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sublimehighRule

Callback phishing via Apple ID display name abuse

Detects callback phishing that abuses legitimate Apple ID notification emails as a delivery mechanism. The threat actor sets their Apple ID display name to a callback scam lure (e.g., a fake charge with a phone number), which Apple then embeds in the "Dear [name]" greeting of a routine account change notification. This legitimate email is forwarded to multiple targets via a distribution list, bypassing sender reputation checks since it originates from Apple's real infrastructure. The rule extracts the name field from the greeting and applies NLU classification to detect callback scam language within it.

MITRE ATT&CK

initial-access

Detection Query

type.inbound
and sender.email.email == "appleid@id.apple.com"
and (
  // the actor controls the name portion of the apple account, so extract that
  // english starts with Dear, but other language might start with Hello,
  // the email template and html div class names are the same between languages
  any(html.xpath(body.html, '//div[@class="email-body"]').nodes,
      any(regex.iextract(.display_text, '^(?P<first_line>[^\n]+)\n'),
          // NLU catches the actor controlled values as callback
          any(ml.nlu_classifier(beta.ml_translate(.named_groups["first_line"]).text
              ).intents,
              .name == "callback_scam"
          )
          // we have to account for NLU not catching it as callback_scam
          // this catches more than one digit followed by all capital letters
          // 599 USD, we use the unicode category Lu for capital letters from a bunch of languges
          or regex.contains(beta.ml_translate(.named_groups["first_line"]).text,
                            '\d{2,} \p{Lu}{2,5} '
          )
          // commonly observed phrase "if not you call"
          or strings.icontains(.named_groups["first_line"], "If not you call")
          // first line ends in a phone number
          or regex.contains(.named_groups["first_line"], '\d+,$')
      )
  )
  // the email address of the apple account appears in the body of the message
  or (
    any(body.current_thread.links,
        .parser == "plain"
        and .href_url.scheme == "mailto"
        // actor observed using `appleservice207@icloud.com`
        and (
          (
            strings.istarts_with(strings.parse_email(.href_url.url).local_part,
                                 'apple'
            )
            and strings.parse_email(.href_url.url).domain.domain not in $org_domains
          )
          // newly registered domains like peekaboo.baby
          or network.whois(.href_url.domain).days_old < 30
        )
    )
  )
)
and not recipients.to[0].email.domain.domain in $org_domains

Data Sources

Email MessagesEmail HeadersEmail Attachments

Platforms

email
Raw Content
name: "Callback phishing via Apple ID display name abuse"
description: >-
  Detects callback phishing that abuses legitimate Apple ID notification
  emails as a delivery mechanism. The threat actor sets their Apple ID
  display name to a callback scam lure (e.g., a fake charge with a phone
  number), which Apple then embeds in the "Dear [name]" greeting of a
  routine account change notification. This legitimate email is forwarded
  to multiple targets via a distribution list, bypassing sender reputation
  checks since it originates from Apple's real infrastructure. The rule
  extracts the name field from the greeting and applies NLU classification
  to detect callback scam language within it.
type: "rule"
severity: "high"
source: |
  type.inbound
  and sender.email.email == "appleid@id.apple.com"
  and (
    // the actor controls the name portion of the apple account, so extract that
    // english starts with Dear, but other language might start with Hello,
    // the email template and html div class names are the same between languages
    any(html.xpath(body.html, '//div[@class="email-body"]').nodes,
        any(regex.iextract(.display_text, '^(?P<first_line>[^\n]+)\n'),
            // NLU catches the actor controlled values as callback
            any(ml.nlu_classifier(beta.ml_translate(.named_groups["first_line"]).text
                ).intents,
                .name == "callback_scam"
            )
            // we have to account for NLU not catching it as callback_scam
            // this catches more than one digit followed by all capital letters
            // 599 USD, we use the unicode category Lu for capital letters from a bunch of languges
            or regex.contains(beta.ml_translate(.named_groups["first_line"]).text,
                              '\d{2,} \p{Lu}{2,5} '
            )
            // commonly observed phrase "if not you call"
            or strings.icontains(.named_groups["first_line"], "If not you call")
            // first line ends in a phone number
            or regex.contains(.named_groups["first_line"], '\d+,$')
        )
    )
    // the email address of the apple account appears in the body of the message
    or (
      any(body.current_thread.links,
          .parser == "plain"
          and .href_url.scheme == "mailto"
          // actor observed using `appleservice207@icloud.com`
          and (
            (
              strings.istarts_with(strings.parse_email(.href_url.url).local_part,
                                   'apple'
              )
              and strings.parse_email(.href_url.url).domain.domain not in $org_domains
            )
            // newly registered domains like peekaboo.baby
            or network.whois(.href_url.domain).days_old < 30
          )
      )
    )
  )
  and not recipients.to[0].email.domain.domain in $org_domains
attack_types:
  - "Callback Phishing"
tactics_and_techniques:
  - "Impersonation: Brand"
  - "Out of band pivot"
  - "Social engineering"
detection_methods:
  - "Content analysis"
  - "Natural Language Understanding"
  - "Sender analysis"
id: "a8607ce1-8614-505a-99c2-c8c716e80bc6"