Sublime Security medium experimental mql

Attachment: Adobe image lure in body or attachment with suspicious link

Detects Adobe phishing messages with an Adobe logo in the body or attachment, with suspicious link language.

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Detection Logic

type.inbound
and (
  // all images
  length(filter(attachments, .file_type not in $file_types_images)) == 0
  // only pdf attachments
  or length(filter(attachments, .file_type != "pdf")) == 0
  // pdf and image attachements where images are all embedded into the message body
  or length(filter(attachments,
                   .file_type == 'pdf'
                   or (
                     .file_type in $file_types_images
                     and strings.icontains(body.html.raw,
                                           strings.concat("cid:", .content_id)
                     )
                   )
            )
  ) == length(attachments)
)
and (
  (
    any(ml.logo_detect(file.message_screenshot()).brands, .name == "Adobe")
    and 0 < length(body.links) < 10
    and any(body.links, .display_text is null)
    and (
      length(filter(body.links,
                    (
                      .display_text is null
                      and .display_url.url == sender.email.domain.root_domain
                    )
                    or .href_url.domain.root_domain in (
                      "aka.ms",
                      "mimecast.com",
                      "mimecastprotect.com",
                      "cisco.com"
                    )
             )
      ) != length(body.links)
    )
  )
  or any(filter(attachments,
                // filter down to attachments with adobe logo
                any(ml.logo_detect(.).brands,
                    .name == "Adobe" and .confidence in ("medium", "high")
                )
         ),
         // the attachment (or message body) contain links
         any(file.explode(.),
             (
               length(.scan.url.urls) > 0
               or length(.scan.pdf.urls) > 0
               or length(body.links) > 0
             )
         )
  )
)
and (
  (
    (length(headers.references) > 0 or headers.in_reply_to is null)
    and not (
      (
        strings.istarts_with(subject.subject, "RE:")
        or strings.istarts_with(subject.subject, "RES:")
        or strings.istarts_with(subject.subject, "R:")
        or strings.istarts_with(subject.subject, "ODG:")
        or strings.istarts_with(subject.subject, "答复:")
        or strings.istarts_with(subject.subject, "AW:")
        or strings.istarts_with(subject.subject, "TR:")
        or strings.istarts_with(subject.subject, "FWD:")
        or regex.imatch(subject.subject, '(\[[^\]]+\]\s?){0,3}(re
| fwd?)\s?:')
      )
    )
  )
  or length(headers.references) == 0
)

// not a newsletter or advertisement
and not any(headers.hops, any(.fields, .name == "List-Unsubscribe-Post"))
and not any(ml.nlu_classifier(body.current_thread.text).topics,
            .name in ("Advertising and Promotions", "Newsletters and Digests")
            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
)
and (
  // exclude solicited senders
  not profile.by_sender_email().solicited
  or profile.by_sender_email().prevalence == "new"
  or length(recipients.to) == 0
  // domains for recipients to/cc must be valid
  or (
    all(recipients.to, .email.domain.valid == false)
    and all(recipients.cc, .email.domain.valid == false)
  )
  or (
    profile.by_sender_email().any_messages_malicious_or_spam
    and not profile.by_sender_email().any_messages_benign
  )
)
and not profile.by_sender_email().any_messages_benign

Field Validations

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