Detect behavioral anomalies

Watch an agent's behavior over a window and flag statistical deviations. EVE uses deterministic detectors (rolling / robust z-score, EWMA, CUSUM) and produces signed monitoring envelopes summarizing behavior over that window.

Prerequisites

  • The EVE embedded service facade (from core.eve_sdk import EVE) — monitoring runs in the service.
  • Synthetic activity to observe; no production credentials.

Installation

# Behavioral monitoring runs in the EVE service (Python).
pip install ./eve_coreguard-0.2.2-py3-none-any.whl   # for the hosted client

Runnable code

Anomaly detection observes governed activity and emits events plus a signed envelope. Conceptually:

# As governed calls flow through EVE, deterministic detectors track per-window
# statistics (rolling/robust z-score, EWMA, CUSUM). Deviations produce anomaly
# events, and the window is summarized in a signed monitoring envelope.

# anomaly event example:
#   {"detector": "robust_zscore", "z_score": 4.2, "escalation": "flag"}
# monitoring envelope example:
#   signed envelope summarizing agent behavior over the window

Wire the detectors to observe your agent's governed calls, then read the emitted anomaly events and the window envelope.

Expected result

  • Normal activity produces no anomaly events.
  • A sharp deviation (spike in call rate or argument size, for example) produces an anomaly event with the detector name, the score, and an escalation level.
  • The window is summarized in a signed monitoring envelope.

Evidence output

anomaly event {detector, z_score, escalation}
monitoring envelope with signature

Verification

The monitoring envelope is signed; verify it offline like any EVE evidence (see verify-evidence-offline.md).

Failure example

Statistical detectors flag deviations, but on their own they are advisory — a flagged anomaly does not block an action unless you wire it to a deterministic enforcement action (for example a CoreGuard decision, a budget, or a sequence rule).

Production considerations

  • Treat anomaly events as advisory signals; connect them to a deterministic enforcement control if you want them to block.
  • Tune detector windows and thresholds to your baseline; deterministic detectors will still flag legitimate but unusual bursts.
  • Retain signed monitoring envelopes as part of your review record.

Limitations

  • Behavioral anomaly detection is PILOT_READY. Detectors are deterministic statistical measures; they flag deviations and are advisory unless wired to a deterministic enforcement action.
  • Monitoring is observational; enforcement decisions are made by CoreGuard, sequence, and budget controls.

Next step

Wire anomalies to enforcement with block-a-prohibited-sequence.md or enforce-a-budget.md, and test candidate detector policies safely with test-a-shadow-policy.md.

Part of the EVE AI Core control plane Deterministic AI Governance Control Plane → Policy decisions that return the same result for the same input every time, before execution.