VIP impersonation with urgent request (strict match, untrusted sender)
Sender is using a display name that matches the display name of someone in your $org_vips list.
Detects potential Business Email Compromise (BEC) attacks by analyzing text within email body from untrusted senders.
Sublime rule (View on GitHub)
1name: "VIP impersonation with urgent request (strict match, untrusted sender)"
2description: |
3 Sender is using a display name that matches the display name of someone in your $org_vips list.
4
5 Detects potential Business Email Compromise (BEC) attacks by analyzing text within email body from untrusted senders.
6type: "rule"
7severity: "high"
8source: |
9 type.inbound
10 and any($org_vips, .display_name =~ sender.display_name)
11 and (
12 any(ml.nlu_classifier(body.current_thread.text).intents,
13 .name == "bec" and .confidence in ("medium", "high")
14 )
15 or (
16 any(ml.nlu_classifier(body.current_thread.text).entities,
17 .name == "urgency"
18 )
19 and any(ml.nlu_classifier(body.current_thread.text).entities,
20 .name == "request"
21 )
22 )
23 )
24 and (
25 (
26 profile.by_sender().prevalence != "common"
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_messages_benign
32 )
33 or profile.by_sender().days_since.last_outbound > 365
34 )
35 // negate sharepoint notifications originating from within the org
36 and not (
37 sender.email.email in ('no-reply@sharepointonline.com')
38 and length(headers.reply_to) > 0
39 and all(headers.reply_to, .email.domain.root_domain in $org_domains)
40 )
41 // negate highly trusted sender domains unless they fail DMARC authentication
42 and (
43 (
44 sender.email.domain.root_domain in $high_trust_sender_root_domains
45 and not headers.auth_summary.dmarc.pass
46 )
47 or sender.email.domain.root_domain not in $high_trust_sender_root_domains
48 )
49 and not profile.by_sender().any_messages_benign
50attack_types:
51 - "BEC/Fraud"
52tactics_and_techniques:
53 - "Impersonation: VIP"
54 - "Social engineering"
55detection_methods:
56 - "Content analysis"
57 - "Content analysis"
58 - "Natural Language Understanding"
59 - "Sender analysis"
60id: "0dd1fa60-6e89-5f70-81a1-6b64eef0e428"