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sublimemediumRule
Brand impersonation: Marriott with gift language
Detects messages impersonating Marriott brand that contain gift-related language such as 'appreciation gift', 'thank you gift', or 'something special' from senders not associated with legitimate Marriott domains.
Detection Query
type.inbound
and (
strings.icontains(subject.base, "marriott")
or strings.icontains(sender.display_name, "marriott")
or strings.ilevenshtein(sender.display_name, 'marriott') <= 2
)
and any([body.current_thread.text, subject.base],
regex.icontains(.,
'(?:appreciation|thank)(?:\s|-)?(you)?\s+gift',
'something special',
'special.{0,10}thank(?:\s|-)you'
)
)
and not (
sender.email.domain.root_domain in~ (
"marriott.com",
"res-marriott.com",
"email-marriott.com",
"feedback-marriott.com",
"marriotthotels.se",
"bookonline.com"
)
and coalesce(headers.auth_summary.dmarc.pass, false)
)
Data Sources
Email MessagesEmail HeadersEmail Attachments
Platforms
email
Raw Content
name: "Brand impersonation: Marriott with gift language"
description: "Detects messages impersonating Marriott brand that contain gift-related language such as 'appreciation gift', 'thank you gift', or 'something special' from senders not associated with legitimate Marriott domains."
type: "rule"
severity: "medium"
source: |
type.inbound
and (
strings.icontains(subject.base, "marriott")
or strings.icontains(sender.display_name, "marriott")
or strings.ilevenshtein(sender.display_name, 'marriott') <= 2
)
and any([body.current_thread.text, subject.base],
regex.icontains(.,
'(?:appreciation|thank)(?:\s|-)?(you)?\s+gift',
'something special',
'special.{0,10}thank(?:\s|-)you'
)
)
and not (
sender.email.domain.root_domain in~ (
"marriott.com",
"res-marriott.com",
"email-marriott.com",
"feedback-marriott.com",
"marriotthotels.se",
"bookonline.com"
)
and coalesce(headers.auth_summary.dmarc.pass, false)
)
attack_types:
- "Credential Phishing"
tactics_and_techniques:
- "Impersonation: Brand"
- "Social engineering"
detection_methods:
- "Content analysis"
- "Header analysis"
- "Sender analysis"
id: "39b32b97-80bc-5033-902e-312377cab6e2"