MITRE ATLAS 2026.09 / technique reference

AML.T0010.005
AI Agent Tool

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Agentic AI Initial AccessSource maturity: Realized

MITRE source definition

Adversaries may target AI agent tools as a means to compromise a victim's AI supply chain. Tools add capabilities to AI agents, allowing them to interact with other services, connect to data sources, access internet resources, run system tools, and execute code. They are an attractive target for adversaries because compromising an AI agent can provide them with broad access and permissions on the victim's system via the agent's other tools.

Poisoned AI agent tools may contain malicious definitions or instructions, hidden executable logic, or deliberately poisoned runtime responses (See AI Agent Tool Poisoning). These changes may manipulate the agent's behavior, modify how other tools are invoked, introduce hidden side effects, or provide unauthorized access to data and services. Adversaries have successfully used a poisoned MCP server to exfiltrate private user data [[koi]].

Agent tools have exploded in popularity, with thousands of MCP servers available publicly [[glama]]. They are often released on open-source software repositories such as GitHub, indexed on hubs specific to MCP servers [[mcp-hub]][[mcp-server-hub]], and published to package registries such as NPM. AI agents can also be connected to remotely-hosted tools [[remote-mcp]]. This creates an environment where malicious tools can proliferate rapidly and safeguards are often not in place.

Source modified 2026-07-31. Reproduced from the pinned ATLAS release; inline technique links resolve to local reference pages.

AML.T0010 AI Supply Chain Compromise — parent

Source-backed defensive context

MITRE mitigations

AML.M0035 AI Red Team

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.T0010.005 AI Agent Tool. 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.

State the exact trust boundary and expected observable behavior.
Pin model, application, dataset, tool permissions and evaluation inputs.
Capture baseline and scenario traces, an authorized look-alike, and a missing-telemetry control.
Evaluate the detector against independently labelled results; do not substitute model output claims for observed tool actions.
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.T0010.005",
  "simulation": false,
  "target": "REQUIRES_OWNED_LAB",
  "source_scenario": [
    "AML.CS0049",
    "AML.CS0053",
    "AML.CS0054"
  ],
  "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

AML.T0010.005AI Agent Tool