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AWS RDS Snapshot Export

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AWS RDS Snapshot Export

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Identifies the export of a DB snapshot or DB cluster data to Amazon S3. Snapshot exports can be used for analytics or migration workflows, but adversaries may abuse them to exfiltrate sensitive data outside of RDS-managed storage. Exporting a snapshot creates a portable copy of the database contents, which, if performed without authorization, can indicate data theft, staging for exfiltration, or operator misconfiguration that exposes regulated information.

Rule type: query

Rule indices:

  • filebeat-*
  • logs-aws.cloudtrail-*

Severity: low

Risk score: 21

Runs every: 5m

Searches indices from: now-6m (Date Math format, see also Additional look-back time)

Maximum alerts per execution: 100

References:

Tags:

  • Domain: Cloud
  • Data Source: AWS
  • Data Source: Amazon Web Services
  • Use Case: Asset Visibility
  • Tactic: Collection
  • Tactic: Exfiltration
  • Resources: Investigation Guide

Version: 210

Rule authors:

  • Elastic
  • Austin Songer

Rule license: Elastic License v2

Investigation guide

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Triage and analysis

Disclaimer: This investigation guide was created using generative AI technology and has been reviewed to improve its accuracy and relevance. While every effort has been made to ensure its quality, validate and adapt it to suit your operational needs.

Investigating AWS RDS Snapshot Export

Exporting an RDS snapshot to Amazon S3 allows the full contents of a database to be written outside the managed RDS service boundary. While legitimate for analytics or migration, this action can also be a mechanism for data exfiltration. Because snapshot exports produce files that can be downloaded, shared, or accessed by other AWS principals, unauthorized exports may indicate staging for data theft or attempts to bypass database access controls.

This rule detects successful StartExportTask events. Activity of this type should be validated to ensure that only authorized database, platform engineering, or analytics workflows initiated the export.

Possible investigation steps

  • Identify the actor and context
  • Review aws.cloudtrail.user_identity.arn and aws.cloudtrail.user_identity.access_key_id to determine which principal initiated the export.
  • Look at source.ip, user.name, and user_agent.original to understand where the export originated (console, CLI, SDK, automation).
  • Check whether the principal has historically performed snapshot exports.
  • Determine what was exported
  • Examine aws.cloudtrail.request_parameters:
  • Snapshot identifier being exported.
  • S3 bucket name and path.
  • KMS key used (or absence of encryption).
  • Map the snapshot and destination bucket to:
  • Application/owner team.
  • Environment (prod/staging/dev).
  • Data classification (PII, PHI, PCI, internal).
  • Reconstruct timing and surrounding context
  • Use @timestamp to correlate the export with:
  • Recent RDS modifications (ModifyDBInstance, ModifyDBCluster), snapshot deletions, or retention changes.
  • IAM role changes, access key issuance, or privilege escalation attempts.
  • Unusual authentication patterns (e.g., successful logins from new locations, failed console logins).
  • Check whether the export timing aligns with approved deployments or maintenance windows.
  • Correlate with broader CloudTrail activity
  • Pivot on the same user, role, or access key ID to look for:
  • Prior reconnaissance (e.g., DescribeDBSnapshots, DescribeDBClusters, ListBuckets).
  • Permission changes (PutRolePolicy, AttachUserPolicy).
  • Public exposure (e.g., S3 bucket ACL changes).
  • Determine whether multiple snapshots were exported around the same time.
  • Validate intent with stakeholders
  • Confirm with the database owner, analytics team, or platform engineering team whether:
  • The export was planned and authorized.
  • The target S3 bucket is approved for storing database contents.
  • Encryption and access controls meet organizational policy.

False positive analysis

  • Authorized data analytics or ETL workflows
  • Many organizations export snapshots for reporting, ML pipelines, or external data processing.
  • Validate that the export aligns with documented ETL or analytics processes.
  • Automated snapshot export tools
  • Backup pipelines, cost optimization, or data replication systems may export snapshots.
  • Tune the rule by excluding known IAM roles or automation user agents.
  • CloudFormation or IaC triggers
  • Infrastructure-as-code pipelines may trigger snapshot exports as part of stack updates.
  • Correlate with CloudFormation events to confirm legitimacy.

Response and remediation

  • Contain potential exfiltration
  • Review access to the destination S3 bucket and confirm that:
  • Bucket is encrypted with the expected KMS key.
  • Access is restricted to authorized principals.
  • No unusual downloads or cross-account accesses occurred.
  • Investigate scope and impact
  • Use CloudTrail to enumerate:
  • All export tasks started by the same actor.
  • Other snapshot or data-access API calls in the same time window.
  • Validate whether sensitive or regulated data may have been included.
  • Credential and access remediation
  • If activity appears unauthorized:
  • Revoke or rotate compromised IAM credentials.
  • Review STS session activity related to the actor.
  • Inspect IAM role policies for privilege escalation.
  • Hardening and preventive controls
  • Restrict the ability to call StartExportTask using:
  • IAM least-privilege policies.
  • Service Control Policies (SCPs) in production accounts.
  • Conditional IAM (e.g., requiring MFA, restricting by VPC endpoint or IP range).
  • Enable guardrails:
  • AWS Config/Security Hub controls for monitoring snapshot policy changes.
  • Alerts for exports to buckets outside approved accounts.

Additional information

Rule query

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event.dataset: aws.cloudtrail
    and event.provider: rds.amazonaws.com
    and event.action: StartExportTask
    and event.outcome: success

Framework: MITRE ATT&CKTM

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