[PR #3477] added rule: Brand impersonation: Adobe with suspicious language and link

Author: github-actions[bot]

detection-rules/3477_impersonation_adobe_suspicious_language_link.yml

@@ -0,0 +1,153 @@
+name: "Brand impersonation: Adobe with suspicious language and link"
+description: "Email contains an Adobe logo, at least one link, and suspicious link language from a new sender."
+type: "rule"
+severity: "high"
+source: |
+  type.inbound
+  // all attachments are images or 0 attachments
+  and (
+    (
+      length(attachments) > 0
+      and all(attachments, .file_type in $file_types_images)
+    )
+    or length(attachments) == 0
+  )
+  and length(body.links) > 0
+  and (
+    any(ml.logo_detect(file.message_screenshot()).brands,
+        .name == "Adobe" and .confidence in ("high")
+    )
+    or (
+      strings.icontains(body.current_thread.text, "adobe")
+      and (
+        // leverage topic analysis to pick up on themes
+        (
+          length(ml.nlu_classifier(body.current_thread.text).topics) == 1
+          and all(ml.nlu_classifier(body.current_thread.text).topics,
+                  .name == "File Sharing and Cloud Services"
+                  and .confidence != "low"
+          )
+        )
+        // keywords if topic anlayis doesn't match
+        or strings.icontains(body.current_thread.text, 'review the document')
+        or strings.icontains(body.current_thread.text, 'review and sign')
+        or strings.icontains(body.current_thread.text, 'access file')
+        or strings.icontains(body.current_thread.text, 'pending document')
+      )
+      and length(body.current_thread.text) < 2000
+    )
+  )
+  and (
+    (
+      //
+      // This rule makes use of a beta feature and is subject to change without notice
+      // using the beta feature in custom rules is not suggested until it has been formally released
+      //
+      strings.ilike(beta.ocr(file.message_screenshot()).text,
+                    "*review*",
+                    "*sign*",
+                    "*view*",
+                    "open",
+                    "*completed document*",
+                    "*open agreement*",
+                    "*open document*"
+      )
+      and not strings.ilike(beta.ocr(file.message_screenshot()).text,
+                            "*view this email*",
+                            "*view*browser*",
+                            "*view online*",
+                            "*business review*"
+      )
+    )
+    or any(body.links,
+           strings.ilike(.display_text,
+                         "*review*",
+                         "*sign*",
+                         "*view*",
+                         "open",
+                         "*completed document*",
+                         "*open agreement*",
+                         "*open document*",
+                         "*continue*"
+           )
+           and not strings.ilike(.display_text,
+                                 "*view this email*",
+                                 "*view*browser*",
+                                 "*view online*"
+           )
+    )
+  )
+  and (
+    (
+      (
+        length(headers.references) > 0
+        or not any(headers.hops,
+                   any(.fields, strings.ilike(.name, "In-Reply-To"))
+        )
+      )
+      and not (
+        (
+          strings.istarts_with(subject.subject, "RE:")
+          or strings.istarts_with(subject.subject, "RES:")
+          or strings.istarts_with(subject.subject, "R:")
+          or strings.istarts_with(subject.subject, "ODG:")
+          or strings.istarts_with(subject.subject, "答复:")
+          or strings.istarts_with(subject.subject, "AW:")
+          or strings.istarts_with(subject.subject, "TR:")
+          or strings.istarts_with(subject.subject, "FWD:")
+          or regex.imatch(subject.subject,
+                          '^\[?/{0,2}(EXT|EXTERNAL)\]?/{0,2}[: ]\s*(RE|FWD?|FW|AW|TR|ODG|答复):.*'
+          )
+        )
+      )
+    )
+    or length(headers.references) == 0
+  )
+  and not any(ml.nlu_classifier(body.current_thread.text).topics,
+              .name in ("Advertising and Promotions", "Events and Webinars")
+              and .confidence != "low"
+  )
+  and (
+    (
+      headers.auth_summary.spf.pass
+      and headers.auth_summary.dmarc.pass
+      and (
+        not profile.by_sender().solicited
+        or profile.by_sender().any_messages_malicious_or_spam
+        or profile.by_sender_email().days_since.last_contact > 14
+      )
+      and not profile.by_sender().any_messages_benign
+      and not sender.email.domain.root_domain in (
+        "adobe-events.com",
+        "frame.io",
+        "workfront.com"
+      )
+    )
+    or not headers.auth_summary.spf.pass
+    or headers.auth_summary.spf.pass is null
+    or not headers.auth_summary.dmarc.pass
+    or headers.auth_summary.dmarc.pass is null
+  )
+  // 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
+  )
+
+attack_types:
+  - "Credential Phishing"
+tactics_and_techniques:
+  - "Impersonation: Brand"
+  - "Social engineering"
+detection_methods:
+  - "Computer Vision"
+  - "Content analysis"
+  - "Header analysis"
+  - "Sender analysis"
+id: "ef29ca07-95f6-5b35-9845-b7222394a146"
+og_id: "32cc8bf1-f4d7-549f-a970-eade24b7c6ae"
+testing_pr: 3477
+testing_sha: 3906e4a4bcf5b118eed91aad5e7df4df653ff8b9