Detection rules › Sublime MQL

Recruitee Infrastructure Abuse

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

Identifies inbound messages from Recruitee domains containing recruitment-related topics and application links, where the sender has limited prior history. The URLs in these messages either point to recently registered domains or appear as standalone links with application-focused text.

Threat classification

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

CategoryValues
Attack typesBEC/Fraud, Credential Phishing
Tactics and techniquesImpersonation: Brand, Social engineering

Event coverage

Rule body MQL

type.inbound
and sender.email.domain.root_domain == "recruitee.com"
and any(beta.ml_topic(body.current_thread.text).topics,
        .name in (
          "Advertising and Promotions",
          "Professional and Career Development"
        )
        and .confidence != "low"
)
and any(body.links,
        (
          network.whois(.href_url.domain).days_old < 30
          or length(body.links) == 1
        )
        and regex.icontains(.display_text, "apply|submit")
)
// use sender email, not domain, to ensure new *.recruitee.com addresses are correctly identified
and profile.by_sender_email().prevalence in ("new", "outlier")
and not profile.by_sender_email().any_messages_benign

Detection logic

Scope: inbound message.

Identifies inbound messages from Recruitee domains containing recruitment-related topics and application links, where the sender has limited prior history. The URLs in these messages either point to recently registered domains or appear as standalone links with application-focused text.

  1. inbound message
  2. sender.email.domain.root_domain is 'recruitee.com'
  3. any of beta.ml_topic(body.current_thread.text).topics where all hold:
    • .name in ('Advertising and Promotions', 'Professional and Career Development')
    • .confidence is not 'low'
  4. any of body.links where all hold:
    • any of:
      • network.whois(.href_url.domain).days_old < 30
      • length(body.links) is 1
    • .display_text matches 'apply|submit'
  5. profile.by_sender_email().prevalence in ('new', 'outlier')
  6. not:
    • profile.by_sender_email().any_messages_benign

Inspects: body.current_thread.text, body.links, body.links[].display_text, body.links[].href_url.domain, sender.email.domain.root_domain, type.inbound. Sensors: beta.ml_topic, network.whois, profile.by_sender_email, regex.icontains.

Indicators matched (4)

FieldMatchValue
sender.email.domain.root_domainequalsrecruitee.com
beta.ml_topic(body.current_thread.text).topics[].namememberAdvertising and Promotions
beta.ml_topic(body.current_thread.text).topics[].namememberProfessional and Career Development
regex.icontainsregexapply|submit