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@ -9,15 +9,24 @@ Resulting output will contain useful information on why this e-mail might have b
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### Example screenshots
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- Chain of MTA servers (nicely parsed `Received` headers):
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![1.png](img/1.png)
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- Various headers decoded as much as possible, according to publicly available documentation (here _Office365 ForeFront Spam Report_):
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![2.png](img/2.png)
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- Different custom heuristics implement to actively validate and seek for clues of spam categorization, here logic detecting _Domain Impersonation_:
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![3.png](img/3.png)
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- Script attempts to reverse-engineer and document some of the Office365 Anti-Spam rules, as well as collect public knowledge about other opaque Anti-Spam headers:
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![4.png](img/4.png)
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### Processed headers
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Processed headers (more than **67+** headers are parsed):
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