arm-secnet - ARM64-first defensive cybersecurity lab framework

项目说明

ARM-SecNet

Defensi labs for Apple Silicon — from zero setup to first in.

ARM-SecNet is an ARM64-first defensi and networking lab toolkit for Apple Silicon students, lecturers, and security learners.

The project helps learners build a small, repeatable security lab using UTM, ARM64 Linux, safe in exercises, setup documentation, screenshot-backed e, and simple checks.

Latest published release: ARM-SecNet V1.1.0 SentinelLite Dashboard Lab
Published: 2026-09-13
Current result: 29 passed, 0 warnings, 0 failures

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Project Purpose

Many cybersecurity and networking learning resources are still designed around x86 systems, , , and older lab setups. Students using Apple Silicon Macs often face ARM64 compatibility issues when building cybersecurity labs.

ARM-SecNet addresses this by pro a small, repeatable, ARM64-first defensi lab toolkit using:

The goal is to make cybersecurity lab learning practical for students using modern MacBooks.

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Current Scope

ARM-SecNet is a lab toolkit.

It is not:

The current release focuses on:

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Latest Release: V1.1.0 SentinelLite Dashboard Lab

ARM-SecNet V1.1.0 SentinelLite Dashboard Lab was published on 2026-09-13 under tag:

V1.1 includes three documented labs:

1. Lab 01 — Linux Baseline In
2. Lab 02 — Authentication Log Analysis
3. Lab 03 — SentinelLite AI Local CLI and Static Dashboard

V1.1 also includes:

Read the release notes:

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How ARM-SecNet and SentinelLite AI Work Together

ARM-SecNet and SentinelLite AI are separate projects.

ARM-SecNet provides the Apple Silicon / UTM / ARM64 Linux lab en.

SentinelLite AI can be installed inside the ARM64 Linux VM for the optional Lab 03 workflow. In that workflow, SentinelLite is used to run safe local commands such as:

The SentinelLite dashboard is static local HTML. It does not start a server, make network requests, provide li, or perform automatic remediation.

For new Lab 03 runs, use the published SentinelLite AI v1.2.0-beta GitHub pre-release wheel or the v1.2.0-beta release tag.

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Important E Limitation

The existing Lab 03 screenshots were recorded before SentinelLite AI v1.2.0-beta was published.

The recorded Lab 03 used:

That source commit already included the dashboard exporter, but the existing screenshots do not the exact SentinelLite v1.2.0-beta release wheel.

A new exact-release run must record separate e before claiming exact v1.2.0-beta wheel .

This project does not claim uni ARM64 compatibility or production security protection.

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Target Users

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Full Setup Path

Follow the repository in this order.

1. Prepare UTM on Apple Silicon macOS

Read:

This guide covers:

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2. Create the ARM64 Linux Security VM

Read:

This guide covers:

Expected architecture check:

Expected result:

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3. Run Lab 01 — Linux Baseline In

Read:

Lab 01 helps learners inspect:

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4. Run Lab 02 — Authentication Log Analysis

Read:

Lab 02 helps learners inspect:

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5. Run Lab 03 — SentinelLite AI Local CLI and Static Dashboard

Read:

Lab 03 is optional. It adds a SentinelLite AI workflow inside the ARM64 Linux VM.

The recommended path for new runs is to install the published SentinelLite AI v1.2.0-beta wheel.

Inside the Ubuntu ARM64 VM:

Expected output:

Then run the safe demo workflow from a fresh temporary directory:

The demo uses bundled synthetic data. It does not read real host logs, observe real processes, inspect acti, scan the network, or send external notifications.

The dashboard export creates:

Open the HTML file manually in a browser to view the local static dashboard.

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Quick Na

Core Documentation

Setup Guides

Labs

E and Demo

Release Notes

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Run the script:

Expected result:

The script checks documentation and e file presence. It does not install SentinelLite, run SentinelLite, or perform a fresh ARM64 .

GitHub Actions also runs:

on pull requests and pushes to main.

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V1 Lab Topology

Optional V1.1 Lab 03 workflow:

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Security Scope

ARM-SecNet is a defensi learning project.

It is intended for:

It is not intended for:

All acti should remain inside the local authorized lab en.

For V1 and V1.1, use UTM Shared/NAT networking.

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Repository Structure

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Historical Release: V1.0.0 Documentation MVP

The historical v1.0.0-docs-mvp release includes:

The V1.0 release remains a here:

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Project Direction

ARM-SecNet will stay small, practical, and defensive.

V1 created the foundation with setup guides, two tested labs, e, , and a demo flow.

V1.1 added the optional SentinelLite dashboard lab and public release workflow.

Future may add more ad defensive labs only after the current documentation and learning experience remain stable.

Possible future impro include:

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Safety Notice

ARM-SecNet follows a defensi approach.

Do not scan public targets, attack external systems, collect real credentials, run malware, create persistence, or expose the to the local network.

Use only local, authorized lab en.

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Author

Ka Samarakoon
Computer Networks Student, NSBM Green Uni
External BIT Student, Uni of Moratuwa
Career Direction: Cybersecurity Analyst and Network Engineer

项目信息

开发语言：Shell

Star 数：3

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ARM64-first defensive cybersecurity lab framework for Apple Silicon, UTM, and Ubuntu ARM64.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。