Attachment: Microsoft 365 credential phishing

  1name: "Attachment: Microsoft 365 credential phishing"
  2description: |
  3    Looks for messages with an image attachment that contains words related to Microsoft, Office365, and passwords.
  4type: "rule"
  5severity: "high"
  6source: |
  7  type.inbound
  8  and length(filter(attachments, .file_type not in $file_types_images)) == 0
  9  and (
 10    any(attachments,
 11        .file_type in $file_types_images
 12        and any(ml.logo_detect(.).brands, strings.starts_with(.name, "Microsoft"))
 13    )
 14    or any(attachments,
 15           .file_type in $file_types_images
 16           and any(file.explode(.),
 17                   strings.ilike(.scan.ocr.raw, "*microsoft*", "*office")
 18                   and length(.scan.ocr.raw) < 1500
 19           )
 20    )
 21  )
 22  and any(attachments,
 23          .file_type in $file_types_images
 24          and any(file.explode(.),
 25                  length(filter([
 26                                  "password",
 27                                  "unread messages",
 28                                  "Shared Documents",
 29                                  "expiration",
 30                                  "expire",
 31                                  "expiring",
 32                                  "kindly",
 33                                  "renew",
 34                                  "review",
 35                                  "emails failed",
 36                                  "kicked out",
 37                                  "prevented",
 38                                  "storage",
 39                                  "required now",
 40                                  "cache",
 41                                  "qr code",
 42                                  "security update",
 43                                  "invoice",
 44                                  "retrieve",
 45                                  "blocked"
 46                                ],
 47                                strings.icontains(..scan.ocr.raw, .)
 48                         )
 49                  ) >= 2
 50                  or (
 51                    any(ml.nlu_classifier(.scan.ocr.raw).intents,
 52                        .name == "cred_theft" and .confidence == "high"
 53                    )
 54                    and length(ml.nlu_classifier(.scan.ocr.raw).entities) > 1
 55                  )
 56          )
 57  )
 58  and (
 59    not any(headers.hops,
 60            .authentication_results.compauth.verdict is not null
 61            and .authentication_results.compauth.verdict == "pass"
 62            and sender.email.domain.domain in (
 63              "microsoft.com",
 64              "sharepointonline.com"
 65            )
 66    )
 67  )
 68  
 69  // negate angelbeat urls and microsoft disclaimer links
 70  and (
 71    length(body.links) > 0
 72    and not all(body.links,
 73                .href_url.domain.root_domain in (
 74                  "abeatinfo.com",
 75                  "abeatinvite.com",
 76                  "aka.ms",
 77                  "angelbeat.com"
 78                )
 79    )
 80  )
 81  
 82  // negate replies
 83  and (
 84    (
 85      (
 86        length(headers.references) > 0
 87        or not any(headers.hops,
 88                   any(.fields, strings.ilike(.name, "In-Reply-To"))
 89        )
 90      )
 91      and not (
 92        (
 93          strings.istarts_with(subject.subject, "RE:")
 94          or strings.istarts_with(subject.subject, "R:")
 95          or strings.istarts_with(subject.subject, "ODG:")
 96          or strings.istarts_with(subject.subject, "答复:")
 97          or strings.istarts_with(subject.subject, "AW:")
 98          or strings.istarts_with(subject.subject, "TR:")
 99          or strings.istarts_with(subject.subject, "FWD:")
100          or regex.icontains(subject.subject,
101                             '^(\[[^\]]+\]\s?){0,3}(re|fwd?)\s?:'
102          )
103        )
104      )
105    )
106    or length(headers.references) == 0
107  )
108  and (
109    not profile.by_sender().solicited
110    or (
111      profile.by_sender().any_messages_malicious_or_spam
112      and not profile.by_sender().any_messages_benign
113    )
114  )
115  
116  // negate highly trusted sender domains unless they fail DMARC authentication
117  and (
118    (
119      sender.email.domain.root_domain in $high_trust_sender_root_domains
120      and not headers.auth_summary.dmarc.pass
121    )
122    or sender.email.domain.root_domain not in $high_trust_sender_root_domains
123  )
124  and not profile.by_sender().any_messages_benign  
125attack_types:
126  - "Credential Phishing"
127tactics_and_techniques:
128  - "Impersonation: Brand"
129  - "Social engineering"
130detection_methods:
131  - "Content analysis"
132  - "File analysis"
133  - "Header analysis"
134  - "Optical Character Recognition"
135  - "Sender analysis"
136id: "edce0229-5e8f-5359-a5c8-36570840049f"