Brand impersonation: Survey request with credential theft indicators

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', 'Medicare Kit')
  )
  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")
)
// 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
)