Provided by: spamoracle_1.4-14build2_i386
spamoracle - a spam classification tool
spamoracle [-config conf] [-f database] mark [ mailbox ... ]
spamoracle [-config conf] [-f database] add [-v] -spam spambox ...
-good goodbox ...
spamoracle [-config conf] [-f database] test [-min prob] [-max prob] [
mailbox ... ]
spamoracle [-config conf] [-f database] stat [ mailbox ... ]
spamoracle [-config conf] [-f database] list regexp ...
spamoracle [-config conf] [-f database] backup > backupfile
spamoracle [-config conf] [-f database] restore < backupfile
spamoracle [-config conf] [-f database] words [ mailbox ... ]
SpamOracle is a tool to help detect and filter away "spam" (unsolicited
commercial e-mail). It proceeds by statistical analysis of the words
that appear in the e-mail, comparing the frequencies of words with
those found in a user-provided corpus of known spam and known
legitimate e-mail. The classification algorithm is based on Bayes'
formula, and is described in Paul Graham's paper, A plan for spam,
This program is designed to work in conjunction with procmail(1). The
result of the analysis is output as an additional message header X-
Spam: followed by yes, no or unknown, plus additional details. A
procmail rule can then test this X-Spam: header and deliver the e-mail
to the appropriate mailbox.
In addition, SpamOracle also analyses MIME attachments, extracting
relevant information such as MIME type, character encoding and attached
file name, and summarizing them in an additional X-Attachments: header.
This allows procmail to easily reject e-mails containing suspicious
attachments, e.g. Windows executables which often indicate a virus.
REQUIREMENTS AND LIMITATIONS
To use SpamOracle, your mail must be delivered to a Unix machine on
which you have a shell account. This machine must have procmail(1)
(see http://www.procmail.org/) installed. Your ~/.forward file must be
set up to run all incoming e-mail through procmail(1). If your mail
server supports the POP or IMAP protocols, you can also use
fetchmail(1) to fetch your mail from the server and have it delivered
to your local machine.
To provide the corpus of messages from which SpamOracle "learns", an
archive of about 1000 of your e-mails is needed. The archive must be
manually or semi-automatically split into known spams and known good
messages. Mis-classified messages in the corpus (e.g. spams mistakenly
stored among the good messages) will decrease the efficiency of the
classification. The archive must be in Unix mailbox format, or in "one
message per file" format (a la MH). Other formats, such as Emacs'
Babyl, are not supported.
The notion of "word" used by SpamOracle is slanted towards Western
European languages, i.e. the ISO Latin-1 and Latin-9 character sets.
Preliminary support for JIS-encoded Japanese can be selected at
compile-time. SpamOracle will not work well if you receive many
legitimate e-mails written in other character sets, such as Chinese or
To build the database of word frequencies from the corpus, do:
spamoracle add -v -good goodmails -spam spammails
By default, the database is stored in the file .spamoracle.db in your
home directory. This can be overriden with the -f option: spamoracle
-f mydatabase add ... The -v option prints progress information during
the processing of the corpus.
This assumes that the good, non-spam messages from the corpus are
stored in the file goodmails, and the known spam messages in the file
spammails. You can also fetch corpus messages from several files,
and/or process them via several invocations of SpamOracle:
spamoracle add -good goodmails1 ... goodmailsN
spamoracle add -spam spammails1 ... spammailsP
TESTING THE DATABASE
To check that the database was built correctly, and familiarize
yourself with the statistical analysis performed by SpamOracle, invoke
the "test" mode on the mailboxes that you just used for building the
spamoracle test goodmails | more
spamoracle test spammails | more
For each message in the given mailboxes, you'll see a summary like
From: bbo <firstname.lastname@example.org>
Subject: Check This Out
Score: 1.00 -- 15
Details: refid:98 $$$$:98 surfing:98 asp:95 click:93 cable:92
instantly:90 https:88 internet:87 www:86 U4:85 isn't:14 month:81
Attachments: cset="GB2312" type="application/octet-stream"
The first two lines are just the From: and Subject: fields of the
The Score: line summarizes the result of the analysis. The first
number (between 0.0 and 1.0) is the probability that the message is
actually spam --- or, equivalently, the degree of similarity of the
message with the spam messages in the corpus. The second number (an
integer between 0 and 15) is the number of "interesting" words found in
the message. "Interesting" words are those that occur at least 5 times
in the corpus. In the example, we have 15 interesting words (the
maximum) and a score of 1.00, indicating a spam with high certainty.
The Details: line provides an explanation of the score. It lists the
15 most interesting words found in the message, that is, the 15
interesting words whose probability of denoting a spam is farthest away
from the neutral 0.5. Each word is given with its individual score,
written as a percentage (between 01 and 99) rather than as a
probability so as to save space. Here, we see a number of very
"spammish" words such as $$$$ or click, with probability 0.98 and 0.93
respectively, and a few "innocent" words such as isn't (probability
0.14). The U4 word with probability 0.85 is actually a pseudo-word
representing a 4-letter word all in uppercase -- something spammers are
The Attachments: line summarizes some information about MIME
attachments for this message. Here, we have one attachment of type
application/octect-stream, file name Guangwen4.zip, and character set
GB2312 (an encoding for Chinese).
The File: line shows the file that is being tested.
Normally, when running spamoracle test goodmails, most messages should
come out with low score (0.2 or less), and when running spamoracle test
spammails, most messages should come out with a high score (0.8 or
more). If not, your corpus isn't very good, or not well classified
into spam and non-spam. To quickly see the outliers, you can reduce
the interval of scores for which message summaries are displayed, as
spamoracle test -min 0.2 goodmails | more
# Shows only good mails with score >= 0.2
spamoracle test -max 0.8 spammails | more
# Shows only spam mails with score <= 0.8
Now, for a more challenging test, take a mailbox that contains
unfiltered e-mails, i.e. a mixture of spam and legitimate e-mails, and
run it through SpamOracle:
spamoracle test mymailbox | less
Marvel at how well the oracle recognizes spam from the rest! If the
result isn't that marvelous to you, keep in mind that certain spams are
just too short to be recognized (not enough significant words). Also,
perhaps your corpus was too small, or not well categorized...
MARKING AND FILTERING INCOMING E-MAIL
Once the database is built, you're ready to run incoming e-mails
through SpamOracle. The command spamoracle mark reads one e-mail from
standard input, and copies it to standard output, with two headers
inserted: X-Spam: and X-Attachments:. The X-Spam: header has one the
X-Spam: yes; score; details
X-Spam: no; score; details
X-Spam: unknown; score; details
The score and details are as described for spamoracle test.
The yes/no/unknown tag synthesizes the results of the analysis: yes
means that the score is >= 0.8 and at least 5 interesting words were
found; no means that the score is <= 0.2 and at least 5 interesting
words were found; unknown is returned otherwise. The unknown case
generally occurs for very short messages, where not enough interesting
words were found.
The X-Attachments: header contains the same information as the
Attachments: output of spamoracle test, that is, a summary of the
To process automatically your incoming e-mail through SpamOracle and
act upon the results of the analysis, just insert the following
"recipes" in the file ~/.procmailrc:
| /usr/local/bin/spamoracle mark
* ^X-Spam: yes;
What these cryptic commands mean is:
- Run every mail through the spamoracle mark command. (If spamoracle
wasn't installed in /usr/local/bin, adjust the path as necessary.)
This adds two headers to the message: X-Spam: and X-Attachments:,
describing the results of the spam analysis and the attachment
- If we have an X-Spam: yes header, deliver the message to the file
spambox rather than to your regular mailbox. Presumably, you'll read
spambox once in a while, but less often than your regular mailbox.
Daring users can put /dev/null instead of spambox to just throw away
the message, but please don't do that until you've used SpamOracle for
a while and are happy with the results. SpamOracle's false positive
rate (i.e. legitimate mails classified as spam) is low (0.1%) but not
null. So, better save the presumed spams somewhere, and scan them
quickly from time to time.
If you'd like to enjoy a bit of attachment-based filtering, here are
some procmail rules for that:
The first rule treats as spam every mail that has a Windows executable
as attachment. These mails are typically sent by viruses. The second
rule does the same with attachments of type x-wav or x-midi. I never
normally receive music by e-mail, however some popular e-mail viruses
seem fond of these attachment types. The third rule treats as spam
every mail that uses character encodings corresponding to Korean,
Chinese, Japanese, and Cyrillic.
UPDATING THE DATABASE
At any time, you can add more known spams or known legitimate messages
to the database by using the spamoracle add command.
For instance, if you find a spam message that was not classified as
such, run it through spamoracle add -spam, so that SpamOracle can learn
from its mistake. (Without additional arguments, this command will
read a single message from standard input and record it as spam.)
Under mutt(1) for instance, just highlight the spam message and type
|spamoracle add -spam
Similarly, if you find a legitimate message while checking your spam
box, run it through spamoracle add -good.
Another option is to collect more known spams or more known good
messages into mailbox files, and once in a while do spamoracle add
-good new_good_mails or spamoracle add -spam new_spam_mails.
QUERYING THE DATABASE
For your edification and entertainment, the contents of the database
can be queried by regular expressions. The spamoracle list regexp
command lists all words in the database that match regexp (an Emacs-
style regular expression), along with their number of occurrences in
spam mail and in good mail. For instance:
spamoracle list '.*' # show all words -- big list!
spamoracle list 'sex.*'
spamoracle list 'linux.*'
The database used by SpamOracle is stored in a compact, binary format
that is not humanly readable. Moreover, this format is subject to
change in later versions of SpamOracle. To facilitate backups and
upgrades, the database contents can also be manipulated in a portable,
The spamoracle backup command dumps the contents of the database to
standard output, in a textual, portable format.
The spamoracle restore command reads such a dump from standard input
and rebuilds the database with this data.
The recommended procedure for upgrading to a newer version of
# Before the upgrade:
spamoracle backup > backupfile
# Upgrade SpamOracle
# Restore the database
spamoracle restore < backupfile
CONFIGURING FILTERING PARAMETERS
Many of the parameters that govern message classification can be
configured via a configuration file. By default, the configuration is
read from the file .spamoracle.conf in the user's home directory. A
different configuration file can be specified on the command line using
the -config option: spamoracle -config myconfigfile ...
The list of configurable parameters and the format of the configuration
file are described in spamoracle.conf(5).
All parameters have reasonable defaults, but you can try to improve the
quality of classification further by tweaking them. To determine the
impact of your changes, use either the test or stat commands to
spamoracle. The spamoracle stat command prints a one-line summary of
how many spam, non-spam, and unknown messages were found in the
mailboxes given as arguments.
SpamOracle's notion of "word" is any run of 3 to 12 of the following
characters: letters, single quotes, and dashes (-). If support for
non-English european languages was compiled in, word characters also
include the relevant accented letters for the languages in question.
All words are mapped to lowercase, and accented letters are mapped to
the corresponding non-accented letters.
A run of 3 to 12 of the following characters also constitutes a word:
digits, dots, commas, and dollar, Euro and percent signs.
In addition, a run of three or more uppercase letters generates a
pseudo-word Un where n is the length of the run. Similarly, a run of
three or more non-ASCII characters (code >= 128) generates a pseudo-
word Wn where n is the length of the run.
For instance, the following text:
SUMMER in English is written "ete" in French
is processed into the following words, assuming French support was
selected at compile-time:
U5 summer english written ete french W3
and if French support was not selected:
U5 summer english written french W3
To see the words that are extracted from a message, issue the
spamoracle words command. It reads either a single message from
standard input, or all messages from the mailbox files given as
arguments, decomposes the messages into words and prints the words.
The database file can be compressed with gzip(1) to save disk space, at
the expense of slower spamoracle operations. If the database file
specified with the -f option has the extension .gz, spamoracle will
automatically uncompress it on start-up, and re-compress it after
If your mail is stored in MH format, you may run into "command line too
long" errors while trying to process a lot of small files with the
spamoracle add command, e.g. when doing
spamoracle add -good archives/*/* -spam spam/*
Instead, do something like:
find archives -type f -print | xargs spamoracle add -good
find spam -type f -print | xargs spamoracle add -spam
Xavier Leroy <Xavier.Leroy@inria.fr>
spamoracle.conf(5); procmail(1); fetchmail(1)
http://cristal.inria.fr/~xleroy/software/ (SpamOracle distribution
http://www.paulgraham.com/spam.html (Paul Graham's seminal paper)