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sublimehighRule
Impersonation: Australian Federal Police with criminal case language
Detects messages impersonating the Australian Federal Police using law enforcement terminology in the subject and sender display name, combined with official correspondence language including case references, investigation details, and compliance demands.
Detection Query
type.inbound
and (
strings.ilike(subject.base, '*afp*')
or strings.ilike(subject.base, '*australian federal police*')
)
and (
2 of (
strings.ilike(subject.base, '*case*'),
strings.ilike(subject.base, '*investigation*'),
strings.ilike(subject.base, '*law enforcement*'),
strings.ilike(subject.base, '*management*'),
strings.ilike(subject.base, '*notice*'),
strings.ilike(subject.base, '*reference*')
)
)
and (
regex.icontains(body.current_thread.text, 'investigation|correspondence')
and regex.icontains(body.current_thread.text, 'case (?:reference|type)')
)
Data Sources
Email MessagesEmail HeadersEmail Attachments
Platforms
email
Raw Content
name: "Impersonation: Australian Federal Police with criminal case language"
description: "Detects messages impersonating the Australian Federal Police using law enforcement terminology in the subject and sender display name, combined with official correspondence language including case references, investigation details, and compliance demands."
type: "rule"
severity: "high"
source: |
type.inbound
and (
strings.ilike(subject.base, '*afp*')
or strings.ilike(subject.base, '*australian federal police*')
)
and (
2 of (
strings.ilike(subject.base, '*case*'),
strings.ilike(subject.base, '*investigation*'),
strings.ilike(subject.base, '*law enforcement*'),
strings.ilike(subject.base, '*management*'),
strings.ilike(subject.base, '*notice*'),
strings.ilike(subject.base, '*reference*')
)
)
and (
regex.icontains(body.current_thread.text, 'investigation|correspondence')
and regex.icontains(body.current_thread.text, 'case (?:reference|type)')
)
attack_types:
- "BEC/Fraud"
- "Extortion"
tactics_and_techniques:
- "Impersonation: Brand"
- "Social engineering"
detection_methods:
- "Content analysis"
- "Header analysis"
- "Natural Language Understanding"
- "Sender analysis"
id: "1f712b4c-597b-53a4-b9b8-fc3d77d9086e"