All Key Vaults Are Critical, But Some Are More Critical Than Others: Finding the Crown Jewels
Introduction A critical asset is one of substantial value, whose compromise or disruption would result in significant adverse effects on the organization. This definition lays the foundation for understanding why Azure Key Vaults often fall into this category. Azure Key Vaults are integral to cloud environments as they manage sensitive data like cryptographic keys, passwords, and certificates. Their frequent use in securing applications, managing secrets, and enabling secure operations makes them highly valuable. Given this importance, identifying which Key Vaults are critical becomes essential. Approach Our approach to identifying critical Key Vaults is based on operational activity. We classify Key Vaults using the top n percentile of operations within each tenant, ensuring that only the most active and essential Key Vaults are flagged as critical. This approach provides a fair evaluation across varying tenant sizes and ensures that thresholds dynamically adjust with data size and distribution, making the classification resilient to outliers and representative of actual operational importance. Why Focus on Key Vaults with High Operation Counts? Increased Usage Indicates High Dependency: A high volume of operations suggests that the Key Vault is heavily utilized, meaning it plays a central role in the security and operational processes within the environment. For example, it might be frequently accessed to retrieve secrets, keys, or certificates, which are essential for the functioning of various applications and services. Sensitive Data Storage: Key Vaults typically store sensitive data, such as cryptographic keys, passwords, and other secrets. A Key Vault with many operations is likely to store and manage a significant amount of this sensitive data, making it a high-value target for potential attacks. Operational Impact: If a heavily used Key Vault were compromised or became unavailable, it could disrupt multiple critical processes across the organization. This could include application outages, security breaches, or other operational failures, making the Key Vault critical to overall business continuity. Security Implications: Frequent access to a Key Vault might indicate its role in automated processes or scripts that require secure handling of credentials and keys. The more a Key Vault is accessed, the higher the potential risk if its security is breached, hence making it essential to protect and monitor it closely. Benefits of Using Percentiles in Criticality Classification In critical asset classification, the use of percentiles offers several distinct advantages over percentage-based methods: Resilience to Outliers: Percentiles rank Key Vaults without being influenced by extreme values. For instance, even if one Key Vault has an unusually high operation count, the percentile method ensures that the classification threshold remains stable. Dynamic Adaptation to Dataset Size: As the number of Key Vaults grows, percentile thresholds adjust dynamically, maintaining consistency and accuracy over time. Fair Evaluation Across Tenants: Different tenants have varying numbers of Key Vaults. Percentiles allow for a fair assessment by ensuring that each tenant’s Key Vaults are evaluated within that tenant’s dataset. This means that even smaller tenants with fewer Key Vaults can have their most active Key Vaults identified as critical without being overshadowed by the larger operation counts of bigger tenants. Percentiles rank within each tenant individually, making the classification equitable across different scales. Mathematical Rigor: Percentiles provide a statistically sound method for ranking Key Vaults, offering a reliable framework for criticality classification. Operational Relevance: By using percentiles, the classification highlights Key Vaults that are truly operationally significant within their own environment, enhancing security monitoring and response efforts. This approach ensures that critical assets are identified accurately, without the distortions caused by outliers, dataset size, or operational scale variations, making it ideal for cloud environments. Findings from Research Overall Critical Assets: Around 0.5% of total KVs were identified as critical Tenant-wise Analysis: Percentile thresholds adjusted dynamically across tenant sizes. Large tenants saw a minimal increase in critical assets, validating accuracy. Smaller tenants benefited from nuanced classification. Percentile-based classification ensures that Key Vaults with relatively high operation counts are identified, regardless of tenant size, providing a balanced approach. Figure 1: Tenant-wise Analysis Finding the Optimal Percentile Threshold The reverse elbow curve method is a data-driven approach to determine the optimal percentile threshold. Figure 2 illustrates this concept by plotting the percentage of Key Vaults classified as critical against various percentile values. As the percentile value increases from 90 to 99, the percentage of critical Key Vaults decreases, forming a clear reverse elbow shape. In this graph, the curve starts to flatten around the 95th percentile, marked as the 'Optimal Percentile Threshold.' This point represents where the rate of decrease in critical Key Vaults slows down significantly. Selecting this threshold ensures that we capture the most critical Key Vaults without unnecessarily including too many lower-priority assets. Before this point, too many Key Vaults are classified as critical, while after this point, too few Key Vaults are included. Figure 2: Identifying the optimal percentile threshold This visual example demonstrates why the reverse elbow curve method is essential for balancing coverage and precision in critical asset classification, ensuring that the most operationally significant Key Vaults are identified efficiently. Conclusion In conclusion, identifying critical Azure Key Vaults is essential for maintaining the security, availability, and operational integrity of cloud environments. By leveraging a percentile-based classification approach, we ensure that only the most active and essential Key Vaults are recognized as critical assets. The use of the reverse elbow curve method further strengthens this classification by selecting an optimal percentile threshold that balances coverage and precision. This methodology not only minimizes noise from less active Key Vaults but also ensures that highly utilized and sensitive Key Vaults receive the attention they deserve. As cloud operations continue to scale, such data-driven classification approaches are vital for effective security management and risk mitigation.
New innovations to protect custom AI applications with Defender for Cloud
Today’s blog post introduced new capabilities to enhance AI security and governance across multi-model and multi-cloud environments. This follow-on blog post dives deeper into how Microsoft Defender for Cloud can help organizations protect their custom-built AI applications. The AI revolution has been transformative for organizations, driving them to integrate sophisticated AI features and products into their existing systems to maintain a competitive edge. However, this rapid development often outpaces their ability to establish adequate security measures for these advanced applications. Moreover, traditional security teams frequently lack the visibility and actionable insights needed, leaving organizations vulnerable to increasingly sophisticated attacks and struggling to protect their AI resources. To address these challenges, we are excited to announce the general availability (GA) of threat protection for AI services, a capability that enhances threat protection in Microsoft Defender for Cloud. Starting May 1, 2025, the new Defender for AI Services plan will support models in Azure AI and Azure OpenAI Services. “Security is paramount at Icertis. That’s why we've partnered with Microsoft to host our Contract Intelligence platform on Azure, fortified by Microsoft Defender for Cloud. As large language models (LLMs) became mainstream, our Icertis ExploreAI Service leveraged generative AI and proprietary models to transform contract management and create value for our customers. Microsoft Defender for Cloud emerged as our natural choice for the first line of defense against AI-related threats. It meticulously evaluates the security of our Azure OpenAI deployments, monitors usage patterns, and promptly alerts us to potential threats. These capabilities empower our Security Operations Center (SOC) teams to make more informed decisions based on AI detections, ensuring that our AI-driven contract management remains secure, reliable, and ahead of emerging threats.” Subodh Patil, Principal Cyber Security Architect at Icertis With these new threat protection capabilities, security teams can: Monitor suspicious activity in Azure AI resources, abiding by security frameworks like the OWASP Top 10 threats for LLM applications to defend against attacks on AI applications, such as direct and indirect prompt injections, wallet abuse, suspicious access to AI resources, and more. Triage and act on detections using contextual and insightful evidence, including prompt and response evidence, application and user context, grounding data origin breadcrumbs, and Microsoft Threat Intelligence details. Gain visibility from cloud to code (right to left) for better posture discovery and remediation by translating runtime findings into posture insights, like smart discovery of grounding data sources. Requires Defender CSPM posture plan to be fully utilized. Leverage frictionless onboarding with one-click, agentless enablement on Azure resources. This includes native integrations to Defender XDR, enabling advanced hunting and incident correlation capabilities. Detect and protect against AI threats Defender for Cloud helps organizations secure their AI applications from the latest threats. It identifies vulnerabilities and protects against sophisticated attacks, such as jailbreaks, invisible encodings, malicious URLs, and sensitive data exposure. It also protects against novel threats like ASCII smuggling, which could otherwise compromise the integrity of their AI applications. Defender for Cloud helps ensure the safety and reliability of critical AI resources by leveraging signals from prompt shields, AI analysis, and Microsoft Threat Intelligence. This provides comprehensive visibility and context, enabling security teams to quickly detect and respond to suspicious activities. Prompt analysis-based detections aren’t the full story. Detections are also designed to analyze the application and user behavior to detect anomalies and suspicious behavior patterns. Analysts can leverage insights into user context, application context, access patterns, and use Microsoft Threat Intelligence tools to uncover complex attacks or threats that escape prompt-based content filtering detectors. For example, wallet attacks are a common threat where attackers aim to cause financial damage by abusing resource capacity. These attacks often appear innocent because the prompts' content looks harmless. However, the attacker's intention is to exploit the resource capacity when left unconstrained. While these prompts might go unnoticed as they don't contain suspicious content, examining the application's historical behavior patterns can reveal anomalies and lead to detection. Respond and act on AI detections effectively The lack of visibility into AI applications is a real struggle for security teams. The detections contain evidence that is hard or impossible for most SOC analysts to access. For example, in the below credential exposure detection, the user was able to solicit secrets from the organizational data connected to the Contoso Outdoors chatbot app. How would the analyst go about understanding this detection? The detection evidence shows the user prompt and the model response (secrets are redacted). The evidence also explicitly calls out what kind of secret was exposed. The prompt evidence of this suspicious interaction is rarely stored, logged, or accessible anywhere outside the detection. The prompt analysis engine also tied the user request to the model response, making sense of the interaction. What is most helpful in this specific detection is the application and user context. The application name instantly assists the SOC in determining if this is a valid scenario for this application. Contoso Outdoors chatbot is not supposed to access organizational secrets, so this is worrisome. Next, the user context reveals who was exposed to the data, through what IP (internal or external) and their supposed intention. Most AI applications are built behind AI gateways, proxies, or Azure API Management (APIM) instances, making it challenging for SOC analysts to obtain these details through conventional logging methods or network solutions. Defender for Cloud addresses this issue by using a straightforward approach that fetches these details directly from the application’s API request to Azure AI. Now, the analyst can reach out to the user (internal) or block (external) the identity or the IP. Finally, to resolve this incident, the SOC analyst intends to remove and decommission the secret to mitigate the impact of the exposure. The final piece of evidence presented reveals the origin of the exposed data. This evidence substantiates the fact that the leak is genuine and originates from internal organizational data. It also provides the analyst with a critical breadcrumb trail to successfully remove the secret from the data store and communicate with the owner on next steps. Trace the invisible lines between your AI application and the grounding sources Defender for Cloud excels in continuous feedback throughout the application lifecycle. While posture capabilities help triage detections, runtime protection provides crucial insights from traffic analysis, such as discovering data stores used for grounding AI applications. The AI application's connection to these stores is often hidden from current control or data plane tools. The credential leak example provided a real-world connection that was then integrated into our resource graph, uncovering previously overlooked data stores. Tagging these stores improves attack path and risk factor identification during posture scanning, ensuring safe configuration. This approach reinforces the feedback loop between runtime protection and posture assessment, maximizing cloud-native application protection platform (CNAPP) effectiveness. Align with AI security frameworks Our guiding principle is widely recognized by OWASP Top 10 for LLMs. By combining our posture capabilities with runtime monitoring, we can comprehensively address a wide range of threats, enabling us to proactively prepare for and detect AI-specific breaches with Defender for Cloud. As the industry evolves and new regulations emerge, frameworks such as OWASP, the EU AI Act, and NIST 600-1 are shaping security expectations. Our detections are aligned with these frameworks as well as the MITRE ATLAS framework, ensuring that organizations stay compliant and are prepared for future regulations and standards. Get started with threat protection for AI services To get started with threat protection capabilities in Defender for Cloud, it’s as simple as one-click to enable it on your relevant subscription in Azure. The integration is agentless and requires zero intervention in the application dev lifecycle. More importantly, the native integration directly inside Azure AI pipeline does not entail scale or performance degradation in the application runtime. Consuming the detections is easy, it appears in Defender for Cloud’s portal, but is also seamlessly connected to Defender XDR and Sentinel, leveraging the existing connectors. SOC analysts can leverage the correlation and analysis capabilities of Defender XDR from day one. Explore these capabilities today with a free 30-day trial*. You can leverage your existing AI application and simply enable the “AI workloads” plan on your chosen subscription to start detecting and responding to AI threats. *Trial free period is limited to up to 75B tokens scanned. 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. Explore additional resources Learn more about Runtime protection Learn more about Posture capabilities Watch the Defender for Cloud in the Field episode on securing AI applications Get started with Defender for CloudImportant Update: Deprecation of “Bring Your Own License” in Microsoft Defender for Cloud
Introduction With the introduction of Microsoft Security Exposure Management data connectors, we are committed to enhancing your enterprise exposure management experience and data consumption through this unified view. As part of this effort, we are making changes to streamline and improve our vulnerability assessment (VA) solutions. One of these changes involves deprecating the “Bring Your Own License” (BYOL) feature in Microsoft Defender for Cloud and transitioning to Exposure Management data connectors for a more seamless and comprehensive solution. Why this change? Our goal is to provide a cohesive and comprehensive VA solution within the unified security operations platform. By consolidating these capabilities, we can deliver a more integrated and efficient experience for vulnerability and exposure management across cloud, hybrid and on-premises. Deprecation timeline The “Bring Your Own License” (BYOL) feature for vulnerability assessment will be deprecated in two phases: February 3, 2025: The feature will no longer be available for onboarding new machines and subscriptions. Any VMs between Feb and May will not have agents deployed May 1, 2025: The feature will be fully deprecated and no longer available. What this means for you? The new data connectors in Exposure Management will replace BYOL in Defender for Cloud and will offer: Multiple scanner options: Integration of different third-party VA solutions, providing more flexibility and coverage. More information about the connectors can be found here. Unified visibility: A single, combined view of all vulnerability assessments across multi-cloud and on-premises, simplifying prioritization, management, and reporting. Seamless integration: Once the data connector is configured, There is no agent installation required, because the connector retrieves data directly from the VA product via API. With the API permissions you provide, Microsoft Security Exposure Management can seamlessly consume your vulnerability data from the connector and the data collected in your environment. Exposure Management: Microsoft Security Exposure Management is a comprehensive security solution that offers a unified view of your security posture across all company assets and workloads. It enhances asset information with valuable security context, enabling you to proactively manage attack surfaces, protect critical assets, and identify and mitigate exposure risks effectively. Read more here. Microsoft Defender for Cloud is already a key component of Exposure Management, providing a unified security flow that ensures consistent application of security measures across all assets. We are continuously working to enhance this collaboration, further strengthening your overall security posture by delivering a cohesive and comprehensive security strategy. A key Initiative in this strategy is vulnerability management. We aim to enhance and centralize this aspect as much as possible, leveraging all available data points from MDC, Microsoft Defender for Endpoint (MDE), Microsoft Defender Vulnerability Managment, and various connectors. This centralized approach ensures that vulnerabilities are identified, prioritized and addressed promptly, minimizing potential risks and improving overall security resilience. This BYOL deprecation and transition to Security Exposure Management connectors is designed to enhance your overall experience and value. Below is a feature comparison to provide more clarity on the additional capabilities that will be available as part of this transition: Feature Defender for Cloud BYOL Microsoft Security Exposure Managment data connectors* Auto provisioning Automatic agent deployment for Azure machines** Customer deploys VA solution according to each vendors recommendation Multi-cloud Azure Only Multi-cloud and non-cloud Supported vendors Rapid7, Qualys Rapid7, Qualys, Tenable (and more planned) Aggregated results from multiple scanners Each device shows results from a single provider Devices show aggregated results from multiple providers Product experience Defender for Cloud portal Defender portal *Note: during the preview phase, use of data connectors is free. Once data connectors become generally available, there will be a consumption-based cost for each of the non-Microsoft data connectors. For more information, please see here. ** Removing BYOL auto-provisioning in Defender for Cloud means that while Microsoft will no longer automatically provision the agent, customers deploy the VA solution according to each vendors recommendation. Actions required If you are currently using BYOL solutions in Defender for Cloud, we encourage you to begin configuring your Microsoft Security Exposure Management data connectors for Qualys and Rapid7 before May 1, 2025. For more information on using the connectors, please visit the connectors onboarding documentation. For another way to obtain vulnerability assessment information, you can utilize our Microsoft Vulnerability Management solution, which is included in Defender for Servers (Plan 1 and Plan 2) as well as Defender CSPM Plan. Additional Note: BYOL is not the recommended migration path for all Defender for Servers customers currently utilizing Qualys Built-in for Vulnerability Assessment. Instead, these customers should migrate to the connector's solution suggested above for a seamless and optimized transition.Cost Calculator for Defender for Cloud (Public Preview)
Did you know Microsoft Defender for Cloud has a built-in cost calculator to easily calculate the costs of protected resources in your cloud environment? No? Well, I didn’t either until I stumbled upon the button in the MDC portal myself. Apparently, Microsoft announced the preview for the MDC cost calculator last month, on February 19, 2025. With this post, I’m sharing my experience with this new cost calculator for Microsoft Defender for Cloud, providing guidance and comparing available options to calculate the costs. https://myronhelgering.com/cost-calculator-for-defender-for-cloud/
Sensitivity Data Flag will not be deleted after Settings are changed
We have a lot of storage accounts which are flaged with risk factor "Sensitive Data" which also means all storage Accounts which have this label have risklevel critical. We deactivated Sensitive Data Scan but nothing happens As I got it correct once a resource is flagged with "Sensitive Data" the flag will not delete anymore What we did so far: turn off/on/off… the data scanning turn off/on/off Data sensitivity deselect all of different data sensitivity categories like Finance, PII, and Credentials turn off/on/off threshold for sensitive data labels turn off/on complete Defender There is also a support ticket where the support can the recommendation was to open a discussion here to have the product team look at this error (#2502031420002278)Microsoft Defender for Cloud Customer Newsletter
What's new in Defender for Cloud? On-demand malware scanning in Defender for Storage is now in GA! This feature also supports blobs up to 50 GB in size (previously limited to 2GB). See this page for more info. 31 new and enhanced Multicloud regulatory standards We’ve published enhanced and expanded support of over 31 security and regulatory frameworks in Defender for Cloud across Azure, AWS & GCP. For more details, please refer to our documentation. Blogs of the month In February, our team published the following blog posts we would like to share: Unveiling Kubernetes lateral movement and attack paths with Microsoft Defender for Cloud Protecting Azure AI Workloads using Threat Protection for AI in Defender for Cloud New and enhanced multicloud regulatory compliance standards in Defender for Cloud Strengthening Cloud Compliance and Governance with Microsoft Defender CSPM GitHub Community Learn more about Code Reachability Vulnerabilities with Endor Labs with Module 26 - Defender for Cloud Code Reachability Vulnerabilities with Endor Labs Defender for Cloud in the field Watch the latest Defender for Cloud in the Field YouTube episodes here: Integrate Defender for Cloud CLI with CI/CD pipelines Code Reachability Analysis Visit our YouTube page! Customer journeys Discover how other organizations successfully use Microsoft Defender for Cloud to protect their cloud workloads. This month we are featuring Kurita Water Industries, a water treatment solutions company, that leverages both Microsoft Entra Permissions Management and Defender for Cloud’s CSPM for resource statuses, vulnerabilities, state of access permissions, and risk prioritization and CWPP capabilities to continuously monitor and protect cloud workloads Security community webinars Join our experts in the upcoming webinars to learn what we are doing to secure your workloads running in Azure and other clouds. Check out our upcoming webinars this month in the link below! MAR 5 Microsoft Defender for Cloud | API Security Posture with Defender for Cloud We offer several customer connection programs within our private communities. By signing up, you can help us shape our products through activities such as reviewing product roadmaps, participating in co-design, previewing features, and staying up-to-date with announcements. Sign up at aka.ms/JoinCCP. We greatly value your input on the types of content that enhance your understanding of our security products. Your insights are crucial in guiding the development of our future public content. We aim to deliver material that not only educates but also resonates with your daily security challenges. Whether it’s through in-depth live webinars, real-world case studies, comprehensive best practice guides through blogs, or the latest product updates, we want to ensure our content meets your needs. Please submit your feedback on which of these formats do you find most beneficial and are there any specific topics you’re interested in https://aka.ms/PublicContentFeedback. Note: If you want to stay current with Defender for Cloud and receive updates in your inbox, please consider subscribing to our monthly newsletter: https://aka.ms/MDCNewsSubscribe
