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sublimemediumRule
Attachment: Fake voicemail via PDF
Identifies inbound messages containing a single-page PDF attachment related to voicemail or missed call notifications that includes either a URL or QR code.
Detection Query
type.inbound
// a single PDF attachment
and length(attachments) == 1
// the subject doesn't contain fax, which is currently a common match for the topic
and not strings.icontains(subject.subject, 'fax')
and ml.nlu_classifier(subject.subject).language == "english"
and any(beta.ml_topic(body.current_thread.text).topics,
.confidence == "high"
and .name == "Voicemail Call and Missed Call Notifications"
)
// the Topic analysis of the PDF is Voicemail
and any(attachments,
.file_extension == "pdf"
// the NLU detected language is english
and ml.nlu_classifier(beta.ocr(.).text).language == "english"
and length(beta.ocr(.).text) > 100
and any(beta.ml_topic(beta.ocr(.).text).topics,
.confidence == "high"
and .name == "Voicemail Call and Missed Call Notifications"
)
and beta.ocr(.).success
// contains a link or QR code
and any(file.explode(.),
0 < length(.scan.pdf.urls) <= 2 or .scan.qr.url.url is not null
)
// there is only a single page
and any(file.explode(.), .depth == 0 and .scan.exiftool.page_count == 1)
)
Data Sources
Email MessagesEmail HeadersEmail Attachments
Platforms
email
Raw Content
name: "Attachment: Fake voicemail via PDF"
description: "Identifies inbound messages containing a single-page PDF attachment related to voicemail or missed call notifications that includes either a URL or QR code."
type: "rule"
severity: "medium"
source: |
type.inbound
// a single PDF attachment
and length(attachments) == 1
// the subject doesn't contain fax, which is currently a common match for the topic
and not strings.icontains(subject.subject, 'fax')
and ml.nlu_classifier(subject.subject).language == "english"
and any(beta.ml_topic(body.current_thread.text).topics,
.confidence == "high"
and .name == "Voicemail Call and Missed Call Notifications"
)
// the Topic analysis of the PDF is Voicemail
and any(attachments,
.file_extension == "pdf"
// the NLU detected language is english
and ml.nlu_classifier(beta.ocr(.).text).language == "english"
and length(beta.ocr(.).text) > 100
and any(beta.ml_topic(beta.ocr(.).text).topics,
.confidence == "high"
and .name == "Voicemail Call and Missed Call Notifications"
)
and beta.ocr(.).success
// contains a link or QR code
and any(file.explode(.),
0 < length(.scan.pdf.urls) <= 2 or .scan.qr.url.url is not null
)
// there is only a single page
and any(file.explode(.), .depth == 0 and .scan.exiftool.page_count == 1)
)
attack_types:
- "Credential Phishing"
tactics_and_techniques:
- "PDF"
- "QR code"
- "Social engineering"
detection_methods:
- "Computer Vision"
- "Content analysis"
- "File analysis"
- "Optical Character Recognition"
- "QR code analysis"
- "URL analysis"
id: "d3587209-a8e6-5209-8dfc-35646b6ccd23"