This is a question I get quite often and it’s a tough one to answer. I don’t really bother with running my own mail system any more, as I’m tired of the headache and happy to leave the server-level spam prevention to somebody else.
And I'm tired of taking other peoples' word for it that a certain blacklist works well or doesn't work well -- I've been burned a number of times by people listing stuff on a blacklist outside of a list's defined charter. It's very frustrating. And lots of people publish stats on how much mail they block with a given list, which is an incomplete measure of whether or not a list is any good. Think about it. If you block all mail, you're going to block all spam. But you're going to block all the rest of your inbound mail, too. And when you block mail with a DNSBL, you don't always have an easy way to tell if that mail was actually wanted or not.
So, I decided to tackle it a bit differently than other folks have. See, I have my own very large spamtrap, and the ability to compare lots of data on the fly.
For this project, I've created two feeds. One is a spam feed, composed of mail received by my many spamtrap addresses, with lots of questionable mail and obvious non-spam weeded out. I then created a non-spam feed. In this “hamtrap” I am directed solicited mail that I signed up for from over 400 senders, big and small. Now, I just have to sit back, watch the mail roll in, and watch the data roll up.
For the past week or so, I’ve been checking every piece of mail received at either the spamtrap or hamtrap against a bunch of different blacklists. I wrote software to ensure that the message is checked within a few minutes of receipt, a necessary step to gather accurate blacklist “hit” data.
After that first week, here’s what I’ve found. It might be obvious to you, or it might not: Spamhaus is a very accurate blacklist, and some others...aren't. Spamhaus’s “ZEN” blacklist correctly tagged about two-thirds of my spam, and tagged no desired mail incorrectly. Fairly impressive, especially when compared to some other blacklists. SORBS correctly tagged 55% of my spam mail, but got it wrong on the non-spam side of things ten percent of the time. If you think throwing away ten percent of the mail you want is troublesome, how about rejecting a third of desired mail? That’s what happens if you use the Fiveten blacklist. It correctly would block 58% of my spam during the test period, but with a false positive rate of 34%, that would make it unacceptable blacklist to use in any corporate environment where you actually want to receive mail your users asked to receive.
One fairly surprising revelation is that Spamcop’s blacklist is nowhere as bad as I had previously believed it to be. I’ve complained periodically here about how Spamcop’s math is often wrong, how it too often lists confirmed opt-in senders, how it is too aggressive against wanted mail, but...my data (so far) shows a complete lack of false positives. This is a nice change, and it makes me very happy to see. Assuming this trend keeps up, I think you'll see me rewriting and putting disclaimers in front of some of my previous rants on that topic.
Want to see for yourself? I'm posting summary data daily, automatically, over on stats.dnsbl.com.