Brand impersonation: Toronto-Dominion Bank

name: "Brand impersonation: Toronto-Dominion Bank"
description: "Impersonation of TD Bank or TD Canada Trust using display name spoofing or logo detection, combined with suspicious content related to security authentication or credential theft from unauthorized senders."
type: "rule"
severity: "medium"
source: |
  type.inbound
  and (
    // display name contains TD Bank
    (
      strings.ilike(strings.replace_confusables(sender.display_name), '*TD Bank*')
      or strings.ilike(strings.replace_confusables(sender.display_name),
                       '*TD Canada Trust*'
      )
      // levenshtein distance similar to TD bank
      or strings.ilevenshtein(strings.replace_confusables(sender.display_name),
                              'TD Bank'
      ) <= 1
      or strings.ilevenshtein(strings.replace_confusables(sender.display_name),
                              'TD Canada Trust'
      ) <= 1
      or any(ml.logo_detect(file.message_screenshot()).brands,
             .name == "TD Bank" and .confidence == "high"
      )
      // TD Secure Email
      or any([subject.base, sender.display_name], strings.ilike(., "*TD?Secure*"))
    )
  )
  and (
    (
      any(ml.nlu_classifier(body.current_thread.text).topics,
          .name in (
            "Security and Authentication",
            "Secure Message",
            "Reminders and Notifications"
          )
          and .confidence in ("medium", "high")
      )
      and not any(ml.nlu_classifier(body.current_thread.text).topics,
                  .name in ("Newsletters and Digests", "Entertainment and Sports")
                  and .confidence in ("medium", "high")
      )
    )
    or (
      beta.ocr(file.message_screenshot()).text != ""
      and any(ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).topics,
              .name in (
                "Security and Authentication",
                "Secure Message",
                "Reminders and Notifications"
              )
              and .confidence in ("medium", "high")
      )
      and not any(ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).topics,
                  .name in ("Newsletters and Digests", "Entertainment and Sports")
                  and .confidence in ("medium", "high")
      )
    )
    or any(ml.nlu_classifier(body.current_thread.text).intents,
           .name == "cred_theft" and .confidence == "high"
    )
    or any(ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).intents,
           .name == "cred_theft" and .confidence == "high"
    )
  )
  
  // and the sender is not in org_domains or from TD domains and passes auth
  and not (
    sender.email.domain.root_domain in $org_domains
    or (
      sender.email.domain.root_domain in (
        "td.com",
        "tdbank.com",
        "tdcanadatrust.com",
        "tdameritrade.com",
        "tdwaterhouse.ca",
        "tdwaterhouse.com",
        "tdassetmanagement.com",
        "tdinsurance.com",
        "tdautofinance.com",
        "tdautofinance.ca",
        "email-td.com",
        "feedback-td.com",
        "interac.ca"
      )
      and headers.auth_summary.dmarc.pass
    )
  )
  // and the sender is not from high trust sender root domains
  and (
    (
      sender.email.domain.root_domain in $high_trust_sender_root_domains
      and not headers.auth_summary.dmarc.pass
    )
    or sender.email.domain.root_domain not in $high_trust_sender_root_domains
  )
  and (
    not profile.by_sender().solicited
    or not headers.auth_summary.dmarc.pass
    or not headers.auth_summary.spf.pass
  )

attack_types:
  - "Credential Phishing"
tactics_and_techniques:
  - "Impersonation: Brand"
  - "Social engineering"
detection_methods:
  - "Computer Vision"
  - "Content analysis"
  - "Header analysis"
  - "Natural Language Understanding"
  - "Optical Character Recognition"
  - "Sender analysis"
id: "2dc16a55-32c0-5731-85bd-08131aa535ab"