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