Detection rules › Splunk
ASL AWS ECR Container Upload Outside Business Hours
The following analytic detects the upload of new containers to AWS Elastic Container Service (ECR) outside of standard business hours through AWS CloudTrail events. It identifies this behavior by monitoring for PutImage events occurring before 8 AM or after 8 PM, as well as any uploads on weekends. This activity is significant for a SOC to investigate as it may indicate unauthorized access or malicious deployments, potentially leading to compromised services or data breaches. Identifying and addressing such uploads promptly can mitigate the risk of security incidents and their associated impacts.
Known false positives
- When your development is spreaded in different time zones, applying this rule can be difficult.
MITRE ATT&CK coverage
| Tactic | Techniques |
|---|---|
| Execution |
Rules detecting the same action
These rules filter on the same operation.
Rule body
name: ASL AWS ECR Container Upload Outside Business Hours
id: 739ed682-27e9-4ba0-80e5-a91b97698213
version: 12
creation_date: '2024-05-22'
modification_date: '2026-05-13'
author: Patrick Bareiss, Splunk
status: production
type: Anomaly
description: The following analytic detects the upload of new containers to AWS Elastic Container Service (ECR) outside of standard business hours through AWS CloudTrail events. It identifies this behavior by monitoring for `PutImage` events occurring before 8 AM or after 8 PM, as well as any uploads on weekends. This activity is significant for a SOC to investigate as it may indicate unauthorized access or malicious deployments, potentially leading to compromised services or data breaches. Identifying and addressing such uploads promptly can mitigate the risk of security incidents and their associated impacts.
data_source:
- ASL AWS CloudTrail
search: |-
`amazon_security_lake` api.operation=PutImage
| eval hour=strftime(time/pow(10,3), "%H"), weekday=strftime(time/pow(10,3), "%A")
| where hour >= 20 OR hour < 8 OR weekday=Saturday OR weekday=Sunday
| 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 api.request.data
bucketName
| 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_ecr_container_upload_outside_business_hours_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: When your development is spreaded in different time zones, applying this rule can be difficult.
references:
- https://attack.mitre.org/techniques/T1204/003/
intermediate_findings:
entities:
- field: user
type: user
score: 20
message: Container uploaded outside business hours from $user$
analytic_story:
- Dev Sec Ops
asset_type: AWS Account
mitre_attack_id:
- T1204.003
product:
- Splunk Enterprise
- Splunk Enterprise Security
- Splunk Cloud
category: cloud
security_domain: network
Stages and Predicates
Stage 1: search
`amazon_security_lake` api.operation=PutImage
Stage 2: eval
| eval hour=strftime(time/pow(10,3), "%H"), weekday=strftime(time/pow(10,3), "%A")
Stage 3: where
| where hour >= 20 OR hour < 8 OR weekday=Saturday OR weekday=Sunday
Stage 4: fillnull
| fillnull
Stage 5: 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 api.request.data
bucketName
Stage 6: 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 7: search
| `security_content_ctime(firstTime)`
Stage 8: search
| `security_content_ctime(lastTime)`
Stage 9: search
| `asl_aws_ecr_container_upload_outside_business_hours_filter`
Indicators
These rows show field, operator, and value matches.
| Field | Kind | Values | Search |
|---|---|---|---|
api.operation | eq |
| field:"aws::eventName" kind:eq value:"PutImage" |
hour | ge |
| field:"hour" kind:ge value:"20" |
hour | lt |
| field:"hour" kind:lt value:"8" |
sourcetype | eq |
| field:"sourcetype" kind:eq value:"aws:asl" |
weekday | cross_field_compare |
| field:"weekday" kind:cross_field_compare |