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I have a great example of a spam message with Bayesian poisoning on my blog. Bayesian spam filters basically keep track of each word used in each message. When a message is marked as spam, the filter treats the words in the message as representative of spam. By using this information, the filter can determine with good accuracy whether a particular message ...


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Lucas Kauffman answer explain the how very well, as for why: If the user is failing to receive important emails and it turns out they got caught in the spam filter then they'll get angry at their admin. False positives can have a very high cost. When a lot of users get angry at the admin the admin is likely to change things so that the spam filter is ...


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There's a good paper published named Bachelor thesis:The Effects of Different Bayesian Poison Methods on the Quality of the Bayesian Spam Filter ‘SpamBayes’ by Martijn Sprengers. I'll try to make TL;DR: Bayesian spamfilters try to decide if an email is spam or not by looking at keywords in an email. What it does is review the words present in normal and ...


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This appears to be standard link farming/blackhat SEO, where the spammer is attempting to increase the google page rank of the target domain by significantly increasing the amount of links to the target website. The nofollow link attribute was introduced to combat this type of attack, but it looks like it may not be applicable in this scenario as the ...


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From the sample you provided, it looks like forum spam where the poster is trying to advertise. I was unable to spot anything malicious at first glance, although the target sites might host malware. It IS possible that they might be trying to trigger a DoS scenario by clogging your forms, but there are more efficient ways to do that. Just looks like simple ...


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Yes, it is a scam. Any email you get, from anyone you don't know, offering you money, is a scam. This is a rule of thumb that is essentially 100% accurate 100% of the time. The best course of action to take, when you receive emails like this, is to delete them as soon as you identify them, in order to minimize the amount of time you waste reading them. ...



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