AWS SageMaker Execution Role Passed by Unusual Principal

Last updated 19 days ago on 2026-07-13

Created 19 days ago on 2026-07-13

About

Identifies the first time an IAM principal passes a given execution role (`roleArn`) to an Amazon SageMaker resource, via `CreateNotebookInstance`, `CreateTrainingJob`, `CreateProcessingJob`, `CreateAutoMLJob`, or `CreatePipeline`. These actions require `iam:PassRole` and attach an IAM role that the created resource then runs as. An adversary holding both SageMaker create permissions and a broad `iam:PassRole` grant can pass a more privileged role to a resource they control and execute code as that role, escalating privileges. The rule keys on the combination of the calling principal and the passed `roleArn`, so it surfaces a principal using an execution role it has not used before in the last 7 days; a role whose account differs from the caller's, or that is more privileged than the caller, is especially suspicious.

Tags

Domain: CloudData Source: AWSData Source: Amazon Web ServicesData Source: AWS SageMakerUse Case: Threat DetectionTactic: Privilege EscalationLanguage: esql

Severity

high

Risk Score

MITRE ATT&CK™

Privilege Escalation (TA0004)(external, opens in a new tab or window)

↳ Valid Accounts (T1078)(external, opens in a new tab or window)

False Positive Examples

MLOps pipelines and data science teams routinely create SageMaker resources with execution roles, and new pipelines or team members appear as new principals on first use. Verify the principal in `aws.cloudtrail.user_identity.arn`, the passed roleArn in `aws.cloudtrail.request_parameters`, and whether the role's privileges and the activity are approved. Known automation roles can be excluded after validation.

License

Elastic License v2(external, opens in a new tab or window)

Definition

Integration Pack: Prebuilt Security Detection Rules
Related Integrations: aws(external, opens in a new tab or window)
Query

✄𐘗text code block:
✄𐘗FROM logs-aws.cloudtrail-*
| WHERE data_stream.dataset == "aws.cloudtrail"
    AND event.provider == "sagemaker.amazonaws.com"
    AND event.action IN (
      "CreateNotebookInstance",
      "CreateTrainingJob",
      "CreateProcessingJob",
      "CreateAutoMLJob",
      "CreatePipeline"
    )
    AND event.outcome == "success"
    AND aws.cloudtrail.user_identity.type != "AWSService"
| GROK aws.cloudtrail.request_parameters """.*roleArn=(?<Esql.aws_cloudtrail_request_parameters_role_arn>arn:aws[a-z-]*:iam::[0-9]{12}:role/[^,}]+).*"""
| WHERE Esql.aws_cloudtrail_request_parameters_role_arn IS NOT NULL
| EVAL Esql.principal_arn = COALESCE(
    aws.cloudtrail.user_identity.session_context.session_issuer.arn,
    aws.cloudtrail.user_identity.arn
  )
| STATS
    Esql.timestamp_min = MIN(@timestamp),
    Esql.timestamp_max = MAX(@timestamp),
    Esql.ingested_min = MIN(COALESCE(event.ingested, @timestamp)),
    Esql.event_count = COUNT(*),
    Esql.event_action_values = VALUES(event.action),
    Esql.source_ip_values = VALUES(source.ip),
    Esql.user_agent_original_values = VALUES(user_agent.original),
    Esql.user_identity_arn_values = VALUES(aws.cloudtrail.user_identity.arn),
    Esql.cloud_account_id_values = VALUES(cloud.account.id),
    Esql.cloud_region_values = VALUES(cloud.region)
  BY Esql.principal_arn,
     Esql.aws_cloudtrail_request_parameters_role_arn
| WHERE Esql.ingested_min >= NOW() - 10 minutes
| KEEP Esql.*

Install detection rules in Elastic Security

Detect AWS SageMaker Execution Role Passed by Unusual Principal in the Elastic Security detection engine by installing this rule into your Elastic Stack.

To setup this rule, check out the installation guide for Prebuilt Security Detection Rules(external, opens in a new tab or window).