Detection rules › Sublime MQL
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.
Threat classification
Sublime's own taxonomy (not MITRE ATT&CK).
| Category | Values |
|---|---|
| Attack types | BEC/Fraud |
| Tactics and techniques | Evasion, Free email provider |
Event coverage
Rule body MQL
type.inbound
and (
(
(
length(recipients.to) == 0
or all(recipients.to,
.display_name in (
"Undisclosed recipients",
"undisclosed-recipients"
)
)
)
and length(recipients.cc) == 0
)
or (
sender.email.domain.root_domain in $free_email_providers
and any(headers.reply_to, .email.email != sender.email.email)
and any(headers.reply_to, .email.email not in $recipient_emails)
)
or (
length(headers.reply_to) > 0
and all(headers.reply_to,
.email.domain.root_domain != sender.email.domain.root_domain
and not .email.domain.root_domain in $org_domains
)
)
or (
length(recipients.to) == 1
and all(recipients.to, .email.email == sender.email.email)
and (length(recipients.cc) > 0 or length(recipients.bcc) > 0)
)
or (
length(recipients.to) == 0
and length(recipients.cc) == 1
and sender.email.email == recipients.cc[0].email.email
)
or (
length(recipients.to) == 1
and length(recipients.cc) == 0
and sender.email.email == recipients.to[0].email.email
)
)
and (
// Group the keyword patterns that specifically indicate RFQ/RFP
(
(
// RFQ/RFP specific language patterns
regex.icontains(body.current_thread.text,
'(discuss.{0,15}purchas(e|ing))'
)
or regex.icontains(body.current_thread.text,
'(sign(ed?)|view).{0,10}(purchase order)|Request for (a Quot(e|ation)|Proposal)'
)
or regex.icontains(body.current_thread.text,
'(please|kindly).{0,30}(?:proposal|quot(e|ation))'
)
or regex.icontains(subject.subject,
'(request for (purchase|quot(e|ation))|\bRFQ\b|\bRFP\b|bid invit(e|ation))'
)
or any(attachments,
regex.icontains(.file_name, "(purchase.?order|Quot(e|ation))")
)
or any(ml.nlu_classifier(body.current_thread.text).tags,
.name == "purchase_order" and .confidence == "high"
)
or any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "financial" and regex.imatch(.text, "rfp|rfq")
)
or any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "request" and strings.icontains(.text, 'submit bid')
)
)
// Required: at least one RFQ/RFP keyword pattern
// Optional: at least one additional indicator (can be another keyword pattern or a non-keyword indicator)
and (
2 of (
// RFQ/RFP keyword patterns (same as above)
regex.icontains(body.current_thread.text,
'(discuss.{0,15}purchas(e|ing))'
),
regex.icontains(body.current_thread.text,
'(sign(ed?)|view).{0,10}(purchase order)|Request for a Quot(e|ation)'
),
regex.icontains(body.current_thread.text,
'(please|kindly).{0,30}(?:proposal|quot(e|ation))'
),
regex.icontains(body.current_thread.text,
'(?:invitation|intent) to bid'
),
regex.icontains(subject.subject,
'(request for (purchase|quot(e|ation))|\bRFQ\b|\bRFP\b|bid invit(e|ation))'
),
any(attachments,
regex.icontains(.file_name, "(purchase.?order|Quot(e|ation))")
),
any(ml.nlu_classifier(body.current_thread.text).tags,
.name == "purchase_order" and .confidence == "high"
),
any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "financial" and regex.imatch(.text, "rfp|rfq")
),
// Non-keyword indicators
(
any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "request"
)
and any(ml.nlu_classifier(body.current_thread.text).entities,
.name == "urgency"
)
and not any(ml.nlu_classifier(body.current_thread.text).topics,
.name == "Advertising and Promotions"
and .confidence == "high"
)
),
(
0 < length(filter(body.links,
(
.href_url.domain.domain in $free_subdomain_hosts
or .href_url.domain.domain in $free_file_hosts
or network.whois(.href_url.domain).days_old < 30
)
and (
regex.match(.display_text, '[A-Z ]+')
or any(ml.nlu_classifier(.display_text).entities,
.name in ("request", "urgency")
)
or any(ml.nlu_classifier(.display_text).intents,
.name in ("cred_theft")
)
)
)
) < 3
),
// mentions an attachment that does not exist
(
length(attachments) == 0
and strings.icontains(body.current_thread.text, "attached")
),
any(body.current_thread.links, regex.icontains(.href_url.url, 'RFP'))
)
)
)
or (
length(attachments) == 1
and length(body.current_thread.text) < 100
and all(attachments,
.file_type in $file_types_images
and any(file.explode(.),
2 of (
regex.icontains(.scan.ocr.raw,
'(discuss.{0,15}purchas(e|ing))'
),
regex.icontains(.scan.ocr.raw,
'(sign(ed?)|view).{0,10}(purchase order)|Request for a Quot(e|ation)'
),
regex.icontains(.scan.ocr.raw,
'(please|kindly).{0,30}quote'
),
(
any(ml.nlu_classifier(.scan.ocr.raw).entities,
.name == "request"
)
and any(ml.nlu_classifier(.scan.ocr.raw).entities,
.name == "urgency"
)
),
any(ml.nlu_classifier(.scan.ocr.raw).tags,
.name == "purchase_order" and .confidence == "high"
),
any(ml.nlu_classifier(.scan.ocr.raw).entities,
.name == "financial"
and regex.imatch(.text, "rfp|rfq")
),
)
)
)
)
// fake PDF file icon used as a link lure with bid solicitation language
or (
regex.icontains(subject.subject, 'project\s+summary')
and any(html.xpath(body.html, '//div[.//img[contains(@src,"pdf")]]//a').nodes,
regex.icontains(.display_text, 'project\s+summary')
)
and regex.icontains(body.current_thread.text,
'(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)'
)
)
)
// wetransfer includes user specific reply-to's & link display text which triggers NLU logic further within the rule
and not (
sender.email.domain.root_domain == "wetransfer.com"
and coalesce(headers.auth_summary.dmarc.pass, false)
)
// 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
)
and (
(
(
not profile.by_sender().solicited
or profile.by_sender().days_since.last_contact > 30
)
and not profile.by_sender().any_messages_benign
)
// sender address listed as a recipient
or (
length(recipients.to) == 1
and sender.email.email in map(recipients.to, .email.email)
)
)
Detection logic
Scope: inbound message.
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.
- inbound message
any of:
all of:
any of:
- length(recipients.to) is 0
all of
recipients.towhere:- .display_name in ('Undisclosed recipients', 'undisclosed-recipients')
- length(recipients.cc) is 0
all of:
- sender.email.domain.root_domain in $free_email_providers
any of
headers.reply_towhere:- .email.email is not sender.email.email
any of
headers.reply_towhere:- .email.email not in $recipient_emails
all of:
- length(headers.reply_to) > 0
all of
headers.reply_towhere all hold:- .email.domain.root_domain is not sender.email.domain.root_domain
not:
- .email.domain.root_domain in $org_domains
all of:
- length(recipients.to) is 1
all of
recipients.towhere:- .email.email is sender.email.email
any of:
- length(recipients.cc) > 0
- length(recipients.bcc) > 0
all of:
- length(recipients.to) is 0
- length(recipients.cc) is 1
- sender.email.email is recipients.cc[0].email.email
all of:
- length(recipients.to) is 1
- length(recipients.cc) is 0
- sender.email.email is recipients.to[0].email.email
any of:
all of:
any of:
- body.current_thread.text matches '(discuss.{0,15}purchas(e|ing))'
- body.current_thread.text matches '(sign(ed?)|view).{0,10}(purchase order)|Request for (a Quot(e|ation)|Proposal)'
- body.current_thread.text matches '(please|kindly).{0,30}(?:proposal|quot(e|ation))'
- subject.subject matches '(request for (purchase|quot(e|ation))|\\bRFQ\\b|\\bRFP\\b|bid invit(e|ation))'
any of
attachmentswhere:- .file_name matches '(purchase.?order|Quot(e|ation))'
any of
ml.nlu_classifier(body.current_thread.text).tagswhere all hold:- .name is 'purchase_order'
- .confidence is 'high'
any of
ml.nlu_classifier(body.current_thread.text).entitieswhere all hold:- .name is 'financial'
- .text matches 'rfp|rfq'
any of
ml.nlu_classifier(body.current_thread.text).entitieswhere all hold:- .name is 'request'
- .text contains 'submit bid'
at least 2 of:
- body.current_thread.text matches '(discuss.{0,15}purchas(e|ing))'
- body.current_thread.text matches '(sign(ed?)|view).{0,10}(purchase order)|Request for a Quot(e|ation)'
- body.current_thread.text matches '(please|kindly).{0,30}(?:proposal|quot(e|ation))'
- body.current_thread.text matches '(?:invitation|intent) to bid'
- subject.subject matches '(request for (purchase|quot(e|ation))|\\bRFQ\\b|\\bRFP\\b|bid invit(e|ation))'
any of
attachmentswhere:- .file_name matches '(purchase.?order|Quot(e|ation))'
any of
ml.nlu_classifier(body.current_thread.text).tagswhere all hold:- .name is 'purchase_order'
- .confidence is 'high'
any of
ml.nlu_classifier(body.current_thread.text).entitieswhere all hold:- .name is 'financial'
- .text matches 'rfp|rfq'
all of:
any of
ml.nlu_classifier(body.current_thread.text).entitieswhere:- .name is 'request'
any of
ml.nlu_classifier(body.current_thread.text).entitieswhere:- .name is 'urgency'
not:
any of
ml.nlu_classifier(body.current_thread.text).topicswhere all hold:- .name is 'Advertising and Promotions'
- .confidence is 'high'
all of:
- length(filter(body.links, .href_url.domain.domain in $free_subdomain_hosts or .href_url.domain.domain in $free_file_hosts or network.whois(.href_url.domain).days_old < 30 and regex.match(.display_text, '[A-Z ]+') or any(ml.nlu_classifier(.display_text).entities, .name in ('request', 'urgency')) or any(ml.nlu_classifier(.display_text).intents, .name in ('cred_theft')))) > 0
- length(filter(body.links, .href_url.domain.domain in $free_subdomain_hosts or .href_url.domain.domain in $free_file_hosts or network.whois(.href_url.domain).days_old < 30 and regex.match(.display_text, '[A-Z ]+') or any(ml.nlu_classifier(.display_text).entities, .name in ('request', 'urgency')) or any(ml.nlu_classifier(.display_text).intents, .name in ('cred_theft')))) < 3
all of:
- length(attachments) is 0
- body.current_thread.text contains 'attached'
any of
body.current_thread.linkswhere:- .href_url.url matches 'RFP'
all of:
- length(attachments) is 1
- length(body.current_thread.text) < 100
all of
attachmentswhere all hold:- .file_type in $file_types_images
any of
file.explode(.)where:at least 2 of:
- .scan.ocr.raw matches '(discuss.{0,15}purchas(e|ing))'
- .scan.ocr.raw matches '(sign(ed?)|view).{0,10}(purchase order)|Request for a Quot(e|ation)'
- .scan.ocr.raw matches '(please|kindly).{0,30}quote'
all of:
any of
ml.nlu_classifier(.scan.ocr.raw).entitieswhere:- .name is 'request'
any of
ml.nlu_classifier(.scan.ocr.raw).entitieswhere:- .name is 'urgency'
any of
ml.nlu_classifier(.scan.ocr.raw).tagswhere all hold:- .name is 'purchase_order'
- .confidence is 'high'
any of
ml.nlu_classifier(.scan.ocr.raw).entitieswhere all hold:- .name is 'financial'
- .text matches 'rfp|rfq'
all of:
- subject.subject matches 'project\\s+summary'
any of
html.xpath(body.html, '//div[.//img[contains(@src,"pdf")]]//a').nodeswhere:- .display_text matches 'project\\s+summary'
- body.current_thread.text matches '(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)'
not:
all of:
- sender.email.domain.root_domain is 'wetransfer.com'
- coalesce(headers.auth_summary.dmarc.pass)
any of:
all of:
- sender.email.domain.root_domain in $high_trust_sender_root_domains
not:
- headers.auth_summary.dmarc.pass
- sender.email.domain.root_domain not in $high_trust_sender_root_domains
any of:
all of:
any of:
not:
- profile.by_sender().solicited
- profile.by_sender().days_since.last_contact > 30
not:
- profile.by_sender().any_messages_benign
all of:
- length(recipients.to) is 1
- sender.email.email in map(recipients.to, .email.email)
Inspects: attachments[].file_name, attachments[].file_type, body.current_thread.links, body.current_thread.links[].href_url.url, body.current_thread.text, body.html, body.links, body.links[].display_text, body.links[].href_url.domain, body.links[].href_url.domain.domain, headers.auth_summary.dmarc.pass, headers.reply_to, headers.reply_to[].email.domain.root_domain, headers.reply_to[].email.email, recipients.bcc, recipients.cc, recipients.cc[0].email.email, recipients.to, recipients.to[0].email.email, recipients.to[].display_name, recipients.to[].email.email, sender.email.domain.root_domain, sender.email.email, subject.subject, type.inbound. Sensors: file.explode, html.xpath, ml.nlu_classifier, network.whois, profile.by_sender, regex.icontains, regex.imatch, regex.match, strings.icontains. Reference lists: $file_types_images, $free_email_providers, $free_file_hosts, $free_subdomain_hosts, $high_trust_sender_root_domains, $org_domains, $recipient_emails.
Indicators matched (33)
| Field | Match | Value |
|---|---|---|
recipients.to[].display_name | member | Undisclosed recipients |
recipients.to[].display_name | member | undisclosed-recipients |
regex.icontains | regex | (discuss.{0,15}purchas(e|ing)) |
regex.icontains | regex | (sign(ed?)|view).{0,10}(purchase order)|Request for (a Quot(e|ation)|Proposal) |
regex.icontains | regex | (please|kindly).{0,30}(?:proposal|quot(e|ation)) |
regex.icontains | regex | (request for (purchase|quot(e|ation))|\bRFQ\b|\bRFP\b|bid invit(e|ation)) |
regex.icontains | regex | (purchase.?order|Quot(e|ation)) |
ml.nlu_classifier(body.current_thread.text).tags[].name | equals | purchase_order |
ml.nlu_classifier(body.current_thread.text).tags[].confidence | equals | high |
ml.nlu_classifier(body.current_thread.text).entities[].name | equals | financial |
regex.imatch | regex | rfp|rfq |
ml.nlu_classifier(body.current_thread.text).entities[].name | equals | request |
21 more
strings.icontains | substring | submit bid |
regex.icontains | regex | (sign(ed?)|view).{0,10}(purchase order)|Request for a Quot(e|ation) |
regex.icontains | regex | (?:invitation|intent) to bid |
ml.nlu_classifier(body.current_thread.text).entities[].name | equals | urgency |
ml.nlu_classifier(body.current_thread.text).topics[].name | equals | Advertising and Promotions |
ml.nlu_classifier(body.current_thread.text).topics[].confidence | equals | high |
regex.match | regex | [A-Z ]+ |
ml.nlu_classifier(body.links[].display_text).entities[].name | member | request |
ml.nlu_classifier(body.links[].display_text).entities[].name | member | urgency |
ml.nlu_classifier(body.links[].display_text).intents[].name | member | cred_theft |
strings.icontains | substring | attached |
regex.icontains | regex | RFP |
regex.icontains | regex | (please|kindly).{0,30}quote |
ml.nlu_classifier(file.explode(attachments[])[].scan.ocr.raw).entities[].name | equals | request |
ml.nlu_classifier(file.explode(attachments[])[].scan.ocr.raw).entities[].name | equals | urgency |
ml.nlu_classifier(file.explode(attachments[])[].scan.ocr.raw).tags[].name | equals | purchase_order |
ml.nlu_classifier(file.explode(attachments[])[].scan.ocr.raw).tags[].confidence | equals | high |
ml.nlu_classifier(file.explode(attachments[])[].scan.ocr.raw).entities[].name | equals | financial |
regex.icontains | regex | project\s+summary |
regex.icontains | regex | (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) |
sender.email.domain.root_domain | equals | wetransfer.com |