1200kmSECURITY RESEARCH
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T1195 Supply Chain Compromise — Attack Simulation

Adversaries may manipulate products or product delivery mechanisms prior to receipt by a final consumer for the purpose of data or system compromise. Supply chain compromise can take place at any stage of the supply chain including: * Manipulation of development tools * Manipulation of a development environment * Manipulation of source code repositories (public or private) * Manipulation of source code in open-source dependencies * Manipulation…

Complete technique description

Adversaries may manipulate products or product delivery mechanisms prior to receipt by a final consumer for the purpose of data or system compromise.

Supply chain compromise can take place at any stage of the supply chain including:

* Manipulation of development tools * Manipulation of a development environment * Manipulation of source code repositories (public or private) * Manipulation of source code in open-source dependencies * Manipulation of software update/distribution mechanisms * Compromised/infected system images (removable media infected at the factory)[IBM Storwize][Schneider Electric USB Malware]
* Replacement of legitimate software with modified versions
* Sales of modified/counterfeit products to legitimate distributors
* Shipment interdiction

While supply chain compromise can impact any component of hardware or software, adversaries looking to gain execution have often focused on malicious additions to legitimate software in software distribution or update channels.[Avast CCleaner3 2018][Microsoft Dofoil 2018][Command Five SK 2011] Adversaries may limit targeting to a desired victim set or distribute malicious software to a broad set of consumers but only follow up with specific victims.[Symantec Elderwood Sept 2012][Avast CCleaner3 2018][Command Five SK 2011] Popular open-source projects that are used as dependencies in many applications may also be targeted as a means to add malicious code to users of the dependency.[Trendmicro NPM Compromise]

In some cases, adversaries may conduct “second-order” supply chain compromises by leveraging the access gained from an initial supply chain compromise to further compromise a software component.[Krebs 3cx overview 2023] This may allow the threat actor to spread to even more victims.

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.

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.

File Metadata · source-mapped

DC0059 collection page — Collect scoped file inventory/FIM metadata with hash algorithm and observation time; preserve original timestamps separately from collector time.

Providers and collection configuration

  • osquery: Scheduled host-state queries; supported tables and privileges vary by OS. Select a table that actually exposes the required object.
  • Linux Audit plus inventory snapshots: Events explain changes; snapshots describe state at collection time.
  • Define the inventory query, allowed host set, interval and least-privileged reader. Store a stable asset ID, observation time and collector version.
  • Keep successive snapshots and calculate additions, removals and changed attributes. Pair state changes with audit events when available.
  • Export collector health and missed-poll counts so a missing snapshot is not misclassified as a missing asset.

Required normalized fields: path, size_bytes, sha256, owner_uid.

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": "DC0059",
  "collector": "illustrative-lab-collector",
  "observation": {
    "path": "/opt/lab/demo.txt",
    "size_bytes": 64,
    "sha256": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
    "owner_uid": 1000
  }
}

Visibility limits: Snapshots miss short-lived objects and do not identify who caused a change. A generic inventory agent is not guaranteed to expose firmware or kernel-level details.

File Modification · source-mapped

DC0061 collection page — Use file-integrity monitoring or scoped OS file-write auditing for general changes. Sysmon 2 records creation-time changes; it is not a general file-write event.

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: path, attribute, before, after.

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": "DC0061",
  "collector": "illustrative-lab-collector",
  "observation": {
    "path": "C:\\Lab\\demo.txt",
    "attribute": "content_hash",
    "before": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
    "after": "bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbb"
  }
}

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.

Module Load · source-mapped

DC0016 collection page — Scope Sysmon ImageLoad (7) to lab processes/paths; retain module hash, signer and destination process. Inventory alone does not prove a module loaded.

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, image_loaded, signed, action.

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": "DC0016",
  "collector": "illustrative-lab-collector",
  "observation": {
    "process_id": 4200,
    "image_loaded": "C:\\Lab\\demo.dll",
    "signed": false,
    "action": "load"
  }
}

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 Flow · source-mapped

DC0078 collection page — Collect Zeek conn.log, Suricata flow events or exporter equivalents, including observation point and sampling settings.

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.
  • AWS VPC Flow Logs: IP traffic metadata alternative; no packet payload or DNS answer history, and some traffic is not logged.
  • 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: source_ip, destination_ip, destination_port, protocol, bytes_sent, bytes_received.

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": "DC0078",
  "collector": "illustrative-lab-collector",
  "observation": {
    "source_ip": "192.0.2.10",
    "destination_ip": "198.51.100.20",
    "destination_port": 443,
    "protocol": "tcp",
    "bytes_sent": 128,
    "bytes_received": 512
  }
}

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.

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.

Process Modification · source-mapped

DC0020 collection page — Use Sysmon ProcessTampering (25) for supported detections and corroborating EDR/memory evidence; it is not a record of every memory write.

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, observation, sensor.

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": "DC0020",
  "collector": "illustrative-lab-collector",
  "observation": {
    "process_id": 4200,
    "observation": "process_image_changed",
    "sensor": "lab-instrumentation"
  }
}

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

DET0537 Behavioral detection for Supply Chain Compromise (package/update tamper → install → first-run)

MITRE detection strategy

AN1480 Analytic 1480

1) New or updated software is delivered/installed from atypical sources or with signature/hash mismatches; 2) installer/updater writes binaries to unexpected paths or replaces existing signed files; 3) first run causes unsigned/abnormally signed modules to load or child processes to execute, optionally followed by network egress to new destinations.

Platforms: Windows.

  • Process Creation — WinEventLog:Sysmon; channel EventCode=1.
  • Module Load — WinEventLog:Sysmon; channel EventCode=7.
  • File Creation — WinEventLog:Sysmon; channel EventCode=11.
  • File Metadata — WinEventLog:Microsoft-Windows-CodeIntegrity/Operational; channel CodeIntegrity reports 'Invalid image hash' or 'Unsigned image' for new/updated binaries.
  • Network Traffic Flow — NSM:Flow; channel First-time egress from host after new install to unknown update endpoints.

AN1481 Analytic 1481

1) Package manager or curl/wget installs/upgrades from non-approved repos or unsigned packages; 2) new ELF written into PATH directories or replacement of existing binaries/libraries; 3) first run leads to unexpected child processes or outbound connections.

Platforms: Linux.

AN1482 Analytic 1482

1) pkg/notarization installs from atypical sources or with Gatekeeper/AMFI warnings; 2) new Mach-O written into /Applications or ~/Library paths or substitution of signed components; 3) first run from installer spawns unsigned children or exfil.

Platforms: macOS.

  • File Metadata — macos:unifiedlog; channel installer or system_installd 'PackageKit: install succeeded/failed' with non-notarized or unknown signer.
  • Process Creation — macos:osquery; channel launchd, processes.
  • File Modification — macos:endpointsecurity; channel write, rename.
  • Network Traffic Flow — NSM:Flow; channel New egress from app just installed to unknown update endpoints.
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

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.

  • 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.
  • Host state and inventory: Compare authorized state snapshots: first-seen drivers/services/modules, unexpected configuration drift and integrity changes. Record collection cadence; absence in a sample is not evidence of deletion.
  • 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.

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.

2 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.

Octopus Scanner Malware Open Source Supply Chain

This test simulates an adversary Octopus drop the RAT dropper ExplorerSync.db octopus-scanner-malware-open-source-supply-chain the-supreme-backdoor-factory

Pinned Atomic procedure · 82a9f001-94c5-495e-9ed5-f530dbded5e2 · windows · command_prompt.

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

Source-defined inputs

  • rat_payload: RAT dropper ExplorerSync.db (type path; source default $env:TEMP\ExplorerSync.db)

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:

  • ExplorerSync.db must exist on disk at specified location (#{rat_payload})

Technique-specific experiment contract

  1. Choose one procedure implementing T1195 Supply Chain Compromise; 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 Supply Chain Compromise, 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
  • M1013 Application Developer Guidance

    Application developers should be cautious when selecting third-party libraries to integrate into their application. Additionally, where possible, developers should lock software dependencies to specific versions rather than pulling the latest version on build.[Cider Security Top 10 CICD Security Risks]

  • M1016 Vulnerability Scanning

    Continuous monitoring of vulnerability sources and the use of automatic and manual code review tools should also be implemented as well.[OWASP Top 10]

  • M1018 User Account Management

    Implement robust user account management practices to limit permissions associated with software execution. Ensure that software runs with the lowest necessary privileges, avoiding the use of root or administrator accounts when possible. By restricting permissions, you can minimize the risk of propagation and unauthorized actions in the event of a supply chain compromise, reducing the attack surface for adversaries to exploit within compromised systems.

  • M1033 Limit Software Installation

    Where possible, consider requiring developers to pull from internal repositories containing verified and approved packages rather than from external ones.[Cider Security Top 10 CICD Security Risks]

  • M1046 Boot Integrity

    Use secure methods to boot a system and verify the integrity of the operating system and loading mechanisms.

  • M1051 Update Software

    A patch management process should be implemented to check unused dependencies, unmaintained and/or previously vulnerable dependencies, unnecessary features, components, files, and documentation.

Connected ecosystem references

Linked tags

Source procedure platform / method / executor tags:

Detection and collection

T1195 detection workspace

No reviewed association in this snapshot.

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.