Robert Menschel wrote: > MK> However, these attempts are only going to be effective against the bayes > portion > MK> of SA. > > As I've said before, my opinion is that these attempts are NOT > effective against SpamAssassin's Bayes system. > > As a rule, we do NOT receive hams which contain such extracted text. > No matter where the spammers extract their text from, they're going to > extract words that are not found in ham, and Bayes is going to learn > that the presence of such words means S P A M.
I agree, mostly, however I have found that SOME emails with extracted text collide with our ham profile. Not all, not even many, but some do collide. Really this is entirely a function of how well the spammer can match your ham profile with his extraction. If he can match it accurately, this technique will be very effective against your bayes. If they can't match your ham profile, it won't work at all. Just today I got one email with this hit list: score=17.817, required 5, autolearn=spam, AB_URI_RBL 1.00, BAYES_10 -0.91, BLACK_URI_RBL 2.00, DRUGS_ERECTILE 1.00, INFO_GREYLIST_NOTDELAYED -0.00, RAZOR2_CF_RANGE_51_100 0.20, RAZOR2_CHECK 1.05, RCVD_IN_BL_SPAMCOP_NET 1.50, RCVD_IN_XBL 4.92, SPAMCOP_URI_RBL 3.00, VIAGRA_ONLINE 4.06 It got the BAYES_10 because the extracted text closely matches the general language style of my end users. The spam content was 1 line and a url. The extracted text was 4 lines.
