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sublimemediumRule
Body: AI-generated invoice template artifacts
Flags inbound messages where NLU classification of the thread text indicates medium or high confidence credential theft or BEC intent, and the message HTML contains comment artifacts characteristic of AI-generated invoice/billing templates (e.g. 'PDF icon', 'File row', 'Billing Table', 'CTA Button'). Messages from highly trusted sender domains are excluded unless they fail DMARC authentication.
Detection Query
type.inbound
and any(ml.nlu_classifier(body.current_thread.text).intents,
.name in ("cred_theft", "bec") and .confidence in ("medium", "high")
)
// templated ai-generated comments
and any(html.xpath(body.html, '//comment()').nodes,
regex.icontains(.raw,
'PDF icon|File row|Status \+ Reference|Billing Table|Invoice Info|CTA Button'
)
)
// negate highly trusted sender domains unless they fail DMARC authentication
and not (
sender.email.domain.root_domain in $high_trust_sender_root_domains
and coalesce(headers.auth_summary.dmarc.pass, false)
)
Data Sources
Email MessagesEmail HeadersEmail Attachments
Platforms
email
Tags
Attack surface reduction
Raw Content
name: "Body: AI-generated invoice template artifacts"
description: "Flags inbound messages where NLU classification of the thread text indicates medium or high confidence credential theft or BEC intent, and the message HTML contains comment artifacts characteristic of AI-generated invoice/billing templates (e.g. 'PDF icon', 'File row', 'Billing Table', 'CTA Button'). Messages from highly trusted sender domains are excluded unless they fail DMARC authentication."
type: "rule"
severity: "medium"
source: |
type.inbound
and any(ml.nlu_classifier(body.current_thread.text).intents,
.name in ("cred_theft", "bec") and .confidence in ("medium", "high")
)
// templated ai-generated comments
and any(html.xpath(body.html, '//comment()').nodes,
regex.icontains(.raw,
'PDF icon|File row|Status \+ Reference|Billing Table|Invoice Info|CTA Button'
)
)
// negate highly trusted sender domains unless they fail DMARC authentication
and not (
sender.email.domain.root_domain in $high_trust_sender_root_domains
and coalesce(headers.auth_summary.dmarc.pass, false)
)
tags:
- "Attack surface reduction"
attack_types:
- "Credential Phishing"
- "BEC/Fraud"
tactics_and_techniques:
- "Social engineering"
- "Spoofing"
detection_methods:
- "Natural Language Understanding"
- "HTML analysis"
- "Header analysis"
- "Sender analysis"
id: "52b593a9-e051-5c80-85ac-ca9da0e215c9"