Understanding and mitigating security risks in MCP implementations
Introducing any new technology can introduce new security challenges or exacerbate existing security risks. In this blog post, we’re going to look at some of the security risks that could be introduced to your environment when using Model Context Protocol (MCP), and what controls you can put in place to mitigate them. MCP is a framework that enables seamless integration between LLM applications and various tools and data sources. MCP defines: A standardized way for AI models to request external actions through a consistent API Structured formats for how data should be passed to and from AI systems Protocols for how AI requests are processed, executed, and returned MCP allows different AI systems to use a common set of tools and patterns, ensuring consistent behavior when AI models interact with external systems. MCP architecture MCP follows a client-server architecture that allows AI models to interact with external tools efficiently. Here’s how it works: MCP Host – The AI model (e.g., Azure OpenAI GPT) requesting data or actions. MCP Client – An intermediary service that forwards the AI model's requests to MCP servers. MCP Server – Lightweight applications that expose specific capabilities (APIs, databases, files, etc.). Data Sources – Various backend systems, including local storage, cloud databases, and external APIs. MCP security controls Any system which has access to important resources has implied security challenges. Security challenges can generally be addressed through correct application of fundamental security controls and concepts. As MCP is only newly defined, the specification is changing very rapidly and as the protocol evolves. Eventually the security controls within it will mature, enabling a better integration with enterprise and established security architectures and best practices. Research published in the Microsoft Digital Defense Report states that 98% of reported breaches would be prevented by robust security hygiene and the best protection against any kind of breach is to get your baseline security hygiene, secure coding best practices and supply chain security right – those tried and tested practices that we already know about still make the most impact in reducing security risk. Let's look at some of the ways that you can start to address security risks when adopting MCP. MCP server authentication (if your MCP implementation was before 26th April 2025) Problem statement: The original MCP specification assumed that developers would write their own authentication server. This requires knowledge of OAuth and related security constraints. MCP servers acted as OAuth 2.0 Authorization Servers, managing the required user authentication directly rather than delegating it to an external service such as Microsoft Entra ID. As of 26 April 2025, an update to the MCP specification allows for MCP servers to delegate user authentication to an external service. Risks: Misconfigured authorization logic in the MCP server can lead to sensitive data exposure and incorrectly applied access controls. OAuth token theft on the local MCP server. If stolen, the token can then be used to impersonate the MCP server and access resources and data from the service that the OAuth token is for. Mitigating controls: Thoroughly review your MCP server authorization logic, here some posts discussing this in more detail - Azure API Management Your Auth Gateway For MCP Servers | Microsoft Community Hub and Using Microsoft Entra ID To Authenticate With MCP Servers Via Sessions · Den Delimarsky Implement best practices for token validation and lifetime Use secure token storage and encrypt tokens Excessive permissions for MCP servers Problem statement: MCP servers may have been granted excessive permissions to the service/resource they are accessing. For example, an MCP server that is part of an AI sales application connecting to an enterprise data store should have access scoped to the sales data and not allowed to access all the files in the store. Referencing back to the principle of least privilege (one of the oldest security principles), no resource should have permissions in excess of what is required for it to execute the tasks it was intended for. AI presents an increased challenge in this space because to enable it to be flexible, it can be challenging to define the exact permissions required. Risks: Granting excessive permissions can allow for exfiltration or amending data that the MCP server was not intended to be able to access. This could also be a privacy issue if the data is personally identifiable information (PII). Mitigating controls: Clearly define the permissions that the MCP server has to access the resource/service it connects to. These permissions should be the minimum required for the MCP server to access the tool or data it is connecting to. Indirect prompt injection attacks Problem statement: Researchers have shown that the Model Context Protocol (MCP) is vulnerable to a subset of Indirect Prompt Injection attacks known as Tool Poisoning Attacks. Tool poisoning is a scenario where an attacker embeds malicious instructions within the descriptions of MCP tools. These instructions are invisible to users but can be interpreted by the AI model and its underlying systems, leading to unintended actions that could ultimately lead to harmful outcomes. Risks: Unintended AI actions present a variety of security risks that include data exfiltration and privacy breaches. Mitigating controls: Implement AI prompt shields: in Azure AI Foundry, you can follow these steps to implement AI prompt shields. Implement robust supply chain security: you can read more about how Microsoft implements supply chain security internally here. Established security best practices that will uplift your MCP implementation’s security posture Any MCP implementation inherits the existing security posture of your organization's environment that it is built upon, so when considering the security of MCP as a component of your overall AI systems it is recommended that you look at uplifting your overall existing security posture. The following established security controls are especially pertinent: Secure coding best practices in your AI application - protect against the OWASP Top 10, the OWASP Top 10 for LLMs, use of secure vaults for secrets and tokens, implementing end-to-end secure communications between all application components, etc. Server hardening – use MFA where possible, keep patching up to date, integrate the server with a third party identity provider for access, etc. Keep devices, infrastructure and applications up to date with patches Security monitoring – implementing logging and monitoring of an AI application (including the MCP client/servers) and sending those logs to a central SIEM for detection of anomalous activities Zero trust architecture – isolating components via network and identity controls in a logical manner to minimize lateral movement if an AI application were compromised. Conclusion MCP is a promising development in the AI space that enables rich data and context access. As developers embrace this new approach to integrating their organization's APIs and connectors into LLMs, they need to be aware of security risks and how to implement controls to reduce those risks. There are mitigating security controls that can be put in place to reduce the risks inherent in the current specification, but as the protocol develops expect that some of the risks will reduce or disappear entirely. We encourage you to contribute to and suggest security related MCP RFCs to make this protocol even better! With thanks to OrinThomas, dasithwijes, dendeli and Peter Marcu for their inputs and collaboration on this post.Enterprise-grade controls for AI apps and agents built with Azure AI Foundry and Copilot Studio
AI innovation is moving faster than ever, and more AI projects are moving beyond experimentation into deployment, to drive tangible business impact. As organizations accelerate innovation with custom AI applications and agents, new risks emerge across the software development lifecycle and AI stack related to data oversharing and leaks, new vulnerabilities and threats, and non-compliance with stringent regulatory requirements Through 2025, poisoning of software supply chains and infrastructure technology stacks will constitute more than 70% of malicious attacks against AI used in the enterprise 1 , highlighting potential threats that originate early in development. Today, the average cost of a data breach is $4.88 million, but when security issues are caught early in the development process, that number drops dramatically to just $80 per incident 2 . The message is very clear; security can’t be an afterthought anymore. It must be a team sport across the organization, embedded from the start and throughout the development lifecycle. That's why developers and security teams should align on processes and tools that bring security into every stage of the AI development lifecycle and give security practitioners visibility into and the ability to mitigate risks. To address these growing challenges and help customers secure and govern their AI workloads across development and security teams, we are: Enabling Azure AI Foundry and Microsoft Copilot Studio to provide best-in-class foundational capabilities to secure and govern AI workloads Deeply integrating and embedding industry-leading capabilities from Microsoft Purview, Microsoft Defender, and Microsoft Entra into Azure AI Foundry and Microsoft Copilot Studio This week, 3,000 developers are gathering in Seattle for the annual Microsoft Build conference, with many more tuning in online, to learn practical skills for accelerating their AI apps and agents' innovation. To support their AI innovation journey, today we are excited to announce several new capabilities to help developers and organizations secure and govern AI apps and agents. New Azure AI Foundry foundational capabilities to secure and govern AI workloads Azure AI Foundry enhancements for AI security and safety With 70,000 customers, 100 trillion tokens processed this quarter, and 2 billion enterprise search queries each day, Azure AI Foundry has grown beyond just an application layer—it's now a comprehensive platform for building agents that can plan, take action, and continuously learn to drive real business outcomes. To help organizations build and deploy AI with confidence, we’re introducing new security and safety capabilities and insights for developers in Azure AI Foundry Introducing Spotlighting to detect and block prompt injection attacks in real time As AI systems increasingly rely on external data sources, a new class of threats has emerged. Indirect prompt injection attacks embed hidden instructions in documents, emails, and web content, tricking models into taking unauthorized actions without any direct user input. These attacks are difficult to detect and hard to prevent using traditional filters alone. To address this, Azure AI Content Safety is introducing Spotlighting, now available in preview. Spotlighting strengthens the Prompt Shields guardrail by improving its ability to detect and handle potential indirect prompt injections, where hidden adversarial instructions are embedded in external content. This new capability helps prevent the model from inadvertently acting on malicious prompts that are not directly visible to the user. Enable Spotlighting in Azure AI Content Safety to detect potential indirect prompt injection attacks New capabilities for task adherence evaluation and task adherence mitigation to ensure agents remain within scope As developers build more capable agents, organizations face growing pressure to help confirm those agents act within defined instructions and policy boundaries. Even small deviations can lead to tool misuse, broken workflows, or risks like unintended exposure of sensitive data. To solve this, Azure AI Foundry now includes task adherence for agents, now in preview and powered by two components: a real-time evaluation and a new control within Azure AI Content Safety. At the core is a real-time task adherence evaluation API, part of Azure AI Content Safety. This API assesses whether an agent’s behavior is aligned with its assigned task by analyzing the user’s query, system instructions, planned tool calls, and the agent’s response. The evaluation framework is built on Microsoft’s Agent Evaluators, which measure intent resolution, tool selection accuracy, completeness of response, and overall alignment to the original request. Developers can run this scoring logic locally using the Task Adherence Evaluator in the Azure AI Evaluation SDK, with a five-point scale that ranges from fully nonadherent to fully adherent. This gives teams a flexible and transparent way to inspect task-level behavior before it causes downstream issues. Task adherence is enforced through a new control in Azure AI Content Safety. If an agent goes off-task, the control can block tool use, pause execution, or trigger human review. In Azure AI Agent Service, it is available as an opt-in feature and runs automatically. Combined with real-time evaluation, this control helps to ensure that agents stay on task, follow instructions, and operate according to enterprise policies. Learn more about Prompt Shields in Azure AI Content Safety. Azure AI Foundry continuous evaluation and monitoring of agentic systems Maintaining high performance and compliance for AI agents after deployment is a growing challenge. Without ongoing oversight, issues like performance degradation, safety risks, or unintentional misuse of resources can slip through unnoticed. To address this, Azure AI Foundry introduces continuous evaluation and monitoring of agentic systems, now in preview, provides a single pane of glass dashboard to track key metrics such as performance, quality, safety, and resource usage in real time. Continuous evaluation runs quality and safety evaluations at a sampled rate of production usage with results made available in the Azure AI Foundry Monitoring dashboard and published to Application Insights. Developers can set alerts to detect drift or regressions and use Azure Monitor to gain full-stack visibility into their AI systems. For example, an organization using an AI agent to assist with customer-facing tasks can monitor groundedness and detect a decline in quality when the agent begins referencing irrelevant information, helping teams to act before it potentially negatively affects trust of users. Azure AI Foundry evaluation integrations with Microsoft Purview Compliance Manager, Credo AI, and Saidot for streamlined compliance AI regulations and standards introduce new requirements for transparency, documentation, and risk management for high-risk AI systems. As developers build AI applications and agents, they may need guidance and tools to help them evaluate risks based on these requirements and seamlessly share control and evaluation insights with compliance and risk teams. Today, we are announcing previews for Azure AI Foundry evaluation tool’s integration with a compliance management solution, Microsoft Purview Compliance Manager, and AI governance solutions, Credo AI and Saidot. These integrations help define risk parameters, run suggested compliance evaluations, and collect evidence for control testing and auditing. For example, for a developer who’s building an AI agent in Europe may be required by their compliance team to complete a Data Protection Impact Assets (DPIA) and Algorithmic Impact Assessment (AIA) to meet internal risk management and technical documentation requirements aligned with emerging AI governance standards and best practices. Based on Purview Compliance Manager’s step-by-step guidance on controls implementation and testing, the compliance teams can evaluate risks such as potential bias, cybersecurity vulnerabilities, or lack of transparency in model behavior. Once the evaluation is conducted in Azure AI Foundry, the developer can obtain a report with documented risk, mitigation, and residual risk for compliance teams to upload to Compliance Manager to support audits and provide evidence to regulators or external stakeholders. Assess controls for Azure AI Foundry against emerging AI governance standards Learn more about Purview Compliance Manager. Learn more about the integration with Credo AI and Saidot in this blogpost. Leading Microsoft Entra, Defender and Purview value extended to Azure AI Foundry and Microsoft Copilot Studio Introducing Microsoft Entra Agent ID to help address agent sprawl and manage agent identity Organizations are rapidly building their own AI agents, leading to agent sprawl and a lack of centralized visibility and management. Security teams often struggle to keep up, unable to see which agents exist and whether they introduce security or compliance risks. Without proper oversight, agent sprawl increases the attack surface and makes it harder to manage these non-human identities. To address this challenge, we’re announcing the public preview of Microsoft Entra Agent ID, a new capability in the Microsoft Entra admin center that gives security admins visibility and control over AI agents built with Copilot Studio and Azure AI Foundry. With Microsoft Entra Agent ID, an agent created through Copilot Studio or Azure AI Foundry is automatically assigned an identity with no additional work required from the developers building them. This is the first step in a broader initiative to manage and protect non-human identities as organizations continue to build AI agents. : Security and identity admins can gain visibility into AI agents built in Copilot Studio and Azure AI Foundry in the Microsoft Entra Admin Center This new capability lays the foundation for more advanced capabilities coming soon to Microsoft Entra. We also know that no one can do it alone. Security has always been a team sport, and that’s especially true as we enter this new era of protecting AI agents and their identities. We’re energized by the momentum across the industry; two weeks ago, we announced support for the Agent-to-Agent (A2A) protocol and began collaborating with partners to shape the future of AI identity workflows. Today, we’re also excited to announce new partnerships with ServiceNow and Workday. As part of this, we’ll integrate Microsoft Entra Agent ID with the ServiceNow AI Platform and the Workday Agent System of Record. This will allow for automated provisioning of identities for future digital employees. Learn more about Microsoft Entra Agent ID. Microsoft Defender security alerts and recommendations now available in Azure AI Foundry As more AI applications are deployed to production, organizations need to predict and prevent potential AI threats with natively integrated security controls backed by industry-leading Gen AI and threat intelligence for AI deployments. Developers need critical signals from security teams to effectively mitigate security risks related to their AI deployments. When these critical signals live in separate systems outside the developer experience, this can create delays in mitigation, leaving opportunities for AI apps and agents to become liabilities and exposing organizations to various threats and compliance violations. Now in preview, Microsoft Defender for Cloud integrates AI security posture management recommendations and runtime threat protection alerts directly into the Azure AI Foundry portal. These capabilities, previously announced as part of the broader Microsoft Defender for Cloud solution, are extended natively into Azure AI Foundry enabling developers to access alerts and recommendations without leaving their workflows. This provides real-time visibility into security risks, misconfigurations, and active threats targeting their AI applications on specific Azure AI projects, without needing to switch tools or wait on security teams to provide details. Security insights from Microsoft Defender for Cloud help developers identify and respond to threats like jailbreak attacks, sensitive data leakage, and misuse of system resources. These insights include: AI security posture recommendations that identify misconfigurations and vulnerabilities in AI services and provide best practices to reduce risk Threat protection alerts for AI services that notify developers of active threats and provide guidance for mitigation, across more than 15 detection types For example, a developer building an AI-powered agent can receive security recommendations suggesting the use of Azure Private Link for Azure AI Services resources. This reduces the risk of data leakage by handling the connectivity between consumers and services over the Azure backbone network. Each recommendation includes actionable remediation steps, helping teams identify and mitigate risks in both pre- and post-deployment phases. This helps to reduce risks without slowing down innovation. : Developers can view security alerts on the Risks + alerts page in Azure AI Foundry : Developers can view recommendations on the Guardrails + controls page in Azure AI Foundry This integration is currently in preview and will be generally available in June 2025 in Azure AI Foundry. Learn more about protecting AI services with Microsoft Defender for Cloud. Microsoft Purview capabilities extended to secure and govern data in custom-built AI apps and agents Data oversharing and leakage are among the top concerns for AI adoption, and central to many regulatory requirements. For organizations to confidently deploy AI applications and agents, both low code and pro code developers need a seamless way to embed security and compliance controls into their AI creations. Without simple, developer-friendly solutions, security gaps can quickly become blockers, delaying deployment and increasing risks as applications move from development to production. Today, Purview is extending its enterprise-grade data security and compliance capabilities, making it easier for both low code and pro code developers to integrate data security and compliance into their AI applications and agents, regardless of which tools or platforms they use. For example, with this update, Microsoft Purview DSPM for AI becomes the one place data security teams can see all the data risk insights across Microsoft Copilots, agents built in Agent Builder and Copilot Studio, and custom AI apps and agents built in Azure AI Foundry and other platforms. Admins can easily drill into security and compliance insights for specific AI apps or agents, making it easier to investigate and take action on potential risks. : Data security admins can now find data security and compliance insights across Microsoft Copilots, agents built with Agent Builder and Copilot Studio, and custom AI apps and agents in Microsoft Purview DSPM for AI In the following sections, we will provide more details about the updates to Purview capabilities in various AI workloads. 1. Microsoft Purview data security and compliance controls can be extended to any custom-built AI application and agent via the new Purview SDK or the native Purview integration with Azure AI Foundry. The new capabilities make it easy and effortless for security teams to bring the same enterprise-grade data security compliance controls available today for Microsoft 365 Copilot to custom AI applications and agents, so organizations can: Discover data security risks, such as sensitive data in user prompts, and data compliance risks, such as harmful content, and get recommended actions to mitigate risks proactively in Microsoft Purview Data Security Posture Management (DSPM) for AI. Protect sensitive data against data leakage and insider risks with Microsoft Purview data security policies. Govern AI interactions with Audit, Data Lifecycle Management, eDiscovery, and Communication Compliance. Microsoft Purview SDK Microsoft Purview now offers Purview SDK, a set of REST APIs, documentation, and code samples, currently in preview, enabling developers to integrate Purview's data security and compliance capabilities into AI applications or agents within any integrated development environment (IDE). : By embedding Purview APIs into the IDE, developers help enable their AI apps to be secured and governed at runtime For example, a developer building an AI agent using an AWS model can use the Purview SDK to enable their AI app to automatically identify and block sensitive data entered by users before it’s exposed to the model, while also providing security teams with valuable signals that support compliance. With Purview SDK, startups, ISVs, and partners can now embed Purview industry-leading capabilities directly into their AI software solutions, making these solutions Purview aware and easier for their customers to secure and govern data in their AI solutions. For example, Infosys Vice President and Delivery Head of Cyber Security Practice, Ashish Adhvaryu indicates, “Infosys Cyber Next platform integrates Microsoft Purview to provide enhanced AI security capabilities. Our solution, the Cyber Next AI assistant (Cyber Advisor) for the SOC analyst, leverages Purview SDK to drive proactive threat mitigation with real-time monitoring and auditing capabilities. This integration provides holistic AI-assisted protection, enhancing cybersecurity posture." Microsoft partner EY (previously known as Ernst and Young) has also leveraged the new Purview SDK to embed Purview value into their GenAI initiatives. “We’re not just building AI tools, we are creating Agentic solutions where trust, security, and transparency are present from the start, supported by the policy controls provided through the Purview SDK. We’re seeing 25 to 30 percent time savings when we build secure features using the Purview SDK,” noted Sumanta Kar, Partner, Innovation and Emerging Tech at EY. Learn more about the Purview SDK. Microsoft Purview integrates natively with Azure AI Foundry Organizations are developing an average of 14 custom AI applications. The rapid pace of AI innovation may leave security teams unaware of potential data security and compliance risks within their environments. With the update announced today, Azure AI Foundry signals are now directly integrated with Purview Data Security Posture Management for AI, Insider Risk Management, and data compliance controls, minimizing the need for additional development work. For example, for AI applications and agents built with Azure AI Foundry models, data security teams can gain visibility into AI usage and data risks in Purview DSPM for AI, with no additional work from developers. Data security teams can also detect, investigate, and respond to both malicious and inadvertent user activities, such as a departing employee leveraging an AI agent to retrieve an anomalous amount of sensitive data, with Microsoft Purview Insider Risk Management (IRM) policies. Lastly, user prompts and AI responses in Azure AI apps and agents can now be ingested into Purview compliance tools as mentioned above. Learn more about Microsoft Purview for Azure AI Foundry. 2. Purview data protections extended to Copilot Studio agents grounded in Microsoft Dataverse data Coming to preview in June, Purview Information Protection extends auto-labeling and label inheritance coverage to Dataverse to help prevent oversharing and data leaks. Information Protection makes it easier for organizations to automatically classify and protect sensitive data at scale. A common challenge is that sensitive data often lands in Dataverse from various sources without consistent labeling or protection. The rapid adoption of agents built using Copilot Studio and grounding data from Dataverse increases the risk of data oversharing and leakage if data is not properly protected. With auto-labeling, data stored in Dataverse tables can be automatically labeled based on policies set in Microsoft Purview, regardless of its source. This reduces the need for manual labeling effort and protects sensitive information from the moment it enters Dataverse. With label inheritance, AI agent responses grounded in Dataverse data will automatically carry and honor the source data’s sensitivity label. If a response pulls from multiple tables with different labels, the most restrictive label is applied to ensure consistent protection. For example, a financial advisor building an agent in Copilot Studio might connect multiple Dataverse tables, some labeled as “General” and others as “Highly Confidential.” If a response pulls from both, it will inherit the most restrictive label, in this case, "Highly Confidential,” to prevent unauthorized access and ensure appropriate protections are applied across both maker and users of the agent. Together, auto-labeling and label inheritance in Dataverse support a more secure, automated foundation for AI. : Sensitivity labels will be automatically applied to data in Dataverse : AI-generated responses will inherit and honor the source data’s sensitivity labels Learn more about protecting Dataverse data with Microsoft Purview. 3. Purview DSPM for AI can now provide visibility into unauthenticated interactions with Copilot Studio agents As organizations increasingly use Microsoft Copilot Studio to deploy AI agents for frontline customer interactions, gaining visibility into unauthenticated user interactions and proactively mitigating risks becomes increasingly critical. Building on existing Purview and Copilot Studio integrations, we’ve extended DSPM for AI and Audit in Copilot Studio to provide visibility into unauthenticated interactions, now in preview. This gives organizations a more comprehensive view of AI-related data security risks across authenticated and unauthenticated users. For example, a healthcare provider hosting an external, customer-facing agent assistant must be able to detect and respond to attempts by unauthenticated users to access sensitive patient data. With these new capabilities in DSPM for AI, data security teams can now identify these interactions, assess potential exposure of sensitive data, and act accordingly. Additionally, integration with Purview Audit provides teams with seamless access to information needed for audit requirements. : Gain visibility into all AI interactions, including those from unauthenticated users Learn more about Purview for Copilot Studio. 4. Purview Data Loss Prevention extended to more Microsoft 365 agent scenarios To help organizations prevent data oversharing through AI, at Ignite 2024, we announced that data security admins could prevent Microsoft 365 Copilot from using certain labeled documents as grounding data to generate summaries or responses. Now in preview, this control also extends to agents published in Microsoft 365 Copilot that are grounded by Microsoft 365 data, including pre-built Microsoft 365 agents, agents built with the Agent Builder, and agents built with Copilot Studio. This helps ensure that files containing sensitive content are used appropriately by AI agents. For example, confidential legal documents with highly specific language that could lead to improper guidance if summarized by an AI agent, or "Internal only” documents that shouldn’t be used to generate content that can be shared outside of the organization. : Extend data loss prevention (DLP) policies to Microsoft 365 Copilot agents to protect sensitive data Learn more about Data Loss Prevention for Microsoft 365 Copilot and agents. The data protection capabilities we are extending to agents in Agent Builder and Copilot Studio demonstrate our continued investment in strengthening the Security and Governance pillar of the Copilot Control System (CSS). CCS provides integrated controls to help IT and security teams secure, manage, and monitor Copilot and agents across Microsoft 365, spanning governance, management, and reporting. Learn more here. Explore additional resources As developers and security teams continue to secure AI throughout its lifecycle, it’s important to stay ahead of emerging risks and ensure protection. Microsoft Security provides a range of tools and resources to help you proactively secure AI models, apps, and agents from code to runtime. Explore the following resources to deepen your understanding and strengthen your approach to AI security: Learn more about Security for AI solutions on our webpage Learn more about Microsoft Purview SDK Get started with Azure AI Foundry Get started with Microsoft Entra Get started with Microsoft Purview Get started with Microsoft Defender for Cloud Get started with Microsoft 365 Copilot Get started with Copilot Studio Sign up for a free Microsoft 365 E5 Security Trial and Microsoft Purview Trial 1 Predicts 2025: Navigating Imminent AI Turbulence for Cybersecurity, Jeremy D'Hoinne, Akif Khan, Manuel Acosta, Avivah Litan, Deepak Seth, Bart Willemsen, 10 February 2025 2 IBM. "Cost of a Data Breach 2024: Financial Industry." IBM Think, 13 Aug. 2024, https://www.ibm.com/think/insights/cost-of-a-data-breach-2024-financial-industry; Cser, Tamas. "The Cost of Finding Bugs Later in the SDLC." Functionize, 5 Jan. 2023, https://www.functionize.com/blog/the-cost-of-finding-bugs-later-in-the-sdlcStep by Step: 2-Tier PKI Lab
Purpose of this blog Public Key Infrastructure (PKI) is the backbone of secure digital identity management, enabling encryption, digital signatures, and certificate-based authentication. However, neither setting up a PKI nor management of certificates is something most IT pros do on a regular basis and given the complexity and vastness of the subject it only makes sense to revisit the topic from time to time. What I have found works best for me is to just set up a lab and get my hands dirty with the topic that I want to revisit. One such topic that I keep coming back to is PKI - be it for creating certificate templates, enrolling clients, or flat out creating a new PKI itself. But every time I start deploying a lab or start planning a PKI setup, I end up spending too much time sifting through the documentations and trying to figure out why my issuing certificate authority won't come online! To make my life easier I decided to create a cheatsheet to deploy a simple but secure 2-tier PKI lab based on industry best practices that I thought would be beneficial for others like me, so I decided to polish it and make it into a blog. This blog walks through deploying a two-tier PKI hierarchy using Active Directory Certificate Services (AD CS) on Windows Server: an offline Root Certification Authority (Root CA) and an online Issuing Certification Authority (Issuing CA). We’ll cover step-by-step deployment and best practices for securing the root CA, conducting key ceremonies, and maintaining Certificate Revocation Lists (CRLs). Overview: Two-Tier PKI Architecture and Components In a two-tier PKI, the Root CA sits at the top of the trust hierarchy and issues a certificate only to the subordinate Issuing CA. The Root CA is kept offline (disconnected from networks) to protect its private key and is typically a standalone CA (not domain-joined). The Issuing CA (sometimes called a subordinate or intermediate CA) is kept online to issue certificates to end-entities (users, computers, services) and is usually an enterprise CA integrated with Active Directory for automation and certificate template support. Key components: Offline Root CA: A standalone CA, often on a workgroup server, powered on only when necessary (initial setup, subordinate CA certificate signing, or periodic CRL publishing). By staying offline, it is insulated from network threats. Its self-signed certificate serves as the trust anchor for the entire PKI. The Root CA’s private key must be rigorously protected (ideally by a Hardware Security Module) because if the root is compromised, all certificates in the hierarchy are compromised. Online Issuing CA: An enterprise subordinate CA (domain-joined) that handles day-to-day certificate issuance for the organization. It trusts the Root CA (via the root’s certificate) and is the one actually responding to certificate requests. Being online, it must also be secured, but its key is kept online for operations. Typically, the Issuing CA publishes certificates and CRLs to Active Directory and/or HTTP locations for clients to download. The following diagram shows the simplified view of this implementations: The table below summarizes the roles and differences: Aspect Offline Root CA Online Issuing CA Role Standalone Root CA (workgroup) Enterprise Subordinate CA (domain member) Network Connectivity Kept offline (powered off or disconnected when not issuing) Online (running continuously to serve requests) Usage Signs only one certificate (the subordinate CA’s cert) and CRLs Issues end-entity certificates (users, computers, services) Active Directory Not a member of AD domain; doesn’t use templates or auto-enrollment Integrated with AD DS; uses certificate templates for streamlined issuance Security Extremely high: physically secured, limited access, often protected by HSM Very High: server hardened, but accessible on network; HSM recommended for private key CRL Publication Manual. Admin must periodically connect, generate, and distribute CRL. Delta CRLs usually disabled. Automatic. Publishes CRLs to configured CDP locations (AD DS, HTTP) at scheduled intervals. Validity Period Longer (e.g. 5-10+ years for the CA certificate) to reduce frequency of renewal. Shorter (e.g. 2 years) to align with organizational policy; renewed under the root when needed. In this lab setup, we will create a Contoso Root CA (offline) and a Contoso Issuing CA (online) as an example. This mirrors real-world best practices which is to "deploy a standalone offline root CA and an online enterprise subordinate CA”. Deploying the Offline Root CA Setting up the offline Root CA involves preparing a dedicated server, installing AD CS, configuring it as a root CA, and then securing it. We’ll also configure certificate CDP/AIA (CRL Distribution Point and Authority Information Access) locations so that issued certificates will point clients to the correct locations to fetch the CA’s certificate and revocation list. Step 1: Prepare the Root CA Server (Offline) Provision an isolated server: Install a Windows Server OS (e.g., Windows Server 2022) on the machine designated to be the Root CA. Preferably on a portable enterprise grade physical server that can be stored in a safe. Do not join this server to any domain – it should function in a Workgroup to remain independent of your AD forest. System configuration: Give the server a descriptive name (e.g., ROOTCA) and assign a static IP (even though it will be offline, a static IP helps when connecting it temporarily for management). Install the latest updates and security patches while it’s still able to go online. Lock down network access: Once setup is complete, disable or unplug network connections. If the server must remain powered on for any reason, ensure all unnecessary services/ports are disabled to minimize exposure. In practice, you will keep this server shut down or physically disconnected except when performing CA maintenance. Step 2: Install the AD CS Role on the Root CA Add the Certification Authority role: On the Root CA server, open Server Manager and add the Active Directory Certificate Services role. During the wizard, select the Certification Authority role service (no need for web enrollment or others on the root). Proceed through the wizard and complete the installation. You can also install the CA role and management tools via PowerShell: Install-WindowsFeature AD-Certificate -IncludeManagementToolsThis Role Services: Choose Certification Authority. Setup Type: Select Standalone CA (since this root CA is not domain-joined). CA Type: Select Root CA. Private Key: Choose “Create a new private key.” Cryptography: If using an HSM, select the HSM’s Cryptographic Service Provider (CSP) here; otherwise use default. Choose a strong key length (e.g., 2048 or 4096 bits) and a secure hash algorithm (SHA-256 or higher). CA Name: Provide a common name for the CA (e.g., “Contoso Root CA”). This name will appear in issued certificates as the Issuer. Avoid using a machine DNS name here for security – pick a name without revealing the server’s actual hostname. Validity Period: Set a long validity (e.g., 10 years) for the root CA’s self-signed certificate. A decade is common for enterprise roots, reducing how often you must touch the offline CA for renewal. Database: Specify locations for the CA database and logs (the defaults are fine for a lab). Review settings and complete the configuration. This process will generate the root CA’s key pair and self-signed certificate, establishing the Root CA.Post-install configuration: After the binary installation, click Configure Active Directory Certificate Services (a notification in Server Manager). In the configuration wizard: You can also perform this configuration via PowerShell in one line: Install-AdcsCertificationAuthority ` -CAType StandaloneRootCA ` -CryptoProviderName "YourHSMProvider" ` -HashAlgorithmName SHA256 -KeyLength 2048 ` -CACommonName "Contoso Root CA" ` -ValidityPeriod Years -ValidityPeriodUnits 10 This would set up a standalone Root CA named "Contoso Root CA" with a 2048-bit key on an HSM provider, valid for 10 years. Step 3: Integrate an HSM (Optional but Recommended) If your lab has a Hardware Security Module, use it to secure the Root CA’s keys. Using an HSM provides a dedicated, tamper-resistant storage for CA private keys and can further protect against key compromise. To integrate: Install the HSM vendor’s software and drivers on the Root CA server. Initialize the HSM and create a security world or partition as per the vendor instructions. Before or during the CA configuration (Step 2 above), ensure the HSM is ready to generate/store the key. When running the AD CS configuration, select the HSM’s CSP/KSP for the cryptographic provider so that the CA’s private key is generated on the HSM. Secure any HSM admin tokens or smartcards. For a root CA, you might employ M of N key splits – requiring multiple key custodians to collaborate to activate the HSM or key – as part of the key ceremony (discussed later). (If an HSM is not available, the root key will be stored on the server’s disk. At minimum, protect it with a strong admin passphrase when prompted, and consider enabling the option to require administrator interaction (e.g., a password) whenever the key is accessed.) Step 4: Configure CA Extensions (CDP/AIA) It’s critical to configure how the Root CA publishes its certificate and revocation list, since the root is offline and cannot use Active Directory auto-publishing. Open the Certification Authority management console (certsrv.msc), right-click the CA name > Properties, and go to the Extensions tab. We will set the CRL Distribution Points (CDP) and Authority Information Access (AIA) URLs: CRL Distribution Point (CDP): This is where certificates will tell clients to fetch the CRL for the Root CA. By default, a standalone CA might have a file:// path or no HTTP URL. Click Add and specify an HTTP URL that will be accessible to all network clients, such as: http://<IssuingCA_Server>/CertEnroll/<CaName><CRLNameSuffix><DeltaCRLAllowed>.crl For example, if your issuing CA’s server name is ISSUINGCA.contoso.local, the URL might be http://issuingca.contoso.local/CertEnroll/Contoso%20Root%20CA.crl This assumes the Issuing CA (or another web server) will host the Root CA’s CRL in the CertEnroll directory. Check the boxes for “Include in the CDP extension of issued certificates” and “Include in all CRLs. Clients use this to find Delta CRLs” (you can uncheck the delta CRL publication on the root, as we won’t use delta CRLs on an offline root). Since the root CA won’t often revoke its single issued cert (the subordinate CA), delta CRLs aren’t necessary. Note: If your Active Directory is in use and you want to publish the Root CA’s CRL to AD, you can also add an ldap:///CN=... path and check “Publish in Active Directory”. However, publishing to AD from an offline CA must be done manually using the following command when the root is temporarily connected. certutil -dspublish Many setups skip LDAP for offline roots and rely on HTTP distribution. Authority Information Access (AIA): This is where the Root CA’s certificate will be published for clients to download (to build certificate chains). Add an HTTP URL similarly, for example: http://<IssuingCA_Server>/CertEnroll/<ServerDNSName>_<CaName><CertificateName>.crt This would point to a copy of the Root CA’s certificate that will be hosted on the issuing CA web server. Check “Include in the AIA extension of issued certificates”. This way, any certificate signed by the Root CA (like your subordinate CA’s cert) contains a URL where clients can fetch the Root CA’s cert if they don’t already have it. After adding these, remove any default entries that are not applicable (e.g., LDAP if the root isn’t going to publish to AD, or file paths that won’t be used by clients). These settings ensure that certificates issued by the Root CA (in practice, just the subordinate CA’s certificate) will carry the correct URLs for chain building and revocation checking. Step 5: Back Up the Root CA and Issue the Subordinate Certificate With the Root CA configured, we need to issue a certificate for the Issuing CA (subordinate). We’ll perform that in the next section from the Issuing CA’s side via a request file. Before taking the root offline, ensure you: Back up the CA’s private key and certificate: In the Certification Authority console, or via the CA Backup wizard, export the Root CA’s key pair and CA certificate. Protect this backup (store it offline in a secure location, e.g., on encrypted removable media in a safe). This backup is crucial for disaster recovery or if the Root CA needs to be migrated or restored. Save the Root CA Certificate: You will need the Root CA’s public certificate (*.crt) to distribute to other systems. Have it exported (Base-64 or DER format) for use on the Issuing CA and for clients. Initial CRL publication: Manually publish the first CRL so that it can be distributed. Open an elevated Command Prompt on the Root CA and run: certutil -crl This generates a new CRL file (in the CA’s configured CRL folder, typically %windir%\system32\CertSrv\CertEnroll). Take that CRL file and copy it to the designated distribution point (for example, to the CertEnroll directory on the Issuing CA’s web server, as per the HTTP URL configured). If using Active Directory for CRL distribution, you would also publish it to AD now (e.g., certutil -dspublish -f RootCA.crl on a domain-connected machine). In most lab setups, copying to an HTTP share is sufficient. With these tasks done, the Root CA is ready. At this point, disconnect or power off the Root CA and store it securely – it should remain offline except when it’s absolutely needed (like publishing a new CRL or renewing the subordinate CA’s certificate in the far future). Keeping the root CA offline maximizes its security by minimizing exposure to compromise. Best Practices for Securing the Root CA: The Root CA is the trust anchor, so apply stringent security practices: Physical security: Store the Root CA machine in a locked, secure location. If it’s a virtual machine, consider storing it on a disconnected hypervisor or a USB drive locked in a safe. Only authorized PKI team members should have access. An offline CA should be treated like crown jewels – offline CAs should be stored in secure locations. Minimal exposure: Keep the Root CA powered off and disconnected when not in use. It should not be left running or connected to any network. Routine operations (like issuing end-entity certs) should never involve the root. Admin access control: Limit administrative access on the Root CA server. Use dedicated accounts for PKI administration. Enable auditing on the CA for any changes or issuance events. No additional roles or software: Do not use the Root CA server for any other function (no web browsing, no email, etc.). Fewer installed components means fewer potential vulnerabilities. Protect the private key: Use an HSM if possible; if not, ensure the key is at least protected by a strong password and consider splitting knowledge of that password among multiple people (so no single person can activate the CA). Many organizations opt for an offline root key ceremony (see below) to generate and handle the root key with multiple witnesses and strict procedures. Keep system time and settings consistent: If the Root CA is powered off for long periods, ensure its clock is accurate whenever it is started (to avoid issuing a CRL or certificate with a wrong date). Don’t change the server name or CA name after installation (doing so invalidates issued certs). Periodic health checks: Even though offline, plan to turn on the Root CA at a secure interval (e.g., semi-annually or annually) to perform tasks like CRL publishing and system updates. Make sure to apply OS security updates during these maintenance windows, as offline does not mean immune to vulnerabilities (especially if it ever connects to a network for CRL publication or uses removable media). Deploying the Online Issuing CA Next, set up the Issuing CA server which will actually issue certificates to end entities in the lab. This server will be domain-joined (if using AD integration) and will obtain its CA certificate from the Root CA we just configured. Step 1: Prepare the Issuing CA Server Provision the server: Install Windows Server on a new machine (or VM) that will be the Issuing CA. Join this server to the Active Directory domain (e.g., Contoso.local). Being an enterprise CA, it needs domain membership to publish templates and integrate with AD security groups. Rename the server to something descriptive like ISSUINGCA for clarity. Assign a static IP and ensure it can communicate on the network. IIS for web enrollment (optional): If you plan to use the Web Enrollment or Certificate Enrollment Web Services, ensure IIS is installed. (The AD CS installation wizard can add it if you include those role services.) For this guide, we will include the Web Enrollment role so that the CertEnroll directory is set up for hosting certificate and CRL files. Step 2: Install AD CS Role on Issuing CA On the Issuing CA server, add the Active Directory Certificate Services role via Server Manager or PowerShell. This time, select both Certification Authority and Certification Authority Web Enrollment role services (Web Enrollment will set up the HTTP endpoints for certificate requests if needed). For example, using PowerShell: Install-WindowsFeature AD-Certificate, ADCS-Web-Enrollment -IncludeManagementTools After installation, launch the AD CS configuration wizard: Role Services: Choose Certification Authority (and Web Enrollment if prompted). Setup Type: Select Enterprise CA (since this CA will integrate with AD DS). CA Type: Select Subordinate CA (this indicates it will get its cert from an existing root CA). Private Key: Choose “Create a new private key” (we’ll generate a new key pair for this CA). Cryptography: If using an HSM here as well, select the HSM’s CSP/KSP for the issuing CA’s key. Otherwise, choose a strong key length (2048+ bits, SHA256 or better for hash). CA Name: Provide a name (e.g., “Contoso Issuing CA”). This name will appear as the Issuer on certificates it issues. Certificate Request: The wizard will ask how you want to get the subordinate CA’s certificate. Choose “Save a certificate request to file”. Specify a path, e.g., C:\CertRequest\issuingCA.req. The wizard will generate a request file that we need to take to the Root CA for signing. (Since our Root CA is offline, this file transfer might be via secure USB or a network share when the root is temporarily online.) CA Database: Choose locations or accept defaults for the certificate DB and logs. Finish the configuration wizard, which will complete pending because the CA doesn’t have a certificate yet. The AD CS service on this server won’t start until we import the issued cert from the root. Step 3: Integrate HSM on Issuing CA (Optional) If available, repeat the HSM setup on the Issuing CA: install HSM drivers, initialize it, and generate/secure the key for the subordinate CA on the HSM. Ensure you chose the HSM provider during the above configuration so that the issuing CA’s private key is stored in the HSM. Even though this CA is online, an HSM still greatly enhances security by protecting the private key from extraction. The issuing CA’s HSM may not require multiple custodians to activate (as it needs to run continuously), but should still be physically secured. Step 4: Obtain the Issuing CA’s Certificate from the Root CA Now we have a pending request (issuingCA.req) for the subordinate CA. To get its certificate: Transport the request to the Root CA: Copy the request file to the offline Root CA (via secure means – e.g., formatted new USB stick). Start up the Root CA (in a secure, offline setting) and open the Certification Authority console. Submit the request on Root CA: Right-click the Root CA in the CA console -> All Tasks -> Submit new request, and select the .req file. The request will appear in the Pending Requests on the root. Issue the subordinate CA certificate: Find the pending request (it will list the Issuing CA’s name). Right-click and choose All Tasks > Issue. The subordinate CA’s certificate is now issued by the Root CA. Export the issued certificate: Still on the Root CA, go to Issued Certificates, find the newly issued subordinate CA cert (you can identify it by the Request ID or by the name). Right-click it and choose Open or All Tasks > Export to get the certificate in a file form. If using the console’s built-in “Export” it might only allow binary; alternatively use the certutil command: certutil -dup <RequestID> .\ContosoIssuingCA.cer or simply open and copy to file. Save the certificate as issuingCA.cer. Also make sure you have a copy of the Root CA’s certificate (if not already done). Publish Root CA cert and CRL as needed: Before leaving the Root CA, you may also want to ensure the Root’s own certificate and latest CRL are available to the issuing CA and clients. If not already done in Step 5 of root deployment, export the Root CA cert (DER format) and copy the CRL file. You might use certutil -crl again if some time has passed since initial CRL. Now take the issuingCA.cer file (and root cert/CRL files) and move them back to the Issuing CA server. Step 5: Install the Issuing CA’s Certificate and Complete Configuration On the Issuing CA server (which is still waiting for its CA cert): Install the subordinate CA certificate: In Server Manager or the Certification Authority console on the Issuing CA, there should be an option to “Install CA Certificate” (if the AD CS configuration wizard is still open, it will prompt for the file; or otherwise, in the CA console right-click the CA name > All Tasks > Install CA Certificate). Provide the issuingCA.cer file obtained from the root. This will install the CA’s own certificate and start the CA service. The Issuing CA is now operational as a subordinate CA. Alternatively, use PowerShell: certutil -installcert C:\CertRequest\issuingCA.cer This installs the cert and associates it with the pending key. Trust the Root CA certificate: Because the Issuing CA is domain-joined, when you install the subordinate cert, it might automatically place the Root CA’s certificate in the Trusted Root Certification Authorities store on that server (and possibly publish it to AD). If not, you should manually install the Root CA’s certificate into the Trusted Root CA store on the Issuing CA machine (using the Certificates MMC or certutil -addstore -f Root rootCA.cer). This step prevents any “chain not trusted” warnings on the Issuing CA and ensures it trusts its parent. In an enterprise environment, you would also distribute the root certificate to all client machines (e.g., via Group Policy) so that they trust the whole chain. Import Root CRL: Copy the Root CA’s CRL (*.crl file) to the Issuing CA’s CRL distribution point location (e.g., C:\Windows\System32\CertSrv\CertEnroll\ if that’s the directory served by the web server). This matches the HTTP URL we configured on the root. Place the CRL file there and ensure it is accessible (the Issuing CA’s IIS might need to serve static .crl files; often, if Web Enrollment is installed, the CertEnroll folder is under C:\Inetpub\wwwroot\CertEnroll). At this point, the subordinate CA and any client hitting the HTTP URL can retrieve the root’s CRL. The subordinate CA is now fully established. It holds a certificate issued by the Root CA (forming a complete chain of trust), and it’s ready to issue end-entity certificates. Step 6: Configure Issuing CA Settings and Start Services Start the Certificate Services: If the CA service (CertSvc) isn’t started automatically, start or restart it. On PowerShell: Restart-Service certsvc The CA should show as running in the CA console with the name “Contoso Issuing CA” (or your chosen name). Configure Certificate Templates: Because this is an Enterprise CA, it can utilize certificate templates stored in Active Directory to simplify issuing common cert types (user auth, computer auth, web server SSL, etc.). By default, some templates (e.g., User, Computer) are available but not issued. In the Certification Authority console under Certificate Templates, you can choose which templates to issue (e.g., right-click > New > Certificate Template to Issue, then select templates like “User” or “Computer”). This lab guide doesn’t require specific templates but know that only Enterprise CAs can use templates. Templates define the policies and settings (cryptography, enrollment permissions, etc.) for issued certificates. Ensure you enable only the templates needed and configure their permissions appropriately (e.g., allow the appropriate groups to enroll). Set CRL publishing schedule: The Issuing CA will automatically publish its own CRL (for certificates it issues) at intervals. You can adjust the CRL and Delta CRL publication interval in the CA’s Properties > CRL Period. A common practice is a small base CRL period (e.g., 1 week or 2 weeks) for issuing CAs, because they may revoke user certs more frequently; and enable Delta CRLs (published daily) for timely revocation information. Make sure the CDP/AIA for the Issuing CA itself are properly configured too (the wizard usually sets LDAP and HTTP locations, but verify in the Extensions tab). In a lab, the default settings are fine. Web Enrollment (if installed): You can verify the web enrollment by browsing to http://<IssuingCA>/certsrv. This web UI allows browser-based certificate requests. It’s a legacy interface mostly, but for testing it can be used if your clients aren’t domain-joined or if you want a manual request method. In modern use, the Certificate Enrollment Web Service/Policy roles or auto-enrollment via Group Policy are preferred for remote and automated enrollment. At this stage, your PKI is operational: the Issuing CA trusts the offline Root CA and can issue certificates. The Root CA can be kept offline with confidence that the subordinate will handle all regular work. Validation and Testing of the PKI It’s important to verify that the PKI is configured correctly: Check CA status: On the Issuing CA, open the Certification Authority console and ensure no errors. Verify that the Issuing CA’s certificate shows OK (no red X). On the Root CA (offline most of the time), you can use the Pkiview.msc snap-in (Microsoft PKI Health Tool) on a domain-connected machine to check the health of the PKI. This tool will show if the CDPs/AIA are reachable and if certificates are properly published. Trust chain on clients: On a domain-joined client PC, the Root CA certificate should be present in the Trusted Root Certification Authorities store (if the Issuing CA was installed as Enterprise CA, it likely published the root cert to AD automatically; you can also distribute it via Group Policy or manually). The Issuing CA’s certificate should appear in the Intermediate Certification Authorities store. This establishes the chain of trust. If not, import the root cert into the domain’s Group Policy for Trusted Roots. A quick test: on a client, run certutil -config "ISSUINGCA\\Contoso Issuing CA" -ping to see if it can contact the CA (or use the Certification Authority MMC targeting the issuing CA). Enroll a test certificate: Try to enroll for a certificate from the Issuing CA. For instance, from a domain-joined client, use the Certificates MMC (in Current User or Computer context) and initiate a certificate request for a User or Computer certificate (depending on templates issued). If auto-enrollment is configured via Group Policy for a template, you can simply log on a client and see if it automatically receives a certificate. Alternatively, use the web enrollment page or certreq command to submit a request. The request should be approved and a certificate issued by "Contoso Issuing CA". After enrollment, inspect the issued certificate: it should chain up to "Contoso Root CA" without errors. Ensure that the certificate’s CDP points to the URL we set (and try to browse that URL to see the CRL file), and that the AIA points to the root cert location. Revocation test (optional): To test CRL behavior, you could revoke a test certificate on the Issuing CA (using the CA console) and publish a new CRL. On the client, after updating the CRL, the revoked certificate should show as revoked. For the Root CA, since it shouldn’t issue end-entity certs, you wouldn’t normally revoke anything except potentially the subordinate CA’s certificate (which would be a drastic action in case of compromise). By issuing a test certificate and validating the chain and revocation, you confirm that your two-tier PKI lab is functioning correctly. Maintaining the PKI: CRLs, Key Ceremonies, and Security Procedures Deploying the PKI is only the beginning. Proper maintenance and operational procedures are crucial to ensure the PKI remains secure and reliable over time. Periodic CRL Updates for the Offline Root: The Root CA’s CRL has a defined validity period (set during configuration, often 6 or 12 months for offline roots). Before the CRL expires, the Root CA must be brought online (in a secure environment) to issue a new CRL. It’s recommended to schedule CRL updates periodically (e.g., semi-annually) to prevent the CRL from expiring. An expired CRL can cause certificate chain validation to fail, potentially disrupting services. Typically, organizations set the offline root CRL validity so that publishing 1-2 times a year is sufficient. When the time comes: Start the Root CA (ensuring the system clock is correct). Run certutil -crl to issue a fresh CRL. Distribute the new CRL: copy it to the HTTP CDP location (overwrite the old file) and, if applicable, use certutil -dspublish -f RootCA.crl to update it in Active Directory. Verify that the new CRL’s next update date is extended appropriately (e.g., another 6 months out). Clients and the Issuing CA will automatically pick up the new CRL when checking for revocation. (The Issuing CA, if configured, might cache the root CRL and need a restart or certutil -setreg ca\CRLFlags +CRLF_REVCHECK_IGNORE_OFFLINE tweak if the root CRL expires unexpectedly. Keeping the schedule prevents such issues.) Issuing CA CRL and OCSP: The Issuing CA’s CRLs are published automatically as it is online. Ensure the IIS or file share hosting the CRL is accessible. Optionally, consider setting up an Online Responder (OCSP) for real-time status checking, especially if CRLs are large or you need faster revocation information. OCSP is another AD CS role service that can be configured on the issuing CA or another server to answer certificate status queries. This might be beyond a simple lab, but it’s worth mentioning for completeness. Key Ceremonies and Documentation: For production environments (and good practice even in labs), formalize the process of handling CA keys in a Key Ceremony. A key ceremony is a carefully controlled process for activities like generating the Root CA’s key pair, installing the CA, and signing subordinate certificates. It often involves multiple people to ensure no single person has unilateral control (principle of dual control) and to witness the process. Best practices for a Root CA key ceremony include: Advance Planning: Create a step-by-step script of the ceremony tasks. Include who will do what, what materials are needed (HSMs, installation media, backup devices, etc.), and the order of operations. Multiple trusted individuals present: Roles might include a Ceremony Administrator (leads the process), a Security Officer (responsible for HSM or key material handling), an Auditor (to observe and record), etc. This prevents any one person from manipulating the process and increases trust. Secure environment: Conduct the ceremony in a secure location (e.g., a locked room) free of recording devices or unauthorized personnel. Ensure the Root CA machine is isolated (no network), and ideally that BIOS/USB access controls are in place to prevent any malware. Generate keys with proper controls: If using an HSM, initialize and generate the key with the required number of key custodians each providing part of the activation material (e.g., smartcards or passphrases). Immediately back up the HSM partition or key to secure media (requiring the same custodians to restore). Sign subordinate CA certificate: As part of the ceremony, once the root key is ready, sign the subordinate’s request. This might also be a witnessed step. Document every action: Write down each command run, each key generated, serial numbers of devices used, and have all participants sign an acknowledgment of the outcomes. Also record the fingerprints of the generated Root CA certificate and any subordinate certificate to ensure they are exactly as expected. Secure storage: After the ceremony, store the Root CA machine (if it’s a laptop or VM) and HSM tokens in a tamper-evident bag or safe. The idea is to make it evident if someone tries to access the root outside of an authorized ceremony. While a full key ceremony might be overkill for a small lab, understanding these practices is important. Even in a lab, you can simulate some aspects (for learning), like documenting the procedure of taking the root online to sign the request and then locking it away. These practices greatly increase the trust in a production PKI by ensuring transparency and accountability for critical operations. Backup and Recovery Plans: Both CAs’ data should be regularly backed up: For the Root CA: since it’s rarely online, backup after any change. Typically, you’d back up the CA’s private key and certificate once (right after setup or any renewal). Store this securely offline (separate from the server itself). Also back up the CA database if it ever issues more than one cert (for root it might not issue many). For the Issuing CA: schedule automated backups of the CA database and private key. You can use the built-in certutil -backup or Windows Server Backup (which is aware of the AD CS database). Keep backups secure and test restoration procedures. Having a documented recovery procedure for the CA is crucial for continuity. Also consider backup of templates and any scripts. Maintain spare hardware or VMs in case you need to restore the CA on new hardware (especially for the root, having a procedure to restore on a new machine if the original is destroyed). Security maintenance: Apply OS updates to the CAs carefully. For the offline root, patch it offline if possible (offline servicing or connecting it briefly to a management network). For the issuing CA, treat it as a critical infrastructure server: limit its exposure (firewall it so only required services are reachable), monitor its event logs (enable auditing for Certificate Services events, which can log each issuance and revocation), and employ anti-malware tools with caution (whitelisting the CA processes to avoid interference). Also, periodically review the CA’s configuration and certificate templates to ensure they meet current security standards (for example, deprecate any weak cryptography or adjust validity periods if needed). By following these maintenance steps and best practices, your two-tier PKI will remain secure and trustworthy over time. Remember that PKI is not “set and forget” – it requires operational diligence, but the payoff is a robust trust infrastructure for your organization’s security. Additional AD CS Features and References Active Directory Certificate Services provides more capabilities than covered in this basic lab. Depending on your needs, you might explore: Certificate Templates: We touched on templates; they are a powerful feature on Enterprise CAs to enforce standardized certificate settings. Administrators can create custom templates for various use cases (SSL, S/MIME email, code signing) and control enrollment permissions. Understanding template versions and permissions is key for enterprise deployments. (Refer to Microsoft’s documentation on Certificate template concepts in Windows Server for details on how templates work and can be customized.) Web Services for Enrollment: In scenarios with remote or non-domain clients, AD CS offers the Certificate Enrollment Web Service (CES) and Certificate Enrollment Policy Web Service (CEP) role services. These allow clients to fetch enrollment policy information and request certificates over HTTP or HTTPS, even when not connected directly to the domain. They work with the certificate templates to enable similar auto-enrollment experiences over the web. See Microsoft’s guides on the Certificate Enrollment Web Service overview and Certificate Enrollment Policy Web Service overview for when to use these. Network Device Enrollment Service (NDES): This AD CS role service implements the Simple Certificate Enrollment Protocol (SCEP) to allow devices like routers, switches, and mobile devices to obtain certificates from the CA without domain credentials. NDES acts as a proxy (Registration Authority) between devices and the CA, using one-time passwords for authentication. If you need to issue certificates to network equipment or MDM-managed mobile devices, NDES is the solution. Microsoft Docs provide a Network Device Enrollment Service(NDES) overview and even details on using a policy module with NDES for advanced scenarios (like customizing how requests are processed or integrating with custom policies). Online Responders (OCSP): As mentioned, an Online Responder can be configured to answer revocation status queries more efficiently than CRLs, especially useful if your CRLs grow large or you have high-volume certificate validation (VPNs, etc.). AD CS’s Online Responder role service can be installed on a member server and configured with the OCSP Response Signing certificate from your Issuing CA. Monitoring and Auditing: Windows Servers have options to audit CA events. Enabling auditing can log events such as certificate issuance, revocation, or changes to the CA configuration. These logs are important in enterprise PKI to track who did what (for compliance and security forensics). Also, tools like the PKI Health Tool (pkiview.msc) and PowerShell cmdlets (like Get-CertificationAuthority, Get-CertificationAuthorityCertificate) can help monitor the health and configuration of your CAs. Conclusion By following this guide, you have set up a secure two-tier PKI environment consisting of an offline Root CA and an online Issuing CA. This design, which uses an offline root, is considered a security best practice for enterprise PKI deployments because it reduces the risk of your root key being compromised. With the offline Root CA acting as a hardened trust anchor and the enterprise Issuing CA handling day-to-day certificate issuance, your lab PKI can issue certificates for various purposes (HTTPS, code signing, user authentication, etc.) in a way that models real-world deployments. As you expand this lab or move to production, always remember that PKI security is as much about process as technology. Applying strict controls to protect CA keys, keeping software up to date, and monitoring your PKI’s health are all part of the journey. For further reading and official guidance, refer to these Microsoft documentation resources: 📖 AD CS PKI Design Considerations: PKI design considerations using Active Directory Certificate Services in Windows Server helps in planning a PKI deployment (number of CAs, hierarchy depth, naming, key lengths, validity periods, etc.). This is useful to read when adapting this lab design to a production environment. It also covers configuring CDP/AIA and why offline roots usually don’t need delta CRLs. 📖 AD CS Step-by-Step Guides: Microsoft’s Test Lab Guide Test Lab Guide: Deploying an AD CS Two-Tier PKI Hierarchy walk through a similar scenario.Rethinking Data Security and Governance in the Era of AI
The era of AI is reshaping industries, enabling unprecedented innovations, and presenting new opportunities for organizations worldwide. But as organizations accelerate AI adoption, many are focused on a growing concern: their current data security and governance practices are not effectively built for the fast-paced AI innovation and ever-evolving regulatory landscape. At Microsoft, we recognize the critical need for an integrated approach to address these risks. In our latest findings, Top 3 Challenges in Securing and Governing Data for the Era of AI, we uncovered critical gaps in how organizations manage data risk. The findings exemplify the current challenges: 91% of leaders are not prepared to manage risks posed by AI 1 and 85% feel unprepared to comply with AI regulations 2 . These gaps not only increase non-compliance but also put innovation at risk. Microsoft Purview has the tools to tackle these challenges head on, helping organizations move to an approach that protects data, meets compliance regulations, and enables trusted AI transformation. We invite you to take this opportunity to evaluate your current practices, platforms, and responsibilities, and to understand how to best secure and govern your organization for growing data risks in the era of AI. Platform fragmentation continues to weaken security outcomes Organizations often rely on fragmented tools across security, compliance, and data teams, leading to a lack of unified visibility and insufficient data hygiene. Our findings reveal the effects of fragmented platforms, leading to duplicated data, inconsistent classification, redundant alerts, and siloed investigations, which ultimately is causing data exposure incidents related to AI to be on the rise 3 . Microsoft Purview offers centralized visibility across your organization’s data estate. This allows teams to break down silos, streamline workflows, and mitigate data leakage and oversharing. With Microsoft Purview, capabilities like data health management and data security posture management are designed to enhance collaboration and deliver enriched insights across your organization to help further protect your data and mitigate risks faster. Microsoft Purview offers the following: Unified insights across your data estate, breaking down silos between security, compliance, and data teams. Microsoft Purview Data Security Posture Management (DSPM) for AI helps organizations gain unified visibility into GenAI usage across users, data, and apps to address the heightened risk of sensitive data exposure from AI. Built-in capabilities like classification, labeling, data loss prevention, and insider risk insights in one platform. In addition, newly launched solutions like Microsoft Purview Data Security Investigations accelerate investigations with AI-powered deep content analysis, which helps data security teams quickly identify and mitigate sensitive data and security risks within impacted data. Organizations like Kern County historically relied on many fragmented systems but adopted Microsoft Purview to unify their organization’s approach to data protection in preparation for increasing risks associated with deploying GenAI. “We have reduced risk exposure, [Microsoft] Purview helped us go from reaction to readiness. We are catching issues proactively instead of retroactively scrambling to contain them.” – Aaron Nance, Deputy Chief Information Security Officer, Kern County Evolving regulations require continuous compliance AI-driven innovation is creating a surge in regulations, resulting in over 200 daily updates across more than 900 regulatory agencies 4 , as highlighted in our research. Compliance has become increasingly difficult, with organizations struggling to avoid fines and comply with varying requirements across regions. To navigate these challenges effectively, security leaders’ responsibilities are expanding to include oversight across governance and compliance, including oversight of traditional data catalog and governance solutions led by the central data office. Leaders also cite the need for regulation and audit readiness. Microsoft Purview enables compliance and governance by: Streamlining compliance with Microsoft Purview Compliance Manager templates, step-by-step guidance, and insights for region and industry-specific regulations, including GDPR, HIPAA, and AI-specific regulation like the EU AI Act. Supporting legal matters such as forensic and internal investigations with audit trail records in Microsoft Purview eDiscovery and Audit. Activating and governing data for trustworthy analytics and AI with Microsoft Purview Unified Catalog, which enables visibility across your data estate and data confidence via data quality, data lineage, and curation capabilities for federated governance. Microsoft Purview’s suite of capabilities provides visibility and accountability, enabling security leaders to meet stringent compliance demands while advancing AI initiatives with confidence. Organizations need a unified approach to secure and govern data Organizations are calling for an integrated platform to address data security, governance, and compliance collectively. Our research shows that 95% of leaders agree that unifying teams and tools is a top priority 5 and 90% plan to adopt a unified solution to mitigate data related risks and maximize impact 6 . Integration isn't just about convenience, it’s about enabling innovation with trusted data protection. Microsoft Purview enables a shared responsibility model, allowing individual business units to own their data while giving central teams oversight and policy control. As organizations adopt a unified platform approach, our findings reveal the upside potential not only being reduced risk but also cost savings. With AI-powered copilots such as Security Copilot in Microsoft Purview, data protection tasks are simplified with natural-language guidance, especially for under resourced teams. Accelerating AI transformation with Microsoft Purview Microsoft Purview helps security, compliance, and governance teams navigate the complexities of AI innovation while implementing effective data protection and governance strategies. Microsoft partner EY highlights the results they are seeing: “We are seeing 25%–30% time savings when we build secure features using [Microsoft] Purview SDK. What was once fragmented is now centralized. With [Microsoft] Purview, everything comes together on one platform, giving a unified foundation to innovate and move forward with confidence.” – Prashant Garg, Partner of Data and AI, EY We invite you to explore how you can propel your organization toward a more secure future by reading the full research paper at https://aka.ms/SecureAndGovernPaper. Visit our website to learn more about Microsoft Purview. 1 Forbes, Only 9% Of Surveyed Companies Are Ready To Manage Risks Posed By AI, 2023 2 SAP LeanIX, AI Survey Results, 2024 3 Microsoft, Data Security Index Report, 2024 4 Forbes, Cost of Compliance, Thomson Reuters, 2021 5 Microsoft, Audience Research, 2024 6 Microsoft, Customer Requirements Research, 2024
Announcing Public Preview of DLP for M365 Copilot in Word, Excel, and PowerPoint
Today, we are excited to announce the public preview of Data Loss Prevention (DLP) for M365 Copilot in Word, Excel, and PowerPoint. This development extends the capabilities you rely on for safeguarding data in M365 Copilot Chat, bringing DLP protections to everyday Copilot scenarios within these core productivity apps. Building on Our Foundation Data oversharing and leakage is a top concern for organizations using generative AI technology, and securing AI-based workflows can feel overwhelming. We’ve been laying a strong foundation with Microsoft Purview Data Loss Prevention—especially with DLP for M365 Copilot—and are excited to expand its reach to further reduce the risk of AI-related oversharing at scale. In the original public preview release, we enabled admins to configure DLP rules that block Copilot from processing or summarizing sensitive documents in M365 Copilot Chat. However, these controls didn’t extend to the powerful in-app Copilot experiences, such as rewriting text in Word, summarizing presentations in PowerPoint, or generating helpful formulas in Excel. That changes now with this public preview. The Next Phase of DLP for M365 Copilot Similar to our original approach for M365 Copilot Chat, we are bringing consistent, flexible protection to M365 Copilot for Word, Excel, and PowerPoint. Here’s how it works in this preview: Current file DLP checks: Copilot now respects sensitivity labels on an opened document or workbook. If a document has a sensitivity label and a DLP rule that excludes its content from Copilot processing, Copilot actions like summarizing or auto-generating content directly in the canvas are blocked. Chatting with Copilot is also unavailable. File reference DLP checks: When a user tries to reference other files in a prompt – like pulling data or slides from other labeled documents – Copilot checks DLP policies before retrieving the content. If there is a DLP policy configured to block Copilot processing of files with that file’s sensitivity label, Copilot will show an apology message rather than summarizing that content – so no accidental oversharing occurs. You can learn more about DLP for M365 Copilot here: Learn about the Microsoft 365 Copilot policy location (preview) Getting Started Enabling DLP for M365 Copilot in Word, Excel, and PowerPoint follows a setup similar to configuring DLP policies for other workloads. From the Purview compliance portal, you can configure the DLP policy for a specific sensitivity label at a file, group, site, and/or user level. If you have already enabled a DLP for M365 Copilot policy with the ongoing DLP for M65 Copilot Chat preview, no further action is needed – the policy will automatically begin to apply in Word, Excel, and PowerPoint Copilot experiences. In this preview, our focus is on ensuring reliability, performance, and seamless integration with the Office apps you use every day. We’ll continue to refine the user experience as we move toward general availability, including improvements to error messages and user guidance for each scenario. Join the Preview This public preview reflects our ongoing commitment to deliver robust data protection for AI-powered workflows. By extending the same DLP principles you trust to Word, Excel, and PowerPoint, we’re empowering you to embrace AI confidently without sacrificing control over your organization’s most valuable information. We invite you to start testing these capabilities in your environment. Your feedback is invaluable to us – we encourage all customers to share their experiences and insights, helping shape the next evolution of DLP for M365 Copilot in Office.Safely activate your data estate with Microsoft Purview
60% of CDOs cite data integration challenges as a top pain-point due to lack of knowledge of where relevant data resides [1]. Companies operate on multi-platform, multi-cloud data estates making it harder than ever to seamlessly discover, secure, govern and activate data. This increases the overall complexity when enabling users to responsibly derive insights and drive business value from data. In the era of AI, data governance is no longer an afterthought, data security and data governance are now both table stakes. Data Governance is not a new concept but with the proliferation of AI and evolving regulatory landscape, data governance is critical for safeguarding data related to AI-driven business innovation. With 95% of organizations implementing or developing an AI strategy [2], customers are facing emerging governance challenges, such as: False signals: The lack of clean accurate data can cause false signals in AI which can trigger consequential business outcomes or lead to incorrect reported forecasting and regulatory fines. Time to insight: Data scientists and analysts spend 60-80% of their time on data access and preparation to feed AI initiatives which leads to staff frustration, increased OPEX, and delays in critical AI innovation priorities. Shadow innovation: Data innovation outside governance can increase business risks around data leakage, oversharing, or inaccurate outcomes. This is why federated governance has surfaced as a top priority across security and data leaders because it unlocks data innovation while maintaining appropriate data oversight to help minimize risks. Customers are seeking more unified solutions that enable data security and governance seamlessly across their complex data estate. To help customers better respond to these needs, Microsoft Purview unifies data security, data governance, and data compliance solutions across the heterogeneous data estate for the era of AI. Microsoft Purview also works closely with Microsoft Fabric to integrate capabilities that help seamlessly secure and govern data to help reduce risks associated with data activation across the Microsoft Intelligent Data Platform and across the Microsoft Cloud portfolio. Microsoft Fabric delivers a pre-integrated and optimized SaaS environment for data teams to work faster together over secure and governed data within the Fabric environment. Combining the strengths of Microsoft Purview and Microsoft Fabric enables organizations to more confidently leverage Fabric to unlock data innovation across data engineers, analysts, data scientists, and developers whilst Purview enables data security teams to extend Purview advanced data security value and enables the central data office to extend Purview advanced data governance value across Fabric, Azure, M365, and the heterogenous data estate. Furthering this vision, today Microsoft is announcing 1. a new name for the Purview Data Governance solution, Purview Unified Catalog, to better reflect its growing catalog capabilities, 2. integration with new OneLake catalog, 3. a new data quality scan engine, 4. Purview Analytics in OneLake, and 5. expanded Data Loss Prevention (DLP) capabilities for Fabric lakehouse and semantic models. Introducing Unified Catalog: a new name for the visionary solution The Microsoft Purview data governance solution, made generally available in September, delivers comprehensive visibility, data confidence, and responsible innovation—for greater business value in the era of AI. The solution streamlines metadata from disparate catalogs and sources, like OneLake, Databricks Unity, and Snowflake Polaris, into a unified experience. To better reflect these comprehensive customer benefits, Microsoft Purview Data Catalog is being renamed to Microsoft Purview Unified Catalog to exemplify the growing catalog capabilities such as deeper data quality support for more cloud sources, and Purview Analytics in OneLake. A data catalog serves as a comprehensive inventory of an organization's data assets. As the Microsoft Purview Unified Catalog continues to add on capabilities within curation, data quality, and third-party platform integration, the new Unified Catalog name reflects the current cross-cloud capability. This cross-cloud capability is illustrated in the figure below. This data product contains data assets from multiple different sources, including a Fabric lakehouse table, Snowflake Table and Azure Databricks Table. With the proper curation of analytics into data products, data users can govern data assets easier than ever. Figure 1: Curation of a data product from disparate data sources within Purview’s Unified Catalog Introducing OneLake catalog (Preview) As announced in the Microsoft Fabric blog earlier today, the OneLake catalog is a solution purpose-built for data engineers, data scientists, developers, analysts, and data consumers to explore, manage, and govern data in Fabric. The new OneLake catalog works with Purview by seamlessly connecting data assets governed by OneLake catalog into Purview Unified Catalog, enabling the central data office to centrally govern and manage data assets. The Purview Unified Catalog offers data stewards and data owners advanced capabilities for data curation, advanced data quality, end-to-end data lineage, and an intuitive global catalog that spans the data estate. For data leaders, Unified Catalog offers built-in reports for actionable insights into data health and risks and the ability to confidently govern data across the heterogeneous data estate. In figure 2, you can see how Fabric data is seamlessly curated into the Corporate Emissions Created by AI for CY2024 Data Product, built with data assets from OneLake. Figure 2: Data product curated with Fabric assets Introducing a new data quality scan engine for deeper data quality (Preview) Purview offers deeper data quality support, through a new data quality scan engine for big data platforms, including: Microsoft Fabric, Databricks Unity Catalog, Snowflake, Google Big Query, and Amazon S3, supporting open standard file and table formats. In short, this new scan engine allows businesses to centrally perform rich data quality management from within the Purview Unified Catalog. In Figure 3, you can see how users can run different data quality rules on a particular asset, in this case, a table hosted in OneLake, and when users click on “run quality scan”, the scanner runs a deep scan on the data itself, running the data quality rules in real time, and updating the quality score for that particular asset. Figure 3: Running a data quality scan on an asset living in OneLake Introducing Purview Analytics in OneLake (Preview) To further an organization’s data quality management practice, data stewards can now leverage a new Purview Analytics in OneLake capability, in preview, to extract tenant-specific metadata from the Purview Unified Catalog and publish to OneLake. This new capability enables deeper data quality and lineage investigation using the rich capabilities in Power BI within Microsoft Fabric. Figure 4: In Unified Catalog settings, a user can add self-serve analytics to Microsoft Fabric Figure 5: Curated metadata from Purview within Fabric Expanded Data Loss Prevention (DLP) capabilities for Fabric lakehouse and semantic models To broaden Purview data security features for Fabric, today we are announcing that the restrict access action in Purview DLP policies now extends to Fabric semantic models. With the restrict access action, DLP admins can configure policies to detect sensitive information in semantic models and limit access to only internal users or data owners. This control is valuable for when a Fabric tenant includes guest users and you want to limit unnecessary access to internal proprietary data. The addition of the restrict access action for Fabric semantic models augments the existing ability to detect upload of sensitive data to Fabric lakehouses announced earlier this year. Learn more about the new Purview DLP capabilities for Fabric lakehouses and semantic models in the DLP blog. Figure 6: Example of restricted access to a Fabric semantic model enforced through a Purview DLP policy. Summary With these investments in security and governance, Microsoft Purview is delivering on its vision to extend data protection customer value and innovation across your heterogenous data estate for reduced complexities and improved risk mitigation. Together Purview and Fabric set the foundations for a modern intelligent data platform with seamless security and governance to drive AI innovation you can trust. Learn more As we continue to innovate our products to expand the security and governance capabilities, check out these resources to stay informed. https://aka.ms/Try-Purview-Governance https://www.microsoft.com/en-us/security/business/microsoft-purview https://aka.ms/try-fabric [1] Top 7 Challenges in Data Integration and How to Solve Them | by Codvo Marketing | Medium [2] Microsoft internal research May 2023, N=638Microsoft Security in Action: Zero Trust Deployment Essentials for Digital Security
The Zero Trust framework is widely regarded as a key security model and a commonly referenced standard in modern cybersecurity. Unlike legacy perimeter-based models, Zero Trust assumes that adversaries will sometimes get access to some assets in the organization, and you must build your security strategy, architecture, processes, and skills accordingly. Implementing this framework requires a deliberate approach to deployment, configuration, and integration of tools. What is Zero Trust? At its core, Zero Trust operates on three guiding principles: Assume Breach (Assume Compromise): Assume attackers can and will successfully attack anything (identity, network, device, app, infrastructure, etc.) and plan accordingly. Verify Explicitly: Protect assets against attacker control by explicitly validating that all trust and security decisions use all relevant available information and telemetry. Use Least Privileged Access: Limit access of a potentially compromised asset, typically with just-in-time and just-enough-access (JIT/JEA) and risk-based policies like adaptive access control. Implementing a Zero Trust architecture is essential for organizations to enhance security and mitigate risks. Microsoft's Zero Trust framework essentially focuses on six key technological pillars: Identity, Endpoints, Data, Applications, Infrastructure, & Networks. This blog provides a structured approach to deploying each pillar. 1. Identity: Secure Access Starts Here Ensure secure and authenticated access to resources by verifying and enforcing policies on all user and service identities. Here are some key deployment steps to get started: Implement Strong Authentication: Enforce Multi-Factor Authentication (MFA) for all users to add an extra layer of security. Adopt phishing-resistant methods, such as password less authentication with biometrics or hardware tokens, to reduce reliance on traditional passwords. Leverage Conditional Access Policies: Define policies that grant or deny access based on real-time risk assessments, user roles, and compliance requirements. Restrict access from non-compliant or unmanaged devices to protect sensitive resources. Monitor and Protect Identities: Use tools like Microsoft Entra ID Protection to detect and respond to identity-based threats. Regularly review and audit user access rights to ensure adherence to the principle of least privilege. Integrate threat signals from diverse security solutions to enhance detection and response capabilities. 2. Endpoints: Protect the Frontlines Endpoints are frequent attack targets. A robust endpoint strategy ensures secure, compliant devices across your ecosystem. Here are some key deployment steps to get started: Implement Device Enrollment: Deploy Microsoft Intune for comprehensive device management, including policy enforcement and compliance monitoring. Enable self-service registration for BYOD to maintain visibility. Enforce Device Compliance Policies: Set and enforce policies requiring devices to meet security standards, such as up-to-date antivirus software and OS patches. Block access from devices that do not comply with established security policies. Utilize and Integrate Endpoint Detection and Response (EDR): Deploy Microsoft Defender for Endpoint to detect, investigate, and respond to advanced threats on endpoints and integrate with Conditional Access. Enable automated remediation to quickly address identified issues. Apply Data Loss Prevention (DLP): Leverage DLP policies alongside Insider Risk Management (IRM) to restrict sensitive data movement, such as copying corporate data to external drives, and address potential insider threats with adaptive protection. 3. Data: Classify, Protect, and Govern Data security spans classification, access control, and lifecycle management. Here are some key deployment steps to get started: Classify and Label Data: Use Microsoft Purview Information Protection to discover and classify sensitive information based on predefined or custom policies. Apply sensitivity labels to data to dictate handling and protection requirements. Implement Data Loss Prevention (DLP): Configure DLP policies to prevent unauthorized sharing or transfer of sensitive data. Monitor and control data movement across endpoints, applications, and cloud services. Encrypt Data at Rest and in Transit: Ensure sensitive data is encrypted both when stored and during transmission. Use Microsoft Purview Information Protection for data security. 4. Applications: Manage and Secure Application Access Securing access to applications ensures that only authenticated and authorized users interact with enterprise resources. Here are some key deployment steps to get started: Implement Application Access Controls: Use Microsoft Entra ID to manage and secure access to applications, enforcing Conditional Access policies. Integrate SaaS and on-premises applications with Microsoft Entra ID for seamless authentication. Monitor Application Usage: Deploy Microsoft Defender for Cloud Apps to gain visibility into application usage and detect risky behaviors. Set up alerts for anomalous activities, such as unusual download patterns or access from unfamiliar locations. Ensure Application Compliance: Regularly assess applications for compliance with security policies and regulatory requirements. Implement measures such as Single Sign-On (SSO) and MFA for application access. 5. Infrastructure: Securing the Foundation It’s vital to protect the assets you have today providing business critical services your organization is creating each day. Cloud and on-premises infrastructure hosts crucial assets that are frequently targeted by attackers. Here are some key deployment steps to get started: Implement Security Baselines: Apply secure configurations to VMs, containers, and Azure services using Microsoft Defender for Cloud. Monitor and Protect Infrastructure: Deploy Microsoft Defender for Cloud to monitor infrastructure for vulnerabilities and threats. Segment workloads using Network Security Groups (NSGs). Enforce Least Privilege Access: Implement Just-In-Time (JIT) access and Privileged Identity Management (PIM). Just-in-time (JIT) mechanisms grant privileges on-demand when required. This technique helps by reducing the time exposure of privileges that are required for people, but are only rarely used. Regularly review access rights to align with current roles and responsibilities. 6. Networks: Safeguard Communication and Limit Lateral Movement Network segmentation and monitoring are critical to Zero Trust implementation. Here are some key deployment steps to get started: Implement Network Segmentation: Use Virtual Networks (VNets) and Network Security Groups (NSGs) to segment and control traffic flow. Secure Remote Access: Deploy Azure Virtual Network Gateway and Azure Bastion for secure remote access. Require device and user health verification for VPN access. Monitor Network Traffic: Use Microsoft Defender for Endpoint to analyze traffic and detect anomalies. Taking the First Step Toward Zero Trust Zero Trust isn’t just a security model—it’s a cultural shift. By implementing the six pillars comprehensively, organizations can potentially enhance their security posture while enabling seamless, secure access for users. Implementing Zero Trust can be complex and may require additional deployment approaches beyond those outlined here. Cybersecurity needs vary widely across organizations and deployment isn’t one-size-fits all, so these steps might not fully address your organization’s specific requirements. However, this guide is intended to provide a helpful starting point or checklist for planning your Zero Trust deployment. For a more detailed walkthrough and additional resources, visit Microsoft Zero Trust Implementation Guidance. The Microsoft Security in Action blog series is an evolving collection of posts that explores practical deployment strategies, real-world implementations, and best practices to help organizations secure their digital estate with Microsoft Security solutions. Stay tuned for our next blog on deploying and maximizing your investments in Microsoft Threat Protection solutions.
