Planning your move to Microsoft Defender portal for all Microsoft Sentinel customers
In November 2023, Microsoft announced our strategy to unify security operations by bringing the best of XDR and SIEM together. Our first step was bringing Microsoft Sentinel into the Microsoft Defender portal, giving teams a single, comprehensive view of incidents, reducing queue management, enriching threat intel, streamlining response and enabling SOC teams to take advantage of Gen AI in their day-to-day workflow. Since then, considerable progress has been made with thousands of customers using this new unified experience; to enhance the value customers gain when using Sentinel in the Defender portal, multi-tenancy and multi-workspace support was added to help customers with more sophisticated deployments. Our mission is to unify security operations by bringing all your data, workflows, and people together to unlock new capabilities and drive better security outcomes. As a strong example of this, last year we added extended posture management, delivering powerful posture insights to the SOC team. This integration helps build a closed-loop feedback system between your pre- and post-breach efforts. Exposure Management is just one example. By bringing everything together, we can take full advantage of AI and automation to shift from a reactive to predictive SOC that anticipates threats and proactively takes action to defend against them. Beyond Exposure Management, Microsoft has been constantly innovating in the Defender experience, adding not just SIEM but also Security Copilot. The Sentinel experience within the Defender portal is the focus of our innovation energy and where we will continue to add advanced Sentinel capabilities going forward. Onboarding to the new unified experience is easy and doesn’t require a typical migration. Just a few clicks and permissions. Customers can continue to use Sentinel in the Azure portal while it is available even after choosing to transition. Today, we’re announcing that we are moving to the next phase of the transition with a target to retire the Azure portal for Microsoft Sentinel by July 1, 2026. Customers not yet using the Defender portal should plan their transition accordingly. “Really amazing to see that coming, because cross querying with tables in one UI is really cool! Amazing, big step forward to the unified [Defender] portal.” Glueckkanja AG “The biggest benefit of a unified security operations solution (Microsoft Sentinel + Microsoft Defender XDR) has been the ability to combine data in Defender XDR with logs from third party security tools. Another advantage developed has been to eliminate the need to switch between Defender XDR and Microsoft Sentinel portals, now having a single pane of glass, which the team has been wanting for some years.” Robel Kidane, Group Information Security Manager, Renishaw PLC Delivering the SOC of the future Unifying threat protection, exposure management and security analytics capabilities in one pane of glass not only streamlines the user experience, but also enables Sentinel customers to realize security outcomes more efficiently: Analyst efficiency: A single portal reduces context switching, simplifies workflows, reduces training overhead, and improves team agility. Integrated insights: SOC-focused case management, threat intelligence, incident correlation, advanced hunting, exposure management, and a prioritized incident queue enriched with business and sensitivity context—enabling faster, more informed detection and response across all products. SOC optimization: Security controls that can be adjusted as threats and business priorities change to control costs and provide better coverage and utilization of data, thus maximizing ROI from the SIEM. Accelerated response: AI-driven detection and response which reduces mean time to respond (MTTR) by 30%, increases security response efficiency by 60%, and enables embedded Gen AI and agentic workflows. What’s next: Preparing for the retirement of the Sentinel Experience in the Azure Portal Microsoft is committed to supporting every single customer in making that transition over the next 12 months. Beginning July 1, 2026, Sentinel users will be automatically redirected to the Defender portal. After helping thousands of customers smoothly make the transition, we recommend that security teams begin planning their migration and change management now to ensure continuity and avoid disruption. While the technical process is very straightforward, we have found that early preparation allows time for workflow validation, training, and process alignment to take full advantage of the new capabilities and experience. Tips for a Successful Migration to Microsoft Defender 1. Leverage Microsoft’s help: Leverage Microsoft documentation, instructional videos, guidance, and in-product support to help you be successful. A good starting point is the documentation on Microsoft Learn. 2. Plan early: Engage stakeholders early including SOC and IT Security leads, MSSPs, and compliance teams to align on timing, training and organizational needs. Make sure you have an actionable timeline and agreement in the organization around when you can prioritize this transition to ensure access to the full potential of the new experience. 3. Prepare your environment: Plan and design your environment thoroughly. This includes understanding the prerequisites for onboarding Microsoft Sentinel workspaces, reviewing and deciding on access controls, and planning the architecture of your tenant and workspace. Proper planning will ensure a smooth transition and help avoid any disruptions to your security operations. 4. Leverage Advanced Threat Detection: The Defender portal offers enhanced threat detection capabilities with advanced AI and machine learning for Microsoft Sentinel. Make sure to leverage these features for faster and more accurate threat detection and response. This will help you identify and address critical threats promptly, improving your overall security posture. 5. Utilize Unified Hunting and Incident Management: Take advantage of the enhanced hunting, incident, and investigation capabilities in Microsoft Defender. This provides a comprehensive view for more efficient threat detection and response. By consolidating all security incidents, alerts, and investigations into a single unified interface, you can streamline your operations and improve efficiency. 6. Optimize Cost and Data Management The Defender portal offers cost and data optimization features, such as SOC Optimization and Summary Rules. Make sure to utilize these features to optimize your data management, reduce costs, and increase coverage and SIEM ROI. This will help you manage your security operations more effectively and efficiently. Unleash the full potential of your Security team The unified SecOps experience available in the Defender portal is designed to support the evolving needs of modern SOCs. The Defender portal is not just a new home for Microsoft Sentinel - it’s a foundation for integrated, AI-driven security operations. We’re committed to helping you make this transition smoothly and confidently. If you haven’t already joined the thousands of security organizations that have done so, now is the time to begin. Resources AI-Powered Security Operations Platform | Microsoft Security Microsoft Sentinel in the Microsoft Defender portal | Microsoft Learn Shifting your Microsoft Sentinel Environment to the Defender Portal | Microsoft Learn Microsoft Sentinel is now in Defender | YouTubeMicrosoft Sentinel’s New Data Lake: Cut Costs & Boost Threat Detection
Microsoft Sentinel is leveling up! Already a trusted cloud-native Security Information and Event Management (SIEM) and Security Orchestration, Automation and Response (SOAR) solution, it empowers security teams to detect, investigate, and respond to threats with speed and precision. Now, with the introduction of its new Data Lake architecture, Sentinel is transforming how security data is stored, accessed, and analyzed, bringing unmatched flexibility and scale to threat investigation. Unlike Microsoft Fabric OneLake, which supports analytics across the organization, Sentinel’s Data Lake is purpose-built for security. It centralizes raw structured, semi-structured, and unstructured data in its original format, enabling advanced analytics without rigid schemas. This article is written by someone who’s spent years helping security teams navigate Microsoft’s evolving ecosystem, translating complex capabilities into practical strategies. What follows is a hands-on look at the key features, benefits, and challenges of Sentinel’s Data Lake, designed to help you make the most of this powerful new architecture. Current Sentinel Features To tackle the challenges security teams, face today—like explosive data growth, integration of varied sources, and tight compliance requirements—organizations need scalable, efficient architectures. Legacy SIEMs often become costly and slow when analyzing multi-year data or correlating diverse events. Security data lakes address these issues by enabling seamless ingestion of logs from any source, schema-on-read flexibility, and parallelized queries over massive datasets. This schema-on-read allows SOC analysts to define how data is interpreted at the time of analysis, rather than when it is stored. This means analysts can flexibly adapt queries and threat detection logic to evolving threats, without reformatting historical data making investigations more agile and responsive to change. This empowers security operations to conduct deep historical analysis, automate enrichment, and apply advanced analytics, such as machine learning, while retaining strict control over data access and residency. Ultimately, decoupling storage and compute allows teams to boost detection and response speed, maintain compliance, and adapt their Security Operation Center (SOC) to future security demands. As organizations manage increasing data and limited budgets, many are moving from legacy SIEMs to advanced cloud-native options. Microsoft Sentinel’s Data Lake separates storage from computing, offering scalable and cost-effective analytics and compliance. For instance, storing 500 TB of logs in Sentinel Data Lake can cut costs by 60–80% compared to Log Analytics, due to lower storage costs and flexible retention. Integration with modern tools and open formats enables efficient threat response and regulatory compliance. Microsoft Sentinel data lake pricing (preview) Sentinel Data Lake Use Cases Log Retention: Long-term retention of security logs for compliance and forensic investigations Hunting: Advanced threat hunting using historical data Interoperability: Integration with Microsoft Fabric and other analytics platforms Cost: Efficient storage prices for high-volume data sources How Microsoft Sentinel Data Lake Helps Microsoft Sentinel’s Data Lake introduces a powerful paradigm shift for security operations by architecting the separation of storage and compute, enabling organizations to achieve petabyte-scale data retention without the traditional overhead and cost penalties of legacy SIEM solutions. Built atop highly scalable, cloud-native infrastructure, Sentinel Data Lake empowers SOCs to ingest telemetry from virtually unlimited sources ranging from on-premises firewalls, proxies, and endpoint logs to SaaS, IaaS, and PaaS environments—while leveraging schema-on-read, a method that allows analysts to define how data is interpreted at query time rather than when it is stored, offering greater flexibility in analytics. For example, a security analyst can adapt to the way historical data is examined as new threats emerge, without needing to reformat or restructure the data stored in the Data Lake. From Microsoft Learn – Retention and data tiering Storing raw security logs in open formats like Parquet (this is a columnar storage file format optimized for efficient data compression and retrieval, commonly used in big data processing frameworks like Apache Spark and Hadoop) enables easy integration with analytics tools and Microsoft Fabric, letting analysts efficiently query historical data using KQL, SQL, or Spark. This approach eliminates the need for complex ETL and archived data rehydration, making incident response faster; for instance, a SOC analyst can quickly search for years of firewall logs for threat detection. From Microsoft Learn – Flexible querying with Kusto Query Language Granular data governance and access controls allow organizations to manage sensitive information and meet legal requirements. Storing raw security logs in open formats enables fast investigations of long-term data incidents, while automated lifecycle management reduces costs and ensures compliance. Data Lakes integrate with Microsoft platforms and other tools for unified analytics and security. Machine learning helps detect unusual login activity across years, overcoming previous storage issues. From Microsoft Learn – Powerful analytics using Jupyter notebooks Pros and Cons The following table highlights the advantages and potential opportunities that Microsoft Sentinel Data Lake offers. This follows the same Pay-As-You-Go pricing model as currently available with Sentinel. Pros Cons License Needed Scalable, cost-effective long-term retention of security data Requires adaptation to new architecture Pay-As-You-Go model Seamless integration with Microsoft Fabric and open data formats Initial setup and integration may involve a learning curve Pay-As-You-Go model Efficient processing of petabyte-scale datasets Transitioning existing workflows may require planning Pay-As-You-Go model Advanced analytics, threat hunting, and AI/ML across historical data Some features may depend on integration with other services Pay-As-You-Go model Supports compliance use cases with robust data governance and audit trails Complexity in new data governance features Pay-As-You-Go model Microsoft Sentinel Data Lake solution advances cloud-native security by overcoming traditional SIEM limitations, allowing organizations to better retain, analyze, and respond to security data. As cyber threats grow, Sentinel Data Lake offers flexible, cost-efficient storage for long-term retention, supporting detection, compliance, and audits without significant expense or complexity. Quick Guide: Deploy Microsoft Sentinel Data Lake Assess Needs: Identify your security data volume, retention, and compliance requirements - Sentinel Data Lake Overview. Prepare Environment: Ensure Azure permissions and workspace readiness - Onboarding Guide. Enable Data Lake: Use Azure CLI or Defender portal to activate - Setup Instructions. Ingest & Import Data: Connect sources and migrate historical logs - Microsoft Sentinel Data Connectors. Integrate Analytics: Use KQL, notebooks, and Microsoft Fabric for scalable analysis - Fabric Overview Train & Optimize: Educate your team and monitor performance - Best Practices. About the Author: Hi! Jacques “Jack” here, I’m a Microsoft Technical Trainer at Microsoft. I wanted to share this as it’s something I often asked during my Security Trainings. This improves the already impressive Microsoft Sentinel feature stack helping the Defender Community to secure their environment in this ever-growing hacked world. I’ve been working with Microsoft Sentinel since September 2019, and I have been teaching learners about this SIEM since March 2020. I have experience using Security Copilot and Security AI Agents, which have been effective in improving my incident response and compromise recovery times.Hacking Made Easy, Patching Made Optional: A Modern Cyber Tragedy
In today’s cyber threat landscape, the tools and techniques required to compromise enterprise environments are no longer confined to highly skilled adversaries or state-sponsored actors. While artificial intelligence is increasingly being used to enhance the sophistication of attacks, the majority of breaches still rely on simple, publicly accessible tools and well-established social engineering tactics. Another major issue is the persistent failure of enterprises to patch common vulnerabilities in a timely manner—despite the availability of fixes and public warnings. This negligence continues to be a key enabler of large-scale breaches, as demonstrated in several recent incidents. The Rise of AI-Enhanced Attacks Attackers are now leveraging AI to increase the credibility and effectiveness of their campaigns. One notable example is the use of deepfake technology—synthetic media generated using AI—to impersonate individuals in video or voice calls. North Korean threat actors, for instance, have been observed using deepfake videos and AI-generated personas to conduct fraudulent job interviews with HR departments at Western technology companies. These scams are designed to gain insider access to corporate systems or to exfiltrate sensitive intellectual property under the guise of legitimate employment. Social Engineering: Still the Most Effective Entry Point And yet, many recent breaches have begun with classic social engineering techniques. In the cases of Coinbase and Marks & Spencer, attackers impersonated employees through phishing or fraudulent communications. Once they had gathered sufficient personal information, they contacted support desks or mobile carriers, convincingly posing as the victims to request password resets or SIM swaps. This impersonation enabled attackers to bypass authentication controls and gain initial access to sensitive systems, which they then leveraged to escalate privileges and move laterally within the network. Threat groups such as Scattered Spider have demonstrated mastery of these techniques, often combining phishing with SIM swap attacks and MFA bypass to infiltrate telecom and cloud infrastructure. Similarly, Solt Thypoon (formerly DEV-0343), linked to North Korean operations, has used AI-generated personas and deepfake content to conduct fraudulent job interviews—gaining insider access under the guise of legitimate employment. These examples underscore the evolving sophistication of social engineering and the need for robust identity verification protocols. Built for Defense, Used for Breach Despite the emergence of AI-driven threats, many of the most successful attacks continue to rely on simple, freely available tools that require minimal technical expertise. These tools are widely used by security professionals for legitimate purposes such as penetration testing, red teaming, and vulnerability assessments. However, they are also routinely abused by attackers to compromise systems Case studies for tools like Nmap, Metasploit, Mimikatz, BloodHound, Cobalt Strike, etc. The dual-use nature of these tools underscores the importance of not only detecting their presence but also understanding the context in which they are being used. From CVE to Compromise While social engineering remains a common entry point, many breaches are ultimately enabled by known vulnerabilities that remain unpatched for extended periods. For example, the MOVEit Transfer vulnerability (CVE-2023-34362) was exploited by the Cl0p ransomware group to compromise hundreds of organizations, despite a patch being available. Similarly, the OpenMetadata vulnerability (CVE-2024-28255, CVE-2024-28847) allowed attackers to gain access to Kubernetes workloads and leverage them for cryptomining activity days after a fix had been issued. Advanced persistent threat groups such as APT29 (also known as Cozy Bear) have historically exploited unpatched systems to maintain long-term access and conduct stealthy operations. Their use of credential harvesting tools like Mimikatz and lateral movement frameworks such as Cobalt Strike highlights the critical importance of timely patch management—not just for ransomware defense, but also for countering nation-state actors. Recommendations To reduce the risk of enterprise breaches stemming from tool misuse, social engineering, and unpatched vulnerabilities, organizations should adopt the following practices: 1. Patch Promptly and Systematically Ensure that software updates and security patches are applied in a timely and consistent manner. This involves automating patch management processes to reduce human error and delay, while prioritizing vulnerabilities based on their exploitability and exposure. Microsoft Intune can be used to enforce update policies across devices, while Windows Autopatch simplifies the deployment of updates for Windows and Microsoft 365 applications. To identify and rank vulnerabilities, Microsoft Defender Vulnerability Management offers risk-based insights that help focus remediation efforts where they matter most. 2. Implement Multi-Factor Authentication (MFA) To mitigate credential-based attacks, MFA should be enforced across all user accounts. Conditional access policies should be configured to adapt authentication requirements based on contextual risk factors such as user behavior, device health, and location. Microsoft Entra Conditional Access allows for dynamic policy enforcement, while Microsoft Entra ID Protection identifies and responds to risky sign-ins. Organizations should also adopt phishing-resistant MFA methods, including FIDO2 security keys and certificate-based authentication, to further reduce exposure. 3. Identity Protection Access Reviews and Least Privilege Enforcement Conducting regular access reviews ensures that users retain only the permissions necessary for their roles. Applying least privilege principles and adopting Microsoft Zero Trust Architecture limits the potential for lateral movement in the event of a compromise. Microsoft Entra Access Reviews automates these processes, while Privileged Identity Management (PIM) provides just-in-time access and approval workflows for elevated roles. Just-in-Time Access and Risk-Based Controls Standing privileges should be minimized to reduce the attack surface. Risk-based conditional access policies can block high-risk sign-ins and enforce additional verification steps. Microsoft Entra ID Protection identifies risky behaviors and applies automated controls, while Conditional Access ensures access decisions are based on real-time risk assessments to block or challenge high-risk authentication attempts. Password Hygiene and Secure Authentication Promoting strong password practices and transitioning to passwordless authentication enhances security and user experience. Microsoft Authenticator supports multi-factor and passwordless sign-ins, while Windows Hello for Business enables biometric authentication using secure hardware-backed credentials. 4. Deploy SIEM and XDR for Detection and Response A robust detection and response capability is vital for identifying and mitigating threats across endpoints, identities, and cloud environments. Microsoft Sentinel serves as a cloud-native SIEM that aggregates and analyses security data, while Microsoft Defender XDR integrates signals from multiple sources to provide a unified view of threats and automate response actions. 5. Map and Harden Attack Paths Organizations should regularly assess their environments for attack paths such as privilege escalation and lateral movement. Tools like Microsoft Defender for Identity help uncover Lateral Movement Paths, while Microsoft Identity Threat Detection and Response (ITDR) integrates identity signals with threat intelligence to automate response. These capabilities are accessible via the Microsoft Defender portal, which includes an attack path analysis feature for prioritizing multicloud risks. 6. Stay Current with Threat Actor TTPs Monitor the evolving tactics, techniques, and procedures (TTPs) employed by sophisticated threat actors. Understanding these behaviours enables organizations to anticipate attacks and strengthen defenses proactively. Microsoft Defender Threat Intelligence provides detailed profiles of threat actors and maps their activities to the MITRE ATT&CK framework. Complementing this, Microsoft Sentinel allows security teams to hunt for these TTPs across enterprise telemetry and correlate signals to detect emerging threats. 7. Build Organizational Awareness Organizations should train staff to identify phishing, impersonation, and deepfake threats. Simulated attacks help improve response readiness and reduce human error. Use Attack Simulation Training, in Microsoft Defender for Office 365 to run realistic phishing scenarios and assess user vulnerability. Additionally, educate users about consent phishing, where attackers trick individuals into granting access to malicious apps. Conclusion The democratization of offensive security tooling, combined with the persistent failure to patch known vulnerabilities, has significantly lowered the barrier to entry for cyber attackers. Organizations must recognize that the tools used against them are often the same ones available to their own security teams. The key to resilience lies not in avoiding these tools, but in mastering them—using them to simulate attacks, identify weaknesses, and build a proactive defense. Cybersecurity is no longer a matter of if, but when. The question is: will you detect the attacker before they achieve their objective? Will you be able to stop them before reaching your most sensitive data? Additional read: Gartner Predicts 30% of Enterprises Will Consider Identity Verification and Authentication Solutions Unreliable in Isolation Due to AI-Generated Deepfakes by 2026 Cyber security breaches survey 2025 - GOV.UK Jasper Sleet: North Korean remote IT workers’ evolving tactics to infiltrate organizations | Microsoft Security Blog MOVEit Transfer vulnerability Solt Thypoon Scattered Spider SIM swaps Attackers exploiting new critical OpenMetadata vulnerabilities on Kubernetes clusters | Microsoft Security Blog Microsoft Defender Vulnerability Management - Microsoft Defender Vulnerability Management | Microsoft Learn Zero Trust Architecture | NIST tactics, techniques, and procedures (TTP) - Glossary | CSRC https://learn.microsoft.com/en-us/security/zero-trust/deploy/overviewEnterprise-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-sdlcUnderstanding 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.Enhance AI security and governance across multi-model and multi-cloud environments
Generative AI adoption is accelerating, with AI transformation happening in real-time across various industries. This rapid adoption is reshaping how organizations operate and innovate, but it also introduces new challenges that require careful attention. At Ignite last fall, we announced several new capabilities to help organizations secure their AI transformation. These capabilities were designed to address top customer priorities such as preventing data oversharing, safeguarding custom AI, and preparing for emerging AI regulations. Organizations like Cummins, KPMG, and Mia Labs have leveraged these capabilities to confidently strengthen their AI security and governance efforts. However, despite these advancements, challenges persist. One major concern is the rise of shadow AI—applications used without IT or security oversight. In fact, 78% of AI users report bringing their own AI tools, such as ChatGPT and DeepSeek, into the workplace 1 . Additionally, new threats, like indirect prompt injection attacks, are emerging, with 77% of organizations expressing concerns and 11% of organizations identifying them as a critical risk 2 . To address these challenges, we are excited to announce new features and capabilities that help customers do the following: Prevent risky access and data leakage in shadow AI with granular access controls and inline data security capabilities Manage AI security posture across multi-cloud and multi-model environments Detect and respond to new AI threats, such as indirect prompt injections and wallet abuse Secure and govern data in Microsoft 365 Copilot and beyond In this blog, we’ll explore these announcements and demonstrate how they help organizations navigate AI adoption with confidence, mitigating risks, and unlocking AI’s full potential on their transformation journey. Prevent risky access and data leakage in shadow AI With the rapid rise of generative AI, organizations are increasingly encountering unauthorized employee use of AI applications without IT or security team approval. This unsanctioned and unprotected usage has given rise to “shadow AI,” significantly heightening the risk of sensitive data exposure. Today, we are introducing a set of access and data security controls designed to support a defense-in-depth strategy, helping you mitigate risks and prevent data leakage in third-party AI applications. Real-time access controls to shadow AI The first line of defense against security risks in AI applications is controlling access. While security teams can use endpoint controls to block access for all users across the organization, this approach is often too restrictive and impractical. Instead, they need more granular controls at the user level to manage access to SaaS-based AI applications. Today we are announcing the general availability of the AI web category filter in Microsoft Entra Internet Access to help enforce access controls that govern which users and groups have access to different AI applications. Internet Access deep integration with Microsoft Entra ID extends Conditional Access to any AI application, enabling organizations to apply AI access policies with granularity. By using Conditional Access as the policy control engine, organizations can enforce policies based on user roles, locations, device compliance, user risk levels, and other conditions, ensuring secure and adaptive access to AI applications. For example, with Internet Access, organizations can allow your strategy team to experiment with all or most consumer AI apps while blocking those apps for highly privileged roles, such as accounts payable or IT infrastructure admins. For even greater security, organizations can further restrict access to all AI applications if Microsoft Entra detects elevated identity risk. Inline discovery and protection of sensitive data Once users gain access to sanctioned AI applications, security teams still need to ensure that sensitive data isn’t shared with those applications. Microsoft Purview provides data security capabilities to prevent users from sending sensitive data to AI applications. Today, we are announcing enhanced Purview data security capabilities for the browser available in preview in the coming weeks. The new inline discovery & protection controls within Microsoft Edge for Business detect and block sensitive data from being sent to AI apps in real-time, even if typed directly. This prevents sensitive data leaks as users interact with consumer AI applications, starting with ChatGPT, Google Gemini, and DeepSeek. For example, if an employee attempts to type sensitive details about an upcoming merger or acquisition into Google Gemini to generate a written summary, the new inline protection controls in Microsoft Purview will block the prompt from being submitted, effectively blocking the potential leaks of confidential data to an unsanctioned AI app. This augments existing DLP controls for Edge for Business, including protections that prevent file uploads and the pasting of sensitive content into AI applications. Since inline protection is built natively into Edge for Business, newly deployed policies automatically take effect in the browser even if endpoint DLP is not deployed to the device. : Inline DLP in Edge for Business prevents sensitive data from being submitted to consumer AI applications like Google Gemini by blocking the action. The new inline protection controls are integrated with Adaptive Protection to dynamically enforce different levels of DLP policies based on the risk level of the user interacting with the AI application. For example, admins can block low-risk users from submitting prompts containing the highest-sensitivity classifiers for their organization, such as M&A-related data or intellectual property, while blocking prompts containing any sensitive information type (SIT) for elevated-risk users. Learn more about inline discovery & protection in the Edge for Business browser in this blog. In addition to the new capabilities within Edge for Business, today we are also introducing Purview data security capabilities for the network layer available in preview starting in early May. Enabled through integrations with Netskope and iboss to start, organizations will be able to extend inline discovery of sensitive data to interactions between managed devices and untrusted AI sites. By integrating Purview DLP with their SASE solution (e.g. Netskope and iBoss), data security admins can gain visibility into the use of sensitive data on the network as users interact with AI applications. These interactions can originate from desktop applications such as the ChatGPT desktop app or Microsoft Word with a ChatGPT plugin installed, or non-Microsoft browsers such as Opera and Brave that are accessing AI sites. Using Purview Data Security Posture Management (DSPM) for AI, admins will also have visibility into how these interactions contribute to organizational risk and can take action through DSPM for AI policy recommendations. For example, if there is a high volume of prompts containing sensitive data sent to ChatGPT, DSPM for AI will detect and recommend a new DLP policy to help mitigate this risk. Learn more about inline discovery for the network, including Purview integrations with Netskope and iBoss, in this blog. Manage AI security posture across multi-cloud and multi-model environments In today’s rapidly evolving AI landscape, developers frequently leverage multiple cloud providers to optimize cost, performance, and availability. Different AI models excel at various tasks, leading developers to deploy models from various providers for different use cases. Consequently, managing security posture across multi-cloud and multi-model environments has become essential. Today, Microsoft Defender for Cloud supports deployed AI workloads across Azure OpenAI Service, Azure Machine Learning, and Amazon Bedrock. To further enhance our security coverage, we are expanding AI Security Posture Management (AI-SPM) in Defender for Cloud to improve compatibility with additional cloud service providers and models. This includes: Support for Google Vertex AI models Enhanced support for Azure AI Foundry model catalog and custom models With this expansion, AI-SPM in Defender for Cloud will now offer the discovery of the AI inventory and vulnerabilities, attack path analysis, and recommended actions to address risks in Google VertexAI workloads. Additionally, it will support all models in Azure AI Foundry model catalog, including Meta Llama, Mistral, DeepSeek, as well as custom models. This expansion ensures a consistent and unified approach to managing AI security risks across multi-model and multi-cloud environments. Support for Google Vertex AI models will be available in public preview starting May 1, while support for Azure AI Foundry model catalog and custom models is generally available today. Learn More. 2: Microsoft Defender for Cloud detects an attack path to a DeepSeek R1 workload. In addition, Defender for Cloud will also offer a new data and AI security dashboard. Security teams will have access to an intuitive overview of their datastores and AI services across their multi-cloud environment, top recommendations, and critical attack paths to prioritize and accelerate remediation. The dashboard will be generally available on May 1. The new data & AI security dashboard in Microsoft Defender for Cloud provides a comprehensive overview of your data and AI security posture. These new capabilities reflect Microsoft’s commitment to helping organizations address the most critical security challenges in managing AI security posture in their heterogeneous environments. Detect and respond to new AI threats Organizations are integrating generative AI into their workflows and facing new security risks unique to AI. Detecting and responding to these evolving threats is critical to maintaining a secure AI environment. The Open Web Application Security Project (OWASP) provides a trusted framework for identifying and mitigating such vulnerabilities, such as prompt injection and sensitive information disclosure. Today, we are announcing Threat protection for AI services, a new capability that enhances threat protection in Defender for Cloud, enabling organizations to secure custom AI applications by detecting and responding to emerging AI threats more effectively. Building on the OWASP Top 10 risks for LLM applications, this capability addresses those critical vulnerabilities highlighted on the top 10 list, such as prompt injections and sensitive information disclosure. Threat protection for AI services helps organizations identify and mitigate threats to their custom AI applications using anomaly detection and AI-powered insights. With this announcement, Defender for Cloud will now extend its threat protection for AI workloads, providing a rich suite of new and enriched detections for Azure OpenAI Service and models in the Azure AI Foundry model catalog. New detections include direct and indirect prompt injections, novel attack techniques like ASCII smuggling, malicious URL in user prompts and AI responses, wallet abuse, suspicious access to AI resources, and more. Security teams can leverage evidence-based security alerts to enhance investigation and response actions through integration with Microsoft Defender XDR. For example, in Microsoft Defender XDR, a SOC analyst can detect and respond to a wallet abuse attack, where an attacker exploits an AI system to overload resources and increase costs. The analyst gains detailed visibility into the attack, including the affected application, user-entered prompts, IP address, and other suspicious activities performed by the bad actor. With this information, the SOC analyst can take action and block the attacker from accessing the AI application, preventing further risks. This capability will be generally available on May 1. Learn More. : Security teams can investigate new detections of AI threats in Defender XDR. Secure and govern data in Microsoft 365 Copilot and beyond Data oversharing and non-compliant AI use are significant concerns when it comes to securing and governing data in Microsoft Copilots. Today, we are announcing new data security and compliance capabilities. New data oversharing insights for unclassified data available in Microsoft Purview DSPM for AI: Today, we are announcing the public preview of on-demand classification for SharePoint and OneDrive. This new capability gives data security admins visibility into unclassified data stored in SharePoint and OneDrive and enables them to classify that data on demand. This helps ensure that Microsoft 365 Copilot is indexing and referencing files in its responses that have been properly classified. Previously, unclassified and unscanned files did not appear in DSPM for AI oversharing assessments. Now admins can initiate an on-demand data classification scan, directly from the oversharing assessment, ensuring that older or previously unscanned files are identified, classified, and incorporated into the reports. This allows organizations to detect and address potential risks more comprehensively. For example, an admin can initiate a scan of legacy customer contracts stored in a specified SharePoint library to detect and classify sensitive information such as account numbers or contact information. If these newly classified documents match the classifiers included in any existing auto-labeling policies, they will be automatically labeled. This helps ensure that documents containing sensitive information remain protected when they are referenced in Microsoft 365 Copilot interactions. Learn More. Security teams can trigger on-demand classification scan results in the oversharing assessment in Purview DSPM for AI. Secure and govern data in Security Copilot and Copilot in Fabric: We are excited to announce the public preview of Purview for Security Copilot and Copilot in Fabric, starting with Copilot in Power BI, offering DSPM for AI, Insider Risk Management, and data compliance controls, including eDiscovery, Audit, Data Lifecycle Management, and Communication Compliance. These capabilities will help organizations enhance data security posture, manage compliance, and mitigate risks more effectively. For example, admins can now use DSPM for AI to discover sensitive data in user prompts and responses and detect unethical or risky AI usage. Purview’s DSPM for AI provides admins with comprehensive reports on user activities and data interactions in Copilot for Power BI, as part of the Copilot in Fabric experience, and Security Copilot. DSPM Discoverability for Communication Compliance: This new feature in Communication Compliance, which will be available in public preview starting May 1, enables organizations to quickly create policies that detect inappropriate messages that could lead to data compliance risks. The new recommendation card on the DSPM for AI page offers a one-click policy creation in Microsoft Purview Communication Compliance, simplifying the detection and mitigation of potential threats, such as regulatory violations or improperly shared sensitive information. With these enhanced capabilities for securing and governing data in Microsoft 365 Copilot and beyond, organizations can confidently embrace AI innovation while maintaining strict security and compliance standards. Explore additional resources As organizations embrace AI, securing and governing its use is more important than ever. Staying informed and equipped with the right tools is key to navigating its challenges. Explore these resources to see how Microsoft Security can help you confidently adopt AI in your organization. Learn more about Security for AI solutions on our webpage Get started with Microsoft Purview Get started with Microsoft Defender for Cloud Sign up for a free Microsoft 365 E5 Security Trial and Microsoft Purview Trial Learn more about the innovations designed to help your organization protect data, defend against cyber threats, and stay compliant. Join Microsoft leaders online at Microsoft Secure on April 9. [1] 2024 Work Trend Index Annual Report, Microsoft and LinkedIn, May 2024, N=31,000. [2] Gartner®, Gartner Peer Community Poll – If your org’s using any virtual assistants with AI capabilities, are you concerned about indirect prompt injection attacks? GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.Microsoft Defender for Cloud Apps - Ninja Training
Welcome to our Ninja Training for Microsoft Defender for Cloud Apps! Are you trying to protect your SaaS applications? Are you concerned about the posture of the apps you are using? Is shadow IT or AI a concern of yours? Then you are in the right place. The training below will aggregate all the relevant resources in one convenient location for you to learn from. Let’s start here with a quick overview of Microsoft Defender for Cloud Apps’ capabilities. Microsoft Defender for Cloud Apps | Microsoft Security Overview of Microsoft Defender for Cloud Apps and the capability of a SaaS Security solution. Overview - Microsoft Defender for Cloud Apps | Microsoft Learn Understand what Microsoft Defender for Cloud Apps is and read about its main capabilities. Quick Start The basic features of Defender for Cloud Apps require almost no effort to deploy. The recommended steps are to: Connect your apps Enable App Discovery Enable App Governance After enabling these features, all default detections and alerts will start triggering in the Microsoft Defender XDR console, and give you tremendous value with minimal configuration. Simplified SaaS Security Deployment with Microsoft Defender for Cloud Apps | Virtual Ninja Training Step-by-step video on how to quickly deploy Defender for Cloud Apps Get started - Microsoft Defender for Cloud Apps This quickstart describes how to start working with Microsoft Defender for Cloud Apps on the Microsoft Defender Portal. Review this if you prefer text to video Basic setup - Microsoft Defender for Cloud Apps The following procedure gives you instructions for customizing your Microsoft Defender for Cloud Apps environment. Connect apps to get visibility and control - Microsoft Defender for Cloud Apps App connectors use the APIs of app providers to enable greater visibility and control by Microsoft Defender for Cloud Apps over the apps you connect to. Make sure to connect all your available apps as you start your deployment Turn on app governance in Microsoft Defender for Cloud Apps App governance in Defender for Cloud Apps is a set of security and policy management capabilities designed for OAuth-enabled apps registered on Microsoft Entra ID, Google, and Salesforce. App governance delivers visibility, remediation, and governance into how these apps and their users access, use, and share sensitive data in Microsoft 365 and other cloud platforms through actionable insights out-of-the box threat detections, OAuth apps attack disruption, automated policy alerts and actions. It only takes a few minutes to enable and provide full visibility on your users’ Oauth app consents Shadow IT Discovery - Integrate with Microsoft Defender for Endpoint This article describes the out-of-the-box integration available between Microsoft Defender for Cloud Apps and Microsoft Defender for Endpoint, which simplifies cloud discovery and enabling device-based investigation. Control cloud apps with policies Policies in Microsoft Defender for Cloud Apps help define user behavior in the cloud, detect risky activities, and enable remediation workflows. There are various types of policies, such as Activity, Anomaly Detection, OAuth App, Malware Detection, File, Access, Session, and App Discovery policies. These policies help mitigate risks like access control, compliance, data loss prevention, and threat detection. Detect Threats and malicious behavior After connecting your cloud apps in Defender for Cloud Apps, you will start seeing alerts in your XDR portal. Here are resources to learn more about these alerts and how to investigate them. Note that we are constantly adding new built-in detections, and they are not necessarily part of our public documentation. How to manage incidents - Microsoft Defender XDR Learn how to manage incidents, from various sources, using Microsoft Defender XDR. How to investigate anomaly detection alerts Microsoft Defender for Cloud Apps provides detections for malicious activities. This guide provides you with general and practical information on each alert, to help with your investigation and remediation tasks. Note that detections are added on a regular basis, and not all of them will have entries in this guide. Configure automatic attack disruption in Microsoft Defender XDR - Microsoft Defender XDR | Microsoft Learn Learn how to take advantage of XDR capabilities to automatically disrupt high confidence attacks before damage is done. OAuth apps are natively integrated as part of Microsoft XDR. Create activity policies - Microsoft Defender for Cloud Apps | Microsoft Learn In addition to all the built-in detections as part of Microsoft Defender for Cloud Apps, you can also create your own policies, including Governance actions, based on the Activity log captured by Defender for Cloud Apps. Create and manage custom detection rules in Microsoft Defender XDR - Microsoft Defender XDR | Microsoft Learn Learn how to leverage XDR custom detection rules based on hunting data in the platform. CloudAppEvents table in the advanced hunting schema - Microsoft Defender XDR | Microsoft Learn Learn about the CloudAppEvents table which contains events from all connected applications with data enriched by Defender for Cloud Apps in a common schema. This data can be hunted across all connected apps and your separate XDR workloads. Investigate behaviors with advanced hunting - Microsoft Defender for Cloud Apps | Microsoft Learn Learn about behaviors and how they can help with security investigations. Investigate activities - Microsoft Defender for Cloud Apps | Microsoft Learn Learn how to search the activity log and investigate activities with a simple UI without the need for KQL App Governance – Protect from App-to-App attack scenario App governance in Microsoft Defender for Cloud Apps is crucial for several reasons. It enhances security by identifying and mitigating risks associated with OAuth-enabled apps, which can be exploited for privilege escalation, lateral movement, and data exfiltration. Organizations gain clear visibility into app compliance, allowing them to monitor how apps access, use, and share sensitive data. It provides alerts for anomalous behaviors, enabling quick responses to potential threats. Automated policy alerts and remediation actions help enforce compliance and protect against noncompliant or malicious apps. By governing app access, organizations can better safeguard their data across various cloud platforms. These features collectively ensure a robust security posture, protecting both data and users from potential threats. Get started with App governance - Microsoft Defender for Cloud Apps Learn how app governance enhances the security of SaaS ecosystems like Microsoft 365, Google Workspace, and Salesforce. This video details how app governance identifies integrated OAuth apps, detects and prevents suspicious activity, and provides in-depth monitoring and visibility into app metadata and behaviors to help strengthen your overall security posture. App governance in Microsoft Defender for Cloud Apps and Microsoft Defender XDR - Microsoft Defender for Cloud Apps | Microsoft Learn Defender for Cloud Apps App governance overview Create app governance policies - Microsoft Defender for Cloud Apps | Microsoft Learn Many third-party productivity apps request access to user data and sign in on behalf of users for other cloud apps like Microsoft 365, Google Workspace, and Salesforce. Users often accept these permissions without reviewing the details, posing security risks. IT departments may lack insight into balancing an app's security risk with its productivity benefits. Monitoring app permissions provides visibility and control to protect your users and applications. App governance visibility and insights - Microsoft Defender for Cloud Apps | Microsoft Learn Managing your applications requires robust visibility and insight. Microsoft Defender for Cloud Apps offers control through in-depth insights into user activities, data flows, and threats, enabling effective monitoring, anomaly detection, and compliance Reduce overprivileged permissions and apps Recommendations for reducing overprivileged permissions App Governance plays a critical role in governing applications in Entra ID. By integrating with Entra ID, App Governance provides deeper insights into application permissions and usage within your identity infrastructure. This correlation enables administrators to enforce stringent access controls and monitor applications more effectively, ensuring compliance and reducing potential security vulnerabilities. This page offers guidelines for reducing unnecessary permissions, focusing on the principle of least privilege to minimize security risks and mitigate the impact of breaches. Investigate app governance threat detection alerts List of app governance threat detection alerts classified according to MITRE ATT&CK and investigation guidance Manage app governance alerts Learn how to govern applications and respond to threat and risky applications directly from app governance or through policies. Hunt for threats in app activities Learn how to hunt for app activities directly form the XDR console (Microsoft 365 Connector required as discussed in quick start section). How to Protect Oauth Apps with App Governance in Microsoft Defender for Cloud Apps Webinar | How to Protect Oauth Apps with App Governance in Microsoft Defender for Cloud Apps. Learn how to protect Oauth applications in your environment, how to efficiently use App governance within Microsoft Defender for Cloud Apps to protect your connected apps and raise your security posture. App Governance is a Key Part of a Customers' Zero Trust Journey Webinar| learn about how the app governance add-on to Microsoft Defender for Cloud Apps is a key component of customers' Zero Trust journey. We will examine how app governance supports managing to least privilege (including identifying unused permissions), provides threat detections that are able and have already protected customers, and gives insights on risky app behaviors even for trusted apps. App Governance Inclusion in Defender for Cloud Apps Overview Webinar| App governance overview and licensing requirements. Frequently asked questions about app governance App governance FAQ Manage the security Posture of your SaaS (SSPM) One of the key components of Microsoft Defender for Cloud Apps is the ability to gain key information about the Security posture of your applications in the cloud (AKA: SaaS). This can give you a proactive approach to help avoid breaches before they happen. SaaS Security posture Management (or SSPM) is part the greater Exposure Management offering, and allows you to review the security configuration of your key apps. More details in the links below: Transform your defense: Microsoft Security Exposure Management | Microsoft Secure Tech Accelerator Overview of Microsoft Exposure Management and it’s capabilities, including how MDA & SSPM feed into this. SaaS Security Posture Management (SSPM) - Overview - Microsoft Defender for Cloud Apps | Microsoft Learn Understand simply how SSPM can help you increase the safety of your environment Turn on and manage SaaS security posture management (SSPM) - Microsoft Defender for Cloud Apps | Microsoft Learn Enabling SSPM in Defender for Cloud Apps requires almost no additional configuration (as long as your apps are already connected), and no extra license. We strongly recommend turning it on, and monitoring its results, as the cost of operation is very low. SaaS Security Initiative - Microsoft Defender for Cloud Apps | Microsoft Learn The SaaS Security Initiative provides a centralized place for software as a service (SaaS) security best practices, so that organizations can manage and prioritize security recommendations effectively. By focusing on the most impactful metrics, organizations can enhance their SaaS security posture. Secure your usage of AI applications AI is Information technologies’ newest tool and strongest innovation area. As we know it also brings its fair share of challenges. Defender for Cloud Apps can help you face these from two different angles: - First, our App Discovery capabilities give you a complete vision of all the Generative AI applications in use in an environment - Second, we provide threat detection capabilities to identify and alert from suspicious usage of Copilot for Microsoft 365, along with the ability to create custom detection using KQL queries. Secure AI applications using Microsoft Defender for Cloud Apps Overview of Microsoft Defender for Cloud Apps capabilities to secure your usage of Generative AI apps Step-by-Step: Discover Which Generative AI Apps Are Used in Your Environment Using Defender for Cloud Apps Detailed video-guide to deploy Discovery of Gen AI apps in your environment in a few minutes Step-by-Step: Protect Your Usage of Copilot for M365 Using Microsoft Defender for Cloud Apps Instructions and examples on how to leverage threat protection and advanced hunting capabilities to detect any risky or suspicious usage of Copilot for Microsoft 365 Get visibility into DeepSeek with Microsoft Defender for Cloud Apps Understand how fast the Microsoft Defender for Cloud Apps team can react when new apps or new threats come in the market. Discover Shadow IT applications Shadow IT and Shadow AI are two big challenges that organizations face today. Defender for Cloud Apps can help give you visibility you need, this will allow you to evaluate the risks, assess for compliance and apply controls over what can be used. Getting started The first step is to ensure the relevant data sources are connected to Defender for Cloud Apps to provide you the required visibility: Integrate Microsoft Defender for Endpoint - Microsoft Defender for Cloud Apps | Microsoft Learn The quickest and most seamless method to get visibility of cloud app usage is to integrate MDA with MDE (MDE license required). Create snapshot cloud discovery reports - Microsoft Defender for Cloud Apps | Microsoft Learn A sample set of logs can be ingested to generate a Snapshot. This lets you view the quality of the data before long term ingestion and also be used for investigations. Configure automatic log upload for continuous reports - Microsoft Defender for Cloud Apps | Microsoft Learn A log collector can be deployed to facilitate the collection of logs from your network appliances, such as firewalls or proxies. Defender for Cloud Apps cloud discovery API - Microsoft Defender for Cloud Apps | Microsoft Learn MDA also offers a Cloud Discovery API which can be used to directly ingest log information and mitigate the need for a log collector. Evaluate Discovered Apps Once Cloud Discovery logs are being populated into Defender for Cloud Apps, you can start the process of evaluating the discovered apps. This includes reviewing their usage, user count, risk scores and compliance factors. View discovered apps on the Cloud discovery dashboard - Microsoft Defender for Cloud Apps | Microsoft Learn View & evaluate the discovered apps within Cloud Discovery and Generate Cloud Discovery Executive Reports Working with the app page - Microsoft Defender for Cloud Apps | Microsoft Learn Investigate app usage and evaluate their compliance and risk factors Discovered app filters and queries - Microsoft Defender for Cloud Apps | Microsoft Learn Apply granular filtering and app tagging to focus on apps that are important to you Work with discovered apps via Graph API - Microsoft Defender for Cloud Apps | Microsoft Learn Investigate discovered apps via the Microsoft Graph API Add custom apps to cloud discovery - Microsoft Defender for Cloud Apps | Microsoft Learn You can add custom apps to the catalog which can then be matched against log data. This is useful for LOB applications. Govern Discovered Apps Having evaluated your discovered apps, you can then take some decisions on what level of governance and control each of the applications require and whether you want custom policies to help govern future applications: Govern discovered apps using Microsoft Defender for Endpoint - Microsoft Defender for Cloud Apps | Microsoft Learn Setup governance enforcement actions when using Microsoft Defender for Endpoint Govern discovered apps - Microsoft Defender for Cloud Apps | Microsoft Learn Apply governance actions to discovered apps from within the Cloud Discovery area Create cloud discovery policies - Microsoft Defender for Cloud Apps | Microsoft Learn Create custom Cloud Discovery policies to identify usage, alert and apply controls Operations and investigations - Sample AH queries - Tips on investigation - (section for SOC) Advanced Hunting Compromised and malicious applications investigation | Microsoft Learn Investigate anomalous app configuration changes Impersonation and EWS in Exchange | Microsoft Learn Audits impersonate privileges in Exchange Online Advanced Hunting Queries Azure-Sentinel/Solutions/Microsoft Entra ID/Analytic Rules/ExchangeFullAccessGrantedToApp.yaml at master · Azure/Azure-Sentinel · GitHub This detection looks for the full_access_as_app permission being granted to an OAuth application with Admin Consent. This permission provide access to all Exchange mailboxes via the EWS API can could be exploited to access sensitive data by being added to a compromised application. The application granted this permission should be reviewed to ensure that it is absolutely necessary for the applications function Azure-Sentinel/Solutions/Microsoft Entra ID/Analytic Rules/AdminPromoAfterRoleMgmtAppPermissionGrant.yaml at master · Azure/Azure-Sentinel · GitHub This rule looks for a service principal being granted permissions that could be used to add a Microsoft Entra ID object or user account to an Admin directory role. Azure-Sentinel/Solutions/Microsoft Entra ID/Analytic Rules/SuspiciousOAuthApp_OfflineAccess.yaml at master · Azure/Azure-Sentinel · GitHub Offline access will provide the Azure App with access to the listed resources without requiring two-factor authentication. Consent to applications with offline access and read capabilities should be rare, especially as the known Applications list is expanded Best Practice recommendations Common threat protection policies - Microsoft Defender for Cloud Apps | Microsoft Learn Common Defender for Cloud Apps Threat Protection policies Recommended Microsoft Defender for Cloud Apps policies for SaaS apps | Microsoft Learn Recommended Microsoft Defender for Cloud Apps policies for SaaS apps Best practices for protecting your organization - Microsoft Defender for Cloud Apps | Microsoft Learn Best practices for protecting your organization with Defender for Cloud Apps Completion certificate! Click here to get your shareable completion certificate!! Advanced configuration Training Title Description Importing user groups from connect apps This article outlines the steps on how to import user groups from connected apps Manage Admin Access This article describes how to manage admin access in Microsoft Defender for Cloud Apps. Configure MSSP Access In this video, we walk through the steps on adding Managed Security Service Provider (MSSP) access to Microsoft Defender for Cloud Apps. Provide managed security service provider (MSSP) access - Microsoft Defender XDR | Microsoft Learn Provide managed security service provider (MSSP) access Integrate with Secure Web Gateways Microsoft Defender for Cloud Apps integrates with several secure web gateways available in the market. Here are the links to configure this integration. Integrate with Zscaler Integrate with iboss Integrate with Corrata Integrate with Menlo Additional resources Microsoft Defender for Cloud Apps Tech Community This is a Microsoft Defender for Cloud Apps Community space that allows users to connect and discuss the latest news, upgrades, and best practices with Microsoft professionals and peers.Microsoft 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.Become a Communication Compliance Ninja
** Updated June 2023 ** We are very excited and pleased to announce this rendition of the Ninja Training Series. There are several videos and resources out there and the overall purpose of the Communication Compliance Ninja training is to help you get the relevant resources to get started and become more proficient in this area.Unlock Proactive Defense: Microsoft Security Exposure Management Now Generally Available
As the digital landscape grows increasingly interconnected, defenders face a critical challenge: the data and insights from various security tools are often siloed or, at best, loosely integrated. This fragmented approach makes it difficult to gain a holistic view of threats or assess their potential impact on critical assets. In a world where a single compromised asset can trigger a domino effect across connected resources, thinking in graphs has become essential for defenders. This approach breaks down silos, allowing them to visualize relationships between assets, vulnerabilities, and threats, ultimately enabling proactive risk management and strengthening their stance against attackers. Traditional vulnerability management is no longer sufficient. While patching every potential weakness might seem like a solution, it's neither practical nor effective. Instead, modern security strategies must focus on the exposures that are easiest for attackers to exploit, prioritizing vulnerabilities that present the greatest risk. This shift marks the evolution of vulnerability management into what we now call exposure management. Earlier this year, we launched Microsoft Security Exposure Management in public preview, introducing defenders to powerful foundational capabilities for holistic exposure management. Backed by extensive threat research and Microsoft’s vast visibility into security signals, these tools provide coverage for commonly observed attack techniques. Exposure Management includes Attack Surface Management, Attack Path Analysis, and Unified Exposure Insights— solutions that offer security teams unmatched visibility and insight into their risk landscape. Attack Surface Management offers a complete, continuous view of an organization’s attack surface, enabling teams to fully explore assets, uncover interdependencies, and monitor exposure across the entire digital estate. Central to this is the identification of critical assets, which are often prime targets for attackers. By highlighting these key assets, security teams can prioritize their efforts and better understand which areas require the most protection. By giving security teams a clear map of their exposure points, Attack Surface Management empowers a more informed and comprehensive defense strategy. Attack Path Analysis takes this a step further, guiding teams in visualizing and prioritizing high-risk attack paths across diverse environments, with a specific focus on critical assets. This capability allows for targeted, effective remediation of vulnerabilities that impact these key assets, helping to significantly reduce exposure and the likelihood of a breach by focusing on the most impactful pathways an attacker might exploit. Unified Exposure Insights gives decision-makers a clear view of an organization's threat exposure, helping security teams address key questions about their posture. Through Security Initiatives, teams focus on priority areas like cloud security and ransomware, supported by actionable metrics to track progress, prioritize risks, and align remediation with business goals for proactive risk management. Exposure Management translates vulnerabilities and exposures into more understandable language about risk and actionable initiatives related to our environment, which helps stakeholders and leadership grasp the impact more clearly. - Bjorn Pauwels Cyber Security Architect Atlas Copco Throughout the public preview, we collaborated closely with customers and industry experts, refining Microsoft Security Exposure Management based on real-world usage and feedback. This partnership revealed that the biggest challenges extended beyond deploying the right tools; they involved enhancing organizational maturity, evolving processes, and fostering a proactive security mindset. These insights drove strategic enhancements to features and user experience, ensuring the solution effectively supports organizations aiming to shift from reactive to proactive threat management. For example, several organizations created a 'RiskOps' role specifically to champion cross-domain threat exposure reduction, breaking down silos and unifying teams around common security goals. Security Operations (SecOps) teams now report significantly streamlined processes by leveraging asset criticality in incident prioritization, helping them address the most impactful threats faster than previously possible. Likewise, vulnerability management teams are using enhanced attack map and path analysis features to refine patching strategies, focusing more precisely on vulnerabilities most likely to lead to real risks. These examples underscore Exposure Management's ability to drive practical, measurable improvements across diverse teams, empowering them to stay ahead of evolving threats with a targeted, collaborative approach to risk management. Exposure Management enables organizations to zero in on their most critical exposures and act quickly. By breaking down silos and connecting security insights across the entire digital estate, organizations gain a holistic view of their risk posture. This comprehensive visibility is crucial for making faster, more informed decisions—reducing exposure before attackers can exploit it. We are excited to announce the general availability of Microsoft Security Exposure Management This release includes several new capabilities designed to help you build and enhance a Continuous Threat Exposure Management (CTEM) program, ensuring that you stay ahead of threats by continuously identifying, prioritizing, and mitigating risks across your digital landscape. Global rollout started 19 Nov, 2024 so keep an eye out for Exposure Management in your Defender portal, https://security.microsoft.com Cyber Asset Attack Surface Management To help you establish a comprehensive, single source of truth for your assets, we are expanding our signal collection beyond Microsoft solutions to include third-party integrations. The new Exposure connectors gallery offers a range of connectors to popular security vendors. Data collected through these connectors is normalized within our exposure graph, enhancing your device inventory, mapping relationships, and revealing new attack paths for comprehensive attack surface visibility. Additional insights like asset criticality, internet exposure and business application or operational affiliation are incorporated from the connected tools to enrich the context that Exposure Management can apply on the collected assets. This integrated data can be visualized through the Attack Map tool or explored using advanced hunting queries via KQL (Kusto Query Language). External data connectors to non-Microsoft security tools are currently in public preview, we are continuously working to add more connectors for leading market solutions, ensuring you have the broadest possible visibility across your security ecosystem. Discover more about data connectors in our documentation. Extended Attack Path Analysis Attack Path Analysis provides organizations with a crucial attacker’s-eye perspective, revealing how adversaries might exploit vulnerabilities and move laterally across both cloud and on-premise environments. By identifying and visualizing potential paths – from initial access points, such as internet-exposed devices, to critical assets – security teams gain valuable insight into the paths attackers could take, including hybrid attack paths that traverse cloud and on-prem infrastructure. Microsoft Security Exposure Management addresses the challenge of fragmented visibility by offering defenders an integrated view of their most critical assets and the likely routes attackers might exploit. This approach moves beyond isolated vulnerabilities, allowing teams to see their environment as a connected landscape of risks across hybrid infrastructures, ultimately enhancing their ability to secure critical assets and discover potential entry points. We are excited to update on our solution’s latest enhancement, which includes a high-level overview experience, offering a clear understanding of top attack scenarios, entry points, and common target types. Additionally, Exposure Management highlights chokepoints with a dedicated experience – these chokepoints are assets that appear in multiple attack paths, enabling cost-effective mitigation. Chokepoints also support blast radius querying, showing how attackers might exploit these assets to reach critical targets. In addition, we are adding support for new adversarial techniques including: DACL Support: We now include Discretionary Access Control Lists (DACLs) in our attack path analysis, through which more extensive attack paths are uncovered, particularly those that exploit misconfigurations or excessive permissions within access control lists. Hybrid Attack Paths: Our expanded analysis now identifies hybrid attack paths, capturing routes that originate on-premises and extend into cloud environments, providing defenders with a more complete view of potential threats across both infrastructures. In essence, attack path management allows defenders to transform isolated vulnerabilities into actionable insights across hybrid infrastructures. This comprehensive perspective enables security teams to shift from reactive to proactive defense, strengthening resilience by focusing on the most critical threats across their entire environment. Unified Exposure Insights With Microsoft Security Exposure Management, organizations can transform raw technical data into actionable insights that bridge the gap between cybersecurity teams and business decision-makers. By offering clear, real-time metrics, this platform answers key questions such as "How secure are we?", "What risks do we face?", and "Where should we focus first to reduce our exposure?" These insights not only provide a comprehensive view of your security posture but also guide prioritization and remediation efforts. To help your organization embrace a proactive security mindset, we introduced Security Initiatives—a strategic framework to focus your teams on critical aspects of your attack surface. These initiatives help teams to scope, discover, prioritize, and validate security findings while ensuring effective communication with stakeholders. Now, we are enhancing these capabilities to offer even greater visibility and control. The expanded initiative catalog now features new programs targeting high-priority areas like SaaS security, IoT, OT, and alongside existing domain and threat-focused initiatives. Each initiative continues to provide real-time metrics, expert-curated recommendations, and progress tracking, empowering security teams to drive maturity across their security programs. With this expanded toolset, organizations can further align their security efforts with evolving risks, ensuring a continuous, dynamic response to the threat landscape. SaaS Security Initiative (Powered by Microsoft Defender for Cloud Apps): Effective SaaS posture management is essential for proactively preventing SaaS-related attacks. The SaaS Security initiative delivers a comprehensive view of your SaaS security coverage, health, configuration, and performance and consolidates all best-practice recommendations for configuring SaaS apps into measurable metrics to help security teams efficiently manage and prioritize critical security controls. To optimize this initiative, activate key application connectors in Defender for Cloud Apps, including Microsoft 365, Salesforce, ServiceNow, GitHub, Okta, Citrix ShareFile, DocuSign, Dropbox, Google Workspace, NetDocuments, Workplace (preview), Zendesk, Zoom (preview), and Atlassian. For more information, check out https://aka.ms/Ignite2024MDA OT Security Initiative (Powered by Microsoft Defender for IoT): The convergence of Operational Technology (OT) and Information Technology (IT) has transformed industries worldwide, but it has also introduced significant new security challenges, particularly for industrial operations and critical infrastructure. The modern threat landscape, now accelerated by the growing capabilities of AI, demands specialized security solutions for these sensitive environments. The OT Security Initiative addresses these challenges by providing practitioners with a comprehensive solution to identify, monitor, and mitigate risks within OT environments, ensuring both operational reliability and safety. By leveraging Microsoft Defender for Endpoint discovery, the initiative offers unified visibility across enterprise and OT networks, empowering organizations to identify unprotected OT assets, assess their risk levels, and implement security measures across all physical sites. Enterprise IoT Security Initiative (Powered by Microsoft Defender for IoT): This initiative delivers comprehensive visibility into the risks associated with IoT devices within the enterprise, enabling organizations to assess their resilience against these emerging threats. As IoT devices frequently connect to endpoints, one another, or the internet, they become prime targets for cyberattacks. Therefore, businesses must continuously monitor the security of these devices, tracking their distribution, configuration, connectivity, exposure, and behavior to prevent the introduction of hidden vulnerabilities. By leveraging this initiative, organizations can proactively manage IoT risks and safeguard their digital landscape. Proactively understand how system updates affect scores The new versioning feature offers proactive notifications about upcoming version updates, giving users advanced visibility into anticipated metric changes and their impact on related initiatives. A dedicated side panel provides comprehensive details about each update, including the expected release date, release notes, current and updated metric values, and any changes to related initiative scores. Additionally, users can share direct feedback on the updates within the platform, fostering continuous improvement and responsiveness to user needs. Exposure History With the new history-reasoning feature, users can investigate metric changes by reviewing detailed asset exposure updates. In the initiative's history tab, selecting a specific metric now reveals a list of assets where exposure has been either added or removed, providing clearer insight into exposure shifts over time. Unified Role-Based Access Control (URBAC) Support We are excited to introduce the capability to manage user privileges and access to Microsoft Security Exposure Management through custom roles within the Microsoft Defender XDR Unified Role-Based Access Control (URBAC) system. This enhancement ensures higher productivity and efficient access control on a single, centralized platform. The unified RBAC permissions model offers administrators an alternative to Entra ID directory roles, allowing for more granular permission management and customization. This model complements Entra ID global roles by enabling administrators to implement access policies based on the principle of least privilege, thereby assigning users only the permissions they need for their daily tasks. We recommend maintaining three custom roles that align with organizational posture personas: Posture Reader: Users with read-only access to Exposure Management data. Posture Contributor: Users with read and manage permissions, enabling them to handle security initiatives and metrics, as well as manage posture recommendations. Posture Admin: Users who likely already hold higher-level permissions within the Microsoft Defender portal and can now perform sensitive posture-related actions within Exposure Management experiences. To learn more about the Microsoft XDR Unified RBAC permissions model, click here. For more information on Microsoft Security Exposure Management access management with unified RBAC, click here. How to get Microsoft Security Exposure Management Exposure Management is available in the Microsoft Defender portal at https://security.microsoft.com. Access to the exposure management blade and features in the Microsoft Defender portal is available with any of the following licenses: Microsoft 365 E5 or A5 Microsoft 365 E3 Microsoft 365 E3 with the Microsoft Enterprise Mobility + Security E5 add-on Microsoft 365 A3 with the Microsoft 365 A5 security add-on Microsoft Enterprise Mobility + Security E5 or A5 Microsoft Defender for Endpoint (Plan 1 and 2) Microsoft Defender for Identity Microsoft Defender for Cloud Apps Microsoft Defender for Office 365 (Plans 1 and 2) Microsoft Defender Vulnerability Management Integration of data from the above tools, as well as other Microsoft security tools like Microsoft Defender for Cloud, Microsoft Defender Cloud Security Posture Management, and Microsoft Defender External Attack Surface Management, is available with these licenses. Integration of non-Microsoft security tools will incur a consumption-based cost based on the number of assets in the connected security tool. The external connectors are currently in public preview, with plans to reach general availability (GA) by the end of Q1 2025. Pricing will be announced before billing for external connectors begins at GA. Learn More The threat landscape is constantly shifting, and the attack surface continues to grow, leaving organizations exposed. Outpacing threat actors through patching alone is no longer feasible. Now is the time to evolve your vulnerability management strategy to be smarter, more dynamic, and more powerful — focused on exposures and built on a proactive mindset. By adopting a Continuous Threat Exposure Management (CTEM) process, you can stay ahead of attackers. Microsoft Security Exposure Management equips you with the tools to scope, discover, prioritize, validate, and mobilize your teams, empowering you to defend your organization with precision and confidence. Embrace the future of cybersecurity resilience—contact us today to learn more, sign up for a demo, or speak with our team about how Microsoft Security Exposure Management can transform your defense strategy. Don’t wait to secure your organization. Get started today. Explore overview and core scenarios on our website Learn about capabilities and scenarios in blog posts written by our engineering and research teams
