Greetings dspam-ers. This has probably been asked before, but I couldn't find the discussion if so.
I know that dspam is all about the baysian filtering of tokens, but is there any way to implement the equivalent of blanket "droplist" rules in addition, at the dspam level of processing? That is, I trust the baysian analysis to learn tokens over time, but I want to *always* treat as spam (as an example) _any_ email with the string "viagra" in the from and/or subject line. I can do this easily client-side, but I'd love to have a way to filter these out at the dspam level. I'm currently getting a few flavors of spam that consistently get through dspam's filtering, even after training, and yet strangely a subset of them always have this string in the "name" portion of the from address. This makes them easy to spot in the client. Does dspam provide any mechanism besides post-hoc training where I can define a simple list of tokens that, upon recognition in parsing, automatically classifies the email as spam, trains and quarantines appropriately, and be done with it? Thanks, Jesse
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