Oliver Kieselbach e86f7efed3 feat(bootstrap): verify the publisher of the extracted agent binaries before --install (D-227)
The SHA-256 check proves the ZIP is the one version.json names, but that
manifest lives in the same container as the ZIP: it cannot outlive a
compromise of the download host. The expected publisher travels inside this
script, which the loader verified before running it, so the chain from the
file an administrator assigns to the process that starts is publisher-anchored
end to end.

Install-AutopilotMonitor.ps1 v2.4 -> v2.5:
- Get-UnverifiedAgentBinaries checks every AutopilotMonitor.*.exe/.dll in the
  extracted payload for status Valid and the same subject pin the loader
  carries; the gate runs immediately before --install and throws on any
  rejection, exactly like the hash check.
- Third-party assemblies keep their own publisher's signature and are not
  checked: System.Management.Automation.dll ships unsigned, so a gate over all
  files would refuse the live payload.
- An extracted folder with no binary of ours is a rejection, not a pass.
- The SHA-256 manifest check is unchanged and still runs first: it proves the
  bytes, the signature proves the author.

Verified against the live payload 2.0.1454 (all five of our PEs Valid and
glueckkanja AG, gate passes); appending one byte to AutopilotMonitor.Shared.dll
makes it reject. Pester 55/55.

The portal privacy and about pages carried the pre-signing wording and are
corrected in the same change.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-09-08 23:11:16 +02:00
2026-09-06 13:13:42 +02:00

Autopilot Monitor logo Autopilot Monitor

Status License Website

Autopilot Monitor is an open-source, real-time monitoring and troubleshooting platform for Windows Autopilot and Microsoft Intune enrollment. It records enrollment events, application installations, policies, device state, and diagnostics while provisioning is still running, instead of collecting logs by hand after a failure. Administrators get live enrollment tracking, Enrollment Status Page (ESP) visibility, detailed session timelines, automated issue detection, on-demand diagnostics, fleet health analytics, and AI-assisted troubleshooting through a hosted Model Context Protocol (MCP) server.

The platform supports classic Windows Autopilot and modern Intune provisioning scenarios, including Windows Autopilot Device Preparation.

Availability

Autopilot Monitor is publicly available — the Community plan is free. Sign in with your work account at autopilotmonitor.com; new organizations complete a short activation step after first sign-in.

Autopilot Monitor dashboard showing live Windows Autopilot and Intune enrollment sessions Autopilot Monitor fleet health dashboard with Windows Autopilot enrollment analytics and success metrics

Autopilot Monitor session details showing device information, diagnostics, apps, policies, and enrollment status Windows Autopilot enrollment timeline showing ESP phases, application installs, policies, events, and errors

Key Features

  • Real-time Windows Autopilot monitoring — follow device provisioning while enrollment is still running
  • Detailed enrollment timelines — correlate Autopilot, ESP, Intune Management Extension, apps, policies, device state, and system events
  • Enrollment Status Page visibility — see which phase, application, or policy is delaying provisioning
  • Automated issue detection — define custom analysis rules that identify known failure patterns
  • Targeted evidence collection — gather registry values, event log entries, files, log-parser matches, and allow-listed commands when specific conditions are detected
  • On-demand diagnostics — request diagnostics packages from enrolled devices remotely
  • Fleet health analytics — success rates, deployment duration, device models, applications, errors, and recurring issues
  • Session reporting — inspect and share detailed enrollment information for individual devices
  • Windows Autopilot Device Preparation support — monitor Device Preparation deployments alongside classic Autopilot scenarios
  • Centralized agent configuration — control diagnostic behavior, automatic reboots, timezone adjustment, and other monitoring settings from the web dashboard
  • AI-assisted troubleshooting — query enrollment data through the built-in Model Context Protocol server

How it works

Autopilot Monitor consists of several components working together throughout Windows enrollment:

  • Bootstrap Script — PowerShell script deployed through Microsoft Intune that starts monitoring early in the provisioning process
  • Monitoring Agent — lightweight .NET application that collects telemetry and evidence during enrollment
  • Backend API — Azure Functions-based ingestion and processing pipeline
  • Web Dashboard — Next.js application for real-time monitoring, troubleshooting, and fleet analytics
  • MCP Server — Model Context Protocol server that lets AI assistants query Autopilot Monitor data in natural language

Windows Autopilot and Intune Troubleshooting

Autopilot Monitor helps investigate common Windows provisioning and enrollment problems such as:

  • Windows Autopilot deployments that fail or appear stuck
  • Enrollment Status Page (ESP) delays and unusually long deployment phases
  • Win32 application installation failures and slow application downloads
  • Intune Management Extension problems
  • Microsoft Entra join, Hybrid Join, and device registration issues
  • policies that block or delay provisioning
  • inconsistent behavior across hardware models and recurring failures affecting multiple devices

Because telemetry is collected during enrollment, many problems can be investigated without reproducing the issue or manually collecting logs from the affected device.

AI Integration (MCP)

Autopilot Monitor ships a hosted Model Context Protocol server. Connect Claude Desktop, VS Code, or any MCP client that speaks Streamable HTTP with OAuth, and ask questions like:

  • "Show me all failed enrollments from the last 24 hours and group them by failure reason."
  • "Why did session X fail, and which app install caused the delay?"
  • "Which devices had unusually long ESP application phases this week?"
  • "Which device models have the highest Autopilot failure rate?"
  • "Which devices in my fleet are affected by CVE-2024-30078?"

Server URL: https://mcp.autopilotmonitor.com/mcp — sign-in runs through your existing work account, access is scoped to your tenant exactly like in the portal, and the MCP server stores no credentials. Setup guide: AI Integration (MCP).

Documentation

Full admin documentation is available at docs.autopilotmonitor.com — deployment, configuration, monitoring, diagnostics, troubleshooting, analysis and gather rules, integrations, and AI-assisted troubleshooting.

Open Source

Autopilot Monitor is developed openly on GitHub. The source is published so that customers and security reviewers can see what runs on their devices and with their data: the repository contains the device agent, shared library, backend, web dashboard, and MCP server.

Feedback

Bug reports and feature requests go through Issues, questions and ideas through Discussions. Security issues are reported privately, see SECURITY.md. For a problem in your own tenant, the Report Session button in the portal is the fastest path.

License

This project uses a split licensing model. The root LICENSE is AGPL-3.0, which covers the server-side components; the device-side components carry their own MIT license file:

  • MIT License — Agent (src/Agent/) and Shared library (src/Shared/) — unrestricted use on end-user devices, no copyleft obligations
  • AGPL-3.0 — Backend (src/Backend/), Web Dashboard (src/Web/), and MCP Server (src/McpServer/) — modifications to server-side components remain open source, especially when deployed as a network service

The Shared library is MIT because it is a dependency of the MIT-licensed Agent. The license file inside each component directory is authoritative for that component.

S
Description
Windows Autopilot & Intune enrollment monitoring: live session timelines, fleet health, diagnostics, and an MCP server for AI-assisted troubleshooting.
Readme AGPL-3.0 60 MiB
Languages
C# 72.7%
TypeScript 25.7%
PowerShell 1%
JavaScript 0.5%