T1603 Scheduled Task/Job — Attack Simulation

Complete technique description

Adversaries may abuse task scheduling functionality to facilitate initial or recurring execution of malicious code. On Android and iOS, APIs and libraries exist to facilitate scheduling tasks to execute at a specified date, time, or interval.

On Android, the `WorkManager` API allows asynchronous tasks to be scheduled with the system. `WorkManager` was introduced to unify task scheduling on Android, using `JobScheduler`, `GcmNetworkManager`, and `AlarmManager` internally. `WorkManager` offers a lot of flexibility for scheduling, including periodically, one time, or constraint-based (e.g. only when the device is charging).[Android WorkManager]

On iOS, the `NSBackgroundActivityScheduler` API allows asynchronous tasks to be scheduled with the system. The tasks can be scheduled to be repeating or non-repeating, however, the system chooses when the tasks will be executed. The app can choose the interval for repeating tasks, or the delay between scheduling and execution for one-time tasks.[Apple NSBackgroundActivityScheduler]

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.

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0021",
  "collector": "illustrative-lab-collector",
  "observation": {
    "process_id": 4200,
    "api": "CreateFileW",
    "path": "C:\\Lab\\demo.txt",
    "result": "success"
  }
}

{
  "schema": "1200km.telemetry.example.v1",
  "synthetic": true,
  "timestamp": "2026-09-27T12:00:00Z",
  "telemetry_id": "DC0001",
  "collector": "illustrative-lab-collector",
  "observation": {
    "task_name": "LabDailyCheck",
    "action": "create",
    "principal": "lab-user",
    "schedule": "daily",
    "program": "lab-check.exe"
  }
}

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

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 T1603 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.

• Application and service audit: Per application, client and route: request rate, rare actions, failure ratios and unusual state transitions. Version changes, retries, health probes and seasonal load need separate baselines.
• Windows and directory audit: Per principal, host and object: unusual access/request rates, new principal-object relationships, and changes outside approved administration windows. Control for service accounts and scheduled directory maintenance.

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.

Software observed in source procedures

These are exact ATT&CK software-use relationships, including malware. They provide behavior context, not recommendations to download or execute malware. No safety or detector claim is inherited.

Simulation design and documented procedures

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

Use owned test devices or emulators, disposable app accounts and test data. Verify platform/version instrumentation; desktop test procedures do not establish mobile coverage.

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 T1603 Scheduled Task/Job; 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 Scheduled Task/Job, 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 824f7d8a37e7893b29e4c6ca6d87b5fbbf3b228ec6384f1a69ee20d523ff59e5. Definition and procedure context are reproduced from this snapshot, not independently re-investigated incidents.

• mitre-attack
• Apple NSBackgroundActivityScheduler
• Android WorkManager