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T1535 Unused/Unsupported Cloud Regions — Attack Simulation

Adversaries may create cloud instances in unused geographic service regions in order to evade detection. Access is usually obtained through compromising accounts used to manage cloud infrastructure. Cloud service providers often provide infrastructure throughout the world in order to improve performance, provide redundancy, and allow customers to meet compliance requirements. Oftentimes, a customer will only use a subset of the available regions…

Complete technique description

Adversaries may create cloud instances in unused geographic service regions in order to evade detection. Access is usually obtained through compromising accounts used to manage cloud infrastructure.

Cloud service providers often provide infrastructure throughout the world in order to improve performance, provide redundancy, and allow customers to meet compliance requirements. Oftentimes, a customer will only use a subset of the available regions and may not actively monitor other regions. If an adversary creates resources in an unused region, they may be able to operate undetected.

A variation on this behavior takes advantage of differences in functionality across cloud regions. An adversary could utilize regions which do not support advanced detection services in order to avoid detection of their activity.

An example of adversary use of unused AWS regions is to mine cryptocurrency through Resource Hijacking, which can cost organizations substantial amounts of money over time depending on the processing power used.[CloudSploit - Unused AWS Regions]

Official technique definition · Open in the interactive matrix

Detection telemetry and configuration

These contracts are selected through exact technique-to-data-component relationships or explicitly labelled planning overrides. Configure a collector at the relevant observation point; a telemetry name alone is not coverage.

Cloud Storage Creation · source-mapped

DC0024 collection page — Collect bucket/container creation APIs and resulting resource state. An object upload is not equivalent to provisioning the storage resource.

Providers and collection configuration

  • Choose only the lab buckets/containers and prefixes. Enable read/write data-event collection when object access is needed; management events alone are insufficient.
  • Keep administrative changes separately from object reads/writes. Set a cost budget and retention limit before enabling high-volume data logging.
  • Preserve object version/key, requesting identity, action, source address, result and request ID. Verify the collector actually receives one benign read and one benign write.

Required normalized fields: action, bucket, region, actor.

Illustrative collection event

Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0024",
  "collector": "illustrative-lab-collector",
  "observation": {
    "action": "create_bucket",
    "bucket": "lab-bucket",
    "region": "lab-region",
    "actor": "lab-admin"
  }
}

Visibility limits: Storage metadata, listing, object access and bucket administration are different operations. Do not equate a successful request with proven exfiltration or complete content visibility.

Instance Start · source-mapped

DC0080 collection page — Collect start APIs and instance-state transitions with request IDs; distinguish accepted from completed.

Providers and collection configuration

  • In the isolated account/project/subscription, route administrative audit logs to a protected destination with retention and access controls.
  • Select the relevant service, regions and read/write operations. Confirm whether the API below is a management or data event in the provider documentation.
  • Preserve actor/session, resource, request ID, service, operation, region and error details. Check delivery latency and avoid logging credentials or sensitive request bodies.

Required normalized fields: instance_id, action, state_before, state_after.

Illustrative collection event

Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0080",
  "collector": "illustrative-lab-collector",
  "observation": {
    "instance_id": "vm-lab-1",
    "action": "start",
    "state_before": "stopped",
    "state_after": "pending"
  }
}

Visibility limits: AWS, Azure and Google expose different APIs and event schemas. An accepted API request does not prove the final resource state; join asynchronous outcomes and inventory.

Network Connection Creation · source-mapped

DC0082 collection page — Enable scoped Sysmon NetworkConnect (3), disabled by default, or a platform-equivalent process-aware network sensor.

Providers and collection configuration

  • Microsoft Sysmon: Windows event-based collection; enable the event types needed below.
  • Linux Audit: Linux alternative for supported system-call and file events; different semantics and fields.
  • Apple Endpoint Security clients: macOS alternative where the subscribed event exists; requires an entitled, approved client, not an iOS collector.
  • On a disposable Windows host, review the installed Sysmon schema and current configuration; merge scoped event filters into the existing policy rather than replacing it.
  • Forward Microsoft-Windows-Sysmon/Operational to the lab collector. Preserve event ID, timestamp, computer, process identifiers and the original event.
  • For Linux or macOS, select the equivalent sensor separately and test its emitted fields; a Windows event ID does not transfer across platforms.

Required normalized fields: process_guid, destination_ip, destination_port, protocol, initiated.

Illustrative collection event

Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0082",
  "collector": "illustrative-lab-collector",
  "observation": {
    "process_guid": "lab-process-001",
    "destination_ip": "198.51.100.20",
    "destination_port": 443,
    "protocol": "tcp",
    "initiated": true
  }
}

Visibility limits: Event filtering and sensor versions change coverage. High-volume image-load and process-access collection needs tuning; endpoint events alone do not establish intent.

User Account Metadata · source-mapped

DC0013 collection page — Export an authorized directory/account inventory with stable IDs, roles, enabled state and collection time; compare snapshots without exposing credentials.

Providers and collection configuration

  • osquery: Scheduled host-state queries; supported tables and privileges vary by OS. Select a table that actually exposes the required object.
  • Linux Audit plus inventory snapshots: Events explain changes; snapshots describe state at collection time.
  • Define the inventory query, allowed host set, interval and least-privileged reader. Store a stable asset ID, observation time and collector version.
  • Keep successive snapshots and calculate additions, removals and changed attributes. Pair state changes with audit events when available.
  • Export collector health and missed-poll counts so a missing snapshot is not misclassified as a missing asset.

Required normalized fields: account_id, enabled, roles, inventory_time.

Illustrative collection event

Project-normalized synthetic JSON, not a native provider log, captured event, attack verdict or validated detection. A parser/adapter is required for a real SIEM. Example names, IPs and values are fictional.

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0013",
  "collector": "illustrative-lab-collector",
  "observation": {
    "account_id": "user-lab-1",
    "enabled": true,
    "roles": [
      "lab-reader"
    ],
    "inventory_time": "2026-09-27T12:00:00Z"
  }
}

Visibility limits: Snapshots miss short-lived objects and do not identify who caused a change. A generic inventory agent is not guaranteed to expose firmware or kernel-level details.

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

DET0247 Detection of Adversary Use of Unused or Unsupported Cloud Regions (IaaS)

MITRE detection strategy

AN0690 Analytic 0690

Detects creation of cloud instances, services, or resources in normally unused or unsupported regions, especially following initial account access or credential use from known regions. Correlates resource provisioning across regions with absence of historical usage and alerting from standard logging services (e.g., GuardDuty not enabled in that region).

Platforms: IaaS.

Source rule directory and observation requirements

No exact-tagged Sigma source rule was imported. This does not establish that the technique is undetectable; the MITRE guidance and collection requirements remain relevant.

Before treating a rule as coverage

  1. Read the actual condition and logsource; identify attacker-side, victim-side or third-party visibility.
  2. Map native sensor fields, parse times and identities, then compile for the selected backend.
  3. Replay a behavior-positive case, a normal control, an authorized look-alike and a missing-telemetry case.
  4. Record matches and misses with rule version and source events. No match is inconclusive when required telemetry is absent.

Anomaly-based detection

No exact technique-specific Atlas model is present for T1535 in the selected source snapshot. The following is a design worksheet, not a newly validated model.

Anomaly engineering worksheet

Start from the exact analytic above. The collection-specific lenses below are analyst recommendations; they do not assert that an arbitrary statistical deviation detects this technique.

  • Cloud storage: Per principal and bucket/container: unusual object-read counts, transferred volume, new access pairs and bulk permission/deletion activity. Model backups, migrations and lifecycle policies separately.
  • Cloud control plane: Per account, role, region and API: rare actions, new role-resource relationships, enumeration bursts and configuration changes. Separate deployment automation and organization-level administrative activity.
  • Endpoint activity: Per host role and user: rare process/object combinations, bursts of object access or modification, and ordered parent/action sequences. Compare maintenance windows and signed software rollout activity.
  • Host state and inventory: Compare authorized state snapshots: first-seen drivers/services/modules, unexpected configuration drift and integrity changes. Record collection cadence; absence in a sample is not evidence of deletion.
  1. Define an entity/peer group and feature; exclude the evaluation period from baseline training.
  2. Use representative normal and maintenance activity. Do not invent a production threshold from a synthetic example.
  3. Evaluate held-out behavior-positive and benign cases; measure false positives, misses and telemetry loss separately.
  4. Keep abnormality separate from maliciousness. Correlate with the behavior-specific source evidence.

Anomaly Detection Atlas · Baseline, validation and blind spots

Attack tools and documented software

No reviewed lab-tool association is selected for this exact technique. This is a curation gap, not a statement that no tool can implement the behavior.

Simulation design and documented procedures

Atomic evidence: no compatible candidate in this snapshot. Live lab status: not run for these imported procedures.

Use disposable lab hosts and test accounts, explicit target allowlists, a clean snapshot, bounded egress and a restore plan. Review every candidate and dependency before any execution.

No compatible Atomic procedure is present in this pinned evidence set. Technical feasibility has not been ruled out. A custom procedure must define the behavior, target, collection point, success observable and rollback before execution.

Technique-specific experiment contract

  1. Choose one procedure implementing T1535 Unused/Unsupported Cloud Regions; identify the observable behavior in the source definition, not just its tactic.
  2. Record exact target, tool/version, inputs, privileges, network limits and approval. Never run an imported default target automatically.
  3. Enable the collection sources above and verify a benign baseline reaches the detector.
  4. Run only the approved isolated scenario; capture native events and an independent behavior observable.
  5. Evaluate the exact rule/model, restore the lab, and preserve configuration, event hashes, alerts, controls and misses.

Synthetic logs and offline contract check

Download synthetic collection fixture (JSON) · Download the complete engineering workbook

This fixture exercises the listed collection fields. It does not reproduce Unused/Unsupported Cloud Regions, label its example events as malicious, or measure detection effectiveness. Use the exact analytic and selected procedure to build an independently labelled behavior-positive dataset.

Not run in this browser. No network scan or attack command is executed by this control.

Validation status and remaining work

Source identity
Joined by exact technique/object IDs against hash-pinned sources.
Collection fixture
Available for offline schema exercises; not attack emulation.
Native telemetry / backend / real attack
Not validated for these imported procedures. Source fidelity and page tests cannot establish sensor or detector effectiveness.

All-page audit and evidence inventory · This page’s machine-readable workbook

Sources and evidence boundaries

Pinned MITRE STIX source · SHA-256 81113ba98afa2928f3dcff62022539f7ce30c315c32e14422f11ff95ce534352. Definition and procedure context are reproduced from this snapshot, not independently re-investigated incidents.

Source-linked mitigations

Connected ecosystem references

Linked tags

Detection and collection

T1535 detection workspace

No reviewed association in this snapshot.

Existing research

Threat Matrix: knowledge routes, evidence and actor context

Pinned research references. No browser attack runner or production-validated detector is asserted. Imported procedures remain unvalidated; any bounded lab evidence has its own scope. ATT&CK / Atomic provenance · Detection provenance.