1200kmSECURITY RESEARCH
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T1005 Data from Local System — Attack Simulation

Adversaries may search local system sources, such as file systems, configuration files, local databases, virtual machine files, or process memory, to find files of interest and sensitive data prior to Exfiltration. Adversaries may do this using a Command and Scripting Interpreter, such as cmd as well as a Network Device CLI, which have functionality to interact with the file system to gather information. Adversaries may also use Automated…

Complete technique description

Adversaries may search local system sources, such as file systems, configuration files, local databases, virtual machine files, or process memory, to find files of interest and sensitive data prior to Exfiltration.

Adversaries may do this using a Command and Scripting Interpreter, such as cmd as well as a Network Device CLI, which have functionality to interact with the file system to gather information.[show_run_config_cmd_cisco] Adversaries may also use Automated Collection on the local system.

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.

Command Execution · source-mapped

DC0064 collection page — Collect process command lines and relevant shell/interpreter audit; shell history alone is neither complete nor tamper-resistant.

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: interpreter, command_line, actor_uid, session_id.

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": "DC0064",
  "collector": "illustrative-lab-collector",
  "observation": {
    "interpreter": "/bin/sh",
    "command_line": "printf LAB_TELEMETRY_CHECK",
    "actor_uid": 1000,
    "session_id": "lab-session-1"
  }
}

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.

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.

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

DET0380 Detection of Local Data Collection Prior to Exfiltration

MITRE detection strategy

AN1070 Analytic 1070

Adversaries collecting local files via PowerShell, WMI, or direct file API calls often include recursive file listings, targeted file reads, and temporary file staging.

Platforms: Windows.

AN1071 Analytic 1071

Adversaries using bash scripts or tools to recursively enumerate user home directories, config files, or SSH keys.

Platforms: Linux.

AN1072 Analytic 1072

Adversary use of bash/zsh or AppleScript to locate files and exfil targets like user keychains or documents.

Platforms: macOS.

AN1073 Analytic 1073

Collection of device configuration via CLI commands (e.g., `show running-config`, `copy flash`, `more`), often followed by TFTP/SCP transfers.

Platforms: Network Devices.

AN1074 Analytic 1074

Adversaries accessing datastore or configuration files via `vim-cmd`, `esxcli`, or SCP to extract logs, VMs, or host configurations.

Platforms: ESXi.

Source rule directory and observation requirements

12 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 T1005 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.

  • 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.
  • 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.
  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.

174 source-documented software associations

Simulation design and documented procedures

Atomic evidence: 3 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.

Find and dump sqlite databases (Linux)

An adversary may know/assume that the user of a system uses sqlite databases which contain interest and sensitive data. In this test we download two databases and a sqlite dump script, then run a find command to find & dump the database content.

Pinned Atomic procedure · 00cbb875-7ae4-4cf1-b638-e543fd825300 · linux · bash.

Elevation: not declared required. Cleanup: defined upstream; review required. This is source documentation, not an execution approval.

Source-defined inputs

  • remote_url: url of remote payload (type url; source default https://raw.githubusercontent.com/redcanaryco/atomic-red-team/master/atomics/T1005/src)

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.

1 prerequisite definitions:

  • Check if running on a Debian based machine.
Copy Apple Notes database files using AppleScript

This command will copy Apple Notes database files using AppleScript as seen in Atomic Stealer.

Pinned Atomic procedure · cfb6d400-a269-4c06-a347-6d88d584d5f7 · macos · sh.

Elevation: not declared required. Cleanup: defined upstream; review required. This is source documentation, not an execution approval.

Source-defined inputs

  • destination_path: Specify the path to copy the database files into. (type path; source default /private/tmp)

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.

Search files of interest and save them to a single zip file (Windows)

This test searches for files of certain extensions and saves them to a single zip file prior to extraction.

Pinned Atomic procedure · d3d9af44-b8ad-4375-8b0a-4bff4b7e419c · windows · powershell.

Elevation: not declared required. Cleanup: defined upstream; review required. This is source documentation, not an execution approval.

Source-defined inputs

  • starting_directory: Path to starting directory for the search (type Path; source default C:\Users)
  • output_zip_folder_path: Path to directory for saving the generated zip file (type Path; source default PathToAtomicsFolder\..\ExternalPayloads\T1005)
  • file_extensions: List of file extensions to be searched and zipped, separated by comma and space (type string; source default .doc, .docx, .txt)

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 T1005 Data from Local System; 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 Data from Local System, 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
  • M1057 Data Loss Prevention

    Data loss prevention can restrict access to sensitive data and detect sensitive data that is unencrypted.

Connected ecosystem references

Linked tags

enterprisecloud-hosted-endpointnetwork-infrastructureonpremvirtualizationESXiLinuxmacOSNetwork DevicesWindowscollectionisolated_authorized_labprocedure_review_requiredtelemetry_configuration_required
Atomic candidate documentedtechniquesource_mapped

Source procedure platform / method / executor tags:

linuxautomatedbashmacosshwindowspowershell

Detection and collection

T1005 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.