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T1616 Call Control — Attack Simulation

Adversaries may make, forward, or block phone calls without user authorization. This could be used for adversary goals such as audio surveillance, blocking or forwarding calls from the device owner, or C2 communication. Several permissions may be used to programmatically control phone calls, including: * `ANSWER_PHONE_CALLS` - Allows the application to answer incoming phone calls * `CALL_PHONE` - Allows the application to initiate a phone call…

Complete technique description

Adversaries may make, forward, or block phone calls without user authorization. This could be used for adversary goals such as audio surveillance, blocking or forwarding calls from the device owner, or C2 communication.

Several permissions may be used to programmatically control phone calls, including:

* `ANSWER_PHONE_CALLS` - Allows the application to answer incoming phone calls[Android Permissions] * `CALL_PHONE` - Allows the application to initiate a phone call without going through the Dialer interface[Android Permissions] * `PROCESS_OUTGOING_CALLS` - Allows the application to see the number being dialed during an outgoing call with the option to redirect the call to a different number or abort the call altogether[Android Permissions] * `MANAGE_OWN_CALLS` - Allows a calling application which manages its own calls through the self-managed `ConnectionService` APIs[Android Permissions] * `BIND_TELECOM_CONNECTION_SERVICE` - Required permission when using a `ConnectionService`[Android Permissions] * `WRITE_CALL_LOG` - Allows an application to write to the device call log, potentially to hide malicious phone calls[Android Permissions]

When granted some of these permissions, an application can make a phone call without opening the dialer first. However, if an application desires to simply redirect the user to the dialer with a phone number filled in, it can launch an Intent using `Intent.ACTION_DIAL`, which requires no specific permissions. This then requires the user to explicitly initiate the call or use some form of Input Injection to programmatically initiate it.

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.

Application Permission · source-mapped

DC0114 collection page — Compare manifest declarations with runtime granted state using authorized package inspection and own-app permission checks.

Providers and collection configuration

  • Android logcat: Permitted logs from a consented test device/emulator; output depends on build, permissions and instrumentation.
  • Android dumpsys: Point-in-time service/package state on an authorized development device.
  • Instrumented test application: Own-app permission, API and state callbacks; not universal visibility into other apps.
  • Use a disposable emulator or owned development device with approved debugging. Record OS/API level, app version and instrumentation privileges.
  • Collect only relevant logcat buffers/tags and service snapshots; add explicit own-app instrumentation for events absent from OS logs.
  • Forward sanitized logs and compare before/after state. Remove test data and revoke debugging access after the lab session.

Required normalized fields: package, permission, declared, granted.

adb shell dumpsys package test.example.lab

Read-only snapshot on a consented debug device. Replace the example package with your owned test app. Output and access vary by Android build; this is not a permission-request event stream.

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": "DC0114",
  "collector": "illustrative-lab-collector",
  "observation": {
    "package": "test.example.lab",
    "permission": "android.permission.CAMERA",
    "declared": true,
    "granted": false
  }
}

Visibility limits: Android tooling does not imply iOS coverage. Standard mobile apps cannot observe all other apps or protected OS internals; MDM status is not full API, filesystem or content telemetry.

File Modification · source-mapped

DC0061 collection page — Use file-integrity monitoring or scoped OS file-write auditing for general changes. Sysmon 2 records creation-time changes; it is not a general file-write event.

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: path, attribute, before, 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": "DC0061",
  "collector": "illustrative-lab-collector",
  "observation": {
    "path": "C:\\Lab\\demo.txt",
    "attribute": "content_hash",
    "before": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
    "after": "bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb"
  }
}

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.

OS API Execution · source-mapped

DC0021 collection page — Use an approved EDR trace or instrument the owned lab process at selected APIs. Define API name, caller, sanitized arguments and return status.

Providers and collection configuration

  • Enable the application audit category or instrument the owned lab application at the authorization/action boundary.
  • Define a schema with timestamp, service, actor, object, action, result and correlation ID. Export structured records through an authenticated collector.
  • Redact secrets and personal content, separate audit from debug logs, set retention and verify delivery during rotation/restart.

Required normalized fields: process_id, api, path, result.

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": "DC0021",
  "collector": "illustrative-lab-collector",
  "observation": {
    "process_id": 4200,
    "api": "CreateFileW",
    "path": "C:\\Lab\\demo.txt",
    "result": "success"
  }
}

Visibility limits: Debug output is not necessarily a durable audit trail. Application developers must emit the relevant event; installing a log pipeline does not make an absent event exist.

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

DET0703 Detection of Call Control

MITRE detection strategy

AN1822 Analytic 1822

For Android, detect Call Control from documented management, network, or vetting evidence; treat state queries as periodic observations rather than real-time events. Correlate Application Permission via Android Enterprise DPC / Application Vetting [DevicePolicyManager.getPermissionGrantState(); PackageManager manifest/requested-permission review]; File Modification via Application Vetting / Forensic Acquisition [Dynamic filesystem trace or acquired app-container/filesystem artifacts: App inserts, updates, or deletes call log records via CallLog.Calls ContentProvider immediately after call-control action — call log tampering to conceal interception]; OS API Execution via Application Vetting / Instrumented Dynamic Analysis [Dynamic API/runtime trace: App invokes TelecomManager.answerCall(), placeCall(), endCall(), or ConnectionService call-handling operations without corresponding user-initiated call UI interaction]. Alert on a sequence or state change inconsistent with the device/app baseline, approved management policy, or expected user workflow; do not infer unobserved API calls, file/process activity, or payload content from management state alone.

Platforms: Android.

  • Application Permission — android:DevicePolicyManager; channel DevicePolicyManager.getPermissionGrantState(); PackageManager manifest/requested-permission review.
  • File Modification — mobile:ForensicArtifacts; channel Dynamic filesystem trace or acquired app-container/filesystem artifacts: App inserts, updates, or deletes call log records via CallLog.Calls ContentProvider immediately after call-control action — call log tampering to conceal interception.
  • OS API Execution — mobile:DynamicAnalysis; channel Dynamic API/runtime trace: App invokes TelecomManager.answerCall(), placeCall(), endCall(), or ConnectionService call-handling operations without corresponding user-initiated call UI interaction.
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 T1616 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.

  • Mobile lab instrumentation: Per owned device, app version and permission state: unexpected API/permission changes, background activity and network destinations. OS privacy restrictions and emulator differences limit observability.
  • 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.
  • 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.
  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.

17 source-documented software associations

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 T1616 Call Control; 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 Call Control, 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.

Source-linked mitigations
  • M1011 User Guidance

    Users should be encouraged to be very careful with what applications they grant phone call-based permissions to. Further, users should not change their default call handler to applications they do not recognize.

Connected ecosystem references

Linked tags

Detection and collection

T1616 detection workspace

No reviewed association in this snapshot.

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.