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⚡ tsecurity.de Intelligence

How I Gave Claude Code Access to 6,500 Azure Cmdlets

TL;DR I told Claude Code: "Create me a VM on Azure for dev testing." It asked a few questions, ran Az module commands through a persistent PowerShell session, hit a capacity error, but the AI recovered on its own and handed me an SSH…

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TL;DR



I told Claude Code: "Create me a VM on Azure for dev testing." It asked a few questions, ran Az module commands through a persistent PowerShell session, hit a capacity error, but the AI recovered on its own and handed me an SSH command. The whole thing took about 15 minutes — including error recovery and retry.



The secret ingredient? PowerShell.MCP — an MCP server that gives AI agents a persistent PowerShell console.






What is PowerShell.MCP?



PowerShell.MCP is an MCP server that gives AI agents a persistent, shared PowerShell console. One installation provides access to 10,000+ PowerShell modules and any CLI tool. It works with any MCP-compatible AI agent.






The Conversation



Here's what actually happened — errors and all.






Step 1: "Make me a VM"



I gave Claude Code a simple request:




I need a VM on Azure for development testing. Please use the Az PowerShell module to create it.




Instead of guessing, Claude presented an interactive prompt asking me to choose OS, VM size, region, and naming:



Claude presents interactive prompts for OS, VM size, region, and naming






Step 2: Pre-flight Checks



Claude launched a PowerShell console on its own — that's the window on the left side of the screen. From this point on, the AI executes commands directly in that console. I'm not typing these commands; Claude is.



PowerShell console launched by Claude, showing Az module and login verification



It confirmed the Az module was installed and I was already logged in. No unnecessary Connect-AzAccount prompts.






Step 3: Resource Group Creation



Claude creating resource group with traceability tags in PowerShell console



Claude tagged the resource group for traceability — a nice touch I didn't ask for.






Step 4: The Capacity Wall



Here's where it gets interesting. The VM creation failed:



SkuNotAvailable error shown in PowerShell console



Claude didn't panic. It queried available SKUs:



Claude querying available VM SKUs in Japan East region



Then presented me with alternatives. I picked Standard_D2s_v3 (2 vCPU, 8 GB RAM) and it continued seamlessly.



Claude presents alternative VM sizes with descriptions






Step 5: VM Created



Claude built the entire infrastructure from scratch — NSG, VNet, public IP, NIC, and the VM itself:



PowerShell console showing VM infrastructure creation in progress



And presented a clean summary:



Claude presenting VM summary with public IP and SSH command










Step 6: Cleanup



When I was done testing:




I'm done testing. Delete the resource group to stop all charges.




Claude deleting the resource group after testing



Confirmed the deletion:




Confirm the resource group has been fully deleted.




PowerShell confirming resource group no longer exists



Gone. No orphaned resources, no surprise bills.






Beyond Azure



This demo used Azure, but PowerShell.MCP works with anything on PowerShell Gallery — Microsoft 365, AWS, Active Directory, and 10,000+ other modules. Tell the AI what you want to do; it will find and install the right module on its own.






Why PowerShell.MCP?





  • One gateway, not dozens of MCP servers. The AI finds and installs the right PowerShell modules on its own, and learns cmdlets through Get-Help. No dedicated MCP server needed per service.


  • Shared console. Every command the AI runs appears in your PowerShell console in real-time. You can run your own commands in the same console between AI operations, and respond to cmdlet prompts directly. You learn just by watching.


  • AI handles interactive prompts. When Connect-AzAccount opens a browser for authentication, you sign in — the AI waits and continues where it left off. Workflows that require human intervention don't break.


  • Session persistence. This VM build chained $nsg → $vnet → $subnet → $pip → $nic → $vmConfig across multiple steps. It worked because variables stayed alive within the session.


  • Pipelines. MCP tools can't be chained together, but cmdlets can. Get-AzComputeResourceSku | Where-Object { ... } handled retrieval and filtering in a single line. The AI translates natural language into efficient pipelines.






How to Set It Up



See the Quick Start guide on GitHub. Once set up, just tell the AI what you want:




Create me a VM on Azure for dev testing.







Wrapping Up



PowerShell.MCP bridges the gap between "I know what I want" and "I know the exact cmdlets, parameters, and sequence to get there." The AI handles the syntax; you make the decisions.



PowerShell is already powerful. PowerShell.MCP gives that power to AI.






PowerShell.MCP is available on the PowerShell Gallery and GitHub.

1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Remote Code Execution (RCE) Defense
Syntax validiert (0 Fehler)
title: Detect Exploitation - How I Gave Claude Code Access to 6,500 Azure Cmdlets
id: 1e1a4d56-88f1-4a2a-852c-076a0b28d030
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-27
logsource:
  category: network_connection
  product: any
detection:
  selection:
      DestinationIp:
        - '13.78.36.131'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
  - attack.t1059
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-27"
        description = "YARA Signature for "
    strings:
        $str = "How I Gave Claude Code Access " ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
(dest_ip="13.78.36.131")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
destination.ip: ("13.78.36.131") and event.category: "network"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where DestinationIP in ("13.78.36.131")
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

2. Cyber Threat Intelligence & Forensik

IoC Intelligence (1 Indikatoren)
13[.]78[.]36[.]131
CTI Threat Relationship Graph6 Knoten / 5 Relationen
CVE / Incident Software MITRE ATT&CK CWE Weakness IoC
🎯
MITRE ATT&CK Matrix Navigator 14 Taktiken
Identifiziert: T1059Command and Scripting Interpreter
Reconnaissance
-
Resource Development
-
Initial Access
Execution
Persistence
-
Privilege Escalation
Defense Evasion
Credential Access
-
Discovery
-
Lateral Movement
-
Collection
-
Command and Control
Exfiltration
-
Impact
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Analyse für identifizierte Bedrohung auf Basis von Live-CTI (ENISA EUVD): CVSS 0.0 · EPSS 0.0% · CISA KEV: nein. Handlungsableitung aus den verlinkten Hersteller-Quellen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

⚡ Empfohlene Sofortmaßnahmen
  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
  • 2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
  • 3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.
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