Suspicious newly registered reply-to domain with engaging financial or urgent language

Detects messages from a mismatched newly registered Reply-to domain that contain a financial or urgent request, or a request and an NLU tag with medium to high confidence, from first time sender. This technique is typically observed in Vendor impersonation.

Sublime rule (View on GitHub)

 1name: "Suspicious newly registered reply-to domain with engaging financial or urgent language"
 2description: |
 3  Detects messages from a mismatched newly registered Reply-to domain that contain a financial or urgent request, or a request and 
 4  an NLU tag with medium to high confidence, from first time sender. This technique is typically observed in Vendor impersonation.  
 5type: "rule"
 6severity: "medium"
 7source: |
 8  type.inbound
 9  and any(headers.reply_to,
10          // mismatched reply-to and sender domain
11          .email.domain.root_domain != sender.email.domain.root_domain
12
13          // newly registered reply-to domain
14          and beta.whois(.email.domain).days_old <= 30
15  )
16
17  // request is being made
18  and any(ml.nlu_classifier(body.current_thread.text).entities, .name == "request")
19
20  // there's financial/urgency OR a tag of medium/high confidence
21  and (
22    any(ml.nlu_classifier(body.current_thread.text).entities, .name in ("financial", "urgency"))
23    or any(ml.nlu_classifier(body.current_thread.text).tags,
24           .name is not null and .confidence in ("medium", "high")
25    )
26  )
27
28  // first-time sender
29  and (
30    (
31      sender.email.domain.root_domain in $free_email_providers
32      and sender.email.email not in $sender_emails
33    )
34    or (
35      sender.email.domain.root_domain not in $free_email_providers
36      and sender.email.domain.domain not in $sender_domains
37    )
38  )  
39attack_types:
40  - "BEC/Fraud"
41tactics_and_techniques:
42  - "Social engineering"
43detection_methods:
44  - "Content analysis"
45  - "Header analysis"
46  - "Natural Language Understanding"
47  - "Sender analysis"
48  - "URL analysis"
49  - "Whois"
50id: "db4d9bb3-0eca-5525-9a99-7c1c773b580f"
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