nn) = @_;
my @probabilities;
return if !$ns || !$nn;
my $threshold = 1; # ignore low-freq tokens below this s+n threshold
if (!USE_ROBINSON_FX_EQUATION_FOR_LOW_FREQS) {
$threshold = 10;
}
if (!$self->{use_hapaxes}) {
$threshold = 2;
}
foreach my $tokendata (@{$tokensdata}) {
my $s = $tokendata->[1]; # spam count
my $n = $tokendata->[2]; # ham count
my $prob;
no warnings 'uninitialized'; # treat undef as zero in addition
if ($s + $n >= $threshold) {
# ignoring low-freq tokens, also covers the (!$s && !$n) case
# my $ratios = $s / $ns;
# my $ration = $n / $nn;
# $prob = $ratios / ($ration + $ratios);
#
$prob = ($s * $nn) / ($n * $ns + $s * $nn); # same thing, faster
if (USE_ROBINSON_FX_EQUATION_FOR_LOW_FREQS) {
# use Robinson's f(x) equation for low-n tokens, instead of just
# ignoring them
my $robn = $s + $n;
$prob =
($Mail::SpamAssassin::Bayes::Combine::FW_S_DOT_X + ($robn * $prob))
/
($Mail::SpamAssassin::Bayes::Combine::FW_S_CONSTANT + $robn);
}
}
# 'log_raw_counts' is used to log the raw data for the Bayes equations
# during a mass-check, allowing the S and X constants to be optimized
# quickly without requiring re-tokenization of the messages for each
# attempt. There's really no need for this code to be uncommented in
# normal use, however. It has never been publicly documented, so
# commenting it out is fine. ;)
#
## if ($self->{log_raw_counts}) {
## $self->{raw_counts} .= " s=$s,n=$n ";
## }
push(@probabilities, $prob);
}
return \@probabilities;
}
# compute the probability that a token is spammish
sub _compute_prob_for_token {
my ($self, $token, $ns, $nn, $s, $n) = @_;
# we allow the caller to give us the token information, just
# to save a potentially expensive lookup
if (!defined($s) || !defined($n)) {
($s, $n, undef) = $self->{store}->tok_get($token);
}
return if !$s && !$n;
my $probabilities_ref =
$self->_compute_prob_for_all_tokens([ [$token, $s, $n, 0] ], $ns, $nn);
return $probabilities_ref->[0];
}
###########################################################################
# If a token is neither hammy nor spammy, return 0.
# For a spammy token, return the minimum number of additional ham messages
# it would have had to appear in to no longer be spammy. Hammy tokens
# are handled similarly. That's what the function does (at the time
# of this writing, 31 July 2003, 16:02:55 CDT). It would be slightly
# more useful if it returned the number of /additional/ ham messages
# a spammy token would have to appear in to no longer be spammy but I
# fear that might require the solution to a cubic equation, and I
# just don't have the time for that now.
sub _compute_declassification_distance {
my ($self, $Ns, $Nn, $ns, $nn, $prob) = @_;
return 0 if $ns == 0 && $nn == 0;
if (!USE_ROBINSON_FX_EQUATION_FOR_LOW_FREQS) {return 0 if ($ns + $nn < 10);}
if (!$self->{use_hapaxes}) {return 0 if ($ns + $nn < 2);}
return 0 if $Ns == 0 || $Nn == 0;
return 0 if abs( $prob - 0.5 ) <
$Mail::SpamAssassin::Bayes::Combine::MIN_PROB_STRENGTH;
my ($Na,$na,$Nb,$nb) = $prob > 0.5 ? ($Nn,$nn,$Ns,$ns) : ($Ns,$ns,$Nn,$nn);
my $p = 0.5 - $Mail::SpamAssassin::Bayes::Combine::MIN_PROB_STRENGTH;
return int( 1.0 - 1e-6 + $nb * $Na * $p / ($Nb * ( 1 - $p )) ) - $na
unless USE_ROBINSON_FX_EQUATION_FOR_LOW_FREQS;
my $s = $Mail::SpamAssassin::Bayes::Combine::FW_S_CONSTANT;
my $sx = $Mail::SpamAssassin::Bayes::Combine::FW_S_DOT_X;
my $a = $Nb * ( 1 - $p );
my $b = $Nb * ( $sx + $nb * ( 1 - $p ) - $p * $s ) - $p * $Na * $nb;
my $c = $Na * $nb * ( $sx - $p * ( $s + $nb ) );
my $discrim = $b * $b - 4 * $a * $c;
my $disc_max_0 = $discrim < 0 ? 0 : $discrim;
my $dd_exact = ( 1.0 - 1e-6 + ( -$b + sqrt( $disc_max_0 ) ) / ( 2*$a ) ) - $na;
# This shouldn't be necessary. Should not be < 1
return $dd_exact < 1 ? 1 : int($dd_exact);
}
###########################################################################
sub _opportunistic_calls {
my($self, $journal_only) = @_;
# If we're not already tied, abort.
if (!$self->{store}->db_readable()) {
dbg("bayes: opportunistic call attempt failed, DB not readable");
return;
}
# Is an expire or sync running?
my $running_expire = $self->{store}->get_running_expire_tok();
if ( defined $running_expire && $running_expire+$OPPORTUNISTIC_LOCK_VALID > time() ) {
dbg("bayes: opportunistic call attempt skipped, found fresh running expire magic token");
return;
}
# handle expiry and syncing
if (!$journal_only && $self->{store}->expiry_due()) {
dbg("bayes: opportunistic call found expiry due");
# sync will bring the DB R/W as necessary, and the expire will remove
# the running_expire token, may untie as well.
$self->{main}->{bayes_scanner}->sync(1,1);
}
elsif ( $self->{store}->sync_due() ) {
dbg("bayes: opportunistic call found journal sync due");
# sync will bring the DB R/W as necessary, may untie as well
$self->{main}->{bayes_scanner}->sync(1,0);
# We can only remove the running_expire token if we're doing R/W
if ($self->{store}->db_writable()) {
$self->{store}->remove_running_expire_tok();
}
}
return;
}
###########################################################################
sub learner_new {
my ($self) = @_;
my $store;
my $module = untaint_var($self->{conf}->{bayes_store_module});
$module = 'Mail::SpamAssassin::BayesStore::DBM' if !$module;
dbg("bayes: learner_new self=%s, bayes_store_module=%s", $self,$module);
undef $self->{store}; # DESTROYs previous object, if any
eval '
require '.$module.';
$store = '.$module.'->new($self);
1;
' or do {
my $eval_stat = $@ ne '' ? $@ : "errno=$!"; chomp $eval_stat;
die "bayes: learner_new $module new() failed: $eval_stat\n";
};
dbg("bayes: learner_new: got store=%s", $store);
$self->{store} = $store;
$self;
}
###########################################################################
sub bayes_report_make_list {
my ($self, $pms, $info, $param) = @_;
return "Tokens not available." unless defined $info;
my ($limit,$fmt_arg,$more) = split /,/, ($param || '5');
my %formats = (
short => '$t',
Short => 'Token: \"$t\"',
compact => '$p-$D--$t',
Compact => 'Probability $p -declassification distance $D (\"+\" means > 9) --token: \"$t\"',
medium => '$p-$D-$N--$t',
long => '$p-$d--${h}h-${s}s--${a}d--$t',
Long => 'Probability $p -declassification distance $D --in ${h} ham messages -and ${s} spam messages --${a} days old--token:\"$t\"'
);
my $raw_fmt = (!$fmt_arg ? '$p-$D--$t' : $formats{$fmt_arg});
return "Invalid format, must be one of: ".join(",",keys %formats)
unless defined $raw_fmt;
my $fmt = '"'.$raw_fmt.'"';
my $amt = $limit < @$info ? $limit : @$info;
return "" unless $amt;
my $ns = $pms->{bayes_nspam};
my $nh = $pms->{bayes_nham};
my $digit = sub { $_[0] > 9 ? "+" : $_[0] };
my $now = time;
join ', ', map {
my($t,$prob,$s,$h,$u) = @$_;
my $a = int(($now - $u)/(3600 * 24));
my $d = $self->_compute_declassification_distance($ns,$nh,$s,$h,$prob);
my $p = sprintf "%.3f", $prob;
my $n = $s + $h;
my ($c,$o) = $prob < 0.5 ? ($h,$s) : ($s,$h);
my ($D,$S,$H,$C,$O,$N) = map &$digit($_), ($d,$s,$h,$c,$o,$n);
eval $fmt; ## no critic
} @{$info}[0..$amt-1];
}
1;