Can base64 encoded messages learnable by sa-learn?

[Thomas Cameron]

All -

I have a client with a Red hat 9 + SA 2.55 + spamass-milter server in
front of a Lotus Notes server.  The client has hired a Notes developer
to give their users an extra button in Notes to forward false negatives
to a spam account the Linux server so I can run sa-learn --spam on the
messages.  The thing is, the messages get sent as base64 encoded
attachments (see example below).

Can sa-learn use this format to learn from?

Thanks in advance!
Thomas

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>From address@hidden  Thu Sep  4 10:51:28 2003
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Received: from nobelium.XXXXinc.com (www.XXXXinc.com [216.110.81.99])
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        for <address@hidden>; Thu, 4 Sep 2003 10:51:02 -0500
Subject: =?iso-2022-jp?B?GyRCTEgbKEI=?= =?gb2312?B?t9HU+Q==?=
 =?iso-2022-jp?B?GyRCOzBKLBsoQg==?= =?gb2312?B?1tM=?=
 =?iso-2022-jp?B?GyRCO19TQztfMzE7NiEkGyhC?= =?gb2312?B?0bA=?=
 =?iso-2022-jp?B?GyRCNWEbKEI/GyhCPw==?= =?gb2312?B?0qk=?=
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To: address@hidden, address@hidden
Message-ID: <address@hidden>
From: address@hidden
Date: Thu, 4 Sep 2003 10:51:07 -0500
X-MIMETrack: Serialize by Router on Zinc/XXXX/US(Release 5.0.10 |March
22, 2002) at 09/04/2003
 11:01:21 AM
MIME-Version: 1.0
Content-type: multipart/mixed; 
       
Boundary="0__=09BBE704DFC495678f9e8a93df938690918c09BBE704DFC49567"
Content-Disposition: inline
X-Spam-Status: No, hits=1.5 required=5.0
        tests=NO_REAL_NAME,PLING_QUERY
        version=2.55
X-Spam-Level: *
X-Spam-Checker-Version: SpamAssassin 2.55 (1.174.2.19-2003-05-19-exp)

--0__=09BBE704DFC495678f9e8a93df938690918c09BBE704DFC49567
Content-type: text/plain; charset=us-ascii

(See attached file: message.txt)

--0__=09BBE704DFC495678f9e8a93df938690918c09BBE704DFC49567
Content-type: application/octet-stream; 
        name="message.txt"
Content-Disposition: attachment; filename="message.txt"
Content-transfer-encoding: base64
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