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BOGOFILTER(1)			   Bogofilter Reference Manual			    BOGOFILTER(1)

NAME
       bogofilter - fast Bayesian spam filter

SYNOPSIS
       bogofilter [help options | classification options | registration options |
		  parameter options | info options] [general options] [config file options]

       where

       help options are:

       [-h] [--help] [-V] [-Q]

       classification options are:

       [-p] [-e] [-t] [-T] [-u] [-H] [-M] [-b] [-B object ...] [-R] [general options]
	[parameter options] [config file options]

       registration options are:

       [-s | -n] [-S | -N] [general options]

       general options are:

       [-c filename] [-C] [-d dir] [-k cachesize] [-l] [-L tag] [-I filename] [-O filename]

       parameter options are:

       [-E value[,value]] [-m value[,value][,value]] [-o value[,value]]

       info options are:

       [-v] [-y date] [-D] [-x flags]

       config file options are:

       [--option=value]

       Note: Use bogofilter --help to display the complete list of options.

DESCRIPTION
       Bogofilter is a Bayesian spam filter. In its normal mode of operation, it takes an email
       message or other text on standard input, does a statistical check against lists of "good"
       and "bad" words, and returns a status code indicating whether or not the message is spam.
       Bogofilter is designed with a fast algorithm, uses the Berkeley DB for fast startup and
       lookups, coded directly in C, and tuned for speed, so it can be used for production by
       sites that process a lot of mail.

THEORY OF OPERATION
       Bogofilter treats its input as a bag of tokens. Each token is checked against a wordlist,
       which maintains counts of the numbers of times it has occurred in non-spam and spam mails.
       These numbers are used to compute an estimate of the probability that a message in which
       the token occurs is spam. Those are combined to indicate whether the message is spam or
       ham.

       While this method sounds crude compared to the more usual pattern-matching approach, it
       turns out to be extremely effective. Paul Graham's paper A Plan For Spam[1] is recommended
       reading.

       This program substantially improves on Paul's proposal by doing smarter lexical analysis.
       Bogofilter does proper MIME decoding and a reasonable HTML parsing. Special kinds of
       tokens like hostnames and IP addresses are retained as recognition features rather than
       broken up. Various kinds of MTA cruft such as dates and message-IDs are ignored so as not
       to bloat the wordlist. Tokens found in various header fields are marked appropriately.

       Another improvement is that this program offers Gary Robinson's suggested modifications to
       the calculations (see the parameters robx and robs below). These modifications are
       described in Robinson's paper Spam Detection[2].

       Since then, Robinson (see his Linux Journal article A Statistical Approach to the Spam
       Problem[3]) and others have realized that the calculation can be further optimized using
       Fisher's method.  Another improvement[4] compensates for token redundancy by applying
       separate effective size factors (ESF) to spam and nonspam probability calculations.

       In short, this is how it works: The estimates for the spam probabilities of the individual
       tokens are combined using the "inverse chi-square function". Its value indicates how badly
       the null hypothesis that the message is just a random collection of independent words with
       probabilities given by our previous estimates fails. This function is very sensitive to
       small probabilities (hammish words), but not to high probabilities (spammish words); so
       the value only indicates strong hammish signs in a message. Now using inverse
       probabilities for the tokens, the same computation is done again, giving an indicator that
       a message looks strongly spammish. Finally, those two indicators are subtracted (and
       scaled into a 0-1-interval). This combined indicator (bogosity) is close to 0 if the signs
       for a hammish message are stronger than for a spammish message and close to 1 if the
       situation is the other way round. If signs for both are equally strong, the value will be
       near 0.5. Since those message don't give a clear indication there is a tristate mode in
       bogofilter to mark those messages as unsure, while the clear messages are marked as spam
       or ham, respectively. In two-state mode, every message is marked as either spam or ham.

       Various parameters influence these calculations, the most important are:

       robx: the score given to a token which has not seen before. robx is the probability that
       the token is spammish.

       robs: a weight on robx which moves the probability of a little seen token towards robx.

       min-dev: a minimum distance from .5 for tokens to use in the calculation. Only tokens
       farther away from 0.5 than this value are used.

       spam-cutoff: messages with scores greater than or equal to will be marked as spam.

       ham-cutoff: If zero or spam-cutoff, all messages with values strictly below spam-cutoff
       are marked as ham, all others as spam (two-state). Else values less than or equal to
       ham-cutoff are marked as ham, messages with values strictly between ham-cutoff and
       spam-cutoff are marked as unsure; the rest as spam (tristate)

       sp-esf: the effective size factor (ESF) for spam.

       ns-esf: the ESF for nonspam. These ESF values default to 1.0, which is the same as not
       using ESF in the calculation. Values suitable to a user's email population can be
       determined with the aid of the bogotune program.

OPTIONS
       HELP OPTIONS

       The -h option prints the help message and exits.

       The -V option prints the version number and exits.

       The -Q (query) option prints bogofilter's configuration, i.e. registration parameters,
       parsing options, bogofilter directory, etc.

       CLASSIFICATION OPTIONS

       The -p (passthrough) option outputs the message with an X-Bogosity line at the end of the
       message header. This requires keeping the entire message in memory when it's read from
       stdin (or from a pipe or socket). If the message is read from a file that can be rewound,
       bogofilter will read it a second time.

       The -e (embed) option tells bogofilter to exit with code 0 if the message can be
       classified, i.e. if there is not an error. Normally bogofilter uses different codes for
       spam, ham, and unsure classifications, but this simplifies using bogofilter with procmail
       or maildrop.

       The -t (terse) option tells bogofilter to print an abbreviated spamicity message
       containing 1 letter and the score. Spam is indicated with "Y", ham by "N", and unsure by
       "U". Note: the formatting can be customized using the config file.

       The -T provides an invariant terse mode for scripts to use.  bogofilter will print an
       abbreviated spamicity message containing 1 letter and the score. Spam is indicated with
       "S", ham by "H", and unsure by "U".

       The -TT provides an invariant terse mode for scripts to use.  Bogofilter prints only the
       score and displays it to 16 significant digits.

       The -u option tells bogofilter to register the message's text after classifying it as spam
       or non-spam. A spam message will be registered on the spamlist and a non-spam message on
       the goodlist. If the classification is "unsure", the message will not be registered.
       Effectively this option runs bogofilter with the -s or -n flag, as appropriate. Caution is
       urged in the use of this capability, as any classification errors bogofilter may make will
       be preserved and will accumulate until manually corrected with the -Sn and -Ns option
       combinations. Note this option causes the database to be opened for write access, which
       can entail massive slowdowns through lock contention and synchronous I/O operations.

       The -H option tells bogofilter to not tag tokens from the header. This option is for
       testing, you should not use it in normal operation.

       The -M option tells bogofilter to process its input as a mbox formatted file. If the -v or
       -t option is also given, a spamicity line will be printed for each message.

       The -b (streaming bulk mode) option tells bogofilter to classify multiple objects whose
       names are read from stdin. If the -v or -t option is also given, bogofilter will print a
       line giving file name and classification information for each file. This is an alternative
       to -B which lists objects on the command line.

       An object in this context shall be a maildir (autodetected), or if it's not a maildir, a
       single mail unless -M is given - in that case it's processed as mbox. (The Content-Length:
       header is not taken into account currently.)

       When reading mbox format, bogofilter relies on the empty line after a mail. If needed,
       formail -es will ensure this is the case.

       The -B object ...  (bulk mode) option tells bogofilter to classify multiple objects named
       on the command line. The objects may be filenames (for single messages), mailboxes (files
       with multiple messages), or directories (of maildir and MH format). If the -v or -t option
       is also given, bogofilter will print a line giving file name and classification
       information for each file. This is an alternative to -b which lists objects on stdin.

       The -R option tells bogofilter to output an R data frame in text form on the standard
       output. See the section on integration with R, below, for further detail.

       REGISTRATION OPTIONS

       The -s option tells bogofilter to register the text presented as spam. The database is
       created if absent.

       The -n option tells bogofilter to register the text presented as non-spam.

       Bogofilter doesn't detect if a message registered twice. If you do this by accident, the
       token counts will off by 1 from what you really want and the corresponding spam scores
       will be slightly off. Given a large number of tokens and messages in the wordlist, this
       doesn't matter. The problem can be corrected by using the -S option or the -N option.

       The -S option tells bogofilter to undo a prior registration of the same message as spam.
       If a message was incorrectly entered as spam by -s or -u and you want to remove it and
       enter it as non-spam, use -Sn. If -S is used for a message that wasn't registered as spam,
       the counts will still be decremented.

       The -N option tells bogofilter to undo a prior registration of the same message as
       non-spam. If a message was incorrectly entered as non-spam by -n or -u and you want to
       remove it and enter it as spam, then use -Ns. If -N is used for a message that wasn't
       registered as non-spam, the counts will still be decremented.

       GENERAL OPTIONS

       The -c filename option tells bogofilter to read the config file named.

       The -C option prevents bogofilter from reading configuration files.

       The -d dir option allows you to set the directory for the database. See the ENVIRONMENT
       section for other directory setting options.

       The -k cachesize option sets the cache size for the BerkeleyDB subsystem, in units of 1
       MiB (1,048,576 bytes). Properly sizing the cache improves bogofilter's performance. The
       recommended size is one third of the size of the database file. You can run the bogotune
       script (in the tuning directory) to determine the recommended size.

       The -l option writes an informational line to the system log each time bogofilter is run.
       The information logged depends on how bogofilter is run.

       The -L tag option configures a tag which can be included in the information being logged
       by the -l option, but it requires a custom format that includes the %l string for now.
       This option implies -l.

       The -I filename option tells bogofilter to read its input from the specified file, rather
       than from stdin.

       The -O filename option tells bogofilter where to write its output in passthrough mode.
       Note that this only works when -p is explicitly given.

       PARAMETER OPTIONS

       The -E value[,value] option allows setting the sp-esf value and the ns-esf value. With two
       values, both sp-esf and ns-esf are set. If only one value is given, parameters are set as
       described in the note below.

       The -m value[,value][,value] option allows setting the min-dev value and, optionally, the
       robs and robx values. With three values, min-dev, robs, and robx are all set. If fewer
       values are given, parameters are set as described in the note below.

       The -o value[,value] option allows setting the spam-cutoff ham-cutoff values. With two
       values, both spam-cutoff and ham-cutoff are set. If only one value is given, parameters
       are set as described in the note below.

       Note: All of these options allow fewer values to be provided. Values can be skipped by
       using just the comma delimiter, in which case the corresponding parameter(s) won't be
       changed. If only the first value is provided, then only the first parameter is set.
       Trailing values can be skipped, in which case the corresponding parameters won't be
       changed. Within the parameter list, spaces are not allowed after commas.

       INFO OPTIONS

       The -v option produces a report to standard output on bogofilter's analysis of the input.
       Each additional v will increase the verbosity of the output, up to a maximum of 4. With
       -vv, the report lists the tokens with highest deviation from a mean of 0.5 association
       with spam.

       Option -y date can be used to override the current date when timestamping tokens. A value
       of zero (0) turns off timestamping.

       The -D option redirects debug output to stdout.

       The -x flags option allows setting of debug flags for printing debug information. See
       header file debug.h for the list of usable flags.

       CONFIG FILE OPTIONS

       Using GNU longopt -- syntax, a config file's name=value statement becomes a command line's
       --option=value. Use command bogofilter --help for a list of options and see
       bogofilter.cf.example for more info on them. For example to change the X-Bogosity header
       to "X-Spam-Header", use:

       --spam-header-name=X-Spam-Header

ENVIRONMENT
       Bogofilter uses a database directory, which can be set in the config file. If not set
       there, bogofilter will use the value of BOGOFILTER_DIR. Both can be overridden by the -d
       dir option. If none of that is available, bogofilter will use directory $HOME/.bogofilter.

CONFIGURATION
       The bogofilter command line allows setting of many options that determine how bogofilter
       operates. File /etc/bogofilter.cf can be used to set additional parameters that affect its
       operation. File /etc/bogofilter.cf.example has samples of all of the parameters. Status
       and logging messages can be customized for each site.

RETURN VALUES
       0 for spam; 1 for non-spam; 2 for unsure ; 3 for I/O or other errors.

       If both -p and -e are used, the return values are: 0 for spam or non-spam; 3 for I/O or
       other errors.

       Error 3 usually means that the wordlist file bogofilter wants to read at startup is
       missing or the hard disk has filled up in -p mode.

INTEGRATION WITH OTHER TOOLS
       Use with procmail

       The following recipe (a) spam-bins anything that bogofilter rates as spam, (b) registers
       the words in messages rated as spam as such, and (c) registers the words in messages rated
       as non-spam as such. With this in place, it will normally only be necessary for the user
       to intervene (with -Ns or -Sn) when bogofilter miscategorizes something.

	   # filter mail through bogofilter, tagging it as Ham, Spam, or Unsure,
	   # and updating the wordlist

	   :0fw
	   | bogofilter -u -e -p

	   # if bogofilter failed, return the mail to the queue;
	   # the MTA will retry to deliver it later
	   # 75 is the value for EX_TEMPFAIL in /usr/include/sysexits.h

	   :0e
	   { EXITCODE=75 HOST }

	   # file the mail to spam-bogofilter if it's spam.

	   :0:
	   * ^X-Bogosity: Spam, tests=bogofilter
	   spam-bogofilter

	   # file the mail to unsure-bogofilter
	   # if it's neither ham nor spam.

	   :0:
	   * ^X-Bogosity: Unsure, tests=bogofilter
	   unsure-bogofilter

	   # With this recipe, you can train bogofilter starting with an empty
	   # wordlist.	Be sure to check your unsure-folder regularly, take the
	   # messages out of it, classify them as ham (or spam), and use them to
	   # train bogofilter.

       The following procmail rule will take mail on stdin and save it to file spam if bogofilter
       thinks it's spam:

	   :0HB:
	   * ? bogofilter
	   spam

       and this similar rule will also register the tokens in the mail according to the
       bogofilter classification:

	   :0HB:
	   * ? bogofilter -u
	   spam

       If bogofilter fails (returning 3) the message will be treated as non-spam.

       This one is for maildrop, it automatically defers the mail and retries later when the
       xfilter command fails, use this in your ~/.mailfilter:

	   xfilter "bogofilter -u -e -p"
	   if (/^X-Bogosity: Spam, tests=bogofilter/)
	   {
	     to "spam-bogofilter"
	   }

       The following .muttrc lines will create mutt macros for dispatching mail to bogofilter.

	   macro index d "<enter-command>unset wait_key\n\
	   <pipe-entry>bogofilter -n\n\
	   <enter-command>set wait_key\n\
	   <delete-message>" "delete message as non-spam"
	   macro index \ed "<enter-command>unset wait_key\n\
	   <pipe-entry>bogofilter -s\n\
	   <enter-command>set wait_key\n\
	   <delete-message>" "delete message as spam"

       Integration with Mail Transport Agent (MTA)

	1. bogofilter can also be integrated into an MTA to filter all incoming mail. While the
	   specific implementation is MTA dependent, the general steps are as follows:

	2. Install bogofilter on the mail server

	3. Prime the bogofilter databases with a spam and non-spam corpus. Since bogofilter will
	   be serving a larger community, it is important to prime it with a representative set
	   of messages.

	4. Set up the MTA to invoke bogofilter on each message. While this is an MTA specific
	   step, you'll probably need to use the -p, -u, and -e options.

	5. Set up a mechanism for users to register spam/non-spam messages, as well as to correct
	   mis-classifications. The most generic solution is to set up alias email addresses to
	   which users bounce messages.

	6. See the doc and contrib directories for more information.

       Use of R to verify bogofilter's calculations

       The -R option tells bogofilter to generate an R data frame. The data frame contains one
       row per token analyzed. Each such row contains the token, the sum of its database "good"
       and "spam" counts, the "good" count divided by the number of non-spam messages used to
       create the training database, the "spam" count divided by the spam message count,
       Robinson's f(w) for the token, the natural logs of (1 - f(w)) and f(w), and an indicator
       character (+ if the token's f(w) value exceeded the minimum deviation from 0.5, - if it
       didn't). There is one additional row at the end of the table that contains a label in the
       token field, followed by the number of words actually used (the ones with + indicators),
       Robinson's P, Q, S, s and x values and the minimum deviation.

       The R data frame can be saved to a file and later read into an R session (see the R
       project website[5] for information about the mathematics package R). Provided with the
       bogofilter distribution is a simple R script (file bogo.R) that can be used to verify
       bogofilter's calculations. Instructions for its use are included in the script in the form
       of comments.

LOG MESSAGES
       Bogofilter writes messages to the system log when the -l option is used. What is written
       depends on which other flags are used.

       A classification run will generate (we are not showing the date and host part here):

	   bogofilter[1412]: X-Bogosity: Ham, spamicity=0.000227
	   bogofilter[1415]: X-Bogosity: Spam, spamicity=0.998918

       Using -u to classify a message and update a wordlist will produce (one a single line):

	   bogofilter[1426]: X-Bogosity: Spam, spamicity=0.998918,
	     register -s, 329 words, 1 messages

       Registering words (-l and -s, -n, -S, or -N) will produce:

	   bogofilter[1440]: register-n, 255 words, 1 messages

       A registration run (using -s, -n, -N, or -S) will generate messages like:

	   bogofilter[17330]: register-n, 574 words, 3 messages
	   bogofilter[6244]: register-s, 1273 words, 4 messages

FILES
       /etc/bogofilter.cf
	   System configuration file.

       ~/.bogofilter.cf
	   User configuration file.

       ~/.bogofilter/wordlist.db
	   Combined list of good and spam tokens.

AUTHOR
	   Eric S. Raymond esr@thyrsus.com.
	   David Relson relson@osagesoftware.com.
	   Matthias Andree matthias.andree@gmx.de.
	   Greg Louis glouis@dynamicro.on.ca.

       For updates, see the bogofilter project page[6].

SEE ALSO
       bogolexer(1), bogotune(1), bogoupgrade(1), bogoutil(1)

NOTES
	1. A Plan For Spam
	   http://www.paulgraham.com/spam.html

	2. Spam Detection
	   http://radio-weblogs.com/0101454/stories/2002/09/16/spamDetection.html

	3. A Statistical Approach to the Spam Problem
	   http://www.linuxjournal.com/article/6467

	4. Another improvement
	   http://www.garyrobinson.net/2004/04/improved%5fchi.html

	5. the R project website
	   http://cran.r-project.org/

	6. bogofilter project page
	   http://bogofilter.sourceforge.net/

Bogofilter				    10/22/2012				    BOGOFILTER(1)
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