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§ I · Domain MON · Control 3 of 12
Control
MON-03
Edition
v.1.3
Status
Public review

MON · Continuous Monitoring & Human Oversight

MON-03Real-time anomaly detection

Real-time anomaly detection is performed against the deployment baseline, covering volume, tool-use patterns, error rates, output distributions, and fairness metrics.

The agent's behavior in production is compared in real time against the deployment baseline captured under SPC-06. Anomaly detection covers volume, tool-use patterns, error rates, output distributions, and fairness metrics. Anomalies that cross documented thresholds trigger alerts and, for critical anomalies, automatic escalation to the human review queue.

Table MON-03.1 · Maturity criteria · v.1.3

L1 to L5 · the lowest level in scope caps the agent
L1Ad hoc

Controls exist informally; documentation is incomplete; no consistent review.

L2Documented

Controls are written down; ownership is assigned; review cadence is defined.

L3Operated

Controls are followed in practice; evidence is collected; deviations are tracked.

Anomaly detection is active for all production agents; detection covers the baseline metrics from SPC-06; thresholds are documented; alerts are generated and routed to the appropriate team; false-positive rates are tracked and tuned.

L4Measured

Control effectiveness is measured against documented thresholds; trends are reported.

L5Continuously Improved

Controls evolve based on incident learning; maturity gains are evidenced over time.

The v1.3 edition publishes a control-specific criterion at L3 (Operated). The other levels apply the general ladder to this control; see the maturity ladder.

Evidence an assessor asks for

  1. E.1

    Anomaly detection is active for all production agents.

  2. E.2

    Detection covers the baseline metrics from SPC-06.

  3. E.3

    Thresholds are documented.

  4. E.4

    Alerts are generated and routed to the appropriate team.

  5. E.5

    False-positive rates are tracked and tuned.

Table MON-03.2 · Framework mappings

5 of 7 frameworks carry a control-level reference
NIST AI RMFMANAGE 1.1, MANAGE 2.1NIST AI Risk Management Framework 1.0
SingaporeMAIGF Incident Reporting, AI Verify Human Agency & OversightSingapore Model AI Governance Framework / AI Verify / PDPA

Mappings are directional: meeting this control evidences but does not by itself satisfy the external requirement. A middle dot means no control-level reference is published at this edition; see the crosswalk.

Cite this control

Human Intelligence. HI-AAF v1.3, MON-03 Real-time anomaly detection. Public review edition, July 2026. https://humanintel.net/standard/mon/mon-03

Edition v.1.3 · July 2026 · Public review · Markdown · PDF

https://humanintel.net/standard/mon/mon-03

Notice

HI-AAF v1.3 is an independent framework published by Human Intelligence. It is not affiliated with NIST, ISO, AICPA, or any government or accreditation body. The framework is offered openly for review during the current draft cycle.