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sublimehighRule

Subject: Suspicious bracketed reference

Detects messages with subject lines containing bracketed patterns that follow a specific format with repeated characters, numeric sequences, and structured tracking identifiers commonly used in malicious automated messaging systems.

MITRE ATT&CK

defense-evasioninitial-access

Detection Query

type.inbound
and strings.contains(subject.base, '[')
and strings.ends_with(subject.base, ']')
and any(regex.extract(subject.base,
                      '\[(?P<first>.)(?P<second>.)\-(?P<second_part>[^\-]+)\-(?P<third_section>[^\]]+)\]$'
        ),
        .named_groups["first"] == .named_groups["second"]
        and regex.match(.named_groups["second_part"], '^\d+$')
        and regex.contains(.named_groups["third_section"], '\d+$')
        and strings.istarts_with(.named_groups["third_section"],
                                 .named_groups["first"]
        )
)

Data Sources

Email MessagesEmail HeadersEmail Attachments

Platforms

email
Raw Content
name: "Subject: Suspicious bracketed reference"
description: "Detects messages with subject lines containing bracketed patterns that follow a specific format with repeated characters, numeric sequences, and structured tracking identifiers commonly used in malicious automated messaging systems."
type: "rule"
severity: "high"
source: |
  type.inbound
  and strings.contains(subject.base, '[')
  and strings.ends_with(subject.base, ']')
  and any(regex.extract(subject.base,
                        '\[(?P<first>.)(?P<second>.)\-(?P<second_part>[^\-]+)\-(?P<third_section>[^\]]+)\]$'
          ),
          .named_groups["first"] == .named_groups["second"]
          and regex.match(.named_groups["second_part"], '^\d+$')
          and regex.contains(.named_groups["third_section"], '\d+$')
          and strings.istarts_with(.named_groups["third_section"],
                                   .named_groups["first"]
          )
  )
attack_types:
  - "Credential Phishing"
tactics_and_techniques:
  - "Evasion"
  - "Impersonation: Brand"
detection_methods:
  - "Header analysis"
  - "Content analysis"
id: "663dbce4-0403-5baf-bf30-45c38a09f9c7"