Brand impersonation: Netflix

name: "Brand impersonation: Netflix"
description: |
  Impersonation of Netflix.
references:
  - "https://news.trendmicro.com/2023/01/18/netflix-scams-2023-job-text-email/"
type: "rule"
severity: "low"
authors:
  - name: "min0k"
source: |
  type.inbound
  and (
    // obfuscated sender display name
    (
      sender.display_name is not null
      and (
        regex.icontains(strings.replace_confusables(sender.display_name),
                        '[nm]etf[li][il]x'
        )
        or strings.ilevenshtein(strings.replace_confusables(sender.display_name),
                                'netflix'
        ) <= 1
        or regex.icontains(strings.replace_confusables(sender.display_name),
                           'n.{0,3}e.{0,3}t.{0,3}f.{0,3}l.{0,3}i.{0,3}x.{0,3}'
        )
      )
    )
    // obfuscated sender email domain
    or regex.icontains(strings.replace_confusables(sender.email.domain.domain),
                       '[nm]etf[li][il]x'
    )
    // logo detection on message screenshot (no link analysis)
    or (
      any(ml.logo_detect(file.message_screenshot()).brands,
          .name == "Netflix" and .confidence in ("medium", "high")
      )
      and (
        // non NLU based keywords on the screenshot
        regex.icontains(beta.ocr(file.message_screenshot()).text,
                        'suspen(?:ded|sion)'
        )
        or 
        // combo of NLU cred_theft + financial + Customer Service and Support
        (
          any(ml.nlu_classifier(body.current_thread.text).intents,
              .name == "cred_theft"
          )
          and any(ml.nlu_classifier(body.current_thread.text).entities,
                  .name == "financial"
          )
          and any(ml.nlu_classifier(body.current_thread.text).topics,
                  .name == "Customer Service and Support"
          )
        )
      )
    )
    // Address Detection
    or 2 of (
      strings.icontains(body.current_thread.text, 'Netflix, Inc'),
      strings.icontains(body.current_thread.text, '100 Winchester Circle'),
      strings.icontains(body.current_thread.text, 'Los Gatos, CA 95032')
    )
    // unusual recipient pattern + logo detect + credphish dispoistion
    or (
      (
        length(recipients.to) == 0
        or (
          all(recipients.to, .email.domain.valid == false)
          and all(recipients.cc, .email.domain.valid == false)
        )
      )
      and any(ml.logo_detect(file.message_screenshot()).brands,
              .name == "Netflix" and .confidence in ("medium", "high")
      )
      and (
        any(body.links,
            ml.link_analysis(.).credphish.disposition == "phishing"
            and ml.link_analysis(.).credphish.confidence in ("medium", "high")
        )
      )
    )
  )
  // negation of legit domains
  and not (
    sender.email.domain.root_domain in (
      'netflix.com',
      'dvd.com',
      'netflixfamily.com',
      'netflixpreviewclub.com',
      'netflixanimation.com',
      'envoy.com',
      'lexisnexis.com',
      'netflix.shop',
      'netflixcontractors.com', // owned by netflix
      'netflixevents.com', // owned by netflix
      'netelixir.com', // unrelated marketing
      'netflixhouse.com', // owned by netflix
      'instagram.com',
      'netflix.net',
      'netflixshopsupport.com', // owned by netflix
      'netflixpartner.com', // owned by netflix
    )
    and coalesce(headers.auth_summary.dmarc.pass, false)
  )
  and not (
    sender.email.domain.domain in (
      'netflix.zendesk.com' // netflix actual support
    )
    and coalesce(headers.auth_summary.dmarc.pass, false)
  )
  and not profile.by_sender_email().solicited
attack_types:
  - "Credential Phishing"
tactics_and_techniques:
  - "Impersonation: Brand"
  - "Lookalike domain"
  - "Social engineering"
detection_methods:
  - "Header analysis"
  - "Sender analysis"
id: "9f39eea5-2edf-524d-b68b-d8d0bdb74273"