T1586.003 Elastic Security · Elastic

Detect Cloud Accounts in Elastic Security

Adversaries may compromise cloud accounts to use during targeting operations. Compromised cloud accounts (Azure, AWS, GCP, Dropbox, OneDrive, GitHub) allow adversaries to leverage trusted third-party infrastructure for command and control, exfiltration to cloud storage, sending phishing or spam via cloud messaging services (AWS SES/SNS, SendGrid, Twilio), and acquiring additional cloud infrastructure without managing their own servers. Compromise methods include phishing for cloud credentials, password spraying, purchasing leaked credential sets from criminal markets, or stealing OAuth access tokens. APT29 has been observed using compromised Azure Virtual Machine accounts with residential proxies to obfuscate access to victim environments. This is a PRE-ATT&CK technique — the initial account compromise occurs outside the victim environment on third-party cloud platforms. Detection pivots to observable downstream effects: anomalous authentication events in cloud identity provider logs, risk signals from Identity Protection engines, MFA bypass indicators, and post-compromise behaviors such as bulk cloud storage access or cloud messaging API abuse.

MITRE ATT&CK

Tactic
Resource Development
Technique
T1586 Compromise Accounts
Sub-technique
T1586.003 Cloud Accounts
Canonical reference
https://attack.mitre.org/techniques/T1586/003/

Elastic Detection Query

Elastic Security (Elastic)
eql
any where event.dataset == "azure.signinlogs"
  and event.outcome == "success"
  and (
    azure.signinlogs.properties.risk_level_during_signin in ("high", "medium")
    or azure.signinlogs.properties.risk_state in ("atRisk", "confirmedCompromised")
    or azure.signinlogs.properties.risk_event_types_v2 like~ ("*impossibletravel*", "*anonymizedipaddress*", "*maliciousipaddress*", "*unfamiliarfeatures*", "*passwordspray*", "*leakedcredentials*", "*nationstateip*", "*riskyipaddress*", "*investigationsthreatintelligence*")
    or (
      azure.signinlogs.properties.authentication_requirement == "singleFactorAuthentication"
      and azure.signinlogs.properties.home_tenant_id != null
      and azure.signinlogs.properties.home_tenant_id != azure.signinlogs.properties.resource_tenant_id
    )
  )
high severity high confidence

Detects compromised Azure cloud account usage via Elastic's Azure integration by correlating Identity Protection risk signals in Azure AD sign-in logs. Matches successful sign-ins with high or medium risk levels, confirmed compromise states, specific risk event categories (impossible travel, leaked credentials, password spray, malicious IP), and cross-tenant single-factor authentication bypass patterns. Uses case-insensitive wildcard matching against the risk_event_types_v2 array field as serialised in the Elastic Azure integration.

Data Sources

Azure Active Directory Sign-in Logs via Elastic Azure Integration (logs-azure.signinlogs-*)

Required Tables

logs-azure.signinlogs-*

False Positives & Tuning

  • Legitimate international travel triggering impossibleTravel risk events for executives or sales staff with frequent intercontinental travel patterns where Azure Identity Protection has not learned the travel baseline
  • Corporate endpoint VPN solutions or enterprise privacy proxies causing all egress to appear as anonymizedIPAddress, generating high-volume false positives for entire user populations on split-tunnel configurations
  • Federated B2B guest accounts or partner-tenant service principals where MFA is satisfied in the home tenant and the resource tenant legitimately records singleFactorAuthentication — expected behaviour in many cross-tenant collaboration architectures
Download portable Sigma rule (.yml)

Other platforms for T1586.003


Testing Methodology

Validate this detection against 4 adversary techniques from Atomic Red Team. Each test below lists the behaviour to exercise and the telemetry you should expect to see. Executable commands and cleanup steps are available with Pro.

  1. Test 1Azure AD Password Spray Simulation

    Expected signal: Azure AD SigninLogs: multiple ResultType != 0 (error code 50126: invalid credentials) entries from the same source IPAddress within a 5-10 minute window, each with a different UserPrincipalName. Azure Identity Protection will aggregate the spray pattern and generate a passwordSpray risk event type within 15-30 minutes of the spray completing, appearing in Azure AD > Security > Identity Protection > Risk Detections.

  2. Test 2Sign-In from Anonymizing Proxy to Trigger Identity Protection Risk Event

    Expected signal: Azure AD SigninLogs: successful sign-in (ResultType=0) with IPAddress matching a known Tor exit node (verifiable against dan.me.uk/torlist or similar). RiskEventTypes_V2 populated with 'anonymizedIPAddress'. RiskLevelDuringSignIn set to 'medium' or 'high' within 5-15 minutes. The risk detection appears in Azure AD > Security > Identity Protection > Risk Detections with detectionTimingType='realtime' or 'nearRealtime'.

  3. Test 3OAuth Access Token Reuse for Cloud Storage Access

    Expected signal: Azure Storage diagnostic logs (StorageBlobLogs): AuthenticationType='OAuth', RequesterObjectId matches the test user's object ID, URI shows container list and blob download operations. No new SigninLogs entry is generated since token reuse does not trigger interactive authentication. Defender for Cloud Apps (if deployed) generates an anomalous cloud storage access alert when detecting storage API access from an unusual user agent or IP without corresponding SigninLogs event.

  4. Test 4AWS Cloud Credential Validation and Reconnaissance

    Expected signal: AWS CloudTrail events (sourcetype=aws:cloudtrail in Splunk): GetCallerIdentity (eventSource=sts.amazonaws.com), ListAttachedUserPolicies and ListGroupsForUser (eventSource=iam.amazonaws.com), ListBuckets (eventSource=s3.amazonaws.com), DescribeInstances (eventSource=ec2.amazonaws.com) — all sharing the same sourceIPAddress, userAgent (aws-cli/<version>), and accessKeyId within a 2-minute window. If AWS GuardDuty is enabled, Recon:IAMUser/MaliciousIPCaller or Recon:IAMUser/PortProbeUnprotectedPort findings may fire depending on source IP reputation.

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