1200kmSECURITY RESEARCH
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T1199 Trusted Relationship — Attack Simulation

Adversaries may breach or otherwise leverage organizations who have access to intended victims. Access through trusted third party relationship abuses an existing connection that may not be protected or receives less scrutiny than standard mechanisms of gaining access to a network. Organizations often grant elevated access to second or third-party external providers in order to allow them to manage internal systems as well as cloud-based…

Complete technique description

Adversaries may breach or otherwise leverage organizations who have access to intended victims. Access through trusted third party relationship abuses an existing connection that may not be protected or receives less scrutiny than standard mechanisms of gaining access to a network.

Organizations often grant elevated access to second or third-party external providers in order to allow them to manage internal systems as well as cloud-based environments. Some examples of these relationships include IT services contractors, managed security providers, infrastructure contractors (e.g. HVAC, elevators, physical security). The third-party provider's access may be intended to be limited to the infrastructure being maintained, but may exist on the same network as the rest of the enterprise. As such, Valid Accounts used by the other party for access to internal network systems may be compromised and used.[CISA IT Service Providers]

In Office 365 environments, organizations may grant Microsoft partners or resellers delegated administrator permissions. By compromising a partner or reseller account, an adversary may be able to leverage existing delegated administrator relationships or send new delegated administrator offers to clients in order to gain administrative control over the victim tenant.[Office 365 Delegated Administration]

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.

Application Log Content · source-mapped

DC0038 collection page — Select the application event family required by the detection and document its native schema before normalization.

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: service, action, actor, record_count, 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": "DC0038",
  "collector": "illustrative-lab-collector",
  "observation": {
    "service": "lab-portal",
    "action": "export_requested",
    "actor": "lab-reader",
    "record_count": 3,
    "result": "authorized"
  }
}

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.

Logon Session Creation · source-mapped

DC0067 collection page — Enable Audit Logon and collect successful session creation on the receiving host; join session/logon IDs rather than only account names.

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: account, logon_id, logon_type, 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": "DC0067",
  "collector": "illustrative-lab-collector",
  "observation": {
    "account": "LAB\\analyst",
    "logon_id": "0x12345",
    "logon_type": 3,
    "source_ip": "192.0.2.10"
  }
}

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.

Logon Session Metadata · source-mapped

DC0088 collection page — Collect supported session inventory and correlate session IDs with authentication, logon and logoff events.

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: session_id, account, host, session_type.

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": "DC0088",
  "collector": "illustrative-lab-collector",
  "observation": {
    "session_id": "lab-session-1",
    "account": "LAB\\analyst",
    "host": "lab-host-1",
    "session_type": "interactive"
  }
}

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.

Network Connection Creation · source-mapped

DC0082 collection page — Enable scoped Sysmon NetworkConnect (3), disabled by default, or a platform-equivalent process-aware network sensor.

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, destination_ip, destination_port, protocol, initiated.

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": "DC0082",
  "collector": "illustrative-lab-collector",
  "observation": {
    "process_guid": "lab-process-001",
    "destination_ip": "198.51.100.20",
    "destination_port": 443,
    "protocol": "tcp",
    "initiated": true
  }
}

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 Content · source-mapped

DC0085 collection page — Scope approved packet capture/protocol content collection to the lab flow; retain capture provenance and truncation indicators.

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.
  • 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: flow_id, protocol, method, path, payload_excerpt.

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": "DC0085",
  "collector": "illustrative-lab-collector",
  "observation": {
    "flow_id": "lab-flow-1",
    "protocol": "http",
    "method": "GET",
    "path": "/lab-check",
    "payload_excerpt": "LAB_TELEMETRY_CHECK"
  }
}

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.

Detection rules and analytic guidance

Open the dedicated detection workspace · Existing query engineering

DET0488 Detect abuse of Trusted Relationships (third-party and delegated admin access)

MITRE detection strategy

AN1344 Analytic 1344

Behavioral chain: (1) a login from a third-party account or untrusted source network establishes an interactive/remote session; (2) the session acquires elevated privileges or accesses sensitive resources atypical for that account; (3) subsequent lateral movement or data access occurs from the same session/device. Correlate Windows logon events, token elevation/privileged use, and resource access with third-party context.

Platforms: Windows.

AN1345 Analytic 1345

Behavioral chain: (1) sshd or federated SSO logins from third-party networks or identities; (2) rapid sudo/su privilege elevation; (3) access to sensitive paths or east-west SSH. Correlate auth logs, process execution, and network flows.

Platforms: Linux.

AN1346 Analytic 1346

Behavioral chain: (1) third-party interactive login or mobileconfig-based device enrollment; (2) privilege use or admin group change; (3) lateral movement mounts/ssh. Correlate unified logs and network telemetry.

Platforms: macOS.

AN1347 Analytic 1347

Behavioral chain: (1) delegated admin or external identity establishes session (e.g., partner/reseller DAP, B2B guest, SAML/OAuth trust); (2) role elevation or app consent/permission grant; (3) downstream privileged actions in the tenant. Correlate IdP sign-in, admin/role assignment, and consent/admin-on-behalf events.

Platforms: Identity Provider.

  • Logon Session Creation — azure:signinlogs; channel InteractiveUser, ServicePrincipalSignIn.
  • Logon Session Metadata — azure:audit; channel Add delegated admin / Assign admin roles / Update application consent.
  • Application Log Content — m365:unified; channel Set-PartnerOfRecord / CompanyAdministrator role assignments / New-DelegatedAdminRelationship.

AN1348 Analytic 1348

Behavioral chain: (1) cross-account or third-party principal assumes a role into the tenant/subscription/project; (2) privileged API calls are made in short succession; (3) access originates from unfamiliar networks or geos. Correlate assume-role/federation events with sensitive API usage.

Platforms: IaaS.

  • Logon Session Creation — AWS:CloudTrail; channel AssumeRole,AssumeRoleWithSAML,AssumeRoleWithWebIdentity.
  • Application Log Content — AWS:CloudTrail; channel CreateUser|AttachRolePolicy|CreateAccessKey|UpdateAssumeRolePolicy|CreateLoginProfile.
  • Logon Session Metadata — gcp:audit; channel google.iam.credentials.generateAccessToken / serviceAccountTokenCreator.

AN1349 Analytic 1349

Behavioral chain: (1) third-party app or admin connects via OAuth/marketplace install; (2) high-privilege scopes granted; (3) anomalous actions (mass read/exports, admin changes).

Platforms: SaaS.

AN1350 Analytic 1350

Behavioral chain: (1) delegated administration offers/relationships created or modified by partner tenants; (2) mailbox delegation/impersonation enabled; (3) follow-on access from partner IPs.

Platforms: Office Suite.

  • Application Log Content — m365:unified; channel Add-DelegatedAdmin, Set-PartnerOfRecord, Add-MailboxPermission, Set-OrganizationRelationship.
  • Logon Session Creation — azure:signinlogs; channel InteractiveUser, NonInteractiveUser.
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 T1199 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.

  • 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.
  • 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.
  • 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.
  • 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.
  • 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.

Simulation design and documented procedures

Atomic evidence: no compatible candidate in this snapshot. 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.

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

  1. Choose one procedure implementing T1199 Trusted Relationship; 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 Trusted Relationship, 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

Connected ecosystem references

Linked tags

Detection and collection

T1199 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

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.