Link: Multistage Landing - Scribd Document

type.inbound
// only one link to Scribd
and length(distinct(filter(body.links,
                           .href_url.domain.root_domain in ("scribd.com")
                           and strings.istarts_with(.href_url.path, "/document")
                    ),
                    .href_url.url
           )
) == 1
and any(body.links,
        .href_url.domain.root_domain == "scribd.com"
        and strings.istarts_with(.href_url.path, "/document")
        and (
          // target the embedded links via XPath
          any(html.xpath(ml.link_analysis(.).final_dom,
                              '//a[@class="ll"]/@href'
              ).nodes,
              strings.parse_url(.raw).domain.tld in $suspicious_tlds
              or strings.parse_url(.raw).domain.domain in $free_subdomain_hosts
              or strings.parse_url(.raw).domain.root_domain in $free_subdomain_hosts
              // observed pattern in credential theft URLs
              or strings.ilike(strings.parse_url(.raw).path,
                               "*o365*",
                               "*office365*",
                               "*microsoft*"
              )
              // observed pattern in credential theft URLs
              or strings.ilike(strings.parse_url(.raw).query_params,
                               "*o365*",
                               "*office365*",
                               "*microsoft*"
              )
              // observed pattern in credential theft URLs
              or any(beta.scan_base64(strings.parse_url(.raw).query_params),
                     strings.ilike(., "*o365*", "*office365*", "*microsoft*")
              )
              or ml.link_analysis(strings.parse_url(.raw), mode="aggressive").credphish.disposition == "phishing"
              or ml.link_analysis(strings.parse_url(.raw), mode="aggressive").credphish.contains_captcha
              or strings.icontains(ml.link_analysis(strings.parse_url(.raw),
                                                    mode="aggressive"
                                   ).final_dom.display_text,
                                   "I'm Human"
              )
              // bails out to a well-known domain, seen in evasion attempts
              or (
                length(ml.link_analysis(strings.parse_url(.raw),
                                        mode="aggressive"
                       ).redirect_history
                ) > 0
                and ml.link_analysis(strings.parse_url(.raw), mode="aggressive").effective_url.domain.root_domain in $tranco_10k
              )
          )
          // credential theft language on the main Scribd page
          or any(ml.nlu_classifier(beta.ocr(ml.link_analysis(.,
                                                             mode="aggressive"
                                            ).screenshot
                                   ).text
                 ).intents,
                 .name == "cred_theft" and .confidence != "low"
          )
        )
)
// negate highly trusted sender domains unless they fail DMARC authentication
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
)