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T1418 Software Discovery — Attack Simulation

Adversaries may attempt to get a listing of applications that are installed on a device. Adversaries may use the information from Software Discovery during automated discovery to shape follow-on behaviors, including whether or not to fully infect the target and/or attempts specific actions. Adversaries may attempt to enumerate applications for a variety of reasons, such as figuring out what security measures are present or to identify the…

Complete technique description

Adversaries may attempt to get a listing of applications that are installed on a device. Adversaries may use the information from Software Discovery during automated discovery to shape follow-on behaviors, including whether or not to fully infect the target and/or attempts specific actions.

Adversaries may attempt to enumerate applications for a variety of reasons, such as figuring out what security measures are present or to identify the presence of target applications.

Official technique definition · Open in the interactive matrix

Parent and sub-techniques

Related pages are navigation context. Their tools, rules and lab results are not automatically inherited.

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.

API Calls · source-mapped

DC0112 collection page — Instrument selected APIs in the owned test app or approved research build; log caller, API, sanitized argument class and return status.

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, api, result, thread.

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": "DC0112",
  "collector": "illustrative-lab-collector",
  "observation": {
    "package": "test.example.lab",
    "api": "android.hardware.camera2.CameraManager.openCamera",
    "result": "permission_denied",
    "thread": "main"
  }
}

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.

Application State · source-mapped

DC0123 collection page — Instrument the owned app lifecycle and corroborate permitted service snapshots; distinguish app events from inferred gateway activity.

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, state_before, state_after, source.

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": "DC0123",
  "collector": "illustrative-lab-collector",
  "observation": {
    "package": "test.example.lab",
    "state_before": "background",
    "state_after": "foreground",
    "source": "own_app_callback"
  }
}

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.

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.

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

DET0600 Detection of Software Discovery

MITRE detection strategy

AN1646 Analytic 1646

For Android, detect Software Discovery by correlating analyst-visible device/network evidence and management state; use streaming or batched telemetry only where the documented collector is deployed. Correlate API Calls via Application Vetting / Instrumented Dynamic Analysis [Dynamic API/runtime trace: PackageManager.getInstalledPackages() or getInstalledApplications() called by app NOT IN $AppEnumAllowList$]; Application State via Android Enterprise / EMM [Managed package inventory/status and package metadata]; Network Connection Creation via Android Enterprise Network Logging / Enterprise VPN [DevicePolicyManager.retrieveNetworkLogs(): DnsEvent / ConnectEvent; VPN flow metadata]. 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.

  • API Calls — mobile:DynamicAnalysis; channel Dynamic API/runtime trace: PackageManager.getInstalledPackages() or getInstalledApplications() called by app NOT IN $AppEnumAllowList$.
  • Application State — android:EMM; channel Managed package inventory/status and package metadata.
  • Network Connection Creation — android:EnterpriseNetworkLog; channel DevicePolicyManager.retrieveNetworkLogs(): DnsEvent / ConnectEvent; VPN flow metadata.

AN1647 Analytic 1647

For iOS, detect Software Discovery by correlating analyst-visible device/network evidence and management state; use streaming or batched telemetry only where the documented collector is deployed. Correlate API Calls via Application Vetting / Instrumented Dynamic Analysis [Dynamic API/runtime trace: UIApplication.canOpenURL() called > $URLProbeThreshold$ times with schemes NOT declared in app's LSApplicationQueriesSchemes within $ProbeWindow$]; Application State via Apple MDM [InstalledApplicationList / ManagedApplicationList]; Network Connection Creation via Apple Network Extension / Enterprise VPN [NEFilterFlow / per-app VPN / secure-web-gateway flow metadata]. 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: iOS.

  • API Calls — mobile:DynamicAnalysis; channel Dynamic API/runtime trace: UIApplication.canOpenURL() called > $URLProbeThreshold$ times with schemes NOT declared in app's LSApplicationQueriesSchemes within $ProbeWindow$.
  • Application State — iOS:MDM; channel InstalledApplicationList / ManagedApplicationList.
  • Network Connection Creation — iOS:NetworkExtension; channel NEFilterFlow / per-app VPN / secure-web-gateway flow metadata.
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 T1418 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.
  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

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.

50 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 T1418 Software Discovery; 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 Software Discovery, 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
  • M1006 Use Recent OS Version

    Android 11 introduced privacy enhancements to package visibility, filtering results that are returned from the package manager. iOS 12 removed the private API that could previously be used to list installed applications on non-app store applications.[Android Package Visibility]

  • M1011 User Guidance

    iOS users should be instructed to not download applications from unofficial sources, as applications distributed via the Apple App Store cannot list installed applications on a device.

Connected ecosystem references

Linked tags

Detection and collection

T1418 detection workspace

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.