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1200KM / simulation

T1589 Gather Victim Identity Information — Attack Simulation

Adversaries may gather information about the victim's identity that can be used during targeting. Information about identities may include a variety of details, including personal data (ex: employee names, email addresses, security question responses, etc.) as well as sensitive details such as credentials or multi-factor authentication (MFA) configurations. Adversaries may gather this information in various ways, such as direct elicitation via…

Complete technique description

Adversaries may gather this information in various ways, such as direct elicitation via Phishing for Information. Information about users could also be enumerated via other active means (i.e. Active Scanning) such as probing and analyzing responses from authentication services that may reveal valid usernames in a system or permitted MFA /methods associated with those usernames.[GrimBlog UsernameEnum][Obsidian SSPR Abuse 2023] Information about victims may also be exposed to adversaries via online or other accessible data sets (ex: Social Media or Search Victim-Owned Websites).[OPM Leak][Register Deloitte][Register Uber][Detectify Slack Tokens][Forbes GitHub Creds][GitHub truffleHog][GitHub Gitrob][CNET Leaks]

Gathering this information may reveal opportunities for other forms of reconnaissance (ex: Search Open Websites/Domains or Phishing for Information), establishing operational resources (ex: Compromise Accounts), and/or initial access (ex: Phishing or Valid Accounts).

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.

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

DET0841 Detection of Gather Victim Identity Information

MITRE detection strategy

AN1973 Analytic 1973

Monitor for suspicious network traffic that could be indicative of probing for user information, such as large/iterative quantities of authentication requests originating from a single source (especially if the source is known to be associated with an adversary/botnet). Analyzing web metadata may also reveal artifacts that can be attributed to potentially malicious activity, such as referer or user-agent string HTTP/S fields.

Platforms: PRE.

Network Traffic Content — Network Traffic; channel not specified upstream.

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.

Azure AD Account Credential Leaked — test; product: azure; service: riskdetection.

Before treating a rule as coverage

Read the actual condition and logsource; identify attacker-side, victim-side or third-party visibility.
Map native sensor fields, parse times and identities, then compile for the selected backend.
Replay a behavior-positive case, a normal control, an authorized look-alike and a missing-telemetry case.
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 T1589 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.

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.

Define an entity/peer group and feature; exclude the evaluation period from baseline training.
Use representative normal and maintenance activity. Do not invent a production threshold from a synthetic example.
Evaluate held-out behavior-positive and benign cases; measure false positives, misses and telemetry loss separately.
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

Choose one procedure implementing T1589 Gather Victim Identity Information; identify the observable behavior in the source definition, not just its tactic.
Record exact target, tool/version, inputs, privileges, network limits and approval. Never run an imported default target automatically.
Enable the collection sources above and verify a benign baseline reaches the detector.
Run only the approved isolated scenario; capture native events and an independent behavior observable.
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 Gather Victim Identity Information, 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

M1056 Pre-compromise
This technique cannot be easily mitigated with preventive controls since it is based on behaviors performed outside of the scope of enterprise defenses and controls. Efforts should focus on minimizing the amount and sensitivity of data available to external parties.

Connected ecosystem references

Linked tags

No Atomic candidate in snapshot technique source_mapped

Detection and collection

T1589 detection workspace

Network Traffic Content · DC0085

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.