NEXUS_BASE_V.1 - Governed AI Execution System with approval gating,

项目说明

NEXUS Base V1

![NEXUS War Test]()

> Go AI Execution System — appro, trust-based automation,
> and rule-based defensi .

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Why This Exists

Most AI systems focus on what AI can do. NEXUS focuses on what AI is allowed to do.

The question driving this project: *Under what conditions, and under whose authority, should an AI system be permitted to execute an action?*

NEXUS Base V1 answers that question with a working, testable control architecture: every action entering the Base V1 go pipeline must pass a security gate, be by a trust registry, recei or trusted auto-approval, and be logged before execution occurs inside that pipeline.

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At a Glance

| Property | Value |
|---|---|
| War test result | 36 PASS / 0 WARN / 0 FAIL |
| Classification | Tier 3.5 — Go + Adapti + Defensive |
| Deployment type | Local-first (no external services required) |
| Python requirement | 3.11+ |
| External dependencies | None (pure standard library) |
| License | Apache 2.0 |

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Quickstart

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Architecture

Every action entering the system is e in sequence:

1. Security Monitor — scans for threat signatures; quarantines on T2 detection
2. Trust Registry — checks whether the action source and type are pre-authorized for auto-approval
3. Approval Gate — routes untrusted actions to human review; blocks unappro
4. Execution Engine — executes only approved, non-quarantined actions
5. Logger — appends an immutable record regardless of pass/fail outcome

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What Is Implemented

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Repository Structure

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Documentation

| Document | Purpose |
|---|---|
| NEXUS Base V1 Deep Dive | Full technical architecture, go model, and design rationale |
| Capstone Paper | Capstone project abstract and scope statement |
| Contributing | How to contribute, review, and report issues |
| ADR-001: Go Architecture | Why authorization gates precede execution |
| ADR-002: Rule-Based Threat Detection | Why rule-based over ML/embedding detection |
| ADR-003: Local-First Architecture | Why local-first o deployment |

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Proof E

| Artifact | Purpose |
|---|---|
| WAR_TEST_REPORT.md | Human-readable report showing 36 PASS / 0 WARN / 0 FAIL |
| war_test_report.json | Machine-readable report supporting the current claim |
| NEXUS War Test CI | GitHub Actions workflow configured to rerun the defensive war test |
| War Test Replay | Presentation/demo artifact for re the war-test flow |

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The war test (nexus_war_test.py) confirms that:

Current result: 36 PASS / 0 WARN / 0 FAIL

The CI pipeline (.github/workflows/ci.yml) is configured to rerun the war test on every push to main and every pull request, with the badge at the top of this file reflecting the current GitHub Actions result.

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Limitations & Status

This is a proof-of-concept and capstone engineering artifact, not a production deployment.

| Limitation | Status |
|---|---|
| Ad anomaly detection | Not yet implemented |
| Adapti intelligence | Not yet implemented |
| Multi-agent orchestration | Not yet implemented |
| External API exposure | Not in scope for Base V1 |
| Production hardening | Not in scope for Base V1 |

The scope of Base V1 is intentional: establish a clean, testable go baseline before adding complexity. The war test defines the boundary of what is currently proven.

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Go

NEXUS operates under a documented go hierarchy rooted in the
Prime Axiom. The
Execution Contract defines the
non-negotiable rules of the runtime. The
Sandbox Protocol
governs how changes are before they reach the public surface.

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License

Copyright 2026 Mason Gines

Licensed under the Apache License, 2.0.
Reviews, questions, and structural feedback are explicitly invited — see CONTRIBUTING.md.

项目信息

开发语言：Python

Star 数：1

技术要点

该项目属于防护思路方向的开源资源，代码结构清晰，适合安全研究人员学习参考。项目围绕Governed AI Execution System with approval gating, trust-based automation, and rule-based defensive security validation.展开，提供了可运行的实现，对理解相关安全机制、工具原理与攻防技术具有较高的研究价值。

从技术实现角度看，此类项目的核心在于对底层原理的深入理解与工程化落地。开发者在研究过程中可以结合官方文档与社区讨论，梳理项目的初始化流程、核心模块职责与数据流转，逐步掌握其中的技术细节与设计思路。

使用与学习建议

1. 下载源码压缩包，解压到本地环境。

2. 根据项目类型准备对应的运行环境与依赖。

3. 按照 README 中的步骤完成配置与部署。

4. 在隔离的测试环境中运行验证，避免影响生产系统。

免责声明

本资源来源于开源社区，仅供安全研究、技术学习与合法授权范围内的攻防演练使用，请勿用于任何非法或侵害他人权益的用途。使用本项目产生的一切后果由使用者自行承担。