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T1635 Steal Application Access Token — Attack Simulation

Adversaries can steal user application access tokens as a means of acquiring credentials to access remote systems and resources. This can occur through social engineering or URI hijacking and typically requires user action to grant access, such as through a system “Open With” dialogue. Application access tokens are used to make authorized API requests on behalf of a user and are commonly used as a way to access resources in cloud-based…

Complete technique description

Adversaries can steal user application access tokens as a means of acquiring credentials to access remote systems and resources. This can occur through social engineering or URI hijacking and typically requires user action to grant access, such as through a system “Open With” dialogue.

Application access tokens are used to make authorized API requests on behalf of a user and are commonly used as a way to access resources in cloud-based applications and software-as-a-service (SaaS).[Auth0 - Why You Should Always Use Access Tokens to Secure APIs Sept 2019] OAuth is one commonly implemented framework used to issue tokens to users for access to systems. An application desiring access to cloud-based services or protected APIs can gain entry through OAuth 2.0 using a variety of authorization protocols. An example of a commonly-used sequence is Microsoft's Authorization Code Grant flow.[Microsoft Identity Platform Protocols May 2019][Microsoft - OAuth Code Authorization flow - June 2019] An OAuth access token enables a third-party application to interact with resources containing user data in the ways requested without requiring user credentials.

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 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.

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.

Network Traffic Content · source-mapped

DC0085 collection page — Scope approved packet capture/protocol content collection to the lab flow; retain capture provenance and truncation indicators.

Providers and collection configuration

  • Zeek: Connection and protocol metadata from traffic visible to the sensor.
  • Suricata EVE: Configured flow, alert, DNS, HTTP, TLS and protocol records.
  • Use an authorized lab TAP/SPAN, virtual mirror or gateway interface. Define which traffic crosses it; avoid assuming visibility into every segment.
  • Enable the required Zeek analyzers or Suricata EVE event types. Export logs with sensor identity, clock synchronization and flow correlation identifiers.
  • Monitor capture loss, truncation and exporter sampling. Capture payload only with approval and restrictive retention; encryption normally prevents plaintext inspection.

Required normalized fields: flow_id, protocol, method, path, payload_excerpt.

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": "DC0085",
  "collector": "illustrative-lab-collector",
  "observation": {
    "flow_id": "lab-flow-1",
    "protocol": "http",
    "method": "GET",
    "path": "/lab-check",
    "payload_excerpt": "LAB_TELEMETRY_CHECK"
  }
}

Visibility limits: Flows are not packet payloads. NAT, asymmetric routes, encryption, missing mirrors and sampling can hide attribution or content. A destination connection alone does not prove malicious intent.

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

DET0656 Detection of Steal Application Access Token

MITRE detection strategy

AN1743 Analytic 1743

For Android, detect Steal Application Access Token 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.queryIntentActivities() returns handler_count > 1 for custom URI scheme]; Application Permission via Android Enterprise DPC / Application Vetting [DevicePolicyManager.getPermissionGrantState(); PackageManager manifest/requested-permission review]; Network Traffic Content via Enterprise Secure Web Gateway / Proxy [DNS/HTTP(S) inspection or proxy transaction metadata where enterprise decryption/inspection is deployed]. 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.queryIntentActivities() returns handler_count > 1 for custom URI scheme.
  • Application Permission — android:DevicePolicyManager; channel DevicePolicyManager.getPermissionGrantState(); PackageManager manifest/requested-permission review.
  • Network Traffic Content — webproxy:applog; channel DNS/HTTP(S) inspection or proxy transaction metadata where enterprise decryption/inspection is deployed.

AN1744 Analytic 1744

For iOS, detect Steal Application Access Token by correlating analyst-visible device/network evidence and management state; use streaming or batched telemetry only where the documented collector is deployed. Correlate Application Permission via Application Vetting [Code-signing entitlements and Info.plist privacy usage-description keys]; Network Connection Creation via Apple Network Extension / Enterprise VPN [NEFilterFlow / per-app VPN / secure-web-gateway flow metadata]; Network Traffic Content via Enterprise Secure Web Gateway / Proxy [DNS/HTTP(S) inspection or proxy transaction metadata where enterprise decryption/inspection is deployed]. 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.

  • Application Permission — mobile:ApplicationVetting; channel Code-signing entitlements and Info.plist privacy usage-description keys.
  • Network Connection Creation — iOS:NetworkExtension; channel NEFilterFlow / per-app VPN / secure-web-gateway flow metadata.
  • Network Traffic Content — webproxy:applog; channel DNS/HTTP(S) inspection or proxy transaction metadata where enterprise decryption/inspection is deployed.
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 T1635 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.
  • Network and protocol telemetry: Per source and observation point: connection rate, destination-host/port fan-out, response/failure ratio and previously unseen destinations. Compare equivalent time windows; separate authorized scanners, NAT and sampling effects.
  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 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 T1635 Steal Application Access Token; 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 Steal Application Access Token, 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

Connected ecosystem references

Linked tags

Detection and collection

T1635 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.