Brand Impersonation: SendGrid

Detects inbound messages that impersonate SendGrid through display name or domain manipulation, combined with security or authentication-themed content, while failing authentication checks and originating from untrusted sources.

Sublime rule (View on GitHub)

 1name: "Brand Impersonation: SendGrid"
 2description: "Detects inbound messages that impersonate SendGrid through display name or domain manipulation, combined with security or authentication-themed content, while failing authentication checks and originating from untrusted sources."
 3type: "rule"
 4severity: "medium"
 5source: |
 6  type.inbound
 7  and (
 8    // display name contains sendgrid
 9    (
10      strings.ilike(strings.replace_confusables(sender.display_name),
11                    '*sendgrid*'
12      )
13      // levenshtein distance similar to sendgrid
14      or strings.ilevenshtein(strings.replace_confusables(sender.display_name),
15                              'sendgrid'
16      ) <= 1
17      // no display name, local_part contains sendgrid 
18      or (
19        strings.ilike(strings.replace_confusables(sender.email.local_part),
20                      '*sendgrid*'
21        )
22        and (
23          sender.display_name is null
24          or strings.ilike(strings.replace_confusables(subject.subject),
25                           '*sendgrid*'
26          )
27        )
28      )
29    )
30  )
31  and (
32    any(beta.ml_topic(body.current_thread.text).topics,
33        .name in (
34          "Security and Authentication",
35          "Secure Message",
36          "Reminders and Notifications",
37          "Software and App Updates"
38        )
39        and .confidence in ("medium", "high")
40    )
41    or any(beta.ml_topic(beta.ocr(beta.message_screenshot()).text).topics,
42           .name in (
43             "Security and Authentication",
44             "Secure Message",
45             "Reminders and Notifications",
46             "Software and App Updates"
47           )
48           and .confidence in ("medium", "high")
49    )
50    or any(ml.nlu_classifier(body.current_thread.text).intents,
51           .name == "cred_theft" and .confidence == "high"
52    )
53    or any(ml.nlu_classifier(beta.ocr(beta.message_screenshot()).text).intents,
54           .name == "cred_theft" and .confidence == "high"
55    )
56  )
57  
58  // and the sender is not in org_domains or from sendgrid domains and passes auth
59  and not (
60    sender.email.domain.root_domain in $org_domains
61    or (
62      sender.email.domain.root_domain in ("sendgrid.com")
63      and headers.auth_summary.dmarc.pass
64    )
65  )
66  // and the sender is not from high trust sender root domains
67  and (
68    (
69      sender.email.domain.root_domain in $high_trust_sender_root_domains
70      and not headers.auth_summary.dmarc.pass
71    )
72    or sender.email.domain.root_domain not in $high_trust_sender_root_domains
73  )
74  and not profile.by_sender().solicited  
75
76attack_types:
77  - "BEC/Fraud"
78  - "Credential Phishing"
79  - "Spam"
80tactics_and_techniques:
81  - "Impersonation: Brand"
82  - "Social engineering"
83detection_methods:
84  - "Content analysis"
85  - "Header analysis"
86  - "Natural Language Understanding"
87  - "Optical Character Recognition"
88  - "Sender analysis"
89id: "d800124f-6aa4-58e1-8fa7-beec4958924f"
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