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Posted to users@spamassassin.apache.org by Turbo Fredriksson <tu...@debian.org> on 2006/10/18 23:18:18 UTC
[lessons come] Bug#63460: defining gender context.
These kind of spam have been getting through for quite some time
now, but now they're really starting to bug me!
I'm running SpamAssassin (spamd+spamc) version 3.1.3.
This is the mail that is in my mailbox, so it's already
processed. Running it again with spamc (still) gives me
0.3 points (same as in the mail):
----- s n i p -----
Content analysis details: (0.3 points, 5.0 required)
pts rule name description
---- ---------------------- --------------------------------------------------
1.1 EXTRA_MPART_TYPE Header has extraneous Content-type:...type= entry
0.0 UNPARSEABLE_RELAY Informational: message has unparseable relay lines
1.8 HTML_IMAGE_ONLY_24 BODY: HTML: images with 2000-2400 bytes of words
0.0 HTML_MESSAGE BODY: HTML included in message
-2.6 BAYES_00 BODY: Bayesian spam probability is 0 to 1%
[score: 0.0000]
----- s n i p -----
First obvious question is WHY this isn't catched and the
second is WHAT I can do about it... Any idea(s)?
Re: [lessons come] Bug#63460: defining gender context.
Posted by Andy Jezierski <aj...@stepan.com>.
Jeroen Tebbens <je...@tebbens.net> wrote on 10/18/2006 04:27:54 PM:
> Theo Van Dinter wrote:
> > On Wed, Oct 18, 2006 at 11:18:18PM +0200, Turbo Fredriksson wrote:
> >
> >> These kind of spam have been getting through for quite some time
> >> now, but now they're really starting to bug me!
> >>
> >
> >
> >> -2.6 BAYES_00 BODY: Bayesian spam probability is 0 to
1%
> >> [score: 0.0000]
> >>
> >
> > Learn the mail as spam, -2.6 isn't helping.
> > Second, you don't have the rules from sa-update so do that. :)
> >
> > That message scores a 7.9 for me w/ no BAYES rules, FWIW.
> >
> >
>
> With imageinfo and FuzzyOcr (using 2.3rc1 atm) you can get it to 33
even. :)
>
> Content analysis details: (33.0 points, 7.0 required)
>
> pts rule name description
> ---- ----------------------
> --------------------------------------------------
> 0.8 MY_DSL I could use a BL for this.
> 1.1 EXTRA_MPART_TYPE Header has extraneous Content-type:...type=
> entry
> 0.0 UNPARSEABLE_RELAY Informational: message has unparseable relay
> lines
> 2.8 TVD_FW_GRAPHIC_ID1 BODY: TVD_FW_GRAPHIC_ID1
> 1.8 HTML_IMAGE_ONLY_24 BODY: HTML: images with 2000-2400 bytes of
words
> 1.0 HTML_MESSAGE BODY: HTML included in message
> 0.0 BAYES_50 BODY: Bayesian spam probability is 40 to 60%
> [score: 0.5000]
> 1.0 INLINE_IMAGE RAW: Inline Images
> 2.5 SARE_GIF_ATTACH FULL: Email has a inline gif
> 0.5 VOWEL_FROM_5 Impronouncable from header (6 consecutive
> vowels)
> 0.9 FM_NO_STYLE FM_NO_STYLE
> 2.5 SARE_GIF_STOX Inline Gif with little HTML
> 18 FUZZY_OCR BODY: Mail contains an image with common
> spam text inside
> Words found:
> "alert" in 1 lines
> "news" in 2 lines
> "alert" in 1 lines
> "stock" in 2 lines
> "investor" in 1 lines
> "company" in 1 lines
> "price" in 1 lines
> "trade" in 1 lines
> "banking" in 1 lines
> "litl" in 2 lines
> "meridia" in 1 lines
> "penis" in 1 lines
> "kunde" in 1 lines
> (16 word occurrences found)
>
Hmmm.... I think I may need to update my FuzzyOCR. I didn't get any
fuzzyocr hits at all, but still managed an 8.6
Andy
Re: [lessons come] Bug#63460: defining gender context.
Posted by Jeroen Tebbens <je...@tebbens.net>.
Theo Van Dinter wrote:
> On Wed, Oct 18, 2006 at 11:18:18PM +0200, Turbo Fredriksson wrote:
>
>> These kind of spam have been getting through for quite some time
>> now, but now they're really starting to bug me!
>>
>
>
>> -2.6 BAYES_00 BODY: Bayesian spam probability is 0 to 1%
>> [score: 0.0000]
>>
>
> Learn the mail as spam, -2.6 isn't helping.
> Second, you don't have the rules from sa-update so do that. :)
>
> That message scores a 7.9 for me w/ no BAYES rules, FWIW.
>
>
With imageinfo and FuzzyOcr (using 2.3rc1 atm) you can get it to 33 even. :)
Content analysis details: (33.0 points, 7.0 required)
pts rule name description
---- ----------------------
--------------------------------------------------
0.8 MY_DSL I could use a BL for this.
1.1 EXTRA_MPART_TYPE Header has extraneous Content-type:...type=
entry
0.0 UNPARSEABLE_RELAY Informational: message has unparseable relay
lines
2.8 TVD_FW_GRAPHIC_ID1 BODY: TVD_FW_GRAPHIC_ID1
1.8 HTML_IMAGE_ONLY_24 BODY: HTML: images with 2000-2400 bytes of words
1.0 HTML_MESSAGE BODY: HTML included in message
0.0 BAYES_50 BODY: Bayesian spam probability is 40 to 60%
[score: 0.5000]
1.0 INLINE_IMAGE RAW: Inline Images
2.5 SARE_GIF_ATTACH FULL: Email has a inline gif
0.5 VOWEL_FROM_5 Impronouncable from header (6 consecutive
vowels)
0.9 FM_NO_STYLE FM_NO_STYLE
2.5 SARE_GIF_STOX Inline Gif with little HTML
18 FUZZY_OCR BODY: Mail contains an image with common
spam text inside
Words found:
"alert" in 1 lines
"news" in 2 lines
"alert" in 1 lines
"stock" in 2 lines
"investor" in 1 lines
"company" in 1 lines
"price" in 1 lines
"trade" in 1 lines
"banking" in 1 lines
"litl" in 2 lines
"meridia" in 1 lines
"penis" in 1 lines
"kunde" in 1 lines
(16 word occurrences found)
Re: [lessons come] Bug#63460: defining gender context.
Posted by Theo Van Dinter <fe...@apache.org>.
On Wed, Oct 18, 2006 at 11:18:18PM +0200, Turbo Fredriksson wrote:
> These kind of spam have been getting through for quite some time
> now, but now they're really starting to bug me!
> -2.6 BAYES_00 BODY: Bayesian spam probability is 0 to 1%
> [score: 0.0000]
Learn the mail as spam, -2.6 isn't helping.
Second, you don't have the rules from sa-update so do that. :)
That message scores a 7.9 for me w/ no BAYES rules, FWIW.
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