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[url "git://git.madduck.net/madduck/"]
  insteadOf = madduck:

do not delay debian mail justme identifies as passable
[etc/mailfilter.git] / spamassassin / user_prefs
1 # SpamAssassin user preferences file.  See 'perldoc Mail::SpamAssassin::Conf'
2 # for details of what can be tweaked.
3 ###########################################################################
4
5 # How many points before a mail is considered spam.
6 # required_score                5
7
8 # Whitelist and blacklist addresses are now file-glob-style patterns, so
9 # "friend@somewhere.com", "*@isp.com", or "*.domain.net" will all work.
10 # whitelist_from        someone@somewhere.com
11
12 # Add your own customised scores for some tests below.  The default scores are
13 # read from the installed spamassassin rules files, but you can override them
14 # here.  To see the list of tests and their default scores, go to
15 # http://spamassassin.apache.org/tests.html .
16 #
17 # score SYMBOLIC_TEST_NAME n.nn
18
19 # Speakers of Asian languages, like Chinese, Japanese and Korean, will almost
20 # definitely want to uncomment the following lines.  They will switch off some
21 # rules that detect 8-bit characters, which commonly trigger on mails using CJK
22 # character sets, or that assume a western-style charset is in use. 
23
24 # score HTML_COMMENT_8BITS      0
25 # score UPPERCASE_25_50         0
26 # score UPPERCASE_50_75         0
27 # score UPPERCASE_75_100        0
28 # score OBSCURED_EMAIL          0
29
30 # Speakers of any language that uses non-English, accented characters may wish
31 # to uncomment the following lines.   They turn off rules that fire on
32 # misformatted messages generated by common mail apps in contravention of the
33 # email RFCs.
34
35 # score SUBJ_ILLEGAL_CHARS      0
36
37 use_auto_whitelist 0
38
39 focr_timeout 30
40
41 report_safe 0
42 report_safe_copy_headers X-CRM114-Status X-CRM114-Notice
43 report_safe_copy_headers X-Greylist
44
45 rewrite_header SUBJECT
46
47 #bayes_path ~/.var/spamassassin/bayes
48 bayes_auto_learn 0
49 bayes_ignore_header X-Original-To
50 bayes_ignore_header X-EqDomain
51 bayes_ignore_header X-EqTo
52 bayes_ignore_header X-Been-There
53 bayes_ignore_header X-Delivered-To
54 bayes_ignore_header X-Greylist
55 bayes_ignore_header X-Virus-Scanned
56 bayes_ignore_header X-Virus-Status
57 bayes_ignore_header X-CRM114-Status
58 bayes_ignore_header X-CRM114-CacheID
59 bayes_ignore_header X-CRM114-Notice
60 bayes_ignore_header X-CRM114-Version
61 #bayes_ignore_header X-Sender-IP #
62 #bayes_ignore_header X-CIDR #
63 #bayes_ignore_header X-ASN #
64 bayes_ignore_header X-Spam-Relays-External 
65 bayes_ignore_header X-Spam-Relays-Internal
66 bayes_ignore_header X-Spam-Relays-Trusted
67 bayes_ignore_header X-Spam-Relays-Untrusted
68 bayes_ignore_header X-Spam-Status
69 bayes_ignore_header X-Spam-Bayes
70 bayes_ignore_header X-Spam-Level
71 bayes_ignore_header X-Spam
72 bayes_ignore_header X-Justme
73 bayes_ignore_header X-Tickle
74 bayes_ignore_header X-Delayed
75 bayes_ignore_header X-Resubmitted
76 bayes_ignore_header X-Trained-As
77 bayes_ignore_from add@ress.com #
78 bayes_learn_to_journal 1
79
80 add_header all Status _YESNO_, score=_SCORE_/_REQD_ tests=_TESTS_ autolearn=_AUTOLEARN_
81 add_header all Bayes score=_BAYES_ sum=_TOKENSUMMARY_ ham=_HAMMYTOKENS_ spam=_SPAMMYTOKENS_
82 add_header all Level _STARS(-)_
83 #add_header all Relays-Trusted _RELAYSTRUSTED_
84 add_header all Relays-Untrusted _RELAYSUNTRUSTED_
85 #add_header all Relays-Internal _RELAYSINTERNAL_
86 #add_header all Relays-External _RELAYSEXTERNAL_
87
88 # the local host
89 #trusted_networks 127.
90 # madduck.net
91 trusted_networks 130.60.75.72 82.197.162.59 213.203.238.82
92 # debian: gluck master murphy spohr rietz
93 trusted_networks 192.25.206.10 70.103.162.29 70.103.162.31 192.25.206.33 140.211.166.43
94 # debian: alioth
95 trusted_networks 217.196.43.134
96 # ifi: bela miraculix
97 trusted_networks 130.60.156.10 130.60.156.214
98 # ailab: gaia
99 trusted_networks 130.60.75.60
100 # fortytwo
101 trusted_networks 193.138.215.60
102 # aerasec: all of MNET-AERASEC
103 trusted_networks 212.18.21.160/26
104 # swat: osprey.sccs
105 trusted_networks 130.58.218.6
106 # acm
107 trusted_networks 63.118.7.109
108 # skynet: calculon gir
109 trusted_networks 193.1.99.88 193.1.99.77
110 # ul: marshal4
111 trusted_networks 193.1.100.137
112 # ieee: ruebert
113 trusted_networks 140.98.193.10
114 # vger.kernel.org
115 trusted_networks 209.132.176.167
116
117 whitelist_from *master@*.madduck.net
118 whitelist_from *master@madduck.net
119 whitelist_from logcheck@*.madduck.net
120 whitelist_from root@*.madduck.net
121 whitelist_from root@madduck.net
122 whitelist_from *-owner@lists.madduck.net
123 whitelist_to *-owner@lists.madduck.net
124 whitelist_from *-owner@lists.ailab.ch
125 whitelist_to *-owner@lists.ailab.ch
126
127 ok_locales en
128 ok_languages en de
129
130 header MADDUCK_IN_REFERENCES References =~ /madduck\.net/
131 tflags MADDUCK_IN_REFERENCES nice
132 describe MADDUCK_IN_REFERENCES madduck.net appears in References header
133 score MADDUCK_IN_REFERENCES -100.0
134
135 # more obfuscated drugs
136 # see http://issues.apache.org/SpamAssassin/show_bug.cgi?id=4875
137 replace_tag WS ( [a-z] )
138 body __L_rp_drug_ws1 /(?!xanax)X<WS>A<WS>N<WS>A<WS>X/i
139 body __L_rp_drug_ws2 /(?!ambien)A<WS>M<WS>B<WS>I<WS>E<WS>N/i
140 body __L_rp_drug_ws3 /(?!viagra)V<WS>I<WS>A<WS>G<WS>R<WS>A/i
141 body __L_rp_drug_ws4 /(?!soma)S<WS>O<WS>M<WS>A/i
142 body __L_rp_drug_ws5 /(?!cialis)C<WS>I<WS>A<WS>L<WS>I<WS>S/i
143 body __L_rp_drug_ws6 /(?!valium)V<WS>A<WS>L<WS>I<WS>U<WS>M/i
144 body __L_rp_drug_ws7 /(?!meridia)M<WS>E<WS>R<WS>I<WS>D<WS>I<WS>A/i
145 replace_rules __L_rp_drug_ws1 __L_rp_drug_ws2 __L_rp_drug_ws3 __L_rp_drug_ws4 __L_rp_drug_ws5 __L_rp_drug_ws6 __L_rp_drug_ws7
146 meta L_drug_ws_obfu (__L_rp_drug_ws1 + __L_rp_drug_ws2 + __L_rp_drug_ws3 + __L_rp_drug_ws4 + __L_rp_drug_ws5 + __L_rp_drug_ws6 + __L_rp_drug_ws7) > 3
147 score L_drug_ws_obfu 3
148
149 # http://marc.info/?t=118544884300001&r=1&w=2
150 score BAYES_60 0.0001 0.0001 1.5 1.5
151 score BAYES_80 0.0001 0.0001 2.5 2.5
152 score BAYES_95 0.0001 0.0001 4.0 4.0
153 score BAYES_99 0.0001 0.0001 5.0 5.0