Detection rules › Splunk

Cisco Duo Bulk Policy Deletion

Status
production
Severity
medium
Group by
action, actionlabel, admin_email, description, policy_count, user
Author
Patrick Bareiss, Splunk
Source
github.com/splunk/security_content

The following analytic detects instances where a Duo administrator performs a bulk deletion of more than three policies in a single action. It identifies this behavior by searching Duo activity logs for the policy_bulk_delete action, extracting the names of deleted policies, and counting them. If the count exceeds three, the event is flagged. This behavior is significant for a Security Operations Center (SOC) because mass deletion of security policies can indicate malicious activity, such as an attacker or rogue administrator attempting to weaken or disable security controls, potentially paving the way for further compromise. Detecting and investigating such actions promptly is critical, as the impact of this attack could include reduced security posture, increased risk of unauthorized access, and potential data breaches. Monitoring for bulk policy deletions helps ensure that any suspicious or unauthorized changes to security configurations are quickly identified and addressed to protect organizational assets and maintain compliance.

Known false positives

  • No false positives have been identified at this time.

MITRE ATT&CK coverage

Rule body

name: Cisco Duo Bulk Policy Deletion
id: 983be012-e408-4cb0-b87f-6756bb5f7047
version: 5
creation_date: '2025-07-10'
modification_date: '2026-05-13'
author: Patrick Bareiss, Splunk
status: production
type: TTP
description: The following analytic detects instances where a Duo administrator performs a bulk deletion of more than three policies in a single action. It identifies this behavior by searching Duo activity logs for the policy_bulk_delete action, extracting the names of deleted policies, and counting them. If the count exceeds three, the event is flagged. This behavior is significant for a Security Operations Center (SOC) because mass deletion of security policies can indicate malicious activity, such as an attacker or rogue administrator attempting to weaken or disable security controls, potentially paving the way for further compromise. Detecting and investigating such actions promptly is critical, as the impact of this attack could include reduced security posture, increased risk of unauthorized access, and potential data breaches. Monitoring for bulk policy deletions helps ensure that any suspicious or unauthorized changes to security configurations are quickly identified and addressed to protect organizational assets and maintain compliance.
data_source:
    - Cisco Duo Administrator
search: '`cisco_duo_administrator` action=policy_bulk_delete | rename username as user | spath input=description | rex field=policies max_match=0 "(?<policy_name>[^:,]+):\s+" | eval policy_count=mvcount(policy_name) | where policy_count > 3 | stats count min(_time) as firstTime max(_time) as lastTime by action actionlabel description user admin_email policy_count | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `cisco_duo_bulk_policy_deletion_filter`'
how_to_implement: The analytic leverages Duo activity logs to be ingested using the Cisco Security Cloud App (https://splunkbase.splunk.com/app/7404).
known_false_positives: No false positives have been identified at this time.
references:
    - https://splunkbase.splunk.com/app/7404
finding:
    title: A user $user$ has deleted more than 3 policies
    entity:
        field: user
        type: user
        score: 50
analytic_story:
    - Cisco Duo Suspicious Activity
asset_type: Identity
mitre_attack_id:
    - T1556
product:
    - Splunk Enterprise
    - Splunk Enterprise Security
    - Splunk Cloud
category: application
security_domain: identity

Stages and Predicates

Stage 1: search

`cisco_duo_administrator` action=policy_bulk_delete

Stage 2: rename

| rename username as user

Stage 3: spath

| spath input=description

Stage 4: rex

| rex field=policies max_match=0 "(?<policy_name>[^:,]+):\s+"

Stage 5: eval

| eval policy_count=mvcount(policy_name)

Stage 6: where

| where policy_count > 3

Stage 7: stats

| stats count min(_time) as firstTime max(_time) as lastTime by action actionlabel description user admin_email policy_count

Stage 8: search

| `security_content_ctime(firstTime)`

Stage 9: search

| `security_content_ctime(lastTime)`

Stage 10: search

| `cisco_duo_bulk_policy_deletion_filter`

Indicators

These rows show field, operator, and value matches.