---
library_name: scikit-learn
license: apache-2.0
tags:
- cybersecurity
- verified-autonomy
- autonomous-defense
- verification
- scikit-learn
datasets:
- avernaut/verified-autonomy-scenarios
metrics:
- accuracy
---

# Security Action Verifier

An Avernaut **reference baseline** for the six-gate verified-autonomy decision used in the companion synthetic dataset.

The model consumes six Boolean inputs:

1. V1 Authorization
2. V2 Target correctness
3. V3 Reachability
4. V4 Availability
5. V5 Blast radius
6. V6 Effectiveness

The expected rule is intentionally explicit:

**VERIFIED iff every required gate passes.**

## Why publish a model for a deterministic rule?

This artifact exists for interoperability, demonstrations, testing pipelines, and model-vs-rule experiments. It is **not** a replacement for deterministic enforcement logic.

For production security controls, implement and audit the verification rule directly rather than relying on a learned approximation.

## Evaluation

The model was checked against the complete 64-row Boolean truth table.

- Truth-table accuracy: **1.000**
- Cases: **64**

## Related dataset

`avernaut/verified-autonomy-scenarios`

## Related project

INVERIQ: https://github.com/avernaut/inveriq

## Safety note

This model does not establish that a cyber action is safe in the real world. Real deployments require authoritative telemetry, policy, topology, service dependencies, rollback mechanisms, and independent enforcement controls.