Interestingly, 2.60(cvs dated 6/30) and Bayes did a pretty good job on this
(I'm using the default cut off of 5, but the result is well over that).
Content analysis details: (11.5 points, 5.0 required)
0.3 NO_REAL_NAME From: does not include a real name
1.6 SUBJ_HAS_SPACES Subject contains lots of white space
0.6 LARGE_HEX BODY: Contains a large block of hexadecimal code
5.2 BAYES_99 BODY: Bayesian spam probability is 99 to 100%
[score: 0.9957]
1.4 SUBJ_HAS_UNIQ_ID Subject contains a unique ID
4.3 FORGED_MUA_THEBAT Mail pretending to be from The Bat! (mid)
0.7 UPPERCASE_25_50 message body is 25-50% uppercase
-2.6 AWL AWL: Auto-whitelist adjustment
---------
The low AWL score is understandable because the address looks like it came
from
the local administrator. <g>
The BAYES_99 score is the result of auto-learning about 500 non-related
messages.
It looks like FORGED_MUA_THEBAT is a big winner on this one.
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