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sublimemediumRule
Newly registered sender or reply-to domain with newly registered linked domain
This rule detects inbound emails that contain links and a reply-to address, where either the sender domain or the reply-to domain is newly registered (≤30 days old), and at least one linked domain is also very new (≤14 days old). It flags potential phishing or business email compromise attempts that use recently created infrastructure and reply-to mismatch tactics to bypass trust and impersonate legitimate contacts.
Detection Query
type.inbound
and length(body.links) > 0
and length(headers.reply_to) > 0
and (
any(headers.reply_to,
network.whois(.email.domain).days_old <= 30
and .email.email != sender.email.email
)
or network.whois(sender.email.domain).days_old <= 30
)
and any(distinct(body.links, .href_url.domain.root_domain),
network.whois(.href_url.domain).days_old < 14
)
Data Sources
Email MessagesEmail HeadersEmail Attachments
Platforms
email
Tags
Attack surface reduction
Raw Content
name: "Newly registered sender or reply-to domain with newly registered linked domain"
description: "This rule detects inbound emails that contain links and a reply-to address, where either the sender domain or the reply-to domain is newly registered (≤30 days old), and at least one linked domain is also very new (≤14 days old). It flags potential phishing or business email compromise attempts that use recently created infrastructure and reply-to mismatch tactics to bypass trust and impersonate legitimate contacts."
type: "rule"
severity: "medium"
source: |
type.inbound
and length(body.links) > 0
and length(headers.reply_to) > 0
and (
any(headers.reply_to,
network.whois(.email.domain).days_old <= 30
and .email.email != sender.email.email
)
or network.whois(sender.email.domain).days_old <= 30
)
and any(distinct(body.links, .href_url.domain.root_domain),
network.whois(.href_url.domain).days_old < 14
)
tags:
- "Attack surface reduction"
attack_types:
- "BEC/Fraud"
- "Credential Phishing"
- "Malware/Ransomware"
tactics_and_techniques:
- "Social engineering"
detection_methods:
- "Header analysis"
- "URL analysis"
- "Whois"
id: "e5b6a81f-8587-585f-957a-712987ad9884"