Graham Murray wrote:
> I have noticed that 'stock' spams hardly ever trigger the razor checks
> in SpamAssassin. Razor seems effective at catching a large proportion of
> every type of spam, it is just the 'stock' ones it never catches. I
> report nearly all of the stock spam I receive.

If you study the stock spams, it shouldn't be too surprising that it misses 
some 
of these runs.

Razor has 2 engines. e4, and e8.

e8 is based on URLs, and stock spams generally don't have URLs, so it won't 
match at all.

e4 is based on hashing part of the body text, and that detects duplicate or 
nearly-duplicate messages.

However, some of the current stock spams are comprised of unique messages. In 
these runs no two emails are exactly the same, and every person gets one that's 
slightly different. This is done using the CPU power of the botnets that 
distribute them to obfuscate the message each time it is sent, and it's done 
differently each time the message is sent.

Of course, I've also seen plenty of other stock spams lately that aren't doing 
uniqueness, or are using a very limited set of changes, and razor works fine on 
these. In Particular today's run trying to get you to invest in a yacht maker 
has been hitting e4 a lot. (Most of the ones for this same stock on 10/1 were 
unique, but today I've been getting a bunch of identical ones that razor is 
tearing up)

Of course, none of this is to say that razor is useless. There's lots of spam 
detection techniques out there, and all of them have a weakness somewhere. Your 
best bet is to use multiple tools that compliment each other to fill in the 
gaps.

Razor is particularly useful against spams advertising a website, spams using 
images that don't change, or low-budget mass-runs of identical messages. It 
also 
keeps pressure on spammers to keep changing their content, which slows them 
down 
a little bit.

In general I find the best tools against the "unique message" spam runs that 
don't contain any URLs are RBLs particularly SpamHaus XBL (or CBL). I also find 
that if properly trained, bayes systems work pretty well on them too. Although 
they mutate a lot, they use a lot of the same mutations so over time they all 
look the same to a bayes system.


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