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sublimemediumRule
Brand impersonation: Mailchimp
Detects messages from senders impersonating Mailchimp through display name spoofing or brand logo usage, combined with security-themed content and suspicious authentication patterns.
Detection Query
type.inbound
and (
// display name contains Mailchimp
(
strings.ilike(strings.replace_confusables(sender.display_name),
'*mailchimp*'
)
// levenshtein distance similar to Mailchimp
or strings.ilevenshtein(strings.replace_confusables(sender.display_name),
'mailchimp'
) <= 1
or any(ml.logo_detect(file.message_screenshot()).brands,
.name == "MailChimp" and .confidence == "high"
)
)
)
and (
any(ml.nlu_classifier(body.current_thread.text).topics,
.name in (
"Security and Authentication",
"Secure Message",
"Reminders and Notifications"
)
and .confidence in ("medium", "high")
)
or any(ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).topics,
.name in (
"Security and Authentication",
"Secure Message",
"Reminders and Notifications"
)
and .confidence in ("medium", "high")
and beta.ocr(file.message_screenshot()).text != ""
)
or any(ml.nlu_classifier(body.current_thread.text).intents,
.name == "cred_theft" and .confidence == "high"
)
or any(ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).intents,
.name == "cred_theft" and .confidence == "high"
)
)
// and the sender is not in org_domains or from Mailchimp domains and passes auth
and not (
sender.email.domain.root_domain in $org_domains
or (
sender.email.domain.root_domain in ("intuit.com", "mailchimp.com")
and headers.auth_summary.dmarc.pass
)
)
and not strings.ends_with(headers.message_id, ".mailchimp.com>")
// and the sender is not from high trust sender root domains
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
Data Sources
Email MessagesEmail HeadersEmail Attachments
Platforms
email
Raw Content
name: "Brand impersonation: Mailchimp"
description: "Detects messages from senders impersonating Mailchimp through display name spoofing or brand logo usage, combined with security-themed content and suspicious authentication patterns."
type: "rule"
severity: "medium"
source: |
type.inbound
and (
// display name contains Mailchimp
(
strings.ilike(strings.replace_confusables(sender.display_name),
'*mailchimp*'
)
// levenshtein distance similar to Mailchimp
or strings.ilevenshtein(strings.replace_confusables(sender.display_name),
'mailchimp'
) <= 1
or any(ml.logo_detect(file.message_screenshot()).brands,
.name == "MailChimp" and .confidence == "high"
)
)
)
and (
any(ml.nlu_classifier(body.current_thread.text).topics,
.name in (
"Security and Authentication",
"Secure Message",
"Reminders and Notifications"
)
and .confidence in ("medium", "high")
)
or any(ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).topics,
.name in (
"Security and Authentication",
"Secure Message",
"Reminders and Notifications"
)
and .confidence in ("medium", "high")
and beta.ocr(file.message_screenshot()).text != ""
)
or any(ml.nlu_classifier(body.current_thread.text).intents,
.name == "cred_theft" and .confidence == "high"
)
or any(ml.nlu_classifier(beta.ocr(file.message_screenshot()).text).intents,
.name == "cred_theft" and .confidence == "high"
)
)
// and the sender is not in org_domains or from Mailchimp domains and passes auth
and not (
sender.email.domain.root_domain in $org_domains
or (
sender.email.domain.root_domain in ("intuit.com", "mailchimp.com")
and headers.auth_summary.dmarc.pass
)
)
and not strings.ends_with(headers.message_id, ".mailchimp.com>")
// and the sender is not from high trust sender root domains
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
attack_types:
- "Credential Phishing"
tactics_and_techniques:
- "Impersonation: Brand"
- "Social engineering"
detection_methods:
- "Computer Vision"
- "Natural Language Understanding"
- "Content analysis"
- "Header analysis"
- "Sender analysis"
id: "48b454c7-fcd7-54d4-b460-5dfec2c1a3e2"