Provided by: qsf_1.2.7-1.3build1_amd64 
NAME
qsf - quick spam filter
SYNOPSIS
Filtering: qsf [-snrAtav] [-d DB] [-g DB]
[-L LVL] [-S SUBJ] [-H MARK] [-Q NUM]
[-X NUM]
Training: qsf -T SPAM NONSPAM [MAXROUNDS] [-d DB]
Retraining: qsf -[m|M] [-d DB] [-w WEIGHT] [-ayN]
Database: qsf -[p|D|R|O] [-d DB]
Database merge: qsf -E OTHERDB [-d DB]
Allowlist query: qsf -e EMAIL [-m|-M|-t] [-d DB] [-g DB]
Denylist query: qsf -y -e EMAIL [-m -m|-M -M|-t] [-d DB] [-g DB]
Help: qsf -[h|V]
DESCRIPTION
qsf reads a single email on standard input, and by default outputs it on standard output. If the email
is determined to be spam, an additional header ("X-Spam: YES") will be added, and optionally the subject
line can have "[SPAM]" prepended to it.
qsf is intended to be used in a procmail(1) recipe, in a ruleset such as this:
:0 wf
| qsf -ra
:0 H:
* X-Spam: YES
$HOME/mail/spam
For more examples, including sample procmail(1) recipes, see the EXAMPLES section below.
TRAINING
Before qsf can be used properly, it needs to be trained. A good way to train qsf is to collect a copy of
all your email into two folders - one for spam, and one for non-spam. Once you have done this, you can
use the training function, like this:
qsf -aT spam-folder non-spam-folder
This will generate a database that can be used by qsf to guess whether email received in the future is
spam or not. Note that this initial training run may take a long time, but you should only need to do it
once.
To mark a single message as spam, pipe it to qsf with the --mark-spam or -m ("mark as spam") option.
This will update the database accordingly and discard the email.
To mark a single message as non-spam, pipe it to qsf with the --mark-nonspam or -M ("mark as non-spam")
option. Again, this will discard the email.
If a message has been mis-tagged, simply send it to qsf as the opposite type, i.e. if it has been
mistakenly tagged as spam, pipe it into qsf --mark-nonspam --weight=2 to add it to the non-spam side of
the database with double the usual weighting.
OPTIONS
The qsf options are listed below.
-d, --database [TYPE:]FILE
Use FILE as the spam/non-spam database. The default is to use /var/lib/qsfdb and, if that is not
available or is read-only, $HOME/.qsfdb. This option can also be useful if there is a system-wide
database but you do not want to use it - specifying your own here will override the default.
If you prefix the filename with a TYPE, of the form btree:$HOME/.qsfdb, then this will specify
what kind of database FILE is, such as list, btree, gdbm, sqlite and so on. Check the output of
qsf -V to see which database backends are available. The default is to auto-detect the type, or,
if the file does not already exist, use list. Note that TYPE is not case-sensitive.
-g, --global [TYPE:]FILE
Use FILE as the default global database, instead of /var/lib/qsfdb. If you also specify a
database with -d, then this "global" database will be used in read-only mode in conjunction with
the read-write database specified with -d. The -g option can be used a second time to specify a
third database, which will also be used in read-only mode. Again, the filename can optionally be
prefixed with a TYPE which specifies the database type.
-P, --plain-map FILE
Maintain a mapping of all database tokens to their non-hashed counterparts in FILE, one token per
line. This can be useful if you want to be able to list the contents of your database at a later
date, for instance to get a list of email addresses in your allow-list. Note that using this
option may slow qsf down, and only entries written to the database while this option is active
will be stored in FILE.
-s, --subject
Rewrite the Subject line of any email that turns out to be spam, adding "[SPAM]" to the start of
the line.
-S, --subject-marker SUBJECT
Instead of adding "[SPAM]", add SUBJECT to the Subject line of any email that turns out to be
spam. Implies -s.
-H, --header-marker MARK
Instead of setting the X-Spam header to "YES", set it to MARK if email turns out to be spam. This
can be useful if your email client can only search all headers for a string, rather than one
particular header (so searching for "YES" might match more than just the output of qsf).
-n, --no-header
Do not add an X-Spam header to messages.
-r, --add-rating
Insert an additional header X-Spam-Rating which is a rating of the "spamminess" of a message from
0 to 100; 90 and above are counted as spam, anything under 90 is not considered spam. If combined
with -t, then the rating (0-100) will be output, on its own, on standard output.
-A, --asterisk
Insert an additional header X-Spam-Level which will contain between 0 and 20 asterisks (*),
depending on the spam rating.
-t, --test
Instead of passing the message out on standard output, output nothing, and exit 0 if the message
is not spam, or exit 1 if the message is spam. If combined with -r, then the spam rating will be
output on standard output.
-a, --allowlist
Enable the allow-list. This causes the email addresses given in the message's "From:" and
"Return-Path:" headers to be checked against a list; if either one matches, then the message is
always treated as non-spam, regardless of what the token database says. When specified with a
retraining flag, -a -m (mark as spam) will remove that address from the allow-list as well as
marking the message as spam, and -a -M (mark as non-spam) will add that address to the allow-list
as well as marking the message as non-spam. The idea is that you add all of your friends to the
allow-list, and then none of their messages ever get marked as spam.
-y, --denylist
Enable the deny-list. This causes the email addresses given in the message's "From:" and "Return-
Path:" headers to be checked against a second list; if either one matches, then theh message is
always treated as spam. Training works in the same way as with -a, except that you must specify
-m or -M twice to modify the deny-list instead of the allow-list, and with the reverse syntax: -y
-m -m (mark as spam) will add that address to the deny-list, whereas -y -M -M (mark as non-spam)
will remove that address from the deny-list. This double specification is so that the usual
retraining process never touches the deny-list; the deny-list should be carefully maintained
rather than automatically generated.
Normally you would not need to use the deny-list.
-L, --level, --threshold LEVEL
Change the spam scoring threshold level which must be reached before an email is classified as
spam. The default is 90.
-Q, --min-tokens NUM
Only give a score if more than NUM tokens are found in the message - otherwise the message is
assumed to be non-spam, and it is not modified in any way. The default is 0. This option might
be useful if you find that very short messages are being frequently miscategorised.
-e, --email, --email-only EMAIL
Query or update the allow-list entry for the email address EMAIL. With no other options, this
will simply output "YES" if EMAIL is in the allow-list, or "NO" if it is not. With -t, it will not
output anything, but will exit 0 (success) if EMAIL is in the allow-list, or 1 (failure) if it is
not. With the -m (mark-spam) option, any previous allow-list entry for EMAIL will be removed.
Finally, with the -M (mark-nonspam) option, EMAIL will be added to the allow-list if it is not
already on it.
If EMAIL is just the word MSG on its own, then an email will be read from standard input, and the
email addresses given in the "From:" and "Return-Path:" headers will be used.
Using -e automatically switches on -a.
If you also specify -y, then the deny-list will be operated on. Remember that -m and -M are
reversed with the deny-list.
If you specify an email address of the form @domain (nothing before the @), then the whole domain
will be allow or deny listed.
-v, --verbose
Add extra X-QSF-Info headers to any filtered email, containing error messages and so on if
applicable. Specify -v more than once to increase verbosity.
-T, --train SPAM NONSPAM [MAXROUNDS]
Train the database using the two mbox folders SPAM and NONSPAM, by testing each message in each
folder and updating the database each time a message is miscategorised. This is done several
times, and may take a while to run. Specify the -a (allow-list) flag to add every sender in the
NONSPAM folder to your allow-list as a side-effect of the training process. If MAXROUNDS is
specified, training will end after this number of rounds if the results are still not good enough.
The default is a maximum of 200 rounds.
-m, --mark-spam
Instead of passing the message out on standard output, mark its contents as spam and update the
database accordingly. If the allow-list (-a) is enabled, the message's "From:" and "Return-Path:"
addresses are removed from the allow-list. If the deny-list (-y) is enabled and you specify -m
twice, the message's addresses are added to the deny-list instead.
-M, --mark-nonspam
Instead of passing the message out on standard output, mark its contents as non-spam and update
the database accordingly. If the allow-list (-a) is enabled, the message's "From:" and "Return-
Path:" addresses are added to the allow-list (see the -a option above). If the deny-list (-y) is
enabled and you specify -M twice, the message's addresses are removed from the deny-list instead.
-w, --weight WEIGHT
When marking as spam or non-spam, update the database with a weighting of WEIGHT per token instead
of the default of 1. Useful when correcting mistakes, eg a message that has been mistakenly
detected as spam should be marked as non-spam using a weighting of 2, i.e. double the usual
weighting, to counteract the error.
-D, --dump [FILE]
Dump the contents of the database as a platform-independent text file, suitable for archival,
transfer to another machine, and so on. The data is output on stdout or into the given FILE.
-R, --restore [FILE]
Rebuild the database from scratch from the text file on stdin. If a FILE is given, data is read
from there instead of from stdin.
-O, --tokens
Instead of filtering, output a list of the tokens found in the message read from standard input,
along with the number of times each token was found. This is only useful if you want to use qsf
as a general tokeniser for use with another filtering package.
-E, --merge OTHERDB
Merge the OTHERDB database into the current database. This can be useful if you want to take one
user's mailbox and merge it into the system-wide one, for instance (this would be done by, as
root, doing qsf -d /var/lib/qsfdb -E /home/user/.qsfdb and then removing /home/user/.qsfdb).
-B, --benchmark SPAM NONSPAM [MAXROUNDS]
Benchmark the training process using the two mbox folders SPAM and NONSPAM. A temporary database
is created and trained using the first 75% of the messages in each folder, and then the entire
contents of each folder is tested to see how many false positives and false negatives occur. Some
timing information is also displayed.
This can be used to decide which backend is best on your system. Use -d to select a backend, eg
qsf -B spam nonspam -d GDBM - this will create a temporary database which is removed afterwards.
The exception to this is the MySQL backend, where a full database specification must be given (-d
MySQL:database=db;host=localhost;...) and the database table given will not be wiped beforehand
or dropped afterwards.
As with -T, if MAXROUNDS is specified, training will never be done for more than this number of
rounds; the default is 200.
-h, --help
Print a usage message on standard output and exit successfully.
-V, --version
Print version information, including a list of available database backends, on standard output and
exit successfully.
DEPRECATED OPTIONS
The following options are only for use with the old binary tree database backend or old databases that
haven't been upgraded to the new format that came in with version 1.1.0.
-N, --no-autoprune
When marking as spam or nonspam, never automatically prune the database. Usually the database is
pruned after every 500 marks; if you would rather --prune manually, use -N to disable automatic
pruning.
-p, --prune
Remove redundant entries from the database and clean it up a little. This is automatically done
after several calls to --mark-spam or --mark-nonspam, and during training with --train if the
training takes a large number of rounds, so it should rarely be necessary to use --prune manually
unless you are using -N / --no-autoprune.
-X, --prune-max NUM
When the database is being pruned, no more than NUM entries will be considered for removal. This
is to prevent CPU and memory resources being taken over. The default is 100,000 but in some
circumstances (if you find that pruning takes too long) this option may be used to reduce it to a
more manageable number.
FILES
/var/lib/qsfdb
The default (system-wide) spam database. If you wish to install qsf system-wide, this should be
read-only to everyone; there should be one user with write access who can update the spam database
with qsf --mark-spam and qsf --mark-non-spam when necessary.
/var/lib/qsfdb2
A second, read-only, system-wide database. This can be useful when installing qsf system-wide and
using third-party spam databases; the first global database can be updated with system-specific
changes, and this second database can be periodically updated when the third-party spam database
is updated.
$HOME/.qsfdb
The default spam database for per-user data. Users without write access to the system-wide
database will have their data written here, and the two databases will be read together. The per-
user database will be given a weighting equivalent to 10 times the weighting of the global
database.
NOTES
Currently, you cannot use qsf to check for spam while the database is being updated. This means that
while an update is in progress, all email is passed through as non-spam.
There is an upper size limit of 512Kb on incoming email; anything larger than this is just passed through
as non-spam, to avoid tying up machine resources.
The plaintext token mapping maintained by --plain-map will never shrink, only grow. It is intended for
use by housekeeping and user interface scripts that, for instance, the user can use to list all email
addresses on their allow-list. These scripts should take care of weeding out entries for tokens that are
no longer in the database. If you have no such scripts, there is probably no point in using --plain-map
anyway.
Avoid using the deny-list (-y) in any automated retraining, as it can be cause the filter to reject mail
unnecessarily. In general the deny-list is probably best left unused unless explicitly required by your
particular setup.
If both the allow-list and the deny-list are enabled, then email addresses will first be checked against
the deny-list, then the allow-list, then the domain of the email address will be checked for matching
"@domain" entries in the deny-list and then in the allow-list.
EXAMPLES
To filter all of your mail through qsf, with the allow-list enabled and the "spam rating" header being
added, add this to your .procmailrc file:
:0 wf
| qsf -ra
If you want qsf to add "[SPAM]" to the subject line of any messages it thinks are spam, do this instead:
:0 wf
| qsf -sra
To automatically mark any email sent to spambox@yourdomain.com as spam (this is the "naive" version):
:0 H
* ^To:.*spambox@yourdomain.com
| qsf -am
To do the same, but cleverly, so that only email to spambox@yourdomain.com which qsf does NOT already
classify as spam gets marked as spam in the database (this stops the database getting too heavily
weighted):
# If sent to spambox@yourdomain.com:
:0
* ^To:.*spambox@yourdomain.com
{
:0 wf
| qsf -a
# The above two lines can be skipped if you've
# already piped the message through qsf.
# If the qsf database says it's not spam,
# mark it as spam!
:0 H
* ^X-Spam: NO
| qsf -am
}
Remove the -a option in the above examples if you don't want to use the allow-list.
A more complicated filtering example - this will only run qsf on messages which don't have a subject line
saying "your <something> is on fire" and which don't have a sender address ending in "@foobar.com",
meaning that messages with that subject line OR that sender address will NEVER be marked as spam, no
matter what:
:0 wf
* ! ^Subject: Your .* is on fire
* ! ^From: .*@foobar.com
| qsf -ra
For more on procmail(1) recipes, see the procmailrc(5) and procmailex(5) manual pages.
A couple of macros to add to your .muttrc file, if you use mutt(1) as a mail user agent:
# Press F5 to mark a message as spam and delete it
macro index <f5> "<pipe-message>qsf -am\n<delete-message>"
macro pager <f5> "<pipe-message>qsf -am\n<delete-message>"
# Press F9 to mark a message as non-spam
macro index <f9> "<pipe-message>qsf -aM\n"
macro pager <f9> "<pipe-message>qsf -aM\n"
Again, remove the -a option in the above examples if you don't want to use the allow-list.
Note, however, that the above macros won't work when operating on multiple tagged messages. For that,
you'd need something like this:
macro index <f5> ":set pipe_split\n<tag-prefix><pipe-message>qsf -am\n<tag-prefix><delete-
message>\n:unset pipe_split\n"
If you use qmail(7), then to get procmail working with it you will need to put a line containing just
DEFAULT=./Maildir/ at the top of your ~/.procmailrc file, so that procmail delivers to your Maildir
folder instead of trying to deliver to /var/spool/mail/$USER, and you will need to put this in your
~/.qmail file:
| preline procmail
This will cause all your mail to be delivered via procmail instead of being delivered directly into your
mail directory.
See the qmail(7) documentation for more about mail delivery with qmail.
If you use postfix(1), you can set up a system-wide mail filter by creating a user account for the
purpose of filtering mail, populating that account's .qsfdb, and then creating a shell script, to run as
that user, which runs qsf on stdin and passes stdout to sendmail(8).
Doing this requires some knowledge of postfix configuration and care needs to be taken to avoid mail
loops. One qsf user's full HOWTO is included in the doc/ directory with this package.
THE ALLOW-LIST
A feature called the "allow-list" can be switched on by specifying the --allowlist or -a option. This
causes messages' "From:" and "Return-Path:" addresses to be checked against a list of people you have
said to allow all messages from, and if a message's "From:" or "Return-Path:" address is in the list, it
is never marked as spam. This means you can add all your friends to an "allow-list" and qsf will then
never mis-file their messages - a quick way to do this is to use -a with -T (train); everyone in your
non-spam folder who has sent you an email will be added to the allow-list automatically during training.
You can manually add and remove addresses to and from the allow-list using the -e (email) option. For
instance, to add foo@bar.com to the allow-list, do this:
qsf -e foo@bar.com -M
To remove bad@nasty.com from the allow-list, do this:
qsf -e bad@nasty.com -m
And to see whether someone@somewhere.com is in the allow-list or not, just do this:
qsf -e someone@somewhere.com
In general, you probably always want to enable the allow-list, so always specify the -a option when using
qsf. This will automatically maintain the allow-list based on what you classify as spam or non-spam.
The only times you might want to turn it off are when people on your allow-list are prone to getting
viruses or if a virus is causing email to be sent to you that is pretending to be from someone on your
allow-list.
BACKUP AND RESTORE
Because the database format is platform-specific, it is a good idea to periodically dump the database to
a text file using qsf -D so that, if necessary, it can be transferred to another machine and restored
with qsf -R later on.
Also note that since the actual contents of email messages are never stored in the database (see
TECHNICAL DETAILS), you can safely share your qsf database with friends - simply dump your database to a
file, like this:
qsf -D > your-database-dump.txt
Once you have sent your-database-dump.txt to another person, they can do this:
qsf -R < your-database-dump.txt
They will then have an identical database to yours.
TECHNICAL DETAILS
When a message is passed to qsf, any attachments are decoded, all HTML elements are removed, and the
message text is then broken up into "tokens", where a "token" is a single word or URL. Each token is
hashed using the MD5 algorithm (see below for why), and that hash is then used to look up each token in
the qsf database.
For full details of which parts of an email (headers, body, attachments, etc) are used to calculate the
spam rating, see the TOKENISATION section below.
Within the database, each token has two numbers associated with it: the number of times that token has
been seen in spam, and the number of times it has been seen in non-spam. These two numbers, along with
the total number of spam and non-spam messages seen, are then used to give a "spamminess" value for that
particular token. This "spamminess" value ranges from "definitely not spammy" at one end of the scale,
through "neutral" in the middle, up to "definitely spammy" at the other end.
Once a "spamminess" value has been calculated for all of the tokens in the message, a summary calculation
is made to give an overall "is this spam?" probability rating for the message. If the overall
probability is 0.9 or above, the message is flagged as spam.
In addition to the probability test is the "allow-list". If enabled (with the -a option), the whole
probability check is skipped if the sender of the message is listed in the allow-list, and the message is
not marked as spam.
When training the database, a message is split up into tokens as described above, and then the numbers in
the database for each token are simply added to: if you tell qsf that a message is spam, it adds one to
the "number of times seen in spam" counter for each token, and if you tell it a message is not spam, it
adds one to the "number of times seen in non-spam" counter for each token. If you specify a weight, with
-w, then the number you specify is added instead of one.
To stop the database growing uncontrollably, the database keeps track of when a token was last used.
Underused tokens are automatically removed from the database. (The old method was to "prune" every 500
updates).
Finally, the reason MD5 hashes were used is privacy. If the actual tokens from the messages, and the
actual email addresses in the allow-list, were stored, you could not share a single qsf database between
multiple users because bits of everyone's messages would be in the database - things like emailed
passwords, keywords relating to personal gossip, and so on. So a hash is stored instead. A hash is a
"one-way" function; it is easy to turn a token into a hash but very hard (some might say impossible) to
turn a hash back into the token that created it. This means that you end up with a database with no
personal information in it.
TOKENISATION
When a message is broken up into tokens, various parts of the message are treated in different ways.
First, all header fields are discarded, except for the important ones: From, Return-Path, Sender, To,
Reply-To, and Subject.
Next, any MIME-encoded attachments are decoded. Any attachments whose MIME type starts with "text/"
(i.e. HTML and text) are tokenised, after having any HTML tags stripped. Any non-textual attachments are
replaced with their MD5 hash (such that two identical attachments will have the same hash), and that hash
is then used as a token.
In addition to single-word tokens from textual message parts, qsf adds doubled-up tokens so that word
pairs get added to the database. This makes the database a bit bigger (although the automatic pruning
tends to take care of that) but makes matching more exact.
SPECIAL FILTERS
As well as using the textual content of email to detect spam, qsf also uses special filters which create
"pseudo-tokens" based on various rules. This means that specific patterns, not just individual words,
can be used to determine whether a message is spam or not.
For example, if a message contains lots of words with multiple consonants, like "ashjkbnxcsdjh", then
each time a word like that is seen the special token ".GIBBERISH-CONSONANTS." is added to the list of
tokens found in the message. If it turns out that most messages with words that trigger this filter rule
are spam, then other messages with gibberish consonant strings will be more likely to be flagged as spam.
Currently the special filters are:
GTUBE Flags any message containing the string XJS*C4JDBQADN1.NSBN3*2IDNEN*GTUBE-STANDARD-ANTI-UBE-TEST-
EMAIL*C.34X as spam - useful for testing that your qsf installation is working.
ATTACH-SCR
ATTACH-PIF
ATTACH-EXE
ATTACH-VBS
ATTACH-VBA
ATTACH-LNK
ATTACH-COM
ATTACH-BAT
Adds a token for every attachment whose filename ends in ".scr", ".pif", ".exe", ".vbs", ".vba",
".lnk", ".com", and ".bat" respectively (these are often viruses).
ATTACH-GIF
ATTACH-JPG
ATTACH-PNG
Adds a token for every attachment whose filename ends in ".gif", ".jpg" or ".jpeg", and ".png"
respectively.
ATTACH-DOC
ATTACH-XLS
ATTACH-PDF
Adds a token for every attachment whose filename ends in ".doc", ".xls", or ".pdf" respectively
(these tend to indicate a non-spam email).
SINGLE-IMAGE
Adds a token if the message contains exactly one attached image.
MULTIPLE-IMAGES
Adds a token if the message contains more than one attached image.
GIBBERISH-CONSONANTS
Adds a token for every word found that has multiple consonants in a row, as described above. Spam
often contains strings of gibberish.
GIBBERISH-VOWELS
Adds a token for every word found that has multiple vowels in a row, eg "aeaiaiaeeio".
GIBBERISH-FROMCONS
Like GIBBERISH-CONSONANTS, but only for the "From:" and "Return-Path:" addresses on their own.
GIBBERISH-FROMVOWL
Like GIBBERISH-VOWELS, but only for the "From:" and "Return-Path:" addresses on their own.
GIBBERISH-BADSTART
Adds a token for every word that starts with a bad character such as %.
GIBBERISH-HYPHENS
Adds a token for every word with more than three hyphens or underscores in it.
GIBBERISH-LONGWORDS
Adds a token for every word with over 30 characters in it (but less than 60).
HTML-COMMENTS-IN-WORDS
Adds a token for every HTML comment found in the middle of a word. Spam often contains HTML
inside words, like this: w<!--dsgfhsdgjgh-->ord
HTML-EXTERNAL-IMG
Adds a token for every HTML <img> (image) tag found that contains :// (i.e. it refers to an
external image).
HTML-FONT
Adds a token for every HTML <font> tag found.
HTML-IP-IN-URLS
Adds a token for every URL found containing an IP address.
HTML-INT-IN-URL
Adds a token for every URL found containing an integer in its hostname.
HTML-URLENCODED-URL
Adds a token for every URL found containing a % sign in its hostname.
Normally, filters will just cause a token to be added, and these tokens are processed by the normal
weighting algorithm. However the GTUBE filter will immediately flag any matching message as spam,
bypassing the token matching.
DATABASE BACKENDS
The inbuilt "list" database backend will not necessarily provide the best performance, but is provided
because using it requires no external libraries.
If, when qsf was compiled, the correct libraries were available, then it will be possible to use qsf with
alternative database backends. To find out which backends you have available, run qsf -V (capital V) and
read the second line of output. To see how well a backend performs, collect some spam and non-spam and
use qsf -d BACKEND -B SPAM NONSPAM (see the entry for -B above).
Some people find that they get the best performance out of the gdbm backend; this is a library that is
widely available on many systems.
To efficiently share a qsf database across multiple machines, you may find the MySQL backend useful.
However, using it is a little more complicated.
To use the MySQL backend you will need to create a table with the fields key1, key2, token, value1,
value2 and value3. The token, value1, value2, and value3 fields must be VARCHAR(64), BIGINT or INT, and
BIGINT or INT respectively, and indexing on the token field is a good idea. The key1 and key2 fields can
be anything, but they must be present.
For example:
USE mydatabase;
CREATE TABLE qsfdb (
key1 BIGINT UNSIGNED NOT NULL,
key2 BIGINT UNSIGNED NOT NULL,
token VARCHAR(64) DEFAULT '' NOT NULL,
value1 INT UNSIGNED NOT NULL,
value2 INT UNSIGNED NOT NULL,
value3 INT UNSIGNED NOT NULL,
PRIMARY KEY (key1,key2,token),
KEY (key1),
KEY (key2),
KEY (token)
);
The key1 and key2 fields allow you to have multiple qsf databases in one table, by specifying different
key1 and key2 values on invocation.
Instead of specifying a database file with the --database / -d option, you must specify either a
specification string as described below, or the name of a file containing such a string on its first
line.
The specification string is as follows:
database=DATABASE;host=HOST;port=PORT;
user=USER;pass=PASS;table=TABLE;
key1=KEY1;key2=KEY2
This string must be all on one line, with no spaces.
DATABASE
is the name of the MySQL database.
HOST is the hostname of the database server (eg "localhost").
PORT is the TCP port to connect on (eg 3306).
USER is the username to connect with.
PASS is the password to connect with.
TABLE is the database table to use. If a table with this name does not exist when qsf is called in
update or training mode, then it will be created if permissions allow this to be done.
KEY1 is the value to use for the key1 field.
KEY2 is the value to use for the key2 field.
Since command lines can be seen in the process list, it is probably best to specify a filename (eg qsf -d
mysql:qsfdb.spec) and put the specification string inside that file.
TROUBLESHOOTING
If you have problems with qsf, please check the list below; if this does not help, go to the qsf home
page and investigate the mailing lists, or email the author.
Nothing is being marked as spam.
First, use the -r option to switch on the X-Spam-Rating header, and check that this header appears
in email passed through qsf. If it does not, then it is likely that qsf is not being run at all -
check your configuration of procmail(1) or its equivalent.
If you are seeing X-Spam-Rating headers, and different emails have different scores, then you may
simply need to retrain your database a little more. Take more spam email and pass it to qsf -m.
If you are seeing X-Spam-Rating headers but they all give the same spam rating, then the most
likely reason is that qsf is not reading any database. Make sure that whatever is processing the
email has read permissions on /var/lib/qsfdb and/or ~/.qsfdb - and make sure that, if you are
using ~/.qsfdb, what your database creator thought was ~ ($HOME) is the same as it is for whatever
is processing the email.
Retraining sometimes takes a very long time.
With the obtree backend or 2-column MySQL or SQLite tables, every 500th retrain (-m or -M), the
database is pruned. On some systems this may take some time, and during this time the database is
locked (except when using the MySQL or SQLite backends). If you constantly do a lot of retraining
and want to avoid this, then use the -N option to suppress auto-pruning, and then have a cron(8)
job or something run a manual prune (qsf -p) every now and again.
Running qsf from procmail fails with an error.
If you can run qsf from the command line, but in your procmail log file you get errors about "qsf:
cannot execute binary file", then contact your system administrator for help. It may be that
incoming email is handled by a different server to the one you normally shell into, and either
they are of a different architecture or operating system, or the mail server is not permitted to
execute user-owned binaries.
ACKNOWLEDGEMENTS
The following people have contributed suggestions, comments, patches, and testing:
Tom Parker <http://www.bits.bris.ac.uk/palfrey/>
Dr Kelly A. Parker
Vesselin Mladenov <http://www.antipodes.bg/>
Glyn Faulkner
Mark Reynolds
Sam Roberts
Scott Allen
Karsten Kankowski
M. Kolbl
Micha Holzmann
Jef Poskanzer <http://www.acme.com/jef/>
Clemens Fischer <http://ino-waiting.gmxhome.de/>
Nelson A. de Oliveira
Michal Vitecek
Tommy Pettersson <http://www.lysator.liu.se/~ptp/>
AUTHOR
The author:
Andrew Wood <andrew.wood@ivarch.com>
http://www.ivarch.com/
Project home page:
http://www.ivarch.com/programs/qsf/
BUGS
If you find any bugs, please contact the author, either by email or by using the contact form on the web
site.
SEE ALSO
procmail(1), procmailrc(5), procmailex(5) Someone has written a guide to using qsf with KMail that can be found at: http://www.softwaredesign.co.uk/Information.SpamFilters.html
LICENSE
This is free software, distributed under the ARTISTIC 2.0 license.