Detection rules › Sublime MQL

Spam: Sexually explicit content with emoji in subject from freemail provider

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

Detects messages from free email providers that contain sexually explicit content and include emojis in the subject line.

Threat classification

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

CategoryValues
Attack typesSpam
Tactics and techniquesFree email provider, Social engineering

Event coverage

Rule body MQL

type.inbound
// sender is a freemail domain
and sender.email.domain.root_domain in $free_email_providers
// look for commonly used emojis in sexually explicit messages
and regex.icontains(subject.subject,
                    '(\x{1F346}|\x{1F608}|\x{1F609}|\x{1F351}|\x{2764}|\x{1F60D}|\x{1F618}|\x{1F48B}|\x{1F63B}|\x{1F445}|\x{1F51E}|\x{1F525}|\x{1F4F7})'
)
and any(ml.nlu_classifier(body.current_thread.text).topics,
        .name == 'Sexually Explicit Messages'
)

Detection logic

Scope: inbound message.

Detects messages from free email providers that contain sexually explicit content and include emojis in the subject line.

  1. inbound message
  2. sender.email.domain.root_domain in $free_email_providers
  3. subject.subject matches '(\\x{1F346}|\\x{1F608}|\\x{1F609}|\\x{1F351}|\\x{2764}|\\x{1F60D}|\\x{1F618}|\\x{1F48B}|\\x{1F63B}|\\x{1F445}|\\x{1F51E}|\\x{1F525}|\\x{1F4F7})'
  4. any of ml.nlu_classifier(body.current_thread.text).topics where:
    • .name is 'Sexually Explicit Messages'

Inspects: body.current_thread.text, sender.email.domain.root_domain, subject.subject, type.inbound. Sensors: ml.nlu_classifier, regex.icontains. Reference lists: $free_email_providers.

Indicators matched (2)

FieldMatchValue
regex.icontainsregex(\x{1F346}|\x{1F608}|\x{1F609}|\x{1F351}|\x{2764}|\x{1F60D}|\x{1F618}|\x{1F48B}|\x{1F63B}|\x{1F445}|\x{1F51E}|\x{1F525}|\x{1F4F7})
ml.nlu_classifier(body.current_thread.text).topics[].nameequalsSexually Explicit Messages