People usually associate spams with unsolicited commercial emails that try to either sell you the “little blue pill”, or Nigerians phishing for your bank account details. There are many techniques fighting email spams, either at the server side or at your email client. However if you run a blog or a forum on the Internet, you would also have experienced fighting comment spams (unless, of course, that you run a spam blog yourself :). I have been blogging since 2001 and have employed various techniques to keep the spams at bay. Some of them worked well — at the beginning — but sooner or later spammers got smartened up and they can almost slip in a few spammy comments.

When I launched this blog 2 years ago, it was running Akismet for Drupal, and recently changed to Mollom, one of Dries’ startup company/project. It has been effective (except for the last few days). Mollom is sort-of similar to Akismet that it (1) uses a classifier to determine the likeliness of incoming comment being a spam (2) acts as a centralised database to collaboratively identify spams. Mollom does a few extra things when the comment is in a “not-so-sure” state, but discussing this would be beyond the scope of this blog post.

My typical set up — 2 email servers for all of my domains. One primary with local delivery, and another one as a backup MX. Then for all my other servers, MTA is installed but either bound only to localhost, or external access to port 25 firewalled. Emails will be sent out from these servers but they shall never receive any from emails, i.e. they are all null mailer. Just in case I mis-configured the MTA and opened them up for relaying, I firewalled all SMTP access.

Well, it has actually caused more problems than I have originally envisioned.

If you have an email address for a while, you’ll know that “spams” are almost inevitable. Once the email address has been used, spams will find their way there sooner or later. Combating email spams has also become one of the most researched topics these days.

Greylisting is a relatively new method to use against spams, and its principle is very different from traditional content filtering/content classifying strategy. The differences make it very effective in stopping spams currently, utilising relatively little CPU time and has small memory footage. It by no means is a replacement for fiter/classifier based spam protections, but can be easily deployed as first level of defense to reduce the CPU/memory demand of your spam filters.

This article was written after successfully implementing greylisting on Postfix using Gld, on a memory-restrained VPS running Gentoo Linux. Hopefully it will be useful to those who are thinking of implementing a similar solution.