Adversaries may employ various means to detect and avoid virtualization and analysis environments. This may include changing behaviors after checking for the presence of artifacts indicative of a virtual machine environment (VME) or sandbox. If the adversary detects a VME, they may alter their malware’s behavior to disengage from the victim or conceal the core functions of the payload. They may also search for VME artifacts before dropping…
Complete technique description
Adversaries may employ various means to detect and avoid virtualization and analysis environments. This may include changing behaviors after checking for the presence of artifacts indicative of a virtual machine environment (VME) or sandbox. If the adversary detects a VME, they may alter their malware’s behavior to disengage from the victim or conceal the core functions of the payload. They may also search for VME artifacts before dropping further payloads. Adversaries may use the information learned from Virtualization/Sandbox Evasion during automated discovery to shape follow-on behaviors.
Adversaries may use several methods to accomplish Virtualization/Sandbox Evasion such as checking for system artifacts associated with analysis or virtualization. Adversaries may also check for legitimate user activity to help determine if it is in an analysis environment.
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.
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.
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.
For Android, detect Evade Analysis Environment primarily during application vetting or controlled analysis rather than assuming a live device SOC feed. Correlate API Calls via Application Vetting / Instrumented Dynamic Analysis [Dynamic API/runtime trace: APK or IPA contains SystemProperties.get() calls, Runtime.exec getprop invocations, or code patterns checking for emulator artifacts (ro.product.model=sdk, IMEI=000000, screen size, sensor absence) — static detection of environment-check co]. 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: APK or IPA contains SystemProperties.get() calls, Runtime.exec getprop invocations, or code patterns checking for emulator artifacts (ro.product.model=sdk, IMEI=000000, screen size, sensor absence) — static detection of environment-check co.
For iOS, detect Evade Analysis Environment primarily during application vetting or controlled analysis rather than assuming a live device SOC feed. Correlate API Calls via Application Vetting / Instrumented Dynamic Analysis [Dynamic API/runtime trace: IPA contains UIDevice.currentDevice.model checks for Simulator strings, CMMotionManager.isDeviceMotionAvailable comparisons, or other Simulator-detection patterns — static detection of iOS environment-check code]. 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: IPA contains UIDevice.currentDevice.model checks for Simulator strings, CMMotionManager.isDeviceMotionAvailable comparisons, or other Simulator-detection patterns — static detection of iOS environment-check code.
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
Read the actual condition and logsource; identify attacker-side, victim-side or third-party visibility.
Map native sensor fields, parse times and identities, then compile for the selected backend.
Replay a behavior-positive case, a normal control, an authorized look-alike and a missing-telemetry case.
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 T1633 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.
Define an entity/peer group and feature; exclude the evaluation period from baseline training.
Use representative normal and maintenance activity. Do not invent a production threshold from a synthetic example.
Evaluate held-out behavior-positive and benign cases; measure false positives, misses and telemetry loss separately.
Keep abnormality separate from maliciousness. Correlate with the behavior-specific source evidence.
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.
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
Choose one procedure implementing T1633 Virtualization/Sandbox Evasion; identify the observable behavior in the source definition, not just its tactic.
Record exact target, tool/version, inputs, privileges, network limits and approval. Never run an imported default target automatically.
Enable the collection sources above and verify a benign baseline reaches the detector.
Run only the approved isolated scenario; capture native events and an independent behavior observable.
Evaluate the exact rule/model, restore the lab, and preserve configuration, event hashes, alerts, controls and misses.
This fixture exercises the listed collection fields. It does not reproduce Virtualization/Sandbox Evasion, 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.
Pinned MITRE STIX source · SHA-256 824f7d8a37e7893b29e4c6ca6d87b5fbbf3b228ec6384f1a69ee20d523ff59e5. Definition and procedure context are reproduced from this snapshot, not independently re-investigated incidents.
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.