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T1622 Debugger Evasion — Attack Simulation

Adversaries may employ various means to detect and avoid debuggers. Debuggers are typically used by defenders to trace and/or analyze the execution of potential malware payloads. Debugger evasion may include changing behaviors based on the results of the checks for the presence of artifacts indicative of a debugged environment. Similar to Virtualization/Sandbox Evasion, if the adversary detects a debugger, they may alter their malware to…

Complete technique description

Adversaries may employ various means to detect and avoid debuggers. Debuggers are typically used by defenders to trace and/or analyze the execution of potential malware payloads.[ProcessHacker Github]

Debugger evasion may include changing behaviors based on the results of the checks for the presence of artifacts indicative of a debugged environment. Similar to Virtualization/Sandbox Evasion, if the adversary detects a debugger, they may alter their malware to disengage from the victim or conceal the core functions of the implant. They may also search for debugger artifacts before dropping secondary or additional payloads.

Specific checks will vary based on the target and/or adversary. On Windows, this may involve Native API function calls such as <code>IsDebuggerPresent()</code> and <code> NtQueryInformationProcess()</code>, or manually checking the <code>BeingDebugged</code> flag of the Process Environment Block (PEB). On Linux, this may involve querying `/proc/self/status` for the `TracerPID` field, which indicates whether or not the process is being traced by dynamic analysis tools.[Cado Security P2PInfect 2023][Positive Technologies Hellhounds 2023] Other checks for debugging artifacts may also seek to enumerate hardware breakpoints, interrupt assembly opcodes, time checks, or measurements if exceptions are raised in the current process (assuming a present debugger would “swallow” or handle the potential error).[hasherezade debug][AlKhaser Debug][vxunderground debug]

Malware may also leverage Structured Exception Handling (SEH) to detect debuggers by throwing an exception and detecting whether the process is suspended. SEH handles both hardware and software expectations, providing control over the exceptions including support for debugging. If a debugger is present, the program’s control will be transferred to the debugger, and the execution of the code will be suspended. If the debugger is not present, control will be transferred to the SEH handler, which will automatically handle the exception and allow the program’s execution to continue.[Apriorit]

Adversaries may use the information learned from these debugger checks during automated discovery to shape follow-on behaviors. Debuggers can also be evaded by detaching the process or flooding debug logs with meaningless data via messages produced by looping Native API function calls such as <code>OutputDebugStringW()</code>.[wardle evilquest partii][Checkpoint Dridex Jan 2021]

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.

File Access · source-mapped

DC0055 collection page — Enable Audit File System plus a narrow SACL on a lab directory; on Linux select path/syscall rules and join associated Audit records.

Providers and collection configuration

  • Use a lab-only GPO under Computer Configuration → Windows Settings → Security Settings → Advanced Audit Policy Configuration. Enable the specific subcategory named below.
  • For object-level auditing, configure a narrow system access control list (SACL) on the test object in addition to policy. Do not audit an entire production directory by default.
  • Forward Security events from the responsible host or controller; retain subject and target identities, object identifiers, result and original XML. Confirm effective policy with auditpol /get /category:*.

Required normalized fields: path, access, actor, 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": "DC0055",
  "collector": "illustrative-lab-collector",
  "observation": {
    "path": "C:\\Lab\\demo.txt",
    "access": "read",
    "actor": "LAB\\analyst",
    "result": "success"
  }
}

Visibility limits: A policy checkbox alone does not guarantee an event. Host role, SACL, success/failure selection and audit policy precedence matter. Directory changes may arrive as multiple records.

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.

Process Creation · source-mapped

DC0032 collection page — Collect Sysmon ProcessCreate (1); preserve ProcessGuid and parent identifiers. Security 4688 is an alternative with separate audit/command-line settings.

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, image, parent_image, command_line, user.

<EventFiltering>
  <ProcessCreate onmatch="include">
    <Image condition="is">C:\Windows\System32\whoami.exe</Image>
  </ProcessCreate>
</EventFiltering>

This fragment only selects the named process. It is not a complete production policy. Inspect the installed schema with sysmon64 -s; preserve existing rules, then apply the reviewed complete configuration with sysmon64 -c <configuration-file>.

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": "DC0032",
  "collector": "illustrative-lab-collector",
  "observation": {
    "process_guid": "lab-process-001",
    "image": "C:\\Windows\\System32\\whoami.exe",
    "parent_image": "C:\\Windows\\System32\\cmd.exe",
    "command_line": "whoami",
    "user": "LAB\\analyst"
  }
}

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

DET0371 Detection Strategy for Debugger Evasion (T1622)

MITRE detection strategy

AN1045 Analytic 1045

Monitor for suspicious use of Windows API calls such as IsDebuggerPresent() and NtQueryInformationProcess(), or processes manually checking the BeingDebugged flag in the Process Environment Block (PEB). Detect sequences of OutputDebugStringW() calls in short intervals that may indicate debugger flooding attempts.

Platforms: Windows.

AN1046 Analytic 1046

Monitor access to /proc/self/status where TracerPID field is queried, as this is a common technique for debugger detection. Detect processes that attempt to trigger exceptions intentionally and monitor whether exception handling indicates presence of a debugger.

Platforms: Linux.

  • File Access — auditd:SYSCALL; channel open/read: Access to /proc/self/status with focus on TracerPID field.

AN1047 Analytic 1047

Detect suspicious calls to sysctl or ptrace API used to determine if a process is being debugged. Monitor for processes that flood OutputDebugString equivalents or generate abnormal exceptions to evade analysis.

Platforms: macOS.

  • OS API Execution — macos:unifiedlog; channel ptrace: Processes invoking ptrace with PTRACE_TRACEME flag.
Source rule directory and observation requirements

1 exact-tagged source rules. A source tag is a discovery aid, not a relevance verdict. Check the observation point and actual condition of each rule.

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 T1622 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.

  • 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.
  • 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.
  • 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.

25 source-documented software associations

Simulation design and documented procedures

Atomic evidence: 1 compatible documented candidates. Live lab status: not run for these imported procedures.

Use disposable lab hosts and test accounts, explicit target allowlists, a clean snapshot, bounded egress and a restore plan. Review every candidate and dependency before any execution.

Detect a Debugger Presence in the Machine

Detecting a running debugger process or if the debugger is attached to a process via PowerShell

Pinned Atomic procedure · 58bd8c8d-3a1a-4467-a69c-439c75469b07 · windows · powershell.

Elevation: required. Cleanup: not declared. This is source documentation, not an execution approval.

No input arguments declared.

Review the upstream command, dependencies and cleanup at the source link. Source defaults may refer to real infrastructure or destructive actions; they are not authorized targets. No automatic install, prerequisite download or command execution is provided.

Technique-specific experiment contract

  1. Choose one procedure implementing T1622 Debugger Evasion; 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 Debugger 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.

All-page audit and evidence inventory · This page’s machine-readable workbook

Sources and evidence boundaries

Pinned MITRE STIX source · SHA-256 81113ba98afa2928f3dcff62022539f7ce30c315c32e14422f11ff95ce534352. Definition and procedure context are reproduced from this snapshot, not independently re-investigated incidents.

Connected ecosystem references

Linked tags

Source procedure platform / method / executor tags:

Detection and collection

T1622 detection workspace

Threat actor context

These are explicit actor-to-technique associations in the existing Threat Matrix snapshot, not attribution of an event or proof that a detector identifies the actor. No tool-to-actor relationship is inferred.

Existing research

Threat Matrix: knowledge routes, evidence and actor context

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.