Brand impersonation: Survey request with credential theft indicators

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 in ("AAA")
             or strings.icontains(.text,
                                  'colgate',
                                  'medicare kit',
                                  'blackstone griddle',
                                  'oral-b',
                                  'united healthcare',
                                  'dewalt tower tool box'
             )
           )
    )
    or any(ml.nlu_classifier(body.current_thread.text).entities,
           .name == "sender"
           and (
             strings.icontains(.text, "sam's club", "kobalt", "ace hardware")
             or regex.icontains(.text, "lowe\'s.{0,10}reward")
           )
    )
    or any(ml.nlu_classifier(body.current_thread.text).entities,
           .name == "request"
           and regex.icontains(.text, 'claim\s+your\s+(?:free|medical)?\s+kit')
    )
    or length(filter(ml.nlu_classifier(body.current_thread.text).entities,
                     .name == "financial"
                     and regex.icontains(.text, '\d{2}%\s*discount$')
              )
    ) >= 2
  )
  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", "share\nyour feedback")
  )
  and not (
    sender.email.domain.root_domain in ("barracudanetworks.com")
    and coalesce(headers.auth_summary.dmarc.pass, false)
  )
  // and the sender is not from high trust sender root domains
  and not (
    sender.email.domain.root_domain in $high_trust_sender_root_domains
    and coalesce(headers.auth_summary.dmarc.pass, false)
  )
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"