Suspicious recipients pattern with no Compauth pass and suspicious content

name: "Suspicious recipients pattern with no Compauth pass and suspicious content"
description: "Detects messages with undisclosed recipients (likely all bcc), where the Compauth verdict is not 'pass', and ML has identified suspicious language or credential phishing links."
type: "rule"
severity: "medium"
source: |
  type.inbound
  and (
    length(recipients.to) == 0
    or all(recipients.to, .display_name == "Undisclosed recipients")
  )
  and length(recipients.cc) == 0
  and length(recipients.bcc) == 0
  and 2 of (
    (
      any(headers.hops,
          .authentication_results.compauth.verdict is not null
          and .authentication_results.compauth.verdict not in ("pass", "softpass")
      )
    ),
    (
      any(ml.nlu_classifier(body.current_thread.text).intents,
          .name in ("bec", "cred_theft", "advance_fee") and .confidence == "high"
      )
    ),
    (
      any(body.links,
          any([ml.link_analysis(.)],
              .credphish.disposition == "phishing"
              and .credphish.confidence in ("high")
          )
      )
    )
  )
  and (
    profile.by_sender().prevalence in ("new", "outlier")
    or (
      profile.by_sender().any_messages_malicious_or_spam
      and not profile.by_sender().any_messages_benign
    )
  )
  // negate highly trusted sender domains unless they fail DMARC authentication
  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
  )
detection_methods:
  - "Content analysis"
  - "Computer Vision"
  - "Header analysis"
  - "Natural Language Understanding"
  - "URL analysis"
  - "URL screenshot"
id: "34fb65f6-03e8-5752-b602-4f294172b5db"