BEC/Fraud: Job scam fake thread or plaintext pivot to freemail

name: "BEC/Fraud: Job scam fake thread or plaintext pivot to freemail"
description: "Detects potential job scams using plaintext or fake threads attempting to pivot to a freemail address from an unsolicited sender."
type: "rule"
severity: "medium"
source: |
  type.inbound
  and any(ml.nlu_classifier(body.current_thread.text).entities,
          .name in ("greeting", "salutation")
  )
  
  // most likely to occur in plain text
  and (
    body.html.raw is null
    or 
  
    // HTML is not null but fake thread
    (
      subject.is_reply or subject.is_forward
    )
    and (
      (length(headers.references) == 0 and headers.in_reply_to is null)
      or not any(headers.hops, any(.fields, strings.ilike(.name, "In-Reply-To")))
    )
  )
  and (
    3 of (
      any([subject.subject, body.current_thread.text],
          regex.icontains(., '(full|part).time')
      ),
      strings.ilike(body.current_thread.text, '*job*'),
      regex.icontains(body.current_thread.text, '\bHR\b'),
      strings.ilike(body.current_thread.text, '*manager*'),
      strings.ilike(body.current_thread.text, '*commission*'),
      strings.ilike(body.current_thread.text, '*hourly*'),
      strings.ilike(body.current_thread.text, '*per hour*'),
      strings.ilike(body.current_thread.text, '*prior experience*'),
      strings.ilike(body.current_thread.text, '*company rep*'),
      strings.ilike(body.current_thread.text, "100% legal")
    )
    or (
      length(ml.nlu_classifier(body.current_thread.text).topics) == 1
      and any(ml.nlu_classifier(body.current_thread.text).topics,
              .name == "Professional and Career Development"
              and .confidence == "high"
      )
      and (
        length(recipients.to) == 0
        or all(recipients.to,
               strings.ilike(.display_name, "Undisclosed?recipients")
        )
      )
    )
  )
  
  // all attachments are images or there's no attachments
  and (
    (
      length(attachments) > 0
      and all(attachments, .file_type in $file_types_images)
    )
    or length(attachments) == 0
  )
  
  // there's an email in the body and it's a freemail
  and any(regex.extract(body.current_thread.text,
                        "[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\\.[A-Za-z]{2,}"
          ),
          strings.parse_email(.full_match).domain.domain in $free_email_providers
          or strings.parse_email(.full_match).domain.root_domain in $free_email_providers
  )
  
  // and that email doesn't match the sender domain
  and (
    all(body.links, .href_url.domain.root_domain != sender.email.domain.domain)
    or sender.email.domain.root_domain in $free_email_providers
  )
  and (
    (
      not profile.by_sender().solicited
      and not profile.by_sender().any_messages_benign
    )
    or profile.by_sender().any_messages_malicious_or_spam
  )
  and not profile.by_sender().any_messages_benign
attack_types:
  - "BEC/Fraud"
tactics_and_techniques:
  - "Free email provider"
  - "Out of band pivot"
detection_methods:
  - "Content analysis"
  - "File analysis"
  - "Natural Language Understanding"
id: "ce21c151-90c2-5573-b19e-3dcbcfc0a195"