BOGOFILTER(1)

🎀 NAME 🎀

bogofilter - fast Bayesian spam filter. That’s the whole NAME section, bestie — this is the bogofilter(1) page from the Bogofilter Reference Manual, and it is literally the fast Bayesian spam filter. Periodt. 💅✨

✨ SYNOPSIS ✨

Okay so here’s the full invocation shape, and yes, every bracket matters:

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]

Tiny PSA from the page itself: 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. 🎯

It is designed with a fast algorithm, uses the Berkeley DB for fast startup and lookups, is coded directly in C, and is tuned for speed, so it can be used for production by sites that process a lot of mail. Slay. 🔥👑

🔥 THEORY OF OPERATION 🔥

Bogofilter treats its input as a bag of tokens. Each token is checked against a wordlist, which maintains counts of the number of times it has occurred in non-spam and spam mails. Those numbers are used to compute an estimate of the probability that a message in which the token occurs is spam. Those estimates are then 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 messages 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 it 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 💅

okay bestie, this is the part where we meet all the little flags that make bogofilter do its thing. there are a LOT of them. buckle up. 🎀

✨ HELP OPTIONS ✨

• -h — prints the help message and then dips out. that's it, that's the whole vibe.
• -V — prints the version number and exits. iconic behavior honestly.
• -Q — the query option. it prints bogofilter's configuration for you — like, the registration parameters, the parsing options, the bogofilter directory, all of it. a little peek behind the curtain 👀.

🔥 CLASSIFICATION OPTIONS 🔥

• -p — the passthrough option. it outputs the message with an X-Bogosity line tacked onto the end of the message header. heads up though: this requires keeping the entire message in memory when it's read from stdin (or from a pipe or socket). if the message is being read from a file that can be rewound, bogofilter will just read it a second time instead. no biggie.
• -e — the 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 one keeps it simple, which makes using bogofilter with procmail or maildrop way easier. 🫶
• -t — the 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, if you're feeling fancy.
• -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". (yes, this is the double-t capital-T situation, lowkey different letters from -t, don't mix them up bestie 💀)
• -TT — provides an invariant terse mode for scripts to use. bogofilter prints only the score and displays it to 16 significant digits. that's a lot of digits. main character precision. 👑
• -u — 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. also 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. so like… use it with intention, okay?
• -H — tells bogofilter to not tag tokens from the header. this option is for testing — you should not use it in normal operation. seriously. it's a lab experiment, not a lifestyle. 🙈
• -M — tells bogofilter to process its input as an mbox formatted file. if the -v or -t option is also given, a spamicity line will be printed for each message.
• -b — the 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 which case it's processed as mbox. (the Content-Length: header is not taken into account currently. noted, bestie. 📝)
  • when reading mbox format, bogofilter relies on the empty line after a mail. if needed, formail -es will ensure this is the case.
• -B object ... — the 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.
• -R — 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. nerd corner activated 🤓✨

🌸 REGISTRATION OPTIONS 🌸

• -s — tells bogofilter to register the text presented as spam. the database is created if absent. very "make it if it doesn't exist" of it.
• -n — tells bogofilter to register the text presented as non-spam.

okay so a little tea ☕: bogofilter doesn't detect if a message is registered twice. if you do this by accident, the token counts will be 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. so, y'know, not the end of the world 💖.

• -S — 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. so like, be aware of that.
• -N — 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. same deal, bestie.

🦋 GENERAL OPTIONS 🦋

• -c filename — tells bogofilter to read the config file named.
• -C — prevents bogofilter from reading configuration files. no config for you ✋.
• -d dir — lets you set the directory for the database. see the ENVIRONMENT section for other directory setting options.
• -k cachesize — 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. math girl summer 📐💅
• -l — writes an informational line to the system log each time bogofilter is run. the information logged depends on how bogofilter is run.
• -L tag — 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.
• -I filename — tells bogofilter to read its input from the specified file, rather than from stdin.
• -O filename — tells bogofilter where to write its output in passthrough mode. ⚠️ note that this only works when -p is explicitly given. no -p, no party.

🧚 PARAMETER OPTIONS 🧚

• -E value[,value] — 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.
• -m value[,value][,value] — 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.
• -o value[,value] — allows setting the spam-cutoff and 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 bestie: 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. commas stay tight, no gaps. 🫶

⭐ INFO OPTIONS ⭐

• -v — 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.
• -y date — can be used to override the current date when timestamping tokens. a value of zero (0) turns off timestamping.
• -D — redirects debug output to stdout.
• -x flags — allows setting of debug flags for printing debug information. see header file debug.h for the list of usable flags.

💜 CONFIG FILE OPTIONS 💜

using the 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

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🌈 ENVIRONMENT 🌈

bogofilter uses a database directory, which can be set in the config file. if it's 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. so there's like… a whole priority order, and the vibes cascade down until something sticks 💫.

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🎀 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. make it yours, bestie 💅✨.

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🫶 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 💌

Okay so bestie, this recipe is the moment: it (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. Periodt.

# 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, so 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. Iykyk, it's giving productivity:

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, and that data frame has one row per token analyzed. Each row is packed with: 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. Obsessed with the structure, honestly.

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.

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📜 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 (on 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/

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That's the whole BOGOFILTER(1) page, bestie — Bogofilter, dated 06/29/2013. Now go forth and filter 💅✨