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sublimehighRule
Service abuse: Coursera callback scam
Detects inbound messages spoofing Coursera transactional notifications - such as email confirmation requests or account change alerts - sent from Coursera's legitimate sending infrastructure, but targeting recipients on newly registered domains or containing mailto links pointing to newly registered non-Coursera domains. The combination of authentic-looking Coursera branding with anomalous recipient or embedded contact domains suggests account takeover or credential harvesting activity targeting Coursera users.
Detection Query
type.inbound
// message is sent from coursera (auth doesn't really matter here)
and sender.email.domain.root_domain == "coursera.org"
and (
// the email being changed appears in the body as a link
any(body.links,
.href_url.scheme == "mailto"
and .href_url.domain.root_domain != "coursera.org"
// the domain is newly registered
and network.whois(.href_url.domain).days_old < 365
)
// in other cases the email address isn't in the email body and it's only as a rcpt
or network.whois(recipients.to[0].email.domain).days_old < 365
// extract the first line and do NLU on it
or any(ml.nlu_classifier(regex.extract(body.current_thread.text,
'^(?P<first_line>[^\n]+)\n'
)[0].named_groups["first_line"]
).intents,
.name == "callback_scam" and .confidence == "high"
)
)
// not in org_domains
and all(recipients.to, .email.domain.domain not in $org_domains)
Data Sources
Email MessagesEmail HeadersEmail Attachments
Platforms
email
Raw Content
name: "Service abuse: Coursera callback scam"
description: "Detects inbound messages spoofing Coursera transactional notifications - such as email confirmation requests or account change alerts - sent from Coursera's legitimate sending infrastructure, but targeting recipients on newly registered domains or containing mailto links pointing to newly registered non-Coursera domains. The combination of authentic-looking Coursera branding with anomalous recipient or embedded contact domains suggests account takeover or credential harvesting activity targeting Coursera users."
type: "rule"
severity: "high"
source: |
type.inbound
// message is sent from coursera (auth doesn't really matter here)
and sender.email.domain.root_domain == "coursera.org"
and (
// the email being changed appears in the body as a link
any(body.links,
.href_url.scheme == "mailto"
and .href_url.domain.root_domain != "coursera.org"
// the domain is newly registered
and network.whois(.href_url.domain).days_old < 365
)
// in other cases the email address isn't in the email body and it's only as a rcpt
or network.whois(recipients.to[0].email.domain).days_old < 365
// extract the first line and do NLU on it
or any(ml.nlu_classifier(regex.extract(body.current_thread.text,
'^(?P<first_line>[^\n]+)\n'
)[0].named_groups["first_line"]
).intents,
.name == "callback_scam" and .confidence == "high"
)
)
// not in org_domains
and all(recipients.to, .email.domain.domain not in $org_domains)
attack_types:
- "Callback Phishing"
tactics_and_techniques:
- "Impersonation: Brand"
- "Lookalike domain"
- "Social engineering"
detection_methods:
- "Sender analysis"
- "URL analysis"
- "Whois"
id: "ea4293c3-8b11-58ba-85f0-0a03af2b21ed"