Skip to content

Create attachment_pdf_microsoft_purview_impersonation.yml #3476

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 7 commits into from
Nov 10, 2025
Merged

Create attachment_pdf_microsoft_purview_impersonation.yml #3476

Changes from 4 commits
Commits
Show all changes
7 commits
Select commit Hold shift + click to select a range
8e96783
new rule
D-Bolton Nov 4, 2025
8e93a98
Auto add rule ID
Nov 4, 2025
4de7c4b
use beta.ocr instead of file.explode
D-Bolton Nov 5, 2025
4821c33
remove Archive analysis detection method
D-Bolton Nov 5, 2025
a2e312e
Update rule name
D-Bolton Nov 10, 2025
73db338
Add standard negation
D-Bolton Nov 10, 2025
0bcf1d0
indent code block
D-Bolton Nov 10, 2025
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
24 changes: 24 additions & 0 deletions detection-rules/attachment_pdf_microsoft_purview_impersonation.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,24 @@
name: "Attachment: PDF With Microsoft Purview Message Impersonation"
description: "Detects PDF attachments containing text that impersonates Microsoft Purview secure message notifications, potentially used to trick users into believing they have received legitimate secure communications from Microsoft services."
type: "rule"
severity: "medium"
source: |
type.inbound
and any(filter(attachments, .file_extension == 'pdf'),
any(ml.nlu_classifier(beta.ocr(.).text).topics,
.name == 'Secure Message' and .confidence == 'high'
)
and strings.icontains(beta.ocr(.).text, "Microsoft Purview Message")
)

attack_types:
- "Credential Phishing"
tactics_and_techniques:
- "Impersonation: Brand"
- "PDF"
- "Social engineering"
detection_methods:
- "File analysis"
- "Natural Language Understanding"
- "Content analysis"
id: "571d4964-dc44-56eb-bff4-11068b1cd119"
Loading