1200kmSECURITY RESEARCH
Loading interactive filters…

1200KM / simulation

T1587 Develop Capabilities — Attack Simulation

Adversaries may build capabilities that can be used during targeting. Rather than purchasing, freely downloading, or stealing capabilities, adversaries may develop their own capabilities in-house. This is the process of identifying development requirements and building solutions such as malware, exploits, and self-signed certificates. Adversaries may develop capabilities to support their operations throughout numerous phases of the adversary…

Complete technique description

Adversaries may build capabilities that can be used during targeting. Rather than purchasing, freely downloading, or stealing capabilities, adversaries may develop their own capabilities in-house. This is the process of identifying development requirements and building solutions such as malware, exploits, and self-signed certificates. Adversaries may develop capabilities to support their operations throughout numerous phases of the adversary lifecycle.[Mandiant APT1][Kaspersky Sofacy][Bitdefender StrongPity June 2020][Talos Promethium June 2020]

As with legitimate development efforts, different skill sets may be required for developing capabilities. The skills needed may be located in-house, or may need to be contracted out. Use of a contractor may be considered an extension of that adversary's development capabilities, provided the adversary plays a role in shaping requirements and maintains a degree of exclusivity to the capability. Adversaries may also employ the use of Artificial Intelligence for development.

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.

Malware Content · source-mapped

DC0011 collection page — Use an isolated sample repository and authorized analysis tooling; preserve hashes, extraction method and custody. Do not execute samples to populate this page.

Providers and collection configuration

  • Work offline with an authorized sample or benign fixture; record its SHA-256, origin and custody before analysis.
  • For static matching, pin reviewed YARA rules/tool version and capture match IDs and offsets where needed. Treat untrusted rules and samples as untrusted input.
  • Store sanitized findings separately from restricted sample bytes. Label static observations, verdicts and any independently obtained dynamic results distinctly.

Required normalized fields: sample_sha256, artifact_kind, content, offset.

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": "DC0011",
  "collector": "illustrative-lab-collector",
  "observation": {
    "sample_sha256": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
    "artifact_kind": "extracted_string",
    "content": "BENIGN LAB MARKER",
    "offset": 4096
  }
}

Visibility limits: A rule match is not a confirmed infection. Metadata is not payload content, and static analysis does not prove a behavior occurred on a victim. No samples are executed by this module.

Malware Metadata · source-mapped

DC0003 collection page — Ingest permitted analysis metadata with sample hash, tool/version, submission provenance and confidence; keep verdicts separate from observed facts.

Providers and collection configuration

  • Work offline with an authorized sample or benign fixture; record its SHA-256, origin and custody before analysis.
  • For static matching, pin reviewed YARA rules/tool version and capture match IDs and offsets where needed. Treat untrusted rules and samples as untrusted input.
  • Store sanitized findings separately from restricted sample bytes. Label static observations, verdicts and any independently obtained dynamic results distinctly.

Required normalized fields: sample_sha256, file_type, analysis_status, verdict.

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": "DC0003",
  "collector": "illustrative-lab-collector",
  "observation": {
    "sample_sha256": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa",
    "file_type": "PE32",
    "analysis_status": "static_only",
    "verdict": "undetermined"
  }
}

Visibility limits: A rule match is not a confirmed infection. Metadata is not payload content, and static analysis does not prove a behavior occurred on a victim. No samples are executed by this module.

Response Content · source-mapped

DC0104 collection page — Capture responses only from authorized lab services or approved datasets; retain request context, response hash and a sanitized bounded excerpt.

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: service, response_excerpt, content_type, body_truncated.

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": "DC0104",
  "collector": "illustrative-lab-collector",
  "observation": {
    "service": "https://lab.example.test/health",
    "response_excerpt": "LAB_OK",
    "content_type": "text/plain",
    "body_truncated": false
  }
}

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

DET0853 Detection of Develop Capabilities

MITRE detection strategy

AN1985 Analytic 1985

Consider analyzing malware for features that may be associated with the adversary and/or their developers, such as compiler used, debugging artifacts, or code similarities. Malware repositories can also be used to identify additional samples associated with the adversary and identify development patterns over time. Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Defense Evasion or Command and Control.
Monitor for contextual data about a malicious payload, such as compilation times, file hashes, as well as watermarks or other identifiable configuration information. Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Defense Evasion or Command and Control.
Consider use of services that may aid in the tracking of capabilities, such as certificates, in use on sites across the Internet. In some cases it may be possible to pivot on known pieces of information to uncover other adversary infrastructure. Much of this activity will take place outside the visibility of the target organization, making detection of this behavior difficult. Detection efforts may be focused on related stages of the adversary lifecycle, such as during Defense Evasion or Command and Control.

Platforms: PRE.

Source rule directory and observation requirements

3 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 T1587 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.

  • Sample analysis and intelligence: Compare sample metadata, behavior traces and structural characteristics against an appropriate analysis corpus. Sample availability and sandbox execution differ from observing a compromise on a protected asset.
  • 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 T1587 Develop Capabilities; 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 Develop Capabilities, 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.

Connected ecosystem references

Linked tags

enterpriseexternal-servicesPREresource-developmentisolated_authorized_labprocedure_review_requiredtelemetry_configuration_required
No Atomic candidate in snapshottechniquesource_mapped

Detection and collection

T1587 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.