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T1588 Obtain Capabilities — Attack Simulation

Adversaries may buy and/or steal capabilities that can be used during targeting. Rather than developing their own capabilities in-house, adversaries may purchase, freely download, or steal them. Activities may include the acquisition of malware, software (including licenses), exploits, certificates, and information relating to vulnerabilities. Adversaries may obtain capabilities to support their operations throughout numerous phases of the…

Complete technique description

Adversaries may buy and/or steal capabilities that can be used during targeting. Rather than developing their own capabilities in-house, adversaries may purchase, freely download, or steal them. Activities may include the acquisition of malware, software (including licenses), exploits, certificates, and information relating to vulnerabilities. Adversaries may obtain capabilities to support their operations throughout numerous phases of the adversary lifecycle.

In addition to downloading free malware, software, and exploits from the internet, adversaries may purchase these capabilities from third-party entities. Third-party entities can include technology companies that specialize in malware and exploits, criminal marketplaces, or from individuals.[NationsBuying][PegasusCitizenLab]

In addition to purchasing capabilities, adversaries may steal capabilities from third-party entities (including other adversaries). This can include stealing software licenses, malware, SSL/TLS and code-signing certificates, or raiding closed databases of vulnerabilities or exploits.[DiginotarCompromise]

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.

Certificate Registration · source-mapped

DC0093 collection page — Ingest authorized certificate/CA or transparency observations with fingerprint, names, issuer and observation/issuance times; do not collect private keys.

Providers and collection configuration

  • Use an approved feed/API or documented lawful export. Store retrieval time, source URL, original record ID, observation time and confidence separately.
  • Retain the raw response, licensing constraints and analyst assessment. Deduplicate observations without erasing independent provenance.
  • Correlate external context with authorized internal observations; do not label ownership, attribution or compromise from a shared indicator alone.

Required normalized fields: certificate_sha256, dns_names, issuer, observation_source.

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": "DC0093",
  "collector": "illustrative-lab-collector",
  "observation": {
    "certificate_sha256": "cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc",
    "dns_names": [
      "lab.example.test"
    ],
    "issuer": "Lab Test CA",
    "observation_source": "lab-ca-export"
  }
}

Visibility limits: Coverage, licensing, redaction and reporting delays vary. External context is not proof of access to the target, and cannot substitute for unavailable provider-side audit.

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

DET0850 Detection of Obtain Capabilities

MITRE detection strategy

AN1982 Analytic 1982

Consider use of services that may aid in the tracking of newly issued certificates and/or certificates in use on sites across the Internet. In some cases it may be possible to pivot on known pieces of certificate information to uncover other adversary infrastructure. Some server-side components of adversary tools may have default values set for SSL/TLS certificates. 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.
Monitor for logged network traffic in response to a scan showing both protocol header and body values that may buy and/or steal capabilities that can be used during targeting. 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 analyzing malware for features that may be associated with malware providers, such as compiler used, debugging artifacts, code similarities, or even group identifiers associated with specific Malware-as-a-Service (MaaS) offerings. Malware repositories can also be used to identify additional samples associated with the developers and the adversary utilizing their services. Identifying overlaps in malware use by different adversaries may indicate malware was obtained by the adversary rather than developed by them. In some cases, identifying overlapping characteristics in malware used by different adversaries may point to a shared quartermaster. Malware repositories can also be used to identify features of tool use associated with an adversary, such as watermarks in Cobalt Strike payloads.

Platforms: PRE.

Source rule directory and observation requirements

2 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 T1588 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.

  • External context and intelligence: Changes in external infrastructure, registration or published intelligence can supply context. They do not expose private attacker actions or establish a victim-side detector; preserve timestamps and attribution uncertainty.
  • 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 T1588 Obtain 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 Obtain 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

T1588 detection workspace

No reviewed association in this snapshot.

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.