Detection rules › Splunk
ASL AWS Defense Evasion Update Cloudtrail
The following analytic detects UpdateTrail events within AWS CloudTrail logs, aiming to identify attempts by attackers to evade detection by altering logging configurations. By updating CloudTrail settings with incorrect parameters, such as changing multi-regional logging to a single region, attackers can impair the logging of their activities across other regions. This behavior is crucial for Security Operations Centers (SOCs) to identify, as it indicates an adversary's intent to operate undetected within a compromised AWS environment. The impact of such evasion tactics is significant, potentially allowing malicious activities to proceed without being logged, thereby hindering incident response and forensic investigations.
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Defense Impairment | T1685.002 Disable or Modify Tools: Disable or Modify Cloud Log |
Rules detecting the same action
Other rules on this platform that filter on the same API call or operation.
Rule body splunk
name: ASL AWS Defense Evasion Update Cloudtrail
id: f3eb471c-16d0-404d-897c-7653f0a78cba
version: 12
creation_date: '2024-05-22'
modification_date: '2026-05-13'
author: Patrick Bareiss, Splunk
status: production
type: TTP
description: The following analytic detects `UpdateTrail` events within AWS CloudTrail logs, aiming to identify attempts by attackers to evade detection by altering logging configurations. By updating CloudTrail settings with incorrect parameters, such as changing multi-regional logging to a single region, attackers can impair the logging of their activities across other regions. This behavior is crucial for Security Operations Centers (SOCs) to identify, as it indicates an adversary's intent to operate undetected within a compromised AWS environment. The impact of such evasion tactics is significant, potentially allowing malicious activities to proceed without being logged, thereby hindering incident response and forensic investigations.
data_source:
- ASL AWS CloudTrail
search: |-
`amazon_security_lake` api.operation=UpdateTrail
| fillnull
| stats count min(_time) as firstTime max(_time) as lastTime
BY actor.user.uid api.operation api.service.name
http_request.user_agent src_endpoint.ip actor.user.account.uid
cloud.provider cloud.region
| rename actor.user.uid as user api.operation as action api.service.name as dest http_request.user_agent as user_agent src_endpoint.ip as src actor.user.account.uid as vendor_account cloud.provider as vendor_product cloud.region as vendor_region
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `asl_aws_defense_evasion_update_cloudtrail_filter`
how_to_implement: The detection is based on Amazon Security Lake events from Amazon Web Services (AWS), which is a centralized data lake that provides security-related data from AWS services. To use this detection, you must ingest CloudTrail logs from Amazon Security Lake into Splunk. To run this search, ensure that you ingest events using the latest version of Splunk Add-on for Amazon Web Services (https://splunkbase.splunk.com/app/1876) or the Federated Analytics App.
known_false_positives: While this search has no known false positives, it is possible that an AWS admin has updated cloudtrail logging. Please investigate this activity.
references:
- https://attack.mitre.org/techniques/T1562/008/
drilldown_searches:
- name: View the detection results for - "$user$"
search: '%original_detection_search% | search user = "$user$"'
earliest_offset: $info_min_time$
latest_offset: $info_max_time$
- name: View risk events for the last 7 days for - "$user$"
search: '| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$user$") | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`'
earliest_offset: 7d
latest_offset: "0"
finding:
title: User $user$ has updated a cloudtrail logging for account id $vendor_account$ from IP $src$
entity:
field: user
type: user
score: 50
threat_objects:
- field: src
type: ip_address
analytic_story:
- AWS Defense Evasion
asset_type: AWS Account
mitre_attack_id:
- T1685.002
product:
- Splunk Enterprise
- Splunk Enterprise Security
- Splunk Cloud
category: cloud
security_domain: threat
tests:
- name: True Positive Test
attack_data:
- data: https://media.githubusercontent.com/media/splunk/attack_data/master/datasets/attack_techniques/T1562.008/update_cloudtrail/asl_ocsf_cloudtrail.json
sourcetype: aws:asl
source: aws_asl
test_type: unit
Stages and Predicates
Stage 1: search
`amazon_security_lake` api.operation=UpdateTrail
Stage 2: fillnull
| fillnull
Stage 3: stats
| stats count min(_time) as firstTime max(_time) as lastTime
BY actor.user.uid api.operation api.service.name
http_request.user_agent src_endpoint.ip actor.user.account.uid
cloud.provider cloud.region
Stage 4: rename
| rename actor.user.uid as user api.operation as action api.service.name as dest http_request.user_agent as user_agent src_endpoint.ip as src actor.user.account.uid as vendor_account cloud.provider as vendor_product cloud.region as vendor_region
Stage 5: search
| `security_content_ctime(firstTime)`
Stage 6: search
| `security_content_ctime(lastTime)`
Stage 7: search
| `asl_aws_defense_evasion_update_cloudtrail_filter`
Indicators
Each row is a field, operator, and value that the rule matches. The corpus column counts how many other rules in the catalog look for the same combination: high numbers point to widely-used, community-vetted indicators. Blank or 1 shows that the indicator is specific to this rule.
| Field | Kind | Values |
|---|---|---|
api.operation | eq |
|
sourcetype | eq |
|