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T1119 Automated Collection — Attack Simulation

Once established within a system or network, an adversary may use automated techniques for collecting internal data. Methods for performing this technique could include use of a Command and Scripting Interpreter to search for and copy information fitting set criteria such as file type, location, or name at specific time intervals. In cloud-based environments, adversaries may also use cloud APIs, data pipelines, command line interfaces, or…

Complete technique description

Once established within a system or network, an adversary may use automated techniques for collecting internal data. Methods for performing this technique could include use of a Command and Scripting Interpreter to search for and copy information fitting set criteria such as file type, location, or name at specific time intervals.

In cloud-based environments, adversaries may also use cloud APIs, data pipelines, command line interfaces, or extract, transform, and load (ETL) services to automatically collect data.[Mandiant UNC3944 SMS Phishing 2023]

This functionality could also be built into remote access tools.

This technique may incorporate use of other techniques such as File and Directory Discovery and Lateral Tool Transfer to identify and move files, as well as Cloud Service Dashboard and Cloud Storage Object Discovery to identify resources in cloud environments.

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.

File Creation · source-mapped

DC0039 collection page — Scope Sysmon FileCreate (11) to the lab directory; retain the process and file path. Differentiate creation/overwrite if the sensor can.

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_id, path, action, size_bytes.

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": "DC0039",
  "collector": "illustrative-lab-collector",
  "observation": {
    "process_id": 4200,
    "path": "C:\\Lab\\demo.txt",
    "action": "create",
    "size_bytes": 64
  }
}

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.

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.

Script Execution · source-mapped

DC0029 collection page — Collect PowerShell 4104 with script-block ID and fragment sequence; instrument other engines separately rather than assigning them the same event ID.

Providers and collection configuration

  • Enable Script Block Logging through the policy/configuration for the installed edition. Forward Microsoft-Windows-PowerShell/Operational for Windows PowerShell, or PowerShellCore/Operational for PowerShell 7.
  • Retain script-block ID and fragment ordering alongside process creation. Protect access to collected script text; secrets may be included.
  • On Linux, use narrowly scoped Audit execution rules for the lab account and supported architectures, and retain joined SYSCALL/EXECVE/PATH records.

Required normalized fields: engine, script_block_id, fragment, fragments_total, script_text.

Get-WinEvent -FilterHashtable @{
  LogName = 'Microsoft-Windows-PowerShell/Operational'
  Id = 4104
} -MaxEvents 5

Read-only check after Script Block Logging is configured. For PowerShell 7 use its registered PowerShellCore/Operational channel. Missing events are not proof of no execution; check policy, channel and permissions.

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": "DC0029",
  "collector": "illustrative-lab-collector",
  "observation": {
    "engine": "PowerShell",
    "script_block_id": "lab-script-1",
    "fragment": 1,
    "fragments_total": 1,
    "script_text": "Write-Output \"LAB_TELEMETRY_CHECK\""
  }
}

Visibility limits: Script content and process command lines are different signals. Logging may be partial, fragmented, filtered or disabled; never assume a command line reveals everything executed.

User Account Authentication · source-mapped

DC0002 collection page — Collect successful and failed sign-ins, authentication method, application and conditional-access context; distinguish account validation from session creation.

Providers and collection configuration

  • Enable/export the required identity sign-in and audit categories from the lab tenant to a protected destination. Document license, role and retention requirements.
  • Correlate issuance or administrative changes with later sign-ins using non-secret credential IDs, application IDs, user IDs and correlation IDs.
  • Exclude passwords, bearer tokens, cookies and private keys. Record success, failure, authentication context and application result separately.

Required normalized fields: account, application, result, reason, source_ip.

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": "DC0002",
  "collector": "illustrative-lab-collector",
  "observation": {
    "account": "analyst@example.test",
    "application": "lab-portal",
    "result": "failure",
    "reason": "invalid_credential",
    "source_ip": "192.0.2.10"
  }
}

Visibility limits: A token creation record is not evidence of token use; a sign-in is not a complete record of every resource access. Some provider-side data is unavailable to the customer.

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

DET0186 Automated File and API Collection Detection Across Platforms

MITRE detection strategy

AN0531 Analytic 0531

Automated execution of native utilities and scripts to discover, enumerate, and exfiltrate files and clipboard content. Focus is on detecting repeated file access, scripting engine use, and use of command-line utilities commonly leveraged by collection scripts.

Platforms: Windows.

AN0532 Analytic 0532

Repeated or automated access to user document directories or clipboard using shell scripts or utilities like xclip/pbpaste. Detectable via auditd syscall logs or osquery file events.

Platforms: Linux.

AN0533 Analytic 0533

Use of pbpaste, AppleScript, or third-party automation frameworks (e.g., Automator) to collect clipboard or file content in bursts. Observable via unified logs.

Platforms: macOS.

  • Process Creation — macos:unifiedlog; channel logMessage contains pbpaste or osascript.
  • Script Execution — macos:unifiedlog; channel subsystem=launchservices.

AN0534 Analytic 0534

Suspicious sign-ins to Graph API or sensitive resources using non-browser scripting agents (e.g., Python, PowerShell), often for programmatic access to mailbox or OneDrive content.

Platforms: SaaS.

Source rule directory and observation requirements

4 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

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.
  • 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.
  • Script and command execution: Per host role and principal: rare interpreters, command argument patterns and parent-child sequences. Normalize scripts carefully; obfuscation, administrative automation and missing command lines change visibility.
  • Identity and SaaS: Per identity and application: first-seen clients/resources, changes in authentication failures and session patterns, and unusual permission changes. Separate automation, travel, shared egress and identity-provider policy changes.
  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: 4 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.

Automated Collection PowerShell

Automated Collection. Upon execution, check the users temp directory (%temp%) for the folder T1119_powershell_collection
to see what was collected.

Pinned Atomic procedure · 634bd9b9-dc83-4229-b19f-7f83ba9ad313 · windows · powershell.

Elevation: not declared required. Cleanup: defined upstream; review required. 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.

Recon information for export with Command Prompt

collect information for exfiltration. Upon execution, check the users temp directory (%temp%) for files T1119_*.txt
to see what was collected.

Pinned Atomic procedure · aa1180e2-f329-4e1e-8625-2472ec0bfaf3 · windows · command_prompt.

Elevation: not declared required. Cleanup: defined upstream; review required. 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.

Recon information for export with PowerShell

collect information for exfiltration. Upon execution, check the users temp directory (%temp%) for files T1119_*.txt
to see what was collected.

Pinned Atomic procedure · c3f6d794-50dd-482f-b640-0384fbb7db26 · windows · powershell.

Elevation: not declared required. Cleanup: defined upstream; review required. 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.

Automated Collection Command Prompt

Automated Collection. Upon execution, check the users temp directory (%temp%) for the folder T1119_command_prompt_collection
to see what was collected.

Pinned Atomic procedure · cb379146-53f1-43e0-b884-7ce2c635ff5b · windows · command_prompt.

Elevation: not declared required. Cleanup: defined upstream; review required. 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 T1119 Automated Collection; 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 Automated Collection, 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.

Source-linked mitigations
  • M1029 Remote Data Storage

    Encryption and off-system storage of sensitive information may be one way to mitigate collection of files, but may not stop an adversary from acquiring the information if an intrusion persists over a long period of time and the adversary is able to discover and access the data through other means.

  • M1041 Encrypt Sensitive Information

    Encryption and off-system storage of sensitive information may be one way to mitigate collection of files, but may not stop an adversary from acquiring the information if an intrusion persists over a long period of time and the adversary is able to discover and access the data through other means. Strong passwords should be used on certain encrypted documents that use them to prevent offline cracking through Brute Force techniques.

Connected ecosystem references

Linked tags

Source procedure platform / method / executor tags:

Detection and collection

T1119 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

Connected anomaly research

Curated research views reached through an exact source technique, a catalog model, or a reviewed collection reference. These are navigation associations, not claims of detector effectiveness or sensor equivalence.

Telemetry contracts · Maintained query examples · Validation and blind spots

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.