detection.wiki

Detection rules › Sublime MQL

Spam: URL shortener with short body content and emojis

Severity
low
Type
rule
Source
github.com/sublime-security/sublime-rules

Detects spam from freemail senders, where the majority of the body is a URL shortener and emojis.

Threat classification

Sublime's own taxonomy (not MITRE ATT&CK).

CategoryValues
Attack typesSpam
Tactics and techniquesFree email provider

Event coverage

Message attribute
body
body.links (collection)
body.plain
sender.email
subject
type

Rule body MQL

type.inbound

// sender is a freemail
and sender.email.domain.root_domain in $free_email_providers

// has a URL shortener
and any(body.links,
        .href_url.domain.root_domain in $url_shorteners
        or .href_url.domain.root_domain in $social_landing_hosts
)

// short body, basically just the URL
and length(body.plain.raw) < 100

// has an emoji in the subject or body
and (
  regex.contains(body.plain.raw,
                 '[\x{1F300}-\x{1F5FF}\x{1F600}-\x{1F64F}\x{1F680}-\x{1F6FF}\x{1F700}-\x{1F77F}\x{1F780}-\x{1F7FF}\x{1F900}-\x{1F9FF}\x{2600}-\x{26FF}\x{2700}-\x{27BF}\x{2300}-\x{23FF}]'
  )
  or regex.contains(subject.subject,
                    '[\x{1F300}-\x{1F5FF}\x{1F600}-\x{1F64F}\x{1F680}-\x{1F6FF}\x{1F700}-\x{1F77F}\x{1F780}-\x{1F7FF}\x{1F900}-\x{1F9FF}\x{2600}-\x{26FF}\x{2700}-\x{27BF}\x{2300}-\x{23FF}]'
  )
)
and (
  profile.by_sender().prevalence in ("new", "outlier")
  or (
    profile.by_sender().any_messages_malicious_or_spam
    and not profile.by_sender().any_messages_benign
  )
)

Detection logic

Scope: inbound message.

Detects spam from freemail senders, where the majority of the body is a URL shortener and emojis.

  1. inbound message
  2. sender.email.domain.root_domain in $free_email_providers
  3. any of body.links where any holds:
    • .href_url.domain.root_domain in $url_shorteners
    • .href_url.domain.root_domain in $social_landing_hosts
  4. length(body.plain.raw) < 100
  5. any of:
    • body.plain.raw matches '[\\x{1F300}-\\x{1F5FF}\\x{1F600}-\\x{1F64F}\\x{1F680}-\\x{1F6FF}\\x{1F700}-\\x{1F77F}\\x{1F780}-\\x{1F7FF}\\x{1F900}-\\x{1F9FF}\\x{2600}-\\x{26FF}\\x{2700}-\\x{27BF}\\x{2300}-\\x{23FF}]'
    • subject.subject matches '[\\x{1F300}-\\x{1F5FF}\\x{1F600}-\\x{1F64F}\\x{1F680}-\\x{1F6FF}\\x{1F700}-\\x{1F77F}\\x{1F780}-\\x{1F7FF}\\x{1F900}-\\x{1F9FF}\\x{2600}-\\x{26FF}\\x{2700}-\\x{27BF}\\x{2300}-\\x{23FF}]'
  6. any of:
    • profile.by_sender().prevalence in ('new', 'outlier')
    • all of:
      • profile.by_sender().any_messages_malicious_or_spam
      • not:
        • profile.by_sender().any_messages_benign

Inspects: body.links, body.links[].href_url.domain.root_domain, body.plain.raw, sender.email.domain.root_domain, subject.subject, type.inbound. Sensors: profile.by_sender, regex.contains. Reference lists: $free_email_providers, $social_landing_hosts, $url_shorteners.

Indicators matched (1)

FieldMatchValue
regex.containsregex[\x{1F300}-\x{1F5FF}\x{1F600}-\x{1F64F}\x{1F680}-\x{1F6FF}\x{1F700}-\x{1F77F}\x{1F780}-\x{1F7FF}\x{1F900}-\x{1F9FF}\x{2600}-\x{26FF}\x{2700}-\x{27BF}\x{2300}-\x{23FF}]