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Every 6 months or so, Microsoft releases its Security and Intelligence Report for the previous 6 months of the year. SIRv7 is now available here . This is a very comprehensive document covering topics from the entire threat landscape that
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MAAWG is an organization that started up in response to the spam problem. Its official name is the Messaging Anti-Abuse Working Group, and they are meeting this week in Philadelphia to discuss all things abusive. I didn’t go this time around,
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Just for the fun of it, I decided to check some statistics on the waledac botnet. I got the total number of distinct IPs sending us spam and broke them out by how much spam they were sending us, by country, for Oct 22, 2009. Below are the
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I received a spam message the other day that went to my Junk Mail Folder. I decided to take a look at it and dissect it piece by piece. It really is amazing to see how spam crosses so many international borders and exploits so many different
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I came across the following game linked off the Anti-phishing Working Group’s web page . It’s an educational game that teaches users how to tell the difference between a legitimate web site and a malicious website. While some of the advice
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I came across an interesting type of spam the other day. Here is a snippet of the headers: Received: from (87.200.53.223) by TX2EHSMHS013.bigfish.com (10.x.x.x) with Microsoft SMTP Server id 14.0.482.32; Wed, 16
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As I was eluding to in my previous post, I have been doing some research on the geographical location of the servers where spammy URLs are hosted. In doing this research, I came across a curious phenomenon which I call the 3+1 scenario – these domains
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A few weeks ago, I posted a piece on where individuals spammers were located in terms of sending IP. The United States was number 1, followed by China. This is in terms of total volume of spam that they send. However, a second piece of data that I did
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The following is an excerpt from Investor's Business Daily: Microsoft ( MSFT ), the software giant, increased its market share in U.S. Web searches to 8.23% in June from 7.81% in May, thanks to its new Bing search site, according to tracking firm StatCounter.
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The other day, I got the following spam message in my inbox (junk mail folder, actually): miaou skoal. ripe fanny hash tome? hypo kirk. griff trow canoe kirk. fix die dance. fix coach born hazy? silky brier mutt wrest. samp cad wrest adopt? ahoy pest
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Way back when I was dealing with spam, I used to through the abuse submission inbox and look for submissions that were good quality. The best were the ones that contained full headers; generally speaking, messages with the spam attached were good
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One of the common questions I get through the feedback form on this blog is what people should do if they are blocked by the 88.blacklist.zap list when they attempt to send a message protected by Forefront Online Security. If you are blocked, send the
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I'd like to continue on in my series on measuring the effectiveness of a spam filter. The requirements I have so far is that is has to be continuous, statistically relevant, automated, and transparent to end users. There is one more requirement.
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Following on from my last post, there are a couple of more considerations that we have to take into account if we want to measure a spam filter's effectiveness. I have already hit on three points (continuous, automated, need a lot of mail).
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Continuing on from my previous post, I'd like to get into more of the considerations when it comes to measuring spam effectiveness. I'm going to combine topics in this post. Measurement has to be automated, and statistically relevant When it comes
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