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mgeeky 2021-10-28 19:13:45 +02:00
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@ -9,15 +9,24 @@ Resulting output will contain useful information on why this e-mail might have b
### Example screenshots
- Chain of MTA servers (nicely parsed `Received` headers):
![1.png](img/1.png)
- Various headers decoded as much as possible, according to publicly available documentation (here _Office365 ForeFront Spam Report_):
![2.png](img/2.png)
- Different custom heuristics implement to actively validate and seek for clues of spam categorization, here logic detecting _Domain Impersonation_:
![3.png](img/3.png)
- 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:
![4.png](img/4.png)
### Processed headers
Processed headers (more than **67+** headers are parsed):