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How to identify the element(s) of an email that triggers the scam detector

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  • Última resposta de sfhowes

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I know how scam detection works. Sometimes an email from a legitimate source is flagged as a scam. That's ok, but sometimes I need to identify exactly the point(s) where the scam detector found the problem, in order to suggest the sender to change. Often it is a simple typo in the footer that makes the link different from the text, and it is good if the sender changes its footer.

The point is that, to do this, I need to open the email source and visually replicate the job done by the scam detector. Is there a way to spot the problem with the help of the scam detector itself? An Add-on maybe?

Regards. Mau.

I know how scam detection works. Sometimes an email from a legitimate source is flagged as a scam. That's ok, but sometimes I need to identify exactly the point(s) where the scam detector found the problem, in order to suggest the sender to change. Often it is a simple typo in the footer that makes the link different from the text, and it is good if the sender changes its footer. The point is that, to do this, I need to open the email source and visually replicate the job done by the scam detector. Is there a way to spot the problem with the help of the scam detector itself? An Add-on maybe? Regards. Mau.

Todas as respostas (3)

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There is a bit of information here. If you want to dig deeper, this recent bug may offer a starting point. There are a few discussions from ca. 2005, but I don't know how many of them are still relevant.

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Thanks for your reply. I have already seen that page and other describing how scam detection works. This is not the point. What I want is an help to spot the single wrong link is 300K+ email. Doing this by hand is almost impossible.

What I would like to have is an hint from the scam detector, on where it has found the problem.

Is this possible? Having Thunderbird underline it with a wiggle would be the best, but even looking at log files or other internal information can be useful.

Regards. Mau.

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As you have found, there appears to be no public, documented description of the scam algorithm, let alone a tool to apply it to bulk quantities of mail in the way you describe. Your best option may be to contact the participants in the Bugzilla reports.