Controlling Spam with SpamAssassin

How to set up SpamAssassin and teach it to recognize spam.

The people who produce unsolicited commercial e-mail
(UCE), or spam, are the big thieves of the information
age, spewing out messages for pharmaceuticals, time
pieces, fast money and fast women. Large chunks of
bandwidth that we have to pay for is eaten up by these
crooks. After getting these messages, we have to waste
time going through our inboxes and deleting the garbage. Further,
unlike magazines, newspapers, commercial radio and
television, where the advertisements reduce the cost or
make the content free, spam gives nothing back to us
as readers or viewers.

Although we can not stop spam, some tools exist to make
spam easier to deal with. One such tool is
SpamAssassin, which looks at each incoming e-mail message and
rates the probability that the e-mail is spam. Messages
that are given a high probability of being spam get
flagged as such, and other programs, such as Evolution,
KMail or Procmail, can deal painlessly with the flagged

SpamAssassin works by going through e-mails and looking
for things that are associated with spam or non-spam
e-mail, which add or subtract points from an
e-mail's score. So, for example, the word Viagra, and
close misspellings of Viagra (as they are used
in many pharmaceutical spam messages), adds to the
total score. On the other hand, a valid Sender Policy
Framework (SPF) record in the e-mail, which shows that
the sender location was not forged, subtracts from
the score. By default, any message that gets a total
score of five or more is assumed to be spam.

One problem with the above calculations is that it
is a fair bit of work for your computer, so if your
machine is currently straining under the workload it
has, or if you deal with a lot of e-mail, you may want
to look at a hardware upgrade (faster CPU chip and/or
more memory) before starting up SpamAssassin.

A number of Linux distributions include SpamAssassin
by default. If yours isn't one of them, it should
be very simple to add. If you have a Debian-based
distribution, it should be as simple as starting up a
terminal window and typing:

sudo apt-get install spamassassin

Once installed, you can start tweaking SpamAssassin's
settings. SpamAssassin's configuration file can be
found at ~/.spamassassin/user_prefs. The first setting is

required_score          5

SpamAssassin is not perfect, no matter how you set
things. There will be some spam e-mail allowed
through, and some valid e-mail will be classed as spam. The
goal with the configuration process is to make sure
this happens as seldom as possible. The score of five is
an excellent compromise for most people. But, if you
find yourself getting a lot of spam coming through as
non-spam, even after taking the configuration steps
noted below, you may want to lower that number to
a four or three (or possibly even lower). If, on the other
hand, you find after configuration you have a lot of
real e-mail identified as spam, you might want to raise
the required_score.

There are some people that you always want to hear
from, or at least, always want their e-mail to come
through, such as coworkers and family members. There also are
people that you never want to hear from again, such as
annoying exes. SpamAssassin deals with these
situations by having a whitelist and blacklist. An
e-mail from someone on the whitelist gets 100
subtracted from the score; anyone on the blacklist
gets 100 added to the score. To add someone to your
white/blacklist, you need to add something like the
following to user_prefs:

whitelist_from       niceperson@somedomain.somewhere
blacklist_from       nastyperson@somedomain.somewhere

Some people have specific reasons why they would want
particular spam tests changed. For example, people
working at a jewelry store, or watch collectors, might
want to allow messages where the word Rolex has been
emphasized, accepting that doing so also will increase the
amount of replica-watch-related spam they will see.
There is a list of SpamAssassin tests at For example, to change
the score that an e-mail message gets when the word
Rolex has been emphasized, reducing the chances that
such a message would be tagged as spam, put
the following line in user_prefs:

score EM_ROLEX 0

If too many legitimate Rolex-brand watch-related
e-mail messages are still being tagged as spam, the above
could be changed to a negative number.

By default, SpamAssassin assumes e-mail in a number of
Asian languages, most notably, but not exclusively
Chinese, Japanese and Korean are probably spam. This
is a problem if you use one of those languages. To allow Asian languages, you need to
uncomment some lines by removing the # character at the start
of the last four lines of user_prefs.

Now, let's further refine SpamAssassin's taste. My
first run-through with SpamAssassin was a
disappointment. Out of some 2,200 spam messages, only
about 10% were correctly identified as spam.
Fortunately, with SpamAssassin there is a utility
program called sa-learn that will “teach” SpamAssassin what
you consider to be spam and ham (non-spam). This
process greatly improves SpamAssassin's ability to
identify spam messages correctly. The trick here is to
create folders, one filled with spam and another filled
with the sort of material you want to keep, and then feed
each folder into sa-learn. Using the Evolution e-mail
program, I created a folder called BULK, and then I
manually placed all the spam messages into that
folder. Next, I ran the sa-learn program with the
following command:

sa-learn --mbox --spam ~/.evolution/mail/local/BULK

Evolution stores all its e-mail in the mbox mail
format, thus the --mbox option in the command above. The
command for the non-spam messages, which I keep in the Inbox folder, is:

sa-learn --mbox --ham ~/.evolution/mail/local/Inbox

The learning system SpamAssassin uses starts to become
good at around 1,000 spam and 1,000 ham messages. With
a semi-exception, the system doesn't improve noticeably
until after seeing more than 5,000 e-mail messages. The
semi-exception relates to the fact that spam is a
moving target. Some spammers are always looking for
better ways to get around filter programs, changing
their spam as they go. What this means is that you
need to re-train SpamAssassin periodically with new
spam and new ham. How often depends on your
situation, but basically you need to re-train whenever you see a noticeable
increase in the amount of spam getting past
SpamAssassin. Still, with training, it is very possible
to reach spam-detection accuracy rates of more than 99%.

Remember that SpamAssassin remembers what e-mail it
has seen before, so although some people may be tempted to
run the same 1,000 e-mail messages through sa-learn five times, all
this will do is waste time.

Let's see how SpamAssassin, actually rates a sample
e-mail. For a test, I created a simple text file,
testmail.txt with the following:

From: MyUserID@SomeDomain.Somewhere
To: aliceithink@somedomain.somewhare
Date: Sat, 2 Dec 2006 13:34:50 -0400 (EDT)
Subject: Back from vacation

Alice, I am back from vacation, anything important
happen when I was away?

Colin McGregor

Then, I ran SpamAssassin as a test with the following

spamassassin -t testmail.txt

I received an output like the following:

From: MyUserID@SomeDomain.Somewhere
To: aliceithink@somedomain.somewhare
Subject: Back from vacation
X-Spam-Checker-Version: SpamAssassin 3.0.3
(2005-04-27) on diamond
X-Spam-Status: No, score=-5.9 required=5.0
        NO_REAL_NAME autolearn=ham version=3.0.3

Alice, I am back from vacation, anything important
happen when I was away?

Colin McGregor
Spam detection software, running on the system
"diamond", has
identified this incoming email as possible spam.  The
original message
isn't spam) or label
similar future email.  If you have any questions, see
the administrator of that system for details.

Content preview:  Alice, I am back from vacation,
anything important
  happen when I was away? Colin McGregor [...]

Content analysis details:   (-5.9 points, 5.0

 pts rule name        description
 0.0 NO_REAL_NAME     From: does not include a real name
-3.3 ALL_TRUSTED      Did not pass through any untrusted hosts
-2.6 BAYES_00         BODY: Bayesian spam probability is 0 to 1%
                      [score: 0.0000]

With a score of -5.9, SpamAssassin
would not consider the above to be actual spam. By
editing testmail.txt and repeating the above, you
can see how SpamAssassin reacts to various sorts
of keywords—in particular, terms commonly found in
spam such as luxury brand-name watches, pharmaceutical
products, financial service terms and/or various
pornographic terms.

It isn't clear yet what the magic bullet will be to
stop spam and regain the bandwidth spam steals
from all of us—better technology, new laws or better
enforcement of laws currently in place. Likely an end
to spam will require a mixture of actions. In the
meantime, SpamAssassin does make dealing with spam a
less painful, but not pain-free experience.

Evolution and SpamAssassin

The Evolution e-mail display program has a good
filtering system for sorting out incoming e-mail, but
it is a bit weak when it comes to identifying spam.
Fortunately, Evolution allows us to use external
programs to help with sorting. From the main screen
click on Tools→Filters. Then, click on +Add to
create a new rule. You need a name for this rule, and
spam should be just fine. Next, we want to send a
copy of each e-mail to SpamAssassin and find out
if SpamAssassin views the e-mail as spam; we do not
care about the score SpamAssassin gives the e-mail,
just a “yes” or “no”. So, we Pipe to Program and then
throw everything except the result code away. We do
this with the instruction:

/usr/bin/spamassassin -e | /dev/null

If the above command returns a value of 0, it
isn't spam. Anything more than 0 means we very likely
have a spam and want it dropped into a separate
folder. In the example shown in Figure 1, I am sending
the e-mail into a folder labeled BULK. After doing the
above steps, we want the filter program to stop and
wait for the next incoming e-mail.

Figure 1. Creating and Editing Rules in Evolution

As noted previously running sa-learn over the
same e-mail twice is a waste of time. This raises
another point when using Evolution and SpamAssassin,
when you delete an e-mail message under Evolution, the
program does not delete the e-mail from the
~/.evolution/mail/<file name> e-mail file, it just
flags it for future removal. This way, if you make an
error deleting an e-mail, you can get it back. To
get rid of deleted e-mails completely under Evolution, you
must click on Actions→Expunge. During your first days with
SpamAssassin, when
you might be running sa-learn several times over your
BULK folder and your Incoming folder, you may not only want to
delete e-mail previously seen by sa-learn, but
also to Expunge it.

Colin McGregor works for a Toronto-area charity, does
consulting on the side and has served as President of
the Toronto Free-Net. He also is secretary for and
occasional guest speaker at the Greater Toronto Area
Linux User Group meetings.


Comment viewing options


Evolution and Spamassassin

pritchey's picture

I'm running Gentoo with Evolution installed. I've tried using spamassassin with it many times, but it never works.

Now with the version, the dialog box for creating the rule where you setup to pipe the message to spamassassin is not the same. Instead of being provided a text box where you can type in the command you want run (like pictured in the article), it opens a dialog box and only lets you drill down to and select spamassassin binary.

Any hints? I've already tried creating a wrapper script and using that instead, but it's still not detecting spam.