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sublimehighRule
VIP impersonation with urgent request (strict match, untrusted sender)
Sender is using a display name that matches the display name of someone in your $org_vips list. Detects potential Business Email Compromise (BEC) attacks by analyzing text within email body from untrusted senders.
Detection Query
type.inbound
and any($org_vips, .display_name =~ sender.display_name)
and (
any(ml.nlu_classifier(body.current_thread.text).intents,
.name == "bec" and .confidence in ("medium", "high")
)
or (
any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "urgency"
)
and any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "request"
)
)
)
and (
(
profile.by_sender().prevalence != "common"
and not profile.by_sender().solicited
)
or (
profile.by_sender().any_messages_malicious_or_spam
and not profile.by_sender().any_messages_benign
)
or profile.by_sender().days_since.last_outbound > 365
)
// negate sharepoint notifications originating from within the org
and not (
sender.email.email in ('no-reply@sharepointonline.com')
and length(headers.reply_to) > 0
and all(headers.reply_to, .email.domain.root_domain in $org_domains)
)
// 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 not profile.by_sender().any_messages_benign
Data Sources
Email MessagesEmail HeadersEmail Attachments
Platforms
email
Raw Content
name: "VIP impersonation with urgent request (strict match, untrusted sender)"
description: |
Sender is using a display name that matches the display name of someone in your $org_vips list.
Detects potential Business Email Compromise (BEC) attacks by analyzing text within email body from untrusted senders.
type: "rule"
severity: "high"
source: |
type.inbound
and any($org_vips, .display_name =~ sender.display_name)
and (
any(ml.nlu_classifier(body.current_thread.text).intents,
.name == "bec" and .confidence in ("medium", "high")
)
or (
any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "urgency"
)
and any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "request"
)
)
)
and (
(
profile.by_sender().prevalence != "common"
and not profile.by_sender().solicited
)
or (
profile.by_sender().any_messages_malicious_or_spam
and not profile.by_sender().any_messages_benign
)
or profile.by_sender().days_since.last_outbound > 365
)
// negate sharepoint notifications originating from within the org
and not (
sender.email.email in ('no-reply@sharepointonline.com')
and length(headers.reply_to) > 0
and all(headers.reply_to, .email.domain.root_domain in $org_domains)
)
// 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 not profile.by_sender().any_messages_benign
attack_types:
- "BEC/Fraud"
tactics_and_techniques:
- "Impersonation: VIP"
- "Social engineering"
detection_methods:
- "Content analysis"
- "Content analysis"
- "Natural Language Understanding"
- "Sender analysis"
id: "0dd1fa60-6e89-5f70-81a1-6b64eef0e428"