Skip to content
Open
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
26 changes: 22 additions & 4 deletions detection-rules/brand_impersonation_robinhood.yml
Original file line number Diff line number Diff line change
Expand Up @@ -17,10 +17,16 @@ source: |
)
or strings.icontains(body.current_thread.text, 'The Robinhood Team')
or regex.icontains(body.current_thread.text, '©\s*20[0-9]{2}\s*\s*Robinhood')
or strings.icontains(body.current_thread.text, "(888) 344-3957")
or strings.icontains(body.current_thread.text, "Financial LLC (Member SIPC)")
or strings.icontains(body.current_thread.text,
"Securities, LLC (Member SIPC)"
)
or 2 of (
strings.icontains(body.current_thread.text, "Robinhood"),
regex.icontains(body.current_thread.text, '42 Willow (?:Road|St)'),
strings.icontains(body.current_thread.text, "Menlo Park, CA 97095")
strings.icontains(body.current_thread.text, "Menlo Park, CA 97095"),
regex.icontains(body.current_thread.text, 'Email ID:?')
)
or (
strings.icontains(sender.display_name, 'Robinhood')
Expand All @@ -29,9 +35,15 @@ source: |
regex.icontains(body.current_thread.text, 'Location:?'),
regex.icontains(body.current_thread.text, 'Time:'),
regex.icontains(body.current_thread.text, 'Device:?'),
regex.icontains(body.current_thread.text, 'IP Address:?')
regex.icontains(body.current_thread.text, 'IP Address:?'),
regex.icontains(body.current_thread.text, 'Date:'),
regex.icontains(body.current_thread.text, 'Region:?'),
regex.icontains(body.current_thread.text, 'App:?'),
)
or strings.icontains(body.current_thread.text, "new passkey added")
or strings.icontains(body.current_thread.text,
"Security support phone number:"
)
)
)
or (
Expand Down Expand Up @@ -67,9 +79,16 @@ source: |
)
// negate newsletters and webinars
and not any(ml.nlu_classifier(body.current_thread.text).topics,
.name in ("Newsletters and Digests", "Events and Webinars")
.name in (
"Newsletters and Digests",
"Health and Wellness",
"Events and Webinars"
)
and .confidence == "high"
)
and not any(ml.nlu_classifier(body.current_thread.text).intents,
.name == "benign" and .confidence == "high"
)
and not (
sender.email.domain.root_domain in (
"robinhood.com",
Expand All @@ -80,7 +99,6 @@ source: |
)
and coalesce(headers.auth_summary.dmarc.pass, false)
)

attack_types:
- "Credential Phishing"
tactics_and_techniques:
Expand Down
Loading