sublimemediumRule

Brand impersonation: Survey request with credential theft indicators

Detects messages containing credential theft language disguised as survey requests from promotional content, targeting organizations from untrusted or spoofed high-trust domains.

MITRE ATT&CK

T1566 T1566.001 T1566.002 T1598 T1598.003

initial-access

Detection Query

type.inbound
and (
  any(ml.nlu_classifier(body.current_thread.text).intents,
      .name == "cred_theft" and .confidence == "high"
  )
  or any(ml.nlu_classifier(body.current_thread.text).entities,
         .name == "org" and .text == 'AAA'
  )
  or any(ml.nlu_classifier(body.current_thread.text).entities,
         .name == "request" and strings.icontains(.text, 'Claim Your Free Kit')
  )
)
and any(ml.nlu_classifier(body.current_thread.text).topics,
        .name == "Advertising and Promotions" and .confidence != "low"
)
and any(ml.nlu_classifier(body.current_thread.text).entities,
        .name in ("request", "org") and strings.icontains(.text, "survey")
)
// and the sender is not from high trust sender root domains
and (
  (
    sender.email.domain.root_domain in $high_trust_sender_root_domains
    and not headers.auth_summary.dmarc.pass
  )
  or sender.email.domain.root_domain not in $high_trust_sender_root_domains
)

Data Sources

Email MessagesEmail HeadersEmail Attachments

Platforms

Raw Content

name: "Brand impersonation: Survey request with credential theft indicators"
description: "Detects messages containing credential theft language disguised as survey requests from promotional content, targeting organizations from untrusted or spoofed high-trust domains."
type: "rule"
severity: "medium"
source: |
  type.inbound
  and (
    any(ml.nlu_classifier(body.current_thread.text).intents,
        .name == "cred_theft" and .confidence == "high"
    )
    or any(ml.nlu_classifier(body.current_thread.text).entities,
           .name == "org" and .text == 'AAA'
    )
    or any(ml.nlu_classifier(body.current_thread.text).entities,
           .name == "request" and strings.icontains(.text, 'Claim Your Free Kit')
    )
  )
  and any(ml.nlu_classifier(body.current_thread.text).topics,
          .name == "Advertising and Promotions" and .confidence != "low"
  )
  and any(ml.nlu_classifier(body.current_thread.text).entities,
          .name in ("request", "org") and strings.icontains(.text, "survey")
  )
  // and the sender is not from high trust sender root domains
  and (
    (
      sender.email.domain.root_domain in $high_trust_sender_root_domains
      and not headers.auth_summary.dmarc.pass
    )
    or sender.email.domain.root_domain not in $high_trust_sender_root_domains
  )
attack_types:
  - "Credential Phishing"
tactics_and_techniques:
  - "Social engineering"
  - "Impersonation: Brand"
  - "Spoofing"
detection_methods:
  - "Content analysis"
  - "Header analysis"
  - "Natural Language Understanding"
  - "Sender analysis"
id: "ea1c0e09-ef3d-5c30-b5c1-ffa1b71a7b88"