Personal Survey of Anti-spam Tools

In the three or four years I’ve been fighting unwanted e-mail messages with better tools than the Delete key I’ve tried almost a dozen different tools. This is a quick survey of the ones I’ve used, and why I don’t (or do) still use them.

In the three or four years I’ve been fighting unwanted e-mail messages with better tools than the Delete key I’ve tried almost a dozen different tools. This is a quick (ha!) survey of the ones I’ve used, and why I don’t (or do) still use them.

My very first anti-spam tool was something called Mailfilter. I used it for my personal e-mail on Mac OS X, wrote about it here, and almost immediately afterwards lost a non-spam message to an aggressive keyword match. That was the end of Mailfilter. I can’t even remotely recommend it, as it’s just not intelligent enough (strict, single expression matching), and had zero safety net.

My next attempt at a solution was a utility called SpamFire. Like Mailfilter, it is a “pre-filter,” which means it would run before my e-mail client, download my mail, and skim out the spam. Unlike Mailfilter, it actually saved the trapped messages, so if it made a mistake, I could recover the message. It had plenty of other differences from Mailfilter, which I wrote about previously, and which made it so useful that it became the first anti-spam tool I paid for. But in the end I switched to a different tool because SpamFire was separate from my e-mail client, and that made it cumbersome to use.

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SpamBayes for Outlook

A while back I recommended an Outlook plug-in called SpamNet, from Cloudmark. At the time, it was a free tool for Outlook users to block spam, that worked quite reliably. Sadly, it’s no longer free. I get so little spam at work (where my e-mail address is relatively unpublished) that I can’t justify buying a subscription. Fortunately, I have found another solution at least as good.

A while back I recommended an Outlook plug-in called SpamNet, from Cloudmark. At the time, it was a free tool for Outlook users to block spam, that worked quite reliably. Sadly, it’s no longer free. I get so little spam at work (where my e-mail address is relatively unpublished) that I can’t justify buying a subscription.

I do still get some spam, though. Fortunately, Jon Udell’s recent weblog entries and review at InfoWorld turned me onto a replacement that is free, and will remain so (it’s Open Source): SpamBayes.

Like SpamNet, it can be installed as an Outlook plug-in, and easily used via buttons on Outlook’s toolbar. But the technology behind it is very different, as it uses Bayesian filtering rather than distributed recognition. It’s also different in that the core project and recognition engine is command line-oriented. The Outlook-only plug-in is terrific, but only a side project. It’s not required, and there are plenty of ways for those who use something other than Outlook for e-mail to use SpamBayes.

You can read the review for a thorough look, but my experience was that it was just as easy to install as SpamNet, is extremely effective at blocking spam, and is also having fewer false positives. I think the reason for that is SpamNet uses other people’s spam reports to decide what to block in my Inbox, and there’s a lot of people who just block e-mails they signed up for (newsletters, promos, etc.), rather than unsubscribe from them. Those false reports pollute the knowledge base, and affect my results. Bayesian filtering is exactly the opposite — it only cares what I think is spam.

Latent Semantic Analysis Is Not Bayesian Filtering

Macworld recently ran an article about anti-spam tools for Mac OS X, which incorrectly simplified the world of anti-spam tools down to Boolean, points-based, and Bayesian filters. There are at least two more categories of anti-spam tools.

Macworld recently ran an article about anti-spam tools for Mac OS X, which incorrectly simplified the world of anti-spam tools down to Boolean, points-based, and Bayesian filters.

Two additional categories are distributed recognition, such as the Distributed Checksum Clearinghouse (DCC) and Vipul’s Razor, and latent semantic analysis. I don’t know of any distributed recognition products for the Mac (there’s a very good one for Windows Outlook, SpamNet by Cloudmark), but there certainly is a latent semantic analysis tool — Apple’s Mail in Jaguar!

The simplification (or oversight) is relatively understandable. From an end-user perspective, there’s no meaningful difference — even though the math is very different. It’s not clear which will prove better at filtering out spam, even though in the article Mail’s filtering did the best. Seems like it’s good to have both in the fight!

While I’m posting about it, I should note that the article was written prior to the release of my new favorite anti-spam tool, Spamnix, and so it doesn’t include it in the roundup. From my own experience with Mac OS anti-spam tools I think that, with the caveat that it only works with Eudora, it would have done well in the evaluation. Perhaps Geoff Duncan, or someone else at TidBITS, will review it soon, and confirm that guess. I know they like Eudora at TidBITS — they literally wrote the book!