Introducing new security and compliance add-ons for Microsoft 365 Business Premium
Small and medium businesses (SMBs) are under pressure like never before. Cyber threats are evolving rapidly, and regulatory requirements are becoming increasingly complex. Microsoft 365 Business Premium is our productivity and security solution designed for SMBs (1–300 users). It includes Office apps, Teams, advanced security such as Microsoft Defender for Business, and device management — all in one cost-effective package. Today, we’re taking that a step further. We’re excited to announce three new Microsoft 365 Business Premium add-ons designed to supercharge security and compliance. Tailored for medium-sized organizations, these add-ons bring enterprise-grade security, compliance, and identity protection to the Business Premium experience without the enterprise price tag. Microsoft Defender Suite for Business Premium: $10/user/month Cyberattacks are becoming more complex. Attackers are getting smarter. Microsoft Defender Suite provides end-to-end security to safeguard your businesses from identity attacks, device threats, email phishing, and risky cloud apps. It enables SMBs to reduce risks, respond faster, and maintain a strong security posture without adding complexity. It includes: Protect your business from identity threats: Microsoft Entra ID P2 offers advanced security and governance features including Microsoft Entra ID Protection and Microsoft Entra ID Governance. Microsoft Entra ID protection offers risk-based conditional access that helps block identity attacks in real time using behavioral analytics and signals from both user risk and sign-in risk. It also enables SMBs to detect, investigate, and remediate potential identity-based risks using sophisticated machine learning and anomaly detection capabilities. With detailed reports and alerts, your business is notified of suspicious user activities and sign-in attempts, including scenarios like a password-spray where attackers try to gain unauthorized access to company employee accounts by trying a small number of commonly used passwords across many different accounts. ID Governance capabilities are also included to help automate workflows and processes that give users access to resources. For example, IT admins historically manage the onboarding process manually and generate repetitive user access requests for Managers to review which is time consuming and inefficient. With ID Governance capabilities, pre-configured workflows facilitate the automation of employee onboarding, user access, and lifecycle management throughout their employment, streamlining the process and reducing onboarding time. Microsoft Defender for Identity includes dedicated sensors and connectors for common identity elements that offer visibility into your unique identity landscape and provide detailed posture recommendations, robust detections and response actions. These powerful detections are then automatically enriched and correlated with data from other domains across Defender XDR for true incident-level visibility. Keep your devices safe: Microsoft Defender for Endpoint Plan 2 offers industry-leading antimalware, cyberattack surface reduction, device-based conditional access, comprehensive endpoint detection and response (EDR), advanced hunting with support for custom detections, and attack surface reduction capabilities powered by Secure Score. Secure email and collaboration: With Microsoft Defender for Office 365 P2, you gain access to cyber-attack simulation training, which provides SMBs with a safe and controlled environment to simulate real-world cyber-attacks, helping to train employees in recognizing phishing attempts. Additionally automated response capabilities and post-breach investigations help reduce the time and resources required to identify and remediate potential security breaches. Detailed reports are also available that capture information on employees’ URL clicks, internal and external email distribution, and more. Protect your cloud apps: Microsoft Defender for Cloud Apps is a comprehensive, AI-powered software-as-a-service (SaaS) security solution that enables IT teams to identify and manage shadow IT and ensure that only approved applications are used. It protects against sophisticated SaaS-based attacks, OAuth attacks, and risky interactions with generative AI apps by combining SaaS app discovery, security posture management, app-to-app protection, and integrated threat protection. IT teams can gain full visibility into their SaaS app landscape, understand the risks and set up controls to manage the apps. SaaS security posture management quickly identifies app misconfigurations and provides remediation actions to reduce the attack surface. Microsoft Purview Suite for Business Premium: $10/user/month Protect against insider threats Microsoft Purview Insider Risk Management uses behavioral analytics to detect risky activities, like an employee downloading large volumes of files before leaving the company. Privacy is built in, so you can act early without breaking employee trust. Protect sensitive data wherever it goes Microsoft Purview Information Protection classifies and labels sensitive data, so the right protections follow the data wherever it goes. Think of it as a ‘security tag’ that stays attached to a document whether it’s stored in OneDrive, shared in Teams, or emailed outside the company. Policies can be set based on the ‘tag’ to prevent data oversharing, ensuring sensitive files are only accessible to the right people. Microsoft Purview Data Loss Prevention (DLP) works in the background to stop sensitive information, like credit card numbers or health data, from being accidentally shared with unauthorized people Microsoft Purview Message Encryption adds another layer by making sure email content stays private, even when sent outside the organization. Microsoft Purview Customer Key gives organizations control of their own encryption keys, helping meet strict regulatory requirements. Ensure data privacy and compliant communications Microsoft Purview Communication Compliance monitors and flags inappropriate or risky communications to protect against policy and compliance violations. Protect AI interactions Microsoft Purview Data Security Posture Management (DSPM) for AI provides visibility into how AI interacts with sensitive data, helping detect oversharing, risky prompts, and unethical behavior. Monitors Copilot and third-party AI usage with real-time alerts, policy enforcement, and risk scoring. Manage information through its lifecycle Microsoft Purview Records and Data Lifecycle Management helps businesses meet compliance obligations by applying policies that enable automatic retention or deletion of data. Stay investigation-ready Microsoft Purview eDiscovery (Premium) makes it easier to respond to internal investigations, legal holds, or compliance reviews. Instead of juggling multiple systems, you can search, place holds, and export information in one place — ensuring legal and compliance teams work efficiently. Microsoft Purview Audit (Premium) provides deeper audit logs and analytics to trace activity like file access, email reads, or user actions. This level of detail is critical for incident response and forensic investigations, helping SMBs maintain regulatory readiness and customer trust. Simplify Compliance Management Microsoft Purview Compliance Manager helps track regulatory requirements, assess risk, and manage improvement actions, all in one dashboard tailored for SMBs. Together, these capabilities help SMBs operate with the same level of compliance and data protection as large enterprises but simplified for smaller teams and tighter budgets. Microsoft Defender and Purview Suites for Business Premium: $15/user/month The new Microsoft Defender and Purview Suites unite the full capabilities of Microsoft Defender and Purview into a single, cost-effective package. This all-in-one solution delivers comprehensive security, compliance, and data protection, while helping SMB customers unlock up to 68% savings compared to buying the products separately, making it easier than ever to safeguard your organization without compromising on features or budget. FAQ Q: When will these new add-ons be available for purchase? A: They will be available for purchase as add-ons to Business Premium in September 2025. Q: How can I purchase? A: You can purchase these as add-ons to your Business Premium subscription through Microsoft Security for SMBs website or through your Partner. Q: Are there any seat limits for the add-on offers? A: Yes. Customers can purchase a mix of add-on offers, but the total number of seats across all add-ons is limited to 300 per customer. Q: Does Microsoft 365 Business Premium plus Microsoft Defender Suite allow mixed licensing for endpoint security solutions? A: Microsoft Defender for Business does not support mixed licensing so a tenant with Defender for Business (included in Microsoft 365 Business Premium) along with Defender for Endpoint Plan 2 (included in Microsoft 365 Security) will default to Defender for Business. For example, if you have 80 users licensed for Microsoft 365 Business Premium and you’ve added Microsoft Defender Suite for 30 of those users, the experience for all users will default to Defender for Business. If you would like to change that to the Defender for Endpoint Plan 2 experience, you should license all users for Defender for Endpoint Plan 2 (either through standalone or Microsoft Defender Suite) and then contact Microsoft Support to request the switch for your tenant. You can learn more here. Q: Can customers who purchased the E5 Security Suite as an add-on to Microsoft 365 Business Premium transition to the new Defender Suite starting from the October billing cycle? A: Yes. Customers currently using the Microsoft 365 E5 Security add-on with Microsoft 365 Business Premium are eligible to transition to the new Defender Suite beginning with the October billing cycle. For detailed guidance, please refer to the guidelines here. Q: As a Partner, how do I build Managed Detection and Response (MDR) services with MDB? A: For partners or customers looking to build their own security operations center (SOC) with MDR, Defender for Business supports the streaming of device events (device file, registry, network, logon events and more) to Azure Event Hub, Azure Storage, and Microsoft Sentinel to support advanced hunting and attack detection. If you are using the streaming API for the first time, you can find step-by-step instructions in the Microsoft 365 Streaming API Guide on configuring the Microsoft 365 Streaming API to stream events to your Azure Event Hubs or to your Azure Storage Account. To learn more about Microsoft Security solutions for SMBs you can visit our website.Intune AI Agent: Instant Threat Defense, Invisible Protection
From Microsoft Learn - Vulnerability Remediation Agent In today’s threat landscape, security teams require more than traditional tools—they need automation that can adapt in real time. Microsoft Intune’s integration with Security Copilot agents addresses this need. This blog introduces the Vulnerability Remediation Agent, an AI-based solution for managing endpoint security. By leveraging Microsoft’s threat intelligence alongside large language models (LLMs), these agents provide insights, automate policy enforcement, and simplify remediation workflows. Whether responding to compromised devices, updating compliance policies, or applying Zero Trust principles, Intune’s Security Copilot agents offer a centralized approach to endpoint protection. This article outlines the functionality of these agents, their features, and implementation strategies, enabling organizations to address threats and enhance their overall security posture. Why Intune Needs AI Agents Vulnerability Remediation Agent in Microsoft Intune are AI-driven tools developed to support security teams in endpoint management and protection. These agents utilize large language models (LLMs) and Microsoft's threat intelligence to deliver insights, automate tasks, and assist with decision-making. With factors such as hybrid work, Bring Your Own Device (BYOD), and changing threat vectors, managing endpoint security has become more complex. Security Copilot agents in Intune address these challenges by: Automating threat detection and response Offering contextual device risk insights Recommending and applying policy modifications Reducing remediation time for compromised devices These agents function within the Security Copilot framework, using Microsoft’s threat intelligence and AI models to provide real-time guidance. From Microsoft Learn - Vulnerability Remediation Agent Key Capabilities of Vulnerability Remediation Agent in Microsoft Intune Microsoft Intune’s Vulnerability Remediation Agent uses AI to scan devices for vulnerabilities, assess their risk, and provide clear remediation steps. It automates or recommends policy changes to guide IT teams from detection through resolution, focusing on the most critical issues. The Compromise Recovery Agent automatically identifies compromised devices using Defender and other signals, then runs recovery actions like isolation, password resets, and policy enforcement to streamline response. Device Compliance Optimization Agent reviews compliance policies and telemetry, highlights gaps, and suggests improvements. It enables gradual policy rollout via report-only mode for safer deployments. Security Posture Insights present dashboards with device risks, policy effectiveness, and remediation history, helping security teams prioritize responses. Security Copilot agents integrate into the Intune admin center, letting administrators use natural language queries to receive recommendations and make changes directly in one platform. Copilot-Driven Recommendations deliver bespoke guidance for strengthening endpoint security, complete with projected impact analyses prior to execution. Collectively, these agents offer several core capabilities: Real-time threat detection and response Automated policy recommendations Endpoint configuration optimization Integration with Microsoft Defender and other security solutions Context-aware insights informed by organizational data Step-by-step vulnerability remediation guidance leveraging Intune’s native tools From Microsoft Learn - Agent suggestions How It Works Vulnerability Remediation Agent in Microsoft Intune operates through an ongoing improvement process: Scan & Evaluate: Review device telemetry and policy coverage. Recommend: Suggest policy adjustments or remediation actions. Remediate: Implement fixes in report-only mode or enforce immediately. Observe & Iterate: Track outcomes and adjust policies accordingly. Utilizing AI Agent in endpoint management allows security teams to: Shorten response time to threats Enhance policy compliance Reduce manual configuration errors Increase visibility into endpoint status and security Learn More Microsoft Vulnerability Remediation Agent in Microsoft Intune From Microsoft Learn - Vulnerability Remediation Agent Setup Use Cases Rapid Response to Compromised Devices: Endpoints identified as infected are automatically isolated and remediated. Policy Optimization: Overlapping compliance policies are consolidated to minimize complexity. Zero Trust Enforcement: Only devices that meet compliance and security standards are permitted access to corporate resources. Operational Efficiency: Manual troubleshooting is reduced, and visibility into operations is improved. Requirements This list outlines the requirements, licensing conditions, user roles, permissions, and a comparison of advantages and disadvantages for deploying Vulnerability Remediation Agent in Microsoft Intune. Licensing: Microsoft Intune and Microsoft Security Copilot Secure Compute Units (SCU) may apply). Roles: Intune Admin, Security Admin, or Global Admin. Permissions: Role-based access controls ensure secure execution. Pros and Cons Pros Cons Notes Automated threat detection and remediation Requires SCUs and proper licensing Plan SCU usage Simplifies compliance policy management Limited customization of agent suggestions Use report-only mode for testing Improves visibility into device risk Initial setup may require training Leverage dashboards and logs Supports Zero Trust principles Preview features may evolve Monitor Microsoft Learn for updates Getting Started with Intune’s AI-Powered Security Agents Step 1: Access the Intune Admin Center Go to the https://intune.microsoft.com. Navigate to Endpoint Security > Security Copilot Agents. Step 2: Enable the Vulnerability Remediation Agent Locate the Vulnerability Remediation Agent tile on the home page. Click Start Agent to begin setup. Follow the guided steps to configure scanning, policy recommendations, and remediation workflows. Step 3: Review Licensing and Permissions Ensure your organization has the required Microsoft Intune licensing and Security Copilot Secure Compute Units (SCUs). Assign appropriate role-based access controls (e.g., Intune Admin, Security Admin, Global Admin) to manage agent capabilities securely. Step 4: Configure Agent Settings Define scanning intervals and telemetry sources. Enable report-only mode for safe testing of policy changes before enforcement. Set up dashboards and logs to monitor agent activity and remediation outcomes. Step 5: Integrate with Microsoft Defender Link Intune with Microsoft Defender for Endpoint to enhance threat detection and response. Use Defender signals to support Compromise Recovery Agent actions like isolation and password resets. Step 6: Use Natural Language Queries In the Intune Admin Center, use Security Copilot to ask questions like: o “Which devices are at risk?” o “What policy changes are recommended?” o “Show remediation history for compromised endpoints.” Step 7: Monitor and Optimize Track device compliance and risk posture using Security Posture Insights. Use the Device Compliance Optimization Agent to identify gaps and suggest improvements. Adjust policies based on observed outcomes and agent recommendations. About the Author Hi! Jacques “Jack” here, Lead Technical Trainer. I help learners and customers adopt Microsoft Intune, Defender, and Security Copilot. This blog post reflects the practical guidance I share in workshops to accelerate secure endpoint management. From my perspective as a trainer, what truly sets Intune apart is how seamlessly it leverages AI-driven agents to automate responses, detect advanced threats, and provide actionable insights in real time. This empowers organizations to proactively defend their environments, reduce manual workloads, and build a culture of security resilience through intelligent automation. With these capabilities, Intune and Security Copilot together not only elevate protection but also simplify the learning curve for IT professionals managing complex digital landscapes. #MicrosoftLearn #SkilledByMTTSecurity Review for Microsoft Edge version 140
We have reviewed the new settings in Microsoft Edge version 140 and determined that there are no additional security settings that require enforcement. The Microsoft Edge version 139 security baseline continues to be our recommended configuration which can be downloaded from the Microsoft Security Compliance Toolkit. Microsoft Edge version 140 introduced 7 new Computer and 6 new User settings, we have included a spreadsheet listing the new settings to make it easier for you to find. As a friendly reminder, all available settings for Microsoft Edge are documented here, and all available settings for Microsoft Edge Update are documented here. Please continue to give us feedback through the Security Baselines Discussion site or this post.Want to earn an Exclusive Security Tech Community Badge? Take our quick survey!
Hey there Security Tech Community! As we prepare for Microsoft Ignite, we’re building a focused, practitioner-led security roundtable and we want your input to ensure it reflects the most relevant and pressing topics in the field. We invite you to take a short survey and share the security topics, trends, and technical questions you want to see covered. Your input will directly influence the structure and substance of the Ignite Security Roundtable. The first 5 people to post a screenshot for proof of survey completion in the comments below will receive this "Microsoft Security Star" Badge to add to their Tech Community profile! TAKE THE SURVEY NOW: https://aka.ms/IgniteSecurityRoundtableSurvey2025Secure Model Context Protocol (MCP) Implementation with Azure and Local Servers
Introduction The Model Context Protocol (MCP) enables AI systems to interact with external data sources and tools through a standardized interface. While powerful, MCP can introduce security risks in enterprise environments. This tutorial shows you how to implement MCP securely using local servers, Azure OpenAI with APIM, and proper authentication. Understanding MCP's Security Risks There are a couple of key security concerns to consider before implementing MCP: Data Exfiltration: External MCP servers could expose sensitive data. Unauthorized Access: Third-party services become potential security risks. Loss of Control: Unknown how external services handle your data. Compliance Issues: Difficulty meeting regulatory requirements with external dependencies. The solution? Keep everything local and controlled. Secure Architecture Before we dive into implementation, let's take a look at the overall architecture of our secure MCP solution: This architecture consists of three key components working together: Local MCP Server - Your custom tools run entirely within your local environment, reducing external exposure risks. Azure OpenAI + APIM Gateway - All AI requests are routed through Azure API Management with Microsoft Entra ID authentication, providing enterprise-grade security controls and compliance. Authenticated Proxy - A lightweight proxy service handles token management and request forwarding, ensuring seamless integration. One of the key benefits of this architecture is that no API key is required. Traditional implementations often require storing OpenAI API keys in configuration files, environment variables, or secrets management systems, creating potential security vulnerabilities. This approach uses Azure Managed Identity for backend authentication and Azure CLI credentials for client authentication, meaning no sensitive API keys are ever stored, logged, or exposed in your codebase. For more security, APIM and Azure OpenAI resources can be configured with IP restrictions or network rules to only accept traffic from certain sources. These configurations are available for most Azure resources and provide an additional layer of network-level security. This security-forward approach gives you the full power of MCP's tool integration capabilities while keeping your implementation completely under your control. How to Implement MCP Securely 1. Local MCP Server Implementation Building the MCP Server Let's start by creating a simple MCP server in .NET Core. 1. Create a web application dotnet new web -n McpServer 2.Add MCP packages dotnet add package ModelContextProtocol --prerelease dotnet add package ModelContextProtocol.AspNetCore --prerelease 3. Configure Program.cs var builder = WebApplication.CreateBuilder(args); builder.Services.AddMcpServer() .WithHttpTransport() .WithToolsFromAssembly(); var app = builder.Build(); app.MapMcp(); app.Run(); WithToolsFromAssembly() automatically discovers and registers tools from the current assembly. Look into the C# SDK for other ways to register tools for your use case. 4. Define Tools Now, we can define some tools that our MCP server can expose. here is a simple example for tools that echo input back to the client: using ModelContextProtocol.Server; using System.ComponentModel; namespace Tools; [McpServerToolType] public static class EchoTool { [McpServerTool] [Description("Echoes the input text back to the client in all capital letters.")] public static string EchoCaps(string input) { return new string(input.ToUpperInvariant()); } [McpServerTool] [Description("Echoes the input text back to the client in reverse.")] public static string ReverseEcho(string input) { return new string(input.Reverse().ToArray()); } } Key components of MCP tools are the McpServerToolType class decorator indicating that this class contains MCP tools, and the McpServerTool method decorator with a description that explains what the tool does. Alternative: STDIO Transport If you want to use STDIO transport instead of SSE (implemented here), check out this guide: Build a Model Context Protocol (MCP) Server in C# 2. Create a MCP Client with Cline Now that we have our MCP server set up with tools, we need a client that can discover and invoke these tools. For this implementation, we'll use Cline as our MCP client, configured to work through our secure Azure infrastructure. 1. Install Cline VS Code Extension Install the Cline extension in VS Code. 2. Deploy secure Azure OpenAI Endpoint with APIM Instead of connecting Cline directly to external AI services (which could expose the secure implementation to external bad actors), we will route through Azure API Management (APIM) for enterprise security. With this implementation, all requests go through Microsoft Entra ID and we use managed identity for all authentications. Quick Setup: Deploy the Azure OpenAI with APIM solution. Ensure your Azure OpenAI resources are configured to allow your APIM's managed identity to make calls. The APIM policy below uses managed identity authentication to connect to Azure OpenAI backends. Refer to the Azure OpenAI documentation on managed identity authentication for detailed setup instructions. 3. Configure APIM Policy After deploying APIM, configure the following policy to enable Azure AD token validation, managed identity authentication, and load balancing across multiple OpenAI backends: <!-- Azure API Management Policy for OpenAI Endpoint --> <!-- Implements Azure AD Token validation, managed identity authentication --> <!-- Supports round-robin load balancing across multiple OpenAI backends --> <!-- Requests with 'gpt-5' in the URL are routed to a single backend --> <!-- The client application ID '04b07795-8ddb-461a-bbee-02f9e1bf7b46' is the official Azure CLI app registration --> <!-- This policy allows requests authenticated by Azure CLI (az login) when the required claims are present --> <policies> <inbound> <!-- IP Allow List Fragment (external fragment for client IP restrictions) --> <include-fragment fragment-id="YourCompany-IPAllowList" /> <!-- Azure AD Token Validation for Azure CLI app ID --> <validate-azure-ad-token tenant-id="YOUR-TENANT-ID-HERE" header-name="Authorization" failed-validation-httpcode="401" failed-validation-error-message="Unauthorized. Access token is missing or invalid."> <client-application-ids> <application-id>04b07795-8ddb-461a-bbee-02f9e1bf7b46</application-id> </client-application-ids> <audiences> <audience>api://YOUR-API-AUDIENCE-ID-HERE</audience> </audiences> <required-claims> <claim name="roles" match="any"> <value>YourApp.User</value> </claim> </required-claims> </validate-azure-ad-token> <!-- Acquire Managed Identity access token for backend authentication --> <authentication-managed-identity resource="https://cognitiveservices.azure.com" output-token-variable-name="managed-id-access-token" ignore-error="false" /> <!-- Set Authorization header for backend using the managed identity token --> <set-header name="Authorization" exists-action="override"> <value>@("Bearer " + (string)context.Variables["managed-id-access-token"])</value> </set-header> <!-- Check if URL contains 'gpt-5' and set backend accordingly --> <choose> <when condition="@(context.Request.Url.Path.ToLower().Contains("gpt-5"))"> <set-variable name="selected-backend-url" value="https://your-region1-oai.openai.azure.com/openai" /> </when> <otherwise> <cache-lookup-value key="backend-counter" variable-name="backend-counter" /> <choose> <when condition="@(context.Variables.ContainsKey("backend-counter") == false)"> <set-variable name="backend-counter" value="@(0)" /> </when> </choose> <set-variable name="current-backend-index" value="@((int)context.Variables["backend-counter"] % 7)" /> <choose> <when condition="@((int)context.Variables["current-backend-index"] == 0)"> <set-variable name="selected-backend-url" value="https://your-region1-oai.openai.azure.com/openai" /> </when> <when condition="@((int)context.Variables["current-backend-index"] == 1)"> <set-variable name="selected-backend-url" value="https://your-region2-oai.openai.azure.com/openai" /> </when> <when condition="@((int)context.Variables["current-backend-index"] == 2)"> <set-variable name="selected-backend-url" value="https://your-region3-oai.openai.azure.com/openai" /> </when> <when condition="@((int)context.Variables["current-backend-index"] == 3)"> <set-variable name="selected-backend-url" value="https://your-region4-oai.openai.azure.com/openai" /> </when> <when condition="@((int)context.Variables["current-backend-index"] == 4)"> <set-variable name="selected-backend-url" value="https://your-region5-oai.openai.azure.com/openai" /> </when> <when condition="@((int)context.Variables["current-backend-index"] == 5)"> <set-variable name="selected-backend-url" value="https://your-region6-oai.openai.azure.com/openai" /> </when> <when condition="@((int)context.Variables["current-backend-index"] == 6)"> <set-variable name="selected-backend-url" value="https://your-region7-oai.openai.azure.com/openai" /> </when> </choose> <set-variable name="next-counter" value="@(((int)context.Variables["backend-counter"] + 1) % 1000)" /> <cache-store-value key="backend-counter" value="@((int)context.Variables["next-counter"])" duration="300" /> </otherwise> </choose> <!-- Always set backend service using selected-backend-url variable --> <set-backend-service base-url="@((string)context.Variables["selected-backend-url"])" /> <!-- Inherit any base policies defined outside this section --> <base /> </inbound> <backend> <base /> </backend> <outbound> <base /> </outbound> <on-error> <base /> </on-error> </policies> This policy creates a secure gateway that validates Azure AD tokens from your local Azure CLI session, then uses APIM's managed identity to authenticate with Azure OpenAI backends, eliminating the need for API keys. It automatically load-balances requests across multiple Azure OpenAI regions using round-robin distribution for optimal performance. 4. Create Azure APIM proxy for Cline This FastAPI-based proxy forwards OpenAI-compatible API requests from Cline through APIM using Azure AD authentication via Azure CLI credentials, eliminating the need to store or manage OpenAI API keys. Prerequisites: Python 3.8 or higher Azure CLI (ensure az login has been run at least once) Ensure the user running the proxy script has appropriate Azure AD roles and permissions. This script uses Azure CLI credentials to obtain bearer tokens. Your user account must have the correct roles assigned and access to the target API audience configured in the APIM policy above. Quick setup for the proxy: Create this requirements.txt: fastapi uvicorn requests azure-identity Create this Python script for the proxy source code azure_proxy.py: import os import requests from fastapi import FastAPI, Request from fastapi.responses import StreamingResponse import uvicorn from azure.identity import AzureCliCredential # CONFIGURATION APIM_BASE_URL = <APIM BASE URL HERE> AZURE_SCOPE = <AZURE SCOPE HERE> PORT = int(os.environ.get("PORT", 8080)) app = FastAPI() credential = AzureCliCredential() # Use a single requests.Session for connection pooling from requests.adapters import HTTPAdapter session = requests.Session() session.mount("https://", HTTPAdapter(pool_connections=100, pool_maxsize=100)) import time _cached_token = None _cached_expiry = 0 def get_bearer_token(scope: str) -> str: """Get an access token using AzureCliCredential, caching until expiry is within 30 seconds.""" global _cached_token, _cached_expiry now = int(time.time()) if _cached_token and (_cached_expiry - now > 30): return _cached_token try: token_obj = credential.get_token(scope) _cached_token = token_obj.token _cached_expiry = token_obj.expires_on return _cached_token except Exception as e: raise RuntimeError(f"Could not get Azure access token: {e}") @app.api_route("/{path:path}", methods=["GET", "POST", "PUT", "PATCH", "DELETE", "OPTIONS"]) async def proxy(request: Request, path: str): # Assemble the destination URL (preserve trailing slash logic) dest_url = f"{APIM_BASE_URL.rstrip('/')}/{path}".rstrip("/") if request.url.query: dest_url += "?" + request.url.query # Get the Bearer token bearer_token = get_bearer_token(AZURE_SCOPE) # Prepare headers (copy all, overwrite Authorization) headers = dict(request.headers) headers["Authorization"] = f"Bearer {bearer_token}" headers.pop("host", None) # Read body body = await request.body() # Send the request to APIM using the pooled session resp = session.request( method=request.method, url=dest_url, headers=headers, data=body if body else None, stream=True, ) # Stream the response back to the client return StreamingResponse( resp.raw, status_code=resp.status_code, headers={k: v for k, v in resp.headers.items() if k.lower() != "transfer-encoding"}, ) if __name__ == "__main__": # Bind the app to 127.0.0.1 to avoid any Firewall updates uvicorn.run(app, host="127.0.0.1", port=PORT) Run the setup: pip install -r requirements.txt az login # Authenticate with Azure python azure_proxy.py Configure Cline to use the proxy: Using the OpenAI Compatible API Provider: Base URL: http://localhost:8080 API Key: <any random string> Model ID: <your Azure OpenAI deployment name> API Version: <your Azure OpenAI deployment version> The API key field is required by Cline but unused in our implementation - any random string works since authentication happens via Azure AD. 5. Configure Cline to listen to your MCP Server Now that we have both our MCP server running and Cline configured with secure OpenAI access, the final step is connecting them together. To enable Cline to discover and use your custom tools, navigate to your installed MCP servers on Cline, select Configure MCP Servers, and add in the configuration for your server: { "mcpServers": { "mcp-tools": { "autoApprove": [ "EchoCaps", "ReverseEcho", ], "disabled": false, "timeout": 60, "type": "sse", "url": "http://<your localhost url>/sse" } } } Now, you can use Cline's chat interface to interact with your secure MCP tools. Try asking Cline to use your custom tools - for example, "Can you echo 'Hello World' in capital letters?" and watch as it calls your local MCP server through the infrastructure you've built. Conclusion There you have it: A secure implementation of MCP that can be tailored to your specific use case. This approach gives you the power of MCP while maintaining enterprise security. You get: AI capabilities through secure Azure infrastructure. Custom tools that never leave your environment. Standard MCP interface for easy integration. Complete control over your data and tools. The key is keeping MCP servers local while routing AI requests through your secure Azure infrastructure. This way, you gain MCP's benefits without compromising security. Disclaimer While this tutorial provides a secure foundation for MCP implementation, organizations are responsible for configuring their Azure resources according to their specific security requirements and compliance standards. Ensure proper review of network rules, access policies, and authentication configurations before deploying to production environments. Resources MCP SDKs and Tools: MCP C# SDK MCP Python SDK Cline SDK Cline User Guide Azure OpenAI with APIM Azure API Management Network Security: Azure API Management - restrict caller IPs Azure API Management with an Azure virtual network Set up inbound private endpoint for Azure API Management Azure OpenAI and AI Services Network Security: Configure Virtual Networks for Azure AI services Securing Azure OpenAI inside a virtual network with private endpoints Add an Azure OpenAI network security perimeter az cognitiveservices account network-ruleNo More Guesswork—Copilot Makes Azure Security Crystal Clear
Elevating Azure Security and Compliance In today’s rapidly evolving digital landscape, security and compliance are more critical than ever. As organizations migrate workloads to Azure, the need for robust security frameworks and proactive compliance strategies grows. Security Copilot, integrated with Azure, is transforming how technical teams approach these challenges, empowering users to build secure, compliant environments with greater efficiency and confidence. As a security expert, I’d like to provide clear guidance on how to effectively utilize Security Copilot in the ever-evolving landscape of security and compliance. Security Copilot is a premium offering; it includes advanced capabilities that go beyond standard Azure security tools. These features may require specific licensing or subscription tiers. It provides deeper insights, enhanced automation, and tailored guidance for complex security scenarios. Below, I’ll highlight a range of security topics with sample Copilot prompts that you can use to help create a more secure and compliant environment. Getting Started with Microsoft Security Copilot Before leveraging the advanced capabilities of Security Copilot, it's important to understand the foundational requirements and setup steps: Azure Subscription Requirement Security Copilot is not automatically available in all Azure subscriptions. To use it, your organization must have an active Azure subscription. This is necessary to provision Security Compute Units (SCUs), which are the core resources that power Copilot workloads. Provisioning Security Compute Units (SCUs) SCUs are billed hourly and can be scaled based on workload needs. At least one SCU must be provisioned to activate Security Copilot. You can manage SCUs via the Azure portal or the Security Copilot portal, adjusting capacity as needed for performance and cost optimization. Role-Based Access Control To set up and manage Security Copilot: You need to be an Azure Owner or Contributor to provision SCUs. Users must be assigned appropriate Microsoft Entra roles (e.g., Security Administrator) to access and interact with Copilot features. Embedded Experience Security Copilot can be used as a standalone tool or embedded within other Microsoft services like Defender for Endpoint, Intune, and Purview, offering unified security management experience. Data Privacy and Security: Foundational Best Practices Why settle for generic security advice when Security Copilot delivers prioritized, actionable guidance backed by Microsoft’s best practices? Copilot doesn’t just recommend security measures, it actively helps you implement them, leveraging advanced features like encryption and granular access controls to safeguard every layer of your Azure environment. While Security Copilot doesn’t directly block threats like a firewall or Web Application Firewall (WAF), it enhances data integrity and confidentiality by analyzing security signals across Azure, identifying vulnerabilities, and guiding teams with prioritized, actionable recommendations. It helps implement encryption, access controls, and compliance-aligned configurations, while integrating with existing security tools to interpret logs and suggest containment strategies. By automating investigations and supporting secure-by-design practices, Copilot empowers organizations to proactively reduce breach risks and maintain a strong security posture. Secure Coding and Developer Productivity While Security Copilot supports secure coding by identifying vulnerabilities like SQL injection, Cross-Site Scripting (XSS), and buffer overflows, it is not a direct replacement for traditional code scanning tools, instead, it complements these tools by leveraging telemetry from integrated Microsoft services and applying AI-driven insights to prioritize risks and guide remediation. Copilot enhances developer productivity by interpreting signals, offering tailored recommendations, and embedding security practices throughout the software lifecycle. Understanding Security Protocols and Mechanisms Azure’s security stands on robust protocols and mechanisms but understanding them shouldn’t require a cryptography degree. Security Copilot demystifies encryption, authentication, and secure communications—making complex concepts accessible and actionable. With Security Copilot as your guide, teams can confidently configure Azure resources and respond to threats with informed, best-practice decisions. Compliance and Regulatory Alignment Regulatory requirements such as GDPR, HIPAA, and PCI-DSS don’t have to slow you down. Security Copilot streamlines Azure compliance with ready-to-use templates, clear guidelines, and robust documentation support. From maintaining audit logs to generating compliance reports, Security Copilot keeps every action tracked and organized—reducing non-compliance risk and making audits a breeze. Incident Response Planning No security strategy is complete without a solid incident response plan. Security Copilot equips Azure teams with detailed protocols for identifying, containing, and mitigating threats. It enhances Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) solutions through ready-made playbooks tailored to diverse scenarios. With built-in incident simulations, Copilot enables teams to rehearse and refine their responses—minimizing breach impact and accelerating recovery. Security Best Practices for Azure Staying ahead of threats means never standing still. Security Copilot builds on Azure’s proven security features—like multi-factor authentication, regular updates, and least privilege access—by automating their implementation, monitoring usage patterns, and surfacing actionable insights. It connects with tools like Microsoft Defender and Entra ID to interpret signals, recommend improvements, and guide teams in real time. With Copilot, your defenses don’t just follow best practices, they evolve dynamically to meet emerging threats, keeping your team sharp and your environment secure. Integrating Copilot into Your Azure Security Strategy Security Copilot isn’t just a technical tool—it’s your strategic partner for Azure security. By weaving Copilot into your workflows, you unlock advanced security enhancements, optimized code, and robust privacy protection. Its holistic approach ensures security and compliance are seamlessly integrated into every corner of your Azure environment. Conclusion Security Copilot is changing the game for Azure security and compliance. By blending secure coding, advanced security expertise, regulatory support, incident response playbooks, and best practices, Copilot empowers technical teams to build resilient, compliant cloud environments. As threats evolve, Copilot keeps your data protected and your organization ahead of the curve. Ready to take your Azure security and compliance to the next level? Start leveraging Security Copilot today to empower your team, streamline operations, and stay ahead of evolving threats. Dive deeper into best practices, hands-on tutorials, and expert guidance to maximize your security posture and unlock the full potential of Copilot in your organization. Explore, learn, and secure your cloud—your journey starts now! Further Reading & Resources Microsoft Security Copilot documentation Get started with Microsoft Security Copilot Microsoft Copilot in Azure Overview Security best practices and patterns - Microsoft Azure Azure compliance documentation Copilot Learning Hub Microsoft Security Copilot Blog Author: Microsoft Principal Technical Trainer, https://www.linkedin.com/in/eliasestevao/ #MicrosoftLearn #SkilledByMTTSecurity baseline for Microsoft Edge version 139
We have reviewed the settings in Microsoft Edge version 139 and updated our guidance with the addition of one setting and the removal of one setting. A new Microsoft Edge security baseline package was just released to the Download Center. You can download the new package from the Security Compliance Toolkit. Allow software WebGL fallback using SwiftShader (Added) The EnableUnsafeSwiftShaderpolicy controls whether SwiftShader is used as a fallback for WebGL when hardware GPU acceleration is disabled or unavailable. SwiftShader, a software-based renderer, was used to enable WebGL support in environments lacking GPU acceleration, such as virtual machines. However, its continued use poses potential risks, whereby malicious web content could exploit vulnerabilities in the renderer. Due to the potential risks, we have decided to enforce the default and disable this setting. Edge for Business Connectors (Worth Mentioning) The new Edge for Business security connectors feature introduces a powerful framework that integrates the browser directly with your organization’s existing security stack covering authentication, data loss prevention (DLP), and reporting. By enabling real-time device trust validation, seamless DLP enforcement, and unified browser-based telemetry, these connectors help close critical gaps in enterprise security while extending the value of your current investments. Additional information can be found on the landing page. The following settings have been removed due to deprecation: Microsoft Edge/Private Network Request Settings/Specifies whether to allow websites to make requests to any network endpoint in an insecure manner. Microsoft Edge version 139 introduces 6 new computer settings and 6 new user settings. We have included a spreadsheet listing the new settings in the release to make it easier for you to find them. As a friendly reminder, all available settings for Microsoft Edge are documented here, and all available settings for Microsoft Edge Update are documented here. Please continue to give us feedback through the Security Baseline Community or in comments on this post.Transforming Enterprise AKS: Multi-Tenancy at Scale with Agentic AI and Semantic Kernel
In this post, I’ll show how you can deploy an AI Agent on Azure Kubernetes Service (AKS) using a multi-tenant approach that maximizes both security and cost efficiency. By isolating each tenant’s agent instance within the cluster and ensuring that every agent has access only to its designated Azure Blob Storage container, cross-tenant data leakage risks are eliminated. This model allows you to allocate compute and storage resources per tenant, optimizing usage and spending while maintaining strong data segregation and operational flexibility—key requirements for scalable, enterprise-grade AI applications.
