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sublimemediumRule

Mass campaign: recipient address in subject, body, and link (untrusted sender)

This detects a pattern commonly observed in mass phishing campaigns. The local_part or the full email address of the recipient is used in the subject, body, and link query parameter to "personalize" the attack.

MITRE ATT&CK

initial-access

Detection Query

type.inbound
and length(recipients.to) + length(recipients.bcc) + length(recipients.cc) == 1

// exclude To: Undisclosed recipients:;
// since we won't have a valid recipient email
and any(recipients.to, .email.domain.valid == true)
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
  )
)
and (
  any(recipients.to,
      (
        strings.icontains(subject.subject, .email.email)
        or strings.icontains(subject.subject, .email.local_part)
      )
      and (
        .email.domain.valid or strings.icontains(.display_name, "undisclosed")
      )
  )
)
and any(recipients.to,
        strings.icontains(body.current_thread.text, .email.email)
)
and any(body.links,
        any(recipients.to,
            strings.icontains(..href_url.query_params, .email.email)
        )
        and (
          (
            not strings.icontains(.display_text, "unsubscribe")
            and not strings.icontains(.href_url.path, "unsubscribe")
          )
        )
)
and any(ml.nlu_classifier(body.current_thread.text).intents,
        .name in ("cred_theft") and .confidence == "high"
)

// 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
)

Data Sources

Email MessagesEmail HeadersEmail Attachments

Platforms

email
Raw Content
name: "Mass campaign: recipient address in subject, body, and link (untrusted sender)"
description: |
  This detects a pattern commonly observed in mass phishing campaigns.

  The local_part or the full email address of the recipient is used in the subject,
  body, and link query parameter to "personalize" the attack.
references:
  - "https://playground.sublimesecurity.com?id=d9143109-8886-4639-b634-d0a671848eb6"
type: "rule"
severity: "medium"
source: |
  type.inbound
  and length(recipients.to) + length(recipients.bcc) + length(recipients.cc) == 1
  
  // exclude To: Undisclosed recipients:;
  // since we won't have a valid recipient email
  and any(recipients.to, .email.domain.valid == true)
  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
    )
  )
  and (
    any(recipients.to,
        (
          strings.icontains(subject.subject, .email.email)
          or strings.icontains(subject.subject, .email.local_part)
        )
        and (
          .email.domain.valid or strings.icontains(.display_name, "undisclosed")
        )
    )
  )
  and any(recipients.to,
          strings.icontains(body.current_thread.text, .email.email)
  )
  and any(body.links,
          any(recipients.to,
              strings.icontains(..href_url.query_params, .email.email)
          )
          and (
            (
              not strings.icontains(.display_text, "unsubscribe")
              and not strings.icontains(.href_url.path, "unsubscribe")
            )
          )
  )
  and any(ml.nlu_classifier(body.current_thread.text).intents,
          .name in ("cred_theft") and .confidence == "high"
  )
  
  // 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
  )
attack_types:
  - "Credential Phishing"
tactics_and_techniques:
  - "Social engineering"
detection_methods:
  - "Header analysis"
  - "Natural Language Understanding"
  - "Sender analysis"
id: "599dabf5-6287-5adf-8a8f-70649ccf0f92"