QSF(1) User Manuals QSF(1)
qsf - quick spam filter
Filtering: qsf [-snrAtav] [-d DB] [-g DB]
[-L LVL] [-S SUBJ] [-H MARK] [-Q 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]
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 addi-
tional 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
| qsf -ra
* X-Spam: YES
For more examples, including sample procmail(1) recipes, see the EXAM-
PLES section below.
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
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 accord-
ingly 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
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.
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,
$HOME/.qsfdb. This option can also be useful if there is a sys-
tem-wide database but you do not want to use it - specifying
your own here will override the default.
If you prefix the filename with a TYPE, of the form
btree:$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 con-
junction 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
-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.
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).
Do not add an X-Spam header to messages.
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.
Insert an additional header X-Spam-Level which will contain
between 0 and 20 asterisks (*), depending on the spam rating.
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.
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.
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 auto-
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 mes-
sage - 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
-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
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
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.
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
-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. Use-
ful when correcting mistakes, eg a message that has been mistak-
enly detected as spam should be marked as non-spam using a
weighting of 2, i.e. double the usual weighting, to counteract
-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
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 pack-
-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
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 after-
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.
Print a usage message on standard output and exit successfully.
Print version information, including a list of available
database backends, on standard output and exit successfully.
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.
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 auto-
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.
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
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.
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.
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
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-
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
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.
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
| qsf -ra
If you want qsf to add "[SPAM]" to the subject line of any messages it
thinks are spam, do this instead:
| qsf -sra
To automatically mark any email sent to firstname.lastname@example.org as spam
(this is the "naive" version):
| qsf -am
To do the same, but cleverly, so that only email to spambox@yourdo-
main.com which qsf does NOT already classify as spam gets marked as
spam in the database (this stops the database getting too heavily
# If sent to email@example.com:
| 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!
* ^X-Spam: NO
| qsf -am
Remove the -a option in the above examples if you don't want to use the
A more complicated filtering example - this will only run qsf on mes-
sages 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:
* ! ^Subject: Your .* is on fire
* ! ^From: .*@foobar.com
| qsf -ra
For more on procmail(1) recipes, see the procmailrc(5) and proc-
mailex(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 mul-
tiple tagged messages. For that, you'd need something like this:
macro index <f5> ":set pipe_split\n<tag-prefix><pipe-mes-
sage>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 cre-
ating 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.
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 firstname.lastname@example.org to the
allow-list, do this:
qsf -e email@example.com -M
To remove firstname.lastname@example.org from the allow-list, do this:
qsf -e email@example.com -m
And to see whether firstname.lastname@example.org is in the allow-list or not,
just do this:
qsf -e email@example.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-
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,
qsf -D > your-database-dump.txt
Once you have sent your-database-dump.txt to another person, they can
qsf -R < your-database-dump.txt
They will then have an identical database to yours.
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, attach-
ments, etc) are used to calculate the spam rating, see the TOKENISATION
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
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
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 infor-
mation in it.
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.
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 conso-
nants, 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
EMAIL*C.34X as spam - useful for testing that your qsf installa-
tion is working.
Adds a token for every attachment whose filename ends in ".scr",
".pif", ".exe", ".vbs", ".vba", ".lnk", ".com", and ".bat"
respectively (these are often viruses).
Adds a token for every attachment whose filename ends in ".gif",
".jpg" or ".jpeg", and ".png" respectively.
Adds a token for every attachment whose filename ends in ".doc",
".xls", or ".pdf" respectively (these tend to indicate a non-
Adds a token if the message contains exactly one attached image.
Adds a token if the message contains more than one attached
Adds a token for every word found that has multiple consonants
in a row, as described above. Spam often contains strings of
Adds a token for every word found that has multiple vowels in a
row, eg "aeaiaiaeeio".
Like GIBBERISH-CONSONANTS, but only for the "From:" and "Return-
Path:" addresses on their own.
Like GIBBERISH-VOWELS, but only for the "From:" and "Return-
Path:" addresses on their own.
Adds a token for every word that starts with a bad character
such as %.
Adds a token for every word with more than three hyphens or
underscores in it.
Adds a token for every word with over 30 characters in it (but
less than 60).
Adds a token for every HTML comment found in the middle of a
word. Spam often contains HTML inside words, like this:
Adds a token for every HTML <img> (image) tag found that con-
tains :// (i.e. it refers to an external image).
Adds a token for every HTML <font> tag found.
Adds a token for every URL found containing an IP address.
Adds a token for every URL found containing an integer in its
Adds a token for every URL found containing a % sign in its
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.
The inbuilt "list" database backend will not necessarily provide the
best performance, but is provided because using it requires no external
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 com-
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
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),
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:
This string must be all on one line, with no spaces.
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.
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
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 back-
ends). 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 archi-
tecture or operating system, or the mail server is not permitted
to execute user-owned binaries.
The following people have contributed suggestions, comments, patches,
Tom Parker <http://www.bits.bris.ac.uk/palfrey/>
Dr Kelly A. Parker
Vesselin Mladenov <http://www.antipodes.bg/>
Jef Poskanzer <http://www.acme.com/jef/>
Clemens Fischer <http://ino-waiting.gmxhome.de/>
Nelson A. de Oliveira
Tommy Pettersson <http://www.lysator.liu.se/~ptp/>
Andrew Wood <firstname.lastname@example.org>
Project home page:
If you find any bugs, please contact the author, either by email or by
using the contact form on the web site.
procmail(1), procmailrc(5), procmailex(5)
Someone has written a guide to using qsf with KMail that can be found
This is free software, distributed under the ARTISTIC 2.0 license.
Linux August 2007 QSF(1)