MITRE ATLAS 2026.09 / technique reference

AML.T0006
Active Scanning

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Predictive AIGenerative AIAgentic AIEnterpriseReconnaissanceSource maturity: Realized

MITRE source definition

Adversaries may actively scan for publicly reachable AI systems and resources for targeting. They may identify resources or systems that are misconfigured or are known vulnerable versions. This is distinct from other reconnaissance techniques that do not involve direct interaction with the victim system.

Since AI systems are often deployed in cloud environments, adversaries can use various enumeration methods to effectively discover AI systems and uncover information about their supporting underlying platforms. For agentic and SaaS-hosted systems, the victim system can include the shared platform and provider control plane on which the victim's agents are deployed.

Adversaries may probe the victim system to gather information and metadata for targeting, or actively scan for specific open ports on a potential victim's network or accessible deployed servers, with the goal of locating different types of deployed AI services. These methods could also include directly scanning a target's assets for publicly available AI agents, or for accessible agentic chat interfaces on SaaS platforms (ex: Copilot Studio Hunter).

Information gained from Active Scanning may yield targets that provide opportunities for other forms of reconnaissance such as Search Open Technical Databases, Search Open Websites/Domains, Search Open AI Vulnerability Analysis, or Gather RAG-Indexed Targets.

Source modified 2026-09-15. Reproduced from the pinned ATLAS release; inline technique links resolve to local reference pages.

Source-backed defensive context

MITRE mitigations

MITRE case studies

These are explicit source relationships, not independently reproduced incidents or validated detection coverage. The local relationship indexes link back to the pinned MITRE source.

Detection and collection design

No executable detector is supplied by this ATLAS source import. Define detection against the specific behavior in the full definition above. MITRE case-study and mitigation relationships supply context, not tested rule coverage.

No explicit AI Telemetry Logging mitigation relationship was found for this technique. Do not manufacture a sensor mapping from its tactic.

Depending on the selected scenario, the experiment may need dataset/model versions, data-access and build audit records, inference or application traces, or agent tool authorization records. These are planning options, not asserted mappings. Minimize sensitive prompt/data capture and retain provenance.

Anomaly detection design

No exact ATLAS anomaly detector is validated here. Select a measurable feature from the behavior definition; compare like-for-like model versions, workloads and identities. Changes caused by model upgrades, retrieval corpora or legitimate workload shifts must be controls, not automatically labelled attacks.

Baseline and validation methodology · AI-security ecosystem

Tools and reproducible source scenarios

No lab-tool association is invented from the technique name. Inspect the exact source scenarios below for the tools and environment actually used; a case study is not itself an executable or safe lab.

Simulation experiment plan

Select an owned, disposable system implementing AML.T0006 Active Scanning. Use synthetic data and sandboxed tools; disable production credentials, external side effects and data exfiltration. For poisoning or supply-chain tests, use throwaway artifacts rather than real training or deployment pipelines.

  1. State the exact trust boundary and expected observable behavior.
  2. Pin model, application, dataset, tool permissions and evaluation inputs.
  3. Capture baseline and scenario traces, an authorized look-alike, and a missing-telemetry control.
  4. Evaluate the detector against independently labelled results; do not substitute model output claims for observed tool actions.
  5. Restore state and preserve redacted evidence.

Experiment worksheet — not fabricated telemetry

The export below is a planning record, not a native event, positive attack fixture or execution result. Unknown fields deliberately remain null.

{
  "schema": "1200km.atlas.experiment-plan.v1",
  "technique_id": "AML.T0006",
  "simulation": false,
  "target": "REQUIRES_OWNED_LAB",
  "source_scenario": [
    "AML.CS0023",
    "AML.CS0063",
    "AML.CS0069",
    "AML.CS0070",
    "AML.CS0071"
  ],
  "input_artifact_hash": null,
  "system_version": null,
  "expected_observable": null,
  "native_telemetry_location": null,
  "baseline_reference": null,
  "result": "not_run"
}

Simulation and telemetry boundary

This is a technique reference page, not a runnable simulation. No ATLAS-specific telemetry mapping, local attack execution or detector validation is asserted. MITRE maturity describes its source evidence, not a 1200km lab result.

For broader context—not technique-specific control mappings—see AI Security, AI Security Course, and detection-validation methodology.

Provenance and attribution

Immutable MITRE ATLAS source · Import provenance · Attribution and transformation notice · Apache License 2.0

Copyright 2021-2026 MITRE. Source text and explicit relationships are retained; navigation, formatting and local links are provided by 1200km.

No explicit relationship in this pinned source.