Business Email Compromise (BEC) attempt from untrusted sender

 1name: "Business Email Compromise (BEC) attempt from untrusted sender"
 2description: |
 3    Detects potential Business Email Compromise (BEC) attacks by analyzing text within the email body from first-time senders.
 4type: "rule"
 5severity: "medium"
 6source: |
 7  type.inbound
 8  and any(ml.nlu_classifier(body.current_thread.text).intents,
 9          .name in ("bec") and .confidence == "high"
10  )
11  // negating legit replies
12  and not (
13    (
14      strings.istarts_with(subject.subject, "RE:")
15      // out of office auto-reply
16      // the NLU model will handle these better natively soon
17      or strings.istarts_with(subject.subject, "Automatic reply:")
18    )
19    and (
20      length(headers.references) > 0
21      or any(headers.hops, any(.fields, strings.ilike(.name, "In-Reply-To")))
22    )
23  )
24  and (
25    (
26      profile.by_sender().prevalence in ("new", "outlier")
27      and not profile.by_sender().solicited
28    )
29    or (
30      profile.by_sender().any_messages_malicious_or_spam
31      and not profile.by_sender().any_false_positives
32    )
33  )
34
35  // negate highly trusted sender domains unless they fail DMARC authentication
36  and
37  (
38    (
39      sender.email.domain.root_domain in $high_trust_sender_root_domains
40      and (
41        any(distinct(headers.hops, .authentication_results.dmarc is not null),
42            strings.ilike(.authentication_results.dmarc, "*fail")
43        )
44      )
45    )
46    or sender.email.domain.root_domain not in $high_trust_sender_root_domains
47  )  
48
49attack_types:
50  - "BEC/Fraud"
51tactics_and_techniques:
52  - "Social engineering"
53detection_methods:
54  - "Content analysis"
55  - "Header analysis"
56  - "Natural Language Understanding"
57  - "Sender analysis"
58id: "96d4c35a-ca53-559e-9db3-349dbbdffc20"