Thanks so much for you help.
I took a combination of rules approach as well - let's hope this stops them
coming through.
-Jamie
Lawrence @ Rogers wrote:
>
> I use the following rule that, combined with other meta rules, catches
> the majority of these
>
> header LW_SUBJECT_SPAMMY Subject =~ /^[0-9a-zA-Z,.+_\-'!\\\/]{31,}$/
> describe LW_SUBJECT_SPAMMY Subject appears spammy (31 or more characters
> without spaces. Only numbers, letters, and formatting)
> score LW_SUBJECT_SPAMMY 0.2
>
> The key is to score the actual subject rule low, but bump the SA score
> with meta rules that increase the score as more indicators are hit. I've
> had moderate success with the rules below:
>
> # Rule 2: Message is HTML and has a tracking ID, or comes from a free
> mail address
> # Therefore, must hit HTML_MESSAGE, and either TRACKER_ID or FREEMAIL_FROM
> meta LW_SPAMMY_EMAIL1 (LW_SUBJECT_SPAMMY && HTML_MESSAGE && (TRACKER_ID
> || FREEMAIL_FROM))
> describe LW_SPAMMY_EMAIL1 Spammy HTML message that has a tracking ID or
> is freemail
> score LW_SPAMMY_EMAIL1 1.0
> #tflags LW_SPAMMY_EMAIL1 noautolearn
>
> # Rule 3: Message hits LW_SPAMMY_EMAIL1 and MIME_QP_LONG_LINE
> # It's unusual for non-spam HTML messages to have really long Quoted
> Printable lines
> meta LW_SPAMMY_EMAIL2 (LW_SPAMMY_EMAIL1 && (MIME_QP_LONG_LINE ||
> __LW_NET_TESTS))
> describe LW_SPAMMY_EMAIL2 Spammy HTML message also has a Quoted
> Printable line > 76 chars, or hits net check
> score LW_SPAMMY_EMAIL2 1.0
> #tflags LW_SPAMMY_EMAIL2 noautolearn
>
> Hope this helps!
>
> Regards,
> Lawrence
>
> On 15/03/2011 1:53 AM, jambroo wrote:
>> Is there a way of filtering emails with very large one-word subjects.
>> They
>> are also in all caps.
>>
>> I can see rules that set emails to spam if they contain specific wording
>> but
>> nothing like this.
>>
>> Thanks.
>
>
>
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