Brand impersonation: USPS

 1name: "Brand impersonation: USPS"
 2description: "Impersonation of the United States Postal Service."
 3type: "rule"
 4severity: "high"
 5source: |
 6  type.inbound
 7  and any(ml.logo_detect(beta.message_screenshot()).brands, .name == "USPS")
 8  and length(body.links) > 0
 9  and 2 of (
10    any(body.links,
11        strings.ilike(.display_text,
12                      "*check now*",
13                      "*track*",
14                      "*package*",
15                      '*view your order*'
16        )
17    ),
18    strings.ilike(body.current_thread.text,
19                  "*returned*to*sender*",
20                  "*redelivery*"
21    ),
22    // impersonal greeting
23    any(ml.nlu_classifier(body.current_thread.text).entities,
24        .name == "recipient" and .text =~ "Customer"
25    ),
26    // no links go to usps.com
27    all(body.links, .href_url.domain.root_domain != "usps.com")
28  )
29  
30  and (
31    sender.email.domain.root_domain not in ("usps.com")
32    or (
33      sender.email.domain.root_domain in ("usps.com")
34      and not headers.auth_summary.dmarc.pass
35    )
36  )
37  
38  // negate highly trusted sender domains unless they fail DMARC authentication
39  and (
40    (
41      sender.email.domain.root_domain in $high_trust_sender_root_domains
42      and not headers.auth_summary.dmarc.pass
43    )
44    or sender.email.domain.root_domain not in $high_trust_sender_root_domains
45  )  
46attack_types:
47  - "Credential Phishing"
48tactics_and_techniques:
49  - "Image as content"
50  - "Impersonation: Brand"
51  - "Social engineering"
52detection_methods:
53  - "Computer Vision"
54  - "Content analysis"
55  - "Natural Language Understanding"
56  - "Sender analysis"
57id: "28b9130a-d8e0-50af-97c9-c1b8f4c46d68"