On Wed, Aug 04, 2010 at 06:58:52AM -0700, Happy Chap wrote: > > > > Henrik K wrote: > > > > > > Instead of speculating, try: > > > > cat msg | spamassassin -t -D bayes 2>&1 | grep bayes: > > > > It will tell you exactly what tokens are considered. > > > > > > Hi Henrik, > > Thanks for your reply. > > I'm not sure I totally understand all of the output to that, but I think > that's telling me that it isn't taking the text in the comments into account > - I can see various strings that it's picking up from the email, but the > commented text isn't obviously there. Maybe that's what you were trying to > tell me anyway :-) > > In that case (and I've been barking up the wrong tree) do you have any > suggestion as to what my next move should be to try to trap this type of > spam? I'm moderately technical, but I think I've probably reached the limit > of my current knowledge but am happy to learn if you could just point me in > the right direction.
Do the tokens look such that they might be used in legimate messages? Usually you just have to sa-learn --spam enough of such spams to get atleast BAYES_50. I have no idea what kind of spams they are, but it all depends on whether they have any tokens in common. But I can tell you that it's very rare to get BAYES_00 for spam if you just learn them properly.
