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Updating rule: link_microsoft_low_reputation.yml #778

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15 changes: 7 additions & 8 deletions detection-rules/link_microsoft_low_reputation.yml
Original file line number Diff line number Diff line change
Expand Up @@ -7,16 +7,14 @@ source: |
// suspicious link
and any(body.links,
(
.href_url.domain.root_domain not in $tranco_1m
.href_url.domain.domain not in $tranco_1m
or .href_url.domain.domain in $free_file_hosts
or .href_url.domain.root_domain in $free_subdomain_hosts
or .href_url.domain.domain in $url_shorteners
or

// mass mailer link, masks the actual URL
.href_url.domain.root_domain in ("hubspotlinks.com", "mandrillapp.com", "sendgrid.net")
)

// exclude sources of potential FPs
and .href_url.domain.root_domain not in (
"svc.ms",
Expand All @@ -31,7 +29,7 @@ source: |
length(headers.references) == 0
or not any(headers.hops, any(.fields, strings.ilike(.name, "In-Reply-To")))
)

// Microsoft logo
and (
any(attachments,
Expand All @@ -40,7 +38,7 @@ source: |
)
or any(ml.logo_detect(beta.message_screenshot()).brands, strings.starts_with(.name, "Microsoft"))
)

// suspicious content
and (
(
Expand Down Expand Up @@ -104,19 +102,20 @@ source: |
or any(attachments,
.file_type in $file_types_images
and any(file.explode(.),
any(ml.nlu_classifier(.scan.ocr.raw).intents, .name == "cred_theft")
any(ml.nlu_classifier(.scan.ocr.raw).intents, .name == "cred_theft" and .confidence != "low")
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)
)
or (
any(ml.nlu_classifier(body.html.inner_text).entities, .name == "urgency")
and not any(ml.nlu_classifier(body.current_thread.text).intents,
.name == "benign" and .confidence == "high"
and any(ml.nlu_classifier(body.current_thread.text).intents,
.name != "benign"
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)
)
)
and sender.email.domain.root_domain not in $org_domains
and sender.email.domain.root_domain not in (
"bing.com",
"cloudappsecurity.com",
"microsoft.com",
"microsoftonline.com",
"microsoftsupport.com",
Expand Down