Request for Quote or Purchase (RFQ|RFP) with suspicious sender or recipient pattern

RFQ/RFP scams involve fraudulent emails posing as legitimate requests for quotations or purchases, often sent by scammers impersonating reputable organizations. These scams aim to deceive recipients into providing sensitive information or conducting unauthorized transactions, often leading to financial loss, or data leakage.

Sublime rule (View on GitHub)

  1name: "Request for Quote or Purchase (RFQ|RFP) with suspicious sender or recipient pattern"
  2description: |
  3  RFQ/RFP scams involve fraudulent emails posing as legitimate requests for quotations or purchases, often sent by scammers impersonating reputable organizations.
  4  These scams aim to deceive recipients into providing sensitive information or conducting unauthorized transactions, often leading to financial loss, or data leakage.  
  5type: "rule"
  6severity: "medium"
  7source: |
  8  type.inbound
  9  and (
 10    (
 11      (
 12        length(recipients.to) == 0
 13        or all(recipients.to,
 14               .display_name in (
 15                 "Undisclosed recipients",
 16                 "undisclosed-recipients"
 17               )
 18        )
 19      )
 20      and length(recipients.cc) == 0
 21    )
 22    or (
 23      sender.email.domain.root_domain in $free_email_providers
 24      and any(headers.reply_to, .email.email != sender.email.email)
 25      and any(headers.reply_to, .email.email not in $recipient_emails)
 26    )
 27    or (
 28      length(headers.reply_to) > 0
 29      and all(headers.reply_to,
 30              .email.domain.root_domain != sender.email.domain.root_domain
 31              and not .email.domain.root_domain in $org_domains
 32      )
 33    )
 34    or (
 35      length(recipients.to) == 1
 36      and all(recipients.to, .email.email == sender.email.email)
 37      and (length(recipients.cc) > 0 or length(recipients.bcc) > 0)
 38    )
 39    or (
 40      length(recipients.to) == 0
 41      and length(recipients.cc) == 1
 42      and sender.email.email == recipients.cc[0].email.email
 43    )
 44    or (
 45      length(recipients.to) == 1
 46      and length(recipients.cc) == 0
 47      and sender.email.email == recipients.to[0].email.email
 48    )
 49  )
 50  and (
 51    // Group the keyword patterns that specifically indicate RFQ/RFP
 52    (
 53      (
 54        // RFQ/RFP specific language patterns
 55        regex.icontains(body.current_thread.text,
 56                        '(discuss.{0,15}purchas(e|ing))'
 57        )
 58        or regex.icontains(body.current_thread.text,
 59                           '(sign(ed?)|view).{0,10}(purchase order)|Request for (a Quot(e|ation)|Proposal)'
 60        )
 61        or regex.icontains(body.current_thread.text,
 62                           '(please|kindly|preferred).{0,30}(?:proposal|quot(e|ation))'
 63        )
 64        or regex.icontains(subject.subject,
 65                           '(request for (purchase|quot(e|ation))|\bRFQ\b|\bRFP\b|bid invit(e|ation))'
 66        )
 67        or any(attachments,
 68               regex.icontains(.file_name, "(purchase.?order|Quot(e|ation))")
 69        )
 70        or any(ml.nlu_classifier(body.current_thread.text).tags,
 71               .name == "purchase_order" and .confidence == "high"
 72        )
 73        or any(ml.nlu_classifier(body.current_thread.text).entities,
 74               .name == "financial" and regex.imatch(.text, "rfp|rfq")
 75        )
 76        or any(ml.nlu_classifier(body.current_thread.text).entities,
 77               .name == "request" and strings.icontains(.text, 'submit bid')
 78        )
 79      )
 80      // Required: at least one RFQ/RFP keyword pattern
 81  
 82      // Optional: at least one additional indicator (can be another keyword pattern or a non-keyword indicator)
 83      and (
 84        2 of (
 85          // RFQ/RFP keyword patterns (same as above)
 86          regex.icontains(body.current_thread.text,
 87                          '(discuss.{0,15}purchas(e|ing))'
 88          ),
 89          regex.icontains(body.current_thread.text,
 90                          '(sign(ed?)|view).{0,10}(purchase order)|Request for a Quot(e|ation)'
 91          ),
 92          regex.icontains(body.current_thread.text,
 93                          '(please|kindly|preferred).{0,30}(?:proposal|quot(e|ation))'
 94          ),
 95          regex.icontains(body.current_thread.text,
 96                          '(?:invitation|intent) to bid'
 97          ),
 98          regex.icontains(subject.subject,
 99                          '(request for (purchase|quot(e|ation))|\bRFQ\b|\bRFP\b|bid invit(e|ation))'
100          ),
101          any(attachments,
102              regex.icontains(.file_name, "(purchase.?order|Quot(e|ation))")
103          ),
104          any(ml.nlu_classifier(body.current_thread.text).tags,
105              .name == "purchase_order" and .confidence == "high"
106          ),
107          any(ml.nlu_classifier(body.current_thread.text).entities,
108              .name == "financial" and regex.imatch(.text, "(?:rfp|rfq)")
109          ),
110          any(attachments,
111              any(file.explode(.),
112                  any(ml.nlu_classifier(.scan.ocr.raw).entities,
113                      .name == "request"
114                      and regex.imatch(.text, "view (?:rfp|rfq)")
115                  )
116              )
117          ),
118  
119          // Non-keyword indicators
120          (
121            any(ml.nlu_classifier(body.current_thread.text).entities,
122                .name == "request"
123            )
124            and any(ml.nlu_classifier(body.current_thread.text).entities,
125                    .name == "urgency"
126            )
127            and not any(ml.nlu_classifier(body.current_thread.text).topics,
128                        .name == "Advertising and Promotions"
129                        and .confidence == "high"
130            )
131          ),
132          (
133            0 < length(filter(body.links,
134                              (
135                                .href_url.domain.domain in $free_subdomain_hosts
136                                or .href_url.domain.domain in $free_file_hosts
137                                or network.whois(.href_url.domain).days_old < 30
138                              )
139                              and (
140                                regex.match(.display_text, '[A-Z ]+')
141                                or any(ml.nlu_classifier(.display_text).entities,
142                                       .name in ("request", "urgency")
143                                )
144                                or any(ml.nlu_classifier(.display_text).intents,
145                                       .name in ("cred_theft")
146                                )
147                              )
148                       )
149            ) < 3
150          ),
151          // mentions an attachment that does not exist
152          (
153            length(attachments) == 0
154            and strings.icontains(body.current_thread.text, "attached")
155          ),
156          any(body.current_thread.links, regex.icontains(.href_url.url, 'RFP'))
157        )
158      )
159    )
160    or (
161      length(attachments) == 1
162      and length(body.current_thread.text) < 100
163      and all(attachments,
164              .file_type in $file_types_images
165              and any(file.explode(.),
166                      2 of (
167                        regex.icontains(.scan.ocr.raw,
168                                        '(discuss.{0,15}purchas(e|ing))'
169                        ),
170                        regex.icontains(.scan.ocr.raw,
171                                        '(sign(ed?)|view).{0,10}(purchase order)|Request for a Quot(e|ation)'
172                        ),
173                        regex.icontains(.scan.ocr.raw,
174                                        '(please|kindly).{0,30}quote'
175                        ),
176                        (
177                          any(ml.nlu_classifier(.scan.ocr.raw).entities,
178                              .name == "request"
179                          )
180                          and any(ml.nlu_classifier(.scan.ocr.raw).entities,
181                                  .name == "urgency"
182                          )
183                        ),
184                        any(ml.nlu_classifier(.scan.ocr.raw).tags,
185                            .name == "purchase_order" and .confidence == "high"
186                        ),
187                        any(ml.nlu_classifier(.scan.ocr.raw).entities,
188                            .name == "financial"
189                            and regex.imatch(.text, "rfp|rfq")
190                        ),
191                      )
192              )
193      )
194    )
195    // fake PDF file icon used as a link lure with bid solicitation language
196    or (
197      regex.icontains(subject.subject, 'project\s+summary')
198      and any(html.xpath(body.html, '//div[.//img[contains(@src,"pdf")]]//a').nodes,
199              regex.icontains(.display_text, 'project\s+summary')
200      )
201      and regex.icontains(body.current_thread.text,
202                          '(put a bid|\bbid\s+(for|on)\b|submit.{1,20}(bid|quot(e|ation))|request for (purchase|quot(e|ation))|\bRFQ\b|\bRFP\b|project\s+summary)'
203      )
204    )
205  )
206  // wetransfer includes user specific reply-to's & link display text which triggers NLU logic further within the rule
207  and not (
208    sender.email.domain.root_domain == "wetransfer.com"
209    and coalesce(headers.auth_summary.dmarc.pass, false)
210  )
211  
212  // negate highly trusted sender domains unless they fail DMARC authentication
213  and (
214    (
215      sender.email.domain.root_domain in $high_trust_sender_root_domains
216      and not headers.auth_summary.dmarc.pass
217    )
218    or sender.email.domain.root_domain not in $high_trust_sender_root_domains
219  )
220  and (
221    (
222      (
223        not profile.by_sender().solicited
224        or profile.by_sender().days_since.last_contact > 30
225      )
226      and not profile.by_sender().any_messages_benign
227    )
228    // sender address listed as a recipient
229    or (
230      length(recipients.to) == 1
231      and sender.email.email in map(recipients.to, .email.email)
232    )
233  )  
234attack_types:
235  - "BEC/Fraud"
236tactics_and_techniques:
237  - "Evasion"
238  - "Free email provider"
239detection_methods:
240  - "Content analysis"
241  - "Natural Language Understanding"
242  - "URL analysis"
243id: "2ac0d329-c1fb-5c87-98dd-ea3e5b85377a"
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